cola Report for GDS3916

Date: 2019-12-25 21:04:25 CET, cola version: 1.3.2

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Summary

All available functions which can be applied to this res_list object:

res_list

#> A 'ConsensusPartitionList' object with 24 methods.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows are extracted by 'SD, CV, MAD, ATC' methods.
#>   Subgroups are detected by 'hclust, kmeans, skmeans, pam, mclust, NMF' method.
#>   Number of partitions are tried for k = 2, 3, 4, 5, 6.
#>   Performed in total 30000 partitions by row resampling.
#> 
#> Following methods can be applied to this 'ConsensusPartitionList' object:
#>  [1] "cola_report"           "collect_classes"       "collect_plots"         "collect_stats"        
#>  [5] "colnames"              "functional_enrichment" "get_anno_col"          "get_anno"             
#>  [9] "get_classes"           "get_matrix"            "get_membership"        "get_stats"            
#> [13] "is_best_k"             "is_stable_k"           "ncol"                  "nrow"                 
#> [17] "rownames"              "show"                  "suggest_best_k"        "test_to_known_factors"
#> [21] "top_rows_heatmap"      "top_rows_overlap"     
#> 
#> You can get result for a single method by, e.g. object["SD", "hclust"] or object["SD:hclust"]
#> or a subset of methods by object[c("SD", "CV")], c("hclust", "kmeans")]

The call of run_all_consensus_partition_methods() was:

#> run_all_consensus_partition_methods(data = mat, mc.cores = 4, anno = anno)

Dimension of the input matrix:

mat = get_matrix(res_list)
dim(mat)

#> [1] 21074   139

Density distribution

The density distribution for each sample is visualized as in one column in the following heatmap. The clustering is based on the distance which is the Kolmogorov-Smirnov statistic between two distributions.

library(ComplexHeatmap)
densityHeatmap(mat, top_annotation = HeatmapAnnotation(df = get_anno(res_list), 
    col = get_anno_col(res_list)), ylab = "value", cluster_columns = TRUE, show_column_names = FALSE,
    mc.cores = 4)

plot of chunk density-heatmap

Suggest the best k

Folowing table shows the best k (number of partitions) for each combination of top-value methods and partition methods. Clicking on the method name in the table goes to the section for a single combination of methods.

The cola vignette explains the definition of the metrics used for determining the best number of partitions.

suggest_best_k(res_list)
The best k 1-PAC Mean silhouette Concordance Optional k
SD:kmeans 2 1.000 0.973 0.979 **
CV:kmeans 2 1.000 0.973 0.985 **
CV:mclust 3 1.000 0.994 0.997 **
MAD:kmeans 2 1.000 0.983 0.992 **
ATC:hclust 2 1.000 0.989 0.995 **
ATC:kmeans 2 1.000 0.992 0.997 **
ATC:skmeans 3 1.000 0.948 0.973 ** 2
ATC:pam 2 1.000 0.978 0.991 **
ATC:mclust 2 1.000 1.000 1.000 **
MAD:pam 6 1.000 0.953 0.982 ** 2,3,4,5
SD:pam 6 0.991 0.953 0.981 ** 2,3,4,5
SD:NMF 2 0.970 0.966 0.985 **
CV:NMF 2 0.970 0.962 0.984 **
MAD:mclust 4 0.969 0.961 0.959 ** 3
CV:pam 6 0.960 0.939 0.941 ** 2,3,5
MAD:skmeans 6 0.940 0.931 0.918 * 2,3,4,5
SD:skmeans 6 0.935 0.925 0.915 * 2,3,4,5
CV:skmeans 6 0.926 0.880 0.899 * 2,3,4,5
SD:mclust 6 0.921 0.889 0.949 * 3
MAD:NMF 4 0.914 0.885 0.951 * 2
ATC:NMF 5 0.908 0.873 0.926 * 2
CV:hclust 3 0.669 0.726 0.883
SD:hclust 3 0.629 0.728 0.866
MAD:hclust 3 0.607 0.756 0.864

**: 1-PAC > 0.95, *: 1-PAC > 0.9

CDF of consensus matrices

Cumulative distribution function curves of consensus matrix for all methods.

collect_plots(res_list, fun = plot_ecdf)

plot of chunk collect-plots

Consensus heatmap

Consensus heatmaps for all methods. (What is a consensus heatmap?)

collect_plots(res_list, k = 2, fun = consensus_heatmap, mc.cores = 4)

plot of chunk tab-collect-consensus-heatmap-1

collect_plots(res_list, k = 3, fun = consensus_heatmap, mc.cores = 4)

plot of chunk tab-collect-consensus-heatmap-2

collect_plots(res_list, k = 4, fun = consensus_heatmap, mc.cores = 4)

plot of chunk tab-collect-consensus-heatmap-3

collect_plots(res_list, k = 5, fun = consensus_heatmap, mc.cores = 4)

plot of chunk tab-collect-consensus-heatmap-4

collect_plots(res_list, k = 6, fun = consensus_heatmap, mc.cores = 4)

plot of chunk tab-collect-consensus-heatmap-5

Membership heatmap

Membership heatmaps for all methods. (What is a membership heatmap?)

collect_plots(res_list, k = 2, fun = membership_heatmap, mc.cores = 4)

plot of chunk tab-collect-membership-heatmap-1

collect_plots(res_list, k = 3, fun = membership_heatmap, mc.cores = 4)

plot of chunk tab-collect-membership-heatmap-2

collect_plots(res_list, k = 4, fun = membership_heatmap, mc.cores = 4)

plot of chunk tab-collect-membership-heatmap-3

collect_plots(res_list, k = 5, fun = membership_heatmap, mc.cores = 4)

plot of chunk tab-collect-membership-heatmap-4

collect_plots(res_list, k = 6, fun = membership_heatmap, mc.cores = 4)

plot of chunk tab-collect-membership-heatmap-5

Signature heatmap

Signature heatmaps for all methods. (What is a signature heatmap?)

Note in following heatmaps, rows are scaled.

collect_plots(res_list, k = 2, fun = get_signatures, mc.cores = 4)

plot of chunk tab-collect-get-signatures-1

collect_plots(res_list, k = 3, fun = get_signatures, mc.cores = 4)

plot of chunk tab-collect-get-signatures-2

collect_plots(res_list, k = 4, fun = get_signatures, mc.cores = 4)

plot of chunk tab-collect-get-signatures-3

collect_plots(res_list, k = 5, fun = get_signatures, mc.cores = 4)

plot of chunk tab-collect-get-signatures-4

collect_plots(res_list, k = 6, fun = get_signatures, mc.cores = 4)

plot of chunk tab-collect-get-signatures-5

Statistics table

The statistics used for measuring the stability of consensus partitioning. (How are they defined?)

get_stats(res_list, k = 2)

#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      2 0.970           0.966       0.985          0.493 0.508   0.508
#> CV:NMF      2 0.970           0.962       0.984          0.495 0.508   0.508
#> MAD:NMF     2 0.985           0.959       0.983          0.495 0.508   0.508
#> ATC:NMF     2 1.000           0.964       0.985          0.495 0.504   0.504
#> SD:skmeans  2 1.000           0.988       0.995          0.491 0.510   0.510
#> CV:skmeans  2 1.000           0.982       0.993          0.490 0.510   0.510
#> MAD:skmeans 2 1.000           0.988       0.995          0.491 0.510   0.510
#> ATC:skmeans 2 1.000           0.978       0.992          0.491 0.510   0.510
#> SD:mclust   2 0.353           0.870       0.856          0.444 0.518   0.518
#> CV:mclust   2 0.348           0.832       0.825          0.428 0.518   0.518
#> MAD:mclust  2 0.752           0.931       0.932          0.475 0.518   0.518
#> ATC:mclust  2 1.000           1.000       1.000          0.482 0.518   0.518
#> SD:kmeans   2 1.000           0.973       0.979          0.482 0.513   0.513
#> CV:kmeans   2 1.000           0.973       0.985          0.483 0.513   0.513
#> MAD:kmeans  2 1.000           0.983       0.992          0.486 0.513   0.513
#> ATC:kmeans  2 1.000           0.992       0.997          0.484 0.515   0.515
#> SD:pam      2 1.000           0.988       0.995          0.490 0.513   0.513
#> CV:pam      2 1.000           0.987       0.994          0.489 0.513   0.513
#> MAD:pam     2 1.000           0.995       0.997          0.489 0.513   0.513
#> ATC:pam     2 1.000           0.978       0.991          0.486 0.515   0.515
#> SD:hclust   2 0.299           0.606       0.779          0.397 0.496   0.496
#> CV:hclust   2 0.328           0.756       0.773          0.381 0.508   0.508
#> MAD:hclust  2 0.370           0.795       0.840          0.427 0.515   0.515
#> ATC:hclust  2 1.000           0.989       0.995          0.485 0.515   0.515

get_stats(res_list, k = 3)

#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      3 0.615           0.562       0.749          0.336 0.769   0.571
#> CV:NMF      3 0.626           0.598       0.808          0.332 0.806   0.628
#> MAD:NMF     3 0.694           0.714       0.841          0.334 0.774   0.577
#> ATC:NMF     3 0.773           0.843       0.921          0.321 0.754   0.546
#> SD:skmeans  3 1.000           0.986       0.993          0.315 0.834   0.678
#> CV:skmeans  3 1.000           0.982       0.993          0.316 0.822   0.659
#> MAD:skmeans 3 1.000           0.982       0.991          0.314 0.834   0.678
#> ATC:skmeans 3 1.000           0.948       0.973          0.268 0.869   0.742
#> SD:mclust   3 1.000           0.991       0.996          0.452 0.837   0.685
#> CV:mclust   3 1.000           0.994       0.997          0.507 0.837   0.685
#> MAD:mclust  3 1.000           0.996       0.998          0.358 0.837   0.685
#> ATC:mclust  3 0.771           0.837       0.903          0.230 0.930   0.864
#> SD:kmeans   3 0.623           0.705       0.777          0.317 0.788   0.601
#> CV:kmeans   3 0.640           0.670       0.568          0.312 0.860   0.745
#> MAD:kmeans  3 0.649           0.544       0.722          0.302 0.938   0.885
#> ATC:kmeans  3 0.659           0.793       0.807          0.303 0.800   0.629
#> SD:pam      3 1.000           0.989       0.995          0.323 0.828   0.668
#> CV:pam      3 1.000           0.983       0.994          0.322 0.831   0.674
#> MAD:pam     3 1.000           0.991       0.996          0.327 0.828   0.668
#> ATC:pam     3 0.718           0.812       0.897          0.351 0.789   0.602
#> SD:hclust   3 0.629           0.728       0.866          0.517 0.789   0.623
#> CV:hclust   3 0.669           0.726       0.883          0.546 0.795   0.640
#> MAD:hclust  3 0.607           0.756       0.864          0.449 0.831   0.675
#> ATC:hclust  3 0.755           0.809       0.902          0.228 0.931   0.865

get_stats(res_list, k = 4)

#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      4 0.880           0.895       0.950         0.1133 0.859   0.619
#> CV:NMF      4 0.891           0.891       0.945         0.1140 0.879   0.666
#> MAD:NMF     4 0.914           0.885       0.951         0.1097 0.852   0.604
#> ATC:NMF     4 0.823           0.841       0.911         0.1156 0.876   0.658
#> SD:skmeans  4 1.000           0.980       0.983         0.1326 0.905   0.737
#> CV:skmeans  4 1.000           0.976       0.982         0.1327 0.910   0.749
#> MAD:skmeans 4 1.000           0.988       0.981         0.1304 0.905   0.737
#> ATC:skmeans 4 0.780           0.864       0.885         0.1047 0.907   0.758
#> SD:mclust   4 0.876           0.940       0.939         0.0897 0.948   0.855
#> CV:mclust   4 0.837           0.913       0.913         0.0939 0.948   0.855
#> MAD:mclust  4 0.969           0.961       0.959         0.0810 0.948   0.855
#> ATC:mclust  4 0.640           0.660       0.801         0.1474 0.876   0.745
#> SD:kmeans   4 0.704           0.876       0.749         0.1411 0.904   0.729
#> CV:kmeans   4 0.630           0.868       0.744         0.1352 0.674   0.374
#> MAD:kmeans  4 0.611           0.445       0.608         0.1328 0.687   0.408
#> ATC:kmeans  4 0.611           0.411       0.684         0.1255 0.808   0.546
#> SD:pam      4 1.000           0.963       0.958         0.1268 0.907   0.741
#> CV:pam      4 0.840           0.901       0.882         0.1261 0.910   0.748
#> MAD:pam     4 1.000           0.963       0.962         0.1250 0.907   0.741
#> ATC:pam     4 0.652           0.726       0.810         0.1169 0.892   0.695
#> SD:hclust   4 0.678           0.700       0.838         0.1591 0.880   0.715
#> CV:hclust   4 0.667           0.680       0.843         0.1835 0.839   0.637
#> MAD:hclust  4 0.698           0.597       0.794         0.1365 0.962   0.895
#> ATC:hclust  4 0.711           0.839       0.895         0.1371 0.895   0.764

get_stats(res_list, k = 5)

#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      5 0.881           0.850       0.919         0.0442 0.977   0.914
#> CV:NMF      5 0.887           0.868       0.930         0.0436 0.966   0.874
#> MAD:NMF     5 0.871           0.849       0.919         0.0483 0.957   0.845
#> ATC:NMF     5 0.908           0.873       0.926         0.0475 0.932   0.761
#> SD:skmeans  5 0.932           0.955       0.966         0.1007 0.918   0.701
#> CV:skmeans  5 0.977           0.971       0.977         0.1001 0.924   0.719
#> MAD:skmeans 5 0.923           0.957       0.962         0.1015 0.918   0.701
#> ATC:skmeans 5 0.775           0.825       0.895         0.0762 0.959   0.865
#> SD:mclust   5 0.842           0.786       0.906         0.1094 0.929   0.765
#> CV:mclust   5 0.817           0.771       0.900         0.1091 0.901   0.682
#> MAD:mclust  5 0.820           0.805       0.903         0.1208 0.931   0.771
#> ATC:mclust  5 0.636           0.638       0.752         0.0777 0.825   0.580
#> SD:kmeans   5 0.704           0.851       0.799         0.0695 0.918   0.701
#> CV:kmeans   5 0.706           0.847       0.801         0.0794 0.924   0.719
#> MAD:kmeans  5 0.690           0.860       0.804         0.0791 0.865   0.532
#> ATC:kmeans  5 0.625           0.553       0.731         0.0696 0.926   0.760
#> SD:pam      5 1.000           0.975       0.991         0.1043 0.924   0.719
#> CV:pam      5 1.000           0.977       0.990         0.1057 0.913   0.683
#> MAD:pam     5 1.000           0.975       0.991         0.1042 0.918   0.701
#> ATC:pam     5 0.750           0.753       0.879         0.0716 0.866   0.568
#> SD:hclust   5 0.685           0.570       0.776         0.0836 0.920   0.752
#> CV:hclust   5 0.707           0.677       0.812         0.0618 0.957   0.857
#> MAD:hclust  5 0.781           0.648       0.817         0.0454 0.932   0.801
#> ATC:hclust  5 0.793           0.758       0.857         0.0601 0.966   0.901

get_stats(res_list, k = 6)

#>             k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> SD:NMF      6 0.889           0.908       0.923         0.0517 0.915   0.674
#> CV:NMF      6 0.891           0.912       0.931         0.0528 0.915   0.672
#> MAD:NMF     6 0.878           0.862       0.891         0.0478 0.912   0.659
#> ATC:NMF     6 0.815           0.710       0.852         0.0371 0.985   0.939
#> SD:skmeans  6 0.935           0.925       0.915         0.0277 0.981   0.900
#> CV:skmeans  6 0.926           0.880       0.899         0.0281 0.977   0.881
#> MAD:skmeans 6 0.940           0.931       0.918         0.0289 0.981   0.900
#> ATC:skmeans 6 0.876           0.761       0.844         0.0541 0.932   0.754
#> SD:mclust   6 0.921           0.889       0.949         0.0242 0.924   0.701
#> CV:mclust   6 0.898           0.863       0.943         0.0176 0.886   0.571
#> MAD:mclust  6 0.898           0.856       0.926         0.0221 0.915   0.673
#> ATC:mclust  6 0.706           0.696       0.820         0.0436 0.960   0.849
#> SD:kmeans   6 0.810           0.754       0.775         0.0452 0.994   0.970
#> CV:kmeans   6 0.754           0.826       0.794         0.0415 0.989   0.943
#> MAD:kmeans  6 0.816           0.820       0.796         0.0457 0.994   0.970
#> ATC:kmeans  6 0.707           0.665       0.754         0.0501 0.940   0.774
#> SD:pam      6 0.991           0.953       0.981         0.0285 0.970   0.848
#> CV:pam      6 0.960           0.939       0.941         0.0277 0.970   0.849
#> MAD:pam     6 1.000           0.953       0.982         0.0290 0.970   0.847
#> ATC:pam     6 0.771           0.685       0.830         0.0404 0.964   0.838
#> SD:hclust   6 0.731           0.611       0.754         0.0403 0.935   0.756
#> CV:hclust   6 0.760           0.731       0.813         0.0536 0.945   0.788
#> MAD:hclust  6 0.825           0.776       0.846         0.0355 0.937   0.784
#> ATC:hclust  6 0.843           0.832       0.891         0.0443 0.923   0.753

Following heatmap plots the partition for each combination of methods and the lightness correspond to the silhouette scores for samples in each method. On top the consensus subgroup is inferred from all methods by taking the mean silhouette scores as weight.

collect_stats(res_list, k = 2)

plot of chunk tab-collect-stats-from-consensus-partition-list-1

collect_stats(res_list, k = 3)

plot of chunk tab-collect-stats-from-consensus-partition-list-2

collect_stats(res_list, k = 4)

plot of chunk tab-collect-stats-from-consensus-partition-list-3

collect_stats(res_list, k = 5)

plot of chunk tab-collect-stats-from-consensus-partition-list-4

collect_stats(res_list, k = 6)

plot of chunk tab-collect-stats-from-consensus-partition-list-5

Partition from all methods

Collect partitions from all methods:

collect_classes(res_list, k = 2)

plot of chunk tab-collect-classes-from-consensus-partition-list-1

collect_classes(res_list, k = 3)

plot of chunk tab-collect-classes-from-consensus-partition-list-2

collect_classes(res_list, k = 4)

plot of chunk tab-collect-classes-from-consensus-partition-list-3

collect_classes(res_list, k = 5)

plot of chunk tab-collect-classes-from-consensus-partition-list-4

collect_classes(res_list, k = 6)

plot of chunk tab-collect-classes-from-consensus-partition-list-5

Top rows overlap

Overlap of top rows from different top-row methods:

top_rows_overlap(res_list, top_n = 1000, method = "euler")

plot of chunk tab-top-rows-overlap-by-euler-1

top_rows_overlap(res_list, top_n = 2000, method = "euler")

plot of chunk tab-top-rows-overlap-by-euler-2

top_rows_overlap(res_list, top_n = 3000, method = "euler")

plot of chunk tab-top-rows-overlap-by-euler-3

top_rows_overlap(res_list, top_n = 4000, method = "euler")

plot of chunk tab-top-rows-overlap-by-euler-4

top_rows_overlap(res_list, top_n = 5000, method = "euler")

plot of chunk tab-top-rows-overlap-by-euler-5

Also visualize the correspondance of rankings between different top-row methods:

top_rows_overlap(res_list, top_n = 1000, method = "correspondance")

plot of chunk tab-top-rows-overlap-by-correspondance-1

top_rows_overlap(res_list, top_n = 2000, method = "correspondance")

plot of chunk tab-top-rows-overlap-by-correspondance-2

top_rows_overlap(res_list, top_n = 3000, method = "correspondance")

plot of chunk tab-top-rows-overlap-by-correspondance-3

top_rows_overlap(res_list, top_n = 4000, method = "correspondance")

plot of chunk tab-top-rows-overlap-by-correspondance-4

top_rows_overlap(res_list, top_n = 5000, method = "correspondance")

plot of chunk tab-top-rows-overlap-by-correspondance-5

Heatmaps of the top rows:

top_rows_heatmap(res_list, top_n = 1000)

plot of chunk tab-top-rows-heatmap-1

top_rows_heatmap(res_list, top_n = 2000)

plot of chunk tab-top-rows-heatmap-2

top_rows_heatmap(res_list, top_n = 3000)

plot of chunk tab-top-rows-heatmap-3

top_rows_heatmap(res_list, top_n = 4000)

plot of chunk tab-top-rows-heatmap-4

top_rows_heatmap(res_list, top_n = 5000)

plot of chunk tab-top-rows-heatmap-5

Test to known annotations

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res_list, k = 2)

#>               n individual(p) time(p) agent(p) k
#> SD:NMF      139      8.18e-23       1    0.856 2
#> CV:NMF      138      1.25e-22       1    0.820 2
#> MAD:NMF     137      7.88e-24       1    0.869 2
#> ATC:NMF     137      5.19e-23       1    0.783 2
#> SD:skmeans  138      9.55e-25       1    0.733 2
#> CV:skmeans  138      9.55e-25       1    0.733 2
#> MAD:skmeans 139      6.01e-25       1    0.651 2
#> ATC:skmeans 137      1.60e-24       1    0.780 2
#> SD:mclust   139      4.62e-29       1    1.000 2
#> CV:mclust   138      7.56e-29       1    1.000 2
#> MAD:mclust  139      4.62e-29       1    1.000 2
#> ATC:mclust  139      4.62e-29       1    1.000 2
#> SD:kmeans   138      1.06e-24       1    0.780 2
#> CV:kmeans   137      2.50e-25       1    0.831 2
#> MAD:kmeans  138      1.06e-24       1    0.780 2
#> ATC:kmeans  138      3.69e-23       1    0.865 2
#> SD:pam      139      2.03e-27       1    1.000 2
#> CV:pam      139      2.03e-27       1    1.000 2
#> MAD:pam     139      2.03e-27       1    1.000 2
#> ATC:pam     138      1.06e-24       1    0.780 2
#> SD:hclust   124      3.50e-21       1    1.000 2
#> CV:hclust   135      2.42e-23       1    1.000 2
#> MAD:hclust  137      1.39e-21       1    1.000 2
#> ATC:hclust  139      5.46e-22       1    1.000 2

test_to_known_factors(res_list, k = 3)

#>               n individual(p) time(p) agent(p) k
#> SD:NMF       81      6.10e-31   0.996  0.66598 3
#> CV:NMF       98      8.68e-37   1.000  0.29271 3
#> MAD:NMF     115      2.97e-36   0.994  0.00537 3
#> ATC:NMF     129      2.11e-27   0.951  0.00148 3
#> SD:skmeans  138      5.92e-53   1.000  0.91412 3
#> CV:skmeans  137      1.49e-53   1.000  0.93431 3
#> MAD:skmeans 139      1.97e-52   1.000  0.89096 3
#> ATC:skmeans 136      1.10e-21   0.928  0.02739 3
#> SD:mclust   139      1.97e-55   1.000  0.99781 3
#> CV:mclust   139      1.97e-55   1.000  0.99781 3
#> MAD:mclust  139      1.97e-55   1.000  0.99781 3
#> ATC:mclust  132      7.80e-32   1.000  0.16333 3
#> SD:kmeans   111      1.97e-42   1.000  0.95096 3
#> CV:kmeans   131      1.21e-50   1.000  0.73157 3
#> MAD:kmeans   54            NA      NA       NA 3
#> ATC:kmeans  128      3.37e-26   0.946  0.01899 3
#> SD:pam      138      5.23e-55   1.000  0.97701 3
#> CV:pam      138      5.23e-55   1.000  0.97701 3
#> MAD:pam     139      6.21e-54   1.000  0.93451 3
#> ATC:pam     130      8.26e-34   0.996  0.24308 3
#> SD:hclust   120      3.71e-32   0.995  0.02443 3
#> CV:hclust   119      8.31e-29   0.991  0.04383 3
#> MAD:hclust  124      9.03e-45   1.000  0.80138 3
#> ATC:hclust  125      1.76e-22   0.967  0.16814 3

test_to_known_factors(res_list, k = 4)

#>               n individual(p) time(p) agent(p) k
#> SD:NMF      134      4.75e-68   1.000   0.5995 4
#> CV:NMF      132      1.98e-68   1.000   0.7255 4
#> MAD:NMF     131      2.80e-69   1.000   0.8735 4
#> ATC:NMF     132      1.26e-32   0.964   0.0175 4
#> SD:skmeans  139      2.80e-78   1.000   0.9963 4
#> CV:skmeans  137      5.48e-79   1.000   0.9946 4
#> MAD:skmeans 139      2.80e-78   1.000   0.9963 4
#> ATC:skmeans 134      2.07e-37   0.999   0.1175 4
#> SD:mclust   139      1.43e-59   1.000   0.0417 4
#> CV:mclust   138      1.57e-59   1.000   0.0465 4
#> MAD:mclust  139      1.43e-59   1.000   0.0417 4
#> ATC:mclust  103      6.10e-23   1.000   0.7818 4
#> SD:kmeans   138      4.25e-79   1.000   0.9980 4
#> CV:kmeans   139      2.80e-78   1.000   0.9963 4
#> MAD:kmeans   88      6.42e-34   1.000   0.5269 4
#> ATC:kmeans   64      4.18e-13   0.828   0.9845 4
#> SD:pam      137      6.35e-79   1.000   0.9625 4
#> CV:pam      136      7.65e-80   1.000   0.9944 4
#> MAD:pam     137      6.35e-79   1.000   0.9625 4
#> ATC:pam     128      4.83e-41   0.998   0.0614 4
#> SD:hclust   120      2.08e-37   0.984   0.0148 4
#> CV:hclust   114      2.60e-36   0.992   0.0209 4
#> MAD:hclust  101      8.61e-37   1.000   0.5080 4
#> ATC:hclust  127      4.72e-21   0.816   0.0380 4

test_to_known_factors(res_list, k = 5)

#>               n individual(p) time(p) agent(p) k
#> SD:NMF      132      2.50e-70   1.000 0.710557 5
#> CV:NMF      133      1.90e-72   1.000 0.738132 5
#> MAD:NMF     130      4.77e-70   1.000 0.548019 5
#> ATC:NMF     132      4.94e-47   0.999 0.095814 5
#> SD:skmeans  139     5.15e-106   1.000 0.999799 5
#> CV:skmeans  138     3.50e-105   1.000 0.995538 5
#> MAD:skmeans 139     5.15e-106   1.000 0.999799 5
#> ATC:skmeans 129      1.14e-39   0.997 0.075269 5
#> SD:mclust   122      8.38e-56   1.000 0.000035 5
#> CV:mclust   123      7.01e-67   1.000 0.002072 5
#> MAD:mclust  134      4.72e-66   1.000 0.001281 5
#> ATC:mclust  114      7.16e-34   0.958 0.357714 5
#> SD:kmeans   138     3.50e-105   1.000 0.997966 5
#> CV:kmeans   138     3.11e-103   1.000 0.996718 5
#> MAD:kmeans  138     3.50e-105   1.000 0.997966 5
#> ATC:kmeans  108      2.25e-27   0.909 0.091123 5
#> SD:pam      136     1.89e-103   1.000 0.984952 5
#> CV:pam      138     2.69e-101   1.000 0.977276 5
#> MAD:pam     137     3.01e-102   1.000 0.984374 5
#> ATC:pam     124      5.19e-54   1.000 0.041818 5
#> SD:hclust   104      2.54e-51   0.999 0.057551 5
#> CV:hclust   120      7.66e-43   0.999 0.021386 5
#> MAD:hclust  109      1.15e-45   1.000 0.520019 5
#> ATC:hclust  128      2.69e-23   0.908 0.075905 5

test_to_known_factors(res_list, k = 6)

#>               n individual(p) time(p) agent(p) k
#> SD:NMF      135      1.25e-99   1.000 9.09e-01 6
#> CV:NMF      135      1.25e-99   1.000 9.09e-01 6
#> MAD:NMF     130      1.88e-97   1.000 9.48e-01 6
#> ATC:NMF     119      3.25e-44   0.993 6.20e-02 6
#> SD:skmeans  139     5.38e-103   1.000 7.67e-01 6
#> CV:skmeans  135      1.08e-99   1.000 2.77e-01 6
#> MAD:skmeans 139     5.38e-103   1.000 7.67e-01 6
#> ATC:skmeans 123      9.70e-54   1.000 8.13e-02 6
#> SD:mclust   133      1.32e-52   0.978 5.60e-10 6
#> CV:mclust   129      9.13e-51   0.965 1.89e-09 6
#> MAD:mclust  131      1.87e-52   0.987 3.41e-10 6
#> ATC:mclust  119      1.88e-36   0.975 3.79e-02 6
#> SD:kmeans   126      4.76e-97   1.000 3.95e-01 6
#> CV:kmeans   138     3.50e-105   1.000 9.98e-01 6
#> MAD:kmeans  138     3.50e-105   1.000 9.98e-01 6
#> ATC:kmeans  119      1.52e-25   0.869 3.00e-02 6
#> SD:pam      136      6.27e-99   1.000 2.61e-02 6
#> CV:pam      138      1.07e-96   1.000 2.41e-02 6
#> MAD:pam     135      5.15e-96   1.000 4.98e-02 6
#> ATC:pam     115      1.29e-59   1.000 1.46e-01 6
#> SD:hclust   104      6.25e-74   1.000 8.93e-02 6
#> CV:hclust   120      6.96e-69   1.000 3.57e-02 6
#> MAD:hclust  121      7.52e-66   1.000 5.96e-01 6
#> ATC:hclust  123      4.30e-24   0.772 5.73e-02 6

Results for each method

SD:hclust

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["SD", "hclust"]
# you can also extract it by
# res = res_list["SD:hclust"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#>   Subgroups are detected by 'hclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 3.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk SD-hclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk SD-hclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.299           0.606       0.779         0.3967 0.496   0.496
#> 3 3 0.629           0.728       0.866         0.5168 0.789   0.623
#> 4 4 0.678           0.700       0.838         0.1591 0.880   0.715
#> 5 5 0.685           0.570       0.776         0.0836 0.920   0.752
#> 6 6 0.731           0.611       0.754         0.0403 0.935   0.756

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 3

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000     0.8232 0.000 1.000
#> GSM379833     2  0.0000     0.8232 0.000 1.000
#> GSM379834     2  0.0000     0.8232 0.000 1.000
#> GSM379827     2  0.4562     0.7422 0.096 0.904
#> GSM379828     2  0.4562     0.7422 0.096 0.904
#> GSM379829     1  0.7056     0.6680 0.808 0.192
#> GSM379830     2  0.4690     0.7366 0.100 0.900
#> GSM379831     2  0.4431     0.7463 0.092 0.908
#> GSM379840     2  0.8861     0.4789 0.304 0.696
#> GSM379841     2  0.0000     0.8232 0.000 1.000
#> GSM379842     2  0.0000     0.8232 0.000 1.000
#> GSM379835     2  0.4562     0.7422 0.096 0.904
#> GSM379836     2  0.4562     0.7422 0.096 0.904
#> GSM379837     2  0.8861     0.4789 0.304 0.696
#> GSM379838     2  0.0000     0.8232 0.000 1.000
#> GSM379839     2  0.8861     0.4789 0.304 0.696
#> GSM379848     2  0.0000     0.8232 0.000 1.000
#> GSM379849     2  0.0000     0.8232 0.000 1.000
#> GSM379850     2  0.0000     0.8232 0.000 1.000
#> GSM379843     2  0.0000     0.8232 0.000 1.000
#> GSM379844     2  0.0000     0.8232 0.000 1.000
#> GSM379845     2  0.8861     0.4789 0.304 0.696
#> GSM379846     2  0.0000     0.8232 0.000 1.000
#> GSM379847     2  0.0000     0.8232 0.000 1.000
#> GSM379853     2  0.0000     0.8232 0.000 1.000
#> GSM379854     2  0.0000     0.8232 0.000 1.000
#> GSM379851     2  0.0000     0.8232 0.000 1.000
#> GSM379852     2  0.0000     0.8232 0.000 1.000
#> GSM379804     1  0.2423     0.6017 0.960 0.040
#> GSM379805     1  0.2423     0.6017 0.960 0.040
#> GSM379806     1  0.2423     0.6017 0.960 0.040
#> GSM379799     1  0.0000     0.5743 1.000 0.000
#> GSM379800     1  0.0000     0.5743 1.000 0.000
#> GSM379801     1  0.0000     0.5743 1.000 0.000
#> GSM379802     1  0.0000     0.5743 1.000 0.000
#> GSM379803     1  0.0672     0.5802 0.992 0.008
#> GSM379812     1  0.8207     0.7122 0.744 0.256
#> GSM379813     1  0.8144     0.7115 0.748 0.252
#> GSM379814     1  0.7745     0.7051 0.772 0.228
#> GSM379807     1  0.7745     0.7051 0.772 0.228
#> GSM379808     1  0.2423     0.6017 0.960 0.040
#> GSM379809     1  0.7219     0.6916 0.800 0.200
#> GSM379810     1  0.7219     0.6916 0.800 0.200
#> GSM379811     1  0.0672     0.5802 0.992 0.008
#> GSM379820     1  0.7745     0.7051 0.772 0.228
#> GSM379821     1  0.8555     0.7148 0.720 0.280
#> GSM379822     1  0.8555     0.7148 0.720 0.280
#> GSM379815     1  0.7745     0.7051 0.772 0.228
#> GSM379816     1  0.8608     0.7148 0.716 0.284
#> GSM379817     1  0.8144     0.7115 0.748 0.252
#> GSM379818     1  0.0000     0.5743 1.000 0.000
#> GSM379819     1  0.6712     0.6820 0.824 0.176
#> GSM379825     1  0.0000     0.5743 1.000 0.000
#> GSM379826     1  0.7745     0.7051 0.772 0.228
#> GSM379823     1  0.8555     0.7148 0.720 0.280
#> GSM379824     1  0.8555     0.7148 0.720 0.280
#> GSM379749     2  0.0000     0.8232 0.000 1.000
#> GSM379750     2  0.0000     0.8232 0.000 1.000
#> GSM379751     2  0.0938     0.8154 0.012 0.988
#> GSM379744     2  0.0000     0.8232 0.000 1.000
#> GSM379745     2  0.0000     0.8232 0.000 1.000
#> GSM379746     2  0.0000     0.8232 0.000 1.000
#> GSM379747     2  0.0672     0.8182 0.008 0.992
#> GSM379748     2  0.0672     0.8182 0.008 0.992
#> GSM379757     2  0.0000     0.8232 0.000 1.000
#> GSM379758     2  0.0000     0.8232 0.000 1.000
#> GSM379752     2  0.0000     0.8232 0.000 1.000
#> GSM379753     2  0.0938     0.8154 0.012 0.988
#> GSM379754     2  0.0000     0.8232 0.000 1.000
#> GSM379755     2  0.0000     0.8232 0.000 1.000
#> GSM379756     2  0.0000     0.8232 0.000 1.000
#> GSM379764     2  0.0000     0.8232 0.000 1.000
#> GSM379765     2  0.0000     0.8232 0.000 1.000
#> GSM379766     2  0.0000     0.8232 0.000 1.000
#> GSM379759     2  0.0000     0.8232 0.000 1.000
#> GSM379760     2  0.0000     0.8232 0.000 1.000
#> GSM379761     2  0.0000     0.8232 0.000 1.000
#> GSM379762     2  0.0000     0.8232 0.000 1.000
#> GSM379763     2  0.0000     0.8232 0.000 1.000
#> GSM379769     2  0.0000     0.8232 0.000 1.000
#> GSM379770     2  0.0000     0.8232 0.000 1.000
#> GSM379767     2  0.0000     0.8232 0.000 1.000
#> GSM379768     2  0.0000     0.8232 0.000 1.000
#> GSM379776     1  0.9970     0.6114 0.532 0.468
#> GSM379777     1  0.9129     0.7057 0.672 0.328
#> GSM379778     2  0.4690     0.7322 0.100 0.900
#> GSM379771     1  0.9970     0.6114 0.532 0.468
#> GSM379772     1  0.9970     0.6114 0.532 0.468
#> GSM379773     2  0.9427    -0.0554 0.360 0.640
#> GSM379774     1  0.9970     0.6114 0.532 0.468
#> GSM379775     1  0.9970     0.6114 0.532 0.468
#> GSM379784     1  0.9129     0.7057 0.672 0.328
#> GSM379785     1  0.9754     0.6678 0.592 0.408
#> GSM379786     1  0.9129     0.7057 0.672 0.328
#> GSM379779     1  0.9970     0.6114 0.532 0.468
#> GSM379780     1  0.9970     0.6114 0.532 0.468
#> GSM379781     1  0.9815     0.6592 0.580 0.420
#> GSM379782     2  0.4690     0.7322 0.100 0.900
#> GSM379783     1  0.9129     0.7057 0.672 0.328
#> GSM379792     1  0.8144     0.6744 0.748 0.252
#> GSM379793     1  0.9661     0.6669 0.608 0.392
#> GSM379794     1  0.9661     0.6669 0.608 0.392
#> GSM379787     2  0.4690     0.7322 0.100 0.900
#> GSM379788     1  0.9129     0.7057 0.672 0.328
#> GSM379789     1  0.9754     0.6596 0.592 0.408
#> GSM379790     1  0.9754     0.6596 0.592 0.408
#> GSM379791     1  0.9661     0.6669 0.608 0.392
#> GSM379797     1  0.0000     0.5743 1.000 0.000
#> GSM379798     1  0.9661     0.6669 0.608 0.392
#> GSM379795     1  0.9661     0.6669 0.608 0.392
#> GSM379796     1  0.8144     0.6744 0.748 0.252
#> GSM379721     1  1.0000     0.5599 0.500 0.500
#> GSM379722     2  1.0000    -0.5725 0.500 0.500
#> GSM379723     1  1.0000     0.5599 0.500 0.500
#> GSM379716     2  1.0000    -0.5725 0.500 0.500
#> GSM379717     1  1.0000     0.5599 0.500 0.500
#> GSM379718     2  1.0000    -0.5725 0.500 0.500
#> GSM379719     2  1.0000    -0.5725 0.500 0.500
#> GSM379720     1  1.0000     0.5599 0.500 0.500
#> GSM379729     1  0.9996     0.5828 0.512 0.488
#> GSM379730     1  0.9996     0.5828 0.512 0.488
#> GSM379731     1  0.9996     0.5828 0.512 0.488
#> GSM379724     2  1.0000    -0.5725 0.500 0.500
#> GSM379725     1  0.9998     0.5753 0.508 0.492
#> GSM379726     1  1.0000     0.5599 0.500 0.500
#> GSM379727     2  1.0000    -0.5725 0.500 0.500
#> GSM379728     1  1.0000     0.5599 0.500 0.500
#> GSM379737     2  1.0000    -0.5725 0.500 0.500
#> GSM379738     2  1.0000    -0.5725 0.500 0.500
#> GSM379739     1  1.0000     0.5599 0.500 0.500
#> GSM379732     1  0.9996     0.5828 0.512 0.488
#> GSM379733     1  1.0000     0.5599 0.500 0.500
#> GSM379734     2  1.0000    -0.5725 0.500 0.500
#> GSM379735     1  0.9996     0.5828 0.512 0.488
#> GSM379736     2  1.0000    -0.5725 0.500 0.500
#> GSM379742     2  0.3733     0.7581 0.072 0.928
#> GSM379743     1  0.9996     0.5828 0.512 0.488
#> GSM379740     1  1.0000     0.5599 0.500 0.500
#> GSM379741     2  0.3733     0.7581 0.072 0.928

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0892      0.867 0.000 0.980 0.020
#> GSM379833     2  0.0892      0.867 0.000 0.980 0.020
#> GSM379834     2  0.0892      0.867 0.000 0.980 0.020
#> GSM379827     2  0.5803      0.691 0.028 0.760 0.212
#> GSM379828     2  0.5803      0.691 0.028 0.760 0.212
#> GSM379829     1  0.4974      0.645 0.764 0.000 0.236
#> GSM379830     2  0.5756      0.695 0.028 0.764 0.208
#> GSM379831     2  0.5111      0.735 0.024 0.808 0.168
#> GSM379840     2  0.9666      0.195 0.228 0.448 0.324
#> GSM379841     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379842     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379835     2  0.5849      0.686 0.028 0.756 0.216
#> GSM379836     2  0.5849      0.686 0.028 0.756 0.216
#> GSM379837     2  0.9678      0.189 0.228 0.444 0.328
#> GSM379838     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379839     2  0.9678      0.189 0.228 0.444 0.328
#> GSM379848     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379849     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379850     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379843     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379844     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379845     2  0.9678      0.189 0.228 0.444 0.328
#> GSM379846     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379847     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379853     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379854     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379851     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379852     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379804     1  0.5650      0.627 0.688 0.000 0.312
#> GSM379805     1  0.5650      0.627 0.688 0.000 0.312
#> GSM379806     1  0.5650      0.627 0.688 0.000 0.312
#> GSM379799     1  0.1163      0.785 0.972 0.000 0.028
#> GSM379800     1  0.1163      0.785 0.972 0.000 0.028
#> GSM379801     1  0.1163      0.785 0.972 0.000 0.028
#> GSM379802     1  0.1031      0.793 0.976 0.000 0.024
#> GSM379803     1  0.4974      0.720 0.764 0.000 0.236
#> GSM379812     3  0.5650      0.573 0.312 0.000 0.688
#> GSM379813     3  0.5810      0.529 0.336 0.000 0.664
#> GSM379814     3  0.6026      0.440 0.376 0.000 0.624
#> GSM379807     3  0.6026      0.440 0.376 0.000 0.624
#> GSM379808     1  0.5650      0.627 0.688 0.000 0.312
#> GSM379809     3  0.6302      0.101 0.480 0.000 0.520
#> GSM379810     3  0.6302      0.101 0.480 0.000 0.520
#> GSM379811     1  0.4974      0.720 0.764 0.000 0.236
#> GSM379820     3  0.6026      0.444 0.376 0.000 0.624
#> GSM379821     3  0.4887      0.696 0.228 0.000 0.772
#> GSM379822     3  0.4887      0.696 0.228 0.000 0.772
#> GSM379815     3  0.6026      0.440 0.376 0.000 0.624
#> GSM379816     3  0.4842      0.699 0.224 0.000 0.776
#> GSM379817     3  0.5810      0.531 0.336 0.000 0.664
#> GSM379818     1  0.1031      0.793 0.976 0.000 0.024
#> GSM379819     3  0.6302      0.120 0.480 0.000 0.520
#> GSM379825     1  0.1031      0.793 0.976 0.000 0.024
#> GSM379826     3  0.6026      0.444 0.376 0.000 0.624
#> GSM379823     3  0.4887      0.696 0.228 0.000 0.772
#> GSM379824     3  0.4887      0.696 0.228 0.000 0.772
#> GSM379749     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379750     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379751     2  0.1643      0.849 0.000 0.956 0.044
#> GSM379744     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379745     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379746     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379747     2  0.1289      0.858 0.000 0.968 0.032
#> GSM379748     2  0.1289      0.858 0.000 0.968 0.032
#> GSM379757     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379758     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379752     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379753     2  0.1643      0.849 0.000 0.956 0.044
#> GSM379754     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379755     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379756     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379764     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379765     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379766     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379759     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379760     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379761     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379762     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379763     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379769     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379770     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379767     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379768     2  0.0000      0.877 0.000 1.000 0.000
#> GSM379776     3  0.2636      0.819 0.048 0.020 0.932
#> GSM379777     3  0.4399      0.736 0.188 0.000 0.812
#> GSM379778     2  0.7278      0.209 0.028 0.516 0.456
#> GSM379771     3  0.2636      0.819 0.048 0.020 0.932
#> GSM379772     3  0.2636      0.819 0.048 0.020 0.932
#> GSM379773     3  0.6423      0.532 0.044 0.228 0.728
#> GSM379774     3  0.2636      0.819 0.048 0.020 0.932
#> GSM379775     3  0.2636      0.819 0.048 0.020 0.932
#> GSM379784     3  0.4235      0.742 0.176 0.000 0.824
#> GSM379785     3  0.3769      0.801 0.104 0.016 0.880
#> GSM379786     3  0.4235      0.742 0.176 0.000 0.824
#> GSM379779     3  0.2636      0.819 0.048 0.020 0.932
#> GSM379780     3  0.2636      0.819 0.048 0.020 0.932
#> GSM379781     3  0.3528      0.806 0.092 0.016 0.892
#> GSM379782     2  0.7278      0.209 0.028 0.516 0.456
#> GSM379783     3  0.4235      0.742 0.176 0.000 0.824
#> GSM379792     3  0.6848      0.309 0.416 0.016 0.568
#> GSM379793     3  0.4349      0.787 0.128 0.020 0.852
#> GSM379794     3  0.4349      0.787 0.128 0.020 0.852
#> GSM379787     2  0.7278      0.209 0.028 0.516 0.456
#> GSM379788     3  0.4235      0.742 0.176 0.000 0.824
#> GSM379789     3  0.4063      0.797 0.112 0.020 0.868
#> GSM379790     3  0.4063      0.797 0.112 0.020 0.868
#> GSM379791     3  0.4349      0.787 0.128 0.020 0.852
#> GSM379797     1  0.2356      0.786 0.928 0.000 0.072
#> GSM379798     3  0.4349      0.787 0.128 0.020 0.852
#> GSM379795     3  0.4349      0.787 0.128 0.020 0.852
#> GSM379796     3  0.6848      0.309 0.416 0.016 0.568
#> GSM379721     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379722     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379723     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379716     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379717     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379718     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379719     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379720     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379729     3  0.1636      0.822 0.016 0.020 0.964
#> GSM379730     3  0.1636      0.822 0.016 0.020 0.964
#> GSM379731     3  0.1636      0.822 0.016 0.020 0.964
#> GSM379724     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379725     3  0.1482      0.821 0.012 0.020 0.968
#> GSM379726     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379727     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379728     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379737     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379738     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379739     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379732     3  0.1636      0.822 0.016 0.020 0.964
#> GSM379733     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379734     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379735     3  0.1636      0.822 0.016 0.020 0.964
#> GSM379736     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379742     2  0.6305      0.213 0.000 0.516 0.484
#> GSM379743     3  0.1636      0.822 0.016 0.020 0.964
#> GSM379740     3  0.1129      0.819 0.004 0.020 0.976
#> GSM379741     2  0.6305      0.213 0.000 0.516 0.484

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.0707     0.8919 0.000 0.980 0.020 0.000
#> GSM379833     2  0.0707     0.8919 0.000 0.980 0.020 0.000
#> GSM379834     2  0.0707     0.8919 0.000 0.980 0.020 0.000
#> GSM379827     2  0.5744     0.7280 0.076 0.760 0.120 0.044
#> GSM379828     2  0.5744     0.7280 0.076 0.760 0.120 0.044
#> GSM379829     4  0.4595     0.5411 0.184 0.000 0.040 0.776
#> GSM379830     2  0.5661     0.7316 0.068 0.764 0.124 0.044
#> GSM379831     2  0.4866     0.7689 0.036 0.808 0.112 0.044
#> GSM379840     2  0.9229     0.2433 0.196 0.448 0.128 0.228
#> GSM379841     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379842     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379835     2  0.5810     0.7247 0.080 0.756 0.120 0.044
#> GSM379836     2  0.5810     0.7247 0.080 0.756 0.120 0.044
#> GSM379837     2  0.9264     0.2385 0.196 0.444 0.132 0.228
#> GSM379838     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379839     2  0.9264     0.2385 0.196 0.444 0.132 0.228
#> GSM379848     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379849     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379850     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379843     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379844     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379845     2  0.9264     0.2385 0.196 0.444 0.132 0.228
#> GSM379846     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379847     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379853     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379854     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379851     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379852     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379804     4  0.5969     0.3569 0.392 0.000 0.044 0.564
#> GSM379805     4  0.5969     0.3569 0.392 0.000 0.044 0.564
#> GSM379806     4  0.5969     0.3569 0.392 0.000 0.044 0.564
#> GSM379799     4  0.1059     0.6970 0.012 0.000 0.016 0.972
#> GSM379800     4  0.1059     0.6970 0.012 0.000 0.016 0.972
#> GSM379801     4  0.1059     0.6970 0.012 0.000 0.016 0.972
#> GSM379802     4  0.1389     0.7117 0.048 0.000 0.000 0.952
#> GSM379803     4  0.4957     0.5342 0.320 0.000 0.012 0.668
#> GSM379812     1  0.5018     0.7725 0.768 0.000 0.088 0.144
#> GSM379813     1  0.5512     0.7612 0.728 0.000 0.100 0.172
#> GSM379814     1  0.5867     0.7337 0.688 0.000 0.096 0.216
#> GSM379807     1  0.5867     0.7337 0.688 0.000 0.096 0.216
#> GSM379808     4  0.5969     0.3569 0.392 0.000 0.044 0.564
#> GSM379809     1  0.6215     0.5523 0.600 0.000 0.072 0.328
#> GSM379810     1  0.6215     0.5523 0.600 0.000 0.072 0.328
#> GSM379811     4  0.4957     0.5342 0.320 0.000 0.012 0.668
#> GSM379820     1  0.5867     0.7351 0.688 0.000 0.096 0.216
#> GSM379821     1  0.2494     0.7619 0.916 0.000 0.036 0.048
#> GSM379822     1  0.2494     0.7619 0.916 0.000 0.036 0.048
#> GSM379815     1  0.5867     0.7337 0.688 0.000 0.096 0.216
#> GSM379816     1  0.4094     0.7496 0.828 0.000 0.116 0.056
#> GSM379817     1  0.5512     0.7616 0.728 0.000 0.100 0.172
#> GSM379818     4  0.1389     0.7117 0.048 0.000 0.000 0.952
#> GSM379819     1  0.6575     0.4579 0.560 0.000 0.092 0.348
#> GSM379825     4  0.1389     0.7117 0.048 0.000 0.000 0.952
#> GSM379826     1  0.5867     0.7351 0.688 0.000 0.096 0.216
#> GSM379823     1  0.3004     0.7699 0.892 0.000 0.060 0.048
#> GSM379824     1  0.2494     0.7619 0.916 0.000 0.036 0.048
#> GSM379749     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379750     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379751     2  0.1302     0.8748 0.000 0.956 0.044 0.000
#> GSM379744     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379745     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379746     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379747     2  0.1022     0.8836 0.000 0.968 0.032 0.000
#> GSM379748     2  0.1022     0.8836 0.000 0.968 0.032 0.000
#> GSM379757     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379758     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379752     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379753     2  0.1302     0.8748 0.000 0.956 0.044 0.000
#> GSM379754     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379755     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379756     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379764     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379765     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379766     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379759     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379760     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379761     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379762     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379763     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379769     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379770     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379767     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379768     2  0.0000     0.9021 0.000 1.000 0.000 0.000
#> GSM379776     3  0.4655     0.6210 0.312 0.000 0.684 0.004
#> GSM379777     1  0.1854     0.7436 0.940 0.000 0.048 0.012
#> GSM379778     2  0.7635     0.1651 0.216 0.496 0.284 0.004
#> GSM379771     3  0.4655     0.6210 0.312 0.000 0.684 0.004
#> GSM379772     3  0.4655     0.6210 0.312 0.000 0.684 0.004
#> GSM379773     3  0.7673     0.3552 0.308 0.208 0.480 0.004
#> GSM379774     3  0.4655     0.6210 0.312 0.000 0.684 0.004
#> GSM379775     3  0.4655     0.6210 0.312 0.000 0.684 0.004
#> GSM379784     1  0.1557     0.7489 0.944 0.000 0.056 0.000
#> GSM379785     3  0.5137     0.3576 0.452 0.000 0.544 0.004
#> GSM379786     1  0.1557     0.7489 0.944 0.000 0.056 0.000
#> GSM379779     3  0.4655     0.6210 0.312 0.000 0.684 0.004
#> GSM379780     3  0.4655     0.6210 0.312 0.000 0.684 0.004
#> GSM379781     3  0.5097     0.4200 0.428 0.000 0.568 0.004
#> GSM379782     2  0.7635     0.1651 0.216 0.496 0.284 0.004
#> GSM379783     1  0.1557     0.7489 0.944 0.000 0.056 0.000
#> GSM379792     3  0.7677     0.1768 0.216 0.000 0.412 0.372
#> GSM379793     3  0.5880     0.6248 0.232 0.000 0.680 0.088
#> GSM379794     3  0.5880     0.6248 0.232 0.000 0.680 0.088
#> GSM379787     2  0.7635     0.1651 0.216 0.496 0.284 0.004
#> GSM379788     1  0.1557     0.7489 0.944 0.000 0.056 0.000
#> GSM379789     3  0.5723     0.6258 0.244 0.000 0.684 0.072
#> GSM379790     3  0.5723     0.6258 0.244 0.000 0.684 0.072
#> GSM379791     3  0.5880     0.6248 0.232 0.000 0.680 0.088
#> GSM379797     4  0.2773     0.6651 0.116 0.000 0.004 0.880
#> GSM379798     3  0.5880     0.6248 0.232 0.000 0.680 0.088
#> GSM379795     3  0.5880     0.6248 0.232 0.000 0.680 0.088
#> GSM379796     3  0.7677     0.1768 0.216 0.000 0.412 0.372
#> GSM379721     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379722     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379723     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379716     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379717     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379718     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379719     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379720     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379729     3  0.3688     0.6328 0.208 0.000 0.792 0.000
#> GSM379730     3  0.3688     0.6328 0.208 0.000 0.792 0.000
#> GSM379731     3  0.3688     0.6328 0.208 0.000 0.792 0.000
#> GSM379724     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379725     3  0.2408     0.7147 0.104 0.000 0.896 0.000
#> GSM379726     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379727     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379728     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379737     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379738     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379739     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379732     3  0.3688     0.6328 0.208 0.000 0.792 0.000
#> GSM379733     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379734     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379735     3  0.3688     0.6328 0.208 0.000 0.792 0.000
#> GSM379736     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379742     3  0.5000    -0.0862 0.000 0.496 0.504 0.000
#> GSM379743     3  0.3688     0.6328 0.208 0.000 0.792 0.000
#> GSM379740     3  0.0000     0.7570 0.000 0.000 1.000 0.000
#> GSM379741     3  0.5000    -0.0862 0.000 0.496 0.504 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     2  0.4182     0.1681 0.000 0.600 0.000 0.000 0.400
#> GSM379833     2  0.4182     0.1681 0.000 0.600 0.000 0.000 0.400
#> GSM379834     2  0.4182     0.1681 0.000 0.600 0.000 0.000 0.400
#> GSM379827     5  0.4958     0.6479 0.000 0.372 0.036 0.000 0.592
#> GSM379828     5  0.4958     0.6479 0.000 0.372 0.036 0.000 0.592
#> GSM379829     4  0.4161     0.4245 0.000 0.000 0.000 0.608 0.392
#> GSM379830     5  0.5037     0.6390 0.000 0.376 0.040 0.000 0.584
#> GSM379831     5  0.5131     0.5183 0.000 0.420 0.040 0.000 0.540
#> GSM379840     5  0.4263     0.6075 0.012 0.060 0.040 0.064 0.824
#> GSM379841     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379842     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379835     5  0.4946     0.6520 0.000 0.368 0.036 0.000 0.596
#> GSM379836     5  0.4946     0.6520 0.000 0.368 0.036 0.000 0.596
#> GSM379837     5  0.4197     0.6072 0.012 0.056 0.040 0.064 0.828
#> GSM379838     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379839     5  0.4197     0.6072 0.012 0.056 0.040 0.064 0.828
#> GSM379848     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379849     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379850     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379843     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379844     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379845     5  0.4197     0.6072 0.012 0.056 0.040 0.064 0.828
#> GSM379846     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379847     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379853     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379854     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379851     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379852     2  0.3837     0.4402 0.000 0.692 0.000 0.000 0.308
#> GSM379804     4  0.5633     0.2258 0.372 0.000 0.044 0.564 0.020
#> GSM379805     4  0.5633     0.2258 0.372 0.000 0.044 0.564 0.020
#> GSM379806     4  0.5633     0.2258 0.372 0.000 0.044 0.564 0.020
#> GSM379799     4  0.1341     0.6213 0.000 0.000 0.000 0.944 0.056
#> GSM379800     4  0.1341     0.6213 0.000 0.000 0.000 0.944 0.056
#> GSM379801     4  0.1341     0.6213 0.000 0.000 0.000 0.944 0.056
#> GSM379802     4  0.0000     0.6244 0.000 0.000 0.000 1.000 0.000
#> GSM379803     4  0.4213     0.4107 0.308 0.000 0.012 0.680 0.000
#> GSM379812     1  0.3748     0.7531 0.836 0.000 0.056 0.088 0.020
#> GSM379813     1  0.4303     0.7456 0.796 0.000 0.068 0.116 0.020
#> GSM379814     1  0.4814     0.7217 0.748 0.000 0.068 0.164 0.020
#> GSM379807     1  0.4814     0.7217 0.748 0.000 0.068 0.164 0.020
#> GSM379808     4  0.5633     0.2258 0.372 0.000 0.044 0.564 0.020
#> GSM379809     1  0.5252     0.5712 0.660 0.000 0.044 0.276 0.020
#> GSM379810     1  0.5252     0.5712 0.660 0.000 0.044 0.276 0.020
#> GSM379811     4  0.4213     0.4107 0.308 0.000 0.012 0.680 0.000
#> GSM379820     1  0.4583     0.7218 0.760 0.000 0.068 0.160 0.012
#> GSM379821     1  0.0404     0.7263 0.988 0.000 0.000 0.000 0.012
#> GSM379822     1  0.0404     0.7263 0.988 0.000 0.000 0.000 0.012
#> GSM379815     1  0.4814     0.7217 0.748 0.000 0.068 0.164 0.020
#> GSM379816     1  0.2894     0.7218 0.876 0.000 0.084 0.004 0.036
#> GSM379817     1  0.4059     0.7449 0.808 0.000 0.068 0.112 0.012
#> GSM379818     4  0.0000     0.6244 0.000 0.000 0.000 1.000 0.000
#> GSM379819     1  0.5666     0.4975 0.592 0.000 0.068 0.328 0.012
#> GSM379825     4  0.0000     0.6244 0.000 0.000 0.000 1.000 0.000
#> GSM379826     1  0.4583     0.7218 0.760 0.000 0.068 0.160 0.012
#> GSM379823     1  0.1106     0.7344 0.964 0.000 0.024 0.000 0.012
#> GSM379824     1  0.0404     0.7263 0.988 0.000 0.000 0.000 0.012
#> GSM379749     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379750     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379751     2  0.3690     0.5065 0.000 0.764 0.012 0.000 0.224
#> GSM379744     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379745     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379746     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379747     2  0.3519     0.5232 0.000 0.776 0.008 0.000 0.216
#> GSM379748     2  0.3519     0.5232 0.000 0.776 0.008 0.000 0.216
#> GSM379757     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379758     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379752     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379753     2  0.3690     0.5065 0.000 0.764 0.012 0.000 0.224
#> GSM379754     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379755     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379756     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379764     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379765     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379766     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379759     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379760     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379761     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379762     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379763     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379769     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379770     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379767     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379768     2  0.0000     0.6775 0.000 1.000 0.000 0.000 0.000
#> GSM379776     3  0.5952     0.5854 0.136 0.000 0.560 0.000 0.304
#> GSM379777     1  0.3475     0.6605 0.804 0.000 0.004 0.012 0.180
#> GSM379778     2  0.7047     0.0255 0.040 0.496 0.164 0.000 0.300
#> GSM379771     3  0.5952     0.5854 0.136 0.000 0.560 0.000 0.304
#> GSM379772     3  0.5952     0.5854 0.136 0.000 0.560 0.000 0.304
#> GSM379773     3  0.8224     0.3284 0.132 0.208 0.356 0.000 0.304
#> GSM379774     3  0.5952     0.5854 0.136 0.000 0.560 0.000 0.304
#> GSM379775     3  0.5952     0.5854 0.136 0.000 0.560 0.000 0.304
#> GSM379784     1  0.3318     0.6668 0.808 0.000 0.012 0.000 0.180
#> GSM379785     3  0.6608     0.3602 0.300 0.000 0.456 0.000 0.244
#> GSM379786     1  0.3318     0.6668 0.808 0.000 0.012 0.000 0.180
#> GSM379779     3  0.5952     0.5854 0.136 0.000 0.560 0.000 0.304
#> GSM379780     3  0.5952     0.5854 0.136 0.000 0.560 0.000 0.304
#> GSM379781     3  0.6552     0.4138 0.276 0.000 0.476 0.000 0.248
#> GSM379782     2  0.7047     0.0255 0.040 0.496 0.164 0.000 0.300
#> GSM379783     1  0.3318     0.6668 0.808 0.000 0.012 0.000 0.180
#> GSM379792     4  0.8080    -0.0560 0.132 0.000 0.328 0.372 0.168
#> GSM379793     3  0.7038     0.5736 0.144 0.000 0.560 0.076 0.220
#> GSM379794     3  0.7038     0.5736 0.144 0.000 0.560 0.076 0.220
#> GSM379787     2  0.7047     0.0255 0.040 0.496 0.164 0.000 0.300
#> GSM379788     1  0.3318     0.6668 0.808 0.000 0.012 0.000 0.180
#> GSM379789     3  0.6891     0.5790 0.136 0.000 0.560 0.060 0.244
#> GSM379790     3  0.6891     0.5790 0.136 0.000 0.560 0.060 0.244
#> GSM379791     3  0.7038     0.5736 0.144 0.000 0.560 0.076 0.220
#> GSM379797     4  0.2036     0.5933 0.024 0.000 0.000 0.920 0.056
#> GSM379798     3  0.7038     0.5736 0.144 0.000 0.560 0.076 0.220
#> GSM379795     3  0.7038     0.5736 0.144 0.000 0.560 0.076 0.220
#> GSM379796     4  0.8080    -0.0560 0.132 0.000 0.328 0.372 0.168
#> GSM379721     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379722     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379723     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379716     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379717     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379718     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379719     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379720     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379729     3  0.3562     0.6299 0.196 0.000 0.788 0.000 0.016
#> GSM379730     3  0.3562     0.6299 0.196 0.000 0.788 0.000 0.016
#> GSM379731     3  0.3562     0.6299 0.196 0.000 0.788 0.000 0.016
#> GSM379724     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379725     3  0.2233     0.7068 0.104 0.000 0.892 0.000 0.004
#> GSM379726     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379727     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379728     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379737     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379738     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379739     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379732     3  0.3562     0.6299 0.196 0.000 0.788 0.000 0.016
#> GSM379733     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379734     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379735     3  0.3462     0.6297 0.196 0.000 0.792 0.000 0.012
#> GSM379736     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379742     2  0.4747    -0.0726 0.000 0.496 0.488 0.000 0.016
#> GSM379743     3  0.3462     0.6297 0.196 0.000 0.792 0.000 0.012
#> GSM379740     3  0.0000     0.7482 0.000 0.000 1.000 0.000 0.000
#> GSM379741     2  0.4747    -0.0726 0.000 0.496 0.488 0.000 0.016

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     2  0.3847     0.0746 0.000 0.544 0.000 0.000 0.456 0.000
#> GSM379833     2  0.3847     0.0746 0.000 0.544 0.000 0.000 0.456 0.000
#> GSM379834     2  0.3847     0.0746 0.000 0.544 0.000 0.000 0.456 0.000
#> GSM379827     5  0.3482     0.6777 0.000 0.316 0.000 0.000 0.684 0.000
#> GSM379828     5  0.3482     0.6777 0.000 0.316 0.000 0.000 0.684 0.000
#> GSM379829     6  0.6312     0.4580 0.008 0.000 0.112 0.036 0.404 0.440
#> GSM379830     5  0.3636     0.6694 0.004 0.320 0.000 0.000 0.676 0.000
#> GSM379831     5  0.3795     0.5597 0.004 0.364 0.000 0.000 0.632 0.000
#> GSM379840     5  0.1844     0.5755 0.012 0.004 0.000 0.024 0.932 0.028
#> GSM379841     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379842     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379835     5  0.3464     0.6814 0.000 0.312 0.000 0.000 0.688 0.000
#> GSM379836     5  0.3464     0.6814 0.000 0.312 0.000 0.000 0.688 0.000
#> GSM379837     5  0.1700     0.5753 0.012 0.000 0.000 0.024 0.936 0.028
#> GSM379838     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379839     5  0.1700     0.5753 0.012 0.000 0.000 0.024 0.936 0.028
#> GSM379848     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379849     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379850     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379843     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379844     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379845     5  0.1700     0.5753 0.012 0.000 0.000 0.024 0.936 0.028
#> GSM379846     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379847     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379853     2  0.3563     0.4336 0.000 0.664 0.000 0.000 0.336 0.000
#> GSM379854     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379851     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379852     2  0.3578     0.4293 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379804     4  0.4847     0.0175 0.032 0.000 0.000 0.492 0.012 0.464
#> GSM379805     4  0.4847     0.0175 0.032 0.000 0.000 0.492 0.012 0.464
#> GSM379806     4  0.4847     0.0175 0.032 0.000 0.000 0.492 0.012 0.464
#> GSM379799     6  0.3670     0.7185 0.000 0.000 0.112 0.024 0.052 0.812
#> GSM379800     6  0.3670     0.7185 0.000 0.000 0.112 0.024 0.052 0.812
#> GSM379801     6  0.3670     0.7185 0.000 0.000 0.112 0.024 0.052 0.812
#> GSM379802     6  0.2201     0.7188 0.000 0.000 0.076 0.028 0.000 0.896
#> GSM379803     6  0.3789     0.2371 0.000 0.000 0.000 0.416 0.000 0.584
#> GSM379812     4  0.3437     0.6290 0.056 0.000 0.056 0.848 0.012 0.028
#> GSM379813     4  0.2909     0.6297 0.064 0.000 0.016 0.876 0.012 0.032
#> GSM379814     4  0.2984     0.6192 0.064 0.000 0.000 0.860 0.012 0.064
#> GSM379807     4  0.2984     0.6192 0.064 0.000 0.000 0.860 0.012 0.064
#> GSM379808     4  0.4847     0.0175 0.032 0.000 0.000 0.492 0.012 0.464
#> GSM379809     4  0.3836     0.5370 0.040 0.000 0.000 0.772 0.012 0.176
#> GSM379810     4  0.3836     0.5370 0.040 0.000 0.000 0.772 0.012 0.176
#> GSM379811     6  0.3789     0.2371 0.000 0.000 0.000 0.416 0.000 0.584
#> GSM379820     4  0.2630     0.6199 0.064 0.000 0.000 0.872 0.000 0.064
#> GSM379821     4  0.3581     0.5714 0.004 0.000 0.188 0.780 0.024 0.004
#> GSM379822     4  0.3581     0.5714 0.004 0.000 0.188 0.780 0.024 0.004
#> GSM379815     4  0.2984     0.6192 0.064 0.000 0.000 0.860 0.012 0.064
#> GSM379816     4  0.4744     0.5762 0.064 0.000 0.208 0.704 0.020 0.004
#> GSM379817     4  0.2555     0.6296 0.064 0.000 0.016 0.888 0.000 0.032
#> GSM379818     6  0.2201     0.7188 0.000 0.000 0.076 0.028 0.000 0.896
#> GSM379819     4  0.4253     0.4895 0.064 0.000 0.000 0.704 0.000 0.232
#> GSM379825     6  0.2488     0.7149 0.000 0.000 0.076 0.044 0.000 0.880
#> GSM379826     4  0.2630     0.6199 0.064 0.000 0.000 0.872 0.000 0.064
#> GSM379823     4  0.4115     0.5792 0.028 0.000 0.188 0.756 0.024 0.004
#> GSM379824     4  0.3581     0.5714 0.004 0.000 0.188 0.780 0.024 0.004
#> GSM379749     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379750     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379751     2  0.3076     0.5264 0.000 0.760 0.000 0.000 0.240 0.000
#> GSM379744     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379745     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379746     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379747     2  0.2996     0.5406 0.000 0.772 0.000 0.000 0.228 0.000
#> GSM379748     2  0.2996     0.5406 0.000 0.772 0.000 0.000 0.228 0.000
#> GSM379757     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379758     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379752     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379753     2  0.3076     0.5264 0.000 0.760 0.000 0.000 0.240 0.000
#> GSM379754     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379755     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379756     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379764     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379765     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379766     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379759     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379760     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379761     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379762     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379763     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379769     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379770     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379767     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379768     2  0.0000     0.6851 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379776     1  0.1387     0.8493 0.932 0.000 0.000 0.000 0.068 0.000
#> GSM379777     4  0.7149     0.4333 0.240 0.000 0.184 0.472 0.092 0.012
#> GSM379778     2  0.5108    -0.0648 0.432 0.496 0.000 0.004 0.068 0.000
#> GSM379771     1  0.1387     0.8493 0.932 0.000 0.000 0.000 0.068 0.000
#> GSM379772     1  0.1387     0.8493 0.932 0.000 0.000 0.000 0.068 0.000
#> GSM379773     1  0.4148     0.6028 0.724 0.208 0.000 0.000 0.068 0.000
#> GSM379774     1  0.1387     0.8493 0.932 0.000 0.000 0.000 0.068 0.000
#> GSM379775     1  0.1387     0.8493 0.932 0.000 0.000 0.000 0.068 0.000
#> GSM379784     4  0.6866     0.4404 0.248 0.000 0.184 0.476 0.092 0.000
#> GSM379785     1  0.3985     0.7138 0.768 0.000 0.008 0.156 0.068 0.000
#> GSM379786     4  0.6866     0.4404 0.248 0.000 0.184 0.476 0.092 0.000
#> GSM379779     1  0.1387     0.8493 0.932 0.000 0.000 0.000 0.068 0.000
#> GSM379780     1  0.1387     0.8493 0.932 0.000 0.000 0.000 0.068 0.000
#> GSM379781     1  0.3758     0.7417 0.792 0.000 0.008 0.132 0.068 0.000
#> GSM379782     2  0.5108    -0.0648 0.432 0.496 0.000 0.004 0.068 0.000
#> GSM379783     4  0.6866     0.4404 0.248 0.000 0.184 0.476 0.092 0.000
#> GSM379792     1  0.5095     0.5082 0.656 0.000 0.004 0.048 0.036 0.256
#> GSM379793     1  0.1225     0.8319 0.952 0.000 0.000 0.012 0.036 0.000
#> GSM379794     1  0.1225     0.8319 0.952 0.000 0.000 0.012 0.036 0.000
#> GSM379787     2  0.5108    -0.0648 0.432 0.496 0.000 0.004 0.068 0.000
#> GSM379788     4  0.6866     0.4404 0.248 0.000 0.184 0.476 0.092 0.000
#> GSM379789     1  0.0603     0.8453 0.980 0.000 0.000 0.004 0.016 0.000
#> GSM379790     1  0.0603     0.8453 0.980 0.000 0.000 0.004 0.016 0.000
#> GSM379791     1  0.1225     0.8319 0.952 0.000 0.000 0.012 0.036 0.000
#> GSM379797     6  0.5308     0.6166 0.108 0.000 0.076 0.056 0.036 0.724
#> GSM379798     1  0.1225     0.8319 0.952 0.000 0.000 0.012 0.036 0.000
#> GSM379795     1  0.1225     0.8319 0.952 0.000 0.000 0.012 0.036 0.000
#> GSM379796     1  0.5095     0.5082 0.656 0.000 0.004 0.048 0.036 0.256
#> GSM379721     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379722     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379723     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379716     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379717     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379718     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379719     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379720     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379729     3  0.3945     0.7318 0.212 0.000 0.748 0.028 0.008 0.004
#> GSM379730     3  0.3945     0.7318 0.212 0.000 0.748 0.028 0.008 0.004
#> GSM379731     3  0.3945     0.7318 0.212 0.000 0.748 0.028 0.008 0.004
#> GSM379724     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379725     3  0.4423     0.8224 0.312 0.000 0.652 0.024 0.008 0.004
#> GSM379726     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379727     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379728     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379737     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379738     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379739     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379732     3  0.3945     0.7318 0.212 0.000 0.748 0.028 0.008 0.004
#> GSM379733     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379734     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379735     3  0.3888     0.7362 0.204 0.000 0.756 0.028 0.008 0.004
#> GSM379736     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379742     2  0.4394    -0.1042 0.016 0.496 0.484 0.004 0.000 0.000
#> GSM379743     3  0.3888     0.7362 0.204 0.000 0.756 0.028 0.008 0.004
#> GSM379740     3  0.3695     0.9106 0.376 0.000 0.624 0.000 0.000 0.000
#> GSM379741     2  0.4394    -0.1042 0.016 0.496 0.484 0.004 0.000 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-SD-hclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-SD-hclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-SD-hclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-SD-hclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-SD-hclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-SD-hclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-SD-hclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-SD-hclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-SD-hclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-SD-hclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-SD-hclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-SD-hclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-SD-hclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-SD-hclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-SD-hclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-SD-hclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-SD-hclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-SD-hclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-SD-hclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-SD-hclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk SD-hclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-SD-hclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-SD-hclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-SD-hclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-SD-hclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-SD-hclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk SD-hclust-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>             n individual(p) time(p) agent(p) k
#> SD:hclust 124      3.50e-21   1.000   1.0000 2
#> SD:hclust 120      3.71e-32   0.995   0.0244 3
#> SD:hclust 120      2.08e-37   0.984   0.0148 4
#> SD:hclust 104      2.54e-51   0.999   0.0576 5
#> SD:hclust 104      6.25e-74   1.000   0.0893 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

SD:kmeans**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["SD", "kmeans"]
# you can also extract it by
# res = res_list["SD:kmeans"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#>   Subgroups are detected by 'kmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk SD-kmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk SD-kmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.973       0.979         0.4822 0.513   0.513
#> 3 3 0.623           0.705       0.777         0.3174 0.788   0.601
#> 4 4 0.704           0.876       0.749         0.1411 0.904   0.729
#> 5 5 0.704           0.851       0.799         0.0695 0.918   0.701
#> 6 6 0.810           0.754       0.775         0.0452 0.994   0.970

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000      0.982 0.000 1.000
#> GSM379833     2  0.0000      0.982 0.000 1.000
#> GSM379834     2  0.0000      0.982 0.000 1.000
#> GSM379827     2  0.0000      0.982 0.000 1.000
#> GSM379828     2  0.0000      0.982 0.000 1.000
#> GSM379829     1  0.1843      0.987 0.972 0.028
#> GSM379830     2  0.0000      0.982 0.000 1.000
#> GSM379831     2  0.0000      0.982 0.000 1.000
#> GSM379840     2  0.0000      0.982 0.000 1.000
#> GSM379841     2  0.0000      0.982 0.000 1.000
#> GSM379842     2  0.0000      0.982 0.000 1.000
#> GSM379835     2  0.0000      0.982 0.000 1.000
#> GSM379836     2  0.0000      0.982 0.000 1.000
#> GSM379837     1  0.7376      0.772 0.792 0.208
#> GSM379838     2  0.0000      0.982 0.000 1.000
#> GSM379839     2  0.0000      0.982 0.000 1.000
#> GSM379848     2  0.0376      0.982 0.004 0.996
#> GSM379849     2  0.0376      0.982 0.004 0.996
#> GSM379850     2  0.0376      0.982 0.004 0.996
#> GSM379843     2  0.0000      0.982 0.000 1.000
#> GSM379844     2  0.0000      0.982 0.000 1.000
#> GSM379845     2  0.0000      0.982 0.000 1.000
#> GSM379846     2  0.0376      0.982 0.004 0.996
#> GSM379847     2  0.0376      0.982 0.004 0.996
#> GSM379853     2  0.0376      0.982 0.004 0.996
#> GSM379854     2  0.0376      0.982 0.004 0.996
#> GSM379851     2  0.0376      0.982 0.004 0.996
#> GSM379852     2  0.0376      0.982 0.004 0.996
#> GSM379804     1  0.1843      0.987 0.972 0.028
#> GSM379805     1  0.1843      0.987 0.972 0.028
#> GSM379806     1  0.1843      0.987 0.972 0.028
#> GSM379799     1  0.1843      0.987 0.972 0.028
#> GSM379800     1  0.1843      0.987 0.972 0.028
#> GSM379801     1  0.1843      0.987 0.972 0.028
#> GSM379802     1  0.1843      0.987 0.972 0.028
#> GSM379803     1  0.1843      0.987 0.972 0.028
#> GSM379812     1  0.1843      0.987 0.972 0.028
#> GSM379813     1  0.1633      0.987 0.976 0.024
#> GSM379814     1  0.1633      0.987 0.976 0.024
#> GSM379807     1  0.1633      0.987 0.976 0.024
#> GSM379808     1  0.1843      0.987 0.972 0.028
#> GSM379809     1  0.1843      0.987 0.972 0.028
#> GSM379810     1  0.1843      0.987 0.972 0.028
#> GSM379811     1  0.1843      0.987 0.972 0.028
#> GSM379820     1  0.1633      0.987 0.976 0.024
#> GSM379821     1  0.1633      0.987 0.976 0.024
#> GSM379822     1  0.1633      0.987 0.976 0.024
#> GSM379815     1  0.1843      0.987 0.972 0.028
#> GSM379816     1  0.1843      0.987 0.972 0.028
#> GSM379817     1  0.1633      0.987 0.976 0.024
#> GSM379818     1  0.1843      0.987 0.972 0.028
#> GSM379819     1  0.1633      0.987 0.976 0.024
#> GSM379825     1  0.1633      0.987 0.976 0.024
#> GSM379826     1  0.1633      0.987 0.976 0.024
#> GSM379823     1  0.1633      0.987 0.976 0.024
#> GSM379824     1  0.1633      0.987 0.976 0.024
#> GSM379749     2  0.0000      0.982 0.000 1.000
#> GSM379750     2  0.0000      0.982 0.000 1.000
#> GSM379751     2  0.0000      0.982 0.000 1.000
#> GSM379744     2  0.0000      0.982 0.000 1.000
#> GSM379745     2  0.0000      0.982 0.000 1.000
#> GSM379746     2  0.0000      0.982 0.000 1.000
#> GSM379747     2  0.0000      0.982 0.000 1.000
#> GSM379748     2  0.0000      0.982 0.000 1.000
#> GSM379757     2  0.0000      0.982 0.000 1.000
#> GSM379758     2  0.0376      0.982 0.004 0.996
#> GSM379752     2  0.0000      0.982 0.000 1.000
#> GSM379753     2  0.0000      0.982 0.000 1.000
#> GSM379754     2  0.0000      0.982 0.000 1.000
#> GSM379755     2  0.0000      0.982 0.000 1.000
#> GSM379756     2  0.0000      0.982 0.000 1.000
#> GSM379764     2  0.0376      0.982 0.004 0.996
#> GSM379765     2  0.0376      0.982 0.004 0.996
#> GSM379766     2  0.0376      0.982 0.004 0.996
#> GSM379759     2  0.0376      0.982 0.004 0.996
#> GSM379760     2  0.0376      0.982 0.004 0.996
#> GSM379761     2  0.0376      0.982 0.004 0.996
#> GSM379762     2  0.0376      0.982 0.004 0.996
#> GSM379763     2  0.0376      0.982 0.004 0.996
#> GSM379769     2  0.0376      0.982 0.004 0.996
#> GSM379770     2  0.0376      0.982 0.004 0.996
#> GSM379767     2  0.0376      0.982 0.004 0.996
#> GSM379768     2  0.0376      0.982 0.004 0.996
#> GSM379776     1  0.1843      0.987 0.972 0.028
#> GSM379777     1  0.1633      0.987 0.976 0.024
#> GSM379778     1  0.1633      0.987 0.976 0.024
#> GSM379771     1  0.1843      0.987 0.972 0.028
#> GSM379772     1  0.1843      0.987 0.972 0.028
#> GSM379773     1  0.1843      0.987 0.972 0.028
#> GSM379774     1  0.1843      0.987 0.972 0.028
#> GSM379775     1  0.1843      0.987 0.972 0.028
#> GSM379784     1  0.1633      0.987 0.976 0.024
#> GSM379785     1  0.1633      0.987 0.976 0.024
#> GSM379786     1  0.1633      0.987 0.976 0.024
#> GSM379779     1  0.1633      0.987 0.976 0.024
#> GSM379780     1  0.1633      0.987 0.976 0.024
#> GSM379781     1  0.1633      0.987 0.976 0.024
#> GSM379782     2  0.6887      0.779 0.184 0.816
#> GSM379783     1  0.1633      0.987 0.976 0.024
#> GSM379792     1  0.1633      0.987 0.976 0.024
#> GSM379793     1  0.1633      0.987 0.976 0.024
#> GSM379794     1  0.1633      0.987 0.976 0.024
#> GSM379787     2  0.9580      0.394 0.380 0.620
#> GSM379788     1  0.1633      0.987 0.976 0.024
#> GSM379789     1  0.1633      0.987 0.976 0.024
#> GSM379790     1  0.1633      0.987 0.976 0.024
#> GSM379791     1  0.1633      0.987 0.976 0.024
#> GSM379797     1  0.1633      0.987 0.976 0.024
#> GSM379798     1  0.1633      0.987 0.976 0.024
#> GSM379795     1  0.1633      0.987 0.976 0.024
#> GSM379796     1  0.1633      0.987 0.976 0.024
#> GSM379721     1  0.0938      0.977 0.988 0.012
#> GSM379722     1  0.0938      0.977 0.988 0.012
#> GSM379723     1  0.0938      0.977 0.988 0.012
#> GSM379716     1  0.0938      0.977 0.988 0.012
#> GSM379717     1  0.0938      0.977 0.988 0.012
#> GSM379718     1  0.0938      0.977 0.988 0.012
#> GSM379719     1  0.0938      0.977 0.988 0.012
#> GSM379720     1  0.0938      0.977 0.988 0.012
#> GSM379729     1  0.0672      0.978 0.992 0.008
#> GSM379730     1  0.0672      0.978 0.992 0.008
#> GSM379731     1  0.0672      0.978 0.992 0.008
#> GSM379724     1  0.0938      0.977 0.988 0.012
#> GSM379725     1  0.0938      0.977 0.988 0.012
#> GSM379726     1  0.0938      0.977 0.988 0.012
#> GSM379727     1  0.0938      0.977 0.988 0.012
#> GSM379728     1  0.0938      0.977 0.988 0.012
#> GSM379737     1  0.0672      0.978 0.992 0.008
#> GSM379738     1  0.0672      0.978 0.992 0.008
#> GSM379739     1  0.0672      0.978 0.992 0.008
#> GSM379732     1  0.0672      0.978 0.992 0.008
#> GSM379733     1  0.0672      0.978 0.992 0.008
#> GSM379734     1  0.0672      0.978 0.992 0.008
#> GSM379735     1  0.0672      0.978 0.992 0.008
#> GSM379736     1  0.0000      0.977 1.000 0.000
#> GSM379742     2  0.6801      0.809 0.180 0.820
#> GSM379743     1  0.0672      0.978 0.992 0.008
#> GSM379740     1  0.0672      0.978 0.992 0.008
#> GSM379741     2  0.6801      0.809 0.180 0.820

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.4346      0.917 0.184 0.816 0.000
#> GSM379833     2  0.4346      0.917 0.184 0.816 0.000
#> GSM379834     2  0.4346      0.917 0.184 0.816 0.000
#> GSM379827     2  0.4346      0.917 0.184 0.816 0.000
#> GSM379828     2  0.4346      0.917 0.184 0.816 0.000
#> GSM379829     1  0.3695      0.607 0.880 0.012 0.108
#> GSM379830     2  0.4346      0.917 0.184 0.816 0.000
#> GSM379831     2  0.4346      0.917 0.184 0.816 0.000
#> GSM379840     2  0.4346      0.917 0.184 0.816 0.000
#> GSM379841     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379842     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379835     2  0.4346      0.917 0.184 0.816 0.000
#> GSM379836     2  0.4346      0.917 0.184 0.816 0.000
#> GSM379837     1  0.7809     -0.156 0.568 0.372 0.060
#> GSM379838     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379839     2  0.6295      0.543 0.472 0.528 0.000
#> GSM379848     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379849     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379850     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379843     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379844     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379845     2  0.4346      0.917 0.184 0.816 0.000
#> GSM379846     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379847     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379853     2  0.3816      0.924 0.148 0.852 0.000
#> GSM379854     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379851     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379852     2  0.3686      0.924 0.140 0.860 0.000
#> GSM379804     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379805     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379806     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379799     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379800     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379801     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379802     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379803     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379812     1  0.5291      0.891 0.732 0.000 0.268
#> GSM379813     1  0.5291      0.891 0.732 0.000 0.268
#> GSM379814     1  0.5291      0.891 0.732 0.000 0.268
#> GSM379807     1  0.5291      0.891 0.732 0.000 0.268
#> GSM379808     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379809     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379810     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379811     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379820     1  0.5291      0.891 0.732 0.000 0.268
#> GSM379821     1  0.5291      0.891 0.732 0.000 0.268
#> GSM379822     1  0.5291      0.891 0.732 0.000 0.268
#> GSM379815     1  0.5216      0.890 0.740 0.000 0.260
#> GSM379816     1  0.6252      0.455 0.556 0.000 0.444
#> GSM379817     1  0.5291      0.891 0.732 0.000 0.268
#> GSM379818     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379819     1  0.5291      0.891 0.732 0.000 0.268
#> GSM379825     1  0.5397      0.890 0.720 0.000 0.280
#> GSM379826     1  0.5291      0.891 0.732 0.000 0.268
#> GSM379823     1  0.5291      0.891 0.732 0.000 0.268
#> GSM379824     1  0.5291      0.891 0.732 0.000 0.268
#> GSM379749     2  0.1860      0.924 0.052 0.948 0.000
#> GSM379750     2  0.1860      0.924 0.052 0.948 0.000
#> GSM379751     2  0.1964      0.924 0.056 0.944 0.000
#> GSM379744     2  0.1964      0.924 0.056 0.944 0.000
#> GSM379745     2  0.1964      0.924 0.056 0.944 0.000
#> GSM379746     2  0.1860      0.924 0.052 0.948 0.000
#> GSM379747     2  0.1964      0.924 0.056 0.944 0.000
#> GSM379748     2  0.1964      0.924 0.056 0.944 0.000
#> GSM379757     2  0.0424      0.925 0.008 0.992 0.000
#> GSM379758     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379752     2  0.1860      0.924 0.052 0.948 0.000
#> GSM379753     2  0.1964      0.924 0.056 0.944 0.000
#> GSM379754     2  0.0000      0.926 0.000 1.000 0.000
#> GSM379755     2  0.0000      0.926 0.000 1.000 0.000
#> GSM379756     2  0.0000      0.926 0.000 1.000 0.000
#> GSM379764     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379765     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379766     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379759     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379760     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379761     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379762     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379763     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379769     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379770     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379767     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379768     2  0.0592      0.924 0.012 0.988 0.000
#> GSM379776     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379777     1  0.5178      0.734 0.744 0.000 0.256
#> GSM379778     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379771     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379772     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379773     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379774     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379775     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379784     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379785     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379786     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379779     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379780     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379781     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379782     3  0.9464      0.207 0.180 0.404 0.416
#> GSM379783     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379792     1  0.5706      0.591 0.680 0.000 0.320
#> GSM379793     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379794     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379787     3  0.9777      0.213 0.248 0.324 0.428
#> GSM379788     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379789     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379790     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379791     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379797     1  0.4555      0.811 0.800 0.000 0.200
#> GSM379798     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379795     3  0.6308      0.186 0.492 0.000 0.508
#> GSM379796     1  0.5706      0.591 0.680 0.000 0.320
#> GSM379721     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379722     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379723     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379716     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379717     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379718     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379719     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379720     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379729     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379730     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379731     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379724     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379725     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379726     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379727     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379728     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379737     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379738     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379739     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379732     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379733     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379734     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379735     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379736     3  0.0424      0.633 0.008 0.000 0.992
#> GSM379742     3  0.5315      0.442 0.012 0.216 0.772
#> GSM379743     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379740     3  0.0000      0.634 0.000 0.000 1.000
#> GSM379741     3  0.5315      0.442 0.012 0.216 0.772

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.3734      0.772 0.044 0.848 0.000 0.108
#> GSM379833     2  0.3734      0.772 0.044 0.848 0.000 0.108
#> GSM379834     2  0.3734      0.772 0.044 0.848 0.000 0.108
#> GSM379827     2  0.4090      0.769 0.044 0.832 0.004 0.120
#> GSM379828     2  0.4090      0.769 0.044 0.832 0.004 0.120
#> GSM379829     4  0.6428      0.473 0.068 0.212 0.036 0.684
#> GSM379830     2  0.4090      0.769 0.044 0.832 0.004 0.120
#> GSM379831     2  0.4090      0.769 0.044 0.832 0.004 0.120
#> GSM379840     2  0.4033      0.769 0.044 0.836 0.004 0.116
#> GSM379841     2  0.0000      0.798 0.000 1.000 0.000 0.000
#> GSM379842     2  0.0672      0.796 0.008 0.984 0.000 0.008
#> GSM379835     2  0.4090      0.769 0.044 0.832 0.004 0.120
#> GSM379836     2  0.4090      0.769 0.044 0.832 0.004 0.120
#> GSM379837     2  0.6160      0.514 0.060 0.616 0.004 0.320
#> GSM379838     2  0.0000      0.798 0.000 1.000 0.000 0.000
#> GSM379839     2  0.6160      0.514 0.060 0.616 0.004 0.320
#> GSM379848     2  0.0779      0.797 0.004 0.980 0.000 0.016
#> GSM379849     2  0.0927      0.797 0.008 0.976 0.000 0.016
#> GSM379850     2  0.0927      0.797 0.008 0.976 0.000 0.016
#> GSM379843     2  0.0672      0.796 0.008 0.984 0.000 0.008
#> GSM379844     2  0.0000      0.798 0.000 1.000 0.000 0.000
#> GSM379845     2  0.4033      0.769 0.044 0.836 0.004 0.116
#> GSM379846     2  0.0188      0.798 0.004 0.996 0.000 0.000
#> GSM379847     2  0.0779      0.797 0.004 0.980 0.000 0.016
#> GSM379853     2  0.1510      0.795 0.016 0.956 0.000 0.028
#> GSM379854     2  0.0927      0.797 0.008 0.976 0.000 0.016
#> GSM379851     2  0.0927      0.797 0.008 0.976 0.000 0.016
#> GSM379852     2  0.0927      0.797 0.008 0.976 0.000 0.016
#> GSM379804     4  0.5631      0.951 0.224 0.000 0.076 0.700
#> GSM379805     4  0.5727      0.950 0.236 0.000 0.076 0.688
#> GSM379806     4  0.5727      0.950 0.236 0.000 0.076 0.688
#> GSM379799     4  0.5727      0.947 0.236 0.000 0.076 0.688
#> GSM379800     4  0.5727      0.947 0.236 0.000 0.076 0.688
#> GSM379801     4  0.5727      0.947 0.236 0.000 0.076 0.688
#> GSM379802     4  0.5727      0.946 0.236 0.000 0.076 0.688
#> GSM379803     4  0.5664      0.951 0.228 0.000 0.076 0.696
#> GSM379812     4  0.5619      0.943 0.248 0.000 0.064 0.688
#> GSM379813     4  0.5559      0.947 0.240 0.000 0.064 0.696
#> GSM379814     4  0.5590      0.947 0.244 0.000 0.064 0.692
#> GSM379807     4  0.5696      0.951 0.232 0.000 0.076 0.692
#> GSM379808     4  0.5727      0.947 0.236 0.000 0.076 0.688
#> GSM379809     4  0.5631      0.951 0.224 0.000 0.076 0.700
#> GSM379810     4  0.5631      0.951 0.224 0.000 0.076 0.700
#> GSM379811     4  0.5727      0.950 0.236 0.000 0.076 0.688
#> GSM379820     4  0.5590      0.947 0.244 0.000 0.064 0.692
#> GSM379821     4  0.5619      0.945 0.248 0.000 0.064 0.688
#> GSM379822     4  0.5648      0.942 0.252 0.000 0.064 0.684
#> GSM379815     4  0.5631      0.951 0.224 0.000 0.076 0.700
#> GSM379816     4  0.6810      0.791 0.248 0.000 0.156 0.596
#> GSM379817     4  0.5559      0.947 0.240 0.000 0.064 0.696
#> GSM379818     4  0.5727      0.950 0.236 0.000 0.076 0.688
#> GSM379819     4  0.5696      0.951 0.232 0.000 0.076 0.692
#> GSM379825     4  0.5727      0.950 0.236 0.000 0.076 0.688
#> GSM379826     4  0.5559      0.947 0.240 0.000 0.064 0.696
#> GSM379823     4  0.5648      0.942 0.252 0.000 0.064 0.684
#> GSM379824     4  0.5590      0.946 0.244 0.000 0.064 0.692
#> GSM379749     2  0.7105      0.792 0.196 0.564 0.000 0.240
#> GSM379750     2  0.7105      0.792 0.196 0.564 0.000 0.240
#> GSM379751     2  0.7494      0.783 0.208 0.524 0.004 0.264
#> GSM379744     2  0.7159      0.790 0.200 0.556 0.000 0.244
#> GSM379745     2  0.7159      0.790 0.200 0.556 0.000 0.244
#> GSM379746     2  0.7105      0.792 0.196 0.564 0.000 0.240
#> GSM379747     2  0.7304      0.785 0.208 0.532 0.000 0.260
#> GSM379748     2  0.7304      0.785 0.208 0.532 0.000 0.260
#> GSM379757     2  0.6363      0.799 0.172 0.656 0.000 0.172
#> GSM379758     2  0.6324      0.799 0.172 0.660 0.000 0.168
#> GSM379752     2  0.7105      0.792 0.196 0.564 0.000 0.240
#> GSM379753     2  0.7474      0.784 0.208 0.528 0.004 0.260
#> GSM379754     2  0.6324      0.800 0.172 0.660 0.000 0.168
#> GSM379755     2  0.6324      0.800 0.172 0.660 0.000 0.168
#> GSM379756     2  0.6324      0.800 0.172 0.660 0.000 0.168
#> GSM379764     2  0.6323      0.800 0.176 0.660 0.000 0.164
#> GSM379765     2  0.6323      0.800 0.176 0.660 0.000 0.164
#> GSM379766     2  0.6323      0.800 0.176 0.660 0.000 0.164
#> GSM379759     2  0.6324      0.799 0.172 0.660 0.000 0.168
#> GSM379760     2  0.6324      0.799 0.172 0.660 0.000 0.168
#> GSM379761     2  0.6324      0.799 0.172 0.660 0.000 0.168
#> GSM379762     2  0.6324      0.799 0.172 0.660 0.000 0.168
#> GSM379763     2  0.6323      0.800 0.176 0.660 0.000 0.164
#> GSM379769     2  0.6323      0.800 0.176 0.660 0.000 0.164
#> GSM379770     2  0.6323      0.800 0.176 0.660 0.000 0.164
#> GSM379767     2  0.6323      0.800 0.176 0.660 0.000 0.164
#> GSM379768     2  0.6323      0.800 0.176 0.660 0.000 0.164
#> GSM379776     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379777     1  0.5208      0.642 0.748 0.000 0.080 0.172
#> GSM379778     1  0.4103      0.955 0.744 0.000 0.256 0.000
#> GSM379771     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379772     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379773     1  0.4134      0.955 0.740 0.000 0.260 0.000
#> GSM379774     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379775     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379784     1  0.4220      0.952 0.748 0.000 0.248 0.004
#> GSM379785     1  0.4040      0.954 0.752 0.000 0.248 0.000
#> GSM379786     1  0.4220      0.952 0.748 0.000 0.248 0.004
#> GSM379779     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379780     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379781     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379782     1  0.6583      0.779 0.636 0.108 0.248 0.008
#> GSM379783     1  0.4220      0.952 0.748 0.000 0.248 0.004
#> GSM379792     1  0.5351      0.801 0.744 0.000 0.152 0.104
#> GSM379793     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379794     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379787     1  0.6451      0.799 0.644 0.096 0.252 0.008
#> GSM379788     1  0.4220      0.952 0.748 0.000 0.248 0.004
#> GSM379789     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379790     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379791     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379797     4  0.5686      0.767 0.376 0.000 0.032 0.592
#> GSM379798     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379795     1  0.4103      0.958 0.744 0.000 0.256 0.000
#> GSM379796     1  0.5339      0.808 0.744 0.000 0.156 0.100
#> GSM379721     3  0.0188      0.975 0.000 0.000 0.996 0.004
#> GSM379722     3  0.0188      0.975 0.000 0.000 0.996 0.004
#> GSM379723     3  0.0188      0.975 0.000 0.000 0.996 0.004
#> GSM379716     3  0.0376      0.972 0.004 0.000 0.992 0.004
#> GSM379717     3  0.0376      0.972 0.004 0.000 0.992 0.004
#> GSM379718     3  0.0376      0.972 0.004 0.000 0.992 0.004
#> GSM379719     3  0.0188      0.975 0.000 0.000 0.996 0.004
#> GSM379720     3  0.0376      0.972 0.004 0.000 0.992 0.004
#> GSM379729     3  0.0921      0.973 0.028 0.000 0.972 0.000
#> GSM379730     3  0.0921      0.973 0.028 0.000 0.972 0.000
#> GSM379731     3  0.0921      0.973 0.028 0.000 0.972 0.000
#> GSM379724     3  0.0188      0.975 0.000 0.000 0.996 0.004
#> GSM379725     3  0.0921      0.973 0.028 0.000 0.972 0.000
#> GSM379726     3  0.0376      0.975 0.004 0.000 0.992 0.004
#> GSM379727     3  0.0376      0.975 0.004 0.000 0.992 0.004
#> GSM379728     3  0.0376      0.975 0.004 0.000 0.992 0.004
#> GSM379737     3  0.0895      0.974 0.020 0.000 0.976 0.004
#> GSM379738     3  0.0895      0.974 0.020 0.000 0.976 0.004
#> GSM379739     3  0.0895      0.974 0.020 0.000 0.976 0.004
#> GSM379732     3  0.1109      0.972 0.028 0.000 0.968 0.004
#> GSM379733     3  0.0895      0.974 0.020 0.000 0.976 0.004
#> GSM379734     3  0.0895      0.974 0.020 0.000 0.976 0.004
#> GSM379735     3  0.1109      0.972 0.028 0.000 0.968 0.004
#> GSM379736     3  0.0672      0.974 0.008 0.000 0.984 0.008
#> GSM379742     3  0.2715      0.899 0.036 0.016 0.916 0.032
#> GSM379743     3  0.1209      0.971 0.032 0.000 0.964 0.004
#> GSM379740     3  0.0895      0.974 0.020 0.000 0.976 0.004
#> GSM379741     3  0.2715      0.899 0.036 0.016 0.916 0.032

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     5  0.3774    0.73472 0.000 0.296 0.000 0.000 0.704
#> GSM379833     5  0.3774    0.73472 0.000 0.296 0.000 0.000 0.704
#> GSM379834     5  0.3774    0.73472 0.000 0.296 0.000 0.000 0.704
#> GSM379827     5  0.5589    0.71308 0.080 0.296 0.008 0.000 0.616
#> GSM379828     5  0.5589    0.71308 0.080 0.296 0.008 0.000 0.616
#> GSM379829     5  0.5752   -0.00482 0.100 0.000 0.008 0.280 0.612
#> GSM379830     5  0.5589    0.71308 0.080 0.296 0.008 0.000 0.616
#> GSM379831     5  0.5589    0.71308 0.080 0.296 0.008 0.000 0.616
#> GSM379840     5  0.5430    0.71951 0.068 0.296 0.008 0.000 0.628
#> GSM379841     5  0.4783    0.72523 0.012 0.452 0.004 0.000 0.532
#> GSM379842     5  0.4752    0.73577 0.012 0.428 0.004 0.000 0.556
#> GSM379835     5  0.5589    0.71308 0.080 0.296 0.008 0.000 0.616
#> GSM379836     5  0.5589    0.71308 0.080 0.296 0.008 0.000 0.616
#> GSM379837     5  0.5335    0.54139 0.084 0.120 0.008 0.044 0.744
#> GSM379838     5  0.4783    0.72523 0.012 0.452 0.004 0.000 0.532
#> GSM379839     5  0.5335    0.54139 0.084 0.120 0.008 0.044 0.744
#> GSM379848     5  0.5051    0.69328 0.024 0.480 0.004 0.000 0.492
#> GSM379849     5  0.5051    0.69328 0.024 0.480 0.004 0.000 0.492
#> GSM379850     5  0.5051    0.69328 0.024 0.480 0.004 0.000 0.492
#> GSM379843     5  0.4752    0.73577 0.012 0.428 0.004 0.000 0.556
#> GSM379844     5  0.4783    0.72523 0.012 0.452 0.004 0.000 0.532
#> GSM379845     5  0.5430    0.71951 0.068 0.296 0.008 0.000 0.628
#> GSM379846     5  0.4783    0.72523 0.012 0.452 0.004 0.000 0.532
#> GSM379847     5  0.4798    0.70960 0.012 0.472 0.004 0.000 0.512
#> GSM379853     5  0.5008    0.72992 0.024 0.428 0.004 0.000 0.544
#> GSM379854     5  0.5051    0.69328 0.024 0.480 0.004 0.000 0.492
#> GSM379851     5  0.5049    0.70115 0.024 0.472 0.004 0.000 0.500
#> GSM379852     5  0.5051    0.69328 0.024 0.480 0.004 0.000 0.492
#> GSM379804     4  0.1430    0.90222 0.004 0.000 0.000 0.944 0.052
#> GSM379805     4  0.3550    0.87511 0.020 0.000 0.000 0.796 0.184
#> GSM379806     4  0.3550    0.87511 0.020 0.000 0.000 0.796 0.184
#> GSM379799     4  0.3550    0.87511 0.020 0.000 0.000 0.796 0.184
#> GSM379800     4  0.3550    0.87511 0.020 0.000 0.000 0.796 0.184
#> GSM379801     4  0.3550    0.87511 0.020 0.000 0.000 0.796 0.184
#> GSM379802     4  0.3745    0.87151 0.024 0.000 0.000 0.780 0.196
#> GSM379803     4  0.3562    0.87476 0.016 0.000 0.000 0.788 0.196
#> GSM379812     4  0.0404    0.90150 0.012 0.000 0.000 0.988 0.000
#> GSM379813     4  0.0404    0.90150 0.012 0.000 0.000 0.988 0.000
#> GSM379814     4  0.0404    0.90150 0.012 0.000 0.000 0.988 0.000
#> GSM379807     4  0.0162    0.90274 0.004 0.000 0.000 0.996 0.000
#> GSM379808     4  0.3550    0.87511 0.020 0.000 0.000 0.796 0.184
#> GSM379809     4  0.0794    0.90442 0.000 0.000 0.000 0.972 0.028
#> GSM379810     4  0.0609    0.90451 0.000 0.000 0.000 0.980 0.020
#> GSM379811     4  0.3745    0.87151 0.024 0.000 0.000 0.780 0.196
#> GSM379820     4  0.0290    0.90225 0.008 0.000 0.000 0.992 0.000
#> GSM379821     4  0.0912    0.89968 0.016 0.000 0.000 0.972 0.012
#> GSM379822     4  0.1117    0.89658 0.016 0.000 0.000 0.964 0.020
#> GSM379815     4  0.0609    0.90451 0.000 0.000 0.000 0.980 0.020
#> GSM379816     4  0.1808    0.85632 0.012 0.000 0.044 0.936 0.008
#> GSM379817     4  0.0404    0.90150 0.012 0.000 0.000 0.988 0.000
#> GSM379818     4  0.3745    0.87151 0.024 0.000 0.000 0.780 0.196
#> GSM379819     4  0.0162    0.90274 0.004 0.000 0.000 0.996 0.000
#> GSM379825     4  0.3675    0.87320 0.024 0.000 0.000 0.788 0.188
#> GSM379826     4  0.0404    0.90150 0.012 0.000 0.000 0.988 0.000
#> GSM379823     4  0.0912    0.89784 0.012 0.000 0.000 0.972 0.016
#> GSM379824     4  0.0912    0.89968 0.016 0.000 0.000 0.972 0.012
#> GSM379749     2  0.4425    0.76702 0.108 0.772 0.004 0.000 0.116
#> GSM379750     2  0.4425    0.76702 0.108 0.772 0.004 0.000 0.116
#> GSM379751     2  0.5351    0.66470 0.136 0.692 0.008 0.000 0.164
#> GSM379744     2  0.4517    0.75934 0.108 0.764 0.004 0.000 0.124
#> GSM379745     2  0.4517    0.75934 0.108 0.764 0.004 0.000 0.124
#> GSM379746     2  0.4425    0.76702 0.108 0.772 0.004 0.000 0.116
#> GSM379747     2  0.4926    0.70980 0.108 0.724 0.004 0.000 0.164
#> GSM379748     2  0.4926    0.70980 0.108 0.724 0.004 0.000 0.164
#> GSM379757     2  0.1892    0.82349 0.080 0.916 0.004 0.000 0.000
#> GSM379758     2  0.0000    0.82452 0.000 1.000 0.000 0.000 0.000
#> GSM379752     2  0.4425    0.76702 0.108 0.772 0.004 0.000 0.116
#> GSM379753     2  0.4888    0.71546 0.108 0.728 0.004 0.000 0.160
#> GSM379754     2  0.2352    0.81928 0.092 0.896 0.004 0.000 0.008
#> GSM379755     2  0.2352    0.81928 0.092 0.896 0.004 0.000 0.008
#> GSM379756     2  0.2228    0.81977 0.092 0.900 0.004 0.000 0.004
#> GSM379764     2  0.1026    0.81020 0.024 0.968 0.004 0.000 0.004
#> GSM379765     2  0.1026    0.81020 0.024 0.968 0.004 0.000 0.004
#> GSM379766     2  0.1026    0.81020 0.024 0.968 0.004 0.000 0.004
#> GSM379759     2  0.0404    0.82714 0.012 0.988 0.000 0.000 0.000
#> GSM379760     2  0.0404    0.82714 0.012 0.988 0.000 0.000 0.000
#> GSM379761     2  0.0162    0.82566 0.004 0.996 0.000 0.000 0.000
#> GSM379762     2  0.0000    0.82452 0.000 1.000 0.000 0.000 0.000
#> GSM379763     2  0.1026    0.81020 0.024 0.968 0.004 0.000 0.004
#> GSM379769     2  0.1026    0.81020 0.024 0.968 0.004 0.000 0.004
#> GSM379770     2  0.1026    0.81020 0.024 0.968 0.004 0.000 0.004
#> GSM379767     2  0.1026    0.81020 0.024 0.968 0.004 0.000 0.004
#> GSM379768     2  0.1026    0.81020 0.024 0.968 0.004 0.000 0.004
#> GSM379776     1  0.4905    0.97109 0.728 0.000 0.116 0.152 0.004
#> GSM379777     1  0.4494    0.85317 0.728 0.000 0.028 0.232 0.012
#> GSM379778     1  0.4833    0.95113 0.748 0.000 0.108 0.132 0.012
#> GSM379771     1  0.4905    0.97109 0.728 0.000 0.116 0.152 0.004
#> GSM379772     1  0.4905    0.97109 0.728 0.000 0.116 0.152 0.004
#> GSM379773     1  0.4732    0.96275 0.744 0.000 0.108 0.144 0.004
#> GSM379774     1  0.4751    0.97081 0.732 0.000 0.116 0.152 0.000
#> GSM379775     1  0.4905    0.97109 0.728 0.000 0.116 0.152 0.004
#> GSM379784     1  0.4859    0.96941 0.732 0.000 0.112 0.152 0.004
#> GSM379785     1  0.4704    0.97009 0.736 0.000 0.112 0.152 0.000
#> GSM379786     1  0.4859    0.96941 0.732 0.000 0.112 0.152 0.004
#> GSM379779     1  0.4751    0.97081 0.732 0.000 0.116 0.152 0.000
#> GSM379780     1  0.4751    0.97081 0.732 0.000 0.116 0.152 0.000
#> GSM379781     1  0.4751    0.97081 0.732 0.000 0.116 0.152 0.000
#> GSM379782     1  0.5266    0.88544 0.760 0.024 0.108 0.072 0.036
#> GSM379783     1  0.4859    0.96941 0.732 0.000 0.112 0.152 0.004
#> GSM379792     1  0.4913    0.90027 0.720 0.000 0.056 0.208 0.016
#> GSM379793     1  0.5229    0.96931 0.716 0.000 0.116 0.152 0.016
#> GSM379794     1  0.5229    0.96931 0.716 0.000 0.116 0.152 0.016
#> GSM379787     1  0.5266    0.88544 0.760 0.024 0.108 0.072 0.036
#> GSM379788     1  0.4704    0.97009 0.736 0.000 0.112 0.152 0.000
#> GSM379789     1  0.5229    0.96931 0.716 0.000 0.116 0.152 0.016
#> GSM379790     1  0.5229    0.96931 0.716 0.000 0.116 0.152 0.016
#> GSM379791     1  0.5229    0.96931 0.716 0.000 0.116 0.152 0.016
#> GSM379797     4  0.5610    0.66710 0.180 0.000 0.000 0.640 0.180
#> GSM379798     1  0.5229    0.96931 0.716 0.000 0.116 0.152 0.016
#> GSM379795     1  0.5229    0.96931 0.716 0.000 0.116 0.152 0.016
#> GSM379796     1  0.4913    0.90027 0.720 0.000 0.056 0.208 0.016
#> GSM379721     3  0.1836    0.96164 0.008 0.000 0.936 0.016 0.040
#> GSM379722     3  0.1836    0.96164 0.008 0.000 0.936 0.016 0.040
#> GSM379723     3  0.1673    0.96214 0.008 0.000 0.944 0.016 0.032
#> GSM379716     3  0.1673    0.96214 0.008 0.000 0.944 0.016 0.032
#> GSM379717     3  0.1673    0.96214 0.008 0.000 0.944 0.016 0.032
#> GSM379718     3  0.1836    0.96164 0.008 0.000 0.936 0.016 0.040
#> GSM379719     3  0.1836    0.96164 0.008 0.000 0.936 0.016 0.040
#> GSM379720     3  0.1836    0.96164 0.008 0.000 0.936 0.016 0.040
#> GSM379729     3  0.1596    0.95922 0.012 0.000 0.948 0.012 0.028
#> GSM379730     3  0.1596    0.95922 0.012 0.000 0.948 0.012 0.028
#> GSM379731     3  0.1483    0.95994 0.008 0.000 0.952 0.012 0.028
#> GSM379724     3  0.1673    0.96214 0.008 0.000 0.944 0.016 0.032
#> GSM379725     3  0.1921    0.96140 0.012 0.000 0.932 0.012 0.044
#> GSM379726     3  0.1673    0.96214 0.008 0.000 0.944 0.016 0.032
#> GSM379727     3  0.1673    0.96214 0.008 0.000 0.944 0.016 0.032
#> GSM379728     3  0.1673    0.96214 0.008 0.000 0.944 0.016 0.032
#> GSM379737     3  0.1617    0.95816 0.020 0.000 0.948 0.012 0.020
#> GSM379738     3  0.1617    0.95816 0.020 0.000 0.948 0.012 0.020
#> GSM379739     3  0.1799    0.95626 0.020 0.000 0.940 0.012 0.028
#> GSM379732     3  0.1764    0.95872 0.012 0.000 0.940 0.012 0.036
#> GSM379733     3  0.1314    0.96066 0.012 0.000 0.960 0.012 0.016
#> GSM379734     3  0.1314    0.96066 0.012 0.000 0.960 0.012 0.016
#> GSM379735     3  0.2217    0.95217 0.024 0.000 0.920 0.012 0.044
#> GSM379736     3  0.1673    0.96192 0.008 0.000 0.944 0.016 0.032
#> GSM379742     3  0.3248    0.90160 0.040 0.048 0.872 0.000 0.040
#> GSM379743     3  0.2217    0.95217 0.024 0.000 0.920 0.012 0.044
#> GSM379740     3  0.1413    0.96001 0.012 0.000 0.956 0.012 0.020
#> GSM379741     3  0.3248    0.90160 0.040 0.048 0.872 0.000 0.040

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     5  0.0508      0.745 0.000 0.004 0.000 0.000 0.984 0.012
#> GSM379833     5  0.0508      0.745 0.000 0.004 0.000 0.000 0.984 0.012
#> GSM379834     5  0.0508      0.745 0.000 0.004 0.000 0.000 0.984 0.012
#> GSM379827     5  0.3023      0.678 0.000 0.000 0.004 0.000 0.784 0.212
#> GSM379828     5  0.3023      0.678 0.000 0.000 0.004 0.000 0.784 0.212
#> GSM379829     6  0.5383      0.240 0.000 0.000 0.000 0.164 0.260 0.576
#> GSM379830     5  0.2933      0.688 0.000 0.000 0.004 0.000 0.796 0.200
#> GSM379831     5  0.2933      0.688 0.000 0.000 0.004 0.000 0.796 0.200
#> GSM379840     5  0.2562      0.706 0.000 0.000 0.000 0.000 0.828 0.172
#> GSM379841     5  0.2378      0.754 0.000 0.152 0.000 0.000 0.848 0.000
#> GSM379842     5  0.2260      0.758 0.000 0.140 0.000 0.000 0.860 0.000
#> GSM379835     5  0.2933      0.688 0.000 0.000 0.004 0.000 0.796 0.200
#> GSM379836     5  0.2933      0.688 0.000 0.000 0.004 0.000 0.796 0.200
#> GSM379837     5  0.3990      0.520 0.000 0.000 0.004 0.016 0.676 0.304
#> GSM379838     5  0.2378      0.754 0.000 0.152 0.000 0.000 0.848 0.000
#> GSM379839     5  0.3990      0.520 0.000 0.000 0.004 0.016 0.676 0.304
#> GSM379848     5  0.3269      0.720 0.000 0.184 0.000 0.000 0.792 0.024
#> GSM379849     5  0.3269      0.720 0.000 0.184 0.000 0.000 0.792 0.024
#> GSM379850     5  0.3269      0.720 0.000 0.184 0.000 0.000 0.792 0.024
#> GSM379843     5  0.2260      0.758 0.000 0.140 0.000 0.000 0.860 0.000
#> GSM379844     5  0.2378      0.754 0.000 0.152 0.000 0.000 0.848 0.000
#> GSM379845     5  0.2562      0.706 0.000 0.000 0.000 0.000 0.828 0.172
#> GSM379846     5  0.2378      0.754 0.000 0.152 0.000 0.000 0.848 0.000
#> GSM379847     5  0.3202      0.727 0.000 0.176 0.000 0.000 0.800 0.024
#> GSM379853     5  0.2831      0.751 0.000 0.136 0.000 0.000 0.840 0.024
#> GSM379854     5  0.3269      0.720 0.000 0.184 0.000 0.000 0.792 0.024
#> GSM379851     5  0.3134      0.733 0.000 0.168 0.000 0.000 0.808 0.024
#> GSM379852     5  0.3269      0.720 0.000 0.184 0.000 0.000 0.792 0.024
#> GSM379804     4  0.3044      0.653 0.048 0.000 0.000 0.836 0.000 0.116
#> GSM379805     4  0.4666      0.418 0.048 0.000 0.000 0.564 0.000 0.388
#> GSM379806     4  0.4682      0.411 0.048 0.000 0.000 0.556 0.000 0.396
#> GSM379799     4  0.4709      0.397 0.048 0.000 0.000 0.540 0.000 0.412
#> GSM379800     4  0.4709      0.397 0.048 0.000 0.000 0.540 0.000 0.412
#> GSM379801     4  0.4709      0.397 0.048 0.000 0.000 0.540 0.000 0.412
#> GSM379802     4  0.4870      0.365 0.048 0.004 0.000 0.512 0.000 0.436
#> GSM379803     4  0.5117      0.384 0.048 0.016 0.000 0.520 0.000 0.416
#> GSM379812     4  0.1921      0.684 0.056 0.012 0.012 0.920 0.000 0.000
#> GSM379813     4  0.1349      0.690 0.056 0.000 0.004 0.940 0.000 0.000
#> GSM379814     4  0.1349      0.690 0.056 0.000 0.004 0.940 0.000 0.000
#> GSM379807     4  0.1141      0.691 0.052 0.000 0.000 0.948 0.000 0.000
#> GSM379808     4  0.4709      0.397 0.048 0.000 0.000 0.540 0.000 0.412
#> GSM379809     4  0.2608      0.672 0.048 0.000 0.000 0.872 0.000 0.080
#> GSM379810     4  0.2066      0.687 0.052 0.000 0.000 0.908 0.000 0.040
#> GSM379811     4  0.4962      0.371 0.048 0.008 0.000 0.516 0.000 0.428
#> GSM379820     4  0.1349      0.690 0.056 0.000 0.004 0.940 0.000 0.000
#> GSM379821     4  0.2962      0.669 0.056 0.028 0.012 0.876 0.000 0.028
#> GSM379822     4  0.3418      0.649 0.056 0.036 0.016 0.852 0.000 0.040
#> GSM379815     4  0.2136      0.685 0.048 0.000 0.000 0.904 0.000 0.048
#> GSM379816     4  0.2813      0.652 0.068 0.024 0.016 0.880 0.000 0.012
#> GSM379817     4  0.1349      0.690 0.056 0.000 0.004 0.940 0.000 0.000
#> GSM379818     4  0.4966      0.366 0.048 0.008 0.000 0.512 0.000 0.432
#> GSM379819     4  0.1141      0.691 0.052 0.000 0.000 0.948 0.000 0.000
#> GSM379825     4  0.4857      0.378 0.048 0.004 0.000 0.524 0.000 0.424
#> GSM379826     4  0.1349      0.690 0.056 0.000 0.004 0.940 0.000 0.000
#> GSM379823     4  0.2955      0.659 0.056 0.036 0.016 0.876 0.000 0.016
#> GSM379824     4  0.2750      0.674 0.056 0.028 0.004 0.884 0.000 0.028
#> GSM379749     2  0.6951      0.713 0.000 0.472 0.052 0.032 0.316 0.128
#> GSM379750     2  0.6951      0.713 0.000 0.472 0.052 0.032 0.316 0.128
#> GSM379751     2  0.7285      0.604 0.000 0.376 0.052 0.032 0.364 0.176
#> GSM379744     2  0.6983      0.700 0.000 0.456 0.052 0.032 0.332 0.128
#> GSM379745     2  0.6983      0.700 0.000 0.456 0.052 0.032 0.332 0.128
#> GSM379746     2  0.6951      0.713 0.000 0.472 0.052 0.032 0.316 0.128
#> GSM379747     2  0.7021      0.671 0.000 0.428 0.052 0.032 0.360 0.128
#> GSM379748     2  0.7021      0.671 0.000 0.428 0.052 0.032 0.360 0.128
#> GSM379757     2  0.5678      0.770 0.000 0.664 0.048 0.028 0.192 0.068
#> GSM379758     2  0.2730      0.777 0.000 0.808 0.000 0.000 0.192 0.000
#> GSM379752     2  0.6951      0.713 0.000 0.472 0.052 0.032 0.316 0.128
#> GSM379753     2  0.7025      0.666 0.000 0.424 0.052 0.032 0.364 0.128
#> GSM379754     2  0.6106      0.764 0.000 0.624 0.048 0.032 0.204 0.092
#> GSM379755     2  0.6106      0.764 0.000 0.624 0.048 0.032 0.204 0.092
#> GSM379756     2  0.6080      0.764 0.000 0.628 0.048 0.032 0.200 0.092
#> GSM379764     2  0.3593      0.760 0.000 0.764 0.000 0.004 0.208 0.024
#> GSM379765     2  0.3593      0.760 0.000 0.764 0.000 0.004 0.208 0.024
#> GSM379766     2  0.3593      0.760 0.000 0.764 0.000 0.004 0.208 0.024
#> GSM379759     2  0.2730      0.777 0.000 0.808 0.000 0.000 0.192 0.000
#> GSM379760     2  0.2730      0.777 0.000 0.808 0.000 0.000 0.192 0.000
#> GSM379761     2  0.2730      0.777 0.000 0.808 0.000 0.000 0.192 0.000
#> GSM379762     2  0.2730      0.777 0.000 0.808 0.000 0.000 0.192 0.000
#> GSM379763     2  0.3454      0.760 0.000 0.768 0.000 0.000 0.208 0.024
#> GSM379769     2  0.3593      0.760 0.000 0.764 0.000 0.004 0.208 0.024
#> GSM379770     2  0.3593      0.760 0.000 0.764 0.000 0.004 0.208 0.024
#> GSM379767     2  0.3593      0.760 0.000 0.764 0.000 0.004 0.208 0.024
#> GSM379768     2  0.3593      0.760 0.000 0.764 0.000 0.004 0.208 0.024
#> GSM379776     1  0.0000      0.963 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379777     1  0.3293      0.844 0.860 0.040 0.016 0.048 0.000 0.036
#> GSM379778     1  0.2009      0.927 0.916 0.040 0.000 0.000 0.004 0.040
#> GSM379771     1  0.0146      0.963 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379772     1  0.0146      0.963 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379773     1  0.1261      0.951 0.952 0.024 0.000 0.000 0.000 0.024
#> GSM379774     1  0.0146      0.963 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379775     1  0.0146      0.963 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379784     1  0.1364      0.951 0.952 0.020 0.016 0.000 0.000 0.012
#> GSM379785     1  0.0976      0.957 0.968 0.016 0.008 0.000 0.000 0.008
#> GSM379786     1  0.1364      0.951 0.952 0.020 0.016 0.000 0.000 0.012
#> GSM379779     1  0.0146      0.963 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379780     1  0.0000      0.963 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379781     1  0.0717      0.959 0.976 0.016 0.000 0.000 0.000 0.008
#> GSM379782     1  0.2384      0.909 0.896 0.056 0.000 0.000 0.008 0.040
#> GSM379783     1  0.1364      0.951 0.952 0.020 0.016 0.000 0.000 0.012
#> GSM379792     1  0.1364      0.945 0.952 0.016 0.000 0.020 0.000 0.012
#> GSM379793     1  0.0820      0.959 0.972 0.016 0.000 0.000 0.000 0.012
#> GSM379794     1  0.0914      0.959 0.968 0.016 0.000 0.000 0.000 0.016
#> GSM379787     1  0.2384      0.909 0.896 0.056 0.000 0.000 0.008 0.040
#> GSM379788     1  0.1173      0.954 0.960 0.016 0.016 0.000 0.000 0.008
#> GSM379789     1  0.0820      0.959 0.972 0.016 0.000 0.000 0.000 0.012
#> GSM379790     1  0.0820      0.959 0.972 0.016 0.000 0.000 0.000 0.012
#> GSM379791     1  0.0820      0.959 0.972 0.016 0.000 0.000 0.000 0.012
#> GSM379797     6  0.6526     -0.172 0.244 0.024 0.000 0.360 0.000 0.372
#> GSM379798     1  0.0820      0.959 0.972 0.016 0.000 0.000 0.000 0.012
#> GSM379795     1  0.0914      0.959 0.968 0.016 0.000 0.000 0.000 0.016
#> GSM379796     1  0.1275      0.948 0.956 0.016 0.000 0.016 0.000 0.012
#> GSM379721     3  0.5294      0.875 0.060 0.052 0.708 0.016 0.004 0.160
#> GSM379722     3  0.5294      0.875 0.060 0.052 0.708 0.016 0.004 0.160
#> GSM379723     3  0.5131      0.876 0.060 0.048 0.724 0.016 0.004 0.148
#> GSM379716     3  0.5131      0.876 0.060 0.048 0.724 0.016 0.004 0.148
#> GSM379717     3  0.5131      0.876 0.060 0.048 0.724 0.016 0.004 0.148
#> GSM379718     3  0.5294      0.875 0.060 0.052 0.708 0.016 0.004 0.160
#> GSM379719     3  0.5294      0.875 0.060 0.052 0.708 0.016 0.004 0.160
#> GSM379720     3  0.5238      0.874 0.056 0.052 0.712 0.016 0.004 0.160
#> GSM379729     3  0.3114      0.868 0.052 0.040 0.860 0.000 0.000 0.048
#> GSM379730     3  0.3181      0.867 0.052 0.044 0.856 0.000 0.000 0.048
#> GSM379731     3  0.3181      0.867 0.052 0.044 0.856 0.000 0.000 0.048
#> GSM379724     3  0.5131      0.876 0.060 0.048 0.724 0.016 0.004 0.148
#> GSM379725     3  0.4515      0.874 0.056 0.052 0.760 0.004 0.000 0.128
#> GSM379726     3  0.5048      0.876 0.064 0.048 0.724 0.016 0.000 0.148
#> GSM379727     3  0.5012      0.876 0.064 0.048 0.728 0.016 0.000 0.144
#> GSM379728     3  0.5012      0.876 0.064 0.048 0.728 0.016 0.000 0.144
#> GSM379737     3  0.1900      0.876 0.068 0.008 0.916 0.000 0.000 0.008
#> GSM379738     3  0.1900      0.876 0.068 0.008 0.916 0.000 0.000 0.008
#> GSM379739     3  0.2102      0.874 0.068 0.012 0.908 0.000 0.000 0.012
#> GSM379732     3  0.2959      0.863 0.056 0.048 0.868 0.000 0.000 0.028
#> GSM379733     3  0.2562      0.880 0.068 0.008 0.888 0.004 0.000 0.032
#> GSM379734     3  0.2562      0.880 0.068 0.008 0.888 0.004 0.000 0.032
#> GSM379735     3  0.3036      0.858 0.052 0.052 0.864 0.000 0.000 0.032
#> GSM379736     3  0.3581      0.881 0.064 0.040 0.840 0.012 0.000 0.044
#> GSM379742     3  0.3407      0.810 0.016 0.108 0.832 0.004 0.000 0.040
#> GSM379743     3  0.3036      0.858 0.052 0.052 0.864 0.000 0.000 0.032
#> GSM379740     3  0.1900      0.876 0.068 0.008 0.916 0.000 0.000 0.008
#> GSM379741     3  0.3407      0.810 0.016 0.108 0.832 0.004 0.000 0.040

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-SD-kmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-SD-kmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-SD-kmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-SD-kmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-SD-kmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-SD-kmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-SD-kmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-SD-kmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-SD-kmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-SD-kmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-kmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-SD-kmeans-get-signatures-2

get_signatures(res, k = 4)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-kmeans-get-signatures-3

get_signatures(res, k = 5)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-kmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-SD-kmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-kmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-SD-kmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-kmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-kmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-SD-kmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk SD-kmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-SD-kmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-SD-kmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-SD-kmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-SD-kmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-SD-kmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk SD-kmeans-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>             n individual(p) time(p) agent(p) k
#> SD:kmeans 138      1.06e-24       1    0.780 2
#> SD:kmeans 111      1.97e-42       1    0.951 3
#> SD:kmeans 138      4.25e-79       1    0.998 4
#> SD:kmeans 138     3.50e-105       1    0.998 5
#> SD:kmeans 126      4.76e-97       1    0.395 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

SD:skmeans*

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["SD", "skmeans"]
# you can also extract it by
# res = res_list["SD:skmeans"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#>   Subgroups are detected by 'skmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 6.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk SD-skmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk SD-skmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.988       0.995         0.4908 0.510   0.510
#> 3 3 1.000           0.986       0.993         0.3151 0.834   0.678
#> 4 4 1.000           0.980       0.983         0.1326 0.905   0.737
#> 5 5 0.932           0.955       0.966         0.1007 0.918   0.701
#> 6 6 0.935           0.925       0.915         0.0277 0.981   0.900

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 6
#> attr(,"optional")
#> [1] 2 3 4 5

There is also optional best \(k\) = 2 3 4 5 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2   0.000      0.996 0.000 1.000
#> GSM379833     2   0.000      0.996 0.000 1.000
#> GSM379834     2   0.000      0.996 0.000 1.000
#> GSM379827     2   0.000      0.996 0.000 1.000
#> GSM379828     2   0.000      0.996 0.000 1.000
#> GSM379829     1   0.141      0.975 0.980 0.020
#> GSM379830     2   0.000      0.996 0.000 1.000
#> GSM379831     2   0.000      0.996 0.000 1.000
#> GSM379840     2   0.000      0.996 0.000 1.000
#> GSM379841     2   0.000      0.996 0.000 1.000
#> GSM379842     2   0.000      0.996 0.000 1.000
#> GSM379835     2   0.000      0.996 0.000 1.000
#> GSM379836     2   0.000      0.996 0.000 1.000
#> GSM379837     2   0.000      0.996 0.000 1.000
#> GSM379838     2   0.000      0.996 0.000 1.000
#> GSM379839     2   0.000      0.996 0.000 1.000
#> GSM379848     2   0.000      0.996 0.000 1.000
#> GSM379849     2   0.000      0.996 0.000 1.000
#> GSM379850     2   0.000      0.996 0.000 1.000
#> GSM379843     2   0.000      0.996 0.000 1.000
#> GSM379844     2   0.000      0.996 0.000 1.000
#> GSM379845     2   0.000      0.996 0.000 1.000
#> GSM379846     2   0.000      0.996 0.000 1.000
#> GSM379847     2   0.000      0.996 0.000 1.000
#> GSM379853     2   0.000      0.996 0.000 1.000
#> GSM379854     2   0.000      0.996 0.000 1.000
#> GSM379851     2   0.000      0.996 0.000 1.000
#> GSM379852     2   0.000      0.996 0.000 1.000
#> GSM379804     1   0.000      0.995 1.000 0.000
#> GSM379805     1   0.000      0.995 1.000 0.000
#> GSM379806     1   0.000      0.995 1.000 0.000
#> GSM379799     1   0.000      0.995 1.000 0.000
#> GSM379800     1   0.000      0.995 1.000 0.000
#> GSM379801     1   0.000      0.995 1.000 0.000
#> GSM379802     1   0.000      0.995 1.000 0.000
#> GSM379803     1   0.000      0.995 1.000 0.000
#> GSM379812     1   0.000      0.995 1.000 0.000
#> GSM379813     1   0.000      0.995 1.000 0.000
#> GSM379814     1   0.000      0.995 1.000 0.000
#> GSM379807     1   0.000      0.995 1.000 0.000
#> GSM379808     1   0.000      0.995 1.000 0.000
#> GSM379809     1   0.000      0.995 1.000 0.000
#> GSM379810     1   0.000      0.995 1.000 0.000
#> GSM379811     1   0.000      0.995 1.000 0.000
#> GSM379820     1   0.000      0.995 1.000 0.000
#> GSM379821     1   0.000      0.995 1.000 0.000
#> GSM379822     1   0.000      0.995 1.000 0.000
#> GSM379815     1   0.000      0.995 1.000 0.000
#> GSM379816     1   0.000      0.995 1.000 0.000
#> GSM379817     1   0.000      0.995 1.000 0.000
#> GSM379818     1   0.000      0.995 1.000 0.000
#> GSM379819     1   0.000      0.995 1.000 0.000
#> GSM379825     1   0.000      0.995 1.000 0.000
#> GSM379826     1   0.000      0.995 1.000 0.000
#> GSM379823     1   0.000      0.995 1.000 0.000
#> GSM379824     1   0.000      0.995 1.000 0.000
#> GSM379749     2   0.000      0.996 0.000 1.000
#> GSM379750     2   0.000      0.996 0.000 1.000
#> GSM379751     2   0.000      0.996 0.000 1.000
#> GSM379744     2   0.000      0.996 0.000 1.000
#> GSM379745     2   0.000      0.996 0.000 1.000
#> GSM379746     2   0.000      0.996 0.000 1.000
#> GSM379747     2   0.000      0.996 0.000 1.000
#> GSM379748     2   0.000      0.996 0.000 1.000
#> GSM379757     2   0.000      0.996 0.000 1.000
#> GSM379758     2   0.000      0.996 0.000 1.000
#> GSM379752     2   0.000      0.996 0.000 1.000
#> GSM379753     2   0.000      0.996 0.000 1.000
#> GSM379754     2   0.000      0.996 0.000 1.000
#> GSM379755     2   0.000      0.996 0.000 1.000
#> GSM379756     2   0.000      0.996 0.000 1.000
#> GSM379764     2   0.000      0.996 0.000 1.000
#> GSM379765     2   0.000      0.996 0.000 1.000
#> GSM379766     2   0.000      0.996 0.000 1.000
#> GSM379759     2   0.000      0.996 0.000 1.000
#> GSM379760     2   0.000      0.996 0.000 1.000
#> GSM379761     2   0.000      0.996 0.000 1.000
#> GSM379762     2   0.000      0.996 0.000 1.000
#> GSM379763     2   0.000      0.996 0.000 1.000
#> GSM379769     2   0.000      0.996 0.000 1.000
#> GSM379770     2   0.000      0.996 0.000 1.000
#> GSM379767     2   0.000      0.996 0.000 1.000
#> GSM379768     2   0.000      0.996 0.000 1.000
#> GSM379776     1   0.000      0.995 1.000 0.000
#> GSM379777     1   0.000      0.995 1.000 0.000
#> GSM379778     1   0.975      0.305 0.592 0.408
#> GSM379771     1   0.000      0.995 1.000 0.000
#> GSM379772     1   0.000      0.995 1.000 0.000
#> GSM379773     1   0.000      0.995 1.000 0.000
#> GSM379774     1   0.000      0.995 1.000 0.000
#> GSM379775     1   0.000      0.995 1.000 0.000
#> GSM379784     1   0.000      0.995 1.000 0.000
#> GSM379785     1   0.000      0.995 1.000 0.000
#> GSM379786     1   0.000      0.995 1.000 0.000
#> GSM379779     1   0.000      0.995 1.000 0.000
#> GSM379780     1   0.000      0.995 1.000 0.000
#> GSM379781     1   0.000      0.995 1.000 0.000
#> GSM379782     2   0.000      0.996 0.000 1.000
#> GSM379783     1   0.000      0.995 1.000 0.000
#> GSM379792     1   0.000      0.995 1.000 0.000
#> GSM379793     1   0.000      0.995 1.000 0.000
#> GSM379794     1   0.000      0.995 1.000 0.000
#> GSM379787     2   0.722      0.748 0.200 0.800
#> GSM379788     1   0.000      0.995 1.000 0.000
#> GSM379789     1   0.000      0.995 1.000 0.000
#> GSM379790     1   0.000      0.995 1.000 0.000
#> GSM379791     1   0.000      0.995 1.000 0.000
#> GSM379797     1   0.000      0.995 1.000 0.000
#> GSM379798     1   0.000      0.995 1.000 0.000
#> GSM379795     1   0.000      0.995 1.000 0.000
#> GSM379796     1   0.000      0.995 1.000 0.000
#> GSM379721     1   0.000      0.995 1.000 0.000
#> GSM379722     1   0.000      0.995 1.000 0.000
#> GSM379723     1   0.000      0.995 1.000 0.000
#> GSM379716     1   0.000      0.995 1.000 0.000
#> GSM379717     1   0.000      0.995 1.000 0.000
#> GSM379718     1   0.000      0.995 1.000 0.000
#> GSM379719     1   0.000      0.995 1.000 0.000
#> GSM379720     1   0.000      0.995 1.000 0.000
#> GSM379729     1   0.000      0.995 1.000 0.000
#> GSM379730     1   0.000      0.995 1.000 0.000
#> GSM379731     1   0.000      0.995 1.000 0.000
#> GSM379724     1   0.000      0.995 1.000 0.000
#> GSM379725     1   0.000      0.995 1.000 0.000
#> GSM379726     1   0.000      0.995 1.000 0.000
#> GSM379727     1   0.000      0.995 1.000 0.000
#> GSM379728     1   0.000      0.995 1.000 0.000
#> GSM379737     1   0.000      0.995 1.000 0.000
#> GSM379738     1   0.000      0.995 1.000 0.000
#> GSM379739     1   0.000      0.995 1.000 0.000
#> GSM379732     1   0.000      0.995 1.000 0.000
#> GSM379733     1   0.000      0.995 1.000 0.000
#> GSM379734     1   0.000      0.995 1.000 0.000
#> GSM379735     1   0.000      0.995 1.000 0.000
#> GSM379736     1   0.000      0.995 1.000 0.000
#> GSM379742     2   0.000      0.996 0.000 1.000
#> GSM379743     1   0.000      0.995 1.000 0.000
#> GSM379740     1   0.000      0.995 1.000 0.000
#> GSM379741     2   0.000      0.996 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379833     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379834     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379827     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379828     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379829     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379830     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379831     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379840     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379841     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379842     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379835     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379836     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379837     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379838     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379839     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379848     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379849     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379850     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379843     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379844     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379845     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379846     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379847     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379853     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379854     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379851     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379852     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379804     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379805     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379806     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379799     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379800     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379801     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379802     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379803     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379812     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379813     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379814     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379807     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379808     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379809     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379810     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379811     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379820     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379821     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379822     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379815     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379816     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379817     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379818     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379819     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379825     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379826     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379823     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379824     1  0.0592      0.994 0.988 0.000 0.012
#> GSM379749     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379750     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379751     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379744     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379745     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379746     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379747     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379748     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379757     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379758     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379752     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379753     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379754     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379755     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379756     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379764     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379765     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379766     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379759     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379760     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379761     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379762     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379763     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379769     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379770     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379767     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379768     2  0.0000      0.987 0.000 1.000 0.000
#> GSM379776     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379777     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379778     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379771     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379772     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379773     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379774     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379775     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379784     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379785     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379786     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379779     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379780     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379781     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379782     2  0.4702      0.728 0.212 0.788 0.000
#> GSM379783     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379792     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379793     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379794     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379787     2  0.6126      0.348 0.400 0.600 0.000
#> GSM379788     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379789     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379790     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379791     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379797     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379798     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379795     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379796     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379721     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379722     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379723     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379716     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379717     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379718     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379719     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379720     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379729     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379730     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379731     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379724     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379725     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379726     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379727     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379728     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379737     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379738     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379739     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379732     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379733     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379734     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379735     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379736     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379742     3  0.0592      0.986 0.000 0.012 0.988
#> GSM379743     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379740     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379741     3  0.0592      0.986 0.000 0.012 0.988

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2 p3    p4
#> GSM379832     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379833     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379834     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379827     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379828     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379829     4  0.0921      0.959 0.000 0.028  0 0.972
#> GSM379830     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379831     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379840     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379841     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379842     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379835     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379836     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379837     2  0.4406      0.569 0.000 0.700  0 0.300
#> GSM379838     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379839     2  0.4382      0.577 0.000 0.704  0 0.296
#> GSM379848     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379849     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379850     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379843     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379844     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379845     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379846     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379847     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379853     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379854     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379851     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379852     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379804     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379805     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379806     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379799     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379800     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379801     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379802     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379803     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379812     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379813     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379814     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379807     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379808     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379809     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379810     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379811     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379820     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379821     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379822     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379815     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379816     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379817     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379818     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379819     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379825     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379826     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379823     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379824     4  0.0000      0.992 0.000 0.000  0 1.000
#> GSM379749     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379750     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379751     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379744     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379745     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379746     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379747     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379748     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379757     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379758     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379752     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379753     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379754     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379755     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379756     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379764     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379765     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379766     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379759     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379760     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379761     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379762     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379763     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379769     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379770     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379767     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379768     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379776     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379777     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379778     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379771     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379772     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379773     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379774     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379775     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379784     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379785     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379786     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379779     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379780     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379781     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379782     1  0.0188      0.971 0.996 0.000  0 0.004
#> GSM379783     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379792     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379793     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379794     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379787     1  0.0336      0.976 0.992 0.000  0 0.008
#> GSM379788     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379789     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379790     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379791     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379797     4  0.3649      0.735 0.204 0.000  0 0.796
#> GSM379798     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379795     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379796     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379721     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379722     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379723     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379716     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379717     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379718     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379719     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379720     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379729     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379730     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379731     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379724     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379725     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379726     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379727     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379728     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379737     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379738     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379739     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379732     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379733     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379734     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379735     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379736     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379742     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379743     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379740     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379741     3  0.0000      1.000 0.000 0.000  1 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2 p3    p4    p5
#> GSM379832     5  0.0609      0.895 0.000 0.020  0 0.000 0.980
#> GSM379833     5  0.0609      0.895 0.000 0.020  0 0.000 0.980
#> GSM379834     5  0.0609      0.895 0.000 0.020  0 0.000 0.980
#> GSM379827     5  0.0609      0.895 0.000 0.020  0 0.000 0.980
#> GSM379828     5  0.0609      0.895 0.000 0.020  0 0.000 0.980
#> GSM379829     5  0.3636      0.546 0.000 0.000  0 0.272 0.728
#> GSM379830     5  0.0609      0.895 0.000 0.020  0 0.000 0.980
#> GSM379831     5  0.0609      0.895 0.000 0.020  0 0.000 0.980
#> GSM379840     5  0.0290      0.889 0.000 0.008  0 0.000 0.992
#> GSM379841     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379842     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379835     5  0.0609      0.895 0.000 0.020  0 0.000 0.980
#> GSM379836     5  0.0609      0.895 0.000 0.020  0 0.000 0.980
#> GSM379837     5  0.0000      0.884 0.000 0.000  0 0.000 1.000
#> GSM379838     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379839     5  0.0000      0.884 0.000 0.000  0 0.000 1.000
#> GSM379848     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379849     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379850     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379843     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379844     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379845     5  0.0609      0.895 0.000 0.020  0 0.000 0.980
#> GSM379846     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379847     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379853     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379854     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379851     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379852     5  0.2813      0.899 0.000 0.168  0 0.000 0.832
#> GSM379804     4  0.0290      0.984 0.000 0.000  0 0.992 0.008
#> GSM379805     4  0.0609      0.983 0.000 0.000  0 0.980 0.020
#> GSM379806     4  0.0609      0.983 0.000 0.000  0 0.980 0.020
#> GSM379799     4  0.0609      0.983 0.000 0.000  0 0.980 0.020
#> GSM379800     4  0.0609      0.983 0.000 0.000  0 0.980 0.020
#> GSM379801     4  0.0609      0.983 0.000 0.000  0 0.980 0.020
#> GSM379802     4  0.0609      0.983 0.000 0.000  0 0.980 0.020
#> GSM379803     4  0.0609      0.983 0.000 0.000  0 0.980 0.020
#> GSM379812     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379813     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379814     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379807     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379808     4  0.0609      0.983 0.000 0.000  0 0.980 0.020
#> GSM379809     4  0.0609      0.983 0.000 0.000  0 0.980 0.020
#> GSM379810     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379811     4  0.0609      0.983 0.000 0.000  0 0.980 0.020
#> GSM379820     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379821     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379822     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379815     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379816     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379817     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379818     4  0.0609      0.983 0.000 0.000  0 0.980 0.020
#> GSM379819     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379825     4  0.0609      0.983 0.000 0.000  0 0.980 0.020
#> GSM379826     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379823     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379824     4  0.0000      0.985 0.000 0.000  0 1.000 0.000
#> GSM379749     2  0.2516      0.887 0.000 0.860  0 0.000 0.140
#> GSM379750     2  0.2516      0.887 0.000 0.860  0 0.000 0.140
#> GSM379751     2  0.2605      0.882 0.000 0.852  0 0.000 0.148
#> GSM379744     2  0.2561      0.885 0.000 0.856  0 0.000 0.144
#> GSM379745     2  0.2561      0.885 0.000 0.856  0 0.000 0.144
#> GSM379746     2  0.2516      0.887 0.000 0.860  0 0.000 0.140
#> GSM379747     2  0.2605      0.882 0.000 0.852  0 0.000 0.148
#> GSM379748     2  0.2605      0.882 0.000 0.852  0 0.000 0.148
#> GSM379757     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379758     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379752     2  0.2516      0.887 0.000 0.860  0 0.000 0.140
#> GSM379753     2  0.2605      0.882 0.000 0.852  0 0.000 0.148
#> GSM379754     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379755     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379756     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379764     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379765     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379766     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379759     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379760     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379761     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379762     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379763     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379769     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379770     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379767     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379768     2  0.0000      0.934 0.000 1.000  0 0.000 0.000
#> GSM379776     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379777     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379778     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379771     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379772     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379773     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379774     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379775     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379784     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379785     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379786     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379779     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379780     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379781     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379782     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379783     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379792     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379793     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379794     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379787     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379788     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379789     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379790     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379791     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379797     4  0.3821      0.721 0.216 0.000  0 0.764 0.020
#> GSM379798     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379795     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379796     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379721     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379722     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379723     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379716     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379717     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379718     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379719     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379720     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379729     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379730     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379731     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379724     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379725     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379726     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379727     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379728     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379737     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379738     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379739     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379732     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379733     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379734     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379735     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379736     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379742     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379743     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379740     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379741     3  0.0000      1.000 0.000 0.000  1 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     6  0.2805      0.653 0.000 0.004 0.000 0.000 0.184 0.812
#> GSM379833     6  0.2805      0.653 0.000 0.004 0.000 0.000 0.184 0.812
#> GSM379834     6  0.2805      0.653 0.000 0.004 0.000 0.000 0.184 0.812
#> GSM379827     5  0.3819      0.911 0.000 0.004 0.000 0.000 0.624 0.372
#> GSM379828     5  0.3819      0.911 0.000 0.004 0.000 0.000 0.624 0.372
#> GSM379829     5  0.2726      0.531 0.000 0.000 0.000 0.032 0.856 0.112
#> GSM379830     5  0.3841      0.915 0.000 0.004 0.000 0.000 0.616 0.380
#> GSM379831     5  0.3852      0.915 0.000 0.004 0.000 0.000 0.612 0.384
#> GSM379840     5  0.3872      0.906 0.000 0.004 0.000 0.000 0.604 0.392
#> GSM379841     6  0.0713      0.920 0.000 0.000 0.000 0.000 0.028 0.972
#> GSM379842     6  0.0713      0.920 0.000 0.000 0.000 0.000 0.028 0.972
#> GSM379835     5  0.3852      0.915 0.000 0.004 0.000 0.000 0.612 0.384
#> GSM379836     5  0.3852      0.915 0.000 0.004 0.000 0.000 0.612 0.384
#> GSM379837     5  0.3756      0.891 0.000 0.004 0.000 0.000 0.644 0.352
#> GSM379838     6  0.0713      0.920 0.000 0.000 0.000 0.000 0.028 0.972
#> GSM379839     5  0.3756      0.891 0.000 0.004 0.000 0.000 0.644 0.352
#> GSM379848     6  0.0000      0.921 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379849     6  0.0000      0.921 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379850     6  0.0000      0.921 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379843     6  0.0713      0.920 0.000 0.000 0.000 0.000 0.028 0.972
#> GSM379844     6  0.0713      0.920 0.000 0.000 0.000 0.000 0.028 0.972
#> GSM379845     5  0.3872      0.906 0.000 0.004 0.000 0.000 0.604 0.392
#> GSM379846     6  0.0713      0.920 0.000 0.000 0.000 0.000 0.028 0.972
#> GSM379847     6  0.0000      0.921 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379853     6  0.0146      0.921 0.000 0.000 0.000 0.000 0.004 0.996
#> GSM379854     6  0.0000      0.921 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379851     6  0.0000      0.921 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379852     6  0.0000      0.921 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379804     4  0.2996      0.887 0.000 0.000 0.000 0.772 0.228 0.000
#> GSM379805     4  0.3076      0.886 0.000 0.000 0.000 0.760 0.240 0.000
#> GSM379806     4  0.3076      0.886 0.000 0.000 0.000 0.760 0.240 0.000
#> GSM379799     4  0.3076      0.886 0.000 0.000 0.000 0.760 0.240 0.000
#> GSM379800     4  0.3076      0.886 0.000 0.000 0.000 0.760 0.240 0.000
#> GSM379801     4  0.3076      0.886 0.000 0.000 0.000 0.760 0.240 0.000
#> GSM379802     4  0.3076      0.886 0.000 0.000 0.000 0.760 0.240 0.000
#> GSM379803     4  0.3076      0.886 0.000 0.000 0.000 0.760 0.240 0.000
#> GSM379812     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379813     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379814     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379807     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379808     4  0.3076      0.886 0.000 0.000 0.000 0.760 0.240 0.000
#> GSM379809     4  0.3076      0.886 0.000 0.000 0.000 0.760 0.240 0.000
#> GSM379810     4  0.2854      0.887 0.000 0.000 0.000 0.792 0.208 0.000
#> GSM379811     4  0.3076      0.886 0.000 0.000 0.000 0.760 0.240 0.000
#> GSM379820     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379821     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379822     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379815     4  0.2854      0.887 0.000 0.000 0.000 0.792 0.208 0.000
#> GSM379816     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379817     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379818     4  0.3076      0.886 0.000 0.000 0.000 0.760 0.240 0.000
#> GSM379819     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379825     4  0.3076      0.886 0.000 0.000 0.000 0.760 0.240 0.000
#> GSM379826     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379823     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379824     4  0.0000      0.873 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379749     2  0.1814      0.919 0.000 0.900 0.000 0.000 0.100 0.000
#> GSM379750     2  0.1863      0.919 0.000 0.896 0.000 0.000 0.104 0.000
#> GSM379751     2  0.3101      0.794 0.000 0.756 0.000 0.000 0.244 0.000
#> GSM379744     2  0.1863      0.919 0.000 0.896 0.000 0.000 0.104 0.000
#> GSM379745     2  0.1863      0.919 0.000 0.896 0.000 0.000 0.104 0.000
#> GSM379746     2  0.1863      0.919 0.000 0.896 0.000 0.000 0.104 0.000
#> GSM379747     2  0.1863      0.919 0.000 0.896 0.000 0.000 0.104 0.000
#> GSM379748     2  0.1863      0.919 0.000 0.896 0.000 0.000 0.104 0.000
#> GSM379757     2  0.1753      0.921 0.000 0.912 0.000 0.000 0.084 0.004
#> GSM379758     2  0.0363      0.914 0.000 0.988 0.000 0.000 0.000 0.012
#> GSM379752     2  0.1863      0.919 0.000 0.896 0.000 0.000 0.104 0.000
#> GSM379753     2  0.1863      0.919 0.000 0.896 0.000 0.000 0.104 0.000
#> GSM379754     2  0.1858      0.921 0.000 0.904 0.000 0.000 0.092 0.004
#> GSM379755     2  0.1858      0.921 0.000 0.904 0.000 0.000 0.092 0.004
#> GSM379756     2  0.1858      0.921 0.000 0.904 0.000 0.000 0.092 0.004
#> GSM379764     2  0.1910      0.882 0.000 0.892 0.000 0.000 0.000 0.108
#> GSM379765     2  0.1910      0.882 0.000 0.892 0.000 0.000 0.000 0.108
#> GSM379766     2  0.1910      0.882 0.000 0.892 0.000 0.000 0.000 0.108
#> GSM379759     2  0.0260      0.915 0.000 0.992 0.000 0.000 0.000 0.008
#> GSM379760     2  0.0260      0.915 0.000 0.992 0.000 0.000 0.000 0.008
#> GSM379761     2  0.0363      0.914 0.000 0.988 0.000 0.000 0.000 0.012
#> GSM379762     2  0.0363      0.914 0.000 0.988 0.000 0.000 0.000 0.012
#> GSM379763     2  0.1910      0.882 0.000 0.892 0.000 0.000 0.000 0.108
#> GSM379769     2  0.1910      0.882 0.000 0.892 0.000 0.000 0.000 0.108
#> GSM379770     2  0.1910      0.882 0.000 0.892 0.000 0.000 0.000 0.108
#> GSM379767     2  0.1910      0.882 0.000 0.892 0.000 0.000 0.000 0.108
#> GSM379768     2  0.1910      0.882 0.000 0.892 0.000 0.000 0.000 0.108
#> GSM379776     1  0.0000      0.996 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379777     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379778     1  0.0260      0.994 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM379771     1  0.0000      0.996 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379772     1  0.0000      0.996 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379773     1  0.0146      0.995 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379774     1  0.0000      0.996 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379775     1  0.0000      0.996 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379784     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379785     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379786     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379779     1  0.0000      0.996 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379780     1  0.0000      0.996 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379781     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379782     1  0.0260      0.994 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM379783     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379792     1  0.0260      0.995 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM379793     1  0.0260      0.995 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM379794     1  0.0260      0.995 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM379787     1  0.0146      0.995 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379788     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379789     1  0.0260      0.995 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM379790     1  0.0260      0.995 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM379791     1  0.0260      0.995 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM379797     4  0.5398      0.669 0.212 0.000 0.000 0.584 0.204 0.000
#> GSM379798     1  0.0260      0.995 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM379795     1  0.0260      0.995 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM379796     1  0.0260      0.995 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM379721     3  0.0547      0.987 0.000 0.000 0.980 0.000 0.020 0.000
#> GSM379722     3  0.0547      0.987 0.000 0.000 0.980 0.000 0.020 0.000
#> GSM379723     3  0.0458      0.987 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM379716     3  0.0458      0.987 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM379717     3  0.0458      0.987 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM379718     3  0.0547      0.987 0.000 0.000 0.980 0.000 0.020 0.000
#> GSM379719     3  0.0547      0.987 0.000 0.000 0.980 0.000 0.020 0.000
#> GSM379720     3  0.0547      0.987 0.000 0.000 0.980 0.000 0.020 0.000
#> GSM379729     3  0.0458      0.985 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM379730     3  0.0458      0.985 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM379731     3  0.0458      0.985 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM379724     3  0.0458      0.987 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM379725     3  0.0790      0.985 0.000 0.000 0.968 0.000 0.032 0.000
#> GSM379726     3  0.0458      0.987 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM379727     3  0.0458      0.987 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM379728     3  0.0458      0.987 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM379737     3  0.0260      0.986 0.000 0.000 0.992 0.000 0.008 0.000
#> GSM379738     3  0.0260      0.986 0.000 0.000 0.992 0.000 0.008 0.000
#> GSM379739     3  0.0260      0.986 0.000 0.000 0.992 0.000 0.008 0.000
#> GSM379732     3  0.0458      0.985 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM379733     3  0.0146      0.987 0.000 0.000 0.996 0.000 0.004 0.000
#> GSM379734     3  0.0146      0.987 0.000 0.000 0.996 0.000 0.004 0.000
#> GSM379735     3  0.0547      0.984 0.000 0.000 0.980 0.000 0.020 0.000
#> GSM379736     3  0.0146      0.987 0.000 0.000 0.996 0.000 0.004 0.000
#> GSM379742     3  0.1176      0.966 0.000 0.024 0.956 0.000 0.020 0.000
#> GSM379743     3  0.0547      0.984 0.000 0.000 0.980 0.000 0.020 0.000
#> GSM379740     3  0.0260      0.986 0.000 0.000 0.992 0.000 0.008 0.000
#> GSM379741     3  0.1176      0.966 0.000 0.024 0.956 0.000 0.020 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-SD-skmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-SD-skmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-SD-skmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-SD-skmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-SD-skmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-SD-skmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-SD-skmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-SD-skmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-SD-skmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-SD-skmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-skmeans-get-signatures-1

get_signatures(res, k = 3)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-skmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-SD-skmeans-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-SD-skmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-SD-skmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-skmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-skmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-SD-skmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-SD-skmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-SD-skmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk SD-skmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-SD-skmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-SD-skmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-SD-skmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-SD-skmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-SD-skmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk SD-skmeans-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>              n individual(p) time(p) agent(p) k
#> SD:skmeans 138      9.55e-25       1    0.733 2
#> SD:skmeans 138      5.92e-53       1    0.914 3
#> SD:skmeans 139      2.80e-78       1    0.996 4
#> SD:skmeans 139     5.15e-106       1    1.000 5
#> SD:skmeans 139     5.38e-103       1    0.767 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

SD:pam**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["SD", "pam"]
# you can also extract it by
# res = res_list["SD:pam"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#>   Subgroups are detected by 'pam' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 6.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk SD-pam-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk SD-pam-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.988       0.995         0.4895 0.513   0.513
#> 3 3 1.000           0.989       0.995         0.3228 0.828   0.668
#> 4 4 1.000           0.963       0.958         0.1268 0.907   0.741
#> 5 5 1.000           0.975       0.991         0.1043 0.924   0.719
#> 6 6 0.991           0.953       0.981         0.0285 0.970   0.848

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 6
#> attr(,"optional")
#> [1] 2 3 4 5

There is also optional best \(k\) = 2 3 4 5 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2   0.000      1.000 0.000 1.000
#> GSM379833     2   0.000      1.000 0.000 1.000
#> GSM379834     2   0.000      1.000 0.000 1.000
#> GSM379827     2   0.000      1.000 0.000 1.000
#> GSM379828     2   0.000      1.000 0.000 1.000
#> GSM379829     2   0.000      1.000 0.000 1.000
#> GSM379830     2   0.000      1.000 0.000 1.000
#> GSM379831     2   0.000      1.000 0.000 1.000
#> GSM379840     2   0.000      1.000 0.000 1.000
#> GSM379841     2   0.000      1.000 0.000 1.000
#> GSM379842     2   0.000      1.000 0.000 1.000
#> GSM379835     2   0.000      1.000 0.000 1.000
#> GSM379836     2   0.000      1.000 0.000 1.000
#> GSM379837     2   0.000      1.000 0.000 1.000
#> GSM379838     2   0.000      1.000 0.000 1.000
#> GSM379839     2   0.000      1.000 0.000 1.000
#> GSM379848     2   0.000      1.000 0.000 1.000
#> GSM379849     2   0.000      1.000 0.000 1.000
#> GSM379850     2   0.000      1.000 0.000 1.000
#> GSM379843     2   0.000      1.000 0.000 1.000
#> GSM379844     2   0.000      1.000 0.000 1.000
#> GSM379845     2   0.000      1.000 0.000 1.000
#> GSM379846     2   0.000      1.000 0.000 1.000
#> GSM379847     2   0.000      1.000 0.000 1.000
#> GSM379853     2   0.000      1.000 0.000 1.000
#> GSM379854     2   0.000      1.000 0.000 1.000
#> GSM379851     2   0.000      1.000 0.000 1.000
#> GSM379852     2   0.000      1.000 0.000 1.000
#> GSM379804     1   0.000      0.991 1.000 0.000
#> GSM379805     1   0.000      0.991 1.000 0.000
#> GSM379806     1   0.000      0.991 1.000 0.000
#> GSM379799     1   0.000      0.991 1.000 0.000
#> GSM379800     1   0.000      0.991 1.000 0.000
#> GSM379801     1   0.000      0.991 1.000 0.000
#> GSM379802     1   0.000      0.991 1.000 0.000
#> GSM379803     1   0.000      0.991 1.000 0.000
#> GSM379812     1   0.118      0.976 0.984 0.016
#> GSM379813     1   0.000      0.991 1.000 0.000
#> GSM379814     1   0.000      0.991 1.000 0.000
#> GSM379807     1   0.000      0.991 1.000 0.000
#> GSM379808     1   0.000      0.991 1.000 0.000
#> GSM379809     1   0.000      0.991 1.000 0.000
#> GSM379810     1   0.000      0.991 1.000 0.000
#> GSM379811     1   0.000      0.991 1.000 0.000
#> GSM379820     1   0.000      0.991 1.000 0.000
#> GSM379821     1   0.000      0.991 1.000 0.000
#> GSM379822     1   0.000      0.991 1.000 0.000
#> GSM379815     1   0.000      0.991 1.000 0.000
#> GSM379816     1   0.706      0.771 0.808 0.192
#> GSM379817     1   0.000      0.991 1.000 0.000
#> GSM379818     1   0.000      0.991 1.000 0.000
#> GSM379819     1   0.000      0.991 1.000 0.000
#> GSM379825     1   0.000      0.991 1.000 0.000
#> GSM379826     1   0.000      0.991 1.000 0.000
#> GSM379823     1   0.000      0.991 1.000 0.000
#> GSM379824     1   0.000      0.991 1.000 0.000
#> GSM379749     2   0.000      1.000 0.000 1.000
#> GSM379750     2   0.000      1.000 0.000 1.000
#> GSM379751     2   0.000      1.000 0.000 1.000
#> GSM379744     2   0.000      1.000 0.000 1.000
#> GSM379745     2   0.000      1.000 0.000 1.000
#> GSM379746     2   0.000      1.000 0.000 1.000
#> GSM379747     2   0.000      1.000 0.000 1.000
#> GSM379748     2   0.000      1.000 0.000 1.000
#> GSM379757     2   0.000      1.000 0.000 1.000
#> GSM379758     2   0.000      1.000 0.000 1.000
#> GSM379752     2   0.000      1.000 0.000 1.000
#> GSM379753     2   0.000      1.000 0.000 1.000
#> GSM379754     2   0.000      1.000 0.000 1.000
#> GSM379755     2   0.000      1.000 0.000 1.000
#> GSM379756     2   0.000      1.000 0.000 1.000
#> GSM379764     2   0.000      1.000 0.000 1.000
#> GSM379765     2   0.000      1.000 0.000 1.000
#> GSM379766     2   0.000      1.000 0.000 1.000
#> GSM379759     2   0.000      1.000 0.000 1.000
#> GSM379760     2   0.000      1.000 0.000 1.000
#> GSM379761     2   0.000      1.000 0.000 1.000
#> GSM379762     2   0.000      1.000 0.000 1.000
#> GSM379763     2   0.000      1.000 0.000 1.000
#> GSM379769     2   0.000      1.000 0.000 1.000
#> GSM379770     2   0.000      1.000 0.000 1.000
#> GSM379767     2   0.000      1.000 0.000 1.000
#> GSM379768     2   0.000      1.000 0.000 1.000
#> GSM379776     1   0.000      0.991 1.000 0.000
#> GSM379777     1   0.000      0.991 1.000 0.000
#> GSM379778     1   0.000      0.991 1.000 0.000
#> GSM379771     1   0.000      0.991 1.000 0.000
#> GSM379772     1   0.000      0.991 1.000 0.000
#> GSM379773     1   0.000      0.991 1.000 0.000
#> GSM379774     1   0.000      0.991 1.000 0.000
#> GSM379775     1   0.000      0.991 1.000 0.000
#> GSM379784     1   0.000      0.991 1.000 0.000
#> GSM379785     1   0.000      0.991 1.000 0.000
#> GSM379786     1   0.000      0.991 1.000 0.000
#> GSM379779     1   0.000      0.991 1.000 0.000
#> GSM379780     1   0.000      0.991 1.000 0.000
#> GSM379781     1   0.000      0.991 1.000 0.000
#> GSM379782     1   0.000      0.991 1.000 0.000
#> GSM379783     1   0.000      0.991 1.000 0.000
#> GSM379792     1   0.000      0.991 1.000 0.000
#> GSM379793     1   0.000      0.991 1.000 0.000
#> GSM379794     1   0.000      0.991 1.000 0.000
#> GSM379787     1   0.000      0.991 1.000 0.000
#> GSM379788     1   0.000      0.991 1.000 0.000
#> GSM379789     1   0.000      0.991 1.000 0.000
#> GSM379790     1   0.000      0.991 1.000 0.000
#> GSM379791     1   0.000      0.991 1.000 0.000
#> GSM379797     1   0.000      0.991 1.000 0.000
#> GSM379798     1   0.000      0.991 1.000 0.000
#> GSM379795     1   0.000      0.991 1.000 0.000
#> GSM379796     1   0.000      0.991 1.000 0.000
#> GSM379721     1   0.000      0.991 1.000 0.000
#> GSM379722     1   0.000      0.991 1.000 0.000
#> GSM379723     1   0.000      0.991 1.000 0.000
#> GSM379716     1   0.000      0.991 1.000 0.000
#> GSM379717     1   0.000      0.991 1.000 0.000
#> GSM379718     1   0.000      0.991 1.000 0.000
#> GSM379719     1   0.000      0.991 1.000 0.000
#> GSM379720     1   0.000      0.991 1.000 0.000
#> GSM379729     1   0.722      0.760 0.800 0.200
#> GSM379730     1   0.722      0.760 0.800 0.200
#> GSM379731     1   0.000      0.991 1.000 0.000
#> GSM379724     1   0.000      0.991 1.000 0.000
#> GSM379725     1   0.615      0.825 0.848 0.152
#> GSM379726     1   0.000      0.991 1.000 0.000
#> GSM379727     1   0.000      0.991 1.000 0.000
#> GSM379728     1   0.000      0.991 1.000 0.000
#> GSM379737     1   0.000      0.991 1.000 0.000
#> GSM379738     1   0.000      0.991 1.000 0.000
#> GSM379739     1   0.000      0.991 1.000 0.000
#> GSM379732     1   0.000      0.991 1.000 0.000
#> GSM379733     1   0.000      0.991 1.000 0.000
#> GSM379734     1   0.000      0.991 1.000 0.000
#> GSM379735     1   0.000      0.991 1.000 0.000
#> GSM379736     1   0.000      0.991 1.000 0.000
#> GSM379742     2   0.000      1.000 0.000 1.000
#> GSM379743     1   0.000      0.991 1.000 0.000
#> GSM379740     1   0.000      0.991 1.000 0.000
#> GSM379741     2   0.000      1.000 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379833     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379834     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379827     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379828     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379829     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379830     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379831     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379840     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379841     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379842     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379835     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379836     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379837     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379838     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379839     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379848     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379849     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379850     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379843     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379844     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379845     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379846     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379847     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379853     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379854     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379851     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379852     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379804     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379805     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379806     1  0.0592      0.983 0.988 0.000 0.012
#> GSM379799     1  0.1860      0.942 0.948 0.000 0.052
#> GSM379800     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379801     3  0.5968      0.426 0.364 0.000 0.636
#> GSM379802     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379803     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379812     1  0.0747      0.977 0.984 0.016 0.000
#> GSM379813     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379814     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379807     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379808     1  0.0424      0.987 0.992 0.000 0.008
#> GSM379809     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379810     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379811     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379820     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379821     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379822     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379815     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379816     1  0.4452      0.750 0.808 0.192 0.000
#> GSM379817     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379818     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379819     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379825     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379826     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379823     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379824     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379749     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379750     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379751     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379744     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379745     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379746     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379747     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379748     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379757     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379758     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379752     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379753     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379754     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379755     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379756     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379764     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379765     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379766     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379759     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379760     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379761     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379762     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379763     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379769     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379770     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379767     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379768     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379776     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379777     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379778     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379771     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379772     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379773     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379774     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379775     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379784     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379785     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379786     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379779     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379780     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379781     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379782     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379783     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379792     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379793     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379794     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379787     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379788     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379789     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379790     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379791     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379797     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379798     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379795     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379796     1  0.0000      0.994 1.000 0.000 0.000
#> GSM379721     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379722     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379723     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379716     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379717     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379718     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379719     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379720     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379729     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379730     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379731     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379724     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379725     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379726     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379727     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379728     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379737     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379738     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379739     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379732     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379733     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379734     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379735     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379736     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379742     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379743     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379740     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379741     3  0.0000      0.987 0.000 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379833     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379834     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379827     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379828     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379829     4  0.2345      0.858 0.000 0.100 0.000 0.900
#> GSM379830     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379831     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379840     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379841     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379842     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379835     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379836     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379837     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379838     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379839     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379848     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379849     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379850     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379843     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379844     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379845     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379846     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379847     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379853     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379854     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379851     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379852     2  0.0000      0.960 0.000 1.000 0.000 0.000
#> GSM379804     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379805     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379806     4  0.0188      0.969 0.000 0.000 0.004 0.996
#> GSM379799     4  0.0469      0.961 0.000 0.000 0.012 0.988
#> GSM379800     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379801     4  0.2149      0.871 0.000 0.000 0.088 0.912
#> GSM379802     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379803     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379812     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379813     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379814     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379807     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379808     4  0.0188      0.969 0.000 0.000 0.004 0.996
#> GSM379809     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379810     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379811     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379820     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379821     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379822     4  0.4730      0.311 0.364 0.000 0.000 0.636
#> GSM379815     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379816     4  0.1302      0.928 0.044 0.000 0.000 0.956
#> GSM379817     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379818     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379819     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379825     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379826     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379823     1  0.4981      0.282 0.536 0.000 0.000 0.464
#> GSM379824     4  0.0000      0.972 0.000 0.000 0.000 1.000
#> GSM379749     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379750     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379751     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379744     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379745     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379746     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379747     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379748     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379757     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379758     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379752     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379753     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379754     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379755     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379756     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379764     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379765     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379766     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379759     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379760     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379761     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379762     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379763     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379769     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379770     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379767     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379768     2  0.2216      0.960 0.092 0.908 0.000 0.000
#> GSM379776     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379777     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379778     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379771     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379772     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379773     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379774     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379775     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379784     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379785     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379786     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379779     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379780     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379781     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379782     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379783     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379792     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379793     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379794     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379787     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379788     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379789     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379790     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379791     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379797     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379798     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379795     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379796     1  0.2216      0.985 0.908 0.000 0.000 0.092
#> GSM379721     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379722     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379723     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379716     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379717     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379718     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379719     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379720     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379729     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379730     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379731     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379724     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379725     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379726     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379727     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379728     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379737     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379738     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379739     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379732     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379733     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379734     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379735     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379736     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379742     3  0.1637      0.937 0.060 0.000 0.940 0.000
#> GSM379743     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379740     3  0.0000      0.998 0.000 0.000 1.000 0.000
#> GSM379741     3  0.0000      0.998 0.000 0.000 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379833     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379834     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379827     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379828     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379829     4   0.029      0.972 0.000 0.000 0.000 0.992 0.008
#> GSM379830     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379831     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379840     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379841     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379842     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379835     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379836     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379837     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379838     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379839     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379848     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379849     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379850     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379843     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379844     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379845     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379846     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379847     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379853     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379854     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379851     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379852     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379804     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379805     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379806     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379799     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379800     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379801     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379802     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379803     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379812     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379813     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379814     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379807     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379808     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379809     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379810     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379811     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379820     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379821     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379822     4   0.426      0.200 0.440 0.000 0.000 0.560 0.000
#> GSM379815     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379816     4   0.185      0.890 0.088 0.000 0.000 0.912 0.000
#> GSM379817     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379818     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379819     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379825     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379826     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379823     1   0.410      0.383 0.628 0.000 0.000 0.372 0.000
#> GSM379824     4   0.000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379749     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379750     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379751     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379744     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379745     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379746     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379747     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379748     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379757     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379758     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379752     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379753     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379754     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379755     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379756     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379764     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379765     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379766     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379759     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379760     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379761     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379762     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379763     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379769     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379770     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379767     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379768     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379776     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379777     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379778     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379771     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379772     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379773     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379774     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379775     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379784     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379785     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379786     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379779     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379780     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379781     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379782     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379783     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379792     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379793     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379794     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379787     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379788     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379789     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379790     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379791     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379797     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379798     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379795     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379796     1   0.000      0.986 1.000 0.000 0.000 0.000 0.000
#> GSM379721     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379722     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379723     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379716     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379717     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379718     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379719     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379720     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379729     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379730     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379731     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379724     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379725     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379726     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379727     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379728     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379737     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379738     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379739     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379732     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379733     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379734     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379735     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379736     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379742     3   0.416      0.355 0.000 0.392 0.608 0.000 0.000
#> GSM379743     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379740     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000
#> GSM379741     3   0.000      0.985 0.000 0.000 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     5   0.026      0.965 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379833     6   0.291      0.739 0.000 0.000 0.000 0.000 0.216 0.784
#> GSM379834     5   0.181      0.878 0.000 0.000 0.000 0.000 0.900 0.100
#> GSM379827     5   0.026      0.965 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379828     5   0.026      0.965 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379829     5   0.026      0.958 0.000 0.000 0.000 0.008 0.992 0.000
#> GSM379830     5   0.026      0.965 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379831     5   0.026      0.965 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379840     5   0.026      0.965 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379841     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379842     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379835     5   0.026      0.965 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379836     5   0.026      0.965 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379837     5   0.026      0.965 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379838     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379839     5   0.026      0.965 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379848     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379849     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379850     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379843     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379844     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379845     6   0.196      0.874 0.000 0.000 0.000 0.000 0.112 0.888
#> GSM379846     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379847     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379853     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379854     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379851     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379852     6   0.000      0.978 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379804     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379805     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379806     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379799     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379800     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379801     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379802     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379803     4   0.026      0.971 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM379812     4   0.026      0.971 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM379813     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379814     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379807     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379808     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379809     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379810     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379811     4   0.026      0.971 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM379820     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379821     4   0.026      0.971 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM379822     4   0.405      0.218 0.432 0.000 0.000 0.560 0.008 0.000
#> GSM379815     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379816     4   0.187      0.880 0.084 0.000 0.000 0.908 0.008 0.000
#> GSM379817     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379818     4   0.026      0.971 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM379819     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379825     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379826     4   0.000      0.975 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379823     1   0.392      0.368 0.620 0.000 0.000 0.372 0.008 0.000
#> GSM379824     4   0.026      0.971 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM379749     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379750     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379751     5   0.256      0.794 0.000 0.172 0.000 0.000 0.828 0.000
#> GSM379744     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379745     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379746     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379747     5   0.200      0.860 0.000 0.116 0.000 0.000 0.884 0.000
#> GSM379748     2   0.322      0.640 0.000 0.736 0.000 0.000 0.264 0.000
#> GSM379757     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379758     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379752     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379753     2   0.320      0.642 0.000 0.740 0.000 0.000 0.260 0.000
#> GSM379754     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379755     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379756     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379764     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379765     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379766     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379759     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379760     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379761     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379762     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379763     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379769     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379770     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379767     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379768     2   0.000      0.977 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379776     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379777     1   0.026      0.977 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM379778     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379771     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379772     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379773     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379774     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379775     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379784     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379785     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379786     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379779     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379780     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379781     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379782     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379783     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379792     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379793     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379794     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379787     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379788     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379789     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379790     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379791     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379797     1   0.026      0.976 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379798     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379795     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379796     1   0.000      0.984 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379721     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379722     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379723     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379716     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379717     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379718     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379719     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379720     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379729     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379730     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379731     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379724     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379725     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379726     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379727     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379728     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379737     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379738     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379739     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379732     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379733     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379734     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379735     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379736     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379742     3   0.374      0.359 0.000 0.392 0.608 0.000 0.000 0.000
#> GSM379743     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379740     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379741     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-SD-pam-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-SD-pam-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-SD-pam-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-SD-pam-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-SD-pam-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-SD-pam-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-SD-pam-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-SD-pam-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-SD-pam-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-SD-pam-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-SD-pam-get-signatures-1

get_signatures(res, k = 3)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-pam-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-SD-pam-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-SD-pam-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-SD-pam-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-SD-pam-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-pam-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-SD-pam-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-SD-pam-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-SD-pam-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk SD-pam-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-SD-pam-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-SD-pam-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-SD-pam-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-SD-pam-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-SD-pam-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk SD-pam-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>          n individual(p) time(p) agent(p) k
#> SD:pam 139      2.03e-27       1   1.0000 2
#> SD:pam 138      5.23e-55       1   0.9770 3
#> SD:pam 137      6.35e-79       1   0.9625 4
#> SD:pam 136     1.89e-103       1   0.9850 5
#> SD:pam 136      6.27e-99       1   0.0261 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

SD:mclust*

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["SD", "mclust"]
# you can also extract it by
# res = res_list["SD:mclust"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#>   Subgroups are detected by 'mclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 6.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk SD-mclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk SD-mclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.353           0.870       0.856         0.4439 0.518   0.518
#> 3 3 1.000           0.991       0.996         0.4517 0.837   0.685
#> 4 4 0.876           0.940       0.939         0.0897 0.948   0.855
#> 5 5 0.842           0.786       0.906         0.1094 0.929   0.765
#> 6 6 0.921           0.889       0.949         0.0242 0.924   0.701

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 6
#> attr(,"optional")
#> [1] 3

There is also optional best \(k\) = 3 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2   0.000      1.000 0.000 1.000
#> GSM379833     2   0.000      1.000 0.000 1.000
#> GSM379834     2   0.000      1.000 0.000 1.000
#> GSM379827     2   0.000      1.000 0.000 1.000
#> GSM379828     2   0.000      1.000 0.000 1.000
#> GSM379829     2   0.000      1.000 0.000 1.000
#> GSM379830     2   0.000      1.000 0.000 1.000
#> GSM379831     2   0.000      1.000 0.000 1.000
#> GSM379840     2   0.000      1.000 0.000 1.000
#> GSM379841     2   0.000      1.000 0.000 1.000
#> GSM379842     2   0.000      1.000 0.000 1.000
#> GSM379835     2   0.000      1.000 0.000 1.000
#> GSM379836     2   0.000      1.000 0.000 1.000
#> GSM379837     2   0.000      1.000 0.000 1.000
#> GSM379838     2   0.000      1.000 0.000 1.000
#> GSM379839     2   0.000      1.000 0.000 1.000
#> GSM379848     2   0.000      1.000 0.000 1.000
#> GSM379849     2   0.000      1.000 0.000 1.000
#> GSM379850     2   0.000      1.000 0.000 1.000
#> GSM379843     2   0.000      1.000 0.000 1.000
#> GSM379844     2   0.000      1.000 0.000 1.000
#> GSM379845     2   0.000      1.000 0.000 1.000
#> GSM379846     2   0.000      1.000 0.000 1.000
#> GSM379847     2   0.000      1.000 0.000 1.000
#> GSM379853     2   0.000      1.000 0.000 1.000
#> GSM379854     2   0.000      1.000 0.000 1.000
#> GSM379851     2   0.000      1.000 0.000 1.000
#> GSM379852     2   0.000      1.000 0.000 1.000
#> GSM379804     1   0.802      0.839 0.756 0.244
#> GSM379805     1   0.802      0.839 0.756 0.244
#> GSM379806     1   0.802      0.839 0.756 0.244
#> GSM379799     1   0.802      0.839 0.756 0.244
#> GSM379800     1   0.802      0.839 0.756 0.244
#> GSM379801     1   0.802      0.839 0.756 0.244
#> GSM379802     1   0.802      0.839 0.756 0.244
#> GSM379803     1   0.808      0.840 0.752 0.248
#> GSM379812     1   0.808      0.840 0.752 0.248
#> GSM379813     1   0.808      0.840 0.752 0.248
#> GSM379814     1   0.808      0.840 0.752 0.248
#> GSM379807     1   0.808      0.840 0.752 0.248
#> GSM379808     1   0.802      0.839 0.756 0.244
#> GSM379809     1   0.802      0.839 0.756 0.244
#> GSM379810     1   0.808      0.840 0.752 0.248
#> GSM379811     1   0.802      0.839 0.756 0.244
#> GSM379820     1   0.808      0.840 0.752 0.248
#> GSM379821     1   0.808      0.840 0.752 0.248
#> GSM379822     1   0.808      0.840 0.752 0.248
#> GSM379815     1   0.808      0.840 0.752 0.248
#> GSM379816     1   0.963      0.697 0.612 0.388
#> GSM379817     1   0.808      0.840 0.752 0.248
#> GSM379818     1   0.808      0.840 0.752 0.248
#> GSM379819     1   0.808      0.840 0.752 0.248
#> GSM379825     1   0.808      0.840 0.752 0.248
#> GSM379826     1   0.808      0.840 0.752 0.248
#> GSM379823     1   0.808      0.840 0.752 0.248
#> GSM379824     1   0.808      0.840 0.752 0.248
#> GSM379749     2   0.000      1.000 0.000 1.000
#> GSM379750     2   0.000      1.000 0.000 1.000
#> GSM379751     2   0.000      1.000 0.000 1.000
#> GSM379744     2   0.000      1.000 0.000 1.000
#> GSM379745     2   0.000      1.000 0.000 1.000
#> GSM379746     2   0.000      1.000 0.000 1.000
#> GSM379747     2   0.000      1.000 0.000 1.000
#> GSM379748     2   0.000      1.000 0.000 1.000
#> GSM379757     2   0.000      1.000 0.000 1.000
#> GSM379758     2   0.000      1.000 0.000 1.000
#> GSM379752     2   0.000      1.000 0.000 1.000
#> GSM379753     2   0.000      1.000 0.000 1.000
#> GSM379754     2   0.000      1.000 0.000 1.000
#> GSM379755     2   0.000      1.000 0.000 1.000
#> GSM379756     2   0.000      1.000 0.000 1.000
#> GSM379764     2   0.000      1.000 0.000 1.000
#> GSM379765     2   0.000      1.000 0.000 1.000
#> GSM379766     2   0.000      1.000 0.000 1.000
#> GSM379759     2   0.000      1.000 0.000 1.000
#> GSM379760     2   0.000      1.000 0.000 1.000
#> GSM379761     2   0.000      1.000 0.000 1.000
#> GSM379762     2   0.000      1.000 0.000 1.000
#> GSM379763     2   0.000      1.000 0.000 1.000
#> GSM379769     2   0.000      1.000 0.000 1.000
#> GSM379770     2   0.000      1.000 0.000 1.000
#> GSM379767     2   0.000      1.000 0.000 1.000
#> GSM379768     2   0.000      1.000 0.000 1.000
#> GSM379776     1   0.808      0.840 0.752 0.248
#> GSM379777     1   0.808      0.840 0.752 0.248
#> GSM379778     1   0.871      0.804 0.708 0.292
#> GSM379771     1   0.802      0.839 0.756 0.244
#> GSM379772     1   0.802      0.839 0.756 0.244
#> GSM379773     1   0.808      0.840 0.752 0.248
#> GSM379774     1   0.808      0.840 0.752 0.248
#> GSM379775     1   0.802      0.839 0.756 0.244
#> GSM379784     1   0.808      0.840 0.752 0.248
#> GSM379785     1   0.808      0.840 0.752 0.248
#> GSM379786     1   0.808      0.840 0.752 0.248
#> GSM379779     1   0.802      0.839 0.756 0.244
#> GSM379780     1   0.808      0.840 0.752 0.248
#> GSM379781     1   0.808      0.840 0.752 0.248
#> GSM379782     1   1.000      0.523 0.504 0.496
#> GSM379783     1   0.814      0.836 0.748 0.252
#> GSM379792     1   0.808      0.840 0.752 0.248
#> GSM379793     1   0.808      0.840 0.752 0.248
#> GSM379794     1   0.808      0.840 0.752 0.248
#> GSM379787     1   0.990      0.614 0.560 0.440
#> GSM379788     1   0.808      0.840 0.752 0.248
#> GSM379789     1   0.808      0.840 0.752 0.248
#> GSM379790     1   0.808      0.840 0.752 0.248
#> GSM379791     1   0.808      0.840 0.752 0.248
#> GSM379797     1   0.808      0.840 0.752 0.248
#> GSM379798     1   0.808      0.840 0.752 0.248
#> GSM379795     1   0.808      0.840 0.752 0.248
#> GSM379796     1   0.808      0.840 0.752 0.248
#> GSM379721     1   0.605      0.702 0.852 0.148
#> GSM379722     1   0.605      0.702 0.852 0.148
#> GSM379723     1   0.605      0.702 0.852 0.148
#> GSM379716     1   0.605      0.702 0.852 0.148
#> GSM379717     1   0.605      0.702 0.852 0.148
#> GSM379718     1   0.605      0.702 0.852 0.148
#> GSM379719     1   0.605      0.702 0.852 0.148
#> GSM379720     1   0.605      0.702 0.852 0.148
#> GSM379729     1   0.605      0.702 0.852 0.148
#> GSM379730     1   0.605      0.702 0.852 0.148
#> GSM379731     1   0.605      0.702 0.852 0.148
#> GSM379724     1   0.605      0.702 0.852 0.148
#> GSM379725     1   0.605      0.702 0.852 0.148
#> GSM379726     1   0.605      0.702 0.852 0.148
#> GSM379727     1   0.605      0.702 0.852 0.148
#> GSM379728     1   0.605      0.702 0.852 0.148
#> GSM379737     1   0.605      0.702 0.852 0.148
#> GSM379738     1   0.605      0.702 0.852 0.148
#> GSM379739     1   0.605      0.702 0.852 0.148
#> GSM379732     1   0.605      0.702 0.852 0.148
#> GSM379733     1   0.605      0.702 0.852 0.148
#> GSM379734     1   0.605      0.702 0.852 0.148
#> GSM379735     1   0.605      0.702 0.852 0.148
#> GSM379736     1   0.605      0.702 0.852 0.148
#> GSM379742     1   0.605      0.702 0.852 0.148
#> GSM379743     1   0.605      0.702 0.852 0.148
#> GSM379740     1   0.605      0.702 0.852 0.148
#> GSM379741     1   0.605      0.702 0.852 0.148

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379833     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379834     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379827     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379828     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379829     2  0.4504      0.743 0.196 0.804 0.000
#> GSM379830     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379831     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379840     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379841     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379842     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379835     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379836     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379837     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379838     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379839     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379848     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379849     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379850     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379843     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379844     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379845     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379846     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379847     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379853     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379854     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379851     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379852     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379804     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379805     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379806     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379799     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379800     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379801     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379802     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379803     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379812     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379813     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379814     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379807     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379808     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379809     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379810     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379811     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379820     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379821     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379822     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379815     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379816     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379817     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379818     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379819     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379825     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379826     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379823     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379824     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379749     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379750     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379751     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379744     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379745     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379746     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379747     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379748     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379757     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379758     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379752     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379753     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379754     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379755     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379756     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379764     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379765     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379766     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379759     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379760     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379761     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379762     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379763     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379769     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379770     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379767     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379768     2  0.0000      0.996 0.000 1.000 0.000
#> GSM379776     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379777     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379778     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379771     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379772     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379773     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379774     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379775     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379784     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379785     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379786     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379779     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379780     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379781     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379782     1  0.0237      0.995 0.996 0.004 0.000
#> GSM379783     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379792     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379793     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379794     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379787     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379788     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379789     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379790     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379791     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379797     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379798     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379795     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379796     1  0.0000      1.000 1.000 0.000 0.000
#> GSM379721     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379722     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379723     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379716     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379717     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379718     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379719     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379720     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379729     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379730     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379731     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379724     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379725     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379726     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379727     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379728     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379737     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379738     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379739     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379732     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379733     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379734     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379735     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379736     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379742     3  0.4121      0.806 0.168 0.000 0.832
#> GSM379743     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379740     3  0.0000      0.987 0.000 0.000 1.000
#> GSM379741     3  0.4121      0.806 0.168 0.000 0.832

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.0921      0.952 0.000 0.972 0.000 0.028
#> GSM379833     2  0.0921      0.952 0.000 0.972 0.000 0.028
#> GSM379834     2  0.0817      0.953 0.000 0.976 0.000 0.024
#> GSM379827     2  0.1302      0.951 0.000 0.956 0.000 0.044
#> GSM379828     2  0.1211      0.951 0.000 0.960 0.000 0.040
#> GSM379829     2  0.3612      0.849 0.100 0.856 0.000 0.044
#> GSM379830     2  0.1118      0.951 0.000 0.964 0.000 0.036
#> GSM379831     2  0.1022      0.952 0.000 0.968 0.000 0.032
#> GSM379840     2  0.1305      0.952 0.004 0.960 0.000 0.036
#> GSM379841     2  0.0188      0.953 0.000 0.996 0.000 0.004
#> GSM379842     2  0.0188      0.953 0.000 0.996 0.000 0.004
#> GSM379835     2  0.1022      0.952 0.000 0.968 0.000 0.032
#> GSM379836     2  0.1716      0.950 0.000 0.936 0.000 0.064
#> GSM379837     2  0.1637      0.950 0.000 0.940 0.000 0.060
#> GSM379838     2  0.0469      0.954 0.000 0.988 0.000 0.012
#> GSM379839     2  0.1118      0.952 0.000 0.964 0.000 0.036
#> GSM379848     2  0.0188      0.953 0.000 0.996 0.000 0.004
#> GSM379849     2  0.0592      0.952 0.000 0.984 0.000 0.016
#> GSM379850     2  0.1022      0.949 0.000 0.968 0.000 0.032
#> GSM379843     2  0.0336      0.953 0.000 0.992 0.000 0.008
#> GSM379844     2  0.0188      0.953 0.000 0.996 0.000 0.004
#> GSM379845     2  0.0817      0.954 0.000 0.976 0.000 0.024
#> GSM379846     2  0.0336      0.953 0.000 0.992 0.000 0.008
#> GSM379847     2  0.0188      0.953 0.000 0.996 0.000 0.004
#> GSM379853     2  0.1022      0.949 0.000 0.968 0.000 0.032
#> GSM379854     2  0.0336      0.953 0.000 0.992 0.000 0.008
#> GSM379851     2  0.1792      0.935 0.000 0.932 0.000 0.068
#> GSM379852     2  0.2704      0.902 0.000 0.876 0.000 0.124
#> GSM379804     1  0.3024      0.821 0.852 0.000 0.000 0.148
#> GSM379805     4  0.4040      1.000 0.248 0.000 0.000 0.752
#> GSM379806     4  0.4040      1.000 0.248 0.000 0.000 0.752
#> GSM379799     4  0.4040      1.000 0.248 0.000 0.000 0.752
#> GSM379800     4  0.4040      1.000 0.248 0.000 0.000 0.752
#> GSM379801     4  0.4040      1.000 0.248 0.000 0.000 0.752
#> GSM379802     4  0.4040      1.000 0.248 0.000 0.000 0.752
#> GSM379803     4  0.4040      1.000 0.248 0.000 0.000 0.752
#> GSM379812     1  0.3400      0.773 0.820 0.000 0.000 0.180
#> GSM379813     1  0.2814      0.839 0.868 0.000 0.000 0.132
#> GSM379814     1  0.1474      0.910 0.948 0.000 0.000 0.052
#> GSM379807     1  0.1557      0.908 0.944 0.000 0.000 0.056
#> GSM379808     4  0.4040      1.000 0.248 0.000 0.000 0.752
#> GSM379809     1  0.1792      0.899 0.932 0.000 0.000 0.068
#> GSM379810     1  0.1474      0.910 0.948 0.000 0.000 0.052
#> GSM379811     4  0.4040      1.000 0.248 0.000 0.000 0.752
#> GSM379820     1  0.2814      0.839 0.868 0.000 0.000 0.132
#> GSM379821     1  0.4193      0.588 0.732 0.000 0.000 0.268
#> GSM379822     1  0.2281      0.877 0.904 0.000 0.000 0.096
#> GSM379815     1  0.3764      0.708 0.784 0.000 0.000 0.216
#> GSM379816     1  0.1389      0.912 0.952 0.000 0.000 0.048
#> GSM379817     1  0.2081      0.887 0.916 0.000 0.000 0.084
#> GSM379818     4  0.4040      1.000 0.248 0.000 0.000 0.752
#> GSM379819     1  0.3266      0.791 0.832 0.000 0.000 0.168
#> GSM379825     4  0.4040      1.000 0.248 0.000 0.000 0.752
#> GSM379826     1  0.2345      0.873 0.900 0.000 0.000 0.100
#> GSM379823     1  0.0188      0.933 0.996 0.000 0.000 0.004
#> GSM379824     1  0.3688      0.724 0.792 0.000 0.000 0.208
#> GSM379749     2  0.1118      0.953 0.000 0.964 0.000 0.036
#> GSM379750     2  0.1118      0.953 0.000 0.964 0.000 0.036
#> GSM379751     2  0.1867      0.949 0.000 0.928 0.000 0.072
#> GSM379744     2  0.1557      0.950 0.000 0.944 0.000 0.056
#> GSM379745     2  0.1474      0.951 0.000 0.948 0.000 0.052
#> GSM379746     2  0.1302      0.952 0.000 0.956 0.000 0.044
#> GSM379747     2  0.1792      0.950 0.000 0.932 0.000 0.068
#> GSM379748     2  0.1211      0.951 0.000 0.960 0.000 0.040
#> GSM379757     2  0.0469      0.954 0.000 0.988 0.000 0.012
#> GSM379758     2  0.0921      0.952 0.000 0.972 0.000 0.028
#> GSM379752     2  0.1474      0.951 0.000 0.948 0.000 0.052
#> GSM379753     2  0.2216      0.944 0.000 0.908 0.000 0.092
#> GSM379754     2  0.1118      0.953 0.000 0.964 0.000 0.036
#> GSM379755     2  0.1118      0.953 0.000 0.964 0.000 0.036
#> GSM379756     2  0.0817      0.954 0.000 0.976 0.000 0.024
#> GSM379764     2  0.3528      0.860 0.000 0.808 0.000 0.192
#> GSM379765     2  0.3400      0.866 0.000 0.820 0.000 0.180
#> GSM379766     2  0.3528      0.860 0.000 0.808 0.000 0.192
#> GSM379759     2  0.1867      0.938 0.000 0.928 0.000 0.072
#> GSM379760     2  0.1716      0.944 0.000 0.936 0.000 0.064
#> GSM379761     2  0.1792      0.942 0.000 0.932 0.000 0.068
#> GSM379762     2  0.2216      0.929 0.000 0.908 0.000 0.092
#> GSM379763     2  0.2647      0.911 0.000 0.880 0.000 0.120
#> GSM379769     2  0.3710      0.857 0.004 0.804 0.000 0.192
#> GSM379770     2  0.3444      0.863 0.000 0.816 0.000 0.184
#> GSM379767     2  0.3528      0.860 0.000 0.808 0.000 0.192
#> GSM379768     2  0.3528      0.860 0.000 0.808 0.000 0.192
#> GSM379776     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379777     1  0.3123      0.808 0.844 0.000 0.000 0.156
#> GSM379778     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379771     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379772     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379773     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379774     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379775     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379784     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379785     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379786     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379779     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379780     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379781     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379782     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379783     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379792     1  0.0188      0.933 0.996 0.000 0.000 0.004
#> GSM379793     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379794     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379787     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379788     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379789     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379790     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379791     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379797     1  0.0188      0.933 0.996 0.000 0.000 0.004
#> GSM379798     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379795     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379796     1  0.0000      0.934 1.000 0.000 0.000 0.000
#> GSM379721     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379722     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379723     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379716     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379717     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379718     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379719     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379720     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379729     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379730     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379731     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379724     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379725     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379726     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379727     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379728     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379737     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379738     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379739     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379732     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379733     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379734     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379735     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379736     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379742     3  0.0188      0.995 0.004 0.000 0.996 0.000
#> GSM379743     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379740     3  0.0000      1.000 0.000 0.000 1.000 0.000
#> GSM379741     3  0.0188      0.995 0.004 0.000 0.996 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     5  0.0404      0.802 0.000 0.012 0.000 0.000 0.988
#> GSM379833     5  0.0510      0.801 0.000 0.016 0.000 0.000 0.984
#> GSM379834     5  0.0880      0.795 0.000 0.032 0.000 0.000 0.968
#> GSM379827     5  0.0000      0.803 0.000 0.000 0.000 0.000 1.000
#> GSM379828     5  0.0000      0.803 0.000 0.000 0.000 0.000 1.000
#> GSM379829     5  0.3109      0.601 0.000 0.000 0.000 0.200 0.800
#> GSM379830     5  0.0000      0.803 0.000 0.000 0.000 0.000 1.000
#> GSM379831     5  0.0510      0.801 0.000 0.016 0.000 0.000 0.984
#> GSM379840     5  0.0000      0.803 0.000 0.000 0.000 0.000 1.000
#> GSM379841     5  0.4201      0.371 0.000 0.408 0.000 0.000 0.592
#> GSM379842     5  0.3966      0.489 0.000 0.336 0.000 0.000 0.664
#> GSM379835     5  0.0000      0.803 0.000 0.000 0.000 0.000 1.000
#> GSM379836     5  0.0000      0.803 0.000 0.000 0.000 0.000 1.000
#> GSM379837     5  0.0000      0.803 0.000 0.000 0.000 0.000 1.000
#> GSM379838     5  0.3857      0.523 0.000 0.312 0.000 0.000 0.688
#> GSM379839     5  0.0000      0.803 0.000 0.000 0.000 0.000 1.000
#> GSM379848     5  0.4283      0.271 0.000 0.456 0.000 0.000 0.544
#> GSM379849     2  0.4182      0.206 0.000 0.600 0.000 0.000 0.400
#> GSM379850     5  0.4300      0.216 0.000 0.476 0.000 0.000 0.524
#> GSM379843     5  0.4278      0.277 0.000 0.452 0.000 0.000 0.548
#> GSM379844     5  0.4300      0.211 0.000 0.476 0.000 0.000 0.524
#> GSM379845     5  0.0000      0.803 0.000 0.000 0.000 0.000 1.000
#> GSM379846     5  0.4278      0.281 0.000 0.452 0.000 0.000 0.548
#> GSM379847     5  0.4268      0.296 0.000 0.444 0.000 0.000 0.556
#> GSM379853     5  0.4210      0.364 0.000 0.412 0.000 0.000 0.588
#> GSM379854     5  0.4294      0.239 0.000 0.468 0.000 0.000 0.532
#> GSM379851     2  0.3999      0.370 0.000 0.656 0.000 0.000 0.344
#> GSM379852     2  0.3508      0.565 0.000 0.748 0.000 0.000 0.252
#> GSM379804     1  0.4273      0.431 0.552 0.000 0.000 0.448 0.000
#> GSM379805     4  0.0000      0.999 0.000 0.000 0.000 1.000 0.000
#> GSM379806     4  0.0000      0.999 0.000 0.000 0.000 1.000 0.000
#> GSM379799     4  0.0000      0.999 0.000 0.000 0.000 1.000 0.000
#> GSM379800     4  0.0000      0.999 0.000 0.000 0.000 1.000 0.000
#> GSM379801     4  0.0162      0.995 0.004 0.000 0.000 0.996 0.000
#> GSM379802     4  0.0000      0.999 0.000 0.000 0.000 1.000 0.000
#> GSM379803     4  0.0000      0.999 0.000 0.000 0.000 1.000 0.000
#> GSM379812     1  0.4201      0.516 0.592 0.000 0.000 0.408 0.000
#> GSM379813     1  0.4030      0.605 0.648 0.000 0.000 0.352 0.000
#> GSM379814     1  0.2929      0.792 0.820 0.000 0.000 0.180 0.000
#> GSM379807     1  0.2074      0.837 0.896 0.000 0.000 0.104 0.000
#> GSM379808     4  0.0000      0.999 0.000 0.000 0.000 1.000 0.000
#> GSM379809     1  0.3534      0.729 0.744 0.000 0.000 0.256 0.000
#> GSM379810     1  0.3274      0.760 0.780 0.000 0.000 0.220 0.000
#> GSM379811     4  0.0000      0.999 0.000 0.000 0.000 1.000 0.000
#> GSM379820     1  0.3480      0.734 0.752 0.000 0.000 0.248 0.000
#> GSM379821     1  0.4273      0.432 0.552 0.000 0.000 0.448 0.000
#> GSM379822     1  0.2471      0.821 0.864 0.000 0.000 0.136 0.000
#> GSM379815     1  0.4219      0.501 0.584 0.000 0.000 0.416 0.000
#> GSM379816     1  0.3326      0.799 0.824 0.000 0.000 0.152 0.024
#> GSM379817     1  0.2929      0.792 0.820 0.000 0.000 0.180 0.000
#> GSM379818     4  0.0000      0.999 0.000 0.000 0.000 1.000 0.000
#> GSM379819     1  0.4192      0.523 0.596 0.000 0.000 0.404 0.000
#> GSM379825     4  0.0162      0.995 0.004 0.000 0.000 0.996 0.000
#> GSM379826     1  0.2648      0.811 0.848 0.000 0.000 0.152 0.000
#> GSM379823     1  0.0162      0.881 0.996 0.000 0.000 0.004 0.000
#> GSM379824     1  0.4171      0.538 0.604 0.000 0.000 0.396 0.000
#> GSM379749     5  0.0703      0.797 0.000 0.024 0.000 0.000 0.976
#> GSM379750     5  0.0000      0.803 0.000 0.000 0.000 0.000 1.000
#> GSM379751     5  0.0703      0.796 0.000 0.024 0.000 0.000 0.976
#> GSM379744     5  0.0880      0.793 0.000 0.032 0.000 0.000 0.968
#> GSM379745     5  0.0703      0.797 0.000 0.024 0.000 0.000 0.976
#> GSM379746     5  0.0703      0.797 0.000 0.024 0.000 0.000 0.976
#> GSM379747     5  0.0794      0.795 0.000 0.028 0.000 0.000 0.972
#> GSM379748     5  0.0162      0.803 0.000 0.004 0.000 0.000 0.996
#> GSM379757     2  0.4101      0.275 0.000 0.628 0.000 0.000 0.372
#> GSM379758     2  0.0000      0.836 0.000 1.000 0.000 0.000 0.000
#> GSM379752     5  0.1478      0.767 0.000 0.064 0.000 0.000 0.936
#> GSM379753     2  0.4227      0.237 0.000 0.580 0.000 0.000 0.420
#> GSM379754     2  0.3913      0.436 0.000 0.676 0.000 0.000 0.324
#> GSM379755     5  0.0880      0.795 0.000 0.032 0.000 0.000 0.968
#> GSM379756     5  0.2127      0.754 0.000 0.108 0.000 0.000 0.892
#> GSM379764     2  0.0510      0.825 0.016 0.984 0.000 0.000 0.000
#> GSM379765     2  0.0000      0.836 0.000 1.000 0.000 0.000 0.000
#> GSM379766     2  0.0000      0.836 0.000 1.000 0.000 0.000 0.000
#> GSM379759     2  0.0000      0.836 0.000 1.000 0.000 0.000 0.000
#> GSM379760     2  0.0000      0.836 0.000 1.000 0.000 0.000 0.000
#> GSM379761     2  0.0000      0.836 0.000 1.000 0.000 0.000 0.000
#> GSM379762     2  0.0000      0.836 0.000 1.000 0.000 0.000 0.000
#> GSM379763     2  0.0000      0.836 0.000 1.000 0.000 0.000 0.000
#> GSM379769     2  0.0510      0.825 0.016 0.984 0.000 0.000 0.000
#> GSM379770     2  0.1732      0.783 0.000 0.920 0.000 0.000 0.080
#> GSM379767     2  0.0000      0.836 0.000 1.000 0.000 0.000 0.000
#> GSM379768     2  0.0000      0.836 0.000 1.000 0.000 0.000 0.000
#> GSM379776     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379777     1  0.4201      0.516 0.592 0.000 0.000 0.408 0.000
#> GSM379778     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379771     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379772     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379773     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379774     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379775     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379784     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379785     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379786     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379779     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379780     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379781     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379782     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379783     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379792     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379793     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379794     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379787     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379788     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379789     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379790     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379791     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379797     1  0.0162      0.880 0.996 0.000 0.000 0.004 0.000
#> GSM379798     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379796     1  0.0000      0.882 1.000 0.000 0.000 0.000 0.000
#> GSM379721     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379722     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379723     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379716     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379717     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379718     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379719     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379720     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379729     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379730     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379731     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379724     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379725     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379726     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379727     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379728     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379737     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379738     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379739     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379732     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379733     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379734     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379735     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379736     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379742     3  0.3730      0.558 0.288 0.000 0.712 0.000 0.000
#> GSM379743     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379740     3  0.0000      0.971 0.000 0.000 1.000 0.000 0.000
#> GSM379741     3  0.3730      0.558 0.288 0.000 0.712 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379833     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379834     5  0.0458      0.928 0.000 0.016 0.000 0.000 0.984 0.000
#> GSM379827     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379828     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379829     5  0.2730      0.720 0.000 0.000 0.000 0.192 0.808 0.000
#> GSM379830     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379831     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379840     5  0.0363      0.931 0.000 0.012 0.000 0.000 0.988 0.000
#> GSM379841     5  0.3804      0.208 0.000 0.424 0.000 0.000 0.576 0.000
#> GSM379842     5  0.3659      0.391 0.000 0.364 0.000 0.000 0.636 0.000
#> GSM379835     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379836     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379837     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379838     5  0.2883      0.710 0.000 0.212 0.000 0.000 0.788 0.000
#> GSM379839     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379848     2  0.1814      0.871 0.000 0.900 0.000 0.000 0.100 0.000
#> GSM379849     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379850     2  0.1714      0.875 0.000 0.908 0.000 0.000 0.092 0.000
#> GSM379843     2  0.3428      0.622 0.000 0.696 0.000 0.000 0.304 0.000
#> GSM379844     2  0.3244      0.681 0.000 0.732 0.000 0.000 0.268 0.000
#> GSM379845     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379846     2  0.3288      0.675 0.000 0.724 0.000 0.000 0.276 0.000
#> GSM379847     2  0.2048      0.857 0.000 0.880 0.000 0.000 0.120 0.000
#> GSM379853     2  0.2416      0.824 0.000 0.844 0.000 0.000 0.156 0.000
#> GSM379854     2  0.1814      0.870 0.000 0.900 0.000 0.000 0.100 0.000
#> GSM379851     2  0.0146      0.915 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379852     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379804     4  0.4389      0.413 0.372 0.000 0.000 0.596 0.000 0.032
#> GSM379805     4  0.0000      0.863 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379806     4  0.0000      0.863 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379799     4  0.0000      0.863 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379800     4  0.0000      0.863 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379801     4  0.0000      0.863 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379802     4  0.0000      0.863 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379803     4  0.0000      0.863 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379812     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379813     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379814     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379807     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379808     4  0.0000      0.863 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379809     4  0.3602      0.635 0.208 0.000 0.000 0.760 0.000 0.032
#> GSM379810     1  0.4098      0.500 0.676 0.000 0.000 0.292 0.000 0.032
#> GSM379811     4  0.0000      0.863 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379820     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379821     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379822     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379815     1  0.1151      0.957 0.956 0.000 0.000 0.012 0.000 0.032
#> GSM379816     1  0.2201      0.912 0.912 0.000 0.000 0.028 0.028 0.032
#> GSM379817     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379818     4  0.0458      0.851 0.016 0.000 0.000 0.984 0.000 0.000
#> GSM379819     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379825     4  0.3747      0.371 0.396 0.000 0.000 0.604 0.000 0.000
#> GSM379826     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379823     1  0.0000      0.978 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379824     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379749     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379750     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379751     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379744     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379745     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379746     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379747     5  0.0363      0.930 0.000 0.012 0.000 0.000 0.988 0.000
#> GSM379748     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379757     2  0.2854      0.751 0.000 0.792 0.000 0.000 0.208 0.000
#> GSM379758     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379752     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379753     5  0.0363      0.930 0.000 0.012 0.000 0.000 0.988 0.000
#> GSM379754     5  0.2491      0.785 0.000 0.164 0.000 0.000 0.836 0.000
#> GSM379755     5  0.0000      0.938 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379756     5  0.2092      0.827 0.000 0.124 0.000 0.000 0.876 0.000
#> GSM379764     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379765     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379766     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379759     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379760     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379761     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379762     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379763     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379769     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379770     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379767     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379768     2  0.0000      0.916 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379776     1  0.0363      0.977 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379777     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379778     1  0.0632      0.969 0.976 0.000 0.000 0.000 0.000 0.024
#> GSM379771     1  0.0937      0.966 0.960 0.000 0.000 0.000 0.000 0.040
#> GSM379772     1  0.0937      0.966 0.960 0.000 0.000 0.000 0.000 0.040
#> GSM379773     1  0.0713      0.966 0.972 0.000 0.000 0.000 0.000 0.028
#> GSM379774     1  0.0713      0.966 0.972 0.000 0.000 0.000 0.000 0.028
#> GSM379775     1  0.0937      0.966 0.960 0.000 0.000 0.000 0.000 0.040
#> GSM379784     1  0.0363      0.977 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379785     1  0.0363      0.977 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379786     1  0.0000      0.978 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379779     1  0.0937      0.966 0.960 0.000 0.000 0.000 0.000 0.040
#> GSM379780     1  0.0458      0.977 0.984 0.000 0.000 0.000 0.000 0.016
#> GSM379781     1  0.0363      0.977 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379782     1  0.0260      0.977 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM379783     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379792     1  0.0146      0.978 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379793     1  0.0260      0.978 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM379794     1  0.0260      0.978 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM379787     1  0.0713      0.966 0.972 0.000 0.000 0.000 0.000 0.028
#> GSM379788     1  0.0363      0.977 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379789     1  0.0363      0.977 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379790     1  0.0363      0.977 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379791     1  0.0363      0.977 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379797     1  0.0363      0.977 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379798     1  0.0363      0.977 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379795     1  0.0363      0.977 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379796     1  0.0363      0.977 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379721     6  0.1007      1.000 0.000 0.000 0.044 0.000 0.000 0.956
#> GSM379722     6  0.1007      1.000 0.000 0.000 0.044 0.000 0.000 0.956
#> GSM379723     6  0.1007      1.000 0.000 0.000 0.044 0.000 0.000 0.956
#> GSM379716     6  0.1007      1.000 0.000 0.000 0.044 0.000 0.000 0.956
#> GSM379717     6  0.1007      1.000 0.000 0.000 0.044 0.000 0.000 0.956
#> GSM379718     6  0.1007      1.000 0.000 0.000 0.044 0.000 0.000 0.956
#> GSM379719     6  0.1007      1.000 0.000 0.000 0.044 0.000 0.000 0.956
#> GSM379720     6  0.1007      1.000 0.000 0.000 0.044 0.000 0.000 0.956
#> GSM379729     3  0.0000      0.900 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379730     3  0.0000      0.900 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379731     3  0.0000      0.900 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379724     6  0.1007      1.000 0.000 0.000 0.044 0.000 0.000 0.956
#> GSM379725     3  0.3126      0.670 0.000 0.000 0.752 0.000 0.000 0.248
#> GSM379726     3  0.3765      0.381 0.000 0.000 0.596 0.000 0.000 0.404
#> GSM379727     3  0.3288      0.633 0.000 0.000 0.724 0.000 0.000 0.276
#> GSM379728     3  0.3727      0.421 0.000 0.000 0.612 0.000 0.000 0.388
#> GSM379737     3  0.0000      0.900 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379738     3  0.0000      0.900 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379739     3  0.0000      0.900 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379732     3  0.0000      0.900 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379733     3  0.0000      0.900 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379734     3  0.0000      0.900 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379735     3  0.0000      0.900 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379736     3  0.0713      0.884 0.000 0.000 0.972 0.000 0.000 0.028
#> GSM379742     3  0.2277      0.793 0.076 0.000 0.892 0.000 0.000 0.032
#> GSM379743     3  0.0000      0.900 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379740     3  0.0000      0.900 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379741     3  0.2277      0.793 0.076 0.000 0.892 0.000 0.000 0.032

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-SD-mclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-SD-mclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-SD-mclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-SD-mclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-SD-mclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-SD-mclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-SD-mclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-SD-mclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-SD-mclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-SD-mclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-SD-mclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-SD-mclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-SD-mclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-SD-mclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-SD-mclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-SD-mclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-SD-mclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-SD-mclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-SD-mclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-SD-mclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk SD-mclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-SD-mclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-SD-mclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-SD-mclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-SD-mclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-SD-mclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk SD-mclust-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>             n individual(p) time(p) agent(p) k
#> SD:mclust 139      4.62e-29   1.000 1.00e+00 2
#> SD:mclust 139      1.97e-55   1.000 9.98e-01 3
#> SD:mclust 139      1.43e-59   1.000 4.17e-02 4
#> SD:mclust 122      8.38e-56   1.000 3.50e-05 5
#> SD:mclust 133      1.32e-52   0.978 5.60e-10 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

SD:NMF**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["SD", "NMF"]
# you can also extract it by
# res = res_list["SD:NMF"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#>   Subgroups are detected by 'NMF' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk SD-NMF-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk SD-NMF-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.970           0.966       0.985         0.4932 0.508   0.508
#> 3 3 0.615           0.562       0.749         0.3365 0.769   0.571
#> 4 4 0.880           0.895       0.950         0.1133 0.859   0.619
#> 5 5 0.881           0.850       0.919         0.0442 0.977   0.914
#> 6 6 0.889           0.908       0.923         0.0517 0.915   0.674

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2   0.000      0.986 0.000 1.000
#> GSM379833     2   0.000      0.986 0.000 1.000
#> GSM379834     2   0.000      0.986 0.000 1.000
#> GSM379827     2   0.000      0.986 0.000 1.000
#> GSM379828     2   0.000      0.986 0.000 1.000
#> GSM379829     1   0.000      0.983 1.000 0.000
#> GSM379830     2   0.000      0.986 0.000 1.000
#> GSM379831     2   0.000      0.986 0.000 1.000
#> GSM379840     2   0.000      0.986 0.000 1.000
#> GSM379841     2   0.000      0.986 0.000 1.000
#> GSM379842     2   0.000      0.986 0.000 1.000
#> GSM379835     2   0.000      0.986 0.000 1.000
#> GSM379836     2   0.000      0.986 0.000 1.000
#> GSM379837     1   0.921      0.511 0.664 0.336
#> GSM379838     2   0.000      0.986 0.000 1.000
#> GSM379839     2   0.730      0.738 0.204 0.796
#> GSM379848     2   0.000      0.986 0.000 1.000
#> GSM379849     2   0.000      0.986 0.000 1.000
#> GSM379850     2   0.000      0.986 0.000 1.000
#> GSM379843     2   0.000      0.986 0.000 1.000
#> GSM379844     2   0.000      0.986 0.000 1.000
#> GSM379845     2   0.000      0.986 0.000 1.000
#> GSM379846     2   0.000      0.986 0.000 1.000
#> GSM379847     2   0.000      0.986 0.000 1.000
#> GSM379853     2   0.000      0.986 0.000 1.000
#> GSM379854     2   0.000      0.986 0.000 1.000
#> GSM379851     2   0.000      0.986 0.000 1.000
#> GSM379852     2   0.000      0.986 0.000 1.000
#> GSM379804     1   0.000      0.983 1.000 0.000
#> GSM379805     1   0.000      0.983 1.000 0.000
#> GSM379806     1   0.000      0.983 1.000 0.000
#> GSM379799     1   0.000      0.983 1.000 0.000
#> GSM379800     1   0.000      0.983 1.000 0.000
#> GSM379801     1   0.000      0.983 1.000 0.000
#> GSM379802     1   0.000      0.983 1.000 0.000
#> GSM379803     1   0.000      0.983 1.000 0.000
#> GSM379812     1   0.000      0.983 1.000 0.000
#> GSM379813     1   0.000      0.983 1.000 0.000
#> GSM379814     1   0.000      0.983 1.000 0.000
#> GSM379807     1   0.000      0.983 1.000 0.000
#> GSM379808     1   0.000      0.983 1.000 0.000
#> GSM379809     1   0.000      0.983 1.000 0.000
#> GSM379810     1   0.000      0.983 1.000 0.000
#> GSM379811     1   0.000      0.983 1.000 0.000
#> GSM379820     1   0.000      0.983 1.000 0.000
#> GSM379821     1   0.000      0.983 1.000 0.000
#> GSM379822     1   0.000      0.983 1.000 0.000
#> GSM379815     1   0.000      0.983 1.000 0.000
#> GSM379816     1   0.494      0.875 0.892 0.108
#> GSM379817     1   0.000      0.983 1.000 0.000
#> GSM379818     1   0.000      0.983 1.000 0.000
#> GSM379819     1   0.000      0.983 1.000 0.000
#> GSM379825     1   0.000      0.983 1.000 0.000
#> GSM379826     1   0.000      0.983 1.000 0.000
#> GSM379823     1   0.000      0.983 1.000 0.000
#> GSM379824     1   0.000      0.983 1.000 0.000
#> GSM379749     2   0.000      0.986 0.000 1.000
#> GSM379750     2   0.000      0.986 0.000 1.000
#> GSM379751     2   0.000      0.986 0.000 1.000
#> GSM379744     2   0.000      0.986 0.000 1.000
#> GSM379745     2   0.000      0.986 0.000 1.000
#> GSM379746     2   0.000      0.986 0.000 1.000
#> GSM379747     2   0.000      0.986 0.000 1.000
#> GSM379748     2   0.000      0.986 0.000 1.000
#> GSM379757     2   0.000      0.986 0.000 1.000
#> GSM379758     2   0.000      0.986 0.000 1.000
#> GSM379752     2   0.000      0.986 0.000 1.000
#> GSM379753     2   0.000      0.986 0.000 1.000
#> GSM379754     2   0.000      0.986 0.000 1.000
#> GSM379755     2   0.000      0.986 0.000 1.000
#> GSM379756     2   0.000      0.986 0.000 1.000
#> GSM379764     2   0.000      0.986 0.000 1.000
#> GSM379765     2   0.000      0.986 0.000 1.000
#> GSM379766     2   0.000      0.986 0.000 1.000
#> GSM379759     2   0.000      0.986 0.000 1.000
#> GSM379760     2   0.000      0.986 0.000 1.000
#> GSM379761     2   0.000      0.986 0.000 1.000
#> GSM379762     2   0.000      0.986 0.000 1.000
#> GSM379763     2   0.000      0.986 0.000 1.000
#> GSM379769     2   0.000      0.986 0.000 1.000
#> GSM379770     2   0.000      0.986 0.000 1.000
#> GSM379767     2   0.000      0.986 0.000 1.000
#> GSM379768     2   0.000      0.986 0.000 1.000
#> GSM379776     1   0.000      0.983 1.000 0.000
#> GSM379777     1   0.000      0.983 1.000 0.000
#> GSM379778     2   0.242      0.948 0.040 0.960
#> GSM379771     1   0.000      0.983 1.000 0.000
#> GSM379772     1   0.000      0.983 1.000 0.000
#> GSM379773     1   0.000      0.983 1.000 0.000
#> GSM379774     1   0.000      0.983 1.000 0.000
#> GSM379775     1   0.000      0.983 1.000 0.000
#> GSM379784     1   0.000      0.983 1.000 0.000
#> GSM379785     1   0.000      0.983 1.000 0.000
#> GSM379786     1   0.760      0.729 0.780 0.220
#> GSM379779     1   0.000      0.983 1.000 0.000
#> GSM379780     1   0.000      0.983 1.000 0.000
#> GSM379781     1   0.000      0.983 1.000 0.000
#> GSM379782     2   0.000      0.986 0.000 1.000
#> GSM379783     2   0.909      0.511 0.324 0.676
#> GSM379792     1   0.000      0.983 1.000 0.000
#> GSM379793     1   0.000      0.983 1.000 0.000
#> GSM379794     1   0.000      0.983 1.000 0.000
#> GSM379787     2   0.714      0.756 0.196 0.804
#> GSM379788     1   0.000      0.983 1.000 0.000
#> GSM379789     1   0.000      0.983 1.000 0.000
#> GSM379790     1   0.000      0.983 1.000 0.000
#> GSM379791     1   0.000      0.983 1.000 0.000
#> GSM379797     1   0.000      0.983 1.000 0.000
#> GSM379798     1   0.000      0.983 1.000 0.000
#> GSM379795     1   0.000      0.983 1.000 0.000
#> GSM379796     1   0.000      0.983 1.000 0.000
#> GSM379721     1   0.000      0.983 1.000 0.000
#> GSM379722     1   0.000      0.983 1.000 0.000
#> GSM379723     1   0.000      0.983 1.000 0.000
#> GSM379716     1   0.000      0.983 1.000 0.000
#> GSM379717     1   0.000      0.983 1.000 0.000
#> GSM379718     1   0.000      0.983 1.000 0.000
#> GSM379719     1   0.000      0.983 1.000 0.000
#> GSM379720     1   0.000      0.983 1.000 0.000
#> GSM379729     1   0.680      0.787 0.820 0.180
#> GSM379730     1   0.722      0.759 0.800 0.200
#> GSM379731     1   0.000      0.983 1.000 0.000
#> GSM379724     1   0.000      0.983 1.000 0.000
#> GSM379725     1   0.204      0.954 0.968 0.032
#> GSM379726     1   0.000      0.983 1.000 0.000
#> GSM379727     1   0.000      0.983 1.000 0.000
#> GSM379728     1   0.000      0.983 1.000 0.000
#> GSM379737     1   0.000      0.983 1.000 0.000
#> GSM379738     1   0.000      0.983 1.000 0.000
#> GSM379739     1   0.000      0.983 1.000 0.000
#> GSM379732     1   0.000      0.983 1.000 0.000
#> GSM379733     1   0.000      0.983 1.000 0.000
#> GSM379734     1   0.000      0.983 1.000 0.000
#> GSM379735     1   0.000      0.983 1.000 0.000
#> GSM379736     1   0.000      0.983 1.000 0.000
#> GSM379742     2   0.000      0.986 0.000 1.000
#> GSM379743     1   0.753      0.735 0.784 0.216
#> GSM379740     1   0.000      0.983 1.000 0.000
#> GSM379741     2   0.000      0.986 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379833     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379834     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379827     2  0.0592   0.975627 0.000 0.988 0.012
#> GSM379828     2  0.0424   0.978411 0.000 0.992 0.008
#> GSM379829     3  0.6305   0.080186 0.484 0.000 0.516
#> GSM379830     2  0.0424   0.978411 0.000 0.992 0.008
#> GSM379831     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379840     2  0.3875   0.874194 0.044 0.888 0.068
#> GSM379841     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379842     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379835     2  0.0237   0.981338 0.000 0.996 0.004
#> GSM379836     2  0.3482   0.853751 0.000 0.872 0.128
#> GSM379837     3  0.9640   0.148028 0.280 0.252 0.468
#> GSM379838     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379839     3  0.9914   0.099894 0.280 0.328 0.392
#> GSM379848     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379849     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379850     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379843     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379844     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379845     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379846     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379847     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379853     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379854     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379851     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379852     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379804     3  0.6309   0.062455 0.496 0.000 0.504
#> GSM379805     1  0.6309  -0.088345 0.504 0.000 0.496
#> GSM379806     3  0.6309   0.062507 0.496 0.000 0.504
#> GSM379799     3  0.6308   0.070938 0.492 0.000 0.508
#> GSM379800     3  0.6308   0.070938 0.492 0.000 0.508
#> GSM379801     3  0.6308   0.070938 0.492 0.000 0.508
#> GSM379802     3  0.6308   0.070938 0.492 0.000 0.508
#> GSM379803     1  0.6309  -0.088345 0.504 0.000 0.496
#> GSM379812     1  0.4002   0.445438 0.840 0.000 0.160
#> GSM379813     1  0.4002   0.445484 0.840 0.000 0.160
#> GSM379814     1  0.4002   0.447277 0.840 0.000 0.160
#> GSM379807     1  0.6095   0.091781 0.608 0.000 0.392
#> GSM379808     3  0.6308   0.070938 0.492 0.000 0.508
#> GSM379809     3  0.6308   0.070938 0.492 0.000 0.508
#> GSM379810     1  0.6309  -0.088345 0.504 0.000 0.496
#> GSM379811     1  0.6309  -0.088345 0.504 0.000 0.496
#> GSM379820     1  0.1031   0.557326 0.976 0.000 0.024
#> GSM379821     1  0.1163   0.555450 0.972 0.000 0.028
#> GSM379822     1  0.4750   0.482245 0.784 0.000 0.216
#> GSM379815     1  0.6305  -0.067660 0.516 0.000 0.484
#> GSM379816     1  0.7640   0.089438 0.592 0.056 0.352
#> GSM379817     1  0.0237   0.562330 0.996 0.000 0.004
#> GSM379818     1  0.6309  -0.088345 0.504 0.000 0.496
#> GSM379819     1  0.4887   0.367805 0.772 0.000 0.228
#> GSM379825     1  0.6308  -0.081238 0.508 0.000 0.492
#> GSM379826     1  0.2711   0.557060 0.912 0.000 0.088
#> GSM379823     1  0.5397   0.423307 0.720 0.000 0.280
#> GSM379824     1  0.2066   0.544994 0.940 0.000 0.060
#> GSM379749     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379750     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379751     2  0.1031   0.965651 0.000 0.976 0.024
#> GSM379744     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379745     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379746     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379747     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379748     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379757     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379758     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379752     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379753     2  0.0592   0.975627 0.000 0.988 0.012
#> GSM379754     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379755     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379756     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379764     2  0.1482   0.957515 0.012 0.968 0.020
#> GSM379765     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379766     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379759     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379760     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379761     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379762     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379763     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379769     2  0.8026   0.499565 0.164 0.656 0.180
#> GSM379770     2  0.2564   0.925445 0.028 0.936 0.036
#> GSM379767     2  0.1163   0.959099 0.000 0.972 0.028
#> GSM379768     2  0.0000   0.984106 0.000 1.000 0.000
#> GSM379776     1  0.2165   0.555772 0.936 0.000 0.064
#> GSM379777     1  0.1529   0.548834 0.960 0.000 0.040
#> GSM379778     1  0.8806   0.196724 0.528 0.344 0.128
#> GSM379771     1  0.3686   0.519041 0.860 0.000 0.140
#> GSM379772     1  0.4452   0.514483 0.808 0.000 0.192
#> GSM379773     1  0.2448   0.561974 0.924 0.000 0.076
#> GSM379774     1  0.1753   0.568736 0.952 0.000 0.048
#> GSM379775     1  0.1289   0.567441 0.968 0.000 0.032
#> GSM379784     1  0.4178   0.530199 0.828 0.000 0.172
#> GSM379785     1  0.3482   0.554473 0.872 0.000 0.128
#> GSM379786     1  0.7165   0.438470 0.716 0.112 0.172
#> GSM379779     1  0.3686   0.546456 0.860 0.000 0.140
#> GSM379780     1  0.3752   0.547329 0.856 0.000 0.144
#> GSM379781     1  0.3752   0.548334 0.856 0.000 0.144
#> GSM379782     1  0.8595   0.159111 0.496 0.404 0.100
#> GSM379783     1  0.8300   0.310690 0.620 0.244 0.136
#> GSM379792     1  0.0592   0.559164 0.988 0.000 0.012
#> GSM379793     1  0.5397   0.423307 0.720 0.000 0.280
#> GSM379794     1  0.5254   0.444234 0.736 0.000 0.264
#> GSM379787     1  0.9100   0.220188 0.548 0.248 0.204
#> GSM379788     1  0.5098   0.462002 0.752 0.000 0.248
#> GSM379789     1  0.4291   0.524538 0.820 0.000 0.180
#> GSM379790     1  0.2625   0.566162 0.916 0.000 0.084
#> GSM379791     1  0.5431   0.419454 0.716 0.000 0.284
#> GSM379797     1  0.5016   0.341118 0.760 0.000 0.240
#> GSM379798     1  0.5216   0.448849 0.740 0.000 0.260
#> GSM379795     1  0.5859   0.325103 0.656 0.000 0.344
#> GSM379796     1  0.2878   0.564921 0.904 0.000 0.096
#> GSM379721     3  0.3038   0.511856 0.104 0.000 0.896
#> GSM379722     3  0.3267   0.507645 0.116 0.000 0.884
#> GSM379723     3  0.1964   0.508281 0.056 0.000 0.944
#> GSM379716     3  0.0892   0.490778 0.020 0.000 0.980
#> GSM379717     3  0.0892   0.490778 0.020 0.000 0.980
#> GSM379718     3  0.1031   0.492481 0.024 0.000 0.976
#> GSM379719     3  0.2625   0.514311 0.084 0.000 0.916
#> GSM379720     3  0.1163   0.491312 0.028 0.000 0.972
#> GSM379729     3  0.7613   0.230908 0.316 0.064 0.620
#> GSM379730     3  0.8169   0.097760 0.388 0.076 0.536
#> GSM379731     3  0.3816   0.486139 0.148 0.000 0.852
#> GSM379724     3  0.2625   0.514311 0.084 0.000 0.916
#> GSM379725     3  0.3686   0.492710 0.140 0.000 0.860
#> GSM379726     3  0.3340   0.505833 0.120 0.000 0.880
#> GSM379727     3  0.3482   0.501184 0.128 0.000 0.872
#> GSM379728     3  0.3038   0.511856 0.104 0.000 0.896
#> GSM379737     3  0.6309  -0.042908 0.496 0.000 0.504
#> GSM379738     3  0.6309  -0.042908 0.496 0.000 0.504
#> GSM379739     1  0.6308   0.023908 0.508 0.000 0.492
#> GSM379732     3  0.5291   0.350916 0.268 0.000 0.732
#> GSM379733     3  0.4399   0.445411 0.188 0.000 0.812
#> GSM379734     3  0.5327   0.342159 0.272 0.000 0.728
#> GSM379735     1  0.6308   0.023908 0.508 0.000 0.492
#> GSM379736     3  0.2796   0.512676 0.092 0.000 0.908
#> GSM379742     3  0.8714   0.039143 0.408 0.108 0.484
#> GSM379743     1  0.6308   0.023908 0.508 0.000 0.492
#> GSM379740     3  0.6295  -0.000109 0.472 0.000 0.528
#> GSM379741     3  0.7990  -0.000788 0.452 0.060 0.488

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379833     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379834     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379827     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379828     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379829     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379830     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379831     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379840     2  0.2469      0.878 0.000 0.892 0.000 0.108
#> GSM379841     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379842     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379835     2  0.0188      0.984 0.000 0.996 0.000 0.004
#> GSM379836     2  0.0188      0.984 0.000 0.996 0.000 0.004
#> GSM379837     4  0.4877      0.296 0.000 0.408 0.000 0.592
#> GSM379838     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379839     4  0.4661      0.448 0.000 0.348 0.000 0.652
#> GSM379848     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379849     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379850     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379843     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379844     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379845     2  0.0188      0.984 0.000 0.996 0.000 0.004
#> GSM379846     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379847     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379853     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379854     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379851     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379852     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379804     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379805     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379806     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379799     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379800     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379801     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379802     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379803     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379812     4  0.3837      0.715 0.224 0.000 0.000 0.776
#> GSM379813     4  0.3942      0.698 0.236 0.000 0.000 0.764
#> GSM379814     4  0.3219      0.787 0.164 0.000 0.000 0.836
#> GSM379807     4  0.0592      0.881 0.016 0.000 0.000 0.984
#> GSM379808     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379809     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379810     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379811     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379820     4  0.2704      0.821 0.124 0.000 0.000 0.876
#> GSM379821     4  0.3569      0.754 0.196 0.000 0.000 0.804
#> GSM379822     1  0.1474      0.869 0.948 0.000 0.000 0.052
#> GSM379815     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379816     4  0.4819      0.775 0.136 0.040 0.024 0.800
#> GSM379817     4  0.4134      0.660 0.260 0.000 0.000 0.740
#> GSM379818     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379819     4  0.1557      0.864 0.056 0.000 0.000 0.944
#> GSM379825     4  0.0000      0.886 0.000 0.000 0.000 1.000
#> GSM379826     4  0.3172      0.803 0.160 0.000 0.000 0.840
#> GSM379823     1  0.0188      0.886 0.996 0.000 0.000 0.004
#> GSM379824     4  0.2011      0.853 0.080 0.000 0.000 0.920
#> GSM379749     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379750     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379751     2  0.0188      0.984 0.000 0.996 0.000 0.004
#> GSM379744     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379745     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379746     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379747     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379748     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379757     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379758     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379752     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379753     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379754     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379755     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379756     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379764     2  0.3311      0.806 0.172 0.828 0.000 0.000
#> GSM379765     2  0.0336      0.981 0.008 0.992 0.000 0.000
#> GSM379766     2  0.0817      0.968 0.024 0.976 0.000 0.000
#> GSM379759     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379760     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379761     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379762     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379763     2  0.0000      0.987 0.000 1.000 0.000 0.000
#> GSM379769     1  0.4008      0.607 0.756 0.244 0.000 0.000
#> GSM379770     2  0.3400      0.796 0.180 0.820 0.000 0.000
#> GSM379767     2  0.2760      0.861 0.128 0.872 0.000 0.000
#> GSM379768     2  0.0592      0.975 0.016 0.984 0.000 0.000
#> GSM379776     1  0.4713      0.476 0.640 0.000 0.000 0.360
#> GSM379777     4  0.4564      0.517 0.328 0.000 0.000 0.672
#> GSM379778     1  0.0469      0.887 0.988 0.000 0.000 0.012
#> GSM379771     1  0.6894      0.389 0.536 0.000 0.120 0.344
#> GSM379772     1  0.6437      0.633 0.648 0.000 0.168 0.184
#> GSM379773     1  0.3837      0.721 0.776 0.000 0.000 0.224
#> GSM379774     1  0.3569      0.754 0.804 0.000 0.000 0.196
#> GSM379775     1  0.4103      0.676 0.744 0.000 0.000 0.256
#> GSM379784     1  0.0336      0.887 0.992 0.000 0.000 0.008
#> GSM379785     1  0.0707      0.885 0.980 0.000 0.000 0.020
#> GSM379786     1  0.0000      0.886 1.000 0.000 0.000 0.000
#> GSM379779     1  0.2928      0.836 0.880 0.000 0.012 0.108
#> GSM379780     1  0.2345      0.844 0.900 0.000 0.000 0.100
#> GSM379781     1  0.1302      0.878 0.956 0.000 0.000 0.044
#> GSM379782     1  0.0336      0.884 0.992 0.008 0.000 0.000
#> GSM379783     1  0.0524      0.887 0.988 0.004 0.000 0.008
#> GSM379792     1  0.4605      0.512 0.664 0.000 0.000 0.336
#> GSM379793     1  0.0000      0.886 1.000 0.000 0.000 0.000
#> GSM379794     1  0.0000      0.886 1.000 0.000 0.000 0.000
#> GSM379787     1  0.0188      0.887 0.996 0.000 0.000 0.004
#> GSM379788     1  0.0000      0.886 1.000 0.000 0.000 0.000
#> GSM379789     1  0.0469      0.887 0.988 0.000 0.000 0.012
#> GSM379790     1  0.1211      0.879 0.960 0.000 0.000 0.040
#> GSM379791     1  0.0000      0.886 1.000 0.000 0.000 0.000
#> GSM379797     4  0.1022      0.876 0.032 0.000 0.000 0.968
#> GSM379798     1  0.0000      0.886 1.000 0.000 0.000 0.000
#> GSM379795     1  0.0000      0.886 1.000 0.000 0.000 0.000
#> GSM379796     1  0.1389      0.876 0.952 0.000 0.000 0.048
#> GSM379721     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379722     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379723     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379716     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379717     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379718     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379719     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379720     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379729     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379730     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379731     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379724     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379725     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379726     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379727     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379728     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379737     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379738     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379739     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379732     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379733     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379734     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379735     3  0.0188      0.974 0.004 0.000 0.996 0.000
#> GSM379736     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379742     3  0.4776      0.418 0.376 0.000 0.624 0.000
#> GSM379743     3  0.1211      0.942 0.040 0.000 0.960 0.000
#> GSM379740     3  0.0000      0.977 0.000 0.000 1.000 0.000
#> GSM379741     3  0.3444      0.774 0.184 0.000 0.816 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379833     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379834     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379827     2  0.2798    0.89404 0.008 0.852 0.000 0.000 0.140
#> GSM379828     2  0.2843    0.89237 0.008 0.848 0.000 0.000 0.144
#> GSM379829     4  0.2270    0.79040 0.016 0.000 0.004 0.908 0.072
#> GSM379830     2  0.3001    0.89054 0.008 0.844 0.000 0.004 0.144
#> GSM379831     2  0.2956    0.89267 0.008 0.848 0.000 0.004 0.140
#> GSM379840     2  0.4436    0.82124 0.008 0.768 0.000 0.068 0.156
#> GSM379841     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379842     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379835     2  0.3362    0.87689 0.008 0.824 0.000 0.012 0.156
#> GSM379836     2  0.3768    0.86459 0.016 0.808 0.000 0.020 0.156
#> GSM379837     4  0.6209    0.22436 0.012 0.244 0.000 0.588 0.156
#> GSM379838     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379839     4  0.4554    0.56982 0.008 0.076 0.000 0.760 0.156
#> GSM379848     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379849     2  0.2843    0.89397 0.008 0.848 0.000 0.000 0.144
#> GSM379850     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379843     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379844     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379845     2  0.3252    0.88097 0.008 0.828 0.000 0.008 0.156
#> GSM379846     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379847     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379853     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379854     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379851     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379852     2  0.2798    0.89505 0.008 0.852 0.000 0.000 0.140
#> GSM379804     4  0.0290    0.85639 0.000 0.000 0.000 0.992 0.008
#> GSM379805     4  0.0290    0.85567 0.000 0.000 0.000 0.992 0.008
#> GSM379806     4  0.0290    0.85567 0.000 0.000 0.000 0.992 0.008
#> GSM379799     4  0.0609    0.85183 0.000 0.000 0.000 0.980 0.020
#> GSM379800     4  0.0609    0.85183 0.000 0.000 0.000 0.980 0.020
#> GSM379801     4  0.0771    0.84997 0.000 0.000 0.004 0.976 0.020
#> GSM379802     4  0.0404    0.85465 0.000 0.000 0.000 0.988 0.012
#> GSM379803     4  0.0510    0.85342 0.000 0.000 0.000 0.984 0.016
#> GSM379812     4  0.4734    0.47343 0.036 0.000 0.000 0.652 0.312
#> GSM379813     4  0.4352    0.59805 0.036 0.000 0.000 0.720 0.244
#> GSM379814     4  0.2676    0.79648 0.036 0.000 0.000 0.884 0.080
#> GSM379807     4  0.0671    0.85192 0.004 0.000 0.000 0.980 0.016
#> GSM379808     4  0.0609    0.85183 0.000 0.000 0.000 0.980 0.020
#> GSM379809     4  0.0290    0.85567 0.000 0.000 0.000 0.992 0.008
#> GSM379810     4  0.0162    0.85589 0.000 0.000 0.000 0.996 0.004
#> GSM379811     4  0.0290    0.85540 0.000 0.000 0.000 0.992 0.008
#> GSM379820     4  0.1992    0.82546 0.032 0.000 0.000 0.924 0.044
#> GSM379821     5  0.5092    0.00624 0.036 0.000 0.000 0.440 0.524
#> GSM379822     5  0.3593    0.66644 0.116 0.000 0.000 0.060 0.824
#> GSM379815     4  0.0000    0.85625 0.000 0.000 0.000 1.000 0.000
#> GSM379816     4  0.5547    0.43650 0.000 0.148 0.000 0.644 0.208
#> GSM379817     4  0.4657    0.50617 0.036 0.000 0.000 0.668 0.296
#> GSM379818     4  0.0162    0.85589 0.000 0.000 0.000 0.996 0.004
#> GSM379819     4  0.1211    0.84357 0.016 0.000 0.000 0.960 0.024
#> GSM379825     4  0.0000    0.85625 0.000 0.000 0.000 1.000 0.000
#> GSM379826     4  0.2848    0.79233 0.028 0.000 0.000 0.868 0.104
#> GSM379823     5  0.3283    0.66790 0.140 0.000 0.000 0.028 0.832
#> GSM379824     4  0.2260    0.81488 0.028 0.000 0.000 0.908 0.064
#> GSM379749     2  0.0000    0.88945 0.000 1.000 0.000 0.000 0.000
#> GSM379750     2  0.0000    0.88945 0.000 1.000 0.000 0.000 0.000
#> GSM379751     2  0.0404    0.88626 0.000 0.988 0.000 0.000 0.012
#> GSM379744     2  0.0162    0.88816 0.000 0.996 0.000 0.000 0.004
#> GSM379745     2  0.0162    0.88816 0.000 0.996 0.000 0.000 0.004
#> GSM379746     2  0.0000    0.88945 0.000 1.000 0.000 0.000 0.000
#> GSM379747     2  0.0162    0.88816 0.000 0.996 0.000 0.000 0.004
#> GSM379748     2  0.0162    0.88898 0.000 0.996 0.000 0.000 0.004
#> GSM379757     2  0.0000    0.88945 0.000 1.000 0.000 0.000 0.000
#> GSM379758     2  0.0000    0.88945 0.000 1.000 0.000 0.000 0.000
#> GSM379752     2  0.0162    0.88816 0.000 0.996 0.000 0.000 0.004
#> GSM379753     2  0.0162    0.88816 0.000 0.996 0.000 0.000 0.004
#> GSM379754     2  0.0000    0.88945 0.000 1.000 0.000 0.000 0.000
#> GSM379755     2  0.0000    0.88945 0.000 1.000 0.000 0.000 0.000
#> GSM379756     2  0.0000    0.88945 0.000 1.000 0.000 0.000 0.000
#> GSM379764     5  0.4045    0.52795 0.000 0.356 0.000 0.000 0.644
#> GSM379765     2  0.1608    0.84041 0.000 0.928 0.000 0.000 0.072
#> GSM379766     2  0.1410    0.85125 0.000 0.940 0.000 0.000 0.060
#> GSM379759     2  0.0162    0.88795 0.000 0.996 0.000 0.000 0.004
#> GSM379760     2  0.0000    0.88945 0.000 1.000 0.000 0.000 0.000
#> GSM379761     2  0.0000    0.88945 0.000 1.000 0.000 0.000 0.000
#> GSM379762     2  0.0000    0.88945 0.000 1.000 0.000 0.000 0.000
#> GSM379763     2  0.0000    0.88945 0.000 1.000 0.000 0.000 0.000
#> GSM379769     5  0.3421    0.66376 0.008 0.204 0.000 0.000 0.788
#> GSM379770     2  0.4294   -0.11461 0.000 0.532 0.000 0.000 0.468
#> GSM379767     2  0.2068    0.80966 0.004 0.904 0.000 0.000 0.092
#> GSM379768     2  0.1410    0.85125 0.000 0.940 0.000 0.000 0.060
#> GSM379776     1  0.1341    0.93809 0.944 0.000 0.000 0.056 0.000
#> GSM379777     1  0.3521    0.79634 0.820 0.000 0.000 0.140 0.040
#> GSM379778     1  0.0671    0.95750 0.980 0.000 0.000 0.004 0.016
#> GSM379771     1  0.2679    0.89447 0.892 0.000 0.056 0.048 0.004
#> GSM379772     1  0.2171    0.90475 0.912 0.000 0.064 0.024 0.000
#> GSM379773     1  0.0771    0.96135 0.976 0.000 0.000 0.020 0.004
#> GSM379774     1  0.0609    0.96203 0.980 0.000 0.000 0.020 0.000
#> GSM379775     1  0.1408    0.94587 0.948 0.000 0.008 0.044 0.000
#> GSM379784     1  0.1041    0.95783 0.964 0.000 0.000 0.004 0.032
#> GSM379785     1  0.0693    0.96325 0.980 0.000 0.000 0.012 0.008
#> GSM379786     1  0.1430    0.94582 0.944 0.000 0.000 0.004 0.052
#> GSM379779     1  0.0898    0.96005 0.972 0.000 0.008 0.020 0.000
#> GSM379780     1  0.0404    0.96275 0.988 0.000 0.000 0.012 0.000
#> GSM379781     1  0.0671    0.96010 0.980 0.000 0.000 0.004 0.016
#> GSM379782     1  0.0671    0.95765 0.980 0.004 0.000 0.000 0.016
#> GSM379783     1  0.1357    0.94530 0.948 0.004 0.000 0.000 0.048
#> GSM379792     1  0.1638    0.92945 0.932 0.000 0.000 0.064 0.004
#> GSM379793     1  0.0609    0.95859 0.980 0.000 0.000 0.000 0.020
#> GSM379794     1  0.0451    0.96089 0.988 0.000 0.000 0.004 0.008
#> GSM379787     1  0.0671    0.95750 0.980 0.000 0.000 0.004 0.016
#> GSM379788     1  0.0992    0.96185 0.968 0.000 0.000 0.008 0.024
#> GSM379789     1  0.0912    0.96279 0.972 0.000 0.000 0.012 0.016
#> GSM379790     1  0.0865    0.96046 0.972 0.000 0.000 0.024 0.004
#> GSM379791     1  0.0566    0.96078 0.984 0.000 0.000 0.004 0.012
#> GSM379797     4  0.4489    0.20496 0.420 0.000 0.000 0.572 0.008
#> GSM379798     1  0.0798    0.96112 0.976 0.000 0.000 0.008 0.016
#> GSM379795     1  0.0566    0.96078 0.984 0.000 0.000 0.004 0.012
#> GSM379796     1  0.1117    0.96101 0.964 0.000 0.000 0.020 0.016
#> GSM379721     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379722     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379723     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379716     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379717     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379718     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379719     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379720     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379729     3  0.0771    0.94205 0.004 0.000 0.976 0.000 0.020
#> GSM379730     3  0.1124    0.93061 0.004 0.000 0.960 0.000 0.036
#> GSM379731     3  0.0703    0.93997 0.000 0.000 0.976 0.000 0.024
#> GSM379724     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379725     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379726     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379727     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379728     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379737     3  0.0162    0.95391 0.004 0.000 0.996 0.000 0.000
#> GSM379738     3  0.0162    0.95391 0.004 0.000 0.996 0.000 0.000
#> GSM379739     3  0.0162    0.95391 0.004 0.000 0.996 0.000 0.000
#> GSM379732     3  0.0162    0.95391 0.004 0.000 0.996 0.000 0.000
#> GSM379733     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379734     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379735     3  0.1831    0.89741 0.004 0.000 0.920 0.000 0.076
#> GSM379736     3  0.0000    0.95560 0.000 0.000 1.000 0.000 0.000
#> GSM379742     3  0.6048    0.21611 0.048 0.036 0.516 0.000 0.400
#> GSM379743     3  0.3756    0.69085 0.008 0.000 0.744 0.000 0.248
#> GSM379740     3  0.0162    0.95391 0.004 0.000 0.996 0.000 0.000
#> GSM379741     3  0.4537    0.65790 0.024 0.016 0.724 0.000 0.236

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     5  0.3136      0.955 0.000 0.228 0.000 0.000 0.768 0.004
#> GSM379833     5  0.3109      0.956 0.000 0.224 0.000 0.000 0.772 0.004
#> GSM379834     5  0.2969      0.956 0.000 0.224 0.000 0.000 0.776 0.000
#> GSM379827     5  0.3052      0.949 0.000 0.216 0.000 0.000 0.780 0.004
#> GSM379828     5  0.3133      0.949 0.000 0.212 0.000 0.000 0.780 0.008
#> GSM379829     4  0.3394      0.541 0.000 0.000 0.000 0.752 0.236 0.012
#> GSM379830     5  0.3023      0.953 0.000 0.212 0.000 0.000 0.784 0.004
#> GSM379831     5  0.3023      0.953 0.000 0.212 0.000 0.000 0.784 0.004
#> GSM379840     5  0.3585      0.892 0.000 0.156 0.000 0.048 0.792 0.004
#> GSM379841     5  0.3023      0.953 0.000 0.232 0.000 0.000 0.768 0.000
#> GSM379842     5  0.2912      0.956 0.000 0.216 0.000 0.000 0.784 0.000
#> GSM379835     5  0.3073      0.947 0.000 0.204 0.000 0.000 0.788 0.008
#> GSM379836     5  0.3073      0.947 0.000 0.204 0.000 0.000 0.788 0.008
#> GSM379837     5  0.3359      0.631 0.000 0.012 0.000 0.196 0.784 0.008
#> GSM379838     5  0.3101      0.943 0.000 0.244 0.000 0.000 0.756 0.000
#> GSM379839     5  0.3329      0.594 0.000 0.004 0.000 0.220 0.768 0.008
#> GSM379848     5  0.3101      0.943 0.000 0.244 0.000 0.000 0.756 0.000
#> GSM379849     5  0.3431      0.949 0.000 0.228 0.000 0.000 0.756 0.016
#> GSM379850     5  0.3109      0.956 0.000 0.224 0.000 0.000 0.772 0.004
#> GSM379843     5  0.2969      0.956 0.000 0.224 0.000 0.000 0.776 0.000
#> GSM379844     5  0.3023      0.953 0.000 0.232 0.000 0.000 0.768 0.000
#> GSM379845     5  0.2964      0.950 0.000 0.204 0.000 0.000 0.792 0.004
#> GSM379846     5  0.2941      0.956 0.000 0.220 0.000 0.000 0.780 0.000
#> GSM379847     5  0.2996      0.955 0.000 0.228 0.000 0.000 0.772 0.000
#> GSM379853     5  0.2994      0.953 0.000 0.208 0.000 0.000 0.788 0.004
#> GSM379854     5  0.3050      0.950 0.000 0.236 0.000 0.000 0.764 0.000
#> GSM379851     5  0.2941      0.956 0.000 0.220 0.000 0.000 0.780 0.000
#> GSM379852     5  0.3190      0.956 0.000 0.220 0.000 0.000 0.772 0.008
#> GSM379804     4  0.0000      0.874 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379805     4  0.0260      0.873 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM379806     4  0.0146      0.874 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM379799     4  0.0725      0.867 0.000 0.000 0.000 0.976 0.012 0.012
#> GSM379800     4  0.0725      0.867 0.000 0.000 0.000 0.976 0.012 0.012
#> GSM379801     4  0.0725      0.867 0.000 0.000 0.000 0.976 0.012 0.012
#> GSM379802     4  0.0146      0.874 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM379803     4  0.0458      0.871 0.000 0.000 0.000 0.984 0.000 0.016
#> GSM379812     4  0.3464      0.560 0.000 0.000 0.000 0.688 0.000 0.312
#> GSM379813     4  0.2772      0.747 0.000 0.000 0.000 0.816 0.004 0.180
#> GSM379814     4  0.1498      0.854 0.000 0.000 0.000 0.940 0.032 0.028
#> GSM379807     4  0.0363      0.872 0.000 0.000 0.000 0.988 0.000 0.012
#> GSM379808     4  0.0520      0.870 0.000 0.000 0.000 0.984 0.008 0.008
#> GSM379809     4  0.0260      0.873 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM379810     4  0.0000      0.874 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379811     4  0.0000      0.874 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379820     4  0.2858      0.790 0.000 0.000 0.000 0.844 0.124 0.032
#> GSM379821     4  0.3706      0.419 0.000 0.000 0.000 0.620 0.000 0.380
#> GSM379822     6  0.1714      0.940 0.000 0.000 0.000 0.092 0.000 0.908
#> GSM379815     4  0.0146      0.874 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM379816     4  0.5208      0.368 0.000 0.148 0.000 0.604 0.000 0.248
#> GSM379817     4  0.3227      0.779 0.000 0.000 0.000 0.828 0.088 0.084
#> GSM379818     4  0.0000      0.874 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379819     4  0.0717      0.869 0.000 0.000 0.000 0.976 0.008 0.016
#> GSM379825     4  0.0405      0.874 0.000 0.000 0.000 0.988 0.008 0.004
#> GSM379826     4  0.2728      0.805 0.000 0.000 0.000 0.860 0.100 0.040
#> GSM379823     6  0.1219      0.943 0.000 0.000 0.000 0.048 0.004 0.948
#> GSM379824     4  0.2260      0.790 0.000 0.000 0.000 0.860 0.000 0.140
#> GSM379749     2  0.0146      0.964 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379750     2  0.0146      0.964 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379751     2  0.0508      0.957 0.000 0.984 0.000 0.000 0.012 0.004
#> GSM379744     2  0.0260      0.961 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379745     2  0.0260      0.961 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379746     2  0.0146      0.964 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379747     2  0.0260      0.961 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379748     2  0.0260      0.961 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379757     2  0.0146      0.964 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379758     2  0.0146      0.964 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379752     2  0.0146      0.964 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379753     2  0.0000      0.963 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379754     2  0.0146      0.964 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379755     2  0.0146      0.964 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379756     2  0.0146      0.964 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379764     2  0.2432      0.833 0.000 0.876 0.000 0.000 0.100 0.024
#> GSM379765     2  0.0692      0.955 0.000 0.976 0.000 0.000 0.004 0.020
#> GSM379766     2  0.0603      0.957 0.000 0.980 0.000 0.000 0.004 0.016
#> GSM379759     2  0.0291      0.963 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM379760     2  0.0146      0.964 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379761     2  0.0146      0.964 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379762     2  0.0146      0.964 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379763     2  0.0260      0.962 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379769     2  0.4990      0.476 0.000 0.644 0.000 0.000 0.204 0.152
#> GSM379770     2  0.3247      0.733 0.000 0.808 0.000 0.000 0.156 0.036
#> GSM379767     2  0.0603      0.958 0.000 0.980 0.000 0.000 0.004 0.016
#> GSM379768     2  0.0458      0.959 0.000 0.984 0.000 0.000 0.000 0.016
#> GSM379776     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379777     1  0.3284      0.711 0.784 0.000 0.000 0.020 0.000 0.196
#> GSM379778     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379771     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379772     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379773     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379774     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379775     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379784     1  0.0363      0.979 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379785     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379786     1  0.0865      0.957 0.964 0.000 0.000 0.000 0.000 0.036
#> GSM379779     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379780     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379781     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379782     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379783     1  0.0713      0.965 0.972 0.000 0.000 0.000 0.000 0.028
#> GSM379792     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379793     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379794     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379787     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379788     1  0.0146      0.985 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379789     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379790     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379791     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379797     4  0.3930      0.161 0.420 0.000 0.000 0.576 0.000 0.004
#> GSM379798     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379796     1  0.0000      0.988 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379721     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379722     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379723     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379716     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379717     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379718     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379719     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379720     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379729     3  0.1204      0.927 0.000 0.000 0.944 0.000 0.000 0.056
#> GSM379730     3  0.2793      0.769 0.000 0.000 0.800 0.000 0.000 0.200
#> GSM379731     3  0.1267      0.923 0.000 0.000 0.940 0.000 0.000 0.060
#> GSM379724     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379725     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379726     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379727     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379728     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379737     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379738     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379739     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379732     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379733     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379734     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379735     3  0.2003      0.871 0.000 0.000 0.884 0.000 0.000 0.116
#> GSM379736     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379742     3  0.4032      0.727 0.000 0.004 0.764 0.000 0.092 0.140
#> GSM379743     3  0.2562      0.809 0.000 0.000 0.828 0.000 0.000 0.172
#> GSM379740     3  0.0000      0.967 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379741     3  0.0993      0.943 0.000 0.000 0.964 0.000 0.012 0.024

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-SD-NMF-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-SD-NMF-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-SD-NMF-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-SD-NMF-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-SD-NMF-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-SD-NMF-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-SD-NMF-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-SD-NMF-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-SD-NMF-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-SD-NMF-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-SD-NMF-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-SD-NMF-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-SD-NMF-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-SD-NMF-get-signatures-4

get_signatures(res, k = 6)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-SD-NMF-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-SD-NMF-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-SD-NMF-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-SD-NMF-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-SD-NMF-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-SD-NMF-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk SD-NMF-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-SD-NMF-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-SD-NMF-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-SD-NMF-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-SD-NMF-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-SD-NMF-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk SD-NMF-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>          n individual(p) time(p) agent(p) k
#> SD:NMF 139      8.18e-23   1.000    0.856 2
#> SD:NMF  81      6.10e-31   0.996    0.666 3
#> SD:NMF 134      4.75e-68   1.000    0.600 4
#> SD:NMF 132      2.50e-70   1.000    0.711 5
#> SD:NMF 135      1.25e-99   1.000    0.909 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

CV:hclust

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["CV", "hclust"]
# you can also extract it by
# res = res_list["CV:hclust"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#>   Subgroups are detected by 'hclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 3.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk CV-hclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk CV-hclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.328           0.756       0.773         0.3813 0.508   0.508
#> 3 3 0.669           0.726       0.883         0.5461 0.795   0.640
#> 4 4 0.667           0.680       0.843         0.1835 0.839   0.637
#> 5 5 0.707           0.677       0.812         0.0618 0.957   0.857
#> 6 6 0.760           0.731       0.813         0.0536 0.945   0.788

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 3

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000     0.9025 0.000 1.000
#> GSM379833     2  0.0000     0.9025 0.000 1.000
#> GSM379834     2  0.0000     0.9025 0.000 1.000
#> GSM379827     2  0.5294     0.7616 0.120 0.880
#> GSM379828     2  0.5294     0.7616 0.120 0.880
#> GSM379829     1  0.7602     0.7033 0.780 0.220
#> GSM379830     2  0.5408     0.7555 0.124 0.876
#> GSM379831     2  0.5737     0.7352 0.136 0.864
#> GSM379840     2  0.9881     0.0117 0.436 0.564
#> GSM379841     2  0.0000     0.9025 0.000 1.000
#> GSM379842     2  0.0000     0.9025 0.000 1.000
#> GSM379835     2  0.7219     0.6013 0.200 0.800
#> GSM379836     2  0.7219     0.6013 0.200 0.800
#> GSM379837     2  0.9881     0.0117 0.436 0.564
#> GSM379838     2  0.0000     0.9025 0.000 1.000
#> GSM379839     2  0.9881     0.0117 0.436 0.564
#> GSM379848     2  0.0000     0.9025 0.000 1.000
#> GSM379849     2  0.0000     0.9025 0.000 1.000
#> GSM379850     2  0.0000     0.9025 0.000 1.000
#> GSM379843     2  0.0000     0.9025 0.000 1.000
#> GSM379844     2  0.0000     0.9025 0.000 1.000
#> GSM379845     2  0.9881     0.0117 0.436 0.564
#> GSM379846     2  0.0000     0.9025 0.000 1.000
#> GSM379847     2  0.0000     0.9025 0.000 1.000
#> GSM379853     2  0.0000     0.9025 0.000 1.000
#> GSM379854     2  0.0000     0.9025 0.000 1.000
#> GSM379851     2  0.0000     0.9025 0.000 1.000
#> GSM379852     2  0.0000     0.9025 0.000 1.000
#> GSM379804     1  0.2778     0.5816 0.952 0.048
#> GSM379805     1  0.2778     0.5816 0.952 0.048
#> GSM379806     1  0.2778     0.5816 0.952 0.048
#> GSM379799     1  0.0000     0.5430 1.000 0.000
#> GSM379800     1  0.0000     0.5430 1.000 0.000
#> GSM379801     1  0.0000     0.5430 1.000 0.000
#> GSM379802     1  0.0000     0.5430 1.000 0.000
#> GSM379803     1  0.1633     0.5629 0.976 0.024
#> GSM379812     1  0.9286     0.7794 0.656 0.344
#> GSM379813     1  0.9129     0.7720 0.672 0.328
#> GSM379814     1  0.7745     0.7174 0.772 0.228
#> GSM379807     1  0.7674     0.7151 0.776 0.224
#> GSM379808     1  0.2778     0.5816 0.952 0.048
#> GSM379809     1  0.7745     0.7174 0.772 0.228
#> GSM379810     1  0.7745     0.7174 0.772 0.228
#> GSM379811     1  0.1414     0.5596 0.980 0.020
#> GSM379820     1  0.7745     0.7174 0.772 0.228
#> GSM379821     1  0.9286     0.7794 0.656 0.344
#> GSM379822     1  0.9286     0.7794 0.656 0.344
#> GSM379815     1  0.7674     0.7151 0.776 0.224
#> GSM379816     1  0.9286     0.7794 0.656 0.344
#> GSM379817     1  0.8813     0.7577 0.700 0.300
#> GSM379818     1  0.0000     0.5430 1.000 0.000
#> GSM379819     1  0.7299     0.7011 0.796 0.204
#> GSM379825     1  0.0000     0.5430 1.000 0.000
#> GSM379826     1  0.7745     0.7174 0.772 0.228
#> GSM379823     1  0.9286     0.7794 0.656 0.344
#> GSM379824     1  0.9286     0.7794 0.656 0.344
#> GSM379749     2  0.0000     0.9025 0.000 1.000
#> GSM379750     2  0.0000     0.9025 0.000 1.000
#> GSM379751     2  0.0376     0.8991 0.004 0.996
#> GSM379744     2  0.0000     0.9025 0.000 1.000
#> GSM379745     2  0.0000     0.9025 0.000 1.000
#> GSM379746     2  0.0000     0.9025 0.000 1.000
#> GSM379747     2  0.0376     0.8991 0.004 0.996
#> GSM379748     2  0.0376     0.8991 0.004 0.996
#> GSM379757     2  0.0000     0.9025 0.000 1.000
#> GSM379758     2  0.0000     0.9025 0.000 1.000
#> GSM379752     2  0.0000     0.9025 0.000 1.000
#> GSM379753     2  0.0376     0.8991 0.004 0.996
#> GSM379754     2  0.0000     0.9025 0.000 1.000
#> GSM379755     2  0.0000     0.9025 0.000 1.000
#> GSM379756     2  0.0000     0.9025 0.000 1.000
#> GSM379764     2  0.0000     0.9025 0.000 1.000
#> GSM379765     2  0.0000     0.9025 0.000 1.000
#> GSM379766     2  0.0000     0.9025 0.000 1.000
#> GSM379759     2  0.0000     0.9025 0.000 1.000
#> GSM379760     2  0.0000     0.9025 0.000 1.000
#> GSM379761     2  0.0000     0.9025 0.000 1.000
#> GSM379762     2  0.0000     0.9025 0.000 1.000
#> GSM379763     2  0.0000     0.9025 0.000 1.000
#> GSM379769     2  0.0000     0.9025 0.000 1.000
#> GSM379770     2  0.0000     0.9025 0.000 1.000
#> GSM379767     2  0.0000     0.9025 0.000 1.000
#> GSM379768     2  0.0000     0.9025 0.000 1.000
#> GSM379776     1  0.9795     0.7842 0.584 0.416
#> GSM379777     1  0.9522     0.7871 0.628 0.372
#> GSM379778     2  0.7453     0.5529 0.212 0.788
#> GSM379771     1  0.9795     0.7842 0.584 0.416
#> GSM379772     1  0.9795     0.7842 0.584 0.416
#> GSM379773     1  0.9970     0.7121 0.532 0.468
#> GSM379774     1  0.9795     0.7842 0.584 0.416
#> GSM379775     1  0.9795     0.7842 0.584 0.416
#> GSM379784     1  0.9580     0.7881 0.620 0.380
#> GSM379785     1  0.9775     0.7859 0.588 0.412
#> GSM379786     1  0.9580     0.7881 0.620 0.380
#> GSM379779     1  0.9795     0.7842 0.584 0.416
#> GSM379780     1  0.9775     0.7859 0.588 0.412
#> GSM379781     1  0.9754     0.7870 0.592 0.408
#> GSM379782     2  0.7453     0.5529 0.212 0.788
#> GSM379783     1  0.9580     0.7881 0.620 0.380
#> GSM379792     1  0.7883     0.7035 0.764 0.236
#> GSM379793     1  0.9710     0.7881 0.600 0.400
#> GSM379794     1  0.9710     0.7881 0.600 0.400
#> GSM379787     2  0.7453     0.5529 0.212 0.788
#> GSM379788     1  0.9580     0.7881 0.620 0.380
#> GSM379789     1  0.9686     0.7887 0.604 0.396
#> GSM379790     1  0.9710     0.7881 0.600 0.400
#> GSM379791     1  0.9710     0.7881 0.600 0.400
#> GSM379797     1  0.0000     0.5430 1.000 0.000
#> GSM379798     1  0.9710     0.7881 0.600 0.400
#> GSM379795     1  0.9710     0.7881 0.600 0.400
#> GSM379796     1  0.7883     0.7035 0.764 0.236
#> GSM379721     1  0.9922     0.7641 0.552 0.448
#> GSM379722     1  0.9922     0.7641 0.552 0.448
#> GSM379723     1  0.9922     0.7641 0.552 0.448
#> GSM379716     1  0.9922     0.7641 0.552 0.448
#> GSM379717     1  0.9922     0.7641 0.552 0.448
#> GSM379718     1  0.9922     0.7641 0.552 0.448
#> GSM379719     1  0.9922     0.7641 0.552 0.448
#> GSM379720     1  0.9922     0.7641 0.552 0.448
#> GSM379729     1  0.9922     0.7641 0.552 0.448
#> GSM379730     1  0.9922     0.7641 0.552 0.448
#> GSM379731     1  0.9922     0.7641 0.552 0.448
#> GSM379724     1  0.9922     0.7641 0.552 0.448
#> GSM379725     1  0.9922     0.7641 0.552 0.448
#> GSM379726     1  0.9922     0.7641 0.552 0.448
#> GSM379727     1  0.9922     0.7641 0.552 0.448
#> GSM379728     1  0.9922     0.7641 0.552 0.448
#> GSM379737     1  0.9922     0.7641 0.552 0.448
#> GSM379738     1  0.9922     0.7641 0.552 0.448
#> GSM379739     1  0.9922     0.7641 0.552 0.448
#> GSM379732     1  0.9922     0.7641 0.552 0.448
#> GSM379733     1  0.9922     0.7641 0.552 0.448
#> GSM379734     1  0.9922     0.7641 0.552 0.448
#> GSM379735     1  0.9922     0.7641 0.552 0.448
#> GSM379736     1  0.9922     0.7641 0.552 0.448
#> GSM379742     2  0.7453     0.5529 0.212 0.788
#> GSM379743     1  0.9922     0.7641 0.552 0.448
#> GSM379740     1  0.9922     0.7641 0.552 0.448
#> GSM379741     2  0.7453     0.5529 0.212 0.788

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.1529     0.8938 0.040 0.960 0.000
#> GSM379833     2  0.1529     0.8938 0.040 0.960 0.000
#> GSM379834     2  0.1529     0.8938 0.040 0.960 0.000
#> GSM379827     2  0.6566     0.3678 0.376 0.612 0.012
#> GSM379828     2  0.6566     0.3678 0.376 0.612 0.012
#> GSM379829     3  0.6180     0.2353 0.416 0.000 0.584
#> GSM379830     2  0.6584     0.3573 0.380 0.608 0.012
#> GSM379831     2  0.6632     0.3245 0.392 0.596 0.012
#> GSM379840     1  0.9581     0.1250 0.476 0.288 0.236
#> GSM379841     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379842     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379835     2  0.7054     0.1285 0.456 0.524 0.020
#> GSM379836     2  0.7054     0.1285 0.456 0.524 0.020
#> GSM379837     1  0.9581     0.1250 0.476 0.288 0.236
#> GSM379838     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379839     1  0.9581     0.1250 0.476 0.288 0.236
#> GSM379848     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379849     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379850     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379843     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379844     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379845     1  0.9581     0.1250 0.476 0.288 0.236
#> GSM379846     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379847     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379853     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379854     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379851     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379852     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379804     3  0.6026     0.4972 0.376 0.000 0.624
#> GSM379805     3  0.6008     0.5072 0.372 0.000 0.628
#> GSM379806     3  0.6008     0.5072 0.372 0.000 0.628
#> GSM379799     3  0.0000     0.7738 0.000 0.000 1.000
#> GSM379800     3  0.0000     0.7738 0.000 0.000 1.000
#> GSM379801     3  0.0000     0.7738 0.000 0.000 1.000
#> GSM379802     3  0.0000     0.7738 0.000 0.000 1.000
#> GSM379803     3  0.4796     0.6947 0.220 0.000 0.780
#> GSM379812     1  0.3192     0.7666 0.888 0.000 0.112
#> GSM379813     1  0.3551     0.7512 0.868 0.000 0.132
#> GSM379814     1  0.5397     0.5538 0.720 0.000 0.280
#> GSM379807     1  0.5431     0.5475 0.716 0.000 0.284
#> GSM379808     3  0.6008     0.5072 0.372 0.000 0.628
#> GSM379809     1  0.5397     0.5538 0.720 0.000 0.280
#> GSM379810     1  0.5397     0.5538 0.720 0.000 0.280
#> GSM379811     3  0.4654     0.7008 0.208 0.000 0.792
#> GSM379820     1  0.5431     0.5465 0.716 0.000 0.284
#> GSM379821     1  0.3116     0.7689 0.892 0.000 0.108
#> GSM379822     1  0.3116     0.7689 0.892 0.000 0.108
#> GSM379815     1  0.5431     0.5475 0.716 0.000 0.284
#> GSM379816     1  0.3192     0.7666 0.888 0.000 0.112
#> GSM379817     1  0.4002     0.7229 0.840 0.000 0.160
#> GSM379818     3  0.0000     0.7738 0.000 0.000 1.000
#> GSM379819     1  0.6286     0.0551 0.536 0.000 0.464
#> GSM379825     3  0.0000     0.7738 0.000 0.000 1.000
#> GSM379826     1  0.5431     0.5465 0.716 0.000 0.284
#> GSM379823     1  0.3116     0.7689 0.892 0.000 0.108
#> GSM379824     1  0.3116     0.7689 0.892 0.000 0.108
#> GSM379749     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379750     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379751     2  0.1031     0.9067 0.024 0.976 0.000
#> GSM379744     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379745     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379746     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379747     2  0.1031     0.9067 0.024 0.976 0.000
#> GSM379748     2  0.1031     0.9067 0.024 0.976 0.000
#> GSM379757     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379758     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379752     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379753     2  0.1031     0.9067 0.024 0.976 0.000
#> GSM379754     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379755     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379756     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379764     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379765     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379766     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379759     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379760     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379761     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379762     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379763     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379769     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379770     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379767     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379768     2  0.0000     0.9266 0.000 1.000 0.000
#> GSM379776     1  0.2280     0.7972 0.940 0.008 0.052
#> GSM379777     1  0.3619     0.7610 0.864 0.000 0.136
#> GSM379778     1  0.7059     0.1327 0.520 0.460 0.020
#> GSM379771     1  0.2280     0.7972 0.940 0.008 0.052
#> GSM379772     1  0.2280     0.7972 0.940 0.008 0.052
#> GSM379773     1  0.4087     0.7656 0.880 0.068 0.052
#> GSM379774     1  0.2280     0.7972 0.940 0.008 0.052
#> GSM379775     1  0.2280     0.7972 0.940 0.008 0.052
#> GSM379784     1  0.2537     0.7867 0.920 0.000 0.080
#> GSM379785     1  0.2096     0.7966 0.944 0.004 0.052
#> GSM379786     1  0.2537     0.7867 0.920 0.000 0.080
#> GSM379779     1  0.2280     0.7972 0.940 0.008 0.052
#> GSM379780     1  0.2096     0.7965 0.944 0.004 0.052
#> GSM379781     1  0.1860     0.7953 0.948 0.000 0.052
#> GSM379782     1  0.7059     0.1327 0.520 0.460 0.020
#> GSM379783     1  0.2537     0.7867 0.920 0.000 0.080
#> GSM379792     1  0.6416     0.2845 0.616 0.008 0.376
#> GSM379793     1  0.4808     0.6825 0.804 0.008 0.188
#> GSM379794     1  0.4808     0.6825 0.804 0.008 0.188
#> GSM379787     1  0.7059     0.1327 0.520 0.460 0.020
#> GSM379788     1  0.2537     0.7867 0.920 0.000 0.080
#> GSM379789     1  0.4629     0.6799 0.808 0.004 0.188
#> GSM379790     1  0.4808     0.6825 0.804 0.008 0.188
#> GSM379791     1  0.4808     0.6825 0.804 0.008 0.188
#> GSM379797     3  0.0747     0.7700 0.016 0.000 0.984
#> GSM379798     1  0.4808     0.6825 0.804 0.008 0.188
#> GSM379795     1  0.4808     0.6825 0.804 0.008 0.188
#> GSM379796     1  0.6416     0.2845 0.616 0.008 0.376
#> GSM379721     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379722     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379723     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379716     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379717     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379718     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379719     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379720     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379729     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379730     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379731     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379724     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379725     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379726     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379727     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379728     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379737     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379738     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379739     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379732     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379733     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379734     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379735     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379736     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379742     1  0.6008     0.3390 0.628 0.372 0.000
#> GSM379743     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379740     1  0.0424     0.8033 0.992 0.008 0.000
#> GSM379741     1  0.6008     0.3390 0.628 0.372 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.1211     0.8752 0.000 0.960 0.040 0.000
#> GSM379833     2  0.1211     0.8752 0.000 0.960 0.040 0.000
#> GSM379834     2  0.1211     0.8752 0.000 0.960 0.040 0.000
#> GSM379827     2  0.6116     0.4300 0.320 0.612 0.068 0.000
#> GSM379828     2  0.6116     0.4300 0.320 0.612 0.068 0.000
#> GSM379829     4  0.5602     0.1024 0.408 0.000 0.024 0.568
#> GSM379830     2  0.6179     0.4227 0.320 0.608 0.072 0.000
#> GSM379831     2  0.6232     0.3954 0.332 0.596 0.072 0.000
#> GSM379840     1  0.9128     0.2279 0.408 0.288 0.084 0.220
#> GSM379841     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379842     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379835     2  0.6708     0.2186 0.392 0.524 0.080 0.004
#> GSM379836     2  0.6708     0.2186 0.392 0.524 0.080 0.004
#> GSM379837     1  0.9128     0.2279 0.408 0.288 0.084 0.220
#> GSM379838     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379839     1  0.9128     0.2279 0.408 0.288 0.084 0.220
#> GSM379848     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379849     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379850     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379843     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379844     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379845     1  0.9128     0.2279 0.408 0.288 0.084 0.220
#> GSM379846     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379847     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379853     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379854     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379851     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379852     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379804     4  0.6882     0.4328 0.328 0.000 0.124 0.548
#> GSM379805     4  0.6852     0.4486 0.320 0.000 0.124 0.556
#> GSM379806     4  0.6867     0.4426 0.324 0.000 0.124 0.552
#> GSM379799     4  0.0469     0.7297 0.012 0.000 0.000 0.988
#> GSM379800     4  0.0469     0.7297 0.012 0.000 0.000 0.988
#> GSM379801     4  0.0469     0.7297 0.012 0.000 0.000 0.988
#> GSM379802     4  0.0469     0.7297 0.012 0.000 0.000 0.988
#> GSM379803     4  0.4606     0.6179 0.264 0.000 0.012 0.724
#> GSM379812     1  0.1833     0.6020 0.944 0.000 0.032 0.024
#> GSM379813     1  0.4356     0.6044 0.804 0.000 0.148 0.048
#> GSM379814     1  0.6330     0.5227 0.656 0.000 0.144 0.200
#> GSM379807     1  0.6364     0.5171 0.652 0.000 0.144 0.204
#> GSM379808     4  0.6867     0.4426 0.324 0.000 0.124 0.552
#> GSM379809     1  0.6330     0.5227 0.656 0.000 0.144 0.200
#> GSM379810     1  0.6330     0.5227 0.656 0.000 0.144 0.200
#> GSM379811     4  0.4422     0.6267 0.256 0.000 0.008 0.736
#> GSM379820     1  0.6440     0.5161 0.644 0.000 0.148 0.208
#> GSM379821     1  0.2131     0.6038 0.932 0.000 0.036 0.032
#> GSM379822     1  0.2131     0.6038 0.932 0.000 0.036 0.032
#> GSM379815     1  0.6364     0.5171 0.652 0.000 0.144 0.204
#> GSM379816     1  0.1833     0.6020 0.944 0.000 0.032 0.024
#> GSM379817     1  0.4985     0.5923 0.768 0.000 0.152 0.080
#> GSM379818     4  0.0188     0.7266 0.004 0.000 0.000 0.996
#> GSM379819     1  0.7093    -0.0440 0.476 0.000 0.128 0.396
#> GSM379825     4  0.0188     0.7266 0.004 0.000 0.000 0.996
#> GSM379826     1  0.6440     0.5161 0.644 0.000 0.148 0.208
#> GSM379823     1  0.2131     0.6038 0.932 0.000 0.036 0.032
#> GSM379824     1  0.2131     0.6038 0.932 0.000 0.036 0.032
#> GSM379749     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379750     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379751     2  0.0817     0.8884 0.000 0.976 0.024 0.000
#> GSM379744     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379745     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379746     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379747     2  0.0817     0.8884 0.000 0.976 0.024 0.000
#> GSM379748     2  0.0817     0.8884 0.000 0.976 0.024 0.000
#> GSM379757     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379758     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379752     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379753     2  0.0817     0.8884 0.000 0.976 0.024 0.000
#> GSM379754     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379755     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379756     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379764     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379765     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379766     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379759     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379760     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379761     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379762     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379763     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379769     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379770     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379767     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379768     2  0.0000     0.9054 0.000 1.000 0.000 0.000
#> GSM379776     3  0.4382     0.6132 0.296 0.000 0.704 0.000
#> GSM379777     1  0.4436     0.5720 0.800 0.000 0.148 0.052
#> GSM379778     2  0.7617     0.0286 0.216 0.452 0.332 0.000
#> GSM379771     3  0.4382     0.6132 0.296 0.000 0.704 0.000
#> GSM379772     3  0.4382     0.6132 0.296 0.000 0.704 0.000
#> GSM379773     3  0.5839     0.5561 0.292 0.060 0.648 0.000
#> GSM379774     3  0.4382     0.6132 0.296 0.000 0.704 0.000
#> GSM379775     3  0.4382     0.6132 0.296 0.000 0.704 0.000
#> GSM379784     1  0.3400     0.5644 0.820 0.000 0.180 0.000
#> GSM379785     3  0.4916     0.4430 0.424 0.000 0.576 0.000
#> GSM379786     1  0.3400     0.5644 0.820 0.000 0.180 0.000
#> GSM379779     3  0.4382     0.6132 0.296 0.000 0.704 0.000
#> GSM379780     3  0.4406     0.6080 0.300 0.000 0.700 0.000
#> GSM379781     3  0.4877     0.4743 0.408 0.000 0.592 0.000
#> GSM379782     2  0.7617     0.0286 0.216 0.452 0.332 0.000
#> GSM379783     1  0.3400     0.5644 0.820 0.000 0.180 0.000
#> GSM379792     3  0.7178     0.3666 0.156 0.000 0.520 0.324
#> GSM379793     3  0.5855     0.6568 0.160 0.000 0.704 0.136
#> GSM379794     3  0.5855     0.6568 0.160 0.000 0.704 0.136
#> GSM379787     2  0.7617     0.0286 0.216 0.452 0.332 0.000
#> GSM379788     1  0.3649     0.5449 0.796 0.000 0.204 0.000
#> GSM379789     3  0.5897     0.6527 0.164 0.000 0.700 0.136
#> GSM379790     3  0.5855     0.6568 0.160 0.000 0.704 0.136
#> GSM379791     3  0.5855     0.6568 0.160 0.000 0.704 0.136
#> GSM379797     4  0.1284     0.7129 0.024 0.000 0.012 0.964
#> GSM379798     3  0.5855     0.6568 0.160 0.000 0.704 0.136
#> GSM379795     3  0.5855     0.6568 0.160 0.000 0.704 0.136
#> GSM379796     3  0.7178     0.3666 0.156 0.000 0.520 0.324
#> GSM379721     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379722     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379723     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379716     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379717     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379718     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379719     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379720     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379729     3  0.1474     0.7752 0.052 0.000 0.948 0.000
#> GSM379730     3  0.1474     0.7752 0.052 0.000 0.948 0.000
#> GSM379731     3  0.1474     0.7752 0.052 0.000 0.948 0.000
#> GSM379724     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379725     3  0.1302     0.7778 0.044 0.000 0.956 0.000
#> GSM379726     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379727     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379728     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379737     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379738     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379739     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379732     3  0.1474     0.7752 0.052 0.000 0.948 0.000
#> GSM379733     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379734     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379735     3  0.1474     0.7752 0.052 0.000 0.948 0.000
#> GSM379736     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379742     3  0.4730     0.2940 0.000 0.364 0.636 0.000
#> GSM379743     3  0.1474     0.7752 0.052 0.000 0.948 0.000
#> GSM379740     3  0.0000     0.7982 0.000 0.000 1.000 0.000
#> GSM379741     3  0.4730     0.2940 0.000 0.364 0.636 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     2  0.3837     0.4952 0.000 0.692 0.000 0.000 0.308
#> GSM379833     2  0.3837     0.4952 0.000 0.692 0.000 0.000 0.308
#> GSM379834     2  0.3837     0.4952 0.000 0.692 0.000 0.000 0.308
#> GSM379827     5  0.3999     0.6431 0.000 0.344 0.000 0.000 0.656
#> GSM379828     5  0.3999     0.6431 0.000 0.344 0.000 0.000 0.656
#> GSM379829     5  0.4288     0.1294 0.004 0.000 0.000 0.384 0.612
#> GSM379830     5  0.3983     0.6497 0.000 0.340 0.000 0.000 0.660
#> GSM379831     5  0.3932     0.6647 0.000 0.328 0.000 0.000 0.672
#> GSM379840     5  0.1728     0.6492 0.004 0.020 0.000 0.036 0.940
#> GSM379841     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379842     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379835     5  0.3689     0.7252 0.004 0.256 0.000 0.000 0.740
#> GSM379836     5  0.3689     0.7252 0.004 0.256 0.000 0.000 0.740
#> GSM379837     5  0.1728     0.6492 0.004 0.020 0.000 0.036 0.940
#> GSM379838     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379839     5  0.1728     0.6492 0.004 0.020 0.000 0.036 0.940
#> GSM379848     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379849     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379850     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379843     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379844     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379845     5  0.1728     0.6492 0.004 0.020 0.000 0.036 0.940
#> GSM379846     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379847     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379853     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379854     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379851     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379852     2  0.1732     0.8496 0.000 0.920 0.000 0.000 0.080
#> GSM379804     4  0.6099     0.4009 0.336 0.000 0.124 0.536 0.004
#> GSM379805     4  0.6075     0.4202 0.328 0.000 0.124 0.544 0.004
#> GSM379806     4  0.6087     0.4128 0.332 0.000 0.124 0.540 0.004
#> GSM379799     4  0.0992     0.7425 0.024 0.000 0.000 0.968 0.008
#> GSM379800     4  0.0992     0.7425 0.024 0.000 0.000 0.968 0.008
#> GSM379801     4  0.0992     0.7425 0.024 0.000 0.000 0.968 0.008
#> GSM379802     4  0.1211     0.7382 0.024 0.000 0.000 0.960 0.016
#> GSM379803     4  0.4088     0.6135 0.276 0.000 0.008 0.712 0.004
#> GSM379812     1  0.0290     0.6868 0.992 0.000 0.000 0.000 0.008
#> GSM379813     1  0.3246     0.6985 0.848 0.000 0.120 0.024 0.008
#> GSM379814     1  0.5365     0.6270 0.688 0.000 0.124 0.180 0.008
#> GSM379807     1  0.5398     0.6218 0.684 0.000 0.124 0.184 0.008
#> GSM379808     4  0.6087     0.4128 0.332 0.000 0.124 0.540 0.004
#> GSM379809     1  0.5365     0.6270 0.688 0.000 0.124 0.180 0.008
#> GSM379810     1  0.5365     0.6270 0.688 0.000 0.124 0.180 0.008
#> GSM379811     4  0.3885     0.6236 0.268 0.000 0.008 0.724 0.000
#> GSM379820     1  0.5312     0.6232 0.684 0.000 0.124 0.188 0.004
#> GSM379821     1  0.0865     0.6858 0.972 0.000 0.000 0.024 0.004
#> GSM379822     1  0.0865     0.6858 0.972 0.000 0.000 0.024 0.004
#> GSM379815     1  0.5398     0.6218 0.684 0.000 0.124 0.184 0.008
#> GSM379816     1  0.0290     0.6868 0.992 0.000 0.000 0.000 0.008
#> GSM379817     1  0.3732     0.6925 0.820 0.000 0.120 0.056 0.004
#> GSM379818     4  0.0510     0.7277 0.000 0.000 0.000 0.984 0.016
#> GSM379819     1  0.6054     0.0917 0.496 0.000 0.124 0.380 0.000
#> GSM379825     4  0.0290     0.7344 0.000 0.000 0.000 0.992 0.008
#> GSM379826     1  0.5312     0.6232 0.684 0.000 0.124 0.188 0.004
#> GSM379823     1  0.0865     0.6858 0.972 0.000 0.000 0.024 0.004
#> GSM379824     1  0.0865     0.6858 0.972 0.000 0.000 0.024 0.004
#> GSM379749     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379750     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379751     2  0.2648     0.7592 0.000 0.848 0.000 0.000 0.152
#> GSM379744     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379745     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379746     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379747     2  0.2648     0.7592 0.000 0.848 0.000 0.000 0.152
#> GSM379748     2  0.2648     0.7592 0.000 0.848 0.000 0.000 0.152
#> GSM379757     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379758     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379752     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379753     2  0.2648     0.7592 0.000 0.848 0.000 0.000 0.152
#> GSM379754     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379755     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379756     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379764     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379765     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379766     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379759     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379760     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379761     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379762     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379763     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379769     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379770     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379767     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379768     2  0.0000     0.8690 0.000 1.000 0.000 0.000 0.000
#> GSM379776     3  0.5557     0.5455 0.260 0.000 0.624 0.000 0.116
#> GSM379777     1  0.4714     0.6371 0.776 0.000 0.120 0.052 0.052
#> GSM379778     2  0.7840    -0.0617 0.172 0.452 0.260 0.000 0.116
#> GSM379771     3  0.5557     0.5455 0.260 0.000 0.624 0.000 0.116
#> GSM379772     3  0.5557     0.5455 0.260 0.000 0.624 0.000 0.116
#> GSM379773     3  0.6765     0.4976 0.256 0.060 0.568 0.000 0.116
#> GSM379774     3  0.5557     0.5455 0.260 0.000 0.624 0.000 0.116
#> GSM379775     3  0.5557     0.5455 0.260 0.000 0.624 0.000 0.116
#> GSM379784     1  0.3888     0.6271 0.796 0.000 0.148 0.000 0.056
#> GSM379785     3  0.5934     0.3485 0.396 0.000 0.496 0.000 0.108
#> GSM379786     1  0.3888     0.6271 0.796 0.000 0.148 0.000 0.056
#> GSM379779     3  0.5557     0.5455 0.260 0.000 0.624 0.000 0.116
#> GSM379780     3  0.5537     0.5429 0.264 0.000 0.624 0.000 0.112
#> GSM379781     3  0.5908     0.3865 0.380 0.000 0.512 0.000 0.108
#> GSM379782     2  0.7840    -0.0617 0.172 0.452 0.260 0.000 0.116
#> GSM379783     1  0.3888     0.6271 0.796 0.000 0.148 0.000 0.056
#> GSM379792     3  0.7513     0.2865 0.144 0.000 0.456 0.316 0.084
#> GSM379793     3  0.6660     0.5826 0.144 0.000 0.624 0.128 0.104
#> GSM379794     3  0.6660     0.5826 0.144 0.000 0.624 0.128 0.104
#> GSM379787     2  0.7840    -0.0617 0.172 0.452 0.260 0.000 0.116
#> GSM379788     1  0.4152     0.6019 0.772 0.000 0.168 0.000 0.060
#> GSM379789     3  0.6651     0.5808 0.148 0.000 0.624 0.128 0.100
#> GSM379790     3  0.6660     0.5826 0.144 0.000 0.624 0.128 0.104
#> GSM379791     3  0.6660     0.5826 0.144 0.000 0.624 0.128 0.104
#> GSM379797     4  0.1668     0.7088 0.028 0.000 0.000 0.940 0.032
#> GSM379798     3  0.6660     0.5826 0.144 0.000 0.624 0.128 0.104
#> GSM379795     3  0.6660     0.5826 0.144 0.000 0.624 0.128 0.104
#> GSM379796     3  0.7513     0.2865 0.144 0.000 0.456 0.316 0.084
#> GSM379721     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379722     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379723     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379716     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379717     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379718     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379719     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379720     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379729     3  0.1270     0.7449 0.052 0.000 0.948 0.000 0.000
#> GSM379730     3  0.1270     0.7449 0.052 0.000 0.948 0.000 0.000
#> GSM379731     3  0.1270     0.7449 0.052 0.000 0.948 0.000 0.000
#> GSM379724     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379725     3  0.1121     0.7478 0.044 0.000 0.956 0.000 0.000
#> GSM379726     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379727     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379728     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379737     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379738     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379739     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379732     3  0.1270     0.7449 0.052 0.000 0.948 0.000 0.000
#> GSM379733     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379734     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379735     3  0.1270     0.7449 0.052 0.000 0.948 0.000 0.000
#> GSM379736     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379742     3  0.4225     0.2632 0.000 0.364 0.632 0.000 0.004
#> GSM379743     3  0.1270     0.7449 0.052 0.000 0.948 0.000 0.000
#> GSM379740     3  0.0000     0.7683 0.000 0.000 1.000 0.000 0.000
#> GSM379741     3  0.4225     0.2632 0.000 0.364 0.632 0.000 0.004

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     2  0.3699     0.4578 0.004 0.660 0.000 0.000 0.336 0.000
#> GSM379833     2  0.3699     0.4578 0.004 0.660 0.000 0.000 0.336 0.000
#> GSM379834     2  0.3699     0.4578 0.004 0.660 0.000 0.000 0.336 0.000
#> GSM379827     5  0.3601     0.6638 0.004 0.312 0.000 0.000 0.684 0.000
#> GSM379828     5  0.3601     0.6638 0.004 0.312 0.000 0.000 0.684 0.000
#> GSM379829     5  0.5046     0.2050 0.144 0.000 0.000 0.224 0.632 0.000
#> GSM379830     5  0.3584     0.6701 0.004 0.308 0.000 0.000 0.688 0.000
#> GSM379831     5  0.3766     0.6787 0.012 0.304 0.000 0.000 0.684 0.000
#> GSM379840     5  0.0622     0.6508 0.008 0.000 0.000 0.012 0.980 0.000
#> GSM379841     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379842     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379835     5  0.2996     0.7365 0.000 0.228 0.000 0.000 0.772 0.000
#> GSM379836     5  0.2996     0.7365 0.000 0.228 0.000 0.000 0.772 0.000
#> GSM379837     5  0.0622     0.6508 0.008 0.000 0.000 0.012 0.980 0.000
#> GSM379838     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379839     5  0.0622     0.6508 0.008 0.000 0.000 0.012 0.980 0.000
#> GSM379848     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379849     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379850     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379843     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379844     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379845     5  0.0622     0.6508 0.008 0.000 0.000 0.012 0.980 0.000
#> GSM379846     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379847     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379853     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379854     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379851     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379852     2  0.1858     0.8421 0.004 0.904 0.000 0.000 0.092 0.000
#> GSM379804     4  0.5887     0.4181 0.064 0.000 0.052 0.532 0.004 0.348
#> GSM379805     4  0.5867     0.4349 0.064 0.000 0.052 0.540 0.004 0.340
#> GSM379806     4  0.5877     0.4297 0.064 0.000 0.052 0.536 0.004 0.344
#> GSM379799     4  0.2911     0.6940 0.144 0.000 0.000 0.832 0.000 0.024
#> GSM379800     4  0.2911     0.6940 0.144 0.000 0.000 0.832 0.000 0.024
#> GSM379801     4  0.2911     0.6940 0.144 0.000 0.000 0.832 0.000 0.024
#> GSM379802     4  0.2058     0.6817 0.048 0.000 0.000 0.916 0.012 0.024
#> GSM379803     4  0.3371     0.5984 0.000 0.000 0.000 0.708 0.000 0.292
#> GSM379812     6  0.0777     0.6361 0.024 0.000 0.000 0.000 0.004 0.972
#> GSM379813     6  0.3065     0.6412 0.060 0.000 0.052 0.020 0.004 0.864
#> GSM379814     6  0.5049     0.5711 0.064 0.000 0.052 0.176 0.004 0.704
#> GSM379807     6  0.5079     0.5656 0.064 0.000 0.052 0.180 0.004 0.700
#> GSM379808     4  0.5877     0.4297 0.064 0.000 0.052 0.536 0.004 0.344
#> GSM379809     6  0.5049     0.5711 0.064 0.000 0.052 0.176 0.004 0.704
#> GSM379810     6  0.5049     0.5711 0.064 0.000 0.052 0.176 0.004 0.704
#> GSM379811     4  0.3309     0.6072 0.000 0.000 0.000 0.720 0.000 0.280
#> GSM379820     6  0.4972     0.5670 0.064 0.000 0.052 0.184 0.000 0.700
#> GSM379821     6  0.1261     0.6341 0.024 0.000 0.000 0.024 0.000 0.952
#> GSM379822     6  0.1261     0.6341 0.024 0.000 0.000 0.024 0.000 0.952
#> GSM379815     6  0.5079     0.5656 0.064 0.000 0.052 0.180 0.004 0.700
#> GSM379816     6  0.0777     0.6361 0.024 0.000 0.000 0.000 0.004 0.972
#> GSM379817     6  0.3494     0.6343 0.060 0.000 0.052 0.052 0.000 0.836
#> GSM379818     4  0.1434     0.6701 0.048 0.000 0.000 0.940 0.012 0.000
#> GSM379819     6  0.5813     0.0474 0.064 0.000 0.052 0.376 0.000 0.508
#> GSM379825     4  0.1007     0.6821 0.044 0.000 0.000 0.956 0.000 0.000
#> GSM379826     6  0.4972     0.5670 0.064 0.000 0.052 0.184 0.000 0.700
#> GSM379823     6  0.1261     0.6341 0.024 0.000 0.000 0.024 0.000 0.952
#> GSM379824     6  0.1261     0.6341 0.024 0.000 0.000 0.024 0.000 0.952
#> GSM379749     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379750     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379751     2  0.2491     0.7486 0.000 0.836 0.000 0.000 0.164 0.000
#> GSM379744     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379745     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379746     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379747     2  0.2491     0.7486 0.000 0.836 0.000 0.000 0.164 0.000
#> GSM379748     2  0.2491     0.7486 0.000 0.836 0.000 0.000 0.164 0.000
#> GSM379757     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379758     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379752     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379753     2  0.2491     0.7486 0.000 0.836 0.000 0.000 0.164 0.000
#> GSM379754     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379755     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379756     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379764     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379765     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379766     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379759     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379760     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379761     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379762     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379763     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379769     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379770     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379767     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379768     2  0.0000     0.8658 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379776     1  0.5394     0.8497 0.632 0.000 0.216 0.000 0.020 0.132
#> GSM379777     6  0.4941     0.4246 0.300 0.000 0.000 0.052 0.020 0.628
#> GSM379778     2  0.5979    -0.1125 0.396 0.452 0.000 0.000 0.020 0.132
#> GSM379771     1  0.5394     0.8497 0.632 0.000 0.216 0.000 0.020 0.132
#> GSM379772     1  0.5394     0.8497 0.632 0.000 0.216 0.000 0.020 0.132
#> GSM379773     1  0.6335     0.7969 0.600 0.060 0.188 0.000 0.020 0.132
#> GSM379774     1  0.5394     0.8497 0.632 0.000 0.216 0.000 0.020 0.132
#> GSM379775     1  0.5394     0.8497 0.632 0.000 0.216 0.000 0.020 0.132
#> GSM379784     6  0.4391     0.3735 0.312 0.000 0.016 0.000 0.020 0.652
#> GSM379785     1  0.5573     0.6975 0.596 0.000 0.128 0.000 0.020 0.256
#> GSM379786     6  0.4391     0.3735 0.312 0.000 0.016 0.000 0.020 0.652
#> GSM379779     1  0.5394     0.8497 0.632 0.000 0.216 0.000 0.020 0.132
#> GSM379780     1  0.5429     0.8466 0.628 0.000 0.216 0.000 0.020 0.136
#> GSM379781     1  0.5627     0.7269 0.596 0.000 0.144 0.000 0.020 0.240
#> GSM379782     2  0.5979    -0.1125 0.396 0.452 0.000 0.000 0.020 0.132
#> GSM379783     6  0.4391     0.3735 0.312 0.000 0.016 0.000 0.020 0.652
#> GSM379792     1  0.5602     0.6715 0.592 0.000 0.212 0.184 0.000 0.012
#> GSM379793     1  0.3259     0.8491 0.772 0.000 0.216 0.000 0.000 0.012
#> GSM379794     1  0.3259     0.8491 0.772 0.000 0.216 0.000 0.000 0.012
#> GSM379787     2  0.5979    -0.1125 0.396 0.452 0.000 0.000 0.020 0.132
#> GSM379788     6  0.4767     0.3068 0.316 0.000 0.036 0.000 0.020 0.628
#> GSM379789     1  0.3348     0.8483 0.768 0.000 0.216 0.000 0.000 0.016
#> GSM379790     1  0.3259     0.8491 0.772 0.000 0.216 0.000 0.000 0.012
#> GSM379791     1  0.3259     0.8491 0.772 0.000 0.216 0.000 0.000 0.012
#> GSM379797     4  0.3287     0.5602 0.220 0.000 0.000 0.768 0.012 0.000
#> GSM379798     1  0.3259     0.8491 0.772 0.000 0.216 0.000 0.000 0.012
#> GSM379795     1  0.3259     0.8491 0.772 0.000 0.216 0.000 0.000 0.012
#> GSM379796     1  0.5602     0.6715 0.592 0.000 0.212 0.184 0.000 0.012
#> GSM379721     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379722     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379723     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379716     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379717     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379718     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379719     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379720     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379729     3  0.1320     0.9062 0.016 0.000 0.948 0.000 0.000 0.036
#> GSM379730     3  0.1320     0.9062 0.016 0.000 0.948 0.000 0.000 0.036
#> GSM379731     3  0.1320     0.9062 0.016 0.000 0.948 0.000 0.000 0.036
#> GSM379724     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379725     3  0.1151     0.9105 0.012 0.000 0.956 0.000 0.000 0.032
#> GSM379726     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379727     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379728     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379737     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379738     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379739     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379732     3  0.1320     0.9062 0.016 0.000 0.948 0.000 0.000 0.036
#> GSM379733     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379734     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379735     3  0.1320     0.9062 0.016 0.000 0.948 0.000 0.000 0.036
#> GSM379736     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379742     3  0.3795     0.3735 0.004 0.364 0.632 0.000 0.000 0.000
#> GSM379743     3  0.1320     0.9062 0.016 0.000 0.948 0.000 0.000 0.036
#> GSM379740     3  0.0000     0.9381 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379741     3  0.3795     0.3735 0.004 0.364 0.632 0.000 0.000 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-CV-hclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-CV-hclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-CV-hclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-CV-hclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-CV-hclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-CV-hclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-CV-hclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-CV-hclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-CV-hclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-CV-hclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-CV-hclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-CV-hclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-CV-hclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-CV-hclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-CV-hclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-CV-hclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-CV-hclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-CV-hclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-CV-hclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-CV-hclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk CV-hclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-CV-hclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-CV-hclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-CV-hclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-CV-hclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-CV-hclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk CV-hclust-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>             n individual(p) time(p) agent(p) k
#> CV:hclust 135      2.42e-23   1.000   1.0000 2
#> CV:hclust 119      8.31e-29   0.991   0.0438 3
#> CV:hclust 114      2.60e-36   0.992   0.0209 4
#> CV:hclust 120      7.66e-43   0.999   0.0214 5
#> CV:hclust 120      6.96e-69   1.000   0.0357 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

CV:kmeans**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["CV", "kmeans"]
# you can also extract it by
# res = res_list["CV:kmeans"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#>   Subgroups are detected by 'kmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk CV-kmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk CV-kmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.973       0.985         0.4832 0.513   0.513
#> 3 3 0.640           0.670       0.568         0.3116 0.860   0.745
#> 4 4 0.630           0.868       0.744         0.1352 0.674   0.374
#> 5 5 0.706           0.847       0.801         0.0794 0.924   0.719
#> 6 6 0.754           0.826       0.794         0.0415 0.989   0.943

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000      0.978 0.000 1.000
#> GSM379833     2  0.0000      0.978 0.000 1.000
#> GSM379834     2  0.0000      0.978 0.000 1.000
#> GSM379827     2  0.0000      0.978 0.000 1.000
#> GSM379828     2  0.0000      0.978 0.000 1.000
#> GSM379829     1  0.0938      0.993 0.988 0.012
#> GSM379830     2  0.0000      0.978 0.000 1.000
#> GSM379831     2  0.0000      0.978 0.000 1.000
#> GSM379840     2  0.0000      0.978 0.000 1.000
#> GSM379841     2  0.0000      0.978 0.000 1.000
#> GSM379842     2  0.0000      0.978 0.000 1.000
#> GSM379835     2  0.0000      0.978 0.000 1.000
#> GSM379836     2  0.0000      0.978 0.000 1.000
#> GSM379837     1  0.7376      0.744 0.792 0.208
#> GSM379838     2  0.0000      0.978 0.000 1.000
#> GSM379839     2  0.1633      0.956 0.024 0.976
#> GSM379848     2  0.0000      0.978 0.000 1.000
#> GSM379849     2  0.0000      0.978 0.000 1.000
#> GSM379850     2  0.0000      0.978 0.000 1.000
#> GSM379843     2  0.0000      0.978 0.000 1.000
#> GSM379844     2  0.0000      0.978 0.000 1.000
#> GSM379845     2  0.0000      0.978 0.000 1.000
#> GSM379846     2  0.0000      0.978 0.000 1.000
#> GSM379847     2  0.0000      0.978 0.000 1.000
#> GSM379853     2  0.0000      0.978 0.000 1.000
#> GSM379854     2  0.0000      0.978 0.000 1.000
#> GSM379851     2  0.0000      0.978 0.000 1.000
#> GSM379852     2  0.0000      0.978 0.000 1.000
#> GSM379804     1  0.0938      0.993 0.988 0.012
#> GSM379805     1  0.0938      0.993 0.988 0.012
#> GSM379806     1  0.0938      0.993 0.988 0.012
#> GSM379799     1  0.0938      0.993 0.988 0.012
#> GSM379800     1  0.0938      0.993 0.988 0.012
#> GSM379801     1  0.0938      0.993 0.988 0.012
#> GSM379802     1  0.0938      0.993 0.988 0.012
#> GSM379803     1  0.0938      0.993 0.988 0.012
#> GSM379812     1  0.0938      0.993 0.988 0.012
#> GSM379813     1  0.0938      0.993 0.988 0.012
#> GSM379814     1  0.0938      0.993 0.988 0.012
#> GSM379807     1  0.0938      0.993 0.988 0.012
#> GSM379808     1  0.0938      0.993 0.988 0.012
#> GSM379809     1  0.0938      0.993 0.988 0.012
#> GSM379810     1  0.0938      0.993 0.988 0.012
#> GSM379811     1  0.0938      0.993 0.988 0.012
#> GSM379820     1  0.0938      0.993 0.988 0.012
#> GSM379821     1  0.0938      0.993 0.988 0.012
#> GSM379822     1  0.0938      0.993 0.988 0.012
#> GSM379815     1  0.0938      0.993 0.988 0.012
#> GSM379816     1  0.0938      0.993 0.988 0.012
#> GSM379817     1  0.0938      0.993 0.988 0.012
#> GSM379818     1  0.0938      0.993 0.988 0.012
#> GSM379819     1  0.0938      0.993 0.988 0.012
#> GSM379825     1  0.0938      0.993 0.988 0.012
#> GSM379826     1  0.0938      0.993 0.988 0.012
#> GSM379823     1  0.0938      0.993 0.988 0.012
#> GSM379824     1  0.0938      0.993 0.988 0.012
#> GSM379749     2  0.0000      0.978 0.000 1.000
#> GSM379750     2  0.0000      0.978 0.000 1.000
#> GSM379751     2  0.0000      0.978 0.000 1.000
#> GSM379744     2  0.0000      0.978 0.000 1.000
#> GSM379745     2  0.0000      0.978 0.000 1.000
#> GSM379746     2  0.0000      0.978 0.000 1.000
#> GSM379747     2  0.0000      0.978 0.000 1.000
#> GSM379748     2  0.0000      0.978 0.000 1.000
#> GSM379757     2  0.0000      0.978 0.000 1.000
#> GSM379758     2  0.0000      0.978 0.000 1.000
#> GSM379752     2  0.0000      0.978 0.000 1.000
#> GSM379753     2  0.0000      0.978 0.000 1.000
#> GSM379754     2  0.0000      0.978 0.000 1.000
#> GSM379755     2  0.0000      0.978 0.000 1.000
#> GSM379756     2  0.0000      0.978 0.000 1.000
#> GSM379764     2  0.0000      0.978 0.000 1.000
#> GSM379765     2  0.0000      0.978 0.000 1.000
#> GSM379766     2  0.0000      0.978 0.000 1.000
#> GSM379759     2  0.0000      0.978 0.000 1.000
#> GSM379760     2  0.0000      0.978 0.000 1.000
#> GSM379761     2  0.0000      0.978 0.000 1.000
#> GSM379762     2  0.0000      0.978 0.000 1.000
#> GSM379763     2  0.0000      0.978 0.000 1.000
#> GSM379769     2  0.0000      0.978 0.000 1.000
#> GSM379770     2  0.0000      0.978 0.000 1.000
#> GSM379767     2  0.0000      0.978 0.000 1.000
#> GSM379768     2  0.0000      0.978 0.000 1.000
#> GSM379776     1  0.0938      0.993 0.988 0.012
#> GSM379777     1  0.0938      0.993 0.988 0.012
#> GSM379778     1  0.0938      0.993 0.988 0.012
#> GSM379771     1  0.0938      0.993 0.988 0.012
#> GSM379772     1  0.0938      0.993 0.988 0.012
#> GSM379773     1  0.0938      0.993 0.988 0.012
#> GSM379774     1  0.0938      0.993 0.988 0.012
#> GSM379775     1  0.0938      0.993 0.988 0.012
#> GSM379784     1  0.0938      0.993 0.988 0.012
#> GSM379785     1  0.0938      0.993 0.988 0.012
#> GSM379786     1  0.0938      0.993 0.988 0.012
#> GSM379779     1  0.0938      0.993 0.988 0.012
#> GSM379780     1  0.0938      0.993 0.988 0.012
#> GSM379781     1  0.0938      0.993 0.988 0.012
#> GSM379782     2  0.9323      0.479 0.348 0.652
#> GSM379783     1  0.0938      0.993 0.988 0.012
#> GSM379792     1  0.0938      0.993 0.988 0.012
#> GSM379793     1  0.0938      0.993 0.988 0.012
#> GSM379794     1  0.0938      0.993 0.988 0.012
#> GSM379787     2  0.9815      0.291 0.420 0.580
#> GSM379788     1  0.0938      0.993 0.988 0.012
#> GSM379789     1  0.0938      0.993 0.988 0.012
#> GSM379790     1  0.0938      0.993 0.988 0.012
#> GSM379791     1  0.0938      0.993 0.988 0.012
#> GSM379797     1  0.0938      0.993 0.988 0.012
#> GSM379798     1  0.0938      0.993 0.988 0.012
#> GSM379795     1  0.0938      0.993 0.988 0.012
#> GSM379796     1  0.0938      0.993 0.988 0.012
#> GSM379721     1  0.0000      0.989 1.000 0.000
#> GSM379722     1  0.0000      0.989 1.000 0.000
#> GSM379723     1  0.0000      0.989 1.000 0.000
#> GSM379716     1  0.0000      0.989 1.000 0.000
#> GSM379717     1  0.0000      0.989 1.000 0.000
#> GSM379718     1  0.0000      0.989 1.000 0.000
#> GSM379719     1  0.0000      0.989 1.000 0.000
#> GSM379720     1  0.0000      0.989 1.000 0.000
#> GSM379729     1  0.0000      0.989 1.000 0.000
#> GSM379730     1  0.0000      0.989 1.000 0.000
#> GSM379731     1  0.0000      0.989 1.000 0.000
#> GSM379724     1  0.0000      0.989 1.000 0.000
#> GSM379725     1  0.0000      0.989 1.000 0.000
#> GSM379726     1  0.0000      0.989 1.000 0.000
#> GSM379727     1  0.0000      0.989 1.000 0.000
#> GSM379728     1  0.0000      0.989 1.000 0.000
#> GSM379737     1  0.0000      0.989 1.000 0.000
#> GSM379738     1  0.0000      0.989 1.000 0.000
#> GSM379739     1  0.0000      0.989 1.000 0.000
#> GSM379732     1  0.0000      0.989 1.000 0.000
#> GSM379733     1  0.0000      0.989 1.000 0.000
#> GSM379734     1  0.0000      0.989 1.000 0.000
#> GSM379735     1  0.0000      0.989 1.000 0.000
#> GSM379736     1  0.0000      0.989 1.000 0.000
#> GSM379742     2  0.7376      0.752 0.208 0.792
#> GSM379743     1  0.0000      0.989 1.000 0.000
#> GSM379740     1  0.0000      0.989 1.000 0.000
#> GSM379741     2  0.7376      0.752 0.208 0.792

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     3   0.630     0.8191 0.000 0.484 0.516
#> GSM379833     3   0.630     0.8191 0.000 0.484 0.516
#> GSM379834     3   0.630     0.8191 0.000 0.484 0.516
#> GSM379827     3   0.630     0.8191 0.000 0.484 0.516
#> GSM379828     3   0.630     0.8191 0.000 0.484 0.516
#> GSM379829     1   0.891     0.5512 0.472 0.404 0.124
#> GSM379830     3   0.630     0.8191 0.000 0.484 0.516
#> GSM379831     3   0.630     0.8191 0.000 0.484 0.516
#> GSM379840     3   0.630     0.8191 0.000 0.484 0.516
#> GSM379841     3   0.628     0.8304 0.000 0.460 0.540
#> GSM379842     3   0.627     0.8359 0.000 0.452 0.548
#> GSM379835     3   0.630     0.8191 0.000 0.484 0.516
#> GSM379836     3   0.630     0.8191 0.000 0.484 0.516
#> GSM379837     2   0.971    -0.0295 0.224 0.420 0.356
#> GSM379838     3   0.628     0.8304 0.000 0.460 0.540
#> GSM379839     2   0.828    -0.0792 0.092 0.564 0.344
#> GSM379848     3   0.626     0.8060 0.000 0.448 0.552
#> GSM379849     3   0.626     0.8060 0.000 0.448 0.552
#> GSM379850     3   0.626     0.8060 0.000 0.448 0.552
#> GSM379843     3   0.627     0.8359 0.000 0.452 0.548
#> GSM379844     3   0.628     0.8304 0.000 0.460 0.540
#> GSM379845     3   0.630     0.8191 0.000 0.484 0.516
#> GSM379846     3   0.628     0.8304 0.000 0.460 0.540
#> GSM379847     3   0.627     0.8146 0.000 0.452 0.548
#> GSM379853     3   0.625     0.8282 0.000 0.444 0.556
#> GSM379854     3   0.626     0.8060 0.000 0.448 0.552
#> GSM379851     3   0.626     0.8060 0.000 0.448 0.552
#> GSM379852     3   0.626     0.8060 0.000 0.448 0.552
#> GSM379804     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379805     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379806     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379799     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379800     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379801     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379802     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379803     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379812     1   0.659     0.6682 0.632 0.352 0.016
#> GSM379813     1   0.659     0.6682 0.632 0.352 0.016
#> GSM379814     1   0.659     0.6682 0.632 0.352 0.016
#> GSM379807     1   0.717     0.6645 0.612 0.352 0.036
#> GSM379808     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379809     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379810     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379811     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379820     1   0.672     0.6680 0.628 0.352 0.020
#> GSM379821     1   0.672     0.6680 0.628 0.352 0.020
#> GSM379822     1   0.613     0.6692 0.644 0.352 0.004
#> GSM379815     1   0.727     0.6635 0.608 0.352 0.040
#> GSM379816     1   0.495     0.7103 0.808 0.176 0.016
#> GSM379817     1   0.672     0.6680 0.628 0.352 0.020
#> GSM379818     1   0.746     0.6641 0.600 0.352 0.048
#> GSM379819     1   0.727     0.6644 0.608 0.352 0.040
#> GSM379825     1   0.755     0.6637 0.596 0.352 0.052
#> GSM379826     1   0.672     0.6680 0.628 0.352 0.020
#> GSM379823     1   0.613     0.6692 0.644 0.352 0.004
#> GSM379824     1   0.672     0.6680 0.628 0.352 0.020
#> GSM379749     2   0.590     0.5442 0.000 0.648 0.352
#> GSM379750     2   0.590     0.5442 0.000 0.648 0.352
#> GSM379751     2   0.599     0.4798 0.000 0.632 0.368
#> GSM379744     2   0.595     0.5161 0.000 0.640 0.360
#> GSM379745     2   0.595     0.5161 0.000 0.640 0.360
#> GSM379746     2   0.590     0.5442 0.000 0.648 0.352
#> GSM379747     2   0.599     0.4798 0.000 0.632 0.368
#> GSM379748     2   0.599     0.4798 0.000 0.632 0.368
#> GSM379757     2   0.613     0.6321 0.000 0.600 0.400
#> GSM379758     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379752     2   0.590     0.5442 0.000 0.648 0.352
#> GSM379753     2   0.599     0.4798 0.000 0.632 0.368
#> GSM379754     2   0.611     0.6261 0.000 0.604 0.396
#> GSM379755     2   0.611     0.6261 0.000 0.604 0.396
#> GSM379756     2   0.611     0.6261 0.000 0.604 0.396
#> GSM379764     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379765     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379766     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379759     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379760     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379761     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379762     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379763     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379769     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379770     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379767     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379768     2   0.614     0.6374 0.000 0.596 0.404
#> GSM379776     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379777     1   0.697     0.6883 0.696 0.244 0.060
#> GSM379778     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379771     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379772     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379773     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379774     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379775     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379784     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379785     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379786     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379779     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379780     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379781     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379782     1   0.733     0.5154 0.692 0.216 0.092
#> GSM379783     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379792     1   0.663     0.6970 0.732 0.204 0.064
#> GSM379793     1   0.216     0.7258 0.936 0.000 0.064
#> GSM379794     1   0.216     0.7258 0.936 0.000 0.064
#> GSM379787     1   0.670     0.5835 0.744 0.164 0.092
#> GSM379788     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379789     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379790     1   0.207     0.7263 0.940 0.000 0.060
#> GSM379791     1   0.216     0.7258 0.936 0.000 0.064
#> GSM379797     1   0.804     0.6575 0.572 0.352 0.076
#> GSM379798     1   0.216     0.7258 0.936 0.000 0.064
#> GSM379795     1   0.216     0.7258 0.936 0.000 0.064
#> GSM379796     1   0.634     0.7018 0.756 0.180 0.064
#> GSM379721     1   0.599     0.6533 0.632 0.000 0.368
#> GSM379722     1   0.597     0.6538 0.636 0.000 0.364
#> GSM379723     1   0.599     0.6533 0.632 0.000 0.368
#> GSM379716     1   0.599     0.6533 0.632 0.000 0.368
#> GSM379717     1   0.599     0.6533 0.632 0.000 0.368
#> GSM379718     1   0.599     0.6533 0.632 0.000 0.368
#> GSM379719     1   0.599     0.6533 0.632 0.000 0.368
#> GSM379720     1   0.599     0.6533 0.632 0.000 0.368
#> GSM379729     1   0.579     0.6542 0.668 0.000 0.332
#> GSM379730     1   0.579     0.6542 0.668 0.000 0.332
#> GSM379731     1   0.579     0.6542 0.668 0.000 0.332
#> GSM379724     1   0.599     0.6533 0.632 0.000 0.368
#> GSM379725     1   0.576     0.6547 0.672 0.000 0.328
#> GSM379726     1   0.599     0.6533 0.632 0.000 0.368
#> GSM379727     1   0.597     0.6538 0.636 0.000 0.364
#> GSM379728     1   0.599     0.6533 0.632 0.000 0.368
#> GSM379737     1   0.579     0.6542 0.668 0.000 0.332
#> GSM379738     1   0.579     0.6542 0.668 0.000 0.332
#> GSM379739     1   0.579     0.6542 0.668 0.000 0.332
#> GSM379732     1   0.579     0.6542 0.668 0.000 0.332
#> GSM379733     1   0.579     0.6542 0.668 0.000 0.332
#> GSM379734     1   0.579     0.6542 0.668 0.000 0.332
#> GSM379735     1   0.579     0.6542 0.668 0.000 0.332
#> GSM379736     1   0.601     0.6524 0.628 0.000 0.372
#> GSM379742     1   0.947     0.3971 0.440 0.184 0.376
#> GSM379743     1   0.581     0.6522 0.664 0.000 0.336
#> GSM379740     1   0.579     0.6542 0.668 0.000 0.332
#> GSM379741     1   0.947     0.3971 0.440 0.184 0.376

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.3205      0.768 0.104 0.872 0.000 0.024
#> GSM379833     2  0.3205      0.768 0.104 0.872 0.000 0.024
#> GSM379834     2  0.3205      0.768 0.104 0.872 0.000 0.024
#> GSM379827     2  0.3840      0.767 0.104 0.844 0.000 0.052
#> GSM379828     2  0.3840      0.767 0.104 0.844 0.000 0.052
#> GSM379829     4  0.6481      0.596 0.112 0.136 0.044 0.708
#> GSM379830     2  0.3840      0.767 0.104 0.844 0.000 0.052
#> GSM379831     2  0.3840      0.767 0.104 0.844 0.000 0.052
#> GSM379840     2  0.3587      0.767 0.104 0.856 0.000 0.040
#> GSM379841     2  0.0188      0.789 0.004 0.996 0.000 0.000
#> GSM379842     2  0.0657      0.786 0.012 0.984 0.000 0.004
#> GSM379835     2  0.3840      0.767 0.104 0.844 0.000 0.052
#> GSM379836     2  0.3840      0.767 0.104 0.844 0.000 0.052
#> GSM379837     2  0.6577      0.507 0.112 0.624 0.004 0.260
#> GSM379838     2  0.0188      0.789 0.004 0.996 0.000 0.000
#> GSM379839     2  0.6377      0.520 0.112 0.632 0.000 0.256
#> GSM379848     2  0.1724      0.786 0.032 0.948 0.000 0.020
#> GSM379849     2  0.1833      0.785 0.032 0.944 0.000 0.024
#> GSM379850     2  0.1833      0.785 0.032 0.944 0.000 0.024
#> GSM379843     2  0.0657      0.786 0.012 0.984 0.000 0.004
#> GSM379844     2  0.0188      0.789 0.004 0.996 0.000 0.000
#> GSM379845     2  0.3587      0.767 0.104 0.856 0.000 0.040
#> GSM379846     2  0.0000      0.788 0.000 1.000 0.000 0.000
#> GSM379847     2  0.1284      0.787 0.024 0.964 0.000 0.012
#> GSM379853     2  0.1624      0.785 0.028 0.952 0.000 0.020
#> GSM379854     2  0.1833      0.785 0.032 0.944 0.000 0.024
#> GSM379851     2  0.1406      0.786 0.024 0.960 0.000 0.016
#> GSM379852     2  0.1833      0.785 0.032 0.944 0.000 0.024
#> GSM379804     4  0.2868      0.951 0.000 0.000 0.136 0.864
#> GSM379805     4  0.3196      0.951 0.008 0.000 0.136 0.856
#> GSM379806     4  0.3196      0.951 0.008 0.000 0.136 0.856
#> GSM379799     4  0.3196      0.951 0.008 0.000 0.136 0.856
#> GSM379800     4  0.3196      0.951 0.008 0.000 0.136 0.856
#> GSM379801     4  0.3196      0.951 0.008 0.000 0.136 0.856
#> GSM379802     4  0.3196      0.951 0.008 0.000 0.136 0.856
#> GSM379803     4  0.3142      0.951 0.008 0.000 0.132 0.860
#> GSM379812     4  0.3428      0.944 0.012 0.000 0.144 0.844
#> GSM379813     4  0.3300      0.946 0.008 0.000 0.144 0.848
#> GSM379814     4  0.3249      0.945 0.008 0.000 0.140 0.852
#> GSM379807     4  0.3088      0.951 0.008 0.000 0.128 0.864
#> GSM379808     4  0.3196      0.951 0.008 0.000 0.136 0.856
#> GSM379809     4  0.2868      0.951 0.000 0.000 0.136 0.864
#> GSM379810     4  0.3052      0.951 0.004 0.000 0.136 0.860
#> GSM379811     4  0.3142      0.951 0.008 0.000 0.132 0.860
#> GSM379820     4  0.3377      0.945 0.012 0.000 0.140 0.848
#> GSM379821     4  0.3495      0.943 0.016 0.000 0.140 0.844
#> GSM379822     4  0.3757      0.929 0.020 0.000 0.152 0.828
#> GSM379815     4  0.2760      0.951 0.000 0.000 0.128 0.872
#> GSM379816     4  0.4434      0.818 0.016 0.000 0.228 0.756
#> GSM379817     4  0.3377      0.945 0.012 0.000 0.140 0.848
#> GSM379818     4  0.3032      0.951 0.008 0.000 0.124 0.868
#> GSM379819     4  0.3161      0.948 0.012 0.000 0.124 0.864
#> GSM379825     4  0.3217      0.950 0.012 0.000 0.128 0.860
#> GSM379826     4  0.3377      0.945 0.012 0.000 0.140 0.848
#> GSM379823     4  0.3757      0.929 0.020 0.000 0.152 0.828
#> GSM379824     4  0.3377      0.945 0.012 0.000 0.140 0.848
#> GSM379749     2  0.5724      0.781 0.424 0.548 0.000 0.028
#> GSM379750     2  0.5724      0.781 0.424 0.548 0.000 0.028
#> GSM379751     2  0.5901      0.777 0.432 0.532 0.000 0.036
#> GSM379744     2  0.5731      0.780 0.428 0.544 0.000 0.028
#> GSM379745     2  0.5731      0.780 0.428 0.544 0.000 0.028
#> GSM379746     2  0.5724      0.781 0.424 0.548 0.000 0.028
#> GSM379747     2  0.5750      0.777 0.440 0.532 0.000 0.028
#> GSM379748     2  0.5750      0.777 0.440 0.532 0.000 0.028
#> GSM379757     2  0.4978      0.783 0.384 0.612 0.000 0.004
#> GSM379758     2  0.5742      0.779 0.368 0.596 0.000 0.036
#> GSM379752     2  0.5724      0.781 0.424 0.548 0.000 0.028
#> GSM379753     2  0.5750      0.777 0.440 0.532 0.000 0.028
#> GSM379754     2  0.4936      0.786 0.372 0.624 0.000 0.004
#> GSM379755     2  0.4936      0.786 0.372 0.624 0.000 0.004
#> GSM379756     2  0.4950      0.785 0.376 0.620 0.000 0.004
#> GSM379764     2  0.5839      0.780 0.352 0.604 0.000 0.044
#> GSM379765     2  0.5839      0.780 0.352 0.604 0.000 0.044
#> GSM379766     2  0.5839      0.780 0.352 0.604 0.000 0.044
#> GSM379759     2  0.5742      0.779 0.368 0.596 0.000 0.036
#> GSM379760     2  0.5742      0.779 0.368 0.596 0.000 0.036
#> GSM379761     2  0.5742      0.779 0.368 0.596 0.000 0.036
#> GSM379762     2  0.5807      0.779 0.364 0.596 0.000 0.040
#> GSM379763     2  0.5839      0.780 0.352 0.604 0.000 0.044
#> GSM379769     2  0.5855      0.778 0.356 0.600 0.000 0.044
#> GSM379770     2  0.5855      0.778 0.356 0.600 0.000 0.044
#> GSM379767     2  0.5839      0.780 0.352 0.604 0.000 0.044
#> GSM379768     2  0.5839      0.780 0.352 0.604 0.000 0.044
#> GSM379776     1  0.7511      0.961 0.468 0.000 0.336 0.196
#> GSM379777     1  0.7518      0.767 0.476 0.000 0.204 0.320
#> GSM379778     1  0.7511      0.961 0.468 0.000 0.336 0.196
#> GSM379771     1  0.7511      0.961 0.468 0.000 0.336 0.196
#> GSM379772     1  0.7511      0.961 0.468 0.000 0.336 0.196
#> GSM379773     1  0.7511      0.961 0.468 0.000 0.336 0.196
#> GSM379774     1  0.7511      0.961 0.468 0.000 0.336 0.196
#> GSM379775     1  0.7511      0.961 0.468 0.000 0.336 0.196
#> GSM379784     1  0.7505      0.955 0.476 0.000 0.324 0.200
#> GSM379785     1  0.7516      0.958 0.472 0.000 0.328 0.200
#> GSM379786     1  0.7505      0.955 0.476 0.000 0.324 0.200
#> GSM379779     1  0.7511      0.961 0.468 0.000 0.336 0.196
#> GSM379780     1  0.7511      0.961 0.468 0.000 0.336 0.196
#> GSM379781     1  0.7511      0.961 0.468 0.000 0.336 0.196
#> GSM379782     1  0.8391      0.825 0.496 0.056 0.284 0.164
#> GSM379783     1  0.7505      0.955 0.476 0.000 0.324 0.200
#> GSM379792     1  0.7636      0.847 0.468 0.000 0.248 0.284
#> GSM379793     1  0.7526      0.961 0.468 0.000 0.332 0.200
#> GSM379794     1  0.7526      0.961 0.468 0.000 0.332 0.200
#> GSM379787     1  0.8406      0.827 0.492 0.056 0.288 0.164
#> GSM379788     1  0.7505      0.955 0.476 0.000 0.324 0.200
#> GSM379789     1  0.7526      0.961 0.468 0.000 0.332 0.200
#> GSM379790     1  0.7526      0.961 0.468 0.000 0.332 0.200
#> GSM379791     1  0.7526      0.961 0.468 0.000 0.332 0.200
#> GSM379797     4  0.5209      0.705 0.140 0.000 0.104 0.756
#> GSM379798     1  0.7526      0.961 0.468 0.000 0.332 0.200
#> GSM379795     1  0.7526      0.961 0.468 0.000 0.332 0.200
#> GSM379796     1  0.7640      0.853 0.468 0.000 0.252 0.280
#> GSM379721     3  0.1256      0.953 0.008 0.000 0.964 0.028
#> GSM379722     3  0.1256      0.953 0.008 0.000 0.964 0.028
#> GSM379723     3  0.1109      0.953 0.004 0.000 0.968 0.028
#> GSM379716     3  0.1109      0.953 0.004 0.000 0.968 0.028
#> GSM379717     3  0.1109      0.953 0.004 0.000 0.968 0.028
#> GSM379718     3  0.1256      0.953 0.008 0.000 0.964 0.028
#> GSM379719     3  0.1256      0.953 0.008 0.000 0.964 0.028
#> GSM379720     3  0.1256      0.953 0.008 0.000 0.964 0.028
#> GSM379729     3  0.0657      0.948 0.012 0.000 0.984 0.004
#> GSM379730     3  0.0657      0.948 0.012 0.000 0.984 0.004
#> GSM379731     3  0.0657      0.948 0.012 0.000 0.984 0.004
#> GSM379724     3  0.1109      0.953 0.004 0.000 0.968 0.028
#> GSM379725     3  0.0779      0.948 0.016 0.000 0.980 0.004
#> GSM379726     3  0.1109      0.953 0.004 0.000 0.968 0.028
#> GSM379727     3  0.1109      0.953 0.004 0.000 0.968 0.028
#> GSM379728     3  0.1109      0.953 0.004 0.000 0.968 0.028
#> GSM379737     3  0.0524      0.947 0.004 0.000 0.988 0.008
#> GSM379738     3  0.0524      0.947 0.004 0.000 0.988 0.008
#> GSM379739     3  0.0524      0.947 0.004 0.000 0.988 0.008
#> GSM379732     3  0.0657      0.948 0.012 0.000 0.984 0.004
#> GSM379733     3  0.0000      0.948 0.000 0.000 1.000 0.000
#> GSM379734     3  0.0188      0.948 0.000 0.000 0.996 0.004
#> GSM379735     3  0.1059      0.943 0.016 0.000 0.972 0.012
#> GSM379736     3  0.1305      0.949 0.004 0.000 0.960 0.036
#> GSM379742     3  0.4277      0.765 0.076 0.028 0.844 0.052
#> GSM379743     3  0.1182      0.942 0.016 0.000 0.968 0.016
#> GSM379740     3  0.0524      0.947 0.004 0.000 0.988 0.008
#> GSM379741     3  0.4277      0.765 0.076 0.028 0.844 0.052

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     5  0.1211      0.765 0.024 0.000 0.000 0.016 0.960
#> GSM379833     5  0.1211      0.765 0.024 0.000 0.000 0.016 0.960
#> GSM379834     5  0.1117      0.765 0.020 0.000 0.000 0.016 0.964
#> GSM379827     5  0.2659      0.747 0.060 0.000 0.000 0.052 0.888
#> GSM379828     5  0.2659      0.747 0.060 0.000 0.000 0.052 0.888
#> GSM379829     4  0.7554      0.525 0.092 0.168 0.004 0.516 0.220
#> GSM379830     5  0.2592      0.750 0.056 0.000 0.000 0.052 0.892
#> GSM379831     5  0.2592      0.750 0.056 0.000 0.000 0.052 0.892
#> GSM379840     5  0.2520      0.752 0.056 0.000 0.000 0.048 0.896
#> GSM379841     5  0.2233      0.760 0.004 0.104 0.000 0.000 0.892
#> GSM379842     5  0.1952      0.768 0.004 0.084 0.000 0.000 0.912
#> GSM379835     5  0.2592      0.750 0.056 0.000 0.000 0.052 0.892
#> GSM379836     5  0.2592      0.750 0.056 0.000 0.000 0.052 0.892
#> GSM379837     5  0.5329      0.583 0.056 0.108 0.000 0.100 0.736
#> GSM379838     5  0.2233      0.760 0.004 0.104 0.000 0.000 0.892
#> GSM379839     5  0.5329      0.583 0.056 0.108 0.000 0.100 0.736
#> GSM379848     5  0.3128      0.711 0.004 0.168 0.000 0.004 0.824
#> GSM379849     5  0.3250      0.707 0.004 0.168 0.000 0.008 0.820
#> GSM379850     5  0.3250      0.707 0.004 0.168 0.000 0.008 0.820
#> GSM379843     5  0.1952      0.768 0.004 0.084 0.000 0.000 0.912
#> GSM379844     5  0.2233      0.760 0.004 0.104 0.000 0.000 0.892
#> GSM379845     5  0.2520      0.752 0.056 0.000 0.000 0.048 0.896
#> GSM379846     5  0.2233      0.760 0.004 0.104 0.000 0.000 0.892
#> GSM379847     5  0.2763      0.732 0.004 0.148 0.000 0.000 0.848
#> GSM379853     5  0.2722      0.749 0.004 0.120 0.000 0.008 0.868
#> GSM379854     5  0.3250      0.707 0.004 0.168 0.000 0.008 0.820
#> GSM379851     5  0.3129      0.720 0.004 0.156 0.000 0.008 0.832
#> GSM379852     5  0.3250      0.707 0.004 0.168 0.000 0.008 0.820
#> GSM379804     4  0.4134      0.892 0.108 0.048 0.032 0.812 0.000
#> GSM379805     4  0.5722      0.876 0.120 0.164 0.032 0.684 0.000
#> GSM379806     4  0.5757      0.876 0.120 0.168 0.032 0.680 0.000
#> GSM379799     4  0.5757      0.876 0.120 0.168 0.032 0.680 0.000
#> GSM379800     4  0.5757      0.876 0.120 0.168 0.032 0.680 0.000
#> GSM379801     4  0.5757      0.876 0.120 0.168 0.032 0.680 0.000
#> GSM379802     4  0.5867      0.874 0.124 0.176 0.032 0.668 0.000
#> GSM379803     4  0.5756      0.875 0.124 0.172 0.028 0.676 0.000
#> GSM379812     4  0.2777      0.882 0.120 0.000 0.016 0.864 0.000
#> GSM379813     4  0.2677      0.884 0.112 0.000 0.016 0.872 0.000
#> GSM379814     4  0.2773      0.884 0.112 0.000 0.020 0.868 0.000
#> GSM379807     4  0.2707      0.888 0.100 0.000 0.024 0.876 0.000
#> GSM379808     4  0.5757      0.876 0.120 0.168 0.032 0.680 0.000
#> GSM379809     4  0.4063      0.892 0.108 0.044 0.032 0.816 0.000
#> GSM379810     4  0.3862      0.892 0.104 0.036 0.032 0.828 0.000
#> GSM379811     4  0.5867      0.874 0.124 0.176 0.032 0.668 0.000
#> GSM379820     4  0.2616      0.885 0.100 0.000 0.020 0.880 0.000
#> GSM379821     4  0.3010      0.881 0.116 0.008 0.016 0.860 0.000
#> GSM379822     4  0.3923      0.847 0.132 0.040 0.016 0.812 0.000
#> GSM379815     4  0.3871      0.892 0.112 0.040 0.024 0.824 0.000
#> GSM379816     4  0.4590      0.823 0.124 0.032 0.064 0.780 0.000
#> GSM379817     4  0.2625      0.882 0.108 0.000 0.016 0.876 0.000
#> GSM379818     4  0.5790      0.875 0.124 0.176 0.028 0.672 0.000
#> GSM379819     4  0.2597      0.887 0.092 0.000 0.024 0.884 0.000
#> GSM379825     4  0.5659      0.875 0.112 0.176 0.028 0.684 0.000
#> GSM379826     4  0.2669      0.884 0.104 0.000 0.020 0.876 0.000
#> GSM379823     4  0.3767      0.848 0.132 0.032 0.016 0.820 0.000
#> GSM379824     4  0.2959      0.882 0.112 0.008 0.016 0.864 0.000
#> GSM379749     2  0.5901      0.780 0.036 0.508 0.004 0.028 0.424
#> GSM379750     2  0.5901      0.780 0.036 0.508 0.004 0.028 0.424
#> GSM379751     5  0.6392     -0.701 0.060 0.436 0.004 0.036 0.464
#> GSM379744     2  0.5920      0.754 0.036 0.484 0.004 0.028 0.448
#> GSM379745     2  0.5920      0.754 0.036 0.484 0.004 0.028 0.448
#> GSM379746     2  0.5901      0.780 0.036 0.508 0.004 0.028 0.424
#> GSM379747     2  0.5925      0.732 0.036 0.468 0.004 0.028 0.464
#> GSM379748     2  0.5925      0.732 0.036 0.468 0.004 0.028 0.464
#> GSM379757     2  0.5426      0.836 0.028 0.620 0.004 0.024 0.324
#> GSM379758     2  0.3774      0.843 0.000 0.704 0.000 0.000 0.296
#> GSM379752     2  0.5901      0.780 0.036 0.508 0.004 0.028 0.424
#> GSM379753     2  0.5925      0.732 0.036 0.468 0.004 0.028 0.464
#> GSM379754     2  0.5547      0.831 0.032 0.604 0.004 0.024 0.336
#> GSM379755     2  0.5547      0.831 0.032 0.604 0.004 0.024 0.336
#> GSM379756     2  0.5517      0.834 0.032 0.612 0.004 0.024 0.328
#> GSM379764     2  0.4201      0.826 0.000 0.664 0.000 0.008 0.328
#> GSM379765     2  0.4201      0.826 0.000 0.664 0.000 0.008 0.328
#> GSM379766     2  0.4201      0.826 0.000 0.664 0.000 0.008 0.328
#> GSM379759     2  0.3774      0.843 0.000 0.704 0.000 0.000 0.296
#> GSM379760     2  0.3774      0.843 0.000 0.704 0.000 0.000 0.296
#> GSM379761     2  0.3774      0.843 0.000 0.704 0.000 0.000 0.296
#> GSM379762     2  0.3774      0.843 0.000 0.704 0.000 0.000 0.296
#> GSM379763     2  0.4201      0.826 0.000 0.664 0.000 0.008 0.328
#> GSM379769     2  0.4201      0.826 0.000 0.664 0.000 0.008 0.328
#> GSM379770     2  0.4201      0.826 0.000 0.664 0.000 0.008 0.328
#> GSM379767     2  0.4201      0.826 0.000 0.664 0.000 0.008 0.328
#> GSM379768     2  0.4201      0.826 0.000 0.664 0.000 0.008 0.328
#> GSM379776     1  0.2690      0.969 0.844 0.000 0.156 0.000 0.000
#> GSM379777     1  0.3383      0.868 0.856 0.012 0.060 0.072 0.000
#> GSM379778     1  0.3396      0.956 0.832 0.028 0.136 0.000 0.004
#> GSM379771     1  0.2690      0.969 0.844 0.000 0.156 0.000 0.000
#> GSM379772     1  0.2690      0.969 0.844 0.000 0.156 0.000 0.000
#> GSM379773     1  0.3055      0.966 0.840 0.016 0.144 0.000 0.000
#> GSM379774     1  0.2690      0.969 0.844 0.000 0.156 0.000 0.000
#> GSM379775     1  0.2690      0.969 0.844 0.000 0.156 0.000 0.000
#> GSM379784     1  0.2865      0.958 0.856 0.004 0.132 0.008 0.000
#> GSM379785     1  0.2818      0.961 0.860 0.004 0.128 0.008 0.000
#> GSM379786     1  0.2865      0.958 0.856 0.004 0.132 0.008 0.000
#> GSM379779     1  0.2690      0.969 0.844 0.000 0.156 0.000 0.000
#> GSM379780     1  0.2848      0.969 0.840 0.004 0.156 0.000 0.000
#> GSM379781     1  0.3001      0.966 0.844 0.004 0.144 0.008 0.000
#> GSM379782     1  0.3708      0.942 0.816 0.044 0.136 0.000 0.004
#> GSM379783     1  0.2865      0.958 0.856 0.004 0.132 0.008 0.000
#> GSM379792     1  0.3653      0.935 0.828 0.012 0.124 0.036 0.000
#> GSM379793     1  0.3123      0.965 0.828 0.012 0.160 0.000 0.000
#> GSM379794     1  0.3123      0.965 0.828 0.012 0.160 0.000 0.000
#> GSM379787     1  0.3678      0.946 0.816 0.040 0.140 0.000 0.004
#> GSM379788     1  0.2865      0.958 0.856 0.004 0.132 0.008 0.000
#> GSM379789     1  0.3039      0.968 0.836 0.012 0.152 0.000 0.000
#> GSM379790     1  0.3039      0.968 0.836 0.012 0.152 0.000 0.000
#> GSM379791     1  0.3039      0.968 0.836 0.012 0.152 0.000 0.000
#> GSM379797     4  0.6831      0.642 0.304 0.160 0.028 0.508 0.000
#> GSM379798     1  0.3123      0.965 0.828 0.012 0.160 0.000 0.000
#> GSM379795     1  0.3123      0.965 0.828 0.012 0.160 0.000 0.000
#> GSM379796     1  0.3584      0.943 0.828 0.012 0.132 0.028 0.000
#> GSM379721     3  0.1095      0.943 0.012 0.008 0.968 0.012 0.000
#> GSM379722     3  0.1095      0.943 0.012 0.008 0.968 0.012 0.000
#> GSM379723     3  0.0807      0.943 0.012 0.000 0.976 0.012 0.000
#> GSM379716     3  0.0807      0.943 0.012 0.000 0.976 0.012 0.000
#> GSM379717     3  0.0807      0.943 0.012 0.000 0.976 0.012 0.000
#> GSM379718     3  0.1095      0.943 0.012 0.008 0.968 0.012 0.000
#> GSM379719     3  0.1095      0.943 0.012 0.008 0.968 0.012 0.000
#> GSM379720     3  0.1095      0.943 0.012 0.008 0.968 0.012 0.000
#> GSM379729     3  0.3052      0.923 0.036 0.072 0.876 0.016 0.000
#> GSM379730     3  0.3130      0.921 0.040 0.072 0.872 0.016 0.000
#> GSM379731     3  0.3130      0.921 0.040 0.072 0.872 0.016 0.000
#> GSM379724     3  0.0807      0.943 0.012 0.000 0.976 0.012 0.000
#> GSM379725     3  0.2967      0.927 0.032 0.060 0.884 0.024 0.000
#> GSM379726     3  0.0807      0.943 0.012 0.000 0.976 0.012 0.000
#> GSM379727     3  0.0807      0.943 0.012 0.000 0.976 0.012 0.000
#> GSM379728     3  0.0807      0.943 0.012 0.000 0.976 0.012 0.000
#> GSM379737     3  0.2321      0.935 0.016 0.044 0.916 0.024 0.000
#> GSM379738     3  0.2321      0.935 0.016 0.044 0.916 0.024 0.000
#> GSM379739     3  0.2321      0.935 0.016 0.044 0.916 0.024 0.000
#> GSM379732     3  0.3093      0.924 0.032 0.080 0.872 0.016 0.000
#> GSM379733     3  0.1356      0.942 0.012 0.028 0.956 0.004 0.000
#> GSM379734     3  0.1356      0.942 0.012 0.028 0.956 0.004 0.000
#> GSM379735     3  0.3589      0.910 0.036 0.084 0.848 0.032 0.000
#> GSM379736     3  0.1503      0.939 0.008 0.020 0.952 0.020 0.000
#> GSM379742     3  0.4282      0.865 0.024 0.148 0.792 0.032 0.004
#> GSM379743     3  0.3669      0.909 0.036 0.084 0.844 0.036 0.000
#> GSM379740     3  0.2228      0.936 0.016 0.044 0.920 0.020 0.000
#> GSM379741     3  0.4282      0.865 0.024 0.148 0.792 0.032 0.004

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5 p6
#> GSM379832     5  0.5253      0.769 0.016 0.168 0.000 0.000 0.652 NA
#> GSM379833     5  0.5253      0.769 0.016 0.168 0.000 0.000 0.652 NA
#> GSM379834     5  0.5283      0.770 0.016 0.168 0.000 0.000 0.648 NA
#> GSM379827     5  0.2632      0.723 0.004 0.164 0.000 0.000 0.832 NA
#> GSM379828     5  0.2632      0.723 0.004 0.164 0.000 0.000 0.832 NA
#> GSM379829     5  0.6004     -0.320 0.000 0.000 0.000 0.236 0.392 NA
#> GSM379830     5  0.2491      0.726 0.000 0.164 0.000 0.000 0.836 NA
#> GSM379831     5  0.2632      0.726 0.004 0.164 0.000 0.000 0.832 NA
#> GSM379840     5  0.2982      0.732 0.004 0.164 0.000 0.000 0.820 NA
#> GSM379841     5  0.6039      0.775 0.012 0.236 0.000 0.000 0.508 NA
#> GSM379842     5  0.5987      0.777 0.012 0.228 0.000 0.000 0.520 NA
#> GSM379835     5  0.2491      0.726 0.000 0.164 0.000 0.000 0.836 NA
#> GSM379836     5  0.2491      0.726 0.000 0.164 0.000 0.000 0.836 NA
#> GSM379837     5  0.3214      0.655 0.000 0.068 0.000 0.008 0.840 NA
#> GSM379838     5  0.6039      0.775 0.012 0.236 0.000 0.000 0.508 NA
#> GSM379839     5  0.3356      0.655 0.004 0.068 0.000 0.008 0.836 NA
#> GSM379848     5  0.6375      0.738 0.012 0.260 0.004 0.000 0.444 NA
#> GSM379849     5  0.6375      0.738 0.012 0.260 0.004 0.000 0.444 NA
#> GSM379850     5  0.6375      0.738 0.012 0.260 0.004 0.000 0.444 NA
#> GSM379843     5  0.5987      0.777 0.012 0.228 0.000 0.000 0.520 NA
#> GSM379844     5  0.6039      0.775 0.012 0.236 0.000 0.000 0.508 NA
#> GSM379845     5  0.2982      0.732 0.004 0.164 0.000 0.000 0.820 NA
#> GSM379846     5  0.6153      0.775 0.012 0.236 0.004 0.000 0.508 NA
#> GSM379847     5  0.6247      0.765 0.012 0.256 0.004 0.000 0.484 NA
#> GSM379853     5  0.6232      0.769 0.012 0.240 0.004 0.000 0.488 NA
#> GSM379854     5  0.6375      0.738 0.012 0.260 0.004 0.000 0.444 NA
#> GSM379851     5  0.6290      0.759 0.012 0.252 0.004 0.000 0.472 NA
#> GSM379852     5  0.6375      0.738 0.012 0.260 0.004 0.000 0.444 NA
#> GSM379804     4  0.2772      0.837 0.004 0.000 0.000 0.816 0.000 NA
#> GSM379805     4  0.3830      0.804 0.000 0.000 0.000 0.620 0.004 NA
#> GSM379806     4  0.3841      0.803 0.000 0.000 0.000 0.616 0.004 NA
#> GSM379799     4  0.3862      0.802 0.000 0.000 0.000 0.608 0.004 NA
#> GSM379800     4  0.3862      0.802 0.000 0.000 0.000 0.608 0.004 NA
#> GSM379801     4  0.3862      0.802 0.000 0.000 0.000 0.608 0.004 NA
#> GSM379802     4  0.3915      0.797 0.004 0.000 0.000 0.584 0.000 NA
#> GSM379803     4  0.4127      0.800 0.008 0.000 0.000 0.588 0.004 NA
#> GSM379812     4  0.0551      0.834 0.008 0.000 0.000 0.984 0.004 NA
#> GSM379813     4  0.0508      0.834 0.012 0.000 0.000 0.984 0.000 NA
#> GSM379814     4  0.0508      0.834 0.012 0.000 0.000 0.984 0.000 NA
#> GSM379807     4  0.0146      0.835 0.004 0.000 0.000 0.996 0.000 NA
#> GSM379808     4  0.3862      0.802 0.000 0.000 0.000 0.608 0.004 NA
#> GSM379809     4  0.2520      0.839 0.004 0.000 0.000 0.844 0.000 NA
#> GSM379810     4  0.2006      0.840 0.004 0.000 0.000 0.892 0.000 NA
#> GSM379811     4  0.3915      0.797 0.004 0.000 0.000 0.584 0.000 NA
#> GSM379820     4  0.0508      0.833 0.012 0.000 0.000 0.984 0.004 NA
#> GSM379821     4  0.1448      0.829 0.012 0.000 0.000 0.948 0.016 NA
#> GSM379822     4  0.1838      0.821 0.012 0.000 0.000 0.928 0.020 NA
#> GSM379815     4  0.2442      0.839 0.004 0.000 0.000 0.852 0.000 NA
#> GSM379816     4  0.1710      0.814 0.008 0.000 0.020 0.940 0.012 NA
#> GSM379817     4  0.0508      0.833 0.012 0.000 0.000 0.984 0.004 NA
#> GSM379818     4  0.3907      0.797 0.004 0.000 0.000 0.588 0.000 NA
#> GSM379819     4  0.0146      0.835 0.004 0.000 0.000 0.996 0.000 NA
#> GSM379825     4  0.3841      0.804 0.004 0.000 0.000 0.616 0.000 NA
#> GSM379826     4  0.0508      0.833 0.012 0.000 0.000 0.984 0.004 NA
#> GSM379823     4  0.1620      0.822 0.012 0.000 0.000 0.940 0.024 NA
#> GSM379824     4  0.1528      0.829 0.012 0.000 0.000 0.944 0.016 NA
#> GSM379749     2  0.1958      0.757 0.004 0.896 0.000 0.000 0.100 NA
#> GSM379750     2  0.1958      0.757 0.004 0.896 0.000 0.000 0.100 NA
#> GSM379751     2  0.2631      0.709 0.008 0.840 0.000 0.000 0.152 NA
#> GSM379744     2  0.2118      0.755 0.008 0.888 0.000 0.000 0.104 NA
#> GSM379745     2  0.2118      0.755 0.008 0.888 0.000 0.000 0.104 NA
#> GSM379746     2  0.1958      0.757 0.004 0.896 0.000 0.000 0.100 NA
#> GSM379747     2  0.2100      0.748 0.004 0.884 0.000 0.000 0.112 NA
#> GSM379748     2  0.2100      0.748 0.004 0.884 0.000 0.000 0.112 NA
#> GSM379757     2  0.0767      0.779 0.004 0.976 0.000 0.000 0.012 NA
#> GSM379758     2  0.4251      0.774 0.092 0.748 0.008 0.000 0.000 NA
#> GSM379752     2  0.2070      0.757 0.008 0.892 0.000 0.000 0.100 NA
#> GSM379753     2  0.2212      0.748 0.008 0.880 0.000 0.000 0.112 NA
#> GSM379754     2  0.0508      0.778 0.004 0.984 0.000 0.000 0.012 NA
#> GSM379755     2  0.0508      0.778 0.004 0.984 0.000 0.000 0.012 NA
#> GSM379756     2  0.0508      0.778 0.004 0.984 0.000 0.000 0.012 NA
#> GSM379764     2  0.4718      0.747 0.088 0.684 0.008 0.000 0.000 NA
#> GSM379765     2  0.4718      0.747 0.088 0.684 0.008 0.000 0.000 NA
#> GSM379766     2  0.4718      0.747 0.088 0.684 0.008 0.000 0.000 NA
#> GSM379759     2  0.4251      0.774 0.092 0.748 0.008 0.000 0.000 NA
#> GSM379760     2  0.4251      0.774 0.092 0.748 0.008 0.000 0.000 NA
#> GSM379761     2  0.4251      0.774 0.092 0.748 0.008 0.000 0.000 NA
#> GSM379762     2  0.4251      0.774 0.092 0.748 0.008 0.000 0.000 NA
#> GSM379763     2  0.4693      0.749 0.088 0.688 0.008 0.000 0.000 NA
#> GSM379769     2  0.4718      0.747 0.088 0.684 0.008 0.000 0.000 NA
#> GSM379770     2  0.4718      0.747 0.088 0.684 0.008 0.000 0.000 NA
#> GSM379767     2  0.4718      0.747 0.088 0.684 0.008 0.000 0.000 NA
#> GSM379768     2  0.4718      0.747 0.088 0.684 0.008 0.000 0.000 NA
#> GSM379776     1  0.3112      0.971 0.840 0.000 0.104 0.052 0.004 NA
#> GSM379777     1  0.4178      0.881 0.796 0.000 0.040 0.108 0.020 NA
#> GSM379778     1  0.4346      0.948 0.788 0.000 0.100 0.052 0.020 NA
#> GSM379771     1  0.2971      0.971 0.844 0.000 0.104 0.052 0.000 NA
#> GSM379772     1  0.2971      0.971 0.844 0.000 0.104 0.052 0.000 NA
#> GSM379773     1  0.3527      0.967 0.828 0.000 0.100 0.052 0.012 NA
#> GSM379774     1  0.2971      0.971 0.844 0.000 0.104 0.052 0.000 NA
#> GSM379775     1  0.2971      0.971 0.844 0.000 0.104 0.052 0.000 NA
#> GSM379784     1  0.3489      0.968 0.828 0.000 0.100 0.056 0.008 NA
#> GSM379785     1  0.3428      0.968 0.832 0.000 0.100 0.052 0.008 NA
#> GSM379786     1  0.3489      0.968 0.828 0.000 0.100 0.056 0.008 NA
#> GSM379779     1  0.2971      0.971 0.844 0.000 0.104 0.052 0.000 NA
#> GSM379780     1  0.3112      0.970 0.840 0.000 0.104 0.052 0.000 NA
#> GSM379781     1  0.3475      0.968 0.828 0.000 0.104 0.052 0.008 NA
#> GSM379782     1  0.4146      0.932 0.800 0.000 0.100 0.032 0.020 NA
#> GSM379783     1  0.3489      0.968 0.828 0.000 0.100 0.056 0.008 NA
#> GSM379792     1  0.4069      0.946 0.804 0.000 0.080 0.076 0.024 NA
#> GSM379793     1  0.4020      0.963 0.804 0.000 0.104 0.052 0.024 NA
#> GSM379794     1  0.4020      0.963 0.804 0.000 0.104 0.052 0.024 NA
#> GSM379787     1  0.4146      0.932 0.800 0.000 0.100 0.032 0.020 NA
#> GSM379788     1  0.3489      0.968 0.828 0.000 0.100 0.056 0.008 NA
#> GSM379789     1  0.3939      0.964 0.808 0.000 0.104 0.052 0.020 NA
#> GSM379790     1  0.4020      0.963 0.804 0.000 0.104 0.052 0.024 NA
#> GSM379791     1  0.3854      0.965 0.812 0.000 0.104 0.052 0.016 NA
#> GSM379797     4  0.6489      0.557 0.204 0.000 0.004 0.440 0.024 NA
#> GSM379798     1  0.4034      0.961 0.804 0.000 0.100 0.056 0.024 NA
#> GSM379795     1  0.3854      0.965 0.812 0.000 0.104 0.052 0.016 NA
#> GSM379796     1  0.4069      0.946 0.804 0.000 0.080 0.076 0.024 NA
#> GSM379721     3  0.2601      0.912 0.016 0.000 0.896 0.012 0.036 NA
#> GSM379722     3  0.2601      0.912 0.016 0.000 0.896 0.012 0.036 NA
#> GSM379723     3  0.2334      0.912 0.008 0.000 0.908 0.012 0.032 NA
#> GSM379716     3  0.2334      0.912 0.008 0.000 0.908 0.012 0.032 NA
#> GSM379717     3  0.2334      0.912 0.008 0.000 0.908 0.012 0.032 NA
#> GSM379718     3  0.2601      0.912 0.016 0.000 0.896 0.012 0.036 NA
#> GSM379719     3  0.2601      0.912 0.016 0.000 0.896 0.012 0.036 NA
#> GSM379720     3  0.2601      0.912 0.016 0.000 0.896 0.012 0.036 NA
#> GSM379729     3  0.2943      0.900 0.024 0.000 0.876 0.008 0.044 NA
#> GSM379730     3  0.2943      0.900 0.024 0.000 0.876 0.008 0.044 NA
#> GSM379731     3  0.2943      0.900 0.024 0.000 0.876 0.008 0.044 NA
#> GSM379724     3  0.2334      0.912 0.008 0.000 0.908 0.012 0.032 NA
#> GSM379725     3  0.3452      0.904 0.028 0.000 0.844 0.008 0.052 NA
#> GSM379726     3  0.2334      0.912 0.008 0.000 0.908 0.012 0.032 NA
#> GSM379727     3  0.2334      0.912 0.008 0.000 0.908 0.012 0.032 NA
#> GSM379728     3  0.2334      0.912 0.008 0.000 0.908 0.012 0.032 NA
#> GSM379737     3  0.2512      0.905 0.008 0.000 0.896 0.008 0.040 NA
#> GSM379738     3  0.2512      0.905 0.008 0.000 0.896 0.008 0.040 NA
#> GSM379739     3  0.2740      0.903 0.012 0.000 0.884 0.008 0.040 NA
#> GSM379732     3  0.2987      0.900 0.020 0.000 0.872 0.008 0.044 NA
#> GSM379733     3  0.1823      0.910 0.004 0.000 0.932 0.008 0.028 NA
#> GSM379734     3  0.1823      0.910 0.004 0.000 0.932 0.008 0.028 NA
#> GSM379735     3  0.3662      0.888 0.024 0.000 0.828 0.008 0.064 NA
#> GSM379736     3  0.2556      0.910 0.000 0.000 0.888 0.012 0.052 NA
#> GSM379742     3  0.5025      0.795 0.076 0.008 0.728 0.000 0.064 NA
#> GSM379743     3  0.3662      0.888 0.024 0.000 0.828 0.008 0.064 NA
#> GSM379740     3  0.2512      0.905 0.008 0.000 0.896 0.008 0.040 NA
#> GSM379741     3  0.5025      0.795 0.076 0.008 0.728 0.000 0.064 NA

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-CV-kmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-CV-kmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-CV-kmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-CV-kmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-CV-kmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-CV-kmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-CV-kmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-CV-kmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-CV-kmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-CV-kmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-CV-kmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-CV-kmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-CV-kmeans-get-signatures-3

get_signatures(res, k = 5)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-kmeans-get-signatures-4

get_signatures(res, k = 6)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-kmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-CV-kmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-CV-kmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-CV-kmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-kmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-kmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk CV-kmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-CV-kmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-CV-kmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-CV-kmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-CV-kmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-CV-kmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk CV-kmeans-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>             n individual(p) time(p) agent(p) k
#> CV:kmeans 137      2.50e-25       1    0.831 2
#> CV:kmeans 131      1.21e-50       1    0.732 3
#> CV:kmeans 139      2.80e-78       1    0.996 4
#> CV:kmeans 138     3.11e-103       1    0.997 5
#> CV:kmeans 138     3.50e-105       1    0.998 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

CV:skmeans*

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["CV", "skmeans"]
# you can also extract it by
# res = res_list["CV:skmeans"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#>   Subgroups are detected by 'skmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 6.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk CV-skmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk CV-skmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.982       0.993         0.4905 0.510   0.510
#> 3 3 1.000           0.982       0.993         0.3161 0.822   0.659
#> 4 4 1.000           0.976       0.982         0.1327 0.910   0.749
#> 5 5 0.977           0.971       0.977         0.1001 0.924   0.719
#> 6 6 0.926           0.880       0.899         0.0281 0.977   0.881

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 6
#> attr(,"optional")
#> [1] 2 3 4 5

There is also optional best \(k\) = 2 3 4 5 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000     0.9922 0.000 1.000
#> GSM379833     2  0.0000     0.9922 0.000 1.000
#> GSM379834     2  0.0000     0.9922 0.000 1.000
#> GSM379827     2  0.0000     0.9922 0.000 1.000
#> GSM379828     2  0.0000     0.9922 0.000 1.000
#> GSM379829     1  0.0376     0.9893 0.996 0.004
#> GSM379830     2  0.0000     0.9922 0.000 1.000
#> GSM379831     2  0.0000     0.9922 0.000 1.000
#> GSM379840     2  0.0000     0.9922 0.000 1.000
#> GSM379841     2  0.0000     0.9922 0.000 1.000
#> GSM379842     2  0.0000     0.9922 0.000 1.000
#> GSM379835     2  0.0000     0.9922 0.000 1.000
#> GSM379836     2  0.0000     0.9922 0.000 1.000
#> GSM379837     2  0.0000     0.9922 0.000 1.000
#> GSM379838     2  0.0000     0.9922 0.000 1.000
#> GSM379839     2  0.0000     0.9922 0.000 1.000
#> GSM379848     2  0.0000     0.9922 0.000 1.000
#> GSM379849     2  0.0000     0.9922 0.000 1.000
#> GSM379850     2  0.0000     0.9922 0.000 1.000
#> GSM379843     2  0.0000     0.9922 0.000 1.000
#> GSM379844     2  0.0000     0.9922 0.000 1.000
#> GSM379845     2  0.0000     0.9922 0.000 1.000
#> GSM379846     2  0.0000     0.9922 0.000 1.000
#> GSM379847     2  0.0000     0.9922 0.000 1.000
#> GSM379853     2  0.0000     0.9922 0.000 1.000
#> GSM379854     2  0.0000     0.9922 0.000 1.000
#> GSM379851     2  0.0000     0.9922 0.000 1.000
#> GSM379852     2  0.0000     0.9922 0.000 1.000
#> GSM379804     1  0.0000     0.9931 1.000 0.000
#> GSM379805     1  0.0000     0.9931 1.000 0.000
#> GSM379806     1  0.0000     0.9931 1.000 0.000
#> GSM379799     1  0.0000     0.9931 1.000 0.000
#> GSM379800     1  0.0000     0.9931 1.000 0.000
#> GSM379801     1  0.0000     0.9931 1.000 0.000
#> GSM379802     1  0.0000     0.9931 1.000 0.000
#> GSM379803     1  0.0000     0.9931 1.000 0.000
#> GSM379812     1  0.0000     0.9931 1.000 0.000
#> GSM379813     1  0.0000     0.9931 1.000 0.000
#> GSM379814     1  0.0000     0.9931 1.000 0.000
#> GSM379807     1  0.0000     0.9931 1.000 0.000
#> GSM379808     1  0.0000     0.9931 1.000 0.000
#> GSM379809     1  0.0000     0.9931 1.000 0.000
#> GSM379810     1  0.0000     0.9931 1.000 0.000
#> GSM379811     1  0.0000     0.9931 1.000 0.000
#> GSM379820     1  0.0000     0.9931 1.000 0.000
#> GSM379821     1  0.0000     0.9931 1.000 0.000
#> GSM379822     1  0.0000     0.9931 1.000 0.000
#> GSM379815     1  0.0000     0.9931 1.000 0.000
#> GSM379816     1  0.3431     0.9260 0.936 0.064
#> GSM379817     1  0.0000     0.9931 1.000 0.000
#> GSM379818     1  0.0000     0.9931 1.000 0.000
#> GSM379819     1  0.0000     0.9931 1.000 0.000
#> GSM379825     1  0.0000     0.9931 1.000 0.000
#> GSM379826     1  0.0000     0.9931 1.000 0.000
#> GSM379823     1  0.0000     0.9931 1.000 0.000
#> GSM379824     1  0.0000     0.9931 1.000 0.000
#> GSM379749     2  0.0000     0.9922 0.000 1.000
#> GSM379750     2  0.0000     0.9922 0.000 1.000
#> GSM379751     2  0.0000     0.9922 0.000 1.000
#> GSM379744     2  0.0000     0.9922 0.000 1.000
#> GSM379745     2  0.0000     0.9922 0.000 1.000
#> GSM379746     2  0.0000     0.9922 0.000 1.000
#> GSM379747     2  0.0000     0.9922 0.000 1.000
#> GSM379748     2  0.0000     0.9922 0.000 1.000
#> GSM379757     2  0.0000     0.9922 0.000 1.000
#> GSM379758     2  0.0000     0.9922 0.000 1.000
#> GSM379752     2  0.0000     0.9922 0.000 1.000
#> GSM379753     2  0.0000     0.9922 0.000 1.000
#> GSM379754     2  0.0000     0.9922 0.000 1.000
#> GSM379755     2  0.0000     0.9922 0.000 1.000
#> GSM379756     2  0.0000     0.9922 0.000 1.000
#> GSM379764     2  0.0000     0.9922 0.000 1.000
#> GSM379765     2  0.0000     0.9922 0.000 1.000
#> GSM379766     2  0.0000     0.9922 0.000 1.000
#> GSM379759     2  0.0000     0.9922 0.000 1.000
#> GSM379760     2  0.0000     0.9922 0.000 1.000
#> GSM379761     2  0.0000     0.9922 0.000 1.000
#> GSM379762     2  0.0000     0.9922 0.000 1.000
#> GSM379763     2  0.0000     0.9922 0.000 1.000
#> GSM379769     2  0.0000     0.9922 0.000 1.000
#> GSM379770     2  0.0000     0.9922 0.000 1.000
#> GSM379767     2  0.0000     0.9922 0.000 1.000
#> GSM379768     2  0.0000     0.9922 0.000 1.000
#> GSM379776     1  0.0000     0.9931 1.000 0.000
#> GSM379777     1  0.0000     0.9931 1.000 0.000
#> GSM379778     1  0.9977     0.0869 0.528 0.472
#> GSM379771     1  0.0000     0.9931 1.000 0.000
#> GSM379772     1  0.0000     0.9931 1.000 0.000
#> GSM379773     1  0.0000     0.9931 1.000 0.000
#> GSM379774     1  0.0000     0.9931 1.000 0.000
#> GSM379775     1  0.0000     0.9931 1.000 0.000
#> GSM379784     1  0.0000     0.9931 1.000 0.000
#> GSM379785     1  0.0000     0.9931 1.000 0.000
#> GSM379786     1  0.0000     0.9931 1.000 0.000
#> GSM379779     1  0.0000     0.9931 1.000 0.000
#> GSM379780     1  0.0000     0.9931 1.000 0.000
#> GSM379781     1  0.0000     0.9931 1.000 0.000
#> GSM379782     2  0.6712     0.7862 0.176 0.824
#> GSM379783     1  0.0376     0.9893 0.996 0.004
#> GSM379792     1  0.0000     0.9931 1.000 0.000
#> GSM379793     1  0.0000     0.9931 1.000 0.000
#> GSM379794     1  0.0000     0.9931 1.000 0.000
#> GSM379787     2  0.8327     0.6433 0.264 0.736
#> GSM379788     1  0.0000     0.9931 1.000 0.000
#> GSM379789     1  0.0000     0.9931 1.000 0.000
#> GSM379790     1  0.0000     0.9931 1.000 0.000
#> GSM379791     1  0.0000     0.9931 1.000 0.000
#> GSM379797     1  0.0000     0.9931 1.000 0.000
#> GSM379798     1  0.0000     0.9931 1.000 0.000
#> GSM379795     1  0.0000     0.9931 1.000 0.000
#> GSM379796     1  0.0000     0.9931 1.000 0.000
#> GSM379721     1  0.0000     0.9931 1.000 0.000
#> GSM379722     1  0.0000     0.9931 1.000 0.000
#> GSM379723     1  0.0000     0.9931 1.000 0.000
#> GSM379716     1  0.0000     0.9931 1.000 0.000
#> GSM379717     1  0.0000     0.9931 1.000 0.000
#> GSM379718     1  0.0000     0.9931 1.000 0.000
#> GSM379719     1  0.0000     0.9931 1.000 0.000
#> GSM379720     1  0.0000     0.9931 1.000 0.000
#> GSM379729     1  0.0000     0.9931 1.000 0.000
#> GSM379730     1  0.0000     0.9931 1.000 0.000
#> GSM379731     1  0.0000     0.9931 1.000 0.000
#> GSM379724     1  0.0000     0.9931 1.000 0.000
#> GSM379725     1  0.0000     0.9931 1.000 0.000
#> GSM379726     1  0.0000     0.9931 1.000 0.000
#> GSM379727     1  0.0000     0.9931 1.000 0.000
#> GSM379728     1  0.0000     0.9931 1.000 0.000
#> GSM379737     1  0.0000     0.9931 1.000 0.000
#> GSM379738     1  0.0000     0.9931 1.000 0.000
#> GSM379739     1  0.0000     0.9931 1.000 0.000
#> GSM379732     1  0.0000     0.9931 1.000 0.000
#> GSM379733     1  0.0000     0.9931 1.000 0.000
#> GSM379734     1  0.0000     0.9931 1.000 0.000
#> GSM379735     1  0.0000     0.9931 1.000 0.000
#> GSM379736     1  0.0000     0.9931 1.000 0.000
#> GSM379742     2  0.0000     0.9922 0.000 1.000
#> GSM379743     1  0.0000     0.9931 1.000 0.000
#> GSM379740     1  0.0000     0.9931 1.000 0.000
#> GSM379741     2  0.0000     0.9922 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379833     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379834     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379827     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379828     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379829     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379830     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379831     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379840     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379841     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379842     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379835     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379836     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379837     2  0.0237     0.9890 0.004 0.996 0.000
#> GSM379838     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379839     2  0.0237     0.9890 0.004 0.996 0.000
#> GSM379848     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379849     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379850     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379843     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379844     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379845     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379846     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379847     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379853     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379854     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379851     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379852     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379804     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379805     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379806     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379799     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379800     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379801     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379802     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379803     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379812     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379813     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379814     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379807     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379808     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379809     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379810     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379811     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379820     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379821     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379822     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379815     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379816     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379817     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379818     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379819     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379825     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379826     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379823     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379824     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379749     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379750     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379751     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379744     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379745     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379746     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379747     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379748     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379757     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379758     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379752     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379753     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379754     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379755     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379756     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379764     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379765     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379766     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379759     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379760     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379761     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379762     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379763     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379769     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379770     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379767     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379768     2  0.0000     0.9928 0.000 1.000 0.000
#> GSM379776     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379777     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379778     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379771     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379772     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379773     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379774     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379775     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379784     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379785     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379786     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379779     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379780     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379781     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379782     2  0.5982     0.4969 0.328 0.668 0.004
#> GSM379783     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379792     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379793     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379794     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379787     1  0.6521     0.0127 0.504 0.492 0.004
#> GSM379788     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379789     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379790     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379791     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379797     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379798     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379795     1  0.0237     0.9872 0.996 0.000 0.004
#> GSM379796     1  0.0000     0.9880 1.000 0.000 0.000
#> GSM379721     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379722     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379723     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379716     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379717     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379718     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379719     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379720     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379729     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379730     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379731     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379724     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379725     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379726     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379727     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379728     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379737     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379738     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379739     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379732     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379733     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379734     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379735     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379736     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379742     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379743     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379740     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379741     3  0.0000     1.0000 0.000 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2 p3    p4
#> GSM379832     2  0.0188      0.976 0.004 0.996  0 0.000
#> GSM379833     2  0.0188      0.976 0.004 0.996  0 0.000
#> GSM379834     2  0.0188      0.976 0.004 0.996  0 0.000
#> GSM379827     2  0.0188      0.976 0.004 0.996  0 0.000
#> GSM379828     2  0.0188      0.976 0.004 0.996  0 0.000
#> GSM379829     4  0.1004      0.955 0.004 0.024  0 0.972
#> GSM379830     2  0.0188      0.976 0.004 0.996  0 0.000
#> GSM379831     2  0.0188      0.976 0.004 0.996  0 0.000
#> GSM379840     2  0.0188      0.976 0.004 0.996  0 0.000
#> GSM379841     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379842     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379835     2  0.0188      0.976 0.004 0.996  0 0.000
#> GSM379836     2  0.0188      0.976 0.004 0.996  0 0.000
#> GSM379837     2  0.4950      0.392 0.004 0.620  0 0.376
#> GSM379838     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379839     2  0.4343      0.634 0.004 0.732  0 0.264
#> GSM379848     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379849     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379850     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379843     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379844     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379845     2  0.0188      0.976 0.004 0.996  0 0.000
#> GSM379846     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379847     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379853     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379854     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379851     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379852     2  0.0000      0.976 0.000 1.000  0 0.000
#> GSM379804     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379805     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379806     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379799     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379800     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379801     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379802     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379803     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379812     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379813     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379814     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379807     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379808     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379809     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379810     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379811     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379820     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379821     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379822     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379815     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379816     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379817     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379818     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379819     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379825     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379826     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379823     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379824     4  0.0000      0.987 0.000 0.000  0 1.000
#> GSM379749     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379750     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379751     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379744     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379745     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379746     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379747     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379748     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379757     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379758     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379752     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379753     2  0.0921      0.977 0.028 0.972  0 0.000
#> GSM379754     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379755     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379756     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379764     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379765     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379766     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379759     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379760     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379761     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379762     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379763     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379769     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379770     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379767     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379768     2  0.0817      0.977 0.024 0.976  0 0.000
#> GSM379776     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379777     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379778     1  0.1004      0.993 0.972 0.004  0 0.024
#> GSM379771     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379772     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379773     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379774     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379775     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379784     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379785     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379786     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379779     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379780     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379781     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379782     1  0.0376      0.972 0.992 0.004  0 0.004
#> GSM379783     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379792     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379793     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379794     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379787     1  0.0524      0.976 0.988 0.004  0 0.008
#> GSM379788     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379789     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379790     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379791     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379797     4  0.4643      0.455 0.344 0.000  0 0.656
#> GSM379798     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379795     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379796     1  0.0921      0.998 0.972 0.000  0 0.028
#> GSM379721     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379722     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379723     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379716     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379717     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379718     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379719     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379720     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379729     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379730     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379731     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379724     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379725     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379726     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379727     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379728     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379737     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379738     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379739     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379732     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379733     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379734     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379735     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379736     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379742     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379743     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379740     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379741     3  0.0000      1.000 0.000 0.000  1 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2 p3    p4    p5
#> GSM379832     5  0.0609      0.951 0.000 0.020  0 0.000 0.980
#> GSM379833     5  0.0609      0.951 0.000 0.020  0 0.000 0.980
#> GSM379834     5  0.0609      0.951 0.000 0.020  0 0.000 0.980
#> GSM379827     5  0.0609      0.951 0.000 0.020  0 0.000 0.980
#> GSM379828     5  0.0609      0.951 0.000 0.020  0 0.000 0.980
#> GSM379829     4  0.3913      0.569 0.000 0.000  0 0.676 0.324
#> GSM379830     5  0.0609      0.951 0.000 0.020  0 0.000 0.980
#> GSM379831     5  0.0609      0.951 0.000 0.020  0 0.000 0.980
#> GSM379840     5  0.0404      0.946 0.000 0.012  0 0.000 0.988
#> GSM379841     5  0.2179      0.949 0.000 0.112  0 0.000 0.888
#> GSM379842     5  0.1908      0.952 0.000 0.092  0 0.000 0.908
#> GSM379835     5  0.0609      0.951 0.000 0.020  0 0.000 0.980
#> GSM379836     5  0.0609      0.951 0.000 0.020  0 0.000 0.980
#> GSM379837     5  0.0290      0.937 0.000 0.000  0 0.008 0.992
#> GSM379838     5  0.2179      0.949 0.000 0.112  0 0.000 0.888
#> GSM379839     5  0.0290      0.937 0.000 0.000  0 0.008 0.992
#> GSM379848     5  0.2179      0.949 0.000 0.112  0 0.000 0.888
#> GSM379849     5  0.2179      0.949 0.000 0.112  0 0.000 0.888
#> GSM379850     5  0.2179      0.949 0.000 0.112  0 0.000 0.888
#> GSM379843     5  0.1965      0.952 0.000 0.096  0 0.000 0.904
#> GSM379844     5  0.2127      0.950 0.000 0.108  0 0.000 0.892
#> GSM379845     5  0.0609      0.951 0.000 0.020  0 0.000 0.980
#> GSM379846     5  0.2127      0.950 0.000 0.108  0 0.000 0.892
#> GSM379847     5  0.2179      0.949 0.000 0.112  0 0.000 0.888
#> GSM379853     5  0.1908      0.952 0.000 0.092  0 0.000 0.908
#> GSM379854     5  0.2179      0.949 0.000 0.112  0 0.000 0.888
#> GSM379851     5  0.2127      0.950 0.000 0.108  0 0.000 0.892
#> GSM379852     5  0.2179      0.949 0.000 0.112  0 0.000 0.888
#> GSM379804     4  0.0162      0.970 0.000 0.000  0 0.996 0.004
#> GSM379805     4  0.0404      0.970 0.000 0.000  0 0.988 0.012
#> GSM379806     4  0.0404      0.970 0.000 0.000  0 0.988 0.012
#> GSM379799     4  0.0404      0.970 0.000 0.000  0 0.988 0.012
#> GSM379800     4  0.0404      0.970 0.000 0.000  0 0.988 0.012
#> GSM379801     4  0.0404      0.970 0.000 0.000  0 0.988 0.012
#> GSM379802     4  0.0404      0.970 0.000 0.000  0 0.988 0.012
#> GSM379803     4  0.0404      0.970 0.000 0.000  0 0.988 0.012
#> GSM379812     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379813     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379814     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379807     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379808     4  0.0404      0.970 0.000 0.000  0 0.988 0.012
#> GSM379809     4  0.0404      0.970 0.000 0.000  0 0.988 0.012
#> GSM379810     4  0.0000      0.970 0.000 0.000  0 1.000 0.000
#> GSM379811     4  0.0404      0.970 0.000 0.000  0 0.988 0.012
#> GSM379820     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379821     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379822     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379815     4  0.0000      0.970 0.000 0.000  0 1.000 0.000
#> GSM379816     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379817     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379818     4  0.0404      0.970 0.000 0.000  0 0.988 0.012
#> GSM379819     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379825     4  0.0404      0.970 0.000 0.000  0 0.988 0.012
#> GSM379826     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379823     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379824     4  0.0290      0.970 0.000 0.000  0 0.992 0.008
#> GSM379749     2  0.1043      0.964 0.000 0.960  0 0.000 0.040
#> GSM379750     2  0.1043      0.964 0.000 0.960  0 0.000 0.040
#> GSM379751     2  0.1908      0.923 0.000 0.908  0 0.000 0.092
#> GSM379744     2  0.1197      0.959 0.000 0.952  0 0.000 0.048
#> GSM379745     2  0.1197      0.959 0.000 0.952  0 0.000 0.048
#> GSM379746     2  0.1043      0.964 0.000 0.960  0 0.000 0.040
#> GSM379747     2  0.1608      0.941 0.000 0.928  0 0.000 0.072
#> GSM379748     2  0.1608      0.941 0.000 0.928  0 0.000 0.072
#> GSM379757     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379758     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379752     2  0.1043      0.964 0.000 0.960  0 0.000 0.040
#> GSM379753     2  0.1544      0.944 0.000 0.932  0 0.000 0.068
#> GSM379754     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379755     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379756     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379764     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379765     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379766     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379759     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379760     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379761     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379762     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379763     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379769     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379770     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379767     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379768     2  0.0000      0.977 0.000 1.000  0 0.000 0.000
#> GSM379776     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379777     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379778     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379771     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379772     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379773     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379774     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379775     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379784     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379785     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379786     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379779     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379780     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379781     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379782     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379783     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379792     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379793     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379794     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379787     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379788     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379789     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379790     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379791     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379797     4  0.4387      0.467 0.348 0.000  0 0.640 0.012
#> GSM379798     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379795     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379796     1  0.0000      1.000 1.000 0.000  0 0.000 0.000
#> GSM379721     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379722     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379723     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379716     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379717     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379718     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379719     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379720     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379729     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379730     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379731     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379724     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379725     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379726     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379727     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379728     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379737     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379738     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379739     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379732     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379733     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379734     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379735     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379736     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379742     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379743     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379740     3  0.0000      1.000 0.000 0.000  1 0.000 0.000
#> GSM379741     3  0.0000      1.000 0.000 0.000  1 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     5  0.3774     -0.524 0.000 0.000 0.000 0.000 0.592 0.408
#> GSM379833     5  0.3774     -0.524 0.000 0.000 0.000 0.000 0.592 0.408
#> GSM379834     5  0.3789     -0.549 0.000 0.000 0.000 0.000 0.584 0.416
#> GSM379827     5  0.0508      0.745 0.000 0.012 0.000 0.000 0.984 0.004
#> GSM379828     5  0.0405      0.750 0.000 0.008 0.000 0.000 0.988 0.004
#> GSM379829     5  0.3684      0.362 0.000 0.000 0.000 0.332 0.664 0.004
#> GSM379830     5  0.0000      0.758 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379831     5  0.0000      0.758 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379840     5  0.0000      0.758 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379841     6  0.4250      0.891 0.000 0.016 0.000 0.000 0.456 0.528
#> GSM379842     6  0.4086      0.876 0.000 0.008 0.000 0.000 0.464 0.528
#> GSM379835     5  0.0000      0.758 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379836     5  0.0000      0.758 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379837     5  0.0260      0.754 0.000 0.000 0.000 0.008 0.992 0.000
#> GSM379838     6  0.4250      0.891 0.000 0.016 0.000 0.000 0.456 0.528
#> GSM379839     5  0.0260      0.754 0.000 0.000 0.000 0.008 0.992 0.000
#> GSM379848     6  0.4131      0.918 0.000 0.016 0.000 0.000 0.384 0.600
#> GSM379849     6  0.4131      0.918 0.000 0.016 0.000 0.000 0.384 0.600
#> GSM379850     6  0.4131      0.918 0.000 0.016 0.000 0.000 0.384 0.600
#> GSM379843     6  0.4086      0.876 0.000 0.008 0.000 0.000 0.464 0.528
#> GSM379844     6  0.4250      0.891 0.000 0.016 0.000 0.000 0.456 0.528
#> GSM379845     5  0.0000      0.758 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379846     6  0.4250      0.891 0.000 0.016 0.000 0.000 0.456 0.528
#> GSM379847     6  0.4150      0.919 0.000 0.016 0.000 0.000 0.392 0.592
#> GSM379853     6  0.3993      0.915 0.000 0.008 0.000 0.000 0.400 0.592
#> GSM379854     6  0.4131      0.918 0.000 0.016 0.000 0.000 0.384 0.600
#> GSM379851     6  0.4131      0.918 0.000 0.016 0.000 0.000 0.384 0.600
#> GSM379852     6  0.4131      0.918 0.000 0.016 0.000 0.000 0.384 0.600
#> GSM379804     4  0.0000      0.897 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379805     4  0.0000      0.897 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379806     4  0.0000      0.897 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379799     4  0.0000      0.897 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379800     4  0.0000      0.897 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379801     4  0.0000      0.897 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379802     4  0.0000      0.897 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379803     4  0.0000      0.897 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379812     4  0.2941      0.880 0.000 0.000 0.000 0.780 0.000 0.220
#> GSM379813     4  0.2883      0.882 0.000 0.000 0.000 0.788 0.000 0.212
#> GSM379814     4  0.2854      0.883 0.000 0.000 0.000 0.792 0.000 0.208
#> GSM379807     4  0.2854      0.883 0.000 0.000 0.000 0.792 0.000 0.208
#> GSM379808     4  0.0000      0.897 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379809     4  0.0000      0.897 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379810     4  0.0260      0.898 0.000 0.000 0.000 0.992 0.000 0.008
#> GSM379811     4  0.0000      0.897 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379820     4  0.2854      0.883 0.000 0.000 0.000 0.792 0.000 0.208
#> GSM379821     4  0.2941      0.880 0.000 0.000 0.000 0.780 0.000 0.220
#> GSM379822     4  0.2941      0.880 0.000 0.000 0.000 0.780 0.000 0.220
#> GSM379815     4  0.0260      0.898 0.000 0.000 0.000 0.992 0.000 0.008
#> GSM379816     4  0.2941      0.880 0.000 0.000 0.000 0.780 0.000 0.220
#> GSM379817     4  0.2883      0.882 0.000 0.000 0.000 0.788 0.000 0.212
#> GSM379818     4  0.0000      0.897 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379819     4  0.2854      0.883 0.000 0.000 0.000 0.792 0.000 0.208
#> GSM379825     4  0.0632      0.897 0.000 0.000 0.000 0.976 0.000 0.024
#> GSM379826     4  0.2854      0.883 0.000 0.000 0.000 0.792 0.000 0.208
#> GSM379823     4  0.2941      0.880 0.000 0.000 0.000 0.780 0.000 0.220
#> GSM379824     4  0.2941      0.880 0.000 0.000 0.000 0.780 0.000 0.220
#> GSM379749     2  0.0146      0.894 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM379750     2  0.0146      0.894 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM379751     2  0.2053      0.815 0.000 0.888 0.000 0.000 0.108 0.004
#> GSM379744     2  0.0405      0.891 0.000 0.988 0.000 0.000 0.008 0.004
#> GSM379745     2  0.0405      0.891 0.000 0.988 0.000 0.000 0.008 0.004
#> GSM379746     2  0.0146      0.894 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM379747     2  0.0405      0.891 0.000 0.988 0.000 0.000 0.008 0.004
#> GSM379748     2  0.0405      0.891 0.000 0.988 0.000 0.000 0.008 0.004
#> GSM379757     2  0.0363      0.895 0.000 0.988 0.000 0.000 0.000 0.012
#> GSM379758     2  0.2378      0.883 0.000 0.848 0.000 0.000 0.000 0.152
#> GSM379752     2  0.0146      0.894 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM379753     2  0.0405      0.891 0.000 0.988 0.000 0.000 0.008 0.004
#> GSM379754     2  0.0000      0.895 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379755     2  0.0000      0.895 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379756     2  0.0000      0.895 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379764     2  0.3309      0.835 0.000 0.720 0.000 0.000 0.000 0.280
#> GSM379765     2  0.3309      0.835 0.000 0.720 0.000 0.000 0.000 0.280
#> GSM379766     2  0.3309      0.835 0.000 0.720 0.000 0.000 0.000 0.280
#> GSM379759     2  0.2300      0.884 0.000 0.856 0.000 0.000 0.000 0.144
#> GSM379760     2  0.2300      0.884 0.000 0.856 0.000 0.000 0.000 0.144
#> GSM379761     2  0.2378      0.883 0.000 0.848 0.000 0.000 0.000 0.152
#> GSM379762     2  0.2378      0.883 0.000 0.848 0.000 0.000 0.000 0.152
#> GSM379763     2  0.3309      0.835 0.000 0.720 0.000 0.000 0.000 0.280
#> GSM379769     2  0.3309      0.835 0.000 0.720 0.000 0.000 0.000 0.280
#> GSM379770     2  0.3309      0.835 0.000 0.720 0.000 0.000 0.000 0.280
#> GSM379767     2  0.3309      0.835 0.000 0.720 0.000 0.000 0.000 0.280
#> GSM379768     2  0.3309      0.835 0.000 0.720 0.000 0.000 0.000 0.280
#> GSM379776     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379777     1  0.0363      0.991 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379778     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379771     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379772     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379773     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379774     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379775     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379784     1  0.0260      0.993 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM379785     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379786     1  0.0363      0.991 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379779     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379780     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379781     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379782     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379783     1  0.0363      0.991 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379792     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379793     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379794     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379787     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379788     1  0.0260      0.993 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM379789     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379790     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379791     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379797     4  0.3464      0.530 0.312 0.000 0.000 0.688 0.000 0.000
#> GSM379798     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379796     1  0.0000      0.998 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379721     3  0.0000      0.985 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379722     3  0.0000      0.985 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379723     3  0.0000      0.985 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379716     3  0.0000      0.985 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379717     3  0.0000      0.985 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379718     3  0.0000      0.985 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379719     3  0.0000      0.985 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379720     3  0.0000      0.985 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379729     3  0.0865      0.977 0.000 0.000 0.964 0.000 0.000 0.036
#> GSM379730     3  0.0865      0.977 0.000 0.000 0.964 0.000 0.000 0.036
#> GSM379731     3  0.0865      0.977 0.000 0.000 0.964 0.000 0.000 0.036
#> GSM379724     3  0.0000      0.985 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379725     3  0.0632      0.980 0.000 0.000 0.976 0.000 0.000 0.024
#> GSM379726     3  0.0000      0.985 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379727     3  0.0000      0.985 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379728     3  0.0000      0.985 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379737     3  0.0458      0.983 0.000 0.000 0.984 0.000 0.000 0.016
#> GSM379738     3  0.0458      0.983 0.000 0.000 0.984 0.000 0.000 0.016
#> GSM379739     3  0.0547      0.983 0.000 0.000 0.980 0.000 0.000 0.020
#> GSM379732     3  0.0865      0.977 0.000 0.000 0.964 0.000 0.000 0.036
#> GSM379733     3  0.0146      0.985 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM379734     3  0.0146      0.985 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM379735     3  0.0937      0.976 0.000 0.000 0.960 0.000 0.000 0.040
#> GSM379736     3  0.0146      0.985 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM379742     3  0.1814      0.929 0.000 0.000 0.900 0.000 0.000 0.100
#> GSM379743     3  0.0937      0.976 0.000 0.000 0.960 0.000 0.000 0.040
#> GSM379740     3  0.0458      0.983 0.000 0.000 0.984 0.000 0.000 0.016
#> GSM379741     3  0.1814      0.929 0.000 0.000 0.900 0.000 0.000 0.100

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-CV-skmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-CV-skmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-CV-skmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-CV-skmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-CV-skmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-CV-skmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-CV-skmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-CV-skmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-CV-skmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-CV-skmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-skmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-CV-skmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-CV-skmeans-get-signatures-3

get_signatures(res, k = 5)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-skmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-CV-skmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-skmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-CV-skmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-CV-skmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-skmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-CV-skmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk CV-skmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-CV-skmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-CV-skmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-CV-skmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-CV-skmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-CV-skmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk CV-skmeans-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>              n individual(p) time(p) agent(p) k
#> CV:skmeans 138      9.55e-25       1    0.733 2
#> CV:skmeans 137      1.49e-53       1    0.934 3
#> CV:skmeans 137      5.48e-79       1    0.995 4
#> CV:skmeans 138     3.50e-105       1    0.996 5
#> CV:skmeans 135      1.08e-99       1    0.277 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

CV:pam**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["CV", "pam"]
# you can also extract it by
# res = res_list["CV:pam"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#>   Subgroups are detected by 'pam' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 6.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk CV-pam-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk CV-pam-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2  1.00           0.987       0.994         0.4894 0.513   0.513
#> 3 3  1.00           0.983       0.994         0.3219 0.831   0.674
#> 4 4  0.84           0.901       0.882         0.1261 0.910   0.748
#> 5 5  1.00           0.977       0.990         0.1057 0.913   0.683
#> 6 6  0.96           0.939       0.941         0.0277 0.970   0.849

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 6
#> attr(,"optional")
#> [1] 2 3 5

There is also optional best \(k\) = 2 3 5 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2   0.000      0.999 0.000 1.000
#> GSM379833     2   0.000      0.999 0.000 1.000
#> GSM379834     2   0.000      0.999 0.000 1.000
#> GSM379827     2   0.000      0.999 0.000 1.000
#> GSM379828     2   0.000      0.999 0.000 1.000
#> GSM379829     2   0.327      0.935 0.060 0.940
#> GSM379830     2   0.000      0.999 0.000 1.000
#> GSM379831     2   0.000      0.999 0.000 1.000
#> GSM379840     2   0.000      0.999 0.000 1.000
#> GSM379841     2   0.000      0.999 0.000 1.000
#> GSM379842     2   0.000      0.999 0.000 1.000
#> GSM379835     2   0.000      0.999 0.000 1.000
#> GSM379836     2   0.000      0.999 0.000 1.000
#> GSM379837     2   0.000      0.999 0.000 1.000
#> GSM379838     2   0.000      0.999 0.000 1.000
#> GSM379839     2   0.000      0.999 0.000 1.000
#> GSM379848     2   0.000      0.999 0.000 1.000
#> GSM379849     2   0.000      0.999 0.000 1.000
#> GSM379850     2   0.000      0.999 0.000 1.000
#> GSM379843     2   0.000      0.999 0.000 1.000
#> GSM379844     2   0.000      0.999 0.000 1.000
#> GSM379845     2   0.000      0.999 0.000 1.000
#> GSM379846     2   0.000      0.999 0.000 1.000
#> GSM379847     2   0.000      0.999 0.000 1.000
#> GSM379853     2   0.000      0.999 0.000 1.000
#> GSM379854     2   0.000      0.999 0.000 1.000
#> GSM379851     2   0.000      0.999 0.000 1.000
#> GSM379852     2   0.000      0.999 0.000 1.000
#> GSM379804     1   0.000      0.990 1.000 0.000
#> GSM379805     1   0.000      0.990 1.000 0.000
#> GSM379806     1   0.000      0.990 1.000 0.000
#> GSM379799     1   0.000      0.990 1.000 0.000
#> GSM379800     1   0.000      0.990 1.000 0.000
#> GSM379801     1   0.000      0.990 1.000 0.000
#> GSM379802     1   0.000      0.990 1.000 0.000
#> GSM379803     1   0.000      0.990 1.000 0.000
#> GSM379812     1   0.430      0.903 0.912 0.088
#> GSM379813     1   0.000      0.990 1.000 0.000
#> GSM379814     1   0.000      0.990 1.000 0.000
#> GSM379807     1   0.000      0.990 1.000 0.000
#> GSM379808     1   0.000      0.990 1.000 0.000
#> GSM379809     1   0.000      0.990 1.000 0.000
#> GSM379810     1   0.000      0.990 1.000 0.000
#> GSM379811     1   0.000      0.990 1.000 0.000
#> GSM379820     1   0.000      0.990 1.000 0.000
#> GSM379821     1   0.000      0.990 1.000 0.000
#> GSM379822     1   0.000      0.990 1.000 0.000
#> GSM379815     1   0.000      0.990 1.000 0.000
#> GSM379816     1   0.730      0.755 0.796 0.204
#> GSM379817     1   0.000      0.990 1.000 0.000
#> GSM379818     1   0.000      0.990 1.000 0.000
#> GSM379819     1   0.000      0.990 1.000 0.000
#> GSM379825     1   0.000      0.990 1.000 0.000
#> GSM379826     1   0.000      0.990 1.000 0.000
#> GSM379823     1   0.000      0.990 1.000 0.000
#> GSM379824     1   0.000      0.990 1.000 0.000
#> GSM379749     2   0.000      0.999 0.000 1.000
#> GSM379750     2   0.000      0.999 0.000 1.000
#> GSM379751     2   0.000      0.999 0.000 1.000
#> GSM379744     2   0.000      0.999 0.000 1.000
#> GSM379745     2   0.000      0.999 0.000 1.000
#> GSM379746     2   0.000      0.999 0.000 1.000
#> GSM379747     2   0.000      0.999 0.000 1.000
#> GSM379748     2   0.000      0.999 0.000 1.000
#> GSM379757     2   0.000      0.999 0.000 1.000
#> GSM379758     2   0.000      0.999 0.000 1.000
#> GSM379752     2   0.000      0.999 0.000 1.000
#> GSM379753     2   0.000      0.999 0.000 1.000
#> GSM379754     2   0.000      0.999 0.000 1.000
#> GSM379755     2   0.000      0.999 0.000 1.000
#> GSM379756     2   0.000      0.999 0.000 1.000
#> GSM379764     2   0.000      0.999 0.000 1.000
#> GSM379765     2   0.000      0.999 0.000 1.000
#> GSM379766     2   0.000      0.999 0.000 1.000
#> GSM379759     2   0.000      0.999 0.000 1.000
#> GSM379760     2   0.000      0.999 0.000 1.000
#> GSM379761     2   0.000      0.999 0.000 1.000
#> GSM379762     2   0.000      0.999 0.000 1.000
#> GSM379763     2   0.000      0.999 0.000 1.000
#> GSM379769     2   0.000      0.999 0.000 1.000
#> GSM379770     2   0.000      0.999 0.000 1.000
#> GSM379767     2   0.000      0.999 0.000 1.000
#> GSM379768     2   0.000      0.999 0.000 1.000
#> GSM379776     1   0.000      0.990 1.000 0.000
#> GSM379777     1   0.000      0.990 1.000 0.000
#> GSM379778     1   0.000      0.990 1.000 0.000
#> GSM379771     1   0.000      0.990 1.000 0.000
#> GSM379772     1   0.000      0.990 1.000 0.000
#> GSM379773     1   0.000      0.990 1.000 0.000
#> GSM379774     1   0.000      0.990 1.000 0.000
#> GSM379775     1   0.000      0.990 1.000 0.000
#> GSM379784     1   0.000      0.990 1.000 0.000
#> GSM379785     1   0.000      0.990 1.000 0.000
#> GSM379786     1   0.000      0.990 1.000 0.000
#> GSM379779     1   0.000      0.990 1.000 0.000
#> GSM379780     1   0.000      0.990 1.000 0.000
#> GSM379781     1   0.000      0.990 1.000 0.000
#> GSM379782     1   0.000      0.990 1.000 0.000
#> GSM379783     1   0.000      0.990 1.000 0.000
#> GSM379792     1   0.000      0.990 1.000 0.000
#> GSM379793     1   0.000      0.990 1.000 0.000
#> GSM379794     1   0.000      0.990 1.000 0.000
#> GSM379787     1   0.000      0.990 1.000 0.000
#> GSM379788     1   0.000      0.990 1.000 0.000
#> GSM379789     1   0.000      0.990 1.000 0.000
#> GSM379790     1   0.000      0.990 1.000 0.000
#> GSM379791     1   0.000      0.990 1.000 0.000
#> GSM379797     1   0.000      0.990 1.000 0.000
#> GSM379798     1   0.000      0.990 1.000 0.000
#> GSM379795     1   0.000      0.990 1.000 0.000
#> GSM379796     1   0.000      0.990 1.000 0.000
#> GSM379721     1   0.000      0.990 1.000 0.000
#> GSM379722     1   0.000      0.990 1.000 0.000
#> GSM379723     1   0.000      0.990 1.000 0.000
#> GSM379716     1   0.000      0.990 1.000 0.000
#> GSM379717     1   0.000      0.990 1.000 0.000
#> GSM379718     1   0.000      0.990 1.000 0.000
#> GSM379719     1   0.000      0.990 1.000 0.000
#> GSM379720     1   0.000      0.990 1.000 0.000
#> GSM379729     1   0.722      0.760 0.800 0.200
#> GSM379730     1   0.722      0.760 0.800 0.200
#> GSM379731     1   0.000      0.990 1.000 0.000
#> GSM379724     1   0.000      0.990 1.000 0.000
#> GSM379725     1   0.541      0.861 0.876 0.124
#> GSM379726     1   0.000      0.990 1.000 0.000
#> GSM379727     1   0.000      0.990 1.000 0.000
#> GSM379728     1   0.000      0.990 1.000 0.000
#> GSM379737     1   0.000      0.990 1.000 0.000
#> GSM379738     1   0.000      0.990 1.000 0.000
#> GSM379739     1   0.000      0.990 1.000 0.000
#> GSM379732     1   0.000      0.990 1.000 0.000
#> GSM379733     1   0.000      0.990 1.000 0.000
#> GSM379734     1   0.000      0.990 1.000 0.000
#> GSM379735     1   0.000      0.990 1.000 0.000
#> GSM379736     1   0.000      0.990 1.000 0.000
#> GSM379742     2   0.000      0.999 0.000 1.000
#> GSM379743     1   0.000      0.990 1.000 0.000
#> GSM379740     1   0.000      0.990 1.000 0.000
#> GSM379741     2   0.000      0.999 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379833     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379834     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379827     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379828     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379829     2  0.2486     0.9224 0.060 0.932 0.008
#> GSM379830     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379831     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379840     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379841     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379842     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379835     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379836     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379837     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379838     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379839     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379848     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379849     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379850     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379843     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379844     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379845     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379846     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379847     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379853     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379854     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379851     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379852     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379804     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379805     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379806     1  0.0747     0.9698 0.984 0.000 0.016
#> GSM379799     1  0.0592     0.9736 0.988 0.000 0.012
#> GSM379800     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379801     1  0.6309     0.0168 0.504 0.000 0.496
#> GSM379802     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379803     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379812     1  0.2711     0.8852 0.912 0.088 0.000
#> GSM379813     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379814     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379807     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379808     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379809     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379810     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379811     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379820     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379821     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379822     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379815     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379816     1  0.4605     0.7344 0.796 0.204 0.000
#> GSM379817     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379818     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379819     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379825     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379826     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379823     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379824     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379749     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379750     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379751     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379744     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379745     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379746     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379747     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379748     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379757     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379758     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379752     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379753     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379754     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379755     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379756     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379764     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379765     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379766     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379759     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379760     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379761     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379762     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379763     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379769     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379770     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379767     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379768     2  0.0000     0.9986 0.000 1.000 0.000
#> GSM379776     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379777     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379778     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379771     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379772     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379773     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379774     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379775     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379784     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379785     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379786     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379779     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379780     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379781     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379782     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379783     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379792     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379793     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379794     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379787     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379788     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379789     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379790     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379791     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379797     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379798     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379795     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379796     1  0.0000     0.9842 1.000 0.000 0.000
#> GSM379721     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379722     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379723     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379716     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379717     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379718     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379719     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379720     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379729     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379730     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379731     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379724     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379725     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379726     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379727     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379728     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379737     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379738     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379739     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379732     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379733     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379734     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379735     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379736     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379742     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379743     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379740     3  0.0000     1.0000 0.000 0.000 1.000
#> GSM379741     3  0.0000     1.0000 0.000 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379833     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379834     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379827     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379828     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379829     4  0.5250      0.275 0.000 0.440 0.008 0.552
#> GSM379830     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379831     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379840     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379841     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379842     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379835     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379836     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379837     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379838     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379839     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379848     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379849     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379850     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379843     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379844     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379845     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379846     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379847     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379853     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379854     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379851     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379852     2  0.0000      0.873 0.000 1.000 0.000 0.000
#> GSM379804     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379805     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379806     4  0.0469      0.895 0.000 0.000 0.012 0.988
#> GSM379799     4  0.0336      0.900 0.000 0.000 0.008 0.992
#> GSM379800     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379801     4  0.4072      0.553 0.000 0.000 0.252 0.748
#> GSM379802     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379803     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379812     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379813     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379814     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379807     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379808     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379809     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379810     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379811     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379820     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379821     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379822     4  0.4999     -0.514 0.492 0.000 0.000 0.508
#> GSM379815     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379816     4  0.1637      0.832 0.060 0.000 0.000 0.940
#> GSM379817     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379818     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379819     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379825     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379826     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379823     4  0.4972     -0.400 0.456 0.000 0.000 0.544
#> GSM379824     4  0.0000      0.909 0.000 0.000 0.000 1.000
#> GSM379749     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379750     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379751     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379744     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379745     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379746     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379747     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379748     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379757     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379758     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379752     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379753     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379754     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379755     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379756     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379764     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379765     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379766     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379759     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379760     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379761     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379762     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379763     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379769     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379770     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379767     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379768     2  0.4222      0.874 0.272 0.728 0.000 0.000
#> GSM379776     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379777     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379778     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379771     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379772     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379773     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379774     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379775     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379784     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379785     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379786     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379779     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379780     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379781     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379782     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379783     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379792     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379793     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379794     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379787     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379788     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379789     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379790     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379791     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379797     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379798     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379795     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379796     1  0.4222      1.000 0.728 0.000 0.000 0.272
#> GSM379721     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379722     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379723     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379716     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379717     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379718     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379719     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379720     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379729     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379730     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379731     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379724     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379725     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379726     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379727     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379728     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379737     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379738     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379739     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379732     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379733     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379734     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379735     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379736     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379742     3  0.4008      0.726 0.244 0.000 0.756 0.000
#> GSM379743     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379740     3  0.0000      0.991 0.000 0.000 1.000 0.000
#> GSM379741     3  0.0000      0.991 0.000 0.000 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379833     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379834     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379827     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379828     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379829     4   0.289      0.779 0.000 0.000 0.000 0.824 0.176
#> GSM379830     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379831     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379840     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379841     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379842     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379835     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379836     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379837     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379838     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379839     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379848     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379849     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379850     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379843     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379844     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379845     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379846     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379847     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379853     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379854     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379851     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379852     5   0.000      1.000 0.000 0.000 0.000 0.000 1.000
#> GSM379804     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379805     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379806     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379799     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379800     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379801     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379802     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379803     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379812     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379813     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379814     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379807     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379808     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379809     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379810     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379811     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379820     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379821     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379822     1   0.340      0.696 0.764 0.000 0.000 0.236 0.000
#> GSM379815     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379816     4   0.334      0.692 0.228 0.000 0.000 0.772 0.000
#> GSM379817     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379818     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379819     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379825     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379826     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379823     1   0.364      0.634 0.728 0.000 0.000 0.272 0.000
#> GSM379824     4   0.000      0.984 0.000 0.000 0.000 1.000 0.000
#> GSM379749     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379750     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379751     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379744     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379745     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379746     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379747     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379748     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379757     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379758     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379752     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379753     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379754     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379755     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379756     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379764     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379765     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379766     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379759     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379760     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379761     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379762     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379763     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379769     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379770     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379767     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379768     2   0.000      1.000 0.000 1.000 0.000 0.000 0.000
#> GSM379776     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379777     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379778     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379771     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379772     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379773     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379774     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379775     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379784     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379785     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379786     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379779     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379780     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379781     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379782     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379783     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379792     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379793     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379794     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379787     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379788     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379789     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379790     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379791     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379797     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379798     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379795     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379796     1   0.000      0.982 1.000 0.000 0.000 0.000 0.000
#> GSM379721     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379722     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379723     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379716     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379717     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379718     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379719     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379720     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379729     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379730     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379731     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379724     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379725     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379726     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379727     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379728     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379737     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379738     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379739     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379732     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379733     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379734     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379735     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379736     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379742     3   0.422      0.288 0.000 0.416 0.584 0.000 0.000
#> GSM379743     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379740     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000
#> GSM379741     3   0.000      0.984 0.000 0.000 1.000 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     5  0.0260      0.918 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379833     6  0.3198      0.873 0.000 0.000 0.000 0.000 0.260 0.740
#> GSM379834     5  0.2340      0.734 0.000 0.000 0.000 0.000 0.852 0.148
#> GSM379827     5  0.0260      0.918 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379828     5  0.0260      0.918 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379829     5  0.2212      0.806 0.000 0.000 0.000 0.008 0.880 0.112
#> GSM379830     5  0.0260      0.918 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379831     5  0.0260      0.918 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379840     5  0.0260      0.918 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379841     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379842     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379835     5  0.0260      0.918 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379836     5  0.0260      0.918 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379837     5  0.0260      0.918 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379838     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379839     5  0.0260      0.918 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM379848     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379849     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379850     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379843     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379844     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379845     6  0.3838      0.524 0.000 0.000 0.000 0.000 0.448 0.552
#> GSM379846     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379847     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379853     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379854     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379851     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379852     6  0.2562      0.971 0.000 0.000 0.000 0.000 0.172 0.828
#> GSM379804     4  0.1957      0.936 0.000 0.000 0.000 0.888 0.000 0.112
#> GSM379805     4  0.1957      0.936 0.000 0.000 0.000 0.888 0.000 0.112
#> GSM379806     4  0.1957      0.936 0.000 0.000 0.000 0.888 0.000 0.112
#> GSM379799     4  0.1957      0.936 0.000 0.000 0.000 0.888 0.000 0.112
#> GSM379800     4  0.1957      0.936 0.000 0.000 0.000 0.888 0.000 0.112
#> GSM379801     4  0.1957      0.936 0.000 0.000 0.000 0.888 0.000 0.112
#> GSM379802     4  0.1957      0.936 0.000 0.000 0.000 0.888 0.000 0.112
#> GSM379803     4  0.1957      0.936 0.000 0.000 0.000 0.888 0.000 0.112
#> GSM379812     4  0.0000      0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379813     4  0.0000      0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379814     4  0.0000      0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379807     4  0.0000      0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379808     4  0.1957      0.936 0.000 0.000 0.000 0.888 0.000 0.112
#> GSM379809     4  0.0937      0.943 0.000 0.000 0.000 0.960 0.000 0.040
#> GSM379810     4  0.0000      0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379811     4  0.1957      0.936 0.000 0.000 0.000 0.888 0.000 0.112
#> GSM379820     4  0.0000      0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379821     4  0.0000      0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379822     1  0.3499      0.566 0.680 0.000 0.000 0.320 0.000 0.000
#> GSM379815     4  0.1075      0.942 0.000 0.000 0.000 0.952 0.000 0.048
#> GSM379816     4  0.3342      0.657 0.228 0.000 0.000 0.760 0.012 0.000
#> GSM379817     4  0.0000      0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379818     4  0.1957      0.936 0.000 0.000 0.000 0.888 0.000 0.112
#> GSM379819     4  0.0000      0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379825     4  0.0363      0.943 0.000 0.000 0.000 0.988 0.000 0.012
#> GSM379826     4  0.0000      0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379823     1  0.3547      0.542 0.668 0.000 0.000 0.332 0.000 0.000
#> GSM379824     4  0.0000      0.942 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379749     2  0.0260      0.963 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379750     2  0.0260      0.963 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379751     5  0.3101      0.673 0.000 0.244 0.000 0.000 0.756 0.000
#> GSM379744     2  0.0260      0.963 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379745     2  0.0260      0.963 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379746     2  0.0260      0.963 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379747     5  0.2793      0.719 0.000 0.200 0.000 0.000 0.800 0.000
#> GSM379748     2  0.0458      0.959 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379757     2  0.0260      0.963 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379758     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379752     2  0.0260      0.963 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379753     2  0.1610      0.895 0.000 0.916 0.000 0.000 0.084 0.000
#> GSM379754     2  0.0260      0.963 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379755     2  0.0260      0.963 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379756     2  0.0260      0.963 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379764     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379765     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379766     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379759     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379760     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379761     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379762     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379763     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379769     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379770     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379767     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379768     2  0.1267      0.968 0.000 0.940 0.000 0.000 0.000 0.060
#> GSM379776     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379777     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379778     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379771     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379772     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379773     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379774     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379775     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379784     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379785     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379786     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379779     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379780     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379781     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379782     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379783     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379792     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379793     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379794     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379787     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379788     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379789     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379790     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379791     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379797     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379798     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379796     1  0.0000      0.976 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379721     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379722     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379723     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379716     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379717     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379718     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379719     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379720     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379729     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379730     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379731     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379724     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379725     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379726     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379727     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379728     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379737     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379738     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379739     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379732     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379733     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379734     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379735     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379736     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379742     3  0.3789      0.271 0.000 0.416 0.584 0.000 0.000 0.000
#> GSM379743     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379740     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379741     3  0.0000      0.982 0.000 0.000 1.000 0.000 0.000 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-CV-pam-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-CV-pam-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-CV-pam-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-CV-pam-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-CV-pam-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-CV-pam-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-CV-pam-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-CV-pam-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-CV-pam-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-CV-pam-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-CV-pam-get-signatures-1

get_signatures(res, k = 3)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-pam-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-CV-pam-get-signatures-3

get_signatures(res, k = 5)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-pam-get-signatures-4

get_signatures(res, k = 6)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-pam-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-CV-pam-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-pam-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-CV-pam-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-pam-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-pam-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk CV-pam-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-CV-pam-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-CV-pam-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-CV-pam-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-CV-pam-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-CV-pam-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk CV-pam-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>          n individual(p) time(p) agent(p) k
#> CV:pam 139      2.03e-27       1   1.0000 2
#> CV:pam 138      5.23e-55       1   0.9770 3
#> CV:pam 136      7.65e-80       1   0.9944 4
#> CV:pam 138     2.69e-101       1   0.9773 5
#> CV:pam 138      1.07e-96       1   0.0241 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

CV:mclust**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["CV", "mclust"]
# you can also extract it by
# res = res_list["CV:mclust"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#>   Subgroups are detected by 'mclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 3.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk CV-mclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk CV-mclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.348           0.832       0.825         0.4280 0.518   0.518
#> 3 3 1.000           0.994       0.997         0.5072 0.837   0.685
#> 4 4 0.837           0.913       0.913         0.0939 0.948   0.855
#> 5 5 0.817           0.771       0.900         0.1091 0.901   0.682
#> 6 6 0.898           0.863       0.943         0.0176 0.886   0.571

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 3

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2   0.929      0.999 0.344 0.656
#> GSM379833     2   0.929      0.999 0.344 0.656
#> GSM379834     2   0.929      0.999 0.344 0.656
#> GSM379827     2   0.929      0.999 0.344 0.656
#> GSM379828     2   0.929      0.999 0.344 0.656
#> GSM379829     2   0.936      0.987 0.352 0.648
#> GSM379830     2   0.929      0.999 0.344 0.656
#> GSM379831     2   0.929      0.999 0.344 0.656
#> GSM379840     2   0.929      0.999 0.344 0.656
#> GSM379841     2   0.929      0.999 0.344 0.656
#> GSM379842     2   0.929      0.999 0.344 0.656
#> GSM379835     2   0.929      0.999 0.344 0.656
#> GSM379836     2   0.929      0.999 0.344 0.656
#> GSM379837     2   0.929      0.999 0.344 0.656
#> GSM379838     2   0.929      0.999 0.344 0.656
#> GSM379839     2   0.929      0.999 0.344 0.656
#> GSM379848     2   0.929      0.999 0.344 0.656
#> GSM379849     2   0.929      0.999 0.344 0.656
#> GSM379850     2   0.929      0.999 0.344 0.656
#> GSM379843     2   0.929      0.999 0.344 0.656
#> GSM379844     2   0.929      0.999 0.344 0.656
#> GSM379845     2   0.929      0.999 0.344 0.656
#> GSM379846     2   0.929      0.999 0.344 0.656
#> GSM379847     2   0.929      0.999 0.344 0.656
#> GSM379853     2   0.929      0.999 0.344 0.656
#> GSM379854     2   0.929      0.999 0.344 0.656
#> GSM379851     2   0.929      0.999 0.344 0.656
#> GSM379852     2   0.929      0.999 0.344 0.656
#> GSM379804     1   0.000      0.781 1.000 0.000
#> GSM379805     1   0.000      0.781 1.000 0.000
#> GSM379806     1   0.000      0.781 1.000 0.000
#> GSM379799     1   0.000      0.781 1.000 0.000
#> GSM379800     1   0.000      0.781 1.000 0.000
#> GSM379801     1   0.000      0.781 1.000 0.000
#> GSM379802     1   0.000      0.781 1.000 0.000
#> GSM379803     1   0.000      0.781 1.000 0.000
#> GSM379812     1   0.000      0.781 1.000 0.000
#> GSM379813     1   0.000      0.781 1.000 0.000
#> GSM379814     1   0.000      0.781 1.000 0.000
#> GSM379807     1   0.000      0.781 1.000 0.000
#> GSM379808     1   0.000      0.781 1.000 0.000
#> GSM379809     1   0.000      0.781 1.000 0.000
#> GSM379810     1   0.000      0.781 1.000 0.000
#> GSM379811     1   0.000      0.781 1.000 0.000
#> GSM379820     1   0.000      0.781 1.000 0.000
#> GSM379821     1   0.000      0.781 1.000 0.000
#> GSM379822     1   0.000      0.781 1.000 0.000
#> GSM379815     1   0.000      0.781 1.000 0.000
#> GSM379816     1   0.714      0.485 0.804 0.196
#> GSM379817     1   0.000      0.781 1.000 0.000
#> GSM379818     1   0.000      0.781 1.000 0.000
#> GSM379819     1   0.000      0.781 1.000 0.000
#> GSM379825     1   0.000      0.781 1.000 0.000
#> GSM379826     1   0.000      0.781 1.000 0.000
#> GSM379823     1   0.000      0.781 1.000 0.000
#> GSM379824     1   0.000      0.781 1.000 0.000
#> GSM379749     2   0.929      0.999 0.344 0.656
#> GSM379750     2   0.929      0.999 0.344 0.656
#> GSM379751     2   0.929      0.999 0.344 0.656
#> GSM379744     2   0.925      0.994 0.340 0.660
#> GSM379745     2   0.925      0.994 0.340 0.660
#> GSM379746     2   0.929      0.999 0.344 0.656
#> GSM379747     2   0.929      0.999 0.344 0.656
#> GSM379748     2   0.929      0.999 0.344 0.656
#> GSM379757     2   0.929      0.999 0.344 0.656
#> GSM379758     2   0.929      0.999 0.344 0.656
#> GSM379752     2   0.925      0.994 0.340 0.660
#> GSM379753     2   0.925      0.994 0.340 0.660
#> GSM379754     2   0.925      0.994 0.340 0.660
#> GSM379755     2   0.929      0.999 0.344 0.656
#> GSM379756     2   0.929      0.999 0.344 0.656
#> GSM379764     2   0.929      0.999 0.344 0.656
#> GSM379765     2   0.929      0.999 0.344 0.656
#> GSM379766     2   0.929      0.999 0.344 0.656
#> GSM379759     2   0.925      0.994 0.340 0.660
#> GSM379760     2   0.925      0.994 0.340 0.660
#> GSM379761     2   0.929      0.999 0.344 0.656
#> GSM379762     2   0.929      0.999 0.344 0.656
#> GSM379763     2   0.929      0.999 0.344 0.656
#> GSM379769     2   0.929      0.999 0.344 0.656
#> GSM379770     2   0.929      0.999 0.344 0.656
#> GSM379767     2   0.929      0.999 0.344 0.656
#> GSM379768     2   0.929      0.999 0.344 0.656
#> GSM379776     1   0.000      0.781 1.000 0.000
#> GSM379777     1   0.000      0.781 1.000 0.000
#> GSM379778     1   0.141      0.761 0.980 0.020
#> GSM379771     1   0.000      0.781 1.000 0.000
#> GSM379772     1   0.000      0.781 1.000 0.000
#> GSM379773     1   0.000      0.781 1.000 0.000
#> GSM379774     1   0.000      0.781 1.000 0.000
#> GSM379775     1   0.000      0.781 1.000 0.000
#> GSM379784     1   0.000      0.781 1.000 0.000
#> GSM379785     1   0.000      0.781 1.000 0.000
#> GSM379786     1   0.000      0.781 1.000 0.000
#> GSM379779     1   0.000      0.781 1.000 0.000
#> GSM379780     1   0.000      0.781 1.000 0.000
#> GSM379781     1   0.000      0.781 1.000 0.000
#> GSM379782     1   0.584      0.606 0.860 0.140
#> GSM379783     1   0.000      0.781 1.000 0.000
#> GSM379792     1   0.000      0.781 1.000 0.000
#> GSM379793     1   0.000      0.781 1.000 0.000
#> GSM379794     1   0.000      0.781 1.000 0.000
#> GSM379787     1   0.506      0.651 0.888 0.112
#> GSM379788     1   0.000      0.781 1.000 0.000
#> GSM379789     1   0.000      0.781 1.000 0.000
#> GSM379790     1   0.000      0.781 1.000 0.000
#> GSM379791     1   0.000      0.781 1.000 0.000
#> GSM379797     1   0.000      0.781 1.000 0.000
#> GSM379798     1   0.000      0.781 1.000 0.000
#> GSM379795     1   0.000      0.781 1.000 0.000
#> GSM379796     1   0.000      0.781 1.000 0.000
#> GSM379721     1   0.995      0.631 0.540 0.460
#> GSM379722     1   0.995      0.631 0.540 0.460
#> GSM379723     1   0.995      0.631 0.540 0.460
#> GSM379716     1   0.995      0.631 0.540 0.460
#> GSM379717     1   0.995      0.631 0.540 0.460
#> GSM379718     1   0.995      0.631 0.540 0.460
#> GSM379719     1   0.995      0.631 0.540 0.460
#> GSM379720     1   0.995      0.631 0.540 0.460
#> GSM379729     1   0.995      0.631 0.540 0.460
#> GSM379730     1   0.995      0.631 0.540 0.460
#> GSM379731     1   0.995      0.631 0.540 0.460
#> GSM379724     1   0.995      0.631 0.540 0.460
#> GSM379725     1   0.995      0.631 0.540 0.460
#> GSM379726     1   0.995      0.631 0.540 0.460
#> GSM379727     1   0.995      0.631 0.540 0.460
#> GSM379728     1   0.995      0.631 0.540 0.460
#> GSM379737     1   0.995      0.631 0.540 0.460
#> GSM379738     1   0.995      0.631 0.540 0.460
#> GSM379739     1   0.995      0.631 0.540 0.460
#> GSM379732     1   0.995      0.631 0.540 0.460
#> GSM379733     1   0.995      0.631 0.540 0.460
#> GSM379734     1   0.995      0.631 0.540 0.460
#> GSM379735     1   0.995      0.631 0.540 0.460
#> GSM379736     1   0.995      0.631 0.540 0.460
#> GSM379742     1   0.995      0.631 0.540 0.460
#> GSM379743     1   0.995      0.631 0.540 0.460
#> GSM379740     1   0.995      0.631 0.540 0.460
#> GSM379741     1   0.995      0.631 0.540 0.460

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2   0.000      0.996 0.000 1.000 0.000
#> GSM379833     2   0.000      0.996 0.000 1.000 0.000
#> GSM379834     2   0.000      0.996 0.000 1.000 0.000
#> GSM379827     2   0.000      0.996 0.000 1.000 0.000
#> GSM379828     2   0.000      0.996 0.000 1.000 0.000
#> GSM379829     2   0.460      0.734 0.204 0.796 0.000
#> GSM379830     2   0.000      0.996 0.000 1.000 0.000
#> GSM379831     2   0.000      0.996 0.000 1.000 0.000
#> GSM379840     2   0.000      0.996 0.000 1.000 0.000
#> GSM379841     2   0.000      0.996 0.000 1.000 0.000
#> GSM379842     2   0.000      0.996 0.000 1.000 0.000
#> GSM379835     2   0.000      0.996 0.000 1.000 0.000
#> GSM379836     2   0.000      0.996 0.000 1.000 0.000
#> GSM379837     2   0.000      0.996 0.000 1.000 0.000
#> GSM379838     2   0.000      0.996 0.000 1.000 0.000
#> GSM379839     2   0.000      0.996 0.000 1.000 0.000
#> GSM379848     2   0.000      0.996 0.000 1.000 0.000
#> GSM379849     2   0.000      0.996 0.000 1.000 0.000
#> GSM379850     2   0.000      0.996 0.000 1.000 0.000
#> GSM379843     2   0.000      0.996 0.000 1.000 0.000
#> GSM379844     2   0.000      0.996 0.000 1.000 0.000
#> GSM379845     2   0.000      0.996 0.000 1.000 0.000
#> GSM379846     2   0.000      0.996 0.000 1.000 0.000
#> GSM379847     2   0.000      0.996 0.000 1.000 0.000
#> GSM379853     2   0.000      0.996 0.000 1.000 0.000
#> GSM379854     2   0.000      0.996 0.000 1.000 0.000
#> GSM379851     2   0.000      0.996 0.000 1.000 0.000
#> GSM379852     2   0.000      0.996 0.000 1.000 0.000
#> GSM379804     1   0.000      0.999 1.000 0.000 0.000
#> GSM379805     1   0.000      0.999 1.000 0.000 0.000
#> GSM379806     1   0.000      0.999 1.000 0.000 0.000
#> GSM379799     1   0.000      0.999 1.000 0.000 0.000
#> GSM379800     1   0.000      0.999 1.000 0.000 0.000
#> GSM379801     1   0.000      0.999 1.000 0.000 0.000
#> GSM379802     1   0.000      0.999 1.000 0.000 0.000
#> GSM379803     1   0.000      0.999 1.000 0.000 0.000
#> GSM379812     1   0.000      0.999 1.000 0.000 0.000
#> GSM379813     1   0.000      0.999 1.000 0.000 0.000
#> GSM379814     1   0.000      0.999 1.000 0.000 0.000
#> GSM379807     1   0.000      0.999 1.000 0.000 0.000
#> GSM379808     1   0.000      0.999 1.000 0.000 0.000
#> GSM379809     1   0.000      0.999 1.000 0.000 0.000
#> GSM379810     1   0.000      0.999 1.000 0.000 0.000
#> GSM379811     1   0.000      0.999 1.000 0.000 0.000
#> GSM379820     1   0.000      0.999 1.000 0.000 0.000
#> GSM379821     1   0.000      0.999 1.000 0.000 0.000
#> GSM379822     1   0.000      0.999 1.000 0.000 0.000
#> GSM379815     1   0.000      0.999 1.000 0.000 0.000
#> GSM379816     1   0.103      0.972 0.976 0.024 0.000
#> GSM379817     1   0.000      0.999 1.000 0.000 0.000
#> GSM379818     1   0.000      0.999 1.000 0.000 0.000
#> GSM379819     1   0.000      0.999 1.000 0.000 0.000
#> GSM379825     1   0.000      0.999 1.000 0.000 0.000
#> GSM379826     1   0.000      0.999 1.000 0.000 0.000
#> GSM379823     1   0.000      0.999 1.000 0.000 0.000
#> GSM379824     1   0.000      0.999 1.000 0.000 0.000
#> GSM379749     2   0.000      0.996 0.000 1.000 0.000
#> GSM379750     2   0.000      0.996 0.000 1.000 0.000
#> GSM379751     2   0.000      0.996 0.000 1.000 0.000
#> GSM379744     2   0.000      0.996 0.000 1.000 0.000
#> GSM379745     2   0.000      0.996 0.000 1.000 0.000
#> GSM379746     2   0.000      0.996 0.000 1.000 0.000
#> GSM379747     2   0.000      0.996 0.000 1.000 0.000
#> GSM379748     2   0.000      0.996 0.000 1.000 0.000
#> GSM379757     2   0.000      0.996 0.000 1.000 0.000
#> GSM379758     2   0.000      0.996 0.000 1.000 0.000
#> GSM379752     2   0.000      0.996 0.000 1.000 0.000
#> GSM379753     2   0.000      0.996 0.000 1.000 0.000
#> GSM379754     2   0.000      0.996 0.000 1.000 0.000
#> GSM379755     2   0.000      0.996 0.000 1.000 0.000
#> GSM379756     2   0.000      0.996 0.000 1.000 0.000
#> GSM379764     2   0.000      0.996 0.000 1.000 0.000
#> GSM379765     2   0.000      0.996 0.000 1.000 0.000
#> GSM379766     2   0.000      0.996 0.000 1.000 0.000
#> GSM379759     2   0.000      0.996 0.000 1.000 0.000
#> GSM379760     2   0.000      0.996 0.000 1.000 0.000
#> GSM379761     2   0.000      0.996 0.000 1.000 0.000
#> GSM379762     2   0.000      0.996 0.000 1.000 0.000
#> GSM379763     2   0.000      0.996 0.000 1.000 0.000
#> GSM379769     2   0.000      0.996 0.000 1.000 0.000
#> GSM379770     2   0.000      0.996 0.000 1.000 0.000
#> GSM379767     2   0.000      0.996 0.000 1.000 0.000
#> GSM379768     2   0.000      0.996 0.000 1.000 0.000
#> GSM379776     1   0.000      0.999 1.000 0.000 0.000
#> GSM379777     1   0.000      0.999 1.000 0.000 0.000
#> GSM379778     1   0.000      0.999 1.000 0.000 0.000
#> GSM379771     1   0.000      0.999 1.000 0.000 0.000
#> GSM379772     1   0.000      0.999 1.000 0.000 0.000
#> GSM379773     1   0.000      0.999 1.000 0.000 0.000
#> GSM379774     1   0.000      0.999 1.000 0.000 0.000
#> GSM379775     1   0.000      0.999 1.000 0.000 0.000
#> GSM379784     1   0.000      0.999 1.000 0.000 0.000
#> GSM379785     1   0.000      0.999 1.000 0.000 0.000
#> GSM379786     1   0.000      0.999 1.000 0.000 0.000
#> GSM379779     1   0.000      0.999 1.000 0.000 0.000
#> GSM379780     1   0.000      0.999 1.000 0.000 0.000
#> GSM379781     1   0.000      0.999 1.000 0.000 0.000
#> GSM379782     1   0.000      0.999 1.000 0.000 0.000
#> GSM379783     1   0.000      0.999 1.000 0.000 0.000
#> GSM379792     1   0.000      0.999 1.000 0.000 0.000
#> GSM379793     1   0.000      0.999 1.000 0.000 0.000
#> GSM379794     1   0.000      0.999 1.000 0.000 0.000
#> GSM379787     1   0.000      0.999 1.000 0.000 0.000
#> GSM379788     1   0.000      0.999 1.000 0.000 0.000
#> GSM379789     1   0.000      0.999 1.000 0.000 0.000
#> GSM379790     1   0.000      0.999 1.000 0.000 0.000
#> GSM379791     1   0.000      0.999 1.000 0.000 0.000
#> GSM379797     1   0.000      0.999 1.000 0.000 0.000
#> GSM379798     1   0.000      0.999 1.000 0.000 0.000
#> GSM379795     1   0.000      0.999 1.000 0.000 0.000
#> GSM379796     1   0.000      0.999 1.000 0.000 0.000
#> GSM379721     3   0.000      0.995 0.000 0.000 1.000
#> GSM379722     3   0.000      0.995 0.000 0.000 1.000
#> GSM379723     3   0.000      0.995 0.000 0.000 1.000
#> GSM379716     3   0.000      0.995 0.000 0.000 1.000
#> GSM379717     3   0.000      0.995 0.000 0.000 1.000
#> GSM379718     3   0.000      0.995 0.000 0.000 1.000
#> GSM379719     3   0.000      0.995 0.000 0.000 1.000
#> GSM379720     3   0.000      0.995 0.000 0.000 1.000
#> GSM379729     3   0.000      0.995 0.000 0.000 1.000
#> GSM379730     3   0.000      0.995 0.000 0.000 1.000
#> GSM379731     3   0.000      0.995 0.000 0.000 1.000
#> GSM379724     3   0.000      0.995 0.000 0.000 1.000
#> GSM379725     3   0.000      0.995 0.000 0.000 1.000
#> GSM379726     3   0.000      0.995 0.000 0.000 1.000
#> GSM379727     3   0.000      0.995 0.000 0.000 1.000
#> GSM379728     3   0.000      0.995 0.000 0.000 1.000
#> GSM379737     3   0.000      0.995 0.000 0.000 1.000
#> GSM379738     3   0.000      0.995 0.000 0.000 1.000
#> GSM379739     3   0.000      0.995 0.000 0.000 1.000
#> GSM379732     3   0.000      0.995 0.000 0.000 1.000
#> GSM379733     3   0.000      0.995 0.000 0.000 1.000
#> GSM379734     3   0.000      0.995 0.000 0.000 1.000
#> GSM379735     3   0.000      0.995 0.000 0.000 1.000
#> GSM379736     3   0.000      0.995 0.000 0.000 1.000
#> GSM379742     3   0.226      0.930 0.068 0.000 0.932
#> GSM379743     3   0.000      0.995 0.000 0.000 1.000
#> GSM379740     3   0.000      0.995 0.000 0.000 1.000
#> GSM379741     3   0.226      0.930 0.068 0.000 0.932

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2 p3    p4
#> GSM379832     2  0.1940      0.932 0.000 0.924  0 0.076
#> GSM379833     2  0.1940      0.932 0.000 0.924  0 0.076
#> GSM379834     2  0.1867      0.933 0.000 0.928  0 0.072
#> GSM379827     2  0.2149      0.929 0.000 0.912  0 0.088
#> GSM379828     2  0.2216      0.928 0.000 0.908  0 0.092
#> GSM379829     2  0.5849      0.640 0.164 0.704  0 0.132
#> GSM379830     2  0.2149      0.927 0.000 0.912  0 0.088
#> GSM379831     2  0.2149      0.927 0.000 0.912  0 0.088
#> GSM379840     2  0.3367      0.904 0.028 0.864  0 0.108
#> GSM379841     2  0.0469      0.943 0.000 0.988  0 0.012
#> GSM379842     2  0.0592      0.943 0.000 0.984  0 0.016
#> GSM379835     2  0.2149      0.927 0.000 0.912  0 0.088
#> GSM379836     2  0.2760      0.914 0.000 0.872  0 0.128
#> GSM379837     2  0.2704      0.911 0.000 0.876  0 0.124
#> GSM379838     2  0.0188      0.944 0.000 0.996  0 0.004
#> GSM379839     2  0.2704      0.911 0.000 0.876  0 0.124
#> GSM379848     2  0.0469      0.942 0.000 0.988  0 0.012
#> GSM379849     2  0.0469      0.942 0.000 0.988  0 0.012
#> GSM379850     2  0.0592      0.942 0.000 0.984  0 0.016
#> GSM379843     2  0.0592      0.943 0.000 0.984  0 0.016
#> GSM379844     2  0.0188      0.943 0.000 0.996  0 0.004
#> GSM379845     2  0.1211      0.940 0.000 0.960  0 0.040
#> GSM379846     2  0.0469      0.942 0.000 0.988  0 0.012
#> GSM379847     2  0.0469      0.942 0.000 0.988  0 0.012
#> GSM379853     2  0.0817      0.942 0.000 0.976  0 0.024
#> GSM379854     2  0.0469      0.942 0.000 0.988  0 0.012
#> GSM379851     2  0.0707      0.942 0.000 0.980  0 0.020
#> GSM379852     2  0.1118      0.938 0.000 0.964  0 0.036
#> GSM379804     1  0.3801      0.714 0.780 0.000  0 0.220
#> GSM379805     4  0.3942      0.988 0.236 0.000  0 0.764
#> GSM379806     4  0.3942      0.988 0.236 0.000  0 0.764
#> GSM379799     4  0.3942      0.988 0.236 0.000  0 0.764
#> GSM379800     4  0.3942      0.988 0.236 0.000  0 0.764
#> GSM379801     4  0.3942      0.988 0.236 0.000  0 0.764
#> GSM379802     4  0.3942      0.988 0.236 0.000  0 0.764
#> GSM379803     4  0.3942      0.988 0.236 0.000  0 0.764
#> GSM379812     1  0.4134      0.636 0.740 0.000  0 0.260
#> GSM379813     1  0.3726      0.722 0.788 0.000  0 0.212
#> GSM379814     1  0.2589      0.828 0.884 0.000  0 0.116
#> GSM379807     1  0.2647      0.825 0.880 0.000  0 0.120
#> GSM379808     4  0.3942      0.988 0.236 0.000  0 0.764
#> GSM379809     1  0.2760      0.820 0.872 0.000  0 0.128
#> GSM379810     1  0.2704      0.822 0.876 0.000  0 0.124
#> GSM379811     4  0.3942      0.988 0.236 0.000  0 0.764
#> GSM379820     1  0.3528      0.751 0.808 0.000  0 0.192
#> GSM379821     1  0.4500      0.499 0.684 0.000  0 0.316
#> GSM379822     1  0.3024      0.801 0.852 0.000  0 0.148
#> GSM379815     1  0.4454      0.522 0.692 0.000  0 0.308
#> GSM379816     1  0.4071      0.762 0.832 0.064  0 0.104
#> GSM379817     1  0.3172      0.788 0.840 0.000  0 0.160
#> GSM379818     4  0.4193      0.944 0.268 0.000  0 0.732
#> GSM379819     1  0.4040      0.660 0.752 0.000  0 0.248
#> GSM379825     4  0.4222      0.939 0.272 0.000  0 0.728
#> GSM379826     1  0.3311      0.776 0.828 0.000  0 0.172
#> GSM379823     1  0.0336      0.891 0.992 0.000  0 0.008
#> GSM379824     1  0.4331      0.573 0.712 0.000  0 0.288
#> GSM379749     2  0.1716      0.941 0.000 0.936  0 0.064
#> GSM379750     2  0.1557      0.942 0.000 0.944  0 0.056
#> GSM379751     2  0.2530      0.929 0.000 0.888  0 0.112
#> GSM379744     2  0.1940      0.939 0.000 0.924  0 0.076
#> GSM379745     2  0.2149      0.937 0.000 0.912  0 0.088
#> GSM379746     2  0.2081      0.938 0.000 0.916  0 0.084
#> GSM379747     2  0.2469      0.930 0.000 0.892  0 0.108
#> GSM379748     2  0.2149      0.927 0.000 0.912  0 0.088
#> GSM379757     2  0.0817      0.942 0.000 0.976  0 0.024
#> GSM379758     2  0.1302      0.939 0.000 0.956  0 0.044
#> GSM379752     2  0.1716      0.941 0.000 0.936  0 0.064
#> GSM379753     2  0.2345      0.937 0.000 0.900  0 0.100
#> GSM379754     2  0.1022      0.943 0.000 0.968  0 0.032
#> GSM379755     2  0.1022      0.943 0.000 0.968  0 0.032
#> GSM379756     2  0.0817      0.942 0.000 0.976  0 0.024
#> GSM379764     2  0.3024      0.888 0.000 0.852  0 0.148
#> GSM379765     2  0.2973      0.890 0.000 0.856  0 0.144
#> GSM379766     2  0.2973      0.890 0.000 0.856  0 0.144
#> GSM379759     2  0.1389      0.938 0.000 0.952  0 0.048
#> GSM379760     2  0.1211      0.940 0.000 0.960  0 0.040
#> GSM379761     2  0.1211      0.940 0.000 0.960  0 0.040
#> GSM379762     2  0.1637      0.935 0.000 0.940  0 0.060
#> GSM379763     2  0.2081      0.925 0.000 0.916  0 0.084
#> GSM379769     2  0.3448      0.874 0.004 0.828  0 0.168
#> GSM379770     2  0.2647      0.895 0.000 0.880  0 0.120
#> GSM379767     2  0.2973      0.890 0.000 0.856  0 0.144
#> GSM379768     2  0.2973      0.890 0.000 0.856  0 0.144
#> GSM379776     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379777     1  0.3569      0.746 0.804 0.000  0 0.196
#> GSM379778     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379771     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379772     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379773     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379774     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379775     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379784     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379785     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379786     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379779     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379780     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379781     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379782     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379783     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379792     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379793     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379794     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379787     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379788     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379789     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379790     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379791     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379797     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379798     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379795     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379796     1  0.0000      0.895 1.000 0.000  0 0.000
#> GSM379721     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379722     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379723     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379716     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379717     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379718     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379719     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379720     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379729     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379730     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379731     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379724     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379725     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379726     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379727     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379728     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379737     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379738     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379739     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379732     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379733     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379734     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379735     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379736     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379742     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379743     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379740     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379741     3  0.0000      1.000 0.000 0.000  1 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     5  0.0703     0.8117 0.000 0.024 0.000 0.000 0.976
#> GSM379833     5  0.0703     0.8117 0.000 0.024 0.000 0.000 0.976
#> GSM379834     5  0.0703     0.8117 0.000 0.024 0.000 0.000 0.976
#> GSM379827     5  0.0290     0.8109 0.000 0.008 0.000 0.000 0.992
#> GSM379828     5  0.0290     0.8109 0.000 0.008 0.000 0.000 0.992
#> GSM379829     5  0.3527     0.6437 0.016 0.000 0.000 0.192 0.792
#> GSM379830     5  0.0000     0.8090 0.000 0.000 0.000 0.000 1.000
#> GSM379831     5  0.0510     0.8116 0.000 0.016 0.000 0.000 0.984
#> GSM379840     5  0.0000     0.8090 0.000 0.000 0.000 0.000 1.000
#> GSM379841     5  0.3636     0.6735 0.000 0.272 0.000 0.000 0.728
#> GSM379842     5  0.3039     0.7394 0.000 0.192 0.000 0.000 0.808
#> GSM379835     5  0.0290     0.8109 0.000 0.008 0.000 0.000 0.992
#> GSM379836     5  0.0000     0.8090 0.000 0.000 0.000 0.000 1.000
#> GSM379837     5  0.0000     0.8090 0.000 0.000 0.000 0.000 1.000
#> GSM379838     5  0.2966     0.7446 0.000 0.184 0.000 0.000 0.816
#> GSM379839     5  0.0000     0.8090 0.000 0.000 0.000 0.000 1.000
#> GSM379848     5  0.3774     0.6484 0.000 0.296 0.000 0.000 0.704
#> GSM379849     5  0.4242     0.3801 0.000 0.428 0.000 0.000 0.572
#> GSM379850     5  0.3796     0.6443 0.000 0.300 0.000 0.000 0.700
#> GSM379843     5  0.3774     0.6484 0.000 0.296 0.000 0.000 0.704
#> GSM379844     5  0.3837     0.6317 0.000 0.308 0.000 0.000 0.692
#> GSM379845     5  0.0162     0.8102 0.000 0.004 0.000 0.000 0.996
#> GSM379846     5  0.3774     0.6484 0.000 0.296 0.000 0.000 0.704
#> GSM379847     5  0.3774     0.6484 0.000 0.296 0.000 0.000 0.704
#> GSM379853     5  0.3508     0.6934 0.000 0.252 0.000 0.000 0.748
#> GSM379854     5  0.3796     0.6443 0.000 0.300 0.000 0.000 0.700
#> GSM379851     5  0.4305     0.2036 0.000 0.488 0.000 0.000 0.512
#> GSM379852     2  0.4171     0.2043 0.000 0.604 0.000 0.000 0.396
#> GSM379804     1  0.4307    -0.1115 0.504 0.000 0.000 0.496 0.000
#> GSM379805     4  0.0162     0.7794 0.004 0.000 0.000 0.996 0.000
#> GSM379806     4  0.0609     0.7785 0.020 0.000 0.000 0.980 0.000
#> GSM379799     4  0.0162     0.7794 0.004 0.000 0.000 0.996 0.000
#> GSM379800     4  0.0162     0.7794 0.004 0.000 0.000 0.996 0.000
#> GSM379801     4  0.1197     0.7670 0.048 0.000 0.000 0.952 0.000
#> GSM379802     4  0.0162     0.7794 0.004 0.000 0.000 0.996 0.000
#> GSM379803     4  0.0162     0.7794 0.004 0.000 0.000 0.996 0.000
#> GSM379812     4  0.4256     0.2997 0.436 0.000 0.000 0.564 0.000
#> GSM379813     1  0.4306    -0.0954 0.508 0.000 0.000 0.492 0.000
#> GSM379814     1  0.3774     0.5396 0.704 0.000 0.000 0.296 0.000
#> GSM379807     1  0.3305     0.6493 0.776 0.000 0.000 0.224 0.000
#> GSM379808     4  0.0510     0.7793 0.016 0.000 0.000 0.984 0.000
#> GSM379809     1  0.3966     0.4622 0.664 0.000 0.000 0.336 0.000
#> GSM379810     1  0.3932     0.4805 0.672 0.000 0.000 0.328 0.000
#> GSM379811     4  0.0162     0.7794 0.004 0.000 0.000 0.996 0.000
#> GSM379820     1  0.4045     0.4051 0.644 0.000 0.000 0.356 0.000
#> GSM379821     4  0.4210     0.3612 0.412 0.000 0.000 0.588 0.000
#> GSM379822     1  0.3707     0.5610 0.716 0.000 0.000 0.284 0.000
#> GSM379815     4  0.4150     0.4099 0.388 0.000 0.000 0.612 0.000
#> GSM379816     1  0.5203     0.4575 0.648 0.000 0.000 0.272 0.080
#> GSM379817     1  0.3857     0.5079 0.688 0.000 0.000 0.312 0.000
#> GSM379818     4  0.0290     0.7790 0.008 0.000 0.000 0.992 0.000
#> GSM379819     4  0.4256     0.3020 0.436 0.000 0.000 0.564 0.000
#> GSM379825     4  0.0290     0.7790 0.008 0.000 0.000 0.992 0.000
#> GSM379826     1  0.3636     0.5805 0.728 0.000 0.000 0.272 0.000
#> GSM379823     1  0.0404     0.8621 0.988 0.000 0.000 0.012 0.000
#> GSM379824     4  0.4242     0.3241 0.428 0.000 0.000 0.572 0.000
#> GSM379749     5  0.2732     0.7425 0.000 0.160 0.000 0.000 0.840
#> GSM379750     5  0.0794     0.8113 0.000 0.028 0.000 0.000 0.972
#> GSM379751     5  0.2424     0.7522 0.000 0.132 0.000 0.000 0.868
#> GSM379744     5  0.2813     0.7355 0.000 0.168 0.000 0.000 0.832
#> GSM379745     5  0.2605     0.7520 0.000 0.148 0.000 0.000 0.852
#> GSM379746     5  0.2690     0.7460 0.000 0.156 0.000 0.000 0.844
#> GSM379747     5  0.2732     0.7315 0.000 0.160 0.000 0.000 0.840
#> GSM379748     5  0.0404     0.8114 0.000 0.012 0.000 0.000 0.988
#> GSM379757     2  0.3684     0.4549 0.000 0.720 0.000 0.000 0.280
#> GSM379758     2  0.0000     0.8877 0.000 1.000 0.000 0.000 0.000
#> GSM379752     5  0.2929     0.7241 0.000 0.180 0.000 0.000 0.820
#> GSM379753     2  0.3636     0.5653 0.000 0.728 0.000 0.000 0.272
#> GSM379754     2  0.2561     0.7535 0.000 0.856 0.000 0.000 0.144
#> GSM379755     5  0.2813     0.7391 0.000 0.168 0.000 0.000 0.832
#> GSM379756     5  0.3452     0.7100 0.000 0.244 0.000 0.000 0.756
#> GSM379764     2  0.0510     0.8758 0.016 0.984 0.000 0.000 0.000
#> GSM379765     2  0.0000     0.8877 0.000 1.000 0.000 0.000 0.000
#> GSM379766     2  0.0000     0.8877 0.000 1.000 0.000 0.000 0.000
#> GSM379759     2  0.0162     0.8866 0.000 0.996 0.000 0.000 0.004
#> GSM379760     2  0.0162     0.8866 0.000 0.996 0.000 0.000 0.004
#> GSM379761     2  0.0162     0.8866 0.000 0.996 0.000 0.000 0.004
#> GSM379762     2  0.0000     0.8877 0.000 1.000 0.000 0.000 0.000
#> GSM379763     2  0.0000     0.8877 0.000 1.000 0.000 0.000 0.000
#> GSM379769     2  0.0510     0.8758 0.016 0.984 0.000 0.000 0.000
#> GSM379770     2  0.3452     0.6051 0.000 0.756 0.000 0.000 0.244
#> GSM379767     2  0.0000     0.8877 0.000 1.000 0.000 0.000 0.000
#> GSM379768     2  0.0000     0.8877 0.000 1.000 0.000 0.000 0.000
#> GSM379776     1  0.0162     0.8681 0.996 0.000 0.000 0.004 0.000
#> GSM379777     4  0.4273     0.2553 0.448 0.000 0.000 0.552 0.000
#> GSM379778     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379771     1  0.0162     0.8681 0.996 0.000 0.000 0.004 0.000
#> GSM379772     1  0.0162     0.8681 0.996 0.000 0.000 0.004 0.000
#> GSM379773     1  0.0162     0.8681 0.996 0.000 0.000 0.004 0.000
#> GSM379774     1  0.0162     0.8681 0.996 0.000 0.000 0.004 0.000
#> GSM379775     1  0.0162     0.8681 0.996 0.000 0.000 0.004 0.000
#> GSM379784     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379785     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379786     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379779     1  0.0162     0.8681 0.996 0.000 0.000 0.004 0.000
#> GSM379780     1  0.0162     0.8681 0.996 0.000 0.000 0.004 0.000
#> GSM379781     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379782     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379783     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379792     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379793     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379794     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379787     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379788     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379789     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379790     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379791     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379797     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379798     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379796     1  0.0000     0.8695 1.000 0.000 0.000 0.000 0.000
#> GSM379721     3  0.0162     0.9870 0.000 0.000 0.996 0.004 0.000
#> GSM379722     3  0.0162     0.9870 0.000 0.000 0.996 0.004 0.000
#> GSM379723     3  0.0162     0.9870 0.000 0.000 0.996 0.004 0.000
#> GSM379716     3  0.0162     0.9870 0.000 0.000 0.996 0.004 0.000
#> GSM379717     3  0.0162     0.9870 0.000 0.000 0.996 0.004 0.000
#> GSM379718     3  0.0162     0.9870 0.000 0.000 0.996 0.004 0.000
#> GSM379719     3  0.0162     0.9870 0.000 0.000 0.996 0.004 0.000
#> GSM379720     3  0.0162     0.9870 0.000 0.000 0.996 0.004 0.000
#> GSM379729     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379730     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379731     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379724     3  0.0162     0.9870 0.000 0.000 0.996 0.004 0.000
#> GSM379725     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379726     3  0.0162     0.9870 0.000 0.000 0.996 0.004 0.000
#> GSM379727     3  0.0162     0.9870 0.000 0.000 0.996 0.004 0.000
#> GSM379728     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379737     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379738     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379739     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379732     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379733     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379734     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379735     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379736     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379742     3  0.2230     0.8410 0.116 0.000 0.884 0.000 0.000
#> GSM379743     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379740     3  0.0000     0.9875 0.000 0.000 1.000 0.000 0.000
#> GSM379741     3  0.2230     0.8410 0.116 0.000 0.884 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379833     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379834     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379827     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379828     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379829     5  0.3023      0.665 0.000 0.000 0.000 0.232 0.768 0.000
#> GSM379830     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379831     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379840     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379841     5  0.3774      0.184 0.000 0.408 0.000 0.000 0.592 0.000
#> GSM379842     5  0.3620      0.370 0.000 0.352 0.000 0.000 0.648 0.000
#> GSM379835     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379836     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379837     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379838     5  0.2883      0.684 0.000 0.212 0.000 0.000 0.788 0.000
#> GSM379839     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379848     2  0.2562      0.797 0.000 0.828 0.000 0.000 0.172 0.000
#> GSM379849     2  0.0865      0.859 0.000 0.964 0.000 0.000 0.036 0.000
#> GSM379850     2  0.2260      0.817 0.000 0.860 0.000 0.000 0.140 0.000
#> GSM379843     2  0.3810      0.378 0.000 0.572 0.000 0.000 0.428 0.000
#> GSM379844     2  0.3684      0.516 0.000 0.628 0.000 0.000 0.372 0.000
#> GSM379845     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379846     2  0.3620      0.556 0.000 0.648 0.000 0.000 0.352 0.000
#> GSM379847     2  0.3390      0.650 0.000 0.704 0.000 0.000 0.296 0.000
#> GSM379853     2  0.2597      0.793 0.000 0.824 0.000 0.000 0.176 0.000
#> GSM379854     2  0.2300      0.815 0.000 0.856 0.000 0.000 0.144 0.000
#> GSM379851     2  0.1204      0.853 0.000 0.944 0.000 0.000 0.056 0.000
#> GSM379852     2  0.0458      0.863 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379804     4  0.3756      0.482 0.352 0.000 0.000 0.644 0.000 0.004
#> GSM379805     4  0.0000      0.844 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379806     4  0.0000      0.844 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379799     4  0.0000      0.844 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379800     4  0.0000      0.844 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379801     4  0.0000      0.844 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379802     4  0.0000      0.844 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379803     4  0.0000      0.844 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379812     1  0.0603      0.973 0.980 0.000 0.000 0.016 0.000 0.004
#> GSM379813     1  0.0508      0.976 0.984 0.000 0.000 0.012 0.000 0.004
#> GSM379814     1  0.0508      0.976 0.984 0.000 0.000 0.012 0.000 0.004
#> GSM379807     1  0.0291      0.976 0.992 0.000 0.000 0.004 0.000 0.004
#> GSM379808     4  0.0000      0.844 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379809     4  0.3290      0.620 0.252 0.000 0.000 0.744 0.000 0.004
#> GSM379810     1  0.3508      0.547 0.704 0.000 0.000 0.292 0.000 0.004
#> GSM379811     4  0.0000      0.844 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379820     1  0.0291      0.976 0.992 0.000 0.000 0.004 0.000 0.004
#> GSM379821     1  0.0291      0.976 0.992 0.000 0.000 0.004 0.000 0.004
#> GSM379822     1  0.0146      0.977 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379815     1  0.2320      0.838 0.864 0.000 0.000 0.132 0.000 0.004
#> GSM379816     1  0.3411      0.762 0.816 0.000 0.000 0.060 0.120 0.004
#> GSM379817     1  0.0146      0.977 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379818     4  0.1910      0.765 0.108 0.000 0.000 0.892 0.000 0.000
#> GSM379819     1  0.0291      0.976 0.992 0.000 0.000 0.004 0.000 0.004
#> GSM379825     4  0.3857      0.202 0.468 0.000 0.000 0.532 0.000 0.000
#> GSM379826     1  0.0146      0.977 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379823     1  0.0146      0.977 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379824     1  0.0291      0.976 0.992 0.000 0.000 0.004 0.000 0.004
#> GSM379749     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379750     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379751     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379744     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379745     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379746     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379747     5  0.0146      0.936 0.000 0.004 0.000 0.000 0.996 0.000
#> GSM379748     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379757     2  0.3774      0.413 0.000 0.592 0.000 0.000 0.408 0.000
#> GSM379758     2  0.0260      0.864 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379752     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379753     5  0.0146      0.936 0.000 0.004 0.000 0.000 0.996 0.000
#> GSM379754     5  0.2340      0.786 0.000 0.148 0.000 0.000 0.852 0.000
#> GSM379755     5  0.0000      0.939 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379756     5  0.2178      0.804 0.000 0.132 0.000 0.000 0.868 0.000
#> GSM379764     2  0.0000      0.862 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379765     2  0.0000      0.862 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379766     2  0.0000      0.862 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379759     2  0.0260      0.864 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379760     2  0.0547      0.861 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379761     2  0.0260      0.864 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379762     2  0.0146      0.863 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379763     2  0.0000      0.862 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379769     2  0.0000      0.862 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379770     2  0.0000      0.862 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379767     2  0.0000      0.862 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379768     2  0.0000      0.862 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379776     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379777     1  0.0508      0.976 0.984 0.000 0.000 0.012 0.000 0.004
#> GSM379778     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379771     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379772     1  0.0405      0.977 0.988 0.000 0.004 0.008 0.000 0.000
#> GSM379773     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379774     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379775     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379784     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379785     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379786     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379779     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379780     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379781     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379782     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379783     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379792     1  0.0146      0.977 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM379793     1  0.0000      0.978 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379794     1  0.0000      0.978 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379787     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379788     1  0.0260      0.978 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM379789     1  0.0000      0.978 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379790     1  0.0000      0.978 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379791     1  0.0000      0.978 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379797     1  0.0000      0.978 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379798     1  0.0000      0.978 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0000      0.978 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379796     1  0.0000      0.978 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379721     6  0.0146      0.870 0.000 0.000 0.004 0.000 0.000 0.996
#> GSM379722     6  0.0146      0.870 0.000 0.000 0.004 0.000 0.000 0.996
#> GSM379723     6  0.0146      0.870 0.000 0.000 0.004 0.000 0.000 0.996
#> GSM379716     6  0.0146      0.870 0.000 0.000 0.004 0.000 0.000 0.996
#> GSM379717     6  0.0146      0.870 0.000 0.000 0.004 0.000 0.000 0.996
#> GSM379718     6  0.0146      0.870 0.000 0.000 0.004 0.000 0.000 0.996
#> GSM379719     6  0.0146      0.870 0.000 0.000 0.004 0.000 0.000 0.996
#> GSM379720     6  0.0146      0.870 0.000 0.000 0.004 0.000 0.000 0.996
#> GSM379729     3  0.0146      0.960 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM379730     3  0.0146      0.960 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM379731     3  0.0146      0.960 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM379724     6  0.0146      0.870 0.000 0.000 0.004 0.000 0.000 0.996
#> GSM379725     3  0.3446      0.461 0.000 0.000 0.692 0.000 0.000 0.308
#> GSM379726     6  0.3672      0.456 0.000 0.000 0.368 0.000 0.000 0.632
#> GSM379727     6  0.3843      0.264 0.000 0.000 0.452 0.000 0.000 0.548
#> GSM379728     6  0.3847      0.255 0.000 0.000 0.456 0.000 0.000 0.544
#> GSM379737     3  0.0000      0.962 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379738     3  0.0000      0.962 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379739     3  0.0000      0.962 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379732     3  0.0146      0.960 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM379733     3  0.0000      0.962 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379734     3  0.0000      0.962 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379735     3  0.0000      0.962 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379736     3  0.2178      0.808 0.000 0.000 0.868 0.000 0.000 0.132
#> GSM379742     3  0.0260      0.953 0.008 0.000 0.992 0.000 0.000 0.000
#> GSM379743     3  0.0000      0.962 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379740     3  0.0000      0.962 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379741     3  0.0260      0.953 0.008 0.000 0.992 0.000 0.000 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-CV-mclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-CV-mclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-CV-mclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-CV-mclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-CV-mclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-CV-mclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-CV-mclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-CV-mclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-CV-mclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-CV-mclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-mclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-CV-mclust-get-signatures-2

get_signatures(res, k = 4)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-mclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-CV-mclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-CV-mclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-mclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-CV-mclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-mclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-CV-mclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-CV-mclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk CV-mclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-CV-mclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-CV-mclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-CV-mclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-CV-mclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-CV-mclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk CV-mclust-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>             n individual(p) time(p) agent(p) k
#> CV:mclust 138      7.56e-29   1.000 1.00e+00 2
#> CV:mclust 139      1.97e-55   1.000 9.98e-01 3
#> CV:mclust 138      1.57e-59   1.000 4.65e-02 4
#> CV:mclust 123      7.01e-67   1.000 2.07e-03 5
#> CV:mclust 129      9.13e-51   0.965 1.89e-09 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

CV:NMF**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["CV", "NMF"]
# you can also extract it by
# res = res_list["CV:NMF"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#>   Subgroups are detected by 'NMF' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk CV-NMF-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk CV-NMF-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.970           0.962       0.984         0.4946 0.508   0.508
#> 3 3 0.626           0.598       0.808         0.3324 0.806   0.628
#> 4 4 0.891           0.891       0.945         0.1140 0.879   0.666
#> 5 5 0.887           0.868       0.930         0.0436 0.966   0.874
#> 6 6 0.891           0.912       0.931         0.0528 0.915   0.672

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000      0.990 0.000 1.000
#> GSM379833     2  0.0000      0.990 0.000 1.000
#> GSM379834     2  0.0000      0.990 0.000 1.000
#> GSM379827     2  0.0000      0.990 0.000 1.000
#> GSM379828     2  0.0000      0.990 0.000 1.000
#> GSM379829     1  0.0000      0.978 1.000 0.000
#> GSM379830     2  0.0000      0.990 0.000 1.000
#> GSM379831     2  0.0000      0.990 0.000 1.000
#> GSM379840     2  0.0000      0.990 0.000 1.000
#> GSM379841     2  0.0000      0.990 0.000 1.000
#> GSM379842     2  0.0000      0.990 0.000 1.000
#> GSM379835     2  0.0000      0.990 0.000 1.000
#> GSM379836     2  0.0000      0.990 0.000 1.000
#> GSM379837     1  0.9129      0.533 0.672 0.328
#> GSM379838     2  0.0000      0.990 0.000 1.000
#> GSM379839     2  0.6712      0.782 0.176 0.824
#> GSM379848     2  0.0000      0.990 0.000 1.000
#> GSM379849     2  0.0000      0.990 0.000 1.000
#> GSM379850     2  0.0000      0.990 0.000 1.000
#> GSM379843     2  0.0000      0.990 0.000 1.000
#> GSM379844     2  0.0000      0.990 0.000 1.000
#> GSM379845     2  0.0000      0.990 0.000 1.000
#> GSM379846     2  0.0000      0.990 0.000 1.000
#> GSM379847     2  0.0000      0.990 0.000 1.000
#> GSM379853     2  0.0000      0.990 0.000 1.000
#> GSM379854     2  0.0000      0.990 0.000 1.000
#> GSM379851     2  0.0000      0.990 0.000 1.000
#> GSM379852     2  0.0000      0.990 0.000 1.000
#> GSM379804     1  0.0000      0.978 1.000 0.000
#> GSM379805     1  0.0000      0.978 1.000 0.000
#> GSM379806     1  0.0000      0.978 1.000 0.000
#> GSM379799     1  0.0000      0.978 1.000 0.000
#> GSM379800     1  0.0000      0.978 1.000 0.000
#> GSM379801     1  0.0000      0.978 1.000 0.000
#> GSM379802     1  0.0000      0.978 1.000 0.000
#> GSM379803     1  0.0000      0.978 1.000 0.000
#> GSM379812     1  0.0000      0.978 1.000 0.000
#> GSM379813     1  0.0000      0.978 1.000 0.000
#> GSM379814     1  0.0000      0.978 1.000 0.000
#> GSM379807     1  0.0000      0.978 1.000 0.000
#> GSM379808     1  0.0000      0.978 1.000 0.000
#> GSM379809     1  0.0000      0.978 1.000 0.000
#> GSM379810     1  0.0000      0.978 1.000 0.000
#> GSM379811     1  0.0000      0.978 1.000 0.000
#> GSM379820     1  0.0000      0.978 1.000 0.000
#> GSM379821     1  0.0000      0.978 1.000 0.000
#> GSM379822     1  0.0000      0.978 1.000 0.000
#> GSM379815     1  0.0000      0.978 1.000 0.000
#> GSM379816     1  0.8267      0.663 0.740 0.260
#> GSM379817     1  0.0000      0.978 1.000 0.000
#> GSM379818     1  0.0000      0.978 1.000 0.000
#> GSM379819     1  0.0000      0.978 1.000 0.000
#> GSM379825     1  0.0000      0.978 1.000 0.000
#> GSM379826     1  0.0000      0.978 1.000 0.000
#> GSM379823     1  0.0000      0.978 1.000 0.000
#> GSM379824     1  0.0000      0.978 1.000 0.000
#> GSM379749     2  0.0000      0.990 0.000 1.000
#> GSM379750     2  0.0000      0.990 0.000 1.000
#> GSM379751     2  0.0000      0.990 0.000 1.000
#> GSM379744     2  0.0000      0.990 0.000 1.000
#> GSM379745     2  0.0000      0.990 0.000 1.000
#> GSM379746     2  0.0000      0.990 0.000 1.000
#> GSM379747     2  0.0000      0.990 0.000 1.000
#> GSM379748     2  0.0000      0.990 0.000 1.000
#> GSM379757     2  0.0000      0.990 0.000 1.000
#> GSM379758     2  0.0000      0.990 0.000 1.000
#> GSM379752     2  0.0000      0.990 0.000 1.000
#> GSM379753     2  0.0000      0.990 0.000 1.000
#> GSM379754     2  0.0000      0.990 0.000 1.000
#> GSM379755     2  0.0000      0.990 0.000 1.000
#> GSM379756     2  0.0000      0.990 0.000 1.000
#> GSM379764     2  0.0000      0.990 0.000 1.000
#> GSM379765     2  0.0000      0.990 0.000 1.000
#> GSM379766     2  0.0000      0.990 0.000 1.000
#> GSM379759     2  0.0000      0.990 0.000 1.000
#> GSM379760     2  0.0000      0.990 0.000 1.000
#> GSM379761     2  0.0000      0.990 0.000 1.000
#> GSM379762     2  0.0000      0.990 0.000 1.000
#> GSM379763     2  0.0000      0.990 0.000 1.000
#> GSM379769     2  0.0000      0.990 0.000 1.000
#> GSM379770     2  0.0000      0.990 0.000 1.000
#> GSM379767     2  0.0000      0.990 0.000 1.000
#> GSM379768     2  0.0000      0.990 0.000 1.000
#> GSM379776     1  0.0000      0.978 1.000 0.000
#> GSM379777     1  0.0000      0.978 1.000 0.000
#> GSM379778     2  0.1633      0.968 0.024 0.976
#> GSM379771     1  0.0000      0.978 1.000 0.000
#> GSM379772     1  0.0000      0.978 1.000 0.000
#> GSM379773     1  0.0000      0.978 1.000 0.000
#> GSM379774     1  0.0000      0.978 1.000 0.000
#> GSM379775     1  0.0000      0.978 1.000 0.000
#> GSM379784     1  0.0672      0.971 0.992 0.008
#> GSM379785     1  0.0000      0.978 1.000 0.000
#> GSM379786     1  0.9909      0.232 0.556 0.444
#> GSM379779     1  0.0000      0.978 1.000 0.000
#> GSM379780     1  0.0000      0.978 1.000 0.000
#> GSM379781     1  0.0000      0.978 1.000 0.000
#> GSM379782     2  0.0000      0.990 0.000 1.000
#> GSM379783     2  0.5842      0.833 0.140 0.860
#> GSM379792     1  0.0000      0.978 1.000 0.000
#> GSM379793     1  0.0000      0.978 1.000 0.000
#> GSM379794     1  0.0000      0.978 1.000 0.000
#> GSM379787     2  0.7139      0.754 0.196 0.804
#> GSM379788     1  0.0000      0.978 1.000 0.000
#> GSM379789     1  0.0000      0.978 1.000 0.000
#> GSM379790     1  0.0000      0.978 1.000 0.000
#> GSM379791     1  0.0000      0.978 1.000 0.000
#> GSM379797     1  0.0000      0.978 1.000 0.000
#> GSM379798     1  0.0000      0.978 1.000 0.000
#> GSM379795     1  0.0000      0.978 1.000 0.000
#> GSM379796     1  0.0000      0.978 1.000 0.000
#> GSM379721     1  0.0000      0.978 1.000 0.000
#> GSM379722     1  0.0000      0.978 1.000 0.000
#> GSM379723     1  0.0000      0.978 1.000 0.000
#> GSM379716     1  0.0000      0.978 1.000 0.000
#> GSM379717     1  0.0000      0.978 1.000 0.000
#> GSM379718     1  0.0000      0.978 1.000 0.000
#> GSM379719     1  0.0000      0.978 1.000 0.000
#> GSM379720     1  0.0000      0.978 1.000 0.000
#> GSM379729     1  0.7139      0.761 0.804 0.196
#> GSM379730     1  0.7453      0.738 0.788 0.212
#> GSM379731     1  0.0000      0.978 1.000 0.000
#> GSM379724     1  0.0000      0.978 1.000 0.000
#> GSM379725     1  0.2603      0.937 0.956 0.044
#> GSM379726     1  0.0000      0.978 1.000 0.000
#> GSM379727     1  0.0000      0.978 1.000 0.000
#> GSM379728     1  0.0000      0.978 1.000 0.000
#> GSM379737     1  0.0000      0.978 1.000 0.000
#> GSM379738     1  0.0000      0.978 1.000 0.000
#> GSM379739     1  0.0000      0.978 1.000 0.000
#> GSM379732     1  0.0376      0.974 0.996 0.004
#> GSM379733     1  0.0000      0.978 1.000 0.000
#> GSM379734     1  0.0000      0.978 1.000 0.000
#> GSM379735     1  0.0000      0.978 1.000 0.000
#> GSM379736     1  0.0000      0.978 1.000 0.000
#> GSM379742     2  0.0000      0.990 0.000 1.000
#> GSM379743     1  0.8144      0.675 0.748 0.252
#> GSM379740     1  0.0000      0.978 1.000 0.000
#> GSM379741     2  0.0000      0.990 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379833     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379834     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379827     2  0.0237     0.9421 0.000 0.996 0.004
#> GSM379828     2  0.0237     0.9421 0.000 0.996 0.004
#> GSM379829     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379830     2  0.0237     0.9421 0.000 0.996 0.004
#> GSM379831     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379840     2  0.4629     0.7468 0.188 0.808 0.004
#> GSM379841     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379842     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379835     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379836     2  0.3120     0.8660 0.080 0.908 0.012
#> GSM379837     1  0.9213     0.3390 0.536 0.236 0.228
#> GSM379838     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379839     1  0.9134     0.2613 0.500 0.344 0.156
#> GSM379848     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379849     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379850     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379843     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379844     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379845     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379846     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379847     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379853     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379854     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379851     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379852     2  0.0237     0.9421 0.004 0.996 0.000
#> GSM379804     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379805     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379806     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379799     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379800     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379801     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379802     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379803     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379812     1  0.5678     0.5119 0.684 0.000 0.316
#> GSM379813     1  0.5733     0.5068 0.676 0.000 0.324
#> GSM379814     1  0.5882     0.5009 0.652 0.000 0.348
#> GSM379807     1  0.5591     0.5257 0.696 0.000 0.304
#> GSM379808     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379809     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379810     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379811     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379820     1  0.4399     0.4198 0.812 0.000 0.188
#> GSM379821     1  0.3686     0.4536 0.860 0.000 0.140
#> GSM379822     1  0.6280    -0.1799 0.540 0.000 0.460
#> GSM379815     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379816     1  0.9109     0.4168 0.488 0.148 0.364
#> GSM379817     1  0.3879     0.4487 0.848 0.000 0.152
#> GSM379818     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379819     1  0.5327     0.5275 0.728 0.000 0.272
#> GSM379825     1  0.5621     0.5253 0.692 0.000 0.308
#> GSM379826     1  0.4931     0.3638 0.768 0.000 0.232
#> GSM379823     1  0.6302    -0.2318 0.520 0.000 0.480
#> GSM379824     1  0.3551     0.4575 0.868 0.000 0.132
#> GSM379749     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379750     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379751     2  0.0475     0.9396 0.004 0.992 0.004
#> GSM379744     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379745     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379746     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379747     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379748     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379757     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379758     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379752     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379753     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379754     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379755     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379756     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379764     2  0.2056     0.9066 0.024 0.952 0.024
#> GSM379765     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379766     2  0.0237     0.9421 0.004 0.996 0.000
#> GSM379759     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379760     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379761     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379762     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379763     2  0.0000     0.9448 0.000 1.000 0.000
#> GSM379769     2  0.8026     0.4945 0.164 0.656 0.180
#> GSM379770     2  0.4179     0.8291 0.072 0.876 0.052
#> GSM379767     2  0.2269     0.8980 0.016 0.944 0.040
#> GSM379768     2  0.0475     0.9394 0.004 0.992 0.004
#> GSM379776     1  0.5560     0.4076 0.700 0.000 0.300
#> GSM379777     1  0.4178     0.4796 0.828 0.000 0.172
#> GSM379778     2  1.0000    -0.3775 0.332 0.336 0.332
#> GSM379771     1  0.5733     0.3967 0.676 0.000 0.324
#> GSM379772     1  0.6154     0.1747 0.592 0.000 0.408
#> GSM379773     1  0.5650     0.3645 0.688 0.000 0.312
#> GSM379774     1  0.5497     0.3686 0.708 0.000 0.292
#> GSM379775     1  0.5465     0.3812 0.712 0.000 0.288
#> GSM379784     1  0.6264     0.0701 0.616 0.004 0.380
#> GSM379785     1  0.5760     0.2143 0.672 0.000 0.328
#> GSM379786     1  0.9521    -0.1766 0.440 0.192 0.368
#> GSM379779     1  0.5859     0.2037 0.656 0.000 0.344
#> GSM379780     1  0.5905     0.1710 0.648 0.000 0.352
#> GSM379781     1  0.5968     0.1360 0.636 0.000 0.364
#> GSM379782     2  0.9921    -0.2529 0.308 0.396 0.296
#> GSM379783     2  0.9989    -0.3382 0.328 0.356 0.316
#> GSM379792     1  0.4178     0.4337 0.828 0.000 0.172
#> GSM379793     3  0.6309     0.2500 0.496 0.000 0.504
#> GSM379794     3  0.6309     0.2411 0.500 0.000 0.500
#> GSM379787     3  0.9616     0.2969 0.344 0.212 0.444
#> GSM379788     1  0.6307    -0.2459 0.512 0.000 0.488
#> GSM379789     1  0.6244    -0.1054 0.560 0.000 0.440
#> GSM379790     1  0.5254     0.3296 0.736 0.000 0.264
#> GSM379791     3  0.6295     0.3018 0.472 0.000 0.528
#> GSM379797     1  0.3816     0.5199 0.852 0.000 0.148
#> GSM379798     1  0.6305    -0.2406 0.516 0.000 0.484
#> GSM379795     3  0.6204     0.4005 0.424 0.000 0.576
#> GSM379796     1  0.5733     0.2194 0.676 0.000 0.324
#> GSM379721     3  0.0592     0.6462 0.012 0.000 0.988
#> GSM379722     3  0.0237     0.6511 0.004 0.000 0.996
#> GSM379723     3  0.1860     0.6063 0.052 0.000 0.948
#> GSM379716     3  0.4291     0.4209 0.180 0.000 0.820
#> GSM379717     3  0.4178     0.4356 0.172 0.000 0.828
#> GSM379718     3  0.3482     0.5087 0.128 0.000 0.872
#> GSM379719     3  0.1031     0.6380 0.024 0.000 0.976
#> GSM379720     3  0.3941     0.4688 0.156 0.000 0.844
#> GSM379729     3  0.5346     0.6176 0.088 0.088 0.824
#> GSM379730     3  0.6726     0.5799 0.132 0.120 0.748
#> GSM379731     3  0.0424     0.6521 0.008 0.000 0.992
#> GSM379724     3  0.1163     0.6333 0.028 0.000 0.972
#> GSM379725     3  0.0592     0.6544 0.012 0.000 0.988
#> GSM379726     3  0.0237     0.6511 0.004 0.000 0.996
#> GSM379727     3  0.0237     0.6511 0.004 0.000 0.996
#> GSM379728     3  0.0747     0.6436 0.016 0.000 0.984
#> GSM379737     3  0.5621     0.5700 0.308 0.000 0.692
#> GSM379738     3  0.5621     0.5700 0.308 0.000 0.692
#> GSM379739     3  0.5621     0.5700 0.308 0.000 0.692
#> GSM379732     3  0.3267     0.6478 0.116 0.000 0.884
#> GSM379733     3  0.1163     0.6557 0.028 0.000 0.972
#> GSM379734     3  0.3192     0.6486 0.112 0.000 0.888
#> GSM379735     3  0.5621     0.5700 0.308 0.000 0.692
#> GSM379736     3  0.1411     0.6252 0.036 0.000 0.964
#> GSM379742     3  0.6770     0.5748 0.264 0.044 0.692
#> GSM379743     3  0.5621     0.5700 0.308 0.000 0.692
#> GSM379740     3  0.5529     0.5775 0.296 0.000 0.704
#> GSM379741     3  0.6193     0.5740 0.292 0.016 0.692

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379833     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379834     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379827     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379828     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379829     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379830     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379831     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379840     2  0.2334      0.896 0.004 0.908 0.000 0.088
#> GSM379841     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379842     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379835     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379836     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379837     4  0.4991      0.377 0.004 0.388 0.000 0.608
#> GSM379838     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379839     4  0.4872      0.455 0.004 0.356 0.000 0.640
#> GSM379848     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379849     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379850     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379843     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379844     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379845     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379846     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379847     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379853     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379854     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379851     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379852     2  0.0188      0.983 0.004 0.996 0.000 0.000
#> GSM379804     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379805     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379806     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379799     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379800     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379801     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379802     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379803     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379812     4  0.2334      0.850 0.088 0.004 0.000 0.908
#> GSM379813     4  0.1940      0.860 0.076 0.000 0.000 0.924
#> GSM379814     4  0.1792      0.865 0.068 0.000 0.000 0.932
#> GSM379807     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379808     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379809     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379810     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379811     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379820     4  0.2675      0.848 0.100 0.000 0.008 0.892
#> GSM379821     4  0.3400      0.777 0.180 0.000 0.000 0.820
#> GSM379822     1  0.1284      0.863 0.964 0.000 0.024 0.012
#> GSM379815     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379816     4  0.6103      0.612 0.116 0.192 0.004 0.688
#> GSM379817     4  0.3219      0.770 0.164 0.000 0.000 0.836
#> GSM379818     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379819     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379825     4  0.0000      0.902 0.000 0.000 0.000 1.000
#> GSM379826     4  0.4542      0.701 0.228 0.000 0.020 0.752
#> GSM379823     1  0.0817      0.862 0.976 0.000 0.024 0.000
#> GSM379824     4  0.2125      0.865 0.076 0.000 0.004 0.920
#> GSM379749     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379750     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379751     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379744     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379745     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379746     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379747     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379748     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379757     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379758     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379752     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379753     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379754     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379755     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379756     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379764     2  0.4059      0.758 0.200 0.788 0.012 0.000
#> GSM379765     2  0.0336      0.978 0.008 0.992 0.000 0.000
#> GSM379766     2  0.1557      0.937 0.056 0.944 0.000 0.000
#> GSM379759     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379760     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379761     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379762     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379763     2  0.0000      0.983 0.000 1.000 0.000 0.000
#> GSM379769     1  0.4744      0.606 0.736 0.240 0.024 0.000
#> GSM379770     2  0.4035      0.783 0.176 0.804 0.020 0.000
#> GSM379767     2  0.3743      0.808 0.160 0.824 0.016 0.000
#> GSM379768     2  0.1022      0.958 0.032 0.968 0.000 0.000
#> GSM379776     1  0.5016      0.452 0.600 0.000 0.004 0.396
#> GSM379777     4  0.4643      0.401 0.344 0.000 0.000 0.656
#> GSM379778     1  0.2131      0.863 0.932 0.036 0.000 0.032
#> GSM379771     1  0.6554      0.357 0.520 0.000 0.080 0.400
#> GSM379772     1  0.5911      0.711 0.692 0.000 0.112 0.196
#> GSM379773     1  0.3873      0.749 0.772 0.000 0.000 0.228
#> GSM379774     1  0.3945      0.761 0.780 0.000 0.004 0.216
#> GSM379775     1  0.4422      0.711 0.736 0.000 0.008 0.256
#> GSM379784     1  0.1302      0.872 0.956 0.000 0.000 0.044
#> GSM379785     1  0.1792      0.866 0.932 0.000 0.000 0.068
#> GSM379786     1  0.0188      0.872 0.996 0.000 0.000 0.004
#> GSM379779     1  0.3249      0.827 0.852 0.000 0.008 0.140
#> GSM379780     1  0.2530      0.847 0.888 0.000 0.000 0.112
#> GSM379781     1  0.2216      0.858 0.908 0.000 0.000 0.092
#> GSM379782     1  0.1389      0.854 0.952 0.048 0.000 0.000
#> GSM379783     1  0.2124      0.842 0.924 0.068 0.000 0.008
#> GSM379792     1  0.4713      0.487 0.640 0.000 0.000 0.360
#> GSM379793     1  0.0188      0.870 0.996 0.000 0.004 0.000
#> GSM379794     1  0.0376      0.872 0.992 0.000 0.004 0.004
#> GSM379787     1  0.0469      0.873 0.988 0.000 0.000 0.012
#> GSM379788     1  0.0188      0.872 0.996 0.000 0.000 0.004
#> GSM379789     1  0.0921      0.874 0.972 0.000 0.000 0.028
#> GSM379790     1  0.2149      0.860 0.912 0.000 0.000 0.088
#> GSM379791     1  0.0376      0.872 0.992 0.000 0.004 0.004
#> GSM379797     4  0.1211      0.882 0.040 0.000 0.000 0.960
#> GSM379798     1  0.0188      0.870 0.996 0.000 0.004 0.000
#> GSM379795     1  0.0188      0.870 0.996 0.000 0.004 0.000
#> GSM379796     1  0.1305      0.869 0.960 0.000 0.004 0.036
#> GSM379721     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379722     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379723     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379716     3  0.0188      0.967 0.000 0.000 0.996 0.004
#> GSM379717     3  0.0188      0.967 0.000 0.000 0.996 0.004
#> GSM379718     3  0.0336      0.963 0.000 0.000 0.992 0.008
#> GSM379719     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379720     3  0.0336      0.963 0.000 0.000 0.992 0.008
#> GSM379729     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379730     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379731     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379724     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379725     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379726     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379727     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379728     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379737     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379738     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379739     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379732     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379733     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379734     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379735     3  0.0188      0.967 0.004 0.000 0.996 0.000
#> GSM379736     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379742     3  0.4977      0.204 0.460 0.000 0.540 0.000
#> GSM379743     3  0.1211      0.936 0.040 0.000 0.960 0.000
#> GSM379740     3  0.0000      0.969 0.000 0.000 1.000 0.000
#> GSM379741     3  0.4331      0.614 0.288 0.000 0.712 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379833     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379834     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379827     2  0.0404      0.905 0.000 0.988 0.000 0.000 0.012
#> GSM379828     2  0.0404      0.905 0.000 0.988 0.000 0.000 0.012
#> GSM379829     4  0.1469      0.859 0.000 0.036 0.000 0.948 0.016
#> GSM379830     2  0.0404      0.905 0.000 0.988 0.000 0.000 0.012
#> GSM379831     2  0.0404      0.905 0.000 0.988 0.000 0.000 0.012
#> GSM379840     2  0.1605      0.865 0.004 0.944 0.000 0.040 0.012
#> GSM379841     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379842     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379835     2  0.0404      0.905 0.000 0.988 0.000 0.000 0.012
#> GSM379836     2  0.0912      0.894 0.012 0.972 0.000 0.000 0.016
#> GSM379837     4  0.4482      0.272 0.000 0.376 0.000 0.612 0.012
#> GSM379838     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379839     4  0.4016      0.499 0.000 0.272 0.000 0.716 0.012
#> GSM379848     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379849     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379850     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379843     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379844     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379845     2  0.0404      0.905 0.000 0.988 0.000 0.000 0.012
#> GSM379846     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379847     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379853     2  0.0162      0.909 0.000 0.996 0.000 0.000 0.004
#> GSM379854     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379851     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379852     2  0.0000      0.911 0.000 1.000 0.000 0.000 0.000
#> GSM379804     4  0.0162      0.895 0.000 0.000 0.000 0.996 0.004
#> GSM379805     4  0.0162      0.895 0.000 0.000 0.000 0.996 0.004
#> GSM379806     4  0.0162      0.895 0.000 0.000 0.000 0.996 0.004
#> GSM379799     4  0.0290      0.894 0.000 0.000 0.000 0.992 0.008
#> GSM379800     4  0.0290      0.894 0.000 0.000 0.000 0.992 0.008
#> GSM379801     4  0.0290      0.894 0.000 0.000 0.000 0.992 0.008
#> GSM379802     4  0.0162      0.895 0.000 0.000 0.000 0.996 0.004
#> GSM379803     4  0.0000      0.895 0.000 0.000 0.000 1.000 0.000
#> GSM379812     4  0.4380      0.554 0.020 0.000 0.000 0.676 0.304
#> GSM379813     4  0.3359      0.757 0.020 0.000 0.000 0.816 0.164
#> GSM379814     4  0.1216      0.878 0.020 0.000 0.000 0.960 0.020
#> GSM379807     4  0.0579      0.890 0.008 0.000 0.000 0.984 0.008
#> GSM379808     4  0.0290      0.894 0.000 0.000 0.000 0.992 0.008
#> GSM379809     4  0.0162      0.895 0.000 0.000 0.000 0.996 0.004
#> GSM379810     4  0.0000      0.895 0.000 0.000 0.000 1.000 0.000
#> GSM379811     4  0.0000      0.895 0.000 0.000 0.000 1.000 0.000
#> GSM379820     4  0.1800      0.863 0.020 0.000 0.000 0.932 0.048
#> GSM379821     5  0.4697      0.143 0.020 0.000 0.000 0.388 0.592
#> GSM379822     5  0.3134      0.660 0.120 0.000 0.000 0.032 0.848
#> GSM379815     4  0.0000      0.895 0.000 0.000 0.000 1.000 0.000
#> GSM379816     4  0.4173      0.558 0.000 0.012 0.000 0.688 0.300
#> GSM379817     4  0.4297      0.583 0.020 0.000 0.000 0.692 0.288
#> GSM379818     4  0.0000      0.895 0.000 0.000 0.000 1.000 0.000
#> GSM379819     4  0.0579      0.890 0.008 0.000 0.000 0.984 0.008
#> GSM379825     4  0.0162      0.894 0.000 0.000 0.000 0.996 0.004
#> GSM379826     4  0.3810      0.739 0.036 0.000 0.000 0.788 0.176
#> GSM379823     5  0.2818      0.662 0.132 0.000 0.000 0.012 0.856
#> GSM379824     4  0.2046      0.854 0.016 0.000 0.000 0.916 0.068
#> GSM379749     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379750     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379751     2  0.2536      0.901 0.000 0.868 0.000 0.004 0.128
#> GSM379744     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379745     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379746     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379747     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379748     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379757     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379758     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379752     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379753     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379754     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379755     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379756     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379764     5  0.3039      0.634 0.000 0.192 0.000 0.000 0.808
#> GSM379765     2  0.3395      0.798 0.000 0.764 0.000 0.000 0.236
#> GSM379766     2  0.3305      0.813 0.000 0.776 0.000 0.000 0.224
#> GSM379759     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379760     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379761     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379762     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379763     2  0.2377      0.903 0.000 0.872 0.000 0.000 0.128
#> GSM379769     5  0.0963      0.690 0.000 0.036 0.000 0.000 0.964
#> GSM379770     5  0.3837      0.392 0.000 0.308 0.000 0.000 0.692
#> GSM379767     2  0.3857      0.678 0.000 0.688 0.000 0.000 0.312
#> GSM379768     2  0.3109      0.840 0.000 0.800 0.000 0.000 0.200
#> GSM379776     1  0.1430      0.929 0.944 0.000 0.000 0.052 0.004
#> GSM379777     1  0.2692      0.875 0.884 0.008 0.000 0.092 0.016
#> GSM379778     1  0.0880      0.943 0.968 0.032 0.000 0.000 0.000
#> GSM379771     1  0.1934      0.922 0.928 0.000 0.016 0.052 0.004
#> GSM379772     1  0.2061      0.925 0.928 0.004 0.024 0.040 0.004
#> GSM379773     1  0.1653      0.940 0.944 0.028 0.000 0.024 0.004
#> GSM379774     1  0.1525      0.940 0.948 0.012 0.000 0.036 0.004
#> GSM379775     1  0.1443      0.935 0.948 0.004 0.000 0.044 0.004
#> GSM379784     1  0.0898      0.948 0.972 0.020 0.000 0.000 0.008
#> GSM379785     1  0.0609      0.948 0.980 0.020 0.000 0.000 0.000
#> GSM379786     1  0.1106      0.946 0.964 0.024 0.000 0.000 0.012
#> GSM379779     1  0.1059      0.948 0.968 0.008 0.000 0.020 0.004
#> GSM379780     1  0.0865      0.948 0.972 0.024 0.000 0.004 0.000
#> GSM379781     1  0.0703      0.947 0.976 0.024 0.000 0.000 0.000
#> GSM379782     1  0.0955      0.945 0.968 0.028 0.000 0.000 0.004
#> GSM379783     1  0.0992      0.947 0.968 0.024 0.000 0.000 0.008
#> GSM379792     1  0.1197      0.933 0.952 0.000 0.000 0.048 0.000
#> GSM379793     1  0.0162      0.945 0.996 0.000 0.000 0.000 0.004
#> GSM379794     1  0.0000      0.946 1.000 0.000 0.000 0.000 0.000
#> GSM379787     1  0.1041      0.939 0.964 0.032 0.000 0.000 0.004
#> GSM379788     1  0.0609      0.948 0.980 0.020 0.000 0.000 0.000
#> GSM379789     1  0.0404      0.948 0.988 0.000 0.000 0.012 0.000
#> GSM379790     1  0.0609      0.947 0.980 0.000 0.000 0.020 0.000
#> GSM379791     1  0.0000      0.946 1.000 0.000 0.000 0.000 0.000
#> GSM379797     1  0.4403      0.266 0.560 0.000 0.000 0.436 0.004
#> GSM379798     1  0.0000      0.946 1.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0000      0.946 1.000 0.000 0.000 0.000 0.000
#> GSM379796     1  0.0162      0.947 0.996 0.000 0.000 0.004 0.000
#> GSM379721     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379722     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379723     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379716     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379717     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379718     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379719     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379720     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379729     3  0.0404      0.949 0.000 0.000 0.988 0.000 0.012
#> GSM379730     3  0.0794      0.937 0.000 0.000 0.972 0.000 0.028
#> GSM379731     3  0.0162      0.954 0.000 0.000 0.996 0.000 0.004
#> GSM379724     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379725     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379726     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379727     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379728     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379737     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379738     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379739     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379732     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379733     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379734     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379735     3  0.1671      0.896 0.000 0.000 0.924 0.000 0.076
#> GSM379736     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379742     3  0.5171      0.187 0.040 0.000 0.504 0.000 0.456
#> GSM379743     3  0.3561      0.680 0.000 0.000 0.740 0.000 0.260
#> GSM379740     3  0.0000      0.957 0.000 0.000 1.000 0.000 0.000
#> GSM379741     3  0.4161      0.626 0.016 0.000 0.704 0.000 0.280

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     5  0.2793     0.9633 0.000 0.200 0.000 0.000 0.800 0.000
#> GSM379833     5  0.2793     0.9633 0.000 0.200 0.000 0.000 0.800 0.000
#> GSM379834     5  0.2793     0.9633 0.000 0.200 0.000 0.000 0.800 0.000
#> GSM379827     5  0.2854     0.9532 0.000 0.208 0.000 0.000 0.792 0.000
#> GSM379828     5  0.2854     0.9532 0.000 0.208 0.000 0.000 0.792 0.000
#> GSM379829     4  0.2632     0.6985 0.000 0.000 0.000 0.832 0.164 0.004
#> GSM379830     5  0.2730     0.9619 0.000 0.192 0.000 0.000 0.808 0.000
#> GSM379831     5  0.2697     0.9615 0.000 0.188 0.000 0.000 0.812 0.000
#> GSM379840     5  0.3175     0.9290 0.000 0.164 0.000 0.028 0.808 0.000
#> GSM379841     5  0.2823     0.9630 0.000 0.204 0.000 0.000 0.796 0.000
#> GSM379842     5  0.2762     0.9639 0.000 0.196 0.000 0.000 0.804 0.000
#> GSM379835     5  0.2730     0.9619 0.000 0.192 0.000 0.000 0.808 0.000
#> GSM379836     5  0.2730     0.9619 0.000 0.192 0.000 0.000 0.808 0.000
#> GSM379837     5  0.2902     0.6412 0.000 0.000 0.000 0.196 0.800 0.004
#> GSM379838     5  0.2823     0.9612 0.000 0.204 0.000 0.000 0.796 0.000
#> GSM379839     5  0.2854     0.6284 0.000 0.000 0.000 0.208 0.792 0.000
#> GSM379848     5  0.2994     0.9603 0.000 0.208 0.000 0.000 0.788 0.004
#> GSM379849     5  0.3110     0.9595 0.000 0.196 0.000 0.000 0.792 0.012
#> GSM379850     5  0.3043     0.9626 0.000 0.200 0.000 0.000 0.792 0.008
#> GSM379843     5  0.2902     0.9622 0.000 0.196 0.000 0.000 0.800 0.004
#> GSM379844     5  0.2933     0.9618 0.000 0.200 0.000 0.000 0.796 0.004
#> GSM379845     5  0.2697     0.9615 0.000 0.188 0.000 0.000 0.812 0.000
#> GSM379846     5  0.2762     0.9639 0.000 0.196 0.000 0.000 0.804 0.000
#> GSM379847     5  0.2933     0.9634 0.000 0.200 0.000 0.000 0.796 0.004
#> GSM379853     5  0.2697     0.9615 0.000 0.188 0.000 0.000 0.812 0.000
#> GSM379854     5  0.2964     0.9620 0.000 0.204 0.000 0.000 0.792 0.004
#> GSM379851     5  0.2902     0.9640 0.000 0.196 0.000 0.000 0.800 0.004
#> GSM379852     5  0.3012     0.9611 0.000 0.196 0.000 0.000 0.796 0.008
#> GSM379804     4  0.0000     0.9132 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379805     4  0.0000     0.9132 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379806     4  0.0146     0.9126 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM379799     4  0.0146     0.9126 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM379800     4  0.0146     0.9126 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM379801     4  0.0436     0.9090 0.000 0.004 0.000 0.988 0.004 0.004
#> GSM379802     4  0.0146     0.9126 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM379803     4  0.0260     0.9104 0.000 0.000 0.000 0.992 0.000 0.008
#> GSM379812     4  0.3464     0.5533 0.000 0.000 0.000 0.688 0.000 0.312
#> GSM379813     4  0.1910     0.8372 0.000 0.000 0.000 0.892 0.000 0.108
#> GSM379814     4  0.0291     0.9109 0.000 0.000 0.000 0.992 0.004 0.004
#> GSM379807     4  0.0000     0.9132 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379808     4  0.0146     0.9126 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM379809     4  0.0146     0.9126 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM379810     4  0.0000     0.9132 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379811     4  0.0000     0.9132 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379820     4  0.1970     0.8525 0.000 0.000 0.000 0.900 0.092 0.008
#> GSM379821     4  0.3866     0.0853 0.000 0.000 0.000 0.516 0.000 0.484
#> GSM379822     6  0.1701     0.9445 0.000 0.000 0.000 0.072 0.008 0.920
#> GSM379815     4  0.0000     0.9132 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379816     4  0.5733     0.2095 0.000 0.208 0.000 0.540 0.004 0.248
#> GSM379817     4  0.2376     0.8484 0.000 0.000 0.000 0.888 0.044 0.068
#> GSM379818     4  0.0000     0.9132 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379819     4  0.0000     0.9132 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379825     4  0.0000     0.9132 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379826     4  0.2309     0.8452 0.000 0.000 0.000 0.888 0.084 0.028
#> GSM379823     6  0.0713     0.9470 0.000 0.000 0.000 0.028 0.000 0.972
#> GSM379824     4  0.1663     0.8550 0.000 0.000 0.000 0.912 0.000 0.088
#> GSM379749     2  0.0363     0.9630 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379750     2  0.0458     0.9619 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379751     2  0.0260     0.9625 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379744     2  0.0260     0.9625 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379745     2  0.0260     0.9625 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379746     2  0.0458     0.9619 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379747     2  0.0260     0.9625 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379748     2  0.0260     0.9625 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379757     2  0.0520     0.9586 0.000 0.984 0.000 0.000 0.008 0.008
#> GSM379758     2  0.0363     0.9622 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379752     2  0.0363     0.9625 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379753     2  0.0260     0.9625 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379754     2  0.0363     0.9630 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379755     2  0.0458     0.9619 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379756     2  0.0260     0.9624 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379764     2  0.1838     0.8802 0.000 0.916 0.000 0.000 0.068 0.016
#> GSM379765     2  0.0260     0.9624 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379766     2  0.0458     0.9591 0.000 0.984 0.000 0.000 0.000 0.016
#> GSM379759     2  0.0622     0.9555 0.000 0.980 0.000 0.000 0.008 0.012
#> GSM379760     2  0.0260     0.9624 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379761     2  0.0363     0.9622 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379762     2  0.0363     0.9622 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379763     2  0.0363     0.9622 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379769     2  0.5362     0.3526 0.000 0.588 0.000 0.000 0.184 0.228
#> GSM379770     2  0.3098     0.7242 0.000 0.812 0.000 0.000 0.164 0.024
#> GSM379767     2  0.0458     0.9591 0.000 0.984 0.000 0.000 0.000 0.016
#> GSM379768     2  0.0363     0.9598 0.000 0.988 0.000 0.000 0.000 0.012
#> GSM379776     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379777     1  0.2482     0.7977 0.848 0.000 0.000 0.004 0.000 0.148
#> GSM379778     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379771     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379772     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379773     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379774     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379775     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379784     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379785     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379786     1  0.0632     0.9509 0.976 0.000 0.000 0.000 0.000 0.024
#> GSM379779     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379780     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379781     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379782     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379783     1  0.0260     0.9665 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM379792     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379793     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379794     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379787     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379788     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379789     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379790     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379791     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379797     1  0.3756     0.2813 0.600 0.000 0.000 0.400 0.000 0.000
#> GSM379798     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379796     1  0.0000     0.9733 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379721     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379722     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379723     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379716     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379717     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379718     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379719     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379720     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379729     3  0.1267     0.9215 0.000 0.000 0.940 0.000 0.000 0.060
#> GSM379730     3  0.2562     0.8075 0.000 0.000 0.828 0.000 0.000 0.172
#> GSM379731     3  0.1075     0.9310 0.000 0.000 0.952 0.000 0.000 0.048
#> GSM379724     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379725     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379726     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379727     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379728     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379737     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379738     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379739     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379732     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379733     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379734     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379735     3  0.1910     0.8785 0.000 0.000 0.892 0.000 0.000 0.108
#> GSM379736     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379742     3  0.4738     0.5940 0.000 0.004 0.684 0.000 0.112 0.200
#> GSM379743     3  0.2527     0.8148 0.000 0.000 0.832 0.000 0.000 0.168
#> GSM379740     3  0.0000     0.9633 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379741     3  0.2039     0.8904 0.000 0.000 0.904 0.000 0.020 0.076

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-CV-NMF-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-CV-NMF-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-CV-NMF-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-CV-NMF-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-CV-NMF-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-CV-NMF-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-CV-NMF-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-CV-NMF-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-CV-NMF-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-CV-NMF-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-NMF-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-CV-NMF-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-CV-NMF-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-CV-NMF-get-signatures-4

get_signatures(res, k = 6)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-NMF-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-CV-NMF-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-CV-NMF-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-CV-NMF-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-CV-NMF-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-CV-NMF-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk CV-NMF-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-CV-NMF-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-CV-NMF-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-CV-NMF-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-CV-NMF-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-CV-NMF-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk CV-NMF-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>          n individual(p) time(p) agent(p) k
#> CV:NMF 138      1.25e-22       1    0.820 2
#> CV:NMF  98      8.68e-37       1    0.293 3
#> CV:NMF 132      1.98e-68       1    0.726 4
#> CV:NMF 133      1.90e-72       1    0.738 5
#> CV:NMF 135      1.25e-99       1    0.909 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

MAD:hclust

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["MAD", "hclust"]
# you can also extract it by
# res = res_list["MAD:hclust"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#>   Subgroups are detected by 'hclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 3.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk MAD-hclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk MAD-hclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.370           0.795       0.840         0.4272 0.515   0.515
#> 3 3 0.607           0.756       0.864         0.4494 0.831   0.675
#> 4 4 0.698           0.597       0.794         0.1365 0.962   0.895
#> 5 5 0.781           0.648       0.817         0.0454 0.932   0.801
#> 6 6 0.825           0.776       0.846         0.0355 0.937   0.784

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 3

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000     0.9426 0.000 1.000
#> GSM379833     2  0.0000     0.9426 0.000 1.000
#> GSM379834     2  0.0000     0.9426 0.000 1.000
#> GSM379827     2  0.5737     0.7755 0.136 0.864
#> GSM379828     2  0.5737     0.7755 0.136 0.864
#> GSM379829     1  0.7219     0.7644 0.800 0.200
#> GSM379830     2  0.4431     0.8392 0.092 0.908
#> GSM379831     2  0.3431     0.8744 0.064 0.936
#> GSM379840     1  0.9909     0.4193 0.556 0.444
#> GSM379841     2  0.0000     0.9426 0.000 1.000
#> GSM379842     2  0.0000     0.9426 0.000 1.000
#> GSM379835     2  0.5946     0.7618 0.144 0.856
#> GSM379836     2  0.5946     0.7618 0.144 0.856
#> GSM379837     1  0.8661     0.7250 0.712 0.288
#> GSM379838     2  0.0000     0.9426 0.000 1.000
#> GSM379839     1  0.8661     0.7250 0.712 0.288
#> GSM379848     2  0.0000     0.9426 0.000 1.000
#> GSM379849     2  0.0000     0.9426 0.000 1.000
#> GSM379850     2  0.0000     0.9426 0.000 1.000
#> GSM379843     2  0.0000     0.9426 0.000 1.000
#> GSM379844     2  0.0000     0.9426 0.000 1.000
#> GSM379845     1  0.8661     0.7250 0.712 0.288
#> GSM379846     2  0.0000     0.9426 0.000 1.000
#> GSM379847     2  0.0000     0.9426 0.000 1.000
#> GSM379853     2  0.0000     0.9426 0.000 1.000
#> GSM379854     2  0.0000     0.9426 0.000 1.000
#> GSM379851     2  0.0000     0.9426 0.000 1.000
#> GSM379852     2  0.0000     0.9426 0.000 1.000
#> GSM379804     1  0.1184     0.7107 0.984 0.016
#> GSM379805     1  0.1184     0.7107 0.984 0.016
#> GSM379806     1  0.0672     0.7056 0.992 0.008
#> GSM379799     1  0.0000     0.6995 1.000 0.000
#> GSM379800     1  0.0000     0.6995 1.000 0.000
#> GSM379801     1  0.0000     0.6995 1.000 0.000
#> GSM379802     1  0.0000     0.6995 1.000 0.000
#> GSM379803     1  0.0672     0.7056 0.992 0.008
#> GSM379812     1  0.6887     0.7784 0.816 0.184
#> GSM379813     1  0.6438     0.7716 0.836 0.164
#> GSM379814     1  0.1843     0.7175 0.972 0.028
#> GSM379807     1  0.1843     0.7175 0.972 0.028
#> GSM379808     1  0.0672     0.7056 0.992 0.008
#> GSM379809     1  0.1184     0.7107 0.984 0.016
#> GSM379810     1  0.1184     0.7107 0.984 0.016
#> GSM379811     1  0.0672     0.7056 0.992 0.008
#> GSM379820     1  0.1843     0.7175 0.972 0.028
#> GSM379821     1  0.6801     0.7789 0.820 0.180
#> GSM379822     1  0.6887     0.7784 0.816 0.184
#> GSM379815     1  0.1843     0.7175 0.972 0.028
#> GSM379816     1  0.6973     0.7793 0.812 0.188
#> GSM379817     1  0.4022     0.7379 0.920 0.080
#> GSM379818     1  0.0000     0.6995 1.000 0.000
#> GSM379819     1  0.1843     0.7175 0.972 0.028
#> GSM379825     1  0.0000     0.6995 1.000 0.000
#> GSM379826     1  0.1843     0.7175 0.972 0.028
#> GSM379823     1  0.6887     0.7784 0.816 0.184
#> GSM379824     1  0.6801     0.7789 0.820 0.180
#> GSM379749     2  0.0000     0.9426 0.000 1.000
#> GSM379750     2  0.0000     0.9426 0.000 1.000
#> GSM379751     2  0.0000     0.9426 0.000 1.000
#> GSM379744     2  0.0000     0.9426 0.000 1.000
#> GSM379745     2  0.0000     0.9426 0.000 1.000
#> GSM379746     2  0.0000     0.9426 0.000 1.000
#> GSM379747     2  0.0000     0.9426 0.000 1.000
#> GSM379748     2  0.0000     0.9426 0.000 1.000
#> GSM379757     2  0.0000     0.9426 0.000 1.000
#> GSM379758     2  0.0000     0.9426 0.000 1.000
#> GSM379752     2  0.0000     0.9426 0.000 1.000
#> GSM379753     2  0.0000     0.9426 0.000 1.000
#> GSM379754     2  0.0000     0.9426 0.000 1.000
#> GSM379755     2  0.0000     0.9426 0.000 1.000
#> GSM379756     2  0.0000     0.9426 0.000 1.000
#> GSM379764     2  0.0000     0.9426 0.000 1.000
#> GSM379765     2  0.0000     0.9426 0.000 1.000
#> GSM379766     2  0.0000     0.9426 0.000 1.000
#> GSM379759     2  0.0000     0.9426 0.000 1.000
#> GSM379760     2  0.0000     0.9426 0.000 1.000
#> GSM379761     2  0.0000     0.9426 0.000 1.000
#> GSM379762     2  0.0000     0.9426 0.000 1.000
#> GSM379763     2  0.0000     0.9426 0.000 1.000
#> GSM379769     2  0.0000     0.9426 0.000 1.000
#> GSM379770     2  0.0000     0.9426 0.000 1.000
#> GSM379767     2  0.0000     0.9426 0.000 1.000
#> GSM379768     2  0.0000     0.9426 0.000 1.000
#> GSM379776     1  0.9000     0.7810 0.684 0.316
#> GSM379777     1  0.7602     0.7859 0.780 0.220
#> GSM379778     2  0.7219     0.6437 0.200 0.800
#> GSM379771     1  0.9000     0.7810 0.684 0.316
#> GSM379772     1  0.9000     0.7810 0.684 0.316
#> GSM379773     2  0.9754    -0.0831 0.408 0.592
#> GSM379774     1  0.9000     0.7810 0.684 0.316
#> GSM379775     1  0.9000     0.7810 0.684 0.316
#> GSM379784     1  0.7602     0.7859 0.780 0.220
#> GSM379785     1  0.8763     0.7847 0.704 0.296
#> GSM379786     1  0.7602     0.7859 0.780 0.220
#> GSM379779     1  0.9000     0.7810 0.684 0.316
#> GSM379780     1  0.9000     0.7810 0.684 0.316
#> GSM379781     1  0.8763     0.7847 0.704 0.296
#> GSM379782     2  0.7219     0.6437 0.200 0.800
#> GSM379783     1  0.7602     0.7859 0.780 0.220
#> GSM379792     1  0.8144     0.7880 0.748 0.252
#> GSM379793     1  0.9000     0.7810 0.684 0.316
#> GSM379794     1  0.9000     0.7810 0.684 0.316
#> GSM379787     2  0.7219     0.6437 0.200 0.800
#> GSM379788     1  0.7602     0.7859 0.780 0.220
#> GSM379789     1  0.9000     0.7810 0.684 0.316
#> GSM379790     1  0.9000     0.7810 0.684 0.316
#> GSM379791     1  0.9000     0.7810 0.684 0.316
#> GSM379797     1  0.0000     0.6995 1.000 0.000
#> GSM379798     1  0.9000     0.7810 0.684 0.316
#> GSM379795     1  0.9000     0.7810 0.684 0.316
#> GSM379796     1  0.8144     0.7880 0.748 0.252
#> GSM379721     1  0.9754     0.7144 0.592 0.408
#> GSM379722     1  0.9754     0.7144 0.592 0.408
#> GSM379723     1  0.9754     0.7144 0.592 0.408
#> GSM379716     1  0.9754     0.7144 0.592 0.408
#> GSM379717     1  0.9754     0.7144 0.592 0.408
#> GSM379718     1  0.9754     0.7144 0.592 0.408
#> GSM379719     1  0.9754     0.7144 0.592 0.408
#> GSM379720     1  0.9754     0.7144 0.592 0.408
#> GSM379729     1  0.9635     0.7333 0.612 0.388
#> GSM379730     1  0.9635     0.7333 0.612 0.388
#> GSM379731     1  0.9635     0.7333 0.612 0.388
#> GSM379724     1  0.9754     0.7144 0.592 0.408
#> GSM379725     1  0.9710     0.7224 0.600 0.400
#> GSM379726     1  0.9754     0.7144 0.592 0.408
#> GSM379727     1  0.9754     0.7144 0.592 0.408
#> GSM379728     1  0.9754     0.7144 0.592 0.408
#> GSM379737     1  0.9754     0.7144 0.592 0.408
#> GSM379738     1  0.9754     0.7144 0.592 0.408
#> GSM379739     1  0.9754     0.7144 0.592 0.408
#> GSM379732     1  0.9635     0.7333 0.612 0.388
#> GSM379733     1  0.9754     0.7144 0.592 0.408
#> GSM379734     1  0.9754     0.7144 0.592 0.408
#> GSM379735     1  0.9635     0.7333 0.612 0.388
#> GSM379736     1  0.9754     0.7144 0.592 0.408
#> GSM379742     2  0.7219     0.6437 0.200 0.800
#> GSM379743     1  0.9635     0.7333 0.612 0.388
#> GSM379740     1  0.9754     0.7144 0.592 0.408
#> GSM379741     2  0.7219     0.6437 0.200 0.800

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0592     0.9091 0.000 0.988 0.012
#> GSM379833     2  0.0592     0.9091 0.000 0.988 0.012
#> GSM379834     2  0.0592     0.9091 0.000 0.988 0.012
#> GSM379827     2  0.5785     0.5669 0.000 0.668 0.332
#> GSM379828     2  0.5785     0.5669 0.000 0.668 0.332
#> GSM379829     1  0.6252     0.3373 0.556 0.000 0.444
#> GSM379830     2  0.5465     0.6292 0.000 0.712 0.288
#> GSM379831     2  0.5098     0.6789 0.000 0.752 0.248
#> GSM379840     3  0.9722    -0.0543 0.312 0.244 0.444
#> GSM379841     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379842     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379835     2  0.5835     0.5524 0.000 0.660 0.340
#> GSM379836     2  0.5835     0.5524 0.000 0.660 0.340
#> GSM379837     1  0.8277     0.2415 0.468 0.076 0.456
#> GSM379838     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379839     1  0.8277     0.2415 0.468 0.076 0.456
#> GSM379848     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379849     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379850     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379843     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379844     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379845     1  0.8277     0.2415 0.468 0.076 0.456
#> GSM379846     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379847     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379853     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379854     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379851     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379852     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379804     1  0.4002     0.7788 0.840 0.000 0.160
#> GSM379805     1  0.4002     0.7788 0.840 0.000 0.160
#> GSM379806     1  0.3686     0.7788 0.860 0.000 0.140
#> GSM379799     1  0.0424     0.7355 0.992 0.000 0.008
#> GSM379800     1  0.0424     0.7355 0.992 0.000 0.008
#> GSM379801     1  0.0424     0.7355 0.992 0.000 0.008
#> GSM379802     1  0.0000     0.7370 1.000 0.000 0.000
#> GSM379803     1  0.3941     0.7796 0.844 0.000 0.156
#> GSM379812     3  0.6148     0.4375 0.356 0.004 0.640
#> GSM379813     1  0.6518     0.1411 0.512 0.004 0.484
#> GSM379814     1  0.5216     0.7162 0.740 0.000 0.260
#> GSM379807     1  0.5216     0.7162 0.740 0.000 0.260
#> GSM379808     1  0.3686     0.7788 0.860 0.000 0.140
#> GSM379809     1  0.4002     0.7788 0.840 0.000 0.160
#> GSM379810     1  0.4002     0.7788 0.840 0.000 0.160
#> GSM379811     1  0.3816     0.7791 0.852 0.000 0.148
#> GSM379820     1  0.5397     0.6924 0.720 0.000 0.280
#> GSM379821     3  0.5882     0.4735 0.348 0.000 0.652
#> GSM379822     3  0.6081     0.4772 0.344 0.004 0.652
#> GSM379815     1  0.5216     0.7162 0.740 0.000 0.260
#> GSM379816     3  0.6057     0.4867 0.340 0.004 0.656
#> GSM379817     1  0.6228     0.5158 0.624 0.004 0.372
#> GSM379818     1  0.0000     0.7370 1.000 0.000 0.000
#> GSM379819     1  0.5397     0.6924 0.720 0.000 0.280
#> GSM379825     1  0.0000     0.7370 1.000 0.000 0.000
#> GSM379826     1  0.5397     0.6924 0.720 0.000 0.280
#> GSM379823     3  0.6081     0.4772 0.344 0.004 0.652
#> GSM379824     3  0.5882     0.4735 0.348 0.000 0.652
#> GSM379749     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379750     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379751     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379744     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379745     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379746     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379747     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379748     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379757     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379758     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379752     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379753     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379754     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379755     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379756     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379764     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379765     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379766     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379759     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379760     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379761     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379762     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379763     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379769     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379770     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379767     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379768     2  0.0000     0.9188 0.000 1.000 0.000
#> GSM379776     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379777     3  0.5244     0.6866 0.240 0.004 0.756
#> GSM379778     2  0.7097     0.5488 0.052 0.668 0.280
#> GSM379771     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379772     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379773     3  0.9086     0.2826 0.148 0.356 0.496
#> GSM379774     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379775     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379784     3  0.5244     0.6866 0.240 0.004 0.756
#> GSM379785     3  0.5574     0.7698 0.184 0.032 0.784
#> GSM379786     3  0.5244     0.6866 0.240 0.004 0.756
#> GSM379779     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379780     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379781     3  0.5574     0.7698 0.184 0.032 0.784
#> GSM379782     2  0.7097     0.5488 0.052 0.668 0.280
#> GSM379783     3  0.5244     0.6866 0.240 0.004 0.756
#> GSM379792     3  0.6264     0.7056 0.256 0.028 0.716
#> GSM379793     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379794     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379787     2  0.7097     0.5488 0.052 0.668 0.280
#> GSM379788     3  0.5244     0.6866 0.240 0.004 0.756
#> GSM379789     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379790     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379791     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379797     1  0.0000     0.7370 1.000 0.000 0.000
#> GSM379798     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379795     3  0.5060     0.7938 0.156 0.028 0.816
#> GSM379796     3  0.6264     0.7056 0.256 0.028 0.716
#> GSM379721     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379722     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379723     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379716     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379717     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379718     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379719     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379720     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379729     3  0.2318     0.8075 0.028 0.028 0.944
#> GSM379730     3  0.2318     0.8075 0.028 0.028 0.944
#> GSM379731     3  0.2318     0.8075 0.028 0.028 0.944
#> GSM379724     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379725     3  0.1751     0.8081 0.012 0.028 0.960
#> GSM379726     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379727     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379728     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379737     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379738     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379739     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379732     3  0.2318     0.8075 0.028 0.028 0.944
#> GSM379733     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379734     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379735     3  0.2318     0.8075 0.028 0.028 0.944
#> GSM379736     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379742     2  0.6244     0.3146 0.000 0.560 0.440
#> GSM379743     3  0.2318     0.8075 0.028 0.028 0.944
#> GSM379740     3  0.1399     0.8074 0.004 0.028 0.968
#> GSM379741     2  0.6244     0.3146 0.000 0.560 0.440

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.0469     0.9110 0.000 0.988 0.012 0.000
#> GSM379833     2  0.0469     0.9110 0.000 0.988 0.012 0.000
#> GSM379834     2  0.0469     0.9110 0.000 0.988 0.012 0.000
#> GSM379827     2  0.6472     0.6015 0.172 0.668 0.152 0.008
#> GSM379828     2  0.6472     0.6015 0.172 0.668 0.152 0.008
#> GSM379829     4  0.7594     0.3840 0.264 0.000 0.256 0.480
#> GSM379830     2  0.5991     0.6547 0.148 0.712 0.132 0.008
#> GSM379831     2  0.5492     0.6972 0.128 0.752 0.112 0.008
#> GSM379840     4  0.9938     0.1818 0.204 0.244 0.256 0.296
#> GSM379841     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379842     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379835     2  0.6556     0.5919 0.172 0.660 0.160 0.008
#> GSM379836     2  0.6556     0.5919 0.172 0.660 0.160 0.008
#> GSM379837     4  0.8952     0.3524 0.216 0.076 0.268 0.440
#> GSM379838     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379839     4  0.8952     0.3524 0.216 0.076 0.268 0.440
#> GSM379848     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379849     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379850     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379843     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379844     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379845     4  0.8952     0.3524 0.216 0.076 0.268 0.440
#> GSM379846     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379847     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379853     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379854     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379851     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379852     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379804     4  0.2861     0.7073 0.016 0.000 0.096 0.888
#> GSM379805     4  0.2861     0.7073 0.016 0.000 0.096 0.888
#> GSM379806     4  0.2266     0.7096 0.004 0.000 0.084 0.912
#> GSM379799     4  0.1940     0.6769 0.076 0.000 0.000 0.924
#> GSM379800     4  0.1940     0.6769 0.076 0.000 0.000 0.924
#> GSM379801     4  0.1940     0.6769 0.076 0.000 0.000 0.924
#> GSM379802     4  0.2271     0.6805 0.076 0.000 0.008 0.916
#> GSM379803     4  0.3245     0.7037 0.028 0.000 0.100 0.872
#> GSM379812     3  0.7370    -0.8993 0.412 0.000 0.428 0.160
#> GSM379813     3  0.7668    -0.6390 0.220 0.000 0.432 0.348
#> GSM379814     4  0.5839     0.5826 0.104 0.000 0.200 0.696
#> GSM379807     4  0.5839     0.5826 0.104 0.000 0.200 0.696
#> GSM379808     4  0.2266     0.7096 0.004 0.000 0.084 0.912
#> GSM379809     4  0.3080     0.7059 0.024 0.000 0.096 0.880
#> GSM379810     4  0.3080     0.7059 0.024 0.000 0.096 0.880
#> GSM379811     4  0.2610     0.7083 0.012 0.000 0.088 0.900
#> GSM379820     4  0.6127     0.5372 0.108 0.000 0.228 0.664
#> GSM379821     1  0.7076     0.9903 0.460 0.000 0.416 0.124
#> GSM379822     1  0.7037     0.9885 0.464 0.000 0.416 0.120
#> GSM379815     4  0.5839     0.5826 0.104 0.000 0.200 0.696
#> GSM379816     3  0.6705    -0.9019 0.440 0.000 0.472 0.088
#> GSM379817     4  0.7254     0.1869 0.176 0.000 0.300 0.524
#> GSM379818     4  0.2271     0.6805 0.076 0.000 0.008 0.916
#> GSM379819     4  0.6127     0.5372 0.108 0.000 0.228 0.664
#> GSM379825     4  0.2271     0.6805 0.076 0.000 0.008 0.916
#> GSM379826     4  0.6127     0.5372 0.108 0.000 0.228 0.664
#> GSM379823     1  0.7044     0.9770 0.452 0.000 0.428 0.120
#> GSM379824     1  0.7076     0.9903 0.460 0.000 0.416 0.124
#> GSM379749     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379750     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379751     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379744     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379745     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379746     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379747     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379748     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379757     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379758     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379752     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379753     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379754     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379755     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379756     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379764     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379765     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379766     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379759     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379760     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379761     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379762     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379763     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379769     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379770     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379767     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379768     2  0.0000     0.9202 0.000 1.000 0.000 0.000
#> GSM379776     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379777     3  0.6491    -0.7905 0.396 0.000 0.528 0.076
#> GSM379778     2  0.4713     0.4916 0.000 0.640 0.360 0.000
#> GSM379771     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379772     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379773     3  0.4564    -0.0531 0.000 0.328 0.672 0.000
#> GSM379774     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379775     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379784     3  0.6491    -0.7905 0.396 0.000 0.528 0.076
#> GSM379785     3  0.1867     0.3061 0.072 0.000 0.928 0.000
#> GSM379786     3  0.6491    -0.7905 0.396 0.000 0.528 0.076
#> GSM379779     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379780     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379781     3  0.1867     0.3061 0.072 0.000 0.928 0.000
#> GSM379782     2  0.4713     0.4916 0.000 0.640 0.360 0.000
#> GSM379783     3  0.6491    -0.7905 0.396 0.000 0.528 0.076
#> GSM379792     3  0.2408     0.3313 0.000 0.000 0.896 0.104
#> GSM379793     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379794     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379787     2  0.4713     0.4916 0.000 0.640 0.360 0.000
#> GSM379788     3  0.6491    -0.7905 0.396 0.000 0.528 0.076
#> GSM379789     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379790     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379791     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379797     4  0.2271     0.6805 0.076 0.000 0.008 0.916
#> GSM379798     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379795     3  0.0000     0.4339 0.000 0.000 1.000 0.000
#> GSM379796     3  0.2408     0.3313 0.000 0.000 0.896 0.104
#> GSM379721     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379722     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379723     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379716     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379717     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379718     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379719     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379720     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379729     3  0.4948     0.6159 0.440 0.000 0.560 0.000
#> GSM379730     3  0.4948     0.6159 0.440 0.000 0.560 0.000
#> GSM379731     3  0.4948     0.6159 0.440 0.000 0.560 0.000
#> GSM379724     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379725     3  0.4898     0.6286 0.416 0.000 0.584 0.000
#> GSM379726     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379727     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379728     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379737     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379738     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379739     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379732     3  0.4948     0.6159 0.440 0.000 0.560 0.000
#> GSM379733     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379734     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379735     3  0.4948     0.6159 0.440 0.000 0.560 0.000
#> GSM379736     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379742     2  0.7281     0.2719 0.272 0.532 0.196 0.000
#> GSM379743     3  0.4948     0.6159 0.440 0.000 0.560 0.000
#> GSM379740     3  0.4955     0.6339 0.444 0.000 0.556 0.000
#> GSM379741     2  0.7281     0.2719 0.272 0.532 0.196 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     2  0.1544     0.8617 0.000 0.932 0.000 0.000 0.068
#> GSM379833     2  0.1544     0.8617 0.000 0.932 0.000 0.000 0.068
#> GSM379834     2  0.1544     0.8617 0.000 0.932 0.000 0.000 0.068
#> GSM379827     2  0.4150     0.4265 0.000 0.612 0.000 0.000 0.388
#> GSM379828     2  0.4150     0.4265 0.000 0.612 0.000 0.000 0.388
#> GSM379829     5  0.4485     0.7781 0.000 0.000 0.028 0.292 0.680
#> GSM379830     2  0.3999     0.5111 0.000 0.656 0.000 0.000 0.344
#> GSM379831     2  0.3816     0.5776 0.000 0.696 0.000 0.000 0.304
#> GSM379840     5  0.5310     0.6558 0.000 0.188 0.028 0.076 0.708
#> GSM379841     2  0.0510     0.8960 0.000 0.984 0.000 0.000 0.016
#> GSM379842     2  0.1043     0.8819 0.000 0.960 0.000 0.000 0.040
#> GSM379835     2  0.4171     0.4092 0.000 0.604 0.000 0.000 0.396
#> GSM379836     2  0.4171     0.4092 0.000 0.604 0.000 0.000 0.396
#> GSM379837     5  0.4473     0.8738 0.000 0.020 0.028 0.204 0.748
#> GSM379838     2  0.0510     0.8960 0.000 0.984 0.000 0.000 0.016
#> GSM379839     5  0.4473     0.8738 0.000 0.020 0.028 0.204 0.748
#> GSM379848     2  0.0510     0.8960 0.000 0.984 0.000 0.000 0.016
#> GSM379849     2  0.0510     0.8960 0.000 0.984 0.000 0.000 0.016
#> GSM379850     2  0.0510     0.8960 0.000 0.984 0.000 0.000 0.016
#> GSM379843     2  0.0510     0.8960 0.000 0.984 0.000 0.000 0.016
#> GSM379844     2  0.0510     0.8960 0.000 0.984 0.000 0.000 0.016
#> GSM379845     5  0.4473     0.8738 0.000 0.020 0.028 0.204 0.748
#> GSM379846     2  0.0510     0.8960 0.000 0.984 0.000 0.000 0.016
#> GSM379847     2  0.0510     0.8960 0.000 0.984 0.000 0.000 0.016
#> GSM379853     2  0.1043     0.8819 0.000 0.960 0.000 0.000 0.040
#> GSM379854     2  0.0510     0.8960 0.000 0.984 0.000 0.000 0.016
#> GSM379851     2  0.0510     0.8960 0.000 0.984 0.000 0.000 0.016
#> GSM379852     2  0.0510     0.8960 0.000 0.984 0.000 0.000 0.016
#> GSM379804     4  0.3857     0.7716 0.132 0.000 0.048 0.812 0.008
#> GSM379805     4  0.3857     0.7716 0.132 0.000 0.048 0.812 0.008
#> GSM379806     4  0.3548     0.7686 0.112 0.000 0.044 0.836 0.008
#> GSM379799     4  0.0404     0.6754 0.000 0.000 0.000 0.988 0.012
#> GSM379800     4  0.0404     0.6754 0.000 0.000 0.000 0.988 0.012
#> GSM379801     4  0.0404     0.6754 0.000 0.000 0.000 0.988 0.012
#> GSM379802     4  0.2891     0.5601 0.000 0.000 0.000 0.824 0.176
#> GSM379803     4  0.3880     0.7698 0.152 0.000 0.044 0.800 0.004
#> GSM379812     1  0.2313     0.6428 0.916 0.000 0.032 0.040 0.012
#> GSM379813     1  0.4954     0.3403 0.700 0.000 0.052 0.236 0.012
#> GSM379814     4  0.5465     0.6701 0.320 0.000 0.056 0.612 0.012
#> GSM379807     4  0.5465     0.6701 0.320 0.000 0.056 0.612 0.012
#> GSM379808     4  0.3548     0.7686 0.112 0.000 0.044 0.836 0.008
#> GSM379809     4  0.3946     0.7710 0.140 0.000 0.048 0.804 0.008
#> GSM379810     4  0.3946     0.7710 0.140 0.000 0.048 0.804 0.008
#> GSM379811     4  0.3570     0.7709 0.124 0.000 0.044 0.828 0.004
#> GSM379820     4  0.5615     0.6106 0.364 0.000 0.056 0.568 0.012
#> GSM379821     1  0.0671     0.6593 0.980 0.000 0.000 0.004 0.016
#> GSM379822     1  0.0510     0.6591 0.984 0.000 0.000 0.000 0.016
#> GSM379815     4  0.5465     0.6701 0.320 0.000 0.056 0.612 0.012
#> GSM379816     1  0.1965     0.6636 0.924 0.000 0.052 0.000 0.024
#> GSM379817     1  0.5680    -0.3289 0.508 0.000 0.052 0.428 0.012
#> GSM379818     4  0.2891     0.5601 0.000 0.000 0.000 0.824 0.176
#> GSM379819     4  0.5615     0.6106 0.364 0.000 0.056 0.568 0.012
#> GSM379825     4  0.0162     0.6763 0.000 0.000 0.000 0.996 0.004
#> GSM379826     4  0.5615     0.6106 0.364 0.000 0.056 0.568 0.012
#> GSM379823     1  0.0898     0.6641 0.972 0.000 0.008 0.000 0.020
#> GSM379824     1  0.0671     0.6593 0.980 0.000 0.000 0.004 0.016
#> GSM379749     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379750     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379751     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379744     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379745     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379746     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379747     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379748     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379757     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379758     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379752     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379753     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379754     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379755     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379756     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379764     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379765     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379766     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379759     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379760     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379761     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379762     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379763     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379769     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379770     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379767     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379768     2  0.0000     0.8995 0.000 1.000 0.000 0.000 0.000
#> GSM379776     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379777     1  0.3002     0.6790 0.856 0.000 0.028 0.000 0.116
#> GSM379778     2  0.6368     0.4037 0.088 0.640 0.088 0.000 0.184
#> GSM379771     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379772     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379773     1  0.8372     0.1468 0.336 0.328 0.144 0.004 0.188
#> GSM379774     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379775     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379784     1  0.3002     0.6790 0.856 0.000 0.028 0.000 0.116
#> GSM379785     1  0.6588    -0.0151 0.452 0.000 0.360 0.004 0.184
#> GSM379786     1  0.3002     0.6790 0.856 0.000 0.028 0.000 0.116
#> GSM379779     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379780     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379781     1  0.6588    -0.0151 0.452 0.000 0.360 0.004 0.184
#> GSM379782     2  0.6368     0.4037 0.088 0.640 0.088 0.000 0.184
#> GSM379783     1  0.3002     0.6790 0.856 0.000 0.028 0.000 0.116
#> GSM379792     3  0.7905     0.0193 0.352 0.000 0.376 0.108 0.164
#> GSM379793     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379794     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379787     2  0.6368     0.4037 0.088 0.640 0.088 0.000 0.184
#> GSM379788     1  0.3002     0.6790 0.856 0.000 0.028 0.000 0.116
#> GSM379789     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379790     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379791     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379797     4  0.2891     0.5601 0.000 0.000 0.000 0.824 0.176
#> GSM379798     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379795     3  0.6651     0.1676 0.380 0.000 0.424 0.004 0.192
#> GSM379796     3  0.7905     0.0193 0.352 0.000 0.376 0.108 0.164
#> GSM379721     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379722     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379723     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379716     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379717     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379718     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379719     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379720     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379729     3  0.1914     0.6711 0.060 0.000 0.924 0.000 0.016
#> GSM379730     3  0.1914     0.6711 0.060 0.000 0.924 0.000 0.016
#> GSM379731     3  0.1914     0.6711 0.060 0.000 0.924 0.000 0.016
#> GSM379724     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379725     3  0.1117     0.6879 0.020 0.000 0.964 0.000 0.016
#> GSM379726     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379727     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379728     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379737     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379738     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379739     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379732     3  0.1914     0.6711 0.060 0.000 0.924 0.000 0.016
#> GSM379733     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379734     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379735     3  0.1914     0.6711 0.060 0.000 0.924 0.000 0.016
#> GSM379736     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379742     2  0.5143     0.2017 0.000 0.532 0.428 0.000 0.040
#> GSM379743     3  0.1914     0.6711 0.060 0.000 0.924 0.000 0.016
#> GSM379740     3  0.0000     0.6984 0.000 0.000 1.000 0.000 0.000
#> GSM379741     2  0.5143     0.2017 0.000 0.532 0.428 0.000 0.040

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     2  0.1610      0.850 0.000 0.916 0.000 0.000 0.084 0.000
#> GSM379833     2  0.1610      0.850 0.000 0.916 0.000 0.000 0.084 0.000
#> GSM379834     2  0.1610      0.850 0.000 0.916 0.000 0.000 0.084 0.000
#> GSM379827     2  0.3765      0.396 0.000 0.596 0.000 0.000 0.404 0.000
#> GSM379828     2  0.3765      0.396 0.000 0.596 0.000 0.000 0.404 0.000
#> GSM379829     5  0.2178      0.814 0.000 0.000 0.000 0.132 0.868 0.000
#> GSM379830     2  0.3647      0.485 0.000 0.640 0.000 0.000 0.360 0.000
#> GSM379831     2  0.3499      0.555 0.000 0.680 0.000 0.000 0.320 0.000
#> GSM379840     5  0.2980      0.652 0.000 0.180 0.000 0.012 0.808 0.000
#> GSM379841     2  0.0547      0.892 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379842     2  0.1075      0.876 0.000 0.952 0.000 0.000 0.048 0.000
#> GSM379835     2  0.3782      0.378 0.000 0.588 0.000 0.000 0.412 0.000
#> GSM379836     2  0.3782      0.378 0.000 0.588 0.000 0.000 0.412 0.000
#> GSM379837     5  0.1219      0.885 0.000 0.004 0.000 0.048 0.948 0.000
#> GSM379838     2  0.0547      0.892 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379839     5  0.1219      0.885 0.000 0.004 0.000 0.048 0.948 0.000
#> GSM379848     2  0.0547      0.892 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379849     2  0.0547      0.892 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379850     2  0.0547      0.892 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379843     2  0.0547      0.892 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379844     2  0.0547      0.892 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379845     5  0.1219      0.885 0.000 0.004 0.000 0.048 0.948 0.000
#> GSM379846     2  0.0547      0.892 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379847     2  0.0547      0.892 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379853     2  0.1075      0.876 0.000 0.952 0.000 0.000 0.048 0.000
#> GSM379854     2  0.0547      0.892 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379851     2  0.0547      0.892 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379852     2  0.0547      0.892 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379804     4  0.3430      0.764 0.056 0.000 0.012 0.832 0.004 0.096
#> GSM379805     4  0.3430      0.764 0.056 0.000 0.012 0.832 0.004 0.096
#> GSM379806     4  0.3103      0.765 0.048 0.000 0.012 0.856 0.004 0.080
#> GSM379799     4  0.1074      0.705 0.028 0.000 0.000 0.960 0.012 0.000
#> GSM379800     4  0.1074      0.705 0.028 0.000 0.000 0.960 0.012 0.000
#> GSM379801     4  0.1074      0.705 0.028 0.000 0.000 0.960 0.012 0.000
#> GSM379802     4  0.4168      0.531 0.256 0.000 0.000 0.696 0.048 0.000
#> GSM379803     4  0.3438      0.760 0.048 0.000 0.012 0.820 0.000 0.120
#> GSM379812     6  0.2675      0.739 0.052 0.000 0.004 0.060 0.004 0.880
#> GSM379813     6  0.4866      0.403 0.064 0.000 0.012 0.256 0.004 0.664
#> GSM379814     4  0.5053      0.610 0.068 0.000 0.012 0.632 0.004 0.284
#> GSM379807     4  0.5053      0.610 0.068 0.000 0.012 0.632 0.004 0.284
#> GSM379808     4  0.3103      0.765 0.048 0.000 0.012 0.856 0.004 0.080
#> GSM379809     4  0.3524      0.762 0.056 0.000 0.012 0.824 0.004 0.104
#> GSM379810     4  0.3524      0.762 0.056 0.000 0.012 0.824 0.004 0.104
#> GSM379811     4  0.3115      0.765 0.048 0.000 0.012 0.848 0.000 0.092
#> GSM379820     4  0.5223      0.542 0.068 0.000 0.012 0.588 0.004 0.328
#> GSM379821     6  0.0146      0.791 0.000 0.000 0.000 0.004 0.000 0.996
#> GSM379822     6  0.0000      0.788 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM379815     4  0.5053      0.610 0.068 0.000 0.012 0.632 0.004 0.284
#> GSM379816     6  0.1636      0.757 0.024 0.000 0.036 0.000 0.004 0.936
#> GSM379817     6  0.5387     -0.260 0.064 0.000 0.012 0.448 0.004 0.472
#> GSM379818     4  0.4168      0.531 0.256 0.000 0.000 0.696 0.048 0.000
#> GSM379819     4  0.5223      0.542 0.068 0.000 0.012 0.588 0.004 0.328
#> GSM379825     4  0.1556      0.700 0.080 0.000 0.000 0.920 0.000 0.000
#> GSM379826     4  0.5223      0.542 0.068 0.000 0.012 0.588 0.004 0.328
#> GSM379823     6  0.0363      0.791 0.012 0.000 0.000 0.000 0.000 0.988
#> GSM379824     6  0.0146      0.791 0.000 0.000 0.000 0.004 0.000 0.996
#> GSM379749     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379750     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379751     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379744     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379745     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379746     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379747     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379748     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379757     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379758     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379752     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379753     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379754     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379755     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379756     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379764     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379765     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379766     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379759     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379760     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379761     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379762     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379763     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379769     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379770     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379767     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379768     2  0.0000      0.896 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379776     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379777     1  0.3862      0.259 0.524 0.000 0.000 0.000 0.000 0.476
#> GSM379778     2  0.3672      0.432 0.368 0.632 0.000 0.000 0.000 0.000
#> GSM379771     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379772     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379773     1  0.4348      0.330 0.640 0.320 0.040 0.000 0.000 0.000
#> GSM379774     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379775     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379784     1  0.3862      0.259 0.524 0.000 0.000 0.000 0.000 0.476
#> GSM379785     1  0.4516      0.797 0.668 0.000 0.260 0.000 0.000 0.072
#> GSM379786     1  0.3862      0.259 0.524 0.000 0.000 0.000 0.000 0.476
#> GSM379779     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379780     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379781     1  0.4516      0.797 0.668 0.000 0.260 0.000 0.000 0.072
#> GSM379782     2  0.3672      0.432 0.368 0.632 0.000 0.000 0.000 0.000
#> GSM379783     1  0.3862      0.259 0.524 0.000 0.000 0.000 0.000 0.476
#> GSM379792     1  0.4895      0.760 0.632 0.000 0.264 0.104 0.000 0.000
#> GSM379793     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379794     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379787     2  0.3672      0.432 0.368 0.632 0.000 0.000 0.000 0.000
#> GSM379788     1  0.3862      0.259 0.524 0.000 0.000 0.000 0.000 0.476
#> GSM379789     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379790     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379791     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379797     4  0.4168      0.531 0.256 0.000 0.000 0.696 0.048 0.000
#> GSM379798     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379795     1  0.3221      0.835 0.736 0.000 0.264 0.000 0.000 0.000
#> GSM379796     1  0.4895      0.760 0.632 0.000 0.264 0.104 0.000 0.000
#> GSM379721     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379722     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379723     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379716     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379717     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379718     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379719     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379720     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379729     3  0.1644      0.930 0.004 0.000 0.920 0.000 0.000 0.076
#> GSM379730     3  0.1644      0.930 0.004 0.000 0.920 0.000 0.000 0.076
#> GSM379731     3  0.1644      0.930 0.004 0.000 0.920 0.000 0.000 0.076
#> GSM379724     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379725     3  0.1010      0.956 0.004 0.000 0.960 0.000 0.000 0.036
#> GSM379726     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379727     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379728     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379737     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379738     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379739     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379732     3  0.1644      0.930 0.004 0.000 0.920 0.000 0.000 0.076
#> GSM379733     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379734     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379735     3  0.1501      0.933 0.000 0.000 0.924 0.000 0.000 0.076
#> GSM379736     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379742     2  0.4731      0.197 0.048 0.524 0.428 0.000 0.000 0.000
#> GSM379743     3  0.1501      0.933 0.000 0.000 0.924 0.000 0.000 0.076
#> GSM379740     3  0.0000      0.978 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379741     2  0.4731      0.197 0.048 0.524 0.428 0.000 0.000 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-MAD-hclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-MAD-hclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-MAD-hclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-MAD-hclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-MAD-hclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-MAD-hclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-MAD-hclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-MAD-hclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-MAD-hclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-MAD-hclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-MAD-hclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-MAD-hclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-MAD-hclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-MAD-hclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-MAD-hclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-MAD-hclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-MAD-hclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-MAD-hclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-MAD-hclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-MAD-hclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk MAD-hclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-MAD-hclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-MAD-hclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-MAD-hclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-MAD-hclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-MAD-hclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk MAD-hclust-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>              n individual(p) time(p) agent(p) k
#> MAD:hclust 137      1.39e-21       1    1.000 2
#> MAD:hclust 124      9.03e-45       1    0.801 3
#> MAD:hclust 101      8.61e-37       1    0.508 4
#> MAD:hclust 109      1.15e-45       1    0.520 5
#> MAD:hclust 121      7.52e-66       1    0.596 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

MAD:kmeans**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["MAD", "kmeans"]
# you can also extract it by
# res = res_list["MAD:kmeans"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#>   Subgroups are detected by 'kmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk MAD-kmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk MAD-kmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.983       0.992         0.4863 0.513   0.513
#> 3 3 0.649           0.544       0.722         0.3017 0.938   0.885
#> 4 4 0.611           0.445       0.608         0.1328 0.687   0.408
#> 5 5 0.690           0.860       0.804         0.0791 0.865   0.532
#> 6 6 0.816           0.820       0.796         0.0457 0.994   0.970

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000      0.988 0.000 1.000
#> GSM379833     2  0.0000      0.988 0.000 1.000
#> GSM379834     2  0.0000      0.988 0.000 1.000
#> GSM379827     2  0.0000      0.988 0.000 1.000
#> GSM379828     2  0.0000      0.988 0.000 1.000
#> GSM379829     1  0.0376      0.995 0.996 0.004
#> GSM379830     2  0.0000      0.988 0.000 1.000
#> GSM379831     2  0.0000      0.988 0.000 1.000
#> GSM379840     2  0.0000      0.988 0.000 1.000
#> GSM379841     2  0.0000      0.988 0.000 1.000
#> GSM379842     2  0.0000      0.988 0.000 1.000
#> GSM379835     2  0.0000      0.988 0.000 1.000
#> GSM379836     2  0.0000      0.988 0.000 1.000
#> GSM379837     1  0.8608      0.605 0.716 0.284
#> GSM379838     2  0.0000      0.988 0.000 1.000
#> GSM379839     2  0.0000      0.988 0.000 1.000
#> GSM379848     2  0.0000      0.988 0.000 1.000
#> GSM379849     2  0.0000      0.988 0.000 1.000
#> GSM379850     2  0.0000      0.988 0.000 1.000
#> GSM379843     2  0.0000      0.988 0.000 1.000
#> GSM379844     2  0.0000      0.988 0.000 1.000
#> GSM379845     2  0.0000      0.988 0.000 1.000
#> GSM379846     2  0.0000      0.988 0.000 1.000
#> GSM379847     2  0.0000      0.988 0.000 1.000
#> GSM379853     2  0.0000      0.988 0.000 1.000
#> GSM379854     2  0.0000      0.988 0.000 1.000
#> GSM379851     2  0.0000      0.988 0.000 1.000
#> GSM379852     2  0.0000      0.988 0.000 1.000
#> GSM379804     1  0.0376      0.995 0.996 0.004
#> GSM379805     1  0.0376      0.995 0.996 0.004
#> GSM379806     1  0.0376      0.995 0.996 0.004
#> GSM379799     1  0.0376      0.995 0.996 0.004
#> GSM379800     1  0.0376      0.995 0.996 0.004
#> GSM379801     1  0.0376      0.995 0.996 0.004
#> GSM379802     1  0.0376      0.995 0.996 0.004
#> GSM379803     1  0.0376      0.995 0.996 0.004
#> GSM379812     1  0.0376      0.995 0.996 0.004
#> GSM379813     1  0.0376      0.995 0.996 0.004
#> GSM379814     1  0.0376      0.995 0.996 0.004
#> GSM379807     1  0.0376      0.995 0.996 0.004
#> GSM379808     1  0.0376      0.995 0.996 0.004
#> GSM379809     1  0.0376      0.995 0.996 0.004
#> GSM379810     1  0.0376      0.995 0.996 0.004
#> GSM379811     1  0.0376      0.995 0.996 0.004
#> GSM379820     1  0.0376      0.995 0.996 0.004
#> GSM379821     1  0.0376      0.995 0.996 0.004
#> GSM379822     1  0.0376      0.995 0.996 0.004
#> GSM379815     1  0.0376      0.995 0.996 0.004
#> GSM379816     1  0.0376      0.995 0.996 0.004
#> GSM379817     1  0.0376      0.995 0.996 0.004
#> GSM379818     1  0.0376      0.995 0.996 0.004
#> GSM379819     1  0.0376      0.995 0.996 0.004
#> GSM379825     1  0.0376      0.995 0.996 0.004
#> GSM379826     1  0.0376      0.995 0.996 0.004
#> GSM379823     1  0.0376      0.995 0.996 0.004
#> GSM379824     1  0.0376      0.995 0.996 0.004
#> GSM379749     2  0.0000      0.988 0.000 1.000
#> GSM379750     2  0.0000      0.988 0.000 1.000
#> GSM379751     2  0.0000      0.988 0.000 1.000
#> GSM379744     2  0.0000      0.988 0.000 1.000
#> GSM379745     2  0.0000      0.988 0.000 1.000
#> GSM379746     2  0.0000      0.988 0.000 1.000
#> GSM379747     2  0.0000      0.988 0.000 1.000
#> GSM379748     2  0.0000      0.988 0.000 1.000
#> GSM379757     2  0.0000      0.988 0.000 1.000
#> GSM379758     2  0.0000      0.988 0.000 1.000
#> GSM379752     2  0.0000      0.988 0.000 1.000
#> GSM379753     2  0.0000      0.988 0.000 1.000
#> GSM379754     2  0.0000      0.988 0.000 1.000
#> GSM379755     2  0.0000      0.988 0.000 1.000
#> GSM379756     2  0.0000      0.988 0.000 1.000
#> GSM379764     2  0.0000      0.988 0.000 1.000
#> GSM379765     2  0.0000      0.988 0.000 1.000
#> GSM379766     2  0.0000      0.988 0.000 1.000
#> GSM379759     2  0.0000      0.988 0.000 1.000
#> GSM379760     2  0.0000      0.988 0.000 1.000
#> GSM379761     2  0.0000      0.988 0.000 1.000
#> GSM379762     2  0.0000      0.988 0.000 1.000
#> GSM379763     2  0.0000      0.988 0.000 1.000
#> GSM379769     2  0.0000      0.988 0.000 1.000
#> GSM379770     2  0.0000      0.988 0.000 1.000
#> GSM379767     2  0.0000      0.988 0.000 1.000
#> GSM379768     2  0.0000      0.988 0.000 1.000
#> GSM379776     1  0.0376      0.995 0.996 0.004
#> GSM379777     1  0.0376      0.995 0.996 0.004
#> GSM379778     1  0.0376      0.995 0.996 0.004
#> GSM379771     1  0.0376      0.995 0.996 0.004
#> GSM379772     1  0.0376      0.995 0.996 0.004
#> GSM379773     1  0.0376      0.995 0.996 0.004
#> GSM379774     1  0.0376      0.995 0.996 0.004
#> GSM379775     1  0.0376      0.995 0.996 0.004
#> GSM379784     1  0.0376      0.995 0.996 0.004
#> GSM379785     1  0.0376      0.995 0.996 0.004
#> GSM379786     1  0.0376      0.995 0.996 0.004
#> GSM379779     1  0.0376      0.995 0.996 0.004
#> GSM379780     1  0.0376      0.995 0.996 0.004
#> GSM379781     1  0.0376      0.995 0.996 0.004
#> GSM379782     2  0.7056      0.763 0.192 0.808
#> GSM379783     1  0.0376      0.995 0.996 0.004
#> GSM379792     1  0.0376      0.995 0.996 0.004
#> GSM379793     1  0.0376      0.995 0.996 0.004
#> GSM379794     1  0.0376      0.995 0.996 0.004
#> GSM379787     2  0.9580      0.394 0.380 0.620
#> GSM379788     1  0.0376      0.995 0.996 0.004
#> GSM379789     1  0.0376      0.995 0.996 0.004
#> GSM379790     1  0.0376      0.995 0.996 0.004
#> GSM379791     1  0.0376      0.995 0.996 0.004
#> GSM379797     1  0.0376      0.995 0.996 0.004
#> GSM379798     1  0.0376      0.995 0.996 0.004
#> GSM379795     1  0.0376      0.995 0.996 0.004
#> GSM379796     1  0.0376      0.995 0.996 0.004
#> GSM379721     1  0.0000      0.994 1.000 0.000
#> GSM379722     1  0.0000      0.994 1.000 0.000
#> GSM379723     1  0.0000      0.994 1.000 0.000
#> GSM379716     1  0.0000      0.994 1.000 0.000
#> GSM379717     1  0.0000      0.994 1.000 0.000
#> GSM379718     1  0.0000      0.994 1.000 0.000
#> GSM379719     1  0.0000      0.994 1.000 0.000
#> GSM379720     1  0.0000      0.994 1.000 0.000
#> GSM379729     1  0.0000      0.994 1.000 0.000
#> GSM379730     1  0.0000      0.994 1.000 0.000
#> GSM379731     1  0.0000      0.994 1.000 0.000
#> GSM379724     1  0.0000      0.994 1.000 0.000
#> GSM379725     1  0.0000      0.994 1.000 0.000
#> GSM379726     1  0.0000      0.994 1.000 0.000
#> GSM379727     1  0.0000      0.994 1.000 0.000
#> GSM379728     1  0.0000      0.994 1.000 0.000
#> GSM379737     1  0.0000      0.994 1.000 0.000
#> GSM379738     1  0.0000      0.994 1.000 0.000
#> GSM379739     1  0.0000      0.994 1.000 0.000
#> GSM379732     1  0.0000      0.994 1.000 0.000
#> GSM379733     1  0.0000      0.994 1.000 0.000
#> GSM379734     1  0.0000      0.994 1.000 0.000
#> GSM379735     1  0.0000      0.994 1.000 0.000
#> GSM379736     1  0.0000      0.994 1.000 0.000
#> GSM379742     2  0.2948      0.942 0.052 0.948
#> GSM379743     1  0.0000      0.994 1.000 0.000
#> GSM379740     1  0.0000      0.994 1.000 0.000
#> GSM379741     2  0.2948      0.942 0.052 0.948

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.2448      0.889 0.000 0.924 0.076
#> GSM379833     2  0.2448      0.889 0.000 0.924 0.076
#> GSM379834     2  0.2448      0.889 0.000 0.924 0.076
#> GSM379827     2  0.2448      0.889 0.000 0.924 0.076
#> GSM379828     2  0.2448      0.889 0.000 0.924 0.076
#> GSM379829     3  0.8535     -0.357 0.404 0.096 0.500
#> GSM379830     2  0.2448      0.889 0.000 0.924 0.076
#> GSM379831     2  0.2448      0.889 0.000 0.924 0.076
#> GSM379840     2  0.2448      0.889 0.000 0.924 0.076
#> GSM379841     2  0.0000      0.902 0.000 1.000 0.000
#> GSM379842     2  0.0237      0.902 0.000 0.996 0.004
#> GSM379835     2  0.2448      0.889 0.000 0.924 0.076
#> GSM379836     2  0.2448      0.889 0.000 0.924 0.076
#> GSM379837     2  0.5435      0.728 0.024 0.784 0.192
#> GSM379838     2  0.0000      0.902 0.000 1.000 0.000
#> GSM379839     2  0.3116      0.869 0.000 0.892 0.108
#> GSM379848     2  0.0592      0.901 0.000 0.988 0.012
#> GSM379849     2  0.0592      0.901 0.000 0.988 0.012
#> GSM379850     2  0.0592      0.901 0.000 0.988 0.012
#> GSM379843     2  0.0237      0.902 0.000 0.996 0.004
#> GSM379844     2  0.0000      0.902 0.000 1.000 0.000
#> GSM379845     2  0.2448      0.889 0.000 0.924 0.076
#> GSM379846     2  0.0000      0.902 0.000 1.000 0.000
#> GSM379847     2  0.0592      0.901 0.000 0.988 0.012
#> GSM379853     2  0.0237      0.902 0.000 0.996 0.004
#> GSM379854     2  0.0592      0.901 0.000 0.988 0.012
#> GSM379851     2  0.0424      0.902 0.000 0.992 0.008
#> GSM379852     2  0.0592      0.901 0.000 0.988 0.012
#> GSM379804     1  0.6204      0.401 0.576 0.000 0.424
#> GSM379805     1  0.6204      0.401 0.576 0.000 0.424
#> GSM379806     1  0.6204      0.401 0.576 0.000 0.424
#> GSM379799     1  0.6204      0.401 0.576 0.000 0.424
#> GSM379800     1  0.6204      0.401 0.576 0.000 0.424
#> GSM379801     1  0.6204      0.401 0.576 0.000 0.424
#> GSM379802     1  0.6204      0.401 0.576 0.000 0.424
#> GSM379803     1  0.6215      0.399 0.572 0.000 0.428
#> GSM379812     1  0.6126      0.410 0.600 0.000 0.400
#> GSM379813     1  0.6126      0.410 0.600 0.000 0.400
#> GSM379814     1  0.6111      0.411 0.604 0.000 0.396
#> GSM379807     1  0.6154      0.408 0.592 0.000 0.408
#> GSM379808     1  0.6204      0.401 0.576 0.000 0.424
#> GSM379809     1  0.6204      0.401 0.576 0.000 0.424
#> GSM379810     1  0.6204      0.401 0.576 0.000 0.424
#> GSM379811     1  0.6215      0.399 0.572 0.000 0.428
#> GSM379820     1  0.6111      0.411 0.604 0.000 0.396
#> GSM379821     1  0.6126      0.410 0.600 0.000 0.400
#> GSM379822     1  0.6126      0.410 0.600 0.000 0.400
#> GSM379815     1  0.6204      0.401 0.576 0.000 0.424
#> GSM379816     1  0.4974      0.442 0.764 0.000 0.236
#> GSM379817     1  0.6126      0.410 0.600 0.000 0.400
#> GSM379818     1  0.6215      0.399 0.572 0.000 0.428
#> GSM379819     1  0.6140      0.409 0.596 0.000 0.404
#> GSM379825     1  0.6204      0.401 0.576 0.000 0.424
#> GSM379826     1  0.6126      0.410 0.600 0.000 0.400
#> GSM379823     1  0.6126      0.410 0.600 0.000 0.400
#> GSM379824     1  0.6126      0.410 0.600 0.000 0.400
#> GSM379749     2  0.4504      0.896 0.000 0.804 0.196
#> GSM379750     2  0.4504      0.896 0.000 0.804 0.196
#> GSM379751     2  0.4605      0.895 0.000 0.796 0.204
#> GSM379744     2  0.4605      0.895 0.000 0.796 0.204
#> GSM379745     2  0.4605      0.895 0.000 0.796 0.204
#> GSM379746     2  0.4504      0.896 0.000 0.804 0.196
#> GSM379747     2  0.4605      0.895 0.000 0.796 0.204
#> GSM379748     2  0.4605      0.895 0.000 0.796 0.204
#> GSM379757     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379758     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379752     2  0.4504      0.896 0.000 0.804 0.196
#> GSM379753     2  0.4605      0.895 0.000 0.796 0.204
#> GSM379754     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379755     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379756     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379764     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379765     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379766     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379759     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379760     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379761     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379762     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379763     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379769     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379770     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379767     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379768     2  0.3686      0.900 0.000 0.860 0.140
#> GSM379776     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379777     1  0.4291      0.424 0.820 0.000 0.180
#> GSM379778     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379771     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379772     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379773     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379774     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379775     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379784     1  0.0237      0.465 0.996 0.000 0.004
#> GSM379785     1  0.0237      0.465 0.996 0.000 0.004
#> GSM379786     1  0.0237      0.465 0.996 0.000 0.004
#> GSM379779     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379780     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379781     1  0.0237      0.465 0.996 0.000 0.004
#> GSM379782     1  0.7406     -0.262 0.596 0.360 0.044
#> GSM379783     1  0.0237      0.465 0.996 0.000 0.004
#> GSM379792     1  0.4062      0.429 0.836 0.000 0.164
#> GSM379793     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379794     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379787     1  0.6956     -0.181 0.660 0.300 0.040
#> GSM379788     1  0.0237      0.465 0.996 0.000 0.004
#> GSM379789     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379790     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379791     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379797     1  0.5760      0.369 0.672 0.000 0.328
#> GSM379798     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379795     1  0.0000      0.466 1.000 0.000 0.000
#> GSM379796     1  0.4062      0.429 0.836 0.000 0.164
#> GSM379721     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379722     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379723     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379716     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379717     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379718     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379719     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379720     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379729     1  0.6267      0.161 0.548 0.000 0.452
#> GSM379730     1  0.6267      0.161 0.548 0.000 0.452
#> GSM379731     1  0.6267      0.161 0.548 0.000 0.452
#> GSM379724     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379725     1  0.6267      0.161 0.548 0.000 0.452
#> GSM379726     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379727     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379728     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379737     1  0.6260      0.163 0.552 0.000 0.448
#> GSM379738     1  0.6260      0.163 0.552 0.000 0.448
#> GSM379739     1  0.6260      0.163 0.552 0.000 0.448
#> GSM379732     1  0.6267      0.161 0.548 0.000 0.452
#> GSM379733     1  0.6260      0.163 0.552 0.000 0.448
#> GSM379734     1  0.6260      0.163 0.552 0.000 0.448
#> GSM379735     1  0.6267      0.161 0.548 0.000 0.452
#> GSM379736     1  0.6299      0.152 0.524 0.000 0.476
#> GSM379742     3  0.9217      0.401 0.344 0.164 0.492
#> GSM379743     1  0.6267      0.161 0.548 0.000 0.452
#> GSM379740     1  0.6260      0.163 0.552 0.000 0.448
#> GSM379741     3  0.9217      0.401 0.344 0.164 0.492

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.0336     0.7616 0.008 0.992 0.000 0.000
#> GSM379833     2  0.0336     0.7616 0.008 0.992 0.000 0.000
#> GSM379834     2  0.0336     0.7616 0.008 0.992 0.000 0.000
#> GSM379827     2  0.1109     0.7592 0.028 0.968 0.004 0.000
#> GSM379828     2  0.1109     0.7592 0.028 0.968 0.004 0.000
#> GSM379829     4  0.6287     0.4146 0.028 0.364 0.024 0.584
#> GSM379830     2  0.1109     0.7592 0.028 0.968 0.004 0.000
#> GSM379831     2  0.0921     0.7605 0.028 0.972 0.000 0.000
#> GSM379840     2  0.1004     0.7597 0.024 0.972 0.004 0.000
#> GSM379841     2  0.3498     0.7517 0.008 0.832 0.160 0.000
#> GSM379842     2  0.3300     0.7538 0.008 0.848 0.144 0.000
#> GSM379835     2  0.1109     0.7592 0.028 0.968 0.004 0.000
#> GSM379836     2  0.1109     0.7592 0.028 0.968 0.004 0.000
#> GSM379837     2  0.2324     0.7325 0.028 0.932 0.020 0.020
#> GSM379838     2  0.3498     0.7517 0.008 0.832 0.160 0.000
#> GSM379839     2  0.2210     0.7362 0.028 0.936 0.020 0.016
#> GSM379848     2  0.3978     0.7340 0.012 0.796 0.192 0.000
#> GSM379849     2  0.3978     0.7340 0.012 0.796 0.192 0.000
#> GSM379850     2  0.3978     0.7340 0.012 0.796 0.192 0.000
#> GSM379843     2  0.3300     0.7538 0.008 0.848 0.144 0.000
#> GSM379844     2  0.3450     0.7526 0.008 0.836 0.156 0.000
#> GSM379845     2  0.1004     0.7597 0.024 0.972 0.004 0.000
#> GSM379846     2  0.3450     0.7526 0.008 0.836 0.156 0.000
#> GSM379847     2  0.3937     0.7357 0.012 0.800 0.188 0.000
#> GSM379853     2  0.3577     0.7499 0.012 0.832 0.156 0.000
#> GSM379854     2  0.3978     0.7340 0.012 0.796 0.192 0.000
#> GSM379851     2  0.3852     0.7385 0.012 0.808 0.180 0.000
#> GSM379852     2  0.3978     0.7340 0.012 0.796 0.192 0.000
#> GSM379804     4  0.0000     0.9555 0.000 0.000 0.000 1.000
#> GSM379805     4  0.0707     0.9525 0.000 0.000 0.020 0.980
#> GSM379806     4  0.0707     0.9525 0.000 0.000 0.020 0.980
#> GSM379799     4  0.0707     0.9525 0.000 0.000 0.020 0.980
#> GSM379800     4  0.0707     0.9525 0.000 0.000 0.020 0.980
#> GSM379801     4  0.0707     0.9525 0.000 0.000 0.020 0.980
#> GSM379802     4  0.0707     0.9525 0.000 0.000 0.020 0.980
#> GSM379803     4  0.0336     0.9556 0.000 0.000 0.008 0.992
#> GSM379812     4  0.0524     0.9550 0.004 0.000 0.008 0.988
#> GSM379813     4  0.0524     0.9550 0.004 0.000 0.008 0.988
#> GSM379814     4  0.0524     0.9550 0.004 0.000 0.008 0.988
#> GSM379807     4  0.0376     0.9553 0.004 0.000 0.004 0.992
#> GSM379808     4  0.0707     0.9525 0.000 0.000 0.020 0.980
#> GSM379809     4  0.0000     0.9555 0.000 0.000 0.000 1.000
#> GSM379810     4  0.0000     0.9555 0.000 0.000 0.000 1.000
#> GSM379811     4  0.0707     0.9525 0.000 0.000 0.020 0.980
#> GSM379820     4  0.0524     0.9550 0.004 0.000 0.008 0.988
#> GSM379821     4  0.0524     0.9550 0.004 0.000 0.008 0.988
#> GSM379822     4  0.0657     0.9527 0.004 0.000 0.012 0.984
#> GSM379815     4  0.0000     0.9555 0.000 0.000 0.000 1.000
#> GSM379816     4  0.2610     0.8169 0.088 0.000 0.012 0.900
#> GSM379817     4  0.0524     0.9550 0.004 0.000 0.008 0.988
#> GSM379818     4  0.0707     0.9525 0.000 0.000 0.020 0.980
#> GSM379819     4  0.0524     0.9550 0.004 0.000 0.008 0.988
#> GSM379825     4  0.0707     0.9525 0.000 0.000 0.020 0.980
#> GSM379826     4  0.0524     0.9550 0.004 0.000 0.008 0.988
#> GSM379823     4  0.0657     0.9527 0.004 0.000 0.012 0.984
#> GSM379824     4  0.0524     0.9550 0.004 0.000 0.008 0.988
#> GSM379749     2  0.5596     0.5535 0.036 0.632 0.332 0.000
#> GSM379750     2  0.5596     0.5535 0.036 0.632 0.332 0.000
#> GSM379751     2  0.5646     0.5708 0.048 0.656 0.296 0.000
#> GSM379744     2  0.5577     0.5554 0.036 0.636 0.328 0.000
#> GSM379745     2  0.5577     0.5554 0.036 0.636 0.328 0.000
#> GSM379746     2  0.5596     0.5535 0.036 0.632 0.332 0.000
#> GSM379747     2  0.5475     0.5638 0.036 0.656 0.308 0.000
#> GSM379748     2  0.5475     0.5638 0.036 0.656 0.308 0.000
#> GSM379757     3  0.5861    -0.4040 0.032 0.476 0.492 0.000
#> GSM379758     3  0.4994    -0.3870 0.000 0.480 0.520 0.000
#> GSM379752     2  0.5596     0.5535 0.036 0.632 0.332 0.000
#> GSM379753     2  0.5496     0.5635 0.036 0.652 0.312 0.000
#> GSM379754     3  0.5861    -0.4087 0.032 0.480 0.488 0.000
#> GSM379755     3  0.5861    -0.4087 0.032 0.480 0.488 0.000
#> GSM379756     3  0.5861    -0.4087 0.032 0.480 0.488 0.000
#> GSM379764     3  0.5165    -0.3878 0.004 0.484 0.512 0.000
#> GSM379765     3  0.5165    -0.3878 0.004 0.484 0.512 0.000
#> GSM379766     3  0.5165    -0.3878 0.004 0.484 0.512 0.000
#> GSM379759     3  0.4992    -0.3878 0.000 0.476 0.524 0.000
#> GSM379760     3  0.5161    -0.3892 0.004 0.476 0.520 0.000
#> GSM379761     3  0.4994    -0.3870 0.000 0.480 0.520 0.000
#> GSM379762     3  0.4994    -0.3870 0.000 0.480 0.520 0.000
#> GSM379763     3  0.5165    -0.3878 0.004 0.484 0.512 0.000
#> GSM379769     3  0.5165    -0.3878 0.004 0.484 0.512 0.000
#> GSM379770     3  0.5165    -0.3878 0.004 0.484 0.512 0.000
#> GSM379767     3  0.5165    -0.3878 0.004 0.484 0.512 0.000
#> GSM379768     3  0.5165    -0.3878 0.004 0.484 0.512 0.000
#> GSM379776     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379777     1  0.5212     0.4081 0.572 0.000 0.008 0.420
#> GSM379778     1  0.4991     0.5912 0.672 0.004 0.008 0.316
#> GSM379771     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379772     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379773     1  0.4836     0.5941 0.672 0.000 0.008 0.320
#> GSM379774     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379775     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379784     1  0.4720     0.5971 0.672 0.000 0.004 0.324
#> GSM379785     1  0.4720     0.5971 0.672 0.000 0.004 0.324
#> GSM379786     1  0.4720     0.5971 0.672 0.000 0.004 0.324
#> GSM379779     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379780     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379781     1  0.4720     0.5971 0.672 0.000 0.004 0.324
#> GSM379782     1  0.6659     0.4839 0.676 0.024 0.144 0.156
#> GSM379783     1  0.4720     0.5971 0.672 0.000 0.004 0.324
#> GSM379792     1  0.4866     0.4511 0.596 0.000 0.000 0.404
#> GSM379793     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379794     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379787     1  0.6692     0.4926 0.672 0.024 0.136 0.168
#> GSM379788     1  0.4720     0.5971 0.672 0.000 0.004 0.324
#> GSM379789     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379790     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379791     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379797     4  0.3335     0.7866 0.120 0.000 0.020 0.860
#> GSM379798     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379795     1  0.4543     0.5987 0.676 0.000 0.000 0.324
#> GSM379796     1  0.4866     0.4511 0.596 0.000 0.000 0.404
#> GSM379721     3  0.7221    -0.1335 0.424 0.000 0.436 0.140
#> GSM379722     3  0.7221    -0.1335 0.424 0.000 0.436 0.140
#> GSM379723     3  0.7220    -0.1334 0.420 0.000 0.440 0.140
#> GSM379716     3  0.7220    -0.1334 0.420 0.000 0.440 0.140
#> GSM379717     3  0.7220    -0.1334 0.420 0.000 0.440 0.140
#> GSM379718     3  0.7221    -0.1335 0.424 0.000 0.436 0.140
#> GSM379719     3  0.7221    -0.1335 0.424 0.000 0.436 0.140
#> GSM379720     3  0.7221    -0.1335 0.424 0.000 0.436 0.140
#> GSM379729     1  0.7154     0.1031 0.436 0.000 0.432 0.132
#> GSM379730     1  0.7154     0.1031 0.436 0.000 0.432 0.132
#> GSM379731     1  0.7154     0.1031 0.436 0.000 0.432 0.132
#> GSM379724     3  0.7220    -0.1334 0.420 0.000 0.440 0.140
#> GSM379725     3  0.7154    -0.1487 0.428 0.000 0.440 0.132
#> GSM379726     3  0.7221    -0.1385 0.424 0.000 0.436 0.140
#> GSM379727     3  0.7221    -0.1385 0.424 0.000 0.436 0.140
#> GSM379728     3  0.7221    -0.1385 0.424 0.000 0.436 0.140
#> GSM379737     1  0.7154     0.1023 0.436 0.000 0.432 0.132
#> GSM379738     1  0.7154     0.1023 0.436 0.000 0.432 0.132
#> GSM379739     1  0.7154     0.1023 0.436 0.000 0.432 0.132
#> GSM379732     1  0.7154     0.1031 0.436 0.000 0.432 0.132
#> GSM379733     1  0.7154     0.1023 0.436 0.000 0.432 0.132
#> GSM379734     1  0.7154     0.1023 0.436 0.000 0.432 0.132
#> GSM379735     1  0.7154     0.1031 0.436 0.000 0.432 0.132
#> GSM379736     1  0.7221     0.0927 0.432 0.000 0.428 0.140
#> GSM379742     3  0.5643    -0.0403 0.440 0.016 0.540 0.004
#> GSM379743     1  0.7154     0.1031 0.436 0.000 0.432 0.132
#> GSM379740     1  0.7154     0.1023 0.436 0.000 0.432 0.132
#> GSM379741     3  0.5643    -0.0403 0.440 0.016 0.540 0.004

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     5  0.3876      0.772 0.000 0.316 0.000 0.000 0.684
#> GSM379833     5  0.3876      0.772 0.000 0.316 0.000 0.000 0.684
#> GSM379834     5  0.3876      0.772 0.000 0.316 0.000 0.000 0.684
#> GSM379827     5  0.5564      0.749 0.064 0.316 0.012 0.000 0.608
#> GSM379828     5  0.5564      0.749 0.064 0.316 0.012 0.000 0.608
#> GSM379829     5  0.5979     -0.218 0.068 0.000 0.016 0.428 0.488
#> GSM379830     5  0.5564      0.749 0.064 0.316 0.012 0.000 0.608
#> GSM379831     5  0.5564      0.749 0.064 0.316 0.012 0.000 0.608
#> GSM379840     5  0.5223      0.760 0.048 0.316 0.008 0.000 0.628
#> GSM379841     5  0.4945      0.774 0.020 0.440 0.004 0.000 0.536
#> GSM379842     5  0.4940      0.776 0.020 0.436 0.004 0.000 0.540
#> GSM379835     5  0.5564      0.749 0.064 0.316 0.012 0.000 0.608
#> GSM379836     5  0.5564      0.749 0.064 0.316 0.012 0.000 0.608
#> GSM379837     5  0.5599      0.655 0.064 0.220 0.016 0.016 0.684
#> GSM379838     5  0.4949      0.771 0.020 0.444 0.004 0.000 0.532
#> GSM379839     5  0.5461      0.665 0.064 0.228 0.012 0.012 0.684
#> GSM379848     5  0.5222      0.756 0.028 0.452 0.008 0.000 0.512
#> GSM379849     5  0.5292      0.752 0.032 0.452 0.008 0.000 0.508
#> GSM379850     5  0.5292      0.752 0.032 0.452 0.008 0.000 0.508
#> GSM379843     5  0.4940      0.776 0.020 0.436 0.004 0.000 0.540
#> GSM379844     5  0.4945      0.774 0.020 0.440 0.004 0.000 0.536
#> GSM379845     5  0.5223      0.760 0.048 0.316 0.008 0.000 0.628
#> GSM379846     5  0.4945      0.774 0.020 0.440 0.004 0.000 0.536
#> GSM379847     5  0.5148      0.760 0.024 0.452 0.008 0.000 0.516
#> GSM379853     5  0.5120      0.774 0.024 0.428 0.008 0.000 0.540
#> GSM379854     5  0.5292      0.752 0.032 0.452 0.008 0.000 0.508
#> GSM379851     5  0.5144      0.764 0.024 0.448 0.008 0.000 0.520
#> GSM379852     5  0.5292      0.752 0.032 0.452 0.008 0.000 0.508
#> GSM379804     4  0.0693      0.919 0.000 0.000 0.008 0.980 0.012
#> GSM379805     4  0.2352      0.905 0.004 0.000 0.008 0.896 0.092
#> GSM379806     4  0.2517      0.902 0.004 0.000 0.008 0.884 0.104
#> GSM379799     4  0.2517      0.902 0.004 0.000 0.008 0.884 0.104
#> GSM379800     4  0.2517      0.902 0.004 0.000 0.008 0.884 0.104
#> GSM379801     4  0.2517      0.902 0.004 0.000 0.008 0.884 0.104
#> GSM379802     4  0.2570      0.902 0.004 0.000 0.008 0.880 0.108
#> GSM379803     4  0.1043      0.917 0.000 0.000 0.000 0.960 0.040
#> GSM379812     4  0.1965      0.911 0.024 0.000 0.000 0.924 0.052
#> GSM379813     4  0.1872      0.914 0.020 0.000 0.000 0.928 0.052
#> GSM379814     4  0.2032      0.915 0.020 0.000 0.004 0.924 0.052
#> GSM379807     4  0.2032      0.915 0.020 0.000 0.004 0.924 0.052
#> GSM379808     4  0.2517      0.902 0.004 0.000 0.008 0.884 0.104
#> GSM379809     4  0.0693      0.919 0.000 0.000 0.008 0.980 0.012
#> GSM379810     4  0.0693      0.919 0.012 0.000 0.008 0.980 0.000
#> GSM379811     4  0.2570      0.902 0.004 0.000 0.008 0.880 0.108
#> GSM379820     4  0.2032      0.915 0.020 0.000 0.004 0.924 0.052
#> GSM379821     4  0.2036      0.911 0.024 0.000 0.000 0.920 0.056
#> GSM379822     4  0.2628      0.892 0.028 0.000 0.000 0.884 0.088
#> GSM379815     4  0.0324      0.919 0.004 0.000 0.004 0.992 0.000
#> GSM379816     4  0.4100      0.818 0.028 0.000 0.060 0.816 0.096
#> GSM379817     4  0.1872      0.914 0.020 0.000 0.000 0.928 0.052
#> GSM379818     4  0.2570      0.902 0.004 0.000 0.008 0.880 0.108
#> GSM379819     4  0.2032      0.915 0.020 0.000 0.004 0.924 0.052
#> GSM379825     4  0.2517      0.902 0.004 0.000 0.008 0.884 0.104
#> GSM379826     4  0.2032      0.915 0.020 0.000 0.004 0.924 0.052
#> GSM379823     4  0.2628      0.892 0.028 0.000 0.000 0.884 0.088
#> GSM379824     4  0.1943      0.912 0.020 0.000 0.000 0.924 0.056
#> GSM379749     2  0.2720      0.777 0.020 0.880 0.004 0.000 0.096
#> GSM379750     2  0.2720      0.777 0.020 0.880 0.004 0.000 0.096
#> GSM379751     2  0.3937      0.683 0.060 0.804 0.004 0.000 0.132
#> GSM379744     2  0.2828      0.769 0.020 0.872 0.004 0.000 0.104
#> GSM379745     2  0.2828      0.769 0.020 0.872 0.004 0.000 0.104
#> GSM379746     2  0.2720      0.777 0.020 0.880 0.004 0.000 0.096
#> GSM379747     2  0.3174      0.737 0.020 0.844 0.004 0.000 0.132
#> GSM379748     2  0.3174      0.737 0.020 0.844 0.004 0.000 0.132
#> GSM379757     2  0.0566      0.823 0.012 0.984 0.004 0.000 0.000
#> GSM379758     2  0.2464      0.829 0.096 0.888 0.016 0.000 0.000
#> GSM379752     2  0.2720      0.777 0.020 0.880 0.004 0.000 0.096
#> GSM379753     2  0.3174      0.737 0.020 0.844 0.004 0.000 0.132
#> GSM379754     2  0.0162      0.821 0.004 0.996 0.000 0.000 0.000
#> GSM379755     2  0.0162      0.821 0.004 0.996 0.000 0.000 0.000
#> GSM379756     2  0.0162      0.821 0.004 0.996 0.000 0.000 0.000
#> GSM379764     2  0.2824      0.819 0.116 0.864 0.020 0.000 0.000
#> GSM379765     2  0.2824      0.819 0.116 0.864 0.020 0.000 0.000
#> GSM379766     2  0.2824      0.819 0.116 0.864 0.020 0.000 0.000
#> GSM379759     2  0.2408      0.830 0.092 0.892 0.016 0.000 0.000
#> GSM379760     2  0.2408      0.830 0.092 0.892 0.016 0.000 0.000
#> GSM379761     2  0.2464      0.829 0.096 0.888 0.016 0.000 0.000
#> GSM379762     2  0.2464      0.829 0.096 0.888 0.016 0.000 0.000
#> GSM379763     2  0.2824      0.819 0.116 0.864 0.020 0.000 0.000
#> GSM379769     2  0.2824      0.819 0.116 0.864 0.020 0.000 0.000
#> GSM379770     2  0.2824      0.819 0.116 0.864 0.020 0.000 0.000
#> GSM379767     2  0.2824      0.819 0.116 0.864 0.020 0.000 0.000
#> GSM379768     2  0.2824      0.819 0.116 0.864 0.020 0.000 0.000
#> GSM379776     1  0.4458      0.970 0.760 0.000 0.120 0.120 0.000
#> GSM379777     1  0.4377      0.900 0.760 0.000 0.048 0.184 0.008
#> GSM379778     1  0.5079      0.942 0.748 0.000 0.104 0.112 0.036
#> GSM379771     1  0.4613      0.970 0.756 0.000 0.120 0.120 0.004
#> GSM379772     1  0.4613      0.970 0.756 0.000 0.120 0.120 0.004
#> GSM379773     1  0.4935      0.954 0.752 0.000 0.112 0.112 0.024
#> GSM379774     1  0.4613      0.970 0.756 0.000 0.120 0.120 0.004
#> GSM379775     1  0.4613      0.970 0.756 0.000 0.120 0.120 0.004
#> GSM379784     1  0.4468      0.965 0.768 0.000 0.104 0.124 0.004
#> GSM379785     1  0.4468      0.965 0.768 0.000 0.104 0.124 0.004
#> GSM379786     1  0.4513      0.963 0.764 0.000 0.104 0.128 0.004
#> GSM379779     1  0.4613      0.970 0.756 0.000 0.120 0.120 0.004
#> GSM379780     1  0.4458      0.970 0.760 0.000 0.120 0.120 0.000
#> GSM379781     1  0.4565      0.968 0.760 0.000 0.112 0.124 0.004
#> GSM379782     1  0.4749      0.871 0.792 0.016 0.100 0.048 0.044
#> GSM379783     1  0.4513      0.963 0.764 0.000 0.104 0.128 0.004
#> GSM379792     1  0.4565      0.910 0.752 0.000 0.064 0.176 0.008
#> GSM379793     1  0.4733      0.969 0.752 0.000 0.120 0.120 0.008
#> GSM379794     1  0.4733      0.969 0.752 0.000 0.120 0.120 0.008
#> GSM379787     1  0.4935      0.882 0.780 0.016 0.104 0.056 0.044
#> GSM379788     1  0.4468      0.965 0.768 0.000 0.104 0.124 0.004
#> GSM379789     1  0.4613      0.970 0.756 0.000 0.120 0.120 0.004
#> GSM379790     1  0.4733      0.969 0.752 0.000 0.120 0.120 0.008
#> GSM379791     1  0.4613      0.970 0.756 0.000 0.120 0.120 0.004
#> GSM379797     4  0.5278      0.706 0.180 0.000 0.008 0.696 0.116
#> GSM379798     1  0.4733      0.969 0.752 0.000 0.120 0.120 0.008
#> GSM379795     1  0.4613      0.970 0.756 0.000 0.120 0.120 0.004
#> GSM379796     1  0.4589      0.916 0.752 0.000 0.068 0.172 0.008
#> GSM379721     3  0.1651      0.945 0.008 0.000 0.944 0.036 0.012
#> GSM379722     3  0.1651      0.945 0.008 0.000 0.944 0.036 0.012
#> GSM379723     3  0.1124      0.945 0.004 0.000 0.960 0.036 0.000
#> GSM379716     3  0.1124      0.945 0.004 0.000 0.960 0.036 0.000
#> GSM379717     3  0.1124      0.945 0.004 0.000 0.960 0.036 0.000
#> GSM379718     3  0.1651      0.945 0.008 0.000 0.944 0.036 0.012
#> GSM379719     3  0.1651      0.945 0.008 0.000 0.944 0.036 0.012
#> GSM379720     3  0.1651      0.945 0.008 0.000 0.944 0.036 0.012
#> GSM379729     3  0.4030      0.920 0.028 0.000 0.816 0.044 0.112
#> GSM379730     3  0.4030      0.920 0.028 0.000 0.816 0.044 0.112
#> GSM379731     3  0.4030      0.920 0.028 0.000 0.816 0.044 0.112
#> GSM379724     3  0.1124      0.945 0.004 0.000 0.960 0.036 0.000
#> GSM379725     3  0.3930      0.923 0.028 0.000 0.824 0.044 0.104
#> GSM379726     3  0.1124      0.945 0.004 0.000 0.960 0.036 0.000
#> GSM379727     3  0.1124      0.945 0.004 0.000 0.960 0.036 0.000
#> GSM379728     3  0.1124      0.945 0.004 0.000 0.960 0.036 0.000
#> GSM379737     3  0.2576      0.942 0.008 0.000 0.900 0.036 0.056
#> GSM379738     3  0.2576      0.942 0.008 0.000 0.900 0.036 0.056
#> GSM379739     3  0.2576      0.942 0.008 0.000 0.900 0.036 0.056
#> GSM379732     3  0.3945      0.921 0.024 0.000 0.820 0.044 0.112
#> GSM379733     3  0.1836      0.946 0.000 0.000 0.932 0.036 0.032
#> GSM379734     3  0.1836      0.946 0.000 0.000 0.932 0.036 0.032
#> GSM379735     3  0.4030      0.920 0.028 0.000 0.816 0.044 0.112
#> GSM379736     3  0.1251      0.946 0.000 0.000 0.956 0.036 0.008
#> GSM379742     3  0.4781      0.821 0.092 0.020 0.760 0.000 0.128
#> GSM379743     3  0.4030      0.920 0.028 0.000 0.816 0.044 0.112
#> GSM379740     3  0.2434      0.943 0.008 0.000 0.908 0.036 0.048
#> GSM379741     3  0.4781      0.821 0.092 0.020 0.760 0.000 0.128

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5 p6
#> GSM379832     5  0.3364      0.768 0.000 0.196 0.000 0.000 0.780 NA
#> GSM379833     5  0.3364      0.768 0.000 0.196 0.000 0.000 0.780 NA
#> GSM379834     5  0.3364      0.768 0.000 0.196 0.000 0.000 0.780 NA
#> GSM379827     5  0.6295      0.703 0.000 0.204 0.004 0.060 0.572 NA
#> GSM379828     5  0.6295      0.703 0.000 0.204 0.004 0.060 0.572 NA
#> GSM379829     4  0.5165      0.175 0.000 0.000 0.000 0.616 0.228 NA
#> GSM379830     5  0.6158      0.720 0.000 0.196 0.004 0.060 0.592 NA
#> GSM379831     5  0.6024      0.722 0.000 0.196 0.000 0.060 0.596 NA
#> GSM379840     5  0.5928      0.729 0.000 0.196 0.000 0.060 0.608 NA
#> GSM379841     5  0.3499      0.776 0.000 0.320 0.000 0.000 0.680 NA
#> GSM379842     5  0.3409      0.781 0.000 0.300 0.000 0.000 0.700 NA
#> GSM379835     5  0.6158      0.720 0.000 0.196 0.004 0.060 0.592 NA
#> GSM379836     5  0.6158      0.720 0.000 0.196 0.004 0.060 0.592 NA
#> GSM379837     5  0.6257      0.647 0.000 0.108 0.004 0.136 0.604 NA
#> GSM379838     5  0.3499      0.776 0.000 0.320 0.000 0.000 0.680 NA
#> GSM379839     5  0.6161      0.654 0.000 0.112 0.000 0.136 0.604 NA
#> GSM379848     5  0.4441      0.738 0.000 0.344 0.004 0.000 0.620 NA
#> GSM379849     5  0.4441      0.738 0.000 0.344 0.004 0.000 0.620 NA
#> GSM379850     5  0.4441      0.738 0.000 0.344 0.004 0.000 0.620 NA
#> GSM379843     5  0.3409      0.781 0.000 0.300 0.000 0.000 0.700 NA
#> GSM379844     5  0.3482      0.777 0.000 0.316 0.000 0.000 0.684 NA
#> GSM379845     5  0.5928      0.729 0.000 0.196 0.000 0.060 0.608 NA
#> GSM379846     5  0.3619      0.778 0.000 0.316 0.004 0.000 0.680 NA
#> GSM379847     5  0.4134      0.754 0.000 0.340 0.004 0.000 0.640 NA
#> GSM379853     5  0.3938      0.775 0.000 0.312 0.004 0.000 0.672 NA
#> GSM379854     5  0.4441      0.738 0.000 0.344 0.004 0.000 0.620 NA
#> GSM379851     5  0.4019      0.764 0.000 0.332 0.004 0.000 0.652 NA
#> GSM379852     5  0.4441      0.738 0.000 0.344 0.004 0.000 0.620 NA
#> GSM379804     4  0.4603      0.829 0.060 0.000 0.008 0.672 0.000 NA
#> GSM379805     4  0.2445      0.790 0.060 0.000 0.008 0.892 0.000 NA
#> GSM379806     4  0.2138      0.782 0.060 0.000 0.008 0.912 0.008 NA
#> GSM379799     4  0.1781      0.779 0.060 0.000 0.008 0.924 0.008 NA
#> GSM379800     4  0.1781      0.779 0.060 0.000 0.008 0.924 0.008 NA
#> GSM379801     4  0.1781      0.779 0.060 0.000 0.008 0.924 0.008 NA
#> GSM379802     4  0.2119      0.777 0.060 0.000 0.008 0.912 0.004 NA
#> GSM379803     4  0.4950      0.827 0.060 0.000 0.008 0.680 0.020 NA
#> GSM379812     4  0.5649      0.820 0.076 0.000 0.012 0.512 0.012 NA
#> GSM379813     4  0.5254      0.823 0.076 0.000 0.008 0.520 0.000 NA
#> GSM379814     4  0.5254      0.823 0.076 0.000 0.008 0.520 0.000 NA
#> GSM379807     4  0.5254      0.823 0.076 0.000 0.008 0.520 0.000 NA
#> GSM379808     4  0.1781      0.779 0.060 0.000 0.008 0.924 0.008 NA
#> GSM379809     4  0.4624      0.829 0.060 0.000 0.008 0.668 0.000 NA
#> GSM379810     4  0.4940      0.829 0.076 0.000 0.008 0.628 0.000 NA
#> GSM379811     4  0.2319      0.778 0.060 0.000 0.008 0.904 0.008 NA
#> GSM379820     4  0.5254      0.823 0.076 0.000 0.008 0.520 0.000 NA
#> GSM379821     4  0.5761      0.820 0.072 0.000 0.012 0.508 0.020 NA
#> GSM379822     4  0.5793      0.809 0.072 0.000 0.012 0.480 0.020 NA
#> GSM379815     4  0.4703      0.830 0.060 0.000 0.008 0.652 0.000 NA
#> GSM379816     4  0.5956      0.798 0.080 0.000 0.020 0.464 0.016 NA
#> GSM379817     4  0.5254      0.823 0.076 0.000 0.008 0.520 0.000 NA
#> GSM379818     4  0.2319      0.778 0.060 0.000 0.008 0.904 0.008 NA
#> GSM379819     4  0.5254      0.823 0.076 0.000 0.008 0.520 0.000 NA
#> GSM379825     4  0.1668      0.780 0.060 0.000 0.008 0.928 0.000 NA
#> GSM379826     4  0.5254      0.823 0.076 0.000 0.008 0.520 0.000 NA
#> GSM379823     4  0.5688      0.809 0.076 0.000 0.012 0.476 0.012 NA
#> GSM379824     4  0.5673      0.821 0.072 0.000 0.008 0.512 0.020 NA
#> GSM379749     2  0.2804      0.716 0.000 0.852 0.004 0.000 0.120 NA
#> GSM379750     2  0.2804      0.716 0.000 0.852 0.004 0.000 0.120 NA
#> GSM379751     2  0.4010      0.614 0.000 0.764 0.004 0.000 0.148 NA
#> GSM379744     2  0.2848      0.713 0.000 0.848 0.004 0.000 0.124 NA
#> GSM379745     2  0.2848      0.713 0.000 0.848 0.004 0.000 0.124 NA
#> GSM379746     2  0.2804      0.716 0.000 0.852 0.004 0.000 0.120 NA
#> GSM379747     2  0.3129      0.686 0.000 0.820 0.004 0.000 0.152 NA
#> GSM379748     2  0.3129      0.686 0.000 0.820 0.004 0.000 0.152 NA
#> GSM379757     2  0.1007      0.766 0.000 0.956 0.000 0.000 0.000 NA
#> GSM379758     2  0.3469      0.771 0.004 0.788 0.020 0.000 0.004 NA
#> GSM379752     2  0.2804      0.716 0.000 0.852 0.004 0.000 0.120 NA
#> GSM379753     2  0.3168      0.684 0.000 0.820 0.004 0.000 0.148 NA
#> GSM379754     2  0.0458      0.756 0.000 0.984 0.000 0.000 0.016 NA
#> GSM379755     2  0.0458      0.756 0.000 0.984 0.000 0.000 0.016 NA
#> GSM379756     2  0.0146      0.758 0.000 0.996 0.000 0.000 0.004 NA
#> GSM379764     2  0.4022      0.758 0.004 0.756 0.020 0.000 0.024 NA
#> GSM379765     2  0.4022      0.758 0.004 0.756 0.020 0.000 0.024 NA
#> GSM379766     2  0.4022      0.758 0.004 0.756 0.020 0.000 0.024 NA
#> GSM379759     2  0.3329      0.772 0.004 0.792 0.020 0.000 0.000 NA
#> GSM379760     2  0.3329      0.772 0.004 0.792 0.020 0.000 0.000 NA
#> GSM379761     2  0.3469      0.771 0.004 0.788 0.020 0.000 0.004 NA
#> GSM379762     2  0.3469      0.771 0.004 0.788 0.020 0.000 0.004 NA
#> GSM379763     2  0.4022      0.758 0.004 0.756 0.020 0.000 0.024 NA
#> GSM379769     2  0.4022      0.758 0.004 0.756 0.020 0.000 0.024 NA
#> GSM379770     2  0.4022      0.758 0.004 0.756 0.020 0.000 0.024 NA
#> GSM379767     2  0.4022      0.758 0.004 0.756 0.020 0.000 0.024 NA
#> GSM379768     2  0.4022      0.758 0.004 0.756 0.020 0.000 0.024 NA
#> GSM379776     1  0.0508      0.971 0.984 0.000 0.012 0.000 0.004 NA
#> GSM379777     1  0.2596      0.918 0.892 0.000 0.004 0.016 0.044 NA
#> GSM379778     1  0.2278      0.929 0.900 0.000 0.004 0.000 0.044 NA
#> GSM379771     1  0.0508      0.971 0.984 0.000 0.012 0.000 0.000 NA
#> GSM379772     1  0.0508      0.971 0.984 0.000 0.012 0.000 0.000 NA
#> GSM379773     1  0.1636      0.952 0.936 0.000 0.004 0.000 0.036 NA
#> GSM379774     1  0.0508      0.971 0.984 0.000 0.012 0.000 0.000 NA
#> GSM379775     1  0.0508      0.971 0.984 0.000 0.012 0.000 0.000 NA
#> GSM379784     1  0.1346      0.964 0.952 0.000 0.016 0.000 0.024 NA
#> GSM379785     1  0.1148      0.967 0.960 0.000 0.016 0.000 0.020 NA
#> GSM379786     1  0.1346      0.964 0.952 0.000 0.016 0.000 0.024 NA
#> GSM379779     1  0.0363      0.970 0.988 0.000 0.012 0.000 0.000 NA
#> GSM379780     1  0.0363      0.970 0.988 0.000 0.012 0.000 0.000 NA
#> GSM379781     1  0.1053      0.967 0.964 0.000 0.012 0.000 0.020 NA
#> GSM379782     1  0.2542      0.902 0.876 0.000 0.000 0.000 0.044 NA
#> GSM379783     1  0.1346      0.964 0.952 0.000 0.016 0.000 0.024 NA
#> GSM379792     1  0.1223      0.961 0.960 0.000 0.004 0.012 0.016 NA
#> GSM379793     1  0.0984      0.968 0.968 0.000 0.012 0.000 0.012 NA
#> GSM379794     1  0.0984      0.968 0.968 0.000 0.012 0.000 0.012 NA
#> GSM379787     1  0.2542      0.902 0.876 0.000 0.000 0.000 0.044 NA
#> GSM379788     1  0.1262      0.965 0.956 0.000 0.016 0.000 0.020 NA
#> GSM379789     1  0.0870      0.969 0.972 0.000 0.012 0.000 0.012 NA
#> GSM379790     1  0.1078      0.967 0.964 0.000 0.012 0.000 0.016 NA
#> GSM379791     1  0.0870      0.969 0.972 0.000 0.012 0.000 0.012 NA
#> GSM379797     4  0.4564      0.574 0.256 0.000 0.004 0.688 0.024 NA
#> GSM379798     1  0.1078      0.967 0.964 0.000 0.012 0.000 0.016 NA
#> GSM379795     1  0.0870      0.969 0.972 0.000 0.012 0.000 0.012 NA
#> GSM379796     1  0.1223      0.961 0.960 0.000 0.004 0.012 0.016 NA
#> GSM379721     3  0.1511      0.902 0.032 0.000 0.944 0.000 0.012 NA
#> GSM379722     3  0.1511      0.902 0.032 0.000 0.944 0.000 0.012 NA
#> GSM379723     3  0.1080      0.902 0.032 0.000 0.960 0.000 0.004 NA
#> GSM379716     3  0.1080      0.902 0.032 0.000 0.960 0.000 0.004 NA
#> GSM379717     3  0.1080      0.902 0.032 0.000 0.960 0.000 0.004 NA
#> GSM379718     3  0.1511      0.902 0.032 0.000 0.944 0.000 0.012 NA
#> GSM379719     3  0.1511      0.902 0.032 0.000 0.944 0.000 0.012 NA
#> GSM379720     3  0.1511      0.902 0.032 0.000 0.944 0.000 0.012 NA
#> GSM379729     3  0.4892      0.877 0.028 0.000 0.720 0.008 0.084 NA
#> GSM379730     3  0.4892      0.877 0.028 0.000 0.720 0.008 0.084 NA
#> GSM379731     3  0.4858      0.878 0.028 0.000 0.724 0.008 0.084 NA
#> GSM379724     3  0.1080      0.902 0.032 0.000 0.960 0.000 0.004 NA
#> GSM379725     3  0.4391      0.885 0.028 0.000 0.764 0.004 0.076 NA
#> GSM379726     3  0.0790      0.903 0.032 0.000 0.968 0.000 0.000 NA
#> GSM379727     3  0.0790      0.903 0.032 0.000 0.968 0.000 0.000 NA
#> GSM379728     3  0.0790      0.903 0.032 0.000 0.968 0.000 0.000 NA
#> GSM379737     3  0.4221      0.896 0.032 0.000 0.788 0.008 0.072 NA
#> GSM379738     3  0.4221      0.896 0.032 0.000 0.788 0.008 0.072 NA
#> GSM379739     3  0.4221      0.896 0.032 0.000 0.788 0.008 0.072 NA
#> GSM379732     3  0.4858      0.878 0.028 0.000 0.724 0.008 0.084 NA
#> GSM379733     3  0.3114      0.904 0.032 0.000 0.864 0.004 0.052 NA
#> GSM379734     3  0.3114      0.904 0.032 0.000 0.864 0.004 0.052 NA
#> GSM379735     3  0.5005      0.873 0.028 0.000 0.708 0.008 0.088 NA
#> GSM379736     3  0.2345      0.904 0.032 0.000 0.908 0.004 0.028 NA
#> GSM379742     3  0.5565      0.778 0.016 0.004 0.620 0.008 0.096 NA
#> GSM379743     3  0.5005      0.873 0.028 0.000 0.708 0.008 0.088 NA
#> GSM379740     3  0.4174      0.897 0.032 0.000 0.792 0.008 0.072 NA
#> GSM379741     3  0.5565      0.778 0.016 0.004 0.620 0.008 0.096 NA

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-MAD-kmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-MAD-kmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-MAD-kmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-MAD-kmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-MAD-kmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-MAD-kmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-MAD-kmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-MAD-kmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-MAD-kmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-MAD-kmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-MAD-kmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-MAD-kmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-MAD-kmeans-get-signatures-3

get_signatures(res, k = 5)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-MAD-kmeans-get-signatures-4

get_signatures(res, k = 6)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-MAD-kmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-MAD-kmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-MAD-kmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-MAD-kmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-MAD-kmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-MAD-kmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk MAD-kmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-MAD-kmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-MAD-kmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-MAD-kmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-MAD-kmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-MAD-kmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk MAD-kmeans-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>              n individual(p) time(p) agent(p) k
#> MAD:kmeans 138      1.06e-24       1    0.780 2
#> MAD:kmeans  54            NA      NA       NA 3
#> MAD:kmeans  88      6.42e-34       1    0.527 4
#> MAD:kmeans 138     3.50e-105       1    0.998 5
#> MAD:kmeans 138     3.50e-105       1    0.998 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

MAD:skmeans*

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["MAD", "skmeans"]
# you can also extract it by
# res = res_list["MAD:skmeans"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#>   Subgroups are detected by 'skmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 6.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk MAD-skmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk MAD-skmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.988       0.995         0.4911 0.510   0.510
#> 3 3 1.000           0.982       0.991         0.3144 0.834   0.678
#> 4 4 1.000           0.988       0.981         0.1304 0.905   0.737
#> 5 5 0.923           0.957       0.962         0.1015 0.918   0.701
#> 6 6 0.940           0.931       0.918         0.0289 0.981   0.900

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 6
#> attr(,"optional")
#> [1] 2 3 4 5

There is also optional best \(k\) = 2 3 4 5 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000      0.996 0.000 1.000
#> GSM379833     2  0.0000      0.996 0.000 1.000
#> GSM379834     2  0.0000      0.996 0.000 1.000
#> GSM379827     2  0.0000      0.996 0.000 1.000
#> GSM379828     2  0.0000      0.996 0.000 1.000
#> GSM379829     1  0.8144      0.663 0.748 0.252
#> GSM379830     2  0.0000      0.996 0.000 1.000
#> GSM379831     2  0.0000      0.996 0.000 1.000
#> GSM379840     2  0.0000      0.996 0.000 1.000
#> GSM379841     2  0.0000      0.996 0.000 1.000
#> GSM379842     2  0.0000      0.996 0.000 1.000
#> GSM379835     2  0.0000      0.996 0.000 1.000
#> GSM379836     2  0.0000      0.996 0.000 1.000
#> GSM379837     2  0.0000      0.996 0.000 1.000
#> GSM379838     2  0.0000      0.996 0.000 1.000
#> GSM379839     2  0.0000      0.996 0.000 1.000
#> GSM379848     2  0.0000      0.996 0.000 1.000
#> GSM379849     2  0.0000      0.996 0.000 1.000
#> GSM379850     2  0.0000      0.996 0.000 1.000
#> GSM379843     2  0.0000      0.996 0.000 1.000
#> GSM379844     2  0.0000      0.996 0.000 1.000
#> GSM379845     2  0.0000      0.996 0.000 1.000
#> GSM379846     2  0.0000      0.996 0.000 1.000
#> GSM379847     2  0.0000      0.996 0.000 1.000
#> GSM379853     2  0.0000      0.996 0.000 1.000
#> GSM379854     2  0.0000      0.996 0.000 1.000
#> GSM379851     2  0.0000      0.996 0.000 1.000
#> GSM379852     2  0.0000      0.996 0.000 1.000
#> GSM379804     1  0.0000      0.993 1.000 0.000
#> GSM379805     1  0.0000      0.993 1.000 0.000
#> GSM379806     1  0.0000      0.993 1.000 0.000
#> GSM379799     1  0.0000      0.993 1.000 0.000
#> GSM379800     1  0.0000      0.993 1.000 0.000
#> GSM379801     1  0.0000      0.993 1.000 0.000
#> GSM379802     1  0.0000      0.993 1.000 0.000
#> GSM379803     1  0.0000      0.993 1.000 0.000
#> GSM379812     1  0.0000      0.993 1.000 0.000
#> GSM379813     1  0.0000      0.993 1.000 0.000
#> GSM379814     1  0.0000      0.993 1.000 0.000
#> GSM379807     1  0.0000      0.993 1.000 0.000
#> GSM379808     1  0.0000      0.993 1.000 0.000
#> GSM379809     1  0.0000      0.993 1.000 0.000
#> GSM379810     1  0.0000      0.993 1.000 0.000
#> GSM379811     1  0.0000      0.993 1.000 0.000
#> GSM379820     1  0.0000      0.993 1.000 0.000
#> GSM379821     1  0.0000      0.993 1.000 0.000
#> GSM379822     1  0.0000      0.993 1.000 0.000
#> GSM379815     1  0.0000      0.993 1.000 0.000
#> GSM379816     1  0.0938      0.982 0.988 0.012
#> GSM379817     1  0.0000      0.993 1.000 0.000
#> GSM379818     1  0.0000      0.993 1.000 0.000
#> GSM379819     1  0.0000      0.993 1.000 0.000
#> GSM379825     1  0.0000      0.993 1.000 0.000
#> GSM379826     1  0.0000      0.993 1.000 0.000
#> GSM379823     1  0.0000      0.993 1.000 0.000
#> GSM379824     1  0.0000      0.993 1.000 0.000
#> GSM379749     2  0.0000      0.996 0.000 1.000
#> GSM379750     2  0.0000      0.996 0.000 1.000
#> GSM379751     2  0.0000      0.996 0.000 1.000
#> GSM379744     2  0.0000      0.996 0.000 1.000
#> GSM379745     2  0.0000      0.996 0.000 1.000
#> GSM379746     2  0.0000      0.996 0.000 1.000
#> GSM379747     2  0.0000      0.996 0.000 1.000
#> GSM379748     2  0.0000      0.996 0.000 1.000
#> GSM379757     2  0.0000      0.996 0.000 1.000
#> GSM379758     2  0.0000      0.996 0.000 1.000
#> GSM379752     2  0.0000      0.996 0.000 1.000
#> GSM379753     2  0.0000      0.996 0.000 1.000
#> GSM379754     2  0.0000      0.996 0.000 1.000
#> GSM379755     2  0.0000      0.996 0.000 1.000
#> GSM379756     2  0.0000      0.996 0.000 1.000
#> GSM379764     2  0.0000      0.996 0.000 1.000
#> GSM379765     2  0.0000      0.996 0.000 1.000
#> GSM379766     2  0.0000      0.996 0.000 1.000
#> GSM379759     2  0.0000      0.996 0.000 1.000
#> GSM379760     2  0.0000      0.996 0.000 1.000
#> GSM379761     2  0.0000      0.996 0.000 1.000
#> GSM379762     2  0.0000      0.996 0.000 1.000
#> GSM379763     2  0.0000      0.996 0.000 1.000
#> GSM379769     2  0.0000      0.996 0.000 1.000
#> GSM379770     2  0.0000      0.996 0.000 1.000
#> GSM379767     2  0.0000      0.996 0.000 1.000
#> GSM379768     2  0.0000      0.996 0.000 1.000
#> GSM379776     1  0.0000      0.993 1.000 0.000
#> GSM379777     1  0.0000      0.993 1.000 0.000
#> GSM379778     1  0.8327      0.641 0.736 0.264
#> GSM379771     1  0.0000      0.993 1.000 0.000
#> GSM379772     1  0.0000      0.993 1.000 0.000
#> GSM379773     1  0.0000      0.993 1.000 0.000
#> GSM379774     1  0.0000      0.993 1.000 0.000
#> GSM379775     1  0.0000      0.993 1.000 0.000
#> GSM379784     1  0.0000      0.993 1.000 0.000
#> GSM379785     1  0.0000      0.993 1.000 0.000
#> GSM379786     1  0.0000      0.993 1.000 0.000
#> GSM379779     1  0.0000      0.993 1.000 0.000
#> GSM379780     1  0.0000      0.993 1.000 0.000
#> GSM379781     1  0.0000      0.993 1.000 0.000
#> GSM379782     2  0.0000      0.996 0.000 1.000
#> GSM379783     1  0.0000      0.993 1.000 0.000
#> GSM379792     1  0.0000      0.993 1.000 0.000
#> GSM379793     1  0.0000      0.993 1.000 0.000
#> GSM379794     1  0.0000      0.993 1.000 0.000
#> GSM379787     2  0.7219      0.747 0.200 0.800
#> GSM379788     1  0.0000      0.993 1.000 0.000
#> GSM379789     1  0.0000      0.993 1.000 0.000
#> GSM379790     1  0.0000      0.993 1.000 0.000
#> GSM379791     1  0.0000      0.993 1.000 0.000
#> GSM379797     1  0.0000      0.993 1.000 0.000
#> GSM379798     1  0.0000      0.993 1.000 0.000
#> GSM379795     1  0.0000      0.993 1.000 0.000
#> GSM379796     1  0.0000      0.993 1.000 0.000
#> GSM379721     1  0.0000      0.993 1.000 0.000
#> GSM379722     1  0.0000      0.993 1.000 0.000
#> GSM379723     1  0.0000      0.993 1.000 0.000
#> GSM379716     1  0.0000      0.993 1.000 0.000
#> GSM379717     1  0.0000      0.993 1.000 0.000
#> GSM379718     1  0.0000      0.993 1.000 0.000
#> GSM379719     1  0.0000      0.993 1.000 0.000
#> GSM379720     1  0.0000      0.993 1.000 0.000
#> GSM379729     1  0.0000      0.993 1.000 0.000
#> GSM379730     1  0.0000      0.993 1.000 0.000
#> GSM379731     1  0.0000      0.993 1.000 0.000
#> GSM379724     1  0.0000      0.993 1.000 0.000
#> GSM379725     1  0.0000      0.993 1.000 0.000
#> GSM379726     1  0.0000      0.993 1.000 0.000
#> GSM379727     1  0.0000      0.993 1.000 0.000
#> GSM379728     1  0.0000      0.993 1.000 0.000
#> GSM379737     1  0.0000      0.993 1.000 0.000
#> GSM379738     1  0.0000      0.993 1.000 0.000
#> GSM379739     1  0.0000      0.993 1.000 0.000
#> GSM379732     1  0.0000      0.993 1.000 0.000
#> GSM379733     1  0.0000      0.993 1.000 0.000
#> GSM379734     1  0.0000      0.993 1.000 0.000
#> GSM379735     1  0.0000      0.993 1.000 0.000
#> GSM379736     1  0.0000      0.993 1.000 0.000
#> GSM379742     2  0.0000      0.996 0.000 1.000
#> GSM379743     1  0.0000      0.993 1.000 0.000
#> GSM379740     1  0.0000      0.993 1.000 0.000
#> GSM379741     2  0.0000      0.996 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379833     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379834     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379827     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379828     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379829     1  0.5803      0.662 0.736 0.248 0.016
#> GSM379830     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379831     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379840     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379841     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379842     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379835     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379836     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379837     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379838     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379839     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379848     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379849     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379850     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379843     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379844     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379845     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379846     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379847     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379853     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379854     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379851     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379852     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379804     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379805     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379806     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379799     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379800     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379801     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379802     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379803     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379812     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379813     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379814     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379807     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379808     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379809     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379810     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379811     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379820     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379821     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379822     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379815     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379816     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379817     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379818     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379819     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379825     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379826     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379823     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379824     1  0.0747      0.987 0.984 0.000 0.016
#> GSM379749     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379750     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379751     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379744     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379745     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379746     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379747     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379748     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379757     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379758     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379752     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379753     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379754     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379755     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379756     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379764     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379765     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379766     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379759     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379760     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379761     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379762     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379763     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379769     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379770     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379767     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379768     2  0.0000      0.989 0.000 1.000 0.000
#> GSM379776     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379777     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379778     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379771     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379772     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379773     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379774     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379775     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379784     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379785     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379786     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379779     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379780     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379781     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379782     2  0.4555      0.748 0.200 0.800 0.000
#> GSM379783     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379792     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379793     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379794     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379787     2  0.5760      0.521 0.328 0.672 0.000
#> GSM379788     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379789     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379790     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379791     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379797     1  0.0237      0.986 0.996 0.000 0.004
#> GSM379798     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379795     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379796     1  0.0000      0.986 1.000 0.000 0.000
#> GSM379721     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379722     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379723     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379716     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379717     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379718     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379719     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379720     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379729     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379730     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379731     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379724     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379725     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379726     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379727     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379728     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379737     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379738     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379739     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379732     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379733     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379734     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379735     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379736     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379742     3  0.0747      0.982 0.000 0.016 0.984
#> GSM379743     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379740     3  0.0000      0.999 0.000 0.000 1.000
#> GSM379741     3  0.0747      0.982 0.000 0.016 0.984

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2 p3    p4
#> GSM379832     2  0.1302      0.982 0.000 0.956  0 0.044
#> GSM379833     2  0.1302      0.982 0.000 0.956  0 0.044
#> GSM379834     2  0.1302      0.982 0.000 0.956  0 0.044
#> GSM379827     2  0.1302      0.982 0.000 0.956  0 0.044
#> GSM379828     2  0.1302      0.982 0.000 0.956  0 0.044
#> GSM379829     4  0.0000      0.939 0.000 0.000  0 1.000
#> GSM379830     2  0.1302      0.982 0.000 0.956  0 0.044
#> GSM379831     2  0.1302      0.982 0.000 0.956  0 0.044
#> GSM379840     2  0.1302      0.982 0.000 0.956  0 0.044
#> GSM379841     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379842     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379835     2  0.1302      0.982 0.000 0.956  0 0.044
#> GSM379836     2  0.1302      0.982 0.000 0.956  0 0.044
#> GSM379837     2  0.1389      0.980 0.000 0.952  0 0.048
#> GSM379838     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379839     2  0.1302      0.982 0.000 0.956  0 0.044
#> GSM379848     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379849     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379850     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379843     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379844     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379845     2  0.1302      0.982 0.000 0.956  0 0.044
#> GSM379846     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379847     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379853     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379854     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379851     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379852     2  0.1211      0.982 0.000 0.960  0 0.040
#> GSM379804     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379805     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379806     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379799     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379800     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379801     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379802     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379803     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379812     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379813     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379814     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379807     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379808     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379809     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379810     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379811     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379820     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379821     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379822     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379815     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379816     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379817     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379818     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379819     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379825     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379826     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379823     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379824     4  0.1302      0.991 0.044 0.000  0 0.956
#> GSM379749     2  0.0188      0.982 0.000 0.996  0 0.004
#> GSM379750     2  0.0188      0.982 0.000 0.996  0 0.004
#> GSM379751     2  0.0188      0.982 0.000 0.996  0 0.004
#> GSM379744     2  0.0188      0.982 0.000 0.996  0 0.004
#> GSM379745     2  0.0188      0.982 0.000 0.996  0 0.004
#> GSM379746     2  0.0188      0.982 0.000 0.996  0 0.004
#> GSM379747     2  0.0188      0.982 0.000 0.996  0 0.004
#> GSM379748     2  0.0188      0.982 0.000 0.996  0 0.004
#> GSM379757     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379758     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379752     2  0.0188      0.982 0.000 0.996  0 0.004
#> GSM379753     2  0.0188      0.982 0.000 0.996  0 0.004
#> GSM379754     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379755     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379756     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379764     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379765     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379766     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379759     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379760     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379761     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379762     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379763     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379769     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379770     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379767     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379768     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379776     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379777     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379778     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379771     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379772     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379773     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379774     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379775     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379784     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379785     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379786     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379779     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379780     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379781     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379782     1  0.0921      0.966 0.972 0.028  0 0.000
#> GSM379783     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379792     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379793     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379794     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379787     1  0.0817      0.971 0.976 0.024  0 0.000
#> GSM379788     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379789     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379790     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379791     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379797     4  0.4040      0.729 0.248 0.000  0 0.752
#> GSM379798     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379795     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379796     1  0.0000      0.997 1.000 0.000  0 0.000
#> GSM379721     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379722     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379723     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379716     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379717     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379718     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379719     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379720     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379729     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379730     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379731     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379724     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379725     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379726     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379727     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379728     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379737     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379738     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379739     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379732     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379733     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379734     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379735     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379736     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379742     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379743     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379740     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379741     3  0.0000      1.000 0.000 0.000  1 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     5  0.1043      0.905 0.000 0.040 0.000 0.000 0.960
#> GSM379833     5  0.1043      0.905 0.000 0.040 0.000 0.000 0.960
#> GSM379834     5  0.1043      0.905 0.000 0.040 0.000 0.000 0.960
#> GSM379827     5  0.1043      0.905 0.000 0.040 0.000 0.000 0.960
#> GSM379828     5  0.1043      0.905 0.000 0.040 0.000 0.000 0.960
#> GSM379829     5  0.1043      0.856 0.000 0.000 0.000 0.040 0.960
#> GSM379830     5  0.1043      0.905 0.000 0.040 0.000 0.000 0.960
#> GSM379831     5  0.1043      0.905 0.000 0.040 0.000 0.000 0.960
#> GSM379840     5  0.0880      0.901 0.000 0.032 0.000 0.000 0.968
#> GSM379841     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379842     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379835     5  0.1043      0.905 0.000 0.040 0.000 0.000 0.960
#> GSM379836     5  0.1043      0.905 0.000 0.040 0.000 0.000 0.960
#> GSM379837     5  0.0290      0.886 0.000 0.008 0.000 0.000 0.992
#> GSM379838     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379839     5  0.0510      0.891 0.000 0.016 0.000 0.000 0.984
#> GSM379848     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379849     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379850     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379843     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379844     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379845     5  0.1043      0.905 0.000 0.040 0.000 0.000 0.960
#> GSM379846     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379847     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379853     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379854     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379851     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379852     5  0.2966      0.907 0.000 0.184 0.000 0.000 0.816
#> GSM379804     4  0.0703      0.980 0.000 0.000 0.000 0.976 0.024
#> GSM379805     4  0.0880      0.979 0.000 0.000 0.000 0.968 0.032
#> GSM379806     4  0.0880      0.979 0.000 0.000 0.000 0.968 0.032
#> GSM379799     4  0.0880      0.979 0.000 0.000 0.000 0.968 0.032
#> GSM379800     4  0.0880      0.979 0.000 0.000 0.000 0.968 0.032
#> GSM379801     4  0.0880      0.979 0.000 0.000 0.000 0.968 0.032
#> GSM379802     4  0.0880      0.979 0.000 0.000 0.000 0.968 0.032
#> GSM379803     4  0.0880      0.979 0.000 0.000 0.000 0.968 0.032
#> GSM379812     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379813     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379814     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379807     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379808     4  0.0880      0.979 0.000 0.000 0.000 0.968 0.032
#> GSM379809     4  0.0880      0.979 0.000 0.000 0.000 0.968 0.032
#> GSM379810     4  0.0404      0.980 0.000 0.000 0.000 0.988 0.012
#> GSM379811     4  0.0880      0.979 0.000 0.000 0.000 0.968 0.032
#> GSM379820     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379821     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379822     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379815     4  0.0404      0.980 0.000 0.000 0.000 0.988 0.012
#> GSM379816     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379817     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379818     4  0.0880      0.979 0.000 0.000 0.000 0.968 0.032
#> GSM379819     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379825     4  0.0880      0.979 0.000 0.000 0.000 0.968 0.032
#> GSM379826     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379823     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379824     4  0.0000      0.980 0.000 0.000 0.000 1.000 0.000
#> GSM379749     2  0.2471      0.888 0.000 0.864 0.000 0.000 0.136
#> GSM379750     2  0.2471      0.888 0.000 0.864 0.000 0.000 0.136
#> GSM379751     2  0.2561      0.883 0.000 0.856 0.000 0.000 0.144
#> GSM379744     2  0.2561      0.883 0.000 0.856 0.000 0.000 0.144
#> GSM379745     2  0.2561      0.883 0.000 0.856 0.000 0.000 0.144
#> GSM379746     2  0.2471      0.888 0.000 0.864 0.000 0.000 0.136
#> GSM379747     2  0.2561      0.883 0.000 0.856 0.000 0.000 0.144
#> GSM379748     2  0.2561      0.883 0.000 0.856 0.000 0.000 0.144
#> GSM379757     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379758     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379752     2  0.2471      0.888 0.000 0.864 0.000 0.000 0.136
#> GSM379753     2  0.2561      0.883 0.000 0.856 0.000 0.000 0.144
#> GSM379754     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379755     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379756     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379764     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379765     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379766     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379759     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379760     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379761     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379762     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379763     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379769     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379770     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379767     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379768     2  0.0000      0.935 0.000 1.000 0.000 0.000 0.000
#> GSM379776     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379777     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379778     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379771     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379772     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379773     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379774     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379775     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379784     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379785     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379786     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379779     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379780     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379781     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379782     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379783     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379792     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379793     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379794     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379787     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379788     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379789     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379790     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379791     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379797     4  0.4058      0.690 0.236 0.000 0.000 0.740 0.024
#> GSM379798     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379796     1  0.0000      1.000 1.000 0.000 0.000 0.000 0.000
#> GSM379721     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379722     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379723     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379716     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379717     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379718     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379719     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379720     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379729     3  0.0290      0.996 0.000 0.000 0.992 0.000 0.008
#> GSM379730     3  0.0290      0.996 0.000 0.000 0.992 0.000 0.008
#> GSM379731     3  0.0290      0.996 0.000 0.000 0.992 0.000 0.008
#> GSM379724     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379725     3  0.0290      0.996 0.000 0.000 0.992 0.000 0.008
#> GSM379726     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379727     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379728     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379737     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379738     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379739     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379732     3  0.0290      0.996 0.000 0.000 0.992 0.000 0.008
#> GSM379733     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379734     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379735     3  0.0290      0.996 0.000 0.000 0.992 0.000 0.008
#> GSM379736     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379742     3  0.0290      0.996 0.000 0.000 0.992 0.000 0.008
#> GSM379743     3  0.0290      0.996 0.000 0.000 0.992 0.000 0.008
#> GSM379740     3  0.0000      0.998 0.000 0.000 1.000 0.000 0.000
#> GSM379741     3  0.0290      0.996 0.000 0.000 0.992 0.000 0.008

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     6  0.1700      0.846 0.000 0.004 0.000 0.000 0.080 0.916
#> GSM379833     6  0.1700      0.846 0.000 0.004 0.000 0.000 0.080 0.916
#> GSM379834     6  0.1700      0.846 0.000 0.004 0.000 0.000 0.080 0.916
#> GSM379827     5  0.3872      0.926 0.000 0.004 0.000 0.000 0.604 0.392
#> GSM379828     5  0.3872      0.926 0.000 0.004 0.000 0.000 0.604 0.392
#> GSM379829     5  0.5269      0.545 0.000 0.004 0.000 0.260 0.604 0.132
#> GSM379830     5  0.3881      0.930 0.000 0.004 0.000 0.000 0.600 0.396
#> GSM379831     5  0.3881      0.930 0.000 0.004 0.000 0.000 0.600 0.396
#> GSM379840     5  0.3944      0.883 0.000 0.004 0.000 0.000 0.568 0.428
#> GSM379841     6  0.0405      0.964 0.000 0.004 0.000 0.000 0.008 0.988
#> GSM379842     6  0.0405      0.964 0.000 0.004 0.000 0.000 0.008 0.988
#> GSM379835     5  0.3881      0.930 0.000 0.004 0.000 0.000 0.600 0.396
#> GSM379836     5  0.3881      0.930 0.000 0.004 0.000 0.000 0.600 0.396
#> GSM379837     5  0.3881      0.930 0.000 0.004 0.000 0.000 0.600 0.396
#> GSM379838     6  0.0405      0.964 0.000 0.004 0.000 0.000 0.008 0.988
#> GSM379839     5  0.3881      0.930 0.000 0.004 0.000 0.000 0.600 0.396
#> GSM379848     6  0.0146      0.965 0.000 0.004 0.000 0.000 0.000 0.996
#> GSM379849     6  0.0146      0.965 0.000 0.004 0.000 0.000 0.000 0.996
#> GSM379850     6  0.0146      0.965 0.000 0.004 0.000 0.000 0.000 0.996
#> GSM379843     6  0.0405      0.964 0.000 0.004 0.000 0.000 0.008 0.988
#> GSM379844     6  0.0405      0.964 0.000 0.004 0.000 0.000 0.008 0.988
#> GSM379845     5  0.3937      0.890 0.000 0.004 0.000 0.000 0.572 0.424
#> GSM379846     6  0.0291      0.965 0.000 0.004 0.000 0.000 0.004 0.992
#> GSM379847     6  0.0146      0.965 0.000 0.004 0.000 0.000 0.000 0.996
#> GSM379853     6  0.0146      0.965 0.000 0.004 0.000 0.000 0.000 0.996
#> GSM379854     6  0.0146      0.965 0.000 0.004 0.000 0.000 0.000 0.996
#> GSM379851     6  0.0146      0.965 0.000 0.004 0.000 0.000 0.000 0.996
#> GSM379852     6  0.0146      0.965 0.000 0.004 0.000 0.000 0.000 0.996
#> GSM379804     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379805     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379806     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379799     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379800     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379801     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379802     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379803     4  0.0146      0.877 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM379812     4  0.3221      0.856 0.000 0.000 0.000 0.736 0.264 0.000
#> GSM379813     4  0.3198      0.857 0.000 0.000 0.000 0.740 0.260 0.000
#> GSM379814     4  0.3198      0.857 0.000 0.000 0.000 0.740 0.260 0.000
#> GSM379807     4  0.3198      0.857 0.000 0.000 0.000 0.740 0.260 0.000
#> GSM379808     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379809     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379810     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379811     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379820     4  0.3198      0.857 0.000 0.000 0.000 0.740 0.260 0.000
#> GSM379821     4  0.3221      0.856 0.000 0.000 0.000 0.736 0.264 0.000
#> GSM379822     4  0.3221      0.856 0.000 0.000 0.000 0.736 0.264 0.000
#> GSM379815     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379816     4  0.3244      0.854 0.000 0.000 0.000 0.732 0.268 0.000
#> GSM379817     4  0.3198      0.857 0.000 0.000 0.000 0.740 0.260 0.000
#> GSM379818     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379819     4  0.3198      0.857 0.000 0.000 0.000 0.740 0.260 0.000
#> GSM379825     4  0.0000      0.878 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379826     4  0.3198      0.857 0.000 0.000 0.000 0.740 0.260 0.000
#> GSM379823     4  0.3221      0.856 0.000 0.000 0.000 0.736 0.264 0.000
#> GSM379824     4  0.3221      0.856 0.000 0.000 0.000 0.736 0.264 0.000
#> GSM379749     2  0.0713      0.922 0.000 0.972 0.000 0.000 0.028 0.000
#> GSM379750     2  0.0713      0.922 0.000 0.972 0.000 0.000 0.028 0.000
#> GSM379751     2  0.3052      0.727 0.000 0.780 0.000 0.000 0.216 0.004
#> GSM379744     2  0.0865      0.919 0.000 0.964 0.000 0.000 0.036 0.000
#> GSM379745     2  0.0865      0.919 0.000 0.964 0.000 0.000 0.036 0.000
#> GSM379746     2  0.0713      0.922 0.000 0.972 0.000 0.000 0.028 0.000
#> GSM379747     2  0.1010      0.917 0.000 0.960 0.000 0.000 0.036 0.004
#> GSM379748     2  0.1010      0.917 0.000 0.960 0.000 0.000 0.036 0.004
#> GSM379757     2  0.0146      0.927 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM379758     2  0.1895      0.923 0.000 0.912 0.000 0.000 0.072 0.016
#> GSM379752     2  0.0713      0.922 0.000 0.972 0.000 0.000 0.028 0.000
#> GSM379753     2  0.1010      0.917 0.000 0.960 0.000 0.000 0.036 0.004
#> GSM379754     2  0.0146      0.927 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM379755     2  0.0146      0.927 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM379756     2  0.0146      0.927 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM379764     2  0.2912      0.905 0.000 0.852 0.000 0.000 0.072 0.076
#> GSM379765     2  0.2912      0.905 0.000 0.852 0.000 0.000 0.072 0.076
#> GSM379766     2  0.2912      0.905 0.000 0.852 0.000 0.000 0.072 0.076
#> GSM379759     2  0.1588      0.924 0.000 0.924 0.000 0.000 0.072 0.004
#> GSM379760     2  0.1588      0.924 0.000 0.924 0.000 0.000 0.072 0.004
#> GSM379761     2  0.1895      0.923 0.000 0.912 0.000 0.000 0.072 0.016
#> GSM379762     2  0.1895      0.923 0.000 0.912 0.000 0.000 0.072 0.016
#> GSM379763     2  0.2912      0.905 0.000 0.852 0.000 0.000 0.072 0.076
#> GSM379769     2  0.2912      0.905 0.000 0.852 0.000 0.000 0.072 0.076
#> GSM379770     2  0.2912      0.905 0.000 0.852 0.000 0.000 0.072 0.076
#> GSM379767     2  0.2912      0.905 0.000 0.852 0.000 0.000 0.072 0.076
#> GSM379768     2  0.2912      0.905 0.000 0.852 0.000 0.000 0.072 0.076
#> GSM379776     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379777     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379778     1  0.0458      0.990 0.984 0.000 0.000 0.000 0.016 0.000
#> GSM379771     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379772     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379773     1  0.0458      0.990 0.984 0.000 0.000 0.000 0.016 0.000
#> GSM379774     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379775     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379784     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379785     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379786     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379779     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379780     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379781     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379782     1  0.0458      0.990 0.984 0.000 0.000 0.000 0.016 0.000
#> GSM379783     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379792     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379793     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379794     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379787     1  0.0458      0.990 0.984 0.000 0.000 0.000 0.016 0.000
#> GSM379788     1  0.0146      0.996 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379789     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379790     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379791     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379797     4  0.3023      0.668 0.232 0.000 0.000 0.768 0.000 0.000
#> GSM379798     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379796     1  0.0000      0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379721     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379722     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379723     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379716     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379717     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379718     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379719     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379720     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379729     3  0.1007      0.970 0.000 0.000 0.956 0.000 0.044 0.000
#> GSM379730     3  0.1007      0.970 0.000 0.000 0.956 0.000 0.044 0.000
#> GSM379731     3  0.1007      0.970 0.000 0.000 0.956 0.000 0.044 0.000
#> GSM379724     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379725     3  0.0713      0.974 0.000 0.000 0.972 0.000 0.028 0.000
#> GSM379726     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379727     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379728     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379737     3  0.0632      0.976 0.000 0.000 0.976 0.000 0.024 0.000
#> GSM379738     3  0.0632      0.976 0.000 0.000 0.976 0.000 0.024 0.000
#> GSM379739     3  0.0713      0.975 0.000 0.000 0.972 0.000 0.028 0.000
#> GSM379732     3  0.1007      0.970 0.000 0.000 0.956 0.000 0.044 0.000
#> GSM379733     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379734     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379735     3  0.1007      0.970 0.000 0.000 0.956 0.000 0.044 0.000
#> GSM379736     3  0.0000      0.980 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379742     3  0.2815      0.879 0.000 0.032 0.848 0.000 0.120 0.000
#> GSM379743     3  0.1007      0.970 0.000 0.000 0.956 0.000 0.044 0.000
#> GSM379740     3  0.0458      0.977 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM379741     3  0.2815      0.879 0.000 0.032 0.848 0.000 0.120 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-MAD-skmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-MAD-skmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-MAD-skmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-MAD-skmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-MAD-skmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-MAD-skmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-MAD-skmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-MAD-skmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-MAD-skmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-MAD-skmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-MAD-skmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-MAD-skmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-MAD-skmeans-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-MAD-skmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-MAD-skmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-MAD-skmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-MAD-skmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-MAD-skmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-MAD-skmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-MAD-skmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk MAD-skmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-MAD-skmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-MAD-skmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-MAD-skmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-MAD-skmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-MAD-skmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk MAD-skmeans-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>               n individual(p) time(p) agent(p) k
#> MAD:skmeans 139      6.01e-25       1    0.651 2
#> MAD:skmeans 139      1.97e-52       1    0.891 3
#> MAD:skmeans 139      2.80e-78       1    0.996 4
#> MAD:skmeans 139     5.15e-106       1    1.000 5
#> MAD:skmeans 139     5.38e-103       1    0.767 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

MAD:pam**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["MAD", "pam"]
# you can also extract it by
# res = res_list["MAD:pam"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#>   Subgroups are detected by 'pam' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 6.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk MAD-pam-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk MAD-pam-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2     1           0.995       0.997          0.489 0.513   0.513
#> 3 3     1           0.991       0.996          0.327 0.828   0.668
#> 4 4     1           0.963       0.962          0.125 0.907   0.741
#> 5 5     1           0.975       0.991          0.104 0.918   0.701
#> 6 6     1           0.953       0.982          0.029 0.970   0.847

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 6
#> attr(,"optional")
#> [1] 2 3 4 5

There is also optional best \(k\) = 2 3 4 5 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000      1.000 0.000 1.000
#> GSM379833     2  0.0000      1.000 0.000 1.000
#> GSM379834     2  0.0000      1.000 0.000 1.000
#> GSM379827     2  0.0000      1.000 0.000 1.000
#> GSM379828     2  0.0000      1.000 0.000 1.000
#> GSM379829     2  0.0376      0.996 0.004 0.996
#> GSM379830     2  0.0000      1.000 0.000 1.000
#> GSM379831     2  0.0000      1.000 0.000 1.000
#> GSM379840     2  0.0000      1.000 0.000 1.000
#> GSM379841     2  0.0000      1.000 0.000 1.000
#> GSM379842     2  0.0000      1.000 0.000 1.000
#> GSM379835     2  0.0000      1.000 0.000 1.000
#> GSM379836     2  0.0000      1.000 0.000 1.000
#> GSM379837     2  0.0000      1.000 0.000 1.000
#> GSM379838     2  0.0000      1.000 0.000 1.000
#> GSM379839     2  0.0000      1.000 0.000 1.000
#> GSM379848     2  0.0000      1.000 0.000 1.000
#> GSM379849     2  0.0000      1.000 0.000 1.000
#> GSM379850     2  0.0000      1.000 0.000 1.000
#> GSM379843     2  0.0000      1.000 0.000 1.000
#> GSM379844     2  0.0000      1.000 0.000 1.000
#> GSM379845     2  0.0000      1.000 0.000 1.000
#> GSM379846     2  0.0000      1.000 0.000 1.000
#> GSM379847     2  0.0000      1.000 0.000 1.000
#> GSM379853     2  0.0000      1.000 0.000 1.000
#> GSM379854     2  0.0000      1.000 0.000 1.000
#> GSM379851     2  0.0000      1.000 0.000 1.000
#> GSM379852     2  0.0000      1.000 0.000 1.000
#> GSM379804     1  0.0000      0.996 1.000 0.000
#> GSM379805     1  0.0000      0.996 1.000 0.000
#> GSM379806     1  0.0000      0.996 1.000 0.000
#> GSM379799     1  0.0000      0.996 1.000 0.000
#> GSM379800     1  0.0000      0.996 1.000 0.000
#> GSM379801     1  0.0000      0.996 1.000 0.000
#> GSM379802     1  0.0000      0.996 1.000 0.000
#> GSM379803     1  0.0000      0.996 1.000 0.000
#> GSM379812     1  0.0000      0.996 1.000 0.000
#> GSM379813     1  0.0000      0.996 1.000 0.000
#> GSM379814     1  0.0000      0.996 1.000 0.000
#> GSM379807     1  0.0000      0.996 1.000 0.000
#> GSM379808     1  0.0000      0.996 1.000 0.000
#> GSM379809     1  0.0000      0.996 1.000 0.000
#> GSM379810     1  0.0000      0.996 1.000 0.000
#> GSM379811     1  0.0000      0.996 1.000 0.000
#> GSM379820     1  0.0000      0.996 1.000 0.000
#> GSM379821     1  0.0000      0.996 1.000 0.000
#> GSM379822     1  0.0000      0.996 1.000 0.000
#> GSM379815     1  0.0000      0.996 1.000 0.000
#> GSM379816     1  0.6801      0.784 0.820 0.180
#> GSM379817     1  0.0000      0.996 1.000 0.000
#> GSM379818     1  0.0000      0.996 1.000 0.000
#> GSM379819     1  0.0000      0.996 1.000 0.000
#> GSM379825     1  0.0000      0.996 1.000 0.000
#> GSM379826     1  0.0000      0.996 1.000 0.000
#> GSM379823     1  0.0000      0.996 1.000 0.000
#> GSM379824     1  0.0000      0.996 1.000 0.000
#> GSM379749     2  0.0000      1.000 0.000 1.000
#> GSM379750     2  0.0000      1.000 0.000 1.000
#> GSM379751     2  0.0000      1.000 0.000 1.000
#> GSM379744     2  0.0000      1.000 0.000 1.000
#> GSM379745     2  0.0000      1.000 0.000 1.000
#> GSM379746     2  0.0000      1.000 0.000 1.000
#> GSM379747     2  0.0000      1.000 0.000 1.000
#> GSM379748     2  0.0000      1.000 0.000 1.000
#> GSM379757     2  0.0000      1.000 0.000 1.000
#> GSM379758     2  0.0000      1.000 0.000 1.000
#> GSM379752     2  0.0000      1.000 0.000 1.000
#> GSM379753     2  0.0000      1.000 0.000 1.000
#> GSM379754     2  0.0000      1.000 0.000 1.000
#> GSM379755     2  0.0000      1.000 0.000 1.000
#> GSM379756     2  0.0000      1.000 0.000 1.000
#> GSM379764     2  0.0000      1.000 0.000 1.000
#> GSM379765     2  0.0000      1.000 0.000 1.000
#> GSM379766     2  0.0000      1.000 0.000 1.000
#> GSM379759     2  0.0000      1.000 0.000 1.000
#> GSM379760     2  0.0000      1.000 0.000 1.000
#> GSM379761     2  0.0000      1.000 0.000 1.000
#> GSM379762     2  0.0000      1.000 0.000 1.000
#> GSM379763     2  0.0000      1.000 0.000 1.000
#> GSM379769     2  0.0000      1.000 0.000 1.000
#> GSM379770     2  0.0000      1.000 0.000 1.000
#> GSM379767     2  0.0000      1.000 0.000 1.000
#> GSM379768     2  0.0000      1.000 0.000 1.000
#> GSM379776     1  0.0000      0.996 1.000 0.000
#> GSM379777     1  0.0000      0.996 1.000 0.000
#> GSM379778     1  0.0000      0.996 1.000 0.000
#> GSM379771     1  0.0000      0.996 1.000 0.000
#> GSM379772     1  0.0000      0.996 1.000 0.000
#> GSM379773     1  0.0000      0.996 1.000 0.000
#> GSM379774     1  0.0000      0.996 1.000 0.000
#> GSM379775     1  0.0000      0.996 1.000 0.000
#> GSM379784     1  0.0000      0.996 1.000 0.000
#> GSM379785     1  0.0000      0.996 1.000 0.000
#> GSM379786     1  0.0000      0.996 1.000 0.000
#> GSM379779     1  0.0000      0.996 1.000 0.000
#> GSM379780     1  0.0000      0.996 1.000 0.000
#> GSM379781     1  0.0000      0.996 1.000 0.000
#> GSM379782     1  0.0000      0.996 1.000 0.000
#> GSM379783     1  0.0000      0.996 1.000 0.000
#> GSM379792     1  0.0000      0.996 1.000 0.000
#> GSM379793     1  0.0000      0.996 1.000 0.000
#> GSM379794     1  0.0000      0.996 1.000 0.000
#> GSM379787     1  0.0000      0.996 1.000 0.000
#> GSM379788     1  0.0000      0.996 1.000 0.000
#> GSM379789     1  0.0000      0.996 1.000 0.000
#> GSM379790     1  0.0000      0.996 1.000 0.000
#> GSM379791     1  0.0000      0.996 1.000 0.000
#> GSM379797     1  0.0000      0.996 1.000 0.000
#> GSM379798     1  0.0000      0.996 1.000 0.000
#> GSM379795     1  0.0000      0.996 1.000 0.000
#> GSM379796     1  0.0000      0.996 1.000 0.000
#> GSM379721     1  0.0000      0.996 1.000 0.000
#> GSM379722     1  0.0000      0.996 1.000 0.000
#> GSM379723     1  0.0000      0.996 1.000 0.000
#> GSM379716     1  0.0000      0.996 1.000 0.000
#> GSM379717     1  0.0000      0.996 1.000 0.000
#> GSM379718     1  0.0000      0.996 1.000 0.000
#> GSM379719     1  0.0000      0.996 1.000 0.000
#> GSM379720     1  0.0000      0.996 1.000 0.000
#> GSM379729     1  0.5842      0.839 0.860 0.140
#> GSM379730     1  0.1633      0.972 0.976 0.024
#> GSM379731     1  0.0000      0.996 1.000 0.000
#> GSM379724     1  0.0000      0.996 1.000 0.000
#> GSM379725     1  0.0000      0.996 1.000 0.000
#> GSM379726     1  0.0000      0.996 1.000 0.000
#> GSM379727     1  0.0000      0.996 1.000 0.000
#> GSM379728     1  0.0000      0.996 1.000 0.000
#> GSM379737     1  0.0000      0.996 1.000 0.000
#> GSM379738     1  0.0000      0.996 1.000 0.000
#> GSM379739     1  0.0000      0.996 1.000 0.000
#> GSM379732     1  0.0000      0.996 1.000 0.000
#> GSM379733     1  0.0000      0.996 1.000 0.000
#> GSM379734     1  0.0000      0.996 1.000 0.000
#> GSM379735     1  0.0000      0.996 1.000 0.000
#> GSM379736     1  0.0000      0.996 1.000 0.000
#> GSM379742     2  0.0000      1.000 0.000 1.000
#> GSM379743     1  0.0000      0.996 1.000 0.000
#> GSM379740     1  0.0000      0.996 1.000 0.000
#> GSM379741     2  0.0000      1.000 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379833     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379834     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379827     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379828     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379829     2  0.0475      0.992 0.004 0.992 0.004
#> GSM379830     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379831     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379840     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379841     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379842     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379835     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379836     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379837     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379838     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379839     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379848     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379849     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379850     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379843     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379844     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379845     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379846     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379847     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379853     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379854     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379851     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379852     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379804     1  0.0237      0.989 0.996 0.000 0.004
#> GSM379805     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379806     1  0.0747      0.978 0.984 0.000 0.016
#> GSM379799     1  0.4121      0.798 0.832 0.000 0.168
#> GSM379800     1  0.1529      0.954 0.960 0.000 0.040
#> GSM379801     3  0.3482      0.852 0.128 0.000 0.872
#> GSM379802     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379803     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379812     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379813     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379814     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379807     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379808     1  0.0237      0.988 0.996 0.000 0.004
#> GSM379809     1  0.0237      0.989 0.996 0.000 0.004
#> GSM379810     1  0.0237      0.989 0.996 0.000 0.004
#> GSM379811     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379820     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379821     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379822     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379815     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379816     1  0.4291      0.770 0.820 0.180 0.000
#> GSM379817     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379818     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379819     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379825     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379826     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379823     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379824     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379749     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379750     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379751     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379744     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379745     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379746     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379747     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379748     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379757     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379758     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379752     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379753     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379754     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379755     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379756     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379764     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379765     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379766     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379759     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379760     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379761     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379762     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379763     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379769     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379770     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379767     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379768     2  0.0000      1.000 0.000 1.000 0.000
#> GSM379776     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379777     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379778     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379771     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379772     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379773     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379774     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379775     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379784     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379785     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379786     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379779     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379780     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379781     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379782     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379783     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379792     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379793     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379794     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379787     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379788     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379789     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379790     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379791     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379797     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379798     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379795     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379796     1  0.0000      0.992 1.000 0.000 0.000
#> GSM379721     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379722     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379723     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379716     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379717     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379718     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379719     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379720     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379729     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379730     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379731     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379724     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379725     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379726     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379727     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379728     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379737     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379738     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379739     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379732     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379733     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379734     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379735     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379736     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379742     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379743     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379740     3  0.0000      0.995 0.000 0.000 1.000
#> GSM379741     3  0.0000      0.995 0.000 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1   p2    p3    p4
#> GSM379832     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379833     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379834     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379827     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379828     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379829     4  0.2011      0.879 0.000 0.08 0.000 0.920
#> GSM379830     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379831     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379840     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379841     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379842     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379835     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379836     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379837     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379838     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379839     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379848     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379849     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379850     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379843     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379844     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379845     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379846     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379847     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379853     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379854     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379851     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379852     2  0.0000      0.965 0.000 1.00 0.000 0.000
#> GSM379804     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379805     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379806     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379799     4  0.2363      0.945 0.056 0.00 0.024 0.920
#> GSM379800     4  0.2125      0.966 0.076 0.00 0.004 0.920
#> GSM379801     4  0.2011      0.880 0.000 0.00 0.080 0.920
#> GSM379802     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379803     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379812     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379813     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379814     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379807     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379808     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379809     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379810     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379811     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379820     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379821     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379822     4  0.4999      0.168 0.492 0.00 0.000 0.508
#> GSM379815     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379816     4  0.3219      0.880 0.164 0.00 0.000 0.836
#> GSM379817     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379818     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379819     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379825     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379826     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379823     1  0.4817      0.241 0.612 0.00 0.000 0.388
#> GSM379824     4  0.2011      0.970 0.080 0.00 0.000 0.920
#> GSM379749     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379750     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379751     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379744     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379745     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379746     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379747     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379748     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379757     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379758     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379752     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379753     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379754     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379755     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379756     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379764     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379765     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379766     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379759     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379760     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379761     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379762     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379763     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379769     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379770     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379767     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379768     2  0.2011      0.965 0.000 0.92 0.000 0.080
#> GSM379776     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379777     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379778     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379771     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379772     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379773     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379774     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379775     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379784     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379785     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379786     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379779     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379780     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379781     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379782     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379783     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379792     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379793     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379794     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379787     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379788     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379789     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379790     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379791     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379797     1  0.0336      0.976 0.992 0.00 0.000 0.008
#> GSM379798     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379795     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379796     1  0.0000      0.984 1.000 0.00 0.000 0.000
#> GSM379721     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379722     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379723     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379716     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379717     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379718     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379719     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379720     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379729     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379730     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379731     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379724     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379725     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379726     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379727     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379728     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379737     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379738     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379739     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379732     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379733     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379734     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379735     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379736     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379742     3  0.2011      0.915 0.000 0.00 0.920 0.080
#> GSM379743     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379740     3  0.0000      0.997 0.000 0.00 1.000 0.000
#> GSM379741     3  0.0000      0.997 0.000 0.00 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1   p2   p3    p4 p5
#> GSM379832     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379833     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379834     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379827     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379828     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379829     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379830     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379831     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379840     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379841     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379842     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379835     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379836     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379837     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379838     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379839     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379848     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379849     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379850     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379843     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379844     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379845     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379846     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379847     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379853     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379854     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379851     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379852     5   0.000     1.0000 0.000 0.00 0.00 0.000  1
#> GSM379804     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379805     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379806     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379799     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379800     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379801     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379802     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379803     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379812     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379813     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379814     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379807     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379808     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379809     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379810     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379811     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379820     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379821     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379822     4   0.431     0.0141 0.492 0.00 0.00 0.508  0
#> GSM379815     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379816     4   0.238     0.8379 0.128 0.00 0.00 0.872  0
#> GSM379817     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379818     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379819     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379825     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379826     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379823     1   0.415     0.3357 0.612 0.00 0.00 0.388  0
#> GSM379824     4   0.000     0.9763 0.000 0.00 0.00 1.000  0
#> GSM379749     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379750     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379751     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379744     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379745     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379746     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379747     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379748     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379757     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379758     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379752     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379753     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379754     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379755     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379756     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379764     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379765     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379766     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379759     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379760     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379761     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379762     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379763     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379769     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379770     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379767     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379768     2   0.000     0.9903 0.000 1.00 0.00 0.000  0
#> GSM379776     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379777     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379778     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379771     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379772     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379773     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379774     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379775     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379784     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379785     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379786     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379779     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379780     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379781     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379782     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379783     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379792     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379793     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379794     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379787     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379788     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379789     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379790     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379791     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379797     1   0.029     0.9776 0.992 0.00 0.00 0.008  0
#> GSM379798     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379795     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379796     1   0.000     0.9852 1.000 0.00 0.00 0.000  0
#> GSM379721     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379722     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379723     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379716     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379717     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379718     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379719     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379720     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379729     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379730     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379731     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379724     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379725     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379726     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379727     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379728     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379737     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379738     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379739     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379732     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379733     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379734     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379735     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379736     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379742     2   0.356     0.6486 0.000 0.74 0.26 0.000  0
#> GSM379743     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379740     3   0.000     1.0000 0.000 0.00 1.00 0.000  0
#> GSM379741     3   0.000     1.0000 0.000 0.00 1.00 0.000  0

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2   p3    p4    p5    p6
#> GSM379832     5  0.0146     0.9650 0.000 0.000 0.00 0.000 0.996 0.004
#> GSM379833     6  0.0260     0.9845 0.000 0.000 0.00 0.000 0.008 0.992
#> GSM379834     5  0.3659     0.4435 0.000 0.000 0.00 0.000 0.636 0.364
#> GSM379827     5  0.0146     0.9650 0.000 0.000 0.00 0.000 0.996 0.004
#> GSM379828     5  0.0146     0.9650 0.000 0.000 0.00 0.000 0.996 0.004
#> GSM379829     5  0.0146     0.9615 0.000 0.000 0.00 0.004 0.996 0.000
#> GSM379830     5  0.0146     0.9650 0.000 0.000 0.00 0.000 0.996 0.004
#> GSM379831     5  0.0146     0.9650 0.000 0.000 0.00 0.000 0.996 0.004
#> GSM379840     5  0.0146     0.9650 0.000 0.000 0.00 0.000 0.996 0.004
#> GSM379841     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379842     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379835     5  0.0146     0.9650 0.000 0.000 0.00 0.000 0.996 0.004
#> GSM379836     5  0.0146     0.9650 0.000 0.000 0.00 0.000 0.996 0.004
#> GSM379837     5  0.0146     0.9650 0.000 0.000 0.00 0.000 0.996 0.004
#> GSM379838     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379839     5  0.0146     0.9650 0.000 0.000 0.00 0.000 0.996 0.004
#> GSM379848     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379849     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379850     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379843     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379844     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379845     6  0.2003     0.8646 0.000 0.000 0.00 0.000 0.116 0.884
#> GSM379846     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379847     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379853     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379854     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379851     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379852     6  0.0000     0.9914 0.000 0.000 0.00 0.000 0.000 1.000
#> GSM379804     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379805     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379806     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379799     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379800     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379801     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379802     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379803     4  0.0146     0.9651 0.000 0.000 0.00 0.996 0.004 0.000
#> GSM379812     4  0.0146     0.9651 0.000 0.000 0.00 0.996 0.004 0.000
#> GSM379813     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379814     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379807     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379808     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379809     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379810     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379811     4  0.0146     0.9651 0.000 0.000 0.00 0.996 0.004 0.000
#> GSM379820     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379821     4  0.0146     0.9651 0.000 0.000 0.00 0.996 0.004 0.000
#> GSM379822     4  0.3997     0.0235 0.488 0.000 0.00 0.508 0.004 0.000
#> GSM379815     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379816     4  0.4277     0.6742 0.124 0.000 0.00 0.732 0.144 0.000
#> GSM379817     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379818     4  0.0146     0.9651 0.000 0.000 0.00 0.996 0.004 0.000
#> GSM379819     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379825     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379826     4  0.0000     0.9669 0.000 0.000 0.00 1.000 0.000 0.000
#> GSM379823     1  0.3862     0.3292 0.608 0.000 0.00 0.388 0.004 0.000
#> GSM379824     4  0.0146     0.9651 0.000 0.000 0.00 0.996 0.004 0.000
#> GSM379749     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379750     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379751     5  0.0458     0.9525 0.000 0.016 0.00 0.000 0.984 0.000
#> GSM379744     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379745     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379746     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379747     5  0.1204     0.9127 0.000 0.056 0.00 0.000 0.944 0.000
#> GSM379748     2  0.1663     0.8829 0.000 0.912 0.00 0.000 0.088 0.000
#> GSM379757     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379758     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379752     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379753     2  0.3706     0.3742 0.000 0.620 0.00 0.000 0.380 0.000
#> GSM379754     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379755     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379756     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379764     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379765     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379766     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379759     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379760     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379761     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379762     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379763     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379769     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379770     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379767     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379768     2  0.0000     0.9681 0.000 1.000 0.00 0.000 0.000 0.000
#> GSM379776     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379777     1  0.0146     0.9801 0.996 0.000 0.00 0.000 0.004 0.000
#> GSM379778     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379771     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379772     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379773     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379774     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379775     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379784     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379785     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379786     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379779     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379780     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379781     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379782     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379783     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379792     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379793     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379794     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379787     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379788     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379789     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379790     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379791     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379797     1  0.0363     0.9715 0.988 0.000 0.00 0.012 0.000 0.000
#> GSM379798     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379795     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379796     1  0.0000     0.9833 1.000 0.000 0.00 0.000 0.000 0.000
#> GSM379721     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379722     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379723     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379716     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379717     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379718     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379719     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379720     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379729     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379730     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379731     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379724     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379725     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379726     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379727     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379728     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379737     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379738     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379739     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379732     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379733     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379734     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379735     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379736     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379742     2  0.3198     0.6431 0.000 0.740 0.26 0.000 0.000 0.000
#> GSM379743     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379740     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000
#> GSM379741     3  0.0000     1.0000 0.000 0.000 1.00 0.000 0.000 0.000

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-MAD-pam-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-MAD-pam-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-MAD-pam-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-MAD-pam-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-MAD-pam-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-MAD-pam-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-MAD-pam-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-MAD-pam-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-MAD-pam-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-MAD-pam-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-MAD-pam-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-MAD-pam-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-MAD-pam-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-MAD-pam-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-MAD-pam-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-MAD-pam-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-MAD-pam-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-MAD-pam-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-MAD-pam-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-MAD-pam-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk MAD-pam-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-MAD-pam-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-MAD-pam-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-MAD-pam-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-MAD-pam-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-MAD-pam-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk MAD-pam-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>           n individual(p) time(p) agent(p) k
#> MAD:pam 139      2.03e-27       1   1.0000 2
#> MAD:pam 139      6.21e-54       1   0.9345 3
#> MAD:pam 137      6.35e-79       1   0.9625 4
#> MAD:pam 137     3.01e-102       1   0.9844 5
#> MAD:pam 135      5.15e-96       1   0.0498 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

MAD:mclust**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["MAD", "mclust"]
# you can also extract it by
# res = res_list["MAD:mclust"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#>   Subgroups are detected by 'mclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 4.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk MAD-mclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk MAD-mclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.752           0.931       0.932         0.4750 0.518   0.518
#> 3 3 1.000           0.996       0.998         0.3580 0.837   0.685
#> 4 4 0.969           0.961       0.959         0.0810 0.948   0.855
#> 5 5 0.820           0.805       0.903         0.1208 0.931   0.771
#> 6 6 0.898           0.856       0.926         0.0221 0.915   0.673

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 4
#> attr(,"optional")
#> [1] 3

There is also optional best \(k\) = 3 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.3584      0.976 0.068 0.932
#> GSM379833     2  0.3584      0.976 0.068 0.932
#> GSM379834     2  0.3584      0.976 0.068 0.932
#> GSM379827     2  0.3584      0.976 0.068 0.932
#> GSM379828     2  0.3584      0.976 0.068 0.932
#> GSM379829     2  0.3584      0.976 0.068 0.932
#> GSM379830     2  0.3584      0.976 0.068 0.932
#> GSM379831     2  0.3584      0.976 0.068 0.932
#> GSM379840     2  0.3584      0.976 0.068 0.932
#> GSM379841     2  0.3584      0.976 0.068 0.932
#> GSM379842     2  0.3584      0.976 0.068 0.932
#> GSM379835     2  0.3584      0.976 0.068 0.932
#> GSM379836     2  0.3584      0.976 0.068 0.932
#> GSM379837     2  0.3584      0.976 0.068 0.932
#> GSM379838     2  0.3584      0.976 0.068 0.932
#> GSM379839     2  0.3584      0.976 0.068 0.932
#> GSM379848     2  0.3584      0.976 0.068 0.932
#> GSM379849     2  0.3584      0.976 0.068 0.932
#> GSM379850     2  0.3584      0.976 0.068 0.932
#> GSM379843     2  0.3584      0.976 0.068 0.932
#> GSM379844     2  0.3584      0.976 0.068 0.932
#> GSM379845     2  0.3584      0.976 0.068 0.932
#> GSM379846     2  0.3584      0.976 0.068 0.932
#> GSM379847     2  0.3584      0.976 0.068 0.932
#> GSM379853     2  0.3584      0.976 0.068 0.932
#> GSM379854     2  0.3584      0.976 0.068 0.932
#> GSM379851     2  0.3584      0.976 0.068 0.932
#> GSM379852     2  0.3584      0.976 0.068 0.932
#> GSM379804     1  0.1843      0.933 0.972 0.028
#> GSM379805     1  0.1843      0.933 0.972 0.028
#> GSM379806     1  0.1843      0.933 0.972 0.028
#> GSM379799     1  0.1843      0.933 0.972 0.028
#> GSM379800     1  0.1843      0.933 0.972 0.028
#> GSM379801     1  0.1843      0.933 0.972 0.028
#> GSM379802     1  0.1843      0.933 0.972 0.028
#> GSM379803     1  0.1843      0.933 0.972 0.028
#> GSM379812     1  0.1843      0.933 0.972 0.028
#> GSM379813     1  0.1843      0.933 0.972 0.028
#> GSM379814     1  0.1843      0.933 0.972 0.028
#> GSM379807     1  0.1843      0.933 0.972 0.028
#> GSM379808     1  0.1843      0.933 0.972 0.028
#> GSM379809     1  0.1843      0.933 0.972 0.028
#> GSM379810     1  0.1843      0.933 0.972 0.028
#> GSM379811     1  0.1843      0.933 0.972 0.028
#> GSM379820     1  0.1843      0.933 0.972 0.028
#> GSM379821     1  0.1843      0.933 0.972 0.028
#> GSM379822     1  0.1843      0.933 0.972 0.028
#> GSM379815     1  0.1843      0.933 0.972 0.028
#> GSM379816     1  0.8443      0.695 0.728 0.272
#> GSM379817     1  0.1843      0.933 0.972 0.028
#> GSM379818     1  0.1843      0.933 0.972 0.028
#> GSM379819     1  0.1843      0.933 0.972 0.028
#> GSM379825     1  0.1843      0.933 0.972 0.028
#> GSM379826     1  0.1843      0.933 0.972 0.028
#> GSM379823     1  0.1843      0.933 0.972 0.028
#> GSM379824     1  0.1843      0.933 0.972 0.028
#> GSM379749     2  0.2603      0.968 0.044 0.956
#> GSM379750     2  0.3584      0.976 0.068 0.932
#> GSM379751     2  0.3584      0.976 0.068 0.932
#> GSM379744     2  0.0672      0.935 0.008 0.992
#> GSM379745     2  0.0000      0.941 0.000 1.000
#> GSM379746     2  0.0672      0.947 0.008 0.992
#> GSM379747     2  0.3274      0.974 0.060 0.940
#> GSM379748     2  0.3584      0.976 0.068 0.932
#> GSM379757     2  0.3114      0.973 0.056 0.944
#> GSM379758     2  0.2778      0.970 0.048 0.952
#> GSM379752     2  0.0672      0.935 0.008 0.992
#> GSM379753     2  0.0672      0.935 0.008 0.992
#> GSM379754     2  0.0672      0.935 0.008 0.992
#> GSM379755     2  0.0376      0.944 0.004 0.996
#> GSM379756     2  0.2236      0.964 0.036 0.964
#> GSM379764     2  0.3274      0.974 0.060 0.940
#> GSM379765     2  0.2948      0.972 0.052 0.948
#> GSM379766     2  0.2423      0.966 0.040 0.960
#> GSM379759     2  0.0672      0.935 0.008 0.992
#> GSM379760     2  0.0672      0.935 0.008 0.992
#> GSM379761     2  0.0000      0.941 0.000 1.000
#> GSM379762     2  0.0376      0.944 0.004 0.996
#> GSM379763     2  0.1843      0.959 0.028 0.972
#> GSM379769     2  0.3584      0.976 0.068 0.932
#> GSM379770     2  0.3584      0.976 0.068 0.932
#> GSM379767     2  0.0672      0.935 0.008 0.992
#> GSM379768     2  0.0938      0.950 0.012 0.988
#> GSM379776     1  0.1843      0.933 0.972 0.028
#> GSM379777     1  0.1843      0.933 0.972 0.028
#> GSM379778     1  0.3274      0.920 0.940 0.060
#> GSM379771     1  0.1843      0.933 0.972 0.028
#> GSM379772     1  0.1843      0.933 0.972 0.028
#> GSM379773     1  0.1843      0.933 0.972 0.028
#> GSM379774     1  0.1843      0.933 0.972 0.028
#> GSM379775     1  0.1843      0.933 0.972 0.028
#> GSM379784     1  0.1843      0.933 0.972 0.028
#> GSM379785     1  0.1843      0.933 0.972 0.028
#> GSM379786     1  0.1843      0.933 0.972 0.028
#> GSM379779     1  0.1843      0.933 0.972 0.028
#> GSM379780     1  0.1843      0.933 0.972 0.028
#> GSM379781     1  0.1843      0.933 0.972 0.028
#> GSM379782     1  0.7139      0.814 0.804 0.196
#> GSM379783     1  0.2423      0.926 0.960 0.040
#> GSM379792     1  0.1843      0.933 0.972 0.028
#> GSM379793     1  0.1843      0.933 0.972 0.028
#> GSM379794     1  0.1843      0.933 0.972 0.028
#> GSM379787     1  0.5629      0.878 0.868 0.132
#> GSM379788     1  0.1843      0.933 0.972 0.028
#> GSM379789     1  0.1843      0.933 0.972 0.028
#> GSM379790     1  0.1843      0.933 0.972 0.028
#> GSM379791     1  0.1843      0.933 0.972 0.028
#> GSM379797     1  0.1843      0.933 0.972 0.028
#> GSM379798     1  0.1843      0.933 0.972 0.028
#> GSM379795     1  0.1843      0.933 0.972 0.028
#> GSM379796     1  0.1843      0.933 0.972 0.028
#> GSM379721     1  0.6438      0.875 0.836 0.164
#> GSM379722     1  0.6438      0.875 0.836 0.164
#> GSM379723     1  0.6438      0.875 0.836 0.164
#> GSM379716     1  0.6438      0.875 0.836 0.164
#> GSM379717     1  0.6438      0.875 0.836 0.164
#> GSM379718     1  0.6438      0.875 0.836 0.164
#> GSM379719     1  0.6438      0.875 0.836 0.164
#> GSM379720     1  0.6438      0.875 0.836 0.164
#> GSM379729     1  0.6438      0.875 0.836 0.164
#> GSM379730     1  0.6438      0.875 0.836 0.164
#> GSM379731     1  0.6438      0.875 0.836 0.164
#> GSM379724     1  0.6438      0.875 0.836 0.164
#> GSM379725     1  0.6438      0.875 0.836 0.164
#> GSM379726     1  0.6438      0.875 0.836 0.164
#> GSM379727     1  0.6438      0.875 0.836 0.164
#> GSM379728     1  0.6438      0.875 0.836 0.164
#> GSM379737     1  0.6438      0.875 0.836 0.164
#> GSM379738     1  0.6438      0.875 0.836 0.164
#> GSM379739     1  0.6438      0.875 0.836 0.164
#> GSM379732     1  0.6438      0.875 0.836 0.164
#> GSM379733     1  0.6438      0.875 0.836 0.164
#> GSM379734     1  0.6438      0.875 0.836 0.164
#> GSM379735     1  0.6438      0.875 0.836 0.164
#> GSM379736     1  0.6438      0.875 0.836 0.164
#> GSM379742     1  0.6438      0.875 0.836 0.164
#> GSM379743     1  0.6438      0.875 0.836 0.164
#> GSM379740     1  0.6438      0.875 0.836 0.164
#> GSM379741     1  0.6438      0.875 0.836 0.164

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2   0.000      0.999 0.000 1.000 0.000
#> GSM379833     2   0.000      0.999 0.000 1.000 0.000
#> GSM379834     2   0.000      0.999 0.000 1.000 0.000
#> GSM379827     2   0.000      0.999 0.000 1.000 0.000
#> GSM379828     2   0.000      0.999 0.000 1.000 0.000
#> GSM379829     2   0.129      0.962 0.032 0.968 0.000
#> GSM379830     2   0.000      0.999 0.000 1.000 0.000
#> GSM379831     2   0.000      0.999 0.000 1.000 0.000
#> GSM379840     2   0.000      0.999 0.000 1.000 0.000
#> GSM379841     2   0.000      0.999 0.000 1.000 0.000
#> GSM379842     2   0.000      0.999 0.000 1.000 0.000
#> GSM379835     2   0.000      0.999 0.000 1.000 0.000
#> GSM379836     2   0.000      0.999 0.000 1.000 0.000
#> GSM379837     2   0.000      0.999 0.000 1.000 0.000
#> GSM379838     2   0.000      0.999 0.000 1.000 0.000
#> GSM379839     2   0.000      0.999 0.000 1.000 0.000
#> GSM379848     2   0.000      0.999 0.000 1.000 0.000
#> GSM379849     2   0.000      0.999 0.000 1.000 0.000
#> GSM379850     2   0.000      0.999 0.000 1.000 0.000
#> GSM379843     2   0.000      0.999 0.000 1.000 0.000
#> GSM379844     2   0.000      0.999 0.000 1.000 0.000
#> GSM379845     2   0.000      0.999 0.000 1.000 0.000
#> GSM379846     2   0.000      0.999 0.000 1.000 0.000
#> GSM379847     2   0.000      0.999 0.000 1.000 0.000
#> GSM379853     2   0.000      0.999 0.000 1.000 0.000
#> GSM379854     2   0.000      0.999 0.000 1.000 0.000
#> GSM379851     2   0.000      0.999 0.000 1.000 0.000
#> GSM379852     2   0.000      0.999 0.000 1.000 0.000
#> GSM379804     1   0.000      0.999 1.000 0.000 0.000
#> GSM379805     1   0.000      0.999 1.000 0.000 0.000
#> GSM379806     1   0.000      0.999 1.000 0.000 0.000
#> GSM379799     1   0.000      0.999 1.000 0.000 0.000
#> GSM379800     1   0.000      0.999 1.000 0.000 0.000
#> GSM379801     1   0.000      0.999 1.000 0.000 0.000
#> GSM379802     1   0.000      0.999 1.000 0.000 0.000
#> GSM379803     1   0.000      0.999 1.000 0.000 0.000
#> GSM379812     1   0.000      0.999 1.000 0.000 0.000
#> GSM379813     1   0.000      0.999 1.000 0.000 0.000
#> GSM379814     1   0.000      0.999 1.000 0.000 0.000
#> GSM379807     1   0.000      0.999 1.000 0.000 0.000
#> GSM379808     1   0.000      0.999 1.000 0.000 0.000
#> GSM379809     1   0.000      0.999 1.000 0.000 0.000
#> GSM379810     1   0.000      0.999 1.000 0.000 0.000
#> GSM379811     1   0.000      0.999 1.000 0.000 0.000
#> GSM379820     1   0.000      0.999 1.000 0.000 0.000
#> GSM379821     1   0.000      0.999 1.000 0.000 0.000
#> GSM379822     1   0.000      0.999 1.000 0.000 0.000
#> GSM379815     1   0.000      0.999 1.000 0.000 0.000
#> GSM379816     1   0.141      0.957 0.964 0.036 0.000
#> GSM379817     1   0.000      0.999 1.000 0.000 0.000
#> GSM379818     1   0.000      0.999 1.000 0.000 0.000
#> GSM379819     1   0.000      0.999 1.000 0.000 0.000
#> GSM379825     1   0.000      0.999 1.000 0.000 0.000
#> GSM379826     1   0.000      0.999 1.000 0.000 0.000
#> GSM379823     1   0.000      0.999 1.000 0.000 0.000
#> GSM379824     1   0.000      0.999 1.000 0.000 0.000
#> GSM379749     2   0.000      0.999 0.000 1.000 0.000
#> GSM379750     2   0.000      0.999 0.000 1.000 0.000
#> GSM379751     2   0.000      0.999 0.000 1.000 0.000
#> GSM379744     2   0.000      0.999 0.000 1.000 0.000
#> GSM379745     2   0.000      0.999 0.000 1.000 0.000
#> GSM379746     2   0.000      0.999 0.000 1.000 0.000
#> GSM379747     2   0.000      0.999 0.000 1.000 0.000
#> GSM379748     2   0.000      0.999 0.000 1.000 0.000
#> GSM379757     2   0.000      0.999 0.000 1.000 0.000
#> GSM379758     2   0.000      0.999 0.000 1.000 0.000
#> GSM379752     2   0.000      0.999 0.000 1.000 0.000
#> GSM379753     2   0.000      0.999 0.000 1.000 0.000
#> GSM379754     2   0.000      0.999 0.000 1.000 0.000
#> GSM379755     2   0.000      0.999 0.000 1.000 0.000
#> GSM379756     2   0.000      0.999 0.000 1.000 0.000
#> GSM379764     2   0.000      0.999 0.000 1.000 0.000
#> GSM379765     2   0.000      0.999 0.000 1.000 0.000
#> GSM379766     2   0.000      0.999 0.000 1.000 0.000
#> GSM379759     2   0.000      0.999 0.000 1.000 0.000
#> GSM379760     2   0.000      0.999 0.000 1.000 0.000
#> GSM379761     2   0.000      0.999 0.000 1.000 0.000
#> GSM379762     2   0.000      0.999 0.000 1.000 0.000
#> GSM379763     2   0.000      0.999 0.000 1.000 0.000
#> GSM379769     2   0.000      0.999 0.000 1.000 0.000
#> GSM379770     2   0.000      0.999 0.000 1.000 0.000
#> GSM379767     2   0.000      0.999 0.000 1.000 0.000
#> GSM379768     2   0.000      0.999 0.000 1.000 0.000
#> GSM379776     1   0.000      0.999 1.000 0.000 0.000
#> GSM379777     1   0.000      0.999 1.000 0.000 0.000
#> GSM379778     1   0.000      0.999 1.000 0.000 0.000
#> GSM379771     1   0.000      0.999 1.000 0.000 0.000
#> GSM379772     1   0.000      0.999 1.000 0.000 0.000
#> GSM379773     1   0.000      0.999 1.000 0.000 0.000
#> GSM379774     1   0.000      0.999 1.000 0.000 0.000
#> GSM379775     1   0.000      0.999 1.000 0.000 0.000
#> GSM379784     1   0.000      0.999 1.000 0.000 0.000
#> GSM379785     1   0.000      0.999 1.000 0.000 0.000
#> GSM379786     1   0.000      0.999 1.000 0.000 0.000
#> GSM379779     1   0.000      0.999 1.000 0.000 0.000
#> GSM379780     1   0.000      0.999 1.000 0.000 0.000
#> GSM379781     1   0.000      0.999 1.000 0.000 0.000
#> GSM379782     1   0.000      0.999 1.000 0.000 0.000
#> GSM379783     1   0.000      0.999 1.000 0.000 0.000
#> GSM379792     1   0.000      0.999 1.000 0.000 0.000
#> GSM379793     1   0.000      0.999 1.000 0.000 0.000
#> GSM379794     1   0.000      0.999 1.000 0.000 0.000
#> GSM379787     1   0.000      0.999 1.000 0.000 0.000
#> GSM379788     1   0.000      0.999 1.000 0.000 0.000
#> GSM379789     1   0.000      0.999 1.000 0.000 0.000
#> GSM379790     1   0.000      0.999 1.000 0.000 0.000
#> GSM379791     1   0.000      0.999 1.000 0.000 0.000
#> GSM379797     1   0.000      0.999 1.000 0.000 0.000
#> GSM379798     1   0.000      0.999 1.000 0.000 0.000
#> GSM379795     1   0.000      0.999 1.000 0.000 0.000
#> GSM379796     1   0.000      0.999 1.000 0.000 0.000
#> GSM379721     3   0.000      0.993 0.000 0.000 1.000
#> GSM379722     3   0.000      0.993 0.000 0.000 1.000
#> GSM379723     3   0.000      0.993 0.000 0.000 1.000
#> GSM379716     3   0.000      0.993 0.000 0.000 1.000
#> GSM379717     3   0.000      0.993 0.000 0.000 1.000
#> GSM379718     3   0.000      0.993 0.000 0.000 1.000
#> GSM379719     3   0.000      0.993 0.000 0.000 1.000
#> GSM379720     3   0.000      0.993 0.000 0.000 1.000
#> GSM379729     3   0.000      0.993 0.000 0.000 1.000
#> GSM379730     3   0.000      0.993 0.000 0.000 1.000
#> GSM379731     3   0.000      0.993 0.000 0.000 1.000
#> GSM379724     3   0.000      0.993 0.000 0.000 1.000
#> GSM379725     3   0.000      0.993 0.000 0.000 1.000
#> GSM379726     3   0.000      0.993 0.000 0.000 1.000
#> GSM379727     3   0.000      0.993 0.000 0.000 1.000
#> GSM379728     3   0.000      0.993 0.000 0.000 1.000
#> GSM379737     3   0.000      0.993 0.000 0.000 1.000
#> GSM379738     3   0.000      0.993 0.000 0.000 1.000
#> GSM379739     3   0.000      0.993 0.000 0.000 1.000
#> GSM379732     3   0.000      0.993 0.000 0.000 1.000
#> GSM379733     3   0.000      0.993 0.000 0.000 1.000
#> GSM379734     3   0.000      0.993 0.000 0.000 1.000
#> GSM379735     3   0.000      0.993 0.000 0.000 1.000
#> GSM379736     3   0.000      0.993 0.000 0.000 1.000
#> GSM379742     3   0.280      0.902 0.092 0.000 0.908
#> GSM379743     3   0.000      0.993 0.000 0.000 1.000
#> GSM379740     3   0.000      0.993 0.000 0.000 1.000
#> GSM379741     3   0.280      0.902 0.092 0.000 0.908

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2 p3    p4
#> GSM379832     2  0.0188      0.981 0.000 0.996  0 0.004
#> GSM379833     2  0.0188      0.981 0.000 0.996  0 0.004
#> GSM379834     2  0.0188      0.981 0.000 0.996  0 0.004
#> GSM379827     2  0.0592      0.983 0.000 0.984  0 0.016
#> GSM379828     2  0.0188      0.981 0.000 0.996  0 0.004
#> GSM379829     2  0.2345      0.898 0.000 0.900  0 0.100
#> GSM379830     2  0.0188      0.981 0.000 0.996  0 0.004
#> GSM379831     2  0.0188      0.981 0.000 0.996  0 0.004
#> GSM379840     2  0.1118      0.963 0.000 0.964  0 0.036
#> GSM379841     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379842     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379835     2  0.0188      0.981 0.000 0.996  0 0.004
#> GSM379836     2  0.0817      0.981 0.000 0.976  0 0.024
#> GSM379837     2  0.1118      0.963 0.000 0.964  0 0.036
#> GSM379838     2  0.0188      0.982 0.000 0.996  0 0.004
#> GSM379839     2  0.0921      0.968 0.000 0.972  0 0.028
#> GSM379848     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379849     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379850     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379843     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379844     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379845     2  0.0188      0.981 0.000 0.996  0 0.004
#> GSM379846     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379847     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379853     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379854     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379851     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379852     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379804     1  0.3219      0.832 0.836 0.000  0 0.164
#> GSM379805     4  0.3688      0.893 0.208 0.000  0 0.792
#> GSM379806     4  0.2149      0.922 0.088 0.000  0 0.912
#> GSM379799     4  0.2149      0.922 0.088 0.000  0 0.912
#> GSM379800     4  0.2149      0.922 0.088 0.000  0 0.912
#> GSM379801     4  0.2149      0.922 0.088 0.000  0 0.912
#> GSM379802     4  0.2149      0.922 0.088 0.000  0 0.912
#> GSM379803     4  0.3688      0.893 0.208 0.000  0 0.792
#> GSM379812     1  0.2216      0.914 0.908 0.000  0 0.092
#> GSM379813     1  0.2216      0.914 0.908 0.000  0 0.092
#> GSM379814     1  0.2011      0.921 0.920 0.000  0 0.080
#> GSM379807     1  0.1867      0.925 0.928 0.000  0 0.072
#> GSM379808     4  0.2149      0.922 0.088 0.000  0 0.912
#> GSM379809     1  0.2469      0.901 0.892 0.000  0 0.108
#> GSM379810     1  0.2281      0.912 0.904 0.000  0 0.096
#> GSM379811     4  0.3688      0.893 0.208 0.000  0 0.792
#> GSM379820     1  0.2149      0.916 0.912 0.000  0 0.088
#> GSM379821     1  0.2530      0.897 0.888 0.000  0 0.112
#> GSM379822     1  0.2081      0.919 0.916 0.000  0 0.084
#> GSM379815     1  0.2469      0.901 0.892 0.000  0 0.108
#> GSM379816     1  0.4336      0.743 0.812 0.128  0 0.060
#> GSM379817     1  0.2081      0.919 0.916 0.000  0 0.084
#> GSM379818     4  0.3726      0.889 0.212 0.000  0 0.788
#> GSM379819     1  0.2216      0.914 0.908 0.000  0 0.092
#> GSM379825     4  0.4103      0.830 0.256 0.000  0 0.744
#> GSM379826     1  0.2011      0.921 0.920 0.000  0 0.080
#> GSM379823     1  0.0921      0.942 0.972 0.000  0 0.028
#> GSM379824     1  0.2408      0.905 0.896 0.000  0 0.104
#> GSM379749     2  0.0817      0.982 0.000 0.976  0 0.024
#> GSM379750     2  0.0707      0.982 0.000 0.980  0 0.020
#> GSM379751     2  0.1022      0.981 0.000 0.968  0 0.032
#> GSM379744     2  0.1022      0.981 0.000 0.968  0 0.032
#> GSM379745     2  0.1022      0.981 0.000 0.968  0 0.032
#> GSM379746     2  0.0817      0.982 0.000 0.976  0 0.024
#> GSM379747     2  0.1022      0.981 0.000 0.968  0 0.032
#> GSM379748     2  0.0000      0.982 0.000 1.000  0 0.000
#> GSM379757     2  0.1022      0.981 0.000 0.968  0 0.032
#> GSM379758     2  0.1022      0.981 0.000 0.968  0 0.032
#> GSM379752     2  0.1022      0.981 0.000 0.968  0 0.032
#> GSM379753     2  0.1211      0.979 0.000 0.960  0 0.040
#> GSM379754     2  0.1022      0.981 0.000 0.968  0 0.032
#> GSM379755     2  0.1022      0.981 0.000 0.968  0 0.032
#> GSM379756     2  0.1022      0.981 0.000 0.968  0 0.032
#> GSM379764     2  0.1211      0.978 0.000 0.960  0 0.040
#> GSM379765     2  0.1118      0.979 0.000 0.964  0 0.036
#> GSM379766     2  0.1211      0.978 0.000 0.960  0 0.040
#> GSM379759     2  0.1211      0.978 0.000 0.960  0 0.040
#> GSM379760     2  0.1118      0.979 0.000 0.964  0 0.036
#> GSM379761     2  0.1118      0.979 0.000 0.964  0 0.036
#> GSM379762     2  0.1211      0.978 0.000 0.960  0 0.040
#> GSM379763     2  0.1211      0.978 0.000 0.960  0 0.040
#> GSM379769     2  0.1398      0.976 0.004 0.956  0 0.040
#> GSM379770     2  0.0592      0.982 0.000 0.984  0 0.016
#> GSM379767     2  0.1211      0.978 0.000 0.960  0 0.040
#> GSM379768     2  0.1211      0.978 0.000 0.960  0 0.040
#> GSM379776     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379777     1  0.2149      0.917 0.912 0.000  0 0.088
#> GSM379778     1  0.0592      0.939 0.984 0.000  0 0.016
#> GSM379771     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379772     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379773     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379774     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379775     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379784     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379785     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379786     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379779     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379780     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379781     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379782     1  0.0592      0.939 0.984 0.000  0 0.016
#> GSM379783     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379792     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379793     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379794     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379787     1  0.0592      0.939 0.984 0.000  0 0.016
#> GSM379788     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379789     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379790     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379791     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379797     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379798     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379795     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379796     1  0.0000      0.951 1.000 0.000  0 0.000
#> GSM379721     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379722     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379723     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379716     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379717     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379718     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379719     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379720     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379729     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379730     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379731     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379724     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379725     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379726     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379727     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379728     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379737     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379738     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379739     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379732     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379733     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379734     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379735     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379736     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379742     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379743     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379740     3  0.0000      1.000 0.000 0.000  1 0.000
#> GSM379741     3  0.0000      1.000 0.000 0.000  1 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2  p3    p4    p5
#> GSM379832     5  0.0162      0.789 0.000 0.004 0.0 0.000 0.996
#> GSM379833     5  0.0290      0.789 0.000 0.008 0.0 0.000 0.992
#> GSM379834     5  0.0404      0.788 0.000 0.012 0.0 0.000 0.988
#> GSM379827     5  0.0000      0.789 0.000 0.000 0.0 0.000 1.000
#> GSM379828     5  0.0000      0.789 0.000 0.000 0.0 0.000 1.000
#> GSM379829     5  0.2179      0.727 0.000 0.000 0.0 0.112 0.888
#> GSM379830     5  0.0000      0.789 0.000 0.000 0.0 0.000 1.000
#> GSM379831     5  0.0000      0.789 0.000 0.000 0.0 0.000 1.000
#> GSM379840     5  0.0000      0.789 0.000 0.000 0.0 0.000 1.000
#> GSM379841     5  0.3913      0.564 0.000 0.324 0.0 0.000 0.676
#> GSM379842     5  0.3109      0.694 0.000 0.200 0.0 0.000 0.800
#> GSM379835     5  0.0000      0.789 0.000 0.000 0.0 0.000 1.000
#> GSM379836     5  0.0000      0.789 0.000 0.000 0.0 0.000 1.000
#> GSM379837     5  0.0000      0.789 0.000 0.000 0.0 0.000 1.000
#> GSM379838     5  0.2690      0.728 0.000 0.156 0.0 0.000 0.844
#> GSM379839     5  0.0000      0.789 0.000 0.000 0.0 0.000 1.000
#> GSM379848     5  0.3983      0.545 0.000 0.340 0.0 0.000 0.660
#> GSM379849     2  0.4227      0.158 0.000 0.580 0.0 0.000 0.420
#> GSM379850     5  0.3966      0.552 0.000 0.336 0.0 0.000 0.664
#> GSM379843     5  0.3966      0.547 0.000 0.336 0.0 0.000 0.664
#> GSM379844     5  0.4015      0.531 0.000 0.348 0.0 0.000 0.652
#> GSM379845     5  0.0000      0.789 0.000 0.000 0.0 0.000 1.000
#> GSM379846     5  0.3966      0.552 0.000 0.336 0.0 0.000 0.664
#> GSM379847     5  0.3966      0.552 0.000 0.336 0.0 0.000 0.664
#> GSM379853     5  0.3424      0.658 0.000 0.240 0.0 0.000 0.760
#> GSM379854     5  0.3949      0.558 0.000 0.332 0.0 0.000 0.668
#> GSM379851     5  0.4273      0.285 0.000 0.448 0.0 0.000 0.552
#> GSM379852     2  0.4242      0.127 0.000 0.572 0.0 0.000 0.428
#> GSM379804     1  0.4235      0.520 0.576 0.000 0.0 0.424 0.000
#> GSM379805     4  0.0000      0.998 0.000 0.000 0.0 1.000 0.000
#> GSM379806     4  0.0000      0.998 0.000 0.000 0.0 1.000 0.000
#> GSM379799     4  0.0000      0.998 0.000 0.000 0.0 1.000 0.000
#> GSM379800     4  0.0000      0.998 0.000 0.000 0.0 1.000 0.000
#> GSM379801     4  0.0162      0.994 0.004 0.000 0.0 0.996 0.000
#> GSM379802     4  0.0000      0.998 0.000 0.000 0.0 1.000 0.000
#> GSM379803     4  0.0000      0.998 0.000 0.000 0.0 1.000 0.000
#> GSM379812     1  0.4171      0.569 0.604 0.000 0.0 0.396 0.000
#> GSM379813     1  0.4101      0.603 0.628 0.000 0.0 0.372 0.000
#> GSM379814     1  0.3636      0.713 0.728 0.000 0.0 0.272 0.000
#> GSM379807     1  0.3366      0.742 0.768 0.000 0.0 0.232 0.000
#> GSM379808     4  0.0000      0.998 0.000 0.000 0.0 1.000 0.000
#> GSM379809     1  0.3857      0.676 0.688 0.000 0.0 0.312 0.000
#> GSM379810     1  0.3661      0.711 0.724 0.000 0.0 0.276 0.000
#> GSM379811     4  0.0000      0.998 0.000 0.000 0.0 1.000 0.000
#> GSM379820     1  0.4088      0.608 0.632 0.000 0.0 0.368 0.000
#> GSM379821     1  0.4256      0.494 0.564 0.000 0.0 0.436 0.000
#> GSM379822     1  0.3774      0.691 0.704 0.000 0.0 0.296 0.000
#> GSM379815     1  0.4219      0.535 0.584 0.000 0.0 0.416 0.000
#> GSM379816     1  0.4054      0.741 0.760 0.000 0.0 0.204 0.036
#> GSM379817     1  0.3684      0.706 0.720 0.000 0.0 0.280 0.000
#> GSM379818     4  0.0000      0.998 0.000 0.000 0.0 1.000 0.000
#> GSM379819     1  0.4150      0.581 0.612 0.000 0.0 0.388 0.000
#> GSM379825     4  0.0290      0.989 0.008 0.000 0.0 0.992 0.000
#> GSM379826     1  0.3661      0.710 0.724 0.000 0.0 0.276 0.000
#> GSM379823     1  0.1197      0.837 0.952 0.000 0.0 0.048 0.000
#> GSM379824     1  0.4171      0.569 0.604 0.000 0.0 0.396 0.000
#> GSM379749     5  0.3274      0.670 0.000 0.220 0.0 0.000 0.780
#> GSM379750     5  0.0703      0.786 0.000 0.024 0.0 0.000 0.976
#> GSM379751     5  0.3143      0.674 0.000 0.204 0.0 0.000 0.796
#> GSM379744     5  0.3336      0.659 0.000 0.228 0.0 0.000 0.772
#> GSM379745     5  0.3274      0.667 0.000 0.220 0.0 0.000 0.780
#> GSM379746     5  0.3210      0.675 0.000 0.212 0.0 0.000 0.788
#> GSM379747     5  0.3424      0.640 0.000 0.240 0.0 0.000 0.760
#> GSM379748     5  0.0000      0.789 0.000 0.000 0.0 0.000 1.000
#> GSM379757     2  0.2813      0.676 0.000 0.832 0.0 0.000 0.168
#> GSM379758     2  0.0000      0.882 0.000 1.000 0.0 0.000 0.000
#> GSM379752     5  0.3336      0.659 0.000 0.228 0.0 0.000 0.772
#> GSM379753     2  0.3796      0.459 0.000 0.700 0.0 0.000 0.300
#> GSM379754     2  0.2074      0.779 0.000 0.896 0.0 0.000 0.104
#> GSM379755     5  0.3336      0.664 0.000 0.228 0.0 0.000 0.772
#> GSM379756     5  0.3857      0.605 0.000 0.312 0.0 0.000 0.688
#> GSM379764     2  0.0000      0.882 0.000 1.000 0.0 0.000 0.000
#> GSM379765     2  0.0000      0.882 0.000 1.000 0.0 0.000 0.000
#> GSM379766     2  0.0000      0.882 0.000 1.000 0.0 0.000 0.000
#> GSM379759     2  0.0000      0.882 0.000 1.000 0.0 0.000 0.000
#> GSM379760     2  0.0000      0.882 0.000 1.000 0.0 0.000 0.000
#> GSM379761     2  0.0000      0.882 0.000 1.000 0.0 0.000 0.000
#> GSM379762     2  0.0000      0.882 0.000 1.000 0.0 0.000 0.000
#> GSM379763     2  0.0000      0.882 0.000 1.000 0.0 0.000 0.000
#> GSM379769     2  0.0000      0.882 0.000 1.000 0.0 0.000 0.000
#> GSM379770     2  0.1732      0.808 0.000 0.920 0.0 0.000 0.080
#> GSM379767     2  0.0000      0.882 0.000 1.000 0.0 0.000 0.000
#> GSM379768     2  0.0000      0.882 0.000 1.000 0.0 0.000 0.000
#> GSM379776     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379777     1  0.4171      0.569 0.604 0.000 0.0 0.396 0.000
#> GSM379778     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379771     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379772     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379773     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379774     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379775     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379784     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379785     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379786     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379779     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379780     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379781     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379782     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379783     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379792     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379793     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379794     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379787     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379788     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379789     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379790     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379791     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379797     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379798     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379795     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379796     1  0.0000      0.855 1.000 0.000 0.0 0.000 0.000
#> GSM379721     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379722     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379723     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379716     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379717     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379718     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379719     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379720     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379729     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379730     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379731     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379724     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379725     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379726     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379727     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379728     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379737     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379738     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379739     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379732     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379733     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379734     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379735     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379736     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379742     3  0.2020      0.862 0.100 0.000 0.9 0.000 0.000
#> GSM379743     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379740     3  0.0000      0.990 0.000 0.000 1.0 0.000 0.000
#> GSM379741     3  0.2020      0.862 0.100 0.000 0.9 0.000 0.000

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     5  0.0363     0.9297 0.000 0.012 0.000 0.000 0.988 0.000
#> GSM379833     5  0.0000     0.9302 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379834     5  0.0146     0.9303 0.000 0.004 0.000 0.000 0.996 0.000
#> GSM379827     5  0.0363     0.9297 0.000 0.012 0.000 0.000 0.988 0.000
#> GSM379828     5  0.0000     0.9302 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379829     5  0.1387     0.8772 0.000 0.000 0.000 0.068 0.932 0.000
#> GSM379830     5  0.0000     0.9302 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379831     5  0.0000     0.9302 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379840     5  0.2260     0.7831 0.000 0.140 0.000 0.000 0.860 0.000
#> GSM379841     2  0.3862     0.2998 0.000 0.524 0.000 0.000 0.476 0.000
#> GSM379842     5  0.3864    -0.2285 0.000 0.480 0.000 0.000 0.520 0.000
#> GSM379835     5  0.0000     0.9302 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379836     5  0.0000     0.9302 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379837     5  0.0000     0.9302 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379838     5  0.3482     0.4353 0.000 0.316 0.000 0.000 0.684 0.000
#> GSM379839     5  0.0000     0.9302 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379848     2  0.3198     0.7496 0.000 0.740 0.000 0.000 0.260 0.000
#> GSM379849     2  0.2135     0.8230 0.000 0.872 0.000 0.000 0.128 0.000
#> GSM379850     2  0.3151     0.7570 0.000 0.748 0.000 0.000 0.252 0.000
#> GSM379843     2  0.3634     0.6108 0.000 0.644 0.000 0.000 0.356 0.000
#> GSM379844     2  0.3547     0.6487 0.000 0.668 0.000 0.000 0.332 0.000
#> GSM379845     5  0.0000     0.9302 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379846     2  0.3531     0.6612 0.000 0.672 0.000 0.000 0.328 0.000
#> GSM379847     2  0.3175     0.7515 0.000 0.744 0.000 0.000 0.256 0.000
#> GSM379853     2  0.3309     0.7372 0.000 0.720 0.000 0.000 0.280 0.000
#> GSM379854     2  0.3126     0.7584 0.000 0.752 0.000 0.000 0.248 0.000
#> GSM379851     2  0.2454     0.8090 0.000 0.840 0.000 0.000 0.160 0.000
#> GSM379852     2  0.1765     0.8306 0.000 0.904 0.000 0.000 0.096 0.000
#> GSM379804     4  0.3337     0.6289 0.260 0.000 0.000 0.736 0.000 0.004
#> GSM379805     4  0.0000     0.8950 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379806     4  0.0000     0.8950 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379799     4  0.0000     0.8950 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379800     4  0.0000     0.8950 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379801     4  0.0000     0.8950 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379802     4  0.0000     0.8950 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379803     4  0.0260     0.8872 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM379812     1  0.0603     0.9433 0.980 0.000 0.000 0.004 0.000 0.016
#> GSM379813     1  0.0603     0.9433 0.980 0.000 0.000 0.004 0.000 0.016
#> GSM379814     1  0.0146     0.9459 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM379807     1  0.0603     0.9433 0.980 0.000 0.000 0.004 0.000 0.016
#> GSM379808     4  0.0000     0.8950 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379809     4  0.2968     0.7346 0.168 0.000 0.000 0.816 0.000 0.016
#> GSM379810     1  0.3867    -0.0992 0.512 0.000 0.000 0.488 0.000 0.000
#> GSM379811     4  0.0000     0.8950 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379820     1  0.0603     0.9433 0.980 0.000 0.000 0.004 0.000 0.016
#> GSM379821     1  0.0458     0.9437 0.984 0.000 0.000 0.000 0.000 0.016
#> GSM379822     1  0.0458     0.9437 0.984 0.000 0.000 0.000 0.000 0.016
#> GSM379815     1  0.1528     0.9106 0.936 0.000 0.000 0.048 0.000 0.016
#> GSM379816     1  0.4371     0.6095 0.732 0.004 0.000 0.116 0.148 0.000
#> GSM379817     1  0.0603     0.9433 0.980 0.000 0.000 0.004 0.000 0.016
#> GSM379818     4  0.0146     0.8925 0.004 0.000 0.000 0.996 0.000 0.000
#> GSM379819     1  0.0458     0.9437 0.984 0.000 0.000 0.000 0.000 0.016
#> GSM379825     4  0.3727     0.3541 0.388 0.000 0.000 0.612 0.000 0.000
#> GSM379826     1  0.0603     0.9433 0.980 0.000 0.000 0.004 0.000 0.016
#> GSM379823     1  0.0000     0.9462 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379824     1  0.0458     0.9437 0.984 0.000 0.000 0.000 0.000 0.016
#> GSM379749     5  0.0547     0.9285 0.000 0.020 0.000 0.000 0.980 0.000
#> GSM379750     5  0.0458     0.9289 0.000 0.016 0.000 0.000 0.984 0.000
#> GSM379751     5  0.0000     0.9302 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379744     5  0.0547     0.9285 0.000 0.020 0.000 0.000 0.980 0.000
#> GSM379745     5  0.0547     0.9285 0.000 0.020 0.000 0.000 0.980 0.000
#> GSM379746     5  0.0547     0.9285 0.000 0.020 0.000 0.000 0.980 0.000
#> GSM379747     5  0.1501     0.8798 0.000 0.076 0.000 0.000 0.924 0.000
#> GSM379748     5  0.0000     0.9302 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379757     2  0.2969     0.7605 0.000 0.776 0.000 0.000 0.224 0.000
#> GSM379758     2  0.0146     0.8342 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379752     5  0.0547     0.9285 0.000 0.020 0.000 0.000 0.980 0.000
#> GSM379753     5  0.1610     0.8750 0.000 0.084 0.000 0.000 0.916 0.000
#> GSM379754     5  0.2793     0.7401 0.000 0.200 0.000 0.000 0.800 0.000
#> GSM379755     5  0.0632     0.9267 0.000 0.024 0.000 0.000 0.976 0.000
#> GSM379756     5  0.1663     0.8688 0.000 0.088 0.000 0.000 0.912 0.000
#> GSM379764     2  0.0000     0.8314 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379765     2  0.0146     0.8342 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379766     2  0.0146     0.8342 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379759     2  0.0146     0.8342 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379760     2  0.0260     0.8350 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379761     2  0.0260     0.8350 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379762     2  0.0146     0.8342 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379763     2  0.0146     0.8342 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379769     2  0.0000     0.8314 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379770     2  0.0000     0.8314 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379767     2  0.0146     0.8342 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379768     2  0.0146     0.8342 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379776     1  0.1411     0.9438 0.936 0.000 0.000 0.004 0.000 0.060
#> GSM379777     1  0.0458     0.9437 0.984 0.000 0.000 0.000 0.000 0.016
#> GSM379778     1  0.0146     0.9462 0.996 0.004 0.000 0.000 0.000 0.000
#> GSM379771     1  0.1411     0.9438 0.936 0.000 0.000 0.004 0.000 0.060
#> GSM379772     1  0.1411     0.9438 0.936 0.000 0.000 0.004 0.000 0.060
#> GSM379773     1  0.0146     0.9459 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM379774     1  0.0146     0.9459 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM379775     1  0.1411     0.9438 0.936 0.000 0.000 0.004 0.000 0.060
#> GSM379784     1  0.1267     0.9435 0.940 0.000 0.000 0.000 0.000 0.060
#> GSM379785     1  0.1267     0.9435 0.940 0.000 0.000 0.000 0.000 0.060
#> GSM379786     1  0.0000     0.9462 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379779     1  0.1411     0.9438 0.936 0.000 0.000 0.004 0.000 0.060
#> GSM379780     1  0.1411     0.9438 0.936 0.000 0.000 0.004 0.000 0.060
#> GSM379781     1  0.1411     0.9438 0.936 0.000 0.000 0.004 0.000 0.060
#> GSM379782     1  0.0146     0.9462 0.996 0.004 0.000 0.000 0.000 0.000
#> GSM379783     1  0.0458     0.9474 0.984 0.000 0.000 0.000 0.000 0.016
#> GSM379792     1  0.0458     0.9437 0.984 0.000 0.000 0.000 0.000 0.016
#> GSM379793     1  0.1267     0.9435 0.940 0.000 0.000 0.000 0.000 0.060
#> GSM379794     1  0.1075     0.9458 0.952 0.000 0.000 0.000 0.000 0.048
#> GSM379787     1  0.0146     0.9462 0.996 0.004 0.000 0.000 0.000 0.000
#> GSM379788     1  0.1267     0.9435 0.940 0.000 0.000 0.000 0.000 0.060
#> GSM379789     1  0.1267     0.9435 0.940 0.000 0.000 0.000 0.000 0.060
#> GSM379790     1  0.1267     0.9435 0.940 0.000 0.000 0.000 0.000 0.060
#> GSM379791     1  0.1267     0.9435 0.940 0.000 0.000 0.000 0.000 0.060
#> GSM379797     1  0.1444     0.9427 0.928 0.000 0.000 0.000 0.000 0.072
#> GSM379798     1  0.1267     0.9435 0.940 0.000 0.000 0.000 0.000 0.060
#> GSM379795     1  0.1411     0.9438 0.936 0.000 0.000 0.004 0.000 0.060
#> GSM379796     1  0.1327     0.9436 0.936 0.000 0.000 0.000 0.000 0.064
#> GSM379721     6  0.1556     0.9074 0.000 0.000 0.080 0.000 0.000 0.920
#> GSM379722     6  0.1556     0.9074 0.000 0.000 0.080 0.000 0.000 0.920
#> GSM379723     6  0.1556     0.9074 0.000 0.000 0.080 0.000 0.000 0.920
#> GSM379716     6  0.1556     0.9074 0.000 0.000 0.080 0.000 0.000 0.920
#> GSM379717     6  0.1556     0.9074 0.000 0.000 0.080 0.000 0.000 0.920
#> GSM379718     6  0.1556     0.9074 0.000 0.000 0.080 0.000 0.000 0.920
#> GSM379719     6  0.1556     0.9074 0.000 0.000 0.080 0.000 0.000 0.920
#> GSM379720     6  0.1556     0.9074 0.000 0.000 0.080 0.000 0.000 0.920
#> GSM379729     3  0.0000     0.9613 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379730     3  0.0000     0.9613 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379731     3  0.0146     0.9590 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM379724     6  0.1556     0.9074 0.000 0.000 0.080 0.000 0.000 0.920
#> GSM379725     3  0.2300     0.7866 0.000 0.000 0.856 0.000 0.000 0.144
#> GSM379726     6  0.3833     0.3429 0.000 0.000 0.444 0.000 0.000 0.556
#> GSM379727     3  0.3499     0.4108 0.000 0.000 0.680 0.000 0.000 0.320
#> GSM379728     6  0.3868     0.1937 0.000 0.000 0.492 0.000 0.000 0.508
#> GSM379737     3  0.0000     0.9613 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379738     3  0.0000     0.9613 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379739     3  0.0000     0.9613 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379732     3  0.0000     0.9613 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379733     3  0.0260     0.9562 0.000 0.000 0.992 0.000 0.000 0.008
#> GSM379734     3  0.0000     0.9613 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379735     3  0.0000     0.9613 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379736     3  0.0547     0.9455 0.000 0.000 0.980 0.000 0.000 0.020
#> GSM379742     3  0.0146     0.9583 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM379743     3  0.0000     0.9613 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379740     3  0.0000     0.9613 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379741     3  0.0146     0.9583 0.000 0.000 0.996 0.000 0.000 0.004

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-MAD-mclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-MAD-mclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-MAD-mclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-MAD-mclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-MAD-mclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-MAD-mclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-MAD-mclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-MAD-mclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-MAD-mclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-MAD-mclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-MAD-mclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-MAD-mclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-MAD-mclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-MAD-mclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-MAD-mclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-MAD-mclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-MAD-mclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-MAD-mclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-MAD-mclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-MAD-mclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk MAD-mclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-MAD-mclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-MAD-mclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-MAD-mclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-MAD-mclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-MAD-mclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk MAD-mclust-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>              n individual(p) time(p) agent(p) k
#> MAD:mclust 139      4.62e-29   1.000 1.00e+00 2
#> MAD:mclust 139      1.97e-55   1.000 9.98e-01 3
#> MAD:mclust 139      1.43e-59   1.000 4.17e-02 4
#> MAD:mclust 134      4.72e-66   1.000 1.28e-03 5
#> MAD:mclust 131      1.87e-52   0.987 3.41e-10 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

MAD:NMF*

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["MAD", "NMF"]
# you can also extract it by
# res = res_list["MAD:NMF"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#>   Subgroups are detected by 'NMF' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 4.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk MAD-NMF-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk MAD-NMF-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 0.985           0.959       0.983         0.4945 0.508   0.508
#> 3 3 0.694           0.714       0.841         0.3343 0.774   0.577
#> 4 4 0.914           0.885       0.951         0.1097 0.852   0.604
#> 5 5 0.871           0.849       0.919         0.0483 0.957   0.845
#> 6 6 0.878           0.862       0.891         0.0478 0.912   0.659

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 4
#> attr(,"optional")
#> [1] 2

There is also optional best \(k\) = 2 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000     0.9915 0.000 1.000
#> GSM379833     2  0.0000     0.9915 0.000 1.000
#> GSM379834     2  0.0000     0.9915 0.000 1.000
#> GSM379827     2  0.0000     0.9915 0.000 1.000
#> GSM379828     2  0.0000     0.9915 0.000 1.000
#> GSM379829     1  0.0000     0.9765 1.000 0.000
#> GSM379830     2  0.0000     0.9915 0.000 1.000
#> GSM379831     2  0.0000     0.9915 0.000 1.000
#> GSM379840     2  0.0000     0.9915 0.000 1.000
#> GSM379841     2  0.0000     0.9915 0.000 1.000
#> GSM379842     2  0.0000     0.9915 0.000 1.000
#> GSM379835     2  0.0000     0.9915 0.000 1.000
#> GSM379836     2  0.0000     0.9915 0.000 1.000
#> GSM379837     1  0.9998     0.0689 0.508 0.492
#> GSM379838     2  0.0000     0.9915 0.000 1.000
#> GSM379839     2  0.0376     0.9876 0.004 0.996
#> GSM379848     2  0.0000     0.9915 0.000 1.000
#> GSM379849     2  0.0000     0.9915 0.000 1.000
#> GSM379850     2  0.0000     0.9915 0.000 1.000
#> GSM379843     2  0.0000     0.9915 0.000 1.000
#> GSM379844     2  0.0000     0.9915 0.000 1.000
#> GSM379845     2  0.0000     0.9915 0.000 1.000
#> GSM379846     2  0.0000     0.9915 0.000 1.000
#> GSM379847     2  0.0000     0.9915 0.000 1.000
#> GSM379853     2  0.0000     0.9915 0.000 1.000
#> GSM379854     2  0.0000     0.9915 0.000 1.000
#> GSM379851     2  0.0000     0.9915 0.000 1.000
#> GSM379852     2  0.0000     0.9915 0.000 1.000
#> GSM379804     1  0.0000     0.9765 1.000 0.000
#> GSM379805     1  0.0000     0.9765 1.000 0.000
#> GSM379806     1  0.0000     0.9765 1.000 0.000
#> GSM379799     1  0.0000     0.9765 1.000 0.000
#> GSM379800     1  0.0000     0.9765 1.000 0.000
#> GSM379801     1  0.0000     0.9765 1.000 0.000
#> GSM379802     1  0.0000     0.9765 1.000 0.000
#> GSM379803     1  0.0000     0.9765 1.000 0.000
#> GSM379812     1  0.0376     0.9732 0.996 0.004
#> GSM379813     1  0.0000     0.9765 1.000 0.000
#> GSM379814     1  0.0000     0.9765 1.000 0.000
#> GSM379807     1  0.0000     0.9765 1.000 0.000
#> GSM379808     1  0.0000     0.9765 1.000 0.000
#> GSM379809     1  0.0000     0.9765 1.000 0.000
#> GSM379810     1  0.0000     0.9765 1.000 0.000
#> GSM379811     1  0.0000     0.9765 1.000 0.000
#> GSM379820     1  0.0000     0.9765 1.000 0.000
#> GSM379821     1  0.0000     0.9765 1.000 0.000
#> GSM379822     1  0.0000     0.9765 1.000 0.000
#> GSM379815     1  0.0000     0.9765 1.000 0.000
#> GSM379816     1  0.7528     0.7352 0.784 0.216
#> GSM379817     1  0.0000     0.9765 1.000 0.000
#> GSM379818     1  0.0000     0.9765 1.000 0.000
#> GSM379819     1  0.0000     0.9765 1.000 0.000
#> GSM379825     1  0.0000     0.9765 1.000 0.000
#> GSM379826     1  0.0000     0.9765 1.000 0.000
#> GSM379823     1  0.0000     0.9765 1.000 0.000
#> GSM379824     1  0.0000     0.9765 1.000 0.000
#> GSM379749     2  0.0000     0.9915 0.000 1.000
#> GSM379750     2  0.0000     0.9915 0.000 1.000
#> GSM379751     2  0.0000     0.9915 0.000 1.000
#> GSM379744     2  0.0000     0.9915 0.000 1.000
#> GSM379745     2  0.0000     0.9915 0.000 1.000
#> GSM379746     2  0.0000     0.9915 0.000 1.000
#> GSM379747     2  0.0000     0.9915 0.000 1.000
#> GSM379748     2  0.0000     0.9915 0.000 1.000
#> GSM379757     2  0.0000     0.9915 0.000 1.000
#> GSM379758     2  0.0000     0.9915 0.000 1.000
#> GSM379752     2  0.0000     0.9915 0.000 1.000
#> GSM379753     2  0.0000     0.9915 0.000 1.000
#> GSM379754     2  0.0000     0.9915 0.000 1.000
#> GSM379755     2  0.0000     0.9915 0.000 1.000
#> GSM379756     2  0.0000     0.9915 0.000 1.000
#> GSM379764     2  0.0000     0.9915 0.000 1.000
#> GSM379765     2  0.0000     0.9915 0.000 1.000
#> GSM379766     2  0.0000     0.9915 0.000 1.000
#> GSM379759     2  0.0000     0.9915 0.000 1.000
#> GSM379760     2  0.0000     0.9915 0.000 1.000
#> GSM379761     2  0.0000     0.9915 0.000 1.000
#> GSM379762     2  0.0000     0.9915 0.000 1.000
#> GSM379763     2  0.0000     0.9915 0.000 1.000
#> GSM379769     2  0.0000     0.9915 0.000 1.000
#> GSM379770     2  0.0000     0.9915 0.000 1.000
#> GSM379767     2  0.0000     0.9915 0.000 1.000
#> GSM379768     2  0.0000     0.9915 0.000 1.000
#> GSM379776     1  0.0000     0.9765 1.000 0.000
#> GSM379777     1  0.0000     0.9765 1.000 0.000
#> GSM379778     2  0.0000     0.9915 0.000 1.000
#> GSM379771     1  0.0000     0.9765 1.000 0.000
#> GSM379772     1  0.0000     0.9765 1.000 0.000
#> GSM379773     1  0.0000     0.9765 1.000 0.000
#> GSM379774     1  0.0000     0.9765 1.000 0.000
#> GSM379775     1  0.0000     0.9765 1.000 0.000
#> GSM379784     1  0.2236     0.9448 0.964 0.036
#> GSM379785     1  0.0000     0.9765 1.000 0.000
#> GSM379786     1  0.9170     0.5259 0.668 0.332
#> GSM379779     1  0.0000     0.9765 1.000 0.000
#> GSM379780     1  0.0000     0.9765 1.000 0.000
#> GSM379781     1  0.0000     0.9765 1.000 0.000
#> GSM379782     2  0.0000     0.9915 0.000 1.000
#> GSM379783     2  0.9909     0.1496 0.444 0.556
#> GSM379792     1  0.0000     0.9765 1.000 0.000
#> GSM379793     1  0.0000     0.9765 1.000 0.000
#> GSM379794     1  0.0000     0.9765 1.000 0.000
#> GSM379787     2  0.1633     0.9670 0.024 0.976
#> GSM379788     1  0.0000     0.9765 1.000 0.000
#> GSM379789     1  0.0000     0.9765 1.000 0.000
#> GSM379790     1  0.0000     0.9765 1.000 0.000
#> GSM379791     1  0.0000     0.9765 1.000 0.000
#> GSM379797     1  0.0000     0.9765 1.000 0.000
#> GSM379798     1  0.0000     0.9765 1.000 0.000
#> GSM379795     1  0.0000     0.9765 1.000 0.000
#> GSM379796     1  0.0000     0.9765 1.000 0.000
#> GSM379721     1  0.0000     0.9765 1.000 0.000
#> GSM379722     1  0.0000     0.9765 1.000 0.000
#> GSM379723     1  0.0000     0.9765 1.000 0.000
#> GSM379716     1  0.0000     0.9765 1.000 0.000
#> GSM379717     1  0.0000     0.9765 1.000 0.000
#> GSM379718     1  0.0000     0.9765 1.000 0.000
#> GSM379719     1  0.0000     0.9765 1.000 0.000
#> GSM379720     1  0.0000     0.9765 1.000 0.000
#> GSM379729     1  0.7139     0.7639 0.804 0.196
#> GSM379730     1  0.7219     0.7583 0.800 0.200
#> GSM379731     1  0.0000     0.9765 1.000 0.000
#> GSM379724     1  0.0000     0.9765 1.000 0.000
#> GSM379725     1  0.5408     0.8537 0.876 0.124
#> GSM379726     1  0.0000     0.9765 1.000 0.000
#> GSM379727     1  0.0000     0.9765 1.000 0.000
#> GSM379728     1  0.0000     0.9765 1.000 0.000
#> GSM379737     1  0.0000     0.9765 1.000 0.000
#> GSM379738     1  0.0000     0.9765 1.000 0.000
#> GSM379739     1  0.0000     0.9765 1.000 0.000
#> GSM379732     1  0.0376     0.9732 0.996 0.004
#> GSM379733     1  0.0000     0.9765 1.000 0.000
#> GSM379734     1  0.0000     0.9765 1.000 0.000
#> GSM379735     1  0.0000     0.9765 1.000 0.000
#> GSM379736     1  0.0000     0.9765 1.000 0.000
#> GSM379742     2  0.0000     0.9915 0.000 1.000
#> GSM379743     1  0.7674     0.7232 0.776 0.224
#> GSM379740     1  0.0000     0.9765 1.000 0.000
#> GSM379741     2  0.0000     0.9915 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379833     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379834     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379827     2  0.0892     0.9644 0.000 0.980 0.020
#> GSM379828     2  0.0892     0.9643 0.000 0.980 0.020
#> GSM379829     3  0.6095     0.5441 0.392 0.000 0.608
#> GSM379830     2  0.0747     0.9677 0.000 0.984 0.016
#> GSM379831     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379840     2  0.1751     0.9471 0.012 0.960 0.028
#> GSM379841     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379842     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379835     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379836     2  0.4555     0.7451 0.000 0.800 0.200
#> GSM379837     3  0.8645     0.4167 0.132 0.300 0.568
#> GSM379838     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379839     2  0.8635     0.1524 0.112 0.532 0.356
#> GSM379848     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379849     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379850     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379843     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379844     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379845     2  0.0237     0.9765 0.000 0.996 0.004
#> GSM379846     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379847     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379853     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379854     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379851     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379852     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379804     3  0.6204     0.5205 0.424 0.000 0.576
#> GSM379805     3  0.6244     0.5027 0.440 0.000 0.560
#> GSM379806     3  0.6235     0.5076 0.436 0.000 0.564
#> GSM379799     3  0.6126     0.5398 0.400 0.000 0.600
#> GSM379800     3  0.6126     0.5398 0.400 0.000 0.600
#> GSM379801     3  0.6111     0.5421 0.396 0.000 0.604
#> GSM379802     3  0.6192     0.5246 0.420 0.000 0.580
#> GSM379803     3  0.6291     0.4622 0.468 0.000 0.532
#> GSM379812     1  0.3038     0.6454 0.896 0.000 0.104
#> GSM379813     1  0.3267     0.6293 0.884 0.000 0.116
#> GSM379814     1  0.3816     0.5809 0.852 0.000 0.148
#> GSM379807     1  0.5785     0.0930 0.668 0.000 0.332
#> GSM379808     3  0.6180     0.5280 0.416 0.000 0.584
#> GSM379809     3  0.6192     0.5247 0.420 0.000 0.580
#> GSM379810     3  0.6260     0.4931 0.448 0.000 0.552
#> GSM379811     3  0.6291     0.4622 0.468 0.000 0.532
#> GSM379820     1  0.0424     0.7331 0.992 0.000 0.008
#> GSM379821     1  0.0237     0.7355 0.996 0.000 0.004
#> GSM379822     1  0.3267     0.7458 0.884 0.000 0.116
#> GSM379815     3  0.6302     0.4402 0.480 0.000 0.520
#> GSM379816     1  0.9489    -0.1968 0.456 0.192 0.352
#> GSM379817     1  0.0237     0.7355 0.996 0.000 0.004
#> GSM379818     3  0.6260     0.4924 0.448 0.000 0.552
#> GSM379819     1  0.2625     0.6738 0.916 0.000 0.084
#> GSM379825     3  0.6295     0.4551 0.472 0.000 0.528
#> GSM379826     1  0.0892     0.7368 0.980 0.000 0.020
#> GSM379823     1  0.4178     0.7172 0.828 0.000 0.172
#> GSM379824     1  0.0424     0.7331 0.992 0.000 0.008
#> GSM379749     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379750     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379751     2  0.2165     0.9218 0.000 0.936 0.064
#> GSM379744     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379745     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379746     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379747     2  0.0237     0.9764 0.000 0.996 0.004
#> GSM379748     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379757     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379758     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379752     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379753     2  0.0892     0.9644 0.000 0.980 0.020
#> GSM379754     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379755     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379756     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379764     2  0.1182     0.9604 0.012 0.976 0.012
#> GSM379765     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379766     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379759     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379760     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379761     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379762     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379763     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379769     2  0.4642     0.8251 0.084 0.856 0.060
#> GSM379770     2  0.0661     0.9702 0.008 0.988 0.004
#> GSM379767     2  0.0424     0.9733 0.000 0.992 0.008
#> GSM379768     2  0.0000     0.9789 0.000 1.000 0.000
#> GSM379776     1  0.0592     0.7410 0.988 0.000 0.012
#> GSM379777     1  0.0237     0.7355 0.996 0.000 0.004
#> GSM379778     1  0.8113     0.4319 0.596 0.312 0.092
#> GSM379771     1  0.2261     0.7048 0.932 0.000 0.068
#> GSM379772     1  0.3551     0.7200 0.868 0.000 0.132
#> GSM379773     1  0.0592     0.7429 0.988 0.000 0.012
#> GSM379774     1  0.0592     0.7410 0.988 0.000 0.012
#> GSM379775     1  0.1031     0.7369 0.976 0.000 0.024
#> GSM379784     1  0.3845     0.7434 0.872 0.012 0.116
#> GSM379785     1  0.2537     0.7525 0.920 0.000 0.080
#> GSM379786     1  0.6039     0.6769 0.788 0.108 0.104
#> GSM379779     1  0.1860     0.7527 0.948 0.000 0.052
#> GSM379780     1  0.1964     0.7528 0.944 0.000 0.056
#> GSM379781     1  0.2448     0.7528 0.924 0.000 0.076
#> GSM379782     1  0.8215     0.3534 0.540 0.380 0.080
#> GSM379783     1  0.6860     0.6046 0.732 0.176 0.092
#> GSM379792     1  0.0592     0.7402 0.988 0.000 0.012
#> GSM379793     1  0.4178     0.7172 0.828 0.000 0.172
#> GSM379794     1  0.4062     0.7226 0.836 0.000 0.164
#> GSM379787     1  0.8894     0.4018 0.548 0.300 0.152
#> GSM379788     1  0.4062     0.7226 0.836 0.000 0.164
#> GSM379789     1  0.3482     0.7409 0.872 0.000 0.128
#> GSM379790     1  0.1860     0.7523 0.948 0.000 0.052
#> GSM379791     1  0.4178     0.7172 0.828 0.000 0.172
#> GSM379797     1  0.4555     0.4730 0.800 0.000 0.200
#> GSM379798     1  0.3482     0.7414 0.872 0.000 0.128
#> GSM379795     1  0.4346     0.7076 0.816 0.000 0.184
#> GSM379796     1  0.2165     0.7541 0.936 0.000 0.064
#> GSM379721     3  0.1031     0.6477 0.024 0.000 0.976
#> GSM379722     3  0.1163     0.6463 0.028 0.000 0.972
#> GSM379723     3  0.0000     0.6492 0.000 0.000 1.000
#> GSM379716     3  0.1411     0.6501 0.036 0.000 0.964
#> GSM379717     3  0.1031     0.6515 0.024 0.000 0.976
#> GSM379718     3  0.0747     0.6516 0.016 0.000 0.984
#> GSM379719     3  0.0747     0.6486 0.016 0.000 0.984
#> GSM379720     3  0.0747     0.6516 0.016 0.000 0.984
#> GSM379729     3  0.7768     0.0107 0.344 0.064 0.592
#> GSM379730     1  0.8405     0.2690 0.460 0.084 0.456
#> GSM379731     3  0.1411     0.6426 0.036 0.000 0.964
#> GSM379724     3  0.0592     0.6492 0.012 0.000 0.988
#> GSM379725     3  0.1411     0.6426 0.036 0.000 0.964
#> GSM379726     3  0.1163     0.6463 0.028 0.000 0.972
#> GSM379727     3  0.1411     0.6426 0.036 0.000 0.964
#> GSM379728     3  0.1031     0.6477 0.024 0.000 0.976
#> GSM379737     1  0.6309     0.3028 0.504 0.000 0.496
#> GSM379738     1  0.6299     0.3374 0.524 0.000 0.476
#> GSM379739     1  0.6215     0.4085 0.572 0.000 0.428
#> GSM379732     3  0.2959     0.5853 0.100 0.000 0.900
#> GSM379733     3  0.1860     0.6310 0.052 0.000 0.948
#> GSM379734     3  0.2878     0.5898 0.096 0.000 0.904
#> GSM379735     1  0.6204     0.4144 0.576 0.000 0.424
#> GSM379736     3  0.0747     0.6498 0.016 0.000 0.984
#> GSM379742     3  0.9786    -0.0135 0.236 0.364 0.400
#> GSM379743     1  0.6192     0.4202 0.580 0.000 0.420
#> GSM379740     3  0.5926     0.0707 0.356 0.000 0.644
#> GSM379741     3  0.9888    -0.1210 0.328 0.272 0.400

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379833     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379834     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379827     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379828     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379829     4  0.0188     0.8796 0.000 0.000 0.004 0.996
#> GSM379830     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379831     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379840     2  0.2868     0.8381 0.000 0.864 0.000 0.136
#> GSM379841     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379842     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379835     2  0.0188     0.9810 0.000 0.996 0.000 0.004
#> GSM379836     2  0.0817     0.9641 0.000 0.976 0.000 0.024
#> GSM379837     4  0.5158     0.0445 0.000 0.472 0.004 0.524
#> GSM379838     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379839     2  0.5168     0.0125 0.004 0.500 0.000 0.496
#> GSM379848     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379849     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379850     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379843     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379844     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379845     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379846     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379847     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379853     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379854     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379851     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379852     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379804     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379805     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379806     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379799     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379800     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379801     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379802     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379803     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379812     4  0.4193     0.6579 0.268 0.000 0.000 0.732
#> GSM379813     4  0.3873     0.7177 0.228 0.000 0.000 0.772
#> GSM379814     4  0.3688     0.7409 0.208 0.000 0.000 0.792
#> GSM379807     4  0.0592     0.8776 0.016 0.000 0.000 0.984
#> GSM379808     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379809     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379810     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379811     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379820     4  0.2530     0.8298 0.112 0.000 0.000 0.888
#> GSM379821     4  0.3907     0.7133 0.232 0.000 0.000 0.768
#> GSM379822     1  0.1867     0.8680 0.928 0.000 0.000 0.072
#> GSM379815     4  0.0188     0.8808 0.004 0.000 0.000 0.996
#> GSM379816     4  0.7535     0.4931 0.164 0.236 0.024 0.576
#> GSM379817     4  0.3942     0.7068 0.236 0.000 0.000 0.764
#> GSM379818     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379819     4  0.2011     0.8495 0.080 0.000 0.000 0.920
#> GSM379825     4  0.0000     0.8817 0.000 0.000 0.000 1.000
#> GSM379826     4  0.2408     0.8356 0.104 0.000 0.000 0.896
#> GSM379823     1  0.0188     0.9099 0.996 0.000 0.000 0.004
#> GSM379824     4  0.2345     0.8383 0.100 0.000 0.000 0.900
#> GSM379749     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379750     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379751     2  0.0188     0.9810 0.000 0.996 0.000 0.004
#> GSM379744     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379745     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379746     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379747     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379748     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379757     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379758     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379752     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379753     2  0.0188     0.9808 0.000 0.996 0.004 0.000
#> GSM379754     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379755     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379756     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379764     2  0.1302     0.9444 0.044 0.956 0.000 0.000
#> GSM379765     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379766     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379759     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379760     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379761     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379762     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379763     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379769     1  0.4888     0.2773 0.588 0.412 0.000 0.000
#> GSM379770     2  0.1474     0.9354 0.052 0.948 0.000 0.000
#> GSM379767     2  0.0921     0.9591 0.028 0.972 0.000 0.000
#> GSM379768     2  0.0000     0.9840 0.000 1.000 0.000 0.000
#> GSM379776     1  0.4304     0.5810 0.716 0.000 0.000 0.284
#> GSM379777     4  0.4998     0.0651 0.488 0.000 0.000 0.512
#> GSM379778     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379771     1  0.5220     0.4143 0.632 0.000 0.016 0.352
#> GSM379772     1  0.3693     0.8210 0.856 0.000 0.072 0.072
#> GSM379773     1  0.1474     0.8810 0.948 0.000 0.000 0.052
#> GSM379774     1  0.2469     0.8339 0.892 0.000 0.000 0.108
#> GSM379775     1  0.3311     0.7617 0.828 0.000 0.000 0.172
#> GSM379784     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379785     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379786     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379779     1  0.0188     0.9100 0.996 0.000 0.000 0.004
#> GSM379780     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379781     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379782     1  0.0188     0.9084 0.996 0.004 0.000 0.000
#> GSM379783     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379792     1  0.4888     0.2447 0.588 0.000 0.000 0.412
#> GSM379793     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379794     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379787     1  0.0188     0.9084 0.996 0.004 0.000 0.000
#> GSM379788     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379789     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379790     1  0.0336     0.9084 0.992 0.000 0.000 0.008
#> GSM379791     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379797     4  0.1211     0.8693 0.040 0.000 0.000 0.960
#> GSM379798     1  0.0336     0.9084 0.992 0.000 0.000 0.008
#> GSM379795     1  0.0000     0.9110 1.000 0.000 0.000 0.000
#> GSM379796     1  0.1716     0.8735 0.936 0.000 0.000 0.064
#> GSM379721     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379722     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379723     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379716     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379717     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379718     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379719     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379720     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379729     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379730     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379731     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379724     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379725     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379726     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379727     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379728     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379737     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379738     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379739     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379732     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379733     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379734     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379735     3  0.0336     0.9616 0.008 0.000 0.992 0.000
#> GSM379736     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379742     3  0.5132     0.2381 0.448 0.004 0.548 0.000
#> GSM379743     3  0.1940     0.8993 0.076 0.000 0.924 0.000
#> GSM379740     3  0.0000     0.9679 0.000 0.000 1.000 0.000
#> GSM379741     3  0.4543     0.5437 0.324 0.000 0.676 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     2  0.0000     0.9026 0.000 1.000 0.000 0.000 0.000
#> GSM379833     2  0.0162     0.9024 0.000 0.996 0.000 0.000 0.004
#> GSM379834     2  0.0162     0.9024 0.000 0.996 0.000 0.000 0.004
#> GSM379827     2  0.0290     0.9006 0.000 0.992 0.000 0.000 0.008
#> GSM379828     2  0.0290     0.9006 0.000 0.992 0.000 0.000 0.008
#> GSM379829     4  0.2589     0.7657 0.012 0.092 0.000 0.888 0.008
#> GSM379830     2  0.0290     0.9006 0.000 0.992 0.000 0.000 0.008
#> GSM379831     2  0.0290     0.9006 0.000 0.992 0.000 0.000 0.008
#> GSM379840     2  0.1956     0.8328 0.000 0.916 0.000 0.076 0.008
#> GSM379841     2  0.0290     0.9021 0.000 0.992 0.000 0.000 0.008
#> GSM379842     2  0.0324     0.9015 0.004 0.992 0.000 0.000 0.004
#> GSM379835     2  0.0451     0.8986 0.000 0.988 0.000 0.004 0.008
#> GSM379836     2  0.1186     0.8834 0.008 0.964 0.000 0.020 0.008
#> GSM379837     4  0.4449     0.2720 0.004 0.388 0.000 0.604 0.004
#> GSM379838     2  0.0162     0.9024 0.000 0.996 0.000 0.000 0.004
#> GSM379839     4  0.4151     0.3651 0.000 0.344 0.000 0.652 0.004
#> GSM379848     2  0.0404     0.9018 0.000 0.988 0.000 0.000 0.012
#> GSM379849     2  0.0510     0.9006 0.000 0.984 0.000 0.000 0.016
#> GSM379850     2  0.0290     0.9021 0.000 0.992 0.000 0.000 0.008
#> GSM379843     2  0.0290     0.9021 0.000 0.992 0.000 0.000 0.008
#> GSM379844     2  0.0290     0.9021 0.000 0.992 0.000 0.000 0.008
#> GSM379845     2  0.0451     0.8998 0.000 0.988 0.000 0.004 0.008
#> GSM379846     2  0.0162     0.9024 0.000 0.996 0.000 0.000 0.004
#> GSM379847     2  0.0290     0.9021 0.000 0.992 0.000 0.000 0.008
#> GSM379853     2  0.0324     0.9015 0.004 0.992 0.000 0.000 0.004
#> GSM379854     2  0.0290     0.9021 0.000 0.992 0.000 0.000 0.008
#> GSM379851     2  0.0290     0.9021 0.000 0.992 0.000 0.000 0.008
#> GSM379852     2  0.0404     0.9018 0.000 0.988 0.000 0.000 0.012
#> GSM379804     4  0.0162     0.8749 0.000 0.000 0.000 0.996 0.004
#> GSM379805     4  0.0000     0.8746 0.000 0.000 0.000 1.000 0.000
#> GSM379806     4  0.0000     0.8746 0.000 0.000 0.000 1.000 0.000
#> GSM379799     4  0.0162     0.8740 0.000 0.000 0.000 0.996 0.004
#> GSM379800     4  0.0162     0.8740 0.000 0.000 0.000 0.996 0.004
#> GSM379801     4  0.0162     0.8740 0.000 0.000 0.000 0.996 0.004
#> GSM379802     4  0.0162     0.8740 0.000 0.000 0.000 0.996 0.004
#> GSM379803     4  0.0671     0.8725 0.004 0.000 0.000 0.980 0.016
#> GSM379812     5  0.5049    -0.0899 0.032 0.000 0.000 0.484 0.484
#> GSM379813     4  0.4428     0.5531 0.032 0.000 0.000 0.700 0.268
#> GSM379814     4  0.2654     0.8113 0.048 0.000 0.000 0.888 0.064
#> GSM379807     4  0.1018     0.8665 0.016 0.000 0.000 0.968 0.016
#> GSM379808     4  0.0162     0.8740 0.000 0.000 0.000 0.996 0.004
#> GSM379809     4  0.0162     0.8740 0.000 0.000 0.000 0.996 0.004
#> GSM379810     4  0.0451     0.8743 0.004 0.000 0.000 0.988 0.008
#> GSM379811     4  0.0566     0.8734 0.004 0.000 0.000 0.984 0.012
#> GSM379820     4  0.1800     0.8497 0.020 0.000 0.000 0.932 0.048
#> GSM379821     5  0.3961     0.5533 0.028 0.000 0.000 0.212 0.760
#> GSM379822     5  0.3861     0.6522 0.128 0.000 0.000 0.068 0.804
#> GSM379815     4  0.0324     0.8751 0.004 0.000 0.000 0.992 0.004
#> GSM379816     4  0.4597     0.2538 0.000 0.012 0.000 0.564 0.424
#> GSM379817     4  0.4642     0.4746 0.032 0.000 0.000 0.660 0.308
#> GSM379818     4  0.0290     0.8748 0.000 0.000 0.000 0.992 0.008
#> GSM379819     4  0.1211     0.8634 0.016 0.000 0.000 0.960 0.024
#> GSM379825     4  0.0324     0.8751 0.004 0.000 0.000 0.992 0.004
#> GSM379826     4  0.1981     0.8427 0.016 0.000 0.000 0.920 0.064
#> GSM379823     5  0.3326     0.6525 0.152 0.000 0.000 0.024 0.824
#> GSM379824     4  0.3011     0.7733 0.016 0.000 0.000 0.844 0.140
#> GSM379749     2  0.2561     0.8993 0.000 0.856 0.000 0.000 0.144
#> GSM379750     2  0.2561     0.8993 0.000 0.856 0.000 0.000 0.144
#> GSM379751     2  0.2843     0.8976 0.000 0.848 0.000 0.008 0.144
#> GSM379744     2  0.2561     0.8993 0.000 0.856 0.000 0.000 0.144
#> GSM379745     2  0.2561     0.8993 0.000 0.856 0.000 0.000 0.144
#> GSM379746     2  0.2561     0.8993 0.000 0.856 0.000 0.000 0.144
#> GSM379747     2  0.2561     0.8993 0.000 0.856 0.000 0.000 0.144
#> GSM379748     2  0.2605     0.8989 0.000 0.852 0.000 0.000 0.148
#> GSM379757     2  0.2648     0.8974 0.000 0.848 0.000 0.000 0.152
#> GSM379758     2  0.2605     0.8980 0.000 0.852 0.000 0.000 0.148
#> GSM379752     2  0.2561     0.8993 0.000 0.856 0.000 0.000 0.144
#> GSM379753     2  0.2605     0.8989 0.000 0.852 0.000 0.000 0.148
#> GSM379754     2  0.2561     0.8993 0.000 0.856 0.000 0.000 0.144
#> GSM379755     2  0.2561     0.8993 0.000 0.856 0.000 0.000 0.144
#> GSM379756     2  0.2561     0.8993 0.000 0.856 0.000 0.000 0.144
#> GSM379764     5  0.3196     0.5383 0.004 0.192 0.000 0.000 0.804
#> GSM379765     2  0.2929     0.8832 0.000 0.820 0.000 0.000 0.180
#> GSM379766     2  0.3086     0.8791 0.004 0.816 0.000 0.000 0.180
#> GSM379759     2  0.2648     0.8974 0.000 0.848 0.000 0.000 0.152
#> GSM379760     2  0.2605     0.8980 0.000 0.852 0.000 0.000 0.148
#> GSM379761     2  0.2605     0.8980 0.000 0.852 0.000 0.000 0.148
#> GSM379762     2  0.2605     0.8980 0.000 0.852 0.000 0.000 0.148
#> GSM379763     2  0.2605     0.8980 0.000 0.852 0.000 0.000 0.148
#> GSM379769     5  0.2124     0.6233 0.004 0.096 0.000 0.000 0.900
#> GSM379770     2  0.4450     0.3406 0.004 0.508 0.000 0.000 0.488
#> GSM379767     2  0.3231     0.8656 0.004 0.800 0.000 0.000 0.196
#> GSM379768     2  0.3048     0.8821 0.004 0.820 0.000 0.000 0.176
#> GSM379776     1  0.1410     0.9135 0.940 0.000 0.000 0.060 0.000
#> GSM379777     1  0.3800     0.7892 0.812 0.000 0.000 0.108 0.080
#> GSM379778     1  0.0865     0.9355 0.972 0.024 0.000 0.000 0.004
#> GSM379771     1  0.2067     0.9055 0.920 0.000 0.032 0.048 0.000
#> GSM379772     1  0.1877     0.8962 0.924 0.000 0.064 0.012 0.000
#> GSM379773     1  0.1408     0.9196 0.948 0.044 0.000 0.008 0.000
#> GSM379774     1  0.1124     0.9321 0.960 0.004 0.000 0.036 0.000
#> GSM379775     1  0.1197     0.9239 0.952 0.000 0.000 0.048 0.000
#> GSM379784     1  0.1410     0.9215 0.940 0.000 0.000 0.000 0.060
#> GSM379785     1  0.0609     0.9418 0.980 0.000 0.000 0.000 0.020
#> GSM379786     1  0.1792     0.9020 0.916 0.000 0.000 0.000 0.084
#> GSM379779     1  0.0566     0.9444 0.984 0.000 0.004 0.012 0.000
#> GSM379780     1  0.0324     0.9452 0.992 0.004 0.000 0.004 0.000
#> GSM379781     1  0.0162     0.9448 0.996 0.004 0.000 0.000 0.000
#> GSM379782     1  0.1310     0.9331 0.956 0.024 0.000 0.000 0.020
#> GSM379783     1  0.1892     0.9054 0.916 0.004 0.000 0.000 0.080
#> GSM379792     1  0.0880     0.9358 0.968 0.000 0.000 0.032 0.000
#> GSM379793     1  0.0290     0.9444 0.992 0.000 0.000 0.000 0.008
#> GSM379794     1  0.0000     0.9448 1.000 0.000 0.000 0.000 0.000
#> GSM379787     1  0.0771     0.9376 0.976 0.020 0.000 0.000 0.004
#> GSM379788     1  0.0609     0.9419 0.980 0.000 0.000 0.000 0.020
#> GSM379789     1  0.0000     0.9448 1.000 0.000 0.000 0.000 0.000
#> GSM379790     1  0.0000     0.9448 1.000 0.000 0.000 0.000 0.000
#> GSM379791     1  0.0162     0.9446 0.996 0.000 0.000 0.000 0.004
#> GSM379797     1  0.4251     0.5186 0.672 0.000 0.000 0.316 0.012
#> GSM379798     1  0.0000     0.9448 1.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0162     0.9446 0.996 0.000 0.000 0.000 0.004
#> GSM379796     1  0.0290     0.9452 0.992 0.000 0.000 0.008 0.000
#> GSM379721     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379722     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379723     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379716     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379717     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379718     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379719     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379720     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379729     3  0.1270     0.9121 0.000 0.000 0.948 0.000 0.052
#> GSM379730     3  0.1671     0.8925 0.000 0.000 0.924 0.000 0.076
#> GSM379731     3  0.1270     0.9118 0.000 0.000 0.948 0.000 0.052
#> GSM379724     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379725     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379726     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379727     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379728     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379737     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379738     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379739     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379732     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379733     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379734     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379735     3  0.2377     0.8408 0.000 0.000 0.872 0.000 0.128
#> GSM379736     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379742     5  0.5434     0.3037 0.076 0.000 0.336 0.000 0.588
#> GSM379743     3  0.4767     0.2780 0.020 0.000 0.560 0.000 0.420
#> GSM379740     3  0.0000     0.9530 0.000 0.000 1.000 0.000 0.000
#> GSM379741     3  0.5155     0.3501 0.052 0.000 0.596 0.000 0.352

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     5  0.3499      0.926 0.000 0.320 0.000 0.000 0.680 0.000
#> GSM379833     5  0.3446      0.930 0.000 0.308 0.000 0.000 0.692 0.000
#> GSM379834     5  0.3482      0.929 0.000 0.316 0.000 0.000 0.684 0.000
#> GSM379827     5  0.3717      0.913 0.000 0.276 0.000 0.000 0.708 0.016
#> GSM379828     5  0.3608      0.910 0.000 0.272 0.000 0.000 0.716 0.012
#> GSM379829     4  0.4206      0.230 0.000 0.000 0.000 0.620 0.356 0.024
#> GSM379830     5  0.3650      0.918 0.000 0.280 0.000 0.000 0.708 0.012
#> GSM379831     5  0.3650      0.918 0.000 0.280 0.000 0.000 0.708 0.012
#> GSM379840     5  0.4166      0.839 0.000 0.196 0.000 0.076 0.728 0.000
#> GSM379841     5  0.3482      0.928 0.000 0.316 0.000 0.000 0.684 0.000
#> GSM379842     5  0.3409      0.929 0.000 0.300 0.000 0.000 0.700 0.000
#> GSM379835     5  0.3629      0.916 0.000 0.276 0.000 0.000 0.712 0.012
#> GSM379836     5  0.3724      0.907 0.000 0.268 0.000 0.004 0.716 0.012
#> GSM379837     5  0.4074      0.480 0.000 0.020 0.000 0.264 0.704 0.012
#> GSM379838     5  0.3531      0.920 0.000 0.328 0.000 0.000 0.672 0.000
#> GSM379839     5  0.4074      0.479 0.000 0.020 0.000 0.264 0.704 0.012
#> GSM379848     5  0.3499      0.923 0.000 0.320 0.000 0.000 0.680 0.000
#> GSM379849     5  0.3784      0.925 0.000 0.308 0.000 0.000 0.680 0.012
#> GSM379850     5  0.3619      0.928 0.000 0.316 0.000 0.000 0.680 0.004
#> GSM379843     5  0.3446      0.929 0.000 0.308 0.000 0.000 0.692 0.000
#> GSM379844     5  0.3464      0.930 0.000 0.312 0.000 0.000 0.688 0.000
#> GSM379845     5  0.3650      0.915 0.000 0.272 0.000 0.004 0.716 0.008
#> GSM379846     5  0.3482      0.929 0.000 0.316 0.000 0.000 0.684 0.000
#> GSM379847     5  0.3464      0.930 0.000 0.312 0.000 0.000 0.688 0.000
#> GSM379853     5  0.3897      0.922 0.000 0.280 0.000 0.000 0.696 0.024
#> GSM379854     5  0.3482      0.928 0.000 0.316 0.000 0.000 0.684 0.000
#> GSM379851     5  0.3464      0.930 0.000 0.312 0.000 0.000 0.688 0.000
#> GSM379852     5  0.3464      0.930 0.000 0.312 0.000 0.000 0.688 0.000
#> GSM379804     4  0.0146      0.865 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM379805     4  0.0291      0.864 0.000 0.000 0.000 0.992 0.004 0.004
#> GSM379806     4  0.0146      0.865 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM379799     4  0.1176      0.844 0.000 0.000 0.000 0.956 0.024 0.020
#> GSM379800     4  0.1176      0.844 0.000 0.000 0.000 0.956 0.024 0.020
#> GSM379801     4  0.1418      0.834 0.000 0.000 0.000 0.944 0.032 0.024
#> GSM379802     4  0.0405      0.863 0.000 0.000 0.000 0.988 0.008 0.004
#> GSM379803     4  0.0865      0.851 0.000 0.000 0.000 0.964 0.000 0.036
#> GSM379812     4  0.3647      0.217 0.000 0.000 0.000 0.640 0.000 0.360
#> GSM379813     4  0.2912      0.606 0.000 0.000 0.000 0.784 0.000 0.216
#> GSM379814     4  0.2001      0.822 0.012 0.000 0.000 0.912 0.068 0.008
#> GSM379807     4  0.0260      0.865 0.000 0.000 0.000 0.992 0.000 0.008
#> GSM379808     4  0.0717      0.858 0.000 0.000 0.000 0.976 0.008 0.016
#> GSM379809     4  0.0520      0.862 0.000 0.000 0.000 0.984 0.008 0.008
#> GSM379810     4  0.0000      0.866 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379811     4  0.0260      0.865 0.000 0.000 0.000 0.992 0.000 0.008
#> GSM379820     4  0.2320      0.770 0.000 0.000 0.000 0.864 0.132 0.004
#> GSM379821     6  0.3817      0.353 0.000 0.000 0.000 0.432 0.000 0.568
#> GSM379822     6  0.2402      0.774 0.000 0.000 0.000 0.140 0.004 0.856
#> GSM379815     4  0.0000      0.866 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379816     4  0.6099     -0.151 0.000 0.152 0.004 0.512 0.020 0.312
#> GSM379817     4  0.3112      0.745 0.000 0.000 0.000 0.836 0.096 0.068
#> GSM379818     4  0.0146      0.865 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM379819     4  0.0520      0.863 0.000 0.000 0.000 0.984 0.008 0.008
#> GSM379825     4  0.0000      0.866 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379826     4  0.1686      0.831 0.000 0.000 0.000 0.924 0.064 0.012
#> GSM379823     6  0.1958      0.760 0.000 0.000 0.000 0.100 0.004 0.896
#> GSM379824     4  0.2597      0.682 0.000 0.000 0.000 0.824 0.000 0.176
#> GSM379749     2  0.0363      0.943 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379750     2  0.0458      0.942 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379751     2  0.1257      0.921 0.000 0.952 0.000 0.000 0.020 0.028
#> GSM379744     2  0.0622      0.939 0.000 0.980 0.000 0.000 0.012 0.008
#> GSM379745     2  0.0622      0.939 0.000 0.980 0.000 0.000 0.012 0.008
#> GSM379746     2  0.0508      0.944 0.000 0.984 0.000 0.000 0.012 0.004
#> GSM379747     2  0.0622      0.939 0.000 0.980 0.000 0.000 0.012 0.008
#> GSM379748     2  0.0508      0.943 0.000 0.984 0.000 0.000 0.012 0.004
#> GSM379757     2  0.0363      0.944 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379758     2  0.0547      0.940 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379752     2  0.0405      0.944 0.000 0.988 0.000 0.000 0.008 0.004
#> GSM379753     2  0.0622      0.939 0.000 0.980 0.000 0.000 0.012 0.008
#> GSM379754     2  0.0363      0.944 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379755     2  0.0458      0.942 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379756     2  0.0458      0.942 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379764     2  0.2889      0.809 0.000 0.848 0.000 0.000 0.108 0.044
#> GSM379765     2  0.0806      0.940 0.000 0.972 0.000 0.000 0.008 0.020
#> GSM379766     2  0.0935      0.937 0.000 0.964 0.000 0.000 0.004 0.032
#> GSM379759     2  0.0777      0.941 0.000 0.972 0.000 0.000 0.024 0.004
#> GSM379760     2  0.0458      0.942 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379761     2  0.0458      0.942 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379762     2  0.0260      0.944 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379763     2  0.0458      0.942 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379769     2  0.4853      0.481 0.000 0.644 0.000 0.000 0.248 0.108
#> GSM379770     2  0.4361      0.610 0.004 0.716 0.000 0.000 0.204 0.076
#> GSM379767     2  0.1080      0.934 0.004 0.960 0.000 0.000 0.004 0.032
#> GSM379768     2  0.0790      0.936 0.000 0.968 0.000 0.000 0.000 0.032
#> GSM379776     1  0.0146      0.959 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM379777     1  0.4061      0.581 0.708 0.000 0.000 0.044 0.000 0.248
#> GSM379778     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379771     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379772     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379773     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379774     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379775     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379784     1  0.0603      0.949 0.980 0.000 0.000 0.004 0.000 0.016
#> GSM379785     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379786     1  0.1411      0.908 0.936 0.000 0.000 0.004 0.000 0.060
#> GSM379779     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379780     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379781     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379782     1  0.0146      0.960 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379783     1  0.1082      0.928 0.956 0.000 0.000 0.004 0.000 0.040
#> GSM379792     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379793     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379794     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379787     1  0.0146      0.960 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM379788     1  0.0291      0.957 0.992 0.000 0.000 0.004 0.000 0.004
#> GSM379789     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379790     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379791     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379797     1  0.3971      0.134 0.548 0.000 0.000 0.448 0.000 0.004
#> GSM379798     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379796     1  0.0000      0.962 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379721     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379722     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379723     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379716     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379717     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379718     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379719     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379720     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379729     3  0.2260      0.829 0.000 0.000 0.860 0.000 0.000 0.140
#> GSM379730     3  0.3198      0.685 0.000 0.000 0.740 0.000 0.000 0.260
#> GSM379731     3  0.1556      0.882 0.000 0.000 0.920 0.000 0.000 0.080
#> GSM379724     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379725     3  0.0146      0.936 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM379726     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379727     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379728     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379737     3  0.0146      0.936 0.000 0.000 0.996 0.000 0.004 0.000
#> GSM379738     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379739     3  0.0146      0.936 0.000 0.000 0.996 0.000 0.004 0.000
#> GSM379732     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379733     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379734     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379735     3  0.2854      0.753 0.000 0.000 0.792 0.000 0.000 0.208
#> GSM379736     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379742     3  0.5865      0.252 0.000 0.012 0.504 0.000 0.152 0.332
#> GSM379743     3  0.3446      0.625 0.000 0.000 0.692 0.000 0.000 0.308
#> GSM379740     3  0.0000      0.938 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379741     3  0.2664      0.817 0.000 0.000 0.848 0.000 0.016 0.136

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-MAD-NMF-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-MAD-NMF-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-MAD-NMF-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-MAD-NMF-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-MAD-NMF-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-MAD-NMF-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-MAD-NMF-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-MAD-NMF-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-MAD-NMF-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-MAD-NMF-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-MAD-NMF-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-MAD-NMF-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-MAD-NMF-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-MAD-NMF-get-signatures-4

get_signatures(res, k = 6)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-MAD-NMF-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-MAD-NMF-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-MAD-NMF-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-MAD-NMF-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-MAD-NMF-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-MAD-NMF-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk MAD-NMF-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-MAD-NMF-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-MAD-NMF-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-MAD-NMF-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-MAD-NMF-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-MAD-NMF-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk MAD-NMF-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>           n individual(p) time(p) agent(p) k
#> MAD:NMF 137      7.88e-24   1.000  0.86881 2
#> MAD:NMF 115      2.97e-36   0.994  0.00537 3
#> MAD:NMF 131      2.80e-69   1.000  0.87355 4
#> MAD:NMF 130      4.77e-70   1.000  0.54802 5
#> MAD:NMF 130      1.88e-97   1.000  0.94808 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

ATC:hclust**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["ATC", "hclust"]
# you can also extract it by
# res = res_list["ATC:hclust"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#>   Subgroups are detected by 'hclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk ATC-hclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk ATC-hclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.989       0.995         0.4852 0.515   0.515
#> 3 3 0.755           0.809       0.902         0.2284 0.931   0.865
#> 4 4 0.711           0.839       0.895         0.1371 0.895   0.764
#> 5 5 0.793           0.758       0.857         0.0601 0.966   0.901
#> 6 6 0.843           0.832       0.891         0.0443 0.923   0.753

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000      0.994 0.000 1.000
#> GSM379833     2  0.0000      0.994 0.000 1.000
#> GSM379834     2  0.0000      0.994 0.000 1.000
#> GSM379827     2  0.0000      0.994 0.000 1.000
#> GSM379828     2  0.0000      0.994 0.000 1.000
#> GSM379829     1  0.0000      0.995 1.000 0.000
#> GSM379830     2  0.0376      0.991 0.004 0.996
#> GSM379831     2  0.0000      0.994 0.000 1.000
#> GSM379840     2  0.6148      0.822 0.152 0.848
#> GSM379841     2  0.0000      0.994 0.000 1.000
#> GSM379842     2  0.0000      0.994 0.000 1.000
#> GSM379835     2  0.0000      0.994 0.000 1.000
#> GSM379836     2  0.6148      0.822 0.152 0.848
#> GSM379837     1  0.2948      0.943 0.948 0.052
#> GSM379838     2  0.0000      0.994 0.000 1.000
#> GSM379839     1  0.2948      0.943 0.948 0.052
#> GSM379848     2  0.0000      0.994 0.000 1.000
#> GSM379849     2  0.0000      0.994 0.000 1.000
#> GSM379850     2  0.0000      0.994 0.000 1.000
#> GSM379843     2  0.0000      0.994 0.000 1.000
#> GSM379844     2  0.0000      0.994 0.000 1.000
#> GSM379845     1  0.8608      0.602 0.716 0.284
#> GSM379846     2  0.0000      0.994 0.000 1.000
#> GSM379847     2  0.0000      0.994 0.000 1.000
#> GSM379853     2  0.0000      0.994 0.000 1.000
#> GSM379854     2  0.0000      0.994 0.000 1.000
#> GSM379851     2  0.0000      0.994 0.000 1.000
#> GSM379852     2  0.0000      0.994 0.000 1.000
#> GSM379804     1  0.0000      0.995 1.000 0.000
#> GSM379805     1  0.0000      0.995 1.000 0.000
#> GSM379806     1  0.0000      0.995 1.000 0.000
#> GSM379799     1  0.0000      0.995 1.000 0.000
#> GSM379800     1  0.0000      0.995 1.000 0.000
#> GSM379801     1  0.0000      0.995 1.000 0.000
#> GSM379802     1  0.0000      0.995 1.000 0.000
#> GSM379803     1  0.0000      0.995 1.000 0.000
#> GSM379812     1  0.0000      0.995 1.000 0.000
#> GSM379813     1  0.0000      0.995 1.000 0.000
#> GSM379814     1  0.0000      0.995 1.000 0.000
#> GSM379807     1  0.0000      0.995 1.000 0.000
#> GSM379808     1  0.0000      0.995 1.000 0.000
#> GSM379809     1  0.0000      0.995 1.000 0.000
#> GSM379810     1  0.0000      0.995 1.000 0.000
#> GSM379811     1  0.0000      0.995 1.000 0.000
#> GSM379820     1  0.0000      0.995 1.000 0.000
#> GSM379821     1  0.0000      0.995 1.000 0.000
#> GSM379822     1  0.0000      0.995 1.000 0.000
#> GSM379815     1  0.0000      0.995 1.000 0.000
#> GSM379816     1  0.0000      0.995 1.000 0.000
#> GSM379817     1  0.0000      0.995 1.000 0.000
#> GSM379818     1  0.0000      0.995 1.000 0.000
#> GSM379819     1  0.0000      0.995 1.000 0.000
#> GSM379825     1  0.0000      0.995 1.000 0.000
#> GSM379826     1  0.0000      0.995 1.000 0.000
#> GSM379823     1  0.0000      0.995 1.000 0.000
#> GSM379824     1  0.0000      0.995 1.000 0.000
#> GSM379749     2  0.0000      0.994 0.000 1.000
#> GSM379750     2  0.0000      0.994 0.000 1.000
#> GSM379751     2  0.0000      0.994 0.000 1.000
#> GSM379744     2  0.0000      0.994 0.000 1.000
#> GSM379745     2  0.0000      0.994 0.000 1.000
#> GSM379746     2  0.0000      0.994 0.000 1.000
#> GSM379747     2  0.0000      0.994 0.000 1.000
#> GSM379748     2  0.0000      0.994 0.000 1.000
#> GSM379757     2  0.0000      0.994 0.000 1.000
#> GSM379758     2  0.0000      0.994 0.000 1.000
#> GSM379752     2  0.0000      0.994 0.000 1.000
#> GSM379753     2  0.0000      0.994 0.000 1.000
#> GSM379754     2  0.0000      0.994 0.000 1.000
#> GSM379755     2  0.0000      0.994 0.000 1.000
#> GSM379756     2  0.0000      0.994 0.000 1.000
#> GSM379764     2  0.0000      0.994 0.000 1.000
#> GSM379765     2  0.0000      0.994 0.000 1.000
#> GSM379766     2  0.0000      0.994 0.000 1.000
#> GSM379759     2  0.0000      0.994 0.000 1.000
#> GSM379760     2  0.0000      0.994 0.000 1.000
#> GSM379761     2  0.0000      0.994 0.000 1.000
#> GSM379762     2  0.0000      0.994 0.000 1.000
#> GSM379763     2  0.0000      0.994 0.000 1.000
#> GSM379769     2  0.0000      0.994 0.000 1.000
#> GSM379770     2  0.0000      0.994 0.000 1.000
#> GSM379767     2  0.0000      0.994 0.000 1.000
#> GSM379768     2  0.0000      0.994 0.000 1.000
#> GSM379776     1  0.0000      0.995 1.000 0.000
#> GSM379777     1  0.0000      0.995 1.000 0.000
#> GSM379778     2  0.0000      0.994 0.000 1.000
#> GSM379771     1  0.0000      0.995 1.000 0.000
#> GSM379772     1  0.0000      0.995 1.000 0.000
#> GSM379773     1  0.0000      0.995 1.000 0.000
#> GSM379774     1  0.0000      0.995 1.000 0.000
#> GSM379775     1  0.0000      0.995 1.000 0.000
#> GSM379784     1  0.0000      0.995 1.000 0.000
#> GSM379785     1  0.0000      0.995 1.000 0.000
#> GSM379786     1  0.0000      0.995 1.000 0.000
#> GSM379779     1  0.0000      0.995 1.000 0.000
#> GSM379780     1  0.0000      0.995 1.000 0.000
#> GSM379781     1  0.0000      0.995 1.000 0.000
#> GSM379782     2  0.0000      0.994 0.000 1.000
#> GSM379783     1  0.0000      0.995 1.000 0.000
#> GSM379792     1  0.0000      0.995 1.000 0.000
#> GSM379793     1  0.0000      0.995 1.000 0.000
#> GSM379794     1  0.0000      0.995 1.000 0.000
#> GSM379787     2  0.0000      0.994 0.000 1.000
#> GSM379788     1  0.0000      0.995 1.000 0.000
#> GSM379789     1  0.0000      0.995 1.000 0.000
#> GSM379790     1  0.0000      0.995 1.000 0.000
#> GSM379791     1  0.0000      0.995 1.000 0.000
#> GSM379797     1  0.0000      0.995 1.000 0.000
#> GSM379798     1  0.0000      0.995 1.000 0.000
#> GSM379795     1  0.0000      0.995 1.000 0.000
#> GSM379796     1  0.0000      0.995 1.000 0.000
#> GSM379721     1  0.0000      0.995 1.000 0.000
#> GSM379722     1  0.0000      0.995 1.000 0.000
#> GSM379723     1  0.0000      0.995 1.000 0.000
#> GSM379716     1  0.0000      0.995 1.000 0.000
#> GSM379717     1  0.0000      0.995 1.000 0.000
#> GSM379718     1  0.0000      0.995 1.000 0.000
#> GSM379719     1  0.0000      0.995 1.000 0.000
#> GSM379720     1  0.0000      0.995 1.000 0.000
#> GSM379729     1  0.0000      0.995 1.000 0.000
#> GSM379730     1  0.0000      0.995 1.000 0.000
#> GSM379731     1  0.0000      0.995 1.000 0.000
#> GSM379724     1  0.0000      0.995 1.000 0.000
#> GSM379725     1  0.0000      0.995 1.000 0.000
#> GSM379726     1  0.0000      0.995 1.000 0.000
#> GSM379727     1  0.0000      0.995 1.000 0.000
#> GSM379728     1  0.0000      0.995 1.000 0.000
#> GSM379737     1  0.0000      0.995 1.000 0.000
#> GSM379738     1  0.0000      0.995 1.000 0.000
#> GSM379739     1  0.0000      0.995 1.000 0.000
#> GSM379732     1  0.0000      0.995 1.000 0.000
#> GSM379733     1  0.0000      0.995 1.000 0.000
#> GSM379734     1  0.0000      0.995 1.000 0.000
#> GSM379735     1  0.0000      0.995 1.000 0.000
#> GSM379736     1  0.0000      0.995 1.000 0.000
#> GSM379742     2  0.0000      0.994 0.000 1.000
#> GSM379743     1  0.0000      0.995 1.000 0.000
#> GSM379740     1  0.0000      0.995 1.000 0.000
#> GSM379741     2  0.0000      0.994 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379833     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379834     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379827     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379828     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379829     1  0.2878     0.7705 0.904 0.000 0.096
#> GSM379830     2  0.0237     0.9889 0.004 0.996 0.000
#> GSM379831     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379840     2  0.4821     0.8139 0.064 0.848 0.088
#> GSM379841     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379842     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379835     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379836     2  0.4821     0.8139 0.064 0.848 0.088
#> GSM379837     1  0.4689     0.7373 0.852 0.052 0.096
#> GSM379838     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379839     1  0.4689     0.7373 0.852 0.052 0.096
#> GSM379848     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379849     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379850     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379843     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379844     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379845     1  0.8000     0.3834 0.620 0.284 0.096
#> GSM379846     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379847     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379853     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379854     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379851     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379852     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379804     1  0.3752     0.6694 0.856 0.000 0.144
#> GSM379805     1  0.5926     0.2069 0.644 0.000 0.356
#> GSM379806     1  0.6274    -0.2221 0.544 0.000 0.456
#> GSM379799     3  0.4974     0.9634 0.236 0.000 0.764
#> GSM379800     3  0.4974     0.9634 0.236 0.000 0.764
#> GSM379801     3  0.5291     0.9292 0.268 0.000 0.732
#> GSM379802     3  0.4974     0.9634 0.236 0.000 0.764
#> GSM379803     3  0.4887     0.7484 0.228 0.000 0.772
#> GSM379812     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379813     1  0.1031     0.8013 0.976 0.000 0.024
#> GSM379814     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379807     1  0.6180    -0.0503 0.584 0.000 0.416
#> GSM379808     1  0.6274    -0.2221 0.544 0.000 0.456
#> GSM379809     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379810     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379811     3  0.5098     0.9539 0.248 0.000 0.752
#> GSM379820     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379821     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379822     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379815     1  0.0747     0.7990 0.984 0.000 0.016
#> GSM379816     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379817     1  0.1031     0.8013 0.976 0.000 0.024
#> GSM379818     3  0.4974     0.9634 0.236 0.000 0.764
#> GSM379819     1  0.5859     0.2476 0.656 0.000 0.344
#> GSM379825     3  0.4974     0.9634 0.236 0.000 0.764
#> GSM379826     1  0.1031     0.8013 0.976 0.000 0.024
#> GSM379823     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379824     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379749     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379750     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379751     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379744     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379745     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379746     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379747     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379748     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379757     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379758     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379752     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379753     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379754     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379755     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379756     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379764     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379765     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379766     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379759     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379760     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379761     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379762     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379763     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379769     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379770     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379767     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379768     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379776     1  0.5859     0.2476 0.656 0.000 0.344
#> GSM379777     1  0.6274     0.3467 0.544 0.000 0.456
#> GSM379778     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379771     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379772     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379773     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379774     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379775     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379784     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379785     1  0.0424     0.8063 0.992 0.000 0.008
#> GSM379786     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379779     1  0.4121     0.6287 0.832 0.000 0.168
#> GSM379780     1  0.0424     0.8063 0.992 0.000 0.008
#> GSM379781     1  0.0424     0.8063 0.992 0.000 0.008
#> GSM379782     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379783     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379792     1  0.5859     0.2476 0.656 0.000 0.344
#> GSM379793     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379794     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379787     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379788     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379789     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379790     1  0.5835     0.2598 0.660 0.000 0.340
#> GSM379791     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379797     3  0.4974     0.9634 0.236 0.000 0.764
#> GSM379798     1  0.5678     0.3294 0.684 0.000 0.316
#> GSM379795     1  0.0000     0.8073 1.000 0.000 0.000
#> GSM379796     1  0.5859     0.2476 0.656 0.000 0.344
#> GSM379721     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379722     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379723     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379716     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379717     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379718     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379719     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379720     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379729     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379730     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379731     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379724     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379725     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379726     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379727     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379728     1  0.5327     0.4368 0.728 0.000 0.272
#> GSM379737     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379738     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379739     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379732     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379733     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379734     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379735     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379736     1  0.5733     0.3074 0.676 0.000 0.324
#> GSM379742     2  0.0000     0.9938 0.000 1.000 0.000
#> GSM379743     1  0.4974     0.6947 0.764 0.000 0.236
#> GSM379740     1  0.0237     0.8067 0.996 0.000 0.004
#> GSM379741     2  0.0000     0.9938 0.000 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379833     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379834     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379827     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379828     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379829     1  0.3208     0.7305 0.848 0.000 0.148 0.004
#> GSM379830     2  0.4307     0.8748 0.000 0.808 0.048 0.144
#> GSM379831     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379840     2  0.5262     0.8176 0.048 0.792 0.100 0.060
#> GSM379841     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379842     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379835     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379836     2  0.5262     0.8176 0.048 0.792 0.100 0.060
#> GSM379837     1  0.4514     0.6657 0.796 0.000 0.148 0.056
#> GSM379838     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379839     1  0.4514     0.6657 0.796 0.000 0.148 0.056
#> GSM379848     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379849     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379850     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379843     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379844     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379845     1  0.7979     0.2683 0.564 0.232 0.148 0.056
#> GSM379846     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379847     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379853     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379854     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379851     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379852     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379804     1  0.3257     0.7363 0.844 0.000 0.004 0.152
#> GSM379805     1  0.4761     0.3801 0.628 0.000 0.000 0.372
#> GSM379806     1  0.4992     0.0186 0.524 0.000 0.000 0.476
#> GSM379799     4  0.3024     0.9602 0.148 0.000 0.000 0.852
#> GSM379800     4  0.3024     0.9602 0.148 0.000 0.000 0.852
#> GSM379801     4  0.3400     0.9261 0.180 0.000 0.000 0.820
#> GSM379802     4  0.3024     0.9602 0.148 0.000 0.000 0.852
#> GSM379803     4  0.5820     0.6756 0.100 0.000 0.204 0.696
#> GSM379812     3  0.2760     0.9444 0.128 0.000 0.872 0.000
#> GSM379813     1  0.1302     0.8313 0.956 0.000 0.044 0.000
#> GSM379814     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379807     1  0.4941     0.1806 0.564 0.000 0.000 0.436
#> GSM379808     1  0.4992     0.0186 0.524 0.000 0.000 0.476
#> GSM379809     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379810     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379811     4  0.3172     0.9501 0.160 0.000 0.000 0.840
#> GSM379820     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379821     3  0.2345     0.9649 0.100 0.000 0.900 0.000
#> GSM379822     3  0.2345     0.9649 0.100 0.000 0.900 0.000
#> GSM379815     1  0.0779     0.8507 0.980 0.000 0.004 0.016
#> GSM379816     3  0.2345     0.9649 0.100 0.000 0.900 0.000
#> GSM379817     1  0.1302     0.8313 0.956 0.000 0.044 0.000
#> GSM379818     4  0.3024     0.9602 0.148 0.000 0.000 0.852
#> GSM379819     1  0.4713     0.4095 0.640 0.000 0.000 0.360
#> GSM379825     4  0.3024     0.9602 0.148 0.000 0.000 0.852
#> GSM379826     1  0.1302     0.8313 0.956 0.000 0.044 0.000
#> GSM379823     3  0.2345     0.9649 0.100 0.000 0.900 0.000
#> GSM379824     3  0.2345     0.9649 0.100 0.000 0.900 0.000
#> GSM379749     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379750     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379751     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379744     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379745     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379746     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379747     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379748     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379757     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379758     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379752     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379753     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379754     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379755     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379756     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379764     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379765     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379766     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379759     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379760     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379761     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379762     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379763     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379769     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379770     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379767     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379768     2  0.0000     0.9320 0.000 1.000 0.000 0.000
#> GSM379776     1  0.4713     0.4095 0.640 0.000 0.000 0.360
#> GSM379777     3  0.6370     0.5430 0.100 0.000 0.620 0.280
#> GSM379778     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379771     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379772     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379773     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379774     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379775     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379784     3  0.2345     0.9649 0.100 0.000 0.900 0.000
#> GSM379785     1  0.0469     0.8541 0.988 0.000 0.012 0.000
#> GSM379786     3  0.2345     0.9649 0.100 0.000 0.900 0.000
#> GSM379779     1  0.3583     0.7022 0.816 0.000 0.004 0.180
#> GSM379780     1  0.0469     0.8541 0.988 0.000 0.012 0.000
#> GSM379781     1  0.0469     0.8541 0.988 0.000 0.012 0.000
#> GSM379782     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379783     3  0.2345     0.9649 0.100 0.000 0.900 0.000
#> GSM379792     1  0.4713     0.4095 0.640 0.000 0.000 0.360
#> GSM379793     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379794     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379787     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379788     3  0.2345     0.9649 0.100 0.000 0.900 0.000
#> GSM379789     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379790     1  0.4697     0.4182 0.644 0.000 0.000 0.356
#> GSM379791     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379797     4  0.3024     0.9602 0.148 0.000 0.000 0.852
#> GSM379798     1  0.4543     0.4833 0.676 0.000 0.000 0.324
#> GSM379795     1  0.0188     0.8584 0.996 0.000 0.004 0.000
#> GSM379796     1  0.4713     0.4095 0.640 0.000 0.000 0.360
#> GSM379721     1  0.0188     0.8579 0.996 0.000 0.004 0.000
#> GSM379722     1  0.0188     0.8579 0.996 0.000 0.004 0.000
#> GSM379723     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379716     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379717     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379718     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379719     1  0.0188     0.8579 0.996 0.000 0.004 0.000
#> GSM379720     1  0.0188     0.8579 0.996 0.000 0.004 0.000
#> GSM379729     3  0.2647     0.9620 0.120 0.000 0.880 0.000
#> GSM379730     3  0.2647     0.9620 0.120 0.000 0.880 0.000
#> GSM379731     3  0.2647     0.9620 0.120 0.000 0.880 0.000
#> GSM379724     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379725     3  0.2647     0.9620 0.120 0.000 0.880 0.000
#> GSM379726     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379727     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379728     1  0.4331     0.5467 0.712 0.000 0.000 0.288
#> GSM379737     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379738     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379739     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379732     3  0.2647     0.9620 0.120 0.000 0.880 0.000
#> GSM379733     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379734     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379735     3  0.2647     0.9620 0.120 0.000 0.880 0.000
#> GSM379736     1  0.4624     0.4505 0.660 0.000 0.000 0.340
#> GSM379742     2  0.4224     0.8773 0.000 0.812 0.044 0.144
#> GSM379743     3  0.2647     0.9620 0.120 0.000 0.880 0.000
#> GSM379740     1  0.0000     0.8584 1.000 0.000 0.000 0.000
#> GSM379741     2  0.4224     0.8773 0.000 0.812 0.044 0.144

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379833     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379834     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379827     2  0.0000     0.6009 0.000 1.000 0.000 0.000 0.000
#> GSM379828     2  0.0000     0.6009 0.000 1.000 0.000 0.000 0.000
#> GSM379829     5  0.6731     0.7294 0.324 0.000 0.056 0.092 0.528
#> GSM379830     2  0.0162     0.5971 0.000 0.996 0.000 0.000 0.004
#> GSM379831     2  0.0000     0.6009 0.000 1.000 0.000 0.000 0.000
#> GSM379840     2  0.3483     0.5423 0.000 0.848 0.052 0.088 0.012
#> GSM379841     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379842     2  0.0880     0.6198 0.000 0.968 0.000 0.000 0.032
#> GSM379835     2  0.0000     0.6009 0.000 1.000 0.000 0.000 0.000
#> GSM379836     2  0.3483     0.5423 0.000 0.848 0.052 0.088 0.012
#> GSM379837     5  0.7618     0.8029 0.272 0.052 0.056 0.092 0.528
#> GSM379838     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379839     5  0.7618     0.8029 0.272 0.052 0.056 0.092 0.528
#> GSM379848     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379849     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379850     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379843     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379844     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379845     5  0.7546     0.5225 0.044 0.284 0.056 0.092 0.524
#> GSM379846     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379847     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379853     2  0.0000     0.6009 0.000 1.000 0.000 0.000 0.000
#> GSM379854     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379851     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379852     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379804     1  0.2890     0.7325 0.836 0.000 0.004 0.160 0.000
#> GSM379805     1  0.4161     0.2900 0.608 0.000 0.000 0.392 0.000
#> GSM379806     4  0.4300     0.1608 0.476 0.000 0.000 0.524 0.000
#> GSM379799     4  0.1908     0.8085 0.092 0.000 0.000 0.908 0.000
#> GSM379800     4  0.1908     0.8085 0.092 0.000 0.000 0.908 0.000
#> GSM379801     4  0.2377     0.7777 0.128 0.000 0.000 0.872 0.000
#> GSM379802     4  0.1908     0.8085 0.092 0.000 0.000 0.908 0.000
#> GSM379803     4  0.4645     0.5592 0.072 0.000 0.204 0.724 0.000
#> GSM379812     3  0.1851     0.9311 0.088 0.000 0.912 0.000 0.000
#> GSM379813     1  0.1121     0.8394 0.956 0.000 0.044 0.000 0.000
#> GSM379814     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379807     1  0.4283     0.0446 0.544 0.000 0.000 0.456 0.000
#> GSM379808     4  0.4300     0.1608 0.476 0.000 0.000 0.524 0.000
#> GSM379809     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379810     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379811     4  0.2074     0.8023 0.104 0.000 0.000 0.896 0.000
#> GSM379820     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379821     3  0.1341     0.9423 0.056 0.000 0.944 0.000 0.000
#> GSM379822     3  0.1341     0.9423 0.056 0.000 0.944 0.000 0.000
#> GSM379815     1  0.0865     0.8605 0.972 0.000 0.004 0.024 0.000
#> GSM379816     3  0.1410     0.9456 0.060 0.000 0.940 0.000 0.000
#> GSM379817     1  0.1121     0.8394 0.956 0.000 0.044 0.000 0.000
#> GSM379818     4  0.1908     0.8085 0.092 0.000 0.000 0.908 0.000
#> GSM379819     1  0.4126     0.3265 0.620 0.000 0.000 0.380 0.000
#> GSM379825     4  0.1908     0.8085 0.092 0.000 0.000 0.908 0.000
#> GSM379826     1  0.1121     0.8394 0.956 0.000 0.044 0.000 0.000
#> GSM379823     3  0.1410     0.9456 0.060 0.000 0.940 0.000 0.000
#> GSM379824     3  0.1341     0.9423 0.056 0.000 0.944 0.000 0.000
#> GSM379749     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379750     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379751     2  0.0000     0.6009 0.000 1.000 0.000 0.000 0.000
#> GSM379744     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379745     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379746     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379747     2  0.0000     0.6009 0.000 1.000 0.000 0.000 0.000
#> GSM379748     2  0.0000     0.6009 0.000 1.000 0.000 0.000 0.000
#> GSM379757     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379758     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379752     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379753     2  0.0000     0.6009 0.000 1.000 0.000 0.000 0.000
#> GSM379754     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379755     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379756     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379764     2  0.0794     0.6177 0.000 0.972 0.000 0.000 0.028
#> GSM379765     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379766     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379759     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379760     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379761     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379762     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379763     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379769     2  0.0794     0.6177 0.000 0.972 0.000 0.000 0.028
#> GSM379770     2  0.0794     0.6177 0.000 0.972 0.000 0.000 0.028
#> GSM379767     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379768     2  0.4291     0.8073 0.000 0.536 0.000 0.000 0.464
#> GSM379776     1  0.4126     0.3265 0.620 0.000 0.000 0.380 0.000
#> GSM379777     3  0.4949     0.5563 0.056 0.000 0.656 0.288 0.000
#> GSM379778     2  0.0290     0.5938 0.000 0.992 0.000 0.000 0.008
#> GSM379771     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379772     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379773     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379774     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379775     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379784     3  0.1410     0.9456 0.060 0.000 0.940 0.000 0.000
#> GSM379785     1  0.0404     0.8704 0.988 0.000 0.012 0.000 0.000
#> GSM379786     3  0.1410     0.9456 0.060 0.000 0.940 0.000 0.000
#> GSM379779     1  0.3086     0.7035 0.816 0.000 0.004 0.180 0.000
#> GSM379780     1  0.0404     0.8704 0.988 0.000 0.012 0.000 0.000
#> GSM379781     1  0.0404     0.8704 0.988 0.000 0.012 0.000 0.000
#> GSM379782     2  0.0290     0.5938 0.000 0.992 0.000 0.000 0.008
#> GSM379783     3  0.1410     0.9456 0.060 0.000 0.940 0.000 0.000
#> GSM379792     1  0.4126     0.3265 0.620 0.000 0.000 0.380 0.000
#> GSM379793     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379794     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379787     2  0.0290     0.5938 0.000 0.992 0.000 0.000 0.008
#> GSM379788     3  0.1410     0.9456 0.060 0.000 0.940 0.000 0.000
#> GSM379789     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379790     1  0.4114     0.3367 0.624 0.000 0.000 0.376 0.000
#> GSM379791     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379797     4  0.1908     0.8085 0.092 0.000 0.000 0.908 0.000
#> GSM379798     1  0.3983     0.4241 0.660 0.000 0.000 0.340 0.000
#> GSM379795     1  0.0162     0.8759 0.996 0.000 0.004 0.000 0.000
#> GSM379796     1  0.4126     0.3265 0.620 0.000 0.000 0.380 0.000
#> GSM379721     1  0.0162     0.8749 0.996 0.000 0.004 0.000 0.000
#> GSM379722     1  0.0162     0.8749 0.996 0.000 0.004 0.000 0.000
#> GSM379723     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379716     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379717     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379718     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379719     1  0.0162     0.8749 0.996 0.000 0.004 0.000 0.000
#> GSM379720     1  0.0162     0.8749 0.996 0.000 0.004 0.000 0.000
#> GSM379729     3  0.2074     0.9362 0.104 0.000 0.896 0.000 0.000
#> GSM379730     3  0.2074     0.9362 0.104 0.000 0.896 0.000 0.000
#> GSM379731     3  0.2074     0.9362 0.104 0.000 0.896 0.000 0.000
#> GSM379724     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379725     3  0.2074     0.9362 0.104 0.000 0.896 0.000 0.000
#> GSM379726     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379727     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379728     1  0.3730     0.5267 0.712 0.000 0.000 0.288 0.000
#> GSM379737     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379738     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379739     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379732     3  0.2074     0.9362 0.104 0.000 0.896 0.000 0.000
#> GSM379733     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379734     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379735     3  0.2074     0.9362 0.104 0.000 0.896 0.000 0.000
#> GSM379736     1  0.4060     0.3725 0.640 0.000 0.000 0.360 0.000
#> GSM379742     2  0.0290     0.5938 0.000 0.992 0.000 0.000 0.008
#> GSM379743     3  0.2074     0.9362 0.104 0.000 0.896 0.000 0.000
#> GSM379740     1  0.0000     0.8758 1.000 0.000 0.000 0.000 0.000
#> GSM379741     2  0.0290     0.5938 0.000 0.992 0.000 0.000 0.008

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379833     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379834     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379827     5  0.3810      0.819 0.000 0.428 0.000 0.000 0.572 0.000
#> GSM379828     5  0.3810      0.819 0.000 0.428 0.000 0.000 0.572 0.000
#> GSM379829     6  0.1141      0.803 0.052 0.000 0.000 0.000 0.000 0.948
#> GSM379830     5  0.3937      0.817 0.000 0.424 0.000 0.000 0.572 0.004
#> GSM379831     5  0.3810      0.819 0.000 0.428 0.000 0.000 0.572 0.000
#> GSM379840     5  0.5658      0.716 0.000 0.416 0.000 0.000 0.432 0.152
#> GSM379841     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379842     5  0.3851      0.780 0.000 0.460 0.000 0.000 0.540 0.000
#> GSM379835     5  0.3810      0.819 0.000 0.428 0.000 0.000 0.572 0.000
#> GSM379836     5  0.5658      0.716 0.000 0.416 0.000 0.000 0.432 0.152
#> GSM379837     6  0.1141      0.864 0.000 0.000 0.000 0.000 0.052 0.948
#> GSM379838     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379839     6  0.1141      0.864 0.000 0.000 0.000 0.000 0.052 0.948
#> GSM379848     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379849     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379850     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379843     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379844     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379845     6  0.3534      0.674 0.000 0.008 0.000 0.000 0.276 0.716
#> GSM379846     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379847     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379853     5  0.3810      0.819 0.000 0.428 0.000 0.000 0.572 0.000
#> GSM379854     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379851     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379852     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379804     1  0.2848      0.755 0.828 0.000 0.004 0.160 0.008 0.000
#> GSM379805     1  0.4066      0.392 0.596 0.000 0.000 0.392 0.012 0.000
#> GSM379806     4  0.4116      0.162 0.416 0.000 0.000 0.572 0.012 0.000
#> GSM379799     4  0.0000      0.741 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379800     4  0.0000      0.741 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379801     4  0.1267      0.706 0.060 0.000 0.000 0.940 0.000 0.000
#> GSM379802     4  0.1765      0.703 0.000 0.000 0.000 0.904 0.096 0.000
#> GSM379803     4  0.3775      0.526 0.012 0.000 0.228 0.744 0.016 0.000
#> GSM379812     3  0.0790      0.928 0.032 0.000 0.968 0.000 0.000 0.000
#> GSM379813     1  0.1007      0.863 0.956 0.000 0.044 0.000 0.000 0.000
#> GSM379814     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379807     1  0.4169      0.201 0.532 0.000 0.000 0.456 0.012 0.000
#> GSM379808     4  0.4116      0.162 0.416 0.000 0.000 0.572 0.012 0.000
#> GSM379809     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379810     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379811     4  0.0820      0.742 0.012 0.000 0.000 0.972 0.016 0.000
#> GSM379820     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379821     3  0.0000      0.941 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379822     3  0.0000      0.941 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379815     1  0.0777      0.880 0.972 0.000 0.004 0.024 0.000 0.000
#> GSM379816     3  0.0146      0.944 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379817     1  0.1007      0.863 0.956 0.000 0.044 0.000 0.000 0.000
#> GSM379818     4  0.1765      0.703 0.000 0.000 0.000 0.904 0.096 0.000
#> GSM379819     1  0.4037      0.420 0.608 0.000 0.000 0.380 0.012 0.000
#> GSM379825     4  0.0146      0.741 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM379826     1  0.1007      0.863 0.956 0.000 0.044 0.000 0.000 0.000
#> GSM379823     3  0.0146      0.944 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379824     3  0.0000      0.941 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379749     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379750     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379751     5  0.3810      0.819 0.000 0.428 0.000 0.000 0.572 0.000
#> GSM379744     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379745     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379746     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379747     5  0.3810      0.819 0.000 0.428 0.000 0.000 0.572 0.000
#> GSM379748     5  0.3810      0.819 0.000 0.428 0.000 0.000 0.572 0.000
#> GSM379757     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379758     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379752     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379753     5  0.3810      0.819 0.000 0.428 0.000 0.000 0.572 0.000
#> GSM379754     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379755     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379756     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379764     5  0.3851      0.782 0.000 0.460 0.000 0.000 0.540 0.000
#> GSM379765     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379766     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379759     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379760     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379761     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379762     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379763     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379769     5  0.3851      0.782 0.000 0.460 0.000 0.000 0.540 0.000
#> GSM379770     5  0.3851      0.782 0.000 0.460 0.000 0.000 0.540 0.000
#> GSM379767     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379768     2  0.0000      1.000 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379776     1  0.4037      0.420 0.608 0.000 0.000 0.380 0.012 0.000
#> GSM379777     3  0.3528      0.545 0.000 0.000 0.700 0.296 0.004 0.000
#> GSM379778     5  0.3017      0.404 0.000 0.108 0.000 0.000 0.840 0.052
#> GSM379771     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379772     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379773     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379774     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379775     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379784     3  0.0146      0.944 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379785     1  0.0363      0.889 0.988 0.000 0.012 0.000 0.000 0.000
#> GSM379786     3  0.0146      0.944 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379779     1  0.2772      0.740 0.816 0.000 0.004 0.180 0.000 0.000
#> GSM379780     1  0.0363      0.889 0.988 0.000 0.012 0.000 0.000 0.000
#> GSM379781     1  0.0363      0.889 0.988 0.000 0.012 0.000 0.000 0.000
#> GSM379782     5  0.3017      0.404 0.000 0.108 0.000 0.000 0.840 0.052
#> GSM379783     3  0.0146      0.944 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379792     1  0.4037      0.420 0.608 0.000 0.000 0.380 0.012 0.000
#> GSM379793     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379794     1  0.0508      0.888 0.984 0.000 0.004 0.000 0.012 0.000
#> GSM379787     5  0.3017      0.404 0.000 0.108 0.000 0.000 0.840 0.052
#> GSM379788     3  0.0146      0.944 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379789     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379790     1  0.4026      0.428 0.612 0.000 0.000 0.376 0.012 0.000
#> GSM379791     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379797     4  0.1765      0.703 0.000 0.000 0.000 0.904 0.096 0.000
#> GSM379798     1  0.3912      0.497 0.648 0.000 0.000 0.340 0.012 0.000
#> GSM379795     1  0.0146      0.893 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379796     1  0.4037      0.420 0.608 0.000 0.000 0.380 0.012 0.000
#> GSM379721     1  0.0146      0.892 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379722     1  0.0146      0.892 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379723     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379716     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379717     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379718     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379719     1  0.0146      0.892 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379720     1  0.0146      0.892 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379729     3  0.1075      0.935 0.048 0.000 0.952 0.000 0.000 0.000
#> GSM379730     3  0.1075      0.935 0.048 0.000 0.952 0.000 0.000 0.000
#> GSM379731     3  0.1075      0.935 0.048 0.000 0.952 0.000 0.000 0.000
#> GSM379724     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379725     3  0.1075      0.935 0.048 0.000 0.952 0.000 0.000 0.000
#> GSM379726     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379727     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379728     1  0.3690      0.581 0.700 0.000 0.000 0.288 0.012 0.000
#> GSM379737     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379738     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379739     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379732     3  0.1075      0.935 0.048 0.000 0.952 0.000 0.000 0.000
#> GSM379733     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379734     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379735     3  0.1075      0.935 0.048 0.000 0.952 0.000 0.000 0.000
#> GSM379736     1  0.3992      0.450 0.624 0.000 0.000 0.364 0.012 0.000
#> GSM379742     5  0.3017      0.404 0.000 0.108 0.000 0.000 0.840 0.052
#> GSM379743     3  0.1075      0.935 0.048 0.000 0.952 0.000 0.000 0.000
#> GSM379740     1  0.0000      0.893 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379741     5  0.3017      0.404 0.000 0.108 0.000 0.000 0.840 0.052

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-ATC-hclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-ATC-hclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-ATC-hclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-ATC-hclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-ATC-hclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-ATC-hclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-ATC-hclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-ATC-hclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-ATC-hclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-ATC-hclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-ATC-hclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-ATC-hclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-ATC-hclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-ATC-hclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-ATC-hclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-ATC-hclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-ATC-hclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-ATC-hclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-ATC-hclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-ATC-hclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk ATC-hclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-ATC-hclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-ATC-hclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-ATC-hclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-ATC-hclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-ATC-hclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk ATC-hclust-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>              n individual(p) time(p) agent(p) k
#> ATC:hclust 139      5.46e-22   1.000   1.0000 2
#> ATC:hclust 125      1.76e-22   0.967   0.1681 3
#> ATC:hclust 127      4.72e-21   0.816   0.0380 4
#> ATC:hclust 128      2.69e-23   0.908   0.0759 5
#> ATC:hclust 123      4.30e-24   0.772   0.0573 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

ATC:kmeans**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["ATC", "kmeans"]
# you can also extract it by
# res = res_list["ATC:kmeans"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#>   Subgroups are detected by 'kmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk ATC-kmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk ATC-kmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.992       0.997         0.4839 0.515   0.515
#> 3 3 0.659           0.793       0.807         0.3034 0.800   0.629
#> 4 4 0.611           0.411       0.684         0.1255 0.808   0.546
#> 5 5 0.625           0.553       0.731         0.0696 0.926   0.760
#> 6 6 0.707           0.665       0.754         0.0501 0.940   0.774

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000      0.992 0.000 1.000
#> GSM379833     2  0.0000      0.992 0.000 1.000
#> GSM379834     2  0.0000      0.992 0.000 1.000
#> GSM379827     2  0.0000      0.992 0.000 1.000
#> GSM379828     2  0.0000      0.992 0.000 1.000
#> GSM379829     1  0.0000      1.000 1.000 0.000
#> GSM379830     2  0.0000      0.992 0.000 1.000
#> GSM379831     2  0.0000      0.992 0.000 1.000
#> GSM379840     2  0.9732      0.322 0.404 0.596
#> GSM379841     2  0.0000      0.992 0.000 1.000
#> GSM379842     2  0.0000      0.992 0.000 1.000
#> GSM379835     2  0.0000      0.992 0.000 1.000
#> GSM379836     2  0.0000      0.992 0.000 1.000
#> GSM379837     1  0.0000      1.000 1.000 0.000
#> GSM379838     2  0.0000      0.992 0.000 1.000
#> GSM379839     1  0.0000      1.000 1.000 0.000
#> GSM379848     2  0.0000      0.992 0.000 1.000
#> GSM379849     2  0.0000      0.992 0.000 1.000
#> GSM379850     2  0.0000      0.992 0.000 1.000
#> GSM379843     2  0.0000      0.992 0.000 1.000
#> GSM379844     2  0.0000      0.992 0.000 1.000
#> GSM379845     2  0.0000      0.992 0.000 1.000
#> GSM379846     2  0.0000      0.992 0.000 1.000
#> GSM379847     2  0.0000      0.992 0.000 1.000
#> GSM379853     2  0.0000      0.992 0.000 1.000
#> GSM379854     2  0.0000      0.992 0.000 1.000
#> GSM379851     2  0.0000      0.992 0.000 1.000
#> GSM379852     2  0.0000      0.992 0.000 1.000
#> GSM379804     1  0.0000      1.000 1.000 0.000
#> GSM379805     1  0.0000      1.000 1.000 0.000
#> GSM379806     1  0.0000      1.000 1.000 0.000
#> GSM379799     1  0.0000      1.000 1.000 0.000
#> GSM379800     1  0.0000      1.000 1.000 0.000
#> GSM379801     1  0.0000      1.000 1.000 0.000
#> GSM379802     1  0.0000      1.000 1.000 0.000
#> GSM379803     1  0.0000      1.000 1.000 0.000
#> GSM379812     1  0.0000      1.000 1.000 0.000
#> GSM379813     1  0.0000      1.000 1.000 0.000
#> GSM379814     1  0.0000      1.000 1.000 0.000
#> GSM379807     1  0.0000      1.000 1.000 0.000
#> GSM379808     1  0.0000      1.000 1.000 0.000
#> GSM379809     1  0.0000      1.000 1.000 0.000
#> GSM379810     1  0.0000      1.000 1.000 0.000
#> GSM379811     1  0.0000      1.000 1.000 0.000
#> GSM379820     1  0.0000      1.000 1.000 0.000
#> GSM379821     1  0.0000      1.000 1.000 0.000
#> GSM379822     1  0.0000      1.000 1.000 0.000
#> GSM379815     1  0.0000      1.000 1.000 0.000
#> GSM379816     1  0.0000      1.000 1.000 0.000
#> GSM379817     1  0.0000      1.000 1.000 0.000
#> GSM379818     1  0.0000      1.000 1.000 0.000
#> GSM379819     1  0.0000      1.000 1.000 0.000
#> GSM379825     1  0.0000      1.000 1.000 0.000
#> GSM379826     1  0.0000      1.000 1.000 0.000
#> GSM379823     1  0.0000      1.000 1.000 0.000
#> GSM379824     1  0.0000      1.000 1.000 0.000
#> GSM379749     2  0.0000      0.992 0.000 1.000
#> GSM379750     2  0.0000      0.992 0.000 1.000
#> GSM379751     2  0.0000      0.992 0.000 1.000
#> GSM379744     2  0.0000      0.992 0.000 1.000
#> GSM379745     2  0.0000      0.992 0.000 1.000
#> GSM379746     2  0.0000      0.992 0.000 1.000
#> GSM379747     2  0.0000      0.992 0.000 1.000
#> GSM379748     2  0.0000      0.992 0.000 1.000
#> GSM379757     2  0.0000      0.992 0.000 1.000
#> GSM379758     2  0.0000      0.992 0.000 1.000
#> GSM379752     2  0.0000      0.992 0.000 1.000
#> GSM379753     2  0.0000      0.992 0.000 1.000
#> GSM379754     2  0.0000      0.992 0.000 1.000
#> GSM379755     2  0.0000      0.992 0.000 1.000
#> GSM379756     2  0.0000      0.992 0.000 1.000
#> GSM379764     2  0.0000      0.992 0.000 1.000
#> GSM379765     2  0.0000      0.992 0.000 1.000
#> GSM379766     2  0.0000      0.992 0.000 1.000
#> GSM379759     2  0.0000      0.992 0.000 1.000
#> GSM379760     2  0.0000      0.992 0.000 1.000
#> GSM379761     2  0.0000      0.992 0.000 1.000
#> GSM379762     2  0.0000      0.992 0.000 1.000
#> GSM379763     2  0.0000      0.992 0.000 1.000
#> GSM379769     2  0.0000      0.992 0.000 1.000
#> GSM379770     2  0.0000      0.992 0.000 1.000
#> GSM379767     2  0.0000      0.992 0.000 1.000
#> GSM379768     2  0.0000      0.992 0.000 1.000
#> GSM379776     1  0.0000      1.000 1.000 0.000
#> GSM379777     1  0.0000      1.000 1.000 0.000
#> GSM379778     1  0.0000      1.000 1.000 0.000
#> GSM379771     1  0.0000      1.000 1.000 0.000
#> GSM379772     1  0.0000      1.000 1.000 0.000
#> GSM379773     1  0.0000      1.000 1.000 0.000
#> GSM379774     1  0.0000      1.000 1.000 0.000
#> GSM379775     1  0.0000      1.000 1.000 0.000
#> GSM379784     1  0.0000      1.000 1.000 0.000
#> GSM379785     1  0.0000      1.000 1.000 0.000
#> GSM379786     1  0.0000      1.000 1.000 0.000
#> GSM379779     1  0.0000      1.000 1.000 0.000
#> GSM379780     1  0.0000      1.000 1.000 0.000
#> GSM379781     1  0.0000      1.000 1.000 0.000
#> GSM379782     2  0.0000      0.992 0.000 1.000
#> GSM379783     1  0.0000      1.000 1.000 0.000
#> GSM379792     1  0.0000      1.000 1.000 0.000
#> GSM379793     1  0.0000      1.000 1.000 0.000
#> GSM379794     1  0.0000      1.000 1.000 0.000
#> GSM379787     2  0.0938      0.981 0.012 0.988
#> GSM379788     1  0.0000      1.000 1.000 0.000
#> GSM379789     1  0.0000      1.000 1.000 0.000
#> GSM379790     1  0.0000      1.000 1.000 0.000
#> GSM379791     1  0.0000      1.000 1.000 0.000
#> GSM379797     1  0.0000      1.000 1.000 0.000
#> GSM379798     1  0.0000      1.000 1.000 0.000
#> GSM379795     1  0.0000      1.000 1.000 0.000
#> GSM379796     1  0.0000      1.000 1.000 0.000
#> GSM379721     1  0.0000      1.000 1.000 0.000
#> GSM379722     1  0.0000      1.000 1.000 0.000
#> GSM379723     1  0.0000      1.000 1.000 0.000
#> GSM379716     1  0.0000      1.000 1.000 0.000
#> GSM379717     1  0.0000      1.000 1.000 0.000
#> GSM379718     1  0.0000      1.000 1.000 0.000
#> GSM379719     1  0.0000      1.000 1.000 0.000
#> GSM379720     1  0.0000      1.000 1.000 0.000
#> GSM379729     1  0.0000      1.000 1.000 0.000
#> GSM379730     1  0.0000      1.000 1.000 0.000
#> GSM379731     1  0.0000      1.000 1.000 0.000
#> GSM379724     1  0.0000      1.000 1.000 0.000
#> GSM379725     1  0.0000      1.000 1.000 0.000
#> GSM379726     1  0.0000      1.000 1.000 0.000
#> GSM379727     1  0.0000      1.000 1.000 0.000
#> GSM379728     1  0.0000      1.000 1.000 0.000
#> GSM379737     1  0.0000      1.000 1.000 0.000
#> GSM379738     1  0.0000      1.000 1.000 0.000
#> GSM379739     1  0.0000      1.000 1.000 0.000
#> GSM379732     1  0.0000      1.000 1.000 0.000
#> GSM379733     1  0.0000      1.000 1.000 0.000
#> GSM379734     1  0.0000      1.000 1.000 0.000
#> GSM379735     1  0.0000      1.000 1.000 0.000
#> GSM379736     1  0.0000      1.000 1.000 0.000
#> GSM379742     2  0.0000      0.992 0.000 1.000
#> GSM379743     1  0.0000      1.000 1.000 0.000
#> GSM379740     1  0.0000      1.000 1.000 0.000
#> GSM379741     2  0.0000      0.992 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379833     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379834     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379827     2  0.5327     0.8165 0.272 0.728 0.000
#> GSM379828     2  0.5327     0.8165 0.272 0.728 0.000
#> GSM379829     1  0.4178     0.8066 0.828 0.000 0.172
#> GSM379830     2  0.5397     0.8116 0.280 0.720 0.000
#> GSM379831     2  0.5327     0.8165 0.272 0.728 0.000
#> GSM379840     3  0.8958     0.3385 0.280 0.168 0.552
#> GSM379841     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379842     2  0.3686     0.8761 0.140 0.860 0.000
#> GSM379835     2  0.5327     0.8165 0.272 0.728 0.000
#> GSM379836     2  0.8727     0.6669 0.280 0.572 0.148
#> GSM379837     3  0.5397     0.5225 0.280 0.000 0.720
#> GSM379838     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379839     3  0.6260     0.3326 0.448 0.000 0.552
#> GSM379848     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379849     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379850     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379843     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379844     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379845     2  0.7277     0.7648 0.280 0.660 0.060
#> GSM379846     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379847     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379853     2  0.5397     0.8116 0.280 0.720 0.000
#> GSM379854     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379851     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379852     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379804     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379805     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379806     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379799     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379800     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379801     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379802     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379803     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379812     3  0.0000     0.7913 0.000 0.000 1.000
#> GSM379813     3  0.2066     0.7959 0.060 0.000 0.940
#> GSM379814     3  0.2066     0.7959 0.060 0.000 0.940
#> GSM379807     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379808     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379809     3  0.5988     0.1588 0.368 0.000 0.632
#> GSM379810     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379811     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379820     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379821     3  0.0000     0.7913 0.000 0.000 1.000
#> GSM379822     3  0.0000     0.7913 0.000 0.000 1.000
#> GSM379815     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379816     3  0.3619     0.6733 0.136 0.000 0.864
#> GSM379817     3  0.2066     0.7959 0.060 0.000 0.940
#> GSM379818     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379819     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379825     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379826     3  0.2165     0.7951 0.064 0.000 0.936
#> GSM379823     3  0.0424     0.7880 0.008 0.000 0.992
#> GSM379824     1  0.6111     0.7845 0.604 0.000 0.396
#> GSM379749     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379750     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379751     2  0.7188     0.7683 0.280 0.664 0.056
#> GSM379744     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379745     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379746     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379747     2  0.5397     0.8116 0.280 0.720 0.000
#> GSM379748     2  0.5291     0.8186 0.268 0.732 0.000
#> GSM379757     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379758     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379752     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379753     2  0.5397     0.8116 0.280 0.720 0.000
#> GSM379754     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379755     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379756     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379764     2  0.3619     0.8776 0.136 0.864 0.000
#> GSM379765     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379766     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379759     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379760     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379761     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379762     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379763     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379769     2  0.4121     0.8640 0.168 0.832 0.000
#> GSM379770     2  0.3879     0.8709 0.152 0.848 0.000
#> GSM379767     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379768     2  0.0000     0.9272 0.000 1.000 0.000
#> GSM379776     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379777     1  0.5859     0.8892 0.656 0.000 0.344
#> GSM379778     3  0.4555     0.6057 0.200 0.000 0.800
#> GSM379771     3  0.6168    -0.0500 0.412 0.000 0.588
#> GSM379772     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379773     3  0.0000     0.7913 0.000 0.000 1.000
#> GSM379774     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379775     3  0.5016     0.5572 0.240 0.000 0.760
#> GSM379784     3  0.0424     0.7880 0.008 0.000 0.992
#> GSM379785     3  0.0000     0.7913 0.000 0.000 1.000
#> GSM379786     3  0.2066     0.7478 0.060 0.000 0.940
#> GSM379779     3  0.2959     0.7789 0.100 0.000 0.900
#> GSM379780     3  0.2066     0.7959 0.060 0.000 0.940
#> GSM379781     3  0.0000     0.7913 0.000 0.000 1.000
#> GSM379782     3  0.7782     0.4705 0.208 0.124 0.668
#> GSM379783     3  0.2878     0.7136 0.096 0.000 0.904
#> GSM379792     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379793     3  0.2066     0.7959 0.060 0.000 0.940
#> GSM379794     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379787     3  0.6850     0.5278 0.208 0.072 0.720
#> GSM379788     3  0.0000     0.7913 0.000 0.000 1.000
#> GSM379789     3  0.2165     0.7951 0.064 0.000 0.936
#> GSM379790     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379791     3  0.2066     0.7959 0.060 0.000 0.940
#> GSM379797     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379798     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379795     3  0.2066     0.7959 0.060 0.000 0.940
#> GSM379796     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379721     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379722     3  0.2448     0.7925 0.076 0.000 0.924
#> GSM379723     3  0.6168    -0.0500 0.412 0.000 0.588
#> GSM379716     1  0.5560     0.9496 0.700 0.000 0.300
#> GSM379717     3  0.6180    -0.0703 0.416 0.000 0.584
#> GSM379718     3  0.6045     0.1000 0.380 0.000 0.620
#> GSM379719     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379720     3  0.6168    -0.0509 0.412 0.000 0.588
#> GSM379729     3  0.2066     0.7478 0.060 0.000 0.940
#> GSM379730     3  0.0424     0.7880 0.008 0.000 0.992
#> GSM379731     3  0.0000     0.7913 0.000 0.000 1.000
#> GSM379724     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379725     3  0.0424     0.7880 0.008 0.000 0.992
#> GSM379726     3  0.4796     0.5953 0.220 0.000 0.780
#> GSM379727     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379728     3  0.6180    -0.0703 0.416 0.000 0.584
#> GSM379737     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379738     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379739     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379732     3  0.0424     0.7880 0.008 0.000 0.992
#> GSM379733     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379734     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379735     3  0.0424     0.7880 0.008 0.000 0.992
#> GSM379736     1  0.5397     0.9795 0.720 0.000 0.280
#> GSM379742     2  0.8379     0.6858 0.208 0.624 0.168
#> GSM379743     3  0.0424     0.7880 0.008 0.000 0.992
#> GSM379740     3  0.2796     0.7865 0.092 0.000 0.908
#> GSM379741     3  0.9627    -0.0744 0.208 0.364 0.428

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.2011    0.91517 0.000 0.920 0.080 0.000
#> GSM379833     2  0.2011    0.91517 0.000 0.920 0.080 0.000
#> GSM379834     2  0.2011    0.91517 0.000 0.920 0.080 0.000
#> GSM379827     4  0.5151   -0.15389 0.000 0.464 0.004 0.532
#> GSM379828     4  0.5151   -0.15389 0.000 0.464 0.004 0.532
#> GSM379829     4  0.6170    0.22219 0.136 0.000 0.192 0.672
#> GSM379830     4  0.5383   -0.13173 0.000 0.452 0.012 0.536
#> GSM379831     4  0.5151   -0.15389 0.000 0.464 0.004 0.532
#> GSM379840     4  0.8226    0.04251 0.084 0.112 0.268 0.536
#> GSM379841     2  0.1716    0.91688 0.000 0.936 0.064 0.000
#> GSM379842     2  0.5559    0.64569 0.000 0.696 0.064 0.240
#> GSM379835     4  0.4981   -0.15195 0.000 0.464 0.000 0.536
#> GSM379836     4  0.6726   -0.00724 0.000 0.364 0.100 0.536
#> GSM379837     4  0.6898   -0.13001 0.116 0.000 0.360 0.524
#> GSM379838     2  0.1302    0.92079 0.000 0.956 0.044 0.000
#> GSM379839     4  0.6015   -0.01095 0.080 0.000 0.268 0.652
#> GSM379848     2  0.1474    0.91941 0.000 0.948 0.052 0.000
#> GSM379849     2  0.1716    0.91688 0.000 0.936 0.064 0.000
#> GSM379850     2  0.1716    0.91688 0.000 0.936 0.064 0.000
#> GSM379843     2  0.1716    0.91688 0.000 0.936 0.064 0.000
#> GSM379844     2  0.1716    0.91688 0.000 0.936 0.064 0.000
#> GSM379845     4  0.6688   -0.01239 0.000 0.368 0.096 0.536
#> GSM379846     2  0.1716    0.91688 0.000 0.936 0.064 0.000
#> GSM379847     2  0.1716    0.91688 0.000 0.936 0.064 0.000
#> GSM379853     4  0.5594   -0.16157 0.000 0.460 0.020 0.520
#> GSM379854     2  0.1474    0.91941 0.000 0.948 0.052 0.000
#> GSM379851     2  0.2048    0.91376 0.000 0.928 0.064 0.008
#> GSM379852     2  0.1716    0.91688 0.000 0.936 0.064 0.000
#> GSM379804     1  0.7883   -0.18407 0.364 0.000 0.352 0.284
#> GSM379805     4  0.7468    0.31313 0.184 0.000 0.352 0.464
#> GSM379806     4  0.7468    0.31313 0.184 0.000 0.352 0.464
#> GSM379799     4  0.7468    0.31313 0.184 0.000 0.352 0.464
#> GSM379800     4  0.7468    0.31313 0.184 0.000 0.352 0.464
#> GSM379801     4  0.7468    0.31313 0.184 0.000 0.352 0.464
#> GSM379802     4  0.7489    0.31074 0.184 0.000 0.364 0.452
#> GSM379803     4  0.7489    0.31074 0.184 0.000 0.364 0.452
#> GSM379812     1  0.4888   -0.10014 0.588 0.000 0.412 0.000
#> GSM379813     1  0.3569    0.38774 0.804 0.000 0.196 0.000
#> GSM379814     1  0.2281    0.50696 0.904 0.000 0.096 0.000
#> GSM379807     3  0.7919   -0.22007 0.324 0.000 0.352 0.324
#> GSM379808     4  0.7468    0.31313 0.184 0.000 0.352 0.464
#> GSM379809     1  0.3245    0.48311 0.872 0.000 0.100 0.028
#> GSM379810     1  0.0000    0.55096 1.000 0.000 0.000 0.000
#> GSM379811     4  0.7489    0.31074 0.184 0.000 0.364 0.452
#> GSM379820     1  0.1545    0.54022 0.952 0.000 0.040 0.008
#> GSM379821     1  0.4916   -0.11003 0.576 0.000 0.424 0.000
#> GSM379822     1  0.4916   -0.11003 0.576 0.000 0.424 0.000
#> GSM379815     1  0.6831    0.08273 0.536 0.000 0.352 0.112
#> GSM379816     1  0.5452   -0.15034 0.556 0.000 0.428 0.016
#> GSM379817     1  0.3569    0.38774 0.804 0.000 0.196 0.000
#> GSM379818     4  0.7489    0.31074 0.184 0.000 0.364 0.452
#> GSM379819     4  0.7827    0.21830 0.260 0.000 0.352 0.388
#> GSM379825     4  0.7468    0.31313 0.184 0.000 0.352 0.464
#> GSM379826     1  0.2973    0.46093 0.856 0.000 0.144 0.000
#> GSM379823     1  0.4907   -0.11422 0.580 0.000 0.420 0.000
#> GSM379824     3  0.6845    0.14997 0.308 0.000 0.564 0.128
#> GSM379749     2  0.0592    0.92253 0.000 0.984 0.016 0.000
#> GSM379750     2  0.0592    0.92253 0.000 0.984 0.016 0.000
#> GSM379751     4  0.6474   -0.03976 0.000 0.388 0.076 0.536
#> GSM379744     2  0.0592    0.92253 0.000 0.984 0.016 0.000
#> GSM379745     2  0.0592    0.92253 0.000 0.984 0.016 0.000
#> GSM379746     2  0.0592    0.92253 0.000 0.984 0.016 0.000
#> GSM379747     4  0.5590   -0.14649 0.000 0.456 0.020 0.524
#> GSM379748     4  0.5500   -0.16608 0.000 0.464 0.016 0.520
#> GSM379757     2  0.0336    0.92418 0.000 0.992 0.008 0.000
#> GSM379758     2  0.0000    0.92512 0.000 1.000 0.000 0.000
#> GSM379752     2  0.0592    0.92253 0.000 0.984 0.016 0.000
#> GSM379753     4  0.5388   -0.13970 0.000 0.456 0.012 0.532
#> GSM379754     2  0.0469    0.92354 0.000 0.988 0.012 0.000
#> GSM379755     2  0.0469    0.92354 0.000 0.988 0.012 0.000
#> GSM379756     2  0.0469    0.92354 0.000 0.988 0.012 0.000
#> GSM379764     2  0.4675    0.65330 0.000 0.736 0.020 0.244
#> GSM379765     2  0.0000    0.92512 0.000 1.000 0.000 0.000
#> GSM379766     2  0.0000    0.92512 0.000 1.000 0.000 0.000
#> GSM379759     2  0.0000    0.92512 0.000 1.000 0.000 0.000
#> GSM379760     2  0.0000    0.92512 0.000 1.000 0.000 0.000
#> GSM379761     2  0.0000    0.92512 0.000 1.000 0.000 0.000
#> GSM379762     2  0.0000    0.92512 0.000 1.000 0.000 0.000
#> GSM379763     2  0.0000    0.92512 0.000 1.000 0.000 0.000
#> GSM379769     2  0.4767    0.63656 0.000 0.724 0.020 0.256
#> GSM379770     2  0.4737    0.64120 0.000 0.728 0.020 0.252
#> GSM379767     2  0.0000    0.92512 0.000 1.000 0.000 0.000
#> GSM379768     2  0.0000    0.92512 0.000 1.000 0.000 0.000
#> GSM379776     3  0.7902   -0.25232 0.296 0.000 0.352 0.352
#> GSM379777     3  0.7188    0.17532 0.244 0.000 0.552 0.204
#> GSM379778     1  0.6937   -0.14285 0.508 0.000 0.376 0.116
#> GSM379771     1  0.4289    0.40155 0.796 0.000 0.172 0.032
#> GSM379772     1  0.0188    0.55061 0.996 0.000 0.004 0.000
#> GSM379773     1  0.3356    0.41425 0.824 0.000 0.176 0.000
#> GSM379774     1  0.0336    0.55001 0.992 0.000 0.008 0.000
#> GSM379775     1  0.2300    0.51947 0.920 0.000 0.064 0.016
#> GSM379784     1  0.4898   -0.09813 0.584 0.000 0.416 0.000
#> GSM379785     1  0.4277    0.21870 0.720 0.000 0.280 0.000
#> GSM379786     1  0.4916   -0.11246 0.576 0.000 0.424 0.000
#> GSM379779     1  0.0336    0.55001 0.992 0.000 0.008 0.000
#> GSM379780     1  0.2345    0.50657 0.900 0.000 0.100 0.000
#> GSM379781     1  0.3726    0.35696 0.788 0.000 0.212 0.000
#> GSM379782     3  0.9538    0.16949 0.292 0.112 0.332 0.264
#> GSM379783     1  0.5220   -0.12517 0.568 0.000 0.424 0.008
#> GSM379792     4  0.7613    0.28690 0.208 0.000 0.352 0.440
#> GSM379793     1  0.2345    0.50657 0.900 0.000 0.100 0.000
#> GSM379794     1  0.0336    0.55001 0.992 0.000 0.008 0.000
#> GSM379787     1  0.9419   -0.22502 0.324 0.096 0.316 0.264
#> GSM379788     1  0.4898   -0.09813 0.584 0.000 0.416 0.000
#> GSM379789     1  0.2345    0.50657 0.900 0.000 0.100 0.000
#> GSM379790     1  0.7674   -0.06681 0.428 0.000 0.352 0.220
#> GSM379791     1  0.2345    0.50657 0.900 0.000 0.100 0.000
#> GSM379797     4  0.7489    0.31074 0.184 0.000 0.364 0.452
#> GSM379798     1  0.7789   -0.12279 0.400 0.000 0.352 0.248
#> GSM379795     1  0.2345    0.50657 0.900 0.000 0.100 0.000
#> GSM379796     4  0.7468    0.31313 0.184 0.000 0.352 0.464
#> GSM379721     1  0.2281    0.54390 0.904 0.000 0.096 0.000
#> GSM379722     1  0.2345    0.54289 0.900 0.000 0.100 0.000
#> GSM379723     1  0.5085    0.38979 0.708 0.000 0.260 0.032
#> GSM379716     1  0.6052    0.19197 0.556 0.000 0.396 0.048
#> GSM379717     1  0.5085    0.38979 0.708 0.000 0.260 0.032
#> GSM379718     1  0.4137    0.46121 0.780 0.000 0.208 0.012
#> GSM379719     1  0.2281    0.54390 0.904 0.000 0.096 0.000
#> GSM379720     1  0.4319    0.44256 0.760 0.000 0.228 0.012
#> GSM379729     3  0.4999    0.21290 0.492 0.000 0.508 0.000
#> GSM379730     3  0.4999    0.21290 0.492 0.000 0.508 0.000
#> GSM379731     3  0.5000    0.19456 0.500 0.000 0.500 0.000
#> GSM379724     1  0.2281    0.54390 0.904 0.000 0.096 0.000
#> GSM379725     3  0.4998    0.21042 0.488 0.000 0.512 0.000
#> GSM379726     1  0.3196    0.51949 0.856 0.000 0.136 0.008
#> GSM379727     1  0.2281    0.54390 0.904 0.000 0.096 0.000
#> GSM379728     1  0.5085    0.38979 0.708 0.000 0.260 0.032
#> GSM379737     1  0.2281    0.54390 0.904 0.000 0.096 0.000
#> GSM379738     1  0.2281    0.54390 0.904 0.000 0.096 0.000
#> GSM379739     1  0.2345    0.54289 0.900 0.000 0.100 0.000
#> GSM379732     3  0.5000    0.19371 0.496 0.000 0.504 0.000
#> GSM379733     1  0.2281    0.54390 0.904 0.000 0.096 0.000
#> GSM379734     1  0.2281    0.54390 0.904 0.000 0.096 0.000
#> GSM379735     3  0.4999    0.21290 0.492 0.000 0.508 0.000
#> GSM379736     4  0.7468    0.31313 0.184 0.000 0.352 0.464
#> GSM379742     2  0.8774    0.13725 0.048 0.416 0.272 0.264
#> GSM379743     3  0.4999    0.21290 0.492 0.000 0.508 0.000
#> GSM379740     1  0.2281    0.54390 0.904 0.000 0.096 0.000
#> GSM379741     3  0.9707    0.11292 0.168 0.208 0.360 0.264

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     2  0.3818     0.8341 0.000 0.812 0.144 0.016 0.028
#> GSM379833     2  0.3775     0.8344 0.000 0.812 0.148 0.016 0.024
#> GSM379834     2  0.3775     0.8344 0.000 0.812 0.148 0.016 0.024
#> GSM379827     5  0.4880     0.6774 0.000 0.256 0.040 0.012 0.692
#> GSM379828     5  0.4880     0.6774 0.000 0.256 0.040 0.012 0.692
#> GSM379829     4  0.7515     0.1442 0.140 0.000 0.080 0.420 0.360
#> GSM379830     5  0.3395     0.7038 0.000 0.236 0.000 0.000 0.764
#> GSM379831     5  0.4394     0.6855 0.000 0.256 0.016 0.012 0.716
#> GSM379840     5  0.4538     0.6038 0.024 0.048 0.100 0.024 0.804
#> GSM379841     2  0.2625     0.8613 0.000 0.876 0.108 0.016 0.000
#> GSM379842     2  0.6249     0.2411 0.000 0.540 0.108 0.016 0.336
#> GSM379835     5  0.4190     0.6869 0.000 0.256 0.008 0.012 0.724
#> GSM379836     5  0.5213     0.7028 0.012 0.192 0.048 0.024 0.724
#> GSM379837     5  0.3631     0.5169 0.012 0.000 0.144 0.024 0.820
#> GSM379838     2  0.1544     0.8777 0.000 0.932 0.068 0.000 0.000
#> GSM379839     5  0.3907     0.5510 0.012 0.000 0.100 0.068 0.820
#> GSM379848     2  0.1671     0.8759 0.000 0.924 0.076 0.000 0.000
#> GSM379849     2  0.2068     0.8710 0.000 0.904 0.092 0.004 0.000
#> GSM379850     2  0.2233     0.8670 0.000 0.892 0.104 0.004 0.000
#> GSM379843     2  0.3122     0.8530 0.000 0.860 0.108 0.016 0.016
#> GSM379844     2  0.2573     0.8625 0.000 0.880 0.104 0.016 0.000
#> GSM379845     5  0.5091     0.7004 0.000 0.208 0.056 0.024 0.712
#> GSM379846     2  0.3019     0.8553 0.000 0.864 0.108 0.016 0.012
#> GSM379847     2  0.2233     0.8670 0.000 0.892 0.104 0.004 0.000
#> GSM379853     5  0.4506     0.6872 0.000 0.244 0.036 0.004 0.716
#> GSM379854     2  0.1732     0.8752 0.000 0.920 0.080 0.000 0.000
#> GSM379851     2  0.3709     0.8340 0.000 0.832 0.108 0.016 0.044
#> GSM379852     2  0.3019     0.8553 0.000 0.864 0.108 0.016 0.012
#> GSM379804     4  0.4909     0.3104 0.472 0.000 0.012 0.508 0.008
#> GSM379805     4  0.1924     0.8479 0.064 0.000 0.008 0.924 0.004
#> GSM379806     4  0.1638     0.8505 0.064 0.000 0.000 0.932 0.004
#> GSM379799     4  0.1764     0.8503 0.064 0.000 0.000 0.928 0.008
#> GSM379800     4  0.1764     0.8503 0.064 0.000 0.000 0.928 0.008
#> GSM379801     4  0.1764     0.8503 0.064 0.000 0.000 0.928 0.008
#> GSM379802     4  0.2141     0.8475 0.064 0.000 0.004 0.916 0.016
#> GSM379803     4  0.2275     0.8471 0.064 0.000 0.012 0.912 0.012
#> GSM379812     1  0.6161    -0.6495 0.444 0.000 0.424 0.000 0.132
#> GSM379813     1  0.3241     0.3507 0.832 0.000 0.144 0.000 0.024
#> GSM379814     1  0.1408     0.5078 0.948 0.000 0.044 0.000 0.008
#> GSM379807     4  0.4817     0.5432 0.368 0.000 0.016 0.608 0.008
#> GSM379808     4  0.1638     0.8505 0.064 0.000 0.000 0.932 0.004
#> GSM379809     1  0.2753     0.5486 0.876 0.000 0.012 0.104 0.008
#> GSM379810     1  0.1443     0.5578 0.948 0.000 0.004 0.044 0.004
#> GSM379811     4  0.2037     0.8485 0.064 0.000 0.004 0.920 0.012
#> GSM379820     1  0.2625     0.5439 0.900 0.000 0.040 0.048 0.012
#> GSM379821     1  0.6191    -0.6535 0.436 0.000 0.428 0.000 0.136
#> GSM379822     1  0.6220    -0.6600 0.432 0.000 0.428 0.000 0.140
#> GSM379815     1  0.4453     0.1805 0.660 0.000 0.008 0.324 0.008
#> GSM379816     3  0.6440     0.6696 0.412 0.000 0.412 0.000 0.176
#> GSM379817     1  0.3241     0.3507 0.832 0.000 0.144 0.000 0.024
#> GSM379818     4  0.2141     0.8475 0.064 0.000 0.004 0.916 0.016
#> GSM379819     4  0.4433     0.6741 0.280 0.000 0.016 0.696 0.008
#> GSM379825     4  0.1764     0.8503 0.064 0.000 0.000 0.928 0.008
#> GSM379826     1  0.2482     0.4534 0.892 0.000 0.084 0.000 0.024
#> GSM379823     1  0.6299    -0.6788 0.432 0.000 0.416 0.000 0.152
#> GSM379824     4  0.8292    -0.2243 0.276 0.000 0.276 0.324 0.124
#> GSM379749     2  0.1695     0.8683 0.000 0.940 0.044 0.008 0.008
#> GSM379750     2  0.1695     0.8683 0.000 0.940 0.044 0.008 0.008
#> GSM379751     5  0.3690     0.7084 0.000 0.224 0.012 0.000 0.764
#> GSM379744     2  0.1695     0.8683 0.000 0.940 0.044 0.008 0.008
#> GSM379745     2  0.1618     0.8687 0.000 0.944 0.040 0.008 0.008
#> GSM379746     2  0.1412     0.8723 0.000 0.952 0.036 0.008 0.004
#> GSM379747     5  0.4352     0.6954 0.000 0.244 0.036 0.000 0.720
#> GSM379748     5  0.5137     0.6710 0.000 0.256 0.044 0.020 0.680
#> GSM379757     2  0.0000     0.8852 0.000 1.000 0.000 0.000 0.000
#> GSM379758     2  0.0000     0.8852 0.000 1.000 0.000 0.000 0.000
#> GSM379752     2  0.1618     0.8687 0.000 0.944 0.040 0.008 0.008
#> GSM379753     5  0.4276     0.6962 0.000 0.244 0.032 0.000 0.724
#> GSM379754     2  0.0324     0.8837 0.000 0.992 0.004 0.004 0.000
#> GSM379755     2  0.0324     0.8837 0.000 0.992 0.004 0.004 0.000
#> GSM379756     2  0.0324     0.8837 0.000 0.992 0.004 0.004 0.000
#> GSM379764     2  0.4774     0.2525 0.000 0.612 0.028 0.000 0.360
#> GSM379765     2  0.0000     0.8852 0.000 1.000 0.000 0.000 0.000
#> GSM379766     2  0.0000     0.8852 0.000 1.000 0.000 0.000 0.000
#> GSM379759     2  0.0000     0.8852 0.000 1.000 0.000 0.000 0.000
#> GSM379760     2  0.0000     0.8852 0.000 1.000 0.000 0.000 0.000
#> GSM379761     2  0.0000     0.8852 0.000 1.000 0.000 0.000 0.000
#> GSM379762     2  0.0000     0.8852 0.000 1.000 0.000 0.000 0.000
#> GSM379763     2  0.0000     0.8852 0.000 1.000 0.000 0.000 0.000
#> GSM379769     2  0.4846     0.1701 0.000 0.588 0.028 0.000 0.384
#> GSM379770     2  0.5203     0.2292 0.000 0.600 0.032 0.012 0.356
#> GSM379767     2  0.0000     0.8852 0.000 1.000 0.000 0.000 0.000
#> GSM379768     2  0.0000     0.8852 0.000 1.000 0.000 0.000 0.000
#> GSM379776     4  0.4419     0.6008 0.344 0.000 0.008 0.644 0.004
#> GSM379777     3  0.8245     0.2739 0.236 0.000 0.344 0.296 0.124
#> GSM379778     5  0.7323    -0.3284 0.344 0.000 0.272 0.024 0.360
#> GSM379771     1  0.2280     0.5396 0.880 0.000 0.000 0.120 0.000
#> GSM379772     1  0.1121     0.5575 0.956 0.000 0.000 0.044 0.000
#> GSM379773     1  0.3961     0.3369 0.812 0.000 0.108 0.008 0.072
#> GSM379774     1  0.1282     0.5569 0.952 0.000 0.000 0.044 0.004
#> GSM379775     1  0.1732     0.5546 0.920 0.000 0.000 0.080 0.000
#> GSM379784     1  0.6239    -0.6558 0.452 0.000 0.404 0.000 0.144
#> GSM379785     1  0.4066    -0.1974 0.672 0.000 0.324 0.000 0.004
#> GSM379786     1  0.6394    -0.6921 0.428 0.000 0.404 0.000 0.168
#> GSM379779     1  0.1197     0.5577 0.952 0.000 0.000 0.048 0.000
#> GSM379780     1  0.1124     0.5093 0.960 0.000 0.036 0.000 0.004
#> GSM379781     1  0.3521     0.1217 0.764 0.000 0.232 0.000 0.004
#> GSM379782     5  0.7742     0.1216 0.244 0.032 0.244 0.024 0.456
#> GSM379783     1  0.6439    -0.7072 0.416 0.000 0.408 0.000 0.176
#> GSM379792     4  0.3910     0.7155 0.248 0.000 0.008 0.740 0.004
#> GSM379793     1  0.1041     0.5131 0.964 0.000 0.032 0.000 0.004
#> GSM379794     1  0.1443     0.5556 0.948 0.000 0.004 0.044 0.004
#> GSM379787     5  0.7632     0.1067 0.276 0.024 0.224 0.024 0.452
#> GSM379788     1  0.6239    -0.6558 0.452 0.000 0.404 0.000 0.144
#> GSM379789     1  0.1202     0.5137 0.960 0.000 0.032 0.004 0.004
#> GSM379790     1  0.4613    -0.0903 0.580 0.000 0.008 0.408 0.004
#> GSM379791     1  0.1041     0.5131 0.964 0.000 0.032 0.000 0.004
#> GSM379797     4  0.2037     0.8485 0.064 0.000 0.004 0.920 0.012
#> GSM379798     1  0.4680    -0.2092 0.540 0.000 0.008 0.448 0.004
#> GSM379795     1  0.1041     0.5131 0.964 0.000 0.032 0.000 0.004
#> GSM379796     4  0.1924     0.8479 0.064 0.000 0.008 0.924 0.004
#> GSM379721     1  0.4713     0.5298 0.676 0.000 0.280 0.044 0.000
#> GSM379722     1  0.4735     0.5264 0.672 0.000 0.284 0.044 0.000
#> GSM379723     1  0.5659     0.5074 0.604 0.000 0.280 0.116 0.000
#> GSM379716     1  0.6438     0.3988 0.500 0.000 0.280 0.220 0.000
#> GSM379717     1  0.5659     0.5074 0.604 0.000 0.280 0.116 0.000
#> GSM379718     1  0.5441     0.5161 0.624 0.000 0.280 0.096 0.000
#> GSM379719     1  0.4713     0.5298 0.676 0.000 0.280 0.044 0.000
#> GSM379720     1  0.5532     0.5131 0.616 0.000 0.280 0.104 0.000
#> GSM379729     3  0.6206     0.8653 0.296 0.000 0.532 0.000 0.172
#> GSM379730     3  0.6206     0.8653 0.296 0.000 0.532 0.000 0.172
#> GSM379731     3  0.6039     0.8398 0.300 0.000 0.552 0.000 0.148
#> GSM379724     1  0.4713     0.5298 0.676 0.000 0.280 0.044 0.000
#> GSM379725     3  0.6206     0.8653 0.296 0.000 0.532 0.000 0.172
#> GSM379726     1  0.4967     0.5273 0.660 0.000 0.280 0.060 0.000
#> GSM379727     1  0.4713     0.5298 0.676 0.000 0.280 0.044 0.000
#> GSM379728     1  0.5659     0.5074 0.604 0.000 0.280 0.116 0.000
#> GSM379737     1  0.4713     0.5298 0.676 0.000 0.280 0.044 0.000
#> GSM379738     1  0.4713     0.5298 0.676 0.000 0.280 0.044 0.000
#> GSM379739     1  0.4713     0.5298 0.676 0.000 0.280 0.044 0.000
#> GSM379732     3  0.6024     0.8438 0.296 0.000 0.556 0.000 0.148
#> GSM379733     1  0.4713     0.5298 0.676 0.000 0.280 0.044 0.000
#> GSM379734     1  0.4713     0.5298 0.676 0.000 0.280 0.044 0.000
#> GSM379735     3  0.6206     0.8653 0.296 0.000 0.532 0.000 0.172
#> GSM379736     4  0.1478     0.8500 0.064 0.000 0.000 0.936 0.000
#> GSM379742     5  0.7776     0.4226 0.048 0.204 0.280 0.016 0.452
#> GSM379743     3  0.6206     0.8653 0.296 0.000 0.532 0.000 0.172
#> GSM379740     1  0.4780     0.5290 0.672 0.000 0.280 0.048 0.000
#> GSM379741     5  0.7868     0.2880 0.100 0.116 0.308 0.016 0.460

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5 p6
#> GSM379832     2  0.4303     0.7617 0.020 0.672 0.000 0.000 0.016 NA
#> GSM379833     2  0.4303     0.7617 0.020 0.672 0.000 0.000 0.016 NA
#> GSM379834     2  0.4303     0.7617 0.020 0.672 0.000 0.000 0.016 NA
#> GSM379827     5  0.3087     0.7847 0.028 0.092 0.000 0.004 0.856 NA
#> GSM379828     5  0.3009     0.7858 0.024 0.092 0.000 0.004 0.860 NA
#> GSM379829     5  0.7588     0.1567 0.068 0.000 0.096 0.336 0.408 NA
#> GSM379830     5  0.1714     0.7905 0.000 0.092 0.000 0.000 0.908 NA
#> GSM379831     5  0.2487     0.7864 0.000 0.092 0.000 0.000 0.876 NA
#> GSM379840     5  0.4384     0.7441 0.108 0.036 0.004 0.020 0.788 NA
#> GSM379841     2  0.3360     0.7783 0.004 0.732 0.000 0.000 0.000 NA
#> GSM379842     2  0.6205     0.1315 0.004 0.368 0.000 0.000 0.356 NA
#> GSM379835     5  0.2163     0.7895 0.000 0.092 0.000 0.000 0.892 NA
#> GSM379836     5  0.3946     0.7785 0.056 0.088 0.000 0.004 0.808 NA
#> GSM379837     5  0.4075     0.7125 0.128 0.000 0.004 0.036 0.788 NA
#> GSM379838     2  0.2743     0.8068 0.008 0.828 0.000 0.000 0.000 NA
#> GSM379839     5  0.4146     0.7151 0.116 0.000 0.004 0.048 0.788 NA
#> GSM379848     2  0.2848     0.8044 0.008 0.816 0.000 0.000 0.000 NA
#> GSM379849     2  0.3245     0.7908 0.008 0.764 0.000 0.000 0.000 NA
#> GSM379850     2  0.3314     0.7815 0.004 0.740 0.000 0.000 0.000 NA
#> GSM379843     2  0.3543     0.7724 0.004 0.720 0.000 0.000 0.004 NA
#> GSM379844     2  0.3360     0.7783 0.004 0.732 0.000 0.000 0.000 NA
#> GSM379845     5  0.4420     0.7740 0.072 0.088 0.000 0.020 0.784 NA
#> GSM379846     2  0.3543     0.7724 0.004 0.720 0.000 0.000 0.004 NA
#> GSM379847     2  0.3360     0.7783 0.004 0.732 0.000 0.000 0.000 NA
#> GSM379853     5  0.2913     0.7838 0.012 0.092 0.000 0.000 0.860 NA
#> GSM379854     2  0.2848     0.8044 0.008 0.816 0.000 0.000 0.000 NA
#> GSM379851     2  0.4505     0.7354 0.004 0.668 0.000 0.000 0.056 NA
#> GSM379852     2  0.3543     0.7724 0.004 0.720 0.000 0.000 0.004 NA
#> GSM379804     3  0.5701    -0.0123 0.020 0.000 0.532 0.372 0.020 NA
#> GSM379805     4  0.2325     0.8710 0.000 0.000 0.048 0.900 0.008 NA
#> GSM379806     4  0.1364     0.8797 0.000 0.000 0.048 0.944 0.004 NA
#> GSM379799     4  0.1364     0.8797 0.000 0.000 0.048 0.944 0.004 NA
#> GSM379800     4  0.1364     0.8797 0.000 0.000 0.048 0.944 0.004 NA
#> GSM379801     4  0.1477     0.8794 0.000 0.000 0.048 0.940 0.004 NA
#> GSM379802     4  0.2143     0.8746 0.008 0.000 0.048 0.916 0.012 NA
#> GSM379803     4  0.2847     0.8689 0.012 0.000 0.048 0.880 0.012 NA
#> GSM379812     1  0.3905     0.8080 0.712 0.000 0.264 0.000 0.012 NA
#> GSM379813     3  0.3892     0.4015 0.208 0.000 0.752 0.000 0.020 NA
#> GSM379814     3  0.2784     0.5714 0.092 0.000 0.868 0.000 0.020 NA
#> GSM379807     4  0.5697     0.3530 0.016 0.000 0.424 0.484 0.020 NA
#> GSM379808     4  0.1364     0.8797 0.000 0.000 0.048 0.944 0.004 NA
#> GSM379809     3  0.2870     0.6202 0.024 0.000 0.884 0.044 0.020 NA
#> GSM379810     3  0.1718     0.6223 0.024 0.000 0.936 0.000 0.020 NA
#> GSM379811     4  0.2143     0.8746 0.008 0.000 0.048 0.916 0.012 NA
#> GSM379820     3  0.2725     0.5988 0.060 0.000 0.884 0.004 0.020 NA
#> GSM379821     1  0.4047     0.8121 0.720 0.000 0.244 0.000 0.016 NA
#> GSM379822     1  0.3998     0.8175 0.728 0.000 0.236 0.000 0.016 NA
#> GSM379815     3  0.4647     0.4787 0.020 0.000 0.740 0.168 0.020 NA
#> GSM379816     1  0.3394     0.8286 0.752 0.000 0.236 0.000 0.000 NA
#> GSM379817     3  0.3892     0.4015 0.208 0.000 0.752 0.000 0.020 NA
#> GSM379818     4  0.2143     0.8746 0.008 0.000 0.048 0.916 0.012 NA
#> GSM379819     4  0.5403     0.5894 0.016 0.000 0.312 0.600 0.020 NA
#> GSM379825     4  0.1075     0.8794 0.000 0.000 0.048 0.952 0.000 NA
#> GSM379826     3  0.3438     0.5107 0.144 0.000 0.812 0.000 0.020 NA
#> GSM379823     1  0.3692     0.8212 0.736 0.000 0.244 0.000 0.008 NA
#> GSM379824     1  0.6277     0.5753 0.596 0.000 0.152 0.188 0.020 NA
#> GSM379749     2  0.2034     0.8123 0.044 0.920 0.000 0.004 0.008 NA
#> GSM379750     2  0.2034     0.8123 0.044 0.920 0.000 0.004 0.008 NA
#> GSM379751     5  0.2113     0.7911 0.004 0.092 0.000 0.000 0.896 NA
#> GSM379744     2  0.2034     0.8123 0.044 0.920 0.000 0.004 0.008 NA
#> GSM379745     2  0.2034     0.8123 0.044 0.920 0.000 0.004 0.008 NA
#> GSM379746     2  0.1921     0.8138 0.044 0.924 0.000 0.004 0.004 NA
#> GSM379747     5  0.2983     0.7847 0.032 0.092 0.000 0.004 0.860 NA
#> GSM379748     5  0.3674     0.7733 0.044 0.092 0.000 0.004 0.824 NA
#> GSM379757     2  0.0405     0.8249 0.004 0.988 0.000 0.000 0.000 NA
#> GSM379758     2  0.0000     0.8264 0.000 1.000 0.000 0.000 0.000 NA
#> GSM379752     2  0.2034     0.8123 0.044 0.920 0.000 0.004 0.008 NA
#> GSM379753     5  0.2808     0.7870 0.028 0.092 0.000 0.004 0.868 NA
#> GSM379754     2  0.1003     0.8223 0.020 0.964 0.000 0.000 0.000 NA
#> GSM379755     2  0.1003     0.8223 0.020 0.964 0.000 0.000 0.000 NA
#> GSM379756     2  0.1088     0.8228 0.024 0.960 0.000 0.000 0.000 NA
#> GSM379764     2  0.4654     0.1450 0.000 0.544 0.000 0.000 0.412 NA
#> GSM379765     2  0.0146     0.8263 0.004 0.996 0.000 0.000 0.000 NA
#> GSM379766     2  0.0146     0.8263 0.004 0.996 0.000 0.000 0.000 NA
#> GSM379759     2  0.0291     0.8261 0.004 0.992 0.000 0.000 0.000 NA
#> GSM379760     2  0.0291     0.8261 0.004 0.992 0.000 0.000 0.000 NA
#> GSM379761     2  0.0291     0.8261 0.004 0.992 0.000 0.000 0.000 NA
#> GSM379762     2  0.0000     0.8264 0.000 1.000 0.000 0.000 0.000 NA
#> GSM379763     2  0.0146     0.8263 0.004 0.996 0.000 0.000 0.000 NA
#> GSM379769     2  0.4689     0.0498 0.000 0.516 0.000 0.000 0.440 NA
#> GSM379770     2  0.4833     0.0634 0.000 0.516 0.000 0.000 0.428 NA
#> GSM379767     2  0.0000     0.8264 0.000 1.000 0.000 0.000 0.000 NA
#> GSM379768     2  0.0146     0.8263 0.004 0.996 0.000 0.000 0.000 NA
#> GSM379776     4  0.4701     0.5040 0.000 0.000 0.396 0.560 0.004 NA
#> GSM379777     1  0.6109     0.6276 0.620 0.000 0.148 0.168 0.020 NA
#> GSM379778     1  0.8102     0.0142 0.280 0.000 0.252 0.020 0.236 NA
#> GSM379771     3  0.2009     0.6075 0.000 0.000 0.908 0.068 0.000 NA
#> GSM379772     3  0.0146     0.6251 0.000 0.000 0.996 0.000 0.000 NA
#> GSM379773     3  0.3376     0.4999 0.120 0.000 0.832 0.016 0.012 NA
#> GSM379774     3  0.0260     0.6213 0.008 0.000 0.992 0.000 0.000 NA
#> GSM379775     3  0.1088     0.6238 0.000 0.000 0.960 0.024 0.000 NA
#> GSM379784     1  0.3288     0.8197 0.724 0.000 0.276 0.000 0.000 NA
#> GSM379785     3  0.3482     0.0425 0.316 0.000 0.684 0.000 0.000 NA
#> GSM379786     1  0.3244     0.8226 0.732 0.000 0.268 0.000 0.000 NA
#> GSM379779     3  0.0405     0.6218 0.008 0.000 0.988 0.000 0.000 NA
#> GSM379780     3  0.1531     0.5824 0.068 0.000 0.928 0.000 0.000 NA
#> GSM379781     3  0.2969     0.3254 0.224 0.000 0.776 0.000 0.000 NA
#> GSM379782     5  0.7968     0.1788 0.240 0.000 0.168 0.020 0.336 NA
#> GSM379783     1  0.3468     0.8234 0.728 0.000 0.264 0.000 0.000 NA
#> GSM379792     4  0.4513     0.6148 0.000 0.000 0.328 0.628 0.004 NA
#> GSM379793     3  0.1531     0.5824 0.068 0.000 0.928 0.000 0.000 NA
#> GSM379794     3  0.0405     0.6212 0.008 0.000 0.988 0.000 0.000 NA
#> GSM379787     5  0.7998     0.1823 0.224 0.000 0.188 0.020 0.336 NA
#> GSM379788     1  0.3309     0.8173 0.720 0.000 0.280 0.000 0.000 NA
#> GSM379789     3  0.1387     0.5823 0.068 0.000 0.932 0.000 0.000 NA
#> GSM379790     3  0.4088     0.3382 0.000 0.000 0.716 0.240 0.004 NA
#> GSM379791     3  0.1531     0.5824 0.068 0.000 0.928 0.000 0.000 NA
#> GSM379797     4  0.2143     0.8746 0.008 0.000 0.048 0.916 0.012 NA
#> GSM379798     3  0.4268     0.2682 0.000 0.000 0.684 0.272 0.004 NA
#> GSM379795     3  0.1471     0.5856 0.064 0.000 0.932 0.000 0.000 NA
#> GSM379796     4  0.2519     0.8699 0.000 0.000 0.056 0.888 0.008 NA
#> GSM379721     3  0.4491     0.5883 0.036 0.000 0.576 0.000 0.000 NA
#> GSM379722     3  0.4491     0.5883 0.036 0.000 0.576 0.000 0.000 NA
#> GSM379723     3  0.5596     0.5702 0.028 0.000 0.500 0.072 0.000 NA
#> GSM379716     3  0.5999     0.5461 0.028 0.000 0.464 0.100 0.004 NA
#> GSM379717     3  0.5726     0.5683 0.028 0.000 0.496 0.072 0.004 NA
#> GSM379718     3  0.5497     0.5749 0.028 0.000 0.512 0.052 0.004 NA
#> GSM379719     3  0.4491     0.5883 0.036 0.000 0.576 0.000 0.000 NA
#> GSM379720     3  0.5547     0.5736 0.028 0.000 0.508 0.056 0.004 NA
#> GSM379729     1  0.4364     0.8062 0.732 0.000 0.152 0.000 0.004 NA
#> GSM379730     1  0.4322     0.8076 0.736 0.000 0.152 0.000 0.004 NA
#> GSM379731     1  0.4107     0.8058 0.756 0.000 0.148 0.000 0.004 NA
#> GSM379724     3  0.4482     0.5908 0.036 0.000 0.580 0.000 0.000 NA
#> GSM379725     1  0.4371     0.8030 0.732 0.000 0.148 0.000 0.004 NA
#> GSM379726     3  0.5141     0.5814 0.032 0.000 0.536 0.032 0.000 NA
#> GSM379727     3  0.4491     0.5883 0.036 0.000 0.576 0.000 0.000 NA
#> GSM379728     3  0.5601     0.5688 0.028 0.000 0.496 0.072 0.000 NA
#> GSM379737     3  0.4482     0.5908 0.036 0.000 0.580 0.000 0.000 NA
#> GSM379738     3  0.4482     0.5908 0.036 0.000 0.580 0.000 0.000 NA
#> GSM379739     3  0.4482     0.5908 0.036 0.000 0.580 0.000 0.000 NA
#> GSM379732     1  0.4313     0.7987 0.728 0.000 0.148 0.000 0.000 NA
#> GSM379733     3  0.4482     0.5908 0.036 0.000 0.580 0.000 0.000 NA
#> GSM379734     3  0.4482     0.5908 0.036 0.000 0.580 0.000 0.000 NA
#> GSM379735     1  0.4364     0.8062 0.732 0.000 0.152 0.000 0.004 NA
#> GSM379736     4  0.2000     0.8749 0.000 0.000 0.048 0.916 0.004 NA
#> GSM379742     5  0.8251     0.3250 0.232 0.132 0.020 0.020 0.340 NA
#> GSM379743     1  0.4364     0.8062 0.732 0.000 0.152 0.000 0.004 NA
#> GSM379740     3  0.4409     0.5932 0.032 0.000 0.588 0.000 0.000 NA
#> GSM379741     5  0.8175     0.2456 0.264 0.056 0.052 0.020 0.340 NA

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-ATC-kmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-ATC-kmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-ATC-kmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-ATC-kmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-ATC-kmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-ATC-kmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-ATC-kmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-ATC-kmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-ATC-kmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-ATC-kmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-ATC-kmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-ATC-kmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-ATC-kmeans-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-ATC-kmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-ATC-kmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-ATC-kmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-ATC-kmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-ATC-kmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-ATC-kmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-ATC-kmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk ATC-kmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-ATC-kmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-ATC-kmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-ATC-kmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-ATC-kmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-ATC-kmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk ATC-kmeans-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>              n individual(p) time(p) agent(p) k
#> ATC:kmeans 138      3.69e-23   1.000   0.8655 2
#> ATC:kmeans 128      3.37e-26   0.946   0.0190 3
#> ATC:kmeans  64      4.18e-13   0.828   0.9845 4
#> ATC:kmeans 108      2.25e-27   0.909   0.0911 5
#> ATC:kmeans 119      1.52e-25   0.869   0.0300 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

ATC:skmeans**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["ATC", "skmeans"]
# you can also extract it by
# res = res_list["ATC:skmeans"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#>   Subgroups are detected by 'skmeans' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 3.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk ATC-skmeans-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk ATC-skmeans-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.978       0.992         0.4910 0.510   0.510
#> 3 3 1.000           0.948       0.973         0.2676 0.869   0.742
#> 4 4 0.780           0.864       0.885         0.1047 0.907   0.758
#> 5 5 0.775           0.825       0.895         0.0762 0.959   0.865
#> 6 6 0.876           0.761       0.844         0.0541 0.932   0.754

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 3
#> attr(,"optional")
#> [1] 2

There is also optional best \(k\) = 2 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000     0.9925 0.000 1.000
#> GSM379833     2  0.0000     0.9925 0.000 1.000
#> GSM379834     2  0.0000     0.9925 0.000 1.000
#> GSM379827     2  0.0000     0.9925 0.000 1.000
#> GSM379828     2  0.0000     0.9925 0.000 1.000
#> GSM379829     1  0.0000     0.9911 1.000 0.000
#> GSM379830     2  0.0000     0.9925 0.000 1.000
#> GSM379831     2  0.0000     0.9925 0.000 1.000
#> GSM379840     2  0.0000     0.9925 0.000 1.000
#> GSM379841     2  0.0000     0.9925 0.000 1.000
#> GSM379842     2  0.0000     0.9925 0.000 1.000
#> GSM379835     2  0.0000     0.9925 0.000 1.000
#> GSM379836     2  0.0000     0.9925 0.000 1.000
#> GSM379837     2  0.9833     0.2558 0.424 0.576
#> GSM379838     2  0.0000     0.9925 0.000 1.000
#> GSM379839     2  0.0000     0.9925 0.000 1.000
#> GSM379848     2  0.0000     0.9925 0.000 1.000
#> GSM379849     2  0.0000     0.9925 0.000 1.000
#> GSM379850     2  0.0000     0.9925 0.000 1.000
#> GSM379843     2  0.0000     0.9925 0.000 1.000
#> GSM379844     2  0.0000     0.9925 0.000 1.000
#> GSM379845     2  0.0000     0.9925 0.000 1.000
#> GSM379846     2  0.0000     0.9925 0.000 1.000
#> GSM379847     2  0.0000     0.9925 0.000 1.000
#> GSM379853     2  0.0000     0.9925 0.000 1.000
#> GSM379854     2  0.0000     0.9925 0.000 1.000
#> GSM379851     2  0.0000     0.9925 0.000 1.000
#> GSM379852     2  0.0000     0.9925 0.000 1.000
#> GSM379804     1  0.0000     0.9911 1.000 0.000
#> GSM379805     1  0.0000     0.9911 1.000 0.000
#> GSM379806     1  0.0000     0.9911 1.000 0.000
#> GSM379799     1  0.0000     0.9911 1.000 0.000
#> GSM379800     1  0.0000     0.9911 1.000 0.000
#> GSM379801     1  0.0000     0.9911 1.000 0.000
#> GSM379802     1  0.0000     0.9911 1.000 0.000
#> GSM379803     1  0.0000     0.9911 1.000 0.000
#> GSM379812     1  0.0000     0.9911 1.000 0.000
#> GSM379813     1  0.0000     0.9911 1.000 0.000
#> GSM379814     1  0.0000     0.9911 1.000 0.000
#> GSM379807     1  0.0000     0.9911 1.000 0.000
#> GSM379808     1  0.0000     0.9911 1.000 0.000
#> GSM379809     1  0.0000     0.9911 1.000 0.000
#> GSM379810     1  0.0000     0.9911 1.000 0.000
#> GSM379811     1  0.0000     0.9911 1.000 0.000
#> GSM379820     1  0.0000     0.9911 1.000 0.000
#> GSM379821     1  0.0000     0.9911 1.000 0.000
#> GSM379822     1  0.0000     0.9911 1.000 0.000
#> GSM379815     1  0.0000     0.9911 1.000 0.000
#> GSM379816     1  0.7528     0.7200 0.784 0.216
#> GSM379817     1  0.0000     0.9911 1.000 0.000
#> GSM379818     1  0.0000     0.9911 1.000 0.000
#> GSM379819     1  0.0000     0.9911 1.000 0.000
#> GSM379825     1  0.0000     0.9911 1.000 0.000
#> GSM379826     1  0.0000     0.9911 1.000 0.000
#> GSM379823     1  0.0000     0.9911 1.000 0.000
#> GSM379824     1  0.0000     0.9911 1.000 0.000
#> GSM379749     2  0.0000     0.9925 0.000 1.000
#> GSM379750     2  0.0000     0.9925 0.000 1.000
#> GSM379751     2  0.0000     0.9925 0.000 1.000
#> GSM379744     2  0.0000     0.9925 0.000 1.000
#> GSM379745     2  0.0000     0.9925 0.000 1.000
#> GSM379746     2  0.0000     0.9925 0.000 1.000
#> GSM379747     2  0.0000     0.9925 0.000 1.000
#> GSM379748     2  0.0000     0.9925 0.000 1.000
#> GSM379757     2  0.0000     0.9925 0.000 1.000
#> GSM379758     2  0.0000     0.9925 0.000 1.000
#> GSM379752     2  0.0000     0.9925 0.000 1.000
#> GSM379753     2  0.0000     0.9925 0.000 1.000
#> GSM379754     2  0.0000     0.9925 0.000 1.000
#> GSM379755     2  0.0000     0.9925 0.000 1.000
#> GSM379756     2  0.0000     0.9925 0.000 1.000
#> GSM379764     2  0.0000     0.9925 0.000 1.000
#> GSM379765     2  0.0000     0.9925 0.000 1.000
#> GSM379766     2  0.0000     0.9925 0.000 1.000
#> GSM379759     2  0.0000     0.9925 0.000 1.000
#> GSM379760     2  0.0000     0.9925 0.000 1.000
#> GSM379761     2  0.0000     0.9925 0.000 1.000
#> GSM379762     2  0.0000     0.9925 0.000 1.000
#> GSM379763     2  0.0000     0.9925 0.000 1.000
#> GSM379769     2  0.0000     0.9925 0.000 1.000
#> GSM379770     2  0.0000     0.9925 0.000 1.000
#> GSM379767     2  0.0000     0.9925 0.000 1.000
#> GSM379768     2  0.0000     0.9925 0.000 1.000
#> GSM379776     1  0.0000     0.9911 1.000 0.000
#> GSM379777     1  0.0000     0.9911 1.000 0.000
#> GSM379778     1  0.9983     0.0905 0.524 0.476
#> GSM379771     1  0.0000     0.9911 1.000 0.000
#> GSM379772     1  0.0000     0.9911 1.000 0.000
#> GSM379773     1  0.0000     0.9911 1.000 0.000
#> GSM379774     1  0.0000     0.9911 1.000 0.000
#> GSM379775     1  0.0000     0.9911 1.000 0.000
#> GSM379784     1  0.0000     0.9911 1.000 0.000
#> GSM379785     1  0.0000     0.9911 1.000 0.000
#> GSM379786     1  0.0000     0.9911 1.000 0.000
#> GSM379779     1  0.0000     0.9911 1.000 0.000
#> GSM379780     1  0.0000     0.9911 1.000 0.000
#> GSM379781     1  0.0000     0.9911 1.000 0.000
#> GSM379782     2  0.0000     0.9925 0.000 1.000
#> GSM379783     1  0.0672     0.9834 0.992 0.008
#> GSM379792     1  0.0000     0.9911 1.000 0.000
#> GSM379793     1  0.0000     0.9911 1.000 0.000
#> GSM379794     1  0.0000     0.9911 1.000 0.000
#> GSM379787     2  0.0000     0.9925 0.000 1.000
#> GSM379788     1  0.0000     0.9911 1.000 0.000
#> GSM379789     1  0.0000     0.9911 1.000 0.000
#> GSM379790     1  0.0000     0.9911 1.000 0.000
#> GSM379791     1  0.0000     0.9911 1.000 0.000
#> GSM379797     1  0.0000     0.9911 1.000 0.000
#> GSM379798     1  0.0000     0.9911 1.000 0.000
#> GSM379795     1  0.0000     0.9911 1.000 0.000
#> GSM379796     1  0.0000     0.9911 1.000 0.000
#> GSM379721     1  0.0000     0.9911 1.000 0.000
#> GSM379722     1  0.0000     0.9911 1.000 0.000
#> GSM379723     1  0.0000     0.9911 1.000 0.000
#> GSM379716     1  0.0000     0.9911 1.000 0.000
#> GSM379717     1  0.0000     0.9911 1.000 0.000
#> GSM379718     1  0.0000     0.9911 1.000 0.000
#> GSM379719     1  0.0000     0.9911 1.000 0.000
#> GSM379720     1  0.0000     0.9911 1.000 0.000
#> GSM379729     1  0.0000     0.9911 1.000 0.000
#> GSM379730     1  0.0000     0.9911 1.000 0.000
#> GSM379731     1  0.0000     0.9911 1.000 0.000
#> GSM379724     1  0.0000     0.9911 1.000 0.000
#> GSM379725     1  0.0000     0.9911 1.000 0.000
#> GSM379726     1  0.0000     0.9911 1.000 0.000
#> GSM379727     1  0.0000     0.9911 1.000 0.000
#> GSM379728     1  0.0000     0.9911 1.000 0.000
#> GSM379737     1  0.0000     0.9911 1.000 0.000
#> GSM379738     1  0.0000     0.9911 1.000 0.000
#> GSM379739     1  0.0000     0.9911 1.000 0.000
#> GSM379732     1  0.0000     0.9911 1.000 0.000
#> GSM379733     1  0.0000     0.9911 1.000 0.000
#> GSM379734     1  0.0000     0.9911 1.000 0.000
#> GSM379735     1  0.0000     0.9911 1.000 0.000
#> GSM379736     1  0.0000     0.9911 1.000 0.000
#> GSM379742     2  0.0000     0.9925 0.000 1.000
#> GSM379743     1  0.0000     0.9911 1.000 0.000
#> GSM379740     1  0.0000     0.9911 1.000 0.000
#> GSM379741     2  0.0000     0.9925 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2   0.000      0.991 0.000 1.000 0.000
#> GSM379833     2   0.000      0.991 0.000 1.000 0.000
#> GSM379834     2   0.000      0.991 0.000 1.000 0.000
#> GSM379827     2   0.000      0.991 0.000 1.000 0.000
#> GSM379828     2   0.000      0.991 0.000 1.000 0.000
#> GSM379829     1   0.000      0.966 1.000 0.000 0.000
#> GSM379830     2   0.000      0.991 0.000 1.000 0.000
#> GSM379831     2   0.000      0.991 0.000 1.000 0.000
#> GSM379840     2   0.000      0.991 0.000 1.000 0.000
#> GSM379841     2   0.000      0.991 0.000 1.000 0.000
#> GSM379842     2   0.000      0.991 0.000 1.000 0.000
#> GSM379835     2   0.000      0.991 0.000 1.000 0.000
#> GSM379836     2   0.000      0.991 0.000 1.000 0.000
#> GSM379837     2   0.774      0.300 0.376 0.568 0.056
#> GSM379838     2   0.000      0.991 0.000 1.000 0.000
#> GSM379839     2   0.000      0.991 0.000 1.000 0.000
#> GSM379848     2   0.000      0.991 0.000 1.000 0.000
#> GSM379849     2   0.000      0.991 0.000 1.000 0.000
#> GSM379850     2   0.000      0.991 0.000 1.000 0.000
#> GSM379843     2   0.000      0.991 0.000 1.000 0.000
#> GSM379844     2   0.000      0.991 0.000 1.000 0.000
#> GSM379845     2   0.000      0.991 0.000 1.000 0.000
#> GSM379846     2   0.000      0.991 0.000 1.000 0.000
#> GSM379847     2   0.000      0.991 0.000 1.000 0.000
#> GSM379853     2   0.000      0.991 0.000 1.000 0.000
#> GSM379854     2   0.000      0.991 0.000 1.000 0.000
#> GSM379851     2   0.000      0.991 0.000 1.000 0.000
#> GSM379852     2   0.000      0.991 0.000 1.000 0.000
#> GSM379804     1   0.000      0.966 1.000 0.000 0.000
#> GSM379805     1   0.000      0.966 1.000 0.000 0.000
#> GSM379806     1   0.000      0.966 1.000 0.000 0.000
#> GSM379799     1   0.000      0.966 1.000 0.000 0.000
#> GSM379800     1   0.000      0.966 1.000 0.000 0.000
#> GSM379801     1   0.000      0.966 1.000 0.000 0.000
#> GSM379802     1   0.000      0.966 1.000 0.000 0.000
#> GSM379803     1   0.000      0.966 1.000 0.000 0.000
#> GSM379812     3   0.207      0.932 0.060 0.000 0.940
#> GSM379813     1   0.597      0.352 0.636 0.000 0.364
#> GSM379814     1   0.000      0.966 1.000 0.000 0.000
#> GSM379807     1   0.000      0.966 1.000 0.000 0.000
#> GSM379808     1   0.000      0.966 1.000 0.000 0.000
#> GSM379809     1   0.000      0.966 1.000 0.000 0.000
#> GSM379810     1   0.000      0.966 1.000 0.000 0.000
#> GSM379811     1   0.000      0.966 1.000 0.000 0.000
#> GSM379820     1   0.000      0.966 1.000 0.000 0.000
#> GSM379821     3   0.207      0.932 0.060 0.000 0.940
#> GSM379822     3   0.207      0.932 0.060 0.000 0.940
#> GSM379815     1   0.000      0.966 1.000 0.000 0.000
#> GSM379816     3   0.000      0.925 0.000 0.000 1.000
#> GSM379817     1   0.597      0.352 0.636 0.000 0.364
#> GSM379818     1   0.000      0.966 1.000 0.000 0.000
#> GSM379819     1   0.000      0.966 1.000 0.000 0.000
#> GSM379825     1   0.000      0.966 1.000 0.000 0.000
#> GSM379826     1   0.000      0.966 1.000 0.000 0.000
#> GSM379823     3   0.207      0.932 0.060 0.000 0.940
#> GSM379824     3   0.484      0.780 0.224 0.000 0.776
#> GSM379749     2   0.000      0.991 0.000 1.000 0.000
#> GSM379750     2   0.000      0.991 0.000 1.000 0.000
#> GSM379751     2   0.000      0.991 0.000 1.000 0.000
#> GSM379744     2   0.000      0.991 0.000 1.000 0.000
#> GSM379745     2   0.000      0.991 0.000 1.000 0.000
#> GSM379746     2   0.000      0.991 0.000 1.000 0.000
#> GSM379747     2   0.000      0.991 0.000 1.000 0.000
#> GSM379748     2   0.000      0.991 0.000 1.000 0.000
#> GSM379757     2   0.000      0.991 0.000 1.000 0.000
#> GSM379758     2   0.000      0.991 0.000 1.000 0.000
#> GSM379752     2   0.000      0.991 0.000 1.000 0.000
#> GSM379753     2   0.000      0.991 0.000 1.000 0.000
#> GSM379754     2   0.000      0.991 0.000 1.000 0.000
#> GSM379755     2   0.000      0.991 0.000 1.000 0.000
#> GSM379756     2   0.000      0.991 0.000 1.000 0.000
#> GSM379764     2   0.000      0.991 0.000 1.000 0.000
#> GSM379765     2   0.000      0.991 0.000 1.000 0.000
#> GSM379766     2   0.000      0.991 0.000 1.000 0.000
#> GSM379759     2   0.000      0.991 0.000 1.000 0.000
#> GSM379760     2   0.000      0.991 0.000 1.000 0.000
#> GSM379761     2   0.000      0.991 0.000 1.000 0.000
#> GSM379762     2   0.000      0.991 0.000 1.000 0.000
#> GSM379763     2   0.000      0.991 0.000 1.000 0.000
#> GSM379769     2   0.000      0.991 0.000 1.000 0.000
#> GSM379770     2   0.000      0.991 0.000 1.000 0.000
#> GSM379767     2   0.000      0.991 0.000 1.000 0.000
#> GSM379768     2   0.000      0.991 0.000 1.000 0.000
#> GSM379776     1   0.000      0.966 1.000 0.000 0.000
#> GSM379777     3   0.207      0.932 0.060 0.000 0.940
#> GSM379778     3   0.652      0.696 0.048 0.228 0.724
#> GSM379771     1   0.000      0.966 1.000 0.000 0.000
#> GSM379772     1   0.000      0.966 1.000 0.000 0.000
#> GSM379773     1   0.000      0.966 1.000 0.000 0.000
#> GSM379774     1   0.000      0.966 1.000 0.000 0.000
#> GSM379775     1   0.000      0.966 1.000 0.000 0.000
#> GSM379784     3   0.207      0.932 0.060 0.000 0.940
#> GSM379785     3   0.506      0.753 0.244 0.000 0.756
#> GSM379786     3   0.207      0.932 0.060 0.000 0.940
#> GSM379779     1   0.000      0.966 1.000 0.000 0.000
#> GSM379780     1   0.000      0.966 1.000 0.000 0.000
#> GSM379781     3   0.506      0.753 0.244 0.000 0.756
#> GSM379782     2   0.000      0.991 0.000 1.000 0.000
#> GSM379783     3   0.207      0.932 0.060 0.000 0.940
#> GSM379792     1   0.000      0.966 1.000 0.000 0.000
#> GSM379793     1   0.000      0.966 1.000 0.000 0.000
#> GSM379794     1   0.000      0.966 1.000 0.000 0.000
#> GSM379787     2   0.000      0.991 0.000 1.000 0.000
#> GSM379788     3   0.207      0.932 0.060 0.000 0.940
#> GSM379789     1   0.000      0.966 1.000 0.000 0.000
#> GSM379790     1   0.000      0.966 1.000 0.000 0.000
#> GSM379791     1   0.000      0.966 1.000 0.000 0.000
#> GSM379797     1   0.000      0.966 1.000 0.000 0.000
#> GSM379798     1   0.000      0.966 1.000 0.000 0.000
#> GSM379795     1   0.000      0.966 1.000 0.000 0.000
#> GSM379796     1   0.000      0.966 1.000 0.000 0.000
#> GSM379721     1   0.207      0.940 0.940 0.000 0.060
#> GSM379722     1   0.207      0.940 0.940 0.000 0.060
#> GSM379723     1   0.207      0.940 0.940 0.000 0.060
#> GSM379716     1   0.207      0.940 0.940 0.000 0.060
#> GSM379717     1   0.207      0.940 0.940 0.000 0.060
#> GSM379718     1   0.207      0.940 0.940 0.000 0.060
#> GSM379719     1   0.207      0.940 0.940 0.000 0.060
#> GSM379720     1   0.207      0.940 0.940 0.000 0.060
#> GSM379729     3   0.000      0.925 0.000 0.000 1.000
#> GSM379730     3   0.000      0.925 0.000 0.000 1.000
#> GSM379731     3   0.000      0.925 0.000 0.000 1.000
#> GSM379724     1   0.207      0.940 0.940 0.000 0.060
#> GSM379725     3   0.000      0.925 0.000 0.000 1.000
#> GSM379726     1   0.207      0.940 0.940 0.000 0.060
#> GSM379727     1   0.207      0.940 0.940 0.000 0.060
#> GSM379728     1   0.207      0.940 0.940 0.000 0.060
#> GSM379737     1   0.207      0.940 0.940 0.000 0.060
#> GSM379738     1   0.207      0.940 0.940 0.000 0.060
#> GSM379739     1   0.207      0.940 0.940 0.000 0.060
#> GSM379732     3   0.000      0.925 0.000 0.000 1.000
#> GSM379733     1   0.207      0.940 0.940 0.000 0.060
#> GSM379734     1   0.207      0.940 0.940 0.000 0.060
#> GSM379735     3   0.000      0.925 0.000 0.000 1.000
#> GSM379736     1   0.000      0.966 1.000 0.000 0.000
#> GSM379742     2   0.000      0.991 0.000 1.000 0.000
#> GSM379743     3   0.000      0.925 0.000 0.000 1.000
#> GSM379740     1   0.207      0.940 0.940 0.000 0.060
#> GSM379741     2   0.000      0.991 0.000 1.000 0.000

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379833     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379834     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379827     2  0.2124     0.9125 0.008 0.924 0.068 0.000
#> GSM379828     2  0.2737     0.8886 0.008 0.888 0.104 0.000
#> GSM379829     4  0.5099     0.3601 0.008 0.000 0.380 0.612
#> GSM379830     2  0.2859     0.8829 0.008 0.880 0.112 0.000
#> GSM379831     2  0.2859     0.8829 0.008 0.880 0.112 0.000
#> GSM379840     2  0.4769     0.6891 0.008 0.684 0.308 0.000
#> GSM379841     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379842     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379835     2  0.2859     0.8829 0.008 0.880 0.112 0.000
#> GSM379836     2  0.4769     0.6891 0.008 0.684 0.308 0.000
#> GSM379837     3  0.8383     0.0259 0.020 0.264 0.392 0.324
#> GSM379838     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379839     2  0.7623     0.3817 0.008 0.496 0.320 0.176
#> GSM379848     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379849     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379850     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379843     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379844     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379845     2  0.4769     0.6891 0.008 0.684 0.308 0.000
#> GSM379846     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379847     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379853     2  0.2859     0.8829 0.008 0.880 0.112 0.000
#> GSM379854     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379851     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379852     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379804     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379805     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379806     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379799     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379800     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379801     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379802     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379803     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379812     1  0.2081     0.8486 0.916 0.000 0.000 0.084
#> GSM379813     4  0.2345     0.8009 0.100 0.000 0.000 0.900
#> GSM379814     4  0.1635     0.8565 0.044 0.000 0.008 0.948
#> GSM379807     4  0.0336     0.8725 0.000 0.000 0.008 0.992
#> GSM379808     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379809     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379810     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379811     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379820     4  0.0336     0.8725 0.000 0.000 0.008 0.992
#> GSM379821     1  0.2081     0.8486 0.916 0.000 0.000 0.084
#> GSM379822     1  0.2081     0.8486 0.916 0.000 0.000 0.084
#> GSM379815     4  0.0336     0.8725 0.000 0.000 0.008 0.992
#> GSM379816     1  0.2197     0.8541 0.916 0.000 0.080 0.004
#> GSM379817     4  0.2345     0.8009 0.100 0.000 0.000 0.900
#> GSM379818     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379819     4  0.0336     0.8725 0.000 0.000 0.008 0.992
#> GSM379825     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379826     4  0.1635     0.8565 0.044 0.000 0.008 0.948
#> GSM379823     1  0.2081     0.8486 0.916 0.000 0.000 0.084
#> GSM379824     1  0.4222     0.6118 0.728 0.000 0.000 0.272
#> GSM379749     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379750     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379751     2  0.3933     0.8068 0.008 0.792 0.200 0.000
#> GSM379744     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379745     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379746     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379747     2  0.0336     0.9509 0.000 0.992 0.008 0.000
#> GSM379748     2  0.0336     0.9509 0.000 0.992 0.008 0.000
#> GSM379757     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379758     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379752     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379753     2  0.0921     0.9407 0.000 0.972 0.028 0.000
#> GSM379754     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379755     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379756     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379764     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379765     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379766     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379759     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379760     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379761     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379762     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379763     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379769     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379770     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379767     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379768     2  0.0000     0.9545 0.000 1.000 0.000 0.000
#> GSM379776     4  0.1940     0.8491 0.076 0.000 0.000 0.924
#> GSM379777     1  0.2216     0.8445 0.908 0.000 0.000 0.092
#> GSM379778     1  0.7077     0.5194 0.628 0.248 0.072 0.052
#> GSM379771     4  0.2635     0.8391 0.076 0.000 0.020 0.904
#> GSM379772     4  0.2635     0.8391 0.076 0.000 0.020 0.904
#> GSM379773     4  0.2742     0.8372 0.076 0.000 0.024 0.900
#> GSM379774     4  0.2635     0.8391 0.076 0.000 0.020 0.904
#> GSM379775     4  0.2635     0.8391 0.076 0.000 0.020 0.904
#> GSM379784     1  0.0336     0.8469 0.992 0.000 0.000 0.008
#> GSM379785     1  0.4933     0.1093 0.568 0.000 0.000 0.432
#> GSM379786     1  0.0336     0.8469 0.992 0.000 0.000 0.008
#> GSM379779     4  0.2635     0.8391 0.076 0.000 0.020 0.904
#> GSM379780     4  0.3335     0.8097 0.120 0.000 0.020 0.860
#> GSM379781     4  0.5564     0.2791 0.436 0.000 0.020 0.544
#> GSM379782     2  0.3849     0.8391 0.084 0.856 0.052 0.008
#> GSM379783     1  0.0336     0.8469 0.992 0.000 0.000 0.008
#> GSM379792     4  0.0000     0.8716 0.000 0.000 0.000 1.000
#> GSM379793     4  0.3335     0.8097 0.120 0.000 0.020 0.860
#> GSM379794     4  0.2635     0.8391 0.076 0.000 0.020 0.904
#> GSM379787     2  0.4139     0.8299 0.080 0.848 0.052 0.020
#> GSM379788     1  0.0336     0.8469 0.992 0.000 0.000 0.008
#> GSM379789     4  0.3335     0.8097 0.120 0.000 0.020 0.860
#> GSM379790     4  0.1940     0.8491 0.076 0.000 0.000 0.924
#> GSM379791     4  0.3335     0.8097 0.120 0.000 0.020 0.860
#> GSM379797     4  0.1302     0.8681 0.000 0.000 0.044 0.956
#> GSM379798     4  0.1940     0.8491 0.076 0.000 0.000 0.924
#> GSM379795     4  0.3335     0.8097 0.120 0.000 0.020 0.860
#> GSM379796     4  0.0000     0.8716 0.000 0.000 0.000 1.000
#> GSM379721     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379722     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379723     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379716     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379717     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379718     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379719     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379720     3  0.4776     0.9127 0.000 0.000 0.624 0.376
#> GSM379729     1  0.2760     0.8442 0.872 0.000 0.128 0.000
#> GSM379730     1  0.2760     0.8442 0.872 0.000 0.128 0.000
#> GSM379731     1  0.2760     0.8442 0.872 0.000 0.128 0.000
#> GSM379724     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379725     1  0.2868     0.8390 0.864 0.000 0.136 0.000
#> GSM379726     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379727     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379728     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379737     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379738     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379739     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379732     1  0.3726     0.7727 0.788 0.000 0.212 0.000
#> GSM379733     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379734     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379735     1  0.2760     0.8442 0.872 0.000 0.128 0.000
#> GSM379736     4  0.1940     0.8314 0.000 0.000 0.076 0.924
#> GSM379742     2  0.1661     0.9201 0.004 0.944 0.052 0.000
#> GSM379743     1  0.2760     0.8442 0.872 0.000 0.128 0.000
#> GSM379740     3  0.4713     0.9395 0.000 0.000 0.640 0.360
#> GSM379741     2  0.1807     0.9172 0.008 0.940 0.052 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379833     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379834     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379827     2  0.3876    0.38941 0.000 0.684 0.000 0.000 0.316
#> GSM379828     2  0.4126    0.18797 0.000 0.620 0.000 0.000 0.380
#> GSM379829     5  0.4138    0.55081 0.000 0.000 0.016 0.276 0.708
#> GSM379830     2  0.4235    0.01425 0.000 0.576 0.000 0.000 0.424
#> GSM379831     2  0.4219    0.05056 0.000 0.584 0.000 0.000 0.416
#> GSM379840     5  0.3730    0.72384 0.000 0.288 0.000 0.000 0.712
#> GSM379841     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379842     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379835     2  0.4227    0.03283 0.000 0.580 0.000 0.000 0.420
#> GSM379836     5  0.3730    0.72384 0.000 0.288 0.000 0.000 0.712
#> GSM379837     5  0.4848    0.62230 0.004 0.040 0.012 0.228 0.716
#> GSM379838     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379839     5  0.4867    0.68197 0.000 0.104 0.000 0.180 0.716
#> GSM379848     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379849     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379850     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379843     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379844     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379845     5  0.3730    0.72384 0.000 0.288 0.000 0.000 0.712
#> GSM379846     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379847     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379853     2  0.4219    0.04851 0.000 0.584 0.000 0.000 0.416
#> GSM379854     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379851     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379852     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379804     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379805     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379806     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379799     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379800     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379801     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379802     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379803     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379812     1  0.1043    0.89942 0.960 0.000 0.000 0.040 0.000
#> GSM379813     4  0.1365    0.86658 0.040 0.000 0.004 0.952 0.004
#> GSM379814     4  0.0854    0.87608 0.012 0.000 0.008 0.976 0.004
#> GSM379807     4  0.0290    0.87685 0.000 0.000 0.008 0.992 0.000
#> GSM379808     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379809     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379810     4  0.0880    0.87537 0.000 0.000 0.032 0.968 0.000
#> GSM379811     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379820     4  0.0290    0.87685 0.000 0.000 0.008 0.992 0.000
#> GSM379821     1  0.1043    0.89942 0.960 0.000 0.000 0.040 0.000
#> GSM379822     1  0.1043    0.89942 0.960 0.000 0.000 0.040 0.000
#> GSM379815     4  0.0290    0.87685 0.000 0.000 0.008 0.992 0.000
#> GSM379816     1  0.1106    0.90320 0.964 0.000 0.012 0.024 0.000
#> GSM379817     4  0.1365    0.86658 0.040 0.000 0.004 0.952 0.004
#> GSM379818     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379819     4  0.0451    0.87636 0.000 0.000 0.008 0.988 0.004
#> GSM379825     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379826     4  0.0693    0.87583 0.012 0.000 0.008 0.980 0.000
#> GSM379823     1  0.1043    0.89942 0.960 0.000 0.000 0.040 0.000
#> GSM379824     1  0.3689    0.60905 0.740 0.000 0.000 0.256 0.004
#> GSM379749     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379750     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379751     5  0.4249    0.43332 0.000 0.432 0.000 0.000 0.568
#> GSM379744     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379745     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379746     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379747     2  0.2377    0.75768 0.000 0.872 0.000 0.000 0.128
#> GSM379748     2  0.2230    0.77321 0.000 0.884 0.000 0.000 0.116
#> GSM379757     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379758     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379752     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379753     2  0.2690    0.71781 0.000 0.844 0.000 0.000 0.156
#> GSM379754     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379755     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379756     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379764     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379765     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379766     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379759     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379760     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379761     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379762     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379763     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379769     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379770     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379767     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379768     2  0.0000    0.89616 0.000 1.000 0.000 0.000 0.000
#> GSM379776     4  0.3883    0.83028 0.036 0.000 0.000 0.780 0.184
#> GSM379777     1  0.1205    0.89740 0.956 0.000 0.000 0.040 0.004
#> GSM379778     1  0.8611   -0.00401 0.348 0.240 0.108 0.020 0.284
#> GSM379771     4  0.3847    0.82974 0.036 0.000 0.000 0.784 0.180
#> GSM379772     4  0.3847    0.82974 0.036 0.000 0.000 0.784 0.180
#> GSM379773     4  0.4470    0.80311 0.036 0.000 0.012 0.744 0.208
#> GSM379774     4  0.3847    0.82974 0.036 0.000 0.000 0.784 0.180
#> GSM379775     4  0.3847    0.82974 0.036 0.000 0.000 0.784 0.180
#> GSM379784     1  0.0162    0.89632 0.996 0.000 0.000 0.004 0.000
#> GSM379785     4  0.5787    0.66319 0.204 0.000 0.000 0.616 0.180
#> GSM379786     1  0.0000    0.89620 1.000 0.000 0.000 0.000 0.000
#> GSM379779     4  0.3847    0.82974 0.036 0.000 0.000 0.784 0.180
#> GSM379780     4  0.4065    0.82539 0.048 0.000 0.000 0.772 0.180
#> GSM379781     4  0.4867    0.78062 0.104 0.000 0.000 0.716 0.180
#> GSM379782     2  0.6048    0.38016 0.032 0.636 0.108 0.000 0.224
#> GSM379783     1  0.0000    0.89620 1.000 0.000 0.000 0.000 0.000
#> GSM379792     4  0.0451    0.87650 0.008 0.000 0.000 0.988 0.004
#> GSM379793     4  0.4065    0.82539 0.048 0.000 0.000 0.772 0.180
#> GSM379794     4  0.3847    0.82974 0.036 0.000 0.000 0.784 0.180
#> GSM379787     2  0.6576    0.30657 0.040 0.600 0.108 0.008 0.244
#> GSM379788     1  0.0162    0.89632 0.996 0.000 0.000 0.004 0.000
#> GSM379789     4  0.4065    0.82539 0.048 0.000 0.000 0.772 0.180
#> GSM379790     4  0.3847    0.82974 0.036 0.000 0.000 0.784 0.180
#> GSM379791     4  0.4065    0.82539 0.048 0.000 0.000 0.772 0.180
#> GSM379797     4  0.1041    0.87496 0.000 0.000 0.032 0.964 0.004
#> GSM379798     4  0.3847    0.82974 0.036 0.000 0.000 0.784 0.180
#> GSM379795     4  0.4065    0.82539 0.048 0.000 0.000 0.772 0.180
#> GSM379796     4  0.0798    0.87619 0.008 0.000 0.000 0.976 0.016
#> GSM379721     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379722     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379723     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379716     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379717     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379718     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379719     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379720     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379729     1  0.1270    0.89974 0.948 0.000 0.052 0.000 0.000
#> GSM379730     1  0.1270    0.89974 0.948 0.000 0.052 0.000 0.000
#> GSM379731     1  0.1270    0.89974 0.948 0.000 0.052 0.000 0.000
#> GSM379724     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379725     1  0.1410    0.89456 0.940 0.000 0.060 0.000 0.000
#> GSM379726     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379727     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379728     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379737     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379738     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379739     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379732     1  0.2471    0.82579 0.864 0.000 0.136 0.000 0.000
#> GSM379733     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379734     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379735     1  0.1270    0.89974 0.948 0.000 0.052 0.000 0.000
#> GSM379736     4  0.2719    0.76971 0.000 0.000 0.144 0.852 0.004
#> GSM379742     2  0.4279    0.64328 0.004 0.784 0.108 0.000 0.104
#> GSM379743     1  0.1270    0.89974 0.948 0.000 0.052 0.000 0.000
#> GSM379740     3  0.2127    1.00000 0.000 0.000 0.892 0.108 0.000
#> GSM379741     2  0.4279    0.64328 0.004 0.784 0.108 0.000 0.104

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     2  0.0603     0.8843 0.000 0.980 0.000 0.004 0.016 0.000
#> GSM379833     2  0.0603     0.8843 0.000 0.980 0.000 0.004 0.016 0.000
#> GSM379834     2  0.0603     0.8843 0.000 0.980 0.000 0.004 0.016 0.000
#> GSM379827     2  0.4747     0.2361 0.000 0.584 0.000 0.060 0.356 0.000
#> GSM379828     2  0.5112     0.0455 0.000 0.516 0.000 0.084 0.400 0.000
#> GSM379829     4  0.4335    -0.5868 0.020 0.000 0.000 0.508 0.472 0.000
#> GSM379830     2  0.5449    -0.1349 0.000 0.456 0.000 0.120 0.424 0.000
#> GSM379831     2  0.5419    -0.1234 0.000 0.460 0.000 0.116 0.424 0.000
#> GSM379840     5  0.5339     0.6184 0.000 0.108 0.000 0.404 0.488 0.000
#> GSM379841     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379842     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379835     2  0.5449    -0.1349 0.000 0.456 0.000 0.120 0.424 0.000
#> GSM379836     5  0.5330     0.6177 0.000 0.108 0.000 0.396 0.496 0.000
#> GSM379837     4  0.4315    -0.6199 0.004 0.012 0.000 0.496 0.488 0.000
#> GSM379838     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379839     5  0.4664     0.5513 0.004 0.032 0.000 0.476 0.488 0.000
#> GSM379848     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379849     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379850     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379843     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379844     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379845     5  0.5339     0.6184 0.000 0.108 0.000 0.404 0.488 0.000
#> GSM379846     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379847     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379853     2  0.5411    -0.0993 0.000 0.472 0.000 0.116 0.412 0.000
#> GSM379854     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379851     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379852     2  0.0405     0.8867 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM379804     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379805     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379806     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379799     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379800     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379801     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379802     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379803     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379812     6  0.0146     0.9437 0.000 0.000 0.000 0.004 0.000 0.996
#> GSM379813     4  0.4800     0.7234 0.448 0.000 0.000 0.500 0.000 0.052
#> GSM379814     4  0.4392     0.7663 0.476 0.000 0.004 0.504 0.000 0.016
#> GSM379807     4  0.3995     0.7894 0.480 0.000 0.004 0.516 0.000 0.000
#> GSM379808     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379809     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379810     4  0.4331     0.8073 0.464 0.000 0.020 0.516 0.000 0.000
#> GSM379811     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379820     4  0.3996     0.7839 0.484 0.000 0.004 0.512 0.000 0.000
#> GSM379821     6  0.0146     0.9437 0.000 0.000 0.000 0.004 0.000 0.996
#> GSM379822     6  0.0146     0.9437 0.000 0.000 0.000 0.004 0.000 0.996
#> GSM379815     4  0.3991     0.7988 0.472 0.000 0.004 0.524 0.000 0.000
#> GSM379816     6  0.1082     0.9403 0.000 0.000 0.000 0.040 0.004 0.956
#> GSM379817     4  0.4800     0.7234 0.448 0.000 0.000 0.500 0.000 0.052
#> GSM379818     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379819     4  0.3982     0.8086 0.460 0.000 0.004 0.536 0.000 0.000
#> GSM379825     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379826     4  0.4533     0.7654 0.468 0.000 0.004 0.504 0.000 0.024
#> GSM379823     6  0.0146     0.9437 0.000 0.000 0.000 0.004 0.000 0.996
#> GSM379824     6  0.4559     0.5428 0.156 0.000 0.004 0.128 0.000 0.712
#> GSM379749     2  0.0260     0.8859 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379750     2  0.0260     0.8859 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379751     5  0.5830     0.4640 0.000 0.284 0.000 0.228 0.488 0.000
#> GSM379744     2  0.0260     0.8859 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379745     2  0.0260     0.8859 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379746     2  0.0260     0.8859 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379747     2  0.1141     0.8506 0.000 0.948 0.000 0.000 0.052 0.000
#> GSM379748     2  0.1075     0.8544 0.000 0.952 0.000 0.000 0.048 0.000
#> GSM379757     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379758     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379752     2  0.0260     0.8859 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379753     2  0.1444     0.8297 0.000 0.928 0.000 0.000 0.072 0.000
#> GSM379754     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379755     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379756     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379764     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379765     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379766     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379759     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379760     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379761     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379762     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379763     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379769     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379770     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379767     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379768     2  0.0000     0.8879 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379776     1  0.0458     0.8452 0.984 0.000 0.000 0.016 0.000 0.000
#> GSM379777     6  0.0363     0.9397 0.000 0.000 0.000 0.012 0.000 0.988
#> GSM379778     5  0.5254     0.0128 0.452 0.024 0.000 0.004 0.484 0.036
#> GSM379771     1  0.0146     0.8649 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379772     1  0.0146     0.8649 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379773     1  0.2595     0.6787 0.836 0.000 0.004 0.000 0.160 0.000
#> GSM379774     1  0.0146     0.8649 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379775     1  0.0146     0.8649 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379784     6  0.0146     0.9435 0.004 0.000 0.000 0.000 0.000 0.996
#> GSM379785     1  0.1501     0.7902 0.924 0.000 0.000 0.000 0.000 0.076
#> GSM379786     6  0.0146     0.9435 0.004 0.000 0.000 0.000 0.000 0.996
#> GSM379779     1  0.0146     0.8649 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379780     1  0.0458     0.8598 0.984 0.000 0.000 0.000 0.000 0.016
#> GSM379781     1  0.1327     0.8060 0.936 0.000 0.000 0.000 0.000 0.064
#> GSM379782     5  0.5694     0.2334 0.144 0.368 0.000 0.000 0.484 0.004
#> GSM379783     6  0.0146     0.9435 0.004 0.000 0.000 0.000 0.000 0.996
#> GSM379792     1  0.3864    -0.7255 0.520 0.000 0.000 0.480 0.000 0.000
#> GSM379793     1  0.0508     0.8622 0.984 0.000 0.004 0.000 0.000 0.012
#> GSM379794     1  0.0146     0.8649 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM379787     5  0.5972     0.3141 0.272 0.240 0.000 0.000 0.484 0.004
#> GSM379788     6  0.0146     0.9435 0.004 0.000 0.000 0.000 0.000 0.996
#> GSM379789     1  0.0363     0.8621 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM379790     1  0.0000     0.8620 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379791     1  0.0508     0.8622 0.984 0.000 0.004 0.000 0.000 0.012
#> GSM379797     4  0.4310     0.8277 0.440 0.000 0.020 0.540 0.000 0.000
#> GSM379798     1  0.0000     0.8620 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379795     1  0.0603     0.8592 0.980 0.000 0.004 0.000 0.000 0.016
#> GSM379796     1  0.3860    -0.7077 0.528 0.000 0.000 0.472 0.000 0.000
#> GSM379721     3  0.0146     0.9912 0.000 0.000 0.996 0.004 0.000 0.000
#> GSM379722     3  0.0146     0.9912 0.000 0.000 0.996 0.004 0.000 0.000
#> GSM379723     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379716     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379717     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379718     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379719     3  0.0146     0.9912 0.000 0.000 0.996 0.004 0.000 0.000
#> GSM379720     3  0.0405     0.9920 0.004 0.000 0.988 0.008 0.000 0.000
#> GSM379729     6  0.1952     0.9340 0.000 0.000 0.016 0.052 0.012 0.920
#> GSM379730     6  0.1858     0.9355 0.000 0.000 0.012 0.052 0.012 0.924
#> GSM379731     6  0.1826     0.9348 0.000 0.000 0.020 0.052 0.004 0.924
#> GSM379724     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379725     6  0.1952     0.9340 0.000 0.000 0.016 0.052 0.012 0.920
#> GSM379726     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379727     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379728     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379737     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379738     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379739     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379732     6  0.2138     0.9236 0.000 0.000 0.036 0.052 0.004 0.908
#> GSM379733     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379734     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379735     6  0.1850     0.9356 0.000 0.000 0.016 0.052 0.008 0.924
#> GSM379736     4  0.5134     0.7204 0.388 0.000 0.088 0.524 0.000 0.000
#> GSM379742     2  0.3997     0.0140 0.000 0.508 0.000 0.000 0.488 0.004
#> GSM379743     6  0.1858     0.9355 0.000 0.000 0.012 0.052 0.012 0.924
#> GSM379740     3  0.0146     0.9978 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379741     2  0.3997     0.0140 0.000 0.508 0.000 0.000 0.488 0.004

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-ATC-skmeans-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-ATC-skmeans-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-ATC-skmeans-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-ATC-skmeans-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-ATC-skmeans-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-ATC-skmeans-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-ATC-skmeans-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-ATC-skmeans-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-ATC-skmeans-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-ATC-skmeans-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-ATC-skmeans-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-ATC-skmeans-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-ATC-skmeans-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-ATC-skmeans-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-ATC-skmeans-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-ATC-skmeans-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-ATC-skmeans-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-ATC-skmeans-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-ATC-skmeans-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-ATC-skmeans-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk ATC-skmeans-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-ATC-skmeans-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-ATC-skmeans-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-ATC-skmeans-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-ATC-skmeans-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-ATC-skmeans-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk ATC-skmeans-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>               n individual(p) time(p) agent(p) k
#> ATC:skmeans 137      1.60e-24   1.000   0.7803 2
#> ATC:skmeans 136      1.10e-21   0.928   0.0274 3
#> ATC:skmeans 134      2.07e-37   0.999   0.1175 4
#> ATC:skmeans 129      1.14e-39   0.997   0.0753 5
#> ATC:skmeans 123      9.70e-54   1.000   0.0813 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

ATC:pam**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["ATC", "pam"]
# you can also extract it by
# res = res_list["ATC:pam"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#>   Subgroups are detected by 'pam' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk ATC-pam-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk ATC-pam-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.978       0.991         0.4856 0.515   0.515
#> 3 3 0.718           0.812       0.897         0.3511 0.789   0.602
#> 4 4 0.652           0.726       0.810         0.1169 0.892   0.695
#> 5 5 0.750           0.753       0.879         0.0716 0.866   0.568
#> 6 6 0.771           0.685       0.830         0.0404 0.964   0.838

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000      0.991 0.000 1.000
#> GSM379833     2  0.0000      0.991 0.000 1.000
#> GSM379834     2  0.0000      0.991 0.000 1.000
#> GSM379827     2  0.0000      0.991 0.000 1.000
#> GSM379828     2  0.0000      0.991 0.000 1.000
#> GSM379829     1  0.0000      0.991 1.000 0.000
#> GSM379830     2  0.0000      0.991 0.000 1.000
#> GSM379831     2  0.0000      0.991 0.000 1.000
#> GSM379840     2  0.3879      0.914 0.076 0.924
#> GSM379841     2  0.0000      0.991 0.000 1.000
#> GSM379842     2  0.0000      0.991 0.000 1.000
#> GSM379835     2  0.0000      0.991 0.000 1.000
#> GSM379836     2  0.0376      0.987 0.004 0.996
#> GSM379837     1  0.9087      0.515 0.676 0.324
#> GSM379838     2  0.0000      0.991 0.000 1.000
#> GSM379839     2  0.5519      0.853 0.128 0.872
#> GSM379848     2  0.0000      0.991 0.000 1.000
#> GSM379849     2  0.0000      0.991 0.000 1.000
#> GSM379850     2  0.0000      0.991 0.000 1.000
#> GSM379843     2  0.0000      0.991 0.000 1.000
#> GSM379844     2  0.0000      0.991 0.000 1.000
#> GSM379845     2  0.0000      0.991 0.000 1.000
#> GSM379846     2  0.0000      0.991 0.000 1.000
#> GSM379847     2  0.0000      0.991 0.000 1.000
#> GSM379853     2  0.0000      0.991 0.000 1.000
#> GSM379854     2  0.0000      0.991 0.000 1.000
#> GSM379851     2  0.0000      0.991 0.000 1.000
#> GSM379852     2  0.0000      0.991 0.000 1.000
#> GSM379804     1  0.0000      0.991 1.000 0.000
#> GSM379805     1  0.0000      0.991 1.000 0.000
#> GSM379806     1  0.0000      0.991 1.000 0.000
#> GSM379799     1  0.0000      0.991 1.000 0.000
#> GSM379800     1  0.0000      0.991 1.000 0.000
#> GSM379801     1  0.0000      0.991 1.000 0.000
#> GSM379802     1  0.0000      0.991 1.000 0.000
#> GSM379803     1  0.0000      0.991 1.000 0.000
#> GSM379812     1  0.0000      0.991 1.000 0.000
#> GSM379813     1  0.0000      0.991 1.000 0.000
#> GSM379814     1  0.0000      0.991 1.000 0.000
#> GSM379807     1  0.0000      0.991 1.000 0.000
#> GSM379808     1  0.0000      0.991 1.000 0.000
#> GSM379809     1  0.0000      0.991 1.000 0.000
#> GSM379810     1  0.0000      0.991 1.000 0.000
#> GSM379811     1  0.0000      0.991 1.000 0.000
#> GSM379820     1  0.0000      0.991 1.000 0.000
#> GSM379821     1  0.0000      0.991 1.000 0.000
#> GSM379822     1  0.0000      0.991 1.000 0.000
#> GSM379815     1  0.0000      0.991 1.000 0.000
#> GSM379816     1  0.0000      0.991 1.000 0.000
#> GSM379817     1  0.0000      0.991 1.000 0.000
#> GSM379818     1  0.0000      0.991 1.000 0.000
#> GSM379819     1  0.0000      0.991 1.000 0.000
#> GSM379825     1  0.0000      0.991 1.000 0.000
#> GSM379826     1  0.0000      0.991 1.000 0.000
#> GSM379823     1  0.0000      0.991 1.000 0.000
#> GSM379824     1  0.0000      0.991 1.000 0.000
#> GSM379749     2  0.0000      0.991 0.000 1.000
#> GSM379750     2  0.0000      0.991 0.000 1.000
#> GSM379751     2  0.0000      0.991 0.000 1.000
#> GSM379744     2  0.0000      0.991 0.000 1.000
#> GSM379745     2  0.0000      0.991 0.000 1.000
#> GSM379746     2  0.0000      0.991 0.000 1.000
#> GSM379747     2  0.0000      0.991 0.000 1.000
#> GSM379748     2  0.0000      0.991 0.000 1.000
#> GSM379757     2  0.0000      0.991 0.000 1.000
#> GSM379758     2  0.0000      0.991 0.000 1.000
#> GSM379752     2  0.0000      0.991 0.000 1.000
#> GSM379753     2  0.0000      0.991 0.000 1.000
#> GSM379754     2  0.0000      0.991 0.000 1.000
#> GSM379755     2  0.0000      0.991 0.000 1.000
#> GSM379756     2  0.0000      0.991 0.000 1.000
#> GSM379764     2  0.0000      0.991 0.000 1.000
#> GSM379765     2  0.0000      0.991 0.000 1.000
#> GSM379766     2  0.0000      0.991 0.000 1.000
#> GSM379759     2  0.0000      0.991 0.000 1.000
#> GSM379760     2  0.0000      0.991 0.000 1.000
#> GSM379761     2  0.0000      0.991 0.000 1.000
#> GSM379762     2  0.0000      0.991 0.000 1.000
#> GSM379763     2  0.0000      0.991 0.000 1.000
#> GSM379769     2  0.0000      0.991 0.000 1.000
#> GSM379770     2  0.0000      0.991 0.000 1.000
#> GSM379767     2  0.0000      0.991 0.000 1.000
#> GSM379768     2  0.0000      0.991 0.000 1.000
#> GSM379776     1  0.0000      0.991 1.000 0.000
#> GSM379777     1  0.0000      0.991 1.000 0.000
#> GSM379778     1  0.0000      0.991 1.000 0.000
#> GSM379771     1  0.0000      0.991 1.000 0.000
#> GSM379772     1  0.0000      0.991 1.000 0.000
#> GSM379773     1  0.0000      0.991 1.000 0.000
#> GSM379774     1  0.0000      0.991 1.000 0.000
#> GSM379775     1  0.0000      0.991 1.000 0.000
#> GSM379784     1  0.0000      0.991 1.000 0.000
#> GSM379785     1  0.0000      0.991 1.000 0.000
#> GSM379786     1  0.0000      0.991 1.000 0.000
#> GSM379779     1  0.0000      0.991 1.000 0.000
#> GSM379780     1  0.0000      0.991 1.000 0.000
#> GSM379781     1  0.0000      0.991 1.000 0.000
#> GSM379782     2  0.8813      0.572 0.300 0.700
#> GSM379783     1  0.0000      0.991 1.000 0.000
#> GSM379792     1  0.0000      0.991 1.000 0.000
#> GSM379793     1  0.0000      0.991 1.000 0.000
#> GSM379794     1  0.0000      0.991 1.000 0.000
#> GSM379787     1  0.9635      0.357 0.612 0.388
#> GSM379788     1  0.0000      0.991 1.000 0.000
#> GSM379789     1  0.0000      0.991 1.000 0.000
#> GSM379790     1  0.0000      0.991 1.000 0.000
#> GSM379791     1  0.0000      0.991 1.000 0.000
#> GSM379797     1  0.0000      0.991 1.000 0.000
#> GSM379798     1  0.0000      0.991 1.000 0.000
#> GSM379795     1  0.0000      0.991 1.000 0.000
#> GSM379796     1  0.0000      0.991 1.000 0.000
#> GSM379721     1  0.0000      0.991 1.000 0.000
#> GSM379722     1  0.0000      0.991 1.000 0.000
#> GSM379723     1  0.0000      0.991 1.000 0.000
#> GSM379716     1  0.0000      0.991 1.000 0.000
#> GSM379717     1  0.0000      0.991 1.000 0.000
#> GSM379718     1  0.0000      0.991 1.000 0.000
#> GSM379719     1  0.0000      0.991 1.000 0.000
#> GSM379720     1  0.0000      0.991 1.000 0.000
#> GSM379729     1  0.0000      0.991 1.000 0.000
#> GSM379730     1  0.0000      0.991 1.000 0.000
#> GSM379731     1  0.0000      0.991 1.000 0.000
#> GSM379724     1  0.0000      0.991 1.000 0.000
#> GSM379725     1  0.0000      0.991 1.000 0.000
#> GSM379726     1  0.0000      0.991 1.000 0.000
#> GSM379727     1  0.0000      0.991 1.000 0.000
#> GSM379728     1  0.0000      0.991 1.000 0.000
#> GSM379737     1  0.0000      0.991 1.000 0.000
#> GSM379738     1  0.0000      0.991 1.000 0.000
#> GSM379739     1  0.0000      0.991 1.000 0.000
#> GSM379732     1  0.0000      0.991 1.000 0.000
#> GSM379733     1  0.0000      0.991 1.000 0.000
#> GSM379734     1  0.0000      0.991 1.000 0.000
#> GSM379735     1  0.0000      0.991 1.000 0.000
#> GSM379736     1  0.0000      0.991 1.000 0.000
#> GSM379742     2  0.0000      0.991 0.000 1.000
#> GSM379743     1  0.0000      0.991 1.000 0.000
#> GSM379740     1  0.0000      0.991 1.000 0.000
#> GSM379741     2  0.0000      0.991 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379833     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379834     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379827     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379828     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379829     1  0.0892     0.7958 0.980 0.000 0.020
#> GSM379830     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379831     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379840     3  0.7757     0.0609 0.048 0.464 0.488
#> GSM379841     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379842     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379835     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379836     2  0.5882     0.4345 0.000 0.652 0.348
#> GSM379837     3  0.2297     0.8077 0.036 0.020 0.944
#> GSM379838     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379839     3  0.6811     0.5994 0.064 0.220 0.716
#> GSM379848     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379849     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379850     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379843     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379844     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379845     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379846     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379847     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379853     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379854     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379851     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379852     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379804     1  0.3482     0.8151 0.872 0.000 0.128
#> GSM379805     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379806     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379799     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379800     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379801     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379802     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379803     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379812     3  0.2959     0.7362 0.100 0.000 0.900
#> GSM379813     1  0.5968     0.6856 0.636 0.000 0.364
#> GSM379814     1  0.4555     0.7905 0.800 0.000 0.200
#> GSM379807     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379808     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379809     1  0.3752     0.8093 0.856 0.000 0.144
#> GSM379810     1  0.5591     0.6623 0.696 0.000 0.304
#> GSM379811     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379820     1  0.3941     0.8111 0.844 0.000 0.156
#> GSM379821     3  0.1753     0.7898 0.048 0.000 0.952
#> GSM379822     3  0.0747     0.8084 0.016 0.000 0.984
#> GSM379815     1  0.3482     0.8151 0.872 0.000 0.128
#> GSM379816     3  0.0237     0.8142 0.004 0.000 0.996
#> GSM379817     1  0.6154     0.6216 0.592 0.000 0.408
#> GSM379818     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379819     1  0.3412     0.8157 0.876 0.000 0.124
#> GSM379825     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379826     1  0.3482     0.8151 0.872 0.000 0.128
#> GSM379823     3  0.1289     0.7987 0.032 0.000 0.968
#> GSM379824     1  0.4178     0.8138 0.828 0.000 0.172
#> GSM379749     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379750     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379751     2  0.1031     0.9535 0.000 0.976 0.024
#> GSM379744     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379745     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379746     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379747     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379748     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379757     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379758     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379752     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379753     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379754     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379755     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379756     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379764     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379765     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379766     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379759     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379760     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379761     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379762     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379763     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379769     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379770     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379767     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379768     2  0.0000     0.9770 0.000 1.000 0.000
#> GSM379776     1  0.4452     0.8071 0.808 0.000 0.192
#> GSM379777     1  0.5968     0.6832 0.636 0.000 0.364
#> GSM379778     3  0.5835     0.1220 0.340 0.000 0.660
#> GSM379771     1  0.3551     0.8157 0.868 0.000 0.132
#> GSM379772     1  0.3752     0.8093 0.856 0.000 0.144
#> GSM379773     1  0.5560     0.7402 0.700 0.000 0.300
#> GSM379774     1  0.5760     0.7169 0.672 0.000 0.328
#> GSM379775     1  0.3482     0.8151 0.872 0.000 0.128
#> GSM379784     3  0.1031     0.8050 0.024 0.000 0.976
#> GSM379785     1  0.6008     0.6698 0.628 0.000 0.372
#> GSM379786     3  0.0000     0.8137 0.000 0.000 1.000
#> GSM379779     1  0.5497     0.7441 0.708 0.000 0.292
#> GSM379780     1  0.5926     0.6893 0.644 0.000 0.356
#> GSM379781     1  0.6305     0.4683 0.516 0.000 0.484
#> GSM379782     2  0.4702     0.7156 0.000 0.788 0.212
#> GSM379783     3  0.0000     0.8137 0.000 0.000 1.000
#> GSM379792     1  0.3482     0.8151 0.872 0.000 0.128
#> GSM379793     1  0.5882     0.6975 0.652 0.000 0.348
#> GSM379794     1  0.4504     0.8054 0.804 0.000 0.196
#> GSM379787     2  0.9767    -0.0630 0.320 0.432 0.248
#> GSM379788     3  0.0000     0.8137 0.000 0.000 1.000
#> GSM379789     1  0.5882     0.6975 0.652 0.000 0.348
#> GSM379790     1  0.4346     0.8096 0.816 0.000 0.184
#> GSM379791     1  0.5882     0.6975 0.652 0.000 0.348
#> GSM379797     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379798     1  0.4235     0.8114 0.824 0.000 0.176
#> GSM379795     1  0.6008     0.6772 0.628 0.000 0.372
#> GSM379796     1  0.1411     0.8085 0.964 0.000 0.036
#> GSM379721     3  0.3879     0.7777 0.152 0.000 0.848
#> GSM379722     3  0.1964     0.8081 0.056 0.000 0.944
#> GSM379723     3  0.6168     0.3423 0.412 0.000 0.588
#> GSM379716     1  0.5327     0.4358 0.728 0.000 0.272
#> GSM379717     3  0.5058     0.7010 0.244 0.000 0.756
#> GSM379718     3  0.4931     0.7143 0.232 0.000 0.768
#> GSM379719     3  0.3879     0.7777 0.152 0.000 0.848
#> GSM379720     3  0.4702     0.7345 0.212 0.000 0.788
#> GSM379729     3  0.0000     0.8137 0.000 0.000 1.000
#> GSM379730     3  0.0000     0.8137 0.000 0.000 1.000
#> GSM379731     3  0.0000     0.8137 0.000 0.000 1.000
#> GSM379724     3  0.4887     0.7183 0.228 0.000 0.772
#> GSM379725     3  0.0000     0.8137 0.000 0.000 1.000
#> GSM379726     3  0.5058     0.7010 0.244 0.000 0.756
#> GSM379727     3  0.3941     0.7755 0.156 0.000 0.844
#> GSM379728     1  0.6274     0.1435 0.544 0.000 0.456
#> GSM379737     3  0.4178     0.7655 0.172 0.000 0.828
#> GSM379738     3  0.4887     0.7183 0.228 0.000 0.772
#> GSM379739     3  0.0424     0.8136 0.008 0.000 0.992
#> GSM379732     3  0.0000     0.8137 0.000 0.000 1.000
#> GSM379733     3  0.4291     0.7600 0.180 0.000 0.820
#> GSM379734     3  0.4178     0.7655 0.172 0.000 0.828
#> GSM379735     3  0.0000     0.8137 0.000 0.000 1.000
#> GSM379736     1  0.0000     0.7999 1.000 0.000 0.000
#> GSM379742     2  0.0424     0.9693 0.000 0.992 0.008
#> GSM379743     3  0.0000     0.8137 0.000 0.000 1.000
#> GSM379740     3  0.5058     0.7010 0.244 0.000 0.756
#> GSM379741     3  0.6291     0.1280 0.000 0.468 0.532

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     1  0.4776     0.6001 0.624 0.376 0.000 0.000
#> GSM379833     1  0.4776     0.6001 0.624 0.376 0.000 0.000
#> GSM379834     1  0.4998     0.2996 0.512 0.488 0.000 0.000
#> GSM379827     1  0.3311     0.8441 0.828 0.172 0.000 0.000
#> GSM379828     1  0.3311     0.8441 0.828 0.172 0.000 0.000
#> GSM379829     1  0.5137     0.2441 0.680 0.000 0.024 0.296
#> GSM379830     1  0.3311     0.8441 0.828 0.172 0.000 0.000
#> GSM379831     1  0.3311     0.8441 0.828 0.172 0.000 0.000
#> GSM379840     1  0.4405     0.8080 0.828 0.112 0.024 0.036
#> GSM379841     2  0.2149     0.8631 0.088 0.912 0.000 0.000
#> GSM379842     2  0.4605     0.4918 0.336 0.664 0.000 0.000
#> GSM379835     1  0.3311     0.8441 0.828 0.172 0.000 0.000
#> GSM379836     1  0.4017     0.8190 0.828 0.128 0.044 0.000
#> GSM379837     1  0.4579     0.5973 0.756 0.004 0.224 0.016
#> GSM379838     2  0.1211     0.8804 0.040 0.960 0.000 0.000
#> GSM379839     1  0.5644     0.6657 0.760 0.036 0.068 0.136
#> GSM379848     2  0.1211     0.8804 0.040 0.960 0.000 0.000
#> GSM379849     2  0.2149     0.8631 0.088 0.912 0.000 0.000
#> GSM379850     2  0.2149     0.8631 0.088 0.912 0.000 0.000
#> GSM379843     1  0.4164     0.7610 0.736 0.264 0.000 0.000
#> GSM379844     2  0.2149     0.8631 0.088 0.912 0.000 0.000
#> GSM379845     1  0.3311     0.8441 0.828 0.172 0.000 0.000
#> GSM379846     2  0.2149     0.8631 0.088 0.912 0.000 0.000
#> GSM379847     2  0.2149     0.8631 0.088 0.912 0.000 0.000
#> GSM379853     1  0.3311     0.8441 0.828 0.172 0.000 0.000
#> GSM379854     2  0.1211     0.8804 0.040 0.960 0.000 0.000
#> GSM379851     2  0.4996    -0.0699 0.484 0.516 0.000 0.000
#> GSM379852     2  0.2149     0.8631 0.088 0.912 0.000 0.000
#> GSM379804     4  0.3047     0.7737 0.116 0.000 0.012 0.872
#> GSM379805     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379806     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379799     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379800     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379801     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379802     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379803     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379812     3  0.3942     0.6628 0.000 0.000 0.764 0.236
#> GSM379813     4  0.4222     0.6259 0.000 0.000 0.272 0.728
#> GSM379814     4  0.2530     0.7299 0.000 0.000 0.112 0.888
#> GSM379807     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379808     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379809     4  0.3356     0.7003 0.000 0.000 0.176 0.824
#> GSM379810     4  0.4585     0.5021 0.000 0.000 0.332 0.668
#> GSM379811     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379820     4  0.1557     0.7590 0.000 0.000 0.056 0.944
#> GSM379821     3  0.3873     0.6852 0.000 0.000 0.772 0.228
#> GSM379822     3  0.3486     0.7176 0.000 0.000 0.812 0.188
#> GSM379815     4  0.2760     0.7355 0.000 0.000 0.128 0.872
#> GSM379816     3  0.4370     0.7272 0.044 0.000 0.800 0.156
#> GSM379817     4  0.4431     0.5807 0.000 0.000 0.304 0.696
#> GSM379818     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379819     4  0.2918     0.7735 0.116 0.000 0.008 0.876
#> GSM379825     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379826     4  0.1022     0.7660 0.000 0.000 0.032 0.968
#> GSM379823     3  0.3444     0.7185 0.000 0.000 0.816 0.184
#> GSM379824     4  0.1389     0.7636 0.000 0.000 0.048 0.952
#> GSM379749     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379750     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379751     1  0.3311     0.8441 0.828 0.172 0.000 0.000
#> GSM379744     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379745     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379746     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379747     1  0.3726     0.8200 0.788 0.212 0.000 0.000
#> GSM379748     2  0.4624     0.4038 0.340 0.660 0.000 0.000
#> GSM379757     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379758     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379752     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379753     1  0.3726     0.8200 0.788 0.212 0.000 0.000
#> GSM379754     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379755     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379756     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379764     2  0.3266     0.7635 0.168 0.832 0.000 0.000
#> GSM379765     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379766     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379759     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379760     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379761     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379762     2  0.1389     0.8772 0.048 0.952 0.000 0.000
#> GSM379763     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379769     2  0.3801     0.6881 0.220 0.780 0.000 0.000
#> GSM379770     2  0.2921     0.7965 0.140 0.860 0.000 0.000
#> GSM379767     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379768     2  0.0000     0.8952 0.000 1.000 0.000 0.000
#> GSM379776     4  0.3693     0.7740 0.072 0.000 0.072 0.856
#> GSM379777     4  0.3837     0.6646 0.000 0.000 0.224 0.776
#> GSM379778     4  0.5000     0.0945 0.000 0.000 0.496 0.504
#> GSM379771     4  0.2868     0.7351 0.000 0.000 0.136 0.864
#> GSM379772     4  0.2589     0.7438 0.000 0.000 0.116 0.884
#> GSM379773     4  0.3400     0.7015 0.000 0.000 0.180 0.820
#> GSM379774     4  0.3649     0.6835 0.000 0.000 0.204 0.796
#> GSM379775     4  0.1940     0.7609 0.000 0.000 0.076 0.924
#> GSM379784     3  0.3726     0.6980 0.000 0.000 0.788 0.212
#> GSM379785     4  0.3975     0.6537 0.000 0.000 0.240 0.760
#> GSM379786     3  0.3400     0.7215 0.000 0.000 0.820 0.180
#> GSM379779     4  0.3356     0.7002 0.000 0.000 0.176 0.824
#> GSM379780     4  0.3837     0.6646 0.000 0.000 0.224 0.776
#> GSM379781     4  0.4661     0.5040 0.000 0.000 0.348 0.652
#> GSM379782     2  0.8103     0.2721 0.288 0.528 0.060 0.124
#> GSM379783     3  0.3764     0.7222 0.012 0.000 0.816 0.172
#> GSM379792     4  0.3047     0.7737 0.116 0.000 0.012 0.872
#> GSM379793     4  0.3975     0.6537 0.000 0.000 0.240 0.760
#> GSM379794     4  0.2011     0.7559 0.000 0.000 0.080 0.920
#> GSM379787     4  0.9201     0.2383 0.180 0.204 0.152 0.464
#> GSM379788     3  0.3649     0.7075 0.000 0.000 0.796 0.204
#> GSM379789     4  0.3837     0.6646 0.000 0.000 0.224 0.776
#> GSM379790     4  0.1716     0.7590 0.000 0.000 0.064 0.936
#> GSM379791     4  0.3975     0.6549 0.000 0.000 0.240 0.760
#> GSM379797     4  0.3311     0.7629 0.172 0.000 0.000 0.828
#> GSM379798     4  0.2142     0.7663 0.016 0.000 0.056 0.928
#> GSM379795     4  0.4072     0.6465 0.000 0.000 0.252 0.748
#> GSM379796     4  0.3300     0.7701 0.144 0.000 0.008 0.848
#> GSM379721     3  0.2921     0.7633 0.000 0.000 0.860 0.140
#> GSM379722     3  0.1302     0.7737 0.000 0.000 0.956 0.044
#> GSM379723     3  0.4697     0.5032 0.000 0.000 0.644 0.356
#> GSM379716     4  0.4948     0.0942 0.000 0.000 0.440 0.560
#> GSM379717     3  0.3726     0.7218 0.000 0.000 0.788 0.212
#> GSM379718     3  0.3726     0.7218 0.000 0.000 0.788 0.212
#> GSM379719     3  0.2921     0.7633 0.000 0.000 0.860 0.140
#> GSM379720     3  0.3837     0.7301 0.000 0.000 0.776 0.224
#> GSM379729     3  0.2589     0.7511 0.000 0.000 0.884 0.116
#> GSM379730     3  0.2589     0.7511 0.000 0.000 0.884 0.116
#> GSM379731     3  0.0817     0.7722 0.000 0.000 0.976 0.024
#> GSM379724     3  0.3726     0.7218 0.000 0.000 0.788 0.212
#> GSM379725     3  0.0188     0.7736 0.000 0.000 0.996 0.004
#> GSM379726     3  0.3726     0.7218 0.000 0.000 0.788 0.212
#> GSM379727     3  0.2973     0.7619 0.000 0.000 0.856 0.144
#> GSM379728     3  0.4972     0.2318 0.000 0.000 0.544 0.456
#> GSM379737     3  0.3172     0.7551 0.000 0.000 0.840 0.160
#> GSM379738     3  0.3726     0.7218 0.000 0.000 0.788 0.212
#> GSM379739     3  0.0188     0.7746 0.000 0.000 0.996 0.004
#> GSM379732     3  0.0000     0.7737 0.000 0.000 1.000 0.000
#> GSM379733     3  0.3266     0.7511 0.000 0.000 0.832 0.168
#> GSM379734     3  0.3172     0.7551 0.000 0.000 0.840 0.160
#> GSM379735     3  0.2345     0.7569 0.000 0.000 0.900 0.100
#> GSM379736     4  0.3494     0.7614 0.172 0.000 0.004 0.824
#> GSM379742     2  0.3982     0.6858 0.220 0.776 0.004 0.000
#> GSM379743     3  0.2589     0.7511 0.000 0.000 0.884 0.116
#> GSM379740     3  0.3726     0.7218 0.000 0.000 0.788 0.212
#> GSM379741     3  0.7392     0.1179 0.232 0.248 0.520 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     5  0.3452     0.6381 0.000 0.244 0.000 0.000 0.756
#> GSM379833     5  0.3452     0.6381 0.000 0.244 0.000 0.000 0.756
#> GSM379834     5  0.4060     0.3876 0.000 0.360 0.000 0.000 0.640
#> GSM379827     5  0.0000     0.8761 0.000 0.000 0.000 0.000 1.000
#> GSM379828     5  0.0000     0.8761 0.000 0.000 0.000 0.000 1.000
#> GSM379829     4  0.6512     0.1546 0.000 0.000 0.200 0.452 0.348
#> GSM379830     5  0.0000     0.8761 0.000 0.000 0.000 0.000 1.000
#> GSM379831     5  0.0000     0.8761 0.000 0.000 0.000 0.000 1.000
#> GSM379840     5  0.0000     0.8761 0.000 0.000 0.000 0.000 1.000
#> GSM379841     2  0.3177     0.7702 0.000 0.792 0.000 0.000 0.208
#> GSM379842     2  0.4291     0.3456 0.000 0.536 0.000 0.000 0.464
#> GSM379835     5  0.0000     0.8761 0.000 0.000 0.000 0.000 1.000
#> GSM379836     5  0.0000     0.8761 0.000 0.000 0.000 0.000 1.000
#> GSM379837     5  0.2929     0.6859 0.000 0.000 0.180 0.000 0.820
#> GSM379838     2  0.1270     0.8407 0.000 0.948 0.000 0.000 0.052
#> GSM379839     5  0.2179     0.7560 0.112 0.000 0.000 0.000 0.888
#> GSM379848     2  0.1270     0.8407 0.000 0.948 0.000 0.000 0.052
#> GSM379849     2  0.3177     0.7702 0.000 0.792 0.000 0.000 0.208
#> GSM379850     2  0.3177     0.7702 0.000 0.792 0.000 0.000 0.208
#> GSM379843     5  0.2020     0.8099 0.000 0.100 0.000 0.000 0.900
#> GSM379844     2  0.3177     0.7702 0.000 0.792 0.000 0.000 0.208
#> GSM379845     5  0.0000     0.8761 0.000 0.000 0.000 0.000 1.000
#> GSM379846     2  0.3177     0.7702 0.000 0.792 0.000 0.000 0.208
#> GSM379847     2  0.3177     0.7702 0.000 0.792 0.000 0.000 0.208
#> GSM379853     5  0.0000     0.8761 0.000 0.000 0.000 0.000 1.000
#> GSM379854     2  0.1270     0.8407 0.000 0.948 0.000 0.000 0.052
#> GSM379851     5  0.4126     0.2031 0.000 0.380 0.000 0.000 0.620
#> GSM379852     2  0.3177     0.7702 0.000 0.792 0.000 0.000 0.208
#> GSM379804     1  0.4555     0.3165 0.520 0.000 0.008 0.472 0.000
#> GSM379805     4  0.0290     0.9061 0.000 0.000 0.008 0.992 0.000
#> GSM379806     4  0.0000     0.9108 0.000 0.000 0.000 1.000 0.000
#> GSM379799     4  0.0000     0.9108 0.000 0.000 0.000 1.000 0.000
#> GSM379800     4  0.0000     0.9108 0.000 0.000 0.000 1.000 0.000
#> GSM379801     4  0.0000     0.9108 0.000 0.000 0.000 1.000 0.000
#> GSM379802     4  0.0000     0.9108 0.000 0.000 0.000 1.000 0.000
#> GSM379803     4  0.0290     0.9061 0.000 0.000 0.008 0.992 0.000
#> GSM379812     1  0.1908     0.7574 0.908 0.000 0.092 0.000 0.000
#> GSM379813     1  0.0000     0.8058 1.000 0.000 0.000 0.000 0.000
#> GSM379814     1  0.0290     0.8062 0.992 0.000 0.008 0.000 0.000
#> GSM379807     4  0.2660     0.7726 0.128 0.000 0.008 0.864 0.000
#> GSM379808     4  0.0000     0.9108 0.000 0.000 0.000 1.000 0.000
#> GSM379809     1  0.4030     0.4744 0.648 0.000 0.352 0.000 0.000
#> GSM379810     1  0.4030     0.4744 0.648 0.000 0.352 0.000 0.000
#> GSM379811     4  0.0000     0.9108 0.000 0.000 0.000 1.000 0.000
#> GSM379820     1  0.0290     0.8062 0.992 0.000 0.008 0.000 0.000
#> GSM379821     1  0.0000     0.8058 1.000 0.000 0.000 0.000 0.000
#> GSM379822     1  0.0510     0.8022 0.984 0.000 0.016 0.000 0.000
#> GSM379815     1  0.4166     0.4783 0.648 0.000 0.348 0.004 0.000
#> GSM379816     1  0.2359     0.7624 0.904 0.000 0.060 0.000 0.036
#> GSM379817     1  0.0000     0.8058 1.000 0.000 0.000 0.000 0.000
#> GSM379818     4  0.0000     0.9108 0.000 0.000 0.000 1.000 0.000
#> GSM379819     1  0.4533     0.3420 0.544 0.000 0.008 0.448 0.000
#> GSM379825     4  0.0000     0.9108 0.000 0.000 0.000 1.000 0.000
#> GSM379826     1  0.1671     0.7856 0.924 0.000 0.076 0.000 0.000
#> GSM379823     1  0.0000     0.8058 1.000 0.000 0.000 0.000 0.000
#> GSM379824     1  0.0290     0.8062 0.992 0.000 0.008 0.000 0.000
#> GSM379749     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379750     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379751     5  0.0000     0.8761 0.000 0.000 0.000 0.000 1.000
#> GSM379744     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379745     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379746     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379747     5  0.1270     0.8476 0.000 0.052 0.000 0.000 0.948
#> GSM379748     2  0.4305     0.1626 0.000 0.512 0.000 0.000 0.488
#> GSM379757     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379758     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379752     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379753     5  0.1270     0.8476 0.000 0.052 0.000 0.000 0.948
#> GSM379754     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379755     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379756     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379764     2  0.3730     0.6618 0.000 0.712 0.000 0.000 0.288
#> GSM379765     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379766     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379759     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379760     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379761     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379762     2  0.2690     0.7921 0.000 0.844 0.000 0.000 0.156
#> GSM379763     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379769     2  0.3999     0.5752 0.000 0.656 0.000 0.000 0.344
#> GSM379770     2  0.3561     0.6967 0.000 0.740 0.000 0.000 0.260
#> GSM379767     2  0.0162     0.8599 0.000 0.996 0.000 0.000 0.004
#> GSM379768     2  0.0000     0.8606 0.000 1.000 0.000 0.000 0.000
#> GSM379776     1  0.4392     0.5173 0.612 0.000 0.008 0.380 0.000
#> GSM379777     1  0.2377     0.7938 0.872 0.000 0.000 0.128 0.000
#> GSM379778     1  0.4096     0.7317 0.784 0.000 0.144 0.072 0.000
#> GSM379771     1  0.5977     0.5128 0.540 0.000 0.332 0.128 0.000
#> GSM379772     1  0.5848     0.5718 0.576 0.000 0.296 0.128 0.000
#> GSM379773     1  0.2536     0.7936 0.868 0.000 0.004 0.128 0.000
#> GSM379774     1  0.2536     0.7936 0.868 0.000 0.004 0.128 0.000
#> GSM379775     1  0.5678     0.6185 0.612 0.000 0.260 0.128 0.000
#> GSM379784     1  0.1341     0.8065 0.944 0.000 0.000 0.056 0.000
#> GSM379785     1  0.0162     0.8064 0.996 0.000 0.000 0.004 0.000
#> GSM379786     1  0.0510     0.8022 0.984 0.000 0.016 0.000 0.000
#> GSM379779     1  0.2377     0.7938 0.872 0.000 0.000 0.128 0.000
#> GSM379780     1  0.2377     0.7938 0.872 0.000 0.000 0.128 0.000
#> GSM379781     1  0.0000     0.8058 1.000 0.000 0.000 0.000 0.000
#> GSM379782     1  0.7631     0.0577 0.408 0.232 0.056 0.000 0.304
#> GSM379783     1  0.0000     0.8058 1.000 0.000 0.000 0.000 0.000
#> GSM379792     1  0.4555     0.3165 0.520 0.000 0.008 0.472 0.000
#> GSM379793     1  0.2230     0.7973 0.884 0.000 0.000 0.116 0.000
#> GSM379794     1  0.3532     0.7834 0.824 0.000 0.048 0.128 0.000
#> GSM379787     1  0.6645     0.6167 0.636 0.012 0.116 0.064 0.172
#> GSM379788     1  0.0000     0.8058 1.000 0.000 0.000 0.000 0.000
#> GSM379789     1  0.2377     0.7938 0.872 0.000 0.000 0.128 0.000
#> GSM379790     1  0.2660     0.7930 0.864 0.000 0.008 0.128 0.000
#> GSM379791     1  0.2377     0.7938 0.872 0.000 0.000 0.128 0.000
#> GSM379797     4  0.0000     0.9108 0.000 0.000 0.000 1.000 0.000
#> GSM379798     1  0.3783     0.6981 0.740 0.000 0.008 0.252 0.000
#> GSM379795     1  0.2377     0.7938 0.872 0.000 0.000 0.128 0.000
#> GSM379796     4  0.4291    -0.2057 0.464 0.000 0.000 0.536 0.000
#> GSM379721     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379722     3  0.0290     0.8905 0.008 0.000 0.992 0.000 0.000
#> GSM379723     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379716     3  0.0609     0.8804 0.000 0.000 0.980 0.020 0.000
#> GSM379717     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379718     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379719     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379720     3  0.3480     0.5699 0.248 0.000 0.752 0.000 0.000
#> GSM379729     3  0.4030     0.5187 0.352 0.000 0.648 0.000 0.000
#> GSM379730     3  0.4101     0.4843 0.372 0.000 0.628 0.000 0.000
#> GSM379731     3  0.3177     0.7236 0.208 0.000 0.792 0.000 0.000
#> GSM379724     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379725     3  0.1410     0.8589 0.060 0.000 0.940 0.000 0.000
#> GSM379726     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379727     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379728     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379737     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379738     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379739     3  0.0290     0.8905 0.008 0.000 0.992 0.000 0.000
#> GSM379732     3  0.0290     0.8905 0.008 0.000 0.992 0.000 0.000
#> GSM379733     3  0.1121     0.8611 0.044 0.000 0.956 0.000 0.000
#> GSM379734     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379735     3  0.3932     0.5600 0.328 0.000 0.672 0.000 0.000
#> GSM379736     4  0.0609     0.8963 0.000 0.000 0.020 0.980 0.000
#> GSM379742     2  0.3999     0.5752 0.000 0.656 0.000 0.000 0.344
#> GSM379743     3  0.4060     0.5084 0.360 0.000 0.640 0.000 0.000
#> GSM379740     3  0.0000     0.8935 0.000 0.000 1.000 0.000 0.000
#> GSM379741     2  0.6483     0.2212 0.000 0.452 0.192 0.000 0.356

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     5  0.4653      0.156 0.000 0.052 0.000 0.000 0.588 0.360
#> GSM379833     6  0.4728      0.309 0.000 0.052 0.000 0.000 0.392 0.556
#> GSM379834     6  0.5426      0.556 0.000 0.152 0.000 0.000 0.292 0.556
#> GSM379827     5  0.0000      0.921 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379828     5  0.0000      0.921 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379829     4  0.5959      0.145 0.000 0.000 0.196 0.452 0.348 0.004
#> GSM379830     5  0.0000      0.921 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379831     5  0.0000      0.921 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379840     5  0.0000      0.921 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379841     6  0.4894      0.675 0.000 0.376 0.000 0.000 0.068 0.556
#> GSM379842     6  0.5127      0.677 0.000 0.348 0.000 0.000 0.096 0.556
#> GSM379835     5  0.0000      0.921 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379836     5  0.0000      0.921 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379837     5  0.1151      0.884 0.000 0.000 0.032 0.000 0.956 0.012
#> GSM379838     2  0.3964      0.353 0.000 0.724 0.000 0.000 0.044 0.232
#> GSM379839     5  0.0458      0.908 0.000 0.000 0.000 0.000 0.984 0.016
#> GSM379848     2  0.3989      0.344 0.000 0.720 0.000 0.000 0.044 0.236
#> GSM379849     2  0.4876     -0.210 0.000 0.564 0.000 0.000 0.068 0.368
#> GSM379850     6  0.4894      0.675 0.000 0.376 0.000 0.000 0.068 0.556
#> GSM379843     6  0.4141      0.171 0.000 0.012 0.000 0.000 0.432 0.556
#> GSM379844     6  0.4894      0.675 0.000 0.376 0.000 0.000 0.068 0.556
#> GSM379845     5  0.0000      0.921 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379846     6  0.4894      0.675 0.000 0.376 0.000 0.000 0.068 0.556
#> GSM379847     6  0.4894      0.675 0.000 0.376 0.000 0.000 0.068 0.556
#> GSM379853     5  0.3499      0.460 0.000 0.000 0.000 0.000 0.680 0.320
#> GSM379854     2  0.3989      0.344 0.000 0.720 0.000 0.000 0.044 0.236
#> GSM379851     6  0.5506      0.656 0.000 0.264 0.000 0.000 0.180 0.556
#> GSM379852     6  0.4894      0.675 0.000 0.376 0.000 0.000 0.068 0.556
#> GSM379804     1  0.4503      0.350 0.560 0.000 0.008 0.412 0.000 0.020
#> GSM379805     4  0.0405      0.898 0.000 0.000 0.008 0.988 0.000 0.004
#> GSM379806     4  0.0000      0.905 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379799     4  0.0000      0.905 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379800     4  0.0000      0.905 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379801     4  0.0000      0.905 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379802     4  0.0000      0.905 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379803     4  0.0405      0.898 0.000 0.000 0.008 0.988 0.000 0.004
#> GSM379812     1  0.3998      0.720 0.712 0.000 0.040 0.000 0.000 0.248
#> GSM379813     1  0.2793      0.760 0.800 0.000 0.000 0.000 0.000 0.200
#> GSM379814     1  0.3043      0.760 0.792 0.000 0.008 0.000 0.000 0.200
#> GSM379807     4  0.3121      0.737 0.004 0.000 0.008 0.796 0.000 0.192
#> GSM379808     4  0.0000      0.905 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379809     1  0.5173      0.554 0.596 0.000 0.276 0.000 0.000 0.128
#> GSM379810     1  0.5723      0.495 0.508 0.000 0.292 0.000 0.000 0.200
#> GSM379811     4  0.0000      0.905 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379820     1  0.3043      0.760 0.792 0.000 0.008 0.000 0.000 0.200
#> GSM379821     1  0.3221      0.735 0.736 0.000 0.000 0.000 0.000 0.264
#> GSM379822     1  0.3817      0.588 0.568 0.000 0.000 0.000 0.000 0.432
#> GSM379815     1  0.5849      0.502 0.508 0.000 0.284 0.004 0.000 0.204
#> GSM379816     1  0.5238      0.500 0.492 0.000 0.016 0.000 0.056 0.436
#> GSM379817     1  0.2793      0.760 0.800 0.000 0.000 0.000 0.000 0.200
#> GSM379818     4  0.0000      0.905 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379819     1  0.5878      0.506 0.524 0.000 0.008 0.264 0.000 0.204
#> GSM379825     4  0.0000      0.905 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379826     1  0.4195      0.737 0.724 0.000 0.076 0.000 0.000 0.200
#> GSM379823     1  0.3797      0.602 0.580 0.000 0.000 0.000 0.000 0.420
#> GSM379824     1  0.3245      0.752 0.764 0.000 0.008 0.000 0.000 0.228
#> GSM379749     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379750     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379751     5  0.0000      0.921 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM379744     2  0.0146      0.792 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM379745     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379746     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379747     5  0.1007      0.879 0.000 0.044 0.000 0.000 0.956 0.000
#> GSM379748     2  0.5832     -0.193 0.000 0.428 0.000 0.000 0.384 0.188
#> GSM379757     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379758     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379752     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379753     5  0.1007      0.879 0.000 0.044 0.000 0.000 0.956 0.000
#> GSM379754     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379755     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379756     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379764     2  0.4219      0.111 0.000 0.648 0.000 0.000 0.032 0.320
#> GSM379765     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379766     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379759     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379760     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379761     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379762     2  0.4094      0.116 0.000 0.652 0.000 0.000 0.024 0.324
#> GSM379763     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379769     2  0.4332      0.104 0.000 0.644 0.000 0.000 0.040 0.316
#> GSM379770     2  0.4094      0.116 0.000 0.652 0.000 0.000 0.024 0.324
#> GSM379767     2  0.2003      0.660 0.000 0.884 0.000 0.000 0.000 0.116
#> GSM379768     2  0.0000      0.796 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379776     1  0.3463      0.617 0.748 0.000 0.008 0.240 0.000 0.004
#> GSM379777     1  0.2632      0.776 0.832 0.000 0.000 0.004 0.000 0.164
#> GSM379778     1  0.1594      0.778 0.932 0.000 0.052 0.000 0.000 0.016
#> GSM379771     1  0.3452      0.606 0.736 0.000 0.256 0.004 0.000 0.004
#> GSM379772     1  0.3215      0.630 0.756 0.000 0.240 0.004 0.000 0.000
#> GSM379773     1  0.0291      0.799 0.992 0.000 0.004 0.004 0.000 0.000
#> GSM379774     1  0.0291      0.799 0.992 0.000 0.004 0.004 0.000 0.000
#> GSM379775     1  0.3248      0.647 0.768 0.000 0.224 0.004 0.000 0.004
#> GSM379784     1  0.0000      0.799 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379785     1  0.0000      0.799 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379786     1  0.1957      0.757 0.888 0.000 0.000 0.000 0.000 0.112
#> GSM379779     1  0.0291      0.799 0.992 0.000 0.000 0.004 0.000 0.004
#> GSM379780     1  0.0146      0.799 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM379781     1  0.0000      0.799 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379782     1  0.6386      0.301 0.480 0.020 0.004 0.000 0.248 0.248
#> GSM379783     1  0.2823      0.681 0.796 0.000 0.000 0.000 0.000 0.204
#> GSM379792     1  0.3583      0.585 0.728 0.000 0.008 0.260 0.000 0.004
#> GSM379793     1  0.0146      0.799 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM379794     1  0.1296      0.788 0.948 0.000 0.044 0.004 0.000 0.004
#> GSM379787     1  0.4307      0.675 0.760 0.004 0.016 0.000 0.144 0.076
#> GSM379788     1  0.0000      0.799 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM379789     1  0.0146      0.799 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM379790     1  0.0551      0.798 0.984 0.000 0.008 0.004 0.000 0.004
#> GSM379791     1  0.0146      0.799 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM379797     4  0.0000      0.905 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM379798     1  0.2488      0.738 0.864 0.000 0.008 0.124 0.000 0.004
#> GSM379795     1  0.0146      0.799 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM379796     4  0.3999     -0.178 0.496 0.000 0.000 0.500 0.000 0.004
#> GSM379721     3  0.1501      0.818 0.000 0.000 0.924 0.000 0.000 0.076
#> GSM379722     3  0.0891      0.834 0.008 0.000 0.968 0.000 0.000 0.024
#> GSM379723     3  0.0000      0.838 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379716     3  0.0146      0.837 0.000 0.000 0.996 0.004 0.000 0.000
#> GSM379717     3  0.0000      0.838 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379718     3  0.0000      0.838 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379719     3  0.0547      0.836 0.000 0.000 0.980 0.000 0.000 0.020
#> GSM379720     3  0.3876      0.506 0.276 0.000 0.700 0.000 0.000 0.024
#> GSM379729     3  0.5826      0.467 0.272 0.000 0.492 0.000 0.000 0.236
#> GSM379730     3  0.5897      0.438 0.280 0.000 0.472 0.000 0.000 0.248
#> GSM379731     3  0.5501      0.572 0.200 0.000 0.564 0.000 0.000 0.236
#> GSM379724     3  0.0000      0.838 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379725     3  0.4223      0.712 0.060 0.000 0.704 0.000 0.000 0.236
#> GSM379726     3  0.0000      0.838 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379727     3  0.0000      0.838 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379728     3  0.0000      0.838 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379737     3  0.1863      0.773 0.104 0.000 0.896 0.000 0.000 0.000
#> GSM379738     3  0.0260      0.836 0.008 0.000 0.992 0.000 0.000 0.000
#> GSM379739     3  0.0260      0.837 0.008 0.000 0.992 0.000 0.000 0.000
#> GSM379732     3  0.3298      0.739 0.008 0.000 0.756 0.000 0.000 0.236
#> GSM379733     3  0.2048      0.752 0.120 0.000 0.880 0.000 0.000 0.000
#> GSM379734     3  0.0000      0.838 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM379735     3  0.5798      0.479 0.264 0.000 0.500 0.000 0.000 0.236
#> GSM379736     4  0.0547      0.890 0.000 0.000 0.020 0.980 0.000 0.000
#> GSM379742     6  0.4534      0.165 0.000 0.472 0.000 0.000 0.032 0.496
#> GSM379743     3  0.5914      0.437 0.272 0.000 0.468 0.000 0.000 0.260
#> GSM379740     3  0.0146      0.838 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM379741     6  0.5782      0.247 0.000 0.396 0.068 0.000 0.044 0.492

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-ATC-pam-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-ATC-pam-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-ATC-pam-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-ATC-pam-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-ATC-pam-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-ATC-pam-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-ATC-pam-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-ATC-pam-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-ATC-pam-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-ATC-pam-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-ATC-pam-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-ATC-pam-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-ATC-pam-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-ATC-pam-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-ATC-pam-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds

plot of chunk tab-ATC-pam-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-ATC-pam-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-ATC-pam-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-ATC-pam-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-ATC-pam-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk ATC-pam-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-ATC-pam-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-ATC-pam-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-ATC-pam-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-ATC-pam-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-ATC-pam-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk ATC-pam-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>           n individual(p) time(p) agent(p) k
#> ATC:pam 138      1.06e-24   1.000   0.7797 2
#> ATC:pam 130      8.26e-34   0.996   0.2431 3
#> ATC:pam 128      4.83e-41   0.998   0.0614 4
#> ATC:pam 124      5.19e-54   1.000   0.0418 5
#> ATC:pam 115      1.29e-59   1.000   0.1464 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

ATC:mclust**

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["ATC", "mclust"]
# you can also extract it by
# res = res_list["ATC:mclust"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#>   Subgroups are detected by 'mclust' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 2.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk ATC-mclust-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk ATC-mclust-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           1.000       1.000         0.4822 0.518   0.518
#> 3 3 0.771           0.837       0.903         0.2295 0.930   0.864
#> 4 4 0.640           0.660       0.801         0.1474 0.876   0.745
#> 5 5 0.636           0.638       0.752         0.0777 0.825   0.580
#> 6 6 0.706           0.696       0.820         0.0436 0.960   0.849

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 2

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette p1 p2
#> GSM379832     2       0          1  0  1
#> GSM379833     2       0          1  0  1
#> GSM379834     2       0          1  0  1
#> GSM379827     2       0          1  0  1
#> GSM379828     2       0          1  0  1
#> GSM379829     2       0          1  0  1
#> GSM379830     2       0          1  0  1
#> GSM379831     2       0          1  0  1
#> GSM379840     2       0          1  0  1
#> GSM379841     2       0          1  0  1
#> GSM379842     2       0          1  0  1
#> GSM379835     2       0          1  0  1
#> GSM379836     2       0          1  0  1
#> GSM379837     2       0          1  0  1
#> GSM379838     2       0          1  0  1
#> GSM379839     2       0          1  0  1
#> GSM379848     2       0          1  0  1
#> GSM379849     2       0          1  0  1
#> GSM379850     2       0          1  0  1
#> GSM379843     2       0          1  0  1
#> GSM379844     2       0          1  0  1
#> GSM379845     2       0          1  0  1
#> GSM379846     2       0          1  0  1
#> GSM379847     2       0          1  0  1
#> GSM379853     2       0          1  0  1
#> GSM379854     2       0          1  0  1
#> GSM379851     2       0          1  0  1
#> GSM379852     2       0          1  0  1
#> GSM379804     1       0          1  1  0
#> GSM379805     1       0          1  1  0
#> GSM379806     1       0          1  1  0
#> GSM379799     1       0          1  1  0
#> GSM379800     1       0          1  1  0
#> GSM379801     1       0          1  1  0
#> GSM379802     1       0          1  1  0
#> GSM379803     1       0          1  1  0
#> GSM379812     1       0          1  1  0
#> GSM379813     1       0          1  1  0
#> GSM379814     1       0          1  1  0
#> GSM379807     1       0          1  1  0
#> GSM379808     1       0          1  1  0
#> GSM379809     1       0          1  1  0
#> GSM379810     1       0          1  1  0
#> GSM379811     1       0          1  1  0
#> GSM379820     1       0          1  1  0
#> GSM379821     1       0          1  1  0
#> GSM379822     1       0          1  1  0
#> GSM379815     1       0          1  1  0
#> GSM379816     1       0          1  1  0
#> GSM379817     1       0          1  1  0
#> GSM379818     1       0          1  1  0
#> GSM379819     1       0          1  1  0
#> GSM379825     1       0          1  1  0
#> GSM379826     1       0          1  1  0
#> GSM379823     1       0          1  1  0
#> GSM379824     1       0          1  1  0
#> GSM379749     2       0          1  0  1
#> GSM379750     2       0          1  0  1
#> GSM379751     2       0          1  0  1
#> GSM379744     2       0          1  0  1
#> GSM379745     2       0          1  0  1
#> GSM379746     2       0          1  0  1
#> GSM379747     2       0          1  0  1
#> GSM379748     2       0          1  0  1
#> GSM379757     2       0          1  0  1
#> GSM379758     2       0          1  0  1
#> GSM379752     2       0          1  0  1
#> GSM379753     2       0          1  0  1
#> GSM379754     2       0          1  0  1
#> GSM379755     2       0          1  0  1
#> GSM379756     2       0          1  0  1
#> GSM379764     2       0          1  0  1
#> GSM379765     2       0          1  0  1
#> GSM379766     2       0          1  0  1
#> GSM379759     2       0          1  0  1
#> GSM379760     2       0          1  0  1
#> GSM379761     2       0          1  0  1
#> GSM379762     2       0          1  0  1
#> GSM379763     2       0          1  0  1
#> GSM379769     2       0          1  0  1
#> GSM379770     2       0          1  0  1
#> GSM379767     2       0          1  0  1
#> GSM379768     2       0          1  0  1
#> GSM379776     1       0          1  1  0
#> GSM379777     1       0          1  1  0
#> GSM379778     1       0          1  1  0
#> GSM379771     1       0          1  1  0
#> GSM379772     1       0          1  1  0
#> GSM379773     1       0          1  1  0
#> GSM379774     1       0          1  1  0
#> GSM379775     1       0          1  1  0
#> GSM379784     1       0          1  1  0
#> GSM379785     1       0          1  1  0
#> GSM379786     1       0          1  1  0
#> GSM379779     1       0          1  1  0
#> GSM379780     1       0          1  1  0
#> GSM379781     1       0          1  1  0
#> GSM379782     1       0          1  1  0
#> GSM379783     1       0          1  1  0
#> GSM379792     1       0          1  1  0
#> GSM379793     1       0          1  1  0
#> GSM379794     1       0          1  1  0
#> GSM379787     1       0          1  1  0
#> GSM379788     1       0          1  1  0
#> GSM379789     1       0          1  1  0
#> GSM379790     1       0          1  1  0
#> GSM379791     1       0          1  1  0
#> GSM379797     1       0          1  1  0
#> GSM379798     1       0          1  1  0
#> GSM379795     1       0          1  1  0
#> GSM379796     1       0          1  1  0
#> GSM379721     1       0          1  1  0
#> GSM379722     1       0          1  1  0
#> GSM379723     1       0          1  1  0
#> GSM379716     1       0          1  1  0
#> GSM379717     1       0          1  1  0
#> GSM379718     1       0          1  1  0
#> GSM379719     1       0          1  1  0
#> GSM379720     1       0          1  1  0
#> GSM379729     1       0          1  1  0
#> GSM379730     1       0          1  1  0
#> GSM379731     1       0          1  1  0
#> GSM379724     1       0          1  1  0
#> GSM379725     1       0          1  1  0
#> GSM379726     1       0          1  1  0
#> GSM379727     1       0          1  1  0
#> GSM379728     1       0          1  1  0
#> GSM379737     1       0          1  1  0
#> GSM379738     1       0          1  1  0
#> GSM379739     1       0          1  1  0
#> GSM379732     1       0          1  1  0
#> GSM379733     1       0          1  1  0
#> GSM379734     1       0          1  1  0
#> GSM379735     1       0          1  1  0
#> GSM379736     1       0          1  1  0
#> GSM379742     1       0          1  1  0
#> GSM379743     1       0          1  1  0
#> GSM379740     1       0          1  1  0
#> GSM379741     1       0          1  1  0

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379833     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379834     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379827     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379828     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379829     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379830     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379831     2  0.0237      0.994 0.000 0.996 0.004
#> GSM379840     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379841     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379842     2  0.0237      0.994 0.000 0.996 0.004
#> GSM379835     2  0.0237      0.994 0.000 0.996 0.004
#> GSM379836     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379837     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379838     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379839     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379848     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379849     2  0.0592      0.992 0.000 0.988 0.012
#> GSM379850     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379843     2  0.0592      0.992 0.000 0.988 0.012
#> GSM379844     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379845     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379846     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379847     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379853     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379854     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379851     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379852     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379804     1  0.0000      0.823 1.000 0.000 0.000
#> GSM379805     1  0.6235      0.145 0.564 0.000 0.436
#> GSM379806     3  0.5497      0.878 0.292 0.000 0.708
#> GSM379799     3  0.4399      0.913 0.188 0.000 0.812
#> GSM379800     3  0.4399      0.913 0.188 0.000 0.812
#> GSM379801     3  0.4452      0.914 0.192 0.000 0.808
#> GSM379802     3  0.5178      0.917 0.256 0.000 0.744
#> GSM379803     1  0.6140      0.454 0.596 0.000 0.404
#> GSM379812     1  0.3941      0.749 0.844 0.000 0.156
#> GSM379813     1  0.2448      0.799 0.924 0.000 0.076
#> GSM379814     1  0.1411      0.816 0.964 0.000 0.036
#> GSM379807     1  0.1031      0.819 0.976 0.000 0.024
#> GSM379808     3  0.5178      0.917 0.256 0.000 0.744
#> GSM379809     1  0.4931      0.655 0.768 0.000 0.232
#> GSM379810     1  0.2537      0.801 0.920 0.000 0.080
#> GSM379811     3  0.5397      0.822 0.280 0.000 0.720
#> GSM379820     1  0.4178      0.726 0.828 0.000 0.172
#> GSM379821     1  0.5810      0.590 0.664 0.000 0.336
#> GSM379822     1  0.5810      0.590 0.664 0.000 0.336
#> GSM379815     1  0.3619      0.760 0.864 0.000 0.136
#> GSM379816     1  0.5968      0.543 0.636 0.000 0.364
#> GSM379817     1  0.3752      0.746 0.856 0.000 0.144
#> GSM379818     3  0.5216      0.914 0.260 0.000 0.740
#> GSM379819     1  0.1411      0.816 0.964 0.000 0.036
#> GSM379825     3  0.4399      0.913 0.188 0.000 0.812
#> GSM379826     1  0.4605      0.679 0.796 0.000 0.204
#> GSM379823     1  0.5810      0.590 0.664 0.000 0.336
#> GSM379824     1  0.5810      0.590 0.664 0.000 0.336
#> GSM379749     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379750     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379751     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379744     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379745     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379746     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379747     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379748     2  0.0237      0.994 0.000 0.996 0.004
#> GSM379757     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379758     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379752     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379753     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379754     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379755     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379756     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379764     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379765     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379766     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379759     2  0.0592      0.992 0.000 0.988 0.012
#> GSM379760     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379761     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379762     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379763     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379769     2  0.0747      0.991 0.000 0.984 0.016
#> GSM379770     2  0.0592      0.992 0.000 0.988 0.012
#> GSM379767     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379768     2  0.0000      0.995 0.000 1.000 0.000
#> GSM379776     1  0.0747      0.821 0.984 0.000 0.016
#> GSM379777     1  0.5810      0.590 0.664 0.000 0.336
#> GSM379778     1  0.4178      0.726 0.828 0.000 0.172
#> GSM379771     1  0.0592      0.824 0.988 0.000 0.012
#> GSM379772     1  0.1163      0.821 0.972 0.000 0.028
#> GSM379773     1  0.2878      0.786 0.904 0.000 0.096
#> GSM379774     1  0.1031      0.818 0.976 0.000 0.024
#> GSM379775     1  0.1964      0.804 0.944 0.000 0.056
#> GSM379784     1  0.3686      0.754 0.860 0.000 0.140
#> GSM379785     1  0.3551      0.757 0.868 0.000 0.132
#> GSM379786     1  0.5810      0.590 0.664 0.000 0.336
#> GSM379779     1  0.0000      0.823 1.000 0.000 0.000
#> GSM379780     1  0.0000      0.823 1.000 0.000 0.000
#> GSM379781     1  0.1964      0.808 0.944 0.000 0.056
#> GSM379782     1  0.5988      0.398 0.632 0.000 0.368
#> GSM379783     1  0.5810      0.590 0.664 0.000 0.336
#> GSM379792     1  0.5465      0.566 0.712 0.000 0.288
#> GSM379793     1  0.2878      0.792 0.904 0.000 0.096
#> GSM379794     1  0.2625      0.791 0.916 0.000 0.084
#> GSM379787     1  0.5988      0.398 0.632 0.000 0.368
#> GSM379788     1  0.5810      0.590 0.664 0.000 0.336
#> GSM379789     1  0.0000      0.823 1.000 0.000 0.000
#> GSM379790     1  0.0237      0.823 0.996 0.000 0.004
#> GSM379791     1  0.0000      0.823 1.000 0.000 0.000
#> GSM379797     1  0.6299     -0.408 0.524 0.000 0.476
#> GSM379798     1  0.0424      0.823 0.992 0.000 0.008
#> GSM379795     1  0.0000      0.823 1.000 0.000 0.000
#> GSM379796     1  0.1163      0.817 0.972 0.000 0.028
#> GSM379721     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379722     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379723     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379716     1  0.0892      0.823 0.980 0.000 0.020
#> GSM379717     1  0.0892      0.823 0.980 0.000 0.020
#> GSM379718     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379719     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379720     1  0.0237      0.824 0.996 0.000 0.004
#> GSM379729     1  0.3619      0.754 0.864 0.000 0.136
#> GSM379730     1  0.3619      0.754 0.864 0.000 0.136
#> GSM379731     1  0.5733      0.606 0.676 0.000 0.324
#> GSM379724     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379725     1  0.3619      0.754 0.864 0.000 0.136
#> GSM379726     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379727     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379728     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379737     1  0.1163      0.821 0.972 0.000 0.028
#> GSM379738     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379739     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379732     1  0.1753      0.815 0.952 0.000 0.048
#> GSM379733     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379734     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379735     1  0.3619      0.754 0.864 0.000 0.136
#> GSM379736     1  0.1031      0.823 0.976 0.000 0.024
#> GSM379742     1  0.5988      0.398 0.632 0.000 0.368
#> GSM379743     1  0.3619      0.754 0.864 0.000 0.136
#> GSM379740     1  0.1289      0.820 0.968 0.000 0.032
#> GSM379741     1  0.5988      0.398 0.632 0.000 0.368

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette p1    p2    p3    p4
#> GSM379832     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379833     2  0.1211    0.89089 NA 0.960 0.000 0.000
#> GSM379834     2  0.0188    0.89469 NA 0.996 0.000 0.000
#> GSM379827     2  0.5172    0.80224 NA 0.704 0.000 0.036
#> GSM379828     2  0.4225    0.84316 NA 0.792 0.000 0.024
#> GSM379829     2  0.5951    0.76321 NA 0.636 0.000 0.064
#> GSM379830     2  0.5883    0.76597 NA 0.640 0.000 0.060
#> GSM379831     2  0.2149    0.88243 NA 0.912 0.000 0.000
#> GSM379840     2  0.5951    0.76321 NA 0.636 0.000 0.064
#> GSM379841     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379842     2  0.1867    0.88604 NA 0.928 0.000 0.000
#> GSM379835     2  0.2216    0.88146 NA 0.908 0.000 0.000
#> GSM379836     2  0.5951    0.76321 NA 0.636 0.000 0.064
#> GSM379837     2  0.5951    0.76321 NA 0.636 0.000 0.064
#> GSM379838     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379839     2  0.5951    0.76321 NA 0.636 0.000 0.064
#> GSM379848     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379849     2  0.3616    0.86308 NA 0.852 0.000 0.036
#> GSM379850     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379843     2  0.3674    0.86195 NA 0.848 0.000 0.036
#> GSM379844     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379845     2  0.5951    0.76321 NA 0.636 0.000 0.064
#> GSM379846     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379847     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379853     2  0.5522    0.78243 NA 0.668 0.000 0.044
#> GSM379854     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379851     2  0.4679    0.83450 NA 0.772 0.000 0.044
#> GSM379852     2  0.1302    0.89079 NA 0.956 0.000 0.000
#> GSM379804     3  0.0000    0.65287 NA 0.000 1.000 0.000
#> GSM379805     3  0.5649    0.34196 NA 0.000 0.664 0.284
#> GSM379806     3  0.5861    0.29941 NA 0.000 0.644 0.296
#> GSM379799     3  0.6942    0.19569 NA 0.000 0.584 0.240
#> GSM379800     3  0.6967    0.18666 NA 0.000 0.580 0.244
#> GSM379801     3  0.6942    0.21450 NA 0.000 0.584 0.240
#> GSM379802     4  0.6844    0.59297 NA 0.000 0.260 0.588
#> GSM379803     4  0.3105    0.78262 NA 0.000 0.120 0.868
#> GSM379812     4  0.4406    0.64827 NA 0.000 0.300 0.700
#> GSM379813     3  0.2973    0.56806 NA 0.000 0.856 0.144
#> GSM379814     3  0.1022    0.64504 NA 0.000 0.968 0.032
#> GSM379807     3  0.0921    0.64653 NA 0.000 0.972 0.028
#> GSM379808     3  0.6609    0.26255 NA 0.000 0.620 0.236
#> GSM379809     3  0.3300    0.57812 NA 0.000 0.848 0.144
#> GSM379810     3  0.1890    0.63718 NA 0.000 0.936 0.056
#> GSM379811     4  0.6788    0.59197 NA 0.000 0.264 0.592
#> GSM379820     3  0.3444    0.51607 NA 0.000 0.816 0.184
#> GSM379821     4  0.3074    0.80423 NA 0.000 0.152 0.848
#> GSM379822     4  0.3074    0.80423 NA 0.000 0.152 0.848
#> GSM379815     3  0.2999    0.58557 NA 0.000 0.864 0.132
#> GSM379816     4  0.4149    0.77583 NA 0.000 0.152 0.812
#> GSM379817     4  0.5000    0.27447 NA 0.000 0.496 0.504
#> GSM379818     4  0.6828    0.59007 NA 0.000 0.264 0.588
#> GSM379819     3  0.1211    0.64214 NA 0.000 0.960 0.040
#> GSM379825     4  0.6916    0.60334 NA 0.000 0.236 0.588
#> GSM379826     4  0.5000    0.26166 NA 0.000 0.500 0.500
#> GSM379823     4  0.3123    0.80386 NA 0.000 0.156 0.844
#> GSM379824     4  0.3074    0.80423 NA 0.000 0.152 0.848
#> GSM379749     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379750     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379751     2  0.5883    0.76597 NA 0.640 0.000 0.060
#> GSM379744     2  0.1302    0.88973 NA 0.956 0.000 0.000
#> GSM379745     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379746     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379747     2  0.5883    0.76597 NA 0.640 0.000 0.060
#> GSM379748     2  0.2011    0.88429 NA 0.920 0.000 0.000
#> GSM379757     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379758     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379752     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379753     2  0.5883    0.76597 NA 0.640 0.000 0.060
#> GSM379754     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379755     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379756     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379764     2  0.5883    0.76597 NA 0.640 0.000 0.060
#> GSM379765     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379766     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379759     2  0.3616    0.86308 NA 0.852 0.000 0.036
#> GSM379760     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379761     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379762     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379763     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379769     2  0.5883    0.76597 NA 0.640 0.000 0.060
#> GSM379770     2  0.4053    0.83404 NA 0.768 0.000 0.004
#> GSM379767     2  0.1118    0.89168 NA 0.964 0.000 0.000
#> GSM379768     2  0.0000    0.89496 NA 1.000 0.000 0.000
#> GSM379776     3  0.0000    0.65287 NA 0.000 1.000 0.000
#> GSM379777     4  0.3074    0.80423 NA 0.000 0.152 0.848
#> GSM379778     3  0.3182    0.61417 NA 0.000 0.876 0.096
#> GSM379771     3  0.3444    0.58719 NA 0.000 0.816 0.000
#> GSM379772     3  0.4585    0.50286 NA 0.000 0.668 0.000
#> GSM379773     3  0.1022    0.64774 NA 0.000 0.968 0.032
#> GSM379774     3  0.0000    0.65287 NA 0.000 1.000 0.000
#> GSM379775     3  0.0672    0.65278 NA 0.000 0.984 0.008
#> GSM379784     3  0.4585    0.24579 NA 0.000 0.668 0.332
#> GSM379785     3  0.3074    0.54889 NA 0.000 0.848 0.152
#> GSM379786     4  0.3123    0.80386 NA 0.000 0.156 0.844
#> GSM379779     3  0.0000    0.65287 NA 0.000 1.000 0.000
#> GSM379780     3  0.0188    0.65239 NA 0.000 0.996 0.004
#> GSM379781     3  0.1716    0.62664 NA 0.000 0.936 0.064
#> GSM379782     3  0.5817    0.39027 NA 0.000 0.676 0.248
#> GSM379783     4  0.3219    0.79943 NA 0.000 0.164 0.836
#> GSM379792     3  0.4610    0.44437 NA 0.000 0.744 0.236
#> GSM379793     3  0.1902    0.63293 NA 0.000 0.932 0.064
#> GSM379794     3  0.0927    0.65239 NA 0.000 0.976 0.016
#> GSM379787     3  0.5817    0.39027 NA 0.000 0.676 0.248
#> GSM379788     4  0.3123    0.80386 NA 0.000 0.156 0.844
#> GSM379789     3  0.0000    0.65287 NA 0.000 1.000 0.000
#> GSM379790     3  0.0188    0.65246 NA 0.000 0.996 0.004
#> GSM379791     3  0.0000    0.65287 NA 0.000 1.000 0.000
#> GSM379797     3  0.5855    0.40386 NA 0.000 0.692 0.208
#> GSM379798     3  0.0000    0.65287 NA 0.000 1.000 0.000
#> GSM379795     3  0.0188    0.65267 NA 0.000 0.996 0.000
#> GSM379796     3  0.0336    0.65274 NA 0.000 0.992 0.008
#> GSM379721     3  0.4977    0.42115 NA 0.000 0.540 0.000
#> GSM379722     3  0.4977    0.42115 NA 0.000 0.540 0.000
#> GSM379723     3  0.4977    0.42115 NA 0.000 0.540 0.000
#> GSM379716     3  0.4977    0.42115 NA 0.000 0.540 0.000
#> GSM379717     3  0.4972    0.42304 NA 0.000 0.544 0.000
#> GSM379718     3  0.4977    0.42115 NA 0.000 0.540 0.000
#> GSM379719     3  0.4977    0.42115 NA 0.000 0.540 0.000
#> GSM379720     3  0.0000    0.65287 NA 0.000 1.000 0.000
#> GSM379729     3  0.3266    0.50858 NA 0.000 0.832 0.168
#> GSM379730     3  0.4277    0.34731 NA 0.000 0.720 0.280
#> GSM379731     3  0.4925    0.00246 NA 0.000 0.572 0.428
#> GSM379724     3  0.4977    0.42115 NA 0.000 0.540 0.000
#> GSM379725     3  0.3356    0.49656 NA 0.000 0.824 0.176
#> GSM379726     3  0.4977    0.42115 NA 0.000 0.540 0.000
#> GSM379727     3  0.4977    0.42115 NA 0.000 0.540 0.000
#> GSM379728     3  0.4977    0.42115 NA 0.000 0.540 0.000
#> GSM379737     3  0.4008    0.55476 NA 0.000 0.756 0.000
#> GSM379738     3  0.4977    0.42115 NA 0.000 0.540 0.000
#> GSM379739     3  0.4790    0.47279 NA 0.000 0.620 0.000
#> GSM379732     3  0.1716    0.62969 NA 0.000 0.936 0.064
#> GSM379733     3  0.4454    0.51792 NA 0.000 0.692 0.000
#> GSM379734     3  0.4977    0.42115 NA 0.000 0.540 0.000
#> GSM379735     3  0.3569    0.47241 NA 0.000 0.804 0.196
#> GSM379736     3  0.4961    0.42637 NA 0.000 0.552 0.000
#> GSM379742     3  0.5845    0.38436 NA 0.000 0.672 0.252
#> GSM379743     3  0.3610    0.46836 NA 0.000 0.800 0.200
#> GSM379740     3  0.4961    0.42967 NA 0.000 0.552 0.000
#> GSM379741     3  0.5817    0.39027 NA 0.000 0.676 0.248

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     2  0.0510     0.8073 0.000 0.984 0.000 0.000 0.016
#> GSM379833     2  0.0404     0.8095 0.000 0.988 0.000 0.000 0.012
#> GSM379834     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379827     2  0.3966    -0.0683 0.000 0.664 0.000 0.000 0.336
#> GSM379828     2  0.3837     0.0982 0.000 0.692 0.000 0.000 0.308
#> GSM379829     5  0.5048     0.8946 0.000 0.380 0.040 0.000 0.580
#> GSM379830     2  0.4307    -0.7826 0.000 0.500 0.000 0.000 0.500
#> GSM379831     2  0.2189     0.7269 0.000 0.904 0.012 0.000 0.084
#> GSM379840     5  0.4798     0.9052 0.000 0.396 0.024 0.000 0.580
#> GSM379841     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379842     2  0.0794     0.7996 0.000 0.972 0.000 0.000 0.028
#> GSM379835     2  0.2069     0.7362 0.000 0.912 0.012 0.000 0.076
#> GSM379836     5  0.4731     0.8638 0.000 0.456 0.016 0.000 0.528
#> GSM379837     5  0.5048     0.8946 0.000 0.380 0.040 0.000 0.580
#> GSM379838     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379839     5  0.5125     0.8892 0.000 0.416 0.040 0.000 0.544
#> GSM379848     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379849     2  0.2690     0.5936 0.000 0.844 0.000 0.000 0.156
#> GSM379850     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379843     2  0.2732     0.5837 0.000 0.840 0.000 0.000 0.160
#> GSM379844     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379845     5  0.4403     0.8939 0.000 0.436 0.004 0.000 0.560
#> GSM379846     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379847     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379853     2  0.3837     0.0759 0.000 0.692 0.000 0.000 0.308
#> GSM379854     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379851     2  0.3480     0.3185 0.000 0.752 0.000 0.000 0.248
#> GSM379852     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379804     1  0.2891     0.7358 0.824 0.000 0.176 0.000 0.000
#> GSM379805     1  0.6376    -0.0158 0.452 0.000 0.116 0.420 0.012
#> GSM379806     4  0.5739     0.4031 0.308 0.000 0.088 0.596 0.008
#> GSM379799     4  0.5471     0.4897 0.176 0.000 0.084 0.704 0.036
#> GSM379800     4  0.5452     0.4904 0.180 0.000 0.080 0.704 0.036
#> GSM379801     4  0.5476     0.4724 0.108 0.000 0.152 0.708 0.032
#> GSM379802     4  0.4275     0.5690 0.104 0.000 0.076 0.800 0.020
#> GSM379803     4  0.6100     0.6512 0.152 0.000 0.000 0.540 0.308
#> GSM379812     4  0.7725     0.4939 0.260 0.000 0.060 0.396 0.284
#> GSM379813     1  0.4393     0.7192 0.772 0.000 0.136 0.088 0.004
#> GSM379814     1  0.3720     0.7251 0.760 0.000 0.228 0.012 0.000
#> GSM379807     1  0.3488     0.7402 0.808 0.000 0.168 0.024 0.000
#> GSM379808     4  0.5482     0.4453 0.224 0.000 0.088 0.672 0.016
#> GSM379809     1  0.4113     0.6889 0.740 0.000 0.232 0.028 0.000
#> GSM379810     1  0.3910     0.6698 0.720 0.000 0.272 0.008 0.000
#> GSM379811     4  0.5052     0.5639 0.136 0.000 0.076 0.748 0.040
#> GSM379820     1  0.3888     0.6947 0.804 0.000 0.120 0.076 0.000
#> GSM379821     4  0.6422     0.6453 0.180 0.000 0.000 0.460 0.360
#> GSM379822     4  0.6422     0.6453 0.180 0.000 0.000 0.460 0.360
#> GSM379815     1  0.4402     0.6997 0.740 0.000 0.204 0.056 0.000
#> GSM379816     4  0.7661     0.5891 0.244 0.000 0.064 0.432 0.260
#> GSM379817     1  0.7394    -0.2213 0.492 0.000 0.064 0.248 0.196
#> GSM379818     4  0.4398     0.5724 0.100 0.000 0.076 0.796 0.028
#> GSM379819     1  0.3359     0.7409 0.816 0.000 0.164 0.020 0.000
#> GSM379825     4  0.3928     0.5646 0.092 0.000 0.084 0.816 0.008
#> GSM379826     1  0.7804    -0.1117 0.464 0.000 0.108 0.224 0.204
#> GSM379823     4  0.6626     0.6331 0.224 0.000 0.000 0.424 0.352
#> GSM379824     4  0.6422     0.6453 0.180 0.000 0.000 0.460 0.360
#> GSM379749     2  0.0290     0.8114 0.000 0.992 0.000 0.000 0.008
#> GSM379750     2  0.0703     0.8015 0.000 0.976 0.000 0.000 0.024
#> GSM379751     5  0.4304     0.7980 0.000 0.484 0.000 0.000 0.516
#> GSM379744     2  0.1671     0.7543 0.000 0.924 0.000 0.000 0.076
#> GSM379745     2  0.0703     0.8015 0.000 0.976 0.000 0.000 0.024
#> GSM379746     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379747     2  0.4300    -0.7053 0.000 0.524 0.000 0.000 0.476
#> GSM379748     2  0.1410     0.7671 0.000 0.940 0.000 0.000 0.060
#> GSM379757     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379758     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379752     2  0.0609     0.8046 0.000 0.980 0.000 0.000 0.020
#> GSM379753     2  0.4300    -0.7053 0.000 0.524 0.000 0.000 0.476
#> GSM379754     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379755     2  0.0290     0.8114 0.000 0.992 0.000 0.000 0.008
#> GSM379756     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379764     2  0.4210    -0.5248 0.000 0.588 0.000 0.000 0.412
#> GSM379765     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379766     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379759     2  0.3003     0.5171 0.000 0.812 0.000 0.000 0.188
#> GSM379760     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379761     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379762     2  0.0404     0.8084 0.000 0.988 0.000 0.000 0.012
#> GSM379763     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379769     2  0.4210    -0.5248 0.000 0.588 0.000 0.000 0.412
#> GSM379770     2  0.3424     0.3929 0.000 0.760 0.000 0.000 0.240
#> GSM379767     2  0.1965     0.7134 0.000 0.904 0.000 0.000 0.096
#> GSM379768     2  0.0000     0.8144 0.000 1.000 0.000 0.000 0.000
#> GSM379776     1  0.2813     0.7352 0.832 0.000 0.168 0.000 0.000
#> GSM379777     4  0.6422     0.6453 0.180 0.000 0.000 0.460 0.360
#> GSM379778     1  0.5740     0.5847 0.580 0.000 0.308 0.112 0.000
#> GSM379771     3  0.3857     0.5970 0.312 0.000 0.688 0.000 0.000
#> GSM379772     3  0.3242     0.8085 0.216 0.000 0.784 0.000 0.000
#> GSM379773     1  0.3807     0.7124 0.748 0.000 0.240 0.012 0.000
#> GSM379774     1  0.3395     0.7169 0.764 0.000 0.236 0.000 0.000
#> GSM379775     1  0.3857     0.6421 0.688 0.000 0.312 0.000 0.000
#> GSM379784     1  0.5109     0.5912 0.720 0.000 0.060 0.192 0.028
#> GSM379785     1  0.3291     0.6885 0.848 0.000 0.064 0.088 0.000
#> GSM379786     4  0.6615     0.6349 0.220 0.000 0.000 0.424 0.356
#> GSM379779     1  0.3177     0.7276 0.792 0.000 0.208 0.000 0.000
#> GSM379780     1  0.2966     0.7364 0.816 0.000 0.184 0.000 0.000
#> GSM379781     1  0.3033     0.7179 0.864 0.000 0.084 0.052 0.000
#> GSM379782     1  0.7041     0.3022 0.464 0.000 0.268 0.248 0.020
#> GSM379783     4  0.6923     0.6217 0.220 0.000 0.012 0.436 0.332
#> GSM379792     1  0.4437     0.6463 0.760 0.000 0.100 0.140 0.000
#> GSM379793     1  0.4536     0.7130 0.712 0.000 0.240 0.048 0.000
#> GSM379794     1  0.3636     0.6864 0.728 0.000 0.272 0.000 0.000
#> GSM379787     1  0.7149     0.2377 0.424 0.000 0.308 0.248 0.020
#> GSM379788     4  0.6734     0.6191 0.264 0.000 0.000 0.404 0.332
#> GSM379789     1  0.2891     0.7361 0.824 0.000 0.176 0.000 0.000
#> GSM379790     1  0.2813     0.7352 0.832 0.000 0.168 0.000 0.000
#> GSM379791     1  0.3242     0.7292 0.784 0.000 0.216 0.000 0.000
#> GSM379797     1  0.5751     0.3413 0.540 0.000 0.096 0.364 0.000
#> GSM379798     1  0.2891     0.7358 0.824 0.000 0.176 0.000 0.000
#> GSM379795     1  0.3857     0.6440 0.688 0.000 0.312 0.000 0.000
#> GSM379796     1  0.3010     0.7359 0.824 0.000 0.172 0.004 0.000
#> GSM379721     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379722     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379723     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379716     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379717     3  0.2127     0.9412 0.108 0.000 0.892 0.000 0.000
#> GSM379718     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379719     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379720     1  0.2891     0.7325 0.824 0.000 0.176 0.000 0.000
#> GSM379729     1  0.3970     0.6768 0.812 0.000 0.076 0.104 0.008
#> GSM379730     1  0.4378     0.6443 0.792 0.000 0.064 0.120 0.024
#> GSM379731     1  0.4712     0.3148 0.684 0.000 0.000 0.268 0.048
#> GSM379724     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379725     1  0.4248     0.6839 0.792 0.000 0.096 0.104 0.008
#> GSM379726     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379727     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379728     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379737     3  0.3796     0.6347 0.300 0.000 0.700 0.000 0.000
#> GSM379738     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379739     3  0.2516     0.9140 0.140 0.000 0.860 0.000 0.000
#> GSM379732     1  0.3011     0.7462 0.844 0.000 0.140 0.016 0.000
#> GSM379733     3  0.3196     0.8455 0.192 0.000 0.804 0.004 0.000
#> GSM379734     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379735     1  0.3787     0.6739 0.824 0.000 0.064 0.104 0.008
#> GSM379736     3  0.2179     0.9408 0.100 0.000 0.896 0.004 0.000
#> GSM379742     1  0.7122     0.2598 0.436 0.000 0.296 0.248 0.020
#> GSM379743     1  0.3849     0.6743 0.820 0.000 0.068 0.104 0.008
#> GSM379740     3  0.2074     0.9463 0.104 0.000 0.896 0.000 0.000
#> GSM379741     1  0.7113     0.2667 0.440 0.000 0.292 0.248 0.020

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379833     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379834     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379827     2  0.3309     0.4689 0.000 0.720 0.000 0.000 0.280 0.000
#> GSM379828     2  0.3531     0.3279 0.000 0.672 0.000 0.000 0.328 0.000
#> GSM379829     5  0.2762     0.8193 0.000 0.196 0.000 0.000 0.804 0.000
#> GSM379830     2  0.3869    -0.4464 0.000 0.500 0.000 0.000 0.500 0.000
#> GSM379831     2  0.3607     0.2480 0.000 0.652 0.000 0.000 0.348 0.000
#> GSM379840     5  0.3101     0.8275 0.000 0.244 0.000 0.000 0.756 0.000
#> GSM379841     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379842     2  0.0260     0.8438 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379835     2  0.3547     0.3011 0.000 0.668 0.000 0.000 0.332 0.000
#> GSM379836     5  0.3782     0.6578 0.000 0.412 0.000 0.000 0.588 0.000
#> GSM379837     5  0.2762     0.8193 0.000 0.196 0.000 0.000 0.804 0.000
#> GSM379838     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379839     5  0.2941     0.8195 0.000 0.220 0.000 0.000 0.780 0.000
#> GSM379848     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379849     2  0.1141     0.8114 0.000 0.948 0.000 0.000 0.052 0.000
#> GSM379850     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379843     2  0.1387     0.7993 0.000 0.932 0.000 0.000 0.068 0.000
#> GSM379844     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379845     5  0.3592     0.7660 0.000 0.344 0.000 0.000 0.656 0.000
#> GSM379846     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379847     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379853     2  0.3607     0.2340 0.000 0.652 0.000 0.000 0.348 0.000
#> GSM379854     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379851     2  0.1863     0.7657 0.000 0.896 0.000 0.000 0.104 0.000
#> GSM379852     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379804     1  0.1444     0.7998 0.928 0.000 0.000 0.072 0.000 0.000
#> GSM379805     4  0.3309     0.6838 0.192 0.000 0.004 0.788 0.000 0.016
#> GSM379806     4  0.1391     0.9080 0.040 0.000 0.000 0.944 0.000 0.016
#> GSM379799     4  0.0603     0.9220 0.016 0.000 0.000 0.980 0.000 0.004
#> GSM379800     4  0.0603     0.9220 0.016 0.000 0.000 0.980 0.000 0.004
#> GSM379801     4  0.2872     0.8031 0.076 0.000 0.052 0.864 0.000 0.008
#> GSM379802     4  0.1088     0.9217 0.016 0.000 0.000 0.960 0.000 0.024
#> GSM379803     6  0.3428     0.4080 0.000 0.000 0.000 0.304 0.000 0.696
#> GSM379812     6  0.4089     0.7793 0.264 0.000 0.000 0.040 0.000 0.696
#> GSM379813     1  0.2795     0.7100 0.856 0.000 0.000 0.044 0.000 0.100
#> GSM379814     1  0.2195     0.7819 0.904 0.000 0.068 0.016 0.000 0.012
#> GSM379807     1  0.1910     0.7868 0.892 0.000 0.000 0.108 0.000 0.000
#> GSM379808     4  0.0713     0.9203 0.028 0.000 0.000 0.972 0.000 0.000
#> GSM379809     1  0.3407     0.6782 0.800 0.000 0.168 0.016 0.000 0.016
#> GSM379810     1  0.3782     0.5999 0.752 0.000 0.216 0.016 0.000 0.016
#> GSM379811     4  0.1320     0.9177 0.016 0.000 0.000 0.948 0.000 0.036
#> GSM379820     1  0.2575     0.7828 0.872 0.000 0.004 0.100 0.000 0.024
#> GSM379821     6  0.1007     0.7617 0.000 0.000 0.000 0.044 0.000 0.956
#> GSM379822     6  0.1007     0.7617 0.000 0.000 0.000 0.044 0.000 0.956
#> GSM379815     1  0.3039     0.7827 0.860 0.000 0.068 0.052 0.000 0.020
#> GSM379816     6  0.4671     0.7702 0.264 0.000 0.024 0.040 0.000 0.672
#> GSM379817     1  0.4700    -0.2386 0.500 0.000 0.000 0.044 0.000 0.456
#> GSM379818     4  0.1245     0.9194 0.016 0.000 0.000 0.952 0.000 0.032
#> GSM379819     1  0.1663     0.7960 0.912 0.000 0.000 0.088 0.000 0.000
#> GSM379825     4  0.0891     0.9196 0.008 0.000 0.000 0.968 0.000 0.024
#> GSM379826     1  0.5268     0.1271 0.532 0.000 0.000 0.108 0.000 0.360
#> GSM379823     6  0.3738     0.8117 0.208 0.000 0.000 0.040 0.000 0.752
#> GSM379824     6  0.1007     0.7617 0.000 0.000 0.000 0.044 0.000 0.956
#> GSM379749     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379750     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379751     5  0.3810     0.6172 0.000 0.428 0.000 0.000 0.572 0.000
#> GSM379744     2  0.2178     0.7297 0.000 0.868 0.000 0.000 0.132 0.000
#> GSM379745     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379746     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379747     2  0.3797    -0.1087 0.000 0.580 0.000 0.000 0.420 0.000
#> GSM379748     2  0.2260     0.7174 0.000 0.860 0.000 0.000 0.140 0.000
#> GSM379757     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379758     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379752     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379753     2  0.3782    -0.0700 0.000 0.588 0.000 0.000 0.412 0.000
#> GSM379754     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379755     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379756     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379764     2  0.3782    -0.0700 0.000 0.588 0.000 0.000 0.412 0.000
#> GSM379765     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379766     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379759     2  0.2597     0.6674 0.000 0.824 0.000 0.000 0.176 0.000
#> GSM379760     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379761     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379762     2  0.0260     0.8434 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379763     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379769     2  0.3782    -0.0700 0.000 0.588 0.000 0.000 0.412 0.000
#> GSM379770     2  0.2793     0.6292 0.000 0.800 0.000 0.000 0.200 0.000
#> GSM379767     2  0.1957     0.7560 0.000 0.888 0.000 0.000 0.112 0.000
#> GSM379768     2  0.0000     0.8484 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM379776     1  0.1444     0.7998 0.928 0.000 0.000 0.072 0.000 0.000
#> GSM379777     6  0.1007     0.7617 0.000 0.000 0.000 0.044 0.000 0.956
#> GSM379778     1  0.4685     0.3887 0.568 0.000 0.388 0.004 0.000 0.040
#> GSM379771     3  0.3607     0.6256 0.348 0.000 0.652 0.000 0.000 0.000
#> GSM379772     3  0.3330     0.7137 0.284 0.000 0.716 0.000 0.000 0.000
#> GSM379773     1  0.2890     0.7333 0.848 0.000 0.124 0.012 0.000 0.016
#> GSM379774     1  0.2375     0.7825 0.896 0.000 0.068 0.020 0.000 0.016
#> GSM379775     1  0.4058     0.5051 0.708 0.000 0.260 0.016 0.000 0.016
#> GSM379784     1  0.2553     0.7012 0.848 0.000 0.000 0.008 0.000 0.144
#> GSM379785     1  0.2346     0.7158 0.868 0.000 0.000 0.008 0.000 0.124
#> GSM379786     6  0.3709     0.8118 0.204 0.000 0.000 0.040 0.000 0.756
#> GSM379779     1  0.1531     0.8002 0.928 0.000 0.004 0.068 0.000 0.000
#> GSM379780     1  0.0146     0.7921 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM379781     1  0.2257     0.7203 0.876 0.000 0.000 0.008 0.000 0.116
#> GSM379782     3  0.6970     0.0639 0.328 0.000 0.408 0.004 0.196 0.064
#> GSM379783     6  0.3794     0.8093 0.216 0.000 0.000 0.040 0.000 0.744
#> GSM379792     1  0.4167     0.4498 0.612 0.000 0.000 0.368 0.000 0.020
#> GSM379793     1  0.2570     0.7796 0.884 0.000 0.076 0.016 0.000 0.024
#> GSM379794     1  0.3542     0.6545 0.784 0.000 0.184 0.016 0.000 0.016
#> GSM379787     3  0.7059     0.0611 0.324 0.000 0.408 0.008 0.196 0.064
#> GSM379788     6  0.3975     0.7899 0.244 0.000 0.000 0.040 0.000 0.716
#> GSM379789     1  0.1444     0.7998 0.928 0.000 0.000 0.072 0.000 0.000
#> GSM379790     1  0.1444     0.7998 0.928 0.000 0.000 0.072 0.000 0.000
#> GSM379791     1  0.1686     0.7806 0.924 0.000 0.064 0.012 0.000 0.000
#> GSM379797     1  0.4076     0.3041 0.540 0.000 0.000 0.452 0.000 0.008
#> GSM379798     1  0.1444     0.7998 0.928 0.000 0.000 0.072 0.000 0.000
#> GSM379795     1  0.3320     0.6000 0.772 0.000 0.212 0.016 0.000 0.000
#> GSM379796     1  0.1556     0.7994 0.920 0.000 0.000 0.080 0.000 0.000
#> GSM379721     3  0.2135     0.8269 0.128 0.000 0.872 0.000 0.000 0.000
#> GSM379722     3  0.2135     0.8269 0.128 0.000 0.872 0.000 0.000 0.000
#> GSM379723     3  0.2135     0.8269 0.128 0.000 0.872 0.000 0.000 0.000
#> GSM379716     3  0.2135     0.8269 0.128 0.000 0.872 0.000 0.000 0.000
#> GSM379717     3  0.2404     0.8138 0.112 0.000 0.872 0.000 0.000 0.016
#> GSM379718     3  0.2135     0.8269 0.128 0.000 0.872 0.000 0.000 0.000
#> GSM379719     3  0.2135     0.8269 0.128 0.000 0.872 0.000 0.000 0.000
#> GSM379720     1  0.1802     0.7979 0.916 0.000 0.000 0.072 0.000 0.012
#> GSM379729     1  0.2588     0.7142 0.860 0.000 0.004 0.012 0.000 0.124
#> GSM379730     1  0.2402     0.7074 0.856 0.000 0.000 0.004 0.000 0.140
#> GSM379731     1  0.3455     0.6408 0.784 0.000 0.000 0.036 0.000 0.180
#> GSM379724     3  0.2357     0.8175 0.116 0.000 0.872 0.000 0.000 0.012
#> GSM379725     1  0.2588     0.7142 0.860 0.000 0.004 0.012 0.000 0.124
#> GSM379726     3  0.2178     0.8239 0.132 0.000 0.868 0.000 0.000 0.000
#> GSM379727     3  0.2135     0.8269 0.128 0.000 0.872 0.000 0.000 0.000
#> GSM379728     3  0.2135     0.8269 0.128 0.000 0.872 0.000 0.000 0.000
#> GSM379737     3  0.3647     0.6043 0.360 0.000 0.640 0.000 0.000 0.000
#> GSM379738     3  0.2135     0.8269 0.128 0.000 0.872 0.000 0.000 0.000
#> GSM379739     3  0.2969     0.7743 0.224 0.000 0.776 0.000 0.000 0.000
#> GSM379732     1  0.2400     0.7279 0.872 0.000 0.004 0.008 0.000 0.116
#> GSM379733     3  0.3076     0.7615 0.240 0.000 0.760 0.000 0.000 0.000
#> GSM379734     3  0.2135     0.8269 0.128 0.000 0.872 0.000 0.000 0.000
#> GSM379735     1  0.2446     0.7139 0.864 0.000 0.000 0.012 0.000 0.124
#> GSM379736     3  0.2135     0.8269 0.128 0.000 0.872 0.000 0.000 0.000
#> GSM379742     3  0.6970     0.0639 0.328 0.000 0.408 0.004 0.196 0.064
#> GSM379743     1  0.2446     0.7139 0.864 0.000 0.000 0.012 0.000 0.124
#> GSM379740     3  0.2135     0.8269 0.128 0.000 0.872 0.000 0.000 0.000
#> GSM379741     3  0.6970     0.0639 0.328 0.000 0.408 0.004 0.196 0.064

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-ATC-mclust-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-ATC-mclust-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-ATC-mclust-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-ATC-mclust-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-ATC-mclust-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-ATC-mclust-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-ATC-mclust-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-ATC-mclust-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-ATC-mclust-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-ATC-mclust-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-ATC-mclust-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-ATC-mclust-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-ATC-mclust-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-ATC-mclust-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-ATC-mclust-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-ATC-mclust-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-ATC-mclust-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-ATC-mclust-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-ATC-mclust-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-ATC-mclust-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk ATC-mclust-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-ATC-mclust-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-ATC-mclust-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-ATC-mclust-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-ATC-mclust-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-ATC-mclust-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk ATC-mclust-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>              n individual(p) time(p) agent(p) k
#> ATC:mclust 139      4.62e-29   1.000   1.0000 2
#> ATC:mclust 132      7.80e-32   1.000   0.1633 3
#> ATC:mclust 103      6.10e-23   1.000   0.7818 4
#> ATC:mclust 114      7.16e-34   0.958   0.3577 5
#> ATC:mclust 119      1.88e-36   0.975   0.0379 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

ATC:NMF*

The object with results only for a single top-value method and a single partition method can be extracted as:

res = res_list["ATC", "NMF"]
# you can also extract it by
# res = res_list["ATC:NMF"]

A summary of res and all the functions that can be applied to it:

res

#> A 'ConsensusPartition' object with k = 2, 3, 4, 5, 6.
#>   On a matrix with 21074 rows and 139 columns.
#>   Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#>   Subgroups are detected by 'NMF' method.
#>   Performed in total 1250 partitions by row resampling.
#>   Best k for subgroups seems to be 5.
#> 
#> Following methods can be applied to this 'ConsensusPartition' object:
#>  [1] "cola_report"             "collect_classes"         "collect_plots"          
#>  [4] "collect_stats"           "colnames"                "compare_signatures"     
#>  [7] "consensus_heatmap"       "dimension_reduction"     "functional_enrichment"  
#> [10] "get_anno_col"            "get_anno"                "get_classes"            
#> [13] "get_consensus"           "get_matrix"              "get_membership"         
#> [16] "get_param"               "get_signatures"          "get_stats"              
#> [19] "is_best_k"               "is_stable_k"             "membership_heatmap"     
#> [22] "ncol"                    "nrow"                    "plot_ecdf"              
#> [25] "rownames"                "select_partition_number" "show"                   
#> [28] "suggest_best_k"          "test_to_known_factors"

collect_plots() function collects all the plots made from res for all k (number of partitions) into one single page to provide an easy and fast comparison between different k.

collect_plots(res)

plot of chunk ATC-NMF-collect-plots

The plots are:

All the plots in panels can be made by individual functions and they are plotted later in this section.

select_partition_number() produces several plots showing different statistics for choosing “optimized” k. There are following statistics:

The detailed explanations of these statistics can be found in the cola vignette.

Generally speaking, lower PAC score, higher mean silhouette score or higher concordance corresponds to better partition. Rand index and Jaccard index measure how similar the current partition is compared to partition with k-1. If they are too similar, we won't accept k is better than k-1.

select_partition_number(res)

plot of chunk ATC-NMF-select-partition-number

The numeric values for all these statistics can be obtained by get_stats().

get_stats(res)

#>   k 1-PAC mean_silhouette concordance area_increased  Rand Jaccard
#> 2 2 1.000           0.964       0.985         0.4948 0.504   0.504
#> 3 3 0.773           0.843       0.921         0.3214 0.754   0.546
#> 4 4 0.823           0.841       0.911         0.1156 0.876   0.658
#> 5 5 0.908           0.873       0.926         0.0475 0.932   0.761
#> 6 6 0.815           0.710       0.852         0.0371 0.985   0.939

suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:

suggest_best_k(res)

#> [1] 5
#> attr(,"optional")
#> [1] 2

There is also optional best \(k\) = 2 that is worth to check.

Following shows the table of the partitions (You need to click the show/hide code output link to see it). The membership matrix (columns with name p*) is inferred by clue::cl_consensus() function with the SE method. Basically the value in the membership matrix represents the probability to belong to a certain group. The finall class label for an item is determined with the group with highest probability it belongs to.

In get_classes() function, the entropy is calculated from the membership matrix and the silhouette score is calculated from the consensus matrix.

show/hide code output

cbind(get_classes(res, k = 2), get_membership(res, k = 2))

#>           class entropy silhouette    p1    p2
#> GSM379832     2  0.0000      0.977 0.000 1.000
#> GSM379833     2  0.0000      0.977 0.000 1.000
#> GSM379834     2  0.0000      0.977 0.000 1.000
#> GSM379827     2  0.0000      0.977 0.000 1.000
#> GSM379828     2  0.0000      0.977 0.000 1.000
#> GSM379829     1  0.0000      0.991 1.000 0.000
#> GSM379830     2  0.0000      0.977 0.000 1.000
#> GSM379831     2  0.0000      0.977 0.000 1.000
#> GSM379840     2  0.0000      0.977 0.000 1.000
#> GSM379841     2  0.0000      0.977 0.000 1.000
#> GSM379842     2  0.0000      0.977 0.000 1.000
#> GSM379835     2  0.0000      0.977 0.000 1.000
#> GSM379836     2  0.0000      0.977 0.000 1.000
#> GSM379837     2  0.9944      0.172 0.456 0.544
#> GSM379838     2  0.0000      0.977 0.000 1.000
#> GSM379839     2  0.7950      0.684 0.240 0.760
#> GSM379848     2  0.0000      0.977 0.000 1.000
#> GSM379849     2  0.0000      0.977 0.000 1.000
#> GSM379850     2  0.0000      0.977 0.000 1.000
#> GSM379843     2  0.0000      0.977 0.000 1.000
#> GSM379844     2  0.0000      0.977 0.000 1.000
#> GSM379845     2  0.0000      0.977 0.000 1.000
#> GSM379846     2  0.0000      0.977 0.000 1.000
#> GSM379847     2  0.0000      0.977 0.000 1.000
#> GSM379853     2  0.0000      0.977 0.000 1.000
#> GSM379854     2  0.0000      0.977 0.000 1.000
#> GSM379851     2  0.0000      0.977 0.000 1.000
#> GSM379852     2  0.0000      0.977 0.000 1.000
#> GSM379804     1  0.0000      0.991 1.000 0.000
#> GSM379805     1  0.0000      0.991 1.000 0.000
#> GSM379806     1  0.0000      0.991 1.000 0.000
#> GSM379799     1  0.0000      0.991 1.000 0.000
#> GSM379800     1  0.0000      0.991 1.000 0.000
#> GSM379801     1  0.0000      0.991 1.000 0.000
#> GSM379802     1  0.0000      0.991 1.000 0.000
#> GSM379803     1  0.0000      0.991 1.000 0.000
#> GSM379812     1  0.0000      0.991 1.000 0.000
#> GSM379813     1  0.0000      0.991 1.000 0.000
#> GSM379814     1  0.0000      0.991 1.000 0.000
#> GSM379807     1  0.0000      0.991 1.000 0.000
#> GSM379808     1  0.0000      0.991 1.000 0.000
#> GSM379809     1  0.0000      0.991 1.000 0.000
#> GSM379810     1  0.0000      0.991 1.000 0.000
#> GSM379811     1  0.0000      0.991 1.000 0.000
#> GSM379820     1  0.0000      0.991 1.000 0.000
#> GSM379821     1  0.0000      0.991 1.000 0.000
#> GSM379822     1  0.0000      0.991 1.000 0.000
#> GSM379815     1  0.0000      0.991 1.000 0.000
#> GSM379816     2  0.4939      0.868 0.108 0.892
#> GSM379817     1  0.0000      0.991 1.000 0.000
#> GSM379818     1  0.0000      0.991 1.000 0.000
#> GSM379819     1  0.0000      0.991 1.000 0.000
#> GSM379825     1  0.0000      0.991 1.000 0.000
#> GSM379826     1  0.0000      0.991 1.000 0.000
#> GSM379823     1  0.0376      0.987 0.996 0.004
#> GSM379824     1  0.0000      0.991 1.000 0.000
#> GSM379749     2  0.0000      0.977 0.000 1.000
#> GSM379750     2  0.0000      0.977 0.000 1.000
#> GSM379751     2  0.0000      0.977 0.000 1.000
#> GSM379744     2  0.0000      0.977 0.000 1.000
#> GSM379745     2  0.0000      0.977 0.000 1.000
#> GSM379746     2  0.0000      0.977 0.000 1.000
#> GSM379747     2  0.0000      0.977 0.000 1.000
#> GSM379748     2  0.0000      0.977 0.000 1.000
#> GSM379757     2  0.0000      0.977 0.000 1.000
#> GSM379758     2  0.0000      0.977 0.000 1.000
#> GSM379752     2  0.0000      0.977 0.000 1.000
#> GSM379753     2  0.0000      0.977 0.000 1.000
#> GSM379754     2  0.0000      0.977 0.000 1.000
#> GSM379755     2  0.0000      0.977 0.000 1.000
#> GSM379756     2  0.0000      0.977 0.000 1.000
#> GSM379764     2  0.0000      0.977 0.000 1.000
#> GSM379765     2  0.0000      0.977 0.000 1.000
#> GSM379766     2  0.0000      0.977 0.000 1.000
#> GSM379759     2  0.0000      0.977 0.000 1.000
#> GSM379760     2  0.0000      0.977 0.000 1.000
#> GSM379761     2  0.0000      0.977 0.000 1.000
#> GSM379762     2  0.0000      0.977 0.000 1.000
#> GSM379763     2  0.0000      0.977 0.000 1.000
#> GSM379769     2  0.0000      0.977 0.000 1.000
#> GSM379770     2  0.0000      0.977 0.000 1.000
#> GSM379767     2  0.0000      0.977 0.000 1.000
#> GSM379768     2  0.0000      0.977 0.000 1.000
#> GSM379776     1  0.0000      0.991 1.000 0.000
#> GSM379777     1  0.0000      0.991 1.000 0.000
#> GSM379778     2  0.4161      0.895 0.084 0.916
#> GSM379771     1  0.0000      0.991 1.000 0.000
#> GSM379772     1  0.0000      0.991 1.000 0.000
#> GSM379773     1  0.0000      0.991 1.000 0.000
#> GSM379774     1  0.0000      0.991 1.000 0.000
#> GSM379775     1  0.0000      0.991 1.000 0.000
#> GSM379784     1  0.0000      0.991 1.000 0.000
#> GSM379785     1  0.0000      0.991 1.000 0.000
#> GSM379786     1  0.7674      0.709 0.776 0.224
#> GSM379779     1  0.0000      0.991 1.000 0.000
#> GSM379780     1  0.0000      0.991 1.000 0.000
#> GSM379781     1  0.0000      0.991 1.000 0.000
#> GSM379782     2  0.0000      0.977 0.000 1.000
#> GSM379783     2  0.9896      0.225 0.440 0.560
#> GSM379792     1  0.0000      0.991 1.000 0.000
#> GSM379793     1  0.0000      0.991 1.000 0.000
#> GSM379794     1  0.0000      0.991 1.000 0.000
#> GSM379787     2  0.0000      0.977 0.000 1.000
#> GSM379788     1  0.0000      0.991 1.000 0.000
#> GSM379789     1  0.0000      0.991 1.000 0.000
#> GSM379790     1  0.0000      0.991 1.000 0.000
#> GSM379791     1  0.0000      0.991 1.000 0.000
#> GSM379797     1  0.0000      0.991 1.000 0.000
#> GSM379798     1  0.0000      0.991 1.000 0.000
#> GSM379795     1  0.0000      0.991 1.000 0.000
#> GSM379796     1  0.0000      0.991 1.000 0.000
#> GSM379721     1  0.0000      0.991 1.000 0.000
#> GSM379722     1  0.0000      0.991 1.000 0.000
#> GSM379723     1  0.0000      0.991 1.000 0.000
#> GSM379716     1  0.0000      0.991 1.000 0.000
#> GSM379717     1  0.0000      0.991 1.000 0.000
#> GSM379718     1  0.0000      0.991 1.000 0.000
#> GSM379719     1  0.0000      0.991 1.000 0.000
#> GSM379720     1  0.0000      0.991 1.000 0.000
#> GSM379729     1  0.7950      0.681 0.760 0.240
#> GSM379730     1  0.3879      0.913 0.924 0.076
#> GSM379731     1  0.0000      0.991 1.000 0.000
#> GSM379724     1  0.0000      0.991 1.000 0.000
#> GSM379725     1  0.0376      0.987 0.996 0.004
#> GSM379726     1  0.0000      0.991 1.000 0.000
#> GSM379727     1  0.0000      0.991 1.000 0.000
#> GSM379728     1  0.0000      0.991 1.000 0.000
#> GSM379737     1  0.0000      0.991 1.000 0.000
#> GSM379738     1  0.0000      0.991 1.000 0.000
#> GSM379739     1  0.0000      0.991 1.000 0.000
#> GSM379732     1  0.0000      0.991 1.000 0.000
#> GSM379733     1  0.0000      0.991 1.000 0.000
#> GSM379734     1  0.0000      0.991 1.000 0.000
#> GSM379735     1  0.0376      0.987 0.996 0.004
#> GSM379736     1  0.0000      0.991 1.000 0.000
#> GSM379742     2  0.0000      0.977 0.000 1.000
#> GSM379743     1  0.5737      0.839 0.864 0.136
#> GSM379740     1  0.0000      0.991 1.000 0.000
#> GSM379741     2  0.0000      0.977 0.000 1.000

show/hide code output

cbind(get_classes(res, k = 3), get_membership(res, k = 3))

#>           class entropy silhouette    p1    p2    p3
#> GSM379832     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379833     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379834     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379827     2  0.0592      0.982 0.012 0.988 0.000
#> GSM379828     2  0.0892      0.977 0.020 0.980 0.000
#> GSM379829     1  0.0000      0.801 1.000 0.000 0.000
#> GSM379830     2  0.1031      0.975 0.024 0.976 0.000
#> GSM379831     2  0.1289      0.969 0.032 0.968 0.000
#> GSM379840     2  0.4002      0.847 0.160 0.840 0.000
#> GSM379841     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379842     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379835     2  0.1411      0.966 0.036 0.964 0.000
#> GSM379836     2  0.3482      0.883 0.128 0.872 0.000
#> GSM379837     1  0.5254      0.500 0.736 0.264 0.000
#> GSM379838     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379839     1  0.6168      0.117 0.588 0.412 0.000
#> GSM379848     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379849     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379850     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379843     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379844     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379845     2  0.3038      0.906 0.104 0.896 0.000
#> GSM379846     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379847     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379853     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379854     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379851     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379852     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379804     1  0.3267      0.819 0.884 0.000 0.116
#> GSM379805     1  0.1964      0.825 0.944 0.000 0.056
#> GSM379806     1  0.1753      0.823 0.952 0.000 0.048
#> GSM379799     1  0.0592      0.809 0.988 0.000 0.012
#> GSM379800     1  0.0592      0.809 0.988 0.000 0.012
#> GSM379801     1  0.0000      0.801 1.000 0.000 0.000
#> GSM379802     1  0.1031      0.815 0.976 0.000 0.024
#> GSM379803     1  0.3267      0.820 0.884 0.000 0.116
#> GSM379812     3  0.0000      0.894 0.000 0.000 1.000
#> GSM379813     3  0.0592      0.894 0.012 0.000 0.988
#> GSM379814     3  0.4452      0.735 0.192 0.000 0.808
#> GSM379807     1  0.3816      0.802 0.852 0.000 0.148
#> GSM379808     1  0.1289      0.818 0.968 0.000 0.032
#> GSM379809     1  0.2878      0.825 0.904 0.000 0.096
#> GSM379810     1  0.5835      0.592 0.660 0.000 0.340
#> GSM379811     1  0.2261      0.827 0.932 0.000 0.068
#> GSM379820     1  0.6126      0.472 0.600 0.000 0.400
#> GSM379821     3  0.0237      0.895 0.004 0.000 0.996
#> GSM379822     3  0.0000      0.894 0.000 0.000 1.000
#> GSM379815     1  0.2878      0.825 0.904 0.000 0.096
#> GSM379816     3  0.0747      0.883 0.000 0.016 0.984
#> GSM379817     3  0.2066      0.870 0.060 0.000 0.940
#> GSM379818     1  0.1411      0.820 0.964 0.000 0.036
#> GSM379819     1  0.4235      0.783 0.824 0.000 0.176
#> GSM379825     1  0.0592      0.809 0.988 0.000 0.012
#> GSM379826     1  0.5988      0.544 0.632 0.000 0.368
#> GSM379823     3  0.0000      0.894 0.000 0.000 1.000
#> GSM379824     3  0.6180      0.158 0.416 0.000 0.584
#> GSM379749     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379750     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379751     2  0.2448      0.933 0.076 0.924 0.000
#> GSM379744     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379745     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379746     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379747     2  0.0237      0.987 0.004 0.996 0.000
#> GSM379748     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379757     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379758     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379752     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379753     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379754     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379755     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379756     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379764     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379765     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379766     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379759     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379760     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379761     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379762     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379763     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379769     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379770     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379767     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379768     2  0.0000      0.990 0.000 1.000 0.000
#> GSM379776     1  0.5926      0.566 0.644 0.000 0.356
#> GSM379777     3  0.2537      0.856 0.080 0.000 0.920
#> GSM379778     3  0.0892      0.879 0.000 0.020 0.980
#> GSM379771     1  0.5835      0.592 0.660 0.000 0.340
#> GSM379772     3  0.6026      0.333 0.376 0.000 0.624
#> GSM379773     3  0.0424      0.895 0.008 0.000 0.992
#> GSM379774     3  0.6126      0.250 0.400 0.000 0.600
#> GSM379775     1  0.5733      0.616 0.676 0.000 0.324
#> GSM379784     3  0.0000      0.894 0.000 0.000 1.000
#> GSM379785     3  0.0237      0.895 0.004 0.000 0.996
#> GSM379786     3  0.0237      0.892 0.000 0.004 0.996
#> GSM379779     3  0.3619      0.807 0.136 0.000 0.864
#> GSM379780     3  0.0424      0.895 0.008 0.000 0.992
#> GSM379781     3  0.0237      0.895 0.004 0.000 0.996
#> GSM379782     3  0.2448      0.822 0.000 0.076 0.924
#> GSM379783     3  0.0237      0.892 0.000 0.004 0.996
#> GSM379792     1  0.2796      0.825 0.908 0.000 0.092
#> GSM379793     3  0.4235      0.757 0.176 0.000 0.824
#> GSM379794     3  0.6062      0.307 0.384 0.000 0.616
#> GSM379787     3  0.3116      0.792 0.000 0.108 0.892
#> GSM379788     3  0.0000      0.894 0.000 0.000 1.000
#> GSM379789     3  0.3816      0.793 0.148 0.000 0.852
#> GSM379790     1  0.6307      0.192 0.512 0.000 0.488
#> GSM379791     3  0.0424      0.895 0.008 0.000 0.992
#> GSM379797     1  0.2356      0.827 0.928 0.000 0.072
#> GSM379798     1  0.6008      0.533 0.628 0.000 0.372
#> GSM379795     3  0.0424      0.895 0.008 0.000 0.992
#> GSM379796     1  0.3879      0.800 0.848 0.000 0.152
#> GSM379721     3  0.1031      0.889 0.024 0.000 0.976
#> GSM379722     3  0.0592      0.894 0.012 0.000 0.988
#> GSM379723     1  0.1860      0.825 0.948 0.000 0.052
#> GSM379716     1  0.0747      0.811 0.984 0.000 0.016
#> GSM379717     1  0.0000      0.801 1.000 0.000 0.000
#> GSM379718     1  0.3038      0.823 0.896 0.000 0.104
#> GSM379719     3  0.3482      0.814 0.128 0.000 0.872
#> GSM379720     1  0.3267      0.819 0.884 0.000 0.116
#> GSM379729     3  0.0237      0.892 0.000 0.004 0.996
#> GSM379730     3  0.0000      0.894 0.000 0.000 1.000
#> GSM379731     3  0.0592      0.894 0.012 0.000 0.988
#> GSM379724     1  0.6168      0.445 0.588 0.000 0.412
#> GSM379725     3  0.0000      0.894 0.000 0.000 1.000
#> GSM379726     1  0.6274      0.316 0.544 0.000 0.456
#> GSM379727     3  0.5138      0.635 0.252 0.000 0.748
#> GSM379728     1  0.4178      0.786 0.828 0.000 0.172
#> GSM379737     3  0.2959      0.842 0.100 0.000 0.900
#> GSM379738     3  0.0592      0.894 0.012 0.000 0.988
#> GSM379739     3  0.0424      0.895 0.008 0.000 0.992
#> GSM379732     3  0.0237      0.895 0.004 0.000 0.996
#> GSM379733     3  0.4555      0.725 0.200 0.000 0.800
#> GSM379734     3  0.4062      0.775 0.164 0.000 0.836
#> GSM379735     3  0.0000      0.894 0.000 0.000 1.000
#> GSM379736     1  0.2261      0.827 0.932 0.000 0.068
#> GSM379742     3  0.3412      0.764 0.000 0.124 0.876
#> GSM379743     3  0.0237      0.892 0.000 0.004 0.996
#> GSM379740     3  0.2796      0.848 0.092 0.000 0.908
#> GSM379741     3  0.2796      0.804 0.000 0.092 0.908

show/hide code output

cbind(get_classes(res, k = 4), get_membership(res, k = 4))

#>           class entropy silhouette    p1    p2    p3    p4
#> GSM379832     2  0.0336     0.9854 0.008 0.992 0.000 0.000
#> GSM379833     2  0.0336     0.9856 0.008 0.992 0.000 0.000
#> GSM379834     2  0.0469     0.9853 0.012 0.988 0.000 0.000
#> GSM379827     2  0.0657     0.9833 0.012 0.984 0.000 0.004
#> GSM379828     2  0.0657     0.9833 0.012 0.984 0.000 0.004
#> GSM379829     4  0.0188     0.8791 0.004 0.000 0.000 0.996
#> GSM379830     2  0.0657     0.9833 0.012 0.984 0.000 0.004
#> GSM379831     2  0.0657     0.9833 0.012 0.984 0.000 0.004
#> GSM379840     2  0.1452     0.9648 0.008 0.956 0.000 0.036
#> GSM379841     2  0.0469     0.9853 0.012 0.988 0.000 0.000
#> GSM379842     2  0.0469     0.9845 0.012 0.988 0.000 0.000
#> GSM379835     2  0.0657     0.9833 0.012 0.984 0.000 0.004
#> GSM379836     2  0.2222     0.9380 0.016 0.924 0.000 0.060
#> GSM379837     4  0.3539     0.6899 0.004 0.176 0.000 0.820
#> GSM379838     2  0.0707     0.9834 0.020 0.980 0.000 0.000
#> GSM379839     4  0.4018     0.6243 0.004 0.224 0.000 0.772
#> GSM379848     2  0.1022     0.9786 0.032 0.968 0.000 0.000
#> GSM379849     2  0.1211     0.9742 0.040 0.960 0.000 0.000
#> GSM379850     2  0.0592     0.9845 0.016 0.984 0.000 0.000
#> GSM379843     2  0.1022     0.9786 0.032 0.968 0.000 0.000
#> GSM379844     2  0.1022     0.9786 0.032 0.968 0.000 0.000
#> GSM379845     2  0.0895     0.9789 0.004 0.976 0.000 0.020
#> GSM379846     2  0.0188     0.9861 0.004 0.996 0.000 0.000
#> GSM379847     2  0.0817     0.9820 0.024 0.976 0.000 0.000
#> GSM379853     2  0.0469     0.9845 0.012 0.988 0.000 0.000
#> GSM379854     2  0.1022     0.9786 0.032 0.968 0.000 0.000
#> GSM379851     2  0.0592     0.9845 0.016 0.984 0.000 0.000
#> GSM379852     2  0.0817     0.9820 0.024 0.976 0.000 0.000
#> GSM379804     4  0.2021     0.8738 0.024 0.000 0.040 0.936
#> GSM379805     4  0.0469     0.8860 0.012 0.000 0.000 0.988
#> GSM379806     4  0.0592     0.8864 0.016 0.000 0.000 0.984
#> GSM379799     4  0.0188     0.8831 0.004 0.000 0.000 0.996
#> GSM379800     4  0.0188     0.8831 0.004 0.000 0.000 0.996
#> GSM379801     4  0.0524     0.8779 0.004 0.000 0.008 0.988
#> GSM379802     4  0.0469     0.8860 0.012 0.000 0.000 0.988
#> GSM379803     4  0.3907     0.7101 0.232 0.000 0.000 0.768
#> GSM379812     1  0.1807     0.8665 0.940 0.000 0.008 0.052
#> GSM379813     1  0.1938     0.8670 0.936 0.000 0.012 0.052
#> GSM379814     1  0.5035     0.7351 0.748 0.000 0.196 0.056
#> GSM379807     4  0.2593     0.8494 0.104 0.000 0.004 0.892
#> GSM379808     4  0.0469     0.8860 0.012 0.000 0.000 0.988
#> GSM379809     4  0.3636     0.7481 0.008 0.000 0.172 0.820
#> GSM379810     3  0.1151     0.8319 0.008 0.000 0.968 0.024
#> GSM379811     4  0.1557     0.8783 0.056 0.000 0.000 0.944
#> GSM379820     4  0.5220     0.2392 0.424 0.000 0.008 0.568
#> GSM379821     1  0.1978     0.8599 0.928 0.000 0.004 0.068
#> GSM379822     1  0.1743     0.8648 0.940 0.000 0.004 0.056
#> GSM379815     4  0.1284     0.8853 0.024 0.000 0.012 0.964
#> GSM379816     1  0.1042     0.8462 0.972 0.020 0.008 0.000
#> GSM379817     1  0.2480     0.8491 0.904 0.000 0.008 0.088
#> GSM379818     4  0.0707     0.8866 0.020 0.000 0.000 0.980
#> GSM379819     4  0.3105     0.8205 0.140 0.000 0.004 0.856
#> GSM379825     4  0.0336     0.8844 0.008 0.000 0.000 0.992
#> GSM379826     1  0.5250     0.2004 0.552 0.000 0.008 0.440
#> GSM379823     1  0.1247     0.8619 0.968 0.004 0.012 0.016
#> GSM379824     1  0.4331     0.5948 0.712 0.000 0.000 0.288
#> GSM379749     2  0.0188     0.9858 0.004 0.996 0.000 0.000
#> GSM379750     2  0.0336     0.9856 0.008 0.992 0.000 0.000
#> GSM379751     2  0.1284     0.9739 0.012 0.964 0.000 0.024
#> GSM379744     2  0.0469     0.9845 0.012 0.988 0.000 0.000
#> GSM379745     2  0.0469     0.9845 0.012 0.988 0.000 0.000
#> GSM379746     2  0.0188     0.9860 0.004 0.996 0.000 0.000
#> GSM379747     2  0.0657     0.9833 0.012 0.984 0.000 0.004
#> GSM379748     2  0.0469     0.9845 0.012 0.988 0.000 0.000
#> GSM379757     2  0.0469     0.9852 0.012 0.988 0.000 0.000
#> GSM379758     2  0.0921     0.9803 0.028 0.972 0.000 0.000
#> GSM379752     2  0.0336     0.9861 0.008 0.992 0.000 0.000
#> GSM379753     2  0.0469     0.9845 0.012 0.988 0.000 0.000
#> GSM379754     2  0.0188     0.9858 0.004 0.996 0.000 0.000
#> GSM379755     2  0.0188     0.9858 0.004 0.996 0.000 0.000
#> GSM379756     2  0.0188     0.9860 0.004 0.996 0.000 0.000
#> GSM379764     2  0.0336     0.9861 0.008 0.992 0.000 0.000
#> GSM379765     2  0.1118     0.9766 0.036 0.964 0.000 0.000
#> GSM379766     2  0.0817     0.9820 0.024 0.976 0.000 0.000
#> GSM379759     2  0.1211     0.9742 0.040 0.960 0.000 0.000
#> GSM379760     2  0.0707     0.9833 0.020 0.980 0.000 0.000
#> GSM379761     2  0.0336     0.9861 0.008 0.992 0.000 0.000
#> GSM379762     2  0.0188     0.9858 0.004 0.996 0.000 0.000
#> GSM379763     2  0.0469     0.9853 0.012 0.988 0.000 0.000
#> GSM379769     2  0.0336     0.9853 0.008 0.992 0.000 0.000
#> GSM379770     2  0.0469     0.9845 0.012 0.988 0.000 0.000
#> GSM379767     2  0.0336     0.9853 0.008 0.992 0.000 0.000
#> GSM379768     2  0.0817     0.9820 0.024 0.976 0.000 0.000
#> GSM379776     4  0.3182     0.8479 0.096 0.000 0.028 0.876
#> GSM379777     1  0.3569     0.7379 0.804 0.000 0.000 0.196
#> GSM379778     3  0.5000     0.0365 0.500 0.000 0.500 0.000
#> GSM379771     3  0.3390     0.7801 0.016 0.000 0.852 0.132
#> GSM379772     3  0.0469     0.8346 0.012 0.000 0.988 0.000
#> GSM379773     3  0.3837     0.6908 0.224 0.000 0.776 0.000
#> GSM379774     3  0.5448     0.6881 0.080 0.000 0.724 0.196
#> GSM379775     3  0.4576     0.6470 0.012 0.000 0.728 0.260
#> GSM379784     1  0.1584     0.8668 0.952 0.000 0.012 0.036
#> GSM379785     1  0.1722     0.8578 0.944 0.000 0.048 0.008
#> GSM379786     1  0.0859     0.8553 0.980 0.008 0.008 0.004
#> GSM379779     3  0.4039     0.7779 0.080 0.000 0.836 0.084
#> GSM379780     1  0.3333     0.8378 0.872 0.000 0.088 0.040
#> GSM379781     1  0.2111     0.8636 0.932 0.000 0.044 0.024
#> GSM379782     3  0.5263     0.2107 0.448 0.008 0.544 0.000
#> GSM379783     1  0.1059     0.8511 0.972 0.016 0.012 0.000
#> GSM379792     4  0.1305     0.8844 0.036 0.000 0.004 0.960
#> GSM379793     1  0.6138     0.6026 0.648 0.000 0.260 0.092
#> GSM379794     3  0.6921     0.5052 0.160 0.000 0.580 0.260
#> GSM379787     3  0.4591     0.7162 0.084 0.116 0.800 0.000
#> GSM379788     1  0.1722     0.8668 0.944 0.000 0.008 0.048
#> GSM379789     1  0.5751     0.7194 0.712 0.000 0.124 0.164
#> GSM379790     4  0.4868     0.7019 0.212 0.000 0.040 0.748
#> GSM379791     1  0.4814     0.5340 0.676 0.000 0.316 0.008
#> GSM379797     4  0.1022     0.8857 0.032 0.000 0.000 0.968
#> GSM379798     4  0.3818     0.8244 0.108 0.000 0.048 0.844
#> GSM379795     3  0.3975     0.6548 0.240 0.000 0.760 0.000
#> GSM379796     4  0.1970     0.8751 0.060 0.000 0.008 0.932
#> GSM379721     3  0.0188     0.8358 0.004 0.000 0.996 0.000
#> GSM379722     3  0.0188     0.8358 0.004 0.000 0.996 0.000
#> GSM379723     3  0.1256     0.8307 0.008 0.000 0.964 0.028
#> GSM379716     3  0.3852     0.7324 0.008 0.000 0.800 0.192
#> GSM379717     3  0.2831     0.7918 0.004 0.000 0.876 0.120
#> GSM379718     3  0.2125     0.8134 0.004 0.000 0.920 0.076
#> GSM379719     3  0.0188     0.8358 0.004 0.000 0.996 0.000
#> GSM379720     3  0.5268     0.1884 0.008 0.000 0.540 0.452
#> GSM379729     1  0.4564     0.4916 0.672 0.000 0.328 0.000
#> GSM379730     1  0.1940     0.8413 0.924 0.000 0.076 0.000
#> GSM379731     1  0.2174     0.8671 0.928 0.000 0.020 0.052
#> GSM379724     3  0.0188     0.8358 0.004 0.000 0.996 0.000
#> GSM379725     3  0.4804     0.4136 0.384 0.000 0.616 0.000
#> GSM379726     3  0.0188     0.8358 0.004 0.000 0.996 0.000
#> GSM379727     3  0.0188     0.8358 0.004 0.000 0.996 0.000
#> GSM379728     3  0.0779     0.8337 0.004 0.000 0.980 0.016
#> GSM379737     3  0.0188     0.8358 0.004 0.000 0.996 0.000
#> GSM379738     3  0.0188     0.8358 0.004 0.000 0.996 0.000
#> GSM379739     3  0.0336     0.8350 0.008 0.000 0.992 0.000
#> GSM379732     3  0.3726     0.6924 0.212 0.000 0.788 0.000
#> GSM379733     3  0.0188     0.8358 0.004 0.000 0.996 0.000
#> GSM379734     3  0.0000     0.8337 0.000 0.000 1.000 0.000
#> GSM379735     1  0.2530     0.8149 0.888 0.000 0.112 0.000
#> GSM379736     4  0.4283     0.6016 0.004 0.000 0.256 0.740
#> GSM379742     3  0.5558     0.6414 0.208 0.080 0.712 0.000
#> GSM379743     1  0.2281     0.8284 0.904 0.000 0.096 0.000
#> GSM379740     3  0.0188     0.8358 0.004 0.000 0.996 0.000
#> GSM379741     3  0.4284     0.6879 0.224 0.012 0.764 0.000

show/hide code output

cbind(get_classes(res, k = 5), get_membership(res, k = 5))

#>           class entropy silhouette    p1    p2    p3    p4    p5
#> GSM379832     2  0.0000     0.9884 0.000 1.000 0.000 0.000 0.000
#> GSM379833     2  0.0162     0.9886 0.000 0.996 0.000 0.000 0.004
#> GSM379834     2  0.0510     0.9867 0.000 0.984 0.000 0.000 0.016
#> GSM379827     2  0.0324     0.9870 0.004 0.992 0.000 0.000 0.004
#> GSM379828     2  0.0324     0.9870 0.004 0.992 0.000 0.000 0.004
#> GSM379829     4  0.1547     0.8484 0.016 0.000 0.032 0.948 0.004
#> GSM379830     2  0.0324     0.9870 0.004 0.992 0.000 0.000 0.004
#> GSM379831     2  0.0000     0.9884 0.000 1.000 0.000 0.000 0.000
#> GSM379840     2  0.0960     0.9754 0.008 0.972 0.000 0.016 0.004
#> GSM379841     2  0.0000     0.9884 0.000 1.000 0.000 0.000 0.000
#> GSM379842     2  0.0324     0.9871 0.004 0.992 0.000 0.000 0.004
#> GSM379835     2  0.0162     0.9881 0.004 0.996 0.000 0.000 0.000
#> GSM379836     2  0.1087     0.9734 0.016 0.968 0.000 0.008 0.008
#> GSM379837     4  0.3900     0.7037 0.016 0.144 0.032 0.808 0.000
#> GSM379838     2  0.0703     0.9839 0.000 0.976 0.000 0.000 0.024
#> GSM379839     4  0.3141     0.7124 0.016 0.152 0.000 0.832 0.000
#> GSM379848     2  0.0880     0.9806 0.000 0.968 0.000 0.000 0.032
#> GSM379849     2  0.1410     0.9620 0.000 0.940 0.000 0.000 0.060
#> GSM379850     2  0.0162     0.9886 0.000 0.996 0.000 0.000 0.004
#> GSM379843     2  0.0880     0.9806 0.000 0.968 0.000 0.000 0.032
#> GSM379844     2  0.0794     0.9823 0.000 0.972 0.000 0.000 0.028
#> GSM379845     2  0.0162     0.9881 0.004 0.996 0.000 0.000 0.000
#> GSM379846     2  0.0162     0.9879 0.000 0.996 0.000 0.000 0.004
#> GSM379847     2  0.0510     0.9870 0.000 0.984 0.000 0.000 0.016
#> GSM379853     2  0.0451     0.9855 0.008 0.988 0.000 0.000 0.004
#> GSM379854     2  0.0880     0.9806 0.000 0.968 0.000 0.000 0.032
#> GSM379851     2  0.0290     0.9886 0.000 0.992 0.000 0.000 0.008
#> GSM379852     2  0.0162     0.9886 0.000 0.996 0.000 0.000 0.004
#> GSM379804     4  0.0613     0.8686 0.004 0.000 0.008 0.984 0.004
#> GSM379805     4  0.0609     0.8692 0.020 0.000 0.000 0.980 0.000
#> GSM379806     4  0.0451     0.8699 0.008 0.000 0.000 0.988 0.004
#> GSM379799     4  0.0000     0.8683 0.000 0.000 0.000 1.000 0.000
#> GSM379800     4  0.0000     0.8683 0.000 0.000 0.000 1.000 0.000
#> GSM379801     4  0.0960     0.8604 0.008 0.000 0.016 0.972 0.004
#> GSM379802     4  0.0451     0.8667 0.008 0.000 0.000 0.988 0.004
#> GSM379803     4  0.3496     0.7013 0.012 0.000 0.000 0.788 0.200
#> GSM379812     5  0.2236     0.8938 0.024 0.000 0.000 0.068 0.908
#> GSM379813     5  0.4210     0.7205 0.224 0.000 0.000 0.036 0.740
#> GSM379814     1  0.1780     0.8805 0.940 0.000 0.008 0.028 0.024
#> GSM379807     4  0.2513     0.8232 0.116 0.000 0.000 0.876 0.008
#> GSM379808     4  0.0451     0.8699 0.008 0.000 0.000 0.988 0.004
#> GSM379809     4  0.1485     0.8632 0.032 0.000 0.020 0.948 0.000
#> GSM379810     3  0.3146     0.8161 0.128 0.000 0.844 0.028 0.000
#> GSM379811     4  0.0693     0.8696 0.012 0.000 0.000 0.980 0.008
#> GSM379820     4  0.4649     0.3481 0.404 0.000 0.000 0.580 0.016
#> GSM379821     5  0.2069     0.8919 0.012 0.000 0.000 0.076 0.912
#> GSM379822     5  0.1894     0.8930 0.008 0.000 0.000 0.072 0.920
#> GSM379815     4  0.2179     0.8301 0.112 0.000 0.000 0.888 0.000
#> GSM379816     5  0.0486     0.8851 0.004 0.004 0.004 0.000 0.988
#> GSM379817     5  0.3955     0.8159 0.116 0.000 0.000 0.084 0.800
#> GSM379818     4  0.0451     0.8699 0.008 0.000 0.000 0.988 0.004
#> GSM379819     4  0.2843     0.8016 0.144 0.000 0.000 0.848 0.008
#> GSM379825     4  0.0290     0.8695 0.008 0.000 0.000 0.992 0.000
#> GSM379826     4  0.5639     0.3754 0.092 0.000 0.000 0.568 0.340
#> GSM379823     5  0.1704     0.8933 0.068 0.000 0.004 0.000 0.928
#> GSM379824     5  0.2660     0.8588 0.008 0.000 0.000 0.128 0.864
#> GSM379749     2  0.0162     0.9886 0.000 0.996 0.000 0.000 0.004
#> GSM379750     2  0.0794     0.9828 0.000 0.972 0.000 0.000 0.028
#> GSM379751     2  0.0613     0.9835 0.008 0.984 0.000 0.004 0.004
#> GSM379744     2  0.0000     0.9884 0.000 1.000 0.000 0.000 0.000
#> GSM379745     2  0.0162     0.9886 0.000 0.996 0.000 0.000 0.004
#> GSM379746     2  0.0510     0.9867 0.000 0.984 0.000 0.000 0.016
#> GSM379747     2  0.0162     0.9879 0.000 0.996 0.000 0.000 0.004
#> GSM379748     2  0.0000     0.9884 0.000 1.000 0.000 0.000 0.000
#> GSM379757     2  0.0880     0.9805 0.000 0.968 0.000 0.000 0.032
#> GSM379758     2  0.0794     0.9827 0.000 0.972 0.000 0.000 0.028
#> GSM379752     2  0.0510     0.9867 0.000 0.984 0.000 0.000 0.016
#> GSM379753     2  0.0162     0.9881 0.000 0.996 0.004 0.000 0.000
#> GSM379754     2  0.0290     0.9882 0.000 0.992 0.000 0.000 0.008
#> GSM379755     2  0.0290     0.9884 0.000 0.992 0.000 0.000 0.008
#> GSM379756     2  0.0404     0.9877 0.000 0.988 0.000 0.000 0.012
#> GSM379764     2  0.0290     0.9886 0.000 0.992 0.000 0.000 0.008
#> GSM379765     2  0.1270     0.9679 0.000 0.948 0.000 0.000 0.052
#> GSM379766     2  0.0404     0.9877 0.000 0.988 0.000 0.000 0.012
#> GSM379759     2  0.1478     0.9589 0.000 0.936 0.000 0.000 0.064
#> GSM379760     2  0.1043     0.9759 0.000 0.960 0.000 0.000 0.040
#> GSM379761     2  0.0290     0.9882 0.000 0.992 0.000 0.000 0.008
#> GSM379762     2  0.0162     0.9879 0.000 0.996 0.000 0.000 0.004
#> GSM379763     2  0.0290     0.9886 0.000 0.992 0.000 0.000 0.008
#> GSM379769     2  0.0162     0.9879 0.000 0.996 0.000 0.000 0.004
#> GSM379770     2  0.0162     0.9879 0.000 0.996 0.000 0.000 0.004
#> GSM379767     2  0.0162     0.9879 0.000 0.996 0.000 0.000 0.004
#> GSM379768     2  0.0404     0.9878 0.000 0.988 0.000 0.000 0.012
#> GSM379776     4  0.4504     0.2838 0.428 0.000 0.000 0.564 0.008
#> GSM379777     5  0.2470     0.8783 0.012 0.000 0.000 0.104 0.884
#> GSM379778     1  0.1753     0.8631 0.936 0.000 0.032 0.000 0.032
#> GSM379771     1  0.1864     0.8666 0.924 0.000 0.004 0.068 0.004
#> GSM379772     1  0.1970     0.8618 0.924 0.000 0.060 0.012 0.004
#> GSM379773     1  0.1393     0.8775 0.956 0.000 0.024 0.012 0.008
#> GSM379774     1  0.1365     0.8802 0.952 0.000 0.004 0.040 0.004
#> GSM379775     1  0.1928     0.8630 0.920 0.000 0.004 0.072 0.004
#> GSM379784     5  0.2286     0.8797 0.108 0.000 0.000 0.004 0.888
#> GSM379785     1  0.2136     0.8412 0.904 0.000 0.000 0.008 0.088
#> GSM379786     5  0.1908     0.8869 0.092 0.000 0.000 0.000 0.908
#> GSM379779     1  0.1788     0.8754 0.932 0.000 0.008 0.056 0.004
#> GSM379780     1  0.2260     0.8581 0.908 0.000 0.000 0.028 0.064
#> GSM379781     1  0.4074     0.3847 0.636 0.000 0.000 0.000 0.364
#> GSM379782     1  0.2629     0.8394 0.896 0.008 0.064 0.000 0.032
#> GSM379783     5  0.1851     0.8874 0.088 0.000 0.000 0.000 0.912
#> GSM379792     4  0.2966     0.7678 0.184 0.000 0.000 0.816 0.000
#> GSM379793     1  0.0955     0.8809 0.968 0.000 0.000 0.028 0.004
#> GSM379794     1  0.0963     0.8801 0.964 0.000 0.000 0.036 0.000
#> GSM379787     1  0.1788     0.8568 0.932 0.008 0.056 0.000 0.004
#> GSM379788     5  0.2304     0.8845 0.100 0.000 0.000 0.008 0.892
#> GSM379789     1  0.1205     0.8799 0.956 0.000 0.000 0.040 0.004
#> GSM379790     1  0.3861     0.5791 0.712 0.000 0.000 0.284 0.004
#> GSM379791     1  0.1059     0.8811 0.968 0.000 0.004 0.020 0.008
#> GSM379797     4  0.0955     0.8673 0.028 0.000 0.000 0.968 0.004
#> GSM379798     1  0.3814     0.5941 0.720 0.000 0.000 0.276 0.004
#> GSM379795     1  0.1026     0.8751 0.968 0.000 0.024 0.004 0.004
#> GSM379796     4  0.3430     0.7213 0.220 0.000 0.000 0.776 0.004
#> GSM379721     3  0.0162     0.9194 0.000 0.000 0.996 0.000 0.004
#> GSM379722     3  0.0162     0.9194 0.000 0.000 0.996 0.000 0.004
#> GSM379723     3  0.0000     0.9201 0.000 0.000 1.000 0.000 0.000
#> GSM379716     3  0.1043     0.9009 0.000 0.000 0.960 0.040 0.000
#> GSM379717     3  0.0798     0.9120 0.008 0.000 0.976 0.016 0.000
#> GSM379718     3  0.0833     0.9124 0.004 0.000 0.976 0.016 0.004
#> GSM379719     3  0.0162     0.9194 0.000 0.000 0.996 0.000 0.004
#> GSM379720     3  0.3134     0.8271 0.012 0.000 0.864 0.096 0.028
#> GSM379729     5  0.2471     0.8410 0.000 0.000 0.136 0.000 0.864
#> GSM379730     5  0.1792     0.8824 0.000 0.000 0.084 0.000 0.916
#> GSM379731     5  0.2580     0.8877 0.000 0.000 0.064 0.044 0.892
#> GSM379724     3  0.0000     0.9201 0.000 0.000 1.000 0.000 0.000
#> GSM379725     5  0.3752     0.6154 0.000 0.000 0.292 0.000 0.708
#> GSM379726     3  0.0000     0.9201 0.000 0.000 1.000 0.000 0.000
#> GSM379727     3  0.0162     0.9202 0.004 0.000 0.996 0.000 0.000
#> GSM379728     3  0.0404     0.9195 0.012 0.000 0.988 0.000 0.000
#> GSM379737     3  0.0963     0.9125 0.036 0.000 0.964 0.000 0.000
#> GSM379738     3  0.1478     0.8958 0.064 0.000 0.936 0.000 0.000
#> GSM379739     3  0.1544     0.8928 0.068 0.000 0.932 0.000 0.000
#> GSM379732     3  0.4219     0.2106 0.000 0.000 0.584 0.000 0.416
#> GSM379733     3  0.0290     0.9198 0.008 0.000 0.992 0.000 0.000
#> GSM379734     3  0.0794     0.9154 0.028 0.000 0.972 0.000 0.000
#> GSM379735     5  0.1792     0.8825 0.000 0.000 0.084 0.000 0.916
#> GSM379736     4  0.2408     0.8210 0.008 0.000 0.096 0.892 0.004
#> GSM379742     1  0.7302     0.0248 0.428 0.140 0.372 0.000 0.060
#> GSM379743     5  0.1851     0.8807 0.000 0.000 0.088 0.000 0.912
#> GSM379740     3  0.1041     0.9147 0.032 0.000 0.964 0.000 0.004
#> GSM379741     3  0.6161     0.1072 0.428 0.028 0.480 0.000 0.064

show/hide code output

cbind(get_classes(res, k = 6), get_membership(res, k = 6))

#>           class entropy silhouette    p1    p2    p3    p4    p5    p6
#> GSM379832     2  0.1588    0.82088 0.000 0.924 0.000 0.000 0.072 0.004
#> GSM379833     2  0.1267    0.83080 0.000 0.940 0.000 0.000 0.060 0.000
#> GSM379834     2  0.1531    0.82061 0.000 0.928 0.000 0.000 0.068 0.004
#> GSM379827     2  0.2762    0.68891 0.000 0.804 0.000 0.000 0.196 0.000
#> GSM379828     2  0.2941    0.65036 0.000 0.780 0.000 0.000 0.220 0.000
#> GSM379829     4  0.4116    0.20731 0.000 0.000 0.012 0.572 0.416 0.000
#> GSM379830     2  0.3991   -0.25684 0.000 0.524 0.004 0.000 0.472 0.000
#> GSM379831     2  0.2697    0.69247 0.000 0.812 0.000 0.000 0.188 0.000
#> GSM379840     2  0.4224   -0.30796 0.008 0.512 0.000 0.000 0.476 0.004
#> GSM379841     2  0.0935    0.84099 0.000 0.964 0.000 0.000 0.032 0.004
#> GSM379842     2  0.2632    0.73504 0.004 0.832 0.000 0.000 0.164 0.000
#> GSM379835     2  0.3578    0.34090 0.000 0.660 0.000 0.000 0.340 0.000
#> GSM379836     2  0.4128   -0.35352 0.000 0.500 0.004 0.004 0.492 0.000
#> GSM379837     5  0.6473    0.00000 0.000 0.280 0.040 0.160 0.512 0.008
#> GSM379838     2  0.0777    0.83885 0.000 0.972 0.000 0.000 0.024 0.004
#> GSM379839     4  0.5133    0.00808 0.000 0.088 0.004 0.576 0.332 0.000
#> GSM379848     2  0.0508    0.84226 0.000 0.984 0.000 0.000 0.012 0.004
#> GSM379849     2  0.1265    0.82442 0.000 0.948 0.000 0.000 0.044 0.008
#> GSM379850     2  0.1010    0.83805 0.000 0.960 0.000 0.000 0.036 0.004
#> GSM379843     2  0.2266    0.78870 0.000 0.880 0.000 0.000 0.108 0.012
#> GSM379844     2  0.1701    0.82243 0.000 0.920 0.000 0.000 0.072 0.008
#> GSM379845     2  0.3784    0.41008 0.000 0.680 0.000 0.012 0.308 0.000
#> GSM379846     2  0.1910    0.79874 0.000 0.892 0.000 0.000 0.108 0.000
#> GSM379847     2  0.1462    0.83054 0.000 0.936 0.000 0.000 0.056 0.008
#> GSM379853     2  0.4468   -0.07154 0.032 0.560 0.000 0.000 0.408 0.000
#> GSM379854     2  0.1333    0.83630 0.000 0.944 0.000 0.000 0.048 0.008
#> GSM379851     2  0.2234    0.78108 0.000 0.872 0.000 0.000 0.124 0.004
#> GSM379852     2  0.2020    0.80759 0.000 0.896 0.000 0.000 0.096 0.008
#> GSM379804     4  0.1485    0.79481 0.004 0.000 0.024 0.944 0.028 0.000
#> GSM379805     4  0.0405    0.79769 0.004 0.000 0.000 0.988 0.008 0.000
#> GSM379806     4  0.1226    0.79672 0.004 0.000 0.000 0.952 0.040 0.004
#> GSM379799     4  0.0260    0.79633 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM379800     4  0.0260    0.79633 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM379801     4  0.2527    0.73743 0.000 0.000 0.024 0.868 0.108 0.000
#> GSM379802     4  0.0363    0.79593 0.000 0.000 0.000 0.988 0.012 0.000
#> GSM379803     4  0.1615    0.77396 0.004 0.000 0.000 0.928 0.004 0.064
#> GSM379812     6  0.1151    0.79871 0.000 0.000 0.000 0.012 0.032 0.956
#> GSM379813     6  0.6797    0.46941 0.144 0.000 0.000 0.112 0.248 0.496
#> GSM379814     1  0.6657    0.50187 0.548 0.000 0.004 0.120 0.196 0.132
#> GSM379807     4  0.6899    0.38606 0.152 0.000 0.000 0.488 0.236 0.124
#> GSM379808     4  0.0508    0.79950 0.004 0.000 0.000 0.984 0.012 0.000
#> GSM379809     4  0.4118    0.72175 0.048 0.000 0.092 0.796 0.060 0.004
#> GSM379810     3  0.5162    0.68998 0.092 0.000 0.716 0.100 0.088 0.004
#> GSM379811     4  0.0405    0.79957 0.004 0.000 0.000 0.988 0.008 0.000
#> GSM379820     4  0.7204    0.04874 0.328 0.000 0.000 0.368 0.200 0.104
#> GSM379821     6  0.1982    0.80008 0.004 0.000 0.000 0.016 0.068 0.912
#> GSM379822     6  0.2312    0.79153 0.000 0.000 0.000 0.012 0.112 0.876
#> GSM379815     4  0.6509    0.27926 0.308 0.000 0.000 0.480 0.156 0.056
#> GSM379816     6  0.1858    0.77831 0.000 0.012 0.000 0.000 0.076 0.912
#> GSM379817     6  0.6499    0.52676 0.092 0.000 0.000 0.124 0.256 0.528
#> GSM379818     4  0.0603    0.79994 0.004 0.000 0.000 0.980 0.016 0.000
#> GSM379819     4  0.3794    0.73315 0.100 0.000 0.000 0.804 0.076 0.020
#> GSM379825     4  0.0405    0.79769 0.004 0.000 0.000 0.988 0.008 0.000
#> GSM379826     6  0.6806    0.46837 0.100 0.000 0.000 0.152 0.264 0.484
#> GSM379823     6  0.2841    0.77384 0.012 0.000 0.000 0.000 0.164 0.824
#> GSM379824     6  0.3803    0.75645 0.004 0.000 0.000 0.068 0.148 0.780
#> GSM379749     2  0.0458    0.84288 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379750     2  0.0972    0.83155 0.000 0.964 0.000 0.000 0.028 0.008
#> GSM379751     2  0.3276    0.60117 0.000 0.764 0.004 0.004 0.228 0.000
#> GSM379744     2  0.0632    0.84158 0.000 0.976 0.000 0.000 0.024 0.000
#> GSM379745     2  0.0146    0.84145 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM379746     2  0.0713    0.83349 0.000 0.972 0.000 0.000 0.028 0.000
#> GSM379747     2  0.1082    0.83747 0.000 0.956 0.004 0.000 0.040 0.000
#> GSM379748     2  0.0547    0.84207 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379757     2  0.0692    0.83603 0.000 0.976 0.000 0.000 0.020 0.004
#> GSM379758     2  0.0692    0.83603 0.000 0.976 0.000 0.000 0.020 0.004
#> GSM379752     2  0.0363    0.83977 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379753     2  0.1003    0.84252 0.000 0.964 0.004 0.000 0.028 0.004
#> GSM379754     2  0.0260    0.84035 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379755     2  0.0363    0.83973 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379756     2  0.0713    0.83349 0.000 0.972 0.000 0.000 0.028 0.000
#> GSM379764     2  0.0865    0.83859 0.000 0.964 0.000 0.000 0.036 0.000
#> GSM379765     2  0.0935    0.82916 0.000 0.964 0.000 0.000 0.032 0.004
#> GSM379766     2  0.0363    0.84140 0.000 0.988 0.000 0.000 0.012 0.000
#> GSM379759     2  0.1462    0.80816 0.000 0.936 0.000 0.000 0.056 0.008
#> GSM379760     2  0.0508    0.83942 0.000 0.984 0.000 0.000 0.012 0.004
#> GSM379761     2  0.0260    0.84035 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379762     2  0.0547    0.84211 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379763     2  0.0260    0.84197 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM379769     2  0.0937    0.83857 0.000 0.960 0.000 0.000 0.040 0.000
#> GSM379770     2  0.0790    0.83958 0.000 0.968 0.000 0.000 0.032 0.000
#> GSM379767     2  0.0547    0.84259 0.000 0.980 0.000 0.000 0.020 0.000
#> GSM379768     2  0.0458    0.83856 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM379776     4  0.3738    0.55368 0.280 0.000 0.000 0.704 0.016 0.000
#> GSM379777     6  0.2250    0.78406 0.000 0.000 0.000 0.092 0.020 0.888
#> GSM379778     1  0.3671    0.78320 0.816 0.000 0.056 0.000 0.100 0.028
#> GSM379771     1  0.1914    0.83797 0.920 0.000 0.008 0.056 0.016 0.000
#> GSM379772     1  0.1390    0.84361 0.948 0.000 0.032 0.004 0.016 0.000
#> GSM379773     1  0.4002    0.78686 0.804 0.000 0.060 0.024 0.100 0.012
#> GSM379774     1  0.0893    0.84751 0.972 0.000 0.004 0.016 0.004 0.004
#> GSM379775     1  0.0972    0.84744 0.964 0.000 0.008 0.028 0.000 0.000
#> GSM379784     6  0.2318    0.79316 0.064 0.000 0.000 0.000 0.044 0.892
#> GSM379785     1  0.2392    0.83480 0.896 0.000 0.000 0.008 0.048 0.048
#> GSM379786     6  0.1492    0.80176 0.024 0.000 0.000 0.000 0.036 0.940
#> GSM379779     1  0.2981    0.82846 0.868 0.000 0.024 0.072 0.032 0.004
#> GSM379780     1  0.3787    0.78292 0.812 0.000 0.000 0.036 0.064 0.088
#> GSM379781     1  0.5167    0.53906 0.632 0.000 0.000 0.012 0.104 0.252
#> GSM379782     1  0.4007    0.76909 0.796 0.004 0.072 0.000 0.104 0.024
#> GSM379783     6  0.1794    0.79360 0.036 0.000 0.000 0.000 0.040 0.924
#> GSM379792     4  0.4476    0.47644 0.308 0.000 0.000 0.640 0.052 0.000
#> GSM379793     1  0.1787    0.83830 0.920 0.000 0.000 0.008 0.068 0.004
#> GSM379794     1  0.0964    0.84761 0.968 0.000 0.000 0.012 0.016 0.004
#> GSM379787     1  0.3548    0.78775 0.828 0.004 0.068 0.004 0.088 0.008
#> GSM379788     6  0.3602    0.76023 0.032 0.000 0.000 0.008 0.176 0.784
#> GSM379789     1  0.2259    0.83477 0.908 0.000 0.000 0.040 0.032 0.020
#> GSM379790     1  0.4122    0.54013 0.680 0.000 0.000 0.292 0.020 0.008
#> GSM379791     1  0.1116    0.84668 0.960 0.000 0.000 0.008 0.028 0.004
#> GSM379797     4  0.0603    0.79948 0.004 0.000 0.000 0.980 0.016 0.000
#> GSM379798     1  0.4034    0.46194 0.648 0.000 0.000 0.336 0.012 0.004
#> GSM379795     1  0.0964    0.84404 0.968 0.000 0.016 0.004 0.012 0.000
#> GSM379796     4  0.2450    0.75464 0.116 0.000 0.000 0.868 0.016 0.000
#> GSM379721     3  0.1116    0.89968 0.004 0.000 0.960 0.000 0.028 0.008
#> GSM379722     3  0.0717    0.89963 0.008 0.000 0.976 0.000 0.016 0.000
#> GSM379723     3  0.0547    0.89872 0.000 0.000 0.980 0.000 0.020 0.000
#> GSM379716     3  0.1049    0.89343 0.000 0.000 0.960 0.008 0.032 0.000
#> GSM379717     3  0.1493    0.88267 0.004 0.000 0.936 0.004 0.056 0.000
#> GSM379718     3  0.1508    0.88605 0.004 0.000 0.940 0.004 0.048 0.004
#> GSM379719     3  0.0777    0.90040 0.004 0.000 0.972 0.000 0.024 0.000
#> GSM379720     3  0.2430    0.86460 0.004 0.000 0.900 0.012 0.048 0.036
#> GSM379729     6  0.3895    0.69758 0.008 0.000 0.172 0.000 0.052 0.768
#> GSM379730     6  0.3039    0.76890 0.004 0.000 0.088 0.000 0.060 0.848
#> GSM379731     6  0.2932    0.75276 0.004 0.000 0.140 0.000 0.020 0.836
#> GSM379724     3  0.0291    0.90147 0.004 0.000 0.992 0.000 0.004 0.000
#> GSM379725     6  0.4879    0.34635 0.008 0.000 0.356 0.000 0.052 0.584
#> GSM379726     3  0.0806    0.89905 0.008 0.000 0.972 0.000 0.020 0.000
#> GSM379727     3  0.0692    0.89982 0.004 0.000 0.976 0.000 0.020 0.000
#> GSM379728     3  0.1334    0.89327 0.020 0.000 0.948 0.000 0.032 0.000
#> GSM379737     3  0.1257    0.89694 0.028 0.000 0.952 0.000 0.020 0.000
#> GSM379738     3  0.2066    0.87580 0.052 0.000 0.908 0.000 0.040 0.000
#> GSM379739     3  0.2129    0.87267 0.056 0.000 0.904 0.000 0.040 0.000
#> GSM379732     3  0.4044    0.47589 0.008 0.000 0.668 0.000 0.012 0.312
#> GSM379733     3  0.0891    0.90043 0.008 0.000 0.968 0.000 0.024 0.000
#> GSM379734     3  0.1341    0.89381 0.024 0.000 0.948 0.000 0.028 0.000
#> GSM379735     6  0.3361    0.75110 0.000 0.000 0.108 0.000 0.076 0.816
#> GSM379736     4  0.1138    0.79358 0.004 0.000 0.024 0.960 0.012 0.000
#> GSM379742     2  0.8923   -0.40249 0.204 0.248 0.196 0.000 0.156 0.196
#> GSM379743     6  0.3128    0.76556 0.008 0.000 0.096 0.000 0.052 0.844
#> GSM379740     3  0.1881    0.89086 0.020 0.000 0.928 0.004 0.040 0.008
#> GSM379741     3  0.8678    0.02429 0.240 0.108 0.296 0.000 0.156 0.200

Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.

consensus_heatmap(res, k = 2)

plot of chunk tab-ATC-NMF-consensus-heatmap-1

consensus_heatmap(res, k = 3)

plot of chunk tab-ATC-NMF-consensus-heatmap-2

consensus_heatmap(res, k = 4)

plot of chunk tab-ATC-NMF-consensus-heatmap-3

consensus_heatmap(res, k = 5)

plot of chunk tab-ATC-NMF-consensus-heatmap-4

consensus_heatmap(res, k = 6)

plot of chunk tab-ATC-NMF-consensus-heatmap-5

Heatmaps for the membership of samples in all partitions to see how consistent they are:

membership_heatmap(res, k = 2)

plot of chunk tab-ATC-NMF-membership-heatmap-1

membership_heatmap(res, k = 3)

plot of chunk tab-ATC-NMF-membership-heatmap-2

membership_heatmap(res, k = 4)

plot of chunk tab-ATC-NMF-membership-heatmap-3

membership_heatmap(res, k = 5)

plot of chunk tab-ATC-NMF-membership-heatmap-4

membership_heatmap(res, k = 6)

plot of chunk tab-ATC-NMF-membership-heatmap-5

As soon as we have had the classes for columns, we can look for signatures which are significantly different between classes which can be candidate marks for certain classes. Following are the heatmaps for signatures.

Signature heatmaps where rows are scaled:

get_signatures(res, k = 2)

plot of chunk tab-ATC-NMF-get-signatures-1

get_signatures(res, k = 3)

plot of chunk tab-ATC-NMF-get-signatures-2

get_signatures(res, k = 4)

plot of chunk tab-ATC-NMF-get-signatures-3

get_signatures(res, k = 5)

plot of chunk tab-ATC-NMF-get-signatures-4

get_signatures(res, k = 6)

plot of chunk tab-ATC-NMF-get-signatures-5

Signature heatmaps where rows are not scaled:

get_signatures(res, k = 2, scale_rows = FALSE)

plot of chunk tab-ATC-NMF-get-signatures-no-scale-1

get_signatures(res, k = 3, scale_rows = FALSE)

plot of chunk tab-ATC-NMF-get-signatures-no-scale-2

get_signatures(res, k = 4, scale_rows = FALSE)

plot of chunk tab-ATC-NMF-get-signatures-no-scale-3

get_signatures(res, k = 5, scale_rows = FALSE)

plot of chunk tab-ATC-NMF-get-signatures-no-scale-4

get_signatures(res, k = 6, scale_rows = FALSE)

plot of chunk tab-ATC-NMF-get-signatures-no-scale-5

Compare the overlap of signatures from different k:

compare_signatures(res)

plot of chunk ATC-NMF-signature_compare

get_signature() returns a data frame invisibly. TO get the list of signatures, the function call should be assigned to a variable explicitly. In following code, if plot argument is set to FALSE, no heatmap is plotted while only the differential analysis is performed.

# code only for demonstration
tb = get_signature(res, k = ..., plot = FALSE)

An example of the output of tb is:

#>   which_row         fdr    mean_1    mean_2 scaled_mean_1 scaled_mean_2 km
#> 1        38 0.042760348  8.373488  9.131774    -0.5533452     0.5164555  1
#> 2        40 0.018707592  7.106213  8.469186    -0.6173731     0.5762149  1
#> 3        55 0.019134737 10.221463 11.207825    -0.6159697     0.5749050  1
#> 4        59 0.006059896  5.921854  7.869574    -0.6899429     0.6439467  1
#> 5        60 0.018055526  8.928898 10.211722    -0.6204761     0.5791110  1
#> 6        98 0.009384629 15.714769 14.887706     0.6635654    -0.6193277  2
...

The columns in tb are:

  1. which_row: row indices corresponding to the input matrix.
  2. fdr: FDR for the differential test.
  3. mean_x: The mean value in group x.
  4. scaled_mean_x: The mean value in group x after rows are scaled.
  5. km: Row groups if k-means clustering is applied to rows.

UMAP plot which shows how samples are separated.

dimension_reduction(res, k = 2, method = "UMAP")

plot of chunk tab-ATC-NMF-dimension-reduction-1

dimension_reduction(res, k = 3, method = "UMAP")

plot of chunk tab-ATC-NMF-dimension-reduction-2

dimension_reduction(res, k = 4, method = "UMAP")

plot of chunk tab-ATC-NMF-dimension-reduction-3

dimension_reduction(res, k = 5, method = "UMAP")

plot of chunk tab-ATC-NMF-dimension-reduction-4

dimension_reduction(res, k = 6, method = "UMAP")

plot of chunk tab-ATC-NMF-dimension-reduction-5

Following heatmap shows how subgroups are split when increasing k:

collect_classes(res)

plot of chunk ATC-NMF-collect-classes

Test correlation between subgroups and known annotations. If the known annotation is numeric, one-way ANOVA test is applied, and if the known annotation is discrete, chi-squared contingency table test is applied.

test_to_known_factors(res)

#>           n individual(p) time(p) agent(p) k
#> ATC:NMF 137      5.19e-23   1.000  0.78285 2
#> ATC:NMF 129      2.11e-27   0.951  0.00148 3
#> ATC:NMF 132      1.26e-32   0.964  0.01755 4
#> ATC:NMF 132      4.94e-47   0.999  0.09581 5
#> ATC:NMF 119      3.25e-44   0.993  0.06201 6

If matrix rows can be associated to genes, consider to use functional_enrichment(res, ...) to perform function enrichment for the signature genes. See this vignette for more detailed explanations.

Session info

sessionInfo()

#> R version 3.6.0 (2019-04-26)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: CentOS Linux 7 (Core)
#> 
#> Matrix products: default
#> BLAS:   /usr/lib64/libblas.so.3.4.2
#> LAPACK: /usr/lib64/liblapack.so.3.4.2
#> 
#> locale:
#>  [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C               LC_TIME=en_GB.UTF-8       
#>  [4] LC_COLLATE=en_GB.UTF-8     LC_MONETARY=en_GB.UTF-8    LC_MESSAGES=en_GB.UTF-8   
#>  [7] LC_PAPER=en_GB.UTF-8       LC_NAME=C                  LC_ADDRESS=C              
#> [10] LC_TELEPHONE=C             LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       
#> 
#> attached base packages:
#> [1] grid      stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] genefilter_1.66.0    ComplexHeatmap_2.3.1 markdown_1.1         knitr_1.26          
#> [5] GetoptLong_0.1.7     cola_1.3.2          
#> 
#> loaded via a namespace (and not attached):
#>  [1] circlize_0.4.8       shape_1.4.4          xfun_0.11            slam_0.1-46         
#>  [5] lattice_0.20-38      splines_3.6.0        colorspace_1.4-1     vctrs_0.2.0         
#>  [9] stats4_3.6.0         blob_1.2.0           XML_3.98-1.20        survival_2.44-1.1   
#> [13] rlang_0.4.2          pillar_1.4.2         DBI_1.0.0            BiocGenerics_0.30.0 
#> [17] bit64_0.9-7          RColorBrewer_1.1-2   matrixStats_0.55.0   stringr_1.4.0       
#> [21] GlobalOptions_0.1.1  evaluate_0.14        memoise_1.1.0        Biobase_2.44.0      
#> [25] IRanges_2.18.3       parallel_3.6.0       AnnotationDbi_1.46.1 highr_0.8           
#> [29] Rcpp_1.0.3           xtable_1.8-4         backports_1.1.5      S4Vectors_0.22.1    
#> [33] annotate_1.62.0      skmeans_0.2-11       bit_1.1-14           microbenchmark_1.4-7
#> [37] brew_1.0-6           impute_1.58.0        rjson_0.2.20         png_0.1-7           
#> [41] digest_0.6.23        stringi_1.4.3        polyclip_1.10-0      clue_0.3-57         
#> [45] tools_3.6.0          bitops_1.0-6         magrittr_1.5         eulerr_6.0.0        
#> [49] RCurl_1.95-4.12      RSQLite_2.1.4        tibble_2.1.3         cluster_2.1.0       
#> [53] crayon_1.3.4         pkgconfig_2.0.3      zeallot_0.1.0        Matrix_1.2-17       
#> [57] xml2_1.2.2           httr_1.4.1           R6_2.4.1             mclust_5.4.5        
#> [61] compiler_3.6.0