Date: 2019-12-25 20:51:22 CET, cola version: 1.3.2
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All available functions which can be applied to this res_list object:
res_list
#> A 'ConsensusPartitionList' object with 24 methods.
#> On a matrix with 19559 rows and 153 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] 19559 153
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)
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:hclust | 5 | 1.000 | 1.000 | 1.000 | ** | 2,3,4 |
| SD:skmeans | 5 | 1.000 | 1.000 | 0.999 | ** | 2,3,4 |
| SD:NMF | 5 | 1.000 | 1.000 | 1.000 | ** | 2,3,4 |
| CV:skmeans | 5 | 1.000 | 0.999 | 0.998 | ** | 2,3 |
| CV:NMF | 5 | 1.000 | 1.000 | 1.000 | ** | 2,4 |
| MAD:skmeans | 5 | 1.000 | 1.000 | 0.999 | ** | 2,4 |
| MAD:mclust | 5 | 1.000 | 0.992 | 0.997 | ** | 4 |
| MAD:NMF | 5 | 1.000 | 1.000 | 1.000 | ** | 2,3 |
| ATC:hclust | 3 | 1.000 | 0.997 | 0.999 | ** | 2 |
| ATC:pam | 6 | 1.000 | 0.989 | 0.996 | ** | 3,4,5 |
| CV:pam | 6 | 0.979 | 0.965 | 0.967 | ** | 2,3,4,5 |
| MAD:pam | 6 | 0.975 | 0.975 | 0.969 | ** | 2,3,4,5 |
| ATC:mclust | 6 | 0.973 | 0.914 | 0.953 | ** | 4,5 |
| SD:pam | 6 | 0.961 | 0.922 | 0.919 | ** | 2,3,4,5 |
| SD:mclust | 6 | 0.936 | 0.833 | 0.907 | * | 4,5 |
| ATC:NMF | 4 | 0.932 | 0.978 | 0.913 | * | 2,3 |
| CV:mclust | 6 | 0.918 | 0.904 | 0.920 | * | 3,4,5 |
| ATC:skmeans | 5 | 0.908 | 0.981 | 0.946 | * | 4 |
| MAD:hclust | 5 | 0.907 | 0.996 | 0.945 | * | 2,3,4 |
| CV:hclust | 5 | 0.903 | 0.997 | 0.968 | * | 2,3,4 |
| ATC:kmeans | 3 | 0.758 | 0.966 | 0.912 | ||
| SD:kmeans | 5 | 0.721 | 0.960 | 0.826 | ||
| CV:kmeans | 5 | 0.719 | 0.954 | 0.811 | ||
| MAD:kmeans | 5 | 0.713 | 0.953 | 0.826 |
**: 1-PAC > 0.95, *: 1-PAC > 0.9
Cumulative distribution function curves of consensus matrix for all methods.
collect_plots(res_list, fun = plot_ecdf)
Consensus heatmaps for all methods. (What is a consensus heatmap?)
collect_plots(res_list, k = 2, fun = consensus_heatmap, mc.cores = 4)
collect_plots(res_list, k = 3, fun = consensus_heatmap, mc.cores = 4)
collect_plots(res_list, k = 4, fun = consensus_heatmap, mc.cores = 4)
collect_plots(res_list, k = 5, fun = consensus_heatmap, mc.cores = 4)
collect_plots(res_list, k = 6, fun = consensus_heatmap, mc.cores = 4)
Membership heatmaps for all methods. (What is a membership heatmap?)
collect_plots(res_list, k = 2, fun = membership_heatmap, mc.cores = 4)
collect_plots(res_list, k = 3, fun = membership_heatmap, mc.cores = 4)
collect_plots(res_list, k = 4, fun = membership_heatmap, mc.cores = 4)
collect_plots(res_list, k = 5, fun = membership_heatmap, mc.cores = 4)
collect_plots(res_list, k = 6, fun = membership_heatmap, mc.cores = 4)
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)
collect_plots(res_list, k = 3, fun = get_signatures, mc.cores = 4)
collect_plots(res_list, k = 4, fun = get_signatures, mc.cores = 4)
collect_plots(res_list, k = 5, fun = get_signatures, mc.cores = 4)
collect_plots(res_list, k = 6, fun = get_signatures, mc.cores = 4)
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 1.000 1.000 1.000 0.471 0.529 0.529
#> CV:NMF 2 1.000 1.000 1.000 0.471 0.529 0.529
#> MAD:NMF 2 1.000 1.000 1.000 0.471 0.529 0.529
#> ATC:NMF 2 0.933 0.930 0.972 0.442 0.557 0.557
#> SD:skmeans 2 1.000 1.000 1.000 0.471 0.529 0.529
#> CV:skmeans 2 1.000 1.000 1.000 0.471 0.529 0.529
#> MAD:skmeans 2 1.000 1.000 1.000 0.471 0.529 0.529
#> ATC:skmeans 2 0.751 0.955 0.972 0.476 0.529 0.529
#> SD:mclust 2 0.540 0.745 0.863 0.485 0.508 0.508
#> CV:mclust 2 0.479 0.743 0.865 0.486 0.508 0.508
#> MAD:mclust 2 0.675 0.806 0.903 0.482 0.508 0.508
#> ATC:mclust 2 0.291 0.765 0.839 0.477 0.506 0.506
#> SD:kmeans 2 0.508 0.873 0.878 0.434 0.529 0.529
#> CV:kmeans 2 0.289 0.872 0.886 0.433 0.529 0.529
#> MAD:kmeans 2 0.420 0.924 0.923 0.455 0.529 0.529
#> ATC:kmeans 2 0.506 0.725 0.796 0.389 0.675 0.675
#> SD:pam 2 1.000 0.984 0.992 0.459 0.540 0.540
#> CV:pam 2 1.000 0.977 0.989 0.456 0.540 0.540
#> MAD:pam 2 1.000 0.999 0.999 0.468 0.533 0.533
#> ATC:pam 2 0.506 0.783 0.793 0.400 0.533 0.533
#> SD:hclust 2 1.000 1.000 1.000 0.471 0.529 0.529
#> CV:hclust 2 1.000 1.000 1.000 0.471 0.529 0.529
#> MAD:hclust 2 1.000 1.000 1.000 0.471 0.529 0.529
#> ATC:hclust 2 1.000 1.000 1.000 0.326 0.675 0.675
get_stats(res_list, k = 3)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 3 0.963 0.962 0.975 0.372 0.827 0.673
#> CV:NMF 3 0.758 0.978 0.961 0.347 0.827 0.673
#> MAD:NMF 3 0.969 0.954 0.977 0.382 0.827 0.673
#> ATC:NMF 3 1.000 1.000 1.000 0.458 0.649 0.444
#> SD:skmeans 3 1.000 0.997 0.996 0.367 0.827 0.673
#> CV:skmeans 3 1.000 0.996 0.996 0.368 0.827 0.673
#> MAD:skmeans 3 0.819 0.956 0.961 0.367 0.827 0.673
#> ATC:skmeans 3 0.829 0.871 0.939 0.381 0.807 0.636
#> SD:mclust 3 0.810 0.959 0.971 0.315 0.719 0.507
#> CV:mclust 3 1.000 0.995 0.997 0.336 0.719 0.507
#> MAD:mclust 3 0.828 0.896 0.934 0.294 0.842 0.689
#> ATC:mclust 3 0.816 0.948 0.969 0.331 0.717 0.505
#> SD:kmeans 3 0.669 0.886 0.824 0.374 0.827 0.673
#> CV:kmeans 3 0.681 0.761 0.756 0.371 1.000 1.000
#> MAD:kmeans 3 0.669 0.605 0.690 0.334 0.827 0.673
#> ATC:kmeans 3 0.758 0.966 0.912 0.569 0.682 0.529
#> SD:pam 3 0.990 0.974 0.987 0.399 0.819 0.664
#> CV:pam 3 1.000 0.975 0.988 0.400 0.819 0.664
#> MAD:pam 3 0.981 0.962 0.983 0.385 0.814 0.654
#> ATC:pam 3 1.000 0.996 0.999 0.610 0.824 0.670
#> SD:hclust 3 1.000 1.000 1.000 0.143 0.933 0.873
#> CV:hclust 3 1.000 1.000 1.000 0.143 0.933 0.873
#> MAD:hclust 3 1.000 0.999 0.999 0.143 0.933 0.873
#> ATC:hclust 3 1.000 0.997 0.999 0.972 0.683 0.530
get_stats(res_list, k = 4)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 4 1.000 0.978 0.987 0.1066 0.933 0.811
#> CV:NMF 4 1.000 0.998 0.999 0.1216 0.933 0.811
#> MAD:NMF 4 0.877 0.946 0.946 0.1053 0.933 0.811
#> ATC:NMF 4 0.932 0.978 0.913 0.0665 0.933 0.811
#> SD:skmeans 4 1.000 0.990 0.976 0.1383 0.909 0.745
#> CV:skmeans 4 0.842 0.979 0.951 0.1354 0.909 0.745
#> MAD:skmeans 4 1.000 0.990 0.977 0.1383 0.909 0.745
#> ATC:skmeans 4 1.000 1.000 1.000 0.1174 0.890 0.691
#> SD:mclust 4 1.000 1.000 1.000 0.1163 0.939 0.825
#> CV:mclust 4 1.000 1.000 1.000 0.0966 0.939 0.825
#> MAD:mclust 4 1.000 1.000 1.000 0.1400 0.939 0.825
#> ATC:mclust 4 1.000 0.989 0.984 0.1217 0.930 0.802
#> SD:kmeans 4 0.667 0.855 0.774 0.1554 0.933 0.811
#> CV:kmeans 4 0.652 0.846 0.757 0.1595 0.759 0.546
#> MAD:kmeans 4 0.656 0.760 0.733 0.1472 0.819 0.594
#> ATC:kmeans 4 0.831 0.830 0.812 0.1472 1.000 1.000
#> SD:pam 4 1.000 0.988 0.994 0.1122 0.920 0.779
#> CV:pam 4 1.000 1.000 1.000 0.1150 0.920 0.779
#> MAD:pam 4 1.000 0.988 0.994 0.1393 0.904 0.732
#> ATC:pam 4 1.000 0.997 0.999 0.1463 0.906 0.738
#> SD:hclust 4 1.000 1.000 1.000 0.3216 0.827 0.625
#> CV:hclust 4 1.000 1.000 1.000 0.3216 0.827 0.625
#> MAD:hclust 4 1.000 1.000 1.000 0.3208 0.827 0.625
#> ATC:hclust 4 1.000 0.997 0.999 0.0157 0.989 0.969
get_stats(res_list, k = 5)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 5 1.000 1.000 1.000 0.1215 0.909 0.686
#> CV:NMF 5 1.000 1.000 1.000 0.1266 0.909 0.686
#> MAD:NMF 5 1.000 1.000 1.000 0.1147 0.909 0.686
#> ATC:NMF 5 0.851 0.973 0.895 0.1183 0.909 0.686
#> SD:skmeans 5 1.000 1.000 0.999 0.0935 0.933 0.747
#> CV:skmeans 5 1.000 0.999 0.998 0.0957 0.933 0.747
#> MAD:skmeans 5 1.000 1.000 0.999 0.0935 0.933 0.747
#> ATC:skmeans 5 0.908 0.981 0.946 0.0782 0.933 0.747
#> SD:mclust 5 1.000 0.996 0.998 0.1262 0.910 0.689
#> CV:mclust 5 1.000 0.996 0.995 0.1248 0.910 0.689
#> MAD:mclust 5 1.000 0.992 0.997 0.1258 0.910 0.689
#> ATC:mclust 5 1.000 0.960 0.984 0.1235 0.910 0.687
#> SD:kmeans 5 0.721 0.960 0.826 0.0864 0.909 0.686
#> CV:kmeans 5 0.719 0.954 0.811 0.0854 0.909 0.686
#> MAD:kmeans 5 0.713 0.953 0.826 0.0786 0.842 0.557
#> ATC:kmeans 5 0.783 0.942 0.791 0.0693 0.842 0.558
#> SD:pam 5 1.000 1.000 1.000 0.1239 0.909 0.686
#> CV:pam 5 1.000 1.000 1.000 0.1273 0.909 0.686
#> MAD:pam 5 1.000 1.000 1.000 0.0865 0.929 0.733
#> ATC:pam 5 1.000 0.995 0.998 0.0860 0.936 0.756
#> SD:hclust 5 1.000 1.000 1.000 0.1273 0.909 0.686
#> CV:hclust 5 0.903 0.997 0.968 0.1100 0.909 0.686
#> MAD:hclust 5 0.907 0.996 0.945 0.0961 0.909 0.686
#> ATC:hclust 5 0.821 0.909 0.891 0.1144 0.909 0.739
get_stats(res_list, k = 6)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 6 1.000 0.987 0.991 0.00352 1.000 1.000
#> CV:NMF 6 1.000 0.973 0.989 0.00439 0.995 0.977
#> MAD:NMF 6 1.000 0.988 0.990 0.00356 1.000 1.000
#> ATC:NMF 6 0.943 0.958 0.938 0.03161 0.998 0.990
#> SD:skmeans 6 0.971 0.955 0.956 0.01578 0.995 0.975
#> CV:skmeans 6 0.971 0.978 0.978 0.01128 0.995 0.975
#> MAD:skmeans 6 0.975 0.942 0.942 0.01847 1.000 1.000
#> ATC:skmeans 6 0.898 0.973 0.911 0.02377 0.975 0.875
#> SD:mclust 6 0.936 0.833 0.907 -0.00410 0.914 0.664
#> CV:mclust 6 0.918 0.904 0.920 0.00567 0.989 0.945
#> MAD:mclust 6 0.989 0.932 0.971 0.01694 0.991 0.957
#> ATC:mclust 6 0.973 0.914 0.953 0.01512 0.986 0.929
#> SD:kmeans 6 0.743 0.929 0.853 0.05674 1.000 1.000
#> CV:kmeans 6 0.734 0.924 0.830 0.05027 1.000 1.000
#> MAD:kmeans 6 0.745 0.918 0.831 0.04676 1.000 1.000
#> ATC:kmeans 6 0.757 0.907 0.829 0.05105 1.000 1.000
#> SD:pam 6 0.961 0.922 0.919 0.02086 0.989 0.943
#> CV:pam 6 0.979 0.965 0.967 0.02706 0.977 0.885
#> MAD:pam 6 0.975 0.975 0.969 0.02505 0.978 0.890
#> ATC:pam 6 1.000 0.989 0.996 0.02749 0.978 0.891
#> SD:hclust 6 1.000 0.978 0.990 0.00673 0.996 0.982
#> CV:hclust 6 1.000 0.974 0.991 0.02300 0.995 0.974
#> MAD:hclust 6 1.000 0.992 0.996 0.03414 0.996 0.982
#> ATC:hclust 6 0.847 0.959 0.903 0.05995 0.939 0.760
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)
collect_stats(res_list, k = 3)
collect_stats(res_list, k = 4)
collect_stats(res_list, k = 5)
collect_stats(res_list, k = 6)
Collect partitions from all methods:
collect_classes(res_list, k = 2)
collect_classes(res_list, k = 3)
collect_classes(res_list, k = 4)
collect_classes(res_list, k = 5)
collect_classes(res_list, k = 6)
Overlap of top rows from different top-row methods:
top_rows_overlap(res_list, top_n = 1000, method = "euler")
top_rows_overlap(res_list, top_n = 2000, method = "euler")
top_rows_overlap(res_list, top_n = 3000, method = "euler")
top_rows_overlap(res_list, top_n = 4000, method = "euler")
top_rows_overlap(res_list, top_n = 5000, method = "euler")
Also visualize the correspondance of rankings between different top-row methods:
top_rows_overlap(res_list, top_n = 1000, method = "correspondance")
top_rows_overlap(res_list, top_n = 2000, method = "correspondance")
top_rows_overlap(res_list, top_n = 3000, method = "correspondance")
top_rows_overlap(res_list, top_n = 4000, method = "correspondance")
top_rows_overlap(res_list, top_n = 5000, method = "correspondance")
Heatmaps of the top rows:
top_rows_heatmap(res_list, top_n = 1000)
top_rows_heatmap(res_list, top_n = 2000)
top_rows_heatmap(res_list, top_n = 3000)
top_rows_heatmap(res_list, top_n = 4000)
top_rows_heatmap(res_list, top_n = 5000)
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) disease.state(p) cell.type(p) k
#> SD:NMF 153 1 1.000 4.63e-32 2
#> CV:NMF 153 1 1.000 4.63e-32 2
#> MAD:NMF 153 1 1.000 4.63e-32 2
#> ATC:NMF 147 1 0.636 4.95e-24 2
#> SD:skmeans 153 1 1.000 4.63e-32 2
#> CV:skmeans 153 1 1.000 4.63e-32 2
#> MAD:skmeans 153 1 1.000 4.63e-32 2
#> ATC:skmeans 153 1 1.000 4.63e-32 2
#> SD:mclust 130 1 1.000 5.41e-28 2
#> CV:mclust 130 1 1.000 5.41e-28 2
#> MAD:mclust 122 1 1.000 2.86e-26 2
#> ATC:mclust 130 1 1.000 5.41e-28 2
#> SD:kmeans 153 1 1.000 4.63e-32 2
#> CV:kmeans 153 1 1.000 4.63e-32 2
#> MAD:kmeans 153 1 1.000 4.63e-32 2
#> ATC:kmeans 153 1 1.000 4.63e-32 2
#> SD:pam 152 1 0.839 3.81e-30 2
#> CV:pam 152 1 0.839 3.81e-30 2
#> MAD:pam 153 1 1.000 3.54e-31 2
#> ATC:pam 153 1 1.000 3.54e-31 2
#> SD:hclust 153 1 1.000 4.63e-32 2
#> CV:hclust 153 1 1.000 4.63e-32 2
#> MAD:hclust 153 1 1.000 4.63e-32 2
#> ATC:hclust 153 1 1.000 4.63e-32 2
test_to_known_factors(res_list, k = 3)
#> n individual(p) disease.state(p) cell.type(p) k
#> SD:NMF 153 1 0.985 2.17e-61 3
#> CV:NMF 153 1 0.985 2.17e-61 3
#> MAD:NMF 151 1 0.984 1.55e-60 3
#> ATC:NMF 153 1 0.985 2.17e-61 3
#> SD:skmeans 153 1 0.985 2.17e-61 3
#> CV:skmeans 153 1 0.985 2.17e-61 3
#> MAD:skmeans 153 1 0.985 2.17e-61 3
#> ATC:skmeans 151 1 0.900 1.67e-51 3
#> SD:mclust 153 1 0.956 2.17e-61 3
#> CV:mclust 153 1 0.956 2.17e-61 3
#> MAD:mclust 153 1 0.956 2.17e-61 3
#> ATC:mclust 153 1 0.946 1.66e-58 3
#> SD:kmeans 153 1 0.985 2.17e-61 3
#> CV:kmeans 153 1 1.000 4.63e-32 3
#> MAD:kmeans 119 1 0.978 1.50e-48 3
#> ATC:kmeans 153 1 0.981 2.32e-60 3
#> SD:pam 153 1 0.856 1.44e-58 3
#> CV:pam 153 1 0.856 1.44e-58 3
#> MAD:pam 150 1 0.974 4.41e-59 3
#> ATC:pam 153 1 0.981 2.32e-60 3
#> SD:hclust 153 1 0.875 2.17e-61 3
#> CV:hclust 153 1 0.875 2.17e-61 3
#> MAD:hclust 153 1 0.875 2.17e-61 3
#> ATC:hclust 153 1 0.937 2.02e-59 3
test_to_known_factors(res_list, k = 4)
#> n individual(p) disease.state(p) cell.type(p) k
#> SD:NMF 153 1 0.964 1.16e-90 4
#> CV:NMF 153 1 0.964 1.16e-90 4
#> MAD:NMF 153 1 0.964 1.16e-90 4
#> ATC:NMF 153 1 0.964 1.16e-90 4
#> SD:skmeans 153 1 0.996 1.16e-90 4
#> CV:skmeans 153 1 0.996 1.16e-90 4
#> MAD:skmeans 153 1 0.996 1.16e-90 4
#> ATC:skmeans 153 1 0.996 1.16e-90 4
#> SD:mclust 153 1 0.964 1.16e-90 4
#> CV:mclust 153 1 0.964 1.16e-90 4
#> MAD:mclust 153 1 0.964 1.16e-90 4
#> ATC:mclust 153 1 0.964 1.16e-90 4
#> SD:kmeans 153 1 0.964 1.16e-90 4
#> CV:kmeans 153 1 0.964 1.16e-90 4
#> MAD:kmeans 153 1 0.985 2.17e-61 4
#> ATC:kmeans 153 1 0.981 2.32e-60 4
#> SD:pam 153 1 0.964 1.16e-90 4
#> CV:pam 153 1 0.964 1.16e-90 4
#> MAD:pam 152 1 0.983 1.39e-88 4
#> ATC:pam 153 1 0.998 3.89e-89 4
#> SD:hclust 153 1 0.964 1.16e-90 4
#> CV:hclust 153 1 0.964 1.16e-90 4
#> MAD:hclust 153 1 0.964 1.16e-90 4
#> ATC:hclust 153 1 0.441 4.82e-60 4
test_to_known_factors(res_list, k = 5)
#> n individual(p) disease.state(p) cell.type(p) k
#> SD:NMF 153 1 0.989 6.51e-120 5
#> CV:NMF 153 1 0.989 6.51e-120 5
#> MAD:NMF 153 1 0.989 6.51e-120 5
#> ATC:NMF 153 1 0.989 6.51e-120 5
#> SD:skmeans 153 1 0.989 6.51e-120 5
#> CV:skmeans 153 1 0.989 6.51e-120 5
#> MAD:skmeans 153 1 0.989 6.51e-120 5
#> ATC:skmeans 153 1 0.989 6.51e-120 5
#> SD:mclust 153 1 0.933 3.93e-116 5
#> CV:mclust 153 1 0.933 3.93e-116 5
#> MAD:mclust 152 1 0.887 3.04e-115 5
#> ATC:mclust 149 1 0.982 1.61e-116 5
#> SD:kmeans 153 1 0.989 6.51e-120 5
#> CV:kmeans 153 1 0.989 6.51e-120 5
#> MAD:kmeans 153 1 0.989 6.51e-120 5
#> ATC:kmeans 153 1 0.998 1.57e-117 5
#> SD:pam 153 1 0.989 6.51e-120 5
#> CV:pam 153 1 0.989 6.51e-120 5
#> MAD:pam 153 1 0.989 6.51e-120 5
#> ATC:pam 153 1 0.998 1.57e-117 5
#> SD:hclust 153 1 0.989 6.51e-120 5
#> CV:hclust 153 1 0.989 6.51e-120 5
#> MAD:hclust 153 1 0.989 6.51e-120 5
#> ATC:hclust 153 1 0.605 2.71e-89 5
test_to_known_factors(res_list, k = 6)
#> n individual(p) disease.state(p) cell.type(p) k
#> SD:NMF 153 1 0.989 6.51e-120 6
#> CV:NMF 150 1 0.998 2.29e-117 6
#> MAD:NMF 153 1 0.989 6.51e-120 6
#> ATC:NMF 151 1 0.994 3.24e-118 6
#> SD:skmeans 153 1 0.662 8.52e-117 6
#> CV:skmeans 153 1 0.662 8.52e-117 6
#> MAD:skmeans 153 1 0.989 6.51e-120 6
#> ATC:skmeans 153 1 0.981 8.52e-117 6
#> SD:mclust 130 1 0.285 4.25e-94 6
#> CV:mclust 143 1 0.322 3.77e-106 6
#> MAD:mclust 150 1 0.431 6.60e-113 6
#> ATC:mclust 150 1 0.726 2.88e-114 6
#> SD:kmeans 153 1 0.989 6.51e-120 6
#> CV:kmeans 153 1 0.989 6.51e-120 6
#> MAD:kmeans 153 1 0.989 6.51e-120 6
#> ATC:kmeans 153 1 0.998 1.57e-117 6
#> SD:pam 150 1 0.984 2.88e-114 6
#> CV:pam 153 1 0.689 8.52e-117 6
#> MAD:pam 153 1 0.822 8.52e-117 6
#> ATC:pam 153 1 0.847 1.98e-114 6
#> SD:hclust 152 1 0.728 5.94e-116 6
#> CV:hclust 150 1 0.640 2.88e-114 6
#> MAD:hclust 153 1 0.740 8.52e-117 6
#> ATC:hclust 153 1 0.740 8.52e-117 6
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 1.000 1.00 0.47112 0.529 0.529
#> 3 3 1 1.000 1.00 0.14261 0.933 0.873
#> 4 4 1 1.000 1.00 0.32159 0.827 0.625
#> 5 5 1 1.000 1.00 0.12728 0.909 0.686
#> 6 6 1 0.978 0.99 0.00673 0.996 0.982
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 3 4
There is also optional best \(k\) = 2 3 4 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0 1 0 1
#> GSM247854 2 0 1 0 1
#> GSM247758 2 0 1 0 1
#> GSM247742 1 0 1 1 0
#> GSM247755 2 0 1 0 1
#> GSM247841 1 0 1 1 0
#> GSM247703 2 0 1 0 1
#> GSM247739 2 0 1 0 1
#> GSM247715 1 0 1 1 0
#> GSM247829 2 0 1 0 1
#> GSM247842 1 0 1 1 0
#> GSM247805 2 0 1 0 1
#> GSM247786 2 0 1 0 1
#> GSM247812 2 0 1 0 1
#> GSM247776 1 0 1 1 0
#> GSM247850 1 0 1 1 0
#> GSM247717 2 0 1 0 1
#> GSM247784 2 0 1 0 1
#> GSM247834 1 0 1 1 0
#> GSM247783 2 0 1 0 1
#> GSM247846 1 0 1 1 0
#> GSM247822 2 0 1 0 1
#> GSM247710 2 0 1 0 1
#> GSM247713 1 0 1 1 0
#> GSM247840 2 0 1 0 1
#> GSM247733 1 0 1 1 0
#> GSM247852 1 0 1 1 0
#> GSM247790 2 0 1 0 1
#> GSM247730 2 0 1 0 1
#> GSM247824 2 0 1 0 1
#> GSM247770 1 0 1 1 0
#> GSM247711 2 0 1 0 1
#> GSM247782 2 0 1 0 1
#> GSM247836 1 0 1 1 0
#> GSM247785 2 0 1 0 1
#> GSM247847 1 0 1 1 0
#> GSM247750 2 0 1 0 1
#> GSM247788 2 0 1 0 1
#> GSM247849 1 0 1 1 0
#> GSM247772 2 0 1 0 1
#> GSM247760 1 0 1 1 0
#> GSM247764 2 0 1 0 1
#> GSM247851 2 0 1 0 1
#> GSM247714 2 0 1 0 1
#> GSM247828 1 0 1 1 0
#> GSM247704 2 0 1 0 1
#> GSM247818 1 0 1 1 0
#> GSM247823 2 0 1 0 1
#> GSM247706 2 0 1 0 1
#> GSM247835 2 0 1 0 1
#> GSM247734 1 0 1 1 0
#> GSM247819 2 0 1 0 1
#> GSM247809 2 0 1 0 1
#> GSM247830 2 0 1 0 1
#> GSM247833 1 0 1 1 0
#> GSM247738 2 0 1 0 1
#> GSM247716 2 0 1 0 1
#> GSM247747 2 0 1 0 1
#> GSM247722 1 0 1 1 0
#> GSM247816 2 0 1 0 1
#> GSM247839 2 0 1 0 1
#> GSM247821 1 0 1 1 0
#> GSM247798 2 0 1 0 1
#> GSM247838 1 0 1 1 0
#> GSM247721 2 0 1 0 1
#> GSM247781 2 0 1 0 1
#> GSM247762 1 0 1 1 0
#> GSM247825 2 0 1 0 1
#> GSM247777 1 0 1 1 0
#> GSM247761 2 0 1 0 1
#> GSM247720 2 0 1 0 1
#> GSM247814 2 0 1 0 1
#> GSM247732 1 0 1 1 0
#> GSM247708 2 0 1 0 1
#> GSM247740 2 0 1 0 1
#> GSM247749 1 0 1 1 0
#> GSM247767 2 0 1 0 1
#> GSM247748 1 0 1 1 0
#> GSM247705 2 0 1 0 1
#> GSM247746 2 0 1 0 1
#> GSM247752 1 0 1 1 0
#> GSM247769 2 0 1 0 1
#> GSM247753 1 0 1 1 0
#> GSM247723 2 0 1 0 1
#> GSM247779 2 0 1 0 1
#> GSM247756 1 0 1 1 0
#> GSM247826 2 0 1 0 1
#> GSM247775 1 0 1 1 0
#> GSM247741 2 0 1 0 1
#> GSM247799 2 0 1 0 1
#> GSM247778 1 0 1 1 0
#> GSM247806 2 0 1 0 1
#> GSM247815 1 0 1 1 0
#> GSM247735 2 0 1 0 1
#> GSM247831 2 0 1 0 1
#> GSM247845 1 0 1 1 0
#> GSM247791 2 0 1 0 1
#> GSM247780 1 0 1 1 0
#> GSM247853 1 0 1 1 0
#> GSM247800 2 0 1 0 1
#> GSM247729 2 0 1 0 1
#> GSM247810 1 0 1 1 0
#> GSM247844 2 0 1 0 1
#> GSM247793 1 0 1 1 0
#> GSM247759 2 0 1 0 1
#> GSM247724 2 0 1 0 1
#> GSM247817 2 0 1 0 1
#> GSM247727 1 0 1 1 0
#> GSM247796 2 0 1 0 1
#> GSM247725 2 0 1 0 1
#> GSM247801 1 0 1 1 0
#> GSM247731 2 0 1 0 1
#> GSM247765 1 0 1 1 0
#> GSM247792 2 0 1 0 1
#> GSM247726 2 0 1 0 1
#> GSM247803 1 0 1 1 0
#> GSM247728 2 0 1 0 1
#> GSM247768 1 0 1 1 0
#> GSM247745 2 0 1 0 1
#> GSM247855 2 0 1 0 1
#> GSM247804 2 0 1 0 1
#> GSM247774 1 0 1 1 0
#> GSM247807 2 0 1 0 1
#> GSM247813 1 0 1 1 0
#> GSM247736 2 0 1 0 1
#> GSM247712 2 0 1 0 1
#> GSM247797 1 0 1 1 0
#> GSM247743 2 0 1 0 1
#> GSM247719 1 0 1 1 0
#> GSM247707 2 0 1 0 1
#> GSM247737 2 0 1 0 1
#> GSM247827 2 0 1 0 1
#> GSM247848 1 0 1 1 0
#> GSM247794 2 0 1 0 1
#> GSM247757 2 0 1 0 1
#> GSM247744 1 0 1 1 0
#> GSM247751 2 0 1 0 1
#> GSM247837 1 0 1 1 0
#> GSM247754 2 0 1 0 1
#> GSM247789 2 0 1 0 1
#> GSM247802 1 0 1 1 0
#> GSM247771 2 0 1 0 1
#> GSM247763 1 0 1 1 0
#> GSM247808 2 0 1 0 1
#> GSM247787 2 0 1 0 1
#> GSM247843 1 0 1 1 0
#> GSM247811 2 0 1 0 1
#> GSM247773 1 0 1 1 0
#> GSM247766 2 0 1 0 1
#> GSM247718 2 0 1 0 1
#> GSM247832 1 0 1 1 0
#> GSM247709 2 0 1 0 1
#> GSM247820 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0 1 0 1 0
#> GSM247854 2 0 1 0 1 0
#> GSM247758 2 0 1 0 1 0
#> GSM247742 3 0 1 0 0 1
#> GSM247755 2 0 1 0 1 0
#> GSM247841 1 0 1 1 0 0
#> GSM247703 2 0 1 0 1 0
#> GSM247739 2 0 1 0 1 0
#> GSM247715 3 0 1 0 0 1
#> GSM247829 2 0 1 0 1 0
#> GSM247842 1 0 1 1 0 0
#> GSM247805 2 0 1 0 1 0
#> GSM247786 2 0 1 0 1 0
#> GSM247812 2 0 1 0 1 0
#> GSM247776 1 0 1 1 0 0
#> GSM247850 1 0 1 1 0 0
#> GSM247717 2 0 1 0 1 0
#> GSM247784 2 0 1 0 1 0
#> GSM247834 3 0 1 0 0 1
#> GSM247783 2 0 1 0 1 0
#> GSM247846 1 0 1 1 0 0
#> GSM247822 2 0 1 0 1 0
#> GSM247710 2 0 1 0 1 0
#> GSM247713 3 0 1 0 0 1
#> GSM247840 2 0 1 0 1 0
#> GSM247733 1 0 1 1 0 0
#> GSM247852 1 0 1 1 0 0
#> GSM247790 2 0 1 0 1 0
#> GSM247730 2 0 1 0 1 0
#> GSM247824 2 0 1 0 1 0
#> GSM247770 1 0 1 1 0 0
#> GSM247711 2 0 1 0 1 0
#> GSM247782 2 0 1 0 1 0
#> GSM247836 3 0 1 0 0 1
#> GSM247785 2 0 1 0 1 0
#> GSM247847 1 0 1 1 0 0
#> GSM247750 2 0 1 0 1 0
#> GSM247788 2 0 1 0 1 0
#> GSM247849 3 0 1 0 0 1
#> GSM247772 2 0 1 0 1 0
#> GSM247760 1 0 1 1 0 0
#> GSM247764 2 0 1 0 1 0
#> GSM247851 2 0 1 0 1 0
#> GSM247714 2 0 1 0 1 0
#> GSM247828 3 0 1 0 0 1
#> GSM247704 2 0 1 0 1 0
#> GSM247818 1 0 1 1 0 0
#> GSM247823 2 0 1 0 1 0
#> GSM247706 2 0 1 0 1 0
#> GSM247835 2 0 1 0 1 0
#> GSM247734 1 0 1 1 0 0
#> GSM247819 2 0 1 0 1 0
#> GSM247809 2 0 1 0 1 0
#> GSM247830 2 0 1 0 1 0
#> GSM247833 1 0 1 1 0 0
#> GSM247738 2 0 1 0 1 0
#> GSM247716 2 0 1 0 1 0
#> GSM247747 2 0 1 0 1 0
#> GSM247722 1 0 1 1 0 0
#> GSM247816 2 0 1 0 1 0
#> GSM247839 2 0 1 0 1 0
#> GSM247821 3 0 1 0 0 1
#> GSM247798 2 0 1 0 1 0
#> GSM247838 1 0 1 1 0 0
#> GSM247721 2 0 1 0 1 0
#> GSM247781 2 0 1 0 1 0
#> GSM247762 3 0 1 0 0 1
#> GSM247825 2 0 1 0 1 0
#> GSM247777 1 0 1 1 0 0
#> GSM247761 2 0 1 0 1 0
#> GSM247720 2 0 1 0 1 0
#> GSM247814 2 0 1 0 1 0
#> GSM247732 1 0 1 1 0 0
#> GSM247708 2 0 1 0 1 0
#> GSM247740 2 0 1 0 1 0
#> GSM247749 3 0 1 0 0 1
#> GSM247767 2 0 1 0 1 0
#> GSM247748 1 0 1 1 0 0
#> GSM247705 2 0 1 0 1 0
#> GSM247746 2 0 1 0 1 0
#> GSM247752 3 0 1 0 0 1
#> GSM247769 2 0 1 0 1 0
#> GSM247753 1 0 1 1 0 0
#> GSM247723 2 0 1 0 1 0
#> GSM247779 2 0 1 0 1 0
#> GSM247756 3 0 1 0 0 1
#> GSM247826 2 0 1 0 1 0
#> GSM247775 1 0 1 1 0 0
#> GSM247741 2 0 1 0 1 0
#> GSM247799 2 0 1 0 1 0
#> GSM247778 3 0 1 0 0 1
#> GSM247806 2 0 1 0 1 0
#> GSM247815 1 0 1 1 0 0
#> GSM247735 2 0 1 0 1 0
#> GSM247831 2 0 1 0 1 0
#> GSM247845 3 0 1 0 0 1
#> GSM247791 2 0 1 0 1 0
#> GSM247780 1 0 1 1 0 0
#> GSM247853 1 0 1 1 0 0
#> GSM247800 2 0 1 0 1 0
#> GSM247729 2 0 1 0 1 0
#> GSM247810 3 0 1 0 0 1
#> GSM247844 2 0 1 0 1 0
#> GSM247793 1 0 1 1 0 0
#> GSM247759 2 0 1 0 1 0
#> GSM247724 2 0 1 0 1 0
#> GSM247817 2 0 1 0 1 0
#> GSM247727 1 0 1 1 0 0
#> GSM247796 2 0 1 0 1 0
#> GSM247725 2 0 1 0 1 0
#> GSM247801 3 0 1 0 0 1
#> GSM247731 2 0 1 0 1 0
#> GSM247765 1 0 1 1 0 0
#> GSM247792 2 0 1 0 1 0
#> GSM247726 2 0 1 0 1 0
#> GSM247803 3 0 1 0 0 1
#> GSM247728 2 0 1 0 1 0
#> GSM247768 1 0 1 1 0 0
#> GSM247745 2 0 1 0 1 0
#> GSM247855 2 0 1 0 1 0
#> GSM247804 2 0 1 0 1 0
#> GSM247774 3 0 1 0 0 1
#> GSM247807 2 0 1 0 1 0
#> GSM247813 1 0 1 1 0 0
#> GSM247736 2 0 1 0 1 0
#> GSM247712 2 0 1 0 1 0
#> GSM247797 3 0 1 0 0 1
#> GSM247743 2 0 1 0 1 0
#> GSM247719 1 0 1 1 0 0
#> GSM247707 2 0 1 0 1 0
#> GSM247737 2 0 1 0 1 0
#> GSM247827 2 0 1 0 1 0
#> GSM247848 1 0 1 1 0 0
#> GSM247794 2 0 1 0 1 0
#> GSM247757 2 0 1 0 1 0
#> GSM247744 3 0 1 0 0 1
#> GSM247751 2 0 1 0 1 0
#> GSM247837 1 0 1 1 0 0
#> GSM247754 2 0 1 0 1 0
#> GSM247789 2 0 1 0 1 0
#> GSM247802 3 0 1 0 0 1
#> GSM247771 2 0 1 0 1 0
#> GSM247763 1 0 1 1 0 0
#> GSM247808 2 0 1 0 1 0
#> GSM247787 2 0 1 0 1 0
#> GSM247843 3 0 1 0 0 1
#> GSM247811 2 0 1 0 1 0
#> GSM247773 1 0 1 1 0 0
#> GSM247766 2 0 1 0 1 0
#> GSM247718 2 0 1 0 1 0
#> GSM247832 3 0 1 0 0 1
#> GSM247709 2 0 1 0 1 0
#> GSM247820 1 0 1 1 0 0
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0 1 0 1 0 0
#> GSM247854 2 0 1 0 1 0 0
#> GSM247758 2 0 1 0 1 0 0
#> GSM247742 4 0 1 0 0 0 1
#> GSM247755 3 0 1 0 0 1 0
#> GSM247841 1 0 1 1 0 0 0
#> GSM247703 2 0 1 0 1 0 0
#> GSM247739 2 0 1 0 1 0 0
#> GSM247715 4 0 1 0 0 0 1
#> GSM247829 3 0 1 0 0 1 0
#> GSM247842 1 0 1 1 0 0 0
#> GSM247805 2 0 1 0 1 0 0
#> GSM247786 2 0 1 0 1 0 0
#> GSM247812 3 0 1 0 0 1 0
#> GSM247776 1 0 1 1 0 0 0
#> GSM247850 1 0 1 1 0 0 0
#> GSM247717 2 0 1 0 1 0 0
#> GSM247784 2 0 1 0 1 0 0
#> GSM247834 4 0 1 0 0 0 1
#> GSM247783 3 0 1 0 0 1 0
#> GSM247846 1 0 1 1 0 0 0
#> GSM247822 2 0 1 0 1 0 0
#> GSM247710 2 0 1 0 1 0 0
#> GSM247713 4 0 1 0 0 0 1
#> GSM247840 3 0 1 0 0 1 0
#> GSM247733 1 0 1 1 0 0 0
#> GSM247852 1 0 1 1 0 0 0
#> GSM247790 2 0 1 0 1 0 0
#> GSM247730 2 0 1 0 1 0 0
#> GSM247824 3 0 1 0 0 1 0
#> GSM247770 1 0 1 1 0 0 0
#> GSM247711 2 0 1 0 1 0 0
#> GSM247782 2 0 1 0 1 0 0
#> GSM247836 4 0 1 0 0 0 1
#> GSM247785 3 0 1 0 0 1 0
#> GSM247847 1 0 1 1 0 0 0
#> GSM247750 2 0 1 0 1 0 0
#> GSM247788 2 0 1 0 1 0 0
#> GSM247849 4 0 1 0 0 0 1
#> GSM247772 3 0 1 0 0 1 0
#> GSM247760 1 0 1 1 0 0 0
#> GSM247764 2 0 1 0 1 0 0
#> GSM247851 2 0 1 0 1 0 0
#> GSM247714 2 0 1 0 1 0 0
#> GSM247828 4 0 1 0 0 0 1
#> GSM247704 3 0 1 0 0 1 0
#> GSM247818 1 0 1 1 0 0 0
#> GSM247823 2 0 1 0 1 0 0
#> GSM247706 2 0 1 0 1 0 0
#> GSM247835 3 0 1 0 0 1 0
#> GSM247734 1 0 1 1 0 0 0
#> GSM247819 2 0 1 0 1 0 0
#> GSM247809 2 0 1 0 1 0 0
#> GSM247830 3 0 1 0 0 1 0
#> GSM247833 1 0 1 1 0 0 0
#> GSM247738 2 0 1 0 1 0 0
#> GSM247716 2 0 1 0 1 0 0
#> GSM247747 3 0 1 0 0 1 0
#> GSM247722 1 0 1 1 0 0 0
#> GSM247816 2 0 1 0 1 0 0
#> GSM247839 2 0 1 0 1 0 0
#> GSM247821 4 0 1 0 0 0 1
#> GSM247798 3 0 1 0 0 1 0
#> GSM247838 1 0 1 1 0 0 0
#> GSM247721 2 0 1 0 1 0 0
#> GSM247781 2 0 1 0 1 0 0
#> GSM247762 4 0 1 0 0 0 1
#> GSM247825 3 0 1 0 0 1 0
#> GSM247777 1 0 1 1 0 0 0
#> GSM247761 2 0 1 0 1 0 0
#> GSM247720 2 0 1 0 1 0 0
#> GSM247814 3 0 1 0 0 1 0
#> GSM247732 1 0 1 1 0 0 0
#> GSM247708 2 0 1 0 1 0 0
#> GSM247740 2 0 1 0 1 0 0
#> GSM247749 4 0 1 0 0 0 1
#> GSM247767 3 0 1 0 0 1 0
#> GSM247748 1 0 1 1 0 0 0
#> GSM247705 2 0 1 0 1 0 0
#> GSM247746 2 0 1 0 1 0 0
#> GSM247752 4 0 1 0 0 0 1
#> GSM247769 3 0 1 0 0 1 0
#> GSM247753 1 0 1 1 0 0 0
#> GSM247723 2 0 1 0 1 0 0
#> GSM247779 2 0 1 0 1 0 0
#> GSM247756 4 0 1 0 0 0 1
#> GSM247826 3 0 1 0 0 1 0
#> GSM247775 1 0 1 1 0 0 0
#> GSM247741 2 0 1 0 1 0 0
#> GSM247799 2 0 1 0 1 0 0
#> GSM247778 4 0 1 0 0 0 1
#> GSM247806 3 0 1 0 0 1 0
#> GSM247815 1 0 1 1 0 0 0
#> GSM247735 2 0 1 0 1 0 0
#> GSM247831 2 0 1 0 1 0 0
#> GSM247845 4 0 1 0 0 0 1
#> GSM247791 3 0 1 0 0 1 0
#> GSM247780 1 0 1 1 0 0 0
#> GSM247853 1 0 1 1 0 0 0
#> GSM247800 2 0 1 0 1 0 0
#> GSM247729 2 0 1 0 1 0 0
#> GSM247810 4 0 1 0 0 0 1
#> GSM247844 3 0 1 0 0 1 0
#> GSM247793 1 0 1 1 0 0 0
#> GSM247759 2 0 1 0 1 0 0
#> GSM247724 2 0 1 0 1 0 0
#> GSM247817 3 0 1 0 0 1 0
#> GSM247727 1 0 1 1 0 0 0
#> GSM247796 2 0 1 0 1 0 0
#> GSM247725 2 0 1 0 1 0 0
#> GSM247801 4 0 1 0 0 0 1
#> GSM247731 3 0 1 0 0 1 0
#> GSM247765 1 0 1 1 0 0 0
#> GSM247792 2 0 1 0 1 0 0
#> GSM247726 2 0 1 0 1 0 0
#> GSM247803 4 0 1 0 0 0 1
#> GSM247728 3 0 1 0 0 1 0
#> GSM247768 1 0 1 1 0 0 0
#> GSM247745 2 0 1 0 1 0 0
#> GSM247855 2 0 1 0 1 0 0
#> GSM247804 2 0 1 0 1 0 0
#> GSM247774 4 0 1 0 0 0 1
#> GSM247807 3 0 1 0 0 1 0
#> GSM247813 1 0 1 1 0 0 0
#> GSM247736 2 0 1 0 1 0 0
#> GSM247712 2 0 1 0 1 0 0
#> GSM247797 4 0 1 0 0 0 1
#> GSM247743 3 0 1 0 0 1 0
#> GSM247719 1 0 1 1 0 0 0
#> GSM247707 2 0 1 0 1 0 0
#> GSM247737 2 0 1 0 1 0 0
#> GSM247827 3 0 1 0 0 1 0
#> GSM247848 1 0 1 1 0 0 0
#> GSM247794 2 0 1 0 1 0 0
#> GSM247757 2 0 1 0 1 0 0
#> GSM247744 4 0 1 0 0 0 1
#> GSM247751 3 0 1 0 0 1 0
#> GSM247837 1 0 1 1 0 0 0
#> GSM247754 2 0 1 0 1 0 0
#> GSM247789 2 0 1 0 1 0 0
#> GSM247802 4 0 1 0 0 0 1
#> GSM247771 3 0 1 0 0 1 0
#> GSM247763 1 0 1 1 0 0 0
#> GSM247808 2 0 1 0 1 0 0
#> GSM247787 2 0 1 0 1 0 0
#> GSM247843 4 0 1 0 0 0 1
#> GSM247811 3 0 1 0 0 1 0
#> GSM247773 1 0 1 1 0 0 0
#> GSM247766 2 0 1 0 1 0 0
#> GSM247718 2 0 1 0 1 0 0
#> GSM247832 4 0 1 0 0 0 1
#> GSM247709 3 0 1 0 0 1 0
#> GSM247820 1 0 1 1 0 0 0
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0 1 0 1 0 0 0
#> GSM247854 2 0 1 0 1 0 0 0
#> GSM247758 5 0 1 0 0 0 0 1
#> GSM247742 4 0 1 0 0 0 1 0
#> GSM247755 3 0 1 0 0 1 0 0
#> GSM247841 1 0 1 1 0 0 0 0
#> GSM247703 2 0 1 0 1 0 0 0
#> GSM247739 5 0 1 0 0 0 0 1
#> GSM247715 4 0 1 0 0 0 1 0
#> GSM247829 3 0 1 0 0 1 0 0
#> GSM247842 1 0 1 1 0 0 0 0
#> GSM247805 2 0 1 0 1 0 0 0
#> GSM247786 5 0 1 0 0 0 0 1
#> GSM247812 3 0 1 0 0 1 0 0
#> GSM247776 1 0 1 1 0 0 0 0
#> GSM247850 1 0 1 1 0 0 0 0
#> GSM247717 2 0 1 0 1 0 0 0
#> GSM247784 5 0 1 0 0 0 0 1
#> GSM247834 4 0 1 0 0 0 1 0
#> GSM247783 3 0 1 0 0 1 0 0
#> GSM247846 1 0 1 1 0 0 0 0
#> GSM247822 2 0 1 0 1 0 0 0
#> GSM247710 5 0 1 0 0 0 0 1
#> GSM247713 4 0 1 0 0 0 1 0
#> GSM247840 3 0 1 0 0 1 0 0
#> GSM247733 1 0 1 1 0 0 0 0
#> GSM247852 1 0 1 1 0 0 0 0
#> GSM247790 2 0 1 0 1 0 0 0
#> GSM247730 5 0 1 0 0 0 0 1
#> GSM247824 3 0 1 0 0 1 0 0
#> GSM247770 1 0 1 1 0 0 0 0
#> GSM247711 2 0 1 0 1 0 0 0
#> GSM247782 5 0 1 0 0 0 0 1
#> GSM247836 4 0 1 0 0 0 1 0
#> GSM247785 3 0 1 0 0 1 0 0
#> GSM247847 1 0 1 1 0 0 0 0
#> GSM247750 2 0 1 0 1 0 0 0
#> GSM247788 5 0 1 0 0 0 0 1
#> GSM247849 4 0 1 0 0 0 1 0
#> GSM247772 3 0 1 0 0 1 0 0
#> GSM247760 1 0 1 1 0 0 0 0
#> GSM247764 2 0 1 0 1 0 0 0
#> GSM247851 2 0 1 0 1 0 0 0
#> GSM247714 5 0 1 0 0 0 0 1
#> GSM247828 4 0 1 0 0 0 1 0
#> GSM247704 3 0 1 0 0 1 0 0
#> GSM247818 1 0 1 1 0 0 0 0
#> GSM247823 2 0 1 0 1 0 0 0
#> GSM247706 5 0 1 0 0 0 0 1
#> GSM247835 3 0 1 0 0 1 0 0
#> GSM247734 1 0 1 1 0 0 0 0
#> GSM247819 2 0 1 0 1 0 0 0
#> GSM247809 5 0 1 0 0 0 0 1
#> GSM247830 3 0 1 0 0 1 0 0
#> GSM247833 1 0 1 1 0 0 0 0
#> GSM247738 2 0 1 0 1 0 0 0
#> GSM247716 5 0 1 0 0 0 0 1
#> GSM247747 3 0 1 0 0 1 0 0
#> GSM247722 1 0 1 1 0 0 0 0
#> GSM247816 2 0 1 0 1 0 0 0
#> GSM247839 5 0 1 0 0 0 0 1
#> GSM247821 4 0 1 0 0 0 1 0
#> GSM247798 3 0 1 0 0 1 0 0
#> GSM247838 1 0 1 1 0 0 0 0
#> GSM247721 2 0 1 0 1 0 0 0
#> GSM247781 5 0 1 0 0 0 0 1
#> GSM247762 4 0 1 0 0 0 1 0
#> GSM247825 3 0 1 0 0 1 0 0
#> GSM247777 1 0 1 1 0 0 0 0
#> GSM247761 2 0 1 0 1 0 0 0
#> GSM247720 5 0 1 0 0 0 0 1
#> GSM247814 3 0 1 0 0 1 0 0
#> GSM247732 1 0 1 1 0 0 0 0
#> GSM247708 2 0 1 0 1 0 0 0
#> GSM247740 5 0 1 0 0 0 0 1
#> GSM247749 4 0 1 0 0 0 1 0
#> GSM247767 3 0 1 0 0 1 0 0
#> GSM247748 1 0 1 1 0 0 0 0
#> GSM247705 2 0 1 0 1 0 0 0
#> GSM247746 5 0 1 0 0 0 0 1
#> GSM247752 4 0 1 0 0 0 1 0
#> GSM247769 3 0 1 0 0 1 0 0
#> GSM247753 1 0 1 1 0 0 0 0
#> GSM247723 2 0 1 0 1 0 0 0
#> GSM247779 5 0 1 0 0 0 0 1
#> GSM247756 4 0 1 0 0 0 1 0
#> GSM247826 3 0 1 0 0 1 0 0
#> GSM247775 1 0 1 1 0 0 0 0
#> GSM247741 2 0 1 0 1 0 0 0
#> GSM247799 5 0 1 0 0 0 0 1
#> GSM247778 4 0 1 0 0 0 1 0
#> GSM247806 3 0 1 0 0 1 0 0
#> GSM247815 1 0 1 1 0 0 0 0
#> GSM247735 2 0 1 0 1 0 0 0
#> GSM247831 5 0 1 0 0 0 0 1
#> GSM247845 4 0 1 0 0 0 1 0
#> GSM247791 3 0 1 0 0 1 0 0
#> GSM247780 1 0 1 1 0 0 0 0
#> GSM247853 1 0 1 1 0 0 0 0
#> GSM247800 2 0 1 0 1 0 0 0
#> GSM247729 5 0 1 0 0 0 0 1
#> GSM247810 4 0 1 0 0 0 1 0
#> GSM247844 3 0 1 0 0 1 0 0
#> GSM247793 1 0 1 1 0 0 0 0
#> GSM247759 2 0 1 0 1 0 0 0
#> GSM247724 5 0 1 0 0 0 0 1
#> GSM247817 3 0 1 0 0 1 0 0
#> GSM247727 1 0 1 1 0 0 0 0
#> GSM247796 2 0 1 0 1 0 0 0
#> GSM247725 5 0 1 0 0 0 0 1
#> GSM247801 4 0 1 0 0 0 1 0
#> GSM247731 3 0 1 0 0 1 0 0
#> GSM247765 1 0 1 1 0 0 0 0
#> GSM247792 2 0 1 0 1 0 0 0
#> GSM247726 5 0 1 0 0 0 0 1
#> GSM247803 4 0 1 0 0 0 1 0
#> GSM247728 3 0 1 0 0 1 0 0
#> GSM247768 1 0 1 1 0 0 0 0
#> GSM247745 2 0 1 0 1 0 0 0
#> GSM247855 2 0 1 0 1 0 0 0
#> GSM247804 5 0 1 0 0 0 0 1
#> GSM247774 4 0 1 0 0 0 1 0
#> GSM247807 3 0 1 0 0 1 0 0
#> GSM247813 1 0 1 1 0 0 0 0
#> GSM247736 2 0 1 0 1 0 0 0
#> GSM247712 5 0 1 0 0 0 0 1
#> GSM247797 4 0 1 0 0 0 1 0
#> GSM247743 3 0 1 0 0 1 0 0
#> GSM247719 1 0 1 1 0 0 0 0
#> GSM247707 2 0 1 0 1 0 0 0
#> GSM247737 5 0 1 0 0 0 0 1
#> GSM247827 3 0 1 0 0 1 0 0
#> GSM247848 1 0 1 1 0 0 0 0
#> GSM247794 2 0 1 0 1 0 0 0
#> GSM247757 5 0 1 0 0 0 0 1
#> GSM247744 4 0 1 0 0 0 1 0
#> GSM247751 3 0 1 0 0 1 0 0
#> GSM247837 1 0 1 1 0 0 0 0
#> GSM247754 2 0 1 0 1 0 0 0
#> GSM247789 5 0 1 0 0 0 0 1
#> GSM247802 4 0 1 0 0 0 1 0
#> GSM247771 3 0 1 0 0 1 0 0
#> GSM247763 1 0 1 1 0 0 0 0
#> GSM247808 2 0 1 0 1 0 0 0
#> GSM247787 5 0 1 0 0 0 0 1
#> GSM247843 4 0 1 0 0 0 1 0
#> GSM247811 3 0 1 0 0 1 0 0
#> GSM247773 1 0 1 1 0 0 0 0
#> GSM247766 2 0 1 0 1 0 0 0
#> GSM247718 5 0 1 0 0 0 0 1
#> GSM247832 4 0 1 0 0 0 1 0
#> GSM247709 3 0 1 0 0 1 0 0
#> GSM247820 1 0 1 1 0 0 0 0
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247854 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247758 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247742 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247755 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247841 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247703 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247739 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247715 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247829 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247842 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247805 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247786 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247812 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247776 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247850 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247717 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247784 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247834 4 0.133 0.896 0 0 0 0.936 0 0.064
#> GSM247783 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247846 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247822 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247710 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247713 4 0.352 0.574 0 0 0 0.676 0 0.324
#> GSM247840 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247733 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247852 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247790 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247730 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247824 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247770 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247711 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247782 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247836 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247785 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247847 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247750 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247788 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247849 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247772 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247760 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247764 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247851 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247714 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247828 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247704 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247818 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247823 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247706 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247835 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247734 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247819 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247809 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247830 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247833 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247738 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247716 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247747 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247722 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247816 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247839 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247821 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247798 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247838 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247721 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247781 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247762 4 0.386 0.243 0 0 0 0.532 0 0.468
#> GSM247825 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247777 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247761 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247720 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247814 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247732 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247708 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247740 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247749 4 0.144 0.891 0 0 0 0.928 0 0.072
#> GSM247767 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247748 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247705 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247746 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247752 6 0.107 0.941 0 0 0 0.048 0 0.952
#> GSM247769 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247753 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247723 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247779 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247756 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247826 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247775 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247741 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247799 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247778 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247806 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247815 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247735 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247831 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247845 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247791 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247780 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247853 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247800 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247729 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247810 4 0.127 0.898 0 0 0 0.940 0 0.060
#> GSM247844 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247793 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247759 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247724 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247817 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247727 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247796 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247725 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247801 4 0.156 0.885 0 0 0 0.920 0 0.080
#> GSM247731 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247765 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247792 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247726 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247803 6 0.000 0.944 0 0 0 0.000 0 1.000
#> GSM247728 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247768 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247745 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247855 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247804 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247774 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247807 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247813 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247736 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247712 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247797 4 0.363 0.519 0 0 0 0.644 0 0.356
#> GSM247743 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247719 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247707 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247737 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247827 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247848 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247794 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247757 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247744 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247751 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247837 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247754 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247789 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247802 4 0.139 0.894 0 0 0 0.932 0 0.068
#> GSM247771 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247763 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247808 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247787 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247843 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247811 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247773 1 0.000 1.000 1 0 0 0.000 0 0.000
#> GSM247766 2 0.000 1.000 0 1 0 0.000 0 0.000
#> GSM247718 5 0.000 1.000 0 0 0 0.000 1 0.000
#> GSM247832 4 0.000 0.922 0 0 0 1.000 0 0.000
#> GSM247709 3 0.000 1.000 0 0 1 0.000 0 0.000
#> GSM247820 1 0.000 1.000 1 0 0 0.000 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
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
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> SD:hclust 153 1 1.000 4.63e-32 2
#> SD:hclust 153 1 0.875 2.17e-61 3
#> SD:hclust 153 1 0.964 1.16e-90 4
#> SD:hclust 153 1 0.989 6.51e-120 5
#> SD:hclust 152 1 0.728 5.94e-116 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.508 0.873 0.878 0.4345 0.529 0.529
#> 3 3 0.669 0.886 0.824 0.3742 0.827 0.673
#> 4 4 0.667 0.855 0.774 0.1554 0.933 0.811
#> 5 5 0.721 0.960 0.826 0.0864 0.909 0.686
#> 6 6 0.743 0.929 0.853 0.0567 1.000 1.000
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 5
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0.000 0.858 0.000 1.000
#> GSM247854 2 0.000 0.858 0.000 1.000
#> GSM247758 2 0.430 0.813 0.088 0.912
#> GSM247742 1 0.839 0.957 0.732 0.268
#> GSM247755 2 0.781 0.780 0.232 0.768
#> GSM247841 1 0.767 0.972 0.776 0.224
#> GSM247703 2 0.000 0.858 0.000 1.000
#> GSM247739 2 0.430 0.813 0.088 0.912
#> GSM247715 1 0.839 0.957 0.732 0.268
#> GSM247829 2 0.781 0.780 0.232 0.768
#> GSM247842 1 0.767 0.972 0.776 0.224
#> GSM247805 2 0.000 0.858 0.000 1.000
#> GSM247786 2 0.430 0.813 0.088 0.912
#> GSM247812 2 0.781 0.780 0.232 0.768
#> GSM247776 1 0.767 0.972 0.776 0.224
#> GSM247850 1 0.767 0.972 0.776 0.224
#> GSM247717 2 0.000 0.858 0.000 1.000
#> GSM247784 2 0.430 0.813 0.088 0.912
#> GSM247834 1 0.839 0.957 0.732 0.268
#> GSM247783 2 0.781 0.780 0.232 0.768
#> GSM247846 1 0.767 0.972 0.776 0.224
#> GSM247822 2 0.000 0.858 0.000 1.000
#> GSM247710 2 0.430 0.813 0.088 0.912
#> GSM247713 1 0.839 0.957 0.732 0.268
#> GSM247840 2 0.781 0.780 0.232 0.768
#> GSM247733 1 0.767 0.972 0.776 0.224
#> GSM247852 1 0.767 0.972 0.776 0.224
#> GSM247790 2 0.000 0.858 0.000 1.000
#> GSM247730 2 0.430 0.813 0.088 0.912
#> GSM247824 2 0.781 0.780 0.232 0.768
#> GSM247770 1 0.767 0.972 0.776 0.224
#> GSM247711 2 0.000 0.858 0.000 1.000
#> GSM247782 2 0.430 0.813 0.088 0.912
#> GSM247836 1 0.839 0.957 0.732 0.268
#> GSM247785 2 0.781 0.780 0.232 0.768
#> GSM247847 1 0.767 0.972 0.776 0.224
#> GSM247750 2 0.000 0.858 0.000 1.000
#> GSM247788 2 0.430 0.813 0.088 0.912
#> GSM247849 1 0.839 0.957 0.732 0.268
#> GSM247772 2 0.781 0.780 0.232 0.768
#> GSM247760 1 0.767 0.972 0.776 0.224
#> GSM247764 2 0.000 0.858 0.000 1.000
#> GSM247851 2 0.000 0.858 0.000 1.000
#> GSM247714 2 0.430 0.813 0.088 0.912
#> GSM247828 1 0.839 0.957 0.732 0.268
#> GSM247704 2 0.781 0.780 0.232 0.768
#> GSM247818 1 0.767 0.972 0.776 0.224
#> GSM247823 2 0.000 0.858 0.000 1.000
#> GSM247706 2 0.430 0.813 0.088 0.912
#> GSM247835 2 0.781 0.780 0.232 0.768
#> GSM247734 1 0.767 0.972 0.776 0.224
#> GSM247819 2 0.000 0.858 0.000 1.000
#> GSM247809 2 0.430 0.813 0.088 0.912
#> GSM247830 2 0.781 0.780 0.232 0.768
#> GSM247833 1 0.767 0.972 0.776 0.224
#> GSM247738 2 0.000 0.858 0.000 1.000
#> GSM247716 2 0.430 0.813 0.088 0.912
#> GSM247747 2 0.781 0.780 0.232 0.768
#> GSM247722 1 0.767 0.972 0.776 0.224
#> GSM247816 2 0.000 0.858 0.000 1.000
#> GSM247839 2 0.430 0.813 0.088 0.912
#> GSM247821 1 0.839 0.957 0.732 0.268
#> GSM247798 2 0.781 0.780 0.232 0.768
#> GSM247838 1 0.767 0.972 0.776 0.224
#> GSM247721 2 0.000 0.858 0.000 1.000
#> GSM247781 2 0.430 0.813 0.088 0.912
#> GSM247762 1 0.839 0.957 0.732 0.268
#> GSM247825 2 0.781 0.780 0.232 0.768
#> GSM247777 1 0.767 0.972 0.776 0.224
#> GSM247761 2 0.000 0.858 0.000 1.000
#> GSM247720 2 0.430 0.813 0.088 0.912
#> GSM247814 2 0.781 0.780 0.232 0.768
#> GSM247732 1 0.767 0.972 0.776 0.224
#> GSM247708 2 0.000 0.858 0.000 1.000
#> GSM247740 2 0.430 0.813 0.088 0.912
#> GSM247749 1 0.839 0.957 0.732 0.268
#> GSM247767 2 0.781 0.780 0.232 0.768
#> GSM247748 1 0.767 0.972 0.776 0.224
#> GSM247705 2 0.000 0.858 0.000 1.000
#> GSM247746 2 0.430 0.813 0.088 0.912
#> GSM247752 1 0.839 0.957 0.732 0.268
#> GSM247769 2 0.781 0.780 0.232 0.768
#> GSM247753 1 0.767 0.972 0.776 0.224
#> GSM247723 2 0.000 0.858 0.000 1.000
#> GSM247779 2 0.430 0.813 0.088 0.912
#> GSM247756 1 0.839 0.957 0.732 0.268
#> GSM247826 2 0.781 0.780 0.232 0.768
#> GSM247775 1 0.767 0.972 0.776 0.224
#> GSM247741 2 0.000 0.858 0.000 1.000
#> GSM247799 2 0.430 0.813 0.088 0.912
#> GSM247778 1 0.839 0.957 0.732 0.268
#> GSM247806 2 0.781 0.780 0.232 0.768
#> GSM247815 1 0.767 0.972 0.776 0.224
#> GSM247735 2 0.000 0.858 0.000 1.000
#> GSM247831 2 0.430 0.813 0.088 0.912
#> GSM247845 1 0.839 0.957 0.732 0.268
#> GSM247791 2 0.781 0.780 0.232 0.768
#> GSM247780 1 0.767 0.972 0.776 0.224
#> GSM247853 1 0.767 0.972 0.776 0.224
#> GSM247800 2 0.000 0.858 0.000 1.000
#> GSM247729 2 0.430 0.813 0.088 0.912
#> GSM247810 1 0.839 0.957 0.732 0.268
#> GSM247844 2 0.781 0.780 0.232 0.768
#> GSM247793 1 0.767 0.972 0.776 0.224
#> GSM247759 2 0.000 0.858 0.000 1.000
#> GSM247724 2 0.430 0.813 0.088 0.912
#> GSM247817 2 0.781 0.780 0.232 0.768
#> GSM247727 1 0.767 0.972 0.776 0.224
#> GSM247796 2 0.000 0.858 0.000 1.000
#> GSM247725 2 0.430 0.813 0.088 0.912
#> GSM247801 1 0.839 0.957 0.732 0.268
#> GSM247731 2 0.781 0.780 0.232 0.768
#> GSM247765 1 0.767 0.972 0.776 0.224
#> GSM247792 2 0.000 0.858 0.000 1.000
#> GSM247726 2 0.430 0.813 0.088 0.912
#> GSM247803 1 0.839 0.957 0.732 0.268
#> GSM247728 2 0.781 0.780 0.232 0.768
#> GSM247768 1 0.767 0.972 0.776 0.224
#> GSM247745 2 0.000 0.858 0.000 1.000
#> GSM247855 2 0.000 0.858 0.000 1.000
#> GSM247804 2 0.430 0.813 0.088 0.912
#> GSM247774 1 0.839 0.957 0.732 0.268
#> GSM247807 2 0.781 0.780 0.232 0.768
#> GSM247813 1 0.767 0.972 0.776 0.224
#> GSM247736 2 0.000 0.858 0.000 1.000
#> GSM247712 2 0.430 0.813 0.088 0.912
#> GSM247797 1 0.839 0.957 0.732 0.268
#> GSM247743 2 0.781 0.780 0.232 0.768
#> GSM247719 1 0.767 0.972 0.776 0.224
#> GSM247707 2 0.000 0.858 0.000 1.000
#> GSM247737 2 0.430 0.813 0.088 0.912
#> GSM247827 2 0.781 0.780 0.232 0.768
#> GSM247848 1 0.767 0.972 0.776 0.224
#> GSM247794 2 0.000 0.858 0.000 1.000
#> GSM247757 2 0.430 0.813 0.088 0.912
#> GSM247744 1 0.839 0.957 0.732 0.268
#> GSM247751 2 0.781 0.780 0.232 0.768
#> GSM247837 1 0.767 0.972 0.776 0.224
#> GSM247754 2 0.000 0.858 0.000 1.000
#> GSM247789 2 0.430 0.813 0.088 0.912
#> GSM247802 1 0.839 0.957 0.732 0.268
#> GSM247771 2 0.781 0.780 0.232 0.768
#> GSM247763 1 0.767 0.972 0.776 0.224
#> GSM247808 2 0.000 0.858 0.000 1.000
#> GSM247787 2 0.430 0.813 0.088 0.912
#> GSM247843 1 0.839 0.957 0.732 0.268
#> GSM247811 2 0.781 0.780 0.232 0.768
#> GSM247773 1 0.767 0.972 0.776 0.224
#> GSM247766 2 0.000 0.858 0.000 1.000
#> GSM247718 2 0.430 0.813 0.088 0.912
#> GSM247832 1 0.839 0.957 0.732 0.268
#> GSM247709 2 0.781 0.780 0.232 0.768
#> GSM247820 1 0.767 0.972 0.776 0.224
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247854 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247758 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247742 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247755 3 0.0592 0.983 0.012 0.000 0.988
#> GSM247841 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247703 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247739 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247715 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247829 3 0.1163 0.982 0.028 0.000 0.972
#> GSM247842 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247805 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247786 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247812 3 0.1411 0.978 0.036 0.000 0.964
#> GSM247776 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247850 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247717 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247784 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247834 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247783 3 0.0424 0.982 0.008 0.000 0.992
#> GSM247846 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247822 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247710 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247713 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247840 3 0.1529 0.977 0.040 0.000 0.960
#> GSM247733 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247852 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247790 2 0.6140 0.853 0.000 0.596 0.404
#> GSM247730 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247824 3 0.0747 0.983 0.016 0.000 0.984
#> GSM247770 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247711 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247782 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247836 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247785 3 0.0424 0.984 0.008 0.000 0.992
#> GSM247847 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247750 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247788 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247849 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247772 3 0.0747 0.983 0.016 0.000 0.984
#> GSM247760 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247764 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247851 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247714 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247828 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247704 3 0.1643 0.978 0.044 0.000 0.956
#> GSM247818 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247823 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247706 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247835 3 0.0424 0.982 0.008 0.000 0.992
#> GSM247734 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247819 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247809 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247830 3 0.0892 0.981 0.020 0.000 0.980
#> GSM247833 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247738 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247716 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247747 3 0.0892 0.983 0.020 0.000 0.980
#> GSM247722 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247816 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247839 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247821 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247798 3 0.0892 0.983 0.020 0.000 0.980
#> GSM247838 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247721 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247781 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247762 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247825 3 0.1411 0.979 0.036 0.000 0.964
#> GSM247777 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247761 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247720 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247814 3 0.0892 0.983 0.020 0.000 0.980
#> GSM247732 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247708 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247740 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247749 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247767 3 0.0747 0.983 0.016 0.000 0.984
#> GSM247748 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247705 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247746 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247752 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247769 3 0.0747 0.983 0.016 0.000 0.984
#> GSM247753 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247723 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247779 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247756 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247826 3 0.0592 0.983 0.012 0.000 0.988
#> GSM247775 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247741 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247799 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247778 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247806 3 0.0424 0.982 0.008 0.000 0.992
#> GSM247815 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247735 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247831 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247845 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247791 3 0.1163 0.980 0.028 0.000 0.972
#> GSM247780 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247853 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247800 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247729 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247810 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247844 3 0.0892 0.983 0.020 0.000 0.980
#> GSM247793 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247759 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247724 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247817 3 0.1163 0.983 0.028 0.000 0.972
#> GSM247727 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247796 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247725 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247801 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247731 3 0.0424 0.982 0.008 0.000 0.992
#> GSM247765 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247792 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247726 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247803 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247728 3 0.1289 0.980 0.032 0.000 0.968
#> GSM247768 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247745 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247855 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247804 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247774 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247807 3 0.1289 0.980 0.032 0.000 0.968
#> GSM247813 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247736 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247712 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247797 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247743 3 0.0592 0.982 0.012 0.000 0.988
#> GSM247719 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247707 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247737 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247827 3 0.1289 0.979 0.032 0.000 0.968
#> GSM247848 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247794 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247757 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247744 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247751 3 0.1289 0.980 0.032 0.000 0.968
#> GSM247837 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247754 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247789 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247802 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247771 3 0.0424 0.982 0.008 0.000 0.992
#> GSM247763 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247808 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247787 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247843 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247811 3 0.1289 0.980 0.032 0.000 0.968
#> GSM247773 1 0.2261 0.894 0.932 0.068 0.000
#> GSM247766 2 0.6192 0.852 0.000 0.580 0.420
#> GSM247718 2 0.5431 0.854 0.000 0.716 0.284
#> GSM247832 1 0.5926 0.837 0.644 0.356 0.000
#> GSM247709 3 0.1753 0.976 0.048 0.000 0.952
#> GSM247820 1 0.2261 0.894 0.932 0.068 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247854 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247758 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247742 4 0.6233 0.987 0.388 0.060 0.000 0.552
#> GSM247755 3 0.3289 0.974 0.004 0.140 0.852 0.004
#> GSM247841 1 0.1732 0.955 0.948 0.008 0.040 0.004
#> GSM247703 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247739 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247715 4 0.6233 0.987 0.388 0.060 0.000 0.552
#> GSM247829 3 0.3711 0.973 0.000 0.140 0.836 0.024
#> GSM247842 1 0.1732 0.955 0.948 0.008 0.040 0.004
#> GSM247805 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247786 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247812 3 0.5290 0.952 0.008 0.140 0.764 0.088
#> GSM247776 1 0.1516 0.955 0.960 0.008 0.016 0.016
#> GSM247850 1 0.1516 0.955 0.960 0.008 0.016 0.016
#> GSM247717 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247784 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247834 4 0.6651 0.985 0.388 0.060 0.012 0.540
#> GSM247783 3 0.3289 0.974 0.004 0.140 0.852 0.004
#> GSM247846 1 0.1732 0.955 0.948 0.008 0.040 0.004
#> GSM247822 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247710 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247713 4 0.7115 0.976 0.388 0.060 0.032 0.520
#> GSM247840 3 0.5227 0.952 0.008 0.140 0.768 0.084
#> GSM247733 1 0.0336 0.960 0.992 0.008 0.000 0.000
#> GSM247852 1 0.0336 0.960 0.992 0.008 0.000 0.000
#> GSM247790 2 0.6536 0.705 0.000 0.580 0.096 0.324
#> GSM247730 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247824 3 0.3377 0.973 0.000 0.140 0.848 0.012
#> GSM247770 1 0.1854 0.957 0.948 0.008 0.024 0.020
#> GSM247711 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247782 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247836 4 0.6233 0.987 0.388 0.060 0.000 0.552
#> GSM247785 3 0.3105 0.974 0.000 0.140 0.856 0.004
#> GSM247847 1 0.2131 0.954 0.936 0.008 0.040 0.016
#> GSM247750 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247788 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247849 4 0.6233 0.987 0.388 0.060 0.000 0.552
#> GSM247772 3 0.2921 0.973 0.000 0.140 0.860 0.000
#> GSM247760 1 0.1394 0.957 0.964 0.008 0.012 0.016
#> GSM247764 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247851 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247714 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247828 4 0.6233 0.987 0.388 0.060 0.000 0.552
#> GSM247704 3 0.5087 0.956 0.004 0.140 0.772 0.084
#> GSM247818 1 0.0672 0.959 0.984 0.008 0.008 0.000
#> GSM247823 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247706 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247835 3 0.3105 0.973 0.000 0.140 0.856 0.004
#> GSM247734 1 0.1516 0.955 0.960 0.008 0.016 0.016
#> GSM247819 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247809 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247830 3 0.3377 0.973 0.000 0.140 0.848 0.012
#> GSM247833 1 0.1822 0.954 0.944 0.008 0.044 0.004
#> GSM247738 2 0.6685 0.705 0.000 0.568 0.108 0.324
#> GSM247716 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247747 3 0.3560 0.974 0.004 0.140 0.844 0.012
#> GSM247722 1 0.2587 0.949 0.916 0.008 0.056 0.020
#> GSM247816 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247839 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247821 4 0.6233 0.987 0.388 0.060 0.000 0.552
#> GSM247798 3 0.3606 0.973 0.000 0.140 0.840 0.020
#> GSM247838 1 0.2587 0.949 0.916 0.008 0.056 0.020
#> GSM247721 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247781 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247762 4 0.7115 0.976 0.388 0.060 0.032 0.520
#> GSM247825 3 0.4888 0.960 0.008 0.140 0.788 0.064
#> GSM247777 1 0.1909 0.953 0.940 0.008 0.048 0.004
#> GSM247761 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247720 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247814 3 0.3495 0.973 0.000 0.140 0.844 0.016
#> GSM247732 1 0.0804 0.959 0.980 0.008 0.012 0.000
#> GSM247708 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247740 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247749 4 0.6651 0.985 0.388 0.060 0.012 0.540
#> GSM247767 3 0.3606 0.973 0.000 0.140 0.840 0.020
#> GSM247748 1 0.0672 0.959 0.984 0.008 0.008 0.000
#> GSM247705 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247746 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247752 4 0.7115 0.976 0.388 0.060 0.032 0.520
#> GSM247769 3 0.3377 0.973 0.000 0.140 0.848 0.012
#> GSM247753 1 0.1994 0.937 0.936 0.008 0.052 0.004
#> GSM247723 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247779 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247756 4 0.6233 0.987 0.388 0.060 0.000 0.552
#> GSM247826 3 0.3289 0.974 0.004 0.140 0.852 0.004
#> GSM247775 1 0.1822 0.954 0.944 0.008 0.044 0.004
#> GSM247741 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247799 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247778 4 0.6233 0.987 0.388 0.060 0.000 0.552
#> GSM247806 3 0.3289 0.974 0.004 0.140 0.852 0.004
#> GSM247815 1 0.2421 0.951 0.924 0.008 0.048 0.020
#> GSM247735 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247831 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247845 4 0.6233 0.987 0.388 0.060 0.000 0.552
#> GSM247791 3 0.5163 0.955 0.008 0.140 0.772 0.080
#> GSM247780 1 0.1854 0.957 0.948 0.008 0.024 0.020
#> GSM247853 1 0.1854 0.957 0.948 0.008 0.024 0.020
#> GSM247800 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247729 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247810 4 0.6651 0.985 0.388 0.060 0.012 0.540
#> GSM247844 3 0.3711 0.973 0.000 0.140 0.836 0.024
#> GSM247793 1 0.0336 0.960 0.992 0.008 0.000 0.000
#> GSM247759 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247724 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247817 3 0.3377 0.973 0.000 0.140 0.848 0.012
#> GSM247727 1 0.0804 0.959 0.980 0.008 0.012 0.000
#> GSM247796 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247725 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247801 4 0.7341 0.969 0.388 0.060 0.044 0.508
#> GSM247731 3 0.3105 0.973 0.000 0.140 0.856 0.004
#> GSM247765 1 0.1516 0.955 0.960 0.008 0.016 0.016
#> GSM247792 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247726 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247803 4 0.7115 0.976 0.388 0.060 0.032 0.520
#> GSM247728 3 0.4673 0.961 0.004 0.140 0.796 0.060
#> GSM247768 1 0.1994 0.937 0.936 0.008 0.052 0.004
#> GSM247745 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247855 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247804 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247774 4 0.6651 0.982 0.388 0.060 0.012 0.540
#> GSM247807 3 0.5163 0.955 0.008 0.140 0.772 0.080
#> GSM247813 1 0.2587 0.949 0.916 0.008 0.056 0.020
#> GSM247736 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247712 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247797 4 0.7115 0.976 0.388 0.060 0.032 0.520
#> GSM247743 3 0.3249 0.973 0.000 0.140 0.852 0.008
#> GSM247719 1 0.0804 0.959 0.980 0.008 0.012 0.000
#> GSM247707 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247737 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247827 3 0.4814 0.960 0.008 0.140 0.792 0.060
#> GSM247848 1 0.1822 0.954 0.944 0.008 0.044 0.004
#> GSM247794 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247757 2 0.0779 0.702 0.000 0.980 0.016 0.004
#> GSM247744 4 0.6651 0.982 0.388 0.060 0.012 0.540
#> GSM247751 3 0.4519 0.964 0.004 0.140 0.804 0.052
#> GSM247837 1 0.1732 0.955 0.948 0.008 0.040 0.004
#> GSM247754 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247789 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247802 4 0.6651 0.985 0.388 0.060 0.012 0.540
#> GSM247771 3 0.3105 0.973 0.000 0.140 0.856 0.004
#> GSM247763 1 0.1516 0.955 0.960 0.008 0.016 0.016
#> GSM247808 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247787 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247843 4 0.6233 0.987 0.388 0.060 0.000 0.552
#> GSM247811 3 0.5290 0.954 0.008 0.140 0.764 0.088
#> GSM247773 1 0.0672 0.959 0.984 0.008 0.008 0.000
#> GSM247766 2 0.6824 0.705 0.000 0.556 0.120 0.324
#> GSM247718 2 0.0592 0.702 0.000 0.984 0.016 0.000
#> GSM247832 4 0.6233 0.987 0.388 0.060 0.000 0.552
#> GSM247709 3 0.5212 0.952 0.004 0.140 0.764 0.092
#> GSM247820 1 0.0804 0.959 0.980 0.008 0.012 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.5394 0.969 0.000 0.608 0.056 0.008 0.328
#> GSM247854 2 0.5394 0.969 0.000 0.608 0.056 0.008 0.328
#> GSM247758 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247742 4 0.4382 0.968 0.228 0.012 0.000 0.736 0.024
#> GSM247755 3 0.2460 0.944 0.000 0.024 0.900 0.004 0.072
#> GSM247841 1 0.1121 0.950 0.956 0.044 0.000 0.000 0.000
#> GSM247703 2 0.5279 0.968 0.000 0.612 0.056 0.004 0.328
#> GSM247739 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247715 4 0.4275 0.968 0.228 0.008 0.000 0.740 0.024
#> GSM247829 3 0.3383 0.944 0.000 0.012 0.856 0.060 0.072
#> GSM247842 1 0.1121 0.950 0.956 0.044 0.000 0.000 0.000
#> GSM247805 2 0.5279 0.968 0.000 0.612 0.056 0.004 0.328
#> GSM247786 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247812 3 0.5117 0.913 0.000 0.052 0.748 0.128 0.072
#> GSM247776 1 0.1768 0.940 0.924 0.072 0.004 0.000 0.000
#> GSM247850 1 0.1768 0.940 0.924 0.072 0.004 0.000 0.000
#> GSM247717 2 0.5279 0.968 0.000 0.612 0.056 0.004 0.328
#> GSM247784 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247834 4 0.5015 0.965 0.228 0.028 0.008 0.712 0.024
#> GSM247783 3 0.2367 0.944 0.000 0.020 0.904 0.004 0.072
#> GSM247846 1 0.1121 0.950 0.956 0.044 0.000 0.000 0.000
#> GSM247822 2 0.6351 0.961 0.000 0.556 0.056 0.060 0.328
#> GSM247710 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247713 4 0.5829 0.950 0.228 0.064 0.016 0.668 0.024
#> GSM247840 3 0.5160 0.913 0.000 0.052 0.744 0.132 0.072
#> GSM247733 1 0.0404 0.953 0.988 0.012 0.000 0.000 0.000
#> GSM247852 1 0.0404 0.953 0.988 0.012 0.000 0.000 0.000
#> GSM247790 2 0.5085 0.951 0.000 0.612 0.040 0.004 0.344
#> GSM247730 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247824 3 0.2868 0.945 0.000 0.012 0.884 0.032 0.072
#> GSM247770 1 0.2130 0.940 0.908 0.080 0.012 0.000 0.000
#> GSM247711 2 0.5129 0.968 0.000 0.616 0.056 0.000 0.328
#> GSM247782 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247836 4 0.4536 0.968 0.228 0.012 0.004 0.732 0.024
#> GSM247785 3 0.2988 0.945 0.000 0.024 0.880 0.024 0.072
#> GSM247847 1 0.1197 0.952 0.952 0.048 0.000 0.000 0.000
#> GSM247750 2 0.5279 0.968 0.000 0.612 0.056 0.004 0.328
#> GSM247788 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247849 4 0.4382 0.968 0.228 0.012 0.000 0.736 0.024
#> GSM247772 3 0.2054 0.945 0.000 0.008 0.916 0.004 0.072
#> GSM247760 1 0.1270 0.949 0.948 0.052 0.000 0.000 0.000
#> GSM247764 2 0.6459 0.958 0.000 0.548 0.056 0.068 0.328
#> GSM247851 2 0.6459 0.958 0.000 0.548 0.056 0.068 0.328
#> GSM247714 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247828 4 0.4382 0.968 0.228 0.012 0.000 0.736 0.024
#> GSM247704 3 0.5158 0.916 0.000 0.040 0.736 0.152 0.072
#> GSM247818 1 0.0771 0.951 0.976 0.020 0.004 0.000 0.000
#> GSM247823 2 0.6237 0.964 0.000 0.564 0.056 0.052 0.328
#> GSM247706 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247835 3 0.2006 0.944 0.000 0.012 0.916 0.000 0.072
#> GSM247734 1 0.1768 0.940 0.924 0.072 0.004 0.000 0.000
#> GSM247819 2 0.6459 0.958 0.000 0.548 0.056 0.068 0.328
#> GSM247809 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247830 3 0.3240 0.940 0.000 0.024 0.868 0.036 0.072
#> GSM247833 1 0.1270 0.948 0.948 0.052 0.000 0.000 0.000
#> GSM247738 2 0.5279 0.968 0.000 0.612 0.056 0.004 0.328
#> GSM247716 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247747 3 0.3411 0.944 0.000 0.032 0.860 0.036 0.072
#> GSM247722 1 0.1851 0.945 0.912 0.088 0.000 0.000 0.000
#> GSM247816 2 0.5394 0.969 0.000 0.608 0.056 0.008 0.328
#> GSM247839 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247821 4 0.4536 0.968 0.228 0.012 0.004 0.732 0.024
#> GSM247798 3 0.3581 0.943 0.000 0.020 0.848 0.060 0.072
#> GSM247838 1 0.1908 0.945 0.908 0.092 0.000 0.000 0.000
#> GSM247721 2 0.5279 0.968 0.000 0.612 0.056 0.004 0.328
#> GSM247781 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247762 4 0.6403 0.933 0.228 0.088 0.028 0.632 0.024
#> GSM247825 3 0.4600 0.924 0.000 0.036 0.784 0.108 0.072
#> GSM247777 1 0.1270 0.948 0.948 0.052 0.000 0.000 0.000
#> GSM247761 2 0.5394 0.969 0.000 0.608 0.056 0.008 0.328
#> GSM247720 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247814 3 0.3103 0.942 0.000 0.012 0.872 0.044 0.072
#> GSM247732 1 0.0510 0.953 0.984 0.016 0.000 0.000 0.000
#> GSM247708 2 0.5129 0.968 0.000 0.616 0.056 0.000 0.328
#> GSM247740 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247749 4 0.5094 0.964 0.228 0.032 0.008 0.708 0.024
#> GSM247767 3 0.3279 0.942 0.000 0.016 0.864 0.048 0.072
#> GSM247748 1 0.0510 0.953 0.984 0.016 0.000 0.000 0.000
#> GSM247705 2 0.6237 0.964 0.000 0.564 0.056 0.052 0.328
#> GSM247746 5 0.0290 0.991 0.000 0.008 0.000 0.000 0.992
#> GSM247752 4 0.6479 0.930 0.228 0.088 0.032 0.628 0.024
#> GSM247769 3 0.3205 0.944 0.000 0.008 0.864 0.056 0.072
#> GSM247753 1 0.2519 0.904 0.884 0.100 0.016 0.000 0.000
#> GSM247723 2 0.6459 0.958 0.000 0.548 0.056 0.068 0.328
#> GSM247779 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247756 4 0.4382 0.968 0.228 0.012 0.000 0.736 0.024
#> GSM247826 3 0.2460 0.944 0.000 0.024 0.900 0.004 0.072
#> GSM247775 1 0.1121 0.950 0.956 0.044 0.000 0.000 0.000
#> GSM247741 2 0.6459 0.958 0.000 0.548 0.056 0.068 0.328
#> GSM247799 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247778 4 0.4536 0.968 0.228 0.012 0.004 0.732 0.024
#> GSM247806 3 0.2367 0.944 0.000 0.020 0.904 0.004 0.072
#> GSM247815 1 0.1671 0.948 0.924 0.076 0.000 0.000 0.000
#> GSM247735 2 0.6459 0.958 0.000 0.548 0.056 0.068 0.328
#> GSM247831 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247845 4 0.4382 0.968 0.228 0.012 0.000 0.736 0.024
#> GSM247791 3 0.4866 0.918 0.000 0.048 0.768 0.112 0.072
#> GSM247780 1 0.1830 0.948 0.924 0.068 0.008 0.000 0.000
#> GSM247853 1 0.1830 0.948 0.924 0.068 0.008 0.000 0.000
#> GSM247800 2 0.6459 0.958 0.000 0.548 0.056 0.068 0.328
#> GSM247729 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247810 4 0.5094 0.964 0.228 0.032 0.008 0.708 0.024
#> GSM247844 3 0.3514 0.941 0.000 0.020 0.852 0.056 0.072
#> GSM247793 1 0.0404 0.953 0.988 0.012 0.000 0.000 0.000
#> GSM247759 2 0.6295 0.963 0.000 0.560 0.056 0.056 0.328
#> GSM247724 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247817 3 0.3514 0.943 0.000 0.020 0.852 0.056 0.072
#> GSM247727 1 0.0510 0.953 0.984 0.016 0.000 0.000 0.000
#> GSM247796 2 0.6459 0.958 0.000 0.548 0.056 0.068 0.328
#> GSM247725 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247801 4 0.6646 0.928 0.228 0.096 0.036 0.616 0.024
#> GSM247731 3 0.2006 0.944 0.000 0.012 0.916 0.000 0.072
#> GSM247765 1 0.1768 0.940 0.924 0.072 0.004 0.000 0.000
#> GSM247792 2 0.6459 0.958 0.000 0.548 0.056 0.068 0.328
#> GSM247726 5 0.0451 0.986 0.000 0.008 0.004 0.000 0.988
#> GSM247803 4 0.6479 0.930 0.228 0.088 0.032 0.628 0.024
#> GSM247728 3 0.4550 0.924 0.000 0.036 0.788 0.104 0.072
#> GSM247768 1 0.2519 0.904 0.884 0.100 0.016 0.000 0.000
#> GSM247745 2 0.5279 0.968 0.000 0.612 0.056 0.004 0.328
#> GSM247855 2 0.5279 0.968 0.000 0.612 0.056 0.004 0.328
#> GSM247804 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247774 4 0.4846 0.963 0.228 0.020 0.008 0.720 0.024
#> GSM247807 3 0.4836 0.920 0.000 0.052 0.772 0.104 0.072
#> GSM247813 1 0.1851 0.945 0.912 0.088 0.000 0.000 0.000
#> GSM247736 2 0.5279 0.968 0.000 0.612 0.056 0.004 0.328
#> GSM247712 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247797 4 0.6303 0.934 0.228 0.080 0.028 0.640 0.024
#> GSM247743 3 0.2988 0.942 0.000 0.024 0.880 0.024 0.072
#> GSM247719 1 0.0671 0.952 0.980 0.016 0.004 0.000 0.000
#> GSM247707 2 0.5279 0.968 0.000 0.612 0.056 0.004 0.328
#> GSM247737 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247827 3 0.4625 0.924 0.000 0.040 0.784 0.104 0.072
#> GSM247848 1 0.1121 0.950 0.956 0.044 0.000 0.000 0.000
#> GSM247794 2 0.5279 0.968 0.000 0.612 0.056 0.004 0.328
#> GSM247757 5 0.0162 0.997 0.000 0.004 0.000 0.000 0.996
#> GSM247744 4 0.4846 0.963 0.228 0.020 0.008 0.720 0.024
#> GSM247751 3 0.4447 0.926 0.000 0.036 0.796 0.096 0.072
#> GSM247837 1 0.1043 0.951 0.960 0.040 0.000 0.000 0.000
#> GSM247754 2 0.6295 0.963 0.000 0.560 0.056 0.056 0.328
#> GSM247789 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247802 4 0.5015 0.965 0.228 0.028 0.008 0.712 0.024
#> GSM247771 3 0.2006 0.944 0.000 0.012 0.916 0.000 0.072
#> GSM247763 1 0.1894 0.939 0.920 0.072 0.008 0.000 0.000
#> GSM247808 2 0.5279 0.968 0.000 0.612 0.056 0.004 0.328
#> GSM247787 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247843 4 0.4275 0.968 0.228 0.008 0.000 0.740 0.024
#> GSM247811 3 0.5177 0.916 0.000 0.048 0.740 0.140 0.072
#> GSM247773 1 0.0510 0.953 0.984 0.016 0.000 0.000 0.000
#> GSM247766 2 0.6406 0.959 0.000 0.552 0.056 0.064 0.328
#> GSM247718 5 0.0000 0.997 0.000 0.000 0.000 0.000 1.000
#> GSM247832 4 0.4382 0.968 0.228 0.012 0.000 0.736 0.024
#> GSM247709 3 0.5344 0.910 0.000 0.040 0.716 0.172 0.072
#> GSM247820 1 0.0671 0.952 0.980 0.016 0.004 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.4192 0.923 0.000 0.740 0.048 0.004 0.200 0.008
#> GSM247854 2 0.4192 0.923 0.000 0.740 0.048 0.004 0.200 0.008
#> GSM247758 5 0.0717 0.979 0.000 0.008 0.000 0.000 0.976 0.016
#> GSM247742 4 0.2356 0.966 0.100 0.004 0.000 0.884 0.004 0.008
#> GSM247755 3 0.0810 0.917 0.000 0.004 0.976 0.004 0.008 0.008
#> GSM247841 1 0.1625 0.924 0.928 0.012 0.000 0.000 0.000 0.060
#> GSM247703 2 0.4663 0.917 0.000 0.720 0.048 0.012 0.200 0.020
#> GSM247739 5 0.1268 0.971 0.000 0.008 0.000 0.004 0.952 0.036
#> GSM247715 4 0.2213 0.966 0.100 0.008 0.000 0.888 0.004 0.000
#> GSM247829 3 0.2467 0.916 0.000 0.004 0.880 0.008 0.008 0.100
#> GSM247842 1 0.1657 0.924 0.928 0.016 0.000 0.000 0.000 0.056
#> GSM247805 2 0.4580 0.918 0.000 0.724 0.048 0.012 0.200 0.016
#> GSM247786 5 0.0777 0.971 0.000 0.000 0.000 0.004 0.972 0.024
#> GSM247812 3 0.4432 0.866 0.000 0.036 0.720 0.016 0.008 0.220
#> GSM247776 1 0.2165 0.915 0.884 0.008 0.000 0.000 0.000 0.108
#> GSM247850 1 0.2165 0.915 0.884 0.008 0.000 0.000 0.000 0.108
#> GSM247717 2 0.3806 0.922 0.000 0.752 0.048 0.000 0.200 0.000
#> GSM247784 5 0.0717 0.979 0.000 0.008 0.000 0.000 0.976 0.016
#> GSM247834 4 0.2828 0.964 0.100 0.024 0.000 0.864 0.004 0.008
#> GSM247783 3 0.0696 0.917 0.000 0.004 0.980 0.004 0.008 0.004
#> GSM247846 1 0.1719 0.924 0.924 0.016 0.000 0.000 0.000 0.060
#> GSM247822 2 0.6597 0.899 0.000 0.584 0.048 0.048 0.200 0.120
#> GSM247710 5 0.0000 0.979 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247713 4 0.3735 0.950 0.100 0.056 0.000 0.816 0.004 0.024
#> GSM247840 3 0.4458 0.865 0.000 0.036 0.716 0.016 0.008 0.224
#> GSM247733 1 0.0972 0.925 0.964 0.008 0.000 0.000 0.000 0.028
#> GSM247852 1 0.0806 0.925 0.972 0.008 0.000 0.000 0.000 0.020
#> GSM247790 2 0.4718 0.915 0.000 0.716 0.044 0.016 0.204 0.020
#> GSM247730 5 0.0000 0.979 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247824 3 0.1584 0.917 0.000 0.000 0.928 0.000 0.008 0.064
#> GSM247770 1 0.2446 0.915 0.864 0.012 0.000 0.000 0.000 0.124
#> GSM247711 2 0.4580 0.918 0.000 0.724 0.048 0.016 0.200 0.012
#> GSM247782 5 0.0717 0.979 0.000 0.008 0.000 0.000 0.976 0.016
#> GSM247836 4 0.2456 0.966 0.100 0.004 0.000 0.880 0.004 0.012
#> GSM247785 3 0.1196 0.919 0.000 0.000 0.952 0.000 0.008 0.040
#> GSM247847 1 0.2039 0.926 0.904 0.020 0.000 0.000 0.000 0.076
#> GSM247750 2 0.4751 0.917 0.000 0.716 0.048 0.016 0.200 0.020
#> GSM247788 5 0.0000 0.979 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247849 4 0.2356 0.966 0.100 0.004 0.000 0.884 0.004 0.008
#> GSM247772 3 0.0767 0.919 0.000 0.000 0.976 0.004 0.008 0.012
#> GSM247760 1 0.2214 0.918 0.888 0.016 0.000 0.000 0.000 0.096
#> GSM247764 2 0.6957 0.889 0.000 0.544 0.048 0.056 0.200 0.152
#> GSM247851 2 0.6957 0.889 0.000 0.544 0.048 0.056 0.200 0.152
#> GSM247714 5 0.0000 0.979 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247828 4 0.2456 0.966 0.100 0.004 0.000 0.880 0.004 0.012
#> GSM247704 3 0.3672 0.868 0.000 0.000 0.688 0.000 0.008 0.304
#> GSM247818 1 0.1049 0.924 0.960 0.008 0.000 0.000 0.000 0.032
#> GSM247823 2 0.6243 0.907 0.000 0.612 0.048 0.032 0.200 0.108
#> GSM247706 5 0.0000 0.979 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247835 3 0.0551 0.917 0.000 0.004 0.984 0.004 0.008 0.000
#> GSM247734 1 0.2212 0.915 0.880 0.008 0.000 0.000 0.000 0.112
#> GSM247819 2 0.6739 0.889 0.000 0.560 0.048 0.040 0.200 0.152
#> GSM247809 5 0.0717 0.979 0.000 0.008 0.000 0.000 0.976 0.016
#> GSM247830 3 0.2107 0.913 0.000 0.008 0.916 0.016 0.008 0.052
#> GSM247833 1 0.2119 0.922 0.904 0.036 0.000 0.000 0.000 0.060
#> GSM247738 2 0.3806 0.922 0.000 0.752 0.048 0.000 0.200 0.000
#> GSM247716 5 0.0717 0.979 0.000 0.008 0.000 0.000 0.976 0.016
#> GSM247747 3 0.1849 0.919 0.000 0.008 0.932 0.020 0.008 0.032
#> GSM247722 1 0.3172 0.909 0.816 0.036 0.000 0.000 0.000 0.148
#> GSM247816 2 0.5287 0.920 0.000 0.684 0.048 0.016 0.200 0.052
#> GSM247839 5 0.0717 0.979 0.000 0.008 0.000 0.000 0.976 0.016
#> GSM247821 4 0.2456 0.966 0.100 0.012 0.000 0.880 0.004 0.004
#> GSM247798 3 0.2662 0.913 0.000 0.004 0.868 0.012 0.008 0.108
#> GSM247838 1 0.3139 0.909 0.816 0.032 0.000 0.000 0.000 0.152
#> GSM247721 2 0.4751 0.917 0.000 0.716 0.048 0.016 0.200 0.020
#> GSM247781 5 0.0717 0.979 0.000 0.008 0.000 0.000 0.976 0.016
#> GSM247762 4 0.4812 0.916 0.100 0.088 0.000 0.744 0.004 0.064
#> GSM247825 3 0.3161 0.883 0.000 0.000 0.776 0.000 0.008 0.216
#> GSM247777 1 0.2106 0.921 0.904 0.032 0.000 0.000 0.000 0.064
#> GSM247761 2 0.4396 0.922 0.000 0.732 0.048 0.008 0.200 0.012
#> GSM247720 5 0.0777 0.971 0.000 0.000 0.000 0.004 0.972 0.024
#> GSM247814 3 0.2144 0.914 0.000 0.004 0.908 0.012 0.008 0.068
#> GSM247732 1 0.1418 0.925 0.944 0.032 0.000 0.000 0.000 0.024
#> GSM247708 2 0.4084 0.922 0.000 0.744 0.048 0.004 0.200 0.004
#> GSM247740 5 0.0777 0.971 0.000 0.000 0.000 0.004 0.972 0.024
#> GSM247749 4 0.3006 0.963 0.100 0.028 0.000 0.856 0.004 0.012
#> GSM247767 3 0.1970 0.917 0.000 0.000 0.900 0.000 0.008 0.092
#> GSM247748 1 0.1049 0.924 0.960 0.008 0.000 0.000 0.000 0.032
#> GSM247705 2 0.6540 0.907 0.000 0.588 0.048 0.044 0.200 0.120
#> GSM247746 5 0.2149 0.916 0.000 0.004 0.000 0.004 0.888 0.104
#> GSM247752 4 0.4859 0.915 0.100 0.092 0.000 0.740 0.004 0.064
#> GSM247769 3 0.1970 0.919 0.000 0.000 0.900 0.000 0.008 0.092
#> GSM247753 1 0.3352 0.854 0.812 0.032 0.008 0.000 0.000 0.148
#> GSM247723 2 0.6679 0.891 0.000 0.568 0.048 0.040 0.200 0.144
#> GSM247779 5 0.0717 0.979 0.000 0.008 0.000 0.000 0.976 0.016
#> GSM247756 4 0.2356 0.966 0.100 0.004 0.000 0.884 0.004 0.008
#> GSM247826 3 0.0551 0.918 0.000 0.000 0.984 0.004 0.008 0.004
#> GSM247775 1 0.1802 0.923 0.916 0.012 0.000 0.000 0.000 0.072
#> GSM247741 2 0.6679 0.890 0.000 0.564 0.048 0.036 0.200 0.152
#> GSM247799 5 0.0717 0.979 0.000 0.008 0.000 0.000 0.976 0.016
#> GSM247778 4 0.2456 0.966 0.100 0.012 0.000 0.880 0.004 0.004
#> GSM247806 3 0.0696 0.917 0.000 0.004 0.980 0.004 0.008 0.004
#> GSM247815 1 0.2750 0.914 0.844 0.020 0.000 0.000 0.000 0.136
#> GSM247735 2 0.6679 0.890 0.000 0.564 0.048 0.036 0.200 0.152
#> GSM247831 5 0.0000 0.979 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247845 4 0.2356 0.966 0.100 0.004 0.000 0.884 0.004 0.008
#> GSM247791 3 0.4293 0.872 0.000 0.036 0.740 0.016 0.008 0.200
#> GSM247780 1 0.2263 0.921 0.884 0.016 0.000 0.000 0.000 0.100
#> GSM247853 1 0.2214 0.922 0.888 0.016 0.000 0.000 0.000 0.096
#> GSM247800 2 0.6739 0.889 0.000 0.560 0.048 0.040 0.200 0.152
#> GSM247729 5 0.0000 0.979 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247810 4 0.3006 0.963 0.100 0.028 0.000 0.856 0.004 0.012
#> GSM247844 3 0.2518 0.912 0.000 0.004 0.880 0.012 0.008 0.096
#> GSM247793 1 0.0622 0.927 0.980 0.008 0.000 0.000 0.000 0.012
#> GSM247759 2 0.6204 0.907 0.000 0.616 0.048 0.032 0.200 0.104
#> GSM247724 5 0.0000 0.979 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247817 3 0.2417 0.915 0.000 0.004 0.888 0.012 0.008 0.088
#> GSM247727 1 0.1418 0.925 0.944 0.032 0.000 0.000 0.000 0.024
#> GSM247796 2 0.6739 0.889 0.000 0.560 0.048 0.040 0.200 0.152
#> GSM247725 5 0.0000 0.979 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247801 4 0.4913 0.921 0.100 0.092 0.000 0.736 0.004 0.068
#> GSM247731 3 0.0696 0.917 0.000 0.004 0.980 0.004 0.008 0.004
#> GSM247765 1 0.2212 0.916 0.880 0.008 0.000 0.000 0.000 0.112
#> GSM247792 2 0.6847 0.889 0.000 0.556 0.048 0.052 0.200 0.144
#> GSM247726 5 0.2149 0.916 0.000 0.004 0.000 0.004 0.888 0.104
#> GSM247803 4 0.4859 0.915 0.100 0.092 0.000 0.740 0.004 0.064
#> GSM247728 3 0.3190 0.881 0.000 0.000 0.772 0.000 0.008 0.220
#> GSM247768 1 0.3352 0.854 0.812 0.032 0.008 0.000 0.000 0.148
#> GSM247745 2 0.3945 0.922 0.000 0.748 0.048 0.004 0.200 0.000
#> GSM247855 2 0.3945 0.922 0.000 0.748 0.048 0.004 0.200 0.000
#> GSM247804 5 0.0717 0.979 0.000 0.008 0.000 0.000 0.976 0.016
#> GSM247774 4 0.3259 0.953 0.100 0.020 0.000 0.844 0.004 0.032
#> GSM247807 3 0.4263 0.874 0.000 0.036 0.744 0.016 0.008 0.196
#> GSM247813 1 0.3101 0.909 0.820 0.032 0.000 0.000 0.000 0.148
#> GSM247736 2 0.3945 0.922 0.000 0.748 0.048 0.004 0.200 0.000
#> GSM247712 5 0.0777 0.971 0.000 0.000 0.000 0.004 0.972 0.024
#> GSM247797 4 0.4286 0.934 0.100 0.080 0.000 0.780 0.004 0.036
#> GSM247743 3 0.1490 0.916 0.000 0.004 0.948 0.016 0.008 0.024
#> GSM247719 1 0.1418 0.925 0.944 0.032 0.000 0.000 0.000 0.024
#> GSM247707 2 0.4751 0.917 0.000 0.716 0.048 0.016 0.200 0.020
#> GSM247737 5 0.0717 0.979 0.000 0.008 0.000 0.000 0.976 0.016
#> GSM247827 3 0.3133 0.883 0.000 0.000 0.780 0.000 0.008 0.212
#> GSM247848 1 0.1951 0.922 0.908 0.016 0.000 0.000 0.000 0.076
#> GSM247794 2 0.4663 0.917 0.000 0.720 0.048 0.012 0.200 0.020
#> GSM247757 5 0.0717 0.979 0.000 0.008 0.000 0.000 0.976 0.016
#> GSM247744 4 0.3259 0.953 0.100 0.020 0.000 0.844 0.004 0.032
#> GSM247751 3 0.3133 0.885 0.000 0.000 0.780 0.000 0.008 0.212
#> GSM247837 1 0.1745 0.923 0.920 0.012 0.000 0.000 0.000 0.068
#> GSM247754 2 0.6164 0.907 0.000 0.620 0.048 0.032 0.200 0.100
#> GSM247789 5 0.0000 0.979 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247802 4 0.2828 0.964 0.100 0.024 0.000 0.864 0.004 0.008
#> GSM247771 3 0.0551 0.917 0.000 0.004 0.984 0.004 0.008 0.000
#> GSM247763 1 0.2212 0.915 0.880 0.008 0.000 0.000 0.000 0.112
#> GSM247808 2 0.4084 0.922 0.000 0.744 0.048 0.004 0.200 0.004
#> GSM247787 5 0.0777 0.971 0.000 0.000 0.000 0.004 0.972 0.024
#> GSM247843 4 0.2213 0.966 0.100 0.008 0.000 0.888 0.004 0.000
#> GSM247811 3 0.4549 0.868 0.000 0.040 0.708 0.016 0.008 0.228
#> GSM247773 1 0.1049 0.924 0.960 0.008 0.000 0.000 0.000 0.032
#> GSM247766 2 0.6708 0.889 0.000 0.560 0.048 0.036 0.200 0.156
#> GSM247718 5 0.0777 0.971 0.000 0.000 0.000 0.004 0.972 0.024
#> GSM247832 4 0.2356 0.966 0.100 0.004 0.000 0.884 0.004 0.008
#> GSM247709 3 0.3827 0.865 0.000 0.004 0.680 0.000 0.008 0.308
#> GSM247820 1 0.1418 0.925 0.944 0.032 0.000 0.000 0.000 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> SD:kmeans 153 1 1.000 4.63e-32 2
#> SD:kmeans 153 1 0.985 2.17e-61 3
#> SD:kmeans 153 1 0.964 1.16e-90 4
#> SD:kmeans 153 1 0.989 6.51e-120 5
#> SD:kmeans 153 1 0.989 6.51e-120 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.4711 0.529 0.529
#> 3 3 1.000 0.997 0.996 0.3675 0.827 0.673
#> 4 4 1.000 0.990 0.976 0.1383 0.909 0.745
#> 5 5 1.000 1.000 0.999 0.0935 0.933 0.747
#> 6 6 0.971 0.955 0.956 0.0158 0.995 0.975
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 3 4
There is also optional best \(k\) = 2 3 4 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0 1 0 1
#> GSM247854 2 0 1 0 1
#> GSM247758 2 0 1 0 1
#> GSM247742 1 0 1 1 0
#> GSM247755 2 0 1 0 1
#> GSM247841 1 0 1 1 0
#> GSM247703 2 0 1 0 1
#> GSM247739 2 0 1 0 1
#> GSM247715 1 0 1 1 0
#> GSM247829 2 0 1 0 1
#> GSM247842 1 0 1 1 0
#> GSM247805 2 0 1 0 1
#> GSM247786 2 0 1 0 1
#> GSM247812 2 0 1 0 1
#> GSM247776 1 0 1 1 0
#> GSM247850 1 0 1 1 0
#> GSM247717 2 0 1 0 1
#> GSM247784 2 0 1 0 1
#> GSM247834 1 0 1 1 0
#> GSM247783 2 0 1 0 1
#> GSM247846 1 0 1 1 0
#> GSM247822 2 0 1 0 1
#> GSM247710 2 0 1 0 1
#> GSM247713 1 0 1 1 0
#> GSM247840 2 0 1 0 1
#> GSM247733 1 0 1 1 0
#> GSM247852 1 0 1 1 0
#> GSM247790 2 0 1 0 1
#> GSM247730 2 0 1 0 1
#> GSM247824 2 0 1 0 1
#> GSM247770 1 0 1 1 0
#> GSM247711 2 0 1 0 1
#> GSM247782 2 0 1 0 1
#> GSM247836 1 0 1 1 0
#> GSM247785 2 0 1 0 1
#> GSM247847 1 0 1 1 0
#> GSM247750 2 0 1 0 1
#> GSM247788 2 0 1 0 1
#> GSM247849 1 0 1 1 0
#> GSM247772 2 0 1 0 1
#> GSM247760 1 0 1 1 0
#> GSM247764 2 0 1 0 1
#> GSM247851 2 0 1 0 1
#> GSM247714 2 0 1 0 1
#> GSM247828 1 0 1 1 0
#> GSM247704 2 0 1 0 1
#> GSM247818 1 0 1 1 0
#> GSM247823 2 0 1 0 1
#> GSM247706 2 0 1 0 1
#> GSM247835 2 0 1 0 1
#> GSM247734 1 0 1 1 0
#> GSM247819 2 0 1 0 1
#> GSM247809 2 0 1 0 1
#> GSM247830 2 0 1 0 1
#> GSM247833 1 0 1 1 0
#> GSM247738 2 0 1 0 1
#> GSM247716 2 0 1 0 1
#> GSM247747 2 0 1 0 1
#> GSM247722 1 0 1 1 0
#> GSM247816 2 0 1 0 1
#> GSM247839 2 0 1 0 1
#> GSM247821 1 0 1 1 0
#> GSM247798 2 0 1 0 1
#> GSM247838 1 0 1 1 0
#> GSM247721 2 0 1 0 1
#> GSM247781 2 0 1 0 1
#> GSM247762 1 0 1 1 0
#> GSM247825 2 0 1 0 1
#> GSM247777 1 0 1 1 0
#> GSM247761 2 0 1 0 1
#> GSM247720 2 0 1 0 1
#> GSM247814 2 0 1 0 1
#> GSM247732 1 0 1 1 0
#> GSM247708 2 0 1 0 1
#> GSM247740 2 0 1 0 1
#> GSM247749 1 0 1 1 0
#> GSM247767 2 0 1 0 1
#> GSM247748 1 0 1 1 0
#> GSM247705 2 0 1 0 1
#> GSM247746 2 0 1 0 1
#> GSM247752 1 0 1 1 0
#> GSM247769 2 0 1 0 1
#> GSM247753 1 0 1 1 0
#> GSM247723 2 0 1 0 1
#> GSM247779 2 0 1 0 1
#> GSM247756 1 0 1 1 0
#> GSM247826 2 0 1 0 1
#> GSM247775 1 0 1 1 0
#> GSM247741 2 0 1 0 1
#> GSM247799 2 0 1 0 1
#> GSM247778 1 0 1 1 0
#> GSM247806 2 0 1 0 1
#> GSM247815 1 0 1 1 0
#> GSM247735 2 0 1 0 1
#> GSM247831 2 0 1 0 1
#> GSM247845 1 0 1 1 0
#> GSM247791 2 0 1 0 1
#> GSM247780 1 0 1 1 0
#> GSM247853 1 0 1 1 0
#> GSM247800 2 0 1 0 1
#> GSM247729 2 0 1 0 1
#> GSM247810 1 0 1 1 0
#> GSM247844 2 0 1 0 1
#> GSM247793 1 0 1 1 0
#> GSM247759 2 0 1 0 1
#> GSM247724 2 0 1 0 1
#> GSM247817 2 0 1 0 1
#> GSM247727 1 0 1 1 0
#> GSM247796 2 0 1 0 1
#> GSM247725 2 0 1 0 1
#> GSM247801 1 0 1 1 0
#> GSM247731 2 0 1 0 1
#> GSM247765 1 0 1 1 0
#> GSM247792 2 0 1 0 1
#> GSM247726 2 0 1 0 1
#> GSM247803 1 0 1 1 0
#> GSM247728 2 0 1 0 1
#> GSM247768 1 0 1 1 0
#> GSM247745 2 0 1 0 1
#> GSM247855 2 0 1 0 1
#> GSM247804 2 0 1 0 1
#> GSM247774 1 0 1 1 0
#> GSM247807 2 0 1 0 1
#> GSM247813 1 0 1 1 0
#> GSM247736 2 0 1 0 1
#> GSM247712 2 0 1 0 1
#> GSM247797 1 0 1 1 0
#> GSM247743 2 0 1 0 1
#> GSM247719 1 0 1 1 0
#> GSM247707 2 0 1 0 1
#> GSM247737 2 0 1 0 1
#> GSM247827 2 0 1 0 1
#> GSM247848 1 0 1 1 0
#> GSM247794 2 0 1 0 1
#> GSM247757 2 0 1 0 1
#> GSM247744 1 0 1 1 0
#> GSM247751 2 0 1 0 1
#> GSM247837 1 0 1 1 0
#> GSM247754 2 0 1 0 1
#> GSM247789 2 0 1 0 1
#> GSM247802 1 0 1 1 0
#> GSM247771 2 0 1 0 1
#> GSM247763 1 0 1 1 0
#> GSM247808 2 0 1 0 1
#> GSM247787 2 0 1 0 1
#> GSM247843 1 0 1 1 0
#> GSM247811 2 0 1 0 1
#> GSM247773 1 0 1 1 0
#> GSM247766 2 0 1 0 1
#> GSM247718 2 0 1 0 1
#> GSM247832 1 0 1 1 0
#> GSM247709 2 0 1 0 1
#> GSM247820 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0747 0.992 0 0.984 0.016
#> GSM247854 2 0.0747 0.992 0 0.984 0.016
#> GSM247758 2 0.0000 0.991 0 1.000 0.000
#> GSM247742 1 0.0000 1.000 1 0.000 0.000
#> GSM247755 3 0.0000 1.000 0 0.000 1.000
#> GSM247841 1 0.0000 1.000 1 0.000 0.000
#> GSM247703 2 0.0747 0.992 0 0.984 0.016
#> GSM247739 2 0.0000 0.991 0 1.000 0.000
#> GSM247715 1 0.0000 1.000 1 0.000 0.000
#> GSM247829 3 0.0000 1.000 0 0.000 1.000
#> GSM247842 1 0.0000 1.000 1 0.000 0.000
#> GSM247805 2 0.0747 0.992 0 0.984 0.016
#> GSM247786 2 0.0000 0.991 0 1.000 0.000
#> GSM247812 3 0.0000 1.000 0 0.000 1.000
#> GSM247776 1 0.0000 1.000 1 0.000 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0.000
#> GSM247717 2 0.0747 0.992 0 0.984 0.016
#> GSM247784 2 0.0000 0.991 0 1.000 0.000
#> GSM247834 1 0.0000 1.000 1 0.000 0.000
#> GSM247783 3 0.0000 1.000 0 0.000 1.000
#> GSM247846 1 0.0000 1.000 1 0.000 0.000
#> GSM247822 2 0.0747 0.992 0 0.984 0.016
#> GSM247710 2 0.0000 0.991 0 1.000 0.000
#> GSM247713 1 0.0000 1.000 1 0.000 0.000
#> GSM247840 3 0.0000 1.000 0 0.000 1.000
#> GSM247733 1 0.0000 1.000 1 0.000 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0.000
#> GSM247790 2 0.0747 0.992 0 0.984 0.016
#> GSM247730 2 0.0000 0.991 0 1.000 0.000
#> GSM247824 3 0.0000 1.000 0 0.000 1.000
#> GSM247770 1 0.0000 1.000 1 0.000 0.000
#> GSM247711 2 0.0747 0.992 0 0.984 0.016
#> GSM247782 2 0.0000 0.991 0 1.000 0.000
#> GSM247836 1 0.0000 1.000 1 0.000 0.000
#> GSM247785 3 0.0000 1.000 0 0.000 1.000
#> GSM247847 1 0.0000 1.000 1 0.000 0.000
#> GSM247750 2 0.0747 0.992 0 0.984 0.016
#> GSM247788 2 0.0000 0.991 0 1.000 0.000
#> GSM247849 1 0.0000 1.000 1 0.000 0.000
#> GSM247772 3 0.0000 1.000 0 0.000 1.000
#> GSM247760 1 0.0000 1.000 1 0.000 0.000
#> GSM247764 2 0.0747 0.992 0 0.984 0.016
#> GSM247851 2 0.0747 0.992 0 0.984 0.016
#> GSM247714 2 0.0000 0.991 0 1.000 0.000
#> GSM247828 1 0.0000 1.000 1 0.000 0.000
#> GSM247704 3 0.0000 1.000 0 0.000 1.000
#> GSM247818 1 0.0000 1.000 1 0.000 0.000
#> GSM247823 2 0.0747 0.992 0 0.984 0.016
#> GSM247706 2 0.0000 0.991 0 1.000 0.000
#> GSM247835 3 0.0000 1.000 0 0.000 1.000
#> GSM247734 1 0.0000 1.000 1 0.000 0.000
#> GSM247819 2 0.0747 0.992 0 0.984 0.016
#> GSM247809 2 0.0000 0.991 0 1.000 0.000
#> GSM247830 3 0.0000 1.000 0 0.000 1.000
#> GSM247833 1 0.0000 1.000 1 0.000 0.000
#> GSM247738 2 0.0747 0.992 0 0.984 0.016
#> GSM247716 2 0.0000 0.991 0 1.000 0.000
#> GSM247747 3 0.0000 1.000 0 0.000 1.000
#> GSM247722 1 0.0000 1.000 1 0.000 0.000
#> GSM247816 2 0.0747 0.992 0 0.984 0.016
#> GSM247839 2 0.0000 0.991 0 1.000 0.000
#> GSM247821 1 0.0000 1.000 1 0.000 0.000
#> GSM247798 3 0.0000 1.000 0 0.000 1.000
#> GSM247838 1 0.0000 1.000 1 0.000 0.000
#> GSM247721 2 0.0747 0.992 0 0.984 0.016
#> GSM247781 2 0.0000 0.991 0 1.000 0.000
#> GSM247762 1 0.0000 1.000 1 0.000 0.000
#> GSM247825 3 0.0000 1.000 0 0.000 1.000
#> GSM247777 1 0.0000 1.000 1 0.000 0.000
#> GSM247761 2 0.0747 0.992 0 0.984 0.016
#> GSM247720 2 0.0000 0.991 0 1.000 0.000
#> GSM247814 3 0.0000 1.000 0 0.000 1.000
#> GSM247732 1 0.0000 1.000 1 0.000 0.000
#> GSM247708 2 0.0747 0.992 0 0.984 0.016
#> GSM247740 2 0.0000 0.991 0 1.000 0.000
#> GSM247749 1 0.0000 1.000 1 0.000 0.000
#> GSM247767 3 0.0000 1.000 0 0.000 1.000
#> GSM247748 1 0.0000 1.000 1 0.000 0.000
#> GSM247705 2 0.0747 0.992 0 0.984 0.016
#> GSM247746 2 0.0000 0.991 0 1.000 0.000
#> GSM247752 1 0.0000 1.000 1 0.000 0.000
#> GSM247769 3 0.0000 1.000 0 0.000 1.000
#> GSM247753 1 0.0000 1.000 1 0.000 0.000
#> GSM247723 2 0.0747 0.992 0 0.984 0.016
#> GSM247779 2 0.0000 0.991 0 1.000 0.000
#> GSM247756 1 0.0000 1.000 1 0.000 0.000
#> GSM247826 3 0.0000 1.000 0 0.000 1.000
#> GSM247775 1 0.0000 1.000 1 0.000 0.000
#> GSM247741 2 0.0747 0.992 0 0.984 0.016
#> GSM247799 2 0.0000 0.991 0 1.000 0.000
#> GSM247778 1 0.0000 1.000 1 0.000 0.000
#> GSM247806 3 0.0000 1.000 0 0.000 1.000
#> GSM247815 1 0.0000 1.000 1 0.000 0.000
#> GSM247735 2 0.0747 0.992 0 0.984 0.016
#> GSM247831 2 0.0000 0.991 0 1.000 0.000
#> GSM247845 1 0.0000 1.000 1 0.000 0.000
#> GSM247791 3 0.0000 1.000 0 0.000 1.000
#> GSM247780 1 0.0000 1.000 1 0.000 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0.000
#> GSM247800 2 0.0747 0.992 0 0.984 0.016
#> GSM247729 2 0.0000 0.991 0 1.000 0.000
#> GSM247810 1 0.0000 1.000 1 0.000 0.000
#> GSM247844 3 0.0000 1.000 0 0.000 1.000
#> GSM247793 1 0.0000 1.000 1 0.000 0.000
#> GSM247759 2 0.0747 0.992 0 0.984 0.016
#> GSM247724 2 0.0000 0.991 0 1.000 0.000
#> GSM247817 3 0.0000 1.000 0 0.000 1.000
#> GSM247727 1 0.0000 1.000 1 0.000 0.000
#> GSM247796 2 0.0747 0.992 0 0.984 0.016
#> GSM247725 2 0.0000 0.991 0 1.000 0.000
#> GSM247801 1 0.0000 1.000 1 0.000 0.000
#> GSM247731 3 0.0000 1.000 0 0.000 1.000
#> GSM247765 1 0.0000 1.000 1 0.000 0.000
#> GSM247792 2 0.0747 0.992 0 0.984 0.016
#> GSM247726 2 0.0000 0.991 0 1.000 0.000
#> GSM247803 1 0.0000 1.000 1 0.000 0.000
#> GSM247728 3 0.0000 1.000 0 0.000 1.000
#> GSM247768 1 0.0000 1.000 1 0.000 0.000
#> GSM247745 2 0.0747 0.992 0 0.984 0.016
#> GSM247855 2 0.0747 0.992 0 0.984 0.016
#> GSM247804 2 0.0000 0.991 0 1.000 0.000
#> GSM247774 1 0.0000 1.000 1 0.000 0.000
#> GSM247807 3 0.0000 1.000 0 0.000 1.000
#> GSM247813 1 0.0000 1.000 1 0.000 0.000
#> GSM247736 2 0.0747 0.992 0 0.984 0.016
#> GSM247712 2 0.0000 0.991 0 1.000 0.000
#> GSM247797 1 0.0000 1.000 1 0.000 0.000
#> GSM247743 3 0.0000 1.000 0 0.000 1.000
#> GSM247719 1 0.0000 1.000 1 0.000 0.000
#> GSM247707 2 0.0747 0.992 0 0.984 0.016
#> GSM247737 2 0.0000 0.991 0 1.000 0.000
#> GSM247827 3 0.0000 1.000 0 0.000 1.000
#> GSM247848 1 0.0000 1.000 1 0.000 0.000
#> GSM247794 2 0.0747 0.992 0 0.984 0.016
#> GSM247757 2 0.0000 0.991 0 1.000 0.000
#> GSM247744 1 0.0000 1.000 1 0.000 0.000
#> GSM247751 3 0.0000 1.000 0 0.000 1.000
#> GSM247837 1 0.0000 1.000 1 0.000 0.000
#> GSM247754 2 0.0747 0.992 0 0.984 0.016
#> GSM247789 2 0.0000 0.991 0 1.000 0.000
#> GSM247802 1 0.0000 1.000 1 0.000 0.000
#> GSM247771 3 0.0000 1.000 0 0.000 1.000
#> GSM247763 1 0.0000 1.000 1 0.000 0.000
#> GSM247808 2 0.0747 0.992 0 0.984 0.016
#> GSM247787 2 0.0000 0.991 0 1.000 0.000
#> GSM247843 1 0.0000 1.000 1 0.000 0.000
#> GSM247811 3 0.0000 1.000 0 0.000 1.000
#> GSM247773 1 0.0000 1.000 1 0.000 0.000
#> GSM247766 2 0.0747 0.992 0 0.984 0.016
#> GSM247718 2 0.0000 0.991 0 1.000 0.000
#> GSM247832 1 0.0000 1.000 1 0.000 0.000
#> GSM247709 3 0.0000 1.000 0 0.000 1.000
#> GSM247820 1 0.0000 1.000 1 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247854 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247758 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247742 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247755 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247841 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247703 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247739 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247715 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247829 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247842 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247805 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247786 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247812 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247776 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247850 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247717 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247784 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247834 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247783 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247846 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247822 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247710 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247713 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247840 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247733 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247852 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247790 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247730 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247824 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247770 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247711 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247782 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247836 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247785 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247847 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247750 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247788 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247849 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247772 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247760 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247764 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247851 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247714 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247828 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247704 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247818 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247823 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247706 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247835 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247734 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247819 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247809 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247830 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247833 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247738 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247716 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247747 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247722 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247816 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247839 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247821 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247798 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247838 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247721 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247781 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247762 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247825 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247777 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247761 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247720 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247814 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247732 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247708 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247740 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247749 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247767 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247748 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247705 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247746 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247752 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247769 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247753 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247723 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247779 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247756 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247826 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247775 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247741 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247799 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247778 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247806 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247815 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247735 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247831 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247845 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247791 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247780 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247853 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247800 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247729 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247810 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247844 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247793 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247759 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247724 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247817 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247727 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247796 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247725 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247801 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247731 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247765 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247792 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247726 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247803 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247728 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247768 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247745 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247855 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247804 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247774 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247807 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247813 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247736 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247712 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247797 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247743 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247719 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247707 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247737 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247827 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247848 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247794 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247757 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247744 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247751 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247837 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247754 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247789 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247802 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247771 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247763 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247808 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247787 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247843 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247811 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247773 1 0.000 0.977 1.000 0.000 0.000 0.000
#> GSM247766 2 0.190 1.000 0.000 0.932 0.004 0.064
#> GSM247718 4 0.000 1.000 0.000 0.000 0.000 1.000
#> GSM247832 1 0.179 0.966 0.932 0.068 0.000 0.000
#> GSM247709 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247820 1 0.000 0.977 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247854 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247758 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247742 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247755 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247841 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247703 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247739 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247715 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247829 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247842 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247805 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247786 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247812 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247776 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247850 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247717 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247784 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247834 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247783 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247846 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247822 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247710 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247713 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247840 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247733 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247852 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247790 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247730 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247824 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247770 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247711 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247782 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247836 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247785 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247847 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247750 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247788 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247849 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247772 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247760 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247764 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247851 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247714 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247828 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247704 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247818 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247823 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247706 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247835 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247734 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247819 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247809 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247830 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247833 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247738 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247716 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247747 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247722 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247816 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247839 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247821 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247798 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247838 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247721 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247781 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247762 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247825 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247777 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247761 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247720 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247814 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247732 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247708 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247740 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247749 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247767 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247748 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247705 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247746 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247752 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247769 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247753 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247723 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247779 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247756 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247826 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247775 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247741 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247799 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247778 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247806 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247815 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247735 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247831 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247845 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247791 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247780 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247853 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247800 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247729 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247810 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247844 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247793 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247759 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247724 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247817 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247727 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247796 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247725 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247801 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247731 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247765 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247792 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247726 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247803 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247728 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247768 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247745 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247855 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247804 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247774 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247807 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247813 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247736 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247712 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247797 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247743 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247719 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247707 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247737 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247827 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247848 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247794 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247757 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247744 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247751 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247837 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247754 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247789 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247802 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247771 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247763 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247808 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247787 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247843 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247811 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247773 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247766 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247718 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247832 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247709 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247820 1 0.0000 1.000 1.000 0.000 0 0.000 0
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.0000 0.817 0 1.000 0 0 0.000 0.000
#> GSM247854 2 0.0000 0.817 0 1.000 0 0 0.000 0.000
#> GSM247758 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247742 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247755 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247841 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247703 2 0.0146 0.816 0 0.996 0 0 0.000 0.004
#> GSM247739 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247715 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247829 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247842 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247805 2 0.0000 0.817 0 1.000 0 0 0.000 0.000
#> GSM247786 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247812 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247776 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247717 2 0.0000 0.817 0 1.000 0 0 0.000 0.000
#> GSM247784 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247834 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247783 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247846 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247822 2 0.3607 0.777 0 0.652 0 0 0.000 0.348
#> GSM247710 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247713 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247840 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247733 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247790 2 0.0146 0.816 0 0.996 0 0 0.000 0.004
#> GSM247730 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247824 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247770 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247711 2 0.0000 0.817 0 1.000 0 0 0.000 0.000
#> GSM247782 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247836 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247785 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247847 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247750 2 0.0146 0.816 0 0.996 0 0 0.000 0.004
#> GSM247788 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247849 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247772 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247760 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247764 2 0.3727 0.768 0 0.612 0 0 0.000 0.388
#> GSM247851 2 0.3727 0.768 0 0.612 0 0 0.000 0.388
#> GSM247714 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247828 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247704 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247818 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247823 2 0.3684 0.773 0 0.628 0 0 0.000 0.372
#> GSM247706 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247835 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247734 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247819 2 0.3717 0.769 0 0.616 0 0 0.000 0.384
#> GSM247809 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247830 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247833 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247738 2 0.0000 0.817 0 1.000 0 0 0.000 0.000
#> GSM247716 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247747 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247722 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247816 2 0.2793 0.795 0 0.800 0 0 0.000 0.200
#> GSM247839 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247821 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247798 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247838 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247721 2 0.0146 0.816 0 0.996 0 0 0.000 0.004
#> GSM247781 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247762 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247825 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247777 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247761 2 0.0146 0.817 0 0.996 0 0 0.000 0.004
#> GSM247720 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247814 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247732 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247708 2 0.0000 0.817 0 1.000 0 0 0.000 0.000
#> GSM247740 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247749 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247767 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247748 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247705 2 0.3695 0.772 0 0.624 0 0 0.000 0.376
#> GSM247746 6 0.3727 1.000 0 0.000 0 0 0.388 0.612
#> GSM247752 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247769 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247753 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247723 2 0.3717 0.769 0 0.616 0 0 0.000 0.384
#> GSM247779 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247756 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247826 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247775 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247741 2 0.3717 0.769 0 0.616 0 0 0.000 0.384
#> GSM247799 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247778 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247806 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247815 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247735 2 0.3717 0.769 0 0.616 0 0 0.000 0.384
#> GSM247831 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247845 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247791 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247780 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247800 2 0.3717 0.769 0 0.616 0 0 0.000 0.384
#> GSM247729 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247810 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247844 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247793 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247759 2 0.3684 0.773 0 0.628 0 0 0.000 0.372
#> GSM247724 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247817 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247727 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247796 2 0.3717 0.769 0 0.616 0 0 0.000 0.384
#> GSM247725 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247801 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247731 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247765 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247792 2 0.3717 0.769 0 0.616 0 0 0.000 0.384
#> GSM247726 6 0.3727 1.000 0 0.000 0 0 0.388 0.612
#> GSM247803 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247728 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247768 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247745 2 0.0000 0.817 0 1.000 0 0 0.000 0.000
#> GSM247855 2 0.0000 0.817 0 1.000 0 0 0.000 0.000
#> GSM247804 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247774 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247807 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247813 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247736 2 0.0000 0.817 0 1.000 0 0 0.000 0.000
#> GSM247712 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247797 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247743 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247719 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247707 2 0.0146 0.816 0 0.996 0 0 0.000 0.004
#> GSM247737 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247827 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247848 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247794 2 0.0146 0.816 0 0.996 0 0 0.000 0.004
#> GSM247757 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247744 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247751 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247837 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247754 2 0.3684 0.773 0 0.628 0 0 0.000 0.372
#> GSM247789 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247802 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247771 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247763 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247808 2 0.0000 0.817 0 1.000 0 0 0.000 0.000
#> GSM247787 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247843 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247811 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247773 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247766 2 0.3717 0.769 0 0.616 0 0 0.000 0.384
#> GSM247718 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247832 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247709 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247820 1 0.0000 1.000 1 0.000 0 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> SD:skmeans 153 1 1.000 4.63e-32 2
#> SD:skmeans 153 1 0.985 2.17e-61 3
#> SD:skmeans 153 1 0.996 1.16e-90 4
#> SD:skmeans 153 1 0.989 6.51e-120 5
#> SD:skmeans 153 1 0.662 8.52e-117 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.
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 19559 rows and 153 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.984 0.992 0.4586 0.540 0.540
#> 3 3 0.990 0.974 0.987 0.3989 0.819 0.664
#> 4 4 1.000 0.988 0.994 0.1122 0.920 0.779
#> 5 5 1.000 1.000 1.000 0.1239 0.909 0.686
#> 6 6 0.961 0.922 0.919 0.0209 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] 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0.0000 0.995 0.000 1.000
#> GSM247854 2 0.0000 0.995 0.000 1.000
#> GSM247758 2 0.0000 0.995 0.000 1.000
#> GSM247742 1 0.0672 0.981 0.992 0.008
#> GSM247755 2 0.0000 0.995 0.000 1.000
#> GSM247841 1 0.0000 0.986 1.000 0.000
#> GSM247703 2 0.0000 0.995 0.000 1.000
#> GSM247739 2 0.0000 0.995 0.000 1.000
#> GSM247715 1 0.0000 0.986 1.000 0.000
#> GSM247829 2 0.0000 0.995 0.000 1.000
#> GSM247842 1 0.0000 0.986 1.000 0.000
#> GSM247805 2 0.0000 0.995 0.000 1.000
#> GSM247786 2 0.0000 0.995 0.000 1.000
#> GSM247812 2 0.0000 0.995 0.000 1.000
#> GSM247776 1 0.0000 0.986 1.000 0.000
#> GSM247850 1 0.0000 0.986 1.000 0.000
#> GSM247717 2 0.0000 0.995 0.000 1.000
#> GSM247784 2 0.0000 0.995 0.000 1.000
#> GSM247834 1 0.3431 0.935 0.936 0.064
#> GSM247783 2 0.0000 0.995 0.000 1.000
#> GSM247846 1 0.0000 0.986 1.000 0.000
#> GSM247822 2 0.0000 0.995 0.000 1.000
#> GSM247710 2 0.0000 0.995 0.000 1.000
#> GSM247713 1 0.2423 0.957 0.960 0.040
#> GSM247840 2 0.0000 0.995 0.000 1.000
#> GSM247733 1 0.0000 0.986 1.000 0.000
#> GSM247852 1 0.0000 0.986 1.000 0.000
#> GSM247790 2 0.0000 0.995 0.000 1.000
#> GSM247730 2 0.0000 0.995 0.000 1.000
#> GSM247824 2 0.0000 0.995 0.000 1.000
#> GSM247770 1 0.0000 0.986 1.000 0.000
#> GSM247711 2 0.0000 0.995 0.000 1.000
#> GSM247782 2 0.0000 0.995 0.000 1.000
#> GSM247836 1 0.1633 0.970 0.976 0.024
#> GSM247785 2 0.0000 0.995 0.000 1.000
#> GSM247847 1 0.0000 0.986 1.000 0.000
#> GSM247750 2 0.0000 0.995 0.000 1.000
#> GSM247788 2 0.0000 0.995 0.000 1.000
#> GSM247849 1 0.0000 0.986 1.000 0.000
#> GSM247772 2 0.0000 0.995 0.000 1.000
#> GSM247760 1 0.0000 0.986 1.000 0.000
#> GSM247764 2 0.0000 0.995 0.000 1.000
#> GSM247851 2 0.0000 0.995 0.000 1.000
#> GSM247714 2 0.0000 0.995 0.000 1.000
#> GSM247828 1 0.0000 0.986 1.000 0.000
#> GSM247704 2 0.0000 0.995 0.000 1.000
#> GSM247818 1 0.0000 0.986 1.000 0.000
#> GSM247823 2 0.0000 0.995 0.000 1.000
#> GSM247706 2 0.0000 0.995 0.000 1.000
#> GSM247835 2 0.0000 0.995 0.000 1.000
#> GSM247734 1 0.0000 0.986 1.000 0.000
#> GSM247819 2 0.0000 0.995 0.000 1.000
#> GSM247809 2 0.0000 0.995 0.000 1.000
#> GSM247830 2 0.0000 0.995 0.000 1.000
#> GSM247833 1 0.0000 0.986 1.000 0.000
#> GSM247738 2 0.0000 0.995 0.000 1.000
#> GSM247716 2 0.0000 0.995 0.000 1.000
#> GSM247747 2 0.0000 0.995 0.000 1.000
#> GSM247722 1 0.0000 0.986 1.000 0.000
#> GSM247816 2 0.0000 0.995 0.000 1.000
#> GSM247839 2 0.0000 0.995 0.000 1.000
#> GSM247821 1 0.1633 0.970 0.976 0.024
#> GSM247798 2 0.0000 0.995 0.000 1.000
#> GSM247838 1 0.0000 0.986 1.000 0.000
#> GSM247721 2 0.0000 0.995 0.000 1.000
#> GSM247781 2 0.0000 0.995 0.000 1.000
#> GSM247762 2 0.9129 0.499 0.328 0.672
#> GSM247825 2 0.0000 0.995 0.000 1.000
#> GSM247777 1 0.0000 0.986 1.000 0.000
#> GSM247761 2 0.0000 0.995 0.000 1.000
#> GSM247720 2 0.0000 0.995 0.000 1.000
#> GSM247814 2 0.0000 0.995 0.000 1.000
#> GSM247732 1 0.0000 0.986 1.000 0.000
#> GSM247708 2 0.0000 0.995 0.000 1.000
#> GSM247740 2 0.0000 0.995 0.000 1.000
#> GSM247749 1 0.2423 0.957 0.960 0.040
#> GSM247767 2 0.0000 0.995 0.000 1.000
#> GSM247748 1 0.0000 0.986 1.000 0.000
#> GSM247705 2 0.0000 0.995 0.000 1.000
#> GSM247746 2 0.0000 0.995 0.000 1.000
#> GSM247752 2 0.4939 0.874 0.108 0.892
#> GSM247769 2 0.0000 0.995 0.000 1.000
#> GSM247753 1 0.0000 0.986 1.000 0.000
#> GSM247723 2 0.0000 0.995 0.000 1.000
#> GSM247779 2 0.0000 0.995 0.000 1.000
#> GSM247756 1 0.0000 0.986 1.000 0.000
#> GSM247826 2 0.0000 0.995 0.000 1.000
#> GSM247775 1 0.0000 0.986 1.000 0.000
#> GSM247741 2 0.0000 0.995 0.000 1.000
#> GSM247799 2 0.0000 0.995 0.000 1.000
#> GSM247778 1 0.0000 0.986 1.000 0.000
#> GSM247806 2 0.0000 0.995 0.000 1.000
#> GSM247815 1 0.0000 0.986 1.000 0.000
#> GSM247735 2 0.0000 0.995 0.000 1.000
#> GSM247831 2 0.0000 0.995 0.000 1.000
#> GSM247845 1 0.0000 0.986 1.000 0.000
#> GSM247791 2 0.0000 0.995 0.000 1.000
#> GSM247780 1 0.0000 0.986 1.000 0.000
#> GSM247853 1 0.0000 0.986 1.000 0.000
#> GSM247800 2 0.0000 0.995 0.000 1.000
#> GSM247729 2 0.0000 0.995 0.000 1.000
#> GSM247810 1 0.6247 0.829 0.844 0.156
#> GSM247844 2 0.0000 0.995 0.000 1.000
#> GSM247793 1 0.0000 0.986 1.000 0.000
#> GSM247759 2 0.0000 0.995 0.000 1.000
#> GSM247724 2 0.0000 0.995 0.000 1.000
#> GSM247817 2 0.0000 0.995 0.000 1.000
#> GSM247727 1 0.0000 0.986 1.000 0.000
#> GSM247796 2 0.0000 0.995 0.000 1.000
#> GSM247725 2 0.0000 0.995 0.000 1.000
#> GSM247801 1 0.6801 0.796 0.820 0.180
#> GSM247731 2 0.0000 0.995 0.000 1.000
#> GSM247765 1 0.0000 0.986 1.000 0.000
#> GSM247792 2 0.0000 0.995 0.000 1.000
#> GSM247726 2 0.0000 0.995 0.000 1.000
#> GSM247803 2 0.0000 0.995 0.000 1.000
#> GSM247728 2 0.0000 0.995 0.000 1.000
#> GSM247768 1 0.0000 0.986 1.000 0.000
#> GSM247745 2 0.0000 0.995 0.000 1.000
#> GSM247855 2 0.0000 0.995 0.000 1.000
#> GSM247804 2 0.0000 0.995 0.000 1.000
#> GSM247774 1 0.5178 0.879 0.884 0.116
#> GSM247807 2 0.0000 0.995 0.000 1.000
#> GSM247813 1 0.0000 0.986 1.000 0.000
#> GSM247736 2 0.0000 0.995 0.000 1.000
#> GSM247712 2 0.0000 0.995 0.000 1.000
#> GSM247797 1 0.3733 0.927 0.928 0.072
#> GSM247743 2 0.0000 0.995 0.000 1.000
#> GSM247719 1 0.0000 0.986 1.000 0.000
#> GSM247707 2 0.0000 0.995 0.000 1.000
#> GSM247737 2 0.0000 0.995 0.000 1.000
#> GSM247827 2 0.0000 0.995 0.000 1.000
#> GSM247848 1 0.0000 0.986 1.000 0.000
#> GSM247794 2 0.0000 0.995 0.000 1.000
#> GSM247757 2 0.0000 0.995 0.000 1.000
#> GSM247744 1 0.1633 0.970 0.976 0.024
#> GSM247751 2 0.0000 0.995 0.000 1.000
#> GSM247837 1 0.0000 0.986 1.000 0.000
#> GSM247754 2 0.0000 0.995 0.000 1.000
#> GSM247789 2 0.0000 0.995 0.000 1.000
#> GSM247802 1 0.0672 0.981 0.992 0.008
#> GSM247771 2 0.0000 0.995 0.000 1.000
#> GSM247763 1 0.0000 0.986 1.000 0.000
#> GSM247808 2 0.0000 0.995 0.000 1.000
#> GSM247787 2 0.0000 0.995 0.000 1.000
#> GSM247843 1 0.0000 0.986 1.000 0.000
#> GSM247811 2 0.0000 0.995 0.000 1.000
#> GSM247773 1 0.0000 0.986 1.000 0.000
#> GSM247766 2 0.0000 0.995 0.000 1.000
#> GSM247718 2 0.0000 0.995 0.000 1.000
#> GSM247832 1 0.0000 0.986 1.000 0.000
#> GSM247709 2 0.0000 0.995 0.000 1.000
#> GSM247820 1 0.0000 0.986 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247854 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247758 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247742 1 0.1964 0.931 0.944 0.056 0.000
#> GSM247755 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247841 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247703 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247739 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247715 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247829 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247842 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247805 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247786 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247812 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247776 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247850 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247717 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247784 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247834 1 0.3941 0.826 0.844 0.156 0.000
#> GSM247783 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247846 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247822 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247710 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247713 1 0.2711 0.901 0.912 0.088 0.000
#> GSM247840 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247733 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247852 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247790 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247730 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247824 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247770 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247711 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247782 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247836 1 0.0892 0.961 0.980 0.020 0.000
#> GSM247785 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247847 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247750 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247788 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247849 1 0.0237 0.972 0.996 0.004 0.000
#> GSM247772 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247760 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247764 2 0.3941 0.825 0.000 0.844 0.156
#> GSM247851 2 0.3879 0.830 0.000 0.848 0.152
#> GSM247714 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247828 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247704 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247818 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247823 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247706 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247835 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247734 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247819 2 0.4504 0.770 0.000 0.804 0.196
#> GSM247809 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247830 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247833 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247738 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247716 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247747 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247722 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247816 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247839 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247821 1 0.2625 0.905 0.916 0.084 0.000
#> GSM247798 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247838 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247721 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247781 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247762 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247825 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247777 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247761 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247720 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247814 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247732 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247708 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247740 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247749 1 0.3340 0.867 0.880 0.120 0.000
#> GSM247767 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247748 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247705 2 0.2625 0.909 0.000 0.916 0.084
#> GSM247746 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247752 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247769 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247753 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247723 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247779 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247756 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247826 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247775 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247741 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247799 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247778 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247806 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247815 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247735 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247831 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247845 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247791 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247780 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247853 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247800 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247729 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247810 1 0.4750 0.749 0.784 0.216 0.000
#> GSM247844 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247793 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247759 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247724 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247817 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247727 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247796 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247725 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247801 1 0.4504 0.776 0.804 0.196 0.000
#> GSM247731 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247765 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247792 2 0.1411 0.956 0.000 0.964 0.036
#> GSM247726 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247803 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247728 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247768 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247745 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247855 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247804 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247774 1 0.2066 0.928 0.940 0.060 0.000
#> GSM247807 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247813 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247736 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247712 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247797 1 0.3192 0.876 0.888 0.112 0.000
#> GSM247743 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247719 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247707 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247737 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247827 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247848 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247794 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247757 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247744 1 0.1289 0.951 0.968 0.032 0.000
#> GSM247751 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247837 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247754 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247789 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247802 1 0.1163 0.955 0.972 0.028 0.000
#> GSM247771 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247763 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247808 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247787 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247843 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247811 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247773 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247766 2 0.3816 0.836 0.000 0.852 0.148
#> GSM247718 2 0.0000 0.988 0.000 1.000 0.000
#> GSM247832 1 0.0000 0.974 1.000 0.000 0.000
#> GSM247709 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247820 1 0.0000 0.974 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247854 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247758 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247742 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247755 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247841 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247703 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247739 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247715 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247829 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247842 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247805 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247786 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247812 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247776 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247850 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247717 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247784 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247834 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247783 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247846 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247822 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247710 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247713 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247840 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247733 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247852 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247790 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247730 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247824 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247770 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247711 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247782 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247836 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247785 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247847 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247750 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247788 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247849 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247772 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247760 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247764 2 0.3219 0.817 0 0.836 0.164 0
#> GSM247851 2 0.3172 0.823 0 0.840 0.160 0
#> GSM247714 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247828 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247704 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247818 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247823 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247706 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247835 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247734 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247819 2 0.3610 0.767 0 0.800 0.200 0
#> GSM247809 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247830 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247833 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247738 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247716 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247747 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247722 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247816 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247839 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247821 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247798 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247838 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247721 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247781 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247762 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247825 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247777 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247761 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247720 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247814 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247732 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247708 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247740 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247749 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247767 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247748 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247705 2 0.2530 0.879 0 0.888 0.112 0
#> GSM247746 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247752 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247769 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247753 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247723 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247779 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247756 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247826 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247775 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247741 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247799 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247778 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247806 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247815 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247735 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247831 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247845 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247791 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247780 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247853 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247800 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247729 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247810 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247844 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247793 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247759 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247724 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247817 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247727 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247796 2 0.0188 0.983 0 0.996 0.004 0
#> GSM247725 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247801 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247731 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247765 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247792 2 0.1557 0.935 0 0.944 0.056 0
#> GSM247726 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247803 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247728 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247768 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247745 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247855 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247804 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247774 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247807 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247813 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247736 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247712 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247797 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247743 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247719 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247707 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247737 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247827 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247848 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247794 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247757 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247744 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247751 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247837 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247754 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247789 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247802 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247771 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247763 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247808 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247787 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247843 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247811 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247773 1 0.0000 1.000 1 0.000 0.000 0
#> GSM247766 2 0.3219 0.818 0 0.836 0.164 0
#> GSM247718 2 0.0000 0.986 0 1.000 0.000 0
#> GSM247832 4 0.0000 1.000 0 0.000 0.000 1
#> GSM247709 3 0.0000 1.000 0 0.000 1.000 0
#> GSM247820 1 0.0000 1.000 1 0.000 0.000 0
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0 1 0 1 0 0 0
#> GSM247854 2 0 1 0 1 0 0 0
#> GSM247758 5 0 1 0 0 0 0 1
#> GSM247742 4 0 1 0 0 0 1 0
#> GSM247755 3 0 1 0 0 1 0 0
#> GSM247841 1 0 1 1 0 0 0 0
#> GSM247703 2 0 1 0 1 0 0 0
#> GSM247739 5 0 1 0 0 0 0 1
#> GSM247715 4 0 1 0 0 0 1 0
#> GSM247829 3 0 1 0 0 1 0 0
#> GSM247842 1 0 1 1 0 0 0 0
#> GSM247805 2 0 1 0 1 0 0 0
#> GSM247786 5 0 1 0 0 0 0 1
#> GSM247812 3 0 1 0 0 1 0 0
#> GSM247776 1 0 1 1 0 0 0 0
#> GSM247850 1 0 1 1 0 0 0 0
#> GSM247717 2 0 1 0 1 0 0 0
#> GSM247784 5 0 1 0 0 0 0 1
#> GSM247834 4 0 1 0 0 0 1 0
#> GSM247783 3 0 1 0 0 1 0 0
#> GSM247846 1 0 1 1 0 0 0 0
#> GSM247822 2 0 1 0 1 0 0 0
#> GSM247710 5 0 1 0 0 0 0 1
#> GSM247713 4 0 1 0 0 0 1 0
#> GSM247840 3 0 1 0 0 1 0 0
#> GSM247733 1 0 1 1 0 0 0 0
#> GSM247852 1 0 1 1 0 0 0 0
#> GSM247790 2 0 1 0 1 0 0 0
#> GSM247730 5 0 1 0 0 0 0 1
#> GSM247824 3 0 1 0 0 1 0 0
#> GSM247770 1 0 1 1 0 0 0 0
#> GSM247711 2 0 1 0 1 0 0 0
#> GSM247782 5 0 1 0 0 0 0 1
#> GSM247836 4 0 1 0 0 0 1 0
#> GSM247785 3 0 1 0 0 1 0 0
#> GSM247847 1 0 1 1 0 0 0 0
#> GSM247750 2 0 1 0 1 0 0 0
#> GSM247788 5 0 1 0 0 0 0 1
#> GSM247849 4 0 1 0 0 0 1 0
#> GSM247772 3 0 1 0 0 1 0 0
#> GSM247760 1 0 1 1 0 0 0 0
#> GSM247764 2 0 1 0 1 0 0 0
#> GSM247851 2 0 1 0 1 0 0 0
#> GSM247714 5 0 1 0 0 0 0 1
#> GSM247828 4 0 1 0 0 0 1 0
#> GSM247704 3 0 1 0 0 1 0 0
#> GSM247818 1 0 1 1 0 0 0 0
#> GSM247823 2 0 1 0 1 0 0 0
#> GSM247706 5 0 1 0 0 0 0 1
#> GSM247835 3 0 1 0 0 1 0 0
#> GSM247734 1 0 1 1 0 0 0 0
#> GSM247819 2 0 1 0 1 0 0 0
#> GSM247809 5 0 1 0 0 0 0 1
#> GSM247830 3 0 1 0 0 1 0 0
#> GSM247833 1 0 1 1 0 0 0 0
#> GSM247738 2 0 1 0 1 0 0 0
#> GSM247716 5 0 1 0 0 0 0 1
#> GSM247747 3 0 1 0 0 1 0 0
#> GSM247722 1 0 1 1 0 0 0 0
#> GSM247816 2 0 1 0 1 0 0 0
#> GSM247839 5 0 1 0 0 0 0 1
#> GSM247821 4 0 1 0 0 0 1 0
#> GSM247798 3 0 1 0 0 1 0 0
#> GSM247838 1 0 1 1 0 0 0 0
#> GSM247721 2 0 1 0 1 0 0 0
#> GSM247781 5 0 1 0 0 0 0 1
#> GSM247762 4 0 1 0 0 0 1 0
#> GSM247825 3 0 1 0 0 1 0 0
#> GSM247777 1 0 1 1 0 0 0 0
#> GSM247761 2 0 1 0 1 0 0 0
#> GSM247720 5 0 1 0 0 0 0 1
#> GSM247814 3 0 1 0 0 1 0 0
#> GSM247732 1 0 1 1 0 0 0 0
#> GSM247708 2 0 1 0 1 0 0 0
#> GSM247740 5 0 1 0 0 0 0 1
#> GSM247749 4 0 1 0 0 0 1 0
#> GSM247767 3 0 1 0 0 1 0 0
#> GSM247748 1 0 1 1 0 0 0 0
#> GSM247705 2 0 1 0 1 0 0 0
#> GSM247746 5 0 1 0 0 0 0 1
#> GSM247752 4 0 1 0 0 0 1 0
#> GSM247769 3 0 1 0 0 1 0 0
#> GSM247753 1 0 1 1 0 0 0 0
#> GSM247723 2 0 1 0 1 0 0 0
#> GSM247779 5 0 1 0 0 0 0 1
#> GSM247756 4 0 1 0 0 0 1 0
#> GSM247826 3 0 1 0 0 1 0 0
#> GSM247775 1 0 1 1 0 0 0 0
#> GSM247741 2 0 1 0 1 0 0 0
#> GSM247799 5 0 1 0 0 0 0 1
#> GSM247778 4 0 1 0 0 0 1 0
#> GSM247806 3 0 1 0 0 1 0 0
#> GSM247815 1 0 1 1 0 0 0 0
#> GSM247735 2 0 1 0 1 0 0 0
#> GSM247831 5 0 1 0 0 0 0 1
#> GSM247845 4 0 1 0 0 0 1 0
#> GSM247791 3 0 1 0 0 1 0 0
#> GSM247780 1 0 1 1 0 0 0 0
#> GSM247853 1 0 1 1 0 0 0 0
#> GSM247800 2 0 1 0 1 0 0 0
#> GSM247729 5 0 1 0 0 0 0 1
#> GSM247810 4 0 1 0 0 0 1 0
#> GSM247844 3 0 1 0 0 1 0 0
#> GSM247793 1 0 1 1 0 0 0 0
#> GSM247759 2 0 1 0 1 0 0 0
#> GSM247724 5 0 1 0 0 0 0 1
#> GSM247817 3 0 1 0 0 1 0 0
#> GSM247727 1 0 1 1 0 0 0 0
#> GSM247796 2 0 1 0 1 0 0 0
#> GSM247725 5 0 1 0 0 0 0 1
#> GSM247801 4 0 1 0 0 0 1 0
#> GSM247731 3 0 1 0 0 1 0 0
#> GSM247765 1 0 1 1 0 0 0 0
#> GSM247792 2 0 1 0 1 0 0 0
#> GSM247726 5 0 1 0 0 0 0 1
#> GSM247803 4 0 1 0 0 0 1 0
#> GSM247728 3 0 1 0 0 1 0 0
#> GSM247768 1 0 1 1 0 0 0 0
#> GSM247745 2 0 1 0 1 0 0 0
#> GSM247855 2 0 1 0 1 0 0 0
#> GSM247804 5 0 1 0 0 0 0 1
#> GSM247774 4 0 1 0 0 0 1 0
#> GSM247807 3 0 1 0 0 1 0 0
#> GSM247813 1 0 1 1 0 0 0 0
#> GSM247736 2 0 1 0 1 0 0 0
#> GSM247712 5 0 1 0 0 0 0 1
#> GSM247797 4 0 1 0 0 0 1 0
#> GSM247743 3 0 1 0 0 1 0 0
#> GSM247719 1 0 1 1 0 0 0 0
#> GSM247707 2 0 1 0 1 0 0 0
#> GSM247737 5 0 1 0 0 0 0 1
#> GSM247827 3 0 1 0 0 1 0 0
#> GSM247848 1 0 1 1 0 0 0 0
#> GSM247794 2 0 1 0 1 0 0 0
#> GSM247757 5 0 1 0 0 0 0 1
#> GSM247744 4 0 1 0 0 0 1 0
#> GSM247751 3 0 1 0 0 1 0 0
#> GSM247837 1 0 1 1 0 0 0 0
#> GSM247754 2 0 1 0 1 0 0 0
#> GSM247789 5 0 1 0 0 0 0 1
#> GSM247802 4 0 1 0 0 0 1 0
#> GSM247771 3 0 1 0 0 1 0 0
#> GSM247763 1 0 1 1 0 0 0 0
#> GSM247808 2 0 1 0 1 0 0 0
#> GSM247787 5 0 1 0 0 0 0 1
#> GSM247843 4 0 1 0 0 0 1 0
#> GSM247811 3 0 1 0 0 1 0 0
#> GSM247773 1 0 1 1 0 0 0 0
#> GSM247766 2 0 1 0 1 0 0 0
#> GSM247718 5 0 1 0 0 0 0 1
#> GSM247832 4 0 1 0 0 0 1 0
#> GSM247709 3 0 1 0 0 1 0 0
#> GSM247820 1 0 1 1 0 0 0 0
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.0790 0.845 0 0.968 0 0.000 0 0.032
#> GSM247854 2 0.0790 0.845 0 0.968 0 0.000 0 0.032
#> GSM247758 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247742 4 0.0000 0.821 0 0.000 0 1.000 0 0.000
#> GSM247755 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247841 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247703 2 0.2527 0.825 0 0.832 0 0.000 0 0.168
#> GSM247739 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247715 4 0.2793 0.378 0 0.000 0 0.800 0 0.200
#> GSM247829 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247842 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247805 2 0.2527 0.825 0 0.832 0 0.000 0 0.168
#> GSM247786 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247812 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247776 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247717 2 0.0790 0.845 0 0.968 0 0.000 0 0.032
#> GSM247784 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247834 6 0.3857 0.997 0 0.000 0 0.468 0 0.532
#> GSM247783 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247846 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247822 2 0.2793 0.805 0 0.800 0 0.000 0 0.200
#> GSM247710 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247713 6 0.3857 0.997 0 0.000 0 0.468 0 0.532
#> GSM247840 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247733 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247790 2 0.2527 0.825 0 0.832 0 0.000 0 0.168
#> GSM247730 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247824 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247770 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247711 2 0.0790 0.845 0 0.968 0 0.000 0 0.032
#> GSM247782 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247836 4 0.0146 0.818 0 0.000 0 0.996 0 0.004
#> GSM247785 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247847 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247750 2 0.2527 0.825 0 0.832 0 0.000 0 0.168
#> GSM247788 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247849 4 0.0000 0.821 0 0.000 0 1.000 0 0.000
#> GSM247772 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247760 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247764 2 0.3823 0.751 0 0.564 0 0.000 0 0.436
#> GSM247851 2 0.3823 0.751 0 0.564 0 0.000 0 0.436
#> GSM247714 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247828 4 0.0146 0.818 0 0.000 0 0.996 0 0.004
#> GSM247704 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247818 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247823 2 0.2454 0.828 0 0.840 0 0.000 0 0.160
#> GSM247706 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247835 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247734 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247819 2 0.3244 0.775 0 0.732 0 0.000 0 0.268
#> GSM247809 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247830 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247833 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247738 2 0.0790 0.845 0 0.968 0 0.000 0 0.032
#> GSM247716 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247747 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247722 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247816 2 0.2527 0.825 0 0.832 0 0.000 0 0.168
#> GSM247839 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247821 6 0.3857 0.997 0 0.000 0 0.468 0 0.532
#> GSM247798 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247838 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247721 2 0.2527 0.825 0 0.832 0 0.000 0 0.168
#> GSM247781 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247762 4 0.3515 -0.316 0 0.000 0 0.676 0 0.324
#> GSM247825 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247777 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247761 2 0.2527 0.825 0 0.832 0 0.000 0 0.168
#> GSM247720 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247814 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247732 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247708 2 0.0000 0.846 0 1.000 0 0.000 0 0.000
#> GSM247740 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247749 6 0.3857 0.997 0 0.000 0 0.468 0 0.532
#> GSM247767 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247748 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247705 2 0.2527 0.825 0 0.832 0 0.000 0 0.168
#> GSM247746 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247752 6 0.3857 0.997 0 0.000 0 0.468 0 0.532
#> GSM247769 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247753 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247723 2 0.3409 0.769 0 0.700 0 0.000 0 0.300
#> GSM247779 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247756 4 0.0000 0.821 0 0.000 0 1.000 0 0.000
#> GSM247826 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247775 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247741 2 0.3409 0.769 0 0.700 0 0.000 0 0.300
#> GSM247799 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247778 6 0.3857 0.997 0 0.000 0 0.468 0 0.532
#> GSM247806 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247815 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247735 2 0.3409 0.769 0 0.700 0 0.000 0 0.300
#> GSM247831 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247845 4 0.0000 0.821 0 0.000 0 1.000 0 0.000
#> GSM247791 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247780 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247800 2 0.3409 0.769 0 0.700 0 0.000 0 0.300
#> GSM247729 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247810 6 0.3857 0.997 0 0.000 0 0.468 0 0.532
#> GSM247844 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247793 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247759 2 0.3371 0.771 0 0.708 0 0.000 0 0.292
#> GSM247724 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247817 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247727 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247796 2 0.3371 0.771 0 0.708 0 0.000 0 0.292
#> GSM247725 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247801 4 0.3866 -0.889 0 0.000 0 0.516 0 0.484
#> GSM247731 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247765 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247792 2 0.3244 0.775 0 0.732 0 0.000 0 0.268
#> GSM247726 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247803 6 0.3857 0.997 0 0.000 0 0.468 0 0.532
#> GSM247728 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247768 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247745 2 0.0790 0.845 0 0.968 0 0.000 0 0.032
#> GSM247855 2 0.0790 0.845 0 0.968 0 0.000 0 0.032
#> GSM247804 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247774 4 0.0000 0.821 0 0.000 0 1.000 0 0.000
#> GSM247807 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247813 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247736 2 0.0790 0.845 0 0.968 0 0.000 0 0.032
#> GSM247712 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247797 6 0.3857 0.997 0 0.000 0 0.468 0 0.532
#> GSM247743 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247719 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247707 2 0.2527 0.825 0 0.832 0 0.000 0 0.168
#> GSM247737 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247827 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247848 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247794 2 0.2527 0.825 0 0.832 0 0.000 0 0.168
#> GSM247757 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247744 4 0.0000 0.821 0 0.000 0 1.000 0 0.000
#> GSM247751 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247837 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247754 2 0.0363 0.846 0 0.988 0 0.000 0 0.012
#> GSM247789 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247802 6 0.3857 0.997 0 0.000 0 0.468 0 0.532
#> GSM247771 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247763 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247808 2 0.0790 0.845 0 0.968 0 0.000 0 0.032
#> GSM247787 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247843 6 0.3864 0.971 0 0.000 0 0.480 0 0.520
#> GSM247811 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247773 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247766 2 0.3706 0.767 0 0.620 0 0.000 0 0.380
#> GSM247718 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247832 4 0.0000 0.821 0 0.000 0 1.000 0 0.000
#> GSM247709 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247820 1 0.0000 1.000 1 0.000 0 0.000 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
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
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> SD:pam 152 1 0.839 3.81e-30 2
#> SD:pam 153 1 0.856 1.44e-58 3
#> SD:pam 153 1 0.964 1.16e-90 4
#> SD:pam 153 1 0.989 6.51e-120 5
#> SD:pam 150 1 0.984 2.88e-114 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.
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 19559 rows and 153 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.540 0.745 0.863 0.4847 0.508 0.508
#> 3 3 0.810 0.959 0.971 0.3150 0.719 0.507
#> 4 4 1.000 1.000 1.000 0.1163 0.939 0.825
#> 5 5 1.000 0.996 0.998 0.1262 0.910 0.689
#> 6 6 0.936 0.833 0.907 -0.0041 0.914 0.664
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] 4 5
There is also optional best \(k\) = 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0.949 0.854 0.368 0.632
#> GSM247854 2 0.949 0.854 0.368 0.632
#> GSM247758 2 0.949 0.854 0.368 0.632
#> GSM247742 2 0.278 0.493 0.048 0.952
#> GSM247755 1 0.000 0.680 1.000 0.000
#> GSM247841 1 0.949 0.764 0.632 0.368
#> GSM247703 2 0.949 0.854 0.368 0.632
#> GSM247739 2 0.949 0.854 0.368 0.632
#> GSM247715 2 0.278 0.493 0.048 0.952
#> GSM247829 1 0.000 0.680 1.000 0.000
#> GSM247842 1 0.949 0.764 0.632 0.368
#> GSM247805 2 0.949 0.854 0.368 0.632
#> GSM247786 2 0.949 0.854 0.368 0.632
#> GSM247812 1 0.000 0.680 1.000 0.000
#> GSM247776 1 0.949 0.764 0.632 0.368
#> GSM247850 1 0.949 0.764 0.632 0.368
#> GSM247717 2 0.949 0.854 0.368 0.632
#> GSM247784 2 0.949 0.854 0.368 0.632
#> GSM247834 2 0.278 0.493 0.048 0.952
#> GSM247783 1 0.000 0.680 1.000 0.000
#> GSM247846 1 0.949 0.764 0.632 0.368
#> GSM247822 2 0.949 0.854 0.368 0.632
#> GSM247710 2 0.949 0.854 0.368 0.632
#> GSM247713 2 0.278 0.493 0.048 0.952
#> GSM247840 1 0.000 0.680 1.000 0.000
#> GSM247733 1 0.949 0.764 0.632 0.368
#> GSM247852 1 0.949 0.764 0.632 0.368
#> GSM247790 2 0.949 0.854 0.368 0.632
#> GSM247730 2 0.949 0.854 0.368 0.632
#> GSM247824 1 0.000 0.680 1.000 0.000
#> GSM247770 1 0.949 0.764 0.632 0.368
#> GSM247711 2 0.949 0.854 0.368 0.632
#> GSM247782 2 0.949 0.854 0.368 0.632
#> GSM247836 2 0.278 0.493 0.048 0.952
#> GSM247785 1 0.000 0.680 1.000 0.000
#> GSM247847 1 0.949 0.764 0.632 0.368
#> GSM247750 2 0.949 0.854 0.368 0.632
#> GSM247788 2 0.949 0.854 0.368 0.632
#> GSM247849 2 0.278 0.493 0.048 0.952
#> GSM247772 1 0.000 0.680 1.000 0.000
#> GSM247760 1 0.949 0.764 0.632 0.368
#> GSM247764 2 0.949 0.854 0.368 0.632
#> GSM247851 2 0.949 0.854 0.368 0.632
#> GSM247714 2 0.949 0.854 0.368 0.632
#> GSM247828 2 0.278 0.493 0.048 0.952
#> GSM247704 1 0.000 0.680 1.000 0.000
#> GSM247818 1 0.949 0.764 0.632 0.368
#> GSM247823 2 0.949 0.854 0.368 0.632
#> GSM247706 2 0.949 0.854 0.368 0.632
#> GSM247835 1 0.000 0.680 1.000 0.000
#> GSM247734 1 0.949 0.764 0.632 0.368
#> GSM247819 2 0.949 0.854 0.368 0.632
#> GSM247809 2 0.949 0.854 0.368 0.632
#> GSM247830 1 0.000 0.680 1.000 0.000
#> GSM247833 1 0.949 0.764 0.632 0.368
#> GSM247738 2 0.949 0.854 0.368 0.632
#> GSM247716 2 0.949 0.854 0.368 0.632
#> GSM247747 1 0.000 0.680 1.000 0.000
#> GSM247722 1 0.949 0.764 0.632 0.368
#> GSM247816 2 0.949 0.854 0.368 0.632
#> GSM247839 2 0.949 0.854 0.368 0.632
#> GSM247821 2 0.278 0.493 0.048 0.952
#> GSM247798 1 0.000 0.680 1.000 0.000
#> GSM247838 1 0.949 0.764 0.632 0.368
#> GSM247721 2 0.949 0.854 0.368 0.632
#> GSM247781 2 0.949 0.854 0.368 0.632
#> GSM247762 2 0.278 0.493 0.048 0.952
#> GSM247825 1 0.000 0.680 1.000 0.000
#> GSM247777 1 0.949 0.764 0.632 0.368
#> GSM247761 2 0.949 0.854 0.368 0.632
#> GSM247720 2 0.949 0.854 0.368 0.632
#> GSM247814 1 0.000 0.680 1.000 0.000
#> GSM247732 1 0.949 0.764 0.632 0.368
#> GSM247708 2 0.949 0.854 0.368 0.632
#> GSM247740 2 0.949 0.854 0.368 0.632
#> GSM247749 2 0.278 0.493 0.048 0.952
#> GSM247767 1 0.000 0.680 1.000 0.000
#> GSM247748 1 0.949 0.764 0.632 0.368
#> GSM247705 2 0.949 0.854 0.368 0.632
#> GSM247746 2 0.949 0.854 0.368 0.632
#> GSM247752 2 0.278 0.493 0.048 0.952
#> GSM247769 1 0.000 0.680 1.000 0.000
#> GSM247753 1 0.949 0.764 0.632 0.368
#> GSM247723 2 0.949 0.854 0.368 0.632
#> GSM247779 2 0.949 0.854 0.368 0.632
#> GSM247756 2 0.278 0.493 0.048 0.952
#> GSM247826 1 0.000 0.680 1.000 0.000
#> GSM247775 1 0.949 0.764 0.632 0.368
#> GSM247741 2 0.949 0.854 0.368 0.632
#> GSM247799 2 0.949 0.854 0.368 0.632
#> GSM247778 2 0.278 0.493 0.048 0.952
#> GSM247806 1 0.000 0.680 1.000 0.000
#> GSM247815 1 0.949 0.764 0.632 0.368
#> GSM247735 2 0.949 0.854 0.368 0.632
#> GSM247831 2 0.949 0.854 0.368 0.632
#> GSM247845 2 0.278 0.493 0.048 0.952
#> GSM247791 1 0.000 0.680 1.000 0.000
#> GSM247780 1 0.949 0.764 0.632 0.368
#> GSM247853 1 0.949 0.764 0.632 0.368
#> GSM247800 2 0.949 0.854 0.368 0.632
#> GSM247729 2 0.949 0.854 0.368 0.632
#> GSM247810 2 0.278 0.493 0.048 0.952
#> GSM247844 1 0.000 0.680 1.000 0.000
#> GSM247793 1 0.949 0.764 0.632 0.368
#> GSM247759 2 0.949 0.854 0.368 0.632
#> GSM247724 2 0.949 0.854 0.368 0.632
#> GSM247817 1 0.000 0.680 1.000 0.000
#> GSM247727 1 0.949 0.764 0.632 0.368
#> GSM247796 2 0.949 0.854 0.368 0.632
#> GSM247725 2 0.949 0.854 0.368 0.632
#> GSM247801 2 0.278 0.493 0.048 0.952
#> GSM247731 1 0.000 0.680 1.000 0.000
#> GSM247765 1 0.949 0.764 0.632 0.368
#> GSM247792 2 0.949 0.854 0.368 0.632
#> GSM247726 2 0.949 0.854 0.368 0.632
#> GSM247803 2 0.278 0.493 0.048 0.952
#> GSM247728 1 0.000 0.680 1.000 0.000
#> GSM247768 1 0.949 0.764 0.632 0.368
#> GSM247745 2 0.949 0.854 0.368 0.632
#> GSM247855 2 0.949 0.854 0.368 0.632
#> GSM247804 2 0.949 0.854 0.368 0.632
#> GSM247774 2 0.278 0.493 0.048 0.952
#> GSM247807 1 0.000 0.680 1.000 0.000
#> GSM247813 1 0.949 0.764 0.632 0.368
#> GSM247736 2 0.949 0.854 0.368 0.632
#> GSM247712 2 0.949 0.854 0.368 0.632
#> GSM247797 2 0.278 0.493 0.048 0.952
#> GSM247743 1 0.000 0.680 1.000 0.000
#> GSM247719 1 0.949 0.764 0.632 0.368
#> GSM247707 2 0.949 0.854 0.368 0.632
#> GSM247737 2 0.949 0.854 0.368 0.632
#> GSM247827 1 0.000 0.680 1.000 0.000
#> GSM247848 1 0.949 0.764 0.632 0.368
#> GSM247794 2 0.949 0.854 0.368 0.632
#> GSM247757 2 0.949 0.854 0.368 0.632
#> GSM247744 2 0.278 0.493 0.048 0.952
#> GSM247751 1 0.000 0.680 1.000 0.000
#> GSM247837 1 0.949 0.764 0.632 0.368
#> GSM247754 2 0.949 0.854 0.368 0.632
#> GSM247789 2 0.949 0.854 0.368 0.632
#> GSM247802 2 0.278 0.493 0.048 0.952
#> GSM247771 1 0.000 0.680 1.000 0.000
#> GSM247763 1 0.949 0.764 0.632 0.368
#> GSM247808 2 0.949 0.854 0.368 0.632
#> GSM247787 2 0.949 0.854 0.368 0.632
#> GSM247843 2 0.278 0.493 0.048 0.952
#> GSM247811 1 0.000 0.680 1.000 0.000
#> GSM247773 1 0.949 0.764 0.632 0.368
#> GSM247766 2 0.949 0.854 0.368 0.632
#> GSM247718 2 0.949 0.854 0.368 0.632
#> GSM247832 2 0.278 0.493 0.048 0.952
#> GSM247709 1 0.000 0.680 1.000 0.000
#> GSM247820 1 0.949 0.764 0.632 0.368
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.000 1.000 0 1.000 0.000
#> GSM247854 2 0.000 1.000 0 1.000 0.000
#> GSM247758 2 0.000 1.000 0 1.000 0.000
#> GSM247742 3 0.445 0.861 0 0.192 0.808
#> GSM247755 3 0.000 0.898 0 0.000 1.000
#> GSM247841 1 0.000 1.000 1 0.000 0.000
#> GSM247703 2 0.000 1.000 0 1.000 0.000
#> GSM247739 2 0.000 1.000 0 1.000 0.000
#> GSM247715 3 0.445 0.861 0 0.192 0.808
#> GSM247829 3 0.000 0.898 0 0.000 1.000
#> GSM247842 1 0.000 1.000 1 0.000 0.000
#> GSM247805 2 0.000 1.000 0 1.000 0.000
#> GSM247786 2 0.000 1.000 0 1.000 0.000
#> GSM247812 3 0.000 0.898 0 0.000 1.000
#> GSM247776 1 0.000 1.000 1 0.000 0.000
#> GSM247850 1 0.000 1.000 1 0.000 0.000
#> GSM247717 2 0.000 1.000 0 1.000 0.000
#> GSM247784 2 0.000 1.000 0 1.000 0.000
#> GSM247834 3 0.445 0.861 0 0.192 0.808
#> GSM247783 3 0.000 0.898 0 0.000 1.000
#> GSM247846 1 0.000 1.000 1 0.000 0.000
#> GSM247822 2 0.000 1.000 0 1.000 0.000
#> GSM247710 2 0.000 1.000 0 1.000 0.000
#> GSM247713 3 0.445 0.861 0 0.192 0.808
#> GSM247840 3 0.000 0.898 0 0.000 1.000
#> GSM247733 1 0.000 1.000 1 0.000 0.000
#> GSM247852 1 0.000 1.000 1 0.000 0.000
#> GSM247790 2 0.000 1.000 0 1.000 0.000
#> GSM247730 2 0.000 1.000 0 1.000 0.000
#> GSM247824 3 0.000 0.898 0 0.000 1.000
#> GSM247770 1 0.000 1.000 1 0.000 0.000
#> GSM247711 2 0.000 1.000 0 1.000 0.000
#> GSM247782 2 0.000 1.000 0 1.000 0.000
#> GSM247836 3 0.445 0.861 0 0.192 0.808
#> GSM247785 3 0.000 0.898 0 0.000 1.000
#> GSM247847 1 0.000 1.000 1 0.000 0.000
#> GSM247750 2 0.000 1.000 0 1.000 0.000
#> GSM247788 2 0.000 1.000 0 1.000 0.000
#> GSM247849 3 0.445 0.861 0 0.192 0.808
#> GSM247772 3 0.000 0.898 0 0.000 1.000
#> GSM247760 1 0.000 1.000 1 0.000 0.000
#> GSM247764 2 0.000 1.000 0 1.000 0.000
#> GSM247851 2 0.000 1.000 0 1.000 0.000
#> GSM247714 2 0.000 1.000 0 1.000 0.000
#> GSM247828 3 0.445 0.861 0 0.192 0.808
#> GSM247704 3 0.000 0.898 0 0.000 1.000
#> GSM247818 1 0.000 1.000 1 0.000 0.000
#> GSM247823 2 0.000 1.000 0 1.000 0.000
#> GSM247706 2 0.000 1.000 0 1.000 0.000
#> GSM247835 3 0.000 0.898 0 0.000 1.000
#> GSM247734 1 0.000 1.000 1 0.000 0.000
#> GSM247819 2 0.000 1.000 0 1.000 0.000
#> GSM247809 2 0.000 1.000 0 1.000 0.000
#> GSM247830 3 0.000 0.898 0 0.000 1.000
#> GSM247833 1 0.000 1.000 1 0.000 0.000
#> GSM247738 2 0.000 1.000 0 1.000 0.000
#> GSM247716 2 0.000 1.000 0 1.000 0.000
#> GSM247747 3 0.000 0.898 0 0.000 1.000
#> GSM247722 1 0.000 1.000 1 0.000 0.000
#> GSM247816 2 0.000 1.000 0 1.000 0.000
#> GSM247839 2 0.000 1.000 0 1.000 0.000
#> GSM247821 3 0.445 0.861 0 0.192 0.808
#> GSM247798 3 0.000 0.898 0 0.000 1.000
#> GSM247838 1 0.000 1.000 1 0.000 0.000
#> GSM247721 2 0.000 1.000 0 1.000 0.000
#> GSM247781 2 0.000 1.000 0 1.000 0.000
#> GSM247762 3 0.445 0.861 0 0.192 0.808
#> GSM247825 3 0.000 0.898 0 0.000 1.000
#> GSM247777 1 0.000 1.000 1 0.000 0.000
#> GSM247761 2 0.000 1.000 0 1.000 0.000
#> GSM247720 2 0.000 1.000 0 1.000 0.000
#> GSM247814 3 0.000 0.898 0 0.000 1.000
#> GSM247732 1 0.000 1.000 1 0.000 0.000
#> GSM247708 2 0.000 1.000 0 1.000 0.000
#> GSM247740 2 0.000 1.000 0 1.000 0.000
#> GSM247749 3 0.445 0.861 0 0.192 0.808
#> GSM247767 3 0.000 0.898 0 0.000 1.000
#> GSM247748 1 0.000 1.000 1 0.000 0.000
#> GSM247705 2 0.000 1.000 0 1.000 0.000
#> GSM247746 2 0.000 1.000 0 1.000 0.000
#> GSM247752 3 0.445 0.861 0 0.192 0.808
#> GSM247769 3 0.000 0.898 0 0.000 1.000
#> GSM247753 1 0.000 1.000 1 0.000 0.000
#> GSM247723 2 0.000 1.000 0 1.000 0.000
#> GSM247779 2 0.000 1.000 0 1.000 0.000
#> GSM247756 3 0.445 0.861 0 0.192 0.808
#> GSM247826 3 0.000 0.898 0 0.000 1.000
#> GSM247775 1 0.000 1.000 1 0.000 0.000
#> GSM247741 2 0.000 1.000 0 1.000 0.000
#> GSM247799 2 0.000 1.000 0 1.000 0.000
#> GSM247778 3 0.445 0.861 0 0.192 0.808
#> GSM247806 3 0.000 0.898 0 0.000 1.000
#> GSM247815 1 0.000 1.000 1 0.000 0.000
#> GSM247735 2 0.000 1.000 0 1.000 0.000
#> GSM247831 2 0.000 1.000 0 1.000 0.000
#> GSM247845 3 0.445 0.861 0 0.192 0.808
#> GSM247791 3 0.000 0.898 0 0.000 1.000
#> GSM247780 1 0.000 1.000 1 0.000 0.000
#> GSM247853 1 0.000 1.000 1 0.000 0.000
#> GSM247800 2 0.000 1.000 0 1.000 0.000
#> GSM247729 2 0.000 1.000 0 1.000 0.000
#> GSM247810 3 0.445 0.861 0 0.192 0.808
#> GSM247844 3 0.000 0.898 0 0.000 1.000
#> GSM247793 1 0.000 1.000 1 0.000 0.000
#> GSM247759 2 0.000 1.000 0 1.000 0.000
#> GSM247724 2 0.000 1.000 0 1.000 0.000
#> GSM247817 3 0.000 0.898 0 0.000 1.000
#> GSM247727 1 0.000 1.000 1 0.000 0.000
#> GSM247796 2 0.000 1.000 0 1.000 0.000
#> GSM247725 2 0.000 1.000 0 1.000 0.000
#> GSM247801 3 0.445 0.861 0 0.192 0.808
#> GSM247731 3 0.000 0.898 0 0.000 1.000
#> GSM247765 1 0.000 1.000 1 0.000 0.000
#> GSM247792 2 0.000 1.000 0 1.000 0.000
#> GSM247726 2 0.000 1.000 0 1.000 0.000
#> GSM247803 3 0.445 0.861 0 0.192 0.808
#> GSM247728 3 0.000 0.898 0 0.000 1.000
#> GSM247768 1 0.000 1.000 1 0.000 0.000
#> GSM247745 2 0.000 1.000 0 1.000 0.000
#> GSM247855 2 0.000 1.000 0 1.000 0.000
#> GSM247804 2 0.000 1.000 0 1.000 0.000
#> GSM247774 3 0.445 0.861 0 0.192 0.808
#> GSM247807 3 0.000 0.898 0 0.000 1.000
#> GSM247813 1 0.000 1.000 1 0.000 0.000
#> GSM247736 2 0.000 1.000 0 1.000 0.000
#> GSM247712 2 0.000 1.000 0 1.000 0.000
#> GSM247797 3 0.445 0.861 0 0.192 0.808
#> GSM247743 3 0.000 0.898 0 0.000 1.000
#> GSM247719 1 0.000 1.000 1 0.000 0.000
#> GSM247707 2 0.000 1.000 0 1.000 0.000
#> GSM247737 2 0.000 1.000 0 1.000 0.000
#> GSM247827 3 0.000 0.898 0 0.000 1.000
#> GSM247848 1 0.000 1.000 1 0.000 0.000
#> GSM247794 2 0.000 1.000 0 1.000 0.000
#> GSM247757 2 0.000 1.000 0 1.000 0.000
#> GSM247744 3 0.445 0.861 0 0.192 0.808
#> GSM247751 3 0.000 0.898 0 0.000 1.000
#> GSM247837 1 0.000 1.000 1 0.000 0.000
#> GSM247754 2 0.000 1.000 0 1.000 0.000
#> GSM247789 2 0.000 1.000 0 1.000 0.000
#> GSM247802 3 0.445 0.861 0 0.192 0.808
#> GSM247771 3 0.000 0.898 0 0.000 1.000
#> GSM247763 1 0.000 1.000 1 0.000 0.000
#> GSM247808 2 0.000 1.000 0 1.000 0.000
#> GSM247787 2 0.000 1.000 0 1.000 0.000
#> GSM247843 3 0.445 0.861 0 0.192 0.808
#> GSM247811 3 0.000 0.898 0 0.000 1.000
#> GSM247773 1 0.000 1.000 1 0.000 0.000
#> GSM247766 2 0.000 1.000 0 1.000 0.000
#> GSM247718 2 0.000 1.000 0 1.000 0.000
#> GSM247832 3 0.445 0.861 0 0.192 0.808
#> GSM247709 3 0.000 0.898 0 0.000 1.000
#> GSM247820 1 0.000 1.000 1 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0 1 0 1 0 0
#> GSM247854 2 0 1 0 1 0 0
#> GSM247758 2 0 1 0 1 0 0
#> GSM247742 4 0 1 0 0 0 1
#> GSM247755 3 0 1 0 0 1 0
#> GSM247841 1 0 1 1 0 0 0
#> GSM247703 2 0 1 0 1 0 0
#> GSM247739 2 0 1 0 1 0 0
#> GSM247715 4 0 1 0 0 0 1
#> GSM247829 3 0 1 0 0 1 0
#> GSM247842 1 0 1 1 0 0 0
#> GSM247805 2 0 1 0 1 0 0
#> GSM247786 2 0 1 0 1 0 0
#> GSM247812 3 0 1 0 0 1 0
#> GSM247776 1 0 1 1 0 0 0
#> GSM247850 1 0 1 1 0 0 0
#> GSM247717 2 0 1 0 1 0 0
#> GSM247784 2 0 1 0 1 0 0
#> GSM247834 4 0 1 0 0 0 1
#> GSM247783 3 0 1 0 0 1 0
#> GSM247846 1 0 1 1 0 0 0
#> GSM247822 2 0 1 0 1 0 0
#> GSM247710 2 0 1 0 1 0 0
#> GSM247713 4 0 1 0 0 0 1
#> GSM247840 3 0 1 0 0 1 0
#> GSM247733 1 0 1 1 0 0 0
#> GSM247852 1 0 1 1 0 0 0
#> GSM247790 2 0 1 0 1 0 0
#> GSM247730 2 0 1 0 1 0 0
#> GSM247824 3 0 1 0 0 1 0
#> GSM247770 1 0 1 1 0 0 0
#> GSM247711 2 0 1 0 1 0 0
#> GSM247782 2 0 1 0 1 0 0
#> GSM247836 4 0 1 0 0 0 1
#> GSM247785 3 0 1 0 0 1 0
#> GSM247847 1 0 1 1 0 0 0
#> GSM247750 2 0 1 0 1 0 0
#> GSM247788 2 0 1 0 1 0 0
#> GSM247849 4 0 1 0 0 0 1
#> GSM247772 3 0 1 0 0 1 0
#> GSM247760 1 0 1 1 0 0 0
#> GSM247764 2 0 1 0 1 0 0
#> GSM247851 2 0 1 0 1 0 0
#> GSM247714 2 0 1 0 1 0 0
#> GSM247828 4 0 1 0 0 0 1
#> GSM247704 3 0 1 0 0 1 0
#> GSM247818 1 0 1 1 0 0 0
#> GSM247823 2 0 1 0 1 0 0
#> GSM247706 2 0 1 0 1 0 0
#> GSM247835 3 0 1 0 0 1 0
#> GSM247734 1 0 1 1 0 0 0
#> GSM247819 2 0 1 0 1 0 0
#> GSM247809 2 0 1 0 1 0 0
#> GSM247830 3 0 1 0 0 1 0
#> GSM247833 1 0 1 1 0 0 0
#> GSM247738 2 0 1 0 1 0 0
#> GSM247716 2 0 1 0 1 0 0
#> GSM247747 3 0 1 0 0 1 0
#> GSM247722 1 0 1 1 0 0 0
#> GSM247816 2 0 1 0 1 0 0
#> GSM247839 2 0 1 0 1 0 0
#> GSM247821 4 0 1 0 0 0 1
#> GSM247798 3 0 1 0 0 1 0
#> GSM247838 1 0 1 1 0 0 0
#> GSM247721 2 0 1 0 1 0 0
#> GSM247781 2 0 1 0 1 0 0
#> GSM247762 4 0 1 0 0 0 1
#> GSM247825 3 0 1 0 0 1 0
#> GSM247777 1 0 1 1 0 0 0
#> GSM247761 2 0 1 0 1 0 0
#> GSM247720 2 0 1 0 1 0 0
#> GSM247814 3 0 1 0 0 1 0
#> GSM247732 1 0 1 1 0 0 0
#> GSM247708 2 0 1 0 1 0 0
#> GSM247740 2 0 1 0 1 0 0
#> GSM247749 4 0 1 0 0 0 1
#> GSM247767 3 0 1 0 0 1 0
#> GSM247748 1 0 1 1 0 0 0
#> GSM247705 2 0 1 0 1 0 0
#> GSM247746 2 0 1 0 1 0 0
#> GSM247752 4 0 1 0 0 0 1
#> GSM247769 3 0 1 0 0 1 0
#> GSM247753 1 0 1 1 0 0 0
#> GSM247723 2 0 1 0 1 0 0
#> GSM247779 2 0 1 0 1 0 0
#> GSM247756 4 0 1 0 0 0 1
#> GSM247826 3 0 1 0 0 1 0
#> GSM247775 1 0 1 1 0 0 0
#> GSM247741 2 0 1 0 1 0 0
#> GSM247799 2 0 1 0 1 0 0
#> GSM247778 4 0 1 0 0 0 1
#> GSM247806 3 0 1 0 0 1 0
#> GSM247815 1 0 1 1 0 0 0
#> GSM247735 2 0 1 0 1 0 0
#> GSM247831 2 0 1 0 1 0 0
#> GSM247845 4 0 1 0 0 0 1
#> GSM247791 3 0 1 0 0 1 0
#> GSM247780 1 0 1 1 0 0 0
#> GSM247853 1 0 1 1 0 0 0
#> GSM247800 2 0 1 0 1 0 0
#> GSM247729 2 0 1 0 1 0 0
#> GSM247810 4 0 1 0 0 0 1
#> GSM247844 3 0 1 0 0 1 0
#> GSM247793 1 0 1 1 0 0 0
#> GSM247759 2 0 1 0 1 0 0
#> GSM247724 2 0 1 0 1 0 0
#> GSM247817 3 0 1 0 0 1 0
#> GSM247727 1 0 1 1 0 0 0
#> GSM247796 2 0 1 0 1 0 0
#> GSM247725 2 0 1 0 1 0 0
#> GSM247801 4 0 1 0 0 0 1
#> GSM247731 3 0 1 0 0 1 0
#> GSM247765 1 0 1 1 0 0 0
#> GSM247792 2 0 1 0 1 0 0
#> GSM247726 2 0 1 0 1 0 0
#> GSM247803 4 0 1 0 0 0 1
#> GSM247728 3 0 1 0 0 1 0
#> GSM247768 1 0 1 1 0 0 0
#> GSM247745 2 0 1 0 1 0 0
#> GSM247855 2 0 1 0 1 0 0
#> GSM247804 2 0 1 0 1 0 0
#> GSM247774 4 0 1 0 0 0 1
#> GSM247807 3 0 1 0 0 1 0
#> GSM247813 1 0 1 1 0 0 0
#> GSM247736 2 0 1 0 1 0 0
#> GSM247712 2 0 1 0 1 0 0
#> GSM247797 4 0 1 0 0 0 1
#> GSM247743 3 0 1 0 0 1 0
#> GSM247719 1 0 1 1 0 0 0
#> GSM247707 2 0 1 0 1 0 0
#> GSM247737 2 0 1 0 1 0 0
#> GSM247827 3 0 1 0 0 1 0
#> GSM247848 1 0 1 1 0 0 0
#> GSM247794 2 0 1 0 1 0 0
#> GSM247757 2 0 1 0 1 0 0
#> GSM247744 4 0 1 0 0 0 1
#> GSM247751 3 0 1 0 0 1 0
#> GSM247837 1 0 1 1 0 0 0
#> GSM247754 2 0 1 0 1 0 0
#> GSM247789 2 0 1 0 1 0 0
#> GSM247802 4 0 1 0 0 0 1
#> GSM247771 3 0 1 0 0 1 0
#> GSM247763 1 0 1 1 0 0 0
#> GSM247808 2 0 1 0 1 0 0
#> GSM247787 2 0 1 0 1 0 0
#> GSM247843 4 0 1 0 0 0 1
#> GSM247811 3 0 1 0 0 1 0
#> GSM247773 1 0 1 1 0 0 0
#> GSM247766 2 0 1 0 1 0 0
#> GSM247718 2 0 1 0 1 0 0
#> GSM247832 4 0 1 0 0 0 1
#> GSM247709 3 0 1 0 0 1 0
#> GSM247820 1 0 1 1 0 0 0
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247854 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247758 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247742 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247755 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247841 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247703 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247739 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247715 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247829 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247842 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247805 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247786 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247812 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247776 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247717 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247784 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247834 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247783 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247846 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247822 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247710 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247713 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247840 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247733 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247790 2 0.3003 0.768 0 0.812 0 0 0.188
#> GSM247730 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247824 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247770 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247711 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247782 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247836 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247785 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247847 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247750 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247788 5 0.0404 0.987 0 0.012 0 0 0.988
#> GSM247849 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247772 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247760 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247764 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247851 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247714 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247828 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247704 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247818 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247823 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247706 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247835 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247734 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247819 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247809 5 0.0404 0.987 0 0.012 0 0 0.988
#> GSM247830 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247833 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247738 2 0.0162 0.990 0 0.996 0 0 0.004
#> GSM247716 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247747 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247722 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247816 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247839 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247821 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247798 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247838 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247721 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247781 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247762 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247825 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247777 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247761 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247720 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247814 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247732 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247708 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247740 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247749 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247767 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247748 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247705 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247746 2 0.0404 0.983 0 0.988 0 0 0.012
#> GSM247752 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247769 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247753 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247723 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247779 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247756 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247826 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247775 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247741 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247799 5 0.0510 0.983 0 0.016 0 0 0.984
#> GSM247778 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247806 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247815 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247735 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247831 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247845 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247791 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247780 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247800 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247729 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247810 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247844 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247793 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247759 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247724 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247817 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247727 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247796 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247725 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247801 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247731 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247765 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247792 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247726 2 0.0404 0.983 0 0.988 0 0 0.012
#> GSM247803 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247728 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247768 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247745 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247855 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247804 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247774 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247807 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247813 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247736 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247712 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247797 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247743 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247719 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247707 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247737 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247827 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247848 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247794 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247757 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247744 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247751 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247837 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247754 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247789 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247802 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247771 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247763 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247808 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247787 5 0.0000 0.997 0 0.000 0 0 1.000
#> GSM247843 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247811 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247773 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247766 2 0.0000 0.994 0 1.000 0 0 0.000
#> GSM247718 5 0.0880 0.966 0 0.032 0 0 0.968
#> GSM247832 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247709 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247820 1 0.0000 1.000 1 0.000 0 0 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 5 0.5887 0.379 0.000 0.392 0 0 0.408 0.200
#> GSM247854 5 0.5887 0.379 0.000 0.392 0 0 0.408 0.200
#> GSM247758 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247742 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247755 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247841 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247703 5 0.5870 0.380 0.000 0.392 0 0 0.412 0.196
#> GSM247739 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247715 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247829 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247842 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247805 5 0.5871 0.376 0.000 0.396 0 0 0.408 0.196
#> GSM247786 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247812 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247776 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247850 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247717 5 0.5887 0.379 0.000 0.392 0 0 0.408 0.200
#> GSM247784 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247834 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247783 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247846 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247822 2 0.0146 0.955 0.000 0.996 0 0 0.000 0.004
#> GSM247710 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247713 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247840 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247733 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247852 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247790 5 0.5771 0.388 0.000 0.380 0 0 0.444 0.176
#> GSM247730 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247824 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247770 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247711 5 0.5887 0.379 0.000 0.392 0 0 0.408 0.200
#> GSM247782 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247836 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247785 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247847 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247750 6 0.2462 0.779 0.000 0.028 0 0 0.096 0.876
#> GSM247788 5 0.0146 0.647 0.000 0.004 0 0 0.996 0.000
#> GSM247849 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247772 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247760 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247764 2 0.0458 0.964 0.000 0.984 0 0 0.000 0.016
#> GSM247851 2 0.0458 0.964 0.000 0.984 0 0 0.000 0.016
#> GSM247714 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247828 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247704 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247818 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247823 5 0.5871 0.375 0.000 0.396 0 0 0.408 0.196
#> GSM247706 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247835 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247734 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247819 2 0.0458 0.964 0.000 0.984 0 0 0.000 0.016
#> GSM247809 5 0.0363 0.644 0.000 0.000 0 0 0.988 0.012
#> GSM247830 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247833 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247738 5 0.5887 0.379 0.000 0.392 0 0 0.408 0.200
#> GSM247716 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247747 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247722 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247816 5 0.5901 0.369 0.000 0.388 0 0 0.408 0.204
#> GSM247839 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247821 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247798 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247838 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247721 5 0.5855 0.376 0.000 0.400 0 0 0.408 0.192
#> GSM247781 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247762 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247825 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247777 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247761 5 0.5871 0.377 0.000 0.396 0 0 0.408 0.196
#> GSM247720 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247814 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247732 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247708 5 0.5887 0.377 0.000 0.392 0 0 0.408 0.200
#> GSM247740 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247749 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247767 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247748 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247705 6 0.0865 0.912 0.000 0.036 0 0 0.000 0.964
#> GSM247746 6 0.0547 0.918 0.000 0.020 0 0 0.000 0.980
#> GSM247752 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247769 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247753 1 0.0632 0.978 0.976 0.000 0 0 0.000 0.024
#> GSM247723 5 0.5929 0.373 0.000 0.380 0 0 0.408 0.212
#> GSM247779 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247756 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247826 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247775 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247741 5 0.5941 0.370 0.000 0.376 0 0 0.408 0.216
#> GSM247799 5 0.0458 0.640 0.000 0.000 0 0 0.984 0.016
#> GSM247778 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247806 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247815 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247735 2 0.1663 0.877 0.000 0.912 0 0 0.000 0.088
#> GSM247831 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247845 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247791 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247780 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247853 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247800 2 0.1141 0.941 0.000 0.948 0 0 0.000 0.052
#> GSM247729 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247810 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247844 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247793 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247759 5 0.5887 0.379 0.000 0.392 0 0 0.408 0.200
#> GSM247724 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247817 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247727 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247796 2 0.0458 0.964 0.000 0.984 0 0 0.000 0.016
#> GSM247725 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247801 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247731 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247765 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247792 2 0.0790 0.952 0.000 0.968 0 0 0.000 0.032
#> GSM247726 6 0.0547 0.918 0.000 0.020 0 0 0.000 0.980
#> GSM247803 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247728 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247768 1 0.0632 0.978 0.976 0.000 0 0 0.000 0.024
#> GSM247745 5 0.5887 0.379 0.000 0.392 0 0 0.408 0.200
#> GSM247855 5 0.5887 0.379 0.000 0.392 0 0 0.408 0.200
#> GSM247804 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247774 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247807 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247813 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247736 5 0.5887 0.379 0.000 0.392 0 0 0.408 0.200
#> GSM247712 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247797 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247743 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247719 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247707 5 0.5855 0.376 0.000 0.400 0 0 0.408 0.192
#> GSM247737 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247827 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247848 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247794 5 0.5901 0.374 0.000 0.388 0 0 0.408 0.204
#> GSM247757 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247744 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247751 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247837 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247754 5 0.5941 0.365 0.000 0.376 0 0 0.408 0.216
#> GSM247789 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247802 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247771 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247763 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247808 5 0.5887 0.379 0.000 0.392 0 0 0.408 0.200
#> GSM247787 5 0.0000 0.648 0.000 0.000 0 0 1.000 0.000
#> GSM247843 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247811 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247773 1 0.0000 0.999 1.000 0.000 0 0 0.000 0.000
#> GSM247766 2 0.0937 0.942 0.000 0.960 0 0 0.000 0.040
#> GSM247718 5 0.0458 0.642 0.000 0.000 0 0 0.984 0.016
#> GSM247832 4 0.0000 1.000 0.000 0.000 0 1 0.000 0.000
#> GSM247709 3 0.0000 1.000 0.000 0.000 1 0 0.000 0.000
#> GSM247820 1 0.0000 0.999 1.000 0.000 0 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> SD:mclust 130 1 1.000 5.41e-28 2
#> SD:mclust 153 1 0.956 2.17e-61 3
#> SD:mclust 153 1 0.964 1.16e-90 4
#> SD:mclust 153 1 0.933 3.93e-116 5
#> SD:mclust 130 1 0.285 4.25e-94 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.47112 0.529 0.529
#> 3 3 0.963 0.962 0.975 0.37167 0.827 0.673
#> 4 4 1.000 0.978 0.987 0.10658 0.933 0.811
#> 5 5 1.000 1.000 1.000 0.12149 0.909 0.686
#> 6 6 1.000 0.987 0.991 0.00352 1.000 1.000
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 3 4
There is also optional best \(k\) = 2 3 4 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0 1 0 1
#> GSM247854 2 0 1 0 1
#> GSM247758 2 0 1 0 1
#> GSM247742 1 0 1 1 0
#> GSM247755 2 0 1 0 1
#> GSM247841 1 0 1 1 0
#> GSM247703 2 0 1 0 1
#> GSM247739 2 0 1 0 1
#> GSM247715 1 0 1 1 0
#> GSM247829 2 0 1 0 1
#> GSM247842 1 0 1 1 0
#> GSM247805 2 0 1 0 1
#> GSM247786 2 0 1 0 1
#> GSM247812 2 0 1 0 1
#> GSM247776 1 0 1 1 0
#> GSM247850 1 0 1 1 0
#> GSM247717 2 0 1 0 1
#> GSM247784 2 0 1 0 1
#> GSM247834 1 0 1 1 0
#> GSM247783 2 0 1 0 1
#> GSM247846 1 0 1 1 0
#> GSM247822 2 0 1 0 1
#> GSM247710 2 0 1 0 1
#> GSM247713 1 0 1 1 0
#> GSM247840 2 0 1 0 1
#> GSM247733 1 0 1 1 0
#> GSM247852 1 0 1 1 0
#> GSM247790 2 0 1 0 1
#> GSM247730 2 0 1 0 1
#> GSM247824 2 0 1 0 1
#> GSM247770 1 0 1 1 0
#> GSM247711 2 0 1 0 1
#> GSM247782 2 0 1 0 1
#> GSM247836 1 0 1 1 0
#> GSM247785 2 0 1 0 1
#> GSM247847 1 0 1 1 0
#> GSM247750 2 0 1 0 1
#> GSM247788 2 0 1 0 1
#> GSM247849 1 0 1 1 0
#> GSM247772 2 0 1 0 1
#> GSM247760 1 0 1 1 0
#> GSM247764 2 0 1 0 1
#> GSM247851 2 0 1 0 1
#> GSM247714 2 0 1 0 1
#> GSM247828 1 0 1 1 0
#> GSM247704 2 0 1 0 1
#> GSM247818 1 0 1 1 0
#> GSM247823 2 0 1 0 1
#> GSM247706 2 0 1 0 1
#> GSM247835 2 0 1 0 1
#> GSM247734 1 0 1 1 0
#> GSM247819 2 0 1 0 1
#> GSM247809 2 0 1 0 1
#> GSM247830 2 0 1 0 1
#> GSM247833 1 0 1 1 0
#> GSM247738 2 0 1 0 1
#> GSM247716 2 0 1 0 1
#> GSM247747 2 0 1 0 1
#> GSM247722 1 0 1 1 0
#> GSM247816 2 0 1 0 1
#> GSM247839 2 0 1 0 1
#> GSM247821 1 0 1 1 0
#> GSM247798 2 0 1 0 1
#> GSM247838 1 0 1 1 0
#> GSM247721 2 0 1 0 1
#> GSM247781 2 0 1 0 1
#> GSM247762 1 0 1 1 0
#> GSM247825 2 0 1 0 1
#> GSM247777 1 0 1 1 0
#> GSM247761 2 0 1 0 1
#> GSM247720 2 0 1 0 1
#> GSM247814 2 0 1 0 1
#> GSM247732 1 0 1 1 0
#> GSM247708 2 0 1 0 1
#> GSM247740 2 0 1 0 1
#> GSM247749 1 0 1 1 0
#> GSM247767 2 0 1 0 1
#> GSM247748 1 0 1 1 0
#> GSM247705 2 0 1 0 1
#> GSM247746 2 0 1 0 1
#> GSM247752 1 0 1 1 0
#> GSM247769 2 0 1 0 1
#> GSM247753 1 0 1 1 0
#> GSM247723 2 0 1 0 1
#> GSM247779 2 0 1 0 1
#> GSM247756 1 0 1 1 0
#> GSM247826 2 0 1 0 1
#> GSM247775 1 0 1 1 0
#> GSM247741 2 0 1 0 1
#> GSM247799 2 0 1 0 1
#> GSM247778 1 0 1 1 0
#> GSM247806 2 0 1 0 1
#> GSM247815 1 0 1 1 0
#> GSM247735 2 0 1 0 1
#> GSM247831 2 0 1 0 1
#> GSM247845 1 0 1 1 0
#> GSM247791 2 0 1 0 1
#> GSM247780 1 0 1 1 0
#> GSM247853 1 0 1 1 0
#> GSM247800 2 0 1 0 1
#> GSM247729 2 0 1 0 1
#> GSM247810 1 0 1 1 0
#> GSM247844 2 0 1 0 1
#> GSM247793 1 0 1 1 0
#> GSM247759 2 0 1 0 1
#> GSM247724 2 0 1 0 1
#> GSM247817 2 0 1 0 1
#> GSM247727 1 0 1 1 0
#> GSM247796 2 0 1 0 1
#> GSM247725 2 0 1 0 1
#> GSM247801 1 0 1 1 0
#> GSM247731 2 0 1 0 1
#> GSM247765 1 0 1 1 0
#> GSM247792 2 0 1 0 1
#> GSM247726 2 0 1 0 1
#> GSM247803 1 0 1 1 0
#> GSM247728 2 0 1 0 1
#> GSM247768 1 0 1 1 0
#> GSM247745 2 0 1 0 1
#> GSM247855 2 0 1 0 1
#> GSM247804 2 0 1 0 1
#> GSM247774 1 0 1 1 0
#> GSM247807 2 0 1 0 1
#> GSM247813 1 0 1 1 0
#> GSM247736 2 0 1 0 1
#> GSM247712 2 0 1 0 1
#> GSM247797 1 0 1 1 0
#> GSM247743 2 0 1 0 1
#> GSM247719 1 0 1 1 0
#> GSM247707 2 0 1 0 1
#> GSM247737 2 0 1 0 1
#> GSM247827 2 0 1 0 1
#> GSM247848 1 0 1 1 0
#> GSM247794 2 0 1 0 1
#> GSM247757 2 0 1 0 1
#> GSM247744 1 0 1 1 0
#> GSM247751 2 0 1 0 1
#> GSM247837 1 0 1 1 0
#> GSM247754 2 0 1 0 1
#> GSM247789 2 0 1 0 1
#> GSM247802 1 0 1 1 0
#> GSM247771 2 0 1 0 1
#> GSM247763 1 0 1 1 0
#> GSM247808 2 0 1 0 1
#> GSM247787 2 0 1 0 1
#> GSM247843 1 0 1 1 0
#> GSM247811 2 0 1 0 1
#> GSM247773 1 0 1 1 0
#> GSM247766 2 0 1 0 1
#> GSM247718 2 0 1 0 1
#> GSM247832 1 0 1 1 0
#> GSM247709 2 0 1 0 1
#> GSM247820 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247854 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247758 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247742 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247755 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247841 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247703 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247739 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247715 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247829 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247842 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247805 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247786 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247812 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247776 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247850 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247717 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247784 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247834 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247783 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247846 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247822 2 0.3412 0.862 0.000 0.876 0.124
#> GSM247710 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247713 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247840 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247733 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247852 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247790 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247730 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247824 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247770 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247711 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247782 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247836 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247785 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247847 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247750 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247788 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247849 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247772 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247760 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247764 2 0.5327 0.665 0.000 0.728 0.272
#> GSM247851 2 0.5431 0.644 0.000 0.716 0.284
#> GSM247714 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247828 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247704 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247818 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247823 2 0.1964 0.926 0.000 0.944 0.056
#> GSM247706 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247835 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247734 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247819 2 0.5178 0.692 0.000 0.744 0.256
#> GSM247809 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247830 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247833 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247738 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247716 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247747 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247722 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247816 2 0.1031 0.951 0.000 0.976 0.024
#> GSM247839 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247821 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247798 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247838 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247721 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247781 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247762 1 0.5167 0.788 0.804 0.172 0.024
#> GSM247825 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247777 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247761 2 0.0237 0.964 0.000 0.996 0.004
#> GSM247720 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247814 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247732 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247708 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247740 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247749 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247767 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247748 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247705 2 0.4235 0.804 0.000 0.824 0.176
#> GSM247746 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247752 1 0.4994 0.804 0.816 0.160 0.024
#> GSM247769 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247753 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247723 2 0.0424 0.961 0.000 0.992 0.008
#> GSM247779 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247756 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247826 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247775 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247741 2 0.1529 0.939 0.000 0.960 0.040
#> GSM247799 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247778 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247806 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247815 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247735 2 0.0592 0.959 0.000 0.988 0.012
#> GSM247831 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247845 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247791 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247780 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247853 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247800 2 0.4062 0.818 0.000 0.836 0.164
#> GSM247729 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247810 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247844 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247793 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247759 2 0.0747 0.956 0.000 0.984 0.016
#> GSM247724 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247817 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247727 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247796 2 0.4399 0.789 0.000 0.812 0.188
#> GSM247725 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247801 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247731 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247765 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247792 2 0.4452 0.784 0.000 0.808 0.192
#> GSM247726 2 0.0892 0.948 0.000 0.980 0.020
#> GSM247803 1 0.4342 0.853 0.856 0.120 0.024
#> GSM247728 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247768 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247745 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247855 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247804 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247774 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247807 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247813 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247736 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247712 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247797 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247743 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247719 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247707 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247737 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247827 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247848 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247794 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247757 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247744 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247751 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247837 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247754 2 0.1163 0.948 0.000 0.972 0.028
#> GSM247789 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247802 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247771 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247763 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247808 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247787 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247843 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247811 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247773 1 0.0000 0.984 1.000 0.000 0.000
#> GSM247766 2 0.4931 0.729 0.000 0.768 0.232
#> GSM247718 2 0.0000 0.966 0.000 1.000 0.000
#> GSM247832 1 0.1031 0.979 0.976 0.000 0.024
#> GSM247709 3 0.1031 1.000 0.000 0.024 0.976
#> GSM247820 1 0.0000 0.984 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247854 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247758 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247742 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247755 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247841 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247703 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247739 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247715 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247829 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247842 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247805 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247786 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247812 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247776 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247850 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247717 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247784 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247834 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247783 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247846 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247822 2 0.1637 0.926 0.000 0.940 0.060 0.000
#> GSM247710 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247713 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247840 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247733 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247852 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247790 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247730 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247824 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247770 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247711 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247782 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247836 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247785 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247847 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247750 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247788 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247849 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247772 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247760 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247764 2 0.3764 0.754 0.000 0.784 0.216 0.000
#> GSM247851 2 0.3873 0.737 0.000 0.772 0.228 0.000
#> GSM247714 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247828 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247704 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247818 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247823 2 0.0592 0.962 0.000 0.984 0.016 0.000
#> GSM247706 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247835 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247734 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247819 2 0.3688 0.765 0.000 0.792 0.208 0.000
#> GSM247809 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247830 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247833 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247738 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247716 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247747 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247722 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247816 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247839 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247821 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247798 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247838 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247721 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247781 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247762 4 0.0000 0.991 0.000 0.000 0.000 1.000
#> GSM247825 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247777 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247761 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247720 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247814 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247732 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247708 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247740 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247749 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247767 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247748 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247705 2 0.3569 0.782 0.000 0.804 0.196 0.000
#> GSM247746 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247752 4 0.0000 0.991 0.000 0.000 0.000 1.000
#> GSM247769 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247753 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247723 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247779 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247756 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247826 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247775 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247741 2 0.0188 0.970 0.000 0.996 0.004 0.000
#> GSM247799 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247778 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247806 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247815 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247735 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247831 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247845 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247791 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247780 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247853 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247800 2 0.1940 0.912 0.000 0.924 0.076 0.000
#> GSM247729 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247810 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247844 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247793 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247759 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247724 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247817 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247727 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247796 2 0.2647 0.869 0.000 0.880 0.120 0.000
#> GSM247725 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247801 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247731 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247765 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247792 2 0.3528 0.787 0.000 0.808 0.192 0.000
#> GSM247726 2 0.0469 0.970 0.000 0.988 0.000 0.012
#> GSM247803 4 0.0000 0.991 0.000 0.000 0.000 1.000
#> GSM247728 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247768 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247745 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247855 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247804 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247774 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247807 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247813 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247736 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247712 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247797 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247743 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247719 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247707 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247737 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247827 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247848 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247794 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247757 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247744 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247751 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247837 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247754 2 0.0336 0.968 0.000 0.992 0.008 0.000
#> GSM247789 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247802 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247771 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247763 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247808 2 0.0000 0.972 0.000 1.000 0.000 0.000
#> GSM247787 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247843 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247811 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247773 1 0.0000 1.000 1.000 0.000 0.000 0.000
#> GSM247766 2 0.3528 0.787 0.000 0.808 0.192 0.000
#> GSM247718 2 0.0336 0.972 0.000 0.992 0.000 0.008
#> GSM247832 4 0.0336 0.999 0.008 0.000 0.000 0.992
#> GSM247709 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247820 1 0.0000 1.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0 1 0 1 0 0 0
#> GSM247854 2 0 1 0 1 0 0 0
#> GSM247758 5 0 1 0 0 0 0 1
#> GSM247742 4 0 1 0 0 0 1 0
#> GSM247755 3 0 1 0 0 1 0 0
#> GSM247841 1 0 1 1 0 0 0 0
#> GSM247703 2 0 1 0 1 0 0 0
#> GSM247739 5 0 1 0 0 0 0 1
#> GSM247715 4 0 1 0 0 0 1 0
#> GSM247829 3 0 1 0 0 1 0 0
#> GSM247842 1 0 1 1 0 0 0 0
#> GSM247805 2 0 1 0 1 0 0 0
#> GSM247786 5 0 1 0 0 0 0 1
#> GSM247812 3 0 1 0 0 1 0 0
#> GSM247776 1 0 1 1 0 0 0 0
#> GSM247850 1 0 1 1 0 0 0 0
#> GSM247717 2 0 1 0 1 0 0 0
#> GSM247784 5 0 1 0 0 0 0 1
#> GSM247834 4 0 1 0 0 0 1 0
#> GSM247783 3 0 1 0 0 1 0 0
#> GSM247846 1 0 1 1 0 0 0 0
#> GSM247822 2 0 1 0 1 0 0 0
#> GSM247710 5 0 1 0 0 0 0 1
#> GSM247713 4 0 1 0 0 0 1 0
#> GSM247840 3 0 1 0 0 1 0 0
#> GSM247733 1 0 1 1 0 0 0 0
#> GSM247852 1 0 1 1 0 0 0 0
#> GSM247790 2 0 1 0 1 0 0 0
#> GSM247730 5 0 1 0 0 0 0 1
#> GSM247824 3 0 1 0 0 1 0 0
#> GSM247770 1 0 1 1 0 0 0 0
#> GSM247711 2 0 1 0 1 0 0 0
#> GSM247782 5 0 1 0 0 0 0 1
#> GSM247836 4 0 1 0 0 0 1 0
#> GSM247785 3 0 1 0 0 1 0 0
#> GSM247847 1 0 1 1 0 0 0 0
#> GSM247750 2 0 1 0 1 0 0 0
#> GSM247788 5 0 1 0 0 0 0 1
#> GSM247849 4 0 1 0 0 0 1 0
#> GSM247772 3 0 1 0 0 1 0 0
#> GSM247760 1 0 1 1 0 0 0 0
#> GSM247764 2 0 1 0 1 0 0 0
#> GSM247851 2 0 1 0 1 0 0 0
#> GSM247714 5 0 1 0 0 0 0 1
#> GSM247828 4 0 1 0 0 0 1 0
#> GSM247704 3 0 1 0 0 1 0 0
#> GSM247818 1 0 1 1 0 0 0 0
#> GSM247823 2 0 1 0 1 0 0 0
#> GSM247706 5 0 1 0 0 0 0 1
#> GSM247835 3 0 1 0 0 1 0 0
#> GSM247734 1 0 1 1 0 0 0 0
#> GSM247819 2 0 1 0 1 0 0 0
#> GSM247809 5 0 1 0 0 0 0 1
#> GSM247830 3 0 1 0 0 1 0 0
#> GSM247833 1 0 1 1 0 0 0 0
#> GSM247738 2 0 1 0 1 0 0 0
#> GSM247716 5 0 1 0 0 0 0 1
#> GSM247747 3 0 1 0 0 1 0 0
#> GSM247722 1 0 1 1 0 0 0 0
#> GSM247816 2 0 1 0 1 0 0 0
#> GSM247839 5 0 1 0 0 0 0 1
#> GSM247821 4 0 1 0 0 0 1 0
#> GSM247798 3 0 1 0 0 1 0 0
#> GSM247838 1 0 1 1 0 0 0 0
#> GSM247721 2 0 1 0 1 0 0 0
#> GSM247781 5 0 1 0 0 0 0 1
#> GSM247762 4 0 1 0 0 0 1 0
#> GSM247825 3 0 1 0 0 1 0 0
#> GSM247777 1 0 1 1 0 0 0 0
#> GSM247761 2 0 1 0 1 0 0 0
#> GSM247720 5 0 1 0 0 0 0 1
#> GSM247814 3 0 1 0 0 1 0 0
#> GSM247732 1 0 1 1 0 0 0 0
#> GSM247708 2 0 1 0 1 0 0 0
#> GSM247740 5 0 1 0 0 0 0 1
#> GSM247749 4 0 1 0 0 0 1 0
#> GSM247767 3 0 1 0 0 1 0 0
#> GSM247748 1 0 1 1 0 0 0 0
#> GSM247705 2 0 1 0 1 0 0 0
#> GSM247746 5 0 1 0 0 0 0 1
#> GSM247752 4 0 1 0 0 0 1 0
#> GSM247769 3 0 1 0 0 1 0 0
#> GSM247753 1 0 1 1 0 0 0 0
#> GSM247723 2 0 1 0 1 0 0 0
#> GSM247779 5 0 1 0 0 0 0 1
#> GSM247756 4 0 1 0 0 0 1 0
#> GSM247826 3 0 1 0 0 1 0 0
#> GSM247775 1 0 1 1 0 0 0 0
#> GSM247741 2 0 1 0 1 0 0 0
#> GSM247799 5 0 1 0 0 0 0 1
#> GSM247778 4 0 1 0 0 0 1 0
#> GSM247806 3 0 1 0 0 1 0 0
#> GSM247815 1 0 1 1 0 0 0 0
#> GSM247735 2 0 1 0 1 0 0 0
#> GSM247831 5 0 1 0 0 0 0 1
#> GSM247845 4 0 1 0 0 0 1 0
#> GSM247791 3 0 1 0 0 1 0 0
#> GSM247780 1 0 1 1 0 0 0 0
#> GSM247853 1 0 1 1 0 0 0 0
#> GSM247800 2 0 1 0 1 0 0 0
#> GSM247729 5 0 1 0 0 0 0 1
#> GSM247810 4 0 1 0 0 0 1 0
#> GSM247844 3 0 1 0 0 1 0 0
#> GSM247793 1 0 1 1 0 0 0 0
#> GSM247759 2 0 1 0 1 0 0 0
#> GSM247724 5 0 1 0 0 0 0 1
#> GSM247817 3 0 1 0 0 1 0 0
#> GSM247727 1 0 1 1 0 0 0 0
#> GSM247796 2 0 1 0 1 0 0 0
#> GSM247725 5 0 1 0 0 0 0 1
#> GSM247801 4 0 1 0 0 0 1 0
#> GSM247731 3 0 1 0 0 1 0 0
#> GSM247765 1 0 1 1 0 0 0 0
#> GSM247792 2 0 1 0 1 0 0 0
#> GSM247726 5 0 1 0 0 0 0 1
#> GSM247803 4 0 1 0 0 0 1 0
#> GSM247728 3 0 1 0 0 1 0 0
#> GSM247768 1 0 1 1 0 0 0 0
#> GSM247745 2 0 1 0 1 0 0 0
#> GSM247855 2 0 1 0 1 0 0 0
#> GSM247804 5 0 1 0 0 0 0 1
#> GSM247774 4 0 1 0 0 0 1 0
#> GSM247807 3 0 1 0 0 1 0 0
#> GSM247813 1 0 1 1 0 0 0 0
#> GSM247736 2 0 1 0 1 0 0 0
#> GSM247712 5 0 1 0 0 0 0 1
#> GSM247797 4 0 1 0 0 0 1 0
#> GSM247743 3 0 1 0 0 1 0 0
#> GSM247719 1 0 1 1 0 0 0 0
#> GSM247707 2 0 1 0 1 0 0 0
#> GSM247737 5 0 1 0 0 0 0 1
#> GSM247827 3 0 1 0 0 1 0 0
#> GSM247848 1 0 1 1 0 0 0 0
#> GSM247794 2 0 1 0 1 0 0 0
#> GSM247757 5 0 1 0 0 0 0 1
#> GSM247744 4 0 1 0 0 0 1 0
#> GSM247751 3 0 1 0 0 1 0 0
#> GSM247837 1 0 1 1 0 0 0 0
#> GSM247754 2 0 1 0 1 0 0 0
#> GSM247789 5 0 1 0 0 0 0 1
#> GSM247802 4 0 1 0 0 0 1 0
#> GSM247771 3 0 1 0 0 1 0 0
#> GSM247763 1 0 1 1 0 0 0 0
#> GSM247808 2 0 1 0 1 0 0 0
#> GSM247787 5 0 1 0 0 0 0 1
#> GSM247843 4 0 1 0 0 0 1 0
#> GSM247811 3 0 1 0 0 1 0 0
#> GSM247773 1 0 1 1 0 0 0 0
#> GSM247766 2 0 1 0 1 0 0 0
#> GSM247718 5 0 1 0 0 0 0 1
#> GSM247832 4 0 1 0 0 0 1 0
#> GSM247709 3 0 1 0 0 1 0 0
#> GSM247820 1 0 1 1 0 0 0 0
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247854 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247758 5 0.0363 0.982 0 0.000 0 0.000 0.988 NA
#> GSM247742 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247755 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247841 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247703 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247739 5 0.0146 0.985 0 0.000 0 0.000 0.996 NA
#> GSM247715 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247829 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247842 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247805 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247786 5 0.0146 0.985 0 0.000 0 0.000 0.996 NA
#> GSM247812 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247776 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247850 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247717 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247784 5 0.0000 0.985 0 0.000 0 0.000 1.000 NA
#> GSM247834 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247783 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247846 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247822 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247710 5 0.0146 0.985 0 0.000 0 0.000 0.996 NA
#> GSM247713 4 0.0363 0.972 0 0.000 0 0.988 0.000 NA
#> GSM247840 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247733 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247852 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247790 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247730 5 0.0000 0.985 0 0.000 0 0.000 1.000 NA
#> GSM247824 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247770 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247711 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247782 5 0.0363 0.983 0 0.000 0 0.000 0.988 NA
#> GSM247836 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247785 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247847 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247750 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247788 5 0.0000 0.985 0 0.000 0 0.000 1.000 NA
#> GSM247849 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247772 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247760 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247764 2 0.0260 0.997 0 0.992 0 0.000 0.000 NA
#> GSM247851 2 0.0260 0.997 0 0.992 0 0.000 0.000 NA
#> GSM247714 5 0.0000 0.985 0 0.000 0 0.000 1.000 NA
#> GSM247828 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247704 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247818 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247823 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247706 5 0.0260 0.984 0 0.000 0 0.000 0.992 NA
#> GSM247835 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247734 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247819 2 0.0260 0.997 0 0.992 0 0.000 0.000 NA
#> GSM247809 5 0.0146 0.984 0 0.000 0 0.000 0.996 NA
#> GSM247830 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247833 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247738 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247716 5 0.0260 0.983 0 0.000 0 0.000 0.992 NA
#> GSM247747 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247722 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247816 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247839 5 0.0146 0.984 0 0.000 0 0.000 0.996 NA
#> GSM247821 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247798 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247838 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247721 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247781 5 0.0000 0.985 0 0.000 0 0.000 1.000 NA
#> GSM247762 4 0.1007 0.955 0 0.000 0 0.956 0.000 NA
#> GSM247825 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247777 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247761 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247720 5 0.0146 0.984 0 0.000 0 0.000 0.996 NA
#> GSM247814 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247732 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247708 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247740 5 0.0000 0.985 0 0.000 0 0.000 1.000 NA
#> GSM247749 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247767 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247748 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247705 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247746 5 0.0363 0.979 0 0.000 0 0.000 0.988 NA
#> GSM247752 4 0.3151 0.818 0 0.000 0 0.748 0.000 NA
#> GSM247769 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247753 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247723 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247779 5 0.0146 0.985 0 0.000 0 0.000 0.996 NA
#> GSM247756 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247826 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247775 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247741 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247799 5 0.0146 0.984 0 0.000 0 0.000 0.996 NA
#> GSM247778 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247806 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247815 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247735 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247831 5 0.0146 0.985 0 0.000 0 0.000 0.996 NA
#> GSM247845 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247791 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247780 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247853 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247800 2 0.0260 0.997 0 0.992 0 0.000 0.000 NA
#> GSM247729 5 0.0000 0.985 0 0.000 0 0.000 1.000 NA
#> GSM247810 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247844 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247793 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247759 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247724 5 0.0260 0.983 0 0.000 0 0.000 0.992 NA
#> GSM247817 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247727 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247796 2 0.0260 0.997 0 0.992 0 0.000 0.000 NA
#> GSM247725 5 0.0260 0.984 0 0.000 0 0.000 0.992 NA
#> GSM247801 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247731 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247765 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247792 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247726 5 0.3838 0.538 0 0.000 0 0.000 0.552 NA
#> GSM247803 4 0.3823 0.673 0 0.000 0 0.564 0.000 NA
#> GSM247728 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247768 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247745 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247855 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247804 5 0.0146 0.984 0 0.000 0 0.000 0.996 NA
#> GSM247774 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247807 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247813 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247736 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247712 5 0.0363 0.983 0 0.000 0 0.000 0.988 NA
#> GSM247797 4 0.0260 0.974 0 0.000 0 0.992 0.000 NA
#> GSM247743 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247719 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247707 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247737 5 0.0000 0.985 0 0.000 0 0.000 1.000 NA
#> GSM247827 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247848 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247794 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247757 5 0.0260 0.984 0 0.000 0 0.000 0.992 NA
#> GSM247744 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247751 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247837 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247754 2 0.0000 0.998 0 1.000 0 0.000 0.000 NA
#> GSM247789 5 0.0146 0.985 0 0.000 0 0.000 0.996 NA
#> GSM247802 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247771 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247763 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247808 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247787 5 0.0260 0.984 0 0.000 0 0.000 0.992 NA
#> GSM247843 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247811 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247773 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
#> GSM247766 2 0.0146 0.997 0 0.996 0 0.000 0.000 NA
#> GSM247718 5 0.0146 0.985 0 0.000 0 0.000 0.996 NA
#> GSM247832 4 0.0000 0.977 0 0.000 0 1.000 0.000 NA
#> GSM247709 3 0.0000 1.000 0 0.000 1 0.000 0.000 NA
#> GSM247820 1 0.0000 1.000 1 0.000 0 0.000 0.000 NA
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> SD:NMF 153 1 1.000 4.63e-32 2
#> SD:NMF 153 1 0.985 2.17e-61 3
#> SD:NMF 153 1 0.964 1.16e-90 4
#> SD:NMF 153 1 0.989 6.51e-120 5
#> SD:NMF 153 1 0.989 6.51e-120 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.471 0.529 0.529
#> 3 3 1.000 1.000 1.000 0.143 0.933 0.873
#> 4 4 1.000 1.000 1.000 0.322 0.827 0.625
#> 5 5 0.903 0.997 0.968 0.110 0.909 0.686
#> 6 6 1.000 0.974 0.991 0.023 0.995 0.974
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 3 4
There is also optional best \(k\) = 2 3 4 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0 1 0 1
#> GSM247854 2 0 1 0 1
#> GSM247758 2 0 1 0 1
#> GSM247742 1 0 1 1 0
#> GSM247755 2 0 1 0 1
#> GSM247841 1 0 1 1 0
#> GSM247703 2 0 1 0 1
#> GSM247739 2 0 1 0 1
#> GSM247715 1 0 1 1 0
#> GSM247829 2 0 1 0 1
#> GSM247842 1 0 1 1 0
#> GSM247805 2 0 1 0 1
#> GSM247786 2 0 1 0 1
#> GSM247812 2 0 1 0 1
#> GSM247776 1 0 1 1 0
#> GSM247850 1 0 1 1 0
#> GSM247717 2 0 1 0 1
#> GSM247784 2 0 1 0 1
#> GSM247834 1 0 1 1 0
#> GSM247783 2 0 1 0 1
#> GSM247846 1 0 1 1 0
#> GSM247822 2 0 1 0 1
#> GSM247710 2 0 1 0 1
#> GSM247713 1 0 1 1 0
#> GSM247840 2 0 1 0 1
#> GSM247733 1 0 1 1 0
#> GSM247852 1 0 1 1 0
#> GSM247790 2 0 1 0 1
#> GSM247730 2 0 1 0 1
#> GSM247824 2 0 1 0 1
#> GSM247770 1 0 1 1 0
#> GSM247711 2 0 1 0 1
#> GSM247782 2 0 1 0 1
#> GSM247836 1 0 1 1 0
#> GSM247785 2 0 1 0 1
#> GSM247847 1 0 1 1 0
#> GSM247750 2 0 1 0 1
#> GSM247788 2 0 1 0 1
#> GSM247849 1 0 1 1 0
#> GSM247772 2 0 1 0 1
#> GSM247760 1 0 1 1 0
#> GSM247764 2 0 1 0 1
#> GSM247851 2 0 1 0 1
#> GSM247714 2 0 1 0 1
#> GSM247828 1 0 1 1 0
#> GSM247704 2 0 1 0 1
#> GSM247818 1 0 1 1 0
#> GSM247823 2 0 1 0 1
#> GSM247706 2 0 1 0 1
#> GSM247835 2 0 1 0 1
#> GSM247734 1 0 1 1 0
#> GSM247819 2 0 1 0 1
#> GSM247809 2 0 1 0 1
#> GSM247830 2 0 1 0 1
#> GSM247833 1 0 1 1 0
#> GSM247738 2 0 1 0 1
#> GSM247716 2 0 1 0 1
#> GSM247747 2 0 1 0 1
#> GSM247722 1 0 1 1 0
#> GSM247816 2 0 1 0 1
#> GSM247839 2 0 1 0 1
#> GSM247821 1 0 1 1 0
#> GSM247798 2 0 1 0 1
#> GSM247838 1 0 1 1 0
#> GSM247721 2 0 1 0 1
#> GSM247781 2 0 1 0 1
#> GSM247762 1 0 1 1 0
#> GSM247825 2 0 1 0 1
#> GSM247777 1 0 1 1 0
#> GSM247761 2 0 1 0 1
#> GSM247720 2 0 1 0 1
#> GSM247814 2 0 1 0 1
#> GSM247732 1 0 1 1 0
#> GSM247708 2 0 1 0 1
#> GSM247740 2 0 1 0 1
#> GSM247749 1 0 1 1 0
#> GSM247767 2 0 1 0 1
#> GSM247748 1 0 1 1 0
#> GSM247705 2 0 1 0 1
#> GSM247746 2 0 1 0 1
#> GSM247752 1 0 1 1 0
#> GSM247769 2 0 1 0 1
#> GSM247753 1 0 1 1 0
#> GSM247723 2 0 1 0 1
#> GSM247779 2 0 1 0 1
#> GSM247756 1 0 1 1 0
#> GSM247826 2 0 1 0 1
#> GSM247775 1 0 1 1 0
#> GSM247741 2 0 1 0 1
#> GSM247799 2 0 1 0 1
#> GSM247778 1 0 1 1 0
#> GSM247806 2 0 1 0 1
#> GSM247815 1 0 1 1 0
#> GSM247735 2 0 1 0 1
#> GSM247831 2 0 1 0 1
#> GSM247845 1 0 1 1 0
#> GSM247791 2 0 1 0 1
#> GSM247780 1 0 1 1 0
#> GSM247853 1 0 1 1 0
#> GSM247800 2 0 1 0 1
#> GSM247729 2 0 1 0 1
#> GSM247810 1 0 1 1 0
#> GSM247844 2 0 1 0 1
#> GSM247793 1 0 1 1 0
#> GSM247759 2 0 1 0 1
#> GSM247724 2 0 1 0 1
#> GSM247817 2 0 1 0 1
#> GSM247727 1 0 1 1 0
#> GSM247796 2 0 1 0 1
#> GSM247725 2 0 1 0 1
#> GSM247801 1 0 1 1 0
#> GSM247731 2 0 1 0 1
#> GSM247765 1 0 1 1 0
#> GSM247792 2 0 1 0 1
#> GSM247726 2 0 1 0 1
#> GSM247803 1 0 1 1 0
#> GSM247728 2 0 1 0 1
#> GSM247768 1 0 1 1 0
#> GSM247745 2 0 1 0 1
#> GSM247855 2 0 1 0 1
#> GSM247804 2 0 1 0 1
#> GSM247774 1 0 1 1 0
#> GSM247807 2 0 1 0 1
#> GSM247813 1 0 1 1 0
#> GSM247736 2 0 1 0 1
#> GSM247712 2 0 1 0 1
#> GSM247797 1 0 1 1 0
#> GSM247743 2 0 1 0 1
#> GSM247719 1 0 1 1 0
#> GSM247707 2 0 1 0 1
#> GSM247737 2 0 1 0 1
#> GSM247827 2 0 1 0 1
#> GSM247848 1 0 1 1 0
#> GSM247794 2 0 1 0 1
#> GSM247757 2 0 1 0 1
#> GSM247744 1 0 1 1 0
#> GSM247751 2 0 1 0 1
#> GSM247837 1 0 1 1 0
#> GSM247754 2 0 1 0 1
#> GSM247789 2 0 1 0 1
#> GSM247802 1 0 1 1 0
#> GSM247771 2 0 1 0 1
#> GSM247763 1 0 1 1 0
#> GSM247808 2 0 1 0 1
#> GSM247787 2 0 1 0 1
#> GSM247843 1 0 1 1 0
#> GSM247811 2 0 1 0 1
#> GSM247773 1 0 1 1 0
#> GSM247766 2 0 1 0 1
#> GSM247718 2 0 1 0 1
#> GSM247832 1 0 1 1 0
#> GSM247709 2 0 1 0 1
#> GSM247820 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0 1 0 1 0
#> GSM247854 2 0 1 0 1 0
#> GSM247758 2 0 1 0 1 0
#> GSM247742 3 0 1 0 0 1
#> GSM247755 2 0 1 0 1 0
#> GSM247841 1 0 1 1 0 0
#> GSM247703 2 0 1 0 1 0
#> GSM247739 2 0 1 0 1 0
#> GSM247715 3 0 1 0 0 1
#> GSM247829 2 0 1 0 1 0
#> GSM247842 1 0 1 1 0 0
#> GSM247805 2 0 1 0 1 0
#> GSM247786 2 0 1 0 1 0
#> GSM247812 2 0 1 0 1 0
#> GSM247776 1 0 1 1 0 0
#> GSM247850 1 0 1 1 0 0
#> GSM247717 2 0 1 0 1 0
#> GSM247784 2 0 1 0 1 0
#> GSM247834 3 0 1 0 0 1
#> GSM247783 2 0 1 0 1 0
#> GSM247846 1 0 1 1 0 0
#> GSM247822 2 0 1 0 1 0
#> GSM247710 2 0 1 0 1 0
#> GSM247713 3 0 1 0 0 1
#> GSM247840 2 0 1 0 1 0
#> GSM247733 1 0 1 1 0 0
#> GSM247852 1 0 1 1 0 0
#> GSM247790 2 0 1 0 1 0
#> GSM247730 2 0 1 0 1 0
#> GSM247824 2 0 1 0 1 0
#> GSM247770 1 0 1 1 0 0
#> GSM247711 2 0 1 0 1 0
#> GSM247782 2 0 1 0 1 0
#> GSM247836 3 0 1 0 0 1
#> GSM247785 2 0 1 0 1 0
#> GSM247847 1 0 1 1 0 0
#> GSM247750 2 0 1 0 1 0
#> GSM247788 2 0 1 0 1 0
#> GSM247849 3 0 1 0 0 1
#> GSM247772 2 0 1 0 1 0
#> GSM247760 1 0 1 1 0 0
#> GSM247764 2 0 1 0 1 0
#> GSM247851 2 0 1 0 1 0
#> GSM247714 2 0 1 0 1 0
#> GSM247828 3 0 1 0 0 1
#> GSM247704 2 0 1 0 1 0
#> GSM247818 1 0 1 1 0 0
#> GSM247823 2 0 1 0 1 0
#> GSM247706 2 0 1 0 1 0
#> GSM247835 2 0 1 0 1 0
#> GSM247734 1 0 1 1 0 0
#> GSM247819 2 0 1 0 1 0
#> GSM247809 2 0 1 0 1 0
#> GSM247830 2 0 1 0 1 0
#> GSM247833 1 0 1 1 0 0
#> GSM247738 2 0 1 0 1 0
#> GSM247716 2 0 1 0 1 0
#> GSM247747 2 0 1 0 1 0
#> GSM247722 1 0 1 1 0 0
#> GSM247816 2 0 1 0 1 0
#> GSM247839 2 0 1 0 1 0
#> GSM247821 3 0 1 0 0 1
#> GSM247798 2 0 1 0 1 0
#> GSM247838 1 0 1 1 0 0
#> GSM247721 2 0 1 0 1 0
#> GSM247781 2 0 1 0 1 0
#> GSM247762 3 0 1 0 0 1
#> GSM247825 2 0 1 0 1 0
#> GSM247777 1 0 1 1 0 0
#> GSM247761 2 0 1 0 1 0
#> GSM247720 2 0 1 0 1 0
#> GSM247814 2 0 1 0 1 0
#> GSM247732 1 0 1 1 0 0
#> GSM247708 2 0 1 0 1 0
#> GSM247740 2 0 1 0 1 0
#> GSM247749 3 0 1 0 0 1
#> GSM247767 2 0 1 0 1 0
#> GSM247748 1 0 1 1 0 0
#> GSM247705 2 0 1 0 1 0
#> GSM247746 2 0 1 0 1 0
#> GSM247752 3 0 1 0 0 1
#> GSM247769 2 0 1 0 1 0
#> GSM247753 1 0 1 1 0 0
#> GSM247723 2 0 1 0 1 0
#> GSM247779 2 0 1 0 1 0
#> GSM247756 3 0 1 0 0 1
#> GSM247826 2 0 1 0 1 0
#> GSM247775 1 0 1 1 0 0
#> GSM247741 2 0 1 0 1 0
#> GSM247799 2 0 1 0 1 0
#> GSM247778 3 0 1 0 0 1
#> GSM247806 2 0 1 0 1 0
#> GSM247815 1 0 1 1 0 0
#> GSM247735 2 0 1 0 1 0
#> GSM247831 2 0 1 0 1 0
#> GSM247845 3 0 1 0 0 1
#> GSM247791 2 0 1 0 1 0
#> GSM247780 1 0 1 1 0 0
#> GSM247853 1 0 1 1 0 0
#> GSM247800 2 0 1 0 1 0
#> GSM247729 2 0 1 0 1 0
#> GSM247810 3 0 1 0 0 1
#> GSM247844 2 0 1 0 1 0
#> GSM247793 1 0 1 1 0 0
#> GSM247759 2 0 1 0 1 0
#> GSM247724 2 0 1 0 1 0
#> GSM247817 2 0 1 0 1 0
#> GSM247727 1 0 1 1 0 0
#> GSM247796 2 0 1 0 1 0
#> GSM247725 2 0 1 0 1 0
#> GSM247801 3 0 1 0 0 1
#> GSM247731 2 0 1 0 1 0
#> GSM247765 1 0 1 1 0 0
#> GSM247792 2 0 1 0 1 0
#> GSM247726 2 0 1 0 1 0
#> GSM247803 3 0 1 0 0 1
#> GSM247728 2 0 1 0 1 0
#> GSM247768 1 0 1 1 0 0
#> GSM247745 2 0 1 0 1 0
#> GSM247855 2 0 1 0 1 0
#> GSM247804 2 0 1 0 1 0
#> GSM247774 3 0 1 0 0 1
#> GSM247807 2 0 1 0 1 0
#> GSM247813 1 0 1 1 0 0
#> GSM247736 2 0 1 0 1 0
#> GSM247712 2 0 1 0 1 0
#> GSM247797 3 0 1 0 0 1
#> GSM247743 2 0 1 0 1 0
#> GSM247719 1 0 1 1 0 0
#> GSM247707 2 0 1 0 1 0
#> GSM247737 2 0 1 0 1 0
#> GSM247827 2 0 1 0 1 0
#> GSM247848 1 0 1 1 0 0
#> GSM247794 2 0 1 0 1 0
#> GSM247757 2 0 1 0 1 0
#> GSM247744 3 0 1 0 0 1
#> GSM247751 2 0 1 0 1 0
#> GSM247837 1 0 1 1 0 0
#> GSM247754 2 0 1 0 1 0
#> GSM247789 2 0 1 0 1 0
#> GSM247802 3 0 1 0 0 1
#> GSM247771 2 0 1 0 1 0
#> GSM247763 1 0 1 1 0 0
#> GSM247808 2 0 1 0 1 0
#> GSM247787 2 0 1 0 1 0
#> GSM247843 3 0 1 0 0 1
#> GSM247811 2 0 1 0 1 0
#> GSM247773 1 0 1 1 0 0
#> GSM247766 2 0 1 0 1 0
#> GSM247718 2 0 1 0 1 0
#> GSM247832 3 0 1 0 0 1
#> GSM247709 2 0 1 0 1 0
#> GSM247820 1 0 1 1 0 0
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0 1 0 1 0 0
#> GSM247854 2 0 1 0 1 0 0
#> GSM247758 2 0 1 0 1 0 0
#> GSM247742 4 0 1 0 0 0 1
#> GSM247755 3 0 1 0 0 1 0
#> GSM247841 1 0 1 1 0 0 0
#> GSM247703 2 0 1 0 1 0 0
#> GSM247739 2 0 1 0 1 0 0
#> GSM247715 4 0 1 0 0 0 1
#> GSM247829 3 0 1 0 0 1 0
#> GSM247842 1 0 1 1 0 0 0
#> GSM247805 2 0 1 0 1 0 0
#> GSM247786 2 0 1 0 1 0 0
#> GSM247812 3 0 1 0 0 1 0
#> GSM247776 1 0 1 1 0 0 0
#> GSM247850 1 0 1 1 0 0 0
#> GSM247717 2 0 1 0 1 0 0
#> GSM247784 2 0 1 0 1 0 0
#> GSM247834 4 0 1 0 0 0 1
#> GSM247783 3 0 1 0 0 1 0
#> GSM247846 1 0 1 1 0 0 0
#> GSM247822 2 0 1 0 1 0 0
#> GSM247710 2 0 1 0 1 0 0
#> GSM247713 4 0 1 0 0 0 1
#> GSM247840 3 0 1 0 0 1 0
#> GSM247733 1 0 1 1 0 0 0
#> GSM247852 1 0 1 1 0 0 0
#> GSM247790 2 0 1 0 1 0 0
#> GSM247730 2 0 1 0 1 0 0
#> GSM247824 3 0 1 0 0 1 0
#> GSM247770 1 0 1 1 0 0 0
#> GSM247711 2 0 1 0 1 0 0
#> GSM247782 2 0 1 0 1 0 0
#> GSM247836 4 0 1 0 0 0 1
#> GSM247785 3 0 1 0 0 1 0
#> GSM247847 1 0 1 1 0 0 0
#> GSM247750 2 0 1 0 1 0 0
#> GSM247788 2 0 1 0 1 0 0
#> GSM247849 4 0 1 0 0 0 1
#> GSM247772 3 0 1 0 0 1 0
#> GSM247760 1 0 1 1 0 0 0
#> GSM247764 2 0 1 0 1 0 0
#> GSM247851 2 0 1 0 1 0 0
#> GSM247714 2 0 1 0 1 0 0
#> GSM247828 4 0 1 0 0 0 1
#> GSM247704 3 0 1 0 0 1 0
#> GSM247818 1 0 1 1 0 0 0
#> GSM247823 2 0 1 0 1 0 0
#> GSM247706 2 0 1 0 1 0 0
#> GSM247835 3 0 1 0 0 1 0
#> GSM247734 1 0 1 1 0 0 0
#> GSM247819 2 0 1 0 1 0 0
#> GSM247809 2 0 1 0 1 0 0
#> GSM247830 3 0 1 0 0 1 0
#> GSM247833 1 0 1 1 0 0 0
#> GSM247738 2 0 1 0 1 0 0
#> GSM247716 2 0 1 0 1 0 0
#> GSM247747 3 0 1 0 0 1 0
#> GSM247722 1 0 1 1 0 0 0
#> GSM247816 2 0 1 0 1 0 0
#> GSM247839 2 0 1 0 1 0 0
#> GSM247821 4 0 1 0 0 0 1
#> GSM247798 3 0 1 0 0 1 0
#> GSM247838 1 0 1 1 0 0 0
#> GSM247721 2 0 1 0 1 0 0
#> GSM247781 2 0 1 0 1 0 0
#> GSM247762 4 0 1 0 0 0 1
#> GSM247825 3 0 1 0 0 1 0
#> GSM247777 1 0 1 1 0 0 0
#> GSM247761 2 0 1 0 1 0 0
#> GSM247720 2 0 1 0 1 0 0
#> GSM247814 3 0 1 0 0 1 0
#> GSM247732 1 0 1 1 0 0 0
#> GSM247708 2 0 1 0 1 0 0
#> GSM247740 2 0 1 0 1 0 0
#> GSM247749 4 0 1 0 0 0 1
#> GSM247767 3 0 1 0 0 1 0
#> GSM247748 1 0 1 1 0 0 0
#> GSM247705 2 0 1 0 1 0 0
#> GSM247746 2 0 1 0 1 0 0
#> GSM247752 4 0 1 0 0 0 1
#> GSM247769 3 0 1 0 0 1 0
#> GSM247753 1 0 1 1 0 0 0
#> GSM247723 2 0 1 0 1 0 0
#> GSM247779 2 0 1 0 1 0 0
#> GSM247756 4 0 1 0 0 0 1
#> GSM247826 3 0 1 0 0 1 0
#> GSM247775 1 0 1 1 0 0 0
#> GSM247741 2 0 1 0 1 0 0
#> GSM247799 2 0 1 0 1 0 0
#> GSM247778 4 0 1 0 0 0 1
#> GSM247806 3 0 1 0 0 1 0
#> GSM247815 1 0 1 1 0 0 0
#> GSM247735 2 0 1 0 1 0 0
#> GSM247831 2 0 1 0 1 0 0
#> GSM247845 4 0 1 0 0 0 1
#> GSM247791 3 0 1 0 0 1 0
#> GSM247780 1 0 1 1 0 0 0
#> GSM247853 1 0 1 1 0 0 0
#> GSM247800 2 0 1 0 1 0 0
#> GSM247729 2 0 1 0 1 0 0
#> GSM247810 4 0 1 0 0 0 1
#> GSM247844 3 0 1 0 0 1 0
#> GSM247793 1 0 1 1 0 0 0
#> GSM247759 2 0 1 0 1 0 0
#> GSM247724 2 0 1 0 1 0 0
#> GSM247817 3 0 1 0 0 1 0
#> GSM247727 1 0 1 1 0 0 0
#> GSM247796 2 0 1 0 1 0 0
#> GSM247725 2 0 1 0 1 0 0
#> GSM247801 4 0 1 0 0 0 1
#> GSM247731 3 0 1 0 0 1 0
#> GSM247765 1 0 1 1 0 0 0
#> GSM247792 2 0 1 0 1 0 0
#> GSM247726 2 0 1 0 1 0 0
#> GSM247803 4 0 1 0 0 0 1
#> GSM247728 3 0 1 0 0 1 0
#> GSM247768 1 0 1 1 0 0 0
#> GSM247745 2 0 1 0 1 0 0
#> GSM247855 2 0 1 0 1 0 0
#> GSM247804 2 0 1 0 1 0 0
#> GSM247774 4 0 1 0 0 0 1
#> GSM247807 3 0 1 0 0 1 0
#> GSM247813 1 0 1 1 0 0 0
#> GSM247736 2 0 1 0 1 0 0
#> GSM247712 2 0 1 0 1 0 0
#> GSM247797 4 0 1 0 0 0 1
#> GSM247743 3 0 1 0 0 1 0
#> GSM247719 1 0 1 1 0 0 0
#> GSM247707 2 0 1 0 1 0 0
#> GSM247737 2 0 1 0 1 0 0
#> GSM247827 3 0 1 0 0 1 0
#> GSM247848 1 0 1 1 0 0 0
#> GSM247794 2 0 1 0 1 0 0
#> GSM247757 2 0 1 0 1 0 0
#> GSM247744 4 0 1 0 0 0 1
#> GSM247751 3 0 1 0 0 1 0
#> GSM247837 1 0 1 1 0 0 0
#> GSM247754 2 0 1 0 1 0 0
#> GSM247789 2 0 1 0 1 0 0
#> GSM247802 4 0 1 0 0 0 1
#> GSM247771 3 0 1 0 0 1 0
#> GSM247763 1 0 1 1 0 0 0
#> GSM247808 2 0 1 0 1 0 0
#> GSM247787 2 0 1 0 1 0 0
#> GSM247843 4 0 1 0 0 0 1
#> GSM247811 3 0 1 0 0 1 0
#> GSM247773 1 0 1 1 0 0 0
#> GSM247766 2 0 1 0 1 0 0
#> GSM247718 2 0 1 0 1 0 0
#> GSM247832 4 0 1 0 0 0 1
#> GSM247709 3 0 1 0 0 1 0
#> GSM247820 1 0 1 1 0 0 0
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247854 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247758 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247742 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247755 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247841 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247703 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247739 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247715 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247829 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247842 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247805 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247786 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247812 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247776 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247717 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247784 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247834 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247783 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247846 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247822 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247710 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247713 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247840 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247733 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247790 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247730 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247824 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247770 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247711 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247782 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247836 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247785 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247847 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247750 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247788 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247849 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247772 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247760 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247764 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247851 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247714 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247828 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247704 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247818 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247823 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247706 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247835 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247734 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247819 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247809 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247830 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247833 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247738 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247716 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247747 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247722 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247816 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247839 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247821 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247798 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247838 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247721 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247781 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247762 4 0.1732 0.948 0 0.000 0 0.920 0.080
#> GSM247825 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247777 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247761 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247720 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247814 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247732 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247708 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247740 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247749 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247767 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247748 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247705 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247746 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247752 4 0.2561 0.910 0 0.000 0 0.856 0.144
#> GSM247769 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247753 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247723 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247779 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247756 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247826 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247775 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247741 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247799 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247778 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247806 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247815 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247735 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247831 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247845 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247791 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247780 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247800 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247729 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247810 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247844 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247793 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247759 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247724 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247817 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247727 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247796 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247725 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247801 4 0.0162 0.987 0 0.000 0 0.996 0.004
#> GSM247731 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247765 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247792 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247726 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247803 4 0.2561 0.910 0 0.000 0 0.856 0.144
#> GSM247728 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247768 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247745 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247855 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247804 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247774 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247807 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247813 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247736 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247712 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247797 4 0.0162 0.987 0 0.000 0 0.996 0.004
#> GSM247743 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247719 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247707 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247737 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247827 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247848 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247794 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247757 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247744 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247751 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247837 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247754 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247789 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247802 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247771 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247763 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247808 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247787 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247843 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247811 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247773 1 0.0000 1.000 1 0.000 0 0.000 0.000
#> GSM247766 2 0.0000 1.000 0 1.000 0 0.000 0.000
#> GSM247718 5 0.2561 1.000 0 0.144 0 0.000 0.856
#> GSM247832 4 0.0000 0.989 0 0.000 0 1.000 0.000
#> GSM247709 3 0.0000 1.000 0 0.000 1 0.000 0.000
#> GSM247820 1 0.0000 1.000 1 0.000 0 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247854 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247758 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247742 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247755 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247841 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247703 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247739 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247715 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247829 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247842 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247805 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247786 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247812 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247776 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247850 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247717 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247784 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247834 4 0.0146 0.934961 0 0 0 0.996 0 0.004
#> GSM247783 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247846 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247822 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247710 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247713 4 0.3747 0.222282 0 0 0 0.604 0 0.396
#> GSM247840 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247733 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247852 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247790 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247730 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247824 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247770 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247711 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247782 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247836 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247785 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247847 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247750 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247788 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247849 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247772 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247760 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247764 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247851 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247714 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247828 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247704 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247818 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247823 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247706 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247835 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247734 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247819 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247809 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247830 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247833 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247738 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247716 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247747 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247722 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247816 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247839 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247821 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247798 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247838 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247721 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247781 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247762 6 0.3563 0.449803 0 0 0 0.336 0 0.664
#> GSM247825 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247777 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247761 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247720 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247814 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247732 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247708 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247740 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247749 4 0.1327 0.880106 0 0 0 0.936 0 0.064
#> GSM247767 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247748 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247705 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247746 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247752 6 0.0790 0.802543 0 0 0 0.032 0 0.968
#> GSM247769 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247753 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247723 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247779 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247756 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247826 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247775 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247741 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247799 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247778 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247806 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247815 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247735 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247831 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247845 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247791 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247780 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247853 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247800 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247729 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247810 4 0.0146 0.934961 0 0 0 0.996 0 0.004
#> GSM247844 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247793 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247759 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247724 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247817 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247727 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247796 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247725 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247801 4 0.0713 0.916084 0 0 0 0.972 0 0.028
#> GSM247731 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247765 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247792 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247726 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247803 6 0.0000 0.791804 0 0 0 0.000 0 1.000
#> GSM247728 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247768 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247745 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247855 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247804 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247774 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247807 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247813 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247736 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247712 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247797 4 0.3847 0.000622 0 0 0 0.544 0 0.456
#> GSM247743 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247719 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247707 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247737 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247827 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247848 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247794 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247757 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247744 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247751 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247837 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247754 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247789 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247802 4 0.1075 0.897953 0 0 0 0.952 0 0.048
#> GSM247771 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247763 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247808 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247787 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247843 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247811 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247773 1 0.0000 1.000000 1 0 0 0.000 0 0.000
#> GSM247766 2 0.0000 1.000000 0 1 0 0.000 0 0.000
#> GSM247718 5 0.0000 1.000000 0 0 0 0.000 1 0.000
#> GSM247832 4 0.0000 0.937133 0 0 0 1.000 0 0.000
#> GSM247709 3 0.0000 1.000000 0 0 1 0.000 0 0.000
#> GSM247820 1 0.0000 1.000000 1 0 0 0.000 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
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
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> CV:hclust 153 1 1.000 4.63e-32 2
#> CV:hclust 153 1 0.875 2.17e-61 3
#> CV:hclust 153 1 0.964 1.16e-90 4
#> CV:hclust 153 1 0.989 6.51e-120 5
#> CV:hclust 150 1 0.640 2.88e-114 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.289 0.872 0.886 0.4333 0.529 0.529
#> 3 3 0.681 0.761 0.756 0.3705 1.000 1.000
#> 4 4 0.652 0.846 0.757 0.1595 0.759 0.546
#> 5 5 0.719 0.954 0.811 0.0854 0.909 0.686
#> 6 6 0.734 0.924 0.830 0.0503 1.000 1.000
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 5
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0.000 0.879 0.000 1.000
#> GSM247854 2 0.000 0.879 0.000 1.000
#> GSM247758 2 0.482 0.827 0.104 0.896
#> GSM247742 1 0.850 0.895 0.724 0.276
#> GSM247755 2 0.671 0.822 0.176 0.824
#> GSM247841 1 0.671 0.936 0.824 0.176
#> GSM247703 2 0.000 0.879 0.000 1.000
#> GSM247739 2 0.482 0.827 0.104 0.896
#> GSM247715 1 0.850 0.895 0.724 0.276
#> GSM247829 2 0.671 0.822 0.176 0.824
#> GSM247842 1 0.671 0.936 0.824 0.176
#> GSM247805 2 0.000 0.879 0.000 1.000
#> GSM247786 2 0.482 0.827 0.104 0.896
#> GSM247812 2 0.671 0.822 0.176 0.824
#> GSM247776 1 0.671 0.936 0.824 0.176
#> GSM247850 1 0.671 0.936 0.824 0.176
#> GSM247717 2 0.000 0.879 0.000 1.000
#> GSM247784 2 0.482 0.827 0.104 0.896
#> GSM247834 1 0.850 0.895 0.724 0.276
#> GSM247783 2 0.671 0.822 0.176 0.824
#> GSM247846 1 0.671 0.936 0.824 0.176
#> GSM247822 2 0.000 0.879 0.000 1.000
#> GSM247710 2 0.482 0.827 0.104 0.896
#> GSM247713 1 0.850 0.895 0.724 0.276
#> GSM247840 2 0.671 0.822 0.176 0.824
#> GSM247733 1 0.671 0.936 0.824 0.176
#> GSM247852 1 0.671 0.936 0.824 0.176
#> GSM247790 2 0.000 0.879 0.000 1.000
#> GSM247730 2 0.482 0.827 0.104 0.896
#> GSM247824 2 0.671 0.822 0.176 0.824
#> GSM247770 1 0.671 0.936 0.824 0.176
#> GSM247711 2 0.000 0.879 0.000 1.000
#> GSM247782 2 0.482 0.827 0.104 0.896
#> GSM247836 1 0.850 0.895 0.724 0.276
#> GSM247785 2 0.671 0.822 0.176 0.824
#> GSM247847 1 0.671 0.936 0.824 0.176
#> GSM247750 2 0.000 0.879 0.000 1.000
#> GSM247788 2 0.482 0.827 0.104 0.896
#> GSM247849 1 0.850 0.895 0.724 0.276
#> GSM247772 2 0.671 0.822 0.176 0.824
#> GSM247760 1 0.671 0.936 0.824 0.176
#> GSM247764 2 0.000 0.879 0.000 1.000
#> GSM247851 2 0.000 0.879 0.000 1.000
#> GSM247714 2 0.482 0.827 0.104 0.896
#> GSM247828 1 0.850 0.895 0.724 0.276
#> GSM247704 2 0.671 0.822 0.176 0.824
#> GSM247818 1 0.671 0.936 0.824 0.176
#> GSM247823 2 0.000 0.879 0.000 1.000
#> GSM247706 2 0.482 0.827 0.104 0.896
#> GSM247835 2 0.671 0.822 0.176 0.824
#> GSM247734 1 0.671 0.936 0.824 0.176
#> GSM247819 2 0.000 0.879 0.000 1.000
#> GSM247809 2 0.482 0.827 0.104 0.896
#> GSM247830 2 0.671 0.822 0.176 0.824
#> GSM247833 1 0.671 0.936 0.824 0.176
#> GSM247738 2 0.000 0.879 0.000 1.000
#> GSM247716 2 0.482 0.827 0.104 0.896
#> GSM247747 2 0.671 0.822 0.176 0.824
#> GSM247722 1 0.671 0.936 0.824 0.176
#> GSM247816 2 0.000 0.879 0.000 1.000
#> GSM247839 2 0.482 0.827 0.104 0.896
#> GSM247821 1 0.850 0.895 0.724 0.276
#> GSM247798 2 0.671 0.822 0.176 0.824
#> GSM247838 1 0.671 0.936 0.824 0.176
#> GSM247721 2 0.000 0.879 0.000 1.000
#> GSM247781 2 0.482 0.827 0.104 0.896
#> GSM247762 1 0.850 0.895 0.724 0.276
#> GSM247825 2 0.671 0.822 0.176 0.824
#> GSM247777 1 0.671 0.936 0.824 0.176
#> GSM247761 2 0.000 0.879 0.000 1.000
#> GSM247720 2 0.482 0.827 0.104 0.896
#> GSM247814 2 0.671 0.822 0.176 0.824
#> GSM247732 1 0.671 0.936 0.824 0.176
#> GSM247708 2 0.000 0.879 0.000 1.000
#> GSM247740 2 0.482 0.827 0.104 0.896
#> GSM247749 1 0.850 0.895 0.724 0.276
#> GSM247767 2 0.671 0.822 0.176 0.824
#> GSM247748 1 0.671 0.936 0.824 0.176
#> GSM247705 2 0.000 0.879 0.000 1.000
#> GSM247746 2 0.482 0.827 0.104 0.896
#> GSM247752 1 0.850 0.895 0.724 0.276
#> GSM247769 2 0.671 0.822 0.176 0.824
#> GSM247753 1 0.671 0.936 0.824 0.176
#> GSM247723 2 0.000 0.879 0.000 1.000
#> GSM247779 2 0.482 0.827 0.104 0.896
#> GSM247756 1 0.850 0.895 0.724 0.276
#> GSM247826 2 0.671 0.822 0.176 0.824
#> GSM247775 1 0.671 0.936 0.824 0.176
#> GSM247741 2 0.000 0.879 0.000 1.000
#> GSM247799 2 0.482 0.827 0.104 0.896
#> GSM247778 1 0.850 0.895 0.724 0.276
#> GSM247806 2 0.671 0.822 0.176 0.824
#> GSM247815 1 0.671 0.936 0.824 0.176
#> GSM247735 2 0.000 0.879 0.000 1.000
#> GSM247831 2 0.482 0.827 0.104 0.896
#> GSM247845 1 0.850 0.895 0.724 0.276
#> GSM247791 2 0.671 0.822 0.176 0.824
#> GSM247780 1 0.671 0.936 0.824 0.176
#> GSM247853 1 0.671 0.936 0.824 0.176
#> GSM247800 2 0.000 0.879 0.000 1.000
#> GSM247729 2 0.482 0.827 0.104 0.896
#> GSM247810 1 0.850 0.895 0.724 0.276
#> GSM247844 2 0.671 0.822 0.176 0.824
#> GSM247793 1 0.671 0.936 0.824 0.176
#> GSM247759 2 0.000 0.879 0.000 1.000
#> GSM247724 2 0.482 0.827 0.104 0.896
#> GSM247817 2 0.671 0.822 0.176 0.824
#> GSM247727 1 0.671 0.936 0.824 0.176
#> GSM247796 2 0.000 0.879 0.000 1.000
#> GSM247725 2 0.482 0.827 0.104 0.896
#> GSM247801 1 0.850 0.895 0.724 0.276
#> GSM247731 2 0.671 0.822 0.176 0.824
#> GSM247765 1 0.671 0.936 0.824 0.176
#> GSM247792 2 0.000 0.879 0.000 1.000
#> GSM247726 2 0.482 0.827 0.104 0.896
#> GSM247803 1 0.850 0.895 0.724 0.276
#> GSM247728 2 0.671 0.822 0.176 0.824
#> GSM247768 1 0.671 0.936 0.824 0.176
#> GSM247745 2 0.000 0.879 0.000 1.000
#> GSM247855 2 0.000 0.879 0.000 1.000
#> GSM247804 2 0.482 0.827 0.104 0.896
#> GSM247774 1 0.850 0.895 0.724 0.276
#> GSM247807 2 0.671 0.822 0.176 0.824
#> GSM247813 1 0.671 0.936 0.824 0.176
#> GSM247736 2 0.000 0.879 0.000 1.000
#> GSM247712 2 0.482 0.827 0.104 0.896
#> GSM247797 1 0.850 0.895 0.724 0.276
#> GSM247743 2 0.671 0.822 0.176 0.824
#> GSM247719 1 0.671 0.936 0.824 0.176
#> GSM247707 2 0.000 0.879 0.000 1.000
#> GSM247737 2 0.482 0.827 0.104 0.896
#> GSM247827 2 0.671 0.822 0.176 0.824
#> GSM247848 1 0.671 0.936 0.824 0.176
#> GSM247794 2 0.000 0.879 0.000 1.000
#> GSM247757 2 0.482 0.827 0.104 0.896
#> GSM247744 1 0.850 0.895 0.724 0.276
#> GSM247751 2 0.671 0.822 0.176 0.824
#> GSM247837 1 0.671 0.936 0.824 0.176
#> GSM247754 2 0.000 0.879 0.000 1.000
#> GSM247789 2 0.482 0.827 0.104 0.896
#> GSM247802 1 0.850 0.895 0.724 0.276
#> GSM247771 2 0.671 0.822 0.176 0.824
#> GSM247763 1 0.671 0.936 0.824 0.176
#> GSM247808 2 0.000 0.879 0.000 1.000
#> GSM247787 2 0.482 0.827 0.104 0.896
#> GSM247843 1 0.850 0.895 0.724 0.276
#> GSM247811 2 0.671 0.822 0.176 0.824
#> GSM247773 1 0.671 0.936 0.824 0.176
#> GSM247766 2 0.000 0.879 0.000 1.000
#> GSM247718 2 0.482 0.827 0.104 0.896
#> GSM247832 1 0.850 0.895 0.724 0.276
#> GSM247709 2 0.671 0.822 0.176 0.824
#> GSM247820 1 0.671 0.936 0.824 0.176
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0000 0.780 0.000 1.000 NA
#> GSM247854 2 0.0000 0.780 0.000 1.000 NA
#> GSM247758 2 0.5092 0.743 0.020 0.804 NA
#> GSM247742 1 0.7760 0.796 0.580 0.060 NA
#> GSM247755 2 0.6678 0.616 0.008 0.512 NA
#> GSM247841 1 0.1878 0.866 0.952 0.044 NA
#> GSM247703 2 0.0000 0.780 0.000 1.000 NA
#> GSM247739 2 0.5092 0.743 0.020 0.804 NA
#> GSM247715 1 0.7760 0.796 0.580 0.060 NA
#> GSM247829 2 0.6678 0.616 0.008 0.512 NA
#> GSM247842 1 0.1878 0.866 0.952 0.044 NA
#> GSM247805 2 0.0000 0.780 0.000 1.000 NA
#> GSM247786 2 0.5092 0.743 0.020 0.804 NA
#> GSM247812 2 0.7476 0.615 0.036 0.512 NA
#> GSM247776 1 0.2063 0.866 0.948 0.044 NA
#> GSM247850 1 0.2063 0.866 0.948 0.044 NA
#> GSM247717 2 0.0000 0.780 0.000 1.000 NA
#> GSM247784 2 0.5092 0.743 0.020 0.804 NA
#> GSM247834 1 0.7760 0.796 0.580 0.060 NA
#> GSM247783 2 0.6678 0.616 0.008 0.512 NA
#> GSM247846 1 0.2063 0.866 0.948 0.044 NA
#> GSM247822 2 0.0000 0.780 0.000 1.000 NA
#> GSM247710 2 0.5092 0.743 0.020 0.804 NA
#> GSM247713 1 0.7760 0.796 0.580 0.060 NA
#> GSM247840 2 0.7476 0.615 0.036 0.512 NA
#> GSM247733 1 0.1878 0.866 0.952 0.044 NA
#> GSM247852 1 0.1878 0.866 0.952 0.044 NA
#> GSM247790 2 0.0424 0.779 0.000 0.992 NA
#> GSM247730 2 0.5092 0.743 0.020 0.804 NA
#> GSM247824 2 0.6819 0.616 0.012 0.512 NA
#> GSM247770 1 0.2063 0.866 0.948 0.044 NA
#> GSM247711 2 0.0000 0.780 0.000 1.000 NA
#> GSM247782 2 0.5092 0.743 0.020 0.804 NA
#> GSM247836 1 0.7760 0.796 0.580 0.060 NA
#> GSM247785 2 0.6678 0.616 0.008 0.512 NA
#> GSM247847 1 0.2229 0.866 0.944 0.044 NA
#> GSM247750 2 0.0000 0.780 0.000 1.000 NA
#> GSM247788 2 0.5092 0.743 0.020 0.804 NA
#> GSM247849 1 0.7760 0.796 0.580 0.060 NA
#> GSM247772 2 0.6518 0.616 0.004 0.512 NA
#> GSM247760 1 0.2063 0.866 0.948 0.044 NA
#> GSM247764 2 0.0000 0.780 0.000 1.000 NA
#> GSM247851 2 0.0000 0.780 0.000 1.000 NA
#> GSM247714 2 0.5092 0.743 0.020 0.804 NA
#> GSM247828 1 0.7760 0.796 0.580 0.060 NA
#> GSM247704 2 0.7283 0.615 0.028 0.512 NA
#> GSM247818 1 0.1878 0.866 0.952 0.044 NA
#> GSM247823 2 0.0000 0.780 0.000 1.000 NA
#> GSM247706 2 0.5092 0.743 0.020 0.804 NA
#> GSM247835 2 0.6518 0.616 0.004 0.512 NA
#> GSM247734 1 0.2063 0.866 0.948 0.044 NA
#> GSM247819 2 0.0000 0.780 0.000 1.000 NA
#> GSM247809 2 0.5092 0.743 0.020 0.804 NA
#> GSM247830 2 0.6518 0.616 0.004 0.512 NA
#> GSM247833 1 0.1878 0.866 0.952 0.044 NA
#> GSM247738 2 0.0237 0.780 0.000 0.996 NA
#> GSM247716 2 0.5092 0.743 0.020 0.804 NA
#> GSM247747 2 0.6518 0.616 0.004 0.512 NA
#> GSM247722 1 0.2229 0.866 0.944 0.044 NA
#> GSM247816 2 0.0000 0.780 0.000 1.000 NA
#> GSM247839 2 0.5092 0.743 0.020 0.804 NA
#> GSM247821 1 0.7760 0.796 0.580 0.060 NA
#> GSM247798 2 0.6518 0.616 0.004 0.512 NA
#> GSM247838 1 0.2229 0.866 0.944 0.044 NA
#> GSM247721 2 0.0000 0.780 0.000 1.000 NA
#> GSM247781 2 0.5092 0.743 0.020 0.804 NA
#> GSM247762 1 0.7760 0.796 0.580 0.060 NA
#> GSM247825 2 0.7178 0.616 0.024 0.512 NA
#> GSM247777 1 0.1878 0.866 0.952 0.044 NA
#> GSM247761 2 0.0000 0.780 0.000 1.000 NA
#> GSM247720 2 0.5092 0.743 0.020 0.804 NA
#> GSM247814 2 0.6678 0.616 0.008 0.512 NA
#> GSM247732 1 0.1878 0.866 0.952 0.044 NA
#> GSM247708 2 0.0000 0.780 0.000 1.000 NA
#> GSM247740 2 0.5092 0.743 0.020 0.804 NA
#> GSM247749 1 0.7760 0.796 0.580 0.060 NA
#> GSM247767 2 0.6678 0.616 0.008 0.512 NA
#> GSM247748 1 0.1878 0.866 0.952 0.044 NA
#> GSM247705 2 0.0000 0.780 0.000 1.000 NA
#> GSM247746 2 0.5092 0.743 0.020 0.804 NA
#> GSM247752 1 0.7760 0.796 0.580 0.060 NA
#> GSM247769 2 0.6518 0.616 0.004 0.512 NA
#> GSM247753 1 0.1878 0.866 0.952 0.044 NA
#> GSM247723 2 0.0000 0.780 0.000 1.000 NA
#> GSM247779 2 0.5092 0.743 0.020 0.804 NA
#> GSM247756 1 0.7760 0.796 0.580 0.060 NA
#> GSM247826 2 0.6518 0.616 0.004 0.512 NA
#> GSM247775 1 0.1878 0.866 0.952 0.044 NA
#> GSM247741 2 0.0000 0.780 0.000 1.000 NA
#> GSM247799 2 0.5092 0.743 0.020 0.804 NA
#> GSM247778 1 0.7760 0.796 0.580 0.060 NA
#> GSM247806 2 0.6678 0.616 0.008 0.512 NA
#> GSM247815 1 0.2229 0.866 0.944 0.044 NA
#> GSM247735 2 0.0000 0.780 0.000 1.000 NA
#> GSM247831 2 0.5092 0.743 0.020 0.804 NA
#> GSM247845 1 0.7760 0.796 0.580 0.060 NA
#> GSM247791 2 0.7476 0.615 0.036 0.512 NA
#> GSM247780 1 0.2063 0.866 0.948 0.044 NA
#> GSM247853 1 0.2063 0.866 0.948 0.044 NA
#> GSM247800 2 0.0000 0.780 0.000 1.000 NA
#> GSM247729 2 0.5092 0.743 0.020 0.804 NA
#> GSM247810 1 0.7760 0.796 0.580 0.060 NA
#> GSM247844 2 0.6819 0.616 0.012 0.512 NA
#> GSM247793 1 0.1878 0.866 0.952 0.044 NA
#> GSM247759 2 0.0000 0.780 0.000 1.000 NA
#> GSM247724 2 0.5092 0.743 0.020 0.804 NA
#> GSM247817 2 0.6678 0.616 0.008 0.512 NA
#> GSM247727 1 0.1878 0.866 0.952 0.044 NA
#> GSM247796 2 0.0000 0.780 0.000 1.000 NA
#> GSM247725 2 0.5092 0.743 0.020 0.804 NA
#> GSM247801 1 0.7760 0.796 0.580 0.060 NA
#> GSM247731 2 0.6678 0.616 0.008 0.512 NA
#> GSM247765 1 0.2063 0.866 0.948 0.044 NA
#> GSM247792 2 0.0000 0.780 0.000 1.000 NA
#> GSM247726 2 0.5092 0.743 0.020 0.804 NA
#> GSM247803 1 0.7760 0.796 0.580 0.060 NA
#> GSM247728 2 0.7178 0.616 0.024 0.512 NA
#> GSM247768 1 0.1878 0.866 0.952 0.044 NA
#> GSM247745 2 0.0000 0.780 0.000 1.000 NA
#> GSM247855 2 0.0000 0.780 0.000 1.000 NA
#> GSM247804 2 0.5092 0.743 0.020 0.804 NA
#> GSM247774 1 0.7760 0.796 0.580 0.060 NA
#> GSM247807 2 0.7476 0.615 0.036 0.512 NA
#> GSM247813 1 0.2229 0.866 0.944 0.044 NA
#> GSM247736 2 0.0000 0.780 0.000 1.000 NA
#> GSM247712 2 0.5092 0.743 0.020 0.804 NA
#> GSM247797 1 0.7760 0.796 0.580 0.060 NA
#> GSM247743 2 0.6518 0.616 0.004 0.512 NA
#> GSM247719 1 0.1878 0.866 0.952 0.044 NA
#> GSM247707 2 0.0000 0.780 0.000 1.000 NA
#> GSM247737 2 0.5092 0.743 0.020 0.804 NA
#> GSM247827 2 0.7067 0.616 0.020 0.512 NA
#> GSM247848 1 0.1878 0.866 0.952 0.044 NA
#> GSM247794 2 0.0000 0.780 0.000 1.000 NA
#> GSM247757 2 0.5092 0.743 0.020 0.804 NA
#> GSM247744 1 0.7760 0.796 0.580 0.060 NA
#> GSM247751 2 0.6948 0.616 0.016 0.512 NA
#> GSM247837 1 0.1878 0.866 0.952 0.044 NA
#> GSM247754 2 0.0000 0.780 0.000 1.000 NA
#> GSM247789 2 0.5092 0.743 0.020 0.804 NA
#> GSM247802 1 0.7760 0.796 0.580 0.060 NA
#> GSM247771 2 0.6678 0.616 0.008 0.512 NA
#> GSM247763 1 0.2063 0.866 0.948 0.044 NA
#> GSM247808 2 0.0000 0.780 0.000 1.000 NA
#> GSM247787 2 0.5092 0.743 0.020 0.804 NA
#> GSM247843 1 0.7760 0.796 0.580 0.060 NA
#> GSM247811 2 0.7476 0.615 0.036 0.512 NA
#> GSM247773 1 0.1878 0.866 0.952 0.044 NA
#> GSM247766 2 0.0000 0.780 0.000 1.000 NA
#> GSM247718 2 0.5092 0.743 0.020 0.804 NA
#> GSM247832 1 0.7760 0.796 0.580 0.060 NA
#> GSM247709 2 0.7382 0.615 0.032 0.512 NA
#> GSM247820 1 0.1878 0.866 0.952 0.044 NA
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247854 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247758 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247742 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247755 3 0.4422 0.956 0.000 0.256 0.736 0.008
#> GSM247841 1 0.1182 0.974 0.968 0.016 0.016 0.000
#> GSM247703 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247739 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247715 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247829 3 0.5937 0.953 0.016 0.256 0.680 0.048
#> GSM247842 1 0.1297 0.973 0.964 0.016 0.020 0.000
#> GSM247805 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247786 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247812 3 0.6829 0.930 0.004 0.256 0.604 0.136
#> GSM247776 1 0.1182 0.973 0.968 0.016 0.016 0.000
#> GSM247850 1 0.1182 0.973 0.968 0.016 0.016 0.000
#> GSM247717 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247784 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247834 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247783 3 0.4422 0.956 0.000 0.256 0.736 0.008
#> GSM247846 1 0.1297 0.973 0.964 0.016 0.020 0.000
#> GSM247822 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247710 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247713 4 0.6574 0.960 0.440 0.016 0.044 0.500
#> GSM247840 3 0.6786 0.930 0.004 0.256 0.608 0.132
#> GSM247733 1 0.1059 0.971 0.972 0.016 0.012 0.000
#> GSM247852 1 0.1059 0.971 0.972 0.016 0.012 0.000
#> GSM247790 2 0.0921 0.685 0.000 0.972 0.028 0.000
#> GSM247730 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247824 3 0.4661 0.957 0.000 0.256 0.728 0.016
#> GSM247770 1 0.1297 0.973 0.964 0.016 0.020 0.000
#> GSM247711 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247782 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247836 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247785 3 0.4661 0.957 0.000 0.256 0.728 0.016
#> GSM247847 1 0.1406 0.974 0.960 0.016 0.024 0.000
#> GSM247750 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247788 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247849 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247772 3 0.4283 0.957 0.000 0.256 0.740 0.004
#> GSM247760 1 0.1059 0.974 0.972 0.016 0.012 0.000
#> GSM247764 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247851 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247714 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247828 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247704 3 0.6902 0.936 0.012 0.256 0.612 0.120
#> GSM247818 1 0.1059 0.971 0.972 0.016 0.012 0.000
#> GSM247823 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247706 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247835 3 0.4283 0.957 0.000 0.256 0.740 0.004
#> GSM247734 1 0.1182 0.973 0.968 0.016 0.016 0.000
#> GSM247819 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247809 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247830 3 0.5185 0.954 0.008 0.256 0.712 0.024
#> GSM247833 1 0.1510 0.971 0.956 0.016 0.028 0.000
#> GSM247738 2 0.0921 0.685 0.000 0.972 0.028 0.000
#> GSM247716 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247747 3 0.5234 0.956 0.004 0.256 0.708 0.032
#> GSM247722 1 0.1798 0.969 0.944 0.016 0.040 0.000
#> GSM247816 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247839 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247821 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247798 3 0.5607 0.953 0.016 0.256 0.696 0.032
#> GSM247838 1 0.1798 0.969 0.944 0.016 0.040 0.000
#> GSM247721 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247781 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247762 4 0.6574 0.960 0.440 0.016 0.044 0.500
#> GSM247825 3 0.6636 0.936 0.008 0.256 0.628 0.108
#> GSM247777 1 0.1510 0.971 0.956 0.016 0.028 0.000
#> GSM247761 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247720 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247814 3 0.5859 0.953 0.016 0.256 0.684 0.044
#> GSM247732 1 0.1406 0.970 0.960 0.016 0.024 0.000
#> GSM247708 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247740 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247749 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247767 3 0.4946 0.957 0.004 0.256 0.720 0.020
#> GSM247748 1 0.1059 0.971 0.972 0.016 0.012 0.000
#> GSM247705 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247746 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247752 4 0.6574 0.960 0.440 0.016 0.044 0.500
#> GSM247769 3 0.4422 0.956 0.000 0.256 0.736 0.008
#> GSM247753 1 0.1798 0.955 0.944 0.016 0.040 0.000
#> GSM247723 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247779 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247756 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247826 3 0.4283 0.957 0.000 0.256 0.740 0.004
#> GSM247775 1 0.1182 0.974 0.968 0.016 0.016 0.000
#> GSM247741 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247799 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247778 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247806 3 0.4422 0.956 0.000 0.256 0.736 0.008
#> GSM247815 1 0.1406 0.973 0.960 0.016 0.024 0.000
#> GSM247735 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247831 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247845 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247791 3 0.6829 0.930 0.004 0.256 0.604 0.136
#> GSM247780 1 0.1406 0.973 0.960 0.016 0.024 0.000
#> GSM247853 1 0.1510 0.973 0.956 0.016 0.028 0.000
#> GSM247800 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247729 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247810 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247844 3 0.5859 0.953 0.016 0.256 0.684 0.044
#> GSM247793 1 0.0592 0.975 0.984 0.016 0.000 0.000
#> GSM247759 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247724 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247817 3 0.5607 0.953 0.016 0.256 0.696 0.032
#> GSM247727 1 0.1406 0.970 0.960 0.016 0.024 0.000
#> GSM247796 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247725 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247801 4 0.6574 0.960 0.440 0.016 0.044 0.500
#> GSM247731 3 0.4283 0.956 0.000 0.256 0.740 0.004
#> GSM247765 1 0.1182 0.973 0.968 0.016 0.016 0.000
#> GSM247792 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247726 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247803 4 0.6574 0.960 0.440 0.016 0.044 0.500
#> GSM247728 3 0.6221 0.939 0.000 0.256 0.644 0.100
#> GSM247768 1 0.1798 0.955 0.944 0.016 0.040 0.000
#> GSM247745 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247855 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247804 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247774 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247807 3 0.6872 0.929 0.004 0.256 0.600 0.140
#> GSM247813 1 0.1798 0.969 0.944 0.016 0.040 0.000
#> GSM247736 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247712 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247797 4 0.6574 0.960 0.440 0.016 0.044 0.500
#> GSM247743 3 0.4946 0.955 0.004 0.256 0.720 0.020
#> GSM247719 1 0.1406 0.970 0.960 0.016 0.024 0.000
#> GSM247707 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247737 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247827 3 0.6221 0.939 0.000 0.256 0.644 0.100
#> GSM247848 1 0.1406 0.974 0.960 0.016 0.024 0.000
#> GSM247794 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247757 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247744 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247751 3 0.5744 0.949 0.000 0.256 0.676 0.068
#> GSM247837 1 0.1182 0.974 0.968 0.016 0.016 0.000
#> GSM247754 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247789 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247802 4 0.5888 0.979 0.440 0.016 0.012 0.532
#> GSM247771 3 0.4283 0.956 0.000 0.256 0.740 0.004
#> GSM247763 1 0.1182 0.973 0.968 0.016 0.016 0.000
#> GSM247808 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247787 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247843 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247811 3 0.6993 0.927 0.004 0.256 0.588 0.152
#> GSM247773 1 0.1059 0.971 0.972 0.016 0.012 0.000
#> GSM247766 2 0.0000 0.685 0.000 1.000 0.000 0.000
#> GSM247718 2 0.7232 0.685 0.000 0.516 0.164 0.320
#> GSM247832 4 0.5472 0.985 0.440 0.016 0.000 0.544
#> GSM247709 3 0.7081 0.931 0.012 0.256 0.596 0.136
#> GSM247820 1 0.1406 0.970 0.960 0.016 0.024 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.0290 0.969 0.008 0.992 0.000 0.000 0.000
#> GSM247854 2 0.0290 0.969 0.008 0.992 0.000 0.000 0.000
#> GSM247758 5 0.4886 0.986 0.004 0.352 0.020 0.004 0.620
#> GSM247742 4 0.0451 0.977 0.000 0.008 0.000 0.988 0.004
#> GSM247755 3 0.3723 0.934 0.004 0.160 0.808 0.004 0.024
#> GSM247841 1 0.5483 0.938 0.680 0.004 0.020 0.228 0.068
#> GSM247703 2 0.0404 0.967 0.012 0.988 0.000 0.000 0.000
#> GSM247739 5 0.4798 0.986 0.004 0.352 0.016 0.004 0.624
#> GSM247715 4 0.0290 0.977 0.000 0.008 0.000 0.992 0.000
#> GSM247829 3 0.4904 0.930 0.032 0.160 0.748 0.000 0.060
#> GSM247842 1 0.5568 0.936 0.676 0.004 0.024 0.228 0.068
#> GSM247805 2 0.0404 0.967 0.012 0.988 0.000 0.000 0.000
#> GSM247786 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247812 3 0.6675 0.891 0.140 0.160 0.624 0.004 0.072
#> GSM247776 1 0.4848 0.939 0.716 0.004 0.012 0.228 0.040
#> GSM247850 1 0.4848 0.939 0.716 0.004 0.012 0.228 0.040
#> GSM247717 2 0.0162 0.968 0.004 0.996 0.000 0.000 0.000
#> GSM247784 5 0.4886 0.986 0.004 0.352 0.020 0.004 0.620
#> GSM247834 4 0.0451 0.977 0.000 0.008 0.004 0.988 0.000
#> GSM247783 3 0.3381 0.933 0.004 0.160 0.820 0.000 0.016
#> GSM247846 1 0.5483 0.937 0.680 0.004 0.020 0.228 0.068
#> GSM247822 2 0.1270 0.961 0.052 0.948 0.000 0.000 0.000
#> GSM247710 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247713 4 0.2158 0.949 0.000 0.008 0.052 0.920 0.020
#> GSM247840 3 0.6637 0.891 0.136 0.160 0.628 0.004 0.072
#> GSM247733 1 0.4430 0.942 0.736 0.004 0.008 0.228 0.024
#> GSM247852 1 0.4129 0.944 0.748 0.004 0.004 0.228 0.016
#> GSM247790 2 0.0566 0.964 0.012 0.984 0.000 0.000 0.004
#> GSM247730 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247824 3 0.3403 0.934 0.008 0.160 0.820 0.000 0.012
#> GSM247770 1 0.4945 0.939 0.712 0.004 0.016 0.228 0.040
#> GSM247711 2 0.0290 0.968 0.008 0.992 0.000 0.000 0.000
#> GSM247782 5 0.4886 0.986 0.004 0.352 0.020 0.004 0.620
#> GSM247836 4 0.0579 0.977 0.000 0.008 0.000 0.984 0.008
#> GSM247785 3 0.3450 0.934 0.004 0.160 0.820 0.008 0.008
#> GSM247847 1 0.5700 0.938 0.664 0.004 0.020 0.228 0.084
#> GSM247750 2 0.0404 0.967 0.012 0.988 0.000 0.000 0.000
#> GSM247788 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247849 4 0.0451 0.977 0.000 0.008 0.000 0.988 0.004
#> GSM247772 3 0.3381 0.934 0.000 0.160 0.820 0.004 0.016
#> GSM247760 1 0.4918 0.939 0.712 0.004 0.012 0.228 0.044
#> GSM247764 2 0.1478 0.959 0.064 0.936 0.000 0.000 0.000
#> GSM247851 2 0.1478 0.959 0.064 0.936 0.000 0.000 0.000
#> GSM247714 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247828 4 0.0579 0.977 0.000 0.008 0.000 0.984 0.008
#> GSM247704 3 0.6605 0.897 0.092 0.160 0.636 0.004 0.108
#> GSM247818 1 0.4619 0.941 0.728 0.004 0.012 0.228 0.028
#> GSM247823 2 0.1197 0.964 0.048 0.952 0.000 0.000 0.000
#> GSM247706 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247835 3 0.3319 0.933 0.000 0.160 0.820 0.000 0.020
#> GSM247734 1 0.4918 0.939 0.712 0.004 0.012 0.228 0.044
#> GSM247819 2 0.1410 0.959 0.060 0.940 0.000 0.000 0.000
#> GSM247809 5 0.4886 0.986 0.004 0.352 0.020 0.004 0.620
#> GSM247830 3 0.4495 0.926 0.016 0.160 0.768 0.000 0.056
#> GSM247833 1 0.5510 0.933 0.680 0.004 0.024 0.228 0.064
#> GSM247738 2 0.0324 0.967 0.004 0.992 0.000 0.000 0.004
#> GSM247716 5 0.4886 0.986 0.004 0.352 0.020 0.004 0.620
#> GSM247747 3 0.4385 0.930 0.020 0.160 0.776 0.000 0.044
#> GSM247722 1 0.5964 0.931 0.648 0.004 0.028 0.228 0.092
#> GSM247816 2 0.0609 0.968 0.020 0.980 0.000 0.000 0.000
#> GSM247839 5 0.4886 0.986 0.004 0.352 0.020 0.004 0.620
#> GSM247821 4 0.0579 0.977 0.000 0.008 0.000 0.984 0.008
#> GSM247798 3 0.4783 0.927 0.028 0.160 0.760 0.004 0.048
#> GSM247838 1 0.5964 0.931 0.648 0.004 0.028 0.228 0.092
#> GSM247721 2 0.0290 0.968 0.008 0.992 0.000 0.000 0.000
#> GSM247781 5 0.4886 0.986 0.004 0.352 0.020 0.004 0.620
#> GSM247762 4 0.2321 0.945 0.000 0.008 0.056 0.912 0.024
#> GSM247825 3 0.6209 0.902 0.072 0.160 0.668 0.004 0.096
#> GSM247777 1 0.5510 0.933 0.680 0.004 0.024 0.228 0.064
#> GSM247761 2 0.0162 0.968 0.004 0.996 0.000 0.000 0.000
#> GSM247720 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247814 3 0.4981 0.927 0.036 0.160 0.744 0.000 0.060
#> GSM247732 1 0.4536 0.945 0.732 0.004 0.012 0.228 0.024
#> GSM247708 2 0.0000 0.969 0.000 1.000 0.000 0.000 0.000
#> GSM247740 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247749 4 0.0613 0.977 0.000 0.008 0.004 0.984 0.004
#> GSM247767 3 0.3798 0.934 0.024 0.160 0.804 0.000 0.012
#> GSM247748 1 0.4430 0.942 0.736 0.004 0.008 0.228 0.024
#> GSM247705 2 0.1341 0.964 0.056 0.944 0.000 0.000 0.000
#> GSM247746 5 0.4883 0.971 0.000 0.348 0.028 0.004 0.620
#> GSM247752 4 0.2562 0.938 0.000 0.008 0.060 0.900 0.032
#> GSM247769 3 0.3293 0.934 0.008 0.160 0.824 0.000 0.008
#> GSM247753 1 0.5623 0.927 0.676 0.004 0.036 0.228 0.056
#> GSM247723 2 0.1410 0.959 0.060 0.940 0.000 0.000 0.000
#> GSM247779 5 0.4886 0.986 0.004 0.352 0.020 0.004 0.620
#> GSM247756 4 0.0451 0.977 0.000 0.008 0.000 0.988 0.004
#> GSM247826 3 0.3566 0.935 0.000 0.160 0.812 0.004 0.024
#> GSM247775 1 0.5705 0.938 0.668 0.004 0.028 0.228 0.072
#> GSM247741 2 0.1410 0.959 0.060 0.940 0.000 0.000 0.000
#> GSM247799 5 0.4886 0.986 0.004 0.352 0.020 0.004 0.620
#> GSM247778 4 0.0451 0.977 0.000 0.008 0.000 0.988 0.004
#> GSM247806 3 0.3381 0.933 0.004 0.160 0.820 0.000 0.016
#> GSM247815 1 0.5915 0.937 0.652 0.004 0.028 0.228 0.088
#> GSM247735 2 0.1410 0.959 0.060 0.940 0.000 0.000 0.000
#> GSM247831 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247845 4 0.0451 0.977 0.000 0.008 0.000 0.988 0.004
#> GSM247791 3 0.6675 0.891 0.140 0.160 0.624 0.004 0.072
#> GSM247780 1 0.4668 0.941 0.724 0.004 0.008 0.228 0.036
#> GSM247853 1 0.4668 0.941 0.724 0.004 0.008 0.228 0.036
#> GSM247800 2 0.1410 0.959 0.060 0.940 0.000 0.000 0.000
#> GSM247729 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247810 4 0.0613 0.977 0.000 0.008 0.004 0.984 0.004
#> GSM247844 3 0.5117 0.926 0.040 0.160 0.736 0.000 0.064
#> GSM247793 1 0.4129 0.945 0.748 0.004 0.004 0.228 0.016
#> GSM247759 2 0.1197 0.964 0.048 0.952 0.000 0.000 0.000
#> GSM247724 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247817 3 0.4783 0.927 0.028 0.160 0.760 0.004 0.048
#> GSM247727 1 0.4536 0.945 0.732 0.004 0.012 0.228 0.024
#> GSM247796 2 0.1410 0.959 0.060 0.940 0.000 0.000 0.000
#> GSM247725 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247801 4 0.2576 0.943 0.000 0.008 0.056 0.900 0.036
#> GSM247731 3 0.3280 0.933 0.004 0.160 0.824 0.000 0.012
#> GSM247765 1 0.5213 0.939 0.696 0.004 0.016 0.228 0.056
#> GSM247792 2 0.1410 0.959 0.060 0.940 0.000 0.000 0.000
#> GSM247726 5 0.4929 0.957 0.000 0.340 0.032 0.004 0.624
#> GSM247803 4 0.2562 0.938 0.000 0.008 0.060 0.900 0.032
#> GSM247728 3 0.5995 0.905 0.064 0.160 0.684 0.004 0.088
#> GSM247768 1 0.5623 0.927 0.676 0.004 0.036 0.228 0.056
#> GSM247745 2 0.0000 0.969 0.000 1.000 0.000 0.000 0.000
#> GSM247855 2 0.0000 0.969 0.000 1.000 0.000 0.000 0.000
#> GSM247804 5 0.4886 0.986 0.004 0.352 0.020 0.004 0.620
#> GSM247774 4 0.0693 0.975 0.000 0.008 0.000 0.980 0.012
#> GSM247807 3 0.6637 0.891 0.136 0.160 0.628 0.004 0.072
#> GSM247813 1 0.5964 0.931 0.648 0.004 0.028 0.228 0.092
#> GSM247736 2 0.0000 0.969 0.000 1.000 0.000 0.000 0.000
#> GSM247712 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247797 4 0.2321 0.945 0.000 0.008 0.056 0.912 0.024
#> GSM247743 3 0.4218 0.929 0.016 0.160 0.784 0.000 0.040
#> GSM247719 1 0.4536 0.945 0.732 0.004 0.012 0.228 0.024
#> GSM247707 2 0.0290 0.968 0.008 0.992 0.000 0.000 0.000
#> GSM247737 5 0.4886 0.986 0.004 0.352 0.020 0.004 0.620
#> GSM247827 3 0.6104 0.905 0.060 0.160 0.680 0.008 0.092
#> GSM247848 1 0.5568 0.936 0.676 0.004 0.024 0.228 0.068
#> GSM247794 2 0.0404 0.967 0.012 0.988 0.000 0.000 0.000
#> GSM247757 5 0.4886 0.986 0.004 0.352 0.020 0.004 0.620
#> GSM247744 4 0.0693 0.975 0.000 0.008 0.000 0.980 0.012
#> GSM247751 3 0.5650 0.914 0.052 0.160 0.708 0.004 0.076
#> GSM247837 1 0.5483 0.938 0.680 0.004 0.020 0.228 0.068
#> GSM247754 2 0.1197 0.963 0.048 0.952 0.000 0.000 0.000
#> GSM247789 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247802 4 0.0798 0.974 0.000 0.008 0.016 0.976 0.000
#> GSM247771 3 0.3280 0.933 0.004 0.160 0.824 0.000 0.012
#> GSM247763 1 0.4848 0.939 0.716 0.004 0.012 0.228 0.040
#> GSM247808 2 0.0000 0.969 0.000 1.000 0.000 0.000 0.000
#> GSM247787 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247843 4 0.0290 0.977 0.000 0.008 0.000 0.992 0.000
#> GSM247811 3 0.6701 0.890 0.148 0.160 0.612 0.000 0.080
#> GSM247773 1 0.4430 0.942 0.736 0.004 0.008 0.228 0.024
#> GSM247766 2 0.1410 0.959 0.060 0.940 0.000 0.000 0.000
#> GSM247718 5 0.4333 0.989 0.000 0.352 0.004 0.004 0.640
#> GSM247832 4 0.0451 0.977 0.000 0.008 0.000 0.988 0.004
#> GSM247709 3 0.6742 0.895 0.100 0.160 0.624 0.004 0.112
#> GSM247820 1 0.4536 0.945 0.732 0.004 0.012 0.228 0.024
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.5388 0.919 0.000 0.652 0.056 0.008 0.236 NA
#> GSM247854 2 0.5388 0.919 0.000 0.652 0.056 0.008 0.236 NA
#> GSM247758 5 0.0458 0.981 0.000 0.000 0.000 0.000 0.984 NA
#> GSM247742 4 0.3429 0.952 0.128 0.028 0.000 0.824 0.012 NA
#> GSM247755 3 0.1804 0.907 0.000 0.016 0.936 0.008 0.020 NA
#> GSM247841 1 0.2164 0.923 0.908 0.028 0.008 0.000 0.000 NA
#> GSM247703 2 0.5317 0.914 0.000 0.660 0.056 0.016 0.236 NA
#> GSM247739 5 0.0632 0.980 0.000 0.000 0.000 0.000 0.976 NA
#> GSM247715 4 0.2489 0.953 0.128 0.000 0.000 0.860 0.012 NA
#> GSM247829 3 0.3522 0.901 0.000 0.024 0.844 0.044 0.020 NA
#> GSM247842 1 0.2377 0.920 0.892 0.024 0.008 0.000 0.000 NA
#> GSM247805 2 0.5137 0.914 0.000 0.668 0.056 0.008 0.236 NA
#> GSM247786 5 0.0458 0.977 0.000 0.000 0.000 0.000 0.984 NA
#> GSM247812 3 0.4468 0.855 0.000 0.016 0.680 0.008 0.020 NA
#> GSM247776 1 0.2249 0.918 0.900 0.032 0.004 0.000 0.000 NA
#> GSM247850 1 0.2307 0.917 0.896 0.032 0.004 0.000 0.000 NA
#> GSM247717 2 0.4507 0.916 0.000 0.696 0.056 0.000 0.236 NA
#> GSM247784 5 0.0458 0.981 0.000 0.000 0.000 0.000 0.984 NA
#> GSM247834 4 0.3094 0.951 0.128 0.012 0.000 0.840 0.012 NA
#> GSM247783 3 0.1508 0.906 0.000 0.012 0.948 0.004 0.020 NA
#> GSM247846 1 0.2322 0.921 0.896 0.024 0.008 0.000 0.000 NA
#> GSM247822 2 0.6478 0.906 0.000 0.580 0.056 0.040 0.236 NA
#> GSM247710 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000 NA
#> GSM247713 4 0.5003 0.912 0.128 0.064 0.000 0.732 0.012 NA
#> GSM247840 3 0.4401 0.852 0.000 0.012 0.680 0.008 0.020 NA
#> GSM247733 1 0.1074 0.928 0.960 0.012 0.000 0.000 0.000 NA
#> GSM247852 1 0.0935 0.928 0.964 0.004 0.000 0.000 0.000 NA
#> GSM247790 2 0.5329 0.909 0.000 0.656 0.048 0.020 0.244 NA
#> GSM247730 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000 NA
#> GSM247824 3 0.1911 0.909 0.000 0.012 0.928 0.004 0.020 NA
#> GSM247770 1 0.2307 0.918 0.896 0.032 0.004 0.000 0.000 NA
#> GSM247711 2 0.4731 0.915 0.000 0.688 0.056 0.004 0.236 NA
#> GSM247782 5 0.0458 0.981 0.000 0.000 0.000 0.000 0.984 NA
#> GSM247836 4 0.3271 0.953 0.128 0.020 0.000 0.832 0.012 NA
#> GSM247785 3 0.2051 0.908 0.000 0.012 0.920 0.004 0.020 NA
#> GSM247847 1 0.2454 0.926 0.884 0.020 0.008 0.000 0.000 NA
#> GSM247750 2 0.5398 0.913 0.000 0.656 0.056 0.020 0.236 NA
#> GSM247788 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000 NA
#> GSM247849 4 0.3503 0.952 0.128 0.032 0.000 0.820 0.012 NA
#> GSM247772 3 0.1520 0.909 0.000 0.008 0.948 0.008 0.020 NA
#> GSM247760 1 0.2094 0.918 0.908 0.024 0.004 0.000 0.000 NA
#> GSM247764 2 0.7134 0.891 0.000 0.504 0.056 0.044 0.236 NA
#> GSM247851 2 0.7134 0.891 0.000 0.504 0.056 0.044 0.236 NA
#> GSM247714 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000 NA
#> GSM247828 4 0.3271 0.953 0.128 0.020 0.000 0.832 0.012 NA
#> GSM247704 3 0.4458 0.863 0.000 0.004 0.688 0.024 0.020 NA
#> GSM247818 1 0.1218 0.925 0.956 0.012 0.004 0.000 0.000 NA
#> GSM247823 2 0.6659 0.908 0.000 0.556 0.056 0.032 0.236 NA
#> GSM247706 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000 NA
#> GSM247835 3 0.1425 0.907 0.000 0.012 0.952 0.008 0.020 NA
#> GSM247734 1 0.2249 0.918 0.900 0.032 0.004 0.000 0.000 NA
#> GSM247819 2 0.6997 0.890 0.000 0.520 0.056 0.040 0.236 NA
#> GSM247809 5 0.0692 0.980 0.000 0.000 0.000 0.004 0.976 NA
#> GSM247830 3 0.2863 0.901 0.000 0.032 0.884 0.044 0.020 NA
#> GSM247833 1 0.2445 0.917 0.872 0.020 0.000 0.000 0.000 NA
#> GSM247738 2 0.4438 0.913 0.000 0.696 0.048 0.000 0.244 NA
#> GSM247716 5 0.0692 0.980 0.000 0.000 0.000 0.004 0.976 NA
#> GSM247747 3 0.2701 0.904 0.000 0.028 0.892 0.044 0.020 NA
#> GSM247722 1 0.2907 0.914 0.828 0.020 0.000 0.000 0.000 NA
#> GSM247816 2 0.6010 0.917 0.000 0.612 0.056 0.020 0.236 NA
#> GSM247839 5 0.0692 0.980 0.000 0.000 0.000 0.004 0.976 NA
#> GSM247821 4 0.3271 0.953 0.128 0.020 0.000 0.832 0.012 NA
#> GSM247798 3 0.3429 0.901 0.000 0.028 0.852 0.048 0.020 NA
#> GSM247838 1 0.2907 0.914 0.828 0.020 0.000 0.000 0.000 NA
#> GSM247721 2 0.4813 0.915 0.000 0.684 0.056 0.004 0.236 NA
#> GSM247781 5 0.0458 0.981 0.000 0.000 0.000 0.000 0.984 NA
#> GSM247762 4 0.5413 0.901 0.128 0.076 0.000 0.700 0.012 NA
#> GSM247825 3 0.3780 0.869 0.000 0.004 0.728 0.000 0.020 NA
#> GSM247777 1 0.2587 0.916 0.868 0.020 0.004 0.000 0.000 NA
#> GSM247761 2 0.5089 0.916 0.000 0.672 0.056 0.012 0.236 NA
#> GSM247720 5 0.0547 0.976 0.000 0.000 0.000 0.000 0.980 NA
#> GSM247814 3 0.3530 0.900 0.000 0.024 0.844 0.048 0.020 NA
#> GSM247732 1 0.1913 0.924 0.908 0.012 0.000 0.000 0.000 NA
#> GSM247708 2 0.4656 0.917 0.000 0.692 0.056 0.008 0.236 NA
#> GSM247740 5 0.0363 0.979 0.000 0.000 0.000 0.000 0.988 NA
#> GSM247749 4 0.2773 0.952 0.128 0.004 0.000 0.852 0.012 NA
#> GSM247767 3 0.1976 0.909 0.000 0.008 0.928 0.024 0.020 NA
#> GSM247748 1 0.0820 0.927 0.972 0.012 0.000 0.000 0.000 NA
#> GSM247705 2 0.6893 0.909 0.000 0.540 0.056 0.048 0.236 NA
#> GSM247746 5 0.2070 0.903 0.000 0.008 0.000 0.000 0.892 NA
#> GSM247752 4 0.5771 0.879 0.128 0.068 0.000 0.664 0.012 NA
#> GSM247769 3 0.1452 0.910 0.000 0.000 0.948 0.012 0.020 NA
#> GSM247753 1 0.2828 0.887 0.864 0.060 0.004 0.000 0.000 NA
#> GSM247723 2 0.7025 0.891 0.000 0.516 0.056 0.040 0.236 NA
#> GSM247779 5 0.0458 0.981 0.000 0.000 0.000 0.000 0.984 NA
#> GSM247756 4 0.3352 0.952 0.128 0.024 0.000 0.828 0.012 NA
#> GSM247826 3 0.1602 0.909 0.000 0.016 0.944 0.004 0.020 NA
#> GSM247775 1 0.2285 0.922 0.900 0.028 0.008 0.000 0.000 NA
#> GSM247741 2 0.6997 0.890 0.000 0.520 0.056 0.040 0.236 NA
#> GSM247799 5 0.0458 0.981 0.000 0.000 0.000 0.000 0.984 NA
#> GSM247778 4 0.2631 0.953 0.128 0.004 0.000 0.856 0.012 NA
#> GSM247806 3 0.1508 0.906 0.000 0.012 0.948 0.004 0.020 NA
#> GSM247815 1 0.2604 0.925 0.872 0.028 0.004 0.000 0.000 NA
#> GSM247735 2 0.6997 0.890 0.000 0.520 0.056 0.040 0.236 NA
#> GSM247831 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000 NA
#> GSM247845 4 0.3271 0.953 0.128 0.020 0.000 0.832 0.012 NA
#> GSM247791 3 0.4468 0.855 0.000 0.016 0.680 0.008 0.020 NA
#> GSM247780 1 0.2088 0.921 0.904 0.028 0.000 0.000 0.000 NA
#> GSM247853 1 0.2255 0.921 0.892 0.028 0.000 0.000 0.000 NA
#> GSM247800 2 0.6997 0.890 0.000 0.520 0.056 0.040 0.236 NA
#> GSM247729 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000 NA
#> GSM247810 4 0.2773 0.952 0.128 0.004 0.000 0.852 0.012 NA
#> GSM247844 3 0.3587 0.899 0.000 0.024 0.840 0.048 0.020 NA
#> GSM247793 1 0.0520 0.928 0.984 0.008 0.000 0.000 0.000 NA
#> GSM247759 2 0.6594 0.907 0.000 0.560 0.056 0.028 0.236 NA
#> GSM247724 5 0.0291 0.981 0.000 0.000 0.000 0.004 0.992 NA
#> GSM247817 3 0.3429 0.901 0.000 0.028 0.852 0.048 0.020 NA
#> GSM247727 1 0.1913 0.924 0.908 0.012 0.000 0.000 0.000 NA
#> GSM247796 2 0.6997 0.890 0.000 0.520 0.056 0.040 0.236 NA
#> GSM247725 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000 NA
#> GSM247801 4 0.5883 0.901 0.128 0.120 0.004 0.664 0.012 NA
#> GSM247731 3 0.1414 0.906 0.000 0.012 0.952 0.004 0.020 NA
#> GSM247765 1 0.2249 0.918 0.900 0.032 0.004 0.000 0.000 NA
#> GSM247792 2 0.7052 0.890 0.000 0.512 0.056 0.040 0.236 NA
#> GSM247726 5 0.2553 0.858 0.000 0.008 0.000 0.000 0.848 NA
#> GSM247803 4 0.5771 0.879 0.128 0.068 0.000 0.664 0.012 NA
#> GSM247728 3 0.3791 0.875 0.000 0.008 0.756 0.004 0.020 NA
#> GSM247768 1 0.2828 0.887 0.864 0.060 0.004 0.000 0.000 NA
#> GSM247745 2 0.4305 0.917 0.000 0.704 0.056 0.004 0.236 NA
#> GSM247855 2 0.4305 0.917 0.000 0.704 0.056 0.004 0.236 NA
#> GSM247804 5 0.0458 0.981 0.000 0.000 0.000 0.000 0.984 NA
#> GSM247774 4 0.4133 0.946 0.128 0.056 0.004 0.788 0.012 NA
#> GSM247807 3 0.4500 0.857 0.000 0.016 0.688 0.012 0.020 NA
#> GSM247813 1 0.2945 0.914 0.824 0.020 0.000 0.000 0.000 NA
#> GSM247736 2 0.4305 0.917 0.000 0.704 0.056 0.004 0.236 NA
#> GSM247712 5 0.0547 0.976 0.000 0.000 0.000 0.000 0.980 NA
#> GSM247797 4 0.5314 0.905 0.128 0.080 0.000 0.708 0.012 NA
#> GSM247743 3 0.2608 0.903 0.000 0.028 0.896 0.044 0.020 NA
#> GSM247719 1 0.1913 0.924 0.908 0.012 0.000 0.000 0.000 NA
#> GSM247707 2 0.5099 0.915 0.000 0.672 0.056 0.016 0.236 NA
#> GSM247737 5 0.0458 0.981 0.000 0.000 0.000 0.000 0.984 NA
#> GSM247827 3 0.3652 0.876 0.000 0.008 0.760 0.000 0.020 NA
#> GSM247848 1 0.2510 0.920 0.884 0.028 0.008 0.000 0.000 NA
#> GSM247794 2 0.5231 0.914 0.000 0.664 0.056 0.012 0.236 NA
#> GSM247757 5 0.0458 0.981 0.000 0.000 0.000 0.000 0.984 NA
#> GSM247744 4 0.4133 0.946 0.128 0.056 0.004 0.788 0.012 NA
#> GSM247751 3 0.3438 0.885 0.000 0.008 0.788 0.000 0.020 NA
#> GSM247837 1 0.2164 0.923 0.908 0.028 0.008 0.000 0.000 NA
#> GSM247754 2 0.6721 0.905 0.000 0.552 0.056 0.036 0.236 NA
#> GSM247789 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000 NA
#> GSM247802 4 0.3461 0.948 0.128 0.016 0.000 0.824 0.012 NA
#> GSM247771 3 0.1414 0.906 0.000 0.012 0.952 0.004 0.020 NA
#> GSM247763 1 0.2249 0.918 0.900 0.032 0.004 0.000 0.000 NA
#> GSM247808 2 0.4549 0.917 0.000 0.696 0.056 0.008 0.236 NA
#> GSM247787 5 0.0458 0.977 0.000 0.000 0.000 0.000 0.984 NA
#> GSM247843 4 0.2489 0.953 0.128 0.000 0.000 0.860 0.012 NA
#> GSM247811 3 0.4679 0.857 0.000 0.012 0.676 0.024 0.020 NA
#> GSM247773 1 0.0909 0.926 0.968 0.012 0.000 0.000 0.000 NA
#> GSM247766 2 0.6997 0.890 0.000 0.520 0.056 0.040 0.236 NA
#> GSM247718 5 0.0458 0.977 0.000 0.000 0.000 0.000 0.984 NA
#> GSM247832 4 0.3503 0.952 0.128 0.032 0.000 0.820 0.012 NA
#> GSM247709 3 0.4520 0.858 0.000 0.004 0.676 0.024 0.020 NA
#> GSM247820 1 0.1967 0.924 0.904 0.012 0.000 0.000 0.000 NA
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> CV:kmeans 153 1 1.000 4.63e-32 2
#> CV:kmeans 153 1 1.000 4.63e-32 3
#> CV:kmeans 153 1 0.964 1.16e-90 4
#> CV:kmeans 153 1 0.989 6.51e-120 5
#> CV:kmeans 153 1 0.989 6.51e-120 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.4711 0.529 0.529
#> 3 3 1.000 0.996 0.996 0.3677 0.827 0.673
#> 4 4 0.842 0.979 0.951 0.1354 0.909 0.745
#> 5 5 1.000 0.999 0.998 0.0957 0.933 0.747
#> 6 6 0.971 0.978 0.978 0.0113 0.995 0.975
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 3
There is also optional best \(k\) = 2 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0 1 0 1
#> GSM247854 2 0 1 0 1
#> GSM247758 2 0 1 0 1
#> GSM247742 1 0 1 1 0
#> GSM247755 2 0 1 0 1
#> GSM247841 1 0 1 1 0
#> GSM247703 2 0 1 0 1
#> GSM247739 2 0 1 0 1
#> GSM247715 1 0 1 1 0
#> GSM247829 2 0 1 0 1
#> GSM247842 1 0 1 1 0
#> GSM247805 2 0 1 0 1
#> GSM247786 2 0 1 0 1
#> GSM247812 2 0 1 0 1
#> GSM247776 1 0 1 1 0
#> GSM247850 1 0 1 1 0
#> GSM247717 2 0 1 0 1
#> GSM247784 2 0 1 0 1
#> GSM247834 1 0 1 1 0
#> GSM247783 2 0 1 0 1
#> GSM247846 1 0 1 1 0
#> GSM247822 2 0 1 0 1
#> GSM247710 2 0 1 0 1
#> GSM247713 1 0 1 1 0
#> GSM247840 2 0 1 0 1
#> GSM247733 1 0 1 1 0
#> GSM247852 1 0 1 1 0
#> GSM247790 2 0 1 0 1
#> GSM247730 2 0 1 0 1
#> GSM247824 2 0 1 0 1
#> GSM247770 1 0 1 1 0
#> GSM247711 2 0 1 0 1
#> GSM247782 2 0 1 0 1
#> GSM247836 1 0 1 1 0
#> GSM247785 2 0 1 0 1
#> GSM247847 1 0 1 1 0
#> GSM247750 2 0 1 0 1
#> GSM247788 2 0 1 0 1
#> GSM247849 1 0 1 1 0
#> GSM247772 2 0 1 0 1
#> GSM247760 1 0 1 1 0
#> GSM247764 2 0 1 0 1
#> GSM247851 2 0 1 0 1
#> GSM247714 2 0 1 0 1
#> GSM247828 1 0 1 1 0
#> GSM247704 2 0 1 0 1
#> GSM247818 1 0 1 1 0
#> GSM247823 2 0 1 0 1
#> GSM247706 2 0 1 0 1
#> GSM247835 2 0 1 0 1
#> GSM247734 1 0 1 1 0
#> GSM247819 2 0 1 0 1
#> GSM247809 2 0 1 0 1
#> GSM247830 2 0 1 0 1
#> GSM247833 1 0 1 1 0
#> GSM247738 2 0 1 0 1
#> GSM247716 2 0 1 0 1
#> GSM247747 2 0 1 0 1
#> GSM247722 1 0 1 1 0
#> GSM247816 2 0 1 0 1
#> GSM247839 2 0 1 0 1
#> GSM247821 1 0 1 1 0
#> GSM247798 2 0 1 0 1
#> GSM247838 1 0 1 1 0
#> GSM247721 2 0 1 0 1
#> GSM247781 2 0 1 0 1
#> GSM247762 1 0 1 1 0
#> GSM247825 2 0 1 0 1
#> GSM247777 1 0 1 1 0
#> GSM247761 2 0 1 0 1
#> GSM247720 2 0 1 0 1
#> GSM247814 2 0 1 0 1
#> GSM247732 1 0 1 1 0
#> GSM247708 2 0 1 0 1
#> GSM247740 2 0 1 0 1
#> GSM247749 1 0 1 1 0
#> GSM247767 2 0 1 0 1
#> GSM247748 1 0 1 1 0
#> GSM247705 2 0 1 0 1
#> GSM247746 2 0 1 0 1
#> GSM247752 1 0 1 1 0
#> GSM247769 2 0 1 0 1
#> GSM247753 1 0 1 1 0
#> GSM247723 2 0 1 0 1
#> GSM247779 2 0 1 0 1
#> GSM247756 1 0 1 1 0
#> GSM247826 2 0 1 0 1
#> GSM247775 1 0 1 1 0
#> GSM247741 2 0 1 0 1
#> GSM247799 2 0 1 0 1
#> GSM247778 1 0 1 1 0
#> GSM247806 2 0 1 0 1
#> GSM247815 1 0 1 1 0
#> GSM247735 2 0 1 0 1
#> GSM247831 2 0 1 0 1
#> GSM247845 1 0 1 1 0
#> GSM247791 2 0 1 0 1
#> GSM247780 1 0 1 1 0
#> GSM247853 1 0 1 1 0
#> GSM247800 2 0 1 0 1
#> GSM247729 2 0 1 0 1
#> GSM247810 1 0 1 1 0
#> GSM247844 2 0 1 0 1
#> GSM247793 1 0 1 1 0
#> GSM247759 2 0 1 0 1
#> GSM247724 2 0 1 0 1
#> GSM247817 2 0 1 0 1
#> GSM247727 1 0 1 1 0
#> GSM247796 2 0 1 0 1
#> GSM247725 2 0 1 0 1
#> GSM247801 1 0 1 1 0
#> GSM247731 2 0 1 0 1
#> GSM247765 1 0 1 1 0
#> GSM247792 2 0 1 0 1
#> GSM247726 2 0 1 0 1
#> GSM247803 1 0 1 1 0
#> GSM247728 2 0 1 0 1
#> GSM247768 1 0 1 1 0
#> GSM247745 2 0 1 0 1
#> GSM247855 2 0 1 0 1
#> GSM247804 2 0 1 0 1
#> GSM247774 1 0 1 1 0
#> GSM247807 2 0 1 0 1
#> GSM247813 1 0 1 1 0
#> GSM247736 2 0 1 0 1
#> GSM247712 2 0 1 0 1
#> GSM247797 1 0 1 1 0
#> GSM247743 2 0 1 0 1
#> GSM247719 1 0 1 1 0
#> GSM247707 2 0 1 0 1
#> GSM247737 2 0 1 0 1
#> GSM247827 2 0 1 0 1
#> GSM247848 1 0 1 1 0
#> GSM247794 2 0 1 0 1
#> GSM247757 2 0 1 0 1
#> GSM247744 1 0 1 1 0
#> GSM247751 2 0 1 0 1
#> GSM247837 1 0 1 1 0
#> GSM247754 2 0 1 0 1
#> GSM247789 2 0 1 0 1
#> GSM247802 1 0 1 1 0
#> GSM247771 2 0 1 0 1
#> GSM247763 1 0 1 1 0
#> GSM247808 2 0 1 0 1
#> GSM247787 2 0 1 0 1
#> GSM247843 1 0 1 1 0
#> GSM247811 2 0 1 0 1
#> GSM247773 1 0 1 1 0
#> GSM247766 2 0 1 0 1
#> GSM247718 2 0 1 0 1
#> GSM247832 1 0 1 1 0
#> GSM247709 2 0 1 0 1
#> GSM247820 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0747 0.991 0 0.984 0.016
#> GSM247854 2 0.0747 0.991 0 0.984 0.016
#> GSM247758 2 0.0237 0.990 0 0.996 0.004
#> GSM247742 1 0.0000 1.000 1 0.000 0.000
#> GSM247755 3 0.0000 1.000 0 0.000 1.000
#> GSM247841 1 0.0000 1.000 1 0.000 0.000
#> GSM247703 2 0.0747 0.991 0 0.984 0.016
#> GSM247739 2 0.0237 0.990 0 0.996 0.004
#> GSM247715 1 0.0000 1.000 1 0.000 0.000
#> GSM247829 3 0.0000 1.000 0 0.000 1.000
#> GSM247842 1 0.0000 1.000 1 0.000 0.000
#> GSM247805 2 0.0747 0.991 0 0.984 0.016
#> GSM247786 2 0.0237 0.990 0 0.996 0.004
#> GSM247812 3 0.0000 1.000 0 0.000 1.000
#> GSM247776 1 0.0000 1.000 1 0.000 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0.000
#> GSM247717 2 0.0747 0.991 0 0.984 0.016
#> GSM247784 2 0.0237 0.990 0 0.996 0.004
#> GSM247834 1 0.0000 1.000 1 0.000 0.000
#> GSM247783 3 0.0000 1.000 0 0.000 1.000
#> GSM247846 1 0.0000 1.000 1 0.000 0.000
#> GSM247822 2 0.0747 0.991 0 0.984 0.016
#> GSM247710 2 0.0237 0.990 0 0.996 0.004
#> GSM247713 1 0.0000 1.000 1 0.000 0.000
#> GSM247840 3 0.0000 1.000 0 0.000 1.000
#> GSM247733 1 0.0000 1.000 1 0.000 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0.000
#> GSM247790 2 0.0747 0.991 0 0.984 0.016
#> GSM247730 2 0.0237 0.990 0 0.996 0.004
#> GSM247824 3 0.0000 1.000 0 0.000 1.000
#> GSM247770 1 0.0000 1.000 1 0.000 0.000
#> GSM247711 2 0.0747 0.991 0 0.984 0.016
#> GSM247782 2 0.0237 0.990 0 0.996 0.004
#> GSM247836 1 0.0000 1.000 1 0.000 0.000
#> GSM247785 3 0.0000 1.000 0 0.000 1.000
#> GSM247847 1 0.0000 1.000 1 0.000 0.000
#> GSM247750 2 0.0747 0.991 0 0.984 0.016
#> GSM247788 2 0.0237 0.990 0 0.996 0.004
#> GSM247849 1 0.0000 1.000 1 0.000 0.000
#> GSM247772 3 0.0000 1.000 0 0.000 1.000
#> GSM247760 1 0.0000 1.000 1 0.000 0.000
#> GSM247764 2 0.0747 0.991 0 0.984 0.016
#> GSM247851 2 0.0747 0.991 0 0.984 0.016
#> GSM247714 2 0.0237 0.990 0 0.996 0.004
#> GSM247828 1 0.0000 1.000 1 0.000 0.000
#> GSM247704 3 0.0000 1.000 0 0.000 1.000
#> GSM247818 1 0.0000 1.000 1 0.000 0.000
#> GSM247823 2 0.0747 0.991 0 0.984 0.016
#> GSM247706 2 0.0237 0.990 0 0.996 0.004
#> GSM247835 3 0.0000 1.000 0 0.000 1.000
#> GSM247734 1 0.0000 1.000 1 0.000 0.000
#> GSM247819 2 0.0747 0.991 0 0.984 0.016
#> GSM247809 2 0.0237 0.990 0 0.996 0.004
#> GSM247830 3 0.0000 1.000 0 0.000 1.000
#> GSM247833 1 0.0000 1.000 1 0.000 0.000
#> GSM247738 2 0.0747 0.991 0 0.984 0.016
#> GSM247716 2 0.0237 0.990 0 0.996 0.004
#> GSM247747 3 0.0000 1.000 0 0.000 1.000
#> GSM247722 1 0.0000 1.000 1 0.000 0.000
#> GSM247816 2 0.0747 0.991 0 0.984 0.016
#> GSM247839 2 0.0237 0.990 0 0.996 0.004
#> GSM247821 1 0.0000 1.000 1 0.000 0.000
#> GSM247798 3 0.0000 1.000 0 0.000 1.000
#> GSM247838 1 0.0000 1.000 1 0.000 0.000
#> GSM247721 2 0.0747 0.991 0 0.984 0.016
#> GSM247781 2 0.0237 0.990 0 0.996 0.004
#> GSM247762 1 0.0000 1.000 1 0.000 0.000
#> GSM247825 3 0.0000 1.000 0 0.000 1.000
#> GSM247777 1 0.0000 1.000 1 0.000 0.000
#> GSM247761 2 0.0747 0.991 0 0.984 0.016
#> GSM247720 2 0.0237 0.990 0 0.996 0.004
#> GSM247814 3 0.0000 1.000 0 0.000 1.000
#> GSM247732 1 0.0000 1.000 1 0.000 0.000
#> GSM247708 2 0.0747 0.991 0 0.984 0.016
#> GSM247740 2 0.0237 0.990 0 0.996 0.004
#> GSM247749 1 0.0000 1.000 1 0.000 0.000
#> GSM247767 3 0.0000 1.000 0 0.000 1.000
#> GSM247748 1 0.0000 1.000 1 0.000 0.000
#> GSM247705 2 0.0747 0.991 0 0.984 0.016
#> GSM247746 2 0.0237 0.990 0 0.996 0.004
#> GSM247752 1 0.0000 1.000 1 0.000 0.000
#> GSM247769 3 0.0000 1.000 0 0.000 1.000
#> GSM247753 1 0.0000 1.000 1 0.000 0.000
#> GSM247723 2 0.0747 0.991 0 0.984 0.016
#> GSM247779 2 0.0237 0.990 0 0.996 0.004
#> GSM247756 1 0.0000 1.000 1 0.000 0.000
#> GSM247826 3 0.0000 1.000 0 0.000 1.000
#> GSM247775 1 0.0000 1.000 1 0.000 0.000
#> GSM247741 2 0.0747 0.991 0 0.984 0.016
#> GSM247799 2 0.0237 0.990 0 0.996 0.004
#> GSM247778 1 0.0000 1.000 1 0.000 0.000
#> GSM247806 3 0.0000 1.000 0 0.000 1.000
#> GSM247815 1 0.0000 1.000 1 0.000 0.000
#> GSM247735 2 0.0747 0.991 0 0.984 0.016
#> GSM247831 2 0.0237 0.990 0 0.996 0.004
#> GSM247845 1 0.0000 1.000 1 0.000 0.000
#> GSM247791 3 0.0000 1.000 0 0.000 1.000
#> GSM247780 1 0.0000 1.000 1 0.000 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0.000
#> GSM247800 2 0.0747 0.991 0 0.984 0.016
#> GSM247729 2 0.0237 0.990 0 0.996 0.004
#> GSM247810 1 0.0000 1.000 1 0.000 0.000
#> GSM247844 3 0.0000 1.000 0 0.000 1.000
#> GSM247793 1 0.0000 1.000 1 0.000 0.000
#> GSM247759 2 0.0747 0.991 0 0.984 0.016
#> GSM247724 2 0.0237 0.990 0 0.996 0.004
#> GSM247817 3 0.0000 1.000 0 0.000 1.000
#> GSM247727 1 0.0000 1.000 1 0.000 0.000
#> GSM247796 2 0.0747 0.991 0 0.984 0.016
#> GSM247725 2 0.0237 0.990 0 0.996 0.004
#> GSM247801 1 0.0000 1.000 1 0.000 0.000
#> GSM247731 3 0.0000 1.000 0 0.000 1.000
#> GSM247765 1 0.0000 1.000 1 0.000 0.000
#> GSM247792 2 0.0747 0.991 0 0.984 0.016
#> GSM247726 2 0.0237 0.990 0 0.996 0.004
#> GSM247803 1 0.0000 1.000 1 0.000 0.000
#> GSM247728 3 0.0000 1.000 0 0.000 1.000
#> GSM247768 1 0.0000 1.000 1 0.000 0.000
#> GSM247745 2 0.0747 0.991 0 0.984 0.016
#> GSM247855 2 0.0747 0.991 0 0.984 0.016
#> GSM247804 2 0.0237 0.990 0 0.996 0.004
#> GSM247774 1 0.0000 1.000 1 0.000 0.000
#> GSM247807 3 0.0000 1.000 0 0.000 1.000
#> GSM247813 1 0.0000 1.000 1 0.000 0.000
#> GSM247736 2 0.0747 0.991 0 0.984 0.016
#> GSM247712 2 0.0237 0.990 0 0.996 0.004
#> GSM247797 1 0.0000 1.000 1 0.000 0.000
#> GSM247743 3 0.0000 1.000 0 0.000 1.000
#> GSM247719 1 0.0000 1.000 1 0.000 0.000
#> GSM247707 2 0.0747 0.991 0 0.984 0.016
#> GSM247737 2 0.0237 0.990 0 0.996 0.004
#> GSM247827 3 0.0000 1.000 0 0.000 1.000
#> GSM247848 1 0.0000 1.000 1 0.000 0.000
#> GSM247794 2 0.0747 0.991 0 0.984 0.016
#> GSM247757 2 0.0237 0.990 0 0.996 0.004
#> GSM247744 1 0.0000 1.000 1 0.000 0.000
#> GSM247751 3 0.0000 1.000 0 0.000 1.000
#> GSM247837 1 0.0000 1.000 1 0.000 0.000
#> GSM247754 2 0.0747 0.991 0 0.984 0.016
#> GSM247789 2 0.0237 0.990 0 0.996 0.004
#> GSM247802 1 0.0000 1.000 1 0.000 0.000
#> GSM247771 3 0.0000 1.000 0 0.000 1.000
#> GSM247763 1 0.0000 1.000 1 0.000 0.000
#> GSM247808 2 0.0747 0.991 0 0.984 0.016
#> GSM247787 2 0.0237 0.990 0 0.996 0.004
#> GSM247843 1 0.0000 1.000 1 0.000 0.000
#> GSM247811 3 0.0000 1.000 0 0.000 1.000
#> GSM247773 1 0.0000 1.000 1 0.000 0.000
#> GSM247766 2 0.0747 0.991 0 0.984 0.016
#> GSM247718 2 0.0237 0.990 0 0.996 0.004
#> GSM247832 1 0.0000 1.000 1 0.000 0.000
#> GSM247709 3 0.0000 1.000 0 0.000 1.000
#> GSM247820 1 0.0000 1.000 1 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247854 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247758 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247742 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247755 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247841 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247703 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247739 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247715 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247829 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247842 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247805 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247786 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247812 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247776 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247850 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247717 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247784 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247834 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247783 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247846 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247822 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247710 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247713 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247840 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247733 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247852 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247790 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247730 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247824 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247770 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247711 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247782 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247836 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247785 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247847 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247750 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247788 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247849 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247772 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247760 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247764 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247851 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247714 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247828 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247704 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247818 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247823 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247706 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247835 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247734 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247819 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247809 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247830 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247833 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247738 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247716 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247747 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247722 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247816 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247839 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247821 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247798 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247838 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247721 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247781 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247762 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247825 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247777 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247761 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247720 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247814 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247732 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247708 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247740 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247749 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247767 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247748 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247705 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247746 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247752 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247769 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247753 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247723 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247779 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247756 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247826 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247775 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247741 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247799 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247778 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247806 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247815 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247735 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247831 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247845 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247791 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247780 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247853 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247800 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247729 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247810 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247844 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247793 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247759 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247724 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247817 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247727 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247796 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247725 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247801 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247731 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247765 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247792 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247726 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247803 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247728 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247768 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247745 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247855 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247804 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247774 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247807 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247813 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247736 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247712 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247797 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247743 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247719 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247707 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247737 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247827 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247848 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247794 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247757 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247744 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247751 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247837 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247754 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247789 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247802 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247771 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247763 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247808 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247787 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247843 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247811 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247773 1 0.000 0.952 1.00 0.00 0.000 0.000
#> GSM247766 2 0.305 1.000 0.00 0.86 0.004 0.136
#> GSM247718 4 0.000 1.000 0.00 0.00 0.000 1.000
#> GSM247832 1 0.292 0.928 0.86 0.14 0.000 0.000
#> GSM247709 3 0.000 1.000 0.00 0.00 1.000 0.000
#> GSM247820 1 0.000 0.952 1.00 0.00 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247854 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247758 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247742 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247755 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247841 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247703 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247739 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247715 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247829 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247842 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247805 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247786 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247812 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247776 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247850 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247717 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247784 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247834 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247783 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247846 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247822 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247710 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247713 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247840 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247733 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247852 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247790 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247730 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247824 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247770 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247711 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247782 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247836 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247785 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247847 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247750 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247788 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247849 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247772 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247760 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247764 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247851 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247714 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247828 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247704 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247818 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247823 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247706 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247835 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247734 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247819 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247809 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247830 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247833 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247738 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247716 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247747 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247722 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247816 2 0.0162 0.997 0.000 0.996 0 0.004 0
#> GSM247839 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247821 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247798 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247838 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247721 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247781 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247762 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247825 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247777 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247761 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247720 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247814 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247732 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247708 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247740 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247749 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247767 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247748 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247705 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247746 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247752 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247769 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247753 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247723 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247779 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247756 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247826 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247775 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247741 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247799 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247778 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247806 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247815 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247735 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247831 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247845 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247791 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247780 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247853 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247800 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247729 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247810 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247844 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247793 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247759 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247724 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247817 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247727 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247796 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247725 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247801 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247731 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247765 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247792 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247726 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247803 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247728 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247768 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247745 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247855 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247804 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247774 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247807 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247813 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247736 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247712 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247797 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247743 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247719 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247707 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247737 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247827 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247848 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247794 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247757 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247744 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247751 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247837 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247754 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247789 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247802 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247771 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247763 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247808 2 0.0000 0.997 0.000 1.000 0 0.000 0
#> GSM247787 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247843 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247811 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247773 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247766 2 0.0290 0.997 0.000 0.992 0 0.008 0
#> GSM247718 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247832 4 0.0290 1.000 0.008 0.000 0 0.992 0
#> GSM247709 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247820 1 0.0000 1.000 1.000 0.000 0 0.000 0
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.2491 0.913 0 0.836 0 0 0.000 0.164
#> GSM247854 2 0.2491 0.913 0 0.836 0 0 0.000 0.164
#> GSM247758 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247742 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247755 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247841 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247703 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247739 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247715 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247829 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247842 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247805 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247786 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247812 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247776 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247717 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247784 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247834 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247783 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247846 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247822 2 0.1267 0.893 0 0.940 0 0 0.000 0.060
#> GSM247710 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247713 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247840 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247733 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247790 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247730 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247824 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247770 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247711 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247782 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247836 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247785 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247847 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247750 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247788 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247849 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247772 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247760 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247764 2 0.0547 0.885 0 0.980 0 0 0.000 0.020
#> GSM247851 2 0.0547 0.885 0 0.980 0 0 0.000 0.020
#> GSM247714 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247828 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247704 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247818 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247823 2 0.0000 0.891 0 1.000 0 0 0.000 0.000
#> GSM247706 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247835 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247734 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247819 2 0.0547 0.885 0 0.980 0 0 0.000 0.020
#> GSM247809 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247830 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247833 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247738 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247716 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247747 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247722 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247816 2 0.2178 0.910 0 0.868 0 0 0.000 0.132
#> GSM247839 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247821 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247798 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247838 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247721 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247781 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247762 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247825 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247777 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247761 2 0.2562 0.913 0 0.828 0 0 0.000 0.172
#> GSM247720 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247814 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247732 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247708 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247740 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247749 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247767 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247748 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247705 2 0.0000 0.891 0 1.000 0 0 0.000 0.000
#> GSM247746 6 0.2762 1.000 0 0.000 0 0 0.196 0.804
#> GSM247752 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247769 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247753 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247723 2 0.0547 0.885 0 0.980 0 0 0.000 0.020
#> GSM247779 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247756 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247826 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247775 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247741 2 0.0547 0.885 0 0.980 0 0 0.000 0.020
#> GSM247799 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247778 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247806 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247815 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247735 2 0.0547 0.885 0 0.980 0 0 0.000 0.020
#> GSM247831 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247845 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247791 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247780 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247800 2 0.0547 0.885 0 0.980 0 0 0.000 0.020
#> GSM247729 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247810 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247844 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247793 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247759 2 0.0000 0.891 0 1.000 0 0 0.000 0.000
#> GSM247724 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247817 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247727 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247796 2 0.0547 0.885 0 0.980 0 0 0.000 0.020
#> GSM247725 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247801 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247731 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247765 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247792 2 0.0547 0.885 0 0.980 0 0 0.000 0.020
#> GSM247726 6 0.2762 1.000 0 0.000 0 0 0.196 0.804
#> GSM247803 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247728 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247768 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247745 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247855 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247804 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247774 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247807 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247813 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247736 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247712 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247797 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247743 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247719 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247707 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247737 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247827 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247848 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247794 2 0.2597 0.913 0 0.824 0 0 0.000 0.176
#> GSM247757 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247744 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247751 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247837 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247754 2 0.0260 0.889 0 0.992 0 0 0.000 0.008
#> GSM247789 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247802 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247771 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247763 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247808 2 0.2664 0.913 0 0.816 0 0 0.000 0.184
#> GSM247787 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247843 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247811 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247773 1 0.0000 1.000 1 0.000 0 0 0.000 0.000
#> GSM247766 2 0.0547 0.885 0 0.980 0 0 0.000 0.020
#> GSM247718 5 0.0000 1.000 0 0.000 0 0 1.000 0.000
#> GSM247832 4 0.0000 1.000 0 0.000 0 1 0.000 0.000
#> GSM247709 3 0.0000 1.000 0 0.000 1 0 0.000 0.000
#> GSM247820 1 0.0000 1.000 1 0.000 0 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> CV:skmeans 153 1 1.000 4.63e-32 2
#> CV:skmeans 153 1 0.985 2.17e-61 3
#> CV:skmeans 153 1 0.996 1.16e-90 4
#> CV:skmeans 153 1 0.989 6.51e-120 5
#> CV:skmeans 153 1 0.662 8.52e-117 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.
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 19559 rows and 153 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.977 0.989 0.4557 0.540 0.540
#> 3 3 1.000 0.975 0.988 0.4000 0.819 0.664
#> 4 4 1.000 1.000 1.000 0.1150 0.920 0.779
#> 5 5 1.000 1.000 1.000 0.1273 0.909 0.686
#> 6 6 0.979 0.965 0.967 0.0271 0.977 0.885
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0.0000 0.996 0.000 1.000
#> GSM247854 2 0.0000 0.996 0.000 1.000
#> GSM247758 2 0.0000 0.996 0.000 1.000
#> GSM247742 1 0.0000 0.975 1.000 0.000
#> GSM247755 2 0.0000 0.996 0.000 1.000
#> GSM247841 1 0.0000 0.975 1.000 0.000
#> GSM247703 2 0.0000 0.996 0.000 1.000
#> GSM247739 2 0.0000 0.996 0.000 1.000
#> GSM247715 1 0.0000 0.975 1.000 0.000
#> GSM247829 2 0.0000 0.996 0.000 1.000
#> GSM247842 1 0.0000 0.975 1.000 0.000
#> GSM247805 2 0.0000 0.996 0.000 1.000
#> GSM247786 2 0.0000 0.996 0.000 1.000
#> GSM247812 2 0.0000 0.996 0.000 1.000
#> GSM247776 1 0.0000 0.975 1.000 0.000
#> GSM247850 1 0.0000 0.975 1.000 0.000
#> GSM247717 2 0.0000 0.996 0.000 1.000
#> GSM247784 2 0.0000 0.996 0.000 1.000
#> GSM247834 1 0.6801 0.803 0.820 0.180
#> GSM247783 2 0.0000 0.996 0.000 1.000
#> GSM247846 1 0.0000 0.975 1.000 0.000
#> GSM247822 2 0.0000 0.996 0.000 1.000
#> GSM247710 2 0.0000 0.996 0.000 1.000
#> GSM247713 1 0.5408 0.868 0.876 0.124
#> GSM247840 2 0.0000 0.996 0.000 1.000
#> GSM247733 1 0.0000 0.975 1.000 0.000
#> GSM247852 1 0.0000 0.975 1.000 0.000
#> GSM247790 2 0.0000 0.996 0.000 1.000
#> GSM247730 2 0.0000 0.996 0.000 1.000
#> GSM247824 2 0.0000 0.996 0.000 1.000
#> GSM247770 1 0.0000 0.975 1.000 0.000
#> GSM247711 2 0.0000 0.996 0.000 1.000
#> GSM247782 2 0.0000 0.996 0.000 1.000
#> GSM247836 1 0.0000 0.975 1.000 0.000
#> GSM247785 2 0.0000 0.996 0.000 1.000
#> GSM247847 1 0.0000 0.975 1.000 0.000
#> GSM247750 2 0.0000 0.996 0.000 1.000
#> GSM247788 2 0.0000 0.996 0.000 1.000
#> GSM247849 1 0.0000 0.975 1.000 0.000
#> GSM247772 2 0.0000 0.996 0.000 1.000
#> GSM247760 1 0.0000 0.975 1.000 0.000
#> GSM247764 2 0.0000 0.996 0.000 1.000
#> GSM247851 2 0.0000 0.996 0.000 1.000
#> GSM247714 2 0.0000 0.996 0.000 1.000
#> GSM247828 1 0.0000 0.975 1.000 0.000
#> GSM247704 2 0.0000 0.996 0.000 1.000
#> GSM247818 1 0.0000 0.975 1.000 0.000
#> GSM247823 2 0.0000 0.996 0.000 1.000
#> GSM247706 2 0.0000 0.996 0.000 1.000
#> GSM247835 2 0.0000 0.996 0.000 1.000
#> GSM247734 1 0.0000 0.975 1.000 0.000
#> GSM247819 2 0.0000 0.996 0.000 1.000
#> GSM247809 2 0.0000 0.996 0.000 1.000
#> GSM247830 2 0.0000 0.996 0.000 1.000
#> GSM247833 1 0.0000 0.975 1.000 0.000
#> GSM247738 2 0.0000 0.996 0.000 1.000
#> GSM247716 2 0.0000 0.996 0.000 1.000
#> GSM247747 2 0.0000 0.996 0.000 1.000
#> GSM247722 1 0.0000 0.975 1.000 0.000
#> GSM247816 2 0.0000 0.996 0.000 1.000
#> GSM247839 2 0.0000 0.996 0.000 1.000
#> GSM247821 1 0.0000 0.975 1.000 0.000
#> GSM247798 2 0.0000 0.996 0.000 1.000
#> GSM247838 1 0.0000 0.975 1.000 0.000
#> GSM247721 2 0.0000 0.996 0.000 1.000
#> GSM247781 2 0.0000 0.996 0.000 1.000
#> GSM247762 2 0.9323 0.435 0.348 0.652
#> GSM247825 2 0.0000 0.996 0.000 1.000
#> GSM247777 1 0.0000 0.975 1.000 0.000
#> GSM247761 2 0.0000 0.996 0.000 1.000
#> GSM247720 2 0.0000 0.996 0.000 1.000
#> GSM247814 2 0.0000 0.996 0.000 1.000
#> GSM247732 1 0.0000 0.975 1.000 0.000
#> GSM247708 2 0.0000 0.996 0.000 1.000
#> GSM247740 2 0.0000 0.996 0.000 1.000
#> GSM247749 1 0.4161 0.906 0.916 0.084
#> GSM247767 2 0.0000 0.996 0.000 1.000
#> GSM247748 1 0.0000 0.975 1.000 0.000
#> GSM247705 2 0.0000 0.996 0.000 1.000
#> GSM247746 2 0.0000 0.996 0.000 1.000
#> GSM247752 2 0.0000 0.996 0.000 1.000
#> GSM247769 2 0.0000 0.996 0.000 1.000
#> GSM247753 1 0.0000 0.975 1.000 0.000
#> GSM247723 2 0.0000 0.996 0.000 1.000
#> GSM247779 2 0.0000 0.996 0.000 1.000
#> GSM247756 1 0.0000 0.975 1.000 0.000
#> GSM247826 2 0.0000 0.996 0.000 1.000
#> GSM247775 1 0.0000 0.975 1.000 0.000
#> GSM247741 2 0.0000 0.996 0.000 1.000
#> GSM247799 2 0.0000 0.996 0.000 1.000
#> GSM247778 1 0.0000 0.975 1.000 0.000
#> GSM247806 2 0.0000 0.996 0.000 1.000
#> GSM247815 1 0.0000 0.975 1.000 0.000
#> GSM247735 2 0.0000 0.996 0.000 1.000
#> GSM247831 2 0.0000 0.996 0.000 1.000
#> GSM247845 1 0.0000 0.975 1.000 0.000
#> GSM247791 2 0.0000 0.996 0.000 1.000
#> GSM247780 1 0.0000 0.975 1.000 0.000
#> GSM247853 1 0.0000 0.975 1.000 0.000
#> GSM247800 2 0.0000 0.996 0.000 1.000
#> GSM247729 2 0.0000 0.996 0.000 1.000
#> GSM247810 1 0.7056 0.787 0.808 0.192
#> GSM247844 2 0.0000 0.996 0.000 1.000
#> GSM247793 1 0.0000 0.975 1.000 0.000
#> GSM247759 2 0.0000 0.996 0.000 1.000
#> GSM247724 2 0.0000 0.996 0.000 1.000
#> GSM247817 2 0.0000 0.996 0.000 1.000
#> GSM247727 1 0.0000 0.975 1.000 0.000
#> GSM247796 2 0.0000 0.996 0.000 1.000
#> GSM247725 2 0.0000 0.996 0.000 1.000
#> GSM247801 1 0.7883 0.721 0.764 0.236
#> GSM247731 2 0.0000 0.996 0.000 1.000
#> GSM247765 1 0.0000 0.975 1.000 0.000
#> GSM247792 2 0.0000 0.996 0.000 1.000
#> GSM247726 2 0.0000 0.996 0.000 1.000
#> GSM247803 2 0.0000 0.996 0.000 1.000
#> GSM247728 2 0.0000 0.996 0.000 1.000
#> GSM247768 1 0.0000 0.975 1.000 0.000
#> GSM247745 2 0.0000 0.996 0.000 1.000
#> GSM247855 2 0.0000 0.996 0.000 1.000
#> GSM247804 2 0.0000 0.996 0.000 1.000
#> GSM247774 1 0.7219 0.776 0.800 0.200
#> GSM247807 2 0.0000 0.996 0.000 1.000
#> GSM247813 1 0.0000 0.975 1.000 0.000
#> GSM247736 2 0.0000 0.996 0.000 1.000
#> GSM247712 2 0.0000 0.996 0.000 1.000
#> GSM247797 1 0.6438 0.823 0.836 0.164
#> GSM247743 2 0.0000 0.996 0.000 1.000
#> GSM247719 1 0.0000 0.975 1.000 0.000
#> GSM247707 2 0.0000 0.996 0.000 1.000
#> GSM247737 2 0.0000 0.996 0.000 1.000
#> GSM247827 2 0.0000 0.996 0.000 1.000
#> GSM247848 1 0.0000 0.975 1.000 0.000
#> GSM247794 2 0.0000 0.996 0.000 1.000
#> GSM247757 2 0.0000 0.996 0.000 1.000
#> GSM247744 1 0.5737 0.855 0.864 0.136
#> GSM247751 2 0.0000 0.996 0.000 1.000
#> GSM247837 1 0.0000 0.975 1.000 0.000
#> GSM247754 2 0.0000 0.996 0.000 1.000
#> GSM247789 2 0.0000 0.996 0.000 1.000
#> GSM247802 1 0.0672 0.969 0.992 0.008
#> GSM247771 2 0.0000 0.996 0.000 1.000
#> GSM247763 1 0.0000 0.975 1.000 0.000
#> GSM247808 2 0.0000 0.996 0.000 1.000
#> GSM247787 2 0.0000 0.996 0.000 1.000
#> GSM247843 1 0.0000 0.975 1.000 0.000
#> GSM247811 2 0.0000 0.996 0.000 1.000
#> GSM247773 1 0.0000 0.975 1.000 0.000
#> GSM247766 2 0.0000 0.996 0.000 1.000
#> GSM247718 2 0.0000 0.996 0.000 1.000
#> GSM247832 1 0.0000 0.975 1.000 0.000
#> GSM247709 2 0.0000 0.996 0.000 1.000
#> GSM247820 1 0.0000 0.975 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247854 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247758 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247742 1 0.2537 0.897 0.920 0.080 0.000
#> GSM247755 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247841 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247703 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247739 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247715 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247829 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247842 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247805 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247786 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247812 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247776 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247850 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247717 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247784 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247834 1 0.5291 0.683 0.732 0.268 0.000
#> GSM247783 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247846 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247822 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247710 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247713 1 0.4291 0.796 0.820 0.180 0.000
#> GSM247840 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247733 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247852 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247790 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247730 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247824 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247770 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247711 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247782 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247836 1 0.0592 0.953 0.988 0.012 0.000
#> GSM247785 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247847 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247750 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247788 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247849 1 0.0747 0.950 0.984 0.016 0.000
#> GSM247772 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247760 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247764 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247851 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247714 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247828 1 0.0237 0.958 0.996 0.004 0.000
#> GSM247704 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247818 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247823 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247706 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247835 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247734 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247819 2 0.0237 0.996 0.000 0.996 0.004
#> GSM247809 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247830 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247833 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247738 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247716 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247747 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247722 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247816 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247839 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247821 1 0.1860 0.923 0.948 0.052 0.000
#> GSM247798 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247838 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247721 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247781 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247762 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247825 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247777 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247761 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247720 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247814 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247732 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247708 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247740 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247749 1 0.4654 0.764 0.792 0.208 0.000
#> GSM247767 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247748 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247705 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247746 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247752 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247769 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247753 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247723 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247779 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247756 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247826 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247775 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247741 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247799 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247778 1 0.0592 0.953 0.988 0.012 0.000
#> GSM247806 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247815 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247735 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247831 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247845 1 0.0237 0.958 0.996 0.004 0.000
#> GSM247791 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247780 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247853 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247800 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247729 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247810 1 0.5291 0.683 0.732 0.268 0.000
#> GSM247844 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247793 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247759 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247724 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247817 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247727 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247796 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247725 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247801 1 0.4842 0.744 0.776 0.224 0.000
#> GSM247731 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247765 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247792 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247726 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247803 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247728 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247768 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247745 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247855 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247804 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247774 1 0.4002 0.818 0.840 0.160 0.000
#> GSM247807 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247813 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247736 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247712 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247797 1 0.4452 0.783 0.808 0.192 0.000
#> GSM247743 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247719 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247707 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247737 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247827 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247848 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247794 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247757 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247744 1 0.1860 0.923 0.948 0.052 0.000
#> GSM247751 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247837 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247754 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247789 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247802 1 0.1753 0.926 0.952 0.048 0.000
#> GSM247771 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247763 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247808 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247787 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247843 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247811 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247773 1 0.0000 0.960 1.000 0.000 0.000
#> GSM247766 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247718 2 0.0000 1.000 0.000 1.000 0.000
#> GSM247832 1 0.0237 0.958 0.996 0.004 0.000
#> GSM247709 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247820 1 0.0000 0.960 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0 1 0 1 0 0
#> GSM247854 2 0 1 0 1 0 0
#> GSM247758 2 0 1 0 1 0 0
#> GSM247742 4 0 1 0 0 0 1
#> GSM247755 3 0 1 0 0 1 0
#> GSM247841 1 0 1 1 0 0 0
#> GSM247703 2 0 1 0 1 0 0
#> GSM247739 2 0 1 0 1 0 0
#> GSM247715 4 0 1 0 0 0 1
#> GSM247829 3 0 1 0 0 1 0
#> GSM247842 1 0 1 1 0 0 0
#> GSM247805 2 0 1 0 1 0 0
#> GSM247786 2 0 1 0 1 0 0
#> GSM247812 3 0 1 0 0 1 0
#> GSM247776 1 0 1 1 0 0 0
#> GSM247850 1 0 1 1 0 0 0
#> GSM247717 2 0 1 0 1 0 0
#> GSM247784 2 0 1 0 1 0 0
#> GSM247834 4 0 1 0 0 0 1
#> GSM247783 3 0 1 0 0 1 0
#> GSM247846 1 0 1 1 0 0 0
#> GSM247822 2 0 1 0 1 0 0
#> GSM247710 2 0 1 0 1 0 0
#> GSM247713 4 0 1 0 0 0 1
#> GSM247840 3 0 1 0 0 1 0
#> GSM247733 1 0 1 1 0 0 0
#> GSM247852 1 0 1 1 0 0 0
#> GSM247790 2 0 1 0 1 0 0
#> GSM247730 2 0 1 0 1 0 0
#> GSM247824 3 0 1 0 0 1 0
#> GSM247770 1 0 1 1 0 0 0
#> GSM247711 2 0 1 0 1 0 0
#> GSM247782 2 0 1 0 1 0 0
#> GSM247836 4 0 1 0 0 0 1
#> GSM247785 3 0 1 0 0 1 0
#> GSM247847 1 0 1 1 0 0 0
#> GSM247750 2 0 1 0 1 0 0
#> GSM247788 2 0 1 0 1 0 0
#> GSM247849 4 0 1 0 0 0 1
#> GSM247772 3 0 1 0 0 1 0
#> GSM247760 1 0 1 1 0 0 0
#> GSM247764 2 0 1 0 1 0 0
#> GSM247851 2 0 1 0 1 0 0
#> GSM247714 2 0 1 0 1 0 0
#> GSM247828 4 0 1 0 0 0 1
#> GSM247704 3 0 1 0 0 1 0
#> GSM247818 1 0 1 1 0 0 0
#> GSM247823 2 0 1 0 1 0 0
#> GSM247706 2 0 1 0 1 0 0
#> GSM247835 3 0 1 0 0 1 0
#> GSM247734 1 0 1 1 0 0 0
#> GSM247819 2 0 1 0 1 0 0
#> GSM247809 2 0 1 0 1 0 0
#> GSM247830 3 0 1 0 0 1 0
#> GSM247833 1 0 1 1 0 0 0
#> GSM247738 2 0 1 0 1 0 0
#> GSM247716 2 0 1 0 1 0 0
#> GSM247747 3 0 1 0 0 1 0
#> GSM247722 1 0 1 1 0 0 0
#> GSM247816 2 0 1 0 1 0 0
#> GSM247839 2 0 1 0 1 0 0
#> GSM247821 4 0 1 0 0 0 1
#> GSM247798 3 0 1 0 0 1 0
#> GSM247838 1 0 1 1 0 0 0
#> GSM247721 2 0 1 0 1 0 0
#> GSM247781 2 0 1 0 1 0 0
#> GSM247762 4 0 1 0 0 0 1
#> GSM247825 3 0 1 0 0 1 0
#> GSM247777 1 0 1 1 0 0 0
#> GSM247761 2 0 1 0 1 0 0
#> GSM247720 2 0 1 0 1 0 0
#> GSM247814 3 0 1 0 0 1 0
#> GSM247732 1 0 1 1 0 0 0
#> GSM247708 2 0 1 0 1 0 0
#> GSM247740 2 0 1 0 1 0 0
#> GSM247749 4 0 1 0 0 0 1
#> GSM247767 3 0 1 0 0 1 0
#> GSM247748 1 0 1 1 0 0 0
#> GSM247705 2 0 1 0 1 0 0
#> GSM247746 2 0 1 0 1 0 0
#> GSM247752 4 0 1 0 0 0 1
#> GSM247769 3 0 1 0 0 1 0
#> GSM247753 1 0 1 1 0 0 0
#> GSM247723 2 0 1 0 1 0 0
#> GSM247779 2 0 1 0 1 0 0
#> GSM247756 4 0 1 0 0 0 1
#> GSM247826 3 0 1 0 0 1 0
#> GSM247775 1 0 1 1 0 0 0
#> GSM247741 2 0 1 0 1 0 0
#> GSM247799 2 0 1 0 1 0 0
#> GSM247778 4 0 1 0 0 0 1
#> GSM247806 3 0 1 0 0 1 0
#> GSM247815 1 0 1 1 0 0 0
#> GSM247735 2 0 1 0 1 0 0
#> GSM247831 2 0 1 0 1 0 0
#> GSM247845 4 0 1 0 0 0 1
#> GSM247791 3 0 1 0 0 1 0
#> GSM247780 1 0 1 1 0 0 0
#> GSM247853 1 0 1 1 0 0 0
#> GSM247800 2 0 1 0 1 0 0
#> GSM247729 2 0 1 0 1 0 0
#> GSM247810 4 0 1 0 0 0 1
#> GSM247844 3 0 1 0 0 1 0
#> GSM247793 1 0 1 1 0 0 0
#> GSM247759 2 0 1 0 1 0 0
#> GSM247724 2 0 1 0 1 0 0
#> GSM247817 3 0 1 0 0 1 0
#> GSM247727 1 0 1 1 0 0 0
#> GSM247796 2 0 1 0 1 0 0
#> GSM247725 2 0 1 0 1 0 0
#> GSM247801 4 0 1 0 0 0 1
#> GSM247731 3 0 1 0 0 1 0
#> GSM247765 1 0 1 1 0 0 0
#> GSM247792 2 0 1 0 1 0 0
#> GSM247726 2 0 1 0 1 0 0
#> GSM247803 4 0 1 0 0 0 1
#> GSM247728 3 0 1 0 0 1 0
#> GSM247768 1 0 1 1 0 0 0
#> GSM247745 2 0 1 0 1 0 0
#> GSM247855 2 0 1 0 1 0 0
#> GSM247804 2 0 1 0 1 0 0
#> GSM247774 4 0 1 0 0 0 1
#> GSM247807 3 0 1 0 0 1 0
#> GSM247813 1 0 1 1 0 0 0
#> GSM247736 2 0 1 0 1 0 0
#> GSM247712 2 0 1 0 1 0 0
#> GSM247797 4 0 1 0 0 0 1
#> GSM247743 3 0 1 0 0 1 0
#> GSM247719 1 0 1 1 0 0 0
#> GSM247707 2 0 1 0 1 0 0
#> GSM247737 2 0 1 0 1 0 0
#> GSM247827 3 0 1 0 0 1 0
#> GSM247848 1 0 1 1 0 0 0
#> GSM247794 2 0 1 0 1 0 0
#> GSM247757 2 0 1 0 1 0 0
#> GSM247744 4 0 1 0 0 0 1
#> GSM247751 3 0 1 0 0 1 0
#> GSM247837 1 0 1 1 0 0 0
#> GSM247754 2 0 1 0 1 0 0
#> GSM247789 2 0 1 0 1 0 0
#> GSM247802 4 0 1 0 0 0 1
#> GSM247771 3 0 1 0 0 1 0
#> GSM247763 1 0 1 1 0 0 0
#> GSM247808 2 0 1 0 1 0 0
#> GSM247787 2 0 1 0 1 0 0
#> GSM247843 4 0 1 0 0 0 1
#> GSM247811 3 0 1 0 0 1 0
#> GSM247773 1 0 1 1 0 0 0
#> GSM247766 2 0 1 0 1 0 0
#> GSM247718 2 0 1 0 1 0 0
#> GSM247832 4 0 1 0 0 0 1
#> GSM247709 3 0 1 0 0 1 0
#> GSM247820 1 0 1 1 0 0 0
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0 1 0 1 0 0 0
#> GSM247854 2 0 1 0 1 0 0 0
#> GSM247758 5 0 1 0 0 0 0 1
#> GSM247742 4 0 1 0 0 0 1 0
#> GSM247755 3 0 1 0 0 1 0 0
#> GSM247841 1 0 1 1 0 0 0 0
#> GSM247703 2 0 1 0 1 0 0 0
#> GSM247739 5 0 1 0 0 0 0 1
#> GSM247715 4 0 1 0 0 0 1 0
#> GSM247829 3 0 1 0 0 1 0 0
#> GSM247842 1 0 1 1 0 0 0 0
#> GSM247805 2 0 1 0 1 0 0 0
#> GSM247786 5 0 1 0 0 0 0 1
#> GSM247812 3 0 1 0 0 1 0 0
#> GSM247776 1 0 1 1 0 0 0 0
#> GSM247850 1 0 1 1 0 0 0 0
#> GSM247717 2 0 1 0 1 0 0 0
#> GSM247784 5 0 1 0 0 0 0 1
#> GSM247834 4 0 1 0 0 0 1 0
#> GSM247783 3 0 1 0 0 1 0 0
#> GSM247846 1 0 1 1 0 0 0 0
#> GSM247822 2 0 1 0 1 0 0 0
#> GSM247710 5 0 1 0 0 0 0 1
#> GSM247713 4 0 1 0 0 0 1 0
#> GSM247840 3 0 1 0 0 1 0 0
#> GSM247733 1 0 1 1 0 0 0 0
#> GSM247852 1 0 1 1 0 0 0 0
#> GSM247790 2 0 1 0 1 0 0 0
#> GSM247730 5 0 1 0 0 0 0 1
#> GSM247824 3 0 1 0 0 1 0 0
#> GSM247770 1 0 1 1 0 0 0 0
#> GSM247711 2 0 1 0 1 0 0 0
#> GSM247782 5 0 1 0 0 0 0 1
#> GSM247836 4 0 1 0 0 0 1 0
#> GSM247785 3 0 1 0 0 1 0 0
#> GSM247847 1 0 1 1 0 0 0 0
#> GSM247750 2 0 1 0 1 0 0 0
#> GSM247788 5 0 1 0 0 0 0 1
#> GSM247849 4 0 1 0 0 0 1 0
#> GSM247772 3 0 1 0 0 1 0 0
#> GSM247760 1 0 1 1 0 0 0 0
#> GSM247764 2 0 1 0 1 0 0 0
#> GSM247851 2 0 1 0 1 0 0 0
#> GSM247714 5 0 1 0 0 0 0 1
#> GSM247828 4 0 1 0 0 0 1 0
#> GSM247704 3 0 1 0 0 1 0 0
#> GSM247818 1 0 1 1 0 0 0 0
#> GSM247823 2 0 1 0 1 0 0 0
#> GSM247706 5 0 1 0 0 0 0 1
#> GSM247835 3 0 1 0 0 1 0 0
#> GSM247734 1 0 1 1 0 0 0 0
#> GSM247819 2 0 1 0 1 0 0 0
#> GSM247809 5 0 1 0 0 0 0 1
#> GSM247830 3 0 1 0 0 1 0 0
#> GSM247833 1 0 1 1 0 0 0 0
#> GSM247738 2 0 1 0 1 0 0 0
#> GSM247716 5 0 1 0 0 0 0 1
#> GSM247747 3 0 1 0 0 1 0 0
#> GSM247722 1 0 1 1 0 0 0 0
#> GSM247816 2 0 1 0 1 0 0 0
#> GSM247839 5 0 1 0 0 0 0 1
#> GSM247821 4 0 1 0 0 0 1 0
#> GSM247798 3 0 1 0 0 1 0 0
#> GSM247838 1 0 1 1 0 0 0 0
#> GSM247721 2 0 1 0 1 0 0 0
#> GSM247781 5 0 1 0 0 0 0 1
#> GSM247762 4 0 1 0 0 0 1 0
#> GSM247825 3 0 1 0 0 1 0 0
#> GSM247777 1 0 1 1 0 0 0 0
#> GSM247761 2 0 1 0 1 0 0 0
#> GSM247720 5 0 1 0 0 0 0 1
#> GSM247814 3 0 1 0 0 1 0 0
#> GSM247732 1 0 1 1 0 0 0 0
#> GSM247708 2 0 1 0 1 0 0 0
#> GSM247740 5 0 1 0 0 0 0 1
#> GSM247749 4 0 1 0 0 0 1 0
#> GSM247767 3 0 1 0 0 1 0 0
#> GSM247748 1 0 1 1 0 0 0 0
#> GSM247705 2 0 1 0 1 0 0 0
#> GSM247746 5 0 1 0 0 0 0 1
#> GSM247752 4 0 1 0 0 0 1 0
#> GSM247769 3 0 1 0 0 1 0 0
#> GSM247753 1 0 1 1 0 0 0 0
#> GSM247723 2 0 1 0 1 0 0 0
#> GSM247779 5 0 1 0 0 0 0 1
#> GSM247756 4 0 1 0 0 0 1 0
#> GSM247826 3 0 1 0 0 1 0 0
#> GSM247775 1 0 1 1 0 0 0 0
#> GSM247741 2 0 1 0 1 0 0 0
#> GSM247799 5 0 1 0 0 0 0 1
#> GSM247778 4 0 1 0 0 0 1 0
#> GSM247806 3 0 1 0 0 1 0 0
#> GSM247815 1 0 1 1 0 0 0 0
#> GSM247735 2 0 1 0 1 0 0 0
#> GSM247831 5 0 1 0 0 0 0 1
#> GSM247845 4 0 1 0 0 0 1 0
#> GSM247791 3 0 1 0 0 1 0 0
#> GSM247780 1 0 1 1 0 0 0 0
#> GSM247853 1 0 1 1 0 0 0 0
#> GSM247800 2 0 1 0 1 0 0 0
#> GSM247729 5 0 1 0 0 0 0 1
#> GSM247810 4 0 1 0 0 0 1 0
#> GSM247844 3 0 1 0 0 1 0 0
#> GSM247793 1 0 1 1 0 0 0 0
#> GSM247759 2 0 1 0 1 0 0 0
#> GSM247724 5 0 1 0 0 0 0 1
#> GSM247817 3 0 1 0 0 1 0 0
#> GSM247727 1 0 1 1 0 0 0 0
#> GSM247796 2 0 1 0 1 0 0 0
#> GSM247725 5 0 1 0 0 0 0 1
#> GSM247801 4 0 1 0 0 0 1 0
#> GSM247731 3 0 1 0 0 1 0 0
#> GSM247765 1 0 1 1 0 0 0 0
#> GSM247792 2 0 1 0 1 0 0 0
#> GSM247726 5 0 1 0 0 0 0 1
#> GSM247803 4 0 1 0 0 0 1 0
#> GSM247728 3 0 1 0 0 1 0 0
#> GSM247768 1 0 1 1 0 0 0 0
#> GSM247745 2 0 1 0 1 0 0 0
#> GSM247855 2 0 1 0 1 0 0 0
#> GSM247804 5 0 1 0 0 0 0 1
#> GSM247774 4 0 1 0 0 0 1 0
#> GSM247807 3 0 1 0 0 1 0 0
#> GSM247813 1 0 1 1 0 0 0 0
#> GSM247736 2 0 1 0 1 0 0 0
#> GSM247712 5 0 1 0 0 0 0 1
#> GSM247797 4 0 1 0 0 0 1 0
#> GSM247743 3 0 1 0 0 1 0 0
#> GSM247719 1 0 1 1 0 0 0 0
#> GSM247707 2 0 1 0 1 0 0 0
#> GSM247737 5 0 1 0 0 0 0 1
#> GSM247827 3 0 1 0 0 1 0 0
#> GSM247848 1 0 1 1 0 0 0 0
#> GSM247794 2 0 1 0 1 0 0 0
#> GSM247757 5 0 1 0 0 0 0 1
#> GSM247744 4 0 1 0 0 0 1 0
#> GSM247751 3 0 1 0 0 1 0 0
#> GSM247837 1 0 1 1 0 0 0 0
#> GSM247754 2 0 1 0 1 0 0 0
#> GSM247789 5 0 1 0 0 0 0 1
#> GSM247802 4 0 1 0 0 0 1 0
#> GSM247771 3 0 1 0 0 1 0 0
#> GSM247763 1 0 1 1 0 0 0 0
#> GSM247808 2 0 1 0 1 0 0 0
#> GSM247787 5 0 1 0 0 0 0 1
#> GSM247843 4 0 1 0 0 0 1 0
#> GSM247811 3 0 1 0 0 1 0 0
#> GSM247773 1 0 1 1 0 0 0 0
#> GSM247766 2 0 1 0 1 0 0 0
#> GSM247718 5 0 1 0 0 0 0 1
#> GSM247832 4 0 1 0 0 0 1 0
#> GSM247709 3 0 1 0 0 1 0 0
#> GSM247820 1 0 1 1 0 0 0 0
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.2697 0.863 0 0.812 0 0.000 0 0.188
#> GSM247854 2 0.2697 0.863 0 0.812 0 0.000 0 0.188
#> GSM247758 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247742 4 0.1387 0.962 0 0.000 0 0.932 0 0.068
#> GSM247755 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247841 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247703 2 0.0000 0.893 0 1.000 0 0.000 0 0.000
#> GSM247739 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247715 4 0.1141 0.964 0 0.000 0 0.948 0 0.052
#> GSM247829 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247842 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247805 2 0.0000 0.893 0 1.000 0 0.000 0 0.000
#> GSM247786 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247812 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247776 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247717 2 0.2527 0.873 0 0.832 0 0.000 0 0.168
#> GSM247784 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247834 4 0.0547 0.967 0 0.000 0 0.980 0 0.020
#> GSM247783 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247846 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247822 6 0.3351 0.830 0 0.288 0 0.000 0 0.712
#> GSM247710 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247713 4 0.0547 0.967 0 0.000 0 0.980 0 0.020
#> GSM247840 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247733 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247790 2 0.0000 0.893 0 1.000 0 0.000 0 0.000
#> GSM247730 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247824 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247770 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247711 2 0.2491 0.874 0 0.836 0 0.000 0 0.164
#> GSM247782 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247836 4 0.1141 0.964 0 0.000 0 0.948 0 0.052
#> GSM247785 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247847 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247750 2 0.0363 0.890 0 0.988 0 0.000 0 0.012
#> GSM247788 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247849 4 0.1387 0.962 0 0.000 0 0.932 0 0.068
#> GSM247772 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247760 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247764 6 0.3175 0.850 0 0.256 0 0.000 0 0.744
#> GSM247851 6 0.3175 0.850 0 0.256 0 0.000 0 0.744
#> GSM247714 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247828 4 0.1141 0.964 0 0.000 0 0.948 0 0.052
#> GSM247704 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247818 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247823 2 0.1501 0.840 0 0.924 0 0.000 0 0.076
#> GSM247706 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247835 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247734 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247819 6 0.2823 0.884 0 0.204 0 0.000 0 0.796
#> GSM247809 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247830 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247833 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247738 2 0.2527 0.873 0 0.832 0 0.000 0 0.168
#> GSM247716 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247747 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247722 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247816 2 0.0547 0.887 0 0.980 0 0.000 0 0.020
#> GSM247839 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247821 4 0.0000 0.969 0 0.000 0 1.000 0 0.000
#> GSM247798 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247838 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247721 2 0.0260 0.895 0 0.992 0 0.000 0 0.008
#> GSM247781 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247762 4 0.0865 0.967 0 0.000 0 0.964 0 0.036
#> GSM247825 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247777 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247761 2 0.0000 0.893 0 1.000 0 0.000 0 0.000
#> GSM247720 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247814 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247732 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247708 2 0.1141 0.889 0 0.948 0 0.000 0 0.052
#> GSM247740 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247749 4 0.0547 0.967 0 0.000 0 0.980 0 0.020
#> GSM247767 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247748 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247705 2 0.0547 0.887 0 0.980 0 0.000 0 0.020
#> GSM247746 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247752 4 0.0547 0.967 0 0.000 0 0.980 0 0.020
#> GSM247769 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247753 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247723 6 0.1663 0.872 0 0.088 0 0.000 0 0.912
#> GSM247779 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247756 4 0.1387 0.962 0 0.000 0 0.932 0 0.068
#> GSM247826 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247775 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247741 6 0.1663 0.872 0 0.088 0 0.000 0 0.912
#> GSM247799 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247778 4 0.0000 0.969 0 0.000 0 1.000 0 0.000
#> GSM247806 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247815 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247735 6 0.1663 0.872 0 0.088 0 0.000 0 0.912
#> GSM247831 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247845 4 0.1387 0.962 0 0.000 0 0.932 0 0.068
#> GSM247791 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247780 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247800 6 0.1663 0.872 0 0.088 0 0.000 0 0.912
#> GSM247729 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247810 4 0.0547 0.967 0 0.000 0 0.980 0 0.020
#> GSM247844 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247793 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247759 6 0.3706 0.589 0 0.380 0 0.000 0 0.620
#> GSM247724 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247817 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247727 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247796 6 0.2092 0.882 0 0.124 0 0.000 0 0.876
#> GSM247725 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247801 4 0.0865 0.967 0 0.000 0 0.964 0 0.036
#> GSM247731 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247765 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247792 6 0.2823 0.883 0 0.204 0 0.000 0 0.796
#> GSM247726 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247803 4 0.0547 0.967 0 0.000 0 0.980 0 0.020
#> GSM247728 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247768 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247745 2 0.2527 0.873 0 0.832 0 0.000 0 0.168
#> GSM247855 2 0.2527 0.873 0 0.832 0 0.000 0 0.168
#> GSM247804 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247774 4 0.1387 0.962 0 0.000 0 0.932 0 0.068
#> GSM247807 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247813 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247736 2 0.2527 0.873 0 0.832 0 0.000 0 0.168
#> GSM247712 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247797 4 0.0547 0.967 0 0.000 0 0.980 0 0.020
#> GSM247743 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247719 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247707 2 0.0000 0.893 0 1.000 0 0.000 0 0.000
#> GSM247737 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247827 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247848 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247794 2 0.0000 0.893 0 1.000 0 0.000 0 0.000
#> GSM247757 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247744 4 0.1387 0.962 0 0.000 0 0.932 0 0.068
#> GSM247751 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247837 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247754 2 0.1814 0.888 0 0.900 0 0.000 0 0.100
#> GSM247789 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247802 4 0.0865 0.967 0 0.000 0 0.964 0 0.036
#> GSM247771 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247763 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247808 2 0.2527 0.873 0 0.832 0 0.000 0 0.168
#> GSM247787 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247843 4 0.0000 0.969 0 0.000 0 1.000 0 0.000
#> GSM247811 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247773 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247766 6 0.2912 0.882 0 0.216 0 0.000 0 0.784
#> GSM247718 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247832 4 0.1387 0.962 0 0.000 0 0.932 0 0.068
#> GSM247709 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247820 1 0.0000 1.000 1 0.000 0 0.000 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
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
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> CV:pam 152 1 0.839 3.81e-30 2
#> CV:pam 153 1 0.856 1.44e-58 3
#> CV:pam 153 1 0.964 1.16e-90 4
#> CV:pam 153 1 0.989 6.51e-120 5
#> CV:pam 153 1 0.689 8.52e-117 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.479 0.743 0.865 0.48576 0.508 0.508
#> 3 3 1.000 0.995 0.997 0.33551 0.719 0.507
#> 4 4 1.000 1.000 1.000 0.09665 0.939 0.825
#> 5 5 1.000 0.996 0.995 0.12482 0.910 0.689
#> 6 6 0.918 0.904 0.920 0.00567 0.989 0.945
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 4 5
There is also optional best \(k\) = 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0.000 0.847 0.000 1.000
#> GSM247854 2 0.000 0.847 0.000 1.000
#> GSM247758 2 0.000 0.847 0.000 1.000
#> GSM247742 2 0.998 0.396 0.472 0.528
#> GSM247755 1 0.900 0.728 0.684 0.316
#> GSM247841 1 0.000 0.795 1.000 0.000
#> GSM247703 2 0.000 0.847 0.000 1.000
#> GSM247739 2 0.000 0.847 0.000 1.000
#> GSM247715 2 0.998 0.396 0.472 0.528
#> GSM247829 1 0.900 0.728 0.684 0.316
#> GSM247842 1 0.000 0.795 1.000 0.000
#> GSM247805 2 0.000 0.847 0.000 1.000
#> GSM247786 2 0.000 0.847 0.000 1.000
#> GSM247812 1 0.900 0.728 0.684 0.316
#> GSM247776 1 0.000 0.795 1.000 0.000
#> GSM247850 1 0.000 0.795 1.000 0.000
#> GSM247717 2 0.000 0.847 0.000 1.000
#> GSM247784 2 0.000 0.847 0.000 1.000
#> GSM247834 2 0.998 0.396 0.472 0.528
#> GSM247783 1 0.900 0.728 0.684 0.316
#> GSM247846 1 0.000 0.795 1.000 0.000
#> GSM247822 2 0.000 0.847 0.000 1.000
#> GSM247710 2 0.000 0.847 0.000 1.000
#> GSM247713 2 0.998 0.396 0.472 0.528
#> GSM247840 1 0.900 0.728 0.684 0.316
#> GSM247733 1 0.000 0.795 1.000 0.000
#> GSM247852 1 0.000 0.795 1.000 0.000
#> GSM247790 2 0.000 0.847 0.000 1.000
#> GSM247730 2 0.000 0.847 0.000 1.000
#> GSM247824 1 0.900 0.728 0.684 0.316
#> GSM247770 1 0.000 0.795 1.000 0.000
#> GSM247711 2 0.000 0.847 0.000 1.000
#> GSM247782 2 0.000 0.847 0.000 1.000
#> GSM247836 2 0.998 0.396 0.472 0.528
#> GSM247785 1 0.900 0.728 0.684 0.316
#> GSM247847 1 0.000 0.795 1.000 0.000
#> GSM247750 2 0.000 0.847 0.000 1.000
#> GSM247788 2 0.000 0.847 0.000 1.000
#> GSM247849 2 0.998 0.396 0.472 0.528
#> GSM247772 1 0.900 0.728 0.684 0.316
#> GSM247760 1 0.000 0.795 1.000 0.000
#> GSM247764 2 0.000 0.847 0.000 1.000
#> GSM247851 2 0.000 0.847 0.000 1.000
#> GSM247714 2 0.000 0.847 0.000 1.000
#> GSM247828 2 0.998 0.396 0.472 0.528
#> GSM247704 1 0.900 0.728 0.684 0.316
#> GSM247818 1 0.000 0.795 1.000 0.000
#> GSM247823 2 0.000 0.847 0.000 1.000
#> GSM247706 2 0.000 0.847 0.000 1.000
#> GSM247835 1 0.900 0.728 0.684 0.316
#> GSM247734 1 0.000 0.795 1.000 0.000
#> GSM247819 2 0.000 0.847 0.000 1.000
#> GSM247809 2 0.000 0.847 0.000 1.000
#> GSM247830 1 0.900 0.728 0.684 0.316
#> GSM247833 1 0.000 0.795 1.000 0.000
#> GSM247738 2 0.000 0.847 0.000 1.000
#> GSM247716 2 0.000 0.847 0.000 1.000
#> GSM247747 1 0.900 0.728 0.684 0.316
#> GSM247722 1 0.000 0.795 1.000 0.000
#> GSM247816 2 0.000 0.847 0.000 1.000
#> GSM247839 2 0.000 0.847 0.000 1.000
#> GSM247821 2 0.998 0.396 0.472 0.528
#> GSM247798 1 0.900 0.728 0.684 0.316
#> GSM247838 1 0.000 0.795 1.000 0.000
#> GSM247721 2 0.000 0.847 0.000 1.000
#> GSM247781 2 0.000 0.847 0.000 1.000
#> GSM247762 2 0.998 0.396 0.472 0.528
#> GSM247825 1 0.900 0.728 0.684 0.316
#> GSM247777 1 0.000 0.795 1.000 0.000
#> GSM247761 2 0.000 0.847 0.000 1.000
#> GSM247720 2 0.000 0.847 0.000 1.000
#> GSM247814 1 0.900 0.728 0.684 0.316
#> GSM247732 1 0.000 0.795 1.000 0.000
#> GSM247708 2 0.000 0.847 0.000 1.000
#> GSM247740 2 0.000 0.847 0.000 1.000
#> GSM247749 2 0.998 0.396 0.472 0.528
#> GSM247767 1 0.900 0.728 0.684 0.316
#> GSM247748 1 0.000 0.795 1.000 0.000
#> GSM247705 2 0.000 0.847 0.000 1.000
#> GSM247746 2 0.000 0.847 0.000 1.000
#> GSM247752 2 0.998 0.396 0.472 0.528
#> GSM247769 1 0.900 0.728 0.684 0.316
#> GSM247753 1 0.000 0.795 1.000 0.000
#> GSM247723 2 0.000 0.847 0.000 1.000
#> GSM247779 2 0.000 0.847 0.000 1.000
#> GSM247756 2 0.998 0.396 0.472 0.528
#> GSM247826 1 0.900 0.728 0.684 0.316
#> GSM247775 1 0.000 0.795 1.000 0.000
#> GSM247741 2 0.000 0.847 0.000 1.000
#> GSM247799 2 0.000 0.847 0.000 1.000
#> GSM247778 2 0.998 0.396 0.472 0.528
#> GSM247806 1 0.900 0.728 0.684 0.316
#> GSM247815 1 0.000 0.795 1.000 0.000
#> GSM247735 2 0.000 0.847 0.000 1.000
#> GSM247831 2 0.000 0.847 0.000 1.000
#> GSM247845 2 0.998 0.396 0.472 0.528
#> GSM247791 1 0.900 0.728 0.684 0.316
#> GSM247780 1 0.000 0.795 1.000 0.000
#> GSM247853 1 0.000 0.795 1.000 0.000
#> GSM247800 2 0.000 0.847 0.000 1.000
#> GSM247729 2 0.000 0.847 0.000 1.000
#> GSM247810 2 0.998 0.396 0.472 0.528
#> GSM247844 1 0.900 0.728 0.684 0.316
#> GSM247793 1 0.000 0.795 1.000 0.000
#> GSM247759 2 0.000 0.847 0.000 1.000
#> GSM247724 2 0.000 0.847 0.000 1.000
#> GSM247817 1 0.900 0.728 0.684 0.316
#> GSM247727 1 0.000 0.795 1.000 0.000
#> GSM247796 2 0.000 0.847 0.000 1.000
#> GSM247725 2 0.000 0.847 0.000 1.000
#> GSM247801 2 0.998 0.396 0.472 0.528
#> GSM247731 1 0.900 0.728 0.684 0.316
#> GSM247765 1 0.000 0.795 1.000 0.000
#> GSM247792 2 0.000 0.847 0.000 1.000
#> GSM247726 2 0.000 0.847 0.000 1.000
#> GSM247803 2 0.998 0.396 0.472 0.528
#> GSM247728 1 0.900 0.728 0.684 0.316
#> GSM247768 1 0.000 0.795 1.000 0.000
#> GSM247745 2 0.000 0.847 0.000 1.000
#> GSM247855 2 0.000 0.847 0.000 1.000
#> GSM247804 2 0.000 0.847 0.000 1.000
#> GSM247774 2 0.998 0.396 0.472 0.528
#> GSM247807 1 0.900 0.728 0.684 0.316
#> GSM247813 1 0.000 0.795 1.000 0.000
#> GSM247736 2 0.000 0.847 0.000 1.000
#> GSM247712 2 0.000 0.847 0.000 1.000
#> GSM247797 2 0.998 0.396 0.472 0.528
#> GSM247743 1 0.900 0.728 0.684 0.316
#> GSM247719 1 0.000 0.795 1.000 0.000
#> GSM247707 2 0.000 0.847 0.000 1.000
#> GSM247737 2 0.000 0.847 0.000 1.000
#> GSM247827 1 0.900 0.728 0.684 0.316
#> GSM247848 1 0.000 0.795 1.000 0.000
#> GSM247794 2 0.000 0.847 0.000 1.000
#> GSM247757 2 0.000 0.847 0.000 1.000
#> GSM247744 2 0.998 0.396 0.472 0.528
#> GSM247751 1 0.900 0.728 0.684 0.316
#> GSM247837 1 0.000 0.795 1.000 0.000
#> GSM247754 2 0.000 0.847 0.000 1.000
#> GSM247789 2 0.000 0.847 0.000 1.000
#> GSM247802 2 0.998 0.396 0.472 0.528
#> GSM247771 1 0.900 0.728 0.684 0.316
#> GSM247763 1 0.000 0.795 1.000 0.000
#> GSM247808 2 0.000 0.847 0.000 1.000
#> GSM247787 2 0.000 0.847 0.000 1.000
#> GSM247843 2 0.998 0.396 0.472 0.528
#> GSM247811 1 0.900 0.728 0.684 0.316
#> GSM247773 1 0.000 0.795 1.000 0.000
#> GSM247766 2 0.000 0.847 0.000 1.000
#> GSM247718 2 0.000 0.847 0.000 1.000
#> GSM247832 2 0.998 0.396 0.472 0.528
#> GSM247709 1 0.900 0.728 0.684 0.316
#> GSM247820 1 0.000 0.795 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247854 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247758 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247742 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247755 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247841 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247703 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247739 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247715 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247829 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247842 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247805 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247786 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247812 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247776 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247850 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247717 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247784 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247834 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247783 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247846 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247822 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247710 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247713 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247840 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247733 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247852 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247790 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247730 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247824 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247770 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247711 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247782 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247836 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247785 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247847 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247750 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247788 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247849 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247772 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247760 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247764 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247851 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247714 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247828 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247704 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247818 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247823 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247706 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247835 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247734 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247819 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247809 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247830 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247833 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247738 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247716 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247747 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247722 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247816 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247839 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247821 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247798 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247838 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247721 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247781 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247762 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247825 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247777 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247761 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247720 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247814 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247732 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247708 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247740 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247749 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247767 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247748 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247705 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247746 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247752 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247769 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247753 1 0.0747 0.981 0.984 0.016 0.00
#> GSM247723 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247779 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247756 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247826 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247775 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247741 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247799 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247778 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247806 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247815 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247735 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247831 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247845 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247791 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247780 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247853 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247800 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247729 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247810 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247844 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247793 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247759 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247724 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247817 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247727 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247796 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247725 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247801 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247731 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247765 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247792 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247726 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247803 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247728 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247768 1 0.0747 0.981 0.984 0.016 0.00
#> GSM247745 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247855 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247804 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247774 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247807 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247813 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247736 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247712 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247797 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247743 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247719 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247707 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247737 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247827 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247848 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247794 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247757 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247744 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247751 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247837 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247754 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247789 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247802 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247771 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247763 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247808 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247787 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247843 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247811 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247773 1 0.0000 0.999 1.000 0.000 0.00
#> GSM247766 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247718 2 0.0000 1.000 0.000 1.000 0.00
#> GSM247832 3 0.0892 0.986 0.000 0.020 0.98
#> GSM247709 3 0.0000 0.990 0.000 0.000 1.00
#> GSM247820 1 0.0000 0.999 1.000 0.000 0.00
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247854 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247758 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247742 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247755 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247841 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247703 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247739 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247715 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247829 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247842 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247805 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247786 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247812 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247776 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247717 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247784 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247834 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247783 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247846 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247822 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247710 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247713 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247840 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247733 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247790 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247730 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247824 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247770 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247711 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247782 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247836 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247785 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247847 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247750 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247788 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247849 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247772 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247760 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247764 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247851 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247714 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247828 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247704 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247818 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247823 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247706 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247835 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247734 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247819 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247809 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247830 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247833 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247738 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247716 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247747 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247722 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247816 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247839 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247821 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247798 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247838 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247721 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247781 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247762 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247825 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247777 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247761 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247720 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247814 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247732 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247708 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247740 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247749 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247767 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247748 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247705 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247746 2 0.0188 0.996 0 0.996 0 0.004
#> GSM247752 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247769 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247753 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247723 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247779 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247756 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247826 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247775 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247741 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247799 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247778 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247806 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247815 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247735 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247831 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247845 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247791 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247780 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247800 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247729 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247810 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247844 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247793 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247759 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247724 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247817 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247727 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247796 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247725 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247801 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247731 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247765 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247792 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247726 2 0.0188 0.996 0 0.996 0 0.004
#> GSM247803 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247728 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247768 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247745 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247855 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247804 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247774 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247807 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247813 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247736 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247712 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247797 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247743 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247719 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247707 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247737 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247827 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247848 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247794 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247757 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247744 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247751 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247837 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247754 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247789 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247802 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247771 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247763 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247808 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247787 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247843 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247811 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247773 1 0.0000 1.000 1 0.000 0 0.000
#> GSM247766 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247718 2 0.0000 1.000 0 1.000 0 0.000
#> GSM247832 4 0.0000 1.000 0 0.000 0 1.000
#> GSM247709 3 0.0000 1.000 0 0.000 1 0.000
#> GSM247820 1 0.0000 1.000 1 0.000 0 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247854 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247758 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247742 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247755 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247841 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247703 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247739 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247715 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247829 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247842 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247805 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247786 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247812 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247776 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247850 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247717 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247784 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247834 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247783 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247846 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247822 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247710 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247713 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247840 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247733 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247852 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247790 2 0.2020 0.898 0.000 0.900 0 0 0.100
#> GSM247730 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247824 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247770 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247711 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247782 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247836 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247785 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247847 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247750 2 0.0290 0.984 0.000 0.992 0 0 0.008
#> GSM247788 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247849 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247772 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247760 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247764 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247851 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247714 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247828 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247704 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247818 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247823 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247706 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247835 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247734 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247819 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247809 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247830 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247833 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247738 2 0.0963 0.968 0.000 0.964 0 0 0.036
#> GSM247716 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247747 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247722 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247816 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247839 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247821 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247798 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247838 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247721 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247781 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247762 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247825 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247777 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247761 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247720 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247814 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247732 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247708 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247740 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247749 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247767 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247748 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247705 2 0.0162 0.987 0.000 0.996 0 0 0.004
#> GSM247746 2 0.0703 0.978 0.000 0.976 0 0 0.024
#> GSM247752 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247769 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247753 1 0.0290 0.994 0.992 0.000 0 0 0.008
#> GSM247723 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247779 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247756 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247826 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247775 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247741 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247799 5 0.0162 0.990 0.000 0.004 0 0 0.996
#> GSM247778 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247806 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247815 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247735 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247831 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247845 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247791 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247780 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247853 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247800 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247729 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247810 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247844 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247793 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247759 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247724 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247817 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247727 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247796 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247725 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247801 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247731 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247765 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247792 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247726 2 0.0703 0.978 0.000 0.976 0 0 0.024
#> GSM247803 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247728 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247768 1 0.0290 0.994 0.992 0.000 0 0 0.008
#> GSM247745 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247855 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247804 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247774 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247807 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247813 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247736 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247712 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247797 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247743 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247719 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247707 2 0.0404 0.989 0.000 0.988 0 0 0.012
#> GSM247737 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247827 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247848 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247794 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247757 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247744 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247751 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247837 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247754 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247789 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247802 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247771 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247763 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247808 2 0.0162 0.990 0.000 0.996 0 0 0.004
#> GSM247787 5 0.0404 0.999 0.000 0.012 0 0 0.988
#> GSM247843 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247811 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247773 1 0.0000 1.000 1.000 0.000 0 0 0.000
#> GSM247766 2 0.0000 0.990 0.000 1.000 0 0 0.000
#> GSM247718 5 0.0880 0.977 0.000 0.032 0 0 0.968
#> GSM247832 4 0.0000 1.000 0.000 0.000 0 1 0.000
#> GSM247709 3 0.0000 1.000 0.000 0.000 1 0 0.000
#> GSM247820 1 0.0000 1.000 1.000 0.000 0 0 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247854 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247758 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247742 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247755 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247841 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247703 2 0.3290 0.729 0.00 0.744 0 0.000 0.252 0.004
#> GSM247739 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247715 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247829 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247842 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247805 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247786 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247812 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247776 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247850 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247717 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247784 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247834 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247783 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247846 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247822 2 0.3314 0.254 0.00 0.740 0 0.000 0.004 0.256
#> GSM247710 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247713 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247840 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247733 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247852 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247790 2 0.5639 0.329 0.00 0.536 0 0.000 0.252 0.212
#> GSM247730 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247824 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247770 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247711 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247782 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247836 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247785 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247847 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247750 6 0.5404 0.634 0.00 0.312 0 0.000 0.140 0.548
#> GSM247788 5 0.0790 0.954 0.00 0.032 0 0.000 0.968 0.000
#> GSM247849 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247772 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247760 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247764 2 0.3547 0.236 0.00 0.696 0 0.000 0.004 0.300
#> GSM247851 2 0.3528 0.242 0.00 0.700 0 0.000 0.004 0.296
#> GSM247714 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247828 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247704 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247818 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247823 2 0.3470 0.726 0.00 0.740 0 0.000 0.248 0.012
#> GSM247706 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247835 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247734 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247819 2 0.3528 0.242 0.00 0.700 0 0.000 0.004 0.296
#> GSM247809 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247830 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247833 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247738 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247716 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247747 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247722 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247816 2 0.3265 0.730 0.00 0.748 0 0.000 0.248 0.004
#> GSM247839 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247821 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247798 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247838 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247721 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247781 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247762 4 0.0146 0.997 0.00 0.004 0 0.996 0.000 0.000
#> GSM247825 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247777 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247761 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247720 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247814 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247732 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247708 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247740 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247749 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247767 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247748 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247705 6 0.3659 0.809 0.00 0.364 0 0.000 0.000 0.636
#> GSM247746 6 0.3288 0.852 0.00 0.276 0 0.000 0.000 0.724
#> GSM247752 4 0.0146 0.997 0.00 0.004 0 0.996 0.000 0.000
#> GSM247769 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247753 1 0.0547 0.981 0.98 0.000 0 0.000 0.000 0.020
#> GSM247723 2 0.4913 0.651 0.00 0.636 0 0.000 0.252 0.112
#> GSM247779 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247756 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247826 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247775 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247741 2 0.4473 0.686 0.00 0.676 0 0.000 0.252 0.072
#> GSM247799 5 0.0865 0.961 0.00 0.000 0 0.000 0.964 0.036
#> GSM247778 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247806 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247815 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247735 2 0.0291 0.385 0.00 0.992 0 0.000 0.004 0.004
#> GSM247831 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247845 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247791 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247780 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247853 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247800 2 0.3448 0.250 0.00 0.716 0 0.000 0.004 0.280
#> GSM247729 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247810 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247844 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247793 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247759 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247724 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247817 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247727 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247796 2 0.3528 0.243 0.00 0.700 0 0.000 0.004 0.296
#> GSM247725 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247801 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247731 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247765 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247792 2 0.3601 0.219 0.00 0.684 0 0.000 0.004 0.312
#> GSM247726 6 0.3288 0.852 0.00 0.276 0 0.000 0.000 0.724
#> GSM247803 4 0.0146 0.997 0.00 0.004 0 0.996 0.000 0.000
#> GSM247728 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247768 1 0.0547 0.981 0.98 0.000 0 0.000 0.000 0.020
#> GSM247745 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247855 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247804 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247774 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247807 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247813 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247736 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247712 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247797 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247743 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247719 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247707 2 0.3290 0.731 0.00 0.744 0 0.000 0.252 0.004
#> GSM247737 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247827 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247848 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247794 2 0.3770 0.705 0.00 0.728 0 0.000 0.244 0.028
#> GSM247757 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247744 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247751 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247837 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247754 2 0.3494 0.726 0.00 0.736 0 0.000 0.252 0.012
#> GSM247789 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247802 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247771 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247763 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247808 2 0.3151 0.732 0.00 0.748 0 0.000 0.252 0.000
#> GSM247787 5 0.0000 0.995 0.00 0.000 0 0.000 1.000 0.000
#> GSM247843 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247811 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247773 1 0.0000 0.999 1.00 0.000 0 0.000 0.000 0.000
#> GSM247766 2 0.3565 0.232 0.00 0.692 0 0.000 0.004 0.304
#> GSM247718 5 0.1075 0.932 0.00 0.048 0 0.000 0.952 0.000
#> GSM247832 4 0.0000 1.000 0.00 0.000 0 1.000 0.000 0.000
#> GSM247709 3 0.0000 1.000 0.00 0.000 1 0.000 0.000 0.000
#> GSM247820 1 0.0000 0.999 1.00 0.000 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> CV:mclust 130 1 1.000 5.41e-28 2
#> CV:mclust 153 1 0.956 2.17e-61 3
#> CV:mclust 153 1 0.964 1.16e-90 4
#> CV:mclust 153 1 0.933 3.93e-116 5
#> CV:mclust 143 1 0.322 3.77e-106 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.47112 0.529 0.529
#> 3 3 0.758 0.978 0.961 0.34724 0.827 0.673
#> 4 4 1.000 0.998 0.999 0.12155 0.933 0.811
#> 5 5 1.000 1.000 1.000 0.12659 0.909 0.686
#> 6 6 1.000 0.973 0.989 0.00439 0.995 0.977
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 4
There is also optional best \(k\) = 2 4 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0 1 0 1
#> GSM247854 2 0 1 0 1
#> GSM247758 2 0 1 0 1
#> GSM247742 1 0 1 1 0
#> GSM247755 2 0 1 0 1
#> GSM247841 1 0 1 1 0
#> GSM247703 2 0 1 0 1
#> GSM247739 2 0 1 0 1
#> GSM247715 1 0 1 1 0
#> GSM247829 2 0 1 0 1
#> GSM247842 1 0 1 1 0
#> GSM247805 2 0 1 0 1
#> GSM247786 2 0 1 0 1
#> GSM247812 2 0 1 0 1
#> GSM247776 1 0 1 1 0
#> GSM247850 1 0 1 1 0
#> GSM247717 2 0 1 0 1
#> GSM247784 2 0 1 0 1
#> GSM247834 1 0 1 1 0
#> GSM247783 2 0 1 0 1
#> GSM247846 1 0 1 1 0
#> GSM247822 2 0 1 0 1
#> GSM247710 2 0 1 0 1
#> GSM247713 1 0 1 1 0
#> GSM247840 2 0 1 0 1
#> GSM247733 1 0 1 1 0
#> GSM247852 1 0 1 1 0
#> GSM247790 2 0 1 0 1
#> GSM247730 2 0 1 0 1
#> GSM247824 2 0 1 0 1
#> GSM247770 1 0 1 1 0
#> GSM247711 2 0 1 0 1
#> GSM247782 2 0 1 0 1
#> GSM247836 1 0 1 1 0
#> GSM247785 2 0 1 0 1
#> GSM247847 1 0 1 1 0
#> GSM247750 2 0 1 0 1
#> GSM247788 2 0 1 0 1
#> GSM247849 1 0 1 1 0
#> GSM247772 2 0 1 0 1
#> GSM247760 1 0 1 1 0
#> GSM247764 2 0 1 0 1
#> GSM247851 2 0 1 0 1
#> GSM247714 2 0 1 0 1
#> GSM247828 1 0 1 1 0
#> GSM247704 2 0 1 0 1
#> GSM247818 1 0 1 1 0
#> GSM247823 2 0 1 0 1
#> GSM247706 2 0 1 0 1
#> GSM247835 2 0 1 0 1
#> GSM247734 1 0 1 1 0
#> GSM247819 2 0 1 0 1
#> GSM247809 2 0 1 0 1
#> GSM247830 2 0 1 0 1
#> GSM247833 1 0 1 1 0
#> GSM247738 2 0 1 0 1
#> GSM247716 2 0 1 0 1
#> GSM247747 2 0 1 0 1
#> GSM247722 1 0 1 1 0
#> GSM247816 2 0 1 0 1
#> GSM247839 2 0 1 0 1
#> GSM247821 1 0 1 1 0
#> GSM247798 2 0 1 0 1
#> GSM247838 1 0 1 1 0
#> GSM247721 2 0 1 0 1
#> GSM247781 2 0 1 0 1
#> GSM247762 1 0 1 1 0
#> GSM247825 2 0 1 0 1
#> GSM247777 1 0 1 1 0
#> GSM247761 2 0 1 0 1
#> GSM247720 2 0 1 0 1
#> GSM247814 2 0 1 0 1
#> GSM247732 1 0 1 1 0
#> GSM247708 2 0 1 0 1
#> GSM247740 2 0 1 0 1
#> GSM247749 1 0 1 1 0
#> GSM247767 2 0 1 0 1
#> GSM247748 1 0 1 1 0
#> GSM247705 2 0 1 0 1
#> GSM247746 2 0 1 0 1
#> GSM247752 1 0 1 1 0
#> GSM247769 2 0 1 0 1
#> GSM247753 1 0 1 1 0
#> GSM247723 2 0 1 0 1
#> GSM247779 2 0 1 0 1
#> GSM247756 1 0 1 1 0
#> GSM247826 2 0 1 0 1
#> GSM247775 1 0 1 1 0
#> GSM247741 2 0 1 0 1
#> GSM247799 2 0 1 0 1
#> GSM247778 1 0 1 1 0
#> GSM247806 2 0 1 0 1
#> GSM247815 1 0 1 1 0
#> GSM247735 2 0 1 0 1
#> GSM247831 2 0 1 0 1
#> GSM247845 1 0 1 1 0
#> GSM247791 2 0 1 0 1
#> GSM247780 1 0 1 1 0
#> GSM247853 1 0 1 1 0
#> GSM247800 2 0 1 0 1
#> GSM247729 2 0 1 0 1
#> GSM247810 1 0 1 1 0
#> GSM247844 2 0 1 0 1
#> GSM247793 1 0 1 1 0
#> GSM247759 2 0 1 0 1
#> GSM247724 2 0 1 0 1
#> GSM247817 2 0 1 0 1
#> GSM247727 1 0 1 1 0
#> GSM247796 2 0 1 0 1
#> GSM247725 2 0 1 0 1
#> GSM247801 1 0 1 1 0
#> GSM247731 2 0 1 0 1
#> GSM247765 1 0 1 1 0
#> GSM247792 2 0 1 0 1
#> GSM247726 2 0 1 0 1
#> GSM247803 1 0 1 1 0
#> GSM247728 2 0 1 0 1
#> GSM247768 1 0 1 1 0
#> GSM247745 2 0 1 0 1
#> GSM247855 2 0 1 0 1
#> GSM247804 2 0 1 0 1
#> GSM247774 1 0 1 1 0
#> GSM247807 2 0 1 0 1
#> GSM247813 1 0 1 1 0
#> GSM247736 2 0 1 0 1
#> GSM247712 2 0 1 0 1
#> GSM247797 1 0 1 1 0
#> GSM247743 2 0 1 0 1
#> GSM247719 1 0 1 1 0
#> GSM247707 2 0 1 0 1
#> GSM247737 2 0 1 0 1
#> GSM247827 2 0 1 0 1
#> GSM247848 1 0 1 1 0
#> GSM247794 2 0 1 0 1
#> GSM247757 2 0 1 0 1
#> GSM247744 1 0 1 1 0
#> GSM247751 2 0 1 0 1
#> GSM247837 1 0 1 1 0
#> GSM247754 2 0 1 0 1
#> GSM247789 2 0 1 0 1
#> GSM247802 1 0 1 1 0
#> GSM247771 2 0 1 0 1
#> GSM247763 1 0 1 1 0
#> GSM247808 2 0 1 0 1
#> GSM247787 2 0 1 0 1
#> GSM247843 1 0 1 1 0
#> GSM247811 2 0 1 0 1
#> GSM247773 1 0 1 1 0
#> GSM247766 2 0 1 0 1
#> GSM247718 2 0 1 0 1
#> GSM247832 1 0 1 1 0
#> GSM247709 2 0 1 0 1
#> GSM247820 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247854 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247758 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247742 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247755 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247841 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247703 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247739 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247715 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247829 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247842 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247805 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247786 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247812 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247776 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247850 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247717 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247784 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247834 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247783 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247846 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247822 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247710 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247713 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247840 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247733 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247852 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247790 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247730 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247824 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247770 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247711 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247782 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247836 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247785 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247847 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247750 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247788 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247849 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247772 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247760 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247764 2 0.2711 0.895 0.000 0.912 0.088
#> GSM247851 2 0.3038 0.874 0.000 0.896 0.104
#> GSM247714 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247828 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247704 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247818 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247823 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247706 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247835 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247734 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247819 2 0.1964 0.934 0.000 0.944 0.056
#> GSM247809 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247830 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247833 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247738 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247716 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247747 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247722 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247816 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247839 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247821 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247798 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247838 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247721 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247781 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247762 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247825 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247777 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247761 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247720 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247814 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247732 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247708 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247740 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247749 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247767 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247748 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247705 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247746 2 0.0237 0.988 0.000 0.996 0.004
#> GSM247752 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247769 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247753 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247723 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247779 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247756 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247826 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247775 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247741 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247799 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247778 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247806 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247815 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247735 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247831 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247845 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247791 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247780 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247853 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247800 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247729 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247810 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247844 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247793 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247759 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247724 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247817 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247727 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247796 2 0.0237 0.989 0.000 0.996 0.004
#> GSM247725 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247801 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247731 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247765 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247792 2 0.1289 0.961 0.000 0.968 0.032
#> GSM247726 2 0.3038 0.866 0.000 0.896 0.104
#> GSM247803 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247728 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247768 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247745 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247855 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247804 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247774 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247807 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247813 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247736 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247712 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247797 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247743 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247719 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247707 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247737 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247827 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247848 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247794 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247757 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247744 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247751 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247837 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247754 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247789 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247802 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247771 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247763 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247808 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247787 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247843 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247811 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247773 1 0.0000 0.965 1.000 0.000 0.000
#> GSM247766 2 0.0592 0.981 0.000 0.988 0.012
#> GSM247718 2 0.0000 0.993 0.000 1.000 0.000
#> GSM247832 1 0.3038 0.947 0.896 0.000 0.104
#> GSM247709 3 0.3038 1.000 0.000 0.104 0.896
#> GSM247820 1 0.0000 0.965 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247854 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247758 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247742 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247755 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247841 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247703 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247739 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247715 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247829 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247842 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247805 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247786 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247812 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247776 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247717 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247784 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247834 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247783 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247846 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247822 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247710 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247713 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247840 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247733 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247790 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247730 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247824 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247770 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247711 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247782 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247836 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247785 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247847 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247750 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247788 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247849 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247772 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247760 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247764 2 0.0921 0.970 0 0.972 0.028 0.000
#> GSM247851 2 0.1302 0.954 0 0.956 0.044 0.000
#> GSM247714 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247828 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247704 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247818 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247823 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247706 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247835 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247734 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247819 2 0.0336 0.990 0 0.992 0.008 0.000
#> GSM247809 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247830 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247833 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247738 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247716 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247747 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247722 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247816 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247839 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247821 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247798 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247838 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247721 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247781 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247762 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247825 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247777 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247761 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247720 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247814 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247732 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247708 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247740 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247749 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247767 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247748 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247705 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247746 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247752 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247769 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247753 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247723 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247779 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247756 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247826 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247775 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247741 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247799 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247778 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247806 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247815 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247735 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247831 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247845 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247791 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247780 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247800 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247729 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247810 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247844 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247793 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247759 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247724 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247817 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247727 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247796 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247725 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247801 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247731 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247765 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247792 2 0.0188 0.994 0 0.996 0.004 0.000
#> GSM247726 2 0.1716 0.932 0 0.936 0.000 0.064
#> GSM247803 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247728 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247768 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247745 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247855 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247804 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247774 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247807 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247813 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247736 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247712 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247797 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247743 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247719 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247707 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247737 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247827 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247848 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247794 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247757 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247744 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247751 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247837 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247754 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247789 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247802 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247771 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247763 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247808 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247787 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247843 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247811 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247773 1 0.0000 1.000 1 0.000 0.000 0.000
#> GSM247766 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247718 2 0.0000 0.998 0 1.000 0.000 0.000
#> GSM247832 4 0.0000 1.000 0 0.000 0.000 1.000
#> GSM247709 3 0.0000 1.000 0 0.000 1.000 0.000
#> GSM247820 1 0.0000 1.000 1 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0 1 0 1 0 0 0
#> GSM247854 2 0 1 0 1 0 0 0
#> GSM247758 5 0 1 0 0 0 0 1
#> GSM247742 4 0 1 0 0 0 1 0
#> GSM247755 3 0 1 0 0 1 0 0
#> GSM247841 1 0 1 1 0 0 0 0
#> GSM247703 2 0 1 0 1 0 0 0
#> GSM247739 5 0 1 0 0 0 0 1
#> GSM247715 4 0 1 0 0 0 1 0
#> GSM247829 3 0 1 0 0 1 0 0
#> GSM247842 1 0 1 1 0 0 0 0
#> GSM247805 2 0 1 0 1 0 0 0
#> GSM247786 5 0 1 0 0 0 0 1
#> GSM247812 3 0 1 0 0 1 0 0
#> GSM247776 1 0 1 1 0 0 0 0
#> GSM247850 1 0 1 1 0 0 0 0
#> GSM247717 2 0 1 0 1 0 0 0
#> GSM247784 5 0 1 0 0 0 0 1
#> GSM247834 4 0 1 0 0 0 1 0
#> GSM247783 3 0 1 0 0 1 0 0
#> GSM247846 1 0 1 1 0 0 0 0
#> GSM247822 2 0 1 0 1 0 0 0
#> GSM247710 5 0 1 0 0 0 0 1
#> GSM247713 4 0 1 0 0 0 1 0
#> GSM247840 3 0 1 0 0 1 0 0
#> GSM247733 1 0 1 1 0 0 0 0
#> GSM247852 1 0 1 1 0 0 0 0
#> GSM247790 2 0 1 0 1 0 0 0
#> GSM247730 5 0 1 0 0 0 0 1
#> GSM247824 3 0 1 0 0 1 0 0
#> GSM247770 1 0 1 1 0 0 0 0
#> GSM247711 2 0 1 0 1 0 0 0
#> GSM247782 5 0 1 0 0 0 0 1
#> GSM247836 4 0 1 0 0 0 1 0
#> GSM247785 3 0 1 0 0 1 0 0
#> GSM247847 1 0 1 1 0 0 0 0
#> GSM247750 2 0 1 0 1 0 0 0
#> GSM247788 5 0 1 0 0 0 0 1
#> GSM247849 4 0 1 0 0 0 1 0
#> GSM247772 3 0 1 0 0 1 0 0
#> GSM247760 1 0 1 1 0 0 0 0
#> GSM247764 2 0 1 0 1 0 0 0
#> GSM247851 2 0 1 0 1 0 0 0
#> GSM247714 5 0 1 0 0 0 0 1
#> GSM247828 4 0 1 0 0 0 1 0
#> GSM247704 3 0 1 0 0 1 0 0
#> GSM247818 1 0 1 1 0 0 0 0
#> GSM247823 2 0 1 0 1 0 0 0
#> GSM247706 5 0 1 0 0 0 0 1
#> GSM247835 3 0 1 0 0 1 0 0
#> GSM247734 1 0 1 1 0 0 0 0
#> GSM247819 2 0 1 0 1 0 0 0
#> GSM247809 5 0 1 0 0 0 0 1
#> GSM247830 3 0 1 0 0 1 0 0
#> GSM247833 1 0 1 1 0 0 0 0
#> GSM247738 2 0 1 0 1 0 0 0
#> GSM247716 5 0 1 0 0 0 0 1
#> GSM247747 3 0 1 0 0 1 0 0
#> GSM247722 1 0 1 1 0 0 0 0
#> GSM247816 2 0 1 0 1 0 0 0
#> GSM247839 5 0 1 0 0 0 0 1
#> GSM247821 4 0 1 0 0 0 1 0
#> GSM247798 3 0 1 0 0 1 0 0
#> GSM247838 1 0 1 1 0 0 0 0
#> GSM247721 2 0 1 0 1 0 0 0
#> GSM247781 5 0 1 0 0 0 0 1
#> GSM247762 4 0 1 0 0 0 1 0
#> GSM247825 3 0 1 0 0 1 0 0
#> GSM247777 1 0 1 1 0 0 0 0
#> GSM247761 2 0 1 0 1 0 0 0
#> GSM247720 5 0 1 0 0 0 0 1
#> GSM247814 3 0 1 0 0 1 0 0
#> GSM247732 1 0 1 1 0 0 0 0
#> GSM247708 2 0 1 0 1 0 0 0
#> GSM247740 5 0 1 0 0 0 0 1
#> GSM247749 4 0 1 0 0 0 1 0
#> GSM247767 3 0 1 0 0 1 0 0
#> GSM247748 1 0 1 1 0 0 0 0
#> GSM247705 2 0 1 0 1 0 0 0
#> GSM247746 5 0 1 0 0 0 0 1
#> GSM247752 4 0 1 0 0 0 1 0
#> GSM247769 3 0 1 0 0 1 0 0
#> GSM247753 1 0 1 1 0 0 0 0
#> GSM247723 2 0 1 0 1 0 0 0
#> GSM247779 5 0 1 0 0 0 0 1
#> GSM247756 4 0 1 0 0 0 1 0
#> GSM247826 3 0 1 0 0 1 0 0
#> GSM247775 1 0 1 1 0 0 0 0
#> GSM247741 2 0 1 0 1 0 0 0
#> GSM247799 5 0 1 0 0 0 0 1
#> GSM247778 4 0 1 0 0 0 1 0
#> GSM247806 3 0 1 0 0 1 0 0
#> GSM247815 1 0 1 1 0 0 0 0
#> GSM247735 2 0 1 0 1 0 0 0
#> GSM247831 5 0 1 0 0 0 0 1
#> GSM247845 4 0 1 0 0 0 1 0
#> GSM247791 3 0 1 0 0 1 0 0
#> GSM247780 1 0 1 1 0 0 0 0
#> GSM247853 1 0 1 1 0 0 0 0
#> GSM247800 2 0 1 0 1 0 0 0
#> GSM247729 5 0 1 0 0 0 0 1
#> GSM247810 4 0 1 0 0 0 1 0
#> GSM247844 3 0 1 0 0 1 0 0
#> GSM247793 1 0 1 1 0 0 0 0
#> GSM247759 2 0 1 0 1 0 0 0
#> GSM247724 5 0 1 0 0 0 0 1
#> GSM247817 3 0 1 0 0 1 0 0
#> GSM247727 1 0 1 1 0 0 0 0
#> GSM247796 2 0 1 0 1 0 0 0
#> GSM247725 5 0 1 0 0 0 0 1
#> GSM247801 4 0 1 0 0 0 1 0
#> GSM247731 3 0 1 0 0 1 0 0
#> GSM247765 1 0 1 1 0 0 0 0
#> GSM247792 2 0 1 0 1 0 0 0
#> GSM247726 5 0 1 0 0 0 0 1
#> GSM247803 4 0 1 0 0 0 1 0
#> GSM247728 3 0 1 0 0 1 0 0
#> GSM247768 1 0 1 1 0 0 0 0
#> GSM247745 2 0 1 0 1 0 0 0
#> GSM247855 2 0 1 0 1 0 0 0
#> GSM247804 5 0 1 0 0 0 0 1
#> GSM247774 4 0 1 0 0 0 1 0
#> GSM247807 3 0 1 0 0 1 0 0
#> GSM247813 1 0 1 1 0 0 0 0
#> GSM247736 2 0 1 0 1 0 0 0
#> GSM247712 5 0 1 0 0 0 0 1
#> GSM247797 4 0 1 0 0 0 1 0
#> GSM247743 3 0 1 0 0 1 0 0
#> GSM247719 1 0 1 1 0 0 0 0
#> GSM247707 2 0 1 0 1 0 0 0
#> GSM247737 5 0 1 0 0 0 0 1
#> GSM247827 3 0 1 0 0 1 0 0
#> GSM247848 1 0 1 1 0 0 0 0
#> GSM247794 2 0 1 0 1 0 0 0
#> GSM247757 5 0 1 0 0 0 0 1
#> GSM247744 4 0 1 0 0 0 1 0
#> GSM247751 3 0 1 0 0 1 0 0
#> GSM247837 1 0 1 1 0 0 0 0
#> GSM247754 2 0 1 0 1 0 0 0
#> GSM247789 5 0 1 0 0 0 0 1
#> GSM247802 4 0 1 0 0 0 1 0
#> GSM247771 3 0 1 0 0 1 0 0
#> GSM247763 1 0 1 1 0 0 0 0
#> GSM247808 2 0 1 0 1 0 0 0
#> GSM247787 5 0 1 0 0 0 0 1
#> GSM247843 4 0 1 0 0 0 1 0
#> GSM247811 3 0 1 0 0 1 0 0
#> GSM247773 1 0 1 1 0 0 0 0
#> GSM247766 2 0 1 0 1 0 0 0
#> GSM247718 5 0 1 0 0 0 0 1
#> GSM247832 4 0 1 0 0 0 1 0
#> GSM247709 3 0 1 0 0 1 0 0
#> GSM247820 1 0 1 1 0 0 0 0
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247854 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247758 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247742 4 0.0146 0.9659 0 0.000 0 0.996 0.000 0.004
#> GSM247755 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247841 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247703 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247739 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247715 4 0.0146 0.9659 0 0.000 0 0.996 0.000 0.004
#> GSM247829 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247842 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247805 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247786 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247812 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247776 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247850 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247717 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247784 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247834 4 0.0146 0.9668 0 0.000 0 0.996 0.000 0.004
#> GSM247783 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247846 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247822 2 0.0260 0.9940 0 0.992 0 0.000 0.000 0.008
#> GSM247710 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247713 4 0.0547 0.9550 0 0.000 0 0.980 0.000 0.020
#> GSM247840 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247733 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247852 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247790 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247730 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247824 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247770 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247711 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247782 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247836 4 0.0146 0.9659 0 0.000 0 0.996 0.000 0.004
#> GSM247785 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247847 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247750 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247788 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247849 4 0.0000 0.9674 0 0.000 0 1.000 0.000 0.000
#> GSM247772 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247760 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247764 2 0.0363 0.9932 0 0.988 0 0.000 0.000 0.012
#> GSM247851 2 0.0363 0.9932 0 0.988 0 0.000 0.000 0.012
#> GSM247714 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247828 4 0.0000 0.9674 0 0.000 0 1.000 0.000 0.000
#> GSM247704 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247818 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247823 2 0.0458 0.9916 0 0.984 0 0.000 0.000 0.016
#> GSM247706 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247835 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247734 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247819 2 0.0363 0.9932 0 0.988 0 0.000 0.000 0.012
#> GSM247809 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247830 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247833 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247738 2 0.0146 0.9930 0 0.996 0 0.000 0.000 0.004
#> GSM247716 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247747 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247722 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247816 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247839 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247821 4 0.0146 0.9668 0 0.000 0 0.996 0.000 0.004
#> GSM247798 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247838 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247721 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247781 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247762 4 0.1957 0.8414 0 0.000 0 0.888 0.000 0.112
#> GSM247825 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247777 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247761 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247720 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247814 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247732 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247708 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247740 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247749 4 0.0146 0.9668 0 0.000 0 0.996 0.000 0.004
#> GSM247767 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247748 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247705 2 0.0363 0.9932 0 0.988 0 0.000 0.000 0.012
#> GSM247746 5 0.0260 0.9902 0 0.000 0 0.000 0.992 0.008
#> GSM247752 4 0.3531 0.3900 0 0.000 0 0.672 0.000 0.328
#> GSM247769 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247753 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247723 2 0.0458 0.9914 0 0.984 0 0.000 0.000 0.016
#> GSM247779 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247756 4 0.0000 0.9674 0 0.000 0 1.000 0.000 0.000
#> GSM247826 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247775 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247741 2 0.0363 0.9932 0 0.988 0 0.000 0.000 0.012
#> GSM247799 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247778 4 0.0000 0.9674 0 0.000 0 1.000 0.000 0.000
#> GSM247806 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247815 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247735 2 0.0363 0.9932 0 0.988 0 0.000 0.000 0.012
#> GSM247831 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247845 4 0.0000 0.9674 0 0.000 0 1.000 0.000 0.000
#> GSM247791 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247780 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247853 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247800 2 0.0458 0.9914 0 0.984 0 0.000 0.000 0.016
#> GSM247729 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247810 4 0.0146 0.9668 0 0.000 0 0.996 0.000 0.004
#> GSM247844 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247793 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247759 2 0.0363 0.9932 0 0.988 0 0.000 0.000 0.012
#> GSM247724 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247817 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247727 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247796 2 0.0458 0.9914 0 0.984 0 0.000 0.000 0.016
#> GSM247725 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247801 4 0.0146 0.9668 0 0.000 0 0.996 0.000 0.004
#> GSM247731 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247765 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247792 2 0.0363 0.9932 0 0.988 0 0.000 0.000 0.012
#> GSM247726 6 0.3971 -0.0764 0 0.000 0 0.004 0.448 0.548
#> GSM247803 6 0.3866 -0.3185 0 0.000 0 0.484 0.000 0.516
#> GSM247728 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247768 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247745 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247855 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247804 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247774 4 0.0865 0.9356 0 0.000 0 0.964 0.000 0.036
#> GSM247807 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247813 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247736 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247712 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247797 4 0.0547 0.9550 0 0.000 0 0.980 0.000 0.020
#> GSM247743 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247719 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247707 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247737 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247827 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247848 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247794 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247757 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247744 4 0.0146 0.9659 0 0.000 0 0.996 0.000 0.004
#> GSM247751 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247837 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247754 2 0.0363 0.9932 0 0.988 0 0.000 0.000 0.012
#> GSM247789 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247802 4 0.0146 0.9668 0 0.000 0 0.996 0.000 0.004
#> GSM247771 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247763 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247808 2 0.0000 0.9949 0 1.000 0 0.000 0.000 0.000
#> GSM247787 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247843 4 0.0000 0.9674 0 0.000 0 1.000 0.000 0.000
#> GSM247811 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247773 1 0.0000 1.0000 1 0.000 0 0.000 0.000 0.000
#> GSM247766 2 0.0363 0.9932 0 0.988 0 0.000 0.000 0.012
#> GSM247718 5 0.0000 0.9997 0 0.000 0 0.000 1.000 0.000
#> GSM247832 4 0.0000 0.9674 0 0.000 0 1.000 0.000 0.000
#> GSM247709 3 0.0000 1.0000 0 0.000 1 0.000 0.000 0.000
#> GSM247820 1 0.0000 1.0000 1 0.000 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> CV:NMF 153 1 1.000 4.63e-32 2
#> CV:NMF 153 1 0.985 2.17e-61 3
#> CV:NMF 153 1 0.964 1.16e-90 4
#> CV:NMF 153 1 0.989 6.51e-120 5
#> CV:NMF 150 1 0.998 2.29e-117 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.4711 0.529 0.529
#> 3 3 1.000 0.999 0.999 0.1433 0.933 0.873
#> 4 4 1.000 1.000 1.000 0.3208 0.827 0.625
#> 5 5 0.907 0.996 0.945 0.0961 0.909 0.686
#> 6 6 1.000 0.992 0.996 0.0341 0.996 0.982
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 3 4
There is also optional best \(k\) = 2 3 4 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0 1 0 1
#> GSM247854 2 0 1 0 1
#> GSM247758 2 0 1 0 1
#> GSM247742 1 0 1 1 0
#> GSM247755 2 0 1 0 1
#> GSM247841 1 0 1 1 0
#> GSM247703 2 0 1 0 1
#> GSM247739 2 0 1 0 1
#> GSM247715 1 0 1 1 0
#> GSM247829 2 0 1 0 1
#> GSM247842 1 0 1 1 0
#> GSM247805 2 0 1 0 1
#> GSM247786 2 0 1 0 1
#> GSM247812 2 0 1 0 1
#> GSM247776 1 0 1 1 0
#> GSM247850 1 0 1 1 0
#> GSM247717 2 0 1 0 1
#> GSM247784 2 0 1 0 1
#> GSM247834 1 0 1 1 0
#> GSM247783 2 0 1 0 1
#> GSM247846 1 0 1 1 0
#> GSM247822 2 0 1 0 1
#> GSM247710 2 0 1 0 1
#> GSM247713 1 0 1 1 0
#> GSM247840 2 0 1 0 1
#> GSM247733 1 0 1 1 0
#> GSM247852 1 0 1 1 0
#> GSM247790 2 0 1 0 1
#> GSM247730 2 0 1 0 1
#> GSM247824 2 0 1 0 1
#> GSM247770 1 0 1 1 0
#> GSM247711 2 0 1 0 1
#> GSM247782 2 0 1 0 1
#> GSM247836 1 0 1 1 0
#> GSM247785 2 0 1 0 1
#> GSM247847 1 0 1 1 0
#> GSM247750 2 0 1 0 1
#> GSM247788 2 0 1 0 1
#> GSM247849 1 0 1 1 0
#> GSM247772 2 0 1 0 1
#> GSM247760 1 0 1 1 0
#> GSM247764 2 0 1 0 1
#> GSM247851 2 0 1 0 1
#> GSM247714 2 0 1 0 1
#> GSM247828 1 0 1 1 0
#> GSM247704 2 0 1 0 1
#> GSM247818 1 0 1 1 0
#> GSM247823 2 0 1 0 1
#> GSM247706 2 0 1 0 1
#> GSM247835 2 0 1 0 1
#> GSM247734 1 0 1 1 0
#> GSM247819 2 0 1 0 1
#> GSM247809 2 0 1 0 1
#> GSM247830 2 0 1 0 1
#> GSM247833 1 0 1 1 0
#> GSM247738 2 0 1 0 1
#> GSM247716 2 0 1 0 1
#> GSM247747 2 0 1 0 1
#> GSM247722 1 0 1 1 0
#> GSM247816 2 0 1 0 1
#> GSM247839 2 0 1 0 1
#> GSM247821 1 0 1 1 0
#> GSM247798 2 0 1 0 1
#> GSM247838 1 0 1 1 0
#> GSM247721 2 0 1 0 1
#> GSM247781 2 0 1 0 1
#> GSM247762 1 0 1 1 0
#> GSM247825 2 0 1 0 1
#> GSM247777 1 0 1 1 0
#> GSM247761 2 0 1 0 1
#> GSM247720 2 0 1 0 1
#> GSM247814 2 0 1 0 1
#> GSM247732 1 0 1 1 0
#> GSM247708 2 0 1 0 1
#> GSM247740 2 0 1 0 1
#> GSM247749 1 0 1 1 0
#> GSM247767 2 0 1 0 1
#> GSM247748 1 0 1 1 0
#> GSM247705 2 0 1 0 1
#> GSM247746 2 0 1 0 1
#> GSM247752 1 0 1 1 0
#> GSM247769 2 0 1 0 1
#> GSM247753 1 0 1 1 0
#> GSM247723 2 0 1 0 1
#> GSM247779 2 0 1 0 1
#> GSM247756 1 0 1 1 0
#> GSM247826 2 0 1 0 1
#> GSM247775 1 0 1 1 0
#> GSM247741 2 0 1 0 1
#> GSM247799 2 0 1 0 1
#> GSM247778 1 0 1 1 0
#> GSM247806 2 0 1 0 1
#> GSM247815 1 0 1 1 0
#> GSM247735 2 0 1 0 1
#> GSM247831 2 0 1 0 1
#> GSM247845 1 0 1 1 0
#> GSM247791 2 0 1 0 1
#> GSM247780 1 0 1 1 0
#> GSM247853 1 0 1 1 0
#> GSM247800 2 0 1 0 1
#> GSM247729 2 0 1 0 1
#> GSM247810 1 0 1 1 0
#> GSM247844 2 0 1 0 1
#> GSM247793 1 0 1 1 0
#> GSM247759 2 0 1 0 1
#> GSM247724 2 0 1 0 1
#> GSM247817 2 0 1 0 1
#> GSM247727 1 0 1 1 0
#> GSM247796 2 0 1 0 1
#> GSM247725 2 0 1 0 1
#> GSM247801 1 0 1 1 0
#> GSM247731 2 0 1 0 1
#> GSM247765 1 0 1 1 0
#> GSM247792 2 0 1 0 1
#> GSM247726 2 0 1 0 1
#> GSM247803 1 0 1 1 0
#> GSM247728 2 0 1 0 1
#> GSM247768 1 0 1 1 0
#> GSM247745 2 0 1 0 1
#> GSM247855 2 0 1 0 1
#> GSM247804 2 0 1 0 1
#> GSM247774 1 0 1 1 0
#> GSM247807 2 0 1 0 1
#> GSM247813 1 0 1 1 0
#> GSM247736 2 0 1 0 1
#> GSM247712 2 0 1 0 1
#> GSM247797 1 0 1 1 0
#> GSM247743 2 0 1 0 1
#> GSM247719 1 0 1 1 0
#> GSM247707 2 0 1 0 1
#> GSM247737 2 0 1 0 1
#> GSM247827 2 0 1 0 1
#> GSM247848 1 0 1 1 0
#> GSM247794 2 0 1 0 1
#> GSM247757 2 0 1 0 1
#> GSM247744 1 0 1 1 0
#> GSM247751 2 0 1 0 1
#> GSM247837 1 0 1 1 0
#> GSM247754 2 0 1 0 1
#> GSM247789 2 0 1 0 1
#> GSM247802 1 0 1 1 0
#> GSM247771 2 0 1 0 1
#> GSM247763 1 0 1 1 0
#> GSM247808 2 0 1 0 1
#> GSM247787 2 0 1 0 1
#> GSM247843 1 0 1 1 0
#> GSM247811 2 0 1 0 1
#> GSM247773 1 0 1 1 0
#> GSM247766 2 0 1 0 1
#> GSM247718 2 0 1 0 1
#> GSM247832 1 0 1 1 0
#> GSM247709 2 0 1 0 1
#> GSM247820 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247854 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247758 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247742 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247755 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247841 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247703 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247739 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247715 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247829 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247842 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247805 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247786 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247812 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247776 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247850 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247717 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247784 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247834 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247783 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247846 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247822 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247710 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247713 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247840 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247733 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247852 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247790 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247730 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247824 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247770 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247711 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247782 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247836 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247785 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247847 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247750 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247788 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247849 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247772 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247760 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247764 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247851 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247714 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247828 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247704 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247818 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247823 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247706 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247835 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247734 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247819 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247809 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247830 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247833 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247738 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247716 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247747 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247722 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247816 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247839 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247821 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247798 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247838 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247721 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247781 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247762 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247825 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247777 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247761 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247720 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247814 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247732 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247708 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247740 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247749 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247767 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247748 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247705 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247746 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247752 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247769 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247753 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247723 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247779 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247756 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247826 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247775 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247741 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247799 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247778 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247806 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247815 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247735 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247831 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247845 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247791 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247780 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247853 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247800 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247729 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247810 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247844 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247793 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247759 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247724 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247817 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247727 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247796 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247725 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247801 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247731 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247765 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247792 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247726 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247803 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247728 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247768 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247745 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247855 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247804 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247774 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247807 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247813 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247736 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247712 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247797 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247743 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247719 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247707 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247737 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247827 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247848 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247794 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247757 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247744 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247751 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247837 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247754 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247789 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247802 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247771 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247763 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247808 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247787 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247843 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247811 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247773 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247766 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247718 2 0.0000 0.999 0.000 1.000 0.000
#> GSM247832 3 0.0237 1.000 0.004 0.000 0.996
#> GSM247709 2 0.0237 0.998 0.000 0.996 0.004
#> GSM247820 1 0.0000 1.000 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0 1 0 1 0 0
#> GSM247854 2 0 1 0 1 0 0
#> GSM247758 2 0 1 0 1 0 0
#> GSM247742 4 0 1 0 0 0 1
#> GSM247755 3 0 1 0 0 1 0
#> GSM247841 1 0 1 1 0 0 0
#> GSM247703 2 0 1 0 1 0 0
#> GSM247739 2 0 1 0 1 0 0
#> GSM247715 4 0 1 0 0 0 1
#> GSM247829 3 0 1 0 0 1 0
#> GSM247842 1 0 1 1 0 0 0
#> GSM247805 2 0 1 0 1 0 0
#> GSM247786 2 0 1 0 1 0 0
#> GSM247812 3 0 1 0 0 1 0
#> GSM247776 1 0 1 1 0 0 0
#> GSM247850 1 0 1 1 0 0 0
#> GSM247717 2 0 1 0 1 0 0
#> GSM247784 2 0 1 0 1 0 0
#> GSM247834 4 0 1 0 0 0 1
#> GSM247783 3 0 1 0 0 1 0
#> GSM247846 1 0 1 1 0 0 0
#> GSM247822 2 0 1 0 1 0 0
#> GSM247710 2 0 1 0 1 0 0
#> GSM247713 4 0 1 0 0 0 1
#> GSM247840 3 0 1 0 0 1 0
#> GSM247733 1 0 1 1 0 0 0
#> GSM247852 1 0 1 1 0 0 0
#> GSM247790 2 0 1 0 1 0 0
#> GSM247730 2 0 1 0 1 0 0
#> GSM247824 3 0 1 0 0 1 0
#> GSM247770 1 0 1 1 0 0 0
#> GSM247711 2 0 1 0 1 0 0
#> GSM247782 2 0 1 0 1 0 0
#> GSM247836 4 0 1 0 0 0 1
#> GSM247785 3 0 1 0 0 1 0
#> GSM247847 1 0 1 1 0 0 0
#> GSM247750 2 0 1 0 1 0 0
#> GSM247788 2 0 1 0 1 0 0
#> GSM247849 4 0 1 0 0 0 1
#> GSM247772 3 0 1 0 0 1 0
#> GSM247760 1 0 1 1 0 0 0
#> GSM247764 2 0 1 0 1 0 0
#> GSM247851 2 0 1 0 1 0 0
#> GSM247714 2 0 1 0 1 0 0
#> GSM247828 4 0 1 0 0 0 1
#> GSM247704 3 0 1 0 0 1 0
#> GSM247818 1 0 1 1 0 0 0
#> GSM247823 2 0 1 0 1 0 0
#> GSM247706 2 0 1 0 1 0 0
#> GSM247835 3 0 1 0 0 1 0
#> GSM247734 1 0 1 1 0 0 0
#> GSM247819 2 0 1 0 1 0 0
#> GSM247809 2 0 1 0 1 0 0
#> GSM247830 3 0 1 0 0 1 0
#> GSM247833 1 0 1 1 0 0 0
#> GSM247738 2 0 1 0 1 0 0
#> GSM247716 2 0 1 0 1 0 0
#> GSM247747 3 0 1 0 0 1 0
#> GSM247722 1 0 1 1 0 0 0
#> GSM247816 2 0 1 0 1 0 0
#> GSM247839 2 0 1 0 1 0 0
#> GSM247821 4 0 1 0 0 0 1
#> GSM247798 3 0 1 0 0 1 0
#> GSM247838 1 0 1 1 0 0 0
#> GSM247721 2 0 1 0 1 0 0
#> GSM247781 2 0 1 0 1 0 0
#> GSM247762 4 0 1 0 0 0 1
#> GSM247825 3 0 1 0 0 1 0
#> GSM247777 1 0 1 1 0 0 0
#> GSM247761 2 0 1 0 1 0 0
#> GSM247720 2 0 1 0 1 0 0
#> GSM247814 3 0 1 0 0 1 0
#> GSM247732 1 0 1 1 0 0 0
#> GSM247708 2 0 1 0 1 0 0
#> GSM247740 2 0 1 0 1 0 0
#> GSM247749 4 0 1 0 0 0 1
#> GSM247767 3 0 1 0 0 1 0
#> GSM247748 1 0 1 1 0 0 0
#> GSM247705 2 0 1 0 1 0 0
#> GSM247746 2 0 1 0 1 0 0
#> GSM247752 4 0 1 0 0 0 1
#> GSM247769 3 0 1 0 0 1 0
#> GSM247753 1 0 1 1 0 0 0
#> GSM247723 2 0 1 0 1 0 0
#> GSM247779 2 0 1 0 1 0 0
#> GSM247756 4 0 1 0 0 0 1
#> GSM247826 3 0 1 0 0 1 0
#> GSM247775 1 0 1 1 0 0 0
#> GSM247741 2 0 1 0 1 0 0
#> GSM247799 2 0 1 0 1 0 0
#> GSM247778 4 0 1 0 0 0 1
#> GSM247806 3 0 1 0 0 1 0
#> GSM247815 1 0 1 1 0 0 0
#> GSM247735 2 0 1 0 1 0 0
#> GSM247831 2 0 1 0 1 0 0
#> GSM247845 4 0 1 0 0 0 1
#> GSM247791 3 0 1 0 0 1 0
#> GSM247780 1 0 1 1 0 0 0
#> GSM247853 1 0 1 1 0 0 0
#> GSM247800 2 0 1 0 1 0 0
#> GSM247729 2 0 1 0 1 0 0
#> GSM247810 4 0 1 0 0 0 1
#> GSM247844 3 0 1 0 0 1 0
#> GSM247793 1 0 1 1 0 0 0
#> GSM247759 2 0 1 0 1 0 0
#> GSM247724 2 0 1 0 1 0 0
#> GSM247817 3 0 1 0 0 1 0
#> GSM247727 1 0 1 1 0 0 0
#> GSM247796 2 0 1 0 1 0 0
#> GSM247725 2 0 1 0 1 0 0
#> GSM247801 4 0 1 0 0 0 1
#> GSM247731 3 0 1 0 0 1 0
#> GSM247765 1 0 1 1 0 0 0
#> GSM247792 2 0 1 0 1 0 0
#> GSM247726 2 0 1 0 1 0 0
#> GSM247803 4 0 1 0 0 0 1
#> GSM247728 3 0 1 0 0 1 0
#> GSM247768 1 0 1 1 0 0 0
#> GSM247745 2 0 1 0 1 0 0
#> GSM247855 2 0 1 0 1 0 0
#> GSM247804 2 0 1 0 1 0 0
#> GSM247774 4 0 1 0 0 0 1
#> GSM247807 3 0 1 0 0 1 0
#> GSM247813 1 0 1 1 0 0 0
#> GSM247736 2 0 1 0 1 0 0
#> GSM247712 2 0 1 0 1 0 0
#> GSM247797 4 0 1 0 0 0 1
#> GSM247743 3 0 1 0 0 1 0
#> GSM247719 1 0 1 1 0 0 0
#> GSM247707 2 0 1 0 1 0 0
#> GSM247737 2 0 1 0 1 0 0
#> GSM247827 3 0 1 0 0 1 0
#> GSM247848 1 0 1 1 0 0 0
#> GSM247794 2 0 1 0 1 0 0
#> GSM247757 2 0 1 0 1 0 0
#> GSM247744 4 0 1 0 0 0 1
#> GSM247751 3 0 1 0 0 1 0
#> GSM247837 1 0 1 1 0 0 0
#> GSM247754 2 0 1 0 1 0 0
#> GSM247789 2 0 1 0 1 0 0
#> GSM247802 4 0 1 0 0 0 1
#> GSM247771 3 0 1 0 0 1 0
#> GSM247763 1 0 1 1 0 0 0
#> GSM247808 2 0 1 0 1 0 0
#> GSM247787 2 0 1 0 1 0 0
#> GSM247843 4 0 1 0 0 0 1
#> GSM247811 3 0 1 0 0 1 0
#> GSM247773 1 0 1 1 0 0 0
#> GSM247766 2 0 1 0 1 0 0
#> GSM247718 2 0 1 0 1 0 0
#> GSM247832 4 0 1 0 0 0 1
#> GSM247709 3 0 1 0 0 1 0
#> GSM247820 1 0 1 1 0 0 0
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247854 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247758 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247742 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247755 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247841 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247703 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247739 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247715 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247829 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247842 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247805 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247786 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247812 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247776 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247850 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247717 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247784 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247834 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247783 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247846 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247822 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247710 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247713 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247840 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247733 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247852 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247790 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247730 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247824 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247770 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247711 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247782 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247836 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247785 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247847 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247750 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247788 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247849 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247772 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247760 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247764 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247851 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247714 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247828 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247704 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247818 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247823 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247706 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247835 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247734 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247819 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247809 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247830 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247833 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247738 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247716 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247747 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247722 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247816 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247839 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247821 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247798 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247838 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247721 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247781 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247762 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247825 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247777 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247761 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247720 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247814 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247732 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247708 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247740 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247749 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247767 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247748 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247705 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247746 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247752 4 0.353 0.825 0 0.256 0 0.744 0.000
#> GSM247769 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247753 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247723 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247779 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247756 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247826 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247775 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247741 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247799 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247778 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247806 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247815 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247735 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247831 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247845 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247791 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247780 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247853 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247800 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247729 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247810 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247844 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247793 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247759 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247724 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247817 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247727 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247796 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247725 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247801 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247731 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247765 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247792 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247726 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247803 4 0.353 0.825 0 0.256 0 0.744 0.000
#> GSM247728 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247768 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247745 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247855 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247804 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247774 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247807 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247813 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247736 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247712 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247797 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247743 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247719 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247707 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247737 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247827 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247848 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247794 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247757 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247744 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247751 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247837 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247754 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247789 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247802 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247771 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247763 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247808 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247787 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247843 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247811 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247773 1 0.000 1.000 1 0.000 0 0.000 0.000
#> GSM247766 2 0.353 1.000 0 0.744 0 0.000 0.256
#> GSM247718 5 0.000 1.000 0 0.000 0 0.000 1.000
#> GSM247832 4 0.000 0.985 0 0.000 0 1.000 0.000
#> GSM247709 3 0.000 1.000 0 0.000 1 0.000 0.000
#> GSM247820 1 0.000 1.000 1 0.000 0 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247854 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247758 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247742 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247755 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247841 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247703 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247739 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247715 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247829 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247842 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247805 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247786 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247812 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247776 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247850 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247717 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247784 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247834 4 0.0260 0.967 0 0 0 0.992 0 0.008
#> GSM247783 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247846 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247822 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247710 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247713 4 0.0632 0.956 0 0 0 0.976 0 0.024
#> GSM247840 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247733 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247852 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247790 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247730 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247824 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247770 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247711 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247782 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247836 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247785 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247847 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247750 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247788 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247849 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247772 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247760 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247764 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247851 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247714 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247828 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247704 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247818 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247823 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247706 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247835 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247734 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247819 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247809 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247830 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247833 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247738 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247716 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247747 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247722 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247816 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247839 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247821 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247798 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247838 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247721 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247781 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247762 4 0.3050 0.729 0 0 0 0.764 0 0.236
#> GSM247825 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247777 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247761 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247720 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247814 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247732 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247708 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247740 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247749 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247767 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247748 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247705 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247746 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247752 6 0.0000 1.000 0 0 0 0.000 0 1.000
#> GSM247769 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247753 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247723 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247779 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247756 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247826 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247775 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247741 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247799 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247778 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247806 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247815 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247735 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247831 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247845 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247791 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247780 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247853 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247800 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247729 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247810 4 0.0146 0.969 0 0 0 0.996 0 0.004
#> GSM247844 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247793 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247759 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247724 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247817 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247727 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247796 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247725 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247801 4 0.2300 0.843 0 0 0 0.856 0 0.144
#> GSM247731 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247765 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247792 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247726 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247803 6 0.0000 1.000 0 0 0 0.000 0 1.000
#> GSM247728 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247768 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247745 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247855 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247804 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247774 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247807 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247813 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247736 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247712 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247797 4 0.2491 0.824 0 0 0 0.836 0 0.164
#> GSM247743 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247719 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247707 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247737 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247827 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247848 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247794 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247757 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247744 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247751 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247837 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247754 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247789 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247802 4 0.0260 0.967 0 0 0 0.992 0 0.008
#> GSM247771 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247763 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247808 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247787 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247843 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247811 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247773 1 0.0000 1.000 1 0 0 0.000 0 0.000
#> GSM247766 2 0.0000 1.000 0 1 0 0.000 0 0.000
#> GSM247718 5 0.0000 1.000 0 0 0 0.000 1 0.000
#> GSM247832 4 0.0000 0.970 0 0 0 1.000 0 0.000
#> GSM247709 3 0.0000 1.000 0 0 1 0.000 0 0.000
#> GSM247820 1 0.0000 1.000 1 0 0 0.000 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> MAD:hclust 153 1 1.000 4.63e-32 2
#> MAD:hclust 153 1 0.875 2.17e-61 3
#> MAD:hclust 153 1 0.964 1.16e-90 4
#> MAD:hclust 153 1 0.989 6.51e-120 5
#> MAD:hclust 153 1 0.740 8.52e-117 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.420 0.924 0.923 0.4553 0.529 0.529
#> 3 3 0.669 0.605 0.690 0.3339 0.827 0.673
#> 4 4 0.656 0.760 0.733 0.1472 0.819 0.594
#> 5 5 0.713 0.953 0.826 0.0786 0.842 0.557
#> 6 6 0.745 0.918 0.831 0.0468 1.000 1.000
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 5
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0.5408 0.909 0.124 0.876
#> GSM247854 2 0.5408 0.909 0.124 0.876
#> GSM247758 2 0.7883 0.859 0.236 0.764
#> GSM247742 1 0.0376 0.997 0.996 0.004
#> GSM247755 2 0.0672 0.871 0.008 0.992
#> GSM247841 1 0.0000 0.998 1.000 0.000
#> GSM247703 2 0.5408 0.909 0.124 0.876
#> GSM247739 2 0.7883 0.859 0.236 0.764
#> GSM247715 1 0.0376 0.997 0.996 0.004
#> GSM247829 2 0.0672 0.871 0.008 0.992
#> GSM247842 1 0.0000 0.998 1.000 0.000
#> GSM247805 2 0.5408 0.909 0.124 0.876
#> GSM247786 2 0.7883 0.859 0.236 0.764
#> GSM247812 2 0.0672 0.871 0.008 0.992
#> GSM247776 1 0.0000 0.998 1.000 0.000
#> GSM247850 1 0.0000 0.998 1.000 0.000
#> GSM247717 2 0.5408 0.909 0.124 0.876
#> GSM247784 2 0.7883 0.859 0.236 0.764
#> GSM247834 1 0.0376 0.997 0.996 0.004
#> GSM247783 2 0.0672 0.871 0.008 0.992
#> GSM247846 1 0.0000 0.998 1.000 0.000
#> GSM247822 2 0.5408 0.909 0.124 0.876
#> GSM247710 2 0.7883 0.859 0.236 0.764
#> GSM247713 1 0.0376 0.997 0.996 0.004
#> GSM247840 2 0.0672 0.871 0.008 0.992
#> GSM247733 1 0.0000 0.998 1.000 0.000
#> GSM247852 1 0.0000 0.998 1.000 0.000
#> GSM247790 2 0.5408 0.909 0.124 0.876
#> GSM247730 2 0.7883 0.859 0.236 0.764
#> GSM247824 2 0.0672 0.871 0.008 0.992
#> GSM247770 1 0.0000 0.998 1.000 0.000
#> GSM247711 2 0.5408 0.909 0.124 0.876
#> GSM247782 2 0.7883 0.859 0.236 0.764
#> GSM247836 1 0.0376 0.997 0.996 0.004
#> GSM247785 2 0.0672 0.871 0.008 0.992
#> GSM247847 1 0.0000 0.998 1.000 0.000
#> GSM247750 2 0.5408 0.909 0.124 0.876
#> GSM247788 2 0.7883 0.859 0.236 0.764
#> GSM247849 1 0.0376 0.997 0.996 0.004
#> GSM247772 2 0.0672 0.871 0.008 0.992
#> GSM247760 1 0.0000 0.998 1.000 0.000
#> GSM247764 2 0.5408 0.909 0.124 0.876
#> GSM247851 2 0.5408 0.909 0.124 0.876
#> GSM247714 2 0.7883 0.859 0.236 0.764
#> GSM247828 1 0.0376 0.997 0.996 0.004
#> GSM247704 2 0.0672 0.871 0.008 0.992
#> GSM247818 1 0.0000 0.998 1.000 0.000
#> GSM247823 2 0.5408 0.909 0.124 0.876
#> GSM247706 2 0.7883 0.859 0.236 0.764
#> GSM247835 2 0.0672 0.871 0.008 0.992
#> GSM247734 1 0.0000 0.998 1.000 0.000
#> GSM247819 2 0.5408 0.909 0.124 0.876
#> GSM247809 2 0.7883 0.859 0.236 0.764
#> GSM247830 2 0.0672 0.871 0.008 0.992
#> GSM247833 1 0.0000 0.998 1.000 0.000
#> GSM247738 2 0.5408 0.909 0.124 0.876
#> GSM247716 2 0.7883 0.859 0.236 0.764
#> GSM247747 2 0.0672 0.871 0.008 0.992
#> GSM247722 1 0.0000 0.998 1.000 0.000
#> GSM247816 2 0.5408 0.909 0.124 0.876
#> GSM247839 2 0.7883 0.859 0.236 0.764
#> GSM247821 1 0.0376 0.997 0.996 0.004
#> GSM247798 2 0.0672 0.871 0.008 0.992
#> GSM247838 1 0.0000 0.998 1.000 0.000
#> GSM247721 2 0.5408 0.909 0.124 0.876
#> GSM247781 2 0.7883 0.859 0.236 0.764
#> GSM247762 1 0.0376 0.997 0.996 0.004
#> GSM247825 2 0.0672 0.871 0.008 0.992
#> GSM247777 1 0.0000 0.998 1.000 0.000
#> GSM247761 2 0.5408 0.909 0.124 0.876
#> GSM247720 2 0.7883 0.859 0.236 0.764
#> GSM247814 2 0.0672 0.871 0.008 0.992
#> GSM247732 1 0.0000 0.998 1.000 0.000
#> GSM247708 2 0.5408 0.909 0.124 0.876
#> GSM247740 2 0.7883 0.859 0.236 0.764
#> GSM247749 1 0.0376 0.997 0.996 0.004
#> GSM247767 2 0.0672 0.871 0.008 0.992
#> GSM247748 1 0.0000 0.998 1.000 0.000
#> GSM247705 2 0.5408 0.909 0.124 0.876
#> GSM247746 2 0.7883 0.859 0.236 0.764
#> GSM247752 1 0.0376 0.997 0.996 0.004
#> GSM247769 2 0.0672 0.871 0.008 0.992
#> GSM247753 1 0.0000 0.998 1.000 0.000
#> GSM247723 2 0.5408 0.909 0.124 0.876
#> GSM247779 2 0.7883 0.859 0.236 0.764
#> GSM247756 1 0.0376 0.997 0.996 0.004
#> GSM247826 2 0.0672 0.871 0.008 0.992
#> GSM247775 1 0.0000 0.998 1.000 0.000
#> GSM247741 2 0.5408 0.909 0.124 0.876
#> GSM247799 2 0.7883 0.859 0.236 0.764
#> GSM247778 1 0.0376 0.997 0.996 0.004
#> GSM247806 2 0.0672 0.871 0.008 0.992
#> GSM247815 1 0.0000 0.998 1.000 0.000
#> GSM247735 2 0.5408 0.909 0.124 0.876
#> GSM247831 2 0.7883 0.859 0.236 0.764
#> GSM247845 1 0.0376 0.997 0.996 0.004
#> GSM247791 2 0.0672 0.871 0.008 0.992
#> GSM247780 1 0.0000 0.998 1.000 0.000
#> GSM247853 1 0.0000 0.998 1.000 0.000
#> GSM247800 2 0.5408 0.909 0.124 0.876
#> GSM247729 2 0.7883 0.859 0.236 0.764
#> GSM247810 1 0.0376 0.997 0.996 0.004
#> GSM247844 2 0.0672 0.871 0.008 0.992
#> GSM247793 1 0.0000 0.998 1.000 0.000
#> GSM247759 2 0.5408 0.909 0.124 0.876
#> GSM247724 2 0.7883 0.859 0.236 0.764
#> GSM247817 2 0.0672 0.871 0.008 0.992
#> GSM247727 1 0.0000 0.998 1.000 0.000
#> GSM247796 2 0.5408 0.909 0.124 0.876
#> GSM247725 2 0.7883 0.859 0.236 0.764
#> GSM247801 1 0.0376 0.997 0.996 0.004
#> GSM247731 2 0.0672 0.871 0.008 0.992
#> GSM247765 1 0.0000 0.998 1.000 0.000
#> GSM247792 2 0.5408 0.909 0.124 0.876
#> GSM247726 2 0.7883 0.859 0.236 0.764
#> GSM247803 1 0.0376 0.997 0.996 0.004
#> GSM247728 2 0.0672 0.871 0.008 0.992
#> GSM247768 1 0.0000 0.998 1.000 0.000
#> GSM247745 2 0.5408 0.909 0.124 0.876
#> GSM247855 2 0.5408 0.909 0.124 0.876
#> GSM247804 2 0.7883 0.859 0.236 0.764
#> GSM247774 1 0.0376 0.997 0.996 0.004
#> GSM247807 2 0.0672 0.871 0.008 0.992
#> GSM247813 1 0.0000 0.998 1.000 0.000
#> GSM247736 2 0.5408 0.909 0.124 0.876
#> GSM247712 2 0.7883 0.859 0.236 0.764
#> GSM247797 1 0.0376 0.997 0.996 0.004
#> GSM247743 2 0.0672 0.871 0.008 0.992
#> GSM247719 1 0.0000 0.998 1.000 0.000
#> GSM247707 2 0.5408 0.909 0.124 0.876
#> GSM247737 2 0.7883 0.859 0.236 0.764
#> GSM247827 2 0.0672 0.871 0.008 0.992
#> GSM247848 1 0.0000 0.998 1.000 0.000
#> GSM247794 2 0.5408 0.909 0.124 0.876
#> GSM247757 2 0.7883 0.859 0.236 0.764
#> GSM247744 1 0.0376 0.997 0.996 0.004
#> GSM247751 2 0.0672 0.871 0.008 0.992
#> GSM247837 1 0.0000 0.998 1.000 0.000
#> GSM247754 2 0.5408 0.909 0.124 0.876
#> GSM247789 2 0.7883 0.859 0.236 0.764
#> GSM247802 1 0.0376 0.997 0.996 0.004
#> GSM247771 2 0.0672 0.871 0.008 0.992
#> GSM247763 1 0.0000 0.998 1.000 0.000
#> GSM247808 2 0.5408 0.909 0.124 0.876
#> GSM247787 2 0.7883 0.859 0.236 0.764
#> GSM247843 1 0.0376 0.997 0.996 0.004
#> GSM247811 2 0.0672 0.871 0.008 0.992
#> GSM247773 1 0.0000 0.998 1.000 0.000
#> GSM247766 2 0.5408 0.909 0.124 0.876
#> GSM247718 2 0.5946 0.902 0.144 0.856
#> GSM247832 1 0.0376 0.997 0.996 0.004
#> GSM247709 2 0.0672 0.871 0.008 0.992
#> GSM247820 1 0.0000 0.998 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247854 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247758 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247742 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247755 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247841 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247703 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247739 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247715 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247829 3 0.0424 0.539 0.000 0.008 0.992
#> GSM247842 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247805 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247786 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247812 3 0.0592 0.539 0.000 0.012 0.988
#> GSM247776 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247850 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247717 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247784 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247834 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247783 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247846 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247822 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247710 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247713 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247840 3 0.0592 0.539 0.000 0.012 0.988
#> GSM247733 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247852 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247790 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247730 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247824 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247770 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247711 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247782 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247836 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247785 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247847 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247750 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247788 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247849 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247772 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247760 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247764 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247851 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247714 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247828 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247704 3 0.0747 0.538 0.000 0.016 0.984
#> GSM247818 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247823 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247706 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247835 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247734 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247819 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247809 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247830 3 0.0237 0.540 0.000 0.004 0.996
#> GSM247833 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247738 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247716 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247747 3 0.0424 0.539 0.000 0.008 0.992
#> GSM247722 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247816 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247839 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247821 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247798 3 0.0747 0.538 0.000 0.016 0.984
#> GSM247838 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247721 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247781 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247762 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247825 3 0.0237 0.540 0.000 0.004 0.996
#> GSM247777 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247761 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247720 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247814 3 0.0424 0.539 0.000 0.008 0.992
#> GSM247732 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247708 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247740 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247749 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247767 3 0.0747 0.538 0.000 0.016 0.984
#> GSM247748 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247705 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247746 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247752 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247769 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247753 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247723 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247779 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247756 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247826 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247775 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247741 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247799 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247778 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247806 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247815 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247735 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247831 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247845 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247791 3 0.0592 0.539 0.000 0.012 0.988
#> GSM247780 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247853 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247800 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247729 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247810 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247844 3 0.0747 0.538 0.000 0.016 0.984
#> GSM247793 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247759 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247724 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247817 3 0.0424 0.539 0.000 0.008 0.992
#> GSM247727 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247796 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247725 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247801 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247731 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247765 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247792 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247726 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247803 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247728 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247768 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247745 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247855 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247804 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247774 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247807 3 0.0592 0.539 0.000 0.012 0.988
#> GSM247813 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247736 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247712 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247797 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247743 3 0.0237 0.540 0.000 0.004 0.996
#> GSM247719 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247707 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247737 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247827 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247848 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247794 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247757 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247744 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247751 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247837 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247754 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247789 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247802 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247771 3 0.0000 0.540 0.000 0.000 1.000
#> GSM247763 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247808 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247787 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247843 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247811 3 0.0747 0.538 0.000 0.016 0.984
#> GSM247773 1 0.0000 0.891 1.000 0.000 0.000
#> GSM247766 3 0.6954 -0.135 0.016 0.484 0.500
#> GSM247718 2 0.6603 1.000 0.020 0.648 0.332
#> GSM247832 1 0.5835 0.832 0.660 0.340 0.000
#> GSM247709 3 0.0747 0.538 0.000 0.016 0.984
#> GSM247820 1 0.0000 0.891 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247854 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247758 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247742 1 0.5760 0.727 0.520 0.020 0.004 0.456
#> GSM247755 3 0.2867 0.960 0.000 0.104 0.884 0.012
#> GSM247841 1 0.0336 0.819 0.992 0.000 0.008 0.000
#> GSM247703 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247739 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247715 1 0.5995 0.727 0.520 0.020 0.012 0.448
#> GSM247829 3 0.3758 0.961 0.000 0.104 0.848 0.048
#> GSM247842 1 0.0524 0.819 0.988 0.000 0.008 0.004
#> GSM247805 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247786 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247812 3 0.5160 0.936 0.000 0.104 0.760 0.136
#> GSM247776 1 0.0817 0.819 0.976 0.000 0.024 0.000
#> GSM247850 1 0.0707 0.819 0.980 0.000 0.020 0.000
#> GSM247717 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247784 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247834 1 0.5995 0.727 0.520 0.020 0.012 0.448
#> GSM247783 3 0.2737 0.960 0.000 0.104 0.888 0.008
#> GSM247846 1 0.0657 0.820 0.984 0.000 0.012 0.004
#> GSM247822 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247710 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247713 1 0.5995 0.727 0.520 0.020 0.012 0.448
#> GSM247840 3 0.5058 0.936 0.000 0.104 0.768 0.128
#> GSM247733 1 0.0188 0.819 0.996 0.000 0.004 0.000
#> GSM247852 1 0.0336 0.819 0.992 0.000 0.008 0.000
#> GSM247790 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247730 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247824 3 0.2867 0.960 0.000 0.104 0.884 0.012
#> GSM247770 1 0.0921 0.819 0.972 0.000 0.028 0.000
#> GSM247711 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247782 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247836 1 0.5594 0.727 0.520 0.020 0.000 0.460
#> GSM247785 3 0.2737 0.960 0.000 0.104 0.888 0.008
#> GSM247847 1 0.0895 0.820 0.976 0.000 0.020 0.004
#> GSM247750 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247788 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247849 1 0.5760 0.727 0.520 0.020 0.004 0.456
#> GSM247772 3 0.2737 0.960 0.000 0.104 0.888 0.008
#> GSM247760 1 0.0817 0.819 0.976 0.000 0.024 0.000
#> GSM247764 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247851 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247714 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247828 1 0.5594 0.727 0.520 0.020 0.000 0.460
#> GSM247704 3 0.4898 0.942 0.000 0.104 0.780 0.116
#> GSM247818 1 0.0921 0.817 0.972 0.000 0.028 0.000
#> GSM247823 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247706 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247835 3 0.2737 0.960 0.000 0.104 0.888 0.008
#> GSM247734 1 0.0817 0.819 0.976 0.000 0.024 0.000
#> GSM247819 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247809 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247830 3 0.3099 0.960 0.000 0.104 0.876 0.020
#> GSM247833 1 0.0779 0.819 0.980 0.000 0.016 0.004
#> GSM247738 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247716 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247747 3 0.3587 0.961 0.000 0.104 0.856 0.040
#> GSM247722 1 0.1305 0.818 0.960 0.000 0.036 0.004
#> GSM247816 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247839 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247821 1 0.5995 0.727 0.520 0.020 0.012 0.448
#> GSM247798 3 0.4608 0.947 0.000 0.104 0.800 0.096
#> GSM247838 1 0.1305 0.818 0.960 0.000 0.036 0.004
#> GSM247721 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247781 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247762 1 0.6095 0.727 0.520 0.020 0.016 0.444
#> GSM247825 3 0.4144 0.957 0.000 0.104 0.828 0.068
#> GSM247777 1 0.0524 0.819 0.988 0.000 0.008 0.004
#> GSM247761 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247720 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247814 3 0.3587 0.960 0.000 0.104 0.856 0.040
#> GSM247732 1 0.0779 0.819 0.980 0.000 0.016 0.004
#> GSM247708 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247740 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247749 1 0.5995 0.727 0.520 0.020 0.012 0.448
#> GSM247767 3 0.4728 0.948 0.000 0.104 0.792 0.104
#> GSM247748 1 0.0336 0.819 0.992 0.000 0.008 0.000
#> GSM247705 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247746 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247752 1 0.6355 0.727 0.520 0.020 0.028 0.432
#> GSM247769 3 0.3205 0.962 0.000 0.104 0.872 0.024
#> GSM247753 1 0.1022 0.816 0.968 0.000 0.032 0.000
#> GSM247723 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247779 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247756 1 0.5594 0.727 0.520 0.020 0.000 0.460
#> GSM247826 3 0.2737 0.960 0.000 0.104 0.888 0.008
#> GSM247775 1 0.0336 0.819 0.992 0.000 0.008 0.000
#> GSM247741 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247799 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247778 1 0.5995 0.727 0.520 0.020 0.012 0.448
#> GSM247806 3 0.2867 0.960 0.000 0.104 0.884 0.012
#> GSM247815 1 0.0817 0.819 0.976 0.000 0.024 0.000
#> GSM247735 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247831 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247845 1 0.5594 0.727 0.520 0.020 0.000 0.460
#> GSM247791 3 0.5160 0.936 0.000 0.104 0.760 0.136
#> GSM247780 1 0.1109 0.819 0.968 0.000 0.028 0.004
#> GSM247853 1 0.1109 0.819 0.968 0.000 0.028 0.004
#> GSM247800 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247729 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247810 1 0.5995 0.727 0.520 0.020 0.012 0.448
#> GSM247844 3 0.4608 0.947 0.000 0.104 0.800 0.096
#> GSM247793 1 0.0188 0.819 0.996 0.000 0.004 0.000
#> GSM247759 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247724 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247817 3 0.3587 0.960 0.000 0.104 0.856 0.040
#> GSM247727 1 0.0779 0.819 0.980 0.000 0.016 0.004
#> GSM247796 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247725 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247801 1 0.6187 0.727 0.520 0.020 0.020 0.440
#> GSM247731 3 0.2737 0.960 0.000 0.104 0.888 0.008
#> GSM247765 1 0.0817 0.819 0.976 0.000 0.024 0.000
#> GSM247792 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247726 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247803 1 0.6355 0.727 0.520 0.020 0.028 0.432
#> GSM247728 3 0.3840 0.956 0.000 0.104 0.844 0.052
#> GSM247768 1 0.1022 0.816 0.968 0.000 0.032 0.000
#> GSM247745 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247855 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247804 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247774 1 0.5885 0.728 0.520 0.020 0.008 0.452
#> GSM247807 3 0.5110 0.936 0.000 0.104 0.764 0.132
#> GSM247813 1 0.1209 0.819 0.964 0.000 0.032 0.004
#> GSM247736 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247712 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247797 1 0.6095 0.727 0.520 0.020 0.016 0.444
#> GSM247743 3 0.2867 0.960 0.000 0.104 0.884 0.012
#> GSM247719 1 0.0779 0.819 0.980 0.000 0.016 0.004
#> GSM247707 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247737 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247827 3 0.3674 0.957 0.000 0.104 0.852 0.044
#> GSM247848 1 0.0657 0.819 0.984 0.000 0.012 0.004
#> GSM247794 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247757 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247744 1 0.5885 0.728 0.520 0.020 0.008 0.452
#> GSM247751 3 0.3840 0.956 0.000 0.104 0.844 0.052
#> GSM247837 1 0.0336 0.819 0.992 0.000 0.008 0.000
#> GSM247754 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247789 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247802 1 0.5995 0.727 0.520 0.020 0.012 0.448
#> GSM247771 3 0.2737 0.960 0.000 0.104 0.888 0.008
#> GSM247763 1 0.0921 0.819 0.972 0.000 0.028 0.000
#> GSM247808 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247787 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247843 1 0.5995 0.727 0.520 0.020 0.012 0.448
#> GSM247811 3 0.5209 0.934 0.000 0.104 0.756 0.140
#> GSM247773 1 0.0336 0.819 0.992 0.000 0.008 0.000
#> GSM247766 2 0.7220 0.647 0.000 0.472 0.144 0.384
#> GSM247718 2 0.0592 0.652 0.000 0.984 0.016 0.000
#> GSM247832 1 0.5760 0.727 0.520 0.020 0.004 0.456
#> GSM247709 3 0.5160 0.935 0.000 0.104 0.760 0.136
#> GSM247820 1 0.0895 0.819 0.976 0.000 0.020 0.004
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.6003 0.961 0.024 0.644 0.144 0.000 0.188
#> GSM247854 2 0.6003 0.961 0.024 0.644 0.144 0.000 0.188
#> GSM247758 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247742 4 0.0290 0.974 0.000 0.000 0.000 0.992 0.008
#> GSM247755 3 0.0162 0.953 0.004 0.000 0.996 0.000 0.000
#> GSM247841 1 0.4423 0.944 0.684 0.012 0.000 0.296 0.008
#> GSM247703 2 0.6382 0.957 0.036 0.628 0.144 0.004 0.188
#> GSM247739 5 0.3605 0.941 0.056 0.024 0.072 0.000 0.848
#> GSM247715 4 0.1117 0.974 0.000 0.020 0.000 0.964 0.016
#> GSM247829 3 0.2125 0.952 0.052 0.024 0.920 0.004 0.000
#> GSM247842 1 0.4735 0.945 0.668 0.032 0.000 0.296 0.004
#> GSM247805 2 0.6382 0.957 0.036 0.628 0.144 0.004 0.188
#> GSM247786 5 0.3605 0.941 0.056 0.024 0.072 0.000 0.848
#> GSM247812 3 0.3291 0.921 0.120 0.040 0.840 0.000 0.000
#> GSM247776 1 0.5587 0.931 0.620 0.072 0.000 0.296 0.012
#> GSM247850 1 0.5691 0.932 0.612 0.080 0.000 0.296 0.012
#> GSM247717 2 0.6154 0.960 0.024 0.640 0.144 0.004 0.188
#> GSM247784 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247834 4 0.1117 0.974 0.000 0.020 0.000 0.964 0.016
#> GSM247783 3 0.0162 0.953 0.004 0.000 0.996 0.000 0.000
#> GSM247846 1 0.4809 0.946 0.664 0.036 0.000 0.296 0.004
#> GSM247822 2 0.6697 0.945 0.068 0.604 0.144 0.000 0.184
#> GSM247710 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247713 4 0.1117 0.974 0.000 0.020 0.000 0.964 0.016
#> GSM247840 3 0.3242 0.923 0.116 0.040 0.844 0.000 0.000
#> GSM247733 1 0.4926 0.943 0.660 0.036 0.000 0.296 0.008
#> GSM247852 1 0.4949 0.942 0.656 0.044 0.000 0.296 0.004
#> GSM247790 2 0.6117 0.952 0.036 0.644 0.132 0.000 0.188
#> GSM247730 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247824 3 0.0162 0.953 0.004 0.000 0.996 0.000 0.000
#> GSM247770 1 0.5691 0.930 0.612 0.080 0.000 0.296 0.012
#> GSM247711 2 0.5599 0.962 0.008 0.664 0.144 0.000 0.184
#> GSM247782 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247836 4 0.0451 0.974 0.000 0.004 0.000 0.988 0.008
#> GSM247785 3 0.0162 0.953 0.004 0.000 0.996 0.000 0.000
#> GSM247847 1 0.5299 0.946 0.640 0.052 0.000 0.296 0.012
#> GSM247750 2 0.6232 0.958 0.036 0.632 0.144 0.000 0.188
#> GSM247788 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247849 4 0.0451 0.973 0.000 0.004 0.000 0.988 0.008
#> GSM247772 3 0.0451 0.952 0.008 0.004 0.988 0.000 0.000
#> GSM247760 1 0.5640 0.930 0.616 0.076 0.000 0.296 0.012
#> GSM247764 2 0.6950 0.942 0.088 0.584 0.144 0.000 0.184
#> GSM247851 2 0.6950 0.942 0.088 0.584 0.144 0.000 0.184
#> GSM247714 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247828 4 0.0290 0.974 0.000 0.000 0.000 0.992 0.008
#> GSM247704 3 0.2983 0.932 0.096 0.040 0.864 0.000 0.000
#> GSM247818 1 0.4880 0.937 0.664 0.028 0.000 0.296 0.012
#> GSM247823 2 0.6583 0.960 0.048 0.616 0.144 0.004 0.188
#> GSM247706 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247835 3 0.0613 0.952 0.008 0.004 0.984 0.004 0.000
#> GSM247734 1 0.5640 0.930 0.616 0.076 0.000 0.296 0.012
#> GSM247819 2 0.6952 0.941 0.076 0.592 0.144 0.004 0.184
#> GSM247809 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247830 3 0.1106 0.951 0.012 0.024 0.964 0.000 0.000
#> GSM247833 1 0.4949 0.944 0.656 0.044 0.000 0.296 0.004
#> GSM247738 2 0.6154 0.960 0.024 0.640 0.144 0.004 0.188
#> GSM247716 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247747 3 0.1828 0.953 0.028 0.032 0.936 0.004 0.000
#> GSM247722 1 0.5826 0.931 0.596 0.100 0.000 0.296 0.008
#> GSM247816 2 0.6583 0.960 0.048 0.616 0.144 0.004 0.188
#> GSM247839 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247821 4 0.1117 0.974 0.000 0.020 0.000 0.964 0.016
#> GSM247798 3 0.2661 0.940 0.056 0.056 0.888 0.000 0.000
#> GSM247838 1 0.5870 0.931 0.592 0.104 0.000 0.296 0.008
#> GSM247721 2 0.5799 0.961 0.016 0.656 0.144 0.000 0.184
#> GSM247781 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247762 4 0.1965 0.940 0.000 0.052 0.000 0.924 0.024
#> GSM247825 3 0.2206 0.946 0.068 0.016 0.912 0.004 0.000
#> GSM247777 1 0.4880 0.944 0.660 0.040 0.000 0.296 0.004
#> GSM247761 2 0.6382 0.957 0.036 0.628 0.144 0.004 0.188
#> GSM247720 5 0.3605 0.941 0.056 0.024 0.072 0.000 0.848
#> GSM247814 3 0.1822 0.951 0.024 0.036 0.936 0.004 0.000
#> GSM247732 1 0.5078 0.943 0.648 0.052 0.000 0.296 0.004
#> GSM247708 2 0.5481 0.962 0.004 0.668 0.144 0.000 0.184
#> GSM247740 5 0.3605 0.941 0.056 0.024 0.072 0.000 0.848
#> GSM247749 4 0.1117 0.974 0.000 0.020 0.000 0.964 0.016
#> GSM247767 3 0.2149 0.945 0.048 0.036 0.916 0.000 0.000
#> GSM247748 1 0.4610 0.941 0.676 0.020 0.000 0.296 0.008
#> GSM247705 2 0.6583 0.959 0.048 0.616 0.144 0.004 0.188
#> GSM247746 5 0.3691 0.939 0.056 0.028 0.072 0.000 0.844
#> GSM247752 4 0.2569 0.936 0.000 0.068 0.000 0.892 0.040
#> GSM247769 3 0.0693 0.955 0.012 0.008 0.980 0.000 0.000
#> GSM247753 1 0.5379 0.929 0.640 0.036 0.000 0.296 0.028
#> GSM247723 2 0.7098 0.943 0.088 0.580 0.144 0.004 0.184
#> GSM247779 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247756 4 0.0290 0.974 0.000 0.000 0.000 0.992 0.008
#> GSM247826 3 0.0613 0.952 0.008 0.004 0.984 0.004 0.000
#> GSM247775 1 0.4520 0.942 0.680 0.016 0.000 0.296 0.008
#> GSM247741 2 0.6803 0.941 0.076 0.596 0.144 0.000 0.184
#> GSM247799 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247778 4 0.1117 0.974 0.000 0.020 0.000 0.964 0.016
#> GSM247806 3 0.0324 0.953 0.004 0.000 0.992 0.004 0.000
#> GSM247815 1 0.5640 0.930 0.616 0.076 0.000 0.296 0.012
#> GSM247735 2 0.6803 0.941 0.076 0.596 0.144 0.000 0.184
#> GSM247831 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247845 4 0.0290 0.974 0.000 0.000 0.000 0.992 0.008
#> GSM247791 3 0.3291 0.921 0.120 0.040 0.840 0.000 0.000
#> GSM247780 1 0.5781 0.934 0.600 0.096 0.000 0.296 0.008
#> GSM247853 1 0.5735 0.936 0.604 0.092 0.000 0.296 0.008
#> GSM247800 2 0.6803 0.941 0.076 0.596 0.144 0.000 0.184
#> GSM247729 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247810 4 0.1117 0.974 0.000 0.020 0.000 0.964 0.016
#> GSM247844 3 0.2729 0.939 0.056 0.060 0.884 0.000 0.000
#> GSM247793 1 0.4318 0.944 0.688 0.008 0.000 0.296 0.008
#> GSM247759 2 0.6382 0.960 0.036 0.628 0.144 0.004 0.188
#> GSM247724 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247817 3 0.1750 0.951 0.028 0.036 0.936 0.000 0.000
#> GSM247727 1 0.5078 0.943 0.648 0.052 0.000 0.296 0.004
#> GSM247796 2 0.6952 0.941 0.076 0.592 0.144 0.004 0.184
#> GSM247725 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247801 4 0.1725 0.949 0.000 0.044 0.000 0.936 0.020
#> GSM247731 3 0.0162 0.953 0.004 0.000 0.996 0.000 0.000
#> GSM247765 1 0.5640 0.931 0.616 0.076 0.000 0.296 0.012
#> GSM247792 2 0.6902 0.941 0.084 0.588 0.144 0.000 0.184
#> GSM247726 5 0.3566 0.932 0.056 0.028 0.064 0.000 0.852
#> GSM247803 4 0.2569 0.936 0.000 0.068 0.000 0.892 0.040
#> GSM247728 3 0.1357 0.949 0.048 0.004 0.948 0.000 0.000
#> GSM247768 1 0.5379 0.929 0.640 0.036 0.000 0.296 0.028
#> GSM247745 2 0.5329 0.962 0.000 0.672 0.144 0.000 0.184
#> GSM247855 2 0.5329 0.962 0.000 0.672 0.144 0.000 0.184
#> GSM247804 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247774 4 0.0579 0.972 0.000 0.008 0.000 0.984 0.008
#> GSM247807 3 0.3267 0.924 0.112 0.044 0.844 0.000 0.000
#> GSM247813 1 0.5870 0.931 0.592 0.104 0.000 0.296 0.008
#> GSM247736 2 0.5481 0.962 0.004 0.668 0.144 0.000 0.184
#> GSM247712 5 0.3605 0.941 0.056 0.024 0.072 0.000 0.848
#> GSM247797 4 0.1648 0.951 0.000 0.040 0.000 0.940 0.020
#> GSM247743 3 0.1059 0.952 0.008 0.020 0.968 0.004 0.000
#> GSM247719 1 0.5140 0.942 0.644 0.056 0.000 0.296 0.004
#> GSM247707 2 0.5799 0.961 0.016 0.656 0.144 0.000 0.184
#> GSM247737 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247827 3 0.1717 0.948 0.052 0.008 0.936 0.004 0.000
#> GSM247848 1 0.5131 0.942 0.648 0.048 0.000 0.296 0.008
#> GSM247794 2 0.6382 0.957 0.036 0.628 0.144 0.004 0.188
#> GSM247757 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247744 4 0.0451 0.973 0.000 0.004 0.000 0.988 0.008
#> GSM247751 3 0.1197 0.950 0.048 0.000 0.952 0.000 0.000
#> GSM247837 1 0.4520 0.942 0.680 0.016 0.000 0.296 0.008
#> GSM247754 2 0.6203 0.962 0.028 0.640 0.144 0.004 0.184
#> GSM247789 5 0.1608 0.976 0.000 0.000 0.072 0.000 0.928
#> GSM247802 4 0.1117 0.974 0.000 0.020 0.000 0.964 0.016
#> GSM247771 3 0.0162 0.953 0.004 0.000 0.996 0.000 0.000
#> GSM247763 1 0.5640 0.930 0.616 0.076 0.000 0.296 0.012
#> GSM247808 2 0.5329 0.962 0.000 0.672 0.144 0.000 0.184
#> GSM247787 5 0.3605 0.941 0.056 0.024 0.072 0.000 0.848
#> GSM247843 4 0.1117 0.974 0.000 0.020 0.000 0.964 0.016
#> GSM247811 3 0.3527 0.919 0.116 0.056 0.828 0.000 0.000
#> GSM247773 1 0.4610 0.941 0.676 0.020 0.000 0.296 0.008
#> GSM247766 2 0.6803 0.941 0.076 0.596 0.144 0.000 0.184
#> GSM247718 5 0.3605 0.941 0.056 0.024 0.072 0.000 0.848
#> GSM247832 4 0.0451 0.973 0.000 0.004 0.000 0.988 0.008
#> GSM247709 3 0.3409 0.922 0.112 0.052 0.836 0.000 0.000
#> GSM247820 1 0.5257 0.941 0.640 0.056 0.000 0.296 0.008
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.4291 0.915 0.012 0.736 0.064 0.000 0.188 0.000
#> GSM247854 2 0.4291 0.915 0.012 0.736 0.064 0.000 0.188 0.000
#> GSM247758 5 0.0000 0.965 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247742 4 0.0551 0.946 0.000 0.008 0.004 0.984 0.004 0.000
#> GSM247755 3 0.1396 0.917 0.012 0.004 0.952 0.000 0.024 0.008
#> GSM247841 1 0.3558 0.922 0.792 0.028 0.000 0.168 0.000 0.012
#> GSM247703 2 0.4998 0.912 0.036 0.704 0.064 0.000 0.188 0.008
#> GSM247739 5 0.2485 0.916 0.024 0.008 0.000 0.000 0.884 0.084
#> GSM247715 4 0.1629 0.947 0.000 0.028 0.004 0.940 0.004 0.024
#> GSM247829 3 0.3376 0.917 0.020 0.004 0.828 0.000 0.024 0.124
#> GSM247842 1 0.3134 0.926 0.808 0.000 0.000 0.168 0.000 0.024
#> GSM247805 2 0.4860 0.913 0.028 0.712 0.064 0.000 0.188 0.008
#> GSM247786 5 0.2485 0.916 0.024 0.008 0.000 0.000 0.884 0.084
#> GSM247812 3 0.5073 0.871 0.072 0.016 0.700 0.000 0.024 0.188
#> GSM247776 1 0.4959 0.908 0.692 0.012 0.004 0.168 0.000 0.124
#> GSM247850 1 0.4744 0.911 0.708 0.008 0.004 0.168 0.000 0.112
#> GSM247717 2 0.4195 0.915 0.008 0.740 0.064 0.000 0.188 0.000
#> GSM247784 5 0.0146 0.964 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM247834 4 0.1710 0.947 0.000 0.028 0.004 0.936 0.004 0.028
#> GSM247783 3 0.1138 0.917 0.012 0.004 0.960 0.000 0.024 0.000
#> GSM247846 1 0.3487 0.929 0.788 0.000 0.000 0.168 0.000 0.044
#> GSM247822 2 0.6626 0.866 0.008 0.536 0.064 0.000 0.188 0.204
#> GSM247710 5 0.0000 0.965 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247713 4 0.1786 0.947 0.000 0.032 0.004 0.932 0.004 0.028
#> GSM247840 3 0.5073 0.871 0.072 0.016 0.700 0.000 0.024 0.188
#> GSM247733 1 0.3888 0.922 0.776 0.028 0.000 0.168 0.000 0.028
#> GSM247852 1 0.3648 0.923 0.788 0.016 0.000 0.168 0.000 0.028
#> GSM247790 2 0.4983 0.909 0.036 0.708 0.056 0.000 0.188 0.012
#> GSM247730 5 0.0000 0.965 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247824 3 0.1630 0.920 0.016 0.000 0.940 0.000 0.024 0.020
#> GSM247770 1 0.4939 0.908 0.688 0.008 0.004 0.168 0.000 0.132
#> GSM247711 2 0.4786 0.916 0.008 0.716 0.064 0.000 0.188 0.024
#> GSM247782 5 0.0146 0.964 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM247836 4 0.0748 0.948 0.000 0.016 0.004 0.976 0.004 0.000
#> GSM247785 3 0.1353 0.919 0.012 0.000 0.952 0.000 0.024 0.012
#> GSM247847 1 0.3869 0.929 0.768 0.004 0.000 0.168 0.000 0.060
#> GSM247750 2 0.5093 0.912 0.036 0.700 0.064 0.000 0.188 0.012
#> GSM247788 5 0.0146 0.964 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM247849 4 0.0748 0.945 0.000 0.016 0.004 0.976 0.004 0.000
#> GSM247772 3 0.1251 0.916 0.008 0.000 0.956 0.000 0.024 0.012
#> GSM247760 1 0.4959 0.908 0.692 0.012 0.004 0.168 0.000 0.124
#> GSM247764 2 0.6813 0.855 0.008 0.496 0.064 0.000 0.188 0.244
#> GSM247851 2 0.6813 0.855 0.008 0.496 0.064 0.000 0.188 0.244
#> GSM247714 5 0.0000 0.965 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247828 4 0.0405 0.947 0.000 0.008 0.000 0.988 0.004 0.000
#> GSM247704 3 0.4449 0.885 0.044 0.000 0.716 0.000 0.024 0.216
#> GSM247818 1 0.4425 0.909 0.748 0.052 0.004 0.168 0.000 0.028
#> GSM247823 2 0.5668 0.912 0.032 0.668 0.064 0.000 0.188 0.048
#> GSM247706 5 0.0000 0.965 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247835 3 0.1138 0.916 0.004 0.000 0.960 0.000 0.024 0.012
#> GSM247734 1 0.4959 0.908 0.692 0.012 0.004 0.168 0.000 0.124
#> GSM247819 2 0.6550 0.857 0.000 0.512 0.064 0.000 0.188 0.236
#> GSM247809 5 0.0291 0.963 0.004 0.000 0.000 0.000 0.992 0.004
#> GSM247830 3 0.2479 0.914 0.012 0.012 0.900 0.000 0.024 0.052
#> GSM247833 1 0.4206 0.922 0.748 0.004 0.004 0.172 0.000 0.072
#> GSM247738 2 0.4291 0.915 0.012 0.736 0.064 0.000 0.188 0.000
#> GSM247716 5 0.0291 0.963 0.004 0.000 0.000 0.000 0.992 0.004
#> GSM247747 3 0.2805 0.920 0.024 0.012 0.884 0.000 0.024 0.056
#> GSM247722 1 0.5134 0.905 0.660 0.012 0.000 0.172 0.000 0.156
#> GSM247816 2 0.5546 0.913 0.032 0.676 0.064 0.000 0.188 0.040
#> GSM247839 5 0.0291 0.963 0.004 0.000 0.000 0.000 0.992 0.004
#> GSM247821 4 0.1786 0.947 0.000 0.032 0.004 0.932 0.004 0.028
#> GSM247798 3 0.4191 0.900 0.040 0.012 0.776 0.000 0.024 0.148
#> GSM247838 1 0.5134 0.905 0.660 0.012 0.000 0.172 0.000 0.156
#> GSM247721 2 0.5025 0.916 0.012 0.704 0.064 0.000 0.188 0.032
#> GSM247781 5 0.0000 0.965 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247762 4 0.3395 0.868 0.000 0.056 0.000 0.816 0.004 0.124
#> GSM247825 3 0.3509 0.911 0.032 0.000 0.816 0.000 0.024 0.128
#> GSM247777 1 0.3691 0.922 0.780 0.004 0.000 0.168 0.000 0.048
#> GSM247761 2 0.4860 0.913 0.028 0.712 0.064 0.000 0.188 0.008
#> GSM247720 5 0.2485 0.916 0.024 0.008 0.000 0.000 0.884 0.084
#> GSM247814 3 0.3329 0.914 0.028 0.012 0.848 0.000 0.024 0.088
#> GSM247732 1 0.4151 0.920 0.756 0.008 0.004 0.172 0.000 0.060
#> GSM247708 2 0.4786 0.916 0.008 0.716 0.064 0.000 0.188 0.024
#> GSM247740 5 0.2485 0.916 0.024 0.008 0.000 0.000 0.884 0.084
#> GSM247749 4 0.1786 0.947 0.000 0.032 0.004 0.932 0.004 0.028
#> GSM247767 3 0.3831 0.908 0.036 0.008 0.804 0.000 0.024 0.128
#> GSM247748 1 0.3631 0.921 0.788 0.032 0.000 0.168 0.000 0.012
#> GSM247705 2 0.5734 0.912 0.036 0.664 0.064 0.000 0.188 0.048
#> GSM247746 5 0.3062 0.889 0.024 0.016 0.000 0.000 0.844 0.116
#> GSM247752 4 0.3999 0.861 0.000 0.072 0.000 0.760 0.004 0.164
#> GSM247769 3 0.2135 0.923 0.012 0.004 0.916 0.000 0.024 0.044
#> GSM247753 1 0.4853 0.899 0.716 0.088 0.008 0.168 0.000 0.020
#> GSM247723 2 0.6588 0.862 0.004 0.528 0.064 0.000 0.188 0.216
#> GSM247779 5 0.0000 0.965 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247756 4 0.0405 0.947 0.000 0.008 0.000 0.988 0.004 0.000
#> GSM247826 3 0.1138 0.916 0.004 0.000 0.960 0.000 0.024 0.012
#> GSM247775 1 0.3631 0.920 0.788 0.032 0.000 0.168 0.000 0.012
#> GSM247741 2 0.6533 0.858 0.000 0.516 0.064 0.000 0.188 0.232
#> GSM247799 5 0.0146 0.964 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM247778 4 0.1786 0.947 0.000 0.032 0.004 0.932 0.004 0.028
#> GSM247806 3 0.1149 0.918 0.008 0.000 0.960 0.000 0.024 0.008
#> GSM247815 1 0.4920 0.910 0.696 0.012 0.004 0.168 0.000 0.120
#> GSM247735 2 0.6533 0.859 0.000 0.516 0.064 0.000 0.188 0.232
#> GSM247831 5 0.0000 0.965 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247845 4 0.0405 0.947 0.000 0.008 0.000 0.988 0.004 0.000
#> GSM247791 3 0.5123 0.870 0.076 0.016 0.696 0.000 0.024 0.188
#> GSM247780 1 0.4874 0.911 0.684 0.008 0.000 0.168 0.000 0.140
#> GSM247853 1 0.4764 0.915 0.696 0.008 0.000 0.168 0.000 0.128
#> GSM247800 2 0.6550 0.857 0.000 0.512 0.064 0.000 0.188 0.236
#> GSM247729 5 0.0000 0.965 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247810 4 0.1786 0.947 0.000 0.032 0.004 0.932 0.004 0.028
#> GSM247844 3 0.4115 0.900 0.040 0.012 0.784 0.000 0.024 0.140
#> GSM247793 1 0.3492 0.927 0.796 0.020 0.000 0.168 0.000 0.016
#> GSM247759 2 0.5327 0.913 0.020 0.688 0.064 0.000 0.188 0.040
#> GSM247724 5 0.0291 0.963 0.004 0.000 0.000 0.000 0.992 0.004
#> GSM247817 3 0.3093 0.913 0.024 0.012 0.864 0.000 0.024 0.076
#> GSM247727 1 0.4151 0.920 0.756 0.008 0.004 0.172 0.000 0.060
#> GSM247796 2 0.6550 0.857 0.000 0.512 0.064 0.000 0.188 0.236
#> GSM247725 5 0.0000 0.965 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247801 4 0.2734 0.906 0.000 0.052 0.004 0.876 0.004 0.064
#> GSM247731 3 0.1138 0.917 0.012 0.004 0.960 0.000 0.024 0.000
#> GSM247765 1 0.5269 0.910 0.680 0.032 0.004 0.168 0.000 0.116
#> GSM247792 2 0.6813 0.855 0.008 0.496 0.064 0.000 0.188 0.244
#> GSM247726 5 0.3192 0.883 0.024 0.020 0.000 0.000 0.836 0.120
#> GSM247803 4 0.4051 0.858 0.000 0.076 0.000 0.756 0.004 0.164
#> GSM247728 3 0.3140 0.910 0.024 0.000 0.844 0.000 0.024 0.108
#> GSM247768 1 0.4931 0.897 0.712 0.088 0.008 0.168 0.000 0.024
#> GSM247745 2 0.4678 0.916 0.004 0.720 0.064 0.000 0.188 0.024
#> GSM247855 2 0.4678 0.916 0.004 0.720 0.064 0.000 0.188 0.024
#> GSM247804 5 0.0146 0.964 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM247774 4 0.0982 0.944 0.000 0.020 0.004 0.968 0.004 0.004
#> GSM247807 3 0.5123 0.874 0.076 0.016 0.696 0.000 0.024 0.188
#> GSM247813 1 0.5071 0.906 0.668 0.012 0.000 0.168 0.000 0.152
#> GSM247736 2 0.4678 0.916 0.004 0.720 0.064 0.000 0.188 0.024
#> GSM247712 5 0.2485 0.916 0.024 0.008 0.000 0.000 0.884 0.084
#> GSM247797 4 0.2662 0.908 0.000 0.044 0.004 0.880 0.004 0.068
#> GSM247743 3 0.1856 0.916 0.008 0.008 0.932 0.000 0.024 0.028
#> GSM247719 1 0.4151 0.920 0.756 0.008 0.004 0.172 0.000 0.060
#> GSM247707 2 0.5272 0.916 0.024 0.692 0.064 0.000 0.188 0.032
#> GSM247737 5 0.0000 0.965 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247827 3 0.2916 0.912 0.020 0.000 0.860 0.000 0.024 0.096
#> GSM247848 1 0.3648 0.923 0.788 0.016 0.000 0.168 0.000 0.028
#> GSM247794 2 0.4860 0.913 0.028 0.712 0.064 0.000 0.188 0.008
#> GSM247757 5 0.0000 0.965 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247744 4 0.0798 0.945 0.000 0.012 0.004 0.976 0.004 0.004
#> GSM247751 3 0.3046 0.912 0.024 0.000 0.852 0.000 0.024 0.100
#> GSM247837 1 0.3648 0.920 0.788 0.028 0.000 0.168 0.000 0.016
#> GSM247754 2 0.5304 0.914 0.004 0.680 0.064 0.000 0.188 0.064
#> GSM247789 5 0.0146 0.964 0.004 0.000 0.000 0.000 0.996 0.000
#> GSM247802 4 0.1629 0.947 0.000 0.028 0.004 0.940 0.004 0.024
#> GSM247771 3 0.1138 0.917 0.012 0.004 0.960 0.000 0.024 0.000
#> GSM247763 1 0.4997 0.908 0.688 0.012 0.004 0.168 0.000 0.128
#> GSM247808 2 0.4678 0.916 0.004 0.720 0.064 0.000 0.188 0.024
#> GSM247787 5 0.2485 0.916 0.024 0.008 0.000 0.000 0.884 0.084
#> GSM247843 4 0.1629 0.947 0.000 0.028 0.004 0.940 0.004 0.024
#> GSM247811 3 0.5310 0.866 0.080 0.020 0.680 0.000 0.024 0.196
#> GSM247773 1 0.3631 0.921 0.788 0.032 0.000 0.168 0.000 0.012
#> GSM247766 2 0.6567 0.857 0.000 0.508 0.064 0.000 0.188 0.240
#> GSM247718 5 0.2485 0.916 0.024 0.008 0.000 0.000 0.884 0.084
#> GSM247832 4 0.0748 0.945 0.000 0.016 0.004 0.976 0.004 0.000
#> GSM247709 3 0.4774 0.874 0.048 0.004 0.688 0.000 0.024 0.236
#> GSM247820 1 0.4314 0.919 0.744 0.008 0.004 0.172 0.000 0.072
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> MAD:kmeans 153 1 1.000 4.63e-32 2
#> MAD:kmeans 119 1 0.978 1.50e-48 3
#> MAD:kmeans 153 1 0.985 2.17e-61 4
#> MAD:kmeans 153 1 0.989 6.51e-120 5
#> MAD:kmeans 153 1 0.989 6.51e-120 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.4711 0.529 0.529
#> 3 3 0.819 0.956 0.961 0.3675 0.827 0.673
#> 4 4 1.000 0.990 0.977 0.1383 0.909 0.745
#> 5 5 1.000 1.000 0.999 0.0935 0.933 0.747
#> 6 6 0.975 0.942 0.942 0.0185 1.000 1.000
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 4
There is also optional best \(k\) = 2 4 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0 1 0 1
#> GSM247854 2 0 1 0 1
#> GSM247758 2 0 1 0 1
#> GSM247742 1 0 1 1 0
#> GSM247755 2 0 1 0 1
#> GSM247841 1 0 1 1 0
#> GSM247703 2 0 1 0 1
#> GSM247739 2 0 1 0 1
#> GSM247715 1 0 1 1 0
#> GSM247829 2 0 1 0 1
#> GSM247842 1 0 1 1 0
#> GSM247805 2 0 1 0 1
#> GSM247786 2 0 1 0 1
#> GSM247812 2 0 1 0 1
#> GSM247776 1 0 1 1 0
#> GSM247850 1 0 1 1 0
#> GSM247717 2 0 1 0 1
#> GSM247784 2 0 1 0 1
#> GSM247834 1 0 1 1 0
#> GSM247783 2 0 1 0 1
#> GSM247846 1 0 1 1 0
#> GSM247822 2 0 1 0 1
#> GSM247710 2 0 1 0 1
#> GSM247713 1 0 1 1 0
#> GSM247840 2 0 1 0 1
#> GSM247733 1 0 1 1 0
#> GSM247852 1 0 1 1 0
#> GSM247790 2 0 1 0 1
#> GSM247730 2 0 1 0 1
#> GSM247824 2 0 1 0 1
#> GSM247770 1 0 1 1 0
#> GSM247711 2 0 1 0 1
#> GSM247782 2 0 1 0 1
#> GSM247836 1 0 1 1 0
#> GSM247785 2 0 1 0 1
#> GSM247847 1 0 1 1 0
#> GSM247750 2 0 1 0 1
#> GSM247788 2 0 1 0 1
#> GSM247849 1 0 1 1 0
#> GSM247772 2 0 1 0 1
#> GSM247760 1 0 1 1 0
#> GSM247764 2 0 1 0 1
#> GSM247851 2 0 1 0 1
#> GSM247714 2 0 1 0 1
#> GSM247828 1 0 1 1 0
#> GSM247704 2 0 1 0 1
#> GSM247818 1 0 1 1 0
#> GSM247823 2 0 1 0 1
#> GSM247706 2 0 1 0 1
#> GSM247835 2 0 1 0 1
#> GSM247734 1 0 1 1 0
#> GSM247819 2 0 1 0 1
#> GSM247809 2 0 1 0 1
#> GSM247830 2 0 1 0 1
#> GSM247833 1 0 1 1 0
#> GSM247738 2 0 1 0 1
#> GSM247716 2 0 1 0 1
#> GSM247747 2 0 1 0 1
#> GSM247722 1 0 1 1 0
#> GSM247816 2 0 1 0 1
#> GSM247839 2 0 1 0 1
#> GSM247821 1 0 1 1 0
#> GSM247798 2 0 1 0 1
#> GSM247838 1 0 1 1 0
#> GSM247721 2 0 1 0 1
#> GSM247781 2 0 1 0 1
#> GSM247762 1 0 1 1 0
#> GSM247825 2 0 1 0 1
#> GSM247777 1 0 1 1 0
#> GSM247761 2 0 1 0 1
#> GSM247720 2 0 1 0 1
#> GSM247814 2 0 1 0 1
#> GSM247732 1 0 1 1 0
#> GSM247708 2 0 1 0 1
#> GSM247740 2 0 1 0 1
#> GSM247749 1 0 1 1 0
#> GSM247767 2 0 1 0 1
#> GSM247748 1 0 1 1 0
#> GSM247705 2 0 1 0 1
#> GSM247746 2 0 1 0 1
#> GSM247752 1 0 1 1 0
#> GSM247769 2 0 1 0 1
#> GSM247753 1 0 1 1 0
#> GSM247723 2 0 1 0 1
#> GSM247779 2 0 1 0 1
#> GSM247756 1 0 1 1 0
#> GSM247826 2 0 1 0 1
#> GSM247775 1 0 1 1 0
#> GSM247741 2 0 1 0 1
#> GSM247799 2 0 1 0 1
#> GSM247778 1 0 1 1 0
#> GSM247806 2 0 1 0 1
#> GSM247815 1 0 1 1 0
#> GSM247735 2 0 1 0 1
#> GSM247831 2 0 1 0 1
#> GSM247845 1 0 1 1 0
#> GSM247791 2 0 1 0 1
#> GSM247780 1 0 1 1 0
#> GSM247853 1 0 1 1 0
#> GSM247800 2 0 1 0 1
#> GSM247729 2 0 1 0 1
#> GSM247810 1 0 1 1 0
#> GSM247844 2 0 1 0 1
#> GSM247793 1 0 1 1 0
#> GSM247759 2 0 1 0 1
#> GSM247724 2 0 1 0 1
#> GSM247817 2 0 1 0 1
#> GSM247727 1 0 1 1 0
#> GSM247796 2 0 1 0 1
#> GSM247725 2 0 1 0 1
#> GSM247801 1 0 1 1 0
#> GSM247731 2 0 1 0 1
#> GSM247765 1 0 1 1 0
#> GSM247792 2 0 1 0 1
#> GSM247726 2 0 1 0 1
#> GSM247803 1 0 1 1 0
#> GSM247728 2 0 1 0 1
#> GSM247768 1 0 1 1 0
#> GSM247745 2 0 1 0 1
#> GSM247855 2 0 1 0 1
#> GSM247804 2 0 1 0 1
#> GSM247774 1 0 1 1 0
#> GSM247807 2 0 1 0 1
#> GSM247813 1 0 1 1 0
#> GSM247736 2 0 1 0 1
#> GSM247712 2 0 1 0 1
#> GSM247797 1 0 1 1 0
#> GSM247743 2 0 1 0 1
#> GSM247719 1 0 1 1 0
#> GSM247707 2 0 1 0 1
#> GSM247737 2 0 1 0 1
#> GSM247827 2 0 1 0 1
#> GSM247848 1 0 1 1 0
#> GSM247794 2 0 1 0 1
#> GSM247757 2 0 1 0 1
#> GSM247744 1 0 1 1 0
#> GSM247751 2 0 1 0 1
#> GSM247837 1 0 1 1 0
#> GSM247754 2 0 1 0 1
#> GSM247789 2 0 1 0 1
#> GSM247802 1 0 1 1 0
#> GSM247771 2 0 1 0 1
#> GSM247763 1 0 1 1 0
#> GSM247808 2 0 1 0 1
#> GSM247787 2 0 1 0 1
#> GSM247843 1 0 1 1 0
#> GSM247811 2 0 1 0 1
#> GSM247773 1 0 1 1 0
#> GSM247766 2 0 1 0 1
#> GSM247718 2 0 1 0 1
#> GSM247832 1 0 1 1 0
#> GSM247709 2 0 1 0 1
#> GSM247820 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.424 0.897 0 0.824 0.176
#> GSM247854 2 0.424 0.897 0 0.824 0.176
#> GSM247758 2 0.000 0.895 0 1.000 0.000
#> GSM247742 1 0.000 1.000 1 0.000 0.000
#> GSM247755 3 0.000 1.000 0 0.000 1.000
#> GSM247841 1 0.000 1.000 1 0.000 0.000
#> GSM247703 2 0.424 0.897 0 0.824 0.176
#> GSM247739 2 0.000 0.895 0 1.000 0.000
#> GSM247715 1 0.000 1.000 1 0.000 0.000
#> GSM247829 3 0.000 1.000 0 0.000 1.000
#> GSM247842 1 0.000 1.000 1 0.000 0.000
#> GSM247805 2 0.424 0.897 0 0.824 0.176
#> GSM247786 2 0.000 0.895 0 1.000 0.000
#> GSM247812 3 0.000 1.000 0 0.000 1.000
#> GSM247776 1 0.000 1.000 1 0.000 0.000
#> GSM247850 1 0.000 1.000 1 0.000 0.000
#> GSM247717 2 0.424 0.897 0 0.824 0.176
#> GSM247784 2 0.000 0.895 0 1.000 0.000
#> GSM247834 1 0.000 1.000 1 0.000 0.000
#> GSM247783 3 0.000 1.000 0 0.000 1.000
#> GSM247846 1 0.000 1.000 1 0.000 0.000
#> GSM247822 2 0.424 0.897 0 0.824 0.176
#> GSM247710 2 0.000 0.895 0 1.000 0.000
#> GSM247713 1 0.000 1.000 1 0.000 0.000
#> GSM247840 3 0.000 1.000 0 0.000 1.000
#> GSM247733 1 0.000 1.000 1 0.000 0.000
#> GSM247852 1 0.000 1.000 1 0.000 0.000
#> GSM247790 2 0.424 0.897 0 0.824 0.176
#> GSM247730 2 0.000 0.895 0 1.000 0.000
#> GSM247824 3 0.000 1.000 0 0.000 1.000
#> GSM247770 1 0.000 1.000 1 0.000 0.000
#> GSM247711 2 0.424 0.897 0 0.824 0.176
#> GSM247782 2 0.000 0.895 0 1.000 0.000
#> GSM247836 1 0.000 1.000 1 0.000 0.000
#> GSM247785 3 0.000 1.000 0 0.000 1.000
#> GSM247847 1 0.000 1.000 1 0.000 0.000
#> GSM247750 2 0.424 0.897 0 0.824 0.176
#> GSM247788 2 0.000 0.895 0 1.000 0.000
#> GSM247849 1 0.000 1.000 1 0.000 0.000
#> GSM247772 3 0.000 1.000 0 0.000 1.000
#> GSM247760 1 0.000 1.000 1 0.000 0.000
#> GSM247764 2 0.424 0.897 0 0.824 0.176
#> GSM247851 2 0.424 0.897 0 0.824 0.176
#> GSM247714 2 0.000 0.895 0 1.000 0.000
#> GSM247828 1 0.000 1.000 1 0.000 0.000
#> GSM247704 3 0.000 1.000 0 0.000 1.000
#> GSM247818 1 0.000 1.000 1 0.000 0.000
#> GSM247823 2 0.424 0.897 0 0.824 0.176
#> GSM247706 2 0.000 0.895 0 1.000 0.000
#> GSM247835 3 0.000 1.000 0 0.000 1.000
#> GSM247734 1 0.000 1.000 1 0.000 0.000
#> GSM247819 2 0.424 0.897 0 0.824 0.176
#> GSM247809 2 0.000 0.895 0 1.000 0.000
#> GSM247830 3 0.000 1.000 0 0.000 1.000
#> GSM247833 1 0.000 1.000 1 0.000 0.000
#> GSM247738 2 0.424 0.897 0 0.824 0.176
#> GSM247716 2 0.000 0.895 0 1.000 0.000
#> GSM247747 3 0.000 1.000 0 0.000 1.000
#> GSM247722 1 0.000 1.000 1 0.000 0.000
#> GSM247816 2 0.424 0.897 0 0.824 0.176
#> GSM247839 2 0.000 0.895 0 1.000 0.000
#> GSM247821 1 0.000 1.000 1 0.000 0.000
#> GSM247798 3 0.000 1.000 0 0.000 1.000
#> GSM247838 1 0.000 1.000 1 0.000 0.000
#> GSM247721 2 0.424 0.897 0 0.824 0.176
#> GSM247781 2 0.000 0.895 0 1.000 0.000
#> GSM247762 1 0.000 1.000 1 0.000 0.000
#> GSM247825 3 0.000 1.000 0 0.000 1.000
#> GSM247777 1 0.000 1.000 1 0.000 0.000
#> GSM247761 2 0.424 0.897 0 0.824 0.176
#> GSM247720 2 0.000 0.895 0 1.000 0.000
#> GSM247814 3 0.000 1.000 0 0.000 1.000
#> GSM247732 1 0.000 1.000 1 0.000 0.000
#> GSM247708 2 0.424 0.897 0 0.824 0.176
#> GSM247740 2 0.000 0.895 0 1.000 0.000
#> GSM247749 1 0.000 1.000 1 0.000 0.000
#> GSM247767 3 0.000 1.000 0 0.000 1.000
#> GSM247748 1 0.000 1.000 1 0.000 0.000
#> GSM247705 2 0.424 0.897 0 0.824 0.176
#> GSM247746 2 0.000 0.895 0 1.000 0.000
#> GSM247752 1 0.000 1.000 1 0.000 0.000
#> GSM247769 3 0.000 1.000 0 0.000 1.000
#> GSM247753 1 0.000 1.000 1 0.000 0.000
#> GSM247723 2 0.424 0.897 0 0.824 0.176
#> GSM247779 2 0.000 0.895 0 1.000 0.000
#> GSM247756 1 0.000 1.000 1 0.000 0.000
#> GSM247826 3 0.000 1.000 0 0.000 1.000
#> GSM247775 1 0.000 1.000 1 0.000 0.000
#> GSM247741 2 0.424 0.897 0 0.824 0.176
#> GSM247799 2 0.000 0.895 0 1.000 0.000
#> GSM247778 1 0.000 1.000 1 0.000 0.000
#> GSM247806 3 0.000 1.000 0 0.000 1.000
#> GSM247815 1 0.000 1.000 1 0.000 0.000
#> GSM247735 2 0.424 0.897 0 0.824 0.176
#> GSM247831 2 0.000 0.895 0 1.000 0.000
#> GSM247845 1 0.000 1.000 1 0.000 0.000
#> GSM247791 3 0.000 1.000 0 0.000 1.000
#> GSM247780 1 0.000 1.000 1 0.000 0.000
#> GSM247853 1 0.000 1.000 1 0.000 0.000
#> GSM247800 2 0.424 0.897 0 0.824 0.176
#> GSM247729 2 0.000 0.895 0 1.000 0.000
#> GSM247810 1 0.000 1.000 1 0.000 0.000
#> GSM247844 3 0.000 1.000 0 0.000 1.000
#> GSM247793 1 0.000 1.000 1 0.000 0.000
#> GSM247759 2 0.424 0.897 0 0.824 0.176
#> GSM247724 2 0.000 0.895 0 1.000 0.000
#> GSM247817 3 0.000 1.000 0 0.000 1.000
#> GSM247727 1 0.000 1.000 1 0.000 0.000
#> GSM247796 2 0.424 0.897 0 0.824 0.176
#> GSM247725 2 0.000 0.895 0 1.000 0.000
#> GSM247801 1 0.000 1.000 1 0.000 0.000
#> GSM247731 3 0.000 1.000 0 0.000 1.000
#> GSM247765 1 0.000 1.000 1 0.000 0.000
#> GSM247792 2 0.424 0.897 0 0.824 0.176
#> GSM247726 2 0.000 0.895 0 1.000 0.000
#> GSM247803 1 0.000 1.000 1 0.000 0.000
#> GSM247728 3 0.000 1.000 0 0.000 1.000
#> GSM247768 1 0.000 1.000 1 0.000 0.000
#> GSM247745 2 0.424 0.897 0 0.824 0.176
#> GSM247855 2 0.424 0.897 0 0.824 0.176
#> GSM247804 2 0.000 0.895 0 1.000 0.000
#> GSM247774 1 0.000 1.000 1 0.000 0.000
#> GSM247807 3 0.000 1.000 0 0.000 1.000
#> GSM247813 1 0.000 1.000 1 0.000 0.000
#> GSM247736 2 0.424 0.897 0 0.824 0.176
#> GSM247712 2 0.000 0.895 0 1.000 0.000
#> GSM247797 1 0.000 1.000 1 0.000 0.000
#> GSM247743 3 0.000 1.000 0 0.000 1.000
#> GSM247719 1 0.000 1.000 1 0.000 0.000
#> GSM247707 2 0.424 0.897 0 0.824 0.176
#> GSM247737 2 0.000 0.895 0 1.000 0.000
#> GSM247827 3 0.000 1.000 0 0.000 1.000
#> GSM247848 1 0.000 1.000 1 0.000 0.000
#> GSM247794 2 0.424 0.897 0 0.824 0.176
#> GSM247757 2 0.000 0.895 0 1.000 0.000
#> GSM247744 1 0.000 1.000 1 0.000 0.000
#> GSM247751 3 0.000 1.000 0 0.000 1.000
#> GSM247837 1 0.000 1.000 1 0.000 0.000
#> GSM247754 2 0.424 0.897 0 0.824 0.176
#> GSM247789 2 0.000 0.895 0 1.000 0.000
#> GSM247802 1 0.000 1.000 1 0.000 0.000
#> GSM247771 3 0.000 1.000 0 0.000 1.000
#> GSM247763 1 0.000 1.000 1 0.000 0.000
#> GSM247808 2 0.424 0.897 0 0.824 0.176
#> GSM247787 2 0.000 0.895 0 1.000 0.000
#> GSM247843 1 0.000 1.000 1 0.000 0.000
#> GSM247811 3 0.000 1.000 0 0.000 1.000
#> GSM247773 1 0.000 1.000 1 0.000 0.000
#> GSM247766 2 0.424 0.897 0 0.824 0.176
#> GSM247718 2 0.000 0.895 0 1.000 0.000
#> GSM247832 1 0.000 1.000 1 0.000 0.000
#> GSM247709 3 0.000 1.000 0 0.000 1.000
#> GSM247820 1 0.000 1.000 1 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247854 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247758 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247742 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247755 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247841 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247703 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247739 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247715 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247829 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247842 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247805 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247786 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247812 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247776 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247850 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247717 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247784 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247834 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247783 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247846 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247822 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247710 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247713 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247840 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247733 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247852 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247790 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247730 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247824 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247770 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247711 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247782 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247836 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247785 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247847 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247750 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247788 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247849 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247772 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247760 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247764 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247851 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247714 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247828 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247704 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247818 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247823 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247706 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247835 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247734 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247819 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247809 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247830 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247833 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247738 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247716 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247747 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247722 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247816 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247839 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247821 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247798 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247838 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247721 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247781 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247762 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247825 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247777 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247761 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247720 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247814 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247732 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247708 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247740 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247749 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247767 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247748 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247705 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247746 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247752 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247769 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247753 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247723 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247779 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247756 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247826 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247775 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247741 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247799 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247778 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247806 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247815 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247735 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247831 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247845 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247791 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247780 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247853 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247800 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247729 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247810 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247844 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247793 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247759 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247724 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247817 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247727 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247796 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247725 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247801 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247731 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247765 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247792 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247726 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247803 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247728 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247768 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247745 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247855 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247804 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247774 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247807 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247813 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247736 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247712 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247797 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247743 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247719 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247707 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247737 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247827 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247848 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247794 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247757 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247744 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247751 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247837 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247754 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247789 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247802 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247771 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247763 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247808 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247787 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247843 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247811 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247773 1 0.000 0.978 1.000 0.000 0 0.000
#> GSM247766 2 0.000 1.000 0.000 1.000 0 0.000
#> GSM247718 4 0.172 1.000 0.000 0.064 0 0.936
#> GSM247832 1 0.172 0.968 0.936 0.000 0 0.064
#> GSM247709 3 0.000 1.000 0.000 0.000 1 0.000
#> GSM247820 1 0.000 0.978 1.000 0.000 0 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247854 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247758 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247742 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247755 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247841 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247703 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247739 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247715 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247829 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247842 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247805 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247786 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247812 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247776 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247850 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247717 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247784 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247834 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247783 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247846 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247822 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247710 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247713 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247840 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247733 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247852 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247790 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247730 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247824 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247770 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247711 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247782 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247836 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247785 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247847 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247750 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247788 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247849 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247772 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247760 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247764 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247851 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247714 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247828 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247704 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247818 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247823 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247706 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247835 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247734 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247819 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247809 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247830 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247833 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247738 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247716 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247747 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247722 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247816 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247839 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247821 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247798 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247838 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247721 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247781 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247762 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247825 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247777 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247761 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247720 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247814 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247732 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247708 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247740 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247749 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247767 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247748 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247705 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247746 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247752 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247769 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247753 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247723 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247779 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247756 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247826 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247775 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247741 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247799 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247778 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247806 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247815 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247735 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247831 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247845 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247791 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247780 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247853 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247800 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247729 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247810 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247844 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247793 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247759 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247724 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247817 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247727 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247796 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247725 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247801 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247731 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247765 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247792 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247726 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247803 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247728 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247768 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247745 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247855 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247804 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247774 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247807 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247813 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247736 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247712 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247797 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247743 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247719 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247707 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247737 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247827 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247848 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247794 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247757 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247744 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247751 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247837 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247754 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247789 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247802 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247771 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247763 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247808 2 0.0000 0.999 0.000 1.000 0 0.000 0
#> GSM247787 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247843 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247811 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247773 1 0.0000 1.000 1.000 0.000 0 0.000 0
#> GSM247766 2 0.0162 0.998 0.000 0.996 0 0.004 0
#> GSM247718 5 0.0000 1.000 0.000 0.000 0 0.000 1
#> GSM247832 4 0.0162 1.000 0.004 0.000 0 0.996 0
#> GSM247709 3 0.0000 1.000 0.000 0.000 1 0.000 0
#> GSM247820 1 0.0000 1.000 1.000 0.000 0 0.000 0
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.0146 0.814 0 0.996 0 0.000 0.000 0.004
#> GSM247854 2 0.0146 0.814 0 0.996 0 0.000 0.000 0.004
#> GSM247758 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247742 4 0.0547 0.982 0 0.000 0 0.980 0.000 0.020
#> GSM247755 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247841 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247703 2 0.0363 0.811 0 0.988 0 0.000 0.000 0.012
#> GSM247739 5 0.0547 0.970 0 0.000 0 0.000 0.980 0.020
#> GSM247715 4 0.0146 0.982 0 0.000 0 0.996 0.000 0.004
#> GSM247829 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247842 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247805 2 0.0547 0.814 0 0.980 0 0.000 0.000 0.020
#> GSM247786 5 0.0547 0.970 0 0.000 0 0.000 0.980 0.020
#> GSM247812 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247776 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247717 2 0.0146 0.814 0 0.996 0 0.000 0.000 0.004
#> GSM247784 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247834 4 0.0146 0.982 0 0.000 0 0.996 0.000 0.004
#> GSM247783 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247846 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247822 2 0.3817 0.782 0 0.568 0 0.000 0.000 0.432
#> GSM247710 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247713 4 0.0146 0.982 0 0.000 0 0.996 0.000 0.004
#> GSM247840 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247733 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247790 2 0.0146 0.813 0 0.996 0 0.000 0.000 0.004
#> GSM247730 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247824 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247770 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247711 2 0.0547 0.816 0 0.980 0 0.000 0.000 0.020
#> GSM247782 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247836 4 0.0000 0.982 0 0.000 0 1.000 0.000 0.000
#> GSM247785 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247847 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247750 2 0.0146 0.813 0 0.996 0 0.000 0.000 0.004
#> GSM247788 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247849 4 0.0547 0.982 0 0.000 0 0.980 0.000 0.020
#> GSM247772 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247760 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247764 2 0.3860 0.773 0 0.528 0 0.000 0.000 0.472
#> GSM247851 2 0.3860 0.773 0 0.528 0 0.000 0.000 0.472
#> GSM247714 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247828 4 0.0547 0.982 0 0.000 0 0.980 0.000 0.020
#> GSM247704 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247818 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247823 2 0.3782 0.783 0 0.588 0 0.000 0.000 0.412
#> GSM247706 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247835 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247734 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247819 2 0.3862 0.773 0 0.524 0 0.000 0.000 0.476
#> GSM247809 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247830 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247833 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247738 2 0.0363 0.811 0 0.988 0 0.000 0.000 0.012
#> GSM247716 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247747 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247722 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247816 2 0.3244 0.798 0 0.732 0 0.000 0.000 0.268
#> GSM247839 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247821 4 0.0146 0.982 0 0.000 0 0.996 0.000 0.004
#> GSM247798 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247838 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247721 2 0.0458 0.816 0 0.984 0 0.000 0.000 0.016
#> GSM247781 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247762 4 0.0865 0.977 0 0.000 0 0.964 0.000 0.036
#> GSM247825 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247777 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247761 2 0.0865 0.816 0 0.964 0 0.000 0.000 0.036
#> GSM247720 5 0.0547 0.970 0 0.000 0 0.000 0.980 0.020
#> GSM247814 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247732 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247708 2 0.0458 0.816 0 0.984 0 0.000 0.000 0.016
#> GSM247740 5 0.0547 0.970 0 0.000 0 0.000 0.980 0.020
#> GSM247749 4 0.0146 0.982 0 0.000 0 0.996 0.000 0.004
#> GSM247767 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247748 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247705 2 0.3843 0.774 0 0.548 0 0.000 0.000 0.452
#> GSM247746 5 0.3309 0.760 0 0.000 0 0.000 0.720 0.280
#> GSM247752 4 0.1501 0.943 0 0.000 0 0.924 0.000 0.076
#> GSM247769 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247753 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247723 2 0.3862 0.773 0 0.524 0 0.000 0.000 0.476
#> GSM247779 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247756 4 0.0547 0.982 0 0.000 0 0.980 0.000 0.020
#> GSM247826 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247775 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247741 2 0.3860 0.773 0 0.528 0 0.000 0.000 0.472
#> GSM247799 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247778 4 0.0146 0.982 0 0.000 0 0.996 0.000 0.004
#> GSM247806 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247815 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247735 2 0.3860 0.773 0 0.528 0 0.000 0.000 0.472
#> GSM247831 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247845 4 0.0547 0.982 0 0.000 0 0.980 0.000 0.020
#> GSM247791 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247780 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247800 2 0.3860 0.773 0 0.528 0 0.000 0.000 0.472
#> GSM247729 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247810 4 0.0146 0.982 0 0.000 0 0.996 0.000 0.004
#> GSM247844 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247793 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247759 2 0.3810 0.780 0 0.572 0 0.000 0.000 0.428
#> GSM247724 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247817 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247727 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247796 2 0.3862 0.773 0 0.524 0 0.000 0.000 0.476
#> GSM247725 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247801 4 0.0713 0.980 0 0.000 0 0.972 0.000 0.028
#> GSM247731 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247765 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247792 2 0.3860 0.773 0 0.528 0 0.000 0.000 0.472
#> GSM247726 5 0.3857 0.559 0 0.000 0 0.000 0.532 0.468
#> GSM247803 4 0.2883 0.838 0 0.000 0 0.788 0.000 0.212
#> GSM247728 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247768 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247745 2 0.0458 0.816 0 0.984 0 0.000 0.000 0.016
#> GSM247855 2 0.0458 0.816 0 0.984 0 0.000 0.000 0.016
#> GSM247804 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247774 4 0.0547 0.982 0 0.000 0 0.980 0.000 0.020
#> GSM247807 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247813 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247736 2 0.0458 0.816 0 0.984 0 0.000 0.000 0.016
#> GSM247712 5 0.0547 0.970 0 0.000 0 0.000 0.980 0.020
#> GSM247797 4 0.0713 0.980 0 0.000 0 0.972 0.000 0.028
#> GSM247743 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247719 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247707 2 0.0632 0.816 0 0.976 0 0.000 0.000 0.024
#> GSM247737 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247827 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247848 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247794 2 0.0632 0.814 0 0.976 0 0.000 0.000 0.024
#> GSM247757 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247744 4 0.0547 0.982 0 0.000 0 0.980 0.000 0.020
#> GSM247751 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247837 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247754 2 0.3854 0.776 0 0.536 0 0.000 0.000 0.464
#> GSM247789 5 0.0000 0.977 0 0.000 0 0.000 1.000 0.000
#> GSM247802 4 0.0146 0.982 0 0.000 0 0.996 0.000 0.004
#> GSM247771 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247763 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247808 2 0.0632 0.816 0 0.976 0 0.000 0.000 0.024
#> GSM247787 5 0.0547 0.970 0 0.000 0 0.000 0.980 0.020
#> GSM247843 4 0.0146 0.982 0 0.000 0 0.996 0.000 0.004
#> GSM247811 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247773 1 0.0000 1.000 1 0.000 0 0.000 0.000 0.000
#> GSM247766 2 0.3860 0.773 0 0.528 0 0.000 0.000 0.472
#> GSM247718 5 0.0547 0.970 0 0.000 0 0.000 0.980 0.020
#> GSM247832 4 0.0547 0.982 0 0.000 0 0.980 0.000 0.020
#> GSM247709 3 0.0000 1.000 0 0.000 1 0.000 0.000 0.000
#> GSM247820 1 0.0000 1.000 1 0.000 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> MAD:skmeans 153 1 1.000 4.63e-32 2
#> MAD:skmeans 153 1 0.985 2.17e-61 3
#> MAD:skmeans 153 1 0.996 1.16e-90 4
#> MAD:skmeans 153 1 0.989 6.51e-120 5
#> MAD:skmeans 153 1 0.989 6.51e-120 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.
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 19559 rows and 153 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.999 0.999 0.4679 0.533 0.533
#> 3 3 0.981 0.962 0.983 0.3848 0.814 0.654
#> 4 4 1.000 0.988 0.994 0.1393 0.904 0.732
#> 5 5 1.000 1.000 1.000 0.0865 0.929 0.733
#> 6 6 0.975 0.975 0.969 0.0251 0.978 0.890
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0.000 0.999 0.000 1.000
#> GSM247854 2 0.000 0.999 0.000 1.000
#> GSM247758 2 0.000 0.999 0.000 1.000
#> GSM247742 1 0.000 1.000 1.000 0.000
#> GSM247755 2 0.000 0.999 0.000 1.000
#> GSM247841 1 0.000 1.000 1.000 0.000
#> GSM247703 2 0.000 0.999 0.000 1.000
#> GSM247739 2 0.000 0.999 0.000 1.000
#> GSM247715 1 0.000 1.000 1.000 0.000
#> GSM247829 2 0.000 0.999 0.000 1.000
#> GSM247842 1 0.000 1.000 1.000 0.000
#> GSM247805 2 0.000 0.999 0.000 1.000
#> GSM247786 2 0.000 0.999 0.000 1.000
#> GSM247812 2 0.000 0.999 0.000 1.000
#> GSM247776 1 0.000 1.000 1.000 0.000
#> GSM247850 1 0.000 1.000 1.000 0.000
#> GSM247717 2 0.000 0.999 0.000 1.000
#> GSM247784 2 0.000 0.999 0.000 1.000
#> GSM247834 1 0.000 1.000 1.000 0.000
#> GSM247783 2 0.000 0.999 0.000 1.000
#> GSM247846 1 0.000 1.000 1.000 0.000
#> GSM247822 2 0.000 0.999 0.000 1.000
#> GSM247710 2 0.000 0.999 0.000 1.000
#> GSM247713 1 0.000 1.000 1.000 0.000
#> GSM247840 2 0.000 0.999 0.000 1.000
#> GSM247733 1 0.000 1.000 1.000 0.000
#> GSM247852 1 0.000 1.000 1.000 0.000
#> GSM247790 2 0.000 0.999 0.000 1.000
#> GSM247730 2 0.000 0.999 0.000 1.000
#> GSM247824 2 0.000 0.999 0.000 1.000
#> GSM247770 1 0.000 1.000 1.000 0.000
#> GSM247711 2 0.000 0.999 0.000 1.000
#> GSM247782 2 0.000 0.999 0.000 1.000
#> GSM247836 1 0.000 1.000 1.000 0.000
#> GSM247785 2 0.000 0.999 0.000 1.000
#> GSM247847 1 0.000 1.000 1.000 0.000
#> GSM247750 2 0.000 0.999 0.000 1.000
#> GSM247788 2 0.000 0.999 0.000 1.000
#> GSM247849 1 0.000 1.000 1.000 0.000
#> GSM247772 2 0.000 0.999 0.000 1.000
#> GSM247760 1 0.000 1.000 1.000 0.000
#> GSM247764 2 0.000 0.999 0.000 1.000
#> GSM247851 2 0.000 0.999 0.000 1.000
#> GSM247714 2 0.000 0.999 0.000 1.000
#> GSM247828 1 0.000 1.000 1.000 0.000
#> GSM247704 2 0.000 0.999 0.000 1.000
#> GSM247818 1 0.000 1.000 1.000 0.000
#> GSM247823 2 0.000 0.999 0.000 1.000
#> GSM247706 2 0.000 0.999 0.000 1.000
#> GSM247835 2 0.000 0.999 0.000 1.000
#> GSM247734 1 0.000 1.000 1.000 0.000
#> GSM247819 2 0.000 0.999 0.000 1.000
#> GSM247809 2 0.000 0.999 0.000 1.000
#> GSM247830 2 0.000 0.999 0.000 1.000
#> GSM247833 1 0.000 1.000 1.000 0.000
#> GSM247738 2 0.000 0.999 0.000 1.000
#> GSM247716 2 0.000 0.999 0.000 1.000
#> GSM247747 2 0.000 0.999 0.000 1.000
#> GSM247722 1 0.000 1.000 1.000 0.000
#> GSM247816 2 0.000 0.999 0.000 1.000
#> GSM247839 2 0.000 0.999 0.000 1.000
#> GSM247821 1 0.000 1.000 1.000 0.000
#> GSM247798 2 0.000 0.999 0.000 1.000
#> GSM247838 1 0.000 1.000 1.000 0.000
#> GSM247721 2 0.000 0.999 0.000 1.000
#> GSM247781 2 0.000 0.999 0.000 1.000
#> GSM247762 1 0.000 1.000 1.000 0.000
#> GSM247825 2 0.000 0.999 0.000 1.000
#> GSM247777 1 0.000 1.000 1.000 0.000
#> GSM247761 2 0.000 0.999 0.000 1.000
#> GSM247720 2 0.000 0.999 0.000 1.000
#> GSM247814 2 0.000 0.999 0.000 1.000
#> GSM247732 1 0.000 1.000 1.000 0.000
#> GSM247708 2 0.000 0.999 0.000 1.000
#> GSM247740 2 0.000 0.999 0.000 1.000
#> GSM247749 1 0.000 1.000 1.000 0.000
#> GSM247767 2 0.000 0.999 0.000 1.000
#> GSM247748 1 0.000 1.000 1.000 0.000
#> GSM247705 2 0.000 0.999 0.000 1.000
#> GSM247746 2 0.000 0.999 0.000 1.000
#> GSM247752 1 0.163 0.975 0.976 0.024
#> GSM247769 2 0.000 0.999 0.000 1.000
#> GSM247753 1 0.000 1.000 1.000 0.000
#> GSM247723 2 0.000 0.999 0.000 1.000
#> GSM247779 2 0.000 0.999 0.000 1.000
#> GSM247756 1 0.000 1.000 1.000 0.000
#> GSM247826 2 0.000 0.999 0.000 1.000
#> GSM247775 1 0.000 1.000 1.000 0.000
#> GSM247741 2 0.000 0.999 0.000 1.000
#> GSM247799 2 0.000 0.999 0.000 1.000
#> GSM247778 1 0.000 1.000 1.000 0.000
#> GSM247806 2 0.000 0.999 0.000 1.000
#> GSM247815 1 0.000 1.000 1.000 0.000
#> GSM247735 2 0.000 0.999 0.000 1.000
#> GSM247831 2 0.000 0.999 0.000 1.000
#> GSM247845 1 0.000 1.000 1.000 0.000
#> GSM247791 2 0.000 0.999 0.000 1.000
#> GSM247780 1 0.000 1.000 1.000 0.000
#> GSM247853 1 0.000 1.000 1.000 0.000
#> GSM247800 2 0.000 0.999 0.000 1.000
#> GSM247729 2 0.000 0.999 0.000 1.000
#> GSM247810 1 0.000 1.000 1.000 0.000
#> GSM247844 2 0.000 0.999 0.000 1.000
#> GSM247793 1 0.000 1.000 1.000 0.000
#> GSM247759 2 0.000 0.999 0.000 1.000
#> GSM247724 2 0.000 0.999 0.000 1.000
#> GSM247817 2 0.000 0.999 0.000 1.000
#> GSM247727 1 0.000 1.000 1.000 0.000
#> GSM247796 2 0.000 0.999 0.000 1.000
#> GSM247725 2 0.000 0.999 0.000 1.000
#> GSM247801 1 0.000 1.000 1.000 0.000
#> GSM247731 2 0.000 0.999 0.000 1.000
#> GSM247765 1 0.000 1.000 1.000 0.000
#> GSM247792 2 0.000 0.999 0.000 1.000
#> GSM247726 2 0.000 0.999 0.000 1.000
#> GSM247803 2 0.388 0.918 0.076 0.924
#> GSM247728 2 0.000 0.999 0.000 1.000
#> GSM247768 1 0.000 1.000 1.000 0.000
#> GSM247745 2 0.000 0.999 0.000 1.000
#> GSM247855 2 0.000 0.999 0.000 1.000
#> GSM247804 2 0.000 0.999 0.000 1.000
#> GSM247774 1 0.000 1.000 1.000 0.000
#> GSM247807 2 0.000 0.999 0.000 1.000
#> GSM247813 1 0.000 1.000 1.000 0.000
#> GSM247736 2 0.000 0.999 0.000 1.000
#> GSM247712 2 0.000 0.999 0.000 1.000
#> GSM247797 1 0.000 1.000 1.000 0.000
#> GSM247743 2 0.000 0.999 0.000 1.000
#> GSM247719 1 0.000 1.000 1.000 0.000
#> GSM247707 2 0.000 0.999 0.000 1.000
#> GSM247737 2 0.000 0.999 0.000 1.000
#> GSM247827 2 0.000 0.999 0.000 1.000
#> GSM247848 1 0.000 1.000 1.000 0.000
#> GSM247794 2 0.000 0.999 0.000 1.000
#> GSM247757 2 0.000 0.999 0.000 1.000
#> GSM247744 1 0.000 1.000 1.000 0.000
#> GSM247751 2 0.000 0.999 0.000 1.000
#> GSM247837 1 0.000 1.000 1.000 0.000
#> GSM247754 2 0.000 0.999 0.000 1.000
#> GSM247789 2 0.000 0.999 0.000 1.000
#> GSM247802 1 0.000 1.000 1.000 0.000
#> GSM247771 2 0.000 0.999 0.000 1.000
#> GSM247763 1 0.000 1.000 1.000 0.000
#> GSM247808 2 0.000 0.999 0.000 1.000
#> GSM247787 2 0.000 0.999 0.000 1.000
#> GSM247843 1 0.000 1.000 1.000 0.000
#> GSM247811 2 0.000 0.999 0.000 1.000
#> GSM247773 1 0.000 1.000 1.000 0.000
#> GSM247766 2 0.000 0.999 0.000 1.000
#> GSM247718 2 0.000 0.999 0.000 1.000
#> GSM247832 1 0.000 1.000 1.000 0.000
#> GSM247709 2 0.000 0.999 0.000 1.000
#> GSM247820 1 0.000 1.000 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247854 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247758 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247742 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247755 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247841 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247703 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247739 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247715 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247829 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247842 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247805 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247786 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247812 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247776 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247850 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247717 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247784 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247834 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247783 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247846 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247822 2 0.2066 0.912 0.000 0.940 0.060
#> GSM247710 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247713 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247840 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247733 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247852 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247790 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247730 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247824 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247770 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247711 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247782 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247836 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247785 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247847 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247750 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247788 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247849 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247772 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247760 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247764 2 0.4555 0.767 0.000 0.800 0.200
#> GSM247851 2 0.4555 0.767 0.000 0.800 0.200
#> GSM247714 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247828 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247704 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247818 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247823 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247706 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247835 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247734 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247819 2 0.6095 0.420 0.000 0.608 0.392
#> GSM247809 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247830 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247833 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247738 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247716 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247747 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247722 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247816 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247839 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247821 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247798 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247838 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247721 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247781 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247762 1 0.0237 0.995 0.996 0.004 0.000
#> GSM247825 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247777 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247761 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247720 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247814 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247732 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247708 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247740 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247749 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247767 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247748 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247705 2 0.4605 0.762 0.000 0.796 0.204
#> GSM247746 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247752 2 0.6225 0.277 0.432 0.568 0.000
#> GSM247769 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247753 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247723 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247779 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247756 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247826 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247775 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247741 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247799 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247778 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247806 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247815 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247735 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247831 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247845 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247791 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247780 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247853 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247800 2 0.4178 0.801 0.000 0.828 0.172
#> GSM247729 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247810 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247844 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247793 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247759 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247724 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247817 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247727 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247796 2 0.4974 0.717 0.000 0.764 0.236
#> GSM247725 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247801 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247731 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247765 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247792 2 0.4504 0.772 0.000 0.804 0.196
#> GSM247726 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247803 2 0.3038 0.860 0.104 0.896 0.000
#> GSM247728 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247768 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247745 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247855 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247804 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247774 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247807 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247813 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247736 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247712 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247797 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247743 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247719 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247707 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247737 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247827 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247848 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247794 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247757 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247744 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247751 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247837 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247754 2 0.0237 0.957 0.000 0.996 0.004
#> GSM247789 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247802 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247771 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247763 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247808 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247787 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247843 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247811 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247773 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247766 2 0.6079 0.430 0.000 0.612 0.388
#> GSM247718 2 0.0000 0.960 0.000 1.000 0.000
#> GSM247832 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247709 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247820 1 0.0000 1.000 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247854 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247758 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247742 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247755 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247841 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247703 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247739 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247715 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247829 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247842 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247805 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247786 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247812 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247776 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247850 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247717 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247784 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247834 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247783 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247846 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247822 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247710 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247713 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247840 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247733 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247852 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247790 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247730 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247824 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247770 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247711 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247782 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247836 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247785 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247847 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247750 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247788 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247849 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247772 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247760 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247764 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247851 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247714 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247828 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247704 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247818 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247823 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247706 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247835 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247734 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247819 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247809 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247830 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247833 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247738 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247716 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247747 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247722 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247816 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247839 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247821 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247798 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247838 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247721 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247781 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247762 1 0.1576 0.948 0.948 0.048 0 0.004
#> GSM247825 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247777 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247761 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247720 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247814 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247732 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247708 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247740 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247749 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247767 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247748 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247705 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247746 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247752 2 0.6449 0.559 0.232 0.636 0 0.132
#> GSM247769 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247753 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247723 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247779 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247756 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247826 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247775 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247741 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247799 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247778 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247806 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247815 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247735 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247831 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247845 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247791 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247780 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247853 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247800 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247729 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247810 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247844 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247793 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247759 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247724 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247817 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247727 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247796 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247725 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247801 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247731 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247765 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247792 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247726 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247803 2 0.4800 0.492 0.004 0.656 0 0.340
#> GSM247728 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247768 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247745 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247855 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247804 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247774 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247807 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247813 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247736 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247712 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247797 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247743 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247719 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247707 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247737 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247827 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247848 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247794 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247757 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247744 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247751 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247837 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247754 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247789 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247802 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247771 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247763 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247808 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247787 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247843 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247811 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247773 1 0.0000 0.998 1.000 0.000 0 0.000
#> GSM247766 2 0.0000 0.980 0.000 1.000 0 0.000
#> GSM247718 4 0.0188 1.000 0.000 0.004 0 0.996
#> GSM247832 1 0.0188 0.997 0.996 0.000 0 0.004
#> GSM247709 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247820 1 0.0000 0.998 1.000 0.000 0 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0 1 0 1 0 0 0
#> GSM247854 2 0 1 0 1 0 0 0
#> GSM247758 5 0 1 0 0 0 0 1
#> GSM247742 4 0 1 0 0 0 1 0
#> GSM247755 3 0 1 0 0 1 0 0
#> GSM247841 1 0 1 1 0 0 0 0
#> GSM247703 2 0 1 0 1 0 0 0
#> GSM247739 5 0 1 0 0 0 0 1
#> GSM247715 4 0 1 0 0 0 1 0
#> GSM247829 3 0 1 0 0 1 0 0
#> GSM247842 1 0 1 1 0 0 0 0
#> GSM247805 2 0 1 0 1 0 0 0
#> GSM247786 5 0 1 0 0 0 0 1
#> GSM247812 3 0 1 0 0 1 0 0
#> GSM247776 1 0 1 1 0 0 0 0
#> GSM247850 1 0 1 1 0 0 0 0
#> GSM247717 2 0 1 0 1 0 0 0
#> GSM247784 5 0 1 0 0 0 0 1
#> GSM247834 4 0 1 0 0 0 1 0
#> GSM247783 3 0 1 0 0 1 0 0
#> GSM247846 1 0 1 1 0 0 0 0
#> GSM247822 2 0 1 0 1 0 0 0
#> GSM247710 5 0 1 0 0 0 0 1
#> GSM247713 4 0 1 0 0 0 1 0
#> GSM247840 3 0 1 0 0 1 0 0
#> GSM247733 1 0 1 1 0 0 0 0
#> GSM247852 1 0 1 1 0 0 0 0
#> GSM247790 2 0 1 0 1 0 0 0
#> GSM247730 5 0 1 0 0 0 0 1
#> GSM247824 3 0 1 0 0 1 0 0
#> GSM247770 1 0 1 1 0 0 0 0
#> GSM247711 2 0 1 0 1 0 0 0
#> GSM247782 5 0 1 0 0 0 0 1
#> GSM247836 4 0 1 0 0 0 1 0
#> GSM247785 3 0 1 0 0 1 0 0
#> GSM247847 1 0 1 1 0 0 0 0
#> GSM247750 2 0 1 0 1 0 0 0
#> GSM247788 5 0 1 0 0 0 0 1
#> GSM247849 4 0 1 0 0 0 1 0
#> GSM247772 3 0 1 0 0 1 0 0
#> GSM247760 1 0 1 1 0 0 0 0
#> GSM247764 2 0 1 0 1 0 0 0
#> GSM247851 2 0 1 0 1 0 0 0
#> GSM247714 5 0 1 0 0 0 0 1
#> GSM247828 4 0 1 0 0 0 1 0
#> GSM247704 3 0 1 0 0 1 0 0
#> GSM247818 1 0 1 1 0 0 0 0
#> GSM247823 2 0 1 0 1 0 0 0
#> GSM247706 5 0 1 0 0 0 0 1
#> GSM247835 3 0 1 0 0 1 0 0
#> GSM247734 1 0 1 1 0 0 0 0
#> GSM247819 2 0 1 0 1 0 0 0
#> GSM247809 5 0 1 0 0 0 0 1
#> GSM247830 3 0 1 0 0 1 0 0
#> GSM247833 1 0 1 1 0 0 0 0
#> GSM247738 2 0 1 0 1 0 0 0
#> GSM247716 5 0 1 0 0 0 0 1
#> GSM247747 3 0 1 0 0 1 0 0
#> GSM247722 1 0 1 1 0 0 0 0
#> GSM247816 2 0 1 0 1 0 0 0
#> GSM247839 5 0 1 0 0 0 0 1
#> GSM247821 4 0 1 0 0 0 1 0
#> GSM247798 3 0 1 0 0 1 0 0
#> GSM247838 1 0 1 1 0 0 0 0
#> GSM247721 2 0 1 0 1 0 0 0
#> GSM247781 5 0 1 0 0 0 0 1
#> GSM247762 4 0 1 0 0 0 1 0
#> GSM247825 3 0 1 0 0 1 0 0
#> GSM247777 1 0 1 1 0 0 0 0
#> GSM247761 2 0 1 0 1 0 0 0
#> GSM247720 5 0 1 0 0 0 0 1
#> GSM247814 3 0 1 0 0 1 0 0
#> GSM247732 1 0 1 1 0 0 0 0
#> GSM247708 2 0 1 0 1 0 0 0
#> GSM247740 5 0 1 0 0 0 0 1
#> GSM247749 4 0 1 0 0 0 1 0
#> GSM247767 3 0 1 0 0 1 0 0
#> GSM247748 1 0 1 1 0 0 0 0
#> GSM247705 2 0 1 0 1 0 0 0
#> GSM247746 5 0 1 0 0 0 0 1
#> GSM247752 4 0 1 0 0 0 1 0
#> GSM247769 3 0 1 0 0 1 0 0
#> GSM247753 1 0 1 1 0 0 0 0
#> GSM247723 2 0 1 0 1 0 0 0
#> GSM247779 5 0 1 0 0 0 0 1
#> GSM247756 4 0 1 0 0 0 1 0
#> GSM247826 3 0 1 0 0 1 0 0
#> GSM247775 1 0 1 1 0 0 0 0
#> GSM247741 2 0 1 0 1 0 0 0
#> GSM247799 5 0 1 0 0 0 0 1
#> GSM247778 4 0 1 0 0 0 1 0
#> GSM247806 3 0 1 0 0 1 0 0
#> GSM247815 1 0 1 1 0 0 0 0
#> GSM247735 2 0 1 0 1 0 0 0
#> GSM247831 5 0 1 0 0 0 0 1
#> GSM247845 4 0 1 0 0 0 1 0
#> GSM247791 3 0 1 0 0 1 0 0
#> GSM247780 1 0 1 1 0 0 0 0
#> GSM247853 1 0 1 1 0 0 0 0
#> GSM247800 2 0 1 0 1 0 0 0
#> GSM247729 5 0 1 0 0 0 0 1
#> GSM247810 4 0 1 0 0 0 1 0
#> GSM247844 3 0 1 0 0 1 0 0
#> GSM247793 1 0 1 1 0 0 0 0
#> GSM247759 2 0 1 0 1 0 0 0
#> GSM247724 5 0 1 0 0 0 0 1
#> GSM247817 3 0 1 0 0 1 0 0
#> GSM247727 1 0 1 1 0 0 0 0
#> GSM247796 2 0 1 0 1 0 0 0
#> GSM247725 5 0 1 0 0 0 0 1
#> GSM247801 4 0 1 0 0 0 1 0
#> GSM247731 3 0 1 0 0 1 0 0
#> GSM247765 1 0 1 1 0 0 0 0
#> GSM247792 2 0 1 0 1 0 0 0
#> GSM247726 5 0 1 0 0 0 0 1
#> GSM247803 4 0 1 0 0 0 1 0
#> GSM247728 3 0 1 0 0 1 0 0
#> GSM247768 1 0 1 1 0 0 0 0
#> GSM247745 2 0 1 0 1 0 0 0
#> GSM247855 2 0 1 0 1 0 0 0
#> GSM247804 5 0 1 0 0 0 0 1
#> GSM247774 4 0 1 0 0 0 1 0
#> GSM247807 3 0 1 0 0 1 0 0
#> GSM247813 1 0 1 1 0 0 0 0
#> GSM247736 2 0 1 0 1 0 0 0
#> GSM247712 5 0 1 0 0 0 0 1
#> GSM247797 4 0 1 0 0 0 1 0
#> GSM247743 3 0 1 0 0 1 0 0
#> GSM247719 1 0 1 1 0 0 0 0
#> GSM247707 2 0 1 0 1 0 0 0
#> GSM247737 5 0 1 0 0 0 0 1
#> GSM247827 3 0 1 0 0 1 0 0
#> GSM247848 1 0 1 1 0 0 0 0
#> GSM247794 2 0 1 0 1 0 0 0
#> GSM247757 5 0 1 0 0 0 0 1
#> GSM247744 4 0 1 0 0 0 1 0
#> GSM247751 3 0 1 0 0 1 0 0
#> GSM247837 1 0 1 1 0 0 0 0
#> GSM247754 2 0 1 0 1 0 0 0
#> GSM247789 5 0 1 0 0 0 0 1
#> GSM247802 4 0 1 0 0 0 1 0
#> GSM247771 3 0 1 0 0 1 0 0
#> GSM247763 1 0 1 1 0 0 0 0
#> GSM247808 2 0 1 0 1 0 0 0
#> GSM247787 5 0 1 0 0 0 0 1
#> GSM247843 4 0 1 0 0 0 1 0
#> GSM247811 3 0 1 0 0 1 0 0
#> GSM247773 1 0 1 1 0 0 0 0
#> GSM247766 2 0 1 0 1 0 0 0
#> GSM247718 5 0 1 0 0 0 0 1
#> GSM247832 4 0 1 0 0 0 1 0
#> GSM247709 3 0 1 0 0 1 0 0
#> GSM247820 1 0 1 1 0 0 0 0
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.1663 0.935 0 0.912 0 0.000 0 0.088
#> GSM247854 2 0.1663 0.935 0 0.912 0 0.000 0 0.088
#> GSM247758 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247742 4 0.0260 0.930 0 0.000 0 0.992 0 0.008
#> GSM247755 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247841 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247703 2 0.0000 0.940 0 1.000 0 0.000 0 0.000
#> GSM247739 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247715 4 0.2260 0.943 0 0.000 0 0.860 0 0.140
#> GSM247829 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247842 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247805 2 0.0000 0.940 0 1.000 0 0.000 0 0.000
#> GSM247786 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247812 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247776 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247717 2 0.1663 0.935 0 0.912 0 0.000 0 0.088
#> GSM247784 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247834 4 0.2260 0.943 0 0.000 0 0.860 0 0.140
#> GSM247783 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247846 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247822 6 0.2454 0.948 0 0.160 0 0.000 0 0.840
#> GSM247710 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247713 4 0.2260 0.943 0 0.000 0 0.860 0 0.140
#> GSM247840 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247733 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247790 2 0.0000 0.940 0 1.000 0 0.000 0 0.000
#> GSM247730 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247824 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247770 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247711 2 0.1663 0.935 0 0.912 0 0.000 0 0.088
#> GSM247782 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247836 4 0.1444 0.941 0 0.000 0 0.928 0 0.072
#> GSM247785 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247847 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247750 2 0.0000 0.940 0 1.000 0 0.000 0 0.000
#> GSM247788 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247849 4 0.0363 0.930 0 0.000 0 0.988 0 0.012
#> GSM247772 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247760 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247764 6 0.3620 0.777 0 0.352 0 0.000 0 0.648
#> GSM247851 6 0.3620 0.777 0 0.352 0 0.000 0 0.648
#> GSM247714 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247828 4 0.1444 0.941 0 0.000 0 0.928 0 0.072
#> GSM247704 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247818 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247823 2 0.0000 0.940 0 1.000 0 0.000 0 0.000
#> GSM247706 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247835 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247734 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247819 6 0.2378 0.953 0 0.152 0 0.000 0 0.848
#> GSM247809 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247830 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247833 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247738 2 0.1663 0.935 0 0.912 0 0.000 0 0.088
#> GSM247716 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247747 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247722 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247816 2 0.0000 0.940 0 1.000 0 0.000 0 0.000
#> GSM247839 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247821 4 0.2260 0.943 0 0.000 0 0.860 0 0.140
#> GSM247798 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247838 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247721 2 0.0000 0.940 0 1.000 0 0.000 0 0.000
#> GSM247781 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247762 4 0.0363 0.930 0 0.000 0 0.988 0 0.012
#> GSM247825 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247777 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247761 2 0.0000 0.940 0 1.000 0 0.000 0 0.000
#> GSM247720 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247814 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247732 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247708 2 0.1075 0.941 0 0.952 0 0.000 0 0.048
#> GSM247740 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247749 4 0.2260 0.943 0 0.000 0 0.860 0 0.140
#> GSM247767 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247748 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247705 2 0.0000 0.940 0 1.000 0 0.000 0 0.000
#> GSM247746 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247752 4 0.2300 0.942 0 0.000 0 0.856 0 0.144
#> GSM247769 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247753 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247723 6 0.2378 0.953 0 0.152 0 0.000 0 0.848
#> GSM247779 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247756 4 0.0260 0.930 0 0.000 0 0.992 0 0.008
#> GSM247826 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247775 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247741 6 0.2378 0.953 0 0.152 0 0.000 0 0.848
#> GSM247799 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247778 4 0.2260 0.943 0 0.000 0 0.860 0 0.140
#> GSM247806 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247815 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247735 6 0.2378 0.953 0 0.152 0 0.000 0 0.848
#> GSM247831 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247845 4 0.0260 0.930 0 0.000 0 0.992 0 0.008
#> GSM247791 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247780 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247800 6 0.2378 0.953 0 0.152 0 0.000 0 0.848
#> GSM247729 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247810 4 0.2260 0.943 0 0.000 0 0.860 0 0.140
#> GSM247844 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247793 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247759 2 0.2135 0.893 0 0.872 0 0.000 0 0.128
#> GSM247724 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247817 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247727 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247796 6 0.2378 0.953 0 0.152 0 0.000 0 0.848
#> GSM247725 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247801 4 0.0363 0.930 0 0.000 0 0.988 0 0.012
#> GSM247731 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247765 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247792 6 0.2378 0.953 0 0.152 0 0.000 0 0.848
#> GSM247726 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247803 4 0.2300 0.942 0 0.000 0 0.856 0 0.144
#> GSM247728 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247768 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247745 2 0.1663 0.935 0 0.912 0 0.000 0 0.088
#> GSM247855 2 0.1663 0.935 0 0.912 0 0.000 0 0.088
#> GSM247804 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247774 4 0.0260 0.930 0 0.000 0 0.992 0 0.008
#> GSM247807 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247813 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247736 2 0.1663 0.935 0 0.912 0 0.000 0 0.088
#> GSM247712 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247797 4 0.2300 0.942 0 0.000 0 0.856 0 0.144
#> GSM247743 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247719 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247707 2 0.0000 0.940 0 1.000 0 0.000 0 0.000
#> GSM247737 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247827 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247848 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247794 2 0.0000 0.940 0 1.000 0 0.000 0 0.000
#> GSM247757 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247744 4 0.0146 0.931 0 0.000 0 0.996 0 0.004
#> GSM247751 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247837 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247754 2 0.1444 0.936 0 0.928 0 0.000 0 0.072
#> GSM247789 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247802 4 0.1444 0.938 0 0.000 0 0.928 0 0.072
#> GSM247771 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247763 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247808 2 0.1663 0.935 0 0.912 0 0.000 0 0.088
#> GSM247787 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247843 4 0.2260 0.943 0 0.000 0 0.860 0 0.140
#> GSM247811 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247773 1 0.0000 1.000 1 0.000 0 0.000 0 0.000
#> GSM247766 6 0.2597 0.937 0 0.176 0 0.000 0 0.824
#> GSM247718 5 0.0000 1.000 0 0.000 0 0.000 1 0.000
#> GSM247832 4 0.0260 0.930 0 0.000 0 0.992 0 0.008
#> GSM247709 3 0.0000 1.000 0 0.000 1 0.000 0 0.000
#> GSM247820 1 0.0000 1.000 1 0.000 0 0.000 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
get_signatures(res, k = 4)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
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
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> MAD:pam 153 1 1.000 3.54e-31 2
#> MAD:pam 150 1 0.974 4.41e-59 3
#> MAD:pam 152 1 0.983 1.39e-88 4
#> MAD:pam 153 1 0.989 6.51e-120 5
#> MAD:pam 153 1 0.822 8.52e-117 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.675 0.806 0.903 0.4822 0.508 0.508
#> 3 3 0.828 0.896 0.934 0.2942 0.842 0.689
#> 4 4 1.000 1.000 1.000 0.1400 0.939 0.825
#> 5 5 1.000 0.992 0.997 0.1258 0.910 0.689
#> 6 6 0.989 0.932 0.971 0.0169 0.991 0.957
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] 4
There is also optional best \(k\) = 4 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0.000 1.000 0.00 1.00
#> GSM247854 2 0.000 1.000 0.00 1.00
#> GSM247758 2 0.000 1.000 0.00 1.00
#> GSM247742 1 0.000 0.809 1.00 0.00
#> GSM247755 1 0.999 0.395 0.52 0.48
#> GSM247841 1 0.000 0.809 1.00 0.00
#> GSM247703 2 0.000 1.000 0.00 1.00
#> GSM247739 2 0.000 1.000 0.00 1.00
#> GSM247715 1 0.000 0.809 1.00 0.00
#> GSM247829 1 0.999 0.395 0.52 0.48
#> GSM247842 1 0.000 0.809 1.00 0.00
#> GSM247805 2 0.000 1.000 0.00 1.00
#> GSM247786 2 0.000 1.000 0.00 1.00
#> GSM247812 1 0.999 0.395 0.52 0.48
#> GSM247776 1 0.000 0.809 1.00 0.00
#> GSM247850 1 0.000 0.809 1.00 0.00
#> GSM247717 2 0.000 1.000 0.00 1.00
#> GSM247784 2 0.000 1.000 0.00 1.00
#> GSM247834 1 0.000 0.809 1.00 0.00
#> GSM247783 1 0.999 0.395 0.52 0.48
#> GSM247846 1 0.000 0.809 1.00 0.00
#> GSM247822 2 0.000 1.000 0.00 1.00
#> GSM247710 2 0.000 1.000 0.00 1.00
#> GSM247713 1 0.000 0.809 1.00 0.00
#> GSM247840 1 0.999 0.395 0.52 0.48
#> GSM247733 1 0.000 0.809 1.00 0.00
#> GSM247852 1 0.000 0.809 1.00 0.00
#> GSM247790 2 0.000 1.000 0.00 1.00
#> GSM247730 2 0.000 1.000 0.00 1.00
#> GSM247824 1 0.999 0.395 0.52 0.48
#> GSM247770 1 0.000 0.809 1.00 0.00
#> GSM247711 2 0.000 1.000 0.00 1.00
#> GSM247782 2 0.000 1.000 0.00 1.00
#> GSM247836 1 0.000 0.809 1.00 0.00
#> GSM247785 1 0.999 0.395 0.52 0.48
#> GSM247847 1 0.000 0.809 1.00 0.00
#> GSM247750 2 0.000 1.000 0.00 1.00
#> GSM247788 2 0.000 1.000 0.00 1.00
#> GSM247849 1 0.000 0.809 1.00 0.00
#> GSM247772 1 0.999 0.395 0.52 0.48
#> GSM247760 1 0.000 0.809 1.00 0.00
#> GSM247764 2 0.000 1.000 0.00 1.00
#> GSM247851 2 0.000 1.000 0.00 1.00
#> GSM247714 2 0.000 1.000 0.00 1.00
#> GSM247828 1 0.000 0.809 1.00 0.00
#> GSM247704 1 0.999 0.395 0.52 0.48
#> GSM247818 1 0.000 0.809 1.00 0.00
#> GSM247823 2 0.000 1.000 0.00 1.00
#> GSM247706 2 0.000 1.000 0.00 1.00
#> GSM247835 1 0.999 0.395 0.52 0.48
#> GSM247734 1 0.000 0.809 1.00 0.00
#> GSM247819 2 0.000 1.000 0.00 1.00
#> GSM247809 2 0.000 1.000 0.00 1.00
#> GSM247830 1 0.999 0.395 0.52 0.48
#> GSM247833 1 0.000 0.809 1.00 0.00
#> GSM247738 2 0.000 1.000 0.00 1.00
#> GSM247716 2 0.000 1.000 0.00 1.00
#> GSM247747 1 0.999 0.395 0.52 0.48
#> GSM247722 1 0.000 0.809 1.00 0.00
#> GSM247816 2 0.000 1.000 0.00 1.00
#> GSM247839 2 0.000 1.000 0.00 1.00
#> GSM247821 1 0.000 0.809 1.00 0.00
#> GSM247798 1 0.999 0.395 0.52 0.48
#> GSM247838 1 0.000 0.809 1.00 0.00
#> GSM247721 2 0.000 1.000 0.00 1.00
#> GSM247781 2 0.000 1.000 0.00 1.00
#> GSM247762 1 0.000 0.809 1.00 0.00
#> GSM247825 1 0.999 0.395 0.52 0.48
#> GSM247777 1 0.000 0.809 1.00 0.00
#> GSM247761 2 0.000 1.000 0.00 1.00
#> GSM247720 2 0.000 1.000 0.00 1.00
#> GSM247814 1 0.999 0.395 0.52 0.48
#> GSM247732 1 0.000 0.809 1.00 0.00
#> GSM247708 2 0.000 1.000 0.00 1.00
#> GSM247740 2 0.000 1.000 0.00 1.00
#> GSM247749 1 0.000 0.809 1.00 0.00
#> GSM247767 1 0.999 0.395 0.52 0.48
#> GSM247748 1 0.000 0.809 1.00 0.00
#> GSM247705 2 0.000 1.000 0.00 1.00
#> GSM247746 2 0.000 1.000 0.00 1.00
#> GSM247752 1 0.000 0.809 1.00 0.00
#> GSM247769 1 0.999 0.395 0.52 0.48
#> GSM247753 1 0.000 0.809 1.00 0.00
#> GSM247723 2 0.000 1.000 0.00 1.00
#> GSM247779 2 0.000 1.000 0.00 1.00
#> GSM247756 1 0.000 0.809 1.00 0.00
#> GSM247826 1 0.999 0.395 0.52 0.48
#> GSM247775 1 0.000 0.809 1.00 0.00
#> GSM247741 2 0.000 1.000 0.00 1.00
#> GSM247799 2 0.000 1.000 0.00 1.00
#> GSM247778 1 0.000 0.809 1.00 0.00
#> GSM247806 1 0.999 0.395 0.52 0.48
#> GSM247815 1 0.000 0.809 1.00 0.00
#> GSM247735 2 0.000 1.000 0.00 1.00
#> GSM247831 2 0.000 1.000 0.00 1.00
#> GSM247845 1 0.000 0.809 1.00 0.00
#> GSM247791 1 0.999 0.395 0.52 0.48
#> GSM247780 1 0.000 0.809 1.00 0.00
#> GSM247853 1 0.000 0.809 1.00 0.00
#> GSM247800 2 0.000 1.000 0.00 1.00
#> GSM247729 2 0.000 1.000 0.00 1.00
#> GSM247810 1 0.000 0.809 1.00 0.00
#> GSM247844 1 0.999 0.395 0.52 0.48
#> GSM247793 1 0.000 0.809 1.00 0.00
#> GSM247759 2 0.000 1.000 0.00 1.00
#> GSM247724 2 0.000 1.000 0.00 1.00
#> GSM247817 1 0.999 0.395 0.52 0.48
#> GSM247727 1 0.000 0.809 1.00 0.00
#> GSM247796 2 0.000 1.000 0.00 1.00
#> GSM247725 2 0.000 1.000 0.00 1.00
#> GSM247801 1 0.000 0.809 1.00 0.00
#> GSM247731 1 0.999 0.395 0.52 0.48
#> GSM247765 1 0.000 0.809 1.00 0.00
#> GSM247792 2 0.000 1.000 0.00 1.00
#> GSM247726 2 0.000 1.000 0.00 1.00
#> GSM247803 1 0.000 0.809 1.00 0.00
#> GSM247728 1 0.999 0.395 0.52 0.48
#> GSM247768 1 0.000 0.809 1.00 0.00
#> GSM247745 2 0.000 1.000 0.00 1.00
#> GSM247855 2 0.000 1.000 0.00 1.00
#> GSM247804 2 0.000 1.000 0.00 1.00
#> GSM247774 1 0.000 0.809 1.00 0.00
#> GSM247807 1 0.999 0.395 0.52 0.48
#> GSM247813 1 0.000 0.809 1.00 0.00
#> GSM247736 2 0.000 1.000 0.00 1.00
#> GSM247712 2 0.000 1.000 0.00 1.00
#> GSM247797 1 0.000 0.809 1.00 0.00
#> GSM247743 1 0.999 0.395 0.52 0.48
#> GSM247719 1 0.000 0.809 1.00 0.00
#> GSM247707 2 0.000 1.000 0.00 1.00
#> GSM247737 2 0.000 1.000 0.00 1.00
#> GSM247827 1 0.999 0.395 0.52 0.48
#> GSM247848 1 0.000 0.809 1.00 0.00
#> GSM247794 2 0.000 1.000 0.00 1.00
#> GSM247757 2 0.000 1.000 0.00 1.00
#> GSM247744 1 0.000 0.809 1.00 0.00
#> GSM247751 1 0.999 0.395 0.52 0.48
#> GSM247837 1 0.000 0.809 1.00 0.00
#> GSM247754 2 0.000 1.000 0.00 1.00
#> GSM247789 2 0.000 1.000 0.00 1.00
#> GSM247802 1 0.000 0.809 1.00 0.00
#> GSM247771 1 0.999 0.395 0.52 0.48
#> GSM247763 1 0.000 0.809 1.00 0.00
#> GSM247808 2 0.000 1.000 0.00 1.00
#> GSM247787 2 0.000 1.000 0.00 1.00
#> GSM247843 1 0.000 0.809 1.00 0.00
#> GSM247811 1 0.999 0.395 0.52 0.48
#> GSM247773 1 0.000 0.809 1.00 0.00
#> GSM247766 2 0.000 1.000 0.00 1.00
#> GSM247718 2 0.000 1.000 0.00 1.00
#> GSM247832 1 0.000 0.809 1.00 0.00
#> GSM247709 1 0.999 0.395 0.52 0.48
#> GSM247820 1 0.000 0.809 1.00 0.00
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247854 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247758 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247742 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247755 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247841 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247703 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247739 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247715 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247829 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247842 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247805 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247786 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247812 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247776 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247850 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247717 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247784 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247834 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247783 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247846 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247822 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247710 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247713 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247840 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247733 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247852 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247790 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247730 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247824 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247770 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247711 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247782 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247836 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247785 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247847 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247750 2 0.0592 0.990 0.000 0.988 0.012
#> GSM247788 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247849 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247772 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247760 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247764 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247851 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247714 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247828 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247704 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247818 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247823 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247706 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247835 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247734 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247819 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247809 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247830 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247833 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247738 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247716 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247747 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247722 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247816 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247839 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247821 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247798 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247838 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247721 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247781 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247762 3 0.7395 0.615 0.040 0.380 0.580
#> GSM247825 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247777 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247761 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247720 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247814 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247732 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247708 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247740 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247749 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247767 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247748 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247705 2 0.0592 0.990 0.000 0.988 0.012
#> GSM247746 2 0.0592 0.988 0.000 0.988 0.012
#> GSM247752 3 0.7395 0.615 0.040 0.380 0.580
#> GSM247769 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247753 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247723 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247779 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247756 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247826 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247775 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247741 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247799 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247778 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247806 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247815 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247735 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247831 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247845 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247791 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247780 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247853 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247800 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247729 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247810 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247844 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247793 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247759 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247724 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247817 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247727 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247796 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247725 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247801 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247731 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247765 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247792 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247726 2 0.0747 0.984 0.000 0.984 0.016
#> GSM247803 3 0.7395 0.615 0.040 0.380 0.580
#> GSM247728 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247768 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247745 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247855 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247804 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247774 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247807 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247813 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247736 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247712 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247797 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247743 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247719 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247707 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247737 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247827 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247848 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247794 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247757 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247744 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247751 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247837 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247754 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247789 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247802 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247771 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247763 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247808 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247787 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247843 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247811 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247773 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247766 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247718 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247832 3 0.7475 0.618 0.044 0.376 0.580
#> GSM247709 3 0.0424 0.778 0.000 0.008 0.992
#> GSM247820 1 0.0000 1.000 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0 1 0 1 0 0
#> GSM247854 2 0 1 0 1 0 0
#> GSM247758 2 0 1 0 1 0 0
#> GSM247742 4 0 1 0 0 0 1
#> GSM247755 3 0 1 0 0 1 0
#> GSM247841 1 0 1 1 0 0 0
#> GSM247703 2 0 1 0 1 0 0
#> GSM247739 2 0 1 0 1 0 0
#> GSM247715 4 0 1 0 0 0 1
#> GSM247829 3 0 1 0 0 1 0
#> GSM247842 1 0 1 1 0 0 0
#> GSM247805 2 0 1 0 1 0 0
#> GSM247786 2 0 1 0 1 0 0
#> GSM247812 3 0 1 0 0 1 0
#> GSM247776 1 0 1 1 0 0 0
#> GSM247850 1 0 1 1 0 0 0
#> GSM247717 2 0 1 0 1 0 0
#> GSM247784 2 0 1 0 1 0 0
#> GSM247834 4 0 1 0 0 0 1
#> GSM247783 3 0 1 0 0 1 0
#> GSM247846 1 0 1 1 0 0 0
#> GSM247822 2 0 1 0 1 0 0
#> GSM247710 2 0 1 0 1 0 0
#> GSM247713 4 0 1 0 0 0 1
#> GSM247840 3 0 1 0 0 1 0
#> GSM247733 1 0 1 1 0 0 0
#> GSM247852 1 0 1 1 0 0 0
#> GSM247790 2 0 1 0 1 0 0
#> GSM247730 2 0 1 0 1 0 0
#> GSM247824 3 0 1 0 0 1 0
#> GSM247770 1 0 1 1 0 0 0
#> GSM247711 2 0 1 0 1 0 0
#> GSM247782 2 0 1 0 1 0 0
#> GSM247836 4 0 1 0 0 0 1
#> GSM247785 3 0 1 0 0 1 0
#> GSM247847 1 0 1 1 0 0 0
#> GSM247750 2 0 1 0 1 0 0
#> GSM247788 2 0 1 0 1 0 0
#> GSM247849 4 0 1 0 0 0 1
#> GSM247772 3 0 1 0 0 1 0
#> GSM247760 1 0 1 1 0 0 0
#> GSM247764 2 0 1 0 1 0 0
#> GSM247851 2 0 1 0 1 0 0
#> GSM247714 2 0 1 0 1 0 0
#> GSM247828 4 0 1 0 0 0 1
#> GSM247704 3 0 1 0 0 1 0
#> GSM247818 1 0 1 1 0 0 0
#> GSM247823 2 0 1 0 1 0 0
#> GSM247706 2 0 1 0 1 0 0
#> GSM247835 3 0 1 0 0 1 0
#> GSM247734 1 0 1 1 0 0 0
#> GSM247819 2 0 1 0 1 0 0
#> GSM247809 2 0 1 0 1 0 0
#> GSM247830 3 0 1 0 0 1 0
#> GSM247833 1 0 1 1 0 0 0
#> GSM247738 2 0 1 0 1 0 0
#> GSM247716 2 0 1 0 1 0 0
#> GSM247747 3 0 1 0 0 1 0
#> GSM247722 1 0 1 1 0 0 0
#> GSM247816 2 0 1 0 1 0 0
#> GSM247839 2 0 1 0 1 0 0
#> GSM247821 4 0 1 0 0 0 1
#> GSM247798 3 0 1 0 0 1 0
#> GSM247838 1 0 1 1 0 0 0
#> GSM247721 2 0 1 0 1 0 0
#> GSM247781 2 0 1 0 1 0 0
#> GSM247762 4 0 1 0 0 0 1
#> GSM247825 3 0 1 0 0 1 0
#> GSM247777 1 0 1 1 0 0 0
#> GSM247761 2 0 1 0 1 0 0
#> GSM247720 2 0 1 0 1 0 0
#> GSM247814 3 0 1 0 0 1 0
#> GSM247732 1 0 1 1 0 0 0
#> GSM247708 2 0 1 0 1 0 0
#> GSM247740 2 0 1 0 1 0 0
#> GSM247749 4 0 1 0 0 0 1
#> GSM247767 3 0 1 0 0 1 0
#> GSM247748 1 0 1 1 0 0 0
#> GSM247705 2 0 1 0 1 0 0
#> GSM247746 2 0 1 0 1 0 0
#> GSM247752 4 0 1 0 0 0 1
#> GSM247769 3 0 1 0 0 1 0
#> GSM247753 1 0 1 1 0 0 0
#> GSM247723 2 0 1 0 1 0 0
#> GSM247779 2 0 1 0 1 0 0
#> GSM247756 4 0 1 0 0 0 1
#> GSM247826 3 0 1 0 0 1 0
#> GSM247775 1 0 1 1 0 0 0
#> GSM247741 2 0 1 0 1 0 0
#> GSM247799 2 0 1 0 1 0 0
#> GSM247778 4 0 1 0 0 0 1
#> GSM247806 3 0 1 0 0 1 0
#> GSM247815 1 0 1 1 0 0 0
#> GSM247735 2 0 1 0 1 0 0
#> GSM247831 2 0 1 0 1 0 0
#> GSM247845 4 0 1 0 0 0 1
#> GSM247791 3 0 1 0 0 1 0
#> GSM247780 1 0 1 1 0 0 0
#> GSM247853 1 0 1 1 0 0 0
#> GSM247800 2 0 1 0 1 0 0
#> GSM247729 2 0 1 0 1 0 0
#> GSM247810 4 0 1 0 0 0 1
#> GSM247844 3 0 1 0 0 1 0
#> GSM247793 1 0 1 1 0 0 0
#> GSM247759 2 0 1 0 1 0 0
#> GSM247724 2 0 1 0 1 0 0
#> GSM247817 3 0 1 0 0 1 0
#> GSM247727 1 0 1 1 0 0 0
#> GSM247796 2 0 1 0 1 0 0
#> GSM247725 2 0 1 0 1 0 0
#> GSM247801 4 0 1 0 0 0 1
#> GSM247731 3 0 1 0 0 1 0
#> GSM247765 1 0 1 1 0 0 0
#> GSM247792 2 0 1 0 1 0 0
#> GSM247726 2 0 1 0 1 0 0
#> GSM247803 4 0 1 0 0 0 1
#> GSM247728 3 0 1 0 0 1 0
#> GSM247768 1 0 1 1 0 0 0
#> GSM247745 2 0 1 0 1 0 0
#> GSM247855 2 0 1 0 1 0 0
#> GSM247804 2 0 1 0 1 0 0
#> GSM247774 4 0 1 0 0 0 1
#> GSM247807 3 0 1 0 0 1 0
#> GSM247813 1 0 1 1 0 0 0
#> GSM247736 2 0 1 0 1 0 0
#> GSM247712 2 0 1 0 1 0 0
#> GSM247797 4 0 1 0 0 0 1
#> GSM247743 3 0 1 0 0 1 0
#> GSM247719 1 0 1 1 0 0 0
#> GSM247707 2 0 1 0 1 0 0
#> GSM247737 2 0 1 0 1 0 0
#> GSM247827 3 0 1 0 0 1 0
#> GSM247848 1 0 1 1 0 0 0
#> GSM247794 2 0 1 0 1 0 0
#> GSM247757 2 0 1 0 1 0 0
#> GSM247744 4 0 1 0 0 0 1
#> GSM247751 3 0 1 0 0 1 0
#> GSM247837 1 0 1 1 0 0 0
#> GSM247754 2 0 1 0 1 0 0
#> GSM247789 2 0 1 0 1 0 0
#> GSM247802 4 0 1 0 0 0 1
#> GSM247771 3 0 1 0 0 1 0
#> GSM247763 1 0 1 1 0 0 0
#> GSM247808 2 0 1 0 1 0 0
#> GSM247787 2 0 1 0 1 0 0
#> GSM247843 4 0 1 0 0 0 1
#> GSM247811 3 0 1 0 0 1 0
#> GSM247773 1 0 1 1 0 0 0
#> GSM247766 2 0 1 0 1 0 0
#> GSM247718 2 0 1 0 1 0 0
#> GSM247832 4 0 1 0 0 0 1
#> GSM247709 3 0 1 0 0 1 0
#> GSM247820 1 0 1 1 0 0 0
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247854 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247758 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247742 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247755 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247841 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247703 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247739 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247715 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247829 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247842 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247805 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247786 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247812 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247776 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247850 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247717 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247784 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247834 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247783 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247846 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247822 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247710 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247713 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247840 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247733 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247852 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247790 2 0.0290 0.989 0 0.992 0 0 0.008
#> GSM247730 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247824 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247770 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247711 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247782 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247836 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247785 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247847 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247750 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247788 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247849 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247772 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247760 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247764 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247851 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247714 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247828 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247704 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247818 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247823 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247706 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247835 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247734 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247819 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247809 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247830 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247833 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247738 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247716 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247747 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247722 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247816 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247839 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247821 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247798 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247838 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247721 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247781 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247762 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247825 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247777 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247761 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247720 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247814 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247732 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247708 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247740 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247749 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247767 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247748 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247705 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247746 2 0.2020 0.889 0 0.900 0 0 0.100
#> GSM247752 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247769 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247753 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247723 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247779 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247756 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247826 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247775 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247741 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247799 5 0.0404 0.973 0 0.012 0 0 0.988
#> GSM247778 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247806 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247815 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247735 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247831 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247845 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247791 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247780 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247853 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247800 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247729 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247810 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247844 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247793 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247759 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247724 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247817 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247727 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247796 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247725 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247801 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247731 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247765 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247792 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247726 2 0.0880 0.965 0 0.968 0 0 0.032
#> GSM247803 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247728 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247768 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247745 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247855 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247804 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247774 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247807 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247813 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247736 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247712 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247797 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247743 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247719 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247707 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247737 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247827 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247848 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247794 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247757 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247744 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247751 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247837 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247754 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247789 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247802 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247771 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247763 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247808 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247787 5 0.0000 0.985 0 0.000 0 0 1.000
#> GSM247843 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247811 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247773 1 0.0000 1.000 1 0.000 0 0 0.000
#> GSM247766 2 0.0000 0.996 0 1.000 0 0 0.000
#> GSM247718 5 0.4045 0.441 0 0.356 0 0 0.644
#> GSM247832 4 0.0000 1.000 0 0.000 0 1 0.000
#> GSM247709 3 0.0000 1.000 0 0.000 1 0 0.000
#> GSM247820 1 0.0000 1.000 1 0.000 0 0 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.0458 0.8724 0.000 0.984 0 0 0.000 0.016
#> GSM247854 2 0.0458 0.8724 0.000 0.984 0 0 0.000 0.016
#> GSM247758 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247742 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247755 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247841 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247703 2 0.3266 0.5838 0.000 0.728 0 0 0.000 0.272
#> GSM247739 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247715 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247829 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247842 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247805 2 0.3126 0.6215 0.000 0.752 0 0 0.000 0.248
#> GSM247786 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247812 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247776 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247850 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247717 2 0.0632 0.8688 0.000 0.976 0 0 0.000 0.024
#> GSM247784 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247834 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247783 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247846 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247822 2 0.1204 0.8532 0.000 0.944 0 0 0.000 0.056
#> GSM247710 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247713 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247840 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247733 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247852 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247790 2 0.4147 0.0353 0.000 0.552 0 0 0.012 0.436
#> GSM247730 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247824 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247770 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247711 2 0.0000 0.8760 0.000 1.000 0 0 0.000 0.000
#> GSM247782 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247836 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247785 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247847 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247750 2 0.3797 0.1542 0.000 0.580 0 0 0.000 0.420
#> GSM247788 5 0.0260 0.9692 0.000 0.000 0 0 0.992 0.008
#> GSM247849 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247772 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247760 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247764 2 0.1141 0.8548 0.000 0.948 0 0 0.000 0.052
#> GSM247851 2 0.1204 0.8532 0.000 0.944 0 0 0.000 0.056
#> GSM247714 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247828 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247704 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247818 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247823 2 0.2823 0.6884 0.000 0.796 0 0 0.000 0.204
#> GSM247706 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247835 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247734 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247819 2 0.1141 0.8548 0.000 0.948 0 0 0.000 0.052
#> GSM247809 5 0.2170 0.8594 0.000 0.012 0 0 0.888 0.100
#> GSM247830 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247833 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247738 2 0.3198 0.6029 0.000 0.740 0 0 0.000 0.260
#> GSM247716 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247747 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247722 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247816 2 0.0260 0.8758 0.000 0.992 0 0 0.000 0.008
#> GSM247839 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247821 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247798 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247838 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247721 2 0.0146 0.8757 0.000 0.996 0 0 0.000 0.004
#> GSM247781 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247762 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247825 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247777 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247761 2 0.2969 0.6600 0.000 0.776 0 0 0.000 0.224
#> GSM247720 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247814 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247732 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247708 2 0.0000 0.8760 0.000 1.000 0 0 0.000 0.000
#> GSM247740 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247749 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247767 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247748 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247705 6 0.3198 0.6825 0.000 0.260 0 0 0.000 0.740
#> GSM247746 6 0.4801 0.6352 0.000 0.280 0 0 0.088 0.632
#> GSM247752 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247769 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247753 1 0.1714 0.9076 0.908 0.000 0 0 0.000 0.092
#> GSM247723 2 0.0790 0.8647 0.000 0.968 0 0 0.000 0.032
#> GSM247779 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247756 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247826 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247775 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247741 2 0.0000 0.8760 0.000 1.000 0 0 0.000 0.000
#> GSM247799 5 0.1806 0.8893 0.000 0.004 0 0 0.908 0.088
#> GSM247778 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247806 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247815 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247735 2 0.0260 0.8740 0.000 0.992 0 0 0.000 0.008
#> GSM247831 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247845 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247791 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247780 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247853 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247800 2 0.1075 0.8566 0.000 0.952 0 0 0.000 0.048
#> GSM247729 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247810 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247844 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247793 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247759 2 0.0363 0.8740 0.000 0.988 0 0 0.000 0.012
#> GSM247724 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247817 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247727 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247796 2 0.1007 0.8575 0.000 0.956 0 0 0.000 0.044
#> GSM247725 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247801 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247731 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247765 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247792 2 0.1007 0.8575 0.000 0.956 0 0 0.000 0.044
#> GSM247726 6 0.1204 0.7014 0.000 0.056 0 0 0.000 0.944
#> GSM247803 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247728 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247768 1 0.1714 0.9076 0.908 0.000 0 0 0.000 0.092
#> GSM247745 2 0.0000 0.8760 0.000 1.000 0 0 0.000 0.000
#> GSM247855 2 0.0000 0.8760 0.000 1.000 0 0 0.000 0.000
#> GSM247804 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247774 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247807 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247813 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247736 2 0.0000 0.8760 0.000 1.000 0 0 0.000 0.000
#> GSM247712 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247797 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247743 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247719 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247707 2 0.0000 0.8760 0.000 1.000 0 0 0.000 0.000
#> GSM247737 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247827 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247848 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247794 2 0.3409 0.5176 0.000 0.700 0 0 0.000 0.300
#> GSM247757 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247744 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247751 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247837 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247754 2 0.1387 0.8388 0.000 0.932 0 0 0.000 0.068
#> GSM247789 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247802 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247771 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247763 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247808 2 0.0000 0.8760 0.000 1.000 0 0 0.000 0.000
#> GSM247787 5 0.0000 0.9764 0.000 0.000 0 0 1.000 0.000
#> GSM247843 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247811 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247773 1 0.0000 0.9947 1.000 0.000 0 0 0.000 0.000
#> GSM247766 2 0.1075 0.8566 0.000 0.952 0 0 0.000 0.048
#> GSM247718 5 0.4967 0.3269 0.000 0.228 0 0 0.640 0.132
#> GSM247832 4 0.0000 1.0000 0.000 0.000 0 1 0.000 0.000
#> GSM247709 3 0.0000 1.0000 0.000 0.000 1 0 0.000 0.000
#> GSM247820 1 0.0000 0.9947 1.000 0.000 0 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
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
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> MAD:mclust 122 1 1.000 2.86e-26 2
#> MAD:mclust 153 1 0.956 2.17e-61 3
#> MAD:mclust 153 1 0.964 1.16e-90 4
#> MAD:mclust 152 1 0.887 3.04e-115 5
#> MAD:mclust 150 1 0.431 6.60e-113 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.47112 0.529 0.529
#> 3 3 0.969 0.954 0.977 0.38164 0.827 0.673
#> 4 4 0.877 0.946 0.946 0.10528 0.933 0.811
#> 5 5 1.000 1.000 1.000 0.11471 0.909 0.686
#> 6 6 1.000 0.988 0.990 0.00356 1.000 1.000
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 3
There is also optional best \(k\) = 2 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0 1 0 1
#> GSM247854 2 0 1 0 1
#> GSM247758 2 0 1 0 1
#> GSM247742 1 0 1 1 0
#> GSM247755 2 0 1 0 1
#> GSM247841 1 0 1 1 0
#> GSM247703 2 0 1 0 1
#> GSM247739 2 0 1 0 1
#> GSM247715 1 0 1 1 0
#> GSM247829 2 0 1 0 1
#> GSM247842 1 0 1 1 0
#> GSM247805 2 0 1 0 1
#> GSM247786 2 0 1 0 1
#> GSM247812 2 0 1 0 1
#> GSM247776 1 0 1 1 0
#> GSM247850 1 0 1 1 0
#> GSM247717 2 0 1 0 1
#> GSM247784 2 0 1 0 1
#> GSM247834 1 0 1 1 0
#> GSM247783 2 0 1 0 1
#> GSM247846 1 0 1 1 0
#> GSM247822 2 0 1 0 1
#> GSM247710 2 0 1 0 1
#> GSM247713 1 0 1 1 0
#> GSM247840 2 0 1 0 1
#> GSM247733 1 0 1 1 0
#> GSM247852 1 0 1 1 0
#> GSM247790 2 0 1 0 1
#> GSM247730 2 0 1 0 1
#> GSM247824 2 0 1 0 1
#> GSM247770 1 0 1 1 0
#> GSM247711 2 0 1 0 1
#> GSM247782 2 0 1 0 1
#> GSM247836 1 0 1 1 0
#> GSM247785 2 0 1 0 1
#> GSM247847 1 0 1 1 0
#> GSM247750 2 0 1 0 1
#> GSM247788 2 0 1 0 1
#> GSM247849 1 0 1 1 0
#> GSM247772 2 0 1 0 1
#> GSM247760 1 0 1 1 0
#> GSM247764 2 0 1 0 1
#> GSM247851 2 0 1 0 1
#> GSM247714 2 0 1 0 1
#> GSM247828 1 0 1 1 0
#> GSM247704 2 0 1 0 1
#> GSM247818 1 0 1 1 0
#> GSM247823 2 0 1 0 1
#> GSM247706 2 0 1 0 1
#> GSM247835 2 0 1 0 1
#> GSM247734 1 0 1 1 0
#> GSM247819 2 0 1 0 1
#> GSM247809 2 0 1 0 1
#> GSM247830 2 0 1 0 1
#> GSM247833 1 0 1 1 0
#> GSM247738 2 0 1 0 1
#> GSM247716 2 0 1 0 1
#> GSM247747 2 0 1 0 1
#> GSM247722 1 0 1 1 0
#> GSM247816 2 0 1 0 1
#> GSM247839 2 0 1 0 1
#> GSM247821 1 0 1 1 0
#> GSM247798 2 0 1 0 1
#> GSM247838 1 0 1 1 0
#> GSM247721 2 0 1 0 1
#> GSM247781 2 0 1 0 1
#> GSM247762 1 0 1 1 0
#> GSM247825 2 0 1 0 1
#> GSM247777 1 0 1 1 0
#> GSM247761 2 0 1 0 1
#> GSM247720 2 0 1 0 1
#> GSM247814 2 0 1 0 1
#> GSM247732 1 0 1 1 0
#> GSM247708 2 0 1 0 1
#> GSM247740 2 0 1 0 1
#> GSM247749 1 0 1 1 0
#> GSM247767 2 0 1 0 1
#> GSM247748 1 0 1 1 0
#> GSM247705 2 0 1 0 1
#> GSM247746 2 0 1 0 1
#> GSM247752 1 0 1 1 0
#> GSM247769 2 0 1 0 1
#> GSM247753 1 0 1 1 0
#> GSM247723 2 0 1 0 1
#> GSM247779 2 0 1 0 1
#> GSM247756 1 0 1 1 0
#> GSM247826 2 0 1 0 1
#> GSM247775 1 0 1 1 0
#> GSM247741 2 0 1 0 1
#> GSM247799 2 0 1 0 1
#> GSM247778 1 0 1 1 0
#> GSM247806 2 0 1 0 1
#> GSM247815 1 0 1 1 0
#> GSM247735 2 0 1 0 1
#> GSM247831 2 0 1 0 1
#> GSM247845 1 0 1 1 0
#> GSM247791 2 0 1 0 1
#> GSM247780 1 0 1 1 0
#> GSM247853 1 0 1 1 0
#> GSM247800 2 0 1 0 1
#> GSM247729 2 0 1 0 1
#> GSM247810 1 0 1 1 0
#> GSM247844 2 0 1 0 1
#> GSM247793 1 0 1 1 0
#> GSM247759 2 0 1 0 1
#> GSM247724 2 0 1 0 1
#> GSM247817 2 0 1 0 1
#> GSM247727 1 0 1 1 0
#> GSM247796 2 0 1 0 1
#> GSM247725 2 0 1 0 1
#> GSM247801 1 0 1 1 0
#> GSM247731 2 0 1 0 1
#> GSM247765 1 0 1 1 0
#> GSM247792 2 0 1 0 1
#> GSM247726 2 0 1 0 1
#> GSM247803 1 0 1 1 0
#> GSM247728 2 0 1 0 1
#> GSM247768 1 0 1 1 0
#> GSM247745 2 0 1 0 1
#> GSM247855 2 0 1 0 1
#> GSM247804 2 0 1 0 1
#> GSM247774 1 0 1 1 0
#> GSM247807 2 0 1 0 1
#> GSM247813 1 0 1 1 0
#> GSM247736 2 0 1 0 1
#> GSM247712 2 0 1 0 1
#> GSM247797 1 0 1 1 0
#> GSM247743 2 0 1 0 1
#> GSM247719 1 0 1 1 0
#> GSM247707 2 0 1 0 1
#> GSM247737 2 0 1 0 1
#> GSM247827 2 0 1 0 1
#> GSM247848 1 0 1 1 0
#> GSM247794 2 0 1 0 1
#> GSM247757 2 0 1 0 1
#> GSM247744 1 0 1 1 0
#> GSM247751 2 0 1 0 1
#> GSM247837 1 0 1 1 0
#> GSM247754 2 0 1 0 1
#> GSM247789 2 0 1 0 1
#> GSM247802 1 0 1 1 0
#> GSM247771 2 0 1 0 1
#> GSM247763 1 0 1 1 0
#> GSM247808 2 0 1 0 1
#> GSM247787 2 0 1 0 1
#> GSM247843 1 0 1 1 0
#> GSM247811 2 0 1 0 1
#> GSM247773 1 0 1 1 0
#> GSM247766 2 0 1 0 1
#> GSM247718 2 0 1 0 1
#> GSM247832 1 0 1 1 0
#> GSM247709 2 0 1 0 1
#> GSM247820 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247854 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247758 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247742 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247755 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247841 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247703 2 0.0747 0.938 0.000 0.984 0.016
#> GSM247739 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247715 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247829 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247842 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247805 2 0.0424 0.941 0.000 0.992 0.008
#> GSM247786 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247812 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247776 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247850 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247717 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247784 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247834 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247783 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247846 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247822 2 0.4654 0.776 0.000 0.792 0.208
#> GSM247710 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247713 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247840 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247733 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247852 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247790 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247730 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247824 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247770 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247711 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247782 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247836 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247785 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247847 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247750 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247788 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247849 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247772 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247760 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247764 2 0.6026 0.503 0.000 0.624 0.376
#> GSM247851 2 0.6062 0.486 0.000 0.616 0.384
#> GSM247714 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247828 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247704 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247818 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247823 2 0.1753 0.920 0.000 0.952 0.048
#> GSM247706 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247835 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247734 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247819 2 0.5926 0.545 0.000 0.644 0.356
#> GSM247809 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247830 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247833 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247738 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247716 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247747 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247722 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247816 2 0.3551 0.854 0.000 0.868 0.132
#> GSM247839 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247821 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247798 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247838 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247721 2 0.0747 0.938 0.000 0.984 0.016
#> GSM247781 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247762 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247825 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247777 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247761 2 0.1753 0.920 0.000 0.952 0.048
#> GSM247720 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247814 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247732 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247708 2 0.1529 0.925 0.000 0.960 0.040
#> GSM247740 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247749 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247767 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247748 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247705 2 0.5529 0.652 0.000 0.704 0.296
#> GSM247746 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247752 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247769 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247753 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247723 2 0.3116 0.876 0.000 0.892 0.108
#> GSM247779 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247756 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247826 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247775 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247741 2 0.2711 0.892 0.000 0.912 0.088
#> GSM247799 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247778 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247806 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247815 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247735 2 0.0424 0.941 0.000 0.992 0.008
#> GSM247831 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247845 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247791 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247780 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247853 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247800 2 0.4796 0.761 0.000 0.780 0.220
#> GSM247729 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247810 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247844 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247793 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247759 2 0.0592 0.939 0.000 0.988 0.012
#> GSM247724 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247817 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247727 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247796 2 0.4796 0.761 0.000 0.780 0.220
#> GSM247725 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247801 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247731 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247765 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247792 2 0.4887 0.751 0.000 0.772 0.228
#> GSM247726 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247803 1 0.0747 0.981 0.984 0.016 0.000
#> GSM247728 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247768 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247745 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247855 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247804 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247774 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247807 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247813 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247736 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247712 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247797 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247743 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247719 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247707 2 0.2066 0.912 0.000 0.940 0.060
#> GSM247737 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247827 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247848 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247794 2 0.2448 0.901 0.000 0.924 0.076
#> GSM247757 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247744 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247751 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247837 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247754 2 0.4399 0.798 0.000 0.812 0.188
#> GSM247789 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247802 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247771 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247763 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247808 2 0.0592 0.939 0.000 0.988 0.012
#> GSM247787 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247843 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247811 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247773 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247766 2 0.6180 0.409 0.000 0.584 0.416
#> GSM247718 2 0.0000 0.944 0.000 1.000 0.000
#> GSM247832 1 0.0000 1.000 1.000 0.000 0.000
#> GSM247709 3 0.0000 1.000 0.000 0.000 1.000
#> GSM247820 1 0.0000 1.000 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247854 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247758 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247742 4 0.234 0.990 0.100 0.000 0.000 0.900
#> GSM247755 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247841 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247703 2 0.293 0.905 0.000 0.880 0.012 0.108
#> GSM247739 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247715 4 0.234 0.990 0.100 0.000 0.000 0.900
#> GSM247829 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247842 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247805 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247786 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247812 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247776 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247850 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247717 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247784 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247834 4 0.228 0.990 0.096 0.000 0.000 0.904
#> GSM247783 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247846 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247822 2 0.558 0.788 0.000 0.724 0.168 0.108
#> GSM247710 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247713 4 0.228 0.990 0.096 0.000 0.000 0.904
#> GSM247840 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247733 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247852 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247790 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247730 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247824 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247770 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247711 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247782 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247836 4 0.234 0.990 0.100 0.000 0.000 0.900
#> GSM247785 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247847 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247750 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247788 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247849 4 0.234 0.990 0.100 0.000 0.000 0.900
#> GSM247772 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247760 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247764 2 0.643 0.646 0.000 0.620 0.272 0.108
#> GSM247851 2 0.654 0.612 0.000 0.600 0.292 0.108
#> GSM247714 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247828 4 0.234 0.990 0.100 0.000 0.000 0.900
#> GSM247704 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247818 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247823 2 0.327 0.901 0.000 0.868 0.024 0.108
#> GSM247706 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247835 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247734 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247819 2 0.630 0.677 0.000 0.640 0.252 0.108
#> GSM247809 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247830 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247833 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247738 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247716 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247747 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247722 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247816 2 0.390 0.887 0.000 0.840 0.052 0.108
#> GSM247839 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247821 4 0.228 0.990 0.096 0.000 0.000 0.904
#> GSM247798 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247838 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247721 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247781 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247762 4 0.227 0.974 0.076 0.008 0.000 0.916
#> GSM247825 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247777 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247761 2 0.327 0.901 0.000 0.868 0.024 0.108
#> GSM247720 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247814 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247732 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247708 2 0.293 0.905 0.000 0.880 0.012 0.108
#> GSM247740 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247749 4 0.228 0.990 0.096 0.000 0.000 0.904
#> GSM247767 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247748 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247705 2 0.668 0.570 0.000 0.576 0.312 0.112
#> GSM247746 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247752 4 0.197 0.955 0.060 0.008 0.000 0.932
#> GSM247769 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247753 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247723 2 0.346 0.898 0.000 0.860 0.032 0.108
#> GSM247779 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247756 4 0.234 0.990 0.100 0.000 0.000 0.900
#> GSM247826 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247775 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247741 2 0.337 0.900 0.000 0.864 0.028 0.108
#> GSM247799 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247778 4 0.234 0.990 0.100 0.000 0.000 0.900
#> GSM247806 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247815 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247735 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247831 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247845 4 0.234 0.990 0.100 0.000 0.000 0.900
#> GSM247791 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247780 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247853 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247800 2 0.554 0.792 0.000 0.728 0.164 0.108
#> GSM247729 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247810 4 0.222 0.988 0.092 0.000 0.000 0.908
#> GSM247844 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247793 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247759 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247724 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247817 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247727 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247796 2 0.566 0.779 0.000 0.716 0.176 0.108
#> GSM247725 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247801 4 0.222 0.988 0.092 0.000 0.000 0.908
#> GSM247731 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247765 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247792 2 0.571 0.774 0.000 0.712 0.180 0.108
#> GSM247726 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247803 4 0.209 0.943 0.048 0.020 0.000 0.932
#> GSM247728 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247768 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247745 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247855 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247804 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247774 4 0.222 0.988 0.092 0.000 0.000 0.908
#> GSM247807 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247813 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247736 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247712 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247797 4 0.222 0.988 0.092 0.000 0.000 0.908
#> GSM247743 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247719 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247707 2 0.337 0.900 0.000 0.864 0.028 0.108
#> GSM247737 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247827 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247848 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247794 2 0.398 0.885 0.000 0.836 0.056 0.108
#> GSM247757 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247744 4 0.228 0.990 0.096 0.000 0.000 0.904
#> GSM247751 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247837 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247754 2 0.496 0.839 0.000 0.776 0.116 0.108
#> GSM247789 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247802 4 0.234 0.990 0.100 0.000 0.000 0.900
#> GSM247771 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247763 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247808 2 0.247 0.909 0.000 0.892 0.000 0.108
#> GSM247787 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247843 4 0.234 0.990 0.100 0.000 0.000 0.900
#> GSM247811 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247773 1 0.000 1.000 1.000 0.000 0.000 0.000
#> GSM247766 2 0.665 0.546 0.000 0.568 0.328 0.104
#> GSM247718 2 0.000 0.916 0.000 1.000 0.000 0.000
#> GSM247832 4 0.234 0.990 0.100 0.000 0.000 0.900
#> GSM247709 3 0.000 1.000 0.000 0.000 1.000 0.000
#> GSM247820 1 0.000 1.000 1.000 0.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0 1 0 1 0 0 0
#> GSM247854 2 0 1 0 1 0 0 0
#> GSM247758 5 0 1 0 0 0 0 1
#> GSM247742 4 0 1 0 0 0 1 0
#> GSM247755 3 0 1 0 0 1 0 0
#> GSM247841 1 0 1 1 0 0 0 0
#> GSM247703 2 0 1 0 1 0 0 0
#> GSM247739 5 0 1 0 0 0 0 1
#> GSM247715 4 0 1 0 0 0 1 0
#> GSM247829 3 0 1 0 0 1 0 0
#> GSM247842 1 0 1 1 0 0 0 0
#> GSM247805 2 0 1 0 1 0 0 0
#> GSM247786 5 0 1 0 0 0 0 1
#> GSM247812 3 0 1 0 0 1 0 0
#> GSM247776 1 0 1 1 0 0 0 0
#> GSM247850 1 0 1 1 0 0 0 0
#> GSM247717 2 0 1 0 1 0 0 0
#> GSM247784 5 0 1 0 0 0 0 1
#> GSM247834 4 0 1 0 0 0 1 0
#> GSM247783 3 0 1 0 0 1 0 0
#> GSM247846 1 0 1 1 0 0 0 0
#> GSM247822 2 0 1 0 1 0 0 0
#> GSM247710 5 0 1 0 0 0 0 1
#> GSM247713 4 0 1 0 0 0 1 0
#> GSM247840 3 0 1 0 0 1 0 0
#> GSM247733 1 0 1 1 0 0 0 0
#> GSM247852 1 0 1 1 0 0 0 0
#> GSM247790 2 0 1 0 1 0 0 0
#> GSM247730 5 0 1 0 0 0 0 1
#> GSM247824 3 0 1 0 0 1 0 0
#> GSM247770 1 0 1 1 0 0 0 0
#> GSM247711 2 0 1 0 1 0 0 0
#> GSM247782 5 0 1 0 0 0 0 1
#> GSM247836 4 0 1 0 0 0 1 0
#> GSM247785 3 0 1 0 0 1 0 0
#> GSM247847 1 0 1 1 0 0 0 0
#> GSM247750 2 0 1 0 1 0 0 0
#> GSM247788 5 0 1 0 0 0 0 1
#> GSM247849 4 0 1 0 0 0 1 0
#> GSM247772 3 0 1 0 0 1 0 0
#> GSM247760 1 0 1 1 0 0 0 0
#> GSM247764 2 0 1 0 1 0 0 0
#> GSM247851 2 0 1 0 1 0 0 0
#> GSM247714 5 0 1 0 0 0 0 1
#> GSM247828 4 0 1 0 0 0 1 0
#> GSM247704 3 0 1 0 0 1 0 0
#> GSM247818 1 0 1 1 0 0 0 0
#> GSM247823 2 0 1 0 1 0 0 0
#> GSM247706 5 0 1 0 0 0 0 1
#> GSM247835 3 0 1 0 0 1 0 0
#> GSM247734 1 0 1 1 0 0 0 0
#> GSM247819 2 0 1 0 1 0 0 0
#> GSM247809 5 0 1 0 0 0 0 1
#> GSM247830 3 0 1 0 0 1 0 0
#> GSM247833 1 0 1 1 0 0 0 0
#> GSM247738 2 0 1 0 1 0 0 0
#> GSM247716 5 0 1 0 0 0 0 1
#> GSM247747 3 0 1 0 0 1 0 0
#> GSM247722 1 0 1 1 0 0 0 0
#> GSM247816 2 0 1 0 1 0 0 0
#> GSM247839 5 0 1 0 0 0 0 1
#> GSM247821 4 0 1 0 0 0 1 0
#> GSM247798 3 0 1 0 0 1 0 0
#> GSM247838 1 0 1 1 0 0 0 0
#> GSM247721 2 0 1 0 1 0 0 0
#> GSM247781 5 0 1 0 0 0 0 1
#> GSM247762 4 0 1 0 0 0 1 0
#> GSM247825 3 0 1 0 0 1 0 0
#> GSM247777 1 0 1 1 0 0 0 0
#> GSM247761 2 0 1 0 1 0 0 0
#> GSM247720 5 0 1 0 0 0 0 1
#> GSM247814 3 0 1 0 0 1 0 0
#> GSM247732 1 0 1 1 0 0 0 0
#> GSM247708 2 0 1 0 1 0 0 0
#> GSM247740 5 0 1 0 0 0 0 1
#> GSM247749 4 0 1 0 0 0 1 0
#> GSM247767 3 0 1 0 0 1 0 0
#> GSM247748 1 0 1 1 0 0 0 0
#> GSM247705 2 0 1 0 1 0 0 0
#> GSM247746 5 0 1 0 0 0 0 1
#> GSM247752 4 0 1 0 0 0 1 0
#> GSM247769 3 0 1 0 0 1 0 0
#> GSM247753 1 0 1 1 0 0 0 0
#> GSM247723 2 0 1 0 1 0 0 0
#> GSM247779 5 0 1 0 0 0 0 1
#> GSM247756 4 0 1 0 0 0 1 0
#> GSM247826 3 0 1 0 0 1 0 0
#> GSM247775 1 0 1 1 0 0 0 0
#> GSM247741 2 0 1 0 1 0 0 0
#> GSM247799 5 0 1 0 0 0 0 1
#> GSM247778 4 0 1 0 0 0 1 0
#> GSM247806 3 0 1 0 0 1 0 0
#> GSM247815 1 0 1 1 0 0 0 0
#> GSM247735 2 0 1 0 1 0 0 0
#> GSM247831 5 0 1 0 0 0 0 1
#> GSM247845 4 0 1 0 0 0 1 0
#> GSM247791 3 0 1 0 0 1 0 0
#> GSM247780 1 0 1 1 0 0 0 0
#> GSM247853 1 0 1 1 0 0 0 0
#> GSM247800 2 0 1 0 1 0 0 0
#> GSM247729 5 0 1 0 0 0 0 1
#> GSM247810 4 0 1 0 0 0 1 0
#> GSM247844 3 0 1 0 0 1 0 0
#> GSM247793 1 0 1 1 0 0 0 0
#> GSM247759 2 0 1 0 1 0 0 0
#> GSM247724 5 0 1 0 0 0 0 1
#> GSM247817 3 0 1 0 0 1 0 0
#> GSM247727 1 0 1 1 0 0 0 0
#> GSM247796 2 0 1 0 1 0 0 0
#> GSM247725 5 0 1 0 0 0 0 1
#> GSM247801 4 0 1 0 0 0 1 0
#> GSM247731 3 0 1 0 0 1 0 0
#> GSM247765 1 0 1 1 0 0 0 0
#> GSM247792 2 0 1 0 1 0 0 0
#> GSM247726 5 0 1 0 0 0 0 1
#> GSM247803 4 0 1 0 0 0 1 0
#> GSM247728 3 0 1 0 0 1 0 0
#> GSM247768 1 0 1 1 0 0 0 0
#> GSM247745 2 0 1 0 1 0 0 0
#> GSM247855 2 0 1 0 1 0 0 0
#> GSM247804 5 0 1 0 0 0 0 1
#> GSM247774 4 0 1 0 0 0 1 0
#> GSM247807 3 0 1 0 0 1 0 0
#> GSM247813 1 0 1 1 0 0 0 0
#> GSM247736 2 0 1 0 1 0 0 0
#> GSM247712 5 0 1 0 0 0 0 1
#> GSM247797 4 0 1 0 0 0 1 0
#> GSM247743 3 0 1 0 0 1 0 0
#> GSM247719 1 0 1 1 0 0 0 0
#> GSM247707 2 0 1 0 1 0 0 0
#> GSM247737 5 0 1 0 0 0 0 1
#> GSM247827 3 0 1 0 0 1 0 0
#> GSM247848 1 0 1 1 0 0 0 0
#> GSM247794 2 0 1 0 1 0 0 0
#> GSM247757 5 0 1 0 0 0 0 1
#> GSM247744 4 0 1 0 0 0 1 0
#> GSM247751 3 0 1 0 0 1 0 0
#> GSM247837 1 0 1 1 0 0 0 0
#> GSM247754 2 0 1 0 1 0 0 0
#> GSM247789 5 0 1 0 0 0 0 1
#> GSM247802 4 0 1 0 0 0 1 0
#> GSM247771 3 0 1 0 0 1 0 0
#> GSM247763 1 0 1 1 0 0 0 0
#> GSM247808 2 0 1 0 1 0 0 0
#> GSM247787 5 0 1 0 0 0 0 1
#> GSM247843 4 0 1 0 0 0 1 0
#> GSM247811 3 0 1 0 0 1 0 0
#> GSM247773 1 0 1 1 0 0 0 0
#> GSM247766 2 0 1 0 1 0 0 0
#> GSM247718 5 0 1 0 0 0 0 1
#> GSM247832 4 0 1 0 0 0 1 0
#> GSM247709 3 0 1 0 0 1 0 0
#> GSM247820 1 0 1 1 0 0 0 0
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.0260 0.994 0.000 0.992 0 0.000 0.000 NA
#> GSM247854 2 0.0260 0.994 0.000 0.992 0 0.000 0.000 NA
#> GSM247758 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247742 4 0.0146 0.978 0.000 0.000 0 0.996 0.000 NA
#> GSM247755 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247841 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247703 2 0.0146 0.995 0.000 0.996 0 0.000 0.000 NA
#> GSM247739 5 0.0000 0.989 0.000 0.000 0 0.000 1.000 NA
#> GSM247715 4 0.0146 0.977 0.000 0.000 0 0.996 0.000 NA
#> GSM247829 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247842 1 0.0000 0.998 1.000 0.000 0 0.000 0.000 NA
#> GSM247805 2 0.0146 0.995 0.000 0.996 0 0.000 0.000 NA
#> GSM247786 5 0.0000 0.989 0.000 0.000 0 0.000 1.000 NA
#> GSM247812 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247776 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247850 1 0.0000 0.998 1.000 0.000 0 0.000 0.000 NA
#> GSM247717 2 0.0146 0.995 0.000 0.996 0 0.000 0.000 NA
#> GSM247784 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247834 4 0.0146 0.977 0.000 0.000 0 0.996 0.000 NA
#> GSM247783 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247846 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247822 2 0.0260 0.995 0.000 0.992 0 0.000 0.000 NA
#> GSM247710 5 0.0000 0.989 0.000 0.000 0 0.000 1.000 NA
#> GSM247713 4 0.0146 0.977 0.000 0.000 0 0.996 0.000 NA
#> GSM247840 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247733 1 0.0000 0.998 1.000 0.000 0 0.000 0.000 NA
#> GSM247852 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247790 2 0.0260 0.994 0.000 0.992 0 0.000 0.000 NA
#> GSM247730 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247824 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247770 1 0.0260 0.995 0.992 0.000 0 0.000 0.000 NA
#> GSM247711 2 0.0146 0.995 0.000 0.996 0 0.000 0.000 NA
#> GSM247782 5 0.0000 0.989 0.000 0.000 0 0.000 1.000 NA
#> GSM247836 4 0.0146 0.978 0.000 0.000 0 0.996 0.000 NA
#> GSM247785 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247847 1 0.0000 0.998 1.000 0.000 0 0.000 0.000 NA
#> GSM247750 2 0.0458 0.991 0.000 0.984 0 0.000 0.000 NA
#> GSM247788 5 0.0000 0.989 0.000 0.000 0 0.000 1.000 NA
#> GSM247849 4 0.0146 0.978 0.000 0.000 0 0.996 0.000 NA
#> GSM247772 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247760 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247764 2 0.0363 0.993 0.000 0.988 0 0.000 0.000 NA
#> GSM247851 2 0.0363 0.993 0.000 0.988 0 0.000 0.000 NA
#> GSM247714 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247828 4 0.0146 0.978 0.000 0.000 0 0.996 0.000 NA
#> GSM247704 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247818 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247823 2 0.0260 0.994 0.000 0.992 0 0.000 0.000 NA
#> GSM247706 5 0.0000 0.989 0.000 0.000 0 0.000 1.000 NA
#> GSM247835 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247734 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247819 2 0.0260 0.994 0.000 0.992 0 0.000 0.000 NA
#> GSM247809 5 0.0363 0.985 0.000 0.000 0 0.000 0.988 NA
#> GSM247830 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247833 1 0.0000 0.998 1.000 0.000 0 0.000 0.000 NA
#> GSM247738 2 0.0260 0.995 0.000 0.992 0 0.000 0.000 NA
#> GSM247716 5 0.0363 0.985 0.000 0.000 0 0.000 0.988 NA
#> GSM247747 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247722 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247816 2 0.0000 0.995 0.000 1.000 0 0.000 0.000 NA
#> GSM247839 5 0.0363 0.985 0.000 0.000 0 0.000 0.988 NA
#> GSM247821 4 0.0260 0.976 0.000 0.000 0 0.992 0.000 NA
#> GSM247798 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247838 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247721 2 0.0260 0.994 0.000 0.992 0 0.000 0.000 NA
#> GSM247781 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247762 4 0.1267 0.948 0.000 0.000 0 0.940 0.000 NA
#> GSM247825 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247777 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247761 2 0.0146 0.995 0.000 0.996 0 0.000 0.000 NA
#> GSM247720 5 0.0000 0.989 0.000 0.000 0 0.000 1.000 NA
#> GSM247814 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247732 1 0.0000 0.998 1.000 0.000 0 0.000 0.000 NA
#> GSM247708 2 0.0146 0.995 0.000 0.996 0 0.000 0.000 NA
#> GSM247740 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247749 4 0.0146 0.977 0.000 0.000 0 0.996 0.000 NA
#> GSM247767 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247748 1 0.0000 0.998 1.000 0.000 0 0.000 0.000 NA
#> GSM247705 2 0.0260 0.994 0.000 0.992 0 0.000 0.000 NA
#> GSM247746 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247752 4 0.3101 0.830 0.000 0.000 0 0.756 0.000 NA
#> GSM247769 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247753 1 0.0000 0.998 1.000 0.000 0 0.000 0.000 NA
#> GSM247723 2 0.0260 0.994 0.000 0.992 0 0.000 0.000 NA
#> GSM247779 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247756 4 0.0146 0.978 0.000 0.000 0 0.996 0.000 NA
#> GSM247826 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247775 1 0.0000 0.998 1.000 0.000 0 0.000 0.000 NA
#> GSM247741 2 0.0000 0.995 0.000 1.000 0 0.000 0.000 NA
#> GSM247799 5 0.0000 0.989 0.000 0.000 0 0.000 1.000 NA
#> GSM247778 4 0.0146 0.977 0.000 0.000 0 0.996 0.000 NA
#> GSM247806 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247815 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247735 2 0.0260 0.994 0.000 0.992 0 0.000 0.000 NA
#> GSM247831 5 0.0000 0.989 0.000 0.000 0 0.000 1.000 NA
#> GSM247845 4 0.0146 0.978 0.000 0.000 0 0.996 0.000 NA
#> GSM247791 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247780 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247853 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247800 2 0.0146 0.995 0.000 0.996 0 0.000 0.000 NA
#> GSM247729 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247810 4 0.0146 0.977 0.000 0.000 0 0.996 0.000 NA
#> GSM247844 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247793 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247759 2 0.0146 0.995 0.000 0.996 0 0.000 0.000 NA
#> GSM247724 5 0.0260 0.987 0.000 0.000 0 0.000 0.992 NA
#> GSM247817 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247727 1 0.0000 0.998 1.000 0.000 0 0.000 0.000 NA
#> GSM247796 2 0.0363 0.993 0.000 0.988 0 0.000 0.000 NA
#> GSM247725 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247801 4 0.0000 0.978 0.000 0.000 0 1.000 0.000 NA
#> GSM247731 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247765 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247792 2 0.0260 0.995 0.000 0.992 0 0.000 0.000 NA
#> GSM247726 5 0.3547 0.681 0.000 0.000 0 0.000 0.668 NA
#> GSM247803 4 0.3672 0.737 0.000 0.000 0 0.632 0.000 NA
#> GSM247728 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247768 1 0.0260 0.995 0.992 0.000 0 0.000 0.000 NA
#> GSM247745 2 0.0260 0.994 0.000 0.992 0 0.000 0.000 NA
#> GSM247855 2 0.0363 0.993 0.000 0.988 0 0.000 0.000 NA
#> GSM247804 5 0.0260 0.987 0.000 0.000 0 0.000 0.992 NA
#> GSM247774 4 0.0146 0.978 0.000 0.000 0 0.996 0.000 NA
#> GSM247807 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247813 1 0.0000 0.998 1.000 0.000 0 0.000 0.000 NA
#> GSM247736 2 0.0260 0.994 0.000 0.992 0 0.000 0.000 NA
#> GSM247712 5 0.0260 0.986 0.000 0.000 0 0.000 0.992 NA
#> GSM247797 4 0.0000 0.978 0.000 0.000 0 1.000 0.000 NA
#> GSM247743 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247719 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247707 2 0.0146 0.995 0.000 0.996 0 0.000 0.000 NA
#> GSM247737 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247827 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247848 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247794 2 0.0260 0.994 0.000 0.992 0 0.000 0.000 NA
#> GSM247757 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247744 4 0.0146 0.978 0.000 0.000 0 0.996 0.000 NA
#> GSM247751 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247837 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247754 2 0.0146 0.995 0.000 0.996 0 0.000 0.000 NA
#> GSM247789 5 0.0000 0.989 0.000 0.000 0 0.000 1.000 NA
#> GSM247802 4 0.0000 0.978 0.000 0.000 0 1.000 0.000 NA
#> GSM247771 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247763 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
#> GSM247808 2 0.0000 0.995 0.000 1.000 0 0.000 0.000 NA
#> GSM247787 5 0.0000 0.989 0.000 0.000 0 0.000 1.000 NA
#> GSM247843 4 0.0146 0.978 0.000 0.000 0 0.996 0.000 NA
#> GSM247811 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247773 1 0.0000 0.998 1.000 0.000 0 0.000 0.000 NA
#> GSM247766 2 0.0146 0.995 0.000 0.996 0 0.000 0.000 NA
#> GSM247718 5 0.0146 0.988 0.000 0.000 0 0.000 0.996 NA
#> GSM247832 4 0.0146 0.978 0.000 0.000 0 0.996 0.000 NA
#> GSM247709 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 NA
#> GSM247820 1 0.0146 0.997 0.996 0.000 0 0.000 0.000 NA
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> MAD:NMF 153 1 1.000 4.63e-32 2
#> MAD:NMF 151 1 0.984 1.55e-60 3
#> MAD:NMF 153 1 0.964 1.16e-90 4
#> MAD:NMF 153 1 0.989 6.51e-120 5
#> MAD:NMF 153 1 0.989 6.51e-120 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.3259 0.675 0.675
#> 3 3 1.000 0.997 0.999 0.9719 0.683 0.530
#> 4 4 1.000 0.997 0.999 0.0157 0.989 0.969
#> 5 5 0.821 0.909 0.891 0.1144 0.909 0.739
#> 6 6 0.847 0.959 0.903 0.0599 0.939 0.760
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 1 0 1 1 0
#> GSM247854 1 0 1 1 0
#> GSM247758 1 0 1 1 0
#> GSM247742 1 0 1 1 0
#> GSM247755 2 0 1 0 1
#> GSM247841 1 0 1 1 0
#> GSM247703 1 0 1 1 0
#> GSM247739 1 0 1 1 0
#> GSM247715 1 0 1 1 0
#> GSM247829 2 0 1 0 1
#> GSM247842 1 0 1 1 0
#> GSM247805 1 0 1 1 0
#> GSM247786 1 0 1 1 0
#> GSM247812 2 0 1 0 1
#> GSM247776 1 0 1 1 0
#> GSM247850 1 0 1 1 0
#> GSM247717 1 0 1 1 0
#> GSM247784 1 0 1 1 0
#> GSM247834 1 0 1 1 0
#> GSM247783 2 0 1 0 1
#> GSM247846 1 0 1 1 0
#> GSM247822 1 0 1 1 0
#> GSM247710 1 0 1 1 0
#> GSM247713 1 0 1 1 0
#> GSM247840 2 0 1 0 1
#> GSM247733 1 0 1 1 0
#> GSM247852 1 0 1 1 0
#> GSM247790 1 0 1 1 0
#> GSM247730 1 0 1 1 0
#> GSM247824 2 0 1 0 1
#> GSM247770 1 0 1 1 0
#> GSM247711 1 0 1 1 0
#> GSM247782 1 0 1 1 0
#> GSM247836 1 0 1 1 0
#> GSM247785 2 0 1 0 1
#> GSM247847 1 0 1 1 0
#> GSM247750 1 0 1 1 0
#> GSM247788 1 0 1 1 0
#> GSM247849 1 0 1 1 0
#> GSM247772 2 0 1 0 1
#> GSM247760 1 0 1 1 0
#> GSM247764 1 0 1 1 0
#> GSM247851 1 0 1 1 0
#> GSM247714 1 0 1 1 0
#> GSM247828 1 0 1 1 0
#> GSM247704 2 0 1 0 1
#> GSM247818 1 0 1 1 0
#> GSM247823 1 0 1 1 0
#> GSM247706 1 0 1 1 0
#> GSM247835 2 0 1 0 1
#> GSM247734 1 0 1 1 0
#> GSM247819 1 0 1 1 0
#> GSM247809 1 0 1 1 0
#> GSM247830 2 0 1 0 1
#> GSM247833 1 0 1 1 0
#> GSM247738 1 0 1 1 0
#> GSM247716 1 0 1 1 0
#> GSM247747 2 0 1 0 1
#> GSM247722 1 0 1 1 0
#> GSM247816 1 0 1 1 0
#> GSM247839 1 0 1 1 0
#> GSM247821 1 0 1 1 0
#> GSM247798 2 0 1 0 1
#> GSM247838 1 0 1 1 0
#> GSM247721 1 0 1 1 0
#> GSM247781 1 0 1 1 0
#> GSM247762 1 0 1 1 0
#> GSM247825 2 0 1 0 1
#> GSM247777 1 0 1 1 0
#> GSM247761 1 0 1 1 0
#> GSM247720 1 0 1 1 0
#> GSM247814 2 0 1 0 1
#> GSM247732 1 0 1 1 0
#> GSM247708 1 0 1 1 0
#> GSM247740 1 0 1 1 0
#> GSM247749 1 0 1 1 0
#> GSM247767 2 0 1 0 1
#> GSM247748 1 0 1 1 0
#> GSM247705 1 0 1 1 0
#> GSM247746 1 0 1 1 0
#> GSM247752 1 0 1 1 0
#> GSM247769 2 0 1 0 1
#> GSM247753 1 0 1 1 0
#> GSM247723 1 0 1 1 0
#> GSM247779 1 0 1 1 0
#> GSM247756 1 0 1 1 0
#> GSM247826 2 0 1 0 1
#> GSM247775 1 0 1 1 0
#> GSM247741 1 0 1 1 0
#> GSM247799 1 0 1 1 0
#> GSM247778 1 0 1 1 0
#> GSM247806 2 0 1 0 1
#> GSM247815 1 0 1 1 0
#> GSM247735 1 0 1 1 0
#> GSM247831 1 0 1 1 0
#> GSM247845 1 0 1 1 0
#> GSM247791 2 0 1 0 1
#> GSM247780 1 0 1 1 0
#> GSM247853 1 0 1 1 0
#> GSM247800 1 0 1 1 0
#> GSM247729 1 0 1 1 0
#> GSM247810 1 0 1 1 0
#> GSM247844 2 0 1 0 1
#> GSM247793 1 0 1 1 0
#> GSM247759 1 0 1 1 0
#> GSM247724 1 0 1 1 0
#> GSM247817 2 0 1 0 1
#> GSM247727 1 0 1 1 0
#> GSM247796 1 0 1 1 0
#> GSM247725 1 0 1 1 0
#> GSM247801 1 0 1 1 0
#> GSM247731 2 0 1 0 1
#> GSM247765 1 0 1 1 0
#> GSM247792 1 0 1 1 0
#> GSM247726 1 0 1 1 0
#> GSM247803 1 0 1 1 0
#> GSM247728 2 0 1 0 1
#> GSM247768 1 0 1 1 0
#> GSM247745 1 0 1 1 0
#> GSM247855 1 0 1 1 0
#> GSM247804 1 0 1 1 0
#> GSM247774 1 0 1 1 0
#> GSM247807 2 0 1 0 1
#> GSM247813 1 0 1 1 0
#> GSM247736 1 0 1 1 0
#> GSM247712 1 0 1 1 0
#> GSM247797 1 0 1 1 0
#> GSM247743 2 0 1 0 1
#> GSM247719 1 0 1 1 0
#> GSM247707 1 0 1 1 0
#> GSM247737 1 0 1 1 0
#> GSM247827 2 0 1 0 1
#> GSM247848 1 0 1 1 0
#> GSM247794 1 0 1 1 0
#> GSM247757 1 0 1 1 0
#> GSM247744 1 0 1 1 0
#> GSM247751 2 0 1 0 1
#> GSM247837 1 0 1 1 0
#> GSM247754 1 0 1 1 0
#> GSM247789 1 0 1 1 0
#> GSM247802 1 0 1 1 0
#> GSM247771 2 0 1 0 1
#> GSM247763 1 0 1 1 0
#> GSM247808 1 0 1 1 0
#> GSM247787 1 0 1 1 0
#> GSM247843 1 0 1 1 0
#> GSM247811 2 0 1 0 1
#> GSM247773 1 0 1 1 0
#> GSM247766 1 0 1 1 0
#> GSM247718 1 0 1 1 0
#> GSM247832 1 0 1 1 0
#> GSM247709 2 0 1 0 1
#> GSM247820 1 0 1 1 0
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.000 0.997 0.000 1.000 0
#> GSM247854 2 0.000 0.997 0.000 1.000 0
#> GSM247758 2 0.000 0.997 0.000 1.000 0
#> GSM247742 1 0.000 1.000 1.000 0.000 0
#> GSM247755 3 0.000 1.000 0.000 0.000 1
#> GSM247841 1 0.000 1.000 1.000 0.000 0
#> GSM247703 2 0.000 0.997 0.000 1.000 0
#> GSM247739 2 0.000 0.997 0.000 1.000 0
#> GSM247715 1 0.000 1.000 1.000 0.000 0
#> GSM247829 3 0.000 1.000 0.000 0.000 1
#> GSM247842 1 0.000 1.000 1.000 0.000 0
#> GSM247805 2 0.000 0.997 0.000 1.000 0
#> GSM247786 2 0.000 0.997 0.000 1.000 0
#> GSM247812 3 0.000 1.000 0.000 0.000 1
#> GSM247776 1 0.000 1.000 1.000 0.000 0
#> GSM247850 1 0.000 1.000 1.000 0.000 0
#> GSM247717 2 0.000 0.997 0.000 1.000 0
#> GSM247784 2 0.000 0.997 0.000 1.000 0
#> GSM247834 1 0.000 1.000 1.000 0.000 0
#> GSM247783 3 0.000 1.000 0.000 0.000 1
#> GSM247846 1 0.000 1.000 1.000 0.000 0
#> GSM247822 2 0.000 0.997 0.000 1.000 0
#> GSM247710 2 0.000 0.997 0.000 1.000 0
#> GSM247713 1 0.000 1.000 1.000 0.000 0
#> GSM247840 3 0.000 1.000 0.000 0.000 1
#> GSM247733 1 0.000 1.000 1.000 0.000 0
#> GSM247852 1 0.000 1.000 1.000 0.000 0
#> GSM247790 2 0.000 0.997 0.000 1.000 0
#> GSM247730 2 0.000 0.997 0.000 1.000 0
#> GSM247824 3 0.000 1.000 0.000 0.000 1
#> GSM247770 1 0.000 1.000 1.000 0.000 0
#> GSM247711 2 0.000 0.997 0.000 1.000 0
#> GSM247782 2 0.000 0.997 0.000 1.000 0
#> GSM247836 1 0.000 1.000 1.000 0.000 0
#> GSM247785 3 0.000 1.000 0.000 0.000 1
#> GSM247847 1 0.000 1.000 1.000 0.000 0
#> GSM247750 2 0.000 0.997 0.000 1.000 0
#> GSM247788 2 0.000 0.997 0.000 1.000 0
#> GSM247849 1 0.000 1.000 1.000 0.000 0
#> GSM247772 3 0.000 1.000 0.000 0.000 1
#> GSM247760 1 0.000 1.000 1.000 0.000 0
#> GSM247764 2 0.000 0.997 0.000 1.000 0
#> GSM247851 2 0.000 0.997 0.000 1.000 0
#> GSM247714 2 0.000 0.997 0.000 1.000 0
#> GSM247828 1 0.000 1.000 1.000 0.000 0
#> GSM247704 3 0.000 1.000 0.000 0.000 1
#> GSM247818 1 0.000 1.000 1.000 0.000 0
#> GSM247823 2 0.000 0.997 0.000 1.000 0
#> GSM247706 2 0.000 0.997 0.000 1.000 0
#> GSM247835 3 0.000 1.000 0.000 0.000 1
#> GSM247734 1 0.000 1.000 1.000 0.000 0
#> GSM247819 2 0.000 0.997 0.000 1.000 0
#> GSM247809 2 0.000 0.997 0.000 1.000 0
#> GSM247830 3 0.000 1.000 0.000 0.000 1
#> GSM247833 1 0.000 1.000 1.000 0.000 0
#> GSM247738 2 0.000 0.997 0.000 1.000 0
#> GSM247716 2 0.000 0.997 0.000 1.000 0
#> GSM247747 3 0.000 1.000 0.000 0.000 1
#> GSM247722 1 0.000 1.000 1.000 0.000 0
#> GSM247816 2 0.000 0.997 0.000 1.000 0
#> GSM247839 2 0.000 0.997 0.000 1.000 0
#> GSM247821 1 0.000 1.000 1.000 0.000 0
#> GSM247798 3 0.000 1.000 0.000 0.000 1
#> GSM247838 1 0.000 1.000 1.000 0.000 0
#> GSM247721 2 0.000 0.997 0.000 1.000 0
#> GSM247781 2 0.000 0.997 0.000 1.000 0
#> GSM247762 1 0.000 1.000 1.000 0.000 0
#> GSM247825 3 0.000 1.000 0.000 0.000 1
#> GSM247777 1 0.000 1.000 1.000 0.000 0
#> GSM247761 2 0.000 0.997 0.000 1.000 0
#> GSM247720 2 0.000 0.997 0.000 1.000 0
#> GSM247814 3 0.000 1.000 0.000 0.000 1
#> GSM247732 1 0.000 1.000 1.000 0.000 0
#> GSM247708 2 0.000 0.997 0.000 1.000 0
#> GSM247740 2 0.000 0.997 0.000 1.000 0
#> GSM247749 1 0.000 1.000 1.000 0.000 0
#> GSM247767 3 0.000 1.000 0.000 0.000 1
#> GSM247748 1 0.000 1.000 1.000 0.000 0
#> GSM247705 2 0.000 0.997 0.000 1.000 0
#> GSM247746 2 0.000 0.997 0.000 1.000 0
#> GSM247752 2 0.445 0.759 0.192 0.808 0
#> GSM247769 3 0.000 1.000 0.000 0.000 1
#> GSM247753 1 0.000 1.000 1.000 0.000 0
#> GSM247723 2 0.000 0.997 0.000 1.000 0
#> GSM247779 2 0.000 0.997 0.000 1.000 0
#> GSM247756 1 0.000 1.000 1.000 0.000 0
#> GSM247826 3 0.000 1.000 0.000 0.000 1
#> GSM247775 1 0.000 1.000 1.000 0.000 0
#> GSM247741 2 0.000 0.997 0.000 1.000 0
#> GSM247799 2 0.000 0.997 0.000 1.000 0
#> GSM247778 1 0.000 1.000 1.000 0.000 0
#> GSM247806 3 0.000 1.000 0.000 0.000 1
#> GSM247815 1 0.000 1.000 1.000 0.000 0
#> GSM247735 2 0.000 0.997 0.000 1.000 0
#> GSM247831 2 0.000 0.997 0.000 1.000 0
#> GSM247845 1 0.000 1.000 1.000 0.000 0
#> GSM247791 3 0.000 1.000 0.000 0.000 1
#> GSM247780 1 0.000 1.000 1.000 0.000 0
#> GSM247853 1 0.000 1.000 1.000 0.000 0
#> GSM247800 2 0.000 0.997 0.000 1.000 0
#> GSM247729 2 0.000 0.997 0.000 1.000 0
#> GSM247810 1 0.000 1.000 1.000 0.000 0
#> GSM247844 3 0.000 1.000 0.000 0.000 1
#> GSM247793 1 0.000 1.000 1.000 0.000 0
#> GSM247759 2 0.000 0.997 0.000 1.000 0
#> GSM247724 2 0.000 0.997 0.000 1.000 0
#> GSM247817 3 0.000 1.000 0.000 0.000 1
#> GSM247727 1 0.000 1.000 1.000 0.000 0
#> GSM247796 2 0.000 0.997 0.000 1.000 0
#> GSM247725 2 0.000 0.997 0.000 1.000 0
#> GSM247801 1 0.000 1.000 1.000 0.000 0
#> GSM247731 3 0.000 1.000 0.000 0.000 1
#> GSM247765 1 0.000 1.000 1.000 0.000 0
#> GSM247792 2 0.000 0.997 0.000 1.000 0
#> GSM247726 2 0.000 0.997 0.000 1.000 0
#> GSM247803 2 0.000 0.997 0.000 1.000 0
#> GSM247728 3 0.000 1.000 0.000 0.000 1
#> GSM247768 1 0.000 1.000 1.000 0.000 0
#> GSM247745 2 0.000 0.997 0.000 1.000 0
#> GSM247855 2 0.000 0.997 0.000 1.000 0
#> GSM247804 2 0.000 0.997 0.000 1.000 0
#> GSM247774 1 0.000 1.000 1.000 0.000 0
#> GSM247807 3 0.000 1.000 0.000 0.000 1
#> GSM247813 1 0.000 1.000 1.000 0.000 0
#> GSM247736 2 0.000 0.997 0.000 1.000 0
#> GSM247712 2 0.000 0.997 0.000 1.000 0
#> GSM247797 1 0.000 1.000 1.000 0.000 0
#> GSM247743 3 0.000 1.000 0.000 0.000 1
#> GSM247719 1 0.000 1.000 1.000 0.000 0
#> GSM247707 2 0.000 0.997 0.000 1.000 0
#> GSM247737 2 0.000 0.997 0.000 1.000 0
#> GSM247827 3 0.000 1.000 0.000 0.000 1
#> GSM247848 1 0.000 1.000 1.000 0.000 0
#> GSM247794 2 0.000 0.997 0.000 1.000 0
#> GSM247757 2 0.000 0.997 0.000 1.000 0
#> GSM247744 1 0.000 1.000 1.000 0.000 0
#> GSM247751 3 0.000 1.000 0.000 0.000 1
#> GSM247837 1 0.000 1.000 1.000 0.000 0
#> GSM247754 2 0.000 0.997 0.000 1.000 0
#> GSM247789 2 0.000 0.997 0.000 1.000 0
#> GSM247802 1 0.000 1.000 1.000 0.000 0
#> GSM247771 3 0.000 1.000 0.000 0.000 1
#> GSM247763 1 0.000 1.000 1.000 0.000 0
#> GSM247808 2 0.000 0.997 0.000 1.000 0
#> GSM247787 2 0.000 0.997 0.000 1.000 0
#> GSM247843 1 0.000 1.000 1.000 0.000 0
#> GSM247811 3 0.000 1.000 0.000 0.000 1
#> GSM247773 1 0.000 1.000 1.000 0.000 0
#> GSM247766 2 0.000 0.997 0.000 1.000 0
#> GSM247718 2 0.000 0.997 0.000 1.000 0
#> GSM247832 1 0.000 1.000 1.000 0.000 0
#> GSM247709 3 0.000 1.000 0.000 0.000 1
#> GSM247820 1 0.000 1.000 1.000 0.000 0
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.000 1.000 0.000 1 0 0.000
#> GSM247854 2 0.000 1.000 0.000 1 0 0.000
#> GSM247758 2 0.000 1.000 0.000 1 0 0.000
#> GSM247742 1 0.000 1.000 1.000 0 0 0.000
#> GSM247755 3 0.000 1.000 0.000 0 1 0.000
#> GSM247841 1 0.000 1.000 1.000 0 0 0.000
#> GSM247703 2 0.000 1.000 0.000 1 0 0.000
#> GSM247739 2 0.000 1.000 0.000 1 0 0.000
#> GSM247715 1 0.000 1.000 1.000 0 0 0.000
#> GSM247829 3 0.000 1.000 0.000 0 1 0.000
#> GSM247842 1 0.000 1.000 1.000 0 0 0.000
#> GSM247805 2 0.000 1.000 0.000 1 0 0.000
#> GSM247786 2 0.000 1.000 0.000 1 0 0.000
#> GSM247812 3 0.000 1.000 0.000 0 1 0.000
#> GSM247776 1 0.000 1.000 1.000 0 0 0.000
#> GSM247850 1 0.000 1.000 1.000 0 0 0.000
#> GSM247717 2 0.000 1.000 0.000 1 0 0.000
#> GSM247784 2 0.000 1.000 0.000 1 0 0.000
#> GSM247834 1 0.000 1.000 1.000 0 0 0.000
#> GSM247783 3 0.000 1.000 0.000 0 1 0.000
#> GSM247846 1 0.000 1.000 1.000 0 0 0.000
#> GSM247822 2 0.000 1.000 0.000 1 0 0.000
#> GSM247710 2 0.000 1.000 0.000 1 0 0.000
#> GSM247713 1 0.000 1.000 1.000 0 0 0.000
#> GSM247840 3 0.000 1.000 0.000 0 1 0.000
#> GSM247733 1 0.000 1.000 1.000 0 0 0.000
#> GSM247852 1 0.000 1.000 1.000 0 0 0.000
#> GSM247790 2 0.000 1.000 0.000 1 0 0.000
#> GSM247730 2 0.000 1.000 0.000 1 0 0.000
#> GSM247824 3 0.000 1.000 0.000 0 1 0.000
#> GSM247770 1 0.000 1.000 1.000 0 0 0.000
#> GSM247711 2 0.000 1.000 0.000 1 0 0.000
#> GSM247782 2 0.000 1.000 0.000 1 0 0.000
#> GSM247836 1 0.000 1.000 1.000 0 0 0.000
#> GSM247785 3 0.000 1.000 0.000 0 1 0.000
#> GSM247847 1 0.000 1.000 1.000 0 0 0.000
#> GSM247750 2 0.000 1.000 0.000 1 0 0.000
#> GSM247788 2 0.000 1.000 0.000 1 0 0.000
#> GSM247849 1 0.000 1.000 1.000 0 0 0.000
#> GSM247772 3 0.000 1.000 0.000 0 1 0.000
#> GSM247760 1 0.000 1.000 1.000 0 0 0.000
#> GSM247764 2 0.000 1.000 0.000 1 0 0.000
#> GSM247851 2 0.000 1.000 0.000 1 0 0.000
#> GSM247714 2 0.000 1.000 0.000 1 0 0.000
#> GSM247828 1 0.000 1.000 1.000 0 0 0.000
#> GSM247704 3 0.000 1.000 0.000 0 1 0.000
#> GSM247818 1 0.000 1.000 1.000 0 0 0.000
#> GSM247823 2 0.000 1.000 0.000 1 0 0.000
#> GSM247706 2 0.000 1.000 0.000 1 0 0.000
#> GSM247835 3 0.000 1.000 0.000 0 1 0.000
#> GSM247734 1 0.000 1.000 1.000 0 0 0.000
#> GSM247819 2 0.000 1.000 0.000 1 0 0.000
#> GSM247809 2 0.000 1.000 0.000 1 0 0.000
#> GSM247830 3 0.000 1.000 0.000 0 1 0.000
#> GSM247833 1 0.000 1.000 1.000 0 0 0.000
#> GSM247738 2 0.000 1.000 0.000 1 0 0.000
#> GSM247716 2 0.000 1.000 0.000 1 0 0.000
#> GSM247747 3 0.000 1.000 0.000 0 1 0.000
#> GSM247722 1 0.000 1.000 1.000 0 0 0.000
#> GSM247816 2 0.000 1.000 0.000 1 0 0.000
#> GSM247839 2 0.000 1.000 0.000 1 0 0.000
#> GSM247821 1 0.000 1.000 1.000 0 0 0.000
#> GSM247798 3 0.000 1.000 0.000 0 1 0.000
#> GSM247838 1 0.000 1.000 1.000 0 0 0.000
#> GSM247721 2 0.000 1.000 0.000 1 0 0.000
#> GSM247781 2 0.000 1.000 0.000 1 0 0.000
#> GSM247762 1 0.000 1.000 1.000 0 0 0.000
#> GSM247825 3 0.000 1.000 0.000 0 1 0.000
#> GSM247777 1 0.000 1.000 1.000 0 0 0.000
#> GSM247761 2 0.000 1.000 0.000 1 0 0.000
#> GSM247720 2 0.000 1.000 0.000 1 0 0.000
#> GSM247814 3 0.000 1.000 0.000 0 1 0.000
#> GSM247732 1 0.000 1.000 1.000 0 0 0.000
#> GSM247708 2 0.000 1.000 0.000 1 0 0.000
#> GSM247740 2 0.000 1.000 0.000 1 0 0.000
#> GSM247749 1 0.000 1.000 1.000 0 0 0.000
#> GSM247767 3 0.000 1.000 0.000 0 1 0.000
#> GSM247748 1 0.000 1.000 1.000 0 0 0.000
#> GSM247705 2 0.000 1.000 0.000 1 0 0.000
#> GSM247746 2 0.000 1.000 0.000 1 0 0.000
#> GSM247752 4 0.353 0.754 0.192 0 0 0.808
#> GSM247769 3 0.000 1.000 0.000 0 1 0.000
#> GSM247753 1 0.000 1.000 1.000 0 0 0.000
#> GSM247723 2 0.000 1.000 0.000 1 0 0.000
#> GSM247779 2 0.000 1.000 0.000 1 0 0.000
#> GSM247756 1 0.000 1.000 1.000 0 0 0.000
#> GSM247826 3 0.000 1.000 0.000 0 1 0.000
#> GSM247775 1 0.000 1.000 1.000 0 0 0.000
#> GSM247741 2 0.000 1.000 0.000 1 0 0.000
#> GSM247799 2 0.000 1.000 0.000 1 0 0.000
#> GSM247778 1 0.000 1.000 1.000 0 0 0.000
#> GSM247806 3 0.000 1.000 0.000 0 1 0.000
#> GSM247815 1 0.000 1.000 1.000 0 0 0.000
#> GSM247735 2 0.000 1.000 0.000 1 0 0.000
#> GSM247831 2 0.000 1.000 0.000 1 0 0.000
#> GSM247845 1 0.000 1.000 1.000 0 0 0.000
#> GSM247791 3 0.000 1.000 0.000 0 1 0.000
#> GSM247780 1 0.000 1.000 1.000 0 0 0.000
#> GSM247853 1 0.000 1.000 1.000 0 0 0.000
#> GSM247800 2 0.000 1.000 0.000 1 0 0.000
#> GSM247729 2 0.000 1.000 0.000 1 0 0.000
#> GSM247810 1 0.000 1.000 1.000 0 0 0.000
#> GSM247844 3 0.000 1.000 0.000 0 1 0.000
#> GSM247793 1 0.000 1.000 1.000 0 0 0.000
#> GSM247759 2 0.000 1.000 0.000 1 0 0.000
#> GSM247724 2 0.000 1.000 0.000 1 0 0.000
#> GSM247817 3 0.000 1.000 0.000 0 1 0.000
#> GSM247727 1 0.000 1.000 1.000 0 0 0.000
#> GSM247796 2 0.000 1.000 0.000 1 0 0.000
#> GSM247725 2 0.000 1.000 0.000 1 0 0.000
#> GSM247801 1 0.000 1.000 1.000 0 0 0.000
#> GSM247731 3 0.000 1.000 0.000 0 1 0.000
#> GSM247765 1 0.000 1.000 1.000 0 0 0.000
#> GSM247792 2 0.000 1.000 0.000 1 0 0.000
#> GSM247726 2 0.000 1.000 0.000 1 0 0.000
#> GSM247803 4 0.000 0.746 0.000 0 0 1.000
#> GSM247728 3 0.000 1.000 0.000 0 1 0.000
#> GSM247768 1 0.000 1.000 1.000 0 0 0.000
#> GSM247745 2 0.000 1.000 0.000 1 0 0.000
#> GSM247855 2 0.000 1.000 0.000 1 0 0.000
#> GSM247804 2 0.000 1.000 0.000 1 0 0.000
#> GSM247774 1 0.000 1.000 1.000 0 0 0.000
#> GSM247807 3 0.000 1.000 0.000 0 1 0.000
#> GSM247813 1 0.000 1.000 1.000 0 0 0.000
#> GSM247736 2 0.000 1.000 0.000 1 0 0.000
#> GSM247712 2 0.000 1.000 0.000 1 0 0.000
#> GSM247797 1 0.000 1.000 1.000 0 0 0.000
#> GSM247743 3 0.000 1.000 0.000 0 1 0.000
#> GSM247719 1 0.000 1.000 1.000 0 0 0.000
#> GSM247707 2 0.000 1.000 0.000 1 0 0.000
#> GSM247737 2 0.000 1.000 0.000 1 0 0.000
#> GSM247827 3 0.000 1.000 0.000 0 1 0.000
#> GSM247848 1 0.000 1.000 1.000 0 0 0.000
#> GSM247794 2 0.000 1.000 0.000 1 0 0.000
#> GSM247757 2 0.000 1.000 0.000 1 0 0.000
#> GSM247744 1 0.000 1.000 1.000 0 0 0.000
#> GSM247751 3 0.000 1.000 0.000 0 1 0.000
#> GSM247837 1 0.000 1.000 1.000 0 0 0.000
#> GSM247754 2 0.000 1.000 0.000 1 0 0.000
#> GSM247789 2 0.000 1.000 0.000 1 0 0.000
#> GSM247802 1 0.000 1.000 1.000 0 0 0.000
#> GSM247771 3 0.000 1.000 0.000 0 1 0.000
#> GSM247763 1 0.000 1.000 1.000 0 0 0.000
#> GSM247808 2 0.000 1.000 0.000 1 0 0.000
#> GSM247787 2 0.000 1.000 0.000 1 0 0.000
#> GSM247843 1 0.000 1.000 1.000 0 0 0.000
#> GSM247811 3 0.000 1.000 0.000 0 1 0.000
#> GSM247773 1 0.000 1.000 1.000 0 0 0.000
#> GSM247766 2 0.000 1.000 0.000 1 0 0.000
#> GSM247718 2 0.000 1.000 0.000 1 0 0.000
#> GSM247832 1 0.000 1.000 1.000 0 0 0.000
#> GSM247709 3 0.000 1.000 0.000 0 1 0.000
#> GSM247820 1 0.000 1.000 1.000 0 0 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.2179 0.805 0.000 0.888 0 0.000 0.112
#> GSM247854 2 0.2179 0.805 0.000 0.888 0 0.000 0.112
#> GSM247758 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247742 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247755 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247841 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247703 2 0.1908 0.822 0.000 0.908 0 0.000 0.092
#> GSM247739 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247715 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247829 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247842 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247805 2 0.2179 0.805 0.000 0.888 0 0.000 0.112
#> GSM247786 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247812 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247776 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247850 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247717 2 0.1908 0.822 0.000 0.908 0 0.000 0.092
#> GSM247784 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247834 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247783 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247846 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247822 2 0.2813 0.739 0.000 0.832 0 0.168 0.000
#> GSM247710 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247713 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247840 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247733 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247852 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247790 2 0.2179 0.805 0.000 0.888 0 0.000 0.112
#> GSM247730 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247824 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247770 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247711 2 0.0000 0.834 0.000 1.000 0 0.000 0.000
#> GSM247782 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247836 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247785 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247847 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247750 2 0.2179 0.805 0.000 0.888 0 0.000 0.112
#> GSM247788 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247849 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247772 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247760 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247764 2 0.2813 0.739 0.000 0.832 0 0.168 0.000
#> GSM247851 2 0.2813 0.739 0.000 0.832 0 0.168 0.000
#> GSM247714 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247828 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247704 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247818 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247823 2 0.2179 0.805 0.000 0.888 0 0.000 0.112
#> GSM247706 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247835 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247734 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247819 2 0.2813 0.739 0.000 0.832 0 0.168 0.000
#> GSM247809 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247830 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247833 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247738 2 0.2179 0.805 0.000 0.888 0 0.000 0.112
#> GSM247716 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247747 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247722 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247816 2 0.1908 0.822 0.000 0.908 0 0.000 0.092
#> GSM247839 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247821 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247798 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247838 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247721 2 0.1792 0.826 0.000 0.916 0 0.000 0.084
#> GSM247781 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247762 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247825 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247777 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247761 2 0.2179 0.805 0.000 0.888 0 0.000 0.112
#> GSM247720 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247814 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247732 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247708 2 0.0000 0.834 0.000 1.000 0 0.000 0.000
#> GSM247740 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247749 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247767 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247748 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247705 2 0.2020 0.816 0.000 0.900 0 0.000 0.100
#> GSM247746 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247752 4 0.5928 0.734 0.192 0.000 0 0.596 0.212
#> GSM247769 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247753 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247723 2 0.0880 0.836 0.000 0.968 0 0.000 0.032
#> GSM247779 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247756 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247826 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247775 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247741 2 0.0794 0.836 0.000 0.972 0 0.000 0.028
#> GSM247799 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247778 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247806 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247815 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247735 2 0.2813 0.739 0.000 0.832 0 0.168 0.000
#> GSM247831 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247845 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247791 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247780 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247853 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247800 2 0.2813 0.739 0.000 0.832 0 0.168 0.000
#> GSM247729 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247810 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247844 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247793 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247759 2 0.1908 0.822 0.000 0.908 0 0.000 0.092
#> GSM247724 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247817 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247727 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247796 2 0.2813 0.739 0.000 0.832 0 0.168 0.000
#> GSM247725 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247801 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247731 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247765 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247792 2 0.2813 0.739 0.000 0.832 0 0.168 0.000
#> GSM247726 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247803 4 0.4101 0.746 0.000 0.000 0 0.628 0.372
#> GSM247728 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247768 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247745 2 0.0000 0.834 0.000 1.000 0 0.000 0.000
#> GSM247855 2 0.0000 0.834 0.000 1.000 0 0.000 0.000
#> GSM247804 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247774 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247807 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247813 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247736 2 0.1851 0.824 0.000 0.912 0 0.000 0.088
#> GSM247712 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247797 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247743 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247719 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247707 2 0.0162 0.835 0.000 0.996 0 0.000 0.004
#> GSM247737 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247827 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247848 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247794 2 0.2179 0.805 0.000 0.888 0 0.000 0.112
#> GSM247757 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247744 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247751 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247837 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247754 2 0.0880 0.836 0.000 0.968 0 0.000 0.032
#> GSM247789 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247802 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247771 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247763 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247808 2 0.0000 0.834 0.000 1.000 0 0.000 0.000
#> GSM247787 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247843 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247811 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247773 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
#> GSM247766 2 0.2813 0.739 0.000 0.832 0 0.168 0.000
#> GSM247718 5 0.4101 1.000 0.000 0.372 0 0.000 0.628
#> GSM247832 1 0.0000 0.839 1.000 0.000 0 0.000 0.000
#> GSM247709 3 0.0000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247820 1 0.3143 0.906 0.796 0.000 0 0.204 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.331 0.855 0.000 0.720 0 0.000 0.280 0.000
#> GSM247854 2 0.331 0.855 0.000 0.720 0 0.000 0.280 0.000
#> GSM247758 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247742 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247755 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247841 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247703 2 0.320 0.865 0.000 0.740 0 0.000 0.260 0.000
#> GSM247739 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247715 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247829 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247842 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247805 2 0.331 0.855 0.000 0.720 0 0.000 0.280 0.000
#> GSM247786 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247812 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247776 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247850 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247717 2 0.320 0.865 0.000 0.740 0 0.000 0.260 0.000
#> GSM247784 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247834 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247783 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247846 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247822 2 0.000 0.726 0.000 1.000 0 0.000 0.000 0.000
#> GSM247710 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247713 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247840 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247733 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247852 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247790 2 0.331 0.855 0.000 0.720 0 0.000 0.280 0.000
#> GSM247730 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247824 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247770 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247711 2 0.253 0.858 0.000 0.832 0 0.000 0.168 0.000
#> GSM247782 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247836 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247785 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247847 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247750 2 0.331 0.855 0.000 0.720 0 0.000 0.280 0.000
#> GSM247788 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247849 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247772 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247760 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247764 2 0.000 0.726 0.000 1.000 0 0.000 0.000 0.000
#> GSM247851 2 0.000 0.726 0.000 1.000 0 0.000 0.000 0.000
#> GSM247714 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247828 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247704 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247818 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247823 2 0.331 0.855 0.000 0.720 0 0.000 0.280 0.000
#> GSM247706 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247835 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247734 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247819 2 0.000 0.726 0.000 1.000 0 0.000 0.000 0.000
#> GSM247809 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247830 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247833 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247738 2 0.331 0.855 0.000 0.720 0 0.000 0.280 0.000
#> GSM247716 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247747 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247722 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247816 2 0.320 0.865 0.000 0.740 0 0.000 0.260 0.000
#> GSM247839 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247821 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247798 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247838 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247721 2 0.315 0.866 0.000 0.748 0 0.000 0.252 0.000
#> GSM247781 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247762 4 0.427 0.960 0.380 0.000 0 0.596 0.000 0.024
#> GSM247825 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247777 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247761 2 0.331 0.855 0.000 0.720 0 0.000 0.280 0.000
#> GSM247720 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247814 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247732 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247708 2 0.253 0.858 0.000 0.832 0 0.000 0.168 0.000
#> GSM247740 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247749 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247767 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247748 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247705 2 0.324 0.861 0.000 0.732 0 0.000 0.268 0.000
#> GSM247746 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247752 6 0.000 0.891 0.000 0.000 0 0.000 0.000 1.000
#> GSM247769 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247753 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247723 2 0.279 0.866 0.000 0.800 0 0.000 0.200 0.000
#> GSM247779 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247756 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247826 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247775 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247741 2 0.276 0.865 0.000 0.804 0 0.000 0.196 0.000
#> GSM247799 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247778 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247806 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247815 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247735 2 0.000 0.726 0.000 1.000 0 0.000 0.000 0.000
#> GSM247831 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247845 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247791 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247780 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247853 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247800 2 0.000 0.726 0.000 1.000 0 0.000 0.000 0.000
#> GSM247729 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247810 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247844 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247793 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247759 2 0.320 0.865 0.000 0.740 0 0.000 0.260 0.000
#> GSM247724 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247817 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247727 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247796 2 0.000 0.726 0.000 1.000 0 0.000 0.000 0.000
#> GSM247725 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247801 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247731 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247765 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247792 2 0.000 0.726 0.000 1.000 0 0.000 0.000 0.000
#> GSM247726 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247803 6 0.377 0.892 0.000 0.000 0 0.404 0.000 0.596
#> GSM247728 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247768 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247745 2 0.253 0.858 0.000 0.832 0 0.000 0.168 0.000
#> GSM247855 2 0.253 0.858 0.000 0.832 0 0.000 0.168 0.000
#> GSM247804 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247774 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247807 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247813 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247736 2 0.317 0.865 0.000 0.744 0 0.000 0.256 0.000
#> GSM247712 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247797 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247743 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247719 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247707 2 0.256 0.860 0.000 0.828 0 0.000 0.172 0.000
#> GSM247737 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247827 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247848 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247794 2 0.331 0.855 0.000 0.720 0 0.000 0.280 0.000
#> GSM247757 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247744 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247751 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247837 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247754 2 0.279 0.866 0.000 0.800 0 0.000 0.200 0.000
#> GSM247789 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247802 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247771 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247763 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247808 2 0.253 0.858 0.000 0.832 0 0.000 0.168 0.000
#> GSM247787 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247843 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247811 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247773 1 0.000 1.000 1.000 0.000 0 0.000 0.000 0.000
#> GSM247766 2 0.000 0.726 0.000 1.000 0 0.000 0.000 0.000
#> GSM247718 5 0.000 1.000 0.000 0.000 0 0.000 1.000 0.000
#> GSM247832 4 0.377 0.998 0.404 0.000 0 0.596 0.000 0.000
#> GSM247709 3 0.000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247820 1 0.000 1.000 1.000 0.000 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
get_signatures(res, k = 5)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> ATC:hclust 153 1 1.000 4.63e-32 2
#> ATC:hclust 153 1 0.937 2.02e-59 3
#> ATC:hclust 153 1 0.441 4.82e-60 4
#> ATC:hclust 153 1 0.605 2.71e-89 5
#> ATC:hclust 153 1 0.740 8.52e-117 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.506 0.725 0.796 0.3888 0.675 0.675
#> 3 3 0.758 0.966 0.912 0.5688 0.682 0.529
#> 4 4 0.831 0.830 0.812 0.1472 1.000 1.000
#> 5 5 0.783 0.942 0.791 0.0693 0.842 0.558
#> 6 6 0.757 0.907 0.829 0.0511 1.000 1.000
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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 1 0.991 0.630 0.556 0.444
#> GSM247854 1 0.991 0.630 0.556 0.444
#> GSM247758 1 0.990 0.634 0.560 0.440
#> GSM247742 1 0.000 0.683 1.000 0.000
#> GSM247755 2 0.000 1.000 0.000 1.000
#> GSM247841 1 0.000 0.683 1.000 0.000
#> GSM247703 1 0.990 0.634 0.560 0.440
#> GSM247739 1 0.990 0.634 0.560 0.440
#> GSM247715 1 0.000 0.683 1.000 0.000
#> GSM247829 2 0.000 1.000 0.000 1.000
#> GSM247842 1 0.000 0.683 1.000 0.000
#> GSM247805 1 0.990 0.634 0.560 0.440
#> GSM247786 1 0.990 0.634 0.560 0.440
#> GSM247812 2 0.000 1.000 0.000 1.000
#> GSM247776 1 0.000 0.683 1.000 0.000
#> GSM247850 1 0.000 0.683 1.000 0.000
#> GSM247717 1 0.991 0.630 0.556 0.444
#> GSM247784 1 0.990 0.634 0.560 0.440
#> GSM247834 1 0.000 0.683 1.000 0.000
#> GSM247783 2 0.000 1.000 0.000 1.000
#> GSM247846 1 0.000 0.683 1.000 0.000
#> GSM247822 1 0.991 0.630 0.556 0.444
#> GSM247710 1 0.990 0.634 0.560 0.440
#> GSM247713 1 0.000 0.683 1.000 0.000
#> GSM247840 2 0.000 1.000 0.000 1.000
#> GSM247733 1 0.000 0.683 1.000 0.000
#> GSM247852 1 0.000 0.683 1.000 0.000
#> GSM247790 1 0.990 0.634 0.560 0.440
#> GSM247730 1 0.990 0.634 0.560 0.440
#> GSM247824 2 0.000 1.000 0.000 1.000
#> GSM247770 1 0.000 0.683 1.000 0.000
#> GSM247711 1 0.991 0.630 0.556 0.444
#> GSM247782 1 0.990 0.634 0.560 0.440
#> GSM247836 1 0.000 0.683 1.000 0.000
#> GSM247785 2 0.000 1.000 0.000 1.000
#> GSM247847 1 0.000 0.683 1.000 0.000
#> GSM247750 1 0.990 0.634 0.560 0.440
#> GSM247788 1 0.990 0.634 0.560 0.440
#> GSM247849 1 0.000 0.683 1.000 0.000
#> GSM247772 2 0.000 1.000 0.000 1.000
#> GSM247760 1 0.000 0.683 1.000 0.000
#> GSM247764 1 0.991 0.630 0.556 0.444
#> GSM247851 1 0.991 0.630 0.556 0.444
#> GSM247714 1 0.990 0.634 0.560 0.440
#> GSM247828 1 0.000 0.683 1.000 0.000
#> GSM247704 2 0.000 1.000 0.000 1.000
#> GSM247818 1 0.000 0.683 1.000 0.000
#> GSM247823 1 0.991 0.630 0.556 0.444
#> GSM247706 1 0.990 0.634 0.560 0.440
#> GSM247835 2 0.000 1.000 0.000 1.000
#> GSM247734 1 0.000 0.683 1.000 0.000
#> GSM247819 1 0.991 0.630 0.556 0.444
#> GSM247809 1 0.990 0.634 0.560 0.440
#> GSM247830 2 0.000 1.000 0.000 1.000
#> GSM247833 1 0.000 0.683 1.000 0.000
#> GSM247738 1 0.990 0.634 0.560 0.440
#> GSM247716 1 0.990 0.634 0.560 0.440
#> GSM247747 2 0.000 1.000 0.000 1.000
#> GSM247722 1 0.000 0.683 1.000 0.000
#> GSM247816 1 0.991 0.630 0.556 0.444
#> GSM247839 1 0.990 0.634 0.560 0.440
#> GSM247821 1 0.000 0.683 1.000 0.000
#> GSM247798 2 0.000 1.000 0.000 1.000
#> GSM247838 1 0.000 0.683 1.000 0.000
#> GSM247721 1 0.991 0.630 0.556 0.444
#> GSM247781 1 0.990 0.634 0.560 0.440
#> GSM247762 1 0.000 0.683 1.000 0.000
#> GSM247825 2 0.000 1.000 0.000 1.000
#> GSM247777 1 0.000 0.683 1.000 0.000
#> GSM247761 1 0.991 0.630 0.556 0.444
#> GSM247720 1 0.990 0.634 0.560 0.440
#> GSM247814 2 0.000 1.000 0.000 1.000
#> GSM247732 1 0.000 0.683 1.000 0.000
#> GSM247708 1 0.991 0.630 0.556 0.444
#> GSM247740 1 0.990 0.634 0.560 0.440
#> GSM247749 1 0.000 0.683 1.000 0.000
#> GSM247767 2 0.000 1.000 0.000 1.000
#> GSM247748 1 0.000 0.683 1.000 0.000
#> GSM247705 1 0.991 0.630 0.556 0.444
#> GSM247746 1 0.990 0.634 0.560 0.440
#> GSM247752 1 0.000 0.683 1.000 0.000
#> GSM247769 2 0.000 1.000 0.000 1.000
#> GSM247753 1 0.000 0.683 1.000 0.000
#> GSM247723 1 0.991 0.630 0.556 0.444
#> GSM247779 1 0.990 0.634 0.560 0.440
#> GSM247756 1 0.000 0.683 1.000 0.000
#> GSM247826 2 0.000 1.000 0.000 1.000
#> GSM247775 1 0.000 0.683 1.000 0.000
#> GSM247741 1 0.991 0.630 0.556 0.444
#> GSM247799 1 0.990 0.634 0.560 0.440
#> GSM247778 1 0.000 0.683 1.000 0.000
#> GSM247806 2 0.000 1.000 0.000 1.000
#> GSM247815 1 0.000 0.683 1.000 0.000
#> GSM247735 1 0.991 0.630 0.556 0.444
#> GSM247831 1 0.990 0.634 0.560 0.440
#> GSM247845 1 0.000 0.683 1.000 0.000
#> GSM247791 2 0.000 1.000 0.000 1.000
#> GSM247780 1 0.000 0.683 1.000 0.000
#> GSM247853 1 0.000 0.683 1.000 0.000
#> GSM247800 1 0.991 0.630 0.556 0.444
#> GSM247729 1 0.990 0.634 0.560 0.440
#> GSM247810 1 0.000 0.683 1.000 0.000
#> GSM247844 2 0.000 1.000 0.000 1.000
#> GSM247793 1 0.000 0.683 1.000 0.000
#> GSM247759 1 0.991 0.630 0.556 0.444
#> GSM247724 1 0.990 0.634 0.560 0.440
#> GSM247817 2 0.000 1.000 0.000 1.000
#> GSM247727 1 0.000 0.683 1.000 0.000
#> GSM247796 1 0.991 0.630 0.556 0.444
#> GSM247725 1 0.990 0.634 0.560 0.440
#> GSM247801 1 0.000 0.683 1.000 0.000
#> GSM247731 2 0.000 1.000 0.000 1.000
#> GSM247765 1 0.000 0.683 1.000 0.000
#> GSM247792 1 0.991 0.630 0.556 0.444
#> GSM247726 1 0.990 0.634 0.560 0.440
#> GSM247803 1 0.990 0.634 0.560 0.440
#> GSM247728 2 0.000 1.000 0.000 1.000
#> GSM247768 1 0.000 0.683 1.000 0.000
#> GSM247745 1 0.991 0.630 0.556 0.444
#> GSM247855 1 0.991 0.630 0.556 0.444
#> GSM247804 1 0.990 0.634 0.560 0.440
#> GSM247774 1 0.000 0.683 1.000 0.000
#> GSM247807 2 0.000 1.000 0.000 1.000
#> GSM247813 1 0.000 0.683 1.000 0.000
#> GSM247736 1 0.991 0.630 0.556 0.444
#> GSM247712 1 0.990 0.634 0.560 0.440
#> GSM247797 1 0.000 0.683 1.000 0.000
#> GSM247743 2 0.000 1.000 0.000 1.000
#> GSM247719 1 0.000 0.683 1.000 0.000
#> GSM247707 1 0.991 0.630 0.556 0.444
#> GSM247737 1 0.990 0.634 0.560 0.440
#> GSM247827 2 0.000 1.000 0.000 1.000
#> GSM247848 1 0.000 0.683 1.000 0.000
#> GSM247794 1 0.990 0.634 0.560 0.440
#> GSM247757 1 0.990 0.634 0.560 0.440
#> GSM247744 1 0.000 0.683 1.000 0.000
#> GSM247751 2 0.000 1.000 0.000 1.000
#> GSM247837 1 0.000 0.683 1.000 0.000
#> GSM247754 1 0.991 0.630 0.556 0.444
#> GSM247789 1 0.990 0.634 0.560 0.440
#> GSM247802 1 0.000 0.683 1.000 0.000
#> GSM247771 2 0.000 1.000 0.000 1.000
#> GSM247763 1 0.000 0.683 1.000 0.000
#> GSM247808 1 0.991 0.630 0.556 0.444
#> GSM247787 1 0.990 0.634 0.560 0.440
#> GSM247843 1 0.000 0.683 1.000 0.000
#> GSM247811 2 0.000 1.000 0.000 1.000
#> GSM247773 1 0.000 0.683 1.000 0.000
#> GSM247766 1 0.991 0.630 0.556 0.444
#> GSM247718 1 0.990 0.634 0.560 0.440
#> GSM247832 1 0.000 0.683 1.000 0.000
#> GSM247709 2 0.000 1.000 0.000 1.000
#> GSM247820 1 0.000 0.683 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.000 0.999 0.000 1.00 0.000
#> GSM247854 2 0.000 0.999 0.000 1.00 0.000
#> GSM247758 2 0.000 0.999 0.000 1.00 0.000
#> GSM247742 1 0.600 0.893 0.760 0.04 0.200
#> GSM247755 3 0.554 0.987 0.024 0.20 0.776
#> GSM247841 1 0.153 0.933 0.960 0.04 0.000
#> GSM247703 2 0.000 0.999 0.000 1.00 0.000
#> GSM247739 2 0.000 0.999 0.000 1.00 0.000
#> GSM247715 1 0.600 0.893 0.760 0.04 0.200
#> GSM247829 3 0.566 0.987 0.028 0.20 0.772
#> GSM247842 1 0.153 0.933 0.960 0.04 0.000
#> GSM247805 2 0.000 0.999 0.000 1.00 0.000
#> GSM247786 2 0.000 0.999 0.000 1.00 0.000
#> GSM247812 3 0.512 0.988 0.012 0.20 0.788
#> GSM247776 1 0.153 0.933 0.960 0.04 0.000
#> GSM247850 1 0.153 0.933 0.960 0.04 0.000
#> GSM247717 2 0.000 0.999 0.000 1.00 0.000
#> GSM247784 2 0.000 0.999 0.000 1.00 0.000
#> GSM247834 1 0.600 0.893 0.760 0.04 0.200
#> GSM247783 3 0.455 0.989 0.000 0.20 0.800
#> GSM247846 1 0.153 0.933 0.960 0.04 0.000
#> GSM247822 2 0.000 0.999 0.000 1.00 0.000
#> GSM247710 2 0.000 0.999 0.000 1.00 0.000
#> GSM247713 1 0.600 0.893 0.760 0.04 0.200
#> GSM247840 3 0.512 0.988 0.012 0.20 0.788
#> GSM247733 1 0.153 0.933 0.960 0.04 0.000
#> GSM247852 1 0.153 0.933 0.960 0.04 0.000
#> GSM247790 2 0.000 0.999 0.000 1.00 0.000
#> GSM247730 2 0.000 0.999 0.000 1.00 0.000
#> GSM247824 3 0.496 0.989 0.008 0.20 0.792
#> GSM247770 1 0.153 0.933 0.960 0.04 0.000
#> GSM247711 2 0.000 0.999 0.000 1.00 0.000
#> GSM247782 2 0.000 0.999 0.000 1.00 0.000
#> GSM247836 1 0.600 0.893 0.760 0.04 0.200
#> GSM247785 3 0.455 0.989 0.000 0.20 0.800
#> GSM247847 1 0.153 0.933 0.960 0.04 0.000
#> GSM247750 2 0.000 0.999 0.000 1.00 0.000
#> GSM247788 2 0.000 0.999 0.000 1.00 0.000
#> GSM247849 1 0.600 0.893 0.760 0.04 0.200
#> GSM247772 3 0.566 0.987 0.028 0.20 0.772
#> GSM247760 1 0.153 0.933 0.960 0.04 0.000
#> GSM247764 2 0.000 0.999 0.000 1.00 0.000
#> GSM247851 2 0.000 0.999 0.000 1.00 0.000
#> GSM247714 2 0.000 0.999 0.000 1.00 0.000
#> GSM247828 1 0.600 0.893 0.760 0.04 0.200
#> GSM247704 3 0.527 0.988 0.016 0.20 0.784
#> GSM247818 1 0.153 0.933 0.960 0.04 0.000
#> GSM247823 2 0.000 0.999 0.000 1.00 0.000
#> GSM247706 2 0.000 0.999 0.000 1.00 0.000
#> GSM247835 3 0.554 0.987 0.024 0.20 0.776
#> GSM247734 1 0.153 0.933 0.960 0.04 0.000
#> GSM247819 2 0.000 0.999 0.000 1.00 0.000
#> GSM247809 2 0.000 0.999 0.000 1.00 0.000
#> GSM247830 3 0.512 0.989 0.012 0.20 0.788
#> GSM247833 1 0.153 0.933 0.960 0.04 0.000
#> GSM247738 2 0.000 0.999 0.000 1.00 0.000
#> GSM247716 2 0.000 0.999 0.000 1.00 0.000
#> GSM247747 3 0.566 0.987 0.028 0.20 0.772
#> GSM247722 1 0.153 0.933 0.960 0.04 0.000
#> GSM247816 2 0.000 0.999 0.000 1.00 0.000
#> GSM247839 2 0.000 0.999 0.000 1.00 0.000
#> GSM247821 1 0.600 0.893 0.760 0.04 0.200
#> GSM247798 3 0.527 0.988 0.016 0.20 0.784
#> GSM247838 1 0.153 0.933 0.960 0.04 0.000
#> GSM247721 2 0.000 0.999 0.000 1.00 0.000
#> GSM247781 2 0.000 0.999 0.000 1.00 0.000
#> GSM247762 1 0.600 0.893 0.760 0.04 0.200
#> GSM247825 3 0.566 0.987 0.028 0.20 0.772
#> GSM247777 1 0.153 0.933 0.960 0.04 0.000
#> GSM247761 2 0.000 0.999 0.000 1.00 0.000
#> GSM247720 2 0.000 0.999 0.000 1.00 0.000
#> GSM247814 3 0.566 0.987 0.028 0.20 0.772
#> GSM247732 1 0.153 0.933 0.960 0.04 0.000
#> GSM247708 2 0.000 0.999 0.000 1.00 0.000
#> GSM247740 2 0.000 0.999 0.000 1.00 0.000
#> GSM247749 1 0.600 0.893 0.760 0.04 0.200
#> GSM247767 3 0.512 0.988 0.012 0.20 0.788
#> GSM247748 1 0.153 0.933 0.960 0.04 0.000
#> GSM247705 2 0.000 0.999 0.000 1.00 0.000
#> GSM247746 2 0.000 0.999 0.000 1.00 0.000
#> GSM247752 1 0.600 0.893 0.760 0.04 0.200
#> GSM247769 3 0.496 0.989 0.008 0.20 0.792
#> GSM247753 1 0.153 0.933 0.960 0.04 0.000
#> GSM247723 2 0.000 0.999 0.000 1.00 0.000
#> GSM247779 2 0.000 0.999 0.000 1.00 0.000
#> GSM247756 1 0.600 0.893 0.760 0.04 0.200
#> GSM247826 3 0.554 0.987 0.024 0.20 0.776
#> GSM247775 1 0.153 0.933 0.960 0.04 0.000
#> GSM247741 2 0.000 0.999 0.000 1.00 0.000
#> GSM247799 2 0.000 0.999 0.000 1.00 0.000
#> GSM247778 1 0.600 0.893 0.760 0.04 0.200
#> GSM247806 3 0.512 0.989 0.012 0.20 0.788
#> GSM247815 1 0.153 0.933 0.960 0.04 0.000
#> GSM247735 2 0.000 0.999 0.000 1.00 0.000
#> GSM247831 2 0.000 0.999 0.000 1.00 0.000
#> GSM247845 1 0.600 0.893 0.760 0.04 0.200
#> GSM247791 3 0.512 0.988 0.012 0.20 0.788
#> GSM247780 1 0.153 0.933 0.960 0.04 0.000
#> GSM247853 1 0.153 0.933 0.960 0.04 0.000
#> GSM247800 2 0.000 0.999 0.000 1.00 0.000
#> GSM247729 2 0.000 0.999 0.000 1.00 0.000
#> GSM247810 1 0.600 0.893 0.760 0.04 0.200
#> GSM247844 3 0.578 0.988 0.032 0.20 0.768
#> GSM247793 1 0.153 0.933 0.960 0.04 0.000
#> GSM247759 2 0.000 0.999 0.000 1.00 0.000
#> GSM247724 2 0.000 0.999 0.000 1.00 0.000
#> GSM247817 3 0.566 0.987 0.028 0.20 0.772
#> GSM247727 1 0.153 0.933 0.960 0.04 0.000
#> GSM247796 2 0.000 0.999 0.000 1.00 0.000
#> GSM247725 2 0.000 0.999 0.000 1.00 0.000
#> GSM247801 1 0.600 0.893 0.760 0.04 0.200
#> GSM247731 3 0.478 0.989 0.004 0.20 0.796
#> GSM247765 1 0.153 0.933 0.960 0.04 0.000
#> GSM247792 2 0.000 0.999 0.000 1.00 0.000
#> GSM247726 2 0.000 0.999 0.000 1.00 0.000
#> GSM247803 2 0.207 0.914 0.000 0.94 0.060
#> GSM247728 3 0.478 0.989 0.004 0.20 0.796
#> GSM247768 1 0.153 0.933 0.960 0.04 0.000
#> GSM247745 2 0.000 0.999 0.000 1.00 0.000
#> GSM247855 2 0.000 0.999 0.000 1.00 0.000
#> GSM247804 2 0.000 0.999 0.000 1.00 0.000
#> GSM247774 1 0.600 0.893 0.760 0.04 0.200
#> GSM247807 3 0.566 0.988 0.028 0.20 0.772
#> GSM247813 1 0.153 0.933 0.960 0.04 0.000
#> GSM247736 2 0.000 0.999 0.000 1.00 0.000
#> GSM247712 2 0.000 0.999 0.000 1.00 0.000
#> GSM247797 1 0.600 0.893 0.760 0.04 0.200
#> GSM247743 3 0.566 0.987 0.028 0.20 0.772
#> GSM247719 1 0.153 0.933 0.960 0.04 0.000
#> GSM247707 2 0.000 0.999 0.000 1.00 0.000
#> GSM247737 2 0.000 0.999 0.000 1.00 0.000
#> GSM247827 3 0.554 0.987 0.024 0.20 0.776
#> GSM247848 1 0.153 0.933 0.960 0.04 0.000
#> GSM247794 2 0.000 0.999 0.000 1.00 0.000
#> GSM247757 2 0.000 0.999 0.000 1.00 0.000
#> GSM247744 1 0.600 0.893 0.760 0.04 0.200
#> GSM247751 3 0.541 0.989 0.020 0.20 0.780
#> GSM247837 1 0.153 0.933 0.960 0.04 0.000
#> GSM247754 2 0.000 0.999 0.000 1.00 0.000
#> GSM247789 2 0.000 0.999 0.000 1.00 0.000
#> GSM247802 1 0.600 0.893 0.760 0.04 0.200
#> GSM247771 3 0.478 0.989 0.004 0.20 0.796
#> GSM247763 1 0.153 0.933 0.960 0.04 0.000
#> GSM247808 2 0.000 0.999 0.000 1.00 0.000
#> GSM247787 2 0.000 0.999 0.000 1.00 0.000
#> GSM247843 1 0.600 0.893 0.760 0.04 0.200
#> GSM247811 3 0.512 0.988 0.012 0.20 0.788
#> GSM247773 1 0.153 0.933 0.960 0.04 0.000
#> GSM247766 2 0.000 0.999 0.000 1.00 0.000
#> GSM247718 2 0.000 0.999 0.000 1.00 0.000
#> GSM247832 1 0.600 0.893 0.760 0.04 0.200
#> GSM247709 3 0.527 0.988 0.016 0.20 0.784
#> GSM247820 1 0.153 0.933 0.960 0.04 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247854 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247758 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247742 1 0.0000 0.757 1.000 0.000 0.000 NA
#> GSM247755 3 0.3966 0.957 0.000 0.072 0.840 NA
#> GSM247841 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247703 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247739 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247715 1 0.1118 0.756 0.964 0.000 0.036 NA
#> GSM247829 3 0.4552 0.952 0.000 0.072 0.800 NA
#> GSM247842 1 0.5060 0.848 0.584 0.000 0.004 NA
#> GSM247805 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247786 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247812 3 0.2563 0.960 0.000 0.072 0.908 NA
#> GSM247776 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247850 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247717 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247784 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247834 1 0.1118 0.756 0.964 0.000 0.036 NA
#> GSM247783 3 0.2450 0.963 0.000 0.072 0.912 NA
#> GSM247846 1 0.5060 0.848 0.584 0.000 0.004 NA
#> GSM247822 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247710 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247713 1 0.1118 0.756 0.964 0.000 0.036 NA
#> GSM247840 3 0.2450 0.961 0.000 0.072 0.912 NA
#> GSM247733 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247852 1 0.5183 0.848 0.584 0.000 0.008 NA
#> GSM247790 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247730 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247824 3 0.2450 0.961 0.000 0.072 0.912 NA
#> GSM247770 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247711 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247782 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247836 1 0.0188 0.757 0.996 0.000 0.004 NA
#> GSM247785 3 0.2450 0.963 0.000 0.072 0.912 NA
#> GSM247847 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247750 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247788 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247849 1 0.0000 0.757 1.000 0.000 0.000 NA
#> GSM247772 3 0.4444 0.953 0.000 0.072 0.808 NA
#> GSM247760 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247764 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247851 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247714 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247828 1 0.0000 0.757 1.000 0.000 0.000 NA
#> GSM247704 3 0.3900 0.953 0.000 0.072 0.844 NA
#> GSM247818 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247823 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247706 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247835 3 0.3966 0.957 0.000 0.072 0.840 NA
#> GSM247734 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247819 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247809 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247830 3 0.2871 0.961 0.000 0.072 0.896 NA
#> GSM247833 1 0.5781 0.845 0.584 0.000 0.036 NA
#> GSM247738 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247716 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247747 3 0.4030 0.957 0.000 0.072 0.836 NA
#> GSM247722 1 0.5781 0.845 0.584 0.000 0.036 NA
#> GSM247816 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247839 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247821 1 0.0592 0.757 0.984 0.000 0.016 NA
#> GSM247798 3 0.3471 0.955 0.000 0.072 0.868 NA
#> GSM247838 1 0.5781 0.845 0.584 0.000 0.036 NA
#> GSM247721 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247781 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247762 1 0.0000 0.757 1.000 0.000 0.000 NA
#> GSM247825 3 0.4444 0.953 0.000 0.072 0.808 NA
#> GSM247777 1 0.5781 0.845 0.584 0.000 0.036 NA
#> GSM247761 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247720 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247814 3 0.4552 0.952 0.000 0.072 0.800 NA
#> GSM247732 1 0.5781 0.845 0.584 0.000 0.036 NA
#> GSM247708 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247740 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247749 1 0.1022 0.756 0.968 0.000 0.032 NA
#> GSM247767 3 0.2563 0.960 0.000 0.072 0.908 NA
#> GSM247748 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247705 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247746 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247752 1 0.1820 0.744 0.944 0.000 0.036 NA
#> GSM247769 3 0.2773 0.960 0.000 0.072 0.900 NA
#> GSM247753 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247723 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247779 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247756 1 0.0000 0.757 1.000 0.000 0.000 NA
#> GSM247826 3 0.3966 0.957 0.000 0.072 0.840 NA
#> GSM247775 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247741 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247799 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247778 1 0.1022 0.756 0.968 0.000 0.032 NA
#> GSM247806 3 0.3547 0.960 0.000 0.072 0.864 NA
#> GSM247815 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247735 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247831 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247845 1 0.0000 0.757 1.000 0.000 0.000 NA
#> GSM247791 3 0.2563 0.960 0.000 0.072 0.908 NA
#> GSM247780 1 0.5781 0.845 0.584 0.000 0.036 NA
#> GSM247853 1 0.5781 0.845 0.584 0.000 0.036 NA
#> GSM247800 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247729 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247810 1 0.1118 0.756 0.964 0.000 0.036 NA
#> GSM247844 3 0.4389 0.954 0.000 0.072 0.812 NA
#> GSM247793 1 0.5183 0.848 0.584 0.000 0.008 NA
#> GSM247759 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247724 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247817 3 0.4605 0.951 0.000 0.072 0.796 NA
#> GSM247727 1 0.5781 0.845 0.584 0.000 0.036 NA
#> GSM247796 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247725 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247801 1 0.0000 0.757 1.000 0.000 0.000 NA
#> GSM247731 3 0.1867 0.962 0.000 0.072 0.928 NA
#> GSM247765 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247792 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247726 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247803 2 0.2324 0.727 0.028 0.932 0.020 NA
#> GSM247728 3 0.2450 0.962 0.000 0.072 0.912 NA
#> GSM247768 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247745 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247855 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247804 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247774 1 0.0000 0.757 1.000 0.000 0.000 NA
#> GSM247807 3 0.3966 0.961 0.000 0.072 0.840 NA
#> GSM247813 1 0.5781 0.845 0.584 0.000 0.036 NA
#> GSM247736 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247712 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247797 1 0.0000 0.757 1.000 0.000 0.000 NA
#> GSM247743 3 0.4093 0.957 0.000 0.072 0.832 NA
#> GSM247719 1 0.5781 0.845 0.584 0.000 0.036 NA
#> GSM247707 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247737 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247827 3 0.3966 0.957 0.000 0.072 0.840 NA
#> GSM247848 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247794 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247757 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247744 1 0.0000 0.757 1.000 0.000 0.000 NA
#> GSM247751 3 0.3833 0.961 0.000 0.072 0.848 NA
#> GSM247837 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247754 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247789 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247802 1 0.1022 0.756 0.968 0.000 0.032 NA
#> GSM247771 3 0.1867 0.962 0.000 0.072 0.928 NA
#> GSM247763 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247808 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247787 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247843 1 0.1022 0.756 0.968 0.000 0.032 NA
#> GSM247811 3 0.3312 0.955 0.000 0.072 0.876 NA
#> GSM247773 1 0.4898 0.848 0.584 0.000 0.000 NA
#> GSM247766 2 0.4855 0.795 0.000 0.600 0.000 NA
#> GSM247718 2 0.0000 0.779 0.000 1.000 0.000 NA
#> GSM247832 1 0.0000 0.757 1.000 0.000 0.000 NA
#> GSM247709 3 0.3900 0.953 0.000 0.072 0.844 NA
#> GSM247820 1 0.5781 0.845 0.584 0.000 0.036 NA
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247854 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247758 5 0.0290 0.981 0.000 0.000 0.000 0.008 0.992
#> GSM247742 4 0.4547 0.966 0.400 0.012 0.000 0.588 0.000
#> GSM247755 3 0.3405 0.922 0.000 0.024 0.848 0.108 0.020
#> GSM247841 1 0.0162 0.944 0.996 0.000 0.004 0.000 0.000
#> GSM247703 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247739 5 0.0404 0.978 0.000 0.000 0.000 0.012 0.988
#> GSM247715 4 0.5106 0.962 0.400 0.032 0.004 0.564 0.000
#> GSM247829 3 0.4312 0.911 0.000 0.040 0.780 0.160 0.020
#> GSM247842 1 0.1012 0.941 0.968 0.020 0.012 0.000 0.000
#> GSM247805 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247786 5 0.0609 0.975 0.000 0.000 0.000 0.020 0.980
#> GSM247812 3 0.2400 0.921 0.000 0.048 0.912 0.020 0.020
#> GSM247776 1 0.0451 0.945 0.988 0.008 0.004 0.000 0.000
#> GSM247850 1 0.0404 0.943 0.988 0.000 0.012 0.000 0.000
#> GSM247717 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247784 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247834 4 0.5106 0.962 0.400 0.032 0.004 0.564 0.000
#> GSM247783 3 0.1405 0.929 0.000 0.008 0.956 0.016 0.020
#> GSM247846 1 0.1012 0.941 0.968 0.020 0.012 0.000 0.000
#> GSM247822 2 0.5934 0.924 0.000 0.496 0.000 0.108 0.396
#> GSM247710 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247713 4 0.5106 0.962 0.400 0.032 0.004 0.564 0.000
#> GSM247840 3 0.2400 0.921 0.000 0.048 0.912 0.020 0.020
#> GSM247733 1 0.0451 0.945 0.988 0.008 0.004 0.000 0.000
#> GSM247852 1 0.1444 0.936 0.948 0.040 0.012 0.000 0.000
#> GSM247790 2 0.4436 0.942 0.000 0.596 0.000 0.008 0.396
#> GSM247730 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247824 3 0.1989 0.923 0.000 0.032 0.932 0.016 0.020
#> GSM247770 1 0.0162 0.944 0.996 0.000 0.004 0.000 0.000
#> GSM247711 2 0.5086 0.946 0.000 0.564 0.000 0.040 0.396
#> GSM247782 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247836 4 0.4331 0.968 0.400 0.004 0.000 0.596 0.000
#> GSM247785 3 0.1503 0.929 0.000 0.008 0.952 0.020 0.020
#> GSM247847 1 0.0404 0.943 0.988 0.000 0.012 0.000 0.000
#> GSM247750 2 0.4321 0.945 0.000 0.600 0.000 0.004 0.396
#> GSM247788 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247849 4 0.4547 0.966 0.400 0.012 0.000 0.588 0.000
#> GSM247772 3 0.4148 0.913 0.000 0.040 0.796 0.144 0.020
#> GSM247760 1 0.0451 0.945 0.988 0.008 0.004 0.000 0.000
#> GSM247764 2 0.5934 0.924 0.000 0.496 0.000 0.108 0.396
#> GSM247851 2 0.5934 0.924 0.000 0.496 0.000 0.108 0.396
#> GSM247714 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247828 4 0.4182 0.968 0.400 0.000 0.000 0.600 0.000
#> GSM247704 3 0.4288 0.908 0.000 0.092 0.800 0.088 0.020
#> GSM247818 1 0.0162 0.944 0.996 0.000 0.004 0.000 0.000
#> GSM247823 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247706 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247835 3 0.3405 0.922 0.000 0.024 0.848 0.108 0.020
#> GSM247734 1 0.0451 0.945 0.988 0.008 0.004 0.000 0.000
#> GSM247819 2 0.5934 0.924 0.000 0.496 0.000 0.108 0.396
#> GSM247809 5 0.0290 0.981 0.000 0.000 0.000 0.008 0.992
#> GSM247830 3 0.2418 0.922 0.000 0.044 0.912 0.024 0.020
#> GSM247833 1 0.2127 0.910 0.892 0.108 0.000 0.000 0.000
#> GSM247738 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247716 5 0.0290 0.981 0.000 0.000 0.000 0.008 0.992
#> GSM247747 3 0.3455 0.922 0.000 0.024 0.844 0.112 0.020
#> GSM247722 1 0.2127 0.910 0.892 0.108 0.000 0.000 0.000
#> GSM247816 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247839 5 0.0290 0.981 0.000 0.000 0.000 0.008 0.992
#> GSM247821 4 0.4547 0.967 0.400 0.012 0.000 0.588 0.000
#> GSM247798 3 0.3977 0.909 0.000 0.100 0.820 0.060 0.020
#> GSM247838 1 0.2127 0.910 0.892 0.108 0.000 0.000 0.000
#> GSM247721 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247781 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247762 4 0.4547 0.966 0.400 0.012 0.000 0.588 0.000
#> GSM247825 3 0.4272 0.911 0.000 0.040 0.784 0.156 0.020
#> GSM247777 1 0.2074 0.909 0.896 0.104 0.000 0.000 0.000
#> GSM247761 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247720 5 0.0609 0.975 0.000 0.000 0.000 0.020 0.980
#> GSM247814 3 0.4156 0.914 0.000 0.036 0.792 0.152 0.020
#> GSM247732 1 0.2127 0.910 0.892 0.108 0.000 0.000 0.000
#> GSM247708 2 0.5086 0.946 0.000 0.564 0.000 0.040 0.396
#> GSM247740 5 0.0404 0.978 0.000 0.000 0.000 0.012 0.988
#> GSM247749 4 0.5106 0.962 0.400 0.032 0.004 0.564 0.000
#> GSM247767 3 0.2374 0.921 0.000 0.052 0.912 0.016 0.020
#> GSM247748 1 0.0451 0.945 0.988 0.008 0.004 0.000 0.000
#> GSM247705 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247746 5 0.0404 0.979 0.000 0.000 0.000 0.012 0.988
#> GSM247752 4 0.6177 0.755 0.316 0.140 0.004 0.540 0.000
#> GSM247769 3 0.2302 0.922 0.000 0.048 0.916 0.016 0.020
#> GSM247753 1 0.0451 0.945 0.988 0.008 0.004 0.000 0.000
#> GSM247723 2 0.5815 0.929 0.000 0.508 0.000 0.096 0.396
#> GSM247779 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247756 4 0.4182 0.968 0.400 0.000 0.000 0.600 0.000
#> GSM247826 3 0.3405 0.922 0.000 0.024 0.848 0.108 0.020
#> GSM247775 1 0.0451 0.945 0.988 0.008 0.004 0.000 0.000
#> GSM247741 2 0.5934 0.924 0.000 0.496 0.000 0.108 0.396
#> GSM247799 5 0.0290 0.981 0.000 0.000 0.000 0.008 0.992
#> GSM247778 4 0.5106 0.962 0.400 0.032 0.004 0.564 0.000
#> GSM247806 3 0.2513 0.927 0.000 0.016 0.904 0.060 0.020
#> GSM247815 1 0.0451 0.945 0.988 0.008 0.004 0.000 0.000
#> GSM247735 2 0.5934 0.924 0.000 0.496 0.000 0.108 0.396
#> GSM247831 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247845 4 0.4182 0.968 0.400 0.000 0.000 0.600 0.000
#> GSM247791 3 0.2400 0.921 0.000 0.048 0.912 0.020 0.020
#> GSM247780 1 0.2074 0.909 0.896 0.104 0.000 0.000 0.000
#> GSM247853 1 0.2179 0.909 0.896 0.100 0.004 0.000 0.000
#> GSM247800 2 0.5934 0.924 0.000 0.496 0.000 0.108 0.396
#> GSM247729 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247810 4 0.5106 0.962 0.400 0.032 0.004 0.564 0.000
#> GSM247844 3 0.4892 0.905 0.000 0.120 0.752 0.108 0.020
#> GSM247793 1 0.1444 0.936 0.948 0.040 0.012 0.000 0.000
#> GSM247759 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247724 5 0.0290 0.981 0.000 0.000 0.000 0.008 0.992
#> GSM247817 3 0.4272 0.913 0.000 0.040 0.784 0.156 0.020
#> GSM247727 1 0.2179 0.908 0.888 0.112 0.000 0.000 0.000
#> GSM247796 2 0.5934 0.924 0.000 0.496 0.000 0.108 0.396
#> GSM247725 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247801 4 0.4547 0.966 0.400 0.012 0.000 0.588 0.000
#> GSM247731 3 0.1216 0.927 0.000 0.020 0.960 0.000 0.020
#> GSM247765 1 0.0162 0.944 0.996 0.000 0.004 0.000 0.000
#> GSM247792 2 0.5934 0.924 0.000 0.496 0.000 0.108 0.396
#> GSM247726 5 0.0290 0.981 0.000 0.000 0.000 0.008 0.992
#> GSM247803 5 0.4519 0.659 0.000 0.120 0.004 0.112 0.764
#> GSM247728 3 0.1405 0.927 0.000 0.016 0.956 0.008 0.020
#> GSM247768 1 0.0162 0.944 0.996 0.000 0.004 0.000 0.000
#> GSM247745 2 0.5086 0.946 0.000 0.564 0.000 0.040 0.396
#> GSM247855 2 0.5086 0.946 0.000 0.564 0.000 0.040 0.396
#> GSM247804 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247774 4 0.4547 0.966 0.400 0.012 0.000 0.588 0.000
#> GSM247807 3 0.4139 0.923 0.000 0.052 0.804 0.124 0.020
#> GSM247813 1 0.2074 0.909 0.896 0.104 0.000 0.000 0.000
#> GSM247736 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247712 5 0.0609 0.975 0.000 0.000 0.000 0.020 0.980
#> GSM247797 4 0.4547 0.966 0.400 0.012 0.000 0.588 0.000
#> GSM247743 3 0.3455 0.922 0.000 0.024 0.844 0.112 0.020
#> GSM247719 1 0.2127 0.910 0.892 0.108 0.000 0.000 0.000
#> GSM247707 2 0.5086 0.946 0.000 0.564 0.000 0.040 0.396
#> GSM247737 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247827 3 0.3405 0.922 0.000 0.024 0.848 0.108 0.020
#> GSM247848 1 0.0404 0.943 0.988 0.000 0.012 0.000 0.000
#> GSM247794 2 0.4171 0.947 0.000 0.604 0.000 0.000 0.396
#> GSM247757 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247744 4 0.4182 0.968 0.400 0.000 0.000 0.600 0.000
#> GSM247751 3 0.3496 0.926 0.000 0.036 0.848 0.096 0.020
#> GSM247837 1 0.0162 0.944 0.996 0.000 0.004 0.000 0.000
#> GSM247754 2 0.5019 0.946 0.000 0.568 0.000 0.036 0.396
#> GSM247789 5 0.0000 0.982 0.000 0.000 0.000 0.000 1.000
#> GSM247802 4 0.5106 0.962 0.400 0.032 0.004 0.564 0.000
#> GSM247771 3 0.1216 0.927 0.000 0.020 0.960 0.000 0.020
#> GSM247763 1 0.0451 0.945 0.988 0.008 0.004 0.000 0.000
#> GSM247808 2 0.5895 0.926 0.000 0.500 0.000 0.104 0.396
#> GSM247787 5 0.0609 0.975 0.000 0.000 0.000 0.020 0.980
#> GSM247843 4 0.5106 0.962 0.400 0.032 0.004 0.564 0.000
#> GSM247811 3 0.3753 0.910 0.000 0.104 0.832 0.044 0.020
#> GSM247773 1 0.0451 0.945 0.988 0.008 0.004 0.000 0.000
#> GSM247766 2 0.5934 0.924 0.000 0.496 0.000 0.108 0.396
#> GSM247718 5 0.0609 0.975 0.000 0.000 0.000 0.020 0.980
#> GSM247832 4 0.4547 0.966 0.400 0.012 0.000 0.588 0.000
#> GSM247709 3 0.4494 0.904 0.000 0.108 0.784 0.088 0.020
#> GSM247820 1 0.2179 0.908 0.888 0.112 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.1643 0.894 0.000 0.924 0.000 0.008 0.000 NA
#> GSM247854 2 0.1643 0.894 0.000 0.924 0.000 0.008 0.000 NA
#> GSM247758 5 0.3265 0.962 0.000 0.248 0.000 0.000 0.748 NA
#> GSM247742 4 0.3708 0.924 0.220 0.000 0.000 0.752 0.008 NA
#> GSM247755 3 0.3109 0.883 0.000 0.000 0.772 0.004 0.000 NA
#> GSM247841 1 0.0622 0.938 0.980 0.000 0.000 0.000 0.012 NA
#> GSM247703 2 0.1838 0.894 0.000 0.916 0.000 0.016 0.000 NA
#> GSM247739 5 0.4136 0.950 0.000 0.248 0.000 0.004 0.708 NA
#> GSM247715 4 0.5460 0.915 0.220 0.000 0.000 0.644 0.052 NA
#> GSM247829 3 0.3508 0.870 0.000 0.000 0.704 0.000 0.004 NA
#> GSM247842 1 0.0972 0.938 0.964 0.000 0.000 0.000 0.008 NA
#> GSM247805 2 0.1838 0.894 0.000 0.916 0.000 0.016 0.000 NA
#> GSM247786 5 0.4685 0.939 0.000 0.248 0.000 0.012 0.676 NA
#> GSM247812 3 0.1369 0.892 0.000 0.000 0.952 0.016 0.016 NA
#> GSM247776 1 0.0508 0.940 0.984 0.000 0.000 0.000 0.004 NA
#> GSM247850 1 0.0146 0.940 0.996 0.000 0.000 0.000 0.000 NA
#> GSM247717 2 0.1838 0.894 0.000 0.916 0.000 0.016 0.000 NA
#> GSM247784 5 0.3265 0.962 0.000 0.248 0.000 0.000 0.748 NA
#> GSM247834 4 0.5460 0.915 0.220 0.000 0.000 0.644 0.052 NA
#> GSM247783 3 0.1411 0.898 0.000 0.000 0.936 0.000 0.004 NA
#> GSM247846 1 0.0972 0.938 0.964 0.000 0.000 0.000 0.008 NA
#> GSM247822 2 0.3139 0.843 0.000 0.816 0.000 0.032 0.000 NA
#> GSM247710 5 0.3126 0.962 0.000 0.248 0.000 0.000 0.752 NA
#> GSM247713 4 0.5460 0.915 0.220 0.000 0.000 0.644 0.052 NA
#> GSM247840 3 0.1369 0.892 0.000 0.000 0.952 0.016 0.016 NA
#> GSM247733 1 0.0622 0.940 0.980 0.000 0.000 0.000 0.008 NA
#> GSM247852 1 0.1333 0.934 0.944 0.000 0.000 0.000 0.008 NA
#> GSM247790 2 0.1757 0.891 0.000 0.916 0.000 0.008 0.000 NA
#> GSM247730 5 0.3265 0.962 0.000 0.248 0.000 0.000 0.748 NA
#> GSM247824 3 0.0964 0.891 0.000 0.000 0.968 0.012 0.004 NA
#> GSM247770 1 0.0405 0.940 0.988 0.000 0.000 0.000 0.004 NA
#> GSM247711 2 0.0622 0.892 0.000 0.980 0.000 0.008 0.000 NA
#> GSM247782 5 0.3265 0.962 0.000 0.248 0.000 0.000 0.748 NA
#> GSM247836 4 0.4024 0.928 0.220 0.000 0.000 0.732 0.004 NA
#> GSM247785 3 0.1327 0.898 0.000 0.000 0.936 0.000 0.000 NA
#> GSM247847 1 0.0146 0.940 0.996 0.000 0.000 0.000 0.000 NA
#> GSM247750 2 0.1745 0.894 0.000 0.920 0.000 0.012 0.000 NA
#> GSM247788 5 0.3265 0.962 0.000 0.248 0.000 0.000 0.748 NA
#> GSM247849 4 0.3708 0.924 0.220 0.000 0.000 0.752 0.008 NA
#> GSM247772 3 0.3371 0.870 0.000 0.000 0.708 0.000 0.000 NA
#> GSM247760 1 0.0508 0.940 0.984 0.000 0.000 0.000 0.004 NA
#> GSM247764 2 0.3139 0.843 0.000 0.816 0.000 0.032 0.000 NA
#> GSM247851 2 0.3139 0.843 0.000 0.816 0.000 0.032 0.000 NA
#> GSM247714 5 0.3126 0.962 0.000 0.248 0.000 0.000 0.752 NA
#> GSM247828 4 0.2941 0.929 0.220 0.000 0.000 0.780 0.000 NA
#> GSM247704 3 0.3648 0.873 0.000 0.000 0.808 0.040 0.024 NA
#> GSM247818 1 0.0622 0.938 0.980 0.000 0.000 0.000 0.012 NA
#> GSM247823 2 0.1838 0.894 0.000 0.916 0.000 0.016 0.000 NA
#> GSM247706 5 0.3126 0.962 0.000 0.248 0.000 0.000 0.752 NA
#> GSM247835 3 0.3109 0.883 0.000 0.000 0.772 0.004 0.000 NA
#> GSM247734 1 0.0508 0.940 0.984 0.000 0.000 0.000 0.004 NA
#> GSM247819 2 0.3139 0.843 0.000 0.816 0.000 0.032 0.000 NA
#> GSM247809 5 0.4110 0.954 0.000 0.248 0.000 0.008 0.712 NA
#> GSM247830 3 0.1251 0.892 0.000 0.000 0.956 0.012 0.008 NA
#> GSM247833 1 0.2667 0.898 0.852 0.000 0.000 0.000 0.020 NA
#> GSM247738 2 0.1838 0.894 0.000 0.916 0.000 0.016 0.000 NA
#> GSM247716 5 0.4110 0.954 0.000 0.248 0.000 0.008 0.712 NA
#> GSM247747 3 0.3163 0.882 0.000 0.000 0.764 0.004 0.000 NA
#> GSM247722 1 0.2667 0.898 0.852 0.000 0.000 0.000 0.020 NA
#> GSM247816 2 0.1838 0.894 0.000 0.916 0.000 0.016 0.000 NA
#> GSM247839 5 0.4110 0.954 0.000 0.248 0.000 0.008 0.712 NA
#> GSM247821 4 0.4762 0.924 0.220 0.000 0.000 0.692 0.024 NA
#> GSM247798 3 0.2954 0.877 0.000 0.000 0.868 0.044 0.028 NA
#> GSM247838 1 0.2667 0.898 0.852 0.000 0.000 0.000 0.020 NA
#> GSM247721 2 0.1745 0.894 0.000 0.920 0.000 0.012 0.000 NA
#> GSM247781 5 0.3265 0.962 0.000 0.248 0.000 0.000 0.748 NA
#> GSM247762 4 0.3906 0.921 0.216 0.000 0.000 0.744 0.008 NA
#> GSM247825 3 0.3489 0.871 0.000 0.000 0.708 0.000 0.004 NA
#> GSM247777 1 0.2667 0.896 0.852 0.000 0.000 0.000 0.020 NA
#> GSM247761 2 0.1838 0.894 0.000 0.916 0.000 0.016 0.000 NA
#> GSM247720 5 0.4685 0.939 0.000 0.248 0.000 0.012 0.676 NA
#> GSM247814 3 0.3330 0.873 0.000 0.000 0.716 0.000 0.000 NA
#> GSM247732 1 0.2667 0.898 0.852 0.000 0.000 0.000 0.020 NA
#> GSM247708 2 0.0622 0.892 0.000 0.980 0.000 0.008 0.000 NA
#> GSM247740 5 0.4199 0.949 0.000 0.248 0.000 0.004 0.704 NA
#> GSM247749 4 0.5309 0.918 0.220 0.000 0.000 0.656 0.048 NA
#> GSM247767 3 0.1173 0.891 0.000 0.000 0.960 0.016 0.008 NA
#> GSM247748 1 0.0622 0.940 0.980 0.000 0.000 0.000 0.012 NA
#> GSM247705 2 0.1838 0.894 0.000 0.916 0.000 0.016 0.000 NA
#> GSM247746 5 0.4110 0.954 0.000 0.248 0.000 0.008 0.712 NA
#> GSM247752 4 0.6653 0.656 0.116 0.000 0.000 0.536 0.164 NA
#> GSM247769 3 0.1167 0.890 0.000 0.000 0.960 0.012 0.008 NA
#> GSM247753 1 0.0622 0.940 0.980 0.000 0.000 0.000 0.008 NA
#> GSM247723 2 0.2662 0.860 0.000 0.856 0.000 0.024 0.000 NA
#> GSM247779 5 0.3265 0.962 0.000 0.248 0.000 0.000 0.748 NA
#> GSM247756 4 0.2941 0.929 0.220 0.000 0.000 0.780 0.000 NA
#> GSM247826 3 0.3109 0.883 0.000 0.000 0.772 0.004 0.000 NA
#> GSM247775 1 0.0622 0.940 0.980 0.000 0.000 0.000 0.008 NA
#> GSM247741 2 0.3139 0.843 0.000 0.816 0.000 0.032 0.000 NA
#> GSM247799 5 0.3932 0.956 0.000 0.248 0.000 0.004 0.720 NA
#> GSM247778 4 0.5309 0.918 0.220 0.000 0.000 0.656 0.048 NA
#> GSM247806 3 0.2320 0.892 0.000 0.000 0.864 0.004 0.000 NA
#> GSM247815 1 0.0508 0.940 0.984 0.000 0.000 0.000 0.004 NA
#> GSM247735 2 0.3139 0.843 0.000 0.816 0.000 0.032 0.000 NA
#> GSM247831 5 0.3265 0.962 0.000 0.248 0.000 0.000 0.748 NA
#> GSM247845 4 0.2941 0.929 0.220 0.000 0.000 0.780 0.000 NA
#> GSM247791 3 0.1369 0.892 0.000 0.000 0.952 0.016 0.016 NA
#> GSM247780 1 0.2667 0.896 0.852 0.000 0.000 0.000 0.020 NA
#> GSM247853 1 0.2667 0.896 0.852 0.000 0.000 0.000 0.020 NA
#> GSM247800 2 0.3139 0.843 0.000 0.816 0.000 0.032 0.000 NA
#> GSM247729 5 0.3265 0.962 0.000 0.248 0.000 0.000 0.748 NA
#> GSM247810 4 0.5460 0.915 0.220 0.000 0.000 0.644 0.052 NA
#> GSM247844 3 0.4196 0.869 0.000 0.000 0.756 0.044 0.028 NA
#> GSM247793 1 0.1367 0.935 0.944 0.000 0.000 0.000 0.012 NA
#> GSM247759 2 0.1838 0.894 0.000 0.916 0.000 0.016 0.000 NA
#> GSM247724 5 0.4110 0.954 0.000 0.248 0.000 0.008 0.712 NA
#> GSM247817 3 0.3489 0.872 0.000 0.000 0.708 0.000 0.004 NA
#> GSM247727 1 0.2750 0.896 0.844 0.000 0.000 0.000 0.020 NA
#> GSM247796 2 0.3139 0.843 0.000 0.816 0.000 0.032 0.000 NA
#> GSM247725 5 0.3126 0.962 0.000 0.248 0.000 0.000 0.752 NA
#> GSM247801 4 0.3708 0.924 0.220 0.000 0.000 0.752 0.008 NA
#> GSM247731 3 0.0291 0.896 0.000 0.000 0.992 0.000 0.004 NA
#> GSM247765 1 0.0622 0.938 0.980 0.000 0.000 0.000 0.012 NA
#> GSM247792 2 0.3139 0.843 0.000 0.816 0.000 0.032 0.000 NA
#> GSM247726 5 0.4367 0.947 0.000 0.248 0.000 0.008 0.696 NA
#> GSM247803 5 0.6085 0.512 0.000 0.096 0.000 0.128 0.608 NA
#> GSM247728 3 0.0146 0.896 0.000 0.000 0.996 0.000 0.000 NA
#> GSM247768 1 0.0622 0.938 0.980 0.000 0.000 0.000 0.012 NA
#> GSM247745 2 0.0622 0.892 0.000 0.980 0.000 0.008 0.000 NA
#> GSM247855 2 0.0622 0.892 0.000 0.980 0.000 0.008 0.000 NA
#> GSM247804 5 0.3265 0.962 0.000 0.248 0.000 0.000 0.748 NA
#> GSM247774 4 0.3708 0.924 0.220 0.000 0.000 0.752 0.008 NA
#> GSM247807 3 0.3484 0.890 0.000 0.000 0.784 0.012 0.016 NA
#> GSM247813 1 0.2667 0.896 0.852 0.000 0.000 0.000 0.020 NA
#> GSM247736 2 0.1643 0.894 0.000 0.924 0.000 0.008 0.000 NA
#> GSM247712 5 0.4685 0.939 0.000 0.248 0.000 0.012 0.676 NA
#> GSM247797 4 0.3708 0.924 0.220 0.000 0.000 0.752 0.008 NA
#> GSM247743 3 0.3163 0.882 0.000 0.000 0.764 0.004 0.000 NA
#> GSM247719 1 0.2667 0.898 0.852 0.000 0.000 0.000 0.020 NA
#> GSM247707 2 0.0508 0.892 0.000 0.984 0.000 0.004 0.000 NA
#> GSM247737 5 0.3265 0.962 0.000 0.248 0.000 0.000 0.748 NA
#> GSM247827 3 0.3109 0.883 0.000 0.000 0.772 0.004 0.000 NA
#> GSM247848 1 0.0405 0.939 0.988 0.000 0.000 0.000 0.008 NA
#> GSM247794 2 0.1838 0.894 0.000 0.916 0.000 0.016 0.000 NA
#> GSM247757 5 0.3126 0.962 0.000 0.248 0.000 0.000 0.752 NA
#> GSM247744 4 0.2941 0.929 0.220 0.000 0.000 0.780 0.000 NA
#> GSM247751 3 0.2902 0.892 0.000 0.000 0.800 0.000 0.004 NA
#> GSM247837 1 0.0622 0.938 0.980 0.000 0.000 0.000 0.012 NA
#> GSM247754 2 0.0260 0.894 0.000 0.992 0.000 0.008 0.000 NA
#> GSM247789 5 0.3265 0.962 0.000 0.248 0.000 0.000 0.748 NA
#> GSM247802 4 0.5309 0.918 0.220 0.000 0.000 0.656 0.048 NA
#> GSM247771 3 0.0291 0.896 0.000 0.000 0.992 0.000 0.004 NA
#> GSM247763 1 0.0508 0.940 0.984 0.000 0.000 0.000 0.004 NA
#> GSM247808 2 0.2771 0.856 0.000 0.852 0.000 0.032 0.000 NA
#> GSM247787 5 0.4685 0.939 0.000 0.248 0.000 0.012 0.676 NA
#> GSM247843 4 0.5309 0.918 0.220 0.000 0.000 0.656 0.048 NA
#> GSM247811 3 0.2911 0.878 0.000 0.000 0.872 0.040 0.036 NA
#> GSM247773 1 0.0622 0.940 0.980 0.000 0.000 0.000 0.012 NA
#> GSM247766 2 0.3139 0.843 0.000 0.816 0.000 0.032 0.000 NA
#> GSM247718 5 0.4685 0.939 0.000 0.248 0.000 0.012 0.676 NA
#> GSM247832 4 0.3708 0.924 0.220 0.000 0.000 0.752 0.008 NA
#> GSM247709 3 0.3886 0.869 0.000 0.000 0.796 0.048 0.032 NA
#> GSM247820 1 0.2750 0.896 0.844 0.000 0.000 0.000 0.020 NA
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> ATC:kmeans 153 1 1.000 4.63e-32 2
#> ATC:kmeans 153 1 0.981 2.32e-60 3
#> ATC:kmeans 153 1 0.981 2.32e-60 4
#> ATC:kmeans 153 1 0.998 1.57e-117 5
#> ATC:kmeans 153 1 0.998 1.57e-117 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.751 0.955 0.972 0.4761 0.529 0.529
#> 3 3 0.829 0.871 0.939 0.3812 0.807 0.636
#> 4 4 1.000 1.000 1.000 0.1174 0.890 0.691
#> 5 5 0.908 0.981 0.946 0.0782 0.933 0.747
#> 6 6 0.898 0.973 0.911 0.0238 0.975 0.875
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] 4
There is also optional best \(k\) = 4 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0.0000 0.954 0.000 1.000
#> GSM247854 2 0.0000 0.954 0.000 1.000
#> GSM247758 2 0.5178 0.896 0.116 0.884
#> GSM247742 1 0.0000 1.000 1.000 0.000
#> GSM247755 2 0.0000 0.954 0.000 1.000
#> GSM247841 1 0.0000 1.000 1.000 0.000
#> GSM247703 2 0.0000 0.954 0.000 1.000
#> GSM247739 2 0.6531 0.850 0.168 0.832
#> GSM247715 1 0.0000 1.000 1.000 0.000
#> GSM247829 2 0.0000 0.954 0.000 1.000
#> GSM247842 1 0.0000 1.000 1.000 0.000
#> GSM247805 2 0.0000 0.954 0.000 1.000
#> GSM247786 2 0.6887 0.833 0.184 0.816
#> GSM247812 2 0.0000 0.954 0.000 1.000
#> GSM247776 1 0.0000 1.000 1.000 0.000
#> GSM247850 1 0.0000 1.000 1.000 0.000
#> GSM247717 2 0.0000 0.954 0.000 1.000
#> GSM247784 2 0.5178 0.896 0.116 0.884
#> GSM247834 1 0.0000 1.000 1.000 0.000
#> GSM247783 2 0.0000 0.954 0.000 1.000
#> GSM247846 1 0.0000 1.000 1.000 0.000
#> GSM247822 2 0.0000 0.954 0.000 1.000
#> GSM247710 2 0.6247 0.862 0.156 0.844
#> GSM247713 1 0.0000 1.000 1.000 0.000
#> GSM247840 2 0.0000 0.954 0.000 1.000
#> GSM247733 1 0.0000 1.000 1.000 0.000
#> GSM247852 1 0.0000 1.000 1.000 0.000
#> GSM247790 2 0.0672 0.951 0.008 0.992
#> GSM247730 2 0.5059 0.898 0.112 0.888
#> GSM247824 2 0.0000 0.954 0.000 1.000
#> GSM247770 1 0.0000 1.000 1.000 0.000
#> GSM247711 2 0.0000 0.954 0.000 1.000
#> GSM247782 2 0.6247 0.862 0.156 0.844
#> GSM247836 1 0.0000 1.000 1.000 0.000
#> GSM247785 2 0.0000 0.954 0.000 1.000
#> GSM247847 1 0.0000 1.000 1.000 0.000
#> GSM247750 2 0.0000 0.954 0.000 1.000
#> GSM247788 2 0.5178 0.896 0.116 0.884
#> GSM247849 1 0.0000 1.000 1.000 0.000
#> GSM247772 2 0.0000 0.954 0.000 1.000
#> GSM247760 1 0.0000 1.000 1.000 0.000
#> GSM247764 2 0.0000 0.954 0.000 1.000
#> GSM247851 2 0.0000 0.954 0.000 1.000
#> GSM247714 2 0.5294 0.893 0.120 0.880
#> GSM247828 1 0.0000 1.000 1.000 0.000
#> GSM247704 2 0.0000 0.954 0.000 1.000
#> GSM247818 1 0.0000 1.000 1.000 0.000
#> GSM247823 2 0.0000 0.954 0.000 1.000
#> GSM247706 2 0.6438 0.854 0.164 0.836
#> GSM247835 2 0.0000 0.954 0.000 1.000
#> GSM247734 1 0.0000 1.000 1.000 0.000
#> GSM247819 2 0.0000 0.954 0.000 1.000
#> GSM247809 2 0.5519 0.887 0.128 0.872
#> GSM247830 2 0.0000 0.954 0.000 1.000
#> GSM247833 1 0.0000 1.000 1.000 0.000
#> GSM247738 2 0.0000 0.954 0.000 1.000
#> GSM247716 2 0.7299 0.810 0.204 0.796
#> GSM247747 2 0.0000 0.954 0.000 1.000
#> GSM247722 1 0.0000 1.000 1.000 0.000
#> GSM247816 2 0.0000 0.954 0.000 1.000
#> GSM247839 2 0.6438 0.854 0.164 0.836
#> GSM247821 1 0.0000 1.000 1.000 0.000
#> GSM247798 2 0.0000 0.954 0.000 1.000
#> GSM247838 1 0.0000 1.000 1.000 0.000
#> GSM247721 2 0.0000 0.954 0.000 1.000
#> GSM247781 2 0.5178 0.896 0.116 0.884
#> GSM247762 1 0.0000 1.000 1.000 0.000
#> GSM247825 2 0.0000 0.954 0.000 1.000
#> GSM247777 1 0.0000 1.000 1.000 0.000
#> GSM247761 2 0.0000 0.954 0.000 1.000
#> GSM247720 2 0.7299 0.810 0.204 0.796
#> GSM247814 2 0.0000 0.954 0.000 1.000
#> GSM247732 1 0.0000 1.000 1.000 0.000
#> GSM247708 2 0.0000 0.954 0.000 1.000
#> GSM247740 2 0.7299 0.810 0.204 0.796
#> GSM247749 1 0.0000 1.000 1.000 0.000
#> GSM247767 2 0.0000 0.954 0.000 1.000
#> GSM247748 1 0.0000 1.000 1.000 0.000
#> GSM247705 2 0.0000 0.954 0.000 1.000
#> GSM247746 2 0.5178 0.896 0.116 0.884
#> GSM247752 1 0.0000 1.000 1.000 0.000
#> GSM247769 2 0.0000 0.954 0.000 1.000
#> GSM247753 1 0.0000 1.000 1.000 0.000
#> GSM247723 2 0.0000 0.954 0.000 1.000
#> GSM247779 2 0.5178 0.896 0.116 0.884
#> GSM247756 1 0.0000 1.000 1.000 0.000
#> GSM247826 2 0.0000 0.954 0.000 1.000
#> GSM247775 1 0.0000 1.000 1.000 0.000
#> GSM247741 2 0.0000 0.954 0.000 1.000
#> GSM247799 2 0.7299 0.810 0.204 0.796
#> GSM247778 1 0.0000 1.000 1.000 0.000
#> GSM247806 2 0.0000 0.954 0.000 1.000
#> GSM247815 1 0.0000 1.000 1.000 0.000
#> GSM247735 2 0.0000 0.954 0.000 1.000
#> GSM247831 2 0.5178 0.896 0.116 0.884
#> GSM247845 1 0.0000 1.000 1.000 0.000
#> GSM247791 2 0.0000 0.954 0.000 1.000
#> GSM247780 1 0.0000 1.000 1.000 0.000
#> GSM247853 1 0.0000 1.000 1.000 0.000
#> GSM247800 2 0.0000 0.954 0.000 1.000
#> GSM247729 2 0.5294 0.893 0.120 0.880
#> GSM247810 1 0.0000 1.000 1.000 0.000
#> GSM247844 2 0.0000 0.954 0.000 1.000
#> GSM247793 1 0.0000 1.000 1.000 0.000
#> GSM247759 2 0.0000 0.954 0.000 1.000
#> GSM247724 2 0.7299 0.810 0.204 0.796
#> GSM247817 2 0.0000 0.954 0.000 1.000
#> GSM247727 1 0.0000 1.000 1.000 0.000
#> GSM247796 2 0.0000 0.954 0.000 1.000
#> GSM247725 2 0.5178 0.896 0.116 0.884
#> GSM247801 1 0.0000 1.000 1.000 0.000
#> GSM247731 2 0.0000 0.954 0.000 1.000
#> GSM247765 1 0.0000 1.000 1.000 0.000
#> GSM247792 2 0.0000 0.954 0.000 1.000
#> GSM247726 2 0.0000 0.954 0.000 1.000
#> GSM247803 1 0.0000 1.000 1.000 0.000
#> GSM247728 2 0.0000 0.954 0.000 1.000
#> GSM247768 1 0.0000 1.000 1.000 0.000
#> GSM247745 2 0.0000 0.954 0.000 1.000
#> GSM247855 2 0.0000 0.954 0.000 1.000
#> GSM247804 2 0.5178 0.896 0.116 0.884
#> GSM247774 1 0.0000 1.000 1.000 0.000
#> GSM247807 2 0.0000 0.954 0.000 1.000
#> GSM247813 1 0.0000 1.000 1.000 0.000
#> GSM247736 2 0.0000 0.954 0.000 1.000
#> GSM247712 2 0.7299 0.810 0.204 0.796
#> GSM247797 1 0.0000 1.000 1.000 0.000
#> GSM247743 2 0.0000 0.954 0.000 1.000
#> GSM247719 1 0.0000 1.000 1.000 0.000
#> GSM247707 2 0.0000 0.954 0.000 1.000
#> GSM247737 2 0.5178 0.896 0.116 0.884
#> GSM247827 2 0.0000 0.954 0.000 1.000
#> GSM247848 1 0.0000 1.000 1.000 0.000
#> GSM247794 2 0.0000 0.954 0.000 1.000
#> GSM247757 2 0.5178 0.896 0.116 0.884
#> GSM247744 1 0.0000 1.000 1.000 0.000
#> GSM247751 2 0.0000 0.954 0.000 1.000
#> GSM247837 1 0.0000 1.000 1.000 0.000
#> GSM247754 2 0.0000 0.954 0.000 1.000
#> GSM247789 2 0.5178 0.896 0.116 0.884
#> GSM247802 1 0.0000 1.000 1.000 0.000
#> GSM247771 2 0.0000 0.954 0.000 1.000
#> GSM247763 1 0.0000 1.000 1.000 0.000
#> GSM247808 2 0.0000 0.954 0.000 1.000
#> GSM247787 2 0.6623 0.846 0.172 0.828
#> GSM247843 1 0.0000 1.000 1.000 0.000
#> GSM247811 2 0.0000 0.954 0.000 1.000
#> GSM247773 1 0.0000 1.000 1.000 0.000
#> GSM247766 2 0.0000 0.954 0.000 1.000
#> GSM247718 2 0.0000 0.954 0.000 1.000
#> GSM247832 1 0.0000 1.000 1.000 0.000
#> GSM247709 2 0.0000 0.954 0.000 1.000
#> GSM247820 1 0.0000 1.000 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.610 0.511 0 0.608 0.392
#> GSM247854 2 0.610 0.511 0 0.608 0.392
#> GSM247758 2 0.000 0.839 0 1.000 0.000
#> GSM247742 1 0.000 1.000 1 0.000 0.000
#> GSM247755 3 0.000 0.935 0 0.000 1.000
#> GSM247841 1 0.000 1.000 1 0.000 0.000
#> GSM247703 2 0.000 0.839 0 1.000 0.000
#> GSM247739 2 0.000 0.839 0 1.000 0.000
#> GSM247715 1 0.000 1.000 1 0.000 0.000
#> GSM247829 3 0.000 0.935 0 0.000 1.000
#> GSM247842 1 0.000 1.000 1 0.000 0.000
#> GSM247805 2 0.000 0.839 0 1.000 0.000
#> GSM247786 2 0.000 0.839 0 1.000 0.000
#> GSM247812 3 0.000 0.935 0 0.000 1.000
#> GSM247776 1 0.000 1.000 1 0.000 0.000
#> GSM247850 1 0.000 1.000 1 0.000 0.000
#> GSM247717 2 0.601 0.537 0 0.628 0.372
#> GSM247784 2 0.000 0.839 0 1.000 0.000
#> GSM247834 1 0.000 1.000 1 0.000 0.000
#> GSM247783 3 0.000 0.935 0 0.000 1.000
#> GSM247846 1 0.000 1.000 1 0.000 0.000
#> GSM247822 3 0.475 0.712 0 0.216 0.784
#> GSM247710 2 0.000 0.839 0 1.000 0.000
#> GSM247713 1 0.000 1.000 1 0.000 0.000
#> GSM247840 3 0.000 0.935 0 0.000 1.000
#> GSM247733 1 0.000 1.000 1 0.000 0.000
#> GSM247852 1 0.000 1.000 1 0.000 0.000
#> GSM247790 2 0.000 0.839 0 1.000 0.000
#> GSM247730 2 0.000 0.839 0 1.000 0.000
#> GSM247824 3 0.000 0.935 0 0.000 1.000
#> GSM247770 1 0.000 1.000 1 0.000 0.000
#> GSM247711 2 0.610 0.511 0 0.608 0.392
#> GSM247782 2 0.000 0.839 0 1.000 0.000
#> GSM247836 1 0.000 1.000 1 0.000 0.000
#> GSM247785 3 0.000 0.935 0 0.000 1.000
#> GSM247847 1 0.000 1.000 1 0.000 0.000
#> GSM247750 2 0.000 0.839 0 1.000 0.000
#> GSM247788 2 0.000 0.839 0 1.000 0.000
#> GSM247849 1 0.000 1.000 1 0.000 0.000
#> GSM247772 3 0.000 0.935 0 0.000 1.000
#> GSM247760 1 0.000 1.000 1 0.000 0.000
#> GSM247764 3 0.475 0.712 0 0.216 0.784
#> GSM247851 3 0.475 0.712 0 0.216 0.784
#> GSM247714 2 0.000 0.839 0 1.000 0.000
#> GSM247828 1 0.000 1.000 1 0.000 0.000
#> GSM247704 3 0.000 0.935 0 0.000 1.000
#> GSM247818 1 0.000 1.000 1 0.000 0.000
#> GSM247823 2 0.601 0.537 0 0.628 0.372
#> GSM247706 2 0.000 0.839 0 1.000 0.000
#> GSM247835 3 0.000 0.935 0 0.000 1.000
#> GSM247734 1 0.000 1.000 1 0.000 0.000
#> GSM247819 3 0.475 0.712 0 0.216 0.784
#> GSM247809 2 0.000 0.839 0 1.000 0.000
#> GSM247830 3 0.000 0.935 0 0.000 1.000
#> GSM247833 1 0.000 1.000 1 0.000 0.000
#> GSM247738 2 0.000 0.839 0 1.000 0.000
#> GSM247716 2 0.000 0.839 0 1.000 0.000
#> GSM247747 3 0.000 0.935 0 0.000 1.000
#> GSM247722 1 0.000 1.000 1 0.000 0.000
#> GSM247816 2 0.610 0.511 0 0.608 0.392
#> GSM247839 2 0.000 0.839 0 1.000 0.000
#> GSM247821 1 0.000 1.000 1 0.000 0.000
#> GSM247798 3 0.000 0.935 0 0.000 1.000
#> GSM247838 1 0.000 1.000 1 0.000 0.000
#> GSM247721 2 0.610 0.511 0 0.608 0.392
#> GSM247781 2 0.000 0.839 0 1.000 0.000
#> GSM247762 1 0.000 1.000 1 0.000 0.000
#> GSM247825 3 0.000 0.935 0 0.000 1.000
#> GSM247777 1 0.000 1.000 1 0.000 0.000
#> GSM247761 2 0.540 0.637 0 0.720 0.280
#> GSM247720 2 0.000 0.839 0 1.000 0.000
#> GSM247814 3 0.000 0.935 0 0.000 1.000
#> GSM247732 1 0.000 1.000 1 0.000 0.000
#> GSM247708 2 0.610 0.511 0 0.608 0.392
#> GSM247740 2 0.000 0.839 0 1.000 0.000
#> GSM247749 1 0.000 1.000 1 0.000 0.000
#> GSM247767 3 0.000 0.935 0 0.000 1.000
#> GSM247748 1 0.000 1.000 1 0.000 0.000
#> GSM247705 2 0.610 0.511 0 0.608 0.392
#> GSM247746 2 0.000 0.839 0 1.000 0.000
#> GSM247752 1 0.000 1.000 1 0.000 0.000
#> GSM247769 3 0.000 0.935 0 0.000 1.000
#> GSM247753 1 0.000 1.000 1 0.000 0.000
#> GSM247723 2 0.610 0.511 0 0.608 0.392
#> GSM247779 2 0.000 0.839 0 1.000 0.000
#> GSM247756 1 0.000 1.000 1 0.000 0.000
#> GSM247826 3 0.000 0.935 0 0.000 1.000
#> GSM247775 1 0.000 1.000 1 0.000 0.000
#> GSM247741 2 0.614 0.485 0 0.596 0.404
#> GSM247799 2 0.000 0.839 0 1.000 0.000
#> GSM247778 1 0.000 1.000 1 0.000 0.000
#> GSM247806 3 0.000 0.935 0 0.000 1.000
#> GSM247815 1 0.000 1.000 1 0.000 0.000
#> GSM247735 3 0.475 0.712 0 0.216 0.784
#> GSM247831 2 0.000 0.839 0 1.000 0.000
#> GSM247845 1 0.000 1.000 1 0.000 0.000
#> GSM247791 3 0.000 0.935 0 0.000 1.000
#> GSM247780 1 0.000 1.000 1 0.000 0.000
#> GSM247853 1 0.000 1.000 1 0.000 0.000
#> GSM247800 3 0.475 0.712 0 0.216 0.784
#> GSM247729 2 0.000 0.839 0 1.000 0.000
#> GSM247810 1 0.000 1.000 1 0.000 0.000
#> GSM247844 3 0.000 0.935 0 0.000 1.000
#> GSM247793 1 0.000 1.000 1 0.000 0.000
#> GSM247759 2 0.610 0.511 0 0.608 0.392
#> GSM247724 2 0.000 0.839 0 1.000 0.000
#> GSM247817 3 0.000 0.935 0 0.000 1.000
#> GSM247727 1 0.000 1.000 1 0.000 0.000
#> GSM247796 3 0.475 0.712 0 0.216 0.784
#> GSM247725 2 0.000 0.839 0 1.000 0.000
#> GSM247801 1 0.000 1.000 1 0.000 0.000
#> GSM247731 3 0.000 0.935 0 0.000 1.000
#> GSM247765 1 0.000 1.000 1 0.000 0.000
#> GSM247792 3 0.475 0.712 0 0.216 0.784
#> GSM247726 2 0.000 0.839 0 1.000 0.000
#> GSM247803 1 0.000 1.000 1 0.000 0.000
#> GSM247728 3 0.000 0.935 0 0.000 1.000
#> GSM247768 1 0.000 1.000 1 0.000 0.000
#> GSM247745 2 0.610 0.511 0 0.608 0.392
#> GSM247855 2 0.610 0.511 0 0.608 0.392
#> GSM247804 2 0.000 0.839 0 1.000 0.000
#> GSM247774 1 0.000 1.000 1 0.000 0.000
#> GSM247807 3 0.000 0.935 0 0.000 1.000
#> GSM247813 1 0.000 1.000 1 0.000 0.000
#> GSM247736 2 0.610 0.511 0 0.608 0.392
#> GSM247712 2 0.000 0.839 0 1.000 0.000
#> GSM247797 1 0.000 1.000 1 0.000 0.000
#> GSM247743 3 0.000 0.935 0 0.000 1.000
#> GSM247719 1 0.000 1.000 1 0.000 0.000
#> GSM247707 2 0.610 0.511 0 0.608 0.392
#> GSM247737 2 0.000 0.839 0 1.000 0.000
#> GSM247827 3 0.000 0.935 0 0.000 1.000
#> GSM247848 1 0.000 1.000 1 0.000 0.000
#> GSM247794 2 0.236 0.799 0 0.928 0.072
#> GSM247757 2 0.000 0.839 0 1.000 0.000
#> GSM247744 1 0.000 1.000 1 0.000 0.000
#> GSM247751 3 0.000 0.935 0 0.000 1.000
#> GSM247837 1 0.000 1.000 1 0.000 0.000
#> GSM247754 2 0.610 0.511 0 0.608 0.392
#> GSM247789 2 0.000 0.839 0 1.000 0.000
#> GSM247802 1 0.000 1.000 1 0.000 0.000
#> GSM247771 3 0.000 0.935 0 0.000 1.000
#> GSM247763 1 0.000 1.000 1 0.000 0.000
#> GSM247808 2 0.614 0.485 0 0.596 0.404
#> GSM247787 2 0.000 0.839 0 1.000 0.000
#> GSM247843 1 0.000 1.000 1 0.000 0.000
#> GSM247811 3 0.000 0.935 0 0.000 1.000
#> GSM247773 1 0.000 1.000 1 0.000 0.000
#> GSM247766 3 0.475 0.712 0 0.216 0.784
#> GSM247718 2 0.000 0.839 0 1.000 0.000
#> GSM247832 1 0.000 1.000 1 0.000 0.000
#> GSM247709 3 0.000 0.935 0 0.000 1.000
#> GSM247820 1 0.000 1.000 1 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0 1 0 1 0 0
#> GSM247854 2 0 1 0 1 0 0
#> GSM247758 4 0 1 0 0 0 1
#> GSM247742 1 0 1 1 0 0 0
#> GSM247755 3 0 1 0 0 1 0
#> GSM247841 1 0 1 1 0 0 0
#> GSM247703 2 0 1 0 1 0 0
#> GSM247739 4 0 1 0 0 0 1
#> GSM247715 1 0 1 1 0 0 0
#> GSM247829 3 0 1 0 0 1 0
#> GSM247842 1 0 1 1 0 0 0
#> GSM247805 2 0 1 0 1 0 0
#> GSM247786 4 0 1 0 0 0 1
#> GSM247812 3 0 1 0 0 1 0
#> GSM247776 1 0 1 1 0 0 0
#> GSM247850 1 0 1 1 0 0 0
#> GSM247717 2 0 1 0 1 0 0
#> GSM247784 4 0 1 0 0 0 1
#> GSM247834 1 0 1 1 0 0 0
#> GSM247783 3 0 1 0 0 1 0
#> GSM247846 1 0 1 1 0 0 0
#> GSM247822 2 0 1 0 1 0 0
#> GSM247710 4 0 1 0 0 0 1
#> GSM247713 1 0 1 1 0 0 0
#> GSM247840 3 0 1 0 0 1 0
#> GSM247733 1 0 1 1 0 0 0
#> GSM247852 1 0 1 1 0 0 0
#> GSM247790 2 0 1 0 1 0 0
#> GSM247730 4 0 1 0 0 0 1
#> GSM247824 3 0 1 0 0 1 0
#> GSM247770 1 0 1 1 0 0 0
#> GSM247711 2 0 1 0 1 0 0
#> GSM247782 4 0 1 0 0 0 1
#> GSM247836 1 0 1 1 0 0 0
#> GSM247785 3 0 1 0 0 1 0
#> GSM247847 1 0 1 1 0 0 0
#> GSM247750 2 0 1 0 1 0 0
#> GSM247788 4 0 1 0 0 0 1
#> GSM247849 1 0 1 1 0 0 0
#> GSM247772 3 0 1 0 0 1 0
#> GSM247760 1 0 1 1 0 0 0
#> GSM247764 2 0 1 0 1 0 0
#> GSM247851 2 0 1 0 1 0 0
#> GSM247714 4 0 1 0 0 0 1
#> GSM247828 1 0 1 1 0 0 0
#> GSM247704 3 0 1 0 0 1 0
#> GSM247818 1 0 1 1 0 0 0
#> GSM247823 2 0 1 0 1 0 0
#> GSM247706 4 0 1 0 0 0 1
#> GSM247835 3 0 1 0 0 1 0
#> GSM247734 1 0 1 1 0 0 0
#> GSM247819 2 0 1 0 1 0 0
#> GSM247809 4 0 1 0 0 0 1
#> GSM247830 3 0 1 0 0 1 0
#> GSM247833 1 0 1 1 0 0 0
#> GSM247738 2 0 1 0 1 0 0
#> GSM247716 4 0 1 0 0 0 1
#> GSM247747 3 0 1 0 0 1 0
#> GSM247722 1 0 1 1 0 0 0
#> GSM247816 2 0 1 0 1 0 0
#> GSM247839 4 0 1 0 0 0 1
#> GSM247821 1 0 1 1 0 0 0
#> GSM247798 3 0 1 0 0 1 0
#> GSM247838 1 0 1 1 0 0 0
#> GSM247721 2 0 1 0 1 0 0
#> GSM247781 4 0 1 0 0 0 1
#> GSM247762 1 0 1 1 0 0 0
#> GSM247825 3 0 1 0 0 1 0
#> GSM247777 1 0 1 1 0 0 0
#> GSM247761 2 0 1 0 1 0 0
#> GSM247720 4 0 1 0 0 0 1
#> GSM247814 3 0 1 0 0 1 0
#> GSM247732 1 0 1 1 0 0 0
#> GSM247708 2 0 1 0 1 0 0
#> GSM247740 4 0 1 0 0 0 1
#> GSM247749 1 0 1 1 0 0 0
#> GSM247767 3 0 1 0 0 1 0
#> GSM247748 1 0 1 1 0 0 0
#> GSM247705 2 0 1 0 1 0 0
#> GSM247746 4 0 1 0 0 0 1
#> GSM247752 1 0 1 1 0 0 0
#> GSM247769 3 0 1 0 0 1 0
#> GSM247753 1 0 1 1 0 0 0
#> GSM247723 2 0 1 0 1 0 0
#> GSM247779 4 0 1 0 0 0 1
#> GSM247756 1 0 1 1 0 0 0
#> GSM247826 3 0 1 0 0 1 0
#> GSM247775 1 0 1 1 0 0 0
#> GSM247741 2 0 1 0 1 0 0
#> GSM247799 4 0 1 0 0 0 1
#> GSM247778 1 0 1 1 0 0 0
#> GSM247806 3 0 1 0 0 1 0
#> GSM247815 1 0 1 1 0 0 0
#> GSM247735 2 0 1 0 1 0 0
#> GSM247831 4 0 1 0 0 0 1
#> GSM247845 1 0 1 1 0 0 0
#> GSM247791 3 0 1 0 0 1 0
#> GSM247780 1 0 1 1 0 0 0
#> GSM247853 1 0 1 1 0 0 0
#> GSM247800 2 0 1 0 1 0 0
#> GSM247729 4 0 1 0 0 0 1
#> GSM247810 1 0 1 1 0 0 0
#> GSM247844 3 0 1 0 0 1 0
#> GSM247793 1 0 1 1 0 0 0
#> GSM247759 2 0 1 0 1 0 0
#> GSM247724 4 0 1 0 0 0 1
#> GSM247817 3 0 1 0 0 1 0
#> GSM247727 1 0 1 1 0 0 0
#> GSM247796 2 0 1 0 1 0 0
#> GSM247725 4 0 1 0 0 0 1
#> GSM247801 1 0 1 1 0 0 0
#> GSM247731 3 0 1 0 0 1 0
#> GSM247765 1 0 1 1 0 0 0
#> GSM247792 2 0 1 0 1 0 0
#> GSM247726 4 0 1 0 0 0 1
#> GSM247803 1 0 1 1 0 0 0
#> GSM247728 3 0 1 0 0 1 0
#> GSM247768 1 0 1 1 0 0 0
#> GSM247745 2 0 1 0 1 0 0
#> GSM247855 2 0 1 0 1 0 0
#> GSM247804 4 0 1 0 0 0 1
#> GSM247774 1 0 1 1 0 0 0
#> GSM247807 3 0 1 0 0 1 0
#> GSM247813 1 0 1 1 0 0 0
#> GSM247736 2 0 1 0 1 0 0
#> GSM247712 4 0 1 0 0 0 1
#> GSM247797 1 0 1 1 0 0 0
#> GSM247743 3 0 1 0 0 1 0
#> GSM247719 1 0 1 1 0 0 0
#> GSM247707 2 0 1 0 1 0 0
#> GSM247737 4 0 1 0 0 0 1
#> GSM247827 3 0 1 0 0 1 0
#> GSM247848 1 0 1 1 0 0 0
#> GSM247794 2 0 1 0 1 0 0
#> GSM247757 4 0 1 0 0 0 1
#> GSM247744 1 0 1 1 0 0 0
#> GSM247751 3 0 1 0 0 1 0
#> GSM247837 1 0 1 1 0 0 0
#> GSM247754 2 0 1 0 1 0 0
#> GSM247789 4 0 1 0 0 0 1
#> GSM247802 1 0 1 1 0 0 0
#> GSM247771 3 0 1 0 0 1 0
#> GSM247763 1 0 1 1 0 0 0
#> GSM247808 2 0 1 0 1 0 0
#> GSM247787 4 0 1 0 0 0 1
#> GSM247843 1 0 1 1 0 0 0
#> GSM247811 3 0 1 0 0 1 0
#> GSM247773 1 0 1 1 0 0 0
#> GSM247766 2 0 1 0 1 0 0
#> GSM247718 4 0 1 0 0 0 1
#> GSM247832 1 0 1 1 0 0 0
#> GSM247709 3 0 1 0 0 1 0
#> GSM247820 1 0 1 1 0 0 0
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247854 2 0.029 0.919 0.000 0.992 0 0.008 0.000
#> GSM247758 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247742 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247755 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247841 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247703 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247739 5 0.051 0.990 0.000 0.000 0 0.016 0.984
#> GSM247715 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247829 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247842 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247805 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247786 5 0.051 0.990 0.000 0.000 0 0.016 0.984
#> GSM247812 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247776 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247850 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247717 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247784 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247834 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247783 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247846 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247822 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247710 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247713 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247840 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247733 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247852 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247790 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247730 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247824 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247770 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247711 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247782 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247836 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247785 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247847 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247750 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247788 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247849 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247772 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247760 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247764 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247851 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247714 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247828 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247704 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247818 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247823 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247706 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247835 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247734 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247819 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247809 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247830 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247833 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247738 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247716 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247747 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247722 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247816 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247839 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247821 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247798 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247838 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247721 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247781 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247762 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247825 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247777 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247761 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247720 5 0.051 0.990 0.000 0.000 0 0.016 0.984
#> GSM247814 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247732 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247708 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247740 5 0.051 0.990 0.000 0.000 0 0.016 0.984
#> GSM247749 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247767 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247748 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247705 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247746 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247752 4 0.321 0.990 0.212 0.000 0 0.788 0.000
#> GSM247769 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247753 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247723 2 0.289 0.927 0.000 0.824 0 0.176 0.000
#> GSM247779 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247756 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247826 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247775 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247741 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247799 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247778 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247806 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247815 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247735 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247831 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247845 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247791 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247780 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247853 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247800 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247729 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247810 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247844 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247793 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247759 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247724 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247817 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247727 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247796 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247725 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247801 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247731 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247765 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247792 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247726 5 0.088 0.981 0.000 0.000 0 0.032 0.968
#> GSM247803 4 0.314 0.980 0.204 0.000 0 0.796 0.000
#> GSM247728 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247768 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247745 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247855 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247804 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247774 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247807 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247813 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247736 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247712 5 0.051 0.990 0.000 0.000 0 0.016 0.984
#> GSM247797 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247743 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247719 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247707 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247737 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247827 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247848 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247794 2 0.000 0.919 0.000 1.000 0 0.000 0.000
#> GSM247757 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247744 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247751 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247837 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247754 2 0.289 0.927 0.000 0.824 0 0.176 0.000
#> GSM247789 5 0.000 0.996 0.000 0.000 0 0.000 1.000
#> GSM247802 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247771 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247763 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247808 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247787 5 0.051 0.990 0.000 0.000 0 0.016 0.984
#> GSM247843 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247811 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247773 1 0.000 1.000 1.000 0.000 0 0.000 0.000
#> GSM247766 2 0.300 0.927 0.000 0.812 0 0.188 0.000
#> GSM247718 5 0.051 0.990 0.000 0.000 0 0.016 0.984
#> GSM247832 4 0.327 0.999 0.220 0.000 0 0.780 0.000
#> GSM247709 3 0.000 1.000 0.000 0.000 1 0.000 0.000
#> GSM247820 1 0.000 1.000 1.000 0.000 0 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 6 0.3833 0.979 0.000 0.444 0 0.000 0.000 0.556
#> GSM247854 6 0.3838 0.974 0.000 0.448 0 0.000 0.000 0.552
#> GSM247758 5 0.0260 0.943 0.000 0.000 0 0.008 0.992 0.000
#> GSM247742 4 0.2454 0.983 0.160 0.000 0 0.840 0.000 0.000
#> GSM247755 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247841 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247703 6 0.3810 0.988 0.000 0.428 0 0.000 0.000 0.572
#> GSM247739 5 0.3354 0.868 0.000 0.000 0 0.060 0.812 0.128
#> GSM247715 4 0.2595 0.982 0.160 0.000 0 0.836 0.000 0.004
#> GSM247829 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247842 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247805 6 0.3810 0.988 0.000 0.428 0 0.000 0.000 0.572
#> GSM247786 5 0.3588 0.862 0.000 0.000 0 0.060 0.788 0.152
#> GSM247812 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247776 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247850 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247717 6 0.3810 0.988 0.000 0.428 0 0.000 0.000 0.572
#> GSM247784 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247834 4 0.2595 0.982 0.160 0.000 0 0.836 0.000 0.004
#> GSM247783 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247846 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247822 2 0.0000 0.993 0.000 1.000 0 0.000 0.000 0.000
#> GSM247710 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247713 4 0.2595 0.982 0.160 0.000 0 0.836 0.000 0.004
#> GSM247840 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247733 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247852 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247790 6 0.3810 0.988 0.000 0.428 0 0.000 0.000 0.572
#> GSM247730 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247824 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247770 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247711 2 0.0363 0.984 0.000 0.988 0 0.000 0.000 0.012
#> GSM247782 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247836 4 0.2454 0.983 0.160 0.000 0 0.840 0.000 0.000
#> GSM247785 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247847 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247750 6 0.3823 0.986 0.000 0.436 0 0.000 0.000 0.564
#> GSM247788 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247849 4 0.2454 0.983 0.160 0.000 0 0.840 0.000 0.000
#> GSM247772 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247760 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247764 2 0.0000 0.993 0.000 1.000 0 0.000 0.000 0.000
#> GSM247851 2 0.0000 0.993 0.000 1.000 0 0.000 0.000 0.000
#> GSM247714 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247828 4 0.2454 0.983 0.160 0.000 0 0.840 0.000 0.000
#> GSM247704 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247818 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247823 6 0.3810 0.988 0.000 0.428 0 0.000 0.000 0.572
#> GSM247706 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247835 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247734 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247819 2 0.0000 0.993 0.000 1.000 0 0.000 0.000 0.000
#> GSM247809 5 0.0972 0.938 0.000 0.000 0 0.008 0.964 0.028
#> GSM247830 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247833 1 0.0363 0.992 0.988 0.000 0 0.000 0.000 0.012
#> GSM247738 6 0.3810 0.988 0.000 0.428 0 0.000 0.000 0.572
#> GSM247716 5 0.0972 0.938 0.000 0.000 0 0.008 0.964 0.028
#> GSM247747 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247722 1 0.0363 0.992 0.988 0.000 0 0.000 0.000 0.012
#> GSM247816 6 0.3823 0.986 0.000 0.436 0 0.000 0.000 0.564
#> GSM247839 5 0.0972 0.938 0.000 0.000 0 0.008 0.964 0.028
#> GSM247821 4 0.2595 0.982 0.160 0.000 0 0.836 0.000 0.004
#> GSM247798 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247838 1 0.0363 0.992 0.988 0.000 0 0.000 0.000 0.012
#> GSM247721 6 0.3843 0.967 0.000 0.452 0 0.000 0.000 0.548
#> GSM247781 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247762 4 0.2454 0.983 0.160 0.000 0 0.840 0.000 0.000
#> GSM247825 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247777 1 0.0363 0.992 0.988 0.000 0 0.000 0.000 0.012
#> GSM247761 6 0.3810 0.988 0.000 0.428 0 0.000 0.000 0.572
#> GSM247720 5 0.3588 0.862 0.000 0.000 0 0.060 0.788 0.152
#> GSM247814 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247732 1 0.0363 0.992 0.988 0.000 0 0.000 0.000 0.012
#> GSM247708 2 0.0363 0.984 0.000 0.988 0 0.000 0.000 0.012
#> GSM247740 5 0.3354 0.868 0.000 0.000 0 0.060 0.812 0.128
#> GSM247749 4 0.2595 0.982 0.160 0.000 0 0.836 0.000 0.004
#> GSM247767 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247748 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247705 6 0.3817 0.985 0.000 0.432 0 0.000 0.000 0.568
#> GSM247746 5 0.1049 0.937 0.000 0.000 0 0.008 0.960 0.032
#> GSM247752 4 0.3700 0.933 0.152 0.000 0 0.780 0.000 0.068
#> GSM247769 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247753 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247723 2 0.0146 0.990 0.000 0.996 0 0.000 0.000 0.004
#> GSM247779 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247756 4 0.2454 0.983 0.160 0.000 0 0.840 0.000 0.000
#> GSM247826 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247775 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247741 2 0.0000 0.993 0.000 1.000 0 0.000 0.000 0.000
#> GSM247799 5 0.0972 0.938 0.000 0.000 0 0.008 0.964 0.028
#> GSM247778 4 0.2595 0.982 0.160 0.000 0 0.836 0.000 0.004
#> GSM247806 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247815 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247735 2 0.0000 0.993 0.000 1.000 0 0.000 0.000 0.000
#> GSM247831 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247845 4 0.2454 0.983 0.160 0.000 0 0.840 0.000 0.000
#> GSM247791 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247780 1 0.0363 0.992 0.988 0.000 0 0.000 0.000 0.012
#> GSM247853 1 0.0363 0.992 0.988 0.000 0 0.000 0.000 0.012
#> GSM247800 2 0.0000 0.993 0.000 1.000 0 0.000 0.000 0.000
#> GSM247729 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247810 4 0.2595 0.982 0.160 0.000 0 0.836 0.000 0.004
#> GSM247844 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247793 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247759 6 0.3823 0.986 0.000 0.436 0 0.000 0.000 0.564
#> GSM247724 5 0.0972 0.938 0.000 0.000 0 0.008 0.964 0.028
#> GSM247817 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247727 1 0.0363 0.992 0.988 0.000 0 0.000 0.000 0.012
#> GSM247796 2 0.0000 0.993 0.000 1.000 0 0.000 0.000 0.000
#> GSM247725 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247801 4 0.2454 0.983 0.160 0.000 0 0.840 0.000 0.000
#> GSM247731 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247765 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247792 2 0.0000 0.993 0.000 1.000 0 0.000 0.000 0.000
#> GSM247726 5 0.5645 0.522 0.000 0.000 0 0.152 0.456 0.392
#> GSM247803 4 0.4382 0.664 0.060 0.000 0 0.676 0.000 0.264
#> GSM247728 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247768 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247745 2 0.0363 0.984 0.000 0.988 0 0.000 0.000 0.012
#> GSM247855 2 0.0363 0.984 0.000 0.988 0 0.000 0.000 0.012
#> GSM247804 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247774 4 0.2454 0.983 0.160 0.000 0 0.840 0.000 0.000
#> GSM247807 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247813 1 0.0363 0.992 0.988 0.000 0 0.000 0.000 0.012
#> GSM247736 6 0.3833 0.979 0.000 0.444 0 0.000 0.000 0.556
#> GSM247712 5 0.3588 0.862 0.000 0.000 0 0.060 0.788 0.152
#> GSM247797 4 0.2454 0.983 0.160 0.000 0 0.840 0.000 0.000
#> GSM247743 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247719 1 0.0363 0.992 0.988 0.000 0 0.000 0.000 0.012
#> GSM247707 2 0.0363 0.984 0.000 0.988 0 0.000 0.000 0.012
#> GSM247737 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247827 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247848 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247794 6 0.3810 0.988 0.000 0.428 0 0.000 0.000 0.572
#> GSM247757 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247744 4 0.2454 0.983 0.160 0.000 0 0.840 0.000 0.000
#> GSM247751 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247837 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247754 2 0.0260 0.988 0.000 0.992 0 0.000 0.000 0.008
#> GSM247789 5 0.0000 0.944 0.000 0.000 0 0.000 1.000 0.000
#> GSM247802 4 0.2595 0.982 0.160 0.000 0 0.836 0.000 0.004
#> GSM247771 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247763 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247808 2 0.0000 0.993 0.000 1.000 0 0.000 0.000 0.000
#> GSM247787 5 0.3588 0.862 0.000 0.000 0 0.060 0.788 0.152
#> GSM247843 4 0.2595 0.982 0.160 0.000 0 0.836 0.000 0.004
#> GSM247811 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247773 1 0.0000 0.996 1.000 0.000 0 0.000 0.000 0.000
#> GSM247766 2 0.0000 0.993 0.000 1.000 0 0.000 0.000 0.000
#> GSM247718 5 0.3588 0.862 0.000 0.000 0 0.060 0.788 0.152
#> GSM247832 4 0.2454 0.983 0.160 0.000 0 0.840 0.000 0.000
#> GSM247709 3 0.0000 1.000 0.000 0.000 1 0.000 0.000 0.000
#> GSM247820 1 0.0363 0.992 0.988 0.000 0 0.000 0.000 0.012
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> ATC:skmeans 153 1 1.000 4.63e-32 2
#> ATC:skmeans 151 1 0.900 1.67e-51 3
#> ATC:skmeans 153 1 0.996 1.16e-90 4
#> ATC:skmeans 153 1 0.989 6.51e-120 5
#> ATC:skmeans 153 1 0.981 8.52e-117 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.506 0.783 0.793 0.3996 0.533 0.533
#> 3 3 1.000 0.996 0.999 0.6095 0.824 0.670
#> 4 4 1.000 0.997 0.999 0.1463 0.906 0.738
#> 5 5 1.000 0.995 0.998 0.0860 0.936 0.756
#> 6 6 1.000 0.989 0.996 0.0275 0.978 0.891
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 4 5
There is also optional best \(k\) = 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0.000 0.702 0.00 1.00
#> GSM247854 2 0.000 0.702 0.00 1.00
#> GSM247758 2 0.000 0.702 0.00 1.00
#> GSM247742 1 0.999 1.000 0.52 0.48
#> GSM247755 2 0.999 0.563 0.48 0.52
#> GSM247841 1 0.999 1.000 0.52 0.48
#> GSM247703 2 0.000 0.702 0.00 1.00
#> GSM247739 2 0.000 0.702 0.00 1.00
#> GSM247715 1 0.999 1.000 0.52 0.48
#> GSM247829 2 0.999 0.563 0.48 0.52
#> GSM247842 1 0.999 1.000 0.52 0.48
#> GSM247805 2 0.000 0.702 0.00 1.00
#> GSM247786 2 0.000 0.702 0.00 1.00
#> GSM247812 2 0.999 0.563 0.48 0.52
#> GSM247776 1 0.999 1.000 0.52 0.48
#> GSM247850 1 0.999 1.000 0.52 0.48
#> GSM247717 2 0.000 0.702 0.00 1.00
#> GSM247784 2 0.000 0.702 0.00 1.00
#> GSM247834 1 0.999 1.000 0.52 0.48
#> GSM247783 2 0.999 0.563 0.48 0.52
#> GSM247846 1 0.999 1.000 0.52 0.48
#> GSM247822 2 0.000 0.702 0.00 1.00
#> GSM247710 2 0.000 0.702 0.00 1.00
#> GSM247713 1 0.999 1.000 0.52 0.48
#> GSM247840 2 0.999 0.563 0.48 0.52
#> GSM247733 1 0.999 1.000 0.52 0.48
#> GSM247852 1 0.999 1.000 0.52 0.48
#> GSM247790 2 0.000 0.702 0.00 1.00
#> GSM247730 2 0.000 0.702 0.00 1.00
#> GSM247824 2 0.999 0.563 0.48 0.52
#> GSM247770 1 0.999 1.000 0.52 0.48
#> GSM247711 2 0.000 0.702 0.00 1.00
#> GSM247782 2 0.000 0.702 0.00 1.00
#> GSM247836 1 0.999 1.000 0.52 0.48
#> GSM247785 2 0.999 0.563 0.48 0.52
#> GSM247847 1 0.999 1.000 0.52 0.48
#> GSM247750 2 0.000 0.702 0.00 1.00
#> GSM247788 2 0.000 0.702 0.00 1.00
#> GSM247849 1 0.999 1.000 0.52 0.48
#> GSM247772 2 0.999 0.563 0.48 0.52
#> GSM247760 1 0.999 1.000 0.52 0.48
#> GSM247764 2 0.000 0.702 0.00 1.00
#> GSM247851 2 0.000 0.702 0.00 1.00
#> GSM247714 2 0.000 0.702 0.00 1.00
#> GSM247828 1 0.999 1.000 0.52 0.48
#> GSM247704 2 0.999 0.563 0.48 0.52
#> GSM247818 1 0.999 1.000 0.52 0.48
#> GSM247823 2 0.000 0.702 0.00 1.00
#> GSM247706 2 0.000 0.702 0.00 1.00
#> GSM247835 2 0.999 0.563 0.48 0.52
#> GSM247734 1 0.999 1.000 0.52 0.48
#> GSM247819 2 0.000 0.702 0.00 1.00
#> GSM247809 2 0.000 0.702 0.00 1.00
#> GSM247830 2 0.999 0.563 0.48 0.52
#> GSM247833 1 0.999 1.000 0.52 0.48
#> GSM247738 2 0.000 0.702 0.00 1.00
#> GSM247716 2 0.000 0.702 0.00 1.00
#> GSM247747 2 0.999 0.563 0.48 0.52
#> GSM247722 1 0.999 1.000 0.52 0.48
#> GSM247816 2 0.000 0.702 0.00 1.00
#> GSM247839 2 0.000 0.702 0.00 1.00
#> GSM247821 1 0.999 1.000 0.52 0.48
#> GSM247798 2 0.999 0.563 0.48 0.52
#> GSM247838 1 0.999 1.000 0.52 0.48
#> GSM247721 2 0.000 0.702 0.00 1.00
#> GSM247781 2 0.000 0.702 0.00 1.00
#> GSM247762 1 0.999 1.000 0.52 0.48
#> GSM247825 2 0.999 0.563 0.48 0.52
#> GSM247777 1 0.999 1.000 0.52 0.48
#> GSM247761 2 0.000 0.702 0.00 1.00
#> GSM247720 2 0.000 0.702 0.00 1.00
#> GSM247814 2 0.999 0.563 0.48 0.52
#> GSM247732 1 0.999 1.000 0.52 0.48
#> GSM247708 2 0.000 0.702 0.00 1.00
#> GSM247740 2 0.000 0.702 0.00 1.00
#> GSM247749 1 0.999 1.000 0.52 0.48
#> GSM247767 2 0.999 0.563 0.48 0.52
#> GSM247748 1 0.999 1.000 0.52 0.48
#> GSM247705 2 0.000 0.702 0.00 1.00
#> GSM247746 2 0.000 0.702 0.00 1.00
#> GSM247752 1 0.999 1.000 0.52 0.48
#> GSM247769 2 0.999 0.563 0.48 0.52
#> GSM247753 1 0.999 1.000 0.52 0.48
#> GSM247723 2 0.000 0.702 0.00 1.00
#> GSM247779 2 0.000 0.702 0.00 1.00
#> GSM247756 1 0.999 1.000 0.52 0.48
#> GSM247826 2 0.999 0.563 0.48 0.52
#> GSM247775 1 0.999 1.000 0.52 0.48
#> GSM247741 2 0.000 0.702 0.00 1.00
#> GSM247799 2 0.000 0.702 0.00 1.00
#> GSM247778 1 0.999 1.000 0.52 0.48
#> GSM247806 2 0.999 0.563 0.48 0.52
#> GSM247815 1 0.999 1.000 0.52 0.48
#> GSM247735 2 0.000 0.702 0.00 1.00
#> GSM247831 2 0.000 0.702 0.00 1.00
#> GSM247845 1 0.999 1.000 0.52 0.48
#> GSM247791 2 0.999 0.563 0.48 0.52
#> GSM247780 1 0.999 1.000 0.52 0.48
#> GSM247853 1 0.999 1.000 0.52 0.48
#> GSM247800 2 0.000 0.702 0.00 1.00
#> GSM247729 2 0.000 0.702 0.00 1.00
#> GSM247810 1 0.999 1.000 0.52 0.48
#> GSM247844 2 0.999 0.563 0.48 0.52
#> GSM247793 1 0.999 1.000 0.52 0.48
#> GSM247759 2 0.000 0.702 0.00 1.00
#> GSM247724 2 0.000 0.702 0.00 1.00
#> GSM247817 2 0.999 0.563 0.48 0.52
#> GSM247727 1 0.999 1.000 0.52 0.48
#> GSM247796 2 0.000 0.702 0.00 1.00
#> GSM247725 2 0.000 0.702 0.00 1.00
#> GSM247801 1 0.999 1.000 0.52 0.48
#> GSM247731 2 0.999 0.563 0.48 0.52
#> GSM247765 1 0.999 1.000 0.52 0.48
#> GSM247792 2 0.000 0.702 0.00 1.00
#> GSM247726 2 0.000 0.702 0.00 1.00
#> GSM247803 2 0.000 0.702 0.00 1.00
#> GSM247728 2 0.999 0.563 0.48 0.52
#> GSM247768 1 0.999 1.000 0.52 0.48
#> GSM247745 2 0.000 0.702 0.00 1.00
#> GSM247855 2 0.000 0.702 0.00 1.00
#> GSM247804 2 0.000 0.702 0.00 1.00
#> GSM247774 1 0.999 1.000 0.52 0.48
#> GSM247807 2 0.999 0.563 0.48 0.52
#> GSM247813 1 0.999 1.000 0.52 0.48
#> GSM247736 2 0.000 0.702 0.00 1.00
#> GSM247712 2 0.000 0.702 0.00 1.00
#> GSM247797 1 0.999 1.000 0.52 0.48
#> GSM247743 2 0.999 0.563 0.48 0.52
#> GSM247719 1 0.999 1.000 0.52 0.48
#> GSM247707 2 0.000 0.702 0.00 1.00
#> GSM247737 2 0.000 0.702 0.00 1.00
#> GSM247827 2 0.999 0.563 0.48 0.52
#> GSM247848 1 0.999 1.000 0.52 0.48
#> GSM247794 2 0.000 0.702 0.00 1.00
#> GSM247757 2 0.000 0.702 0.00 1.00
#> GSM247744 1 0.999 1.000 0.52 0.48
#> GSM247751 2 0.999 0.563 0.48 0.52
#> GSM247837 1 0.999 1.000 0.52 0.48
#> GSM247754 2 0.000 0.702 0.00 1.00
#> GSM247789 2 0.000 0.702 0.00 1.00
#> GSM247802 1 0.999 1.000 0.52 0.48
#> GSM247771 2 0.999 0.563 0.48 0.52
#> GSM247763 1 0.999 1.000 0.52 0.48
#> GSM247808 2 0.000 0.702 0.00 1.00
#> GSM247787 2 0.000 0.702 0.00 1.00
#> GSM247843 1 0.999 1.000 0.52 0.48
#> GSM247811 2 0.999 0.563 0.48 0.52
#> GSM247773 1 0.999 1.000 0.52 0.48
#> GSM247766 2 0.000 0.702 0.00 1.00
#> GSM247718 2 0.000 0.702 0.00 1.00
#> GSM247832 1 0.999 1.000 0.52 0.48
#> GSM247709 2 0.999 0.563 0.48 0.52
#> GSM247820 1 0.999 1.000 0.52 0.48
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.000 1.000 0.000 1.000 0
#> GSM247854 2 0.000 1.000 0.000 1.000 0
#> GSM247758 2 0.000 1.000 0.000 1.000 0
#> GSM247742 1 0.000 0.995 1.000 0.000 0
#> GSM247755 3 0.000 1.000 0.000 0.000 1
#> GSM247841 1 0.000 0.995 1.000 0.000 0
#> GSM247703 2 0.000 1.000 0.000 1.000 0
#> GSM247739 2 0.000 1.000 0.000 1.000 0
#> GSM247715 1 0.000 0.995 1.000 0.000 0
#> GSM247829 3 0.000 1.000 0.000 0.000 1
#> GSM247842 1 0.000 0.995 1.000 0.000 0
#> GSM247805 2 0.000 1.000 0.000 1.000 0
#> GSM247786 2 0.000 1.000 0.000 1.000 0
#> GSM247812 3 0.000 1.000 0.000 0.000 1
#> GSM247776 1 0.000 0.995 1.000 0.000 0
#> GSM247850 1 0.000 0.995 1.000 0.000 0
#> GSM247717 2 0.000 1.000 0.000 1.000 0
#> GSM247784 2 0.000 1.000 0.000 1.000 0
#> GSM247834 1 0.000 0.995 1.000 0.000 0
#> GSM247783 3 0.000 1.000 0.000 0.000 1
#> GSM247846 1 0.000 0.995 1.000 0.000 0
#> GSM247822 2 0.000 1.000 0.000 1.000 0
#> GSM247710 2 0.000 1.000 0.000 1.000 0
#> GSM247713 1 0.000 0.995 1.000 0.000 0
#> GSM247840 3 0.000 1.000 0.000 0.000 1
#> GSM247733 1 0.000 0.995 1.000 0.000 0
#> GSM247852 1 0.000 0.995 1.000 0.000 0
#> GSM247790 2 0.000 1.000 0.000 1.000 0
#> GSM247730 2 0.000 1.000 0.000 1.000 0
#> GSM247824 3 0.000 1.000 0.000 0.000 1
#> GSM247770 1 0.000 0.995 1.000 0.000 0
#> GSM247711 2 0.000 1.000 0.000 1.000 0
#> GSM247782 2 0.000 1.000 0.000 1.000 0
#> GSM247836 1 0.000 0.995 1.000 0.000 0
#> GSM247785 3 0.000 1.000 0.000 0.000 1
#> GSM247847 1 0.000 0.995 1.000 0.000 0
#> GSM247750 2 0.000 1.000 0.000 1.000 0
#> GSM247788 2 0.000 1.000 0.000 1.000 0
#> GSM247849 1 0.000 0.995 1.000 0.000 0
#> GSM247772 3 0.000 1.000 0.000 0.000 1
#> GSM247760 1 0.000 0.995 1.000 0.000 0
#> GSM247764 2 0.000 1.000 0.000 1.000 0
#> GSM247851 2 0.000 1.000 0.000 1.000 0
#> GSM247714 2 0.000 1.000 0.000 1.000 0
#> GSM247828 1 0.000 0.995 1.000 0.000 0
#> GSM247704 3 0.000 1.000 0.000 0.000 1
#> GSM247818 1 0.000 0.995 1.000 0.000 0
#> GSM247823 2 0.000 1.000 0.000 1.000 0
#> GSM247706 2 0.000 1.000 0.000 1.000 0
#> GSM247835 3 0.000 1.000 0.000 0.000 1
#> GSM247734 1 0.000 0.995 1.000 0.000 0
#> GSM247819 2 0.000 1.000 0.000 1.000 0
#> GSM247809 2 0.000 1.000 0.000 1.000 0
#> GSM247830 3 0.000 1.000 0.000 0.000 1
#> GSM247833 1 0.000 0.995 1.000 0.000 0
#> GSM247738 2 0.000 1.000 0.000 1.000 0
#> GSM247716 2 0.000 1.000 0.000 1.000 0
#> GSM247747 3 0.000 1.000 0.000 0.000 1
#> GSM247722 1 0.000 0.995 1.000 0.000 0
#> GSM247816 2 0.000 1.000 0.000 1.000 0
#> GSM247839 2 0.000 1.000 0.000 1.000 0
#> GSM247821 1 0.000 0.995 1.000 0.000 0
#> GSM247798 3 0.000 1.000 0.000 0.000 1
#> GSM247838 1 0.000 0.995 1.000 0.000 0
#> GSM247721 2 0.000 1.000 0.000 1.000 0
#> GSM247781 2 0.000 1.000 0.000 1.000 0
#> GSM247762 1 0.000 0.995 1.000 0.000 0
#> GSM247825 3 0.000 1.000 0.000 0.000 1
#> GSM247777 1 0.000 0.995 1.000 0.000 0
#> GSM247761 2 0.000 1.000 0.000 1.000 0
#> GSM247720 2 0.000 1.000 0.000 1.000 0
#> GSM247814 3 0.000 1.000 0.000 0.000 1
#> GSM247732 1 0.000 0.995 1.000 0.000 0
#> GSM247708 2 0.000 1.000 0.000 1.000 0
#> GSM247740 2 0.000 1.000 0.000 1.000 0
#> GSM247749 1 0.000 0.995 1.000 0.000 0
#> GSM247767 3 0.000 1.000 0.000 0.000 1
#> GSM247748 1 0.000 0.995 1.000 0.000 0
#> GSM247705 2 0.000 1.000 0.000 1.000 0
#> GSM247746 2 0.000 1.000 0.000 1.000 0
#> GSM247752 1 0.489 0.695 0.772 0.228 0
#> GSM247769 3 0.000 1.000 0.000 0.000 1
#> GSM247753 1 0.000 0.995 1.000 0.000 0
#> GSM247723 2 0.000 1.000 0.000 1.000 0
#> GSM247779 2 0.000 1.000 0.000 1.000 0
#> GSM247756 1 0.000 0.995 1.000 0.000 0
#> GSM247826 3 0.000 1.000 0.000 0.000 1
#> GSM247775 1 0.000 0.995 1.000 0.000 0
#> GSM247741 2 0.000 1.000 0.000 1.000 0
#> GSM247799 2 0.000 1.000 0.000 1.000 0
#> GSM247778 1 0.000 0.995 1.000 0.000 0
#> GSM247806 3 0.000 1.000 0.000 0.000 1
#> GSM247815 1 0.000 0.995 1.000 0.000 0
#> GSM247735 2 0.000 1.000 0.000 1.000 0
#> GSM247831 2 0.000 1.000 0.000 1.000 0
#> GSM247845 1 0.000 0.995 1.000 0.000 0
#> GSM247791 3 0.000 1.000 0.000 0.000 1
#> GSM247780 1 0.000 0.995 1.000 0.000 0
#> GSM247853 1 0.000 0.995 1.000 0.000 0
#> GSM247800 2 0.000 1.000 0.000 1.000 0
#> GSM247729 2 0.000 1.000 0.000 1.000 0
#> GSM247810 1 0.000 0.995 1.000 0.000 0
#> GSM247844 3 0.000 1.000 0.000 0.000 1
#> GSM247793 1 0.000 0.995 1.000 0.000 0
#> GSM247759 2 0.000 1.000 0.000 1.000 0
#> GSM247724 2 0.000 1.000 0.000 1.000 0
#> GSM247817 3 0.000 1.000 0.000 0.000 1
#> GSM247727 1 0.000 0.995 1.000 0.000 0
#> GSM247796 2 0.000 1.000 0.000 1.000 0
#> GSM247725 2 0.000 1.000 0.000 1.000 0
#> GSM247801 1 0.000 0.995 1.000 0.000 0
#> GSM247731 3 0.000 1.000 0.000 0.000 1
#> GSM247765 1 0.000 0.995 1.000 0.000 0
#> GSM247792 2 0.000 1.000 0.000 1.000 0
#> GSM247726 2 0.000 1.000 0.000 1.000 0
#> GSM247803 2 0.000 1.000 0.000 1.000 0
#> GSM247728 3 0.000 1.000 0.000 0.000 1
#> GSM247768 1 0.000 0.995 1.000 0.000 0
#> GSM247745 2 0.000 1.000 0.000 1.000 0
#> GSM247855 2 0.000 1.000 0.000 1.000 0
#> GSM247804 2 0.000 1.000 0.000 1.000 0
#> GSM247774 1 0.000 0.995 1.000 0.000 0
#> GSM247807 3 0.000 1.000 0.000 0.000 1
#> GSM247813 1 0.000 0.995 1.000 0.000 0
#> GSM247736 2 0.000 1.000 0.000 1.000 0
#> GSM247712 2 0.000 1.000 0.000 1.000 0
#> GSM247797 1 0.000 0.995 1.000 0.000 0
#> GSM247743 3 0.000 1.000 0.000 0.000 1
#> GSM247719 1 0.000 0.995 1.000 0.000 0
#> GSM247707 2 0.000 1.000 0.000 1.000 0
#> GSM247737 2 0.000 1.000 0.000 1.000 0
#> GSM247827 3 0.000 1.000 0.000 0.000 1
#> GSM247848 1 0.000 0.995 1.000 0.000 0
#> GSM247794 2 0.000 1.000 0.000 1.000 0
#> GSM247757 2 0.000 1.000 0.000 1.000 0
#> GSM247744 1 0.000 0.995 1.000 0.000 0
#> GSM247751 3 0.000 1.000 0.000 0.000 1
#> GSM247837 1 0.000 0.995 1.000 0.000 0
#> GSM247754 2 0.000 1.000 0.000 1.000 0
#> GSM247789 2 0.000 1.000 0.000 1.000 0
#> GSM247802 1 0.000 0.995 1.000 0.000 0
#> GSM247771 3 0.000 1.000 0.000 0.000 1
#> GSM247763 1 0.000 0.995 1.000 0.000 0
#> GSM247808 2 0.000 1.000 0.000 1.000 0
#> GSM247787 2 0.000 1.000 0.000 1.000 0
#> GSM247843 1 0.000 0.995 1.000 0.000 0
#> GSM247811 3 0.000 1.000 0.000 0.000 1
#> GSM247773 1 0.000 0.995 1.000 0.000 0
#> GSM247766 2 0.000 1.000 0.000 1.000 0
#> GSM247718 2 0.000 1.000 0.000 1.000 0
#> GSM247832 1 0.000 0.995 1.000 0.000 0
#> GSM247709 3 0.000 1.000 0.000 0.000 1
#> GSM247820 1 0.000 0.995 1.000 0.000 0
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.000 1.000 0.000 1 0 0.000
#> GSM247854 2 0.000 1.000 0.000 1 0 0.000
#> GSM247758 4 0.000 1.000 0.000 0 0 1.000
#> GSM247742 1 0.000 0.996 1.000 0 0 0.000
#> GSM247755 3 0.000 1.000 0.000 0 1 0.000
#> GSM247841 1 0.000 0.996 1.000 0 0 0.000
#> GSM247703 2 0.000 1.000 0.000 1 0 0.000
#> GSM247739 4 0.000 1.000 0.000 0 0 1.000
#> GSM247715 1 0.000 0.996 1.000 0 0 0.000
#> GSM247829 3 0.000 1.000 0.000 0 1 0.000
#> GSM247842 1 0.000 0.996 1.000 0 0 0.000
#> GSM247805 2 0.000 1.000 0.000 1 0 0.000
#> GSM247786 4 0.000 1.000 0.000 0 0 1.000
#> GSM247812 3 0.000 1.000 0.000 0 1 0.000
#> GSM247776 1 0.000 0.996 1.000 0 0 0.000
#> GSM247850 1 0.000 0.996 1.000 0 0 0.000
#> GSM247717 2 0.000 1.000 0.000 1 0 0.000
#> GSM247784 4 0.000 1.000 0.000 0 0 1.000
#> GSM247834 1 0.000 0.996 1.000 0 0 0.000
#> GSM247783 3 0.000 1.000 0.000 0 1 0.000
#> GSM247846 1 0.000 0.996 1.000 0 0 0.000
#> GSM247822 2 0.000 1.000 0.000 1 0 0.000
#> GSM247710 4 0.000 1.000 0.000 0 0 1.000
#> GSM247713 1 0.000 0.996 1.000 0 0 0.000
#> GSM247840 3 0.000 1.000 0.000 0 1 0.000
#> GSM247733 1 0.000 0.996 1.000 0 0 0.000
#> GSM247852 1 0.000 0.996 1.000 0 0 0.000
#> GSM247790 2 0.000 1.000 0.000 1 0 0.000
#> GSM247730 4 0.000 1.000 0.000 0 0 1.000
#> GSM247824 3 0.000 1.000 0.000 0 1 0.000
#> GSM247770 1 0.000 0.996 1.000 0 0 0.000
#> GSM247711 2 0.000 1.000 0.000 1 0 0.000
#> GSM247782 4 0.000 1.000 0.000 0 0 1.000
#> GSM247836 1 0.000 0.996 1.000 0 0 0.000
#> GSM247785 3 0.000 1.000 0.000 0 1 0.000
#> GSM247847 1 0.000 0.996 1.000 0 0 0.000
#> GSM247750 2 0.000 1.000 0.000 1 0 0.000
#> GSM247788 4 0.000 1.000 0.000 0 0 1.000
#> GSM247849 1 0.000 0.996 1.000 0 0 0.000
#> GSM247772 3 0.000 1.000 0.000 0 1 0.000
#> GSM247760 1 0.000 0.996 1.000 0 0 0.000
#> GSM247764 2 0.000 1.000 0.000 1 0 0.000
#> GSM247851 2 0.000 1.000 0.000 1 0 0.000
#> GSM247714 4 0.000 1.000 0.000 0 0 1.000
#> GSM247828 1 0.000 0.996 1.000 0 0 0.000
#> GSM247704 3 0.000 1.000 0.000 0 1 0.000
#> GSM247818 1 0.000 0.996 1.000 0 0 0.000
#> GSM247823 2 0.000 1.000 0.000 1 0 0.000
#> GSM247706 4 0.000 1.000 0.000 0 0 1.000
#> GSM247835 3 0.000 1.000 0.000 0 1 0.000
#> GSM247734 1 0.000 0.996 1.000 0 0 0.000
#> GSM247819 2 0.000 1.000 0.000 1 0 0.000
#> GSM247809 4 0.000 1.000 0.000 0 0 1.000
#> GSM247830 3 0.000 1.000 0.000 0 1 0.000
#> GSM247833 1 0.000 0.996 1.000 0 0 0.000
#> GSM247738 2 0.000 1.000 0.000 1 0 0.000
#> GSM247716 4 0.000 1.000 0.000 0 0 1.000
#> GSM247747 3 0.000 1.000 0.000 0 1 0.000
#> GSM247722 1 0.000 0.996 1.000 0 0 0.000
#> GSM247816 2 0.000 1.000 0.000 1 0 0.000
#> GSM247839 4 0.000 1.000 0.000 0 0 1.000
#> GSM247821 1 0.000 0.996 1.000 0 0 0.000
#> GSM247798 3 0.000 1.000 0.000 0 1 0.000
#> GSM247838 1 0.000 0.996 1.000 0 0 0.000
#> GSM247721 2 0.000 1.000 0.000 1 0 0.000
#> GSM247781 4 0.000 1.000 0.000 0 0 1.000
#> GSM247762 1 0.000 0.996 1.000 0 0 0.000
#> GSM247825 3 0.000 1.000 0.000 0 1 0.000
#> GSM247777 1 0.000 0.996 1.000 0 0 0.000
#> GSM247761 2 0.000 1.000 0.000 1 0 0.000
#> GSM247720 4 0.000 1.000 0.000 0 0 1.000
#> GSM247814 3 0.000 1.000 0.000 0 1 0.000
#> GSM247732 1 0.000 0.996 1.000 0 0 0.000
#> GSM247708 2 0.000 1.000 0.000 1 0 0.000
#> GSM247740 4 0.000 1.000 0.000 0 0 1.000
#> GSM247749 1 0.000 0.996 1.000 0 0 0.000
#> GSM247767 3 0.000 1.000 0.000 0 1 0.000
#> GSM247748 1 0.000 0.996 1.000 0 0 0.000
#> GSM247705 2 0.000 1.000 0.000 1 0 0.000
#> GSM247746 4 0.000 1.000 0.000 0 0 1.000
#> GSM247752 1 0.387 0.705 0.772 0 0 0.228
#> GSM247769 3 0.000 1.000 0.000 0 1 0.000
#> GSM247753 1 0.000 0.996 1.000 0 0 0.000
#> GSM247723 2 0.000 1.000 0.000 1 0 0.000
#> GSM247779 4 0.000 1.000 0.000 0 0 1.000
#> GSM247756 1 0.000 0.996 1.000 0 0 0.000
#> GSM247826 3 0.000 1.000 0.000 0 1 0.000
#> GSM247775 1 0.000 0.996 1.000 0 0 0.000
#> GSM247741 2 0.000 1.000 0.000 1 0 0.000
#> GSM247799 4 0.000 1.000 0.000 0 0 1.000
#> GSM247778 1 0.000 0.996 1.000 0 0 0.000
#> GSM247806 3 0.000 1.000 0.000 0 1 0.000
#> GSM247815 1 0.000 0.996 1.000 0 0 0.000
#> GSM247735 2 0.000 1.000 0.000 1 0 0.000
#> GSM247831 4 0.000 1.000 0.000 0 0 1.000
#> GSM247845 1 0.000 0.996 1.000 0 0 0.000
#> GSM247791 3 0.000 1.000 0.000 0 1 0.000
#> GSM247780 1 0.000 0.996 1.000 0 0 0.000
#> GSM247853 1 0.000 0.996 1.000 0 0 0.000
#> GSM247800 2 0.000 1.000 0.000 1 0 0.000
#> GSM247729 4 0.000 1.000 0.000 0 0 1.000
#> GSM247810 1 0.000 0.996 1.000 0 0 0.000
#> GSM247844 3 0.000 1.000 0.000 0 1 0.000
#> GSM247793 1 0.000 0.996 1.000 0 0 0.000
#> GSM247759 2 0.000 1.000 0.000 1 0 0.000
#> GSM247724 4 0.000 1.000 0.000 0 0 1.000
#> GSM247817 3 0.000 1.000 0.000 0 1 0.000
#> GSM247727 1 0.000 0.996 1.000 0 0 0.000
#> GSM247796 2 0.000 1.000 0.000 1 0 0.000
#> GSM247725 4 0.000 1.000 0.000 0 0 1.000
#> GSM247801 1 0.000 0.996 1.000 0 0 0.000
#> GSM247731 3 0.000 1.000 0.000 0 1 0.000
#> GSM247765 1 0.000 0.996 1.000 0 0 0.000
#> GSM247792 2 0.000 1.000 0.000 1 0 0.000
#> GSM247726 4 0.000 1.000 0.000 0 0 1.000
#> GSM247803 4 0.000 1.000 0.000 0 0 1.000
#> GSM247728 3 0.000 1.000 0.000 0 1 0.000
#> GSM247768 1 0.000 0.996 1.000 0 0 0.000
#> GSM247745 2 0.000 1.000 0.000 1 0 0.000
#> GSM247855 2 0.000 1.000 0.000 1 0 0.000
#> GSM247804 4 0.000 1.000 0.000 0 0 1.000
#> GSM247774 1 0.000 0.996 1.000 0 0 0.000
#> GSM247807 3 0.000 1.000 0.000 0 1 0.000
#> GSM247813 1 0.000 0.996 1.000 0 0 0.000
#> GSM247736 2 0.000 1.000 0.000 1 0 0.000
#> GSM247712 4 0.000 1.000 0.000 0 0 1.000
#> GSM247797 1 0.000 0.996 1.000 0 0 0.000
#> GSM247743 3 0.000 1.000 0.000 0 1 0.000
#> GSM247719 1 0.000 0.996 1.000 0 0 0.000
#> GSM247707 2 0.000 1.000 0.000 1 0 0.000
#> GSM247737 4 0.000 1.000 0.000 0 0 1.000
#> GSM247827 3 0.000 1.000 0.000 0 1 0.000
#> GSM247848 1 0.000 0.996 1.000 0 0 0.000
#> GSM247794 2 0.000 1.000 0.000 1 0 0.000
#> GSM247757 4 0.000 1.000 0.000 0 0 1.000
#> GSM247744 1 0.000 0.996 1.000 0 0 0.000
#> GSM247751 3 0.000 1.000 0.000 0 1 0.000
#> GSM247837 1 0.000 0.996 1.000 0 0 0.000
#> GSM247754 2 0.000 1.000 0.000 1 0 0.000
#> GSM247789 4 0.000 1.000 0.000 0 0 1.000
#> GSM247802 1 0.000 0.996 1.000 0 0 0.000
#> GSM247771 3 0.000 1.000 0.000 0 1 0.000
#> GSM247763 1 0.000 0.996 1.000 0 0 0.000
#> GSM247808 2 0.000 1.000 0.000 1 0 0.000
#> GSM247787 4 0.000 1.000 0.000 0 0 1.000
#> GSM247843 1 0.000 0.996 1.000 0 0 0.000
#> GSM247811 3 0.000 1.000 0.000 0 1 0.000
#> GSM247773 1 0.000 0.996 1.000 0 0 0.000
#> GSM247766 2 0.000 1.000 0.000 1 0 0.000
#> GSM247718 4 0.000 1.000 0.000 0 0 1.000
#> GSM247832 1 0.000 0.996 1.000 0 0 0.000
#> GSM247709 3 0.000 1.000 0.000 0 1 0.000
#> GSM247820 1 0.000 0.996 1.000 0 0 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247854 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247758 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247742 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247755 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247841 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247703 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247739 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247715 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247829 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247842 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247805 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247786 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247812 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247776 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247850 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247717 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247784 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247834 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247783 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247846 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247822 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247710 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247713 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247840 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247733 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247852 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247790 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247730 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247824 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247770 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247711 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247782 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247836 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247785 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247847 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247750 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247788 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247849 4 0.029 0.976 0.008 0 0 0.992 0
#> GSM247772 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247760 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247764 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247851 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247714 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247828 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247704 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247818 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247823 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247706 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247835 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247734 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247819 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247809 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247830 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247833 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247738 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247716 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247747 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247722 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247816 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247839 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247821 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247798 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247838 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247721 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247781 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247762 4 0.277 0.813 0.164 0 0 0.836 0
#> GSM247825 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247777 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247761 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247720 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247814 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247732 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247708 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247740 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247749 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247767 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247748 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247705 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247746 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247752 4 0.293 0.791 0.180 0 0 0.820 0
#> GSM247769 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247753 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247723 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247779 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247756 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247826 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247775 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247741 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247799 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247778 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247806 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247815 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247735 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247831 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247845 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247791 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247780 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247853 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247800 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247729 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247810 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247844 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247793 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247759 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247724 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247817 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247727 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247796 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247725 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247801 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247731 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247765 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247792 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247726 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247803 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247728 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247768 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247745 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247855 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247804 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247774 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247807 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247813 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247736 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247712 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247797 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247743 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247719 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247707 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247737 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247827 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247848 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247794 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247757 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247744 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247751 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247837 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247754 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247789 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247802 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247771 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247763 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247808 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247787 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247843 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247811 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247773 1 0.000 1.000 1.000 0 0 0.000 0
#> GSM247766 2 0.000 1.000 0.000 1 0 0.000 0
#> GSM247718 5 0.000 1.000 0.000 0 0 0.000 1
#> GSM247832 4 0.000 0.983 0.000 0 0 1.000 0
#> GSM247709 3 0.000 1.000 0.000 0 1 0.000 0
#> GSM247820 1 0.000 1.000 1.000 0 0 0.000 0
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247854 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247758 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247742 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247755 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247841 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247703 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247739 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247715 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247829 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247842 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247805 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247786 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247812 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247776 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247850 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247717 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247784 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247834 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247783 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247846 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247822 6 0.0000 0.999 0.000 0.000 0 0.000 0 1.000
#> GSM247710 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247713 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247840 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247733 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247852 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247790 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247730 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247824 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247770 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247711 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247782 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247836 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247785 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247847 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247750 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247788 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247849 4 0.0260 0.970 0.008 0.000 0 0.992 0 0.000
#> GSM247772 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247760 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247764 6 0.0000 0.999 0.000 0.000 0 0.000 0 1.000
#> GSM247851 6 0.0000 0.999 0.000 0.000 0 0.000 0 1.000
#> GSM247714 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247828 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247704 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247818 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247823 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247706 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247835 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247734 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247819 6 0.0000 0.999 0.000 0.000 0 0.000 0 1.000
#> GSM247809 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247830 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247833 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247738 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247716 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247747 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247722 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247816 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247839 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247821 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247798 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247838 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247721 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247781 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247762 4 0.2491 0.779 0.164 0.000 0 0.836 0 0.000
#> GSM247825 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247777 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247761 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247720 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247814 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247732 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247708 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247740 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247749 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247767 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247748 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247705 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247746 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247752 4 0.2631 0.756 0.180 0.000 0 0.820 0 0.000
#> GSM247769 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247753 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247723 6 0.0146 0.996 0.000 0.004 0 0.000 0 0.996
#> GSM247779 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247756 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247826 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247775 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247741 6 0.0146 0.996 0.000 0.004 0 0.000 0 0.996
#> GSM247799 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247778 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247806 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247815 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247735 6 0.0000 0.999 0.000 0.000 0 0.000 0 1.000
#> GSM247831 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247845 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247791 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247780 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247853 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247800 6 0.0000 0.999 0.000 0.000 0 0.000 0 1.000
#> GSM247729 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247810 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247844 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247793 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247759 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247724 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247817 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247727 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247796 6 0.0000 0.999 0.000 0.000 0 0.000 0 1.000
#> GSM247725 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247801 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247731 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247765 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247792 6 0.0000 0.999 0.000 0.000 0 0.000 0 1.000
#> GSM247726 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247803 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247728 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247768 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247745 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247855 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247804 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247774 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247807 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247813 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247736 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247712 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247797 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247743 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247719 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247707 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247737 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247827 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247848 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247794 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247757 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247744 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247751 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247837 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247754 2 0.0000 0.986 0.000 1.000 0 0.000 0 0.000
#> GSM247789 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247802 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247771 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247763 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247808 2 0.3428 0.563 0.000 0.696 0 0.000 0 0.304
#> GSM247787 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247843 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247811 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247773 1 0.0000 1.000 1.000 0.000 0 0.000 0 0.000
#> GSM247766 6 0.0000 0.999 0.000 0.000 0 0.000 0 1.000
#> GSM247718 5 0.0000 1.000 0.000 0.000 0 0.000 1 0.000
#> GSM247832 4 0.0000 0.978 0.000 0.000 0 1.000 0 0.000
#> GSM247709 3 0.0000 1.000 0.000 0.000 1 0.000 0 0.000
#> GSM247820 1 0.0000 1.000 1.000 0.000 0 0.000 0 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> ATC:pam 153 1 1.000 3.54e-31 2
#> ATC:pam 153 1 0.981 2.32e-60 3
#> ATC:pam 153 1 0.998 3.89e-89 4
#> ATC:pam 153 1 0.998 1.57e-117 5
#> ATC:pam 153 1 0.847 1.98e-114 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.291 0.765 0.839 0.4773 0.506 0.506
#> 3 3 0.816 0.948 0.969 0.3314 0.717 0.505
#> 4 4 1.000 0.989 0.984 0.1217 0.930 0.802
#> 5 5 1.000 0.960 0.984 0.1235 0.910 0.687
#> 6 6 0.973 0.914 0.953 0.0151 0.986 0.929
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] 4 5
There is also optional best \(k\) = 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 2 0.000 0.853 0.000 1.000
#> GSM247854 2 0.000 0.853 0.000 1.000
#> GSM247758 2 0.163 0.856 0.024 0.976
#> GSM247742 2 0.992 0.449 0.448 0.552
#> GSM247755 1 0.795 0.781 0.760 0.240
#> GSM247841 1 0.469 0.811 0.900 0.100
#> GSM247703 2 0.000 0.853 0.000 1.000
#> GSM247739 2 0.163 0.856 0.024 0.976
#> GSM247715 2 0.992 0.449 0.448 0.552
#> GSM247829 1 0.795 0.781 0.760 0.240
#> GSM247842 1 0.469 0.811 0.900 0.100
#> GSM247805 2 0.000 0.853 0.000 1.000
#> GSM247786 2 0.163 0.856 0.024 0.976
#> GSM247812 1 0.795 0.781 0.760 0.240
#> GSM247776 1 0.469 0.811 0.900 0.100
#> GSM247850 1 0.469 0.811 0.900 0.100
#> GSM247717 2 0.000 0.853 0.000 1.000
#> GSM247784 2 0.163 0.856 0.024 0.976
#> GSM247834 2 0.992 0.449 0.448 0.552
#> GSM247783 1 0.795 0.781 0.760 0.240
#> GSM247846 1 0.469 0.811 0.900 0.100
#> GSM247822 2 0.000 0.853 0.000 1.000
#> GSM247710 2 0.163 0.856 0.024 0.976
#> GSM247713 2 0.992 0.449 0.448 0.552
#> GSM247840 1 0.795 0.781 0.760 0.240
#> GSM247733 1 0.469 0.811 0.900 0.100
#> GSM247852 1 0.469 0.811 0.900 0.100
#> GSM247790 2 0.000 0.853 0.000 1.000
#> GSM247730 2 0.163 0.856 0.024 0.976
#> GSM247824 1 0.795 0.781 0.760 0.240
#> GSM247770 1 0.469 0.811 0.900 0.100
#> GSM247711 2 0.000 0.853 0.000 1.000
#> GSM247782 2 0.163 0.856 0.024 0.976
#> GSM247836 2 0.992 0.449 0.448 0.552
#> GSM247785 1 0.795 0.781 0.760 0.240
#> GSM247847 1 0.469 0.811 0.900 0.100
#> GSM247750 2 0.000 0.853 0.000 1.000
#> GSM247788 2 0.163 0.856 0.024 0.976
#> GSM247849 2 0.988 0.454 0.436 0.564
#> GSM247772 1 0.795 0.781 0.760 0.240
#> GSM247760 1 0.469 0.811 0.900 0.100
#> GSM247764 2 0.000 0.853 0.000 1.000
#> GSM247851 2 0.000 0.853 0.000 1.000
#> GSM247714 2 0.163 0.856 0.024 0.976
#> GSM247828 2 0.992 0.449 0.448 0.552
#> GSM247704 1 0.795 0.781 0.760 0.240
#> GSM247818 1 0.469 0.811 0.900 0.100
#> GSM247823 2 0.000 0.853 0.000 1.000
#> GSM247706 2 0.163 0.856 0.024 0.976
#> GSM247835 1 0.795 0.781 0.760 0.240
#> GSM247734 1 0.469 0.811 0.900 0.100
#> GSM247819 2 0.000 0.853 0.000 1.000
#> GSM247809 2 0.163 0.856 0.024 0.976
#> GSM247830 1 0.795 0.781 0.760 0.240
#> GSM247833 1 0.469 0.811 0.900 0.100
#> GSM247738 2 0.000 0.853 0.000 1.000
#> GSM247716 2 0.163 0.856 0.024 0.976
#> GSM247747 1 0.795 0.781 0.760 0.240
#> GSM247722 1 0.469 0.811 0.900 0.100
#> GSM247816 2 0.000 0.853 0.000 1.000
#> GSM247839 2 0.163 0.856 0.024 0.976
#> GSM247821 2 0.992 0.449 0.448 0.552
#> GSM247798 1 0.795 0.781 0.760 0.240
#> GSM247838 1 0.469 0.811 0.900 0.100
#> GSM247721 2 0.000 0.853 0.000 1.000
#> GSM247781 2 0.163 0.856 0.024 0.976
#> GSM247762 2 0.992 0.449 0.448 0.552
#> GSM247825 1 0.795 0.781 0.760 0.240
#> GSM247777 1 0.469 0.811 0.900 0.100
#> GSM247761 2 0.000 0.853 0.000 1.000
#> GSM247720 2 0.163 0.856 0.024 0.976
#> GSM247814 1 0.795 0.781 0.760 0.240
#> GSM247732 1 0.469 0.811 0.900 0.100
#> GSM247708 2 0.000 0.853 0.000 1.000
#> GSM247740 2 0.163 0.856 0.024 0.976
#> GSM247749 2 0.992 0.449 0.448 0.552
#> GSM247767 1 0.795 0.781 0.760 0.240
#> GSM247748 1 0.469 0.811 0.900 0.100
#> GSM247705 2 0.000 0.853 0.000 1.000
#> GSM247746 2 0.163 0.856 0.024 0.976
#> GSM247752 2 0.992 0.449 0.448 0.552
#> GSM247769 1 0.795 0.781 0.760 0.240
#> GSM247753 1 0.469 0.811 0.900 0.100
#> GSM247723 2 0.000 0.853 0.000 1.000
#> GSM247779 2 0.163 0.856 0.024 0.976
#> GSM247756 2 0.992 0.449 0.448 0.552
#> GSM247826 1 0.795 0.781 0.760 0.240
#> GSM247775 1 0.469 0.811 0.900 0.100
#> GSM247741 2 0.000 0.853 0.000 1.000
#> GSM247799 2 0.163 0.856 0.024 0.976
#> GSM247778 2 0.992 0.449 0.448 0.552
#> GSM247806 1 0.795 0.781 0.760 0.240
#> GSM247815 1 0.469 0.811 0.900 0.100
#> GSM247735 2 0.000 0.853 0.000 1.000
#> GSM247831 2 0.163 0.856 0.024 0.976
#> GSM247845 2 0.992 0.449 0.448 0.552
#> GSM247791 1 0.795 0.781 0.760 0.240
#> GSM247780 1 0.469 0.811 0.900 0.100
#> GSM247853 1 0.469 0.811 0.900 0.100
#> GSM247800 2 0.000 0.853 0.000 1.000
#> GSM247729 2 0.163 0.856 0.024 0.976
#> GSM247810 2 0.992 0.449 0.448 0.552
#> GSM247844 1 0.795 0.781 0.760 0.240
#> GSM247793 1 0.469 0.811 0.900 0.100
#> GSM247759 2 0.000 0.853 0.000 1.000
#> GSM247724 2 0.163 0.856 0.024 0.976
#> GSM247817 1 0.795 0.781 0.760 0.240
#> GSM247727 1 0.469 0.811 0.900 0.100
#> GSM247796 2 0.000 0.853 0.000 1.000
#> GSM247725 2 0.163 0.856 0.024 0.976
#> GSM247801 2 0.992 0.449 0.448 0.552
#> GSM247731 1 0.795 0.781 0.760 0.240
#> GSM247765 1 0.469 0.811 0.900 0.100
#> GSM247792 2 0.000 0.853 0.000 1.000
#> GSM247726 2 0.184 0.855 0.028 0.972
#> GSM247803 1 0.996 -0.119 0.536 0.464
#> GSM247728 1 0.795 0.781 0.760 0.240
#> GSM247768 1 0.469 0.811 0.900 0.100
#> GSM247745 2 0.000 0.853 0.000 1.000
#> GSM247855 2 0.000 0.853 0.000 1.000
#> GSM247804 2 0.163 0.856 0.024 0.976
#> GSM247774 2 0.992 0.449 0.448 0.552
#> GSM247807 1 0.795 0.781 0.760 0.240
#> GSM247813 1 0.469 0.811 0.900 0.100
#> GSM247736 2 0.000 0.853 0.000 1.000
#> GSM247712 2 0.163 0.856 0.024 0.976
#> GSM247797 2 0.992 0.449 0.448 0.552
#> GSM247743 1 0.795 0.781 0.760 0.240
#> GSM247719 1 0.469 0.811 0.900 0.100
#> GSM247707 2 0.000 0.853 0.000 1.000
#> GSM247737 2 0.163 0.856 0.024 0.976
#> GSM247827 1 0.795 0.781 0.760 0.240
#> GSM247848 1 0.469 0.811 0.900 0.100
#> GSM247794 2 0.000 0.853 0.000 1.000
#> GSM247757 2 0.163 0.856 0.024 0.976
#> GSM247744 2 0.992 0.449 0.448 0.552
#> GSM247751 1 0.795 0.781 0.760 0.240
#> GSM247837 1 0.469 0.811 0.900 0.100
#> GSM247754 2 0.000 0.853 0.000 1.000
#> GSM247789 2 0.163 0.856 0.024 0.976
#> GSM247802 2 0.992 0.449 0.448 0.552
#> GSM247771 1 0.795 0.781 0.760 0.240
#> GSM247763 1 0.469 0.811 0.900 0.100
#> GSM247808 2 0.000 0.853 0.000 1.000
#> GSM247787 2 0.163 0.856 0.024 0.976
#> GSM247843 2 0.992 0.449 0.448 0.552
#> GSM247811 1 0.795 0.781 0.760 0.240
#> GSM247773 1 0.469 0.811 0.900 0.100
#> GSM247766 2 0.000 0.853 0.000 1.000
#> GSM247718 2 0.163 0.856 0.024 0.976
#> GSM247832 2 0.992 0.449 0.448 0.552
#> GSM247709 1 0.795 0.781 0.760 0.240
#> GSM247820 1 0.469 0.811 0.900 0.100
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247854 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247758 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247742 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247755 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247841 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247703 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247739 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247715 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247829 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247842 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247805 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247786 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247812 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247776 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247850 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247717 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247784 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247834 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247783 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247846 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247822 2 0.0747 0.987 0.000 0.984 0.016
#> GSM247710 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247713 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247840 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247733 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247852 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247790 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247730 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247824 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247770 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247711 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247782 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247836 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247785 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247847 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247750 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247788 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247849 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247772 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247760 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247764 2 0.0424 0.995 0.000 0.992 0.008
#> GSM247851 2 0.0424 0.995 0.000 0.992 0.008
#> GSM247714 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247828 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247704 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247818 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247823 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247706 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247835 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247734 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247819 2 0.0424 0.995 0.000 0.992 0.008
#> GSM247809 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247830 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247833 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247738 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247716 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247747 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247722 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247816 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247839 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247821 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247798 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247838 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247721 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247781 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247762 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247825 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247777 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247761 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247720 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247814 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247732 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247708 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247740 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247749 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247767 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247748 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247705 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247746 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247752 3 0.6585 0.666 0.064 0.200 0.736
#> GSM247769 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247753 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247723 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247779 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247756 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247826 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247775 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247741 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247799 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247778 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247806 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247815 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247735 2 0.0592 0.991 0.000 0.988 0.012
#> GSM247831 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247845 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247791 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247780 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247853 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247800 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247729 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247810 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247844 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247793 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247759 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247724 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247817 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247727 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247796 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247725 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247801 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247731 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247765 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247792 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247726 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247803 3 0.6106 0.690 0.044 0.200 0.756
#> GSM247728 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247768 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247745 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247855 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247804 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247774 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247807 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247813 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247736 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247712 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247797 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247743 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247719 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247707 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247737 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247827 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247848 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247794 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247757 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247744 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247751 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247837 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247754 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247789 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247802 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247771 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247763 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247808 2 0.0237 0.997 0.000 0.996 0.004
#> GSM247787 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247843 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247811 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247773 1 0.0000 0.905 1.000 0.000 0.000
#> GSM247766 2 0.0747 0.987 0.000 0.984 0.016
#> GSM247718 2 0.0000 0.997 0.000 1.000 0.000
#> GSM247832 1 0.4504 0.843 0.804 0.196 0.000
#> GSM247709 3 0.0000 0.983 0.000 0.000 1.000
#> GSM247820 1 0.0000 0.905 1.000 0.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247854 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247758 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247742 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247755 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247841 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247703 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247739 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247715 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247829 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247842 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247805 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247786 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247812 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247776 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247850 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247717 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247784 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247834 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247783 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247846 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247822 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247710 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247713 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247840 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247733 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247852 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247790 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247730 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247824 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247770 1 0.0188 0.995 0.996 0.000 0 0.004
#> GSM247711 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247782 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247836 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247785 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247847 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247750 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247788 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247849 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247772 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247760 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247764 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247851 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247714 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247828 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247704 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247818 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247823 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247706 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247835 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247734 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247819 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247809 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247830 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247833 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247738 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247716 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247747 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247722 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247816 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247839 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247821 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247798 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247838 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247721 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247781 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247762 4 0.1022 0.994 0.032 0.000 0 0.968
#> GSM247825 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247777 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247761 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247720 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247814 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247732 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247708 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247740 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247749 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247767 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247748 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247705 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247746 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247752 4 0.1022 0.994 0.032 0.000 0 0.968
#> GSM247769 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247753 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247723 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247779 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247756 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247826 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247775 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247741 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247799 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247778 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247806 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247815 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247735 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247831 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247845 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247791 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247780 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247853 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247800 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247729 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247810 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247844 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247793 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247759 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247724 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247817 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247727 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247796 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247725 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247801 4 0.1022 0.994 0.032 0.000 0 0.968
#> GSM247731 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247765 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247792 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247726 2 0.1474 0.975 0.000 0.948 0 0.052
#> GSM247803 4 0.1042 0.973 0.020 0.008 0 0.972
#> GSM247728 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247768 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247745 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247855 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247804 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247774 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247807 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247813 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247736 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247712 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247797 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247743 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247719 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247707 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247737 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247827 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247848 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247794 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247757 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247744 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247751 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247837 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247754 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247789 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247802 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247771 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247763 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247808 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247787 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247843 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247811 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247773 1 0.0000 1.000 1.000 0.000 0 0.000
#> GSM247766 2 0.0188 0.978 0.000 0.996 0 0.004
#> GSM247718 2 0.1389 0.975 0.000 0.952 0 0.048
#> GSM247832 4 0.1118 0.998 0.036 0.000 0 0.964
#> GSM247709 3 0.0000 1.000 0.000 0.000 1 0.000
#> GSM247820 1 0.0000 1.000 1.000 0.000 0 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247854 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247758 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247742 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247755 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247841 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247703 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247739 5 0.1121 0.9290 0.000 0.044 0.000 0.000 0.956
#> GSM247715 4 0.0451 0.9917 0.008 0.000 0.000 0.988 0.004
#> GSM247829 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247842 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247805 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247786 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247812 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247776 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247850 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247717 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247784 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247834 4 0.0451 0.9934 0.004 0.000 0.000 0.988 0.008
#> GSM247783 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247846 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247822 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247710 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247713 4 0.0324 0.9946 0.004 0.000 0.000 0.992 0.004
#> GSM247840 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247733 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247852 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247790 2 0.3876 0.5275 0.000 0.684 0.000 0.000 0.316
#> GSM247730 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247824 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247770 1 0.1732 0.9135 0.920 0.000 0.000 0.080 0.000
#> GSM247711 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247782 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247836 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247785 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247847 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247750 2 0.4126 0.3790 0.000 0.620 0.000 0.000 0.380
#> GSM247788 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247849 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247772 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247760 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247764 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247851 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247714 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247828 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247704 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247818 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247823 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247706 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247835 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247734 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247819 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247809 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247830 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247833 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247738 2 0.0162 0.9613 0.000 0.996 0.000 0.000 0.004
#> GSM247716 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247747 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247722 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247816 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247839 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247821 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247798 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247838 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247721 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247781 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247762 4 0.0162 0.9952 0.004 0.000 0.000 0.996 0.000
#> GSM247825 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247777 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247761 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247720 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247814 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247732 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247708 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247740 5 0.4302 0.0666 0.000 0.480 0.000 0.000 0.520
#> GSM247749 4 0.0290 0.9950 0.000 0.000 0.000 0.992 0.008
#> GSM247767 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247748 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247705 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247746 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247752 4 0.0451 0.9934 0.004 0.000 0.000 0.988 0.008
#> GSM247769 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247753 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247723 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247779 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247756 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247826 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247775 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247741 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247799 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247778 4 0.0162 0.9962 0.000 0.000 0.000 0.996 0.004
#> GSM247806 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247815 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247735 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247831 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247845 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247791 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247780 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247853 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247800 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247729 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247810 4 0.0162 0.9962 0.000 0.000 0.000 0.996 0.004
#> GSM247844 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247793 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247759 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247724 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247817 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247727 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247796 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247725 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247801 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247731 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247765 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247792 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247726 2 0.4242 0.2217 0.000 0.572 0.000 0.000 0.428
#> GSM247803 4 0.1029 0.9825 0.008 0.008 0.004 0.972 0.008
#> GSM247728 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247768 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247745 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247855 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247804 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247774 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247807 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247813 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247736 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247712 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247797 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247743 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247719 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247707 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247737 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247827 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247848 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247794 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247757 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247744 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247751 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247837 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247754 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247789 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247802 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247771 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247763 1 0.0290 0.9899 0.992 0.000 0.000 0.008 0.000
#> GSM247808 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247787 5 0.0290 0.9634 0.000 0.008 0.000 0.000 0.992
#> GSM247843 4 0.0162 0.9962 0.000 0.000 0.000 0.996 0.004
#> GSM247811 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247773 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
#> GSM247766 2 0.0000 0.9649 0.000 1.000 0.000 0.000 0.000
#> GSM247718 5 0.4291 0.1225 0.000 0.464 0.000 0.000 0.536
#> GSM247832 4 0.0000 0.9970 0.000 0.000 0.000 1.000 0.000
#> GSM247709 3 0.0000 1.0000 0.000 0.000 1.000 0.000 0.000
#> GSM247820 1 0.0000 0.9973 1.000 0.000 0.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.0291 0.907 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM247854 2 0.0291 0.907 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM247758 5 0.0458 0.925 0.000 0.000 0.000 0.000 0.984 0.016
#> GSM247742 4 0.1556 0.873 0.000 0.000 0.000 0.920 0.000 0.080
#> GSM247755 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247841 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247703 2 0.3198 0.761 0.000 0.740 0.000 0.000 0.000 0.260
#> GSM247739 5 0.1908 0.853 0.000 0.004 0.000 0.000 0.900 0.096
#> GSM247715 4 0.2431 0.694 0.008 0.000 0.000 0.860 0.000 0.132
#> GSM247829 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247842 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247805 2 0.3198 0.761 0.000 0.740 0.000 0.000 0.000 0.260
#> GSM247786 5 0.0146 0.933 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM247812 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247776 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247850 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247717 2 0.3101 0.774 0.000 0.756 0.000 0.000 0.000 0.244
#> GSM247784 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247834 4 0.1663 0.797 0.000 0.000 0.000 0.912 0.000 0.088
#> GSM247783 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247846 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247822 2 0.1010 0.899 0.000 0.960 0.000 0.000 0.004 0.036
#> GSM247710 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247713 4 0.0000 0.888 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM247840 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247733 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247852 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247790 2 0.5508 0.047 0.000 0.444 0.000 0.000 0.428 0.128
#> GSM247730 5 0.0260 0.930 0.000 0.000 0.000 0.000 0.992 0.008
#> GSM247824 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247770 1 0.1921 0.910 0.916 0.000 0.000 0.032 0.000 0.052
#> GSM247711 2 0.0291 0.907 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM247782 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247836 4 0.0000 0.888 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM247785 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247847 1 0.0146 0.994 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM247750 5 0.5238 0.108 0.000 0.408 0.000 0.000 0.496 0.096
#> GSM247788 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247849 4 0.1556 0.873 0.000 0.000 0.000 0.920 0.000 0.080
#> GSM247772 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247760 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247764 2 0.1010 0.899 0.000 0.960 0.000 0.000 0.004 0.036
#> GSM247851 2 0.1010 0.899 0.000 0.960 0.000 0.000 0.004 0.036
#> GSM247714 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247828 4 0.1327 0.879 0.000 0.000 0.000 0.936 0.000 0.064
#> GSM247704 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247818 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247823 2 0.2520 0.834 0.000 0.844 0.000 0.000 0.004 0.152
#> GSM247706 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247835 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247734 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247819 2 0.1010 0.899 0.000 0.960 0.000 0.000 0.004 0.036
#> GSM247809 5 0.0146 0.933 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM247830 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247833 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247738 2 0.3290 0.771 0.000 0.744 0.000 0.000 0.004 0.252
#> GSM247716 5 0.0146 0.933 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM247747 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247722 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247816 2 0.0291 0.907 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM247839 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247821 4 0.0000 0.888 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM247798 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247838 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247721 2 0.0291 0.907 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM247781 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247762 4 0.2491 0.607 0.000 0.000 0.000 0.836 0.000 0.164
#> GSM247825 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247777 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247761 2 0.3175 0.765 0.000 0.744 0.000 0.000 0.000 0.256
#> GSM247720 5 0.0146 0.933 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM247814 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247732 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247708 2 0.0146 0.907 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM247740 5 0.4691 0.601 0.000 0.124 0.000 0.000 0.680 0.196
#> GSM247749 4 0.2340 0.673 0.000 0.000 0.000 0.852 0.000 0.148
#> GSM247767 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247748 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247705 2 0.3584 0.711 0.000 0.688 0.000 0.000 0.004 0.308
#> GSM247746 5 0.0146 0.933 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM247752 6 0.3817 0.963 0.000 0.000 0.000 0.432 0.000 0.568
#> GSM247769 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247753 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247723 2 0.0937 0.893 0.000 0.960 0.000 0.000 0.000 0.040
#> GSM247779 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247756 4 0.1387 0.877 0.000 0.000 0.000 0.932 0.000 0.068
#> GSM247826 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247775 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247741 2 0.0146 0.907 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM247799 5 0.0865 0.910 0.000 0.000 0.000 0.000 0.964 0.036
#> GSM247778 4 0.0146 0.887 0.000 0.000 0.000 0.996 0.000 0.004
#> GSM247806 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247815 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247735 2 0.1010 0.899 0.000 0.960 0.000 0.000 0.004 0.036
#> GSM247831 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247845 4 0.1387 0.877 0.000 0.000 0.000 0.932 0.000 0.068
#> GSM247791 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247780 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247853 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247800 2 0.1010 0.899 0.000 0.960 0.000 0.000 0.004 0.036
#> GSM247729 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247810 4 0.1327 0.832 0.000 0.000 0.000 0.936 0.000 0.064
#> GSM247844 3 0.0363 0.988 0.000 0.000 0.988 0.000 0.000 0.012
#> GSM247793 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247759 2 0.0291 0.907 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM247724 5 0.0146 0.933 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM247817 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247727 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247796 2 0.1010 0.899 0.000 0.960 0.000 0.000 0.004 0.036
#> GSM247725 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247801 4 0.1204 0.858 0.000 0.000 0.000 0.944 0.000 0.056
#> GSM247731 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247765 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247792 2 0.1010 0.899 0.000 0.960 0.000 0.000 0.004 0.036
#> GSM247726 5 0.5829 0.249 0.000 0.164 0.000 0.004 0.456 0.376
#> GSM247803 6 0.4025 0.964 0.008 0.000 0.000 0.416 0.000 0.576
#> GSM247728 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247768 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247745 2 0.0291 0.907 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM247855 2 0.0291 0.907 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM247804 5 0.0146 0.932 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM247774 4 0.1556 0.873 0.000 0.000 0.000 0.920 0.000 0.080
#> GSM247807 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247813 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247736 2 0.0146 0.907 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM247712 5 0.0146 0.933 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM247797 4 0.0000 0.888 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM247743 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247719 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247707 2 0.0291 0.907 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM247737 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247827 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247848 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247794 2 0.3221 0.758 0.000 0.736 0.000 0.000 0.000 0.264
#> GSM247757 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247744 4 0.1387 0.877 0.000 0.000 0.000 0.932 0.000 0.068
#> GSM247751 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247837 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247754 2 0.0291 0.907 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM247789 5 0.0000 0.933 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM247802 4 0.0000 0.888 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM247771 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247763 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247808 2 0.0291 0.907 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM247787 5 0.0146 0.933 0.000 0.000 0.000 0.000 0.996 0.004
#> GSM247843 4 0.0000 0.888 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM247811 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247773 1 0.0000 0.997 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247766 2 0.1010 0.899 0.000 0.960 0.000 0.000 0.004 0.036
#> GSM247718 5 0.5022 0.538 0.000 0.204 0.000 0.000 0.640 0.156
#> GSM247832 4 0.1556 0.873 0.000 0.000 0.000 0.920 0.000 0.080
#> GSM247709 3 0.0000 1.000 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247820 1 0.0000 0.997 1.000 0.000 0.000 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
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
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> ATC:mclust 130 1 1.000 5.41e-28 2
#> ATC:mclust 153 1 0.946 1.66e-58 3
#> ATC:mclust 153 1 0.964 1.16e-90 4
#> ATC:mclust 149 1 0.982 1.61e-116 5
#> ATC:mclust 150 1 0.726 2.88e-114 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.
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 19559 rows and 153 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 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)
The plots are:
k and the heatmap of
predicted classes for each k.k.k.k.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:
k;k, the area increased is defined as \(A_k - A_{k-1}\).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)
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 0.933 0.930 0.972 0.4418 0.557 0.557
#> 3 3 1.000 1.000 1.000 0.4581 0.649 0.444
#> 4 4 0.932 0.978 0.913 0.0665 0.933 0.811
#> 5 5 0.851 0.973 0.895 0.1183 0.909 0.686
#> 6 6 0.943 0.958 0.938 0.0316 0.998 0.990
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 3
There is also optional best \(k\) = 2 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.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM247795 1 0.671 0.7749 0.824 0.176
#> GSM247854 1 0.917 0.4918 0.668 0.332
#> GSM247758 1 0.000 0.9774 1.000 0.000
#> GSM247742 1 0.000 0.9774 1.000 0.000
#> GSM247755 2 0.000 0.9559 0.000 1.000
#> GSM247841 1 0.000 0.9774 1.000 0.000
#> GSM247703 1 0.000 0.9774 1.000 0.000
#> GSM247739 1 0.000 0.9774 1.000 0.000
#> GSM247715 1 0.000 0.9774 1.000 0.000
#> GSM247829 2 0.000 0.9559 0.000 1.000
#> GSM247842 1 0.000 0.9774 1.000 0.000
#> GSM247805 1 0.000 0.9774 1.000 0.000
#> GSM247786 1 0.000 0.9774 1.000 0.000
#> GSM247812 2 0.000 0.9559 0.000 1.000
#> GSM247776 1 0.000 0.9774 1.000 0.000
#> GSM247850 1 0.000 0.9774 1.000 0.000
#> GSM247717 1 0.456 0.8789 0.904 0.096
#> GSM247784 1 0.000 0.9774 1.000 0.000
#> GSM247834 1 0.000 0.9774 1.000 0.000
#> GSM247783 2 0.000 0.9559 0.000 1.000
#> GSM247846 1 0.000 0.9774 1.000 0.000
#> GSM247822 2 0.000 0.9559 0.000 1.000
#> GSM247710 1 0.000 0.9774 1.000 0.000
#> GSM247713 1 0.000 0.9774 1.000 0.000
#> GSM247840 2 0.000 0.9559 0.000 1.000
#> GSM247733 1 0.000 0.9774 1.000 0.000
#> GSM247852 1 0.000 0.9774 1.000 0.000
#> GSM247790 1 0.000 0.9774 1.000 0.000
#> GSM247730 1 0.000 0.9774 1.000 0.000
#> GSM247824 2 0.000 0.9559 0.000 1.000
#> GSM247770 1 0.000 0.9774 1.000 0.000
#> GSM247711 2 0.605 0.8124 0.148 0.852
#> GSM247782 1 0.000 0.9774 1.000 0.000
#> GSM247836 1 0.000 0.9774 1.000 0.000
#> GSM247785 2 0.000 0.9559 0.000 1.000
#> GSM247847 1 0.000 0.9774 1.000 0.000
#> GSM247750 1 0.000 0.9774 1.000 0.000
#> GSM247788 1 0.000 0.9774 1.000 0.000
#> GSM247849 1 0.000 0.9774 1.000 0.000
#> GSM247772 2 0.000 0.9559 0.000 1.000
#> GSM247760 1 0.000 0.9774 1.000 0.000
#> GSM247764 2 0.000 0.9559 0.000 1.000
#> GSM247851 2 0.000 0.9559 0.000 1.000
#> GSM247714 1 0.000 0.9774 1.000 0.000
#> GSM247828 1 0.000 0.9774 1.000 0.000
#> GSM247704 2 0.000 0.9559 0.000 1.000
#> GSM247818 1 0.000 0.9774 1.000 0.000
#> GSM247823 1 0.416 0.8925 0.916 0.084
#> GSM247706 1 0.000 0.9774 1.000 0.000
#> GSM247835 2 0.000 0.9559 0.000 1.000
#> GSM247734 1 0.000 0.9774 1.000 0.000
#> GSM247819 2 0.000 0.9559 0.000 1.000
#> GSM247809 1 0.000 0.9774 1.000 0.000
#> GSM247830 2 0.000 0.9559 0.000 1.000
#> GSM247833 1 0.000 0.9774 1.000 0.000
#> GSM247738 1 0.000 0.9774 1.000 0.000
#> GSM247716 1 0.000 0.9774 1.000 0.000
#> GSM247747 2 0.000 0.9559 0.000 1.000
#> GSM247722 1 0.000 0.9774 1.000 0.000
#> GSM247816 2 1.000 0.0312 0.496 0.504
#> GSM247839 1 0.000 0.9774 1.000 0.000
#> GSM247821 1 0.000 0.9774 1.000 0.000
#> GSM247798 2 0.000 0.9559 0.000 1.000
#> GSM247838 1 0.000 0.9774 1.000 0.000
#> GSM247721 1 0.895 0.5359 0.688 0.312
#> GSM247781 1 0.000 0.9774 1.000 0.000
#> GSM247762 1 0.000 0.9774 1.000 0.000
#> GSM247825 2 0.000 0.9559 0.000 1.000
#> GSM247777 1 0.000 0.9774 1.000 0.000
#> GSM247761 1 0.430 0.8881 0.912 0.088
#> GSM247720 1 0.000 0.9774 1.000 0.000
#> GSM247814 2 0.000 0.9559 0.000 1.000
#> GSM247732 1 0.000 0.9774 1.000 0.000
#> GSM247708 2 0.706 0.7559 0.192 0.808
#> GSM247740 1 0.000 0.9774 1.000 0.000
#> GSM247749 1 0.000 0.9774 1.000 0.000
#> GSM247767 2 0.000 0.9559 0.000 1.000
#> GSM247748 1 0.000 0.9774 1.000 0.000
#> GSM247705 1 0.997 0.0852 0.532 0.468
#> GSM247746 1 0.000 0.9774 1.000 0.000
#> GSM247752 1 0.000 0.9774 1.000 0.000
#> GSM247769 2 0.000 0.9559 0.000 1.000
#> GSM247753 1 0.000 0.9774 1.000 0.000
#> GSM247723 2 0.000 0.9559 0.000 1.000
#> GSM247779 1 0.000 0.9774 1.000 0.000
#> GSM247756 1 0.000 0.9774 1.000 0.000
#> GSM247826 2 0.000 0.9559 0.000 1.000
#> GSM247775 1 0.000 0.9774 1.000 0.000
#> GSM247741 2 0.000 0.9559 0.000 1.000
#> GSM247799 1 0.000 0.9774 1.000 0.000
#> GSM247778 1 0.000 0.9774 1.000 0.000
#> GSM247806 2 0.000 0.9559 0.000 1.000
#> GSM247815 1 0.000 0.9774 1.000 0.000
#> GSM247735 2 0.000 0.9559 0.000 1.000
#> GSM247831 1 0.000 0.9774 1.000 0.000
#> GSM247845 1 0.000 0.9774 1.000 0.000
#> GSM247791 2 0.000 0.9559 0.000 1.000
#> GSM247780 1 0.000 0.9774 1.000 0.000
#> GSM247853 1 0.000 0.9774 1.000 0.000
#> GSM247800 2 0.000 0.9559 0.000 1.000
#> GSM247729 1 0.000 0.9774 1.000 0.000
#> GSM247810 1 0.000 0.9774 1.000 0.000
#> GSM247844 2 0.000 0.9559 0.000 1.000
#> GSM247793 1 0.000 0.9774 1.000 0.000
#> GSM247759 1 0.917 0.4916 0.668 0.332
#> GSM247724 1 0.000 0.9774 1.000 0.000
#> GSM247817 2 0.000 0.9559 0.000 1.000
#> GSM247727 1 0.000 0.9774 1.000 0.000
#> GSM247796 2 0.000 0.9559 0.000 1.000
#> GSM247725 1 0.000 0.9774 1.000 0.000
#> GSM247801 1 0.000 0.9774 1.000 0.000
#> GSM247731 2 0.000 0.9559 0.000 1.000
#> GSM247765 1 0.000 0.9774 1.000 0.000
#> GSM247792 2 0.000 0.9559 0.000 1.000
#> GSM247726 1 0.000 0.9774 1.000 0.000
#> GSM247803 1 0.000 0.9774 1.000 0.000
#> GSM247728 2 0.000 0.9559 0.000 1.000
#> GSM247768 1 0.000 0.9774 1.000 0.000
#> GSM247745 2 0.999 0.0929 0.480 0.520
#> GSM247855 2 0.722 0.7446 0.200 0.800
#> GSM247804 1 0.000 0.9774 1.000 0.000
#> GSM247774 1 0.000 0.9774 1.000 0.000
#> GSM247807 2 0.000 0.9559 0.000 1.000
#> GSM247813 1 0.000 0.9774 1.000 0.000
#> GSM247736 1 0.844 0.6162 0.728 0.272
#> GSM247712 1 0.000 0.9774 1.000 0.000
#> GSM247797 1 0.000 0.9774 1.000 0.000
#> GSM247743 2 0.000 0.9559 0.000 1.000
#> GSM247719 1 0.000 0.9774 1.000 0.000
#> GSM247707 2 0.978 0.3123 0.412 0.588
#> GSM247737 1 0.000 0.9774 1.000 0.000
#> GSM247827 2 0.000 0.9559 0.000 1.000
#> GSM247848 1 0.000 0.9774 1.000 0.000
#> GSM247794 1 0.000 0.9774 1.000 0.000
#> GSM247757 1 0.000 0.9774 1.000 0.000
#> GSM247744 1 0.000 0.9774 1.000 0.000
#> GSM247751 2 0.000 0.9559 0.000 1.000
#> GSM247837 1 0.000 0.9774 1.000 0.000
#> GSM247754 2 0.563 0.8310 0.132 0.868
#> GSM247789 1 0.000 0.9774 1.000 0.000
#> GSM247802 1 0.000 0.9774 1.000 0.000
#> GSM247771 2 0.000 0.9559 0.000 1.000
#> GSM247763 1 0.000 0.9774 1.000 0.000
#> GSM247808 2 0.000 0.9559 0.000 1.000
#> GSM247787 1 0.000 0.9774 1.000 0.000
#> GSM247843 1 0.000 0.9774 1.000 0.000
#> GSM247811 2 0.000 0.9559 0.000 1.000
#> GSM247773 1 0.000 0.9774 1.000 0.000
#> GSM247766 2 0.000 0.9559 0.000 1.000
#> GSM247718 1 0.000 0.9774 1.000 0.000
#> GSM247832 1 0.000 0.9774 1.000 0.000
#> GSM247709 2 0.000 0.9559 0.000 1.000
#> GSM247820 1 0.000 0.9774 1.000 0.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM247795 2 0 1 0 1 0
#> GSM247854 2 0 1 0 1 0
#> GSM247758 2 0 1 0 1 0
#> GSM247742 1 0 1 1 0 0
#> GSM247755 3 0 1 0 0 1
#> GSM247841 1 0 1 1 0 0
#> GSM247703 2 0 1 0 1 0
#> GSM247739 2 0 1 0 1 0
#> GSM247715 1 0 1 1 0 0
#> GSM247829 3 0 1 0 0 1
#> GSM247842 1 0 1 1 0 0
#> GSM247805 2 0 1 0 1 0
#> GSM247786 2 0 1 0 1 0
#> GSM247812 3 0 1 0 0 1
#> GSM247776 1 0 1 1 0 0
#> GSM247850 1 0 1 1 0 0
#> GSM247717 2 0 1 0 1 0
#> GSM247784 2 0 1 0 1 0
#> GSM247834 1 0 1 1 0 0
#> GSM247783 3 0 1 0 0 1
#> GSM247846 1 0 1 1 0 0
#> GSM247822 2 0 1 0 1 0
#> GSM247710 2 0 1 0 1 0
#> GSM247713 1 0 1 1 0 0
#> GSM247840 3 0 1 0 0 1
#> GSM247733 1 0 1 1 0 0
#> GSM247852 1 0 1 1 0 0
#> GSM247790 2 0 1 0 1 0
#> GSM247730 2 0 1 0 1 0
#> GSM247824 3 0 1 0 0 1
#> GSM247770 1 0 1 1 0 0
#> GSM247711 2 0 1 0 1 0
#> GSM247782 2 0 1 0 1 0
#> GSM247836 1 0 1 1 0 0
#> GSM247785 3 0 1 0 0 1
#> GSM247847 1 0 1 1 0 0
#> GSM247750 2 0 1 0 1 0
#> GSM247788 2 0 1 0 1 0
#> GSM247849 1 0 1 1 0 0
#> GSM247772 3 0 1 0 0 1
#> GSM247760 1 0 1 1 0 0
#> GSM247764 2 0 1 0 1 0
#> GSM247851 2 0 1 0 1 0
#> GSM247714 2 0 1 0 1 0
#> GSM247828 1 0 1 1 0 0
#> GSM247704 3 0 1 0 0 1
#> GSM247818 1 0 1 1 0 0
#> GSM247823 2 0 1 0 1 0
#> GSM247706 2 0 1 0 1 0
#> GSM247835 3 0 1 0 0 1
#> GSM247734 1 0 1 1 0 0
#> GSM247819 2 0 1 0 1 0
#> GSM247809 2 0 1 0 1 0
#> GSM247830 3 0 1 0 0 1
#> GSM247833 1 0 1 1 0 0
#> GSM247738 2 0 1 0 1 0
#> GSM247716 2 0 1 0 1 0
#> GSM247747 3 0 1 0 0 1
#> GSM247722 1 0 1 1 0 0
#> GSM247816 2 0 1 0 1 0
#> GSM247839 2 0 1 0 1 0
#> GSM247821 1 0 1 1 0 0
#> GSM247798 3 0 1 0 0 1
#> GSM247838 1 0 1 1 0 0
#> GSM247721 2 0 1 0 1 0
#> GSM247781 2 0 1 0 1 0
#> GSM247762 1 0 1 1 0 0
#> GSM247825 3 0 1 0 0 1
#> GSM247777 1 0 1 1 0 0
#> GSM247761 2 0 1 0 1 0
#> GSM247720 2 0 1 0 1 0
#> GSM247814 3 0 1 0 0 1
#> GSM247732 1 0 1 1 0 0
#> GSM247708 2 0 1 0 1 0
#> GSM247740 2 0 1 0 1 0
#> GSM247749 1 0 1 1 0 0
#> GSM247767 3 0 1 0 0 1
#> GSM247748 1 0 1 1 0 0
#> GSM247705 2 0 1 0 1 0
#> GSM247746 2 0 1 0 1 0
#> GSM247752 1 0 1 1 0 0
#> GSM247769 3 0 1 0 0 1
#> GSM247753 1 0 1 1 0 0
#> GSM247723 2 0 1 0 1 0
#> GSM247779 2 0 1 0 1 0
#> GSM247756 1 0 1 1 0 0
#> GSM247826 3 0 1 0 0 1
#> GSM247775 1 0 1 1 0 0
#> GSM247741 2 0 1 0 1 0
#> GSM247799 2 0 1 0 1 0
#> GSM247778 1 0 1 1 0 0
#> GSM247806 3 0 1 0 0 1
#> GSM247815 1 0 1 1 0 0
#> GSM247735 2 0 1 0 1 0
#> GSM247831 2 0 1 0 1 0
#> GSM247845 1 0 1 1 0 0
#> GSM247791 3 0 1 0 0 1
#> GSM247780 1 0 1 1 0 0
#> GSM247853 1 0 1 1 0 0
#> GSM247800 2 0 1 0 1 0
#> GSM247729 2 0 1 0 1 0
#> GSM247810 1 0 1 1 0 0
#> GSM247844 3 0 1 0 0 1
#> GSM247793 1 0 1 1 0 0
#> GSM247759 2 0 1 0 1 0
#> GSM247724 2 0 1 0 1 0
#> GSM247817 3 0 1 0 0 1
#> GSM247727 1 0 1 1 0 0
#> GSM247796 2 0 1 0 1 0
#> GSM247725 2 0 1 0 1 0
#> GSM247801 1 0 1 1 0 0
#> GSM247731 3 0 1 0 0 1
#> GSM247765 1 0 1 1 0 0
#> GSM247792 2 0 1 0 1 0
#> GSM247726 2 0 1 0 1 0
#> GSM247803 1 0 1 1 0 0
#> GSM247728 3 0 1 0 0 1
#> GSM247768 1 0 1 1 0 0
#> GSM247745 2 0 1 0 1 0
#> GSM247855 2 0 1 0 1 0
#> GSM247804 2 0 1 0 1 0
#> GSM247774 1 0 1 1 0 0
#> GSM247807 3 0 1 0 0 1
#> GSM247813 1 0 1 1 0 0
#> GSM247736 2 0 1 0 1 0
#> GSM247712 2 0 1 0 1 0
#> GSM247797 1 0 1 1 0 0
#> GSM247743 3 0 1 0 0 1
#> GSM247719 1 0 1 1 0 0
#> GSM247707 2 0 1 0 1 0
#> GSM247737 2 0 1 0 1 0
#> GSM247827 3 0 1 0 0 1
#> GSM247848 1 0 1 1 0 0
#> GSM247794 2 0 1 0 1 0
#> GSM247757 2 0 1 0 1 0
#> GSM247744 1 0 1 1 0 0
#> GSM247751 3 0 1 0 0 1
#> GSM247837 1 0 1 1 0 0
#> GSM247754 2 0 1 0 1 0
#> GSM247789 2 0 1 0 1 0
#> GSM247802 1 0 1 1 0 0
#> GSM247771 3 0 1 0 0 1
#> GSM247763 1 0 1 1 0 0
#> GSM247808 2 0 1 0 1 0
#> GSM247787 2 0 1 0 1 0
#> GSM247843 1 0 1 1 0 0
#> GSM247811 3 0 1 0 0 1
#> GSM247773 1 0 1 1 0 0
#> GSM247766 2 0 1 0 1 0
#> GSM247718 2 0 1 0 1 0
#> GSM247832 1 0 1 1 0 0
#> GSM247709 3 0 1 0 0 1
#> GSM247820 1 0 1 1 0 0
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM247795 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247854 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247758 2 0.1474 0.970 0.052 0.948 0.000 0.000
#> GSM247742 4 0.0592 0.960 0.016 0.000 0.000 0.984
#> GSM247755 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247841 1 0.4985 0.983 0.532 0.000 0.000 0.468
#> GSM247703 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247739 2 0.1474 0.970 0.052 0.948 0.000 0.000
#> GSM247715 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247829 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247842 1 0.4994 0.984 0.520 0.000 0.000 0.480
#> GSM247805 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247786 2 0.1389 0.970 0.048 0.952 0.000 0.000
#> GSM247812 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247776 1 0.4985 0.983 0.532 0.000 0.000 0.468
#> GSM247850 1 0.4985 0.983 0.532 0.000 0.000 0.468
#> GSM247717 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247784 2 0.1867 0.964 0.072 0.928 0.000 0.000
#> GSM247834 4 0.0188 0.979 0.004 0.000 0.000 0.996
#> GSM247783 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247846 1 0.4989 0.985 0.528 0.000 0.000 0.472
#> GSM247822 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247710 2 0.1637 0.968 0.060 0.940 0.000 0.000
#> GSM247713 4 0.0188 0.979 0.004 0.000 0.000 0.996
#> GSM247840 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247733 1 0.4989 0.985 0.528 0.000 0.000 0.472
#> GSM247852 1 0.4989 0.985 0.528 0.000 0.000 0.472
#> GSM247790 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247730 2 0.1716 0.967 0.064 0.936 0.000 0.000
#> GSM247824 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247770 1 0.4985 0.983 0.532 0.000 0.000 0.468
#> GSM247711 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247782 2 0.2216 0.954 0.092 0.908 0.000 0.000
#> GSM247836 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247785 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247847 1 0.4981 0.977 0.536 0.000 0.000 0.464
#> GSM247750 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247788 2 0.1940 0.962 0.076 0.924 0.000 0.000
#> GSM247849 4 0.2469 0.742 0.108 0.000 0.000 0.892
#> GSM247772 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247760 1 0.4989 0.985 0.528 0.000 0.000 0.472
#> GSM247764 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247851 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247714 2 0.1637 0.968 0.060 0.940 0.000 0.000
#> GSM247828 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247704 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247818 1 0.4989 0.985 0.528 0.000 0.000 0.472
#> GSM247823 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247706 2 0.1716 0.967 0.064 0.936 0.000 0.000
#> GSM247835 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247734 1 0.4985 0.983 0.532 0.000 0.000 0.468
#> GSM247819 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247809 2 0.1557 0.969 0.056 0.944 0.000 0.000
#> GSM247830 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247833 1 0.4998 0.979 0.512 0.000 0.000 0.488
#> GSM247738 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247716 2 0.1661 0.969 0.052 0.944 0.000 0.004
#> GSM247747 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247722 1 0.4998 0.979 0.512 0.000 0.000 0.488
#> GSM247816 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247839 2 0.1970 0.966 0.060 0.932 0.000 0.008
#> GSM247821 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247798 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247838 1 0.4998 0.979 0.512 0.000 0.000 0.488
#> GSM247721 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247781 2 0.2081 0.958 0.084 0.916 0.000 0.000
#> GSM247762 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247825 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247777 1 0.4998 0.979 0.512 0.000 0.000 0.488
#> GSM247761 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247720 2 0.1389 0.970 0.048 0.952 0.000 0.000
#> GSM247814 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247732 1 0.4998 0.979 0.512 0.000 0.000 0.488
#> GSM247708 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247740 2 0.1661 0.970 0.052 0.944 0.000 0.004
#> GSM247749 4 0.0188 0.979 0.004 0.000 0.000 0.996
#> GSM247767 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247748 1 0.4989 0.985 0.528 0.000 0.000 0.472
#> GSM247705 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247746 2 0.1389 0.970 0.048 0.952 0.000 0.000
#> GSM247752 4 0.0188 0.979 0.004 0.000 0.000 0.996
#> GSM247769 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247753 1 0.4996 0.983 0.516 0.000 0.000 0.484
#> GSM247723 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247779 2 0.2714 0.938 0.112 0.884 0.000 0.004
#> GSM247756 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247826 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247775 1 0.4985 0.983 0.532 0.000 0.000 0.468
#> GSM247741 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247799 2 0.1637 0.968 0.060 0.940 0.000 0.000
#> GSM247778 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247806 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247815 1 0.4992 0.985 0.524 0.000 0.000 0.476
#> GSM247735 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247831 2 0.1637 0.968 0.060 0.940 0.000 0.000
#> GSM247845 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247791 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247780 1 0.4996 0.983 0.516 0.000 0.000 0.484
#> GSM247853 1 0.4996 0.983 0.516 0.000 0.000 0.484
#> GSM247800 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247729 2 0.1792 0.965 0.068 0.932 0.000 0.000
#> GSM247810 4 0.0188 0.979 0.004 0.000 0.000 0.996
#> GSM247844 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247793 1 0.4996 0.983 0.516 0.000 0.000 0.484
#> GSM247759 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247724 2 0.1389 0.970 0.048 0.952 0.000 0.000
#> GSM247817 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247727 1 0.4998 0.979 0.512 0.000 0.000 0.488
#> GSM247796 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247725 2 0.1716 0.967 0.064 0.936 0.000 0.000
#> GSM247801 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247731 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247765 1 0.4985 0.983 0.532 0.000 0.000 0.468
#> GSM247792 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247726 2 0.2563 0.952 0.072 0.908 0.000 0.020
#> GSM247803 4 0.1661 0.919 0.052 0.000 0.004 0.944
#> GSM247728 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247768 1 0.4985 0.983 0.532 0.000 0.000 0.468
#> GSM247745 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247855 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247804 2 0.3545 0.893 0.164 0.828 0.000 0.008
#> GSM247774 4 0.0188 0.977 0.004 0.000 0.000 0.996
#> GSM247807 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247813 1 0.4996 0.983 0.516 0.000 0.000 0.484
#> GSM247736 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247712 2 0.1389 0.970 0.048 0.952 0.000 0.000
#> GSM247797 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247743 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247719 1 0.4998 0.979 0.512 0.000 0.000 0.488
#> GSM247707 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247737 2 0.2814 0.926 0.132 0.868 0.000 0.000
#> GSM247827 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247848 1 0.4989 0.985 0.528 0.000 0.000 0.472
#> GSM247794 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247757 2 0.1716 0.967 0.064 0.936 0.000 0.000
#> GSM247744 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247751 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247837 1 0.4985 0.983 0.532 0.000 0.000 0.468
#> GSM247754 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247789 2 0.1867 0.964 0.072 0.928 0.000 0.000
#> GSM247802 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247771 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247763 1 0.4996 0.983 0.516 0.000 0.000 0.484
#> GSM247808 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247787 2 0.1474 0.970 0.052 0.948 0.000 0.000
#> GSM247843 4 0.0000 0.982 0.000 0.000 0.000 1.000
#> GSM247811 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247773 1 0.4989 0.985 0.528 0.000 0.000 0.472
#> GSM247766 2 0.0000 0.975 0.000 1.000 0.000 0.000
#> GSM247718 2 0.1474 0.970 0.052 0.948 0.000 0.000
#> GSM247832 4 0.0592 0.960 0.016 0.000 0.000 0.984
#> GSM247709 3 0.0000 1.000 0.000 0.000 1.000 0.000
#> GSM247820 1 0.4998 0.979 0.512 0.000 0.000 0.488
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM247795 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247854 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247758 5 0.3177 0.928 0.000 0.208 0.000 0.000 0.792
#> GSM247742 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247755 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247841 1 0.0404 0.977 0.988 0.000 0.000 0.012 0.000
#> GSM247703 2 0.0000 0.995 0.000 1.000 0.000 0.000 0.000
#> GSM247739 5 0.2629 0.961 0.000 0.136 0.000 0.004 0.860
#> GSM247715 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247829 3 0.0162 0.998 0.000 0.000 0.996 0.004 0.000
#> GSM247842 1 0.0162 0.985 0.996 0.000 0.000 0.004 0.000
#> GSM247805 2 0.0324 0.993 0.000 0.992 0.000 0.004 0.004
#> GSM247786 5 0.3242 0.920 0.000 0.216 0.000 0.000 0.784
#> GSM247812 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247776 1 0.0162 0.983 0.996 0.000 0.000 0.004 0.000
#> GSM247850 1 0.0162 0.983 0.996 0.000 0.000 0.004 0.000
#> GSM247717 2 0.0000 0.995 0.000 1.000 0.000 0.000 0.000
#> GSM247784 5 0.2377 0.958 0.000 0.128 0.000 0.000 0.872
#> GSM247834 4 0.4015 0.958 0.348 0.000 0.000 0.652 0.000
#> GSM247783 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247846 1 0.0000 0.985 1.000 0.000 0.000 0.000 0.000
#> GSM247822 2 0.0162 0.992 0.000 0.996 0.000 0.004 0.000
#> GSM247710 5 0.2648 0.961 0.000 0.152 0.000 0.000 0.848
#> GSM247713 4 0.4015 0.958 0.348 0.000 0.000 0.652 0.000
#> GSM247840 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247733 1 0.0000 0.985 1.000 0.000 0.000 0.000 0.000
#> GSM247852 1 0.0162 0.985 0.996 0.000 0.000 0.004 0.000
#> GSM247790 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247730 5 0.2280 0.953 0.000 0.120 0.000 0.000 0.880
#> GSM247824 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247770 1 0.0566 0.973 0.984 0.000 0.000 0.012 0.004
#> GSM247711 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247782 5 0.2536 0.958 0.000 0.128 0.000 0.004 0.868
#> GSM247836 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247785 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247847 1 0.0404 0.977 0.988 0.000 0.000 0.012 0.000
#> GSM247750 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247788 5 0.2329 0.956 0.000 0.124 0.000 0.000 0.876
#> GSM247849 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247772 3 0.0162 0.998 0.000 0.000 0.996 0.004 0.000
#> GSM247760 1 0.0162 0.985 0.996 0.000 0.000 0.004 0.000
#> GSM247764 2 0.0000 0.995 0.000 1.000 0.000 0.000 0.000
#> GSM247851 2 0.0000 0.995 0.000 1.000 0.000 0.000 0.000
#> GSM247714 5 0.2516 0.961 0.000 0.140 0.000 0.000 0.860
#> GSM247828 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247704 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247818 1 0.0290 0.981 0.992 0.000 0.000 0.008 0.000
#> GSM247823 2 0.0290 0.993 0.000 0.992 0.000 0.000 0.008
#> GSM247706 5 0.2813 0.956 0.000 0.168 0.000 0.000 0.832
#> GSM247835 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247734 1 0.0162 0.983 0.996 0.000 0.000 0.004 0.000
#> GSM247819 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247809 5 0.2690 0.961 0.000 0.156 0.000 0.000 0.844
#> GSM247830 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247833 1 0.0510 0.981 0.984 0.000 0.000 0.016 0.000
#> GSM247738 2 0.0404 0.990 0.000 0.988 0.000 0.000 0.012
#> GSM247716 5 0.2719 0.962 0.000 0.144 0.000 0.004 0.852
#> GSM247747 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247722 1 0.0510 0.981 0.984 0.000 0.000 0.016 0.000
#> GSM247816 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247839 5 0.2471 0.960 0.000 0.136 0.000 0.000 0.864
#> GSM247821 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247798 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247838 1 0.0510 0.981 0.984 0.000 0.000 0.016 0.000
#> GSM247721 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247781 5 0.2280 0.953 0.000 0.120 0.000 0.000 0.880
#> GSM247762 4 0.4015 0.958 0.348 0.000 0.000 0.652 0.000
#> GSM247825 3 0.0162 0.998 0.000 0.000 0.996 0.004 0.000
#> GSM247777 1 0.0609 0.977 0.980 0.000 0.000 0.020 0.000
#> GSM247761 2 0.0162 0.994 0.000 0.996 0.000 0.000 0.004
#> GSM247720 5 0.3210 0.924 0.000 0.212 0.000 0.000 0.788
#> GSM247814 3 0.0162 0.998 0.000 0.000 0.996 0.004 0.000
#> GSM247732 1 0.0510 0.981 0.984 0.000 0.000 0.016 0.000
#> GSM247708 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247740 5 0.2970 0.956 0.000 0.168 0.000 0.004 0.828
#> GSM247749 4 0.4015 0.958 0.348 0.000 0.000 0.652 0.000
#> GSM247767 3 0.0162 0.997 0.000 0.000 0.996 0.004 0.000
#> GSM247748 1 0.0162 0.985 0.996 0.000 0.000 0.004 0.000
#> GSM247705 2 0.0324 0.993 0.000 0.992 0.000 0.004 0.004
#> GSM247746 5 0.2891 0.953 0.000 0.176 0.000 0.000 0.824
#> GSM247752 4 0.5611 0.737 0.196 0.004 0.000 0.652 0.148
#> GSM247769 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247753 1 0.0510 0.981 0.984 0.000 0.000 0.016 0.000
#> GSM247723 2 0.0162 0.993 0.000 0.996 0.000 0.004 0.000
#> GSM247779 5 0.2179 0.947 0.000 0.112 0.000 0.000 0.888
#> GSM247756 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247826 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247775 1 0.0404 0.982 0.988 0.000 0.000 0.012 0.000
#> GSM247741 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247799 5 0.3074 0.939 0.000 0.196 0.000 0.000 0.804
#> GSM247778 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247806 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247815 1 0.0290 0.985 0.992 0.000 0.000 0.008 0.000
#> GSM247735 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247831 5 0.2605 0.962 0.000 0.148 0.000 0.000 0.852
#> GSM247845 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247791 3 0.0162 0.997 0.000 0.000 0.996 0.004 0.000
#> GSM247780 1 0.0404 0.983 0.988 0.000 0.000 0.012 0.000
#> GSM247853 1 0.0290 0.985 0.992 0.000 0.000 0.008 0.000
#> GSM247800 2 0.0000 0.995 0.000 1.000 0.000 0.000 0.000
#> GSM247729 5 0.2583 0.960 0.000 0.132 0.000 0.004 0.864
#> GSM247810 4 0.4015 0.958 0.348 0.000 0.000 0.652 0.000
#> GSM247844 3 0.0162 0.998 0.000 0.000 0.996 0.004 0.000
#> GSM247793 1 0.0404 0.983 0.988 0.000 0.000 0.012 0.000
#> GSM247759 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247724 5 0.2813 0.957 0.000 0.168 0.000 0.000 0.832
#> GSM247817 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247727 1 0.0510 0.981 0.984 0.000 0.000 0.016 0.000
#> GSM247796 2 0.0000 0.995 0.000 1.000 0.000 0.000 0.000
#> GSM247725 5 0.2690 0.961 0.000 0.156 0.000 0.000 0.844
#> GSM247801 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247731 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247765 1 0.0566 0.973 0.984 0.000 0.000 0.012 0.004
#> GSM247792 2 0.0000 0.995 0.000 1.000 0.000 0.000 0.000
#> GSM247726 5 0.1670 0.887 0.000 0.052 0.000 0.012 0.936
#> GSM247803 4 0.5822 0.505 0.108 0.000 0.000 0.548 0.344
#> GSM247728 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247768 1 0.0404 0.977 0.988 0.000 0.000 0.012 0.000
#> GSM247745 2 0.0566 0.989 0.000 0.984 0.000 0.004 0.012
#> GSM247855 2 0.0579 0.990 0.000 0.984 0.000 0.008 0.008
#> GSM247804 5 0.1956 0.911 0.000 0.076 0.000 0.008 0.916
#> GSM247774 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247807 3 0.0162 0.998 0.000 0.000 0.996 0.004 0.000
#> GSM247813 1 0.0404 0.983 0.988 0.000 0.000 0.012 0.000
#> GSM247736 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247712 5 0.3636 0.845 0.000 0.272 0.000 0.000 0.728
#> GSM247797 4 0.4015 0.958 0.348 0.000 0.000 0.652 0.000
#> GSM247743 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247719 1 0.0510 0.981 0.984 0.000 0.000 0.016 0.000
#> GSM247707 2 0.0162 0.993 0.000 0.996 0.000 0.004 0.000
#> GSM247737 5 0.1965 0.934 0.000 0.096 0.000 0.000 0.904
#> GSM247827 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247848 1 0.0162 0.983 0.996 0.000 0.000 0.004 0.000
#> GSM247794 2 0.0162 0.993 0.000 0.996 0.000 0.004 0.000
#> GSM247757 5 0.2690 0.961 0.000 0.156 0.000 0.000 0.844
#> GSM247744 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247751 3 0.0162 0.998 0.000 0.000 0.996 0.004 0.000
#> GSM247837 1 0.0290 0.981 0.992 0.000 0.000 0.008 0.000
#> GSM247754 2 0.0000 0.995 0.000 1.000 0.000 0.000 0.000
#> GSM247789 5 0.2516 0.961 0.000 0.140 0.000 0.000 0.860
#> GSM247802 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247771 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247763 1 0.0510 0.981 0.984 0.000 0.000 0.016 0.000
#> GSM247808 2 0.0162 0.996 0.000 0.996 0.000 0.000 0.004
#> GSM247787 5 0.3003 0.945 0.000 0.188 0.000 0.000 0.812
#> GSM247843 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247811 3 0.0162 0.997 0.000 0.000 0.996 0.004 0.000
#> GSM247773 1 0.0000 0.985 1.000 0.000 0.000 0.000 0.000
#> GSM247766 2 0.0162 0.994 0.000 0.996 0.004 0.000 0.000
#> GSM247718 5 0.3074 0.939 0.000 0.196 0.000 0.000 0.804
#> GSM247832 4 0.4030 0.960 0.352 0.000 0.000 0.648 0.000
#> GSM247709 3 0.0000 0.999 0.000 0.000 1.000 0.000 0.000
#> GSM247820 1 0.0880 0.962 0.968 0.000 0.000 0.032 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM247795 2 0.1616 0.948 0.000 0.932 0.000 0.000 0.048 0.020
#> GSM247854 2 0.1633 0.950 0.000 0.932 0.000 0.000 0.044 0.024
#> GSM247758 5 0.0993 0.958 0.000 0.024 0.000 0.000 0.964 0.012
#> GSM247742 4 0.3215 0.914 0.240 0.000 0.000 0.756 0.000 0.004
#> GSM247755 3 0.0146 0.995 0.000 0.000 0.996 0.004 0.000 0.000
#> GSM247841 1 0.0405 0.981 0.988 0.000 0.000 0.008 0.000 0.004
#> GSM247703 2 0.0508 0.981 0.000 0.984 0.000 0.000 0.012 0.004
#> GSM247739 5 0.1480 0.951 0.000 0.020 0.000 0.000 0.940 0.040
#> GSM247715 4 0.3078 0.939 0.192 0.000 0.000 0.796 0.000 0.012
#> GSM247829 3 0.0146 0.995 0.000 0.000 0.996 0.004 0.000 0.000
#> GSM247842 1 0.0458 0.983 0.984 0.000 0.000 0.016 0.000 0.000
#> GSM247805 2 0.0436 0.980 0.000 0.988 0.000 0.004 0.004 0.004
#> GSM247786 5 0.0993 0.958 0.000 0.024 0.000 0.000 0.964 0.012
#> GSM247812 3 0.0260 0.994 0.000 0.000 0.992 0.000 0.000 0.008
#> GSM247776 1 0.0260 0.980 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM247850 1 0.0000 0.982 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM247717 2 0.0260 0.981 0.000 0.992 0.000 0.000 0.008 0.000
#> GSM247784 5 0.1168 0.954 0.000 0.016 0.000 0.000 0.956 0.028
#> GSM247834 4 0.3014 0.932 0.184 0.000 0.000 0.804 0.000 0.012
#> GSM247783 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247846 1 0.0458 0.983 0.984 0.000 0.000 0.016 0.000 0.000
#> GSM247822 2 0.0665 0.977 0.000 0.980 0.008 0.000 0.008 0.004
#> GSM247710 5 0.0632 0.960 0.000 0.024 0.000 0.000 0.976 0.000
#> GSM247713 4 0.2980 0.927 0.180 0.000 0.000 0.808 0.000 0.012
#> GSM247840 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247733 1 0.0146 0.983 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM247852 1 0.0547 0.983 0.980 0.000 0.000 0.020 0.000 0.000
#> GSM247790 2 0.1492 0.959 0.000 0.940 0.000 0.000 0.036 0.024
#> GSM247730 5 0.1719 0.935 0.000 0.016 0.000 0.000 0.924 0.060
#> GSM247824 3 0.0146 0.996 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM247770 1 0.0508 0.971 0.984 0.000 0.000 0.012 0.000 0.004
#> GSM247711 2 0.0870 0.980 0.000 0.972 0.000 0.004 0.012 0.012
#> GSM247782 5 0.1059 0.958 0.000 0.016 0.000 0.004 0.964 0.016
#> GSM247836 4 0.2994 0.943 0.208 0.000 0.000 0.788 0.000 0.004
#> GSM247785 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247847 1 0.0260 0.980 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM247750 2 0.1334 0.965 0.000 0.948 0.000 0.000 0.032 0.020
#> GSM247788 5 0.1528 0.944 0.000 0.016 0.000 0.000 0.936 0.048
#> GSM247849 4 0.3426 0.857 0.276 0.000 0.000 0.720 0.000 0.004
#> GSM247772 3 0.0146 0.995 0.000 0.000 0.996 0.004 0.000 0.000
#> GSM247760 1 0.0508 0.984 0.984 0.000 0.000 0.012 0.000 0.004
#> GSM247764 2 0.0665 0.978 0.000 0.980 0.008 0.000 0.004 0.008
#> GSM247851 2 0.0665 0.979 0.000 0.980 0.008 0.000 0.004 0.008
#> GSM247714 5 0.0547 0.960 0.000 0.020 0.000 0.000 0.980 0.000
#> GSM247828 4 0.2994 0.943 0.208 0.000 0.000 0.788 0.000 0.004
#> GSM247704 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247818 1 0.0291 0.979 0.992 0.004 0.000 0.004 0.000 0.000
#> GSM247823 2 0.0622 0.981 0.000 0.980 0.000 0.000 0.012 0.008
#> GSM247706 5 0.0891 0.960 0.000 0.024 0.000 0.000 0.968 0.008
#> GSM247835 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247734 1 0.0291 0.980 0.992 0.000 0.000 0.004 0.000 0.004
#> GSM247819 2 0.0520 0.981 0.000 0.984 0.000 0.000 0.008 0.008
#> GSM247809 5 0.1088 0.957 0.000 0.024 0.000 0.000 0.960 0.016
#> GSM247830 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247833 1 0.0790 0.974 0.968 0.000 0.000 0.032 0.000 0.000
#> GSM247738 2 0.1333 0.953 0.000 0.944 0.000 0.000 0.048 0.008
#> GSM247716 5 0.0458 0.960 0.000 0.016 0.000 0.000 0.984 0.000
#> GSM247747 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247722 1 0.0713 0.977 0.972 0.000 0.000 0.028 0.000 0.000
#> GSM247816 2 0.0820 0.978 0.000 0.972 0.000 0.000 0.016 0.012
#> GSM247839 5 0.0603 0.960 0.000 0.016 0.000 0.000 0.980 0.004
#> GSM247821 4 0.3012 0.943 0.196 0.000 0.000 0.796 0.000 0.008
#> GSM247798 3 0.0260 0.994 0.000 0.000 0.992 0.000 0.000 0.008
#> GSM247838 1 0.0547 0.982 0.980 0.000 0.000 0.020 0.000 0.000
#> GSM247721 2 0.0914 0.976 0.000 0.968 0.000 0.000 0.016 0.016
#> GSM247781 5 0.1245 0.952 0.000 0.016 0.000 0.000 0.952 0.032
#> GSM247762 4 0.2664 0.938 0.184 0.000 0.000 0.816 0.000 0.000
#> GSM247825 3 0.0146 0.995 0.000 0.000 0.996 0.004 0.000 0.000
#> GSM247777 1 0.1074 0.972 0.960 0.000 0.000 0.028 0.000 0.012
#> GSM247761 2 0.0405 0.981 0.000 0.988 0.000 0.000 0.008 0.004
#> GSM247720 5 0.1341 0.951 0.000 0.024 0.000 0.000 0.948 0.028
#> GSM247814 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247732 1 0.0632 0.980 0.976 0.000 0.000 0.024 0.000 0.000
#> GSM247708 2 0.0508 0.981 0.000 0.984 0.000 0.000 0.012 0.004
#> GSM247740 5 0.0972 0.960 0.000 0.028 0.000 0.000 0.964 0.008
#> GSM247749 4 0.2805 0.936 0.184 0.000 0.000 0.812 0.000 0.004
#> GSM247767 3 0.0363 0.992 0.000 0.000 0.988 0.000 0.000 0.012
#> GSM247748 1 0.0363 0.983 0.988 0.000 0.000 0.012 0.000 0.000
#> GSM247705 2 0.0405 0.975 0.000 0.988 0.000 0.008 0.000 0.004
#> GSM247746 5 0.1564 0.944 0.000 0.024 0.000 0.000 0.936 0.040
#> GSM247752 4 0.4233 0.652 0.104 0.004 0.000 0.768 0.012 0.112
#> GSM247769 3 0.0146 0.996 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM247753 1 0.0458 0.983 0.984 0.000 0.000 0.016 0.000 0.000
#> GSM247723 2 0.0291 0.978 0.000 0.992 0.000 0.004 0.000 0.004
#> GSM247779 5 0.1367 0.944 0.000 0.012 0.000 0.000 0.944 0.044
#> GSM247756 4 0.3081 0.936 0.220 0.000 0.000 0.776 0.000 0.004
#> GSM247826 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247775 1 0.0260 0.980 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM247741 2 0.0508 0.981 0.000 0.984 0.000 0.000 0.012 0.004
#> GSM247799 5 0.1492 0.946 0.000 0.024 0.000 0.000 0.940 0.036
#> GSM247778 4 0.3012 0.942 0.196 0.000 0.000 0.796 0.000 0.008
#> GSM247806 3 0.0146 0.996 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM247815 1 0.0260 0.980 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM247735 2 0.0665 0.980 0.000 0.980 0.004 0.000 0.008 0.008
#> GSM247831 5 0.0806 0.960 0.000 0.020 0.000 0.000 0.972 0.008
#> GSM247845 4 0.3109 0.931 0.224 0.000 0.000 0.772 0.000 0.004
#> GSM247791 3 0.0363 0.992 0.000 0.000 0.988 0.000 0.000 0.012
#> GSM247780 1 0.0891 0.980 0.968 0.000 0.000 0.024 0.000 0.008
#> GSM247853 1 0.1176 0.973 0.956 0.000 0.000 0.024 0.000 0.020
#> GSM247800 2 0.0622 0.981 0.000 0.980 0.000 0.000 0.008 0.012
#> GSM247729 5 0.1297 0.946 0.000 0.012 0.000 0.000 0.948 0.040
#> GSM247810 4 0.2980 0.927 0.180 0.000 0.000 0.808 0.000 0.012
#> GSM247844 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247793 1 0.0458 0.983 0.984 0.000 0.000 0.016 0.000 0.000
#> GSM247759 2 0.0622 0.981 0.000 0.980 0.000 0.000 0.012 0.008
#> GSM247724 5 0.0891 0.959 0.000 0.024 0.000 0.000 0.968 0.008
#> GSM247817 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247727 1 0.0777 0.978 0.972 0.000 0.000 0.024 0.000 0.004
#> GSM247796 2 0.0436 0.981 0.000 0.988 0.004 0.000 0.004 0.004
#> GSM247725 5 0.0891 0.960 0.000 0.024 0.000 0.000 0.968 0.008
#> GSM247801 4 0.2994 0.943 0.208 0.000 0.000 0.788 0.000 0.004
#> GSM247731 3 0.0146 0.996 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM247765 1 0.0405 0.975 0.988 0.000 0.000 0.008 0.000 0.004
#> GSM247792 2 0.0665 0.979 0.000 0.980 0.008 0.000 0.004 0.008
#> GSM247726 5 0.4187 0.492 0.000 0.012 0.000 0.012 0.652 0.324
#> GSM247803 6 0.5384 0.000 0.020 0.004 0.004 0.260 0.080 0.632
#> GSM247728 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247768 1 0.0146 0.980 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM247745 2 0.1138 0.974 0.000 0.960 0.000 0.004 0.024 0.012
#> GSM247855 2 0.1148 0.976 0.000 0.960 0.000 0.004 0.020 0.016
#> GSM247804 5 0.1812 0.912 0.000 0.008 0.000 0.000 0.912 0.080
#> GSM247774 4 0.3509 0.894 0.240 0.000 0.000 0.744 0.000 0.016
#> GSM247807 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247813 1 0.0777 0.978 0.972 0.000 0.000 0.024 0.000 0.004
#> GSM247736 2 0.1168 0.971 0.000 0.956 0.000 0.000 0.028 0.016
#> GSM247712 5 0.2113 0.920 0.000 0.028 0.000 0.004 0.908 0.060
#> GSM247797 4 0.2838 0.939 0.188 0.000 0.000 0.808 0.000 0.004
#> GSM247743 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247719 1 0.0713 0.977 0.972 0.000 0.000 0.028 0.000 0.000
#> GSM247707 2 0.0520 0.980 0.000 0.984 0.000 0.000 0.008 0.008
#> GSM247737 5 0.1643 0.923 0.000 0.008 0.000 0.000 0.924 0.068
#> GSM247827 3 0.0146 0.996 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM247848 1 0.0146 0.983 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM247794 2 0.0291 0.978 0.000 0.992 0.000 0.004 0.000 0.004
#> GSM247757 5 0.0777 0.960 0.000 0.024 0.000 0.000 0.972 0.004
#> GSM247744 4 0.3023 0.941 0.212 0.000 0.000 0.784 0.000 0.004
#> GSM247751 3 0.0000 0.997 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM247837 1 0.0146 0.980 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM247754 2 0.0405 0.981 0.000 0.988 0.000 0.000 0.008 0.004
#> GSM247789 5 0.0806 0.960 0.000 0.020 0.000 0.000 0.972 0.008
#> GSM247802 4 0.2980 0.941 0.192 0.000 0.000 0.800 0.000 0.008
#> GSM247771 3 0.0146 0.996 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM247763 1 0.0622 0.983 0.980 0.000 0.000 0.012 0.000 0.008
#> GSM247808 2 0.0870 0.980 0.000 0.972 0.000 0.004 0.012 0.012
#> GSM247787 5 0.0632 0.960 0.000 0.024 0.000 0.000 0.976 0.000
#> GSM247843 4 0.2994 0.944 0.208 0.000 0.000 0.788 0.000 0.004
#> GSM247811 3 0.0363 0.992 0.000 0.000 0.988 0.000 0.000 0.012
#> GSM247773 1 0.0260 0.984 0.992 0.000 0.000 0.008 0.000 0.000
#> GSM247766 2 0.0870 0.977 0.000 0.972 0.012 0.000 0.004 0.012
#> GSM247718 5 0.0713 0.960 0.000 0.028 0.000 0.000 0.972 0.000
#> GSM247832 4 0.3215 0.912 0.240 0.000 0.000 0.756 0.000 0.004
#> GSM247709 3 0.0146 0.996 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM247820 1 0.1219 0.954 0.948 0.000 0.000 0.048 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)
consensus_heatmap(res, k = 3)
consensus_heatmap(res, k = 4)
consensus_heatmap(res, k = 5)
consensus_heatmap(res, k = 6)
Heatmaps for the membership of samples in all partitions to see how consistent they are:
membership_heatmap(res, k = 2)
membership_heatmap(res, k = 3)
membership_heatmap(res, k = 4)
membership_heatmap(res, k = 5)
membership_heatmap(res, k = 6)
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)
get_signatures(res, k = 3)
get_signatures(res, k = 4)
get_signatures(res, k = 5)
get_signatures(res, k = 6)
#> Error in mat[ceiling(1:nr/h_ratio), ceiling(1:nc/w_ratio), drop = FALSE]: subscript out of bounds
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
get_signatures(res, k = 4, scale_rows = FALSE)
get_signatures(res, k = 5, scale_rows = FALSE)
get_signatures(res, k = 6, scale_rows = FALSE)
Compare the overlap of signatures from different k:
compare_signatures(res)
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:
which_row: row indices corresponding to the input matrix.fdr: FDR for the differential test. mean_x: The mean value in group x.scaled_mean_x: The mean value in group x after rows are scaled.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")
dimension_reduction(res, k = 3, method = "UMAP")
dimension_reduction(res, k = 4, method = "UMAP")
dimension_reduction(res, k = 5, method = "UMAP")
dimension_reduction(res, k = 6, method = "UMAP")
Following heatmap shows how subgroups are split when increasing k:
collect_classes(res)
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) disease.state(p) cell.type(p) k
#> ATC:NMF 147 1 0.636 4.95e-24 2
#> ATC:NMF 153 1 0.985 2.17e-61 3
#> ATC:NMF 153 1 0.964 1.16e-90 4
#> ATC:NMF 153 1 0.989 6.51e-120 5
#> ATC:NMF 151 1 0.994 3.24e-118 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.
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