Date: 2019-12-25 21:57:07 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 51941 rows and 156 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] 51941 156
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 | ||
|---|---|---|---|---|---|---|
| CV:skmeans | 2 | 1.000 | 0.961 | 0.984 | ** | |
| ATC:kmeans | 3 | 1.000 | 0.954 | 0.984 | ** | 2 |
| CV:kmeans | 2 | 0.999 | 0.958 | 0.982 | ** | |
| MAD:mclust | 2 | 0.990 | 0.958 | 0.957 | ** | |
| SD:skmeans | 2 | 0.972 | 0.952 | 0.980 | ** | |
| MAD:skmeans | 2 | 0.960 | 0.950 | 0.980 | ** | |
| ATC:skmeans | 3 | 0.957 | 0.936 | 0.971 | ** | 2 |
| SD:kmeans | 2 | 0.946 | 0.928 | 0.972 | * | |
| MAD:kmeans | 2 | 0.933 | 0.931 | 0.972 | * | |
| CV:pam | 2 | 0.929 | 0.937 | 0.971 | * | |
| CV:NMF | 2 | 0.919 | 0.932 | 0.971 | * | |
| ATC:pam | 5 | 0.911 | 0.840 | 0.940 | * | 2,3 |
| ATC:hclust | 2 | 0.708 | 0.873 | 0.935 | ||
| CV:mclust | 6 | 0.697 | 0.677 | 0.783 | ||
| SD:NMF | 2 | 0.683 | 0.851 | 0.936 | ||
| ATC:mclust | 2 | 0.594 | 0.863 | 0.932 | ||
| MAD:NMF | 2 | 0.545 | 0.783 | 0.908 | ||
| SD:mclust | 2 | 0.410 | 0.822 | 0.864 | ||
| ATC:NMF | 3 | 0.387 | 0.617 | 0.797 | ||
| MAD:hclust | 2 | 0.339 | 0.785 | 0.881 | ||
| SD:pam | 3 | 0.308 | 0.590 | 0.760 | ||
| MAD:pam | 3 | 0.305 | 0.581 | 0.789 | ||
| CV:hclust | 2 | 0.299 | 0.689 | 0.841 | ||
| SD:hclust | 3 | 0.272 | 0.606 | 0.773 |
**: 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 0.683 0.851 0.936 0.480 0.527 0.527
#> CV:NMF 2 0.919 0.932 0.971 0.475 0.527 0.527
#> MAD:NMF 2 0.545 0.783 0.908 0.497 0.497 0.497
#> ATC:NMF 2 0.337 0.567 0.778 0.413 0.650 0.650
#> SD:skmeans 2 0.972 0.952 0.980 0.499 0.502 0.502
#> CV:skmeans 2 1.000 0.961 0.984 0.503 0.497 0.497
#> MAD:skmeans 2 0.960 0.950 0.980 0.500 0.500 0.500
#> ATC:skmeans 2 1.000 0.991 0.997 0.499 0.502 0.502
#> SD:mclust 2 0.410 0.822 0.864 0.415 0.581 0.581
#> CV:mclust 2 0.200 0.560 0.787 0.442 0.507 0.507
#> MAD:mclust 2 0.990 0.958 0.957 0.423 0.562 0.562
#> ATC:mclust 2 0.594 0.863 0.932 0.428 0.557 0.557
#> SD:kmeans 2 0.946 0.928 0.972 0.469 0.533 0.533
#> CV:kmeans 2 0.999 0.958 0.982 0.500 0.500 0.500
#> MAD:kmeans 2 0.933 0.931 0.972 0.479 0.518 0.518
#> ATC:kmeans 2 1.000 0.985 0.994 0.474 0.524 0.524
#> SD:pam 2 0.245 0.634 0.825 0.429 0.562 0.562
#> CV:pam 2 0.929 0.937 0.971 0.471 0.530 0.530
#> MAD:pam 2 0.403 0.713 0.863 0.444 0.524 0.524
#> ATC:pam 2 1.000 0.978 0.990 0.468 0.530 0.530
#> SD:hclust 2 0.303 0.716 0.862 0.346 0.664 0.664
#> CV:hclust 2 0.299 0.689 0.841 0.447 0.530 0.530
#> MAD:hclust 2 0.339 0.785 0.881 0.410 0.587 0.587
#> ATC:hclust 2 0.708 0.873 0.935 0.462 0.518 0.518
get_stats(res_list, k = 3)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 3 0.463 0.598 0.817 0.369 0.706 0.489
#> CV:NMF 3 0.437 0.461 0.731 0.391 0.768 0.576
#> MAD:NMF 3 0.330 0.483 0.742 0.315 0.682 0.445
#> ATC:NMF 3 0.387 0.617 0.797 0.526 0.619 0.458
#> SD:skmeans 3 0.705 0.830 0.916 0.328 0.752 0.544
#> CV:skmeans 3 0.695 0.811 0.908 0.304 0.773 0.575
#> MAD:skmeans 3 0.681 0.678 0.847 0.316 0.737 0.525
#> ATC:skmeans 3 0.957 0.936 0.971 0.113 0.936 0.874
#> SD:mclust 3 0.299 0.472 0.705 0.409 0.718 0.571
#> CV:mclust 3 0.373 0.592 0.783 0.327 0.657 0.450
#> MAD:mclust 3 0.496 0.626 0.811 0.359 0.872 0.777
#> ATC:mclust 3 0.392 0.815 0.774 0.186 0.497 0.348
#> SD:kmeans 3 0.460 0.544 0.799 0.389 0.668 0.448
#> CV:kmeans 3 0.450 0.454 0.750 0.321 0.714 0.487
#> MAD:kmeans 3 0.448 0.560 0.758 0.364 0.714 0.498
#> ATC:kmeans 3 1.000 0.954 0.984 0.396 0.679 0.458
#> SD:pam 3 0.308 0.590 0.760 0.469 0.636 0.432
#> CV:pam 3 0.485 0.560 0.789 0.379 0.771 0.586
#> MAD:pam 3 0.305 0.581 0.789 0.445 0.648 0.427
#> ATC:pam 3 0.999 0.967 0.985 0.373 0.642 0.425
#> SD:hclust 3 0.272 0.606 0.773 0.502 0.718 0.599
#> CV:hclust 3 0.231 0.474 0.723 0.352 0.752 0.581
#> MAD:hclust 3 0.300 0.628 0.777 0.278 0.949 0.914
#> ATC:hclust 3 0.540 0.680 0.825 0.257 0.847 0.720
get_stats(res_list, k = 4)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 4 0.476 0.481 0.711 0.1257 0.751 0.403
#> CV:NMF 4 0.544 0.607 0.795 0.1336 0.757 0.410
#> MAD:NMF 4 0.427 0.542 0.741 0.1284 0.813 0.515
#> ATC:NMF 4 0.403 0.435 0.644 0.1613 0.769 0.474
#> SD:skmeans 4 0.655 0.712 0.860 0.1206 0.820 0.535
#> CV:skmeans 4 0.616 0.651 0.827 0.1174 0.820 0.546
#> MAD:skmeans 4 0.694 0.725 0.866 0.1181 0.790 0.485
#> ATC:skmeans 4 0.883 0.844 0.939 0.0596 0.991 0.980
#> SD:mclust 4 0.524 0.599 0.748 0.2148 0.714 0.425
#> CV:mclust 4 0.521 0.567 0.769 0.2358 0.775 0.485
#> MAD:mclust 4 0.398 0.422 0.683 0.2096 0.684 0.402
#> ATC:mclust 4 0.388 0.384 0.639 0.2768 0.549 0.300
#> SD:kmeans 4 0.556 0.647 0.809 0.1303 0.750 0.411
#> CV:kmeans 4 0.655 0.716 0.850 0.1306 0.778 0.443
#> MAD:kmeans 4 0.593 0.631 0.810 0.1306 0.831 0.558
#> ATC:kmeans 4 0.731 0.653 0.853 0.1134 0.784 0.477
#> SD:pam 4 0.465 0.595 0.758 0.1571 0.748 0.423
#> CV:pam 4 0.653 0.739 0.866 0.1316 0.813 0.532
#> MAD:pam 4 0.505 0.652 0.776 0.1458 0.807 0.524
#> ATC:pam 4 0.806 0.815 0.919 0.1279 0.778 0.480
#> SD:hclust 4 0.244 0.486 0.678 0.1916 0.865 0.723
#> CV:hclust 4 0.299 0.468 0.679 0.1291 0.847 0.657
#> MAD:hclust 4 0.321 0.494 0.678 0.1992 0.763 0.574
#> ATC:hclust 4 0.661 0.809 0.888 0.2030 0.803 0.573
get_stats(res_list, k = 5)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 5 0.582 0.566 0.760 0.0714 0.852 0.507
#> CV:NMF 5 0.594 0.544 0.744 0.0684 0.854 0.502
#> MAD:NMF 5 0.544 0.572 0.758 0.0706 0.888 0.606
#> ATC:NMF 5 0.440 0.410 0.617 0.0750 0.825 0.471
#> SD:skmeans 5 0.634 0.584 0.767 0.0581 0.936 0.768
#> CV:skmeans 5 0.595 0.555 0.762 0.0604 0.955 0.838
#> MAD:skmeans 5 0.616 0.561 0.753 0.0592 0.953 0.829
#> ATC:skmeans 5 0.863 0.816 0.915 0.0405 0.973 0.937
#> SD:mclust 5 0.628 0.564 0.789 0.0789 0.794 0.418
#> CV:mclust 5 0.565 0.607 0.742 0.0654 0.841 0.480
#> MAD:mclust 5 0.548 0.451 0.667 0.0992 0.789 0.415
#> ATC:mclust 5 0.447 0.466 0.653 0.0759 0.631 0.287
#> SD:kmeans 5 0.604 0.581 0.763 0.0652 0.894 0.634
#> CV:kmeans 5 0.633 0.521 0.724 0.0607 0.918 0.706
#> MAD:kmeans 5 0.648 0.651 0.794 0.0654 0.910 0.680
#> ATC:kmeans 5 0.863 0.840 0.921 0.0695 0.825 0.466
#> SD:pam 5 0.547 0.455 0.693 0.0628 0.936 0.781
#> CV:pam 5 0.656 0.577 0.784 0.0677 0.945 0.798
#> MAD:pam 5 0.577 0.556 0.753 0.0583 0.954 0.832
#> ATC:pam 5 0.911 0.840 0.940 0.0917 0.837 0.493
#> SD:hclust 5 0.323 0.497 0.682 0.0846 0.858 0.658
#> CV:hclust 5 0.379 0.403 0.652 0.0745 0.959 0.884
#> MAD:hclust 5 0.354 0.484 0.684 0.1010 0.918 0.772
#> ATC:hclust 5 0.724 0.776 0.868 0.0743 0.941 0.811
get_stats(res_list, k = 6)
#> k 1-PAC mean_silhouette concordance area_increased Rand Jaccard
#> SD:NMF 6 0.581 0.434 0.660 0.0419 0.923 0.655
#> CV:NMF 6 0.625 0.528 0.720 0.0407 0.888 0.526
#> MAD:NMF 6 0.553 0.414 0.640 0.0418 0.891 0.557
#> ATC:NMF 6 0.514 0.376 0.593 0.0454 0.882 0.549
#> SD:skmeans 6 0.622 0.501 0.712 0.0421 0.961 0.841
#> CV:skmeans 6 0.604 0.442 0.696 0.0388 0.958 0.838
#> MAD:skmeans 6 0.630 0.528 0.711 0.0411 0.952 0.813
#> ATC:skmeans 6 0.866 0.779 0.897 0.0312 0.992 0.981
#> SD:mclust 6 0.648 0.553 0.753 0.0472 0.917 0.682
#> CV:mclust 6 0.697 0.677 0.783 0.0596 0.896 0.565
#> MAD:mclust 6 0.610 0.580 0.729 0.0518 0.908 0.640
#> ATC:mclust 6 0.551 0.621 0.739 0.0823 0.870 0.626
#> SD:kmeans 6 0.626 0.497 0.693 0.0399 0.951 0.782
#> CV:kmeans 6 0.657 0.536 0.720 0.0409 0.890 0.572
#> MAD:kmeans 6 0.648 0.482 0.717 0.0396 0.994 0.974
#> ATC:kmeans 6 0.871 0.862 0.918 0.0502 0.889 0.545
#> SD:pam 6 0.589 0.483 0.704 0.0433 0.897 0.626
#> CV:pam 6 0.693 0.502 0.741 0.0461 0.901 0.607
#> MAD:pam 6 0.663 0.604 0.770 0.0444 0.911 0.654
#> ATC:pam 6 0.859 0.831 0.912 0.0359 0.935 0.712
#> SD:hclust 6 0.357 0.488 0.645 0.0448 0.968 0.898
#> CV:hclust 6 0.436 0.452 0.624 0.0497 0.883 0.655
#> MAD:hclust 6 0.400 0.487 0.694 0.0308 0.975 0.920
#> ATC:hclust 6 0.716 0.713 0.773 0.0370 0.985 0.944
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 genotype/variation(p) protocol(p) other(p) k
#> SD:NMF 143 0.00146 0.622 0.0291 2
#> CV:NMF 152 0.00122 0.417 0.0187 2
#> MAD:NMF 136 0.01281 0.245 0.1836 2
#> ATC:NMF 143 0.57006 0.951 0.3684 2
#> SD:skmeans 153 0.87239 0.318 0.8632 2
#> CV:skmeans 153 0.39472 0.740 0.5292 2
#> MAD:skmeans 152 0.75926 0.389 0.8497 2
#> ATC:skmeans 155 0.37018 1.000 0.7283 2
#> SD:mclust 151 0.73184 1.000 1.0000 2
#> CV:mclust 105 0.00530 0.379 0.0184 2
#> MAD:mclust 155 0.71296 1.000 1.0000 2
#> ATC:mclust 151 0.20214 0.992 0.3225 2
#> SD:kmeans 149 1.00000 0.737 0.7240 2
#> CV:kmeans 152 0.50263 0.597 0.8697 2
#> MAD:kmeans 149 0.97868 0.577 0.7318 2
#> ATC:kmeans 154 1.00000 0.939 0.9763 2
#> SD:pam 118 0.91932 0.946 1.0000 2
#> CV:pam 152 1.00000 1.000 0.6397 2
#> MAD:pam 139 0.37016 0.559 1.0000 2
#> ATC:pam 156 0.96563 1.000 0.9428 2
#> SD:hclust 139 0.05854 0.386 0.4707 2
#> CV:hclust 131 0.32622 0.777 1.0000 2
#> MAD:hclust 148 0.24049 0.513 0.8627 2
#> ATC:hclust 152 0.79809 0.901 0.8243 2
test_to_known_factors(res_list, k = 3)
#> n genotype/variation(p) protocol(p) other(p) k
#> SD:NMF 111 1.25e-05 0.2910 0.00503 3
#> CV:NMF 70 5.13e-03 0.0261 0.00104 3
#> MAD:NMF 96 8.47e-04 0.3145 0.03595 3
#> ATC:NMF 131 2.77e-01 0.6441 0.44879 3
#> SD:skmeans 145 1.54e-03 0.3157 0.03474 3
#> CV:skmeans 143 2.87e-03 0.7388 0.09616 3
#> MAD:skmeans 111 1.16e-02 0.2765 0.20452 3
#> ATC:skmeans 149 7.82e-01 0.6083 0.42097 3
#> SD:mclust 101 1.06e-05 0.0796 0.01529 3
#> CV:mclust 121 2.31e-07 0.0444 0.02262 3
#> MAD:mclust 130 3.15e-01 0.7976 0.03656 3
#> ATC:mclust 155 5.09e-01 0.1854 0.72414 3
#> SD:kmeans 107 2.59e-03 0.6572 0.03205 3
#> CV:kmeans 79 2.36e-02 0.6322 0.08619 3
#> MAD:kmeans 103 4.76e-01 0.9086 0.39974 3
#> ATC:kmeans 151 6.67e-01 0.6270 0.87076 3
#> SD:pam 126 8.68e-07 0.3338 0.06300 3
#> CV:pam 103 9.57e-01 0.9211 0.27807 3
#> MAD:pam 118 2.47e-04 0.1127 0.11668 3
#> ATC:pam 155 4.36e-01 0.5165 0.90856 3
#> SD:hclust 115 2.24e-01 0.5896 0.55150 3
#> CV:hclust 74 1.66e-02 0.1349 0.13623 3
#> MAD:hclust 111 2.59e-02 0.7132 0.76165 3
#> ATC:hclust 133 1.09e-01 0.2287 0.11492 3
test_to_known_factors(res_list, k = 4)
#> n genotype/variation(p) protocol(p) other(p) k
#> SD:NMF 86 2.80e-05 0.03877 0.02155 4
#> CV:NMF 116 4.34e-06 0.09780 0.03117 4
#> MAD:NMF 109 4.41e-05 0.04471 0.04316 4
#> ATC:NMF 76 4.29e-02 0.49059 0.67041 4
#> SD:skmeans 132 2.75e-06 0.07570 0.00210 4
#> CV:skmeans 122 3.08e-06 0.24569 0.01930 4
#> MAD:skmeans 130 3.64e-04 0.45006 0.06112 4
#> ATC:skmeans 138 7.99e-01 0.74588 1.00000 4
#> SD:mclust 122 5.01e-04 0.20221 0.01343 4
#> CV:mclust 113 3.13e-06 0.11565 0.04576 4
#> MAD:mclust 74 1.42e-06 0.00567 0.00667 4
#> ATC:mclust 60 7.32e-02 0.47782 0.19703 4
#> SD:kmeans 130 5.35e-06 0.10234 0.02829 4
#> CV:kmeans 134 5.48e-04 0.16501 0.05450 4
#> MAD:kmeans 127 4.57e-03 0.53196 0.25566 4
#> ATC:kmeans 117 3.74e-01 0.63103 0.32499 4
#> SD:pam 114 5.61e-06 0.23705 0.04334 4
#> CV:pam 140 5.14e-06 0.28903 0.03094 4
#> MAD:pam 126 1.51e-03 0.28106 0.40889 4
#> ATC:pam 139 4.27e-01 0.75461 0.40035 4
#> SD:hclust 79 3.02e-02 0.59017 0.51925 4
#> CV:hclust 74 8.91e-04 0.04033 0.02837 4
#> MAD:hclust 87 2.27e-02 0.07700 0.41864 4
#> ATC:hclust 150 1.79e-01 0.35483 0.02484 4
test_to_known_factors(res_list, k = 5)
#> n genotype/variation(p) protocol(p) other(p) k
#> SD:NMF 110 1.64e-05 0.01626 0.00159 5
#> CV:NMF 99 6.29e-06 0.02148 0.00195 5
#> MAD:NMF 116 3.24e-06 0.00866 0.00761 5
#> ATC:NMF 71 1.10e-02 0.51296 0.74223 5
#> SD:skmeans 104 4.75e-06 0.14489 0.02310 5
#> CV:skmeans 108 1.13e-05 0.26720 0.04297 5
#> MAD:skmeans 102 2.62e-04 0.25566 0.05483 5
#> ATC:skmeans 132 8.16e-01 0.49732 1.00000 5
#> SD:mclust 109 1.18e-07 0.01218 0.05416 5
#> CV:mclust 114 7.10e-09 0.00868 0.03413 5
#> MAD:mclust 87 3.40e-06 0.04095 0.16562 5
#> ATC:mclust 94 1.11e-02 0.04989 0.26307 5
#> SD:kmeans 106 1.26e-05 0.34602 0.02454 5
#> CV:kmeans 112 4.50e-05 0.19711 0.04510 5
#> MAD:kmeans 122 1.21e-03 0.23652 0.00886 5
#> ATC:kmeans 145 1.52e-01 0.35790 0.03317 5
#> SD:pam 93 1.62e-07 0.07342 0.02753 5
#> CV:pam 109 1.94e-06 0.20293 0.01432 5
#> MAD:pam 105 3.12e-03 0.24644 0.33958 5
#> ATC:pam 140 4.79e-01 0.46280 0.16644 5
#> SD:hclust 89 1.36e-02 0.19055 0.37488 5
#> CV:hclust 66 2.82e-04 0.08767 0.17049 5
#> MAD:hclust 96 3.99e-01 0.60380 0.18180 5
#> ATC:hclust 143 2.31e-01 0.62122 0.08175 5
test_to_known_factors(res_list, k = 6)
#> n genotype/variation(p) protocol(p) other(p) k
#> SD:NMF 71 8.97e-05 0.00959 0.00293 6
#> CV:NMF 94 5.52e-06 0.05236 0.02997 6
#> MAD:NMF 70 2.48e-03 0.06671 0.06669 6
#> ATC:NMF 52 2.46e-01 0.77863 0.89640 6
#> SD:skmeans 93 1.78e-06 0.07847 0.01127 6
#> CV:skmeans 85 2.02e-02 0.26962 0.79670 6
#> MAD:skmeans 104 2.42e-03 0.23069 0.12474 6
#> ATC:skmeans 130 8.22e-01 0.61141 1.00000 6
#> SD:mclust 110 5.76e-06 0.05054 0.02630 6
#> CV:mclust 123 3.80e-09 0.00910 0.03383 6
#> MAD:mclust 120 3.37e-05 0.08218 0.13668 6
#> ATC:mclust 127 7.50e-02 0.03633 0.43731 6
#> SD:kmeans 88 1.21e-05 0.13276 0.03866 6
#> CV:kmeans 110 3.78e-03 0.65782 0.37819 6
#> MAD:kmeans 86 1.87e-03 0.11604 0.00119 6
#> ATC:kmeans 151 2.98e-01 0.46153 0.07529 6
#> SD:pam 89 2.96e-06 0.16737 0.05386 6
#> CV:pam 93 1.68e-04 0.36795 0.14235 6
#> MAD:pam 114 7.47e-03 0.35543 0.72229 6
#> ATC:pam 147 4.00e-01 0.32609 0.20379 6
#> SD:hclust 88 2.44e-02 0.17226 0.23868 6
#> CV:hclust 79 1.24e-05 0.05758 0.28314 6
#> MAD:hclust 97 2.39e-01 0.81706 0.17475 6
#> ATC:hclust 132 1.83e-01 0.63353 0.20771 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 51941 rows and 156 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.303 0.716 0.862 0.3455 0.664 0.664
#> 3 3 0.272 0.606 0.773 0.5016 0.718 0.599
#> 4 4 0.244 0.486 0.678 0.1916 0.865 0.723
#> 5 5 0.323 0.497 0.682 0.0846 0.858 0.658
#> 6 6 0.357 0.488 0.645 0.0448 0.968 0.898
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
#> GSM1232995 2 0.0000 0.8466 0.000 1.000
#> GSM1233002 2 0.5737 0.8029 0.136 0.864
#> GSM1233003 1 0.8813 0.6630 0.700 0.300
#> GSM1233014 2 0.2236 0.8461 0.036 0.964
#> GSM1233015 1 0.9552 0.5602 0.624 0.376
#> GSM1233016 2 0.9427 0.4172 0.360 0.640
#> GSM1233024 2 0.0938 0.8483 0.012 0.988
#> GSM1233049 1 0.0000 0.7172 1.000 0.000
#> GSM1233064 2 0.0672 0.8477 0.008 0.992
#> GSM1233068 2 0.7674 0.7132 0.224 0.776
#> GSM1233073 2 0.6973 0.7542 0.188 0.812
#> GSM1233093 1 0.0000 0.7172 1.000 0.000
#> GSM1233115 2 1.0000 -0.1834 0.500 0.500
#> GSM1232992 2 0.0000 0.8466 0.000 1.000
#> GSM1232993 2 0.2043 0.8470 0.032 0.968
#> GSM1233005 2 0.0000 0.8466 0.000 1.000
#> GSM1233007 2 0.1414 0.8483 0.020 0.980
#> GSM1233010 2 0.6438 0.7785 0.164 0.836
#> GSM1233013 2 0.0000 0.8466 0.000 1.000
#> GSM1233018 2 0.0000 0.8466 0.000 1.000
#> GSM1233019 2 0.0376 0.8472 0.004 0.996
#> GSM1233021 2 0.0000 0.8466 0.000 1.000
#> GSM1233025 2 0.9552 0.3868 0.376 0.624
#> GSM1233029 2 0.0672 0.8481 0.008 0.992
#> GSM1233030 2 0.0000 0.8466 0.000 1.000
#> GSM1233031 2 0.5519 0.8106 0.128 0.872
#> GSM1233032 1 0.9710 0.5165 0.600 0.400
#> GSM1233035 2 0.6531 0.7758 0.168 0.832
#> GSM1233038 1 0.0938 0.7246 0.988 0.012
#> GSM1233039 2 0.0938 0.8480 0.012 0.988
#> GSM1233042 2 0.5519 0.8073 0.128 0.872
#> GSM1233043 2 0.5519 0.8073 0.128 0.872
#> GSM1233044 2 0.6531 0.7775 0.168 0.832
#> GSM1233046 2 0.8661 0.6050 0.288 0.712
#> GSM1233051 1 0.9983 0.2531 0.524 0.476
#> GSM1233054 2 0.9881 0.1028 0.436 0.564
#> GSM1233057 2 0.1414 0.8483 0.020 0.980
#> GSM1233060 2 0.5519 0.8073 0.128 0.872
#> GSM1233062 2 0.0938 0.8483 0.012 0.988
#> GSM1233075 2 0.0000 0.8466 0.000 1.000
#> GSM1233078 2 0.5629 0.8031 0.132 0.868
#> GSM1233079 1 0.9608 0.5371 0.616 0.384
#> GSM1233082 2 0.9087 0.5211 0.324 0.676
#> GSM1233083 1 0.5519 0.7431 0.872 0.128
#> GSM1233091 2 0.5842 0.8027 0.140 0.860
#> GSM1233095 1 0.2236 0.7362 0.964 0.036
#> GSM1233096 1 0.9522 0.5679 0.628 0.372
#> GSM1233101 1 0.4022 0.7445 0.920 0.080
#> GSM1233105 2 0.9933 0.0738 0.452 0.548
#> GSM1233117 2 0.0000 0.8466 0.000 1.000
#> GSM1233118 2 0.0000 0.8466 0.000 1.000
#> GSM1233001 2 0.0000 0.8466 0.000 1.000
#> GSM1233006 2 0.0376 0.8472 0.004 0.996
#> GSM1233008 2 0.0000 0.8466 0.000 1.000
#> GSM1233009 2 0.0000 0.8466 0.000 1.000
#> GSM1233017 2 0.0000 0.8466 0.000 1.000
#> GSM1233020 2 0.0000 0.8466 0.000 1.000
#> GSM1233022 2 0.2948 0.8431 0.052 0.948
#> GSM1233026 2 0.6531 0.7747 0.168 0.832
#> GSM1233028 2 0.5629 0.8050 0.132 0.868
#> GSM1233034 2 0.0672 0.8473 0.008 0.992
#> GSM1233040 1 0.9129 0.6333 0.672 0.328
#> GSM1233048 1 0.7139 0.7300 0.804 0.196
#> GSM1233056 1 0.0000 0.7172 1.000 0.000
#> GSM1233058 2 0.6343 0.7825 0.160 0.840
#> GSM1233059 1 0.2948 0.7409 0.948 0.052
#> GSM1233066 2 0.1184 0.8485 0.016 0.984
#> GSM1233071 2 0.3431 0.8388 0.064 0.936
#> GSM1233074 2 0.0000 0.8466 0.000 1.000
#> GSM1233076 2 0.2778 0.8442 0.048 0.952
#> GSM1233080 1 0.0938 0.7246 0.988 0.012
#> GSM1233088 2 0.1414 0.8484 0.020 0.980
#> GSM1233090 1 0.1633 0.7313 0.976 0.024
#> GSM1233092 2 0.7602 0.7029 0.220 0.780
#> GSM1233094 2 0.3431 0.8397 0.064 0.936
#> GSM1233097 2 0.5059 0.8173 0.112 0.888
#> GSM1233100 2 0.4562 0.8263 0.096 0.904
#> GSM1233104 2 0.4939 0.8194 0.108 0.892
#> GSM1233106 2 0.9996 -0.1448 0.488 0.512
#> GSM1233111 1 0.9129 0.6333 0.672 0.328
#> GSM1233122 2 0.0000 0.8466 0.000 1.000
#> GSM1233146 2 0.5737 0.8047 0.136 0.864
#> GSM1232994 2 0.0000 0.8466 0.000 1.000
#> GSM1232996 2 0.0000 0.8466 0.000 1.000
#> GSM1232997 2 0.0000 0.8466 0.000 1.000
#> GSM1232998 2 0.1843 0.8467 0.028 0.972
#> GSM1232999 2 0.0000 0.8466 0.000 1.000
#> GSM1233000 2 0.0000 0.8466 0.000 1.000
#> GSM1233004 2 0.9710 0.2970 0.400 0.600
#> GSM1233011 2 0.4298 0.8305 0.088 0.912
#> GSM1233012 2 0.0000 0.8466 0.000 1.000
#> GSM1233023 2 0.0000 0.8466 0.000 1.000
#> GSM1233027 2 0.0000 0.8466 0.000 1.000
#> GSM1233033 1 0.8713 0.6708 0.708 0.292
#> GSM1233036 2 0.1633 0.8482 0.024 0.976
#> GSM1233037 2 0.2778 0.8445 0.048 0.952
#> GSM1233041 1 0.2603 0.7392 0.956 0.044
#> GSM1233045 2 0.6343 0.7825 0.160 0.840
#> GSM1233047 2 0.9286 0.4482 0.344 0.656
#> GSM1233050 1 0.6148 0.7422 0.848 0.152
#> GSM1233052 2 0.9170 0.5093 0.332 0.668
#> GSM1233053 2 0.9881 0.1028 0.436 0.564
#> GSM1233055 1 0.0000 0.7172 1.000 0.000
#> GSM1233061 2 0.2423 0.8462 0.040 0.960
#> GSM1233063 1 0.9427 0.5895 0.640 0.360
#> GSM1233065 2 0.0000 0.8466 0.000 1.000
#> GSM1233070 2 0.1633 0.8480 0.024 0.976
#> GSM1233077 2 0.5629 0.8032 0.132 0.868
#> GSM1233081 1 0.9896 0.3815 0.560 0.440
#> GSM1233084 1 0.2603 0.7393 0.956 0.044
#> GSM1233087 1 0.9993 0.2228 0.516 0.484
#> GSM1233089 2 0.0000 0.8466 0.000 1.000
#> GSM1233099 2 0.9087 0.5358 0.324 0.676
#> GSM1233112 1 0.6887 0.7314 0.816 0.184
#> GSM1233085 2 0.9209 0.4739 0.336 0.664
#> GSM1233098 2 0.0376 0.8471 0.004 0.996
#> GSM1233114 2 0.8327 0.6494 0.264 0.736
#> GSM1233119 2 0.9044 0.5408 0.320 0.680
#> GSM1233129 2 0.0000 0.8466 0.000 1.000
#> GSM1233132 2 0.9044 0.5440 0.320 0.680
#> GSM1233139 2 0.0376 0.8474 0.004 0.996
#> GSM1233143 2 0.0000 0.8466 0.000 1.000
#> GSM1233145 1 0.5408 0.7442 0.876 0.124
#> GSM1233067 2 0.0000 0.8466 0.000 1.000
#> GSM1233069 2 0.5294 0.8119 0.120 0.880
#> GSM1233072 2 0.0376 0.8472 0.004 0.996
#> GSM1233086 2 0.2043 0.8478 0.032 0.968
#> GSM1233102 2 0.9209 0.5073 0.336 0.664
#> GSM1233103 2 0.8443 0.6360 0.272 0.728
#> GSM1233107 2 0.7376 0.7264 0.208 0.792
#> GSM1233108 1 0.9754 0.4752 0.592 0.408
#> GSM1233109 2 0.9754 0.2677 0.408 0.592
#> GSM1233110 2 0.5408 0.8058 0.124 0.876
#> GSM1233113 2 0.0000 0.8466 0.000 1.000
#> GSM1233116 2 0.0000 0.8466 0.000 1.000
#> GSM1233120 2 0.9087 0.5358 0.324 0.676
#> GSM1233121 2 0.5629 0.8032 0.132 0.868
#> GSM1233123 2 0.4431 0.8246 0.092 0.908
#> GSM1233124 2 0.0938 0.8484 0.012 0.988
#> GSM1233125 1 0.9754 0.4925 0.592 0.408
#> GSM1233126 2 0.9170 0.4948 0.332 0.668
#> GSM1233127 2 0.0000 0.8466 0.000 1.000
#> GSM1233128 1 0.8207 0.6994 0.744 0.256
#> GSM1233130 2 0.5629 0.8039 0.132 0.868
#> GSM1233131 2 0.8327 0.6496 0.264 0.736
#> GSM1233133 2 0.8713 0.5777 0.292 0.708
#> GSM1233134 2 0.0672 0.8477 0.008 0.992
#> GSM1233135 2 0.0000 0.8466 0.000 1.000
#> GSM1233136 2 0.5408 0.8111 0.124 0.876
#> GSM1233137 2 0.8909 0.5421 0.308 0.692
#> GSM1233138 2 0.9000 0.5354 0.316 0.684
#> GSM1233140 1 0.9686 0.5242 0.604 0.396
#> GSM1233141 2 0.0000 0.8466 0.000 1.000
#> GSM1233142 2 0.0000 0.8466 0.000 1.000
#> GSM1233144 2 0.8608 0.5925 0.284 0.716
#> GSM1233147 2 0.2948 0.8437 0.052 0.948
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.1129 0.7973 0.020 0.976 0.004
#> GSM1233002 2 0.6129 0.5044 0.324 0.668 0.008
#> GSM1233003 1 0.8202 0.1363 0.580 0.092 0.328
#> GSM1233014 2 0.4555 0.7142 0.200 0.800 0.000
#> GSM1233015 1 0.5634 0.2951 0.800 0.056 0.144
#> GSM1233016 1 0.7328 0.5494 0.612 0.344 0.044
#> GSM1233024 2 0.2066 0.8059 0.060 0.940 0.000
#> GSM1233049 3 0.1289 0.7702 0.032 0.000 0.968
#> GSM1233064 2 0.1643 0.8084 0.044 0.956 0.000
#> GSM1233068 2 0.7030 0.2023 0.396 0.580 0.024
#> GSM1233073 2 0.6769 0.2850 0.392 0.592 0.016
#> GSM1233093 3 0.1643 0.7736 0.044 0.000 0.956
#> GSM1233115 1 0.7756 0.5577 0.672 0.200 0.128
#> GSM1232992 2 0.1289 0.8063 0.032 0.968 0.000
#> GSM1232993 2 0.3686 0.7655 0.140 0.860 0.000
#> GSM1233005 2 0.1289 0.8063 0.032 0.968 0.000
#> GSM1233007 2 0.3192 0.7892 0.112 0.888 0.000
#> GSM1233010 2 0.6244 0.1869 0.440 0.560 0.000
#> GSM1233013 2 0.1129 0.8033 0.020 0.976 0.004
#> GSM1233018 2 0.0747 0.8030 0.016 0.984 0.000
#> GSM1233019 2 0.1964 0.8057 0.056 0.944 0.000
#> GSM1233021 2 0.1163 0.8062 0.028 0.972 0.000
#> GSM1233025 1 0.7284 0.5544 0.620 0.336 0.044
#> GSM1233029 2 0.1860 0.8062 0.052 0.948 0.000
#> GSM1233030 2 0.1267 0.7994 0.024 0.972 0.004
#> GSM1233031 2 0.6247 0.3968 0.376 0.620 0.004
#> GSM1233032 1 0.7216 0.3974 0.712 0.112 0.176
#> GSM1233035 2 0.6753 0.2614 0.388 0.596 0.016
#> GSM1233038 3 0.4346 0.7903 0.184 0.000 0.816
#> GSM1233039 2 0.1753 0.8085 0.048 0.952 0.000
#> GSM1233042 2 0.5815 0.5485 0.304 0.692 0.004
#> GSM1233043 2 0.5815 0.5485 0.304 0.692 0.004
#> GSM1233044 2 0.6811 0.2831 0.404 0.580 0.016
#> GSM1233046 1 0.7069 0.4453 0.568 0.408 0.024
#> GSM1233051 1 0.6975 0.5314 0.732 0.144 0.124
#> GSM1233054 1 0.8483 0.5195 0.600 0.260 0.140
#> GSM1233057 2 0.2772 0.7976 0.080 0.916 0.004
#> GSM1233060 2 0.5815 0.5485 0.304 0.692 0.004
#> GSM1233062 2 0.2066 0.8043 0.060 0.940 0.000
#> GSM1233075 2 0.1525 0.7942 0.032 0.964 0.004
#> GSM1233078 2 0.6018 0.5323 0.308 0.684 0.008
#> GSM1233079 1 0.5988 0.3452 0.776 0.056 0.168
#> GSM1233082 1 0.7767 0.4297 0.536 0.412 0.052
#> GSM1233083 3 0.6548 0.5399 0.372 0.012 0.616
#> GSM1233091 2 0.5835 0.4726 0.340 0.660 0.000
#> GSM1233095 3 0.4931 0.8018 0.232 0.000 0.768
#> GSM1233096 1 0.5696 0.2902 0.796 0.056 0.148
#> GSM1233101 3 0.5775 0.7866 0.260 0.012 0.728
#> GSM1233105 1 0.7058 0.6023 0.708 0.212 0.080
#> GSM1233117 2 0.1525 0.8051 0.032 0.964 0.004
#> GSM1233118 2 0.1411 0.8069 0.036 0.964 0.000
#> GSM1233001 2 0.1129 0.7938 0.020 0.976 0.004
#> GSM1233006 2 0.1964 0.8056 0.056 0.944 0.000
#> GSM1233008 2 0.1163 0.8067 0.028 0.972 0.000
#> GSM1233009 2 0.1267 0.7979 0.024 0.972 0.004
#> GSM1233017 2 0.1878 0.8073 0.044 0.952 0.004
#> GSM1233020 2 0.0747 0.8027 0.016 0.984 0.000
#> GSM1233022 2 0.4842 0.6846 0.224 0.776 0.000
#> GSM1233026 2 0.6260 0.1504 0.448 0.552 0.000
#> GSM1233028 2 0.6008 0.4153 0.372 0.628 0.000
#> GSM1233034 2 0.1031 0.8043 0.024 0.976 0.000
#> GSM1233040 1 0.5508 0.1756 0.784 0.028 0.188
#> GSM1233048 1 0.7360 -0.4323 0.528 0.032 0.440
#> GSM1233056 3 0.1031 0.7687 0.024 0.000 0.976
#> GSM1233058 2 0.6235 0.2047 0.436 0.564 0.000
#> GSM1233059 3 0.6082 0.7633 0.296 0.012 0.692
#> GSM1233066 2 0.2796 0.8005 0.092 0.908 0.000
#> GSM1233071 2 0.3983 0.7551 0.144 0.852 0.004
#> GSM1233074 2 0.1525 0.7942 0.032 0.964 0.004
#> GSM1233076 2 0.3851 0.7747 0.136 0.860 0.004
#> GSM1233080 3 0.4062 0.7989 0.164 0.000 0.836
#> GSM1233088 2 0.2066 0.8071 0.060 0.940 0.000
#> GSM1233090 3 0.4702 0.8018 0.212 0.000 0.788
#> GSM1233092 2 0.7091 0.1406 0.416 0.560 0.024
#> GSM1233094 2 0.5138 0.6526 0.252 0.748 0.000
#> GSM1233097 2 0.5678 0.5501 0.316 0.684 0.000
#> GSM1233100 2 0.5397 0.6016 0.280 0.720 0.000
#> GSM1233104 2 0.5621 0.5638 0.308 0.692 0.000
#> GSM1233106 1 0.7457 0.5648 0.688 0.208 0.104
#> GSM1233111 1 0.5508 0.1756 0.784 0.028 0.188
#> GSM1233122 2 0.1860 0.8066 0.052 0.948 0.000
#> GSM1233146 2 0.6180 0.5017 0.332 0.660 0.008
#> GSM1232994 2 0.1399 0.8021 0.028 0.968 0.004
#> GSM1232996 2 0.0747 0.8030 0.016 0.984 0.000
#> GSM1232997 2 0.1163 0.8003 0.028 0.972 0.000
#> GSM1232998 2 0.4178 0.7406 0.172 0.828 0.000
#> GSM1232999 2 0.1964 0.8055 0.056 0.944 0.000
#> GSM1233000 2 0.1267 0.8013 0.024 0.972 0.004
#> GSM1233004 1 0.7788 0.6134 0.632 0.284 0.084
#> GSM1233011 2 0.5291 0.6340 0.268 0.732 0.000
#> GSM1233012 2 0.1765 0.7986 0.040 0.956 0.004
#> GSM1233023 2 0.1267 0.7998 0.024 0.972 0.004
#> GSM1233027 2 0.1289 0.8063 0.032 0.968 0.000
#> GSM1233033 1 0.8242 0.1120 0.572 0.092 0.336
#> GSM1233036 2 0.3412 0.7855 0.124 0.876 0.000
#> GSM1233037 2 0.3784 0.7730 0.132 0.864 0.004
#> GSM1233041 3 0.5656 0.7857 0.264 0.008 0.728
#> GSM1233045 2 0.6235 0.2047 0.436 0.564 0.000
#> GSM1233047 1 0.7644 0.5323 0.604 0.336 0.060
#> GSM1233050 3 0.7067 0.5708 0.468 0.020 0.512
#> GSM1233052 1 0.7712 0.4661 0.556 0.392 0.052
#> GSM1233053 1 0.8483 0.5195 0.600 0.260 0.140
#> GSM1233055 3 0.1163 0.7697 0.028 0.000 0.972
#> GSM1233061 2 0.4002 0.7567 0.160 0.840 0.000
#> GSM1233063 1 0.6254 0.2854 0.756 0.056 0.188
#> GSM1233065 2 0.0892 0.8003 0.020 0.980 0.000
#> GSM1233070 2 0.2772 0.8007 0.080 0.916 0.004
#> GSM1233077 2 0.5929 0.5185 0.320 0.676 0.004
#> GSM1233081 1 0.7147 0.4731 0.720 0.124 0.156
#> GSM1233084 3 0.5728 0.7853 0.272 0.008 0.720
#> GSM1233087 1 0.9385 0.5366 0.512 0.248 0.240
#> GSM1233089 2 0.1643 0.8081 0.044 0.956 0.000
#> GSM1233099 1 0.7492 0.5465 0.608 0.340 0.052
#> GSM1233112 3 0.6822 0.3885 0.480 0.012 0.508
#> GSM1233085 1 0.7620 0.5181 0.596 0.348 0.056
#> GSM1233098 2 0.1964 0.8091 0.056 0.944 0.000
#> GSM1233114 1 0.7299 0.4188 0.556 0.412 0.032
#> GSM1233119 1 0.6969 0.4754 0.596 0.380 0.024
#> GSM1233129 2 0.1289 0.8057 0.032 0.968 0.000
#> GSM1233132 1 0.7513 0.5412 0.604 0.344 0.052
#> GSM1233139 2 0.1647 0.8046 0.036 0.960 0.004
#> GSM1233143 2 0.1878 0.7934 0.044 0.952 0.004
#> GSM1233145 3 0.6244 0.5393 0.440 0.000 0.560
#> GSM1233067 2 0.1525 0.7978 0.032 0.964 0.004
#> GSM1233069 2 0.5958 0.5489 0.300 0.692 0.008
#> GSM1233072 2 0.1860 0.8072 0.052 0.948 0.000
#> GSM1233086 2 0.3752 0.7773 0.144 0.856 0.000
#> GSM1233102 1 0.7514 0.5628 0.616 0.328 0.056
#> GSM1233103 1 0.7138 0.3637 0.540 0.436 0.024
#> GSM1233107 1 0.6291 0.2419 0.532 0.468 0.000
#> GSM1233108 1 0.6622 0.4093 0.748 0.088 0.164
#> GSM1233109 1 0.7433 0.6271 0.660 0.268 0.072
#> GSM1233110 2 0.6018 0.5231 0.308 0.684 0.008
#> GSM1233113 2 0.1399 0.7943 0.028 0.968 0.004
#> GSM1233116 2 0.1525 0.7954 0.032 0.964 0.004
#> GSM1233120 1 0.7492 0.5465 0.608 0.340 0.052
#> GSM1233121 2 0.5929 0.5185 0.320 0.676 0.004
#> GSM1233123 2 0.5541 0.6235 0.252 0.740 0.008
#> GSM1233124 2 0.3349 0.7930 0.108 0.888 0.004
#> GSM1233125 1 0.8311 0.4533 0.628 0.156 0.216
#> GSM1233126 1 0.7099 0.4741 0.588 0.384 0.028
#> GSM1233127 2 0.2496 0.7981 0.068 0.928 0.004
#> GSM1233128 1 0.6113 -0.0557 0.688 0.012 0.300
#> GSM1233130 2 0.6047 0.5291 0.312 0.680 0.008
#> GSM1233131 1 0.6897 0.3550 0.548 0.436 0.016
#> GSM1233133 1 0.7464 0.4229 0.560 0.400 0.040
#> GSM1233134 2 0.2866 0.7845 0.076 0.916 0.008
#> GSM1233135 2 0.1585 0.7960 0.028 0.964 0.008
#> GSM1233136 2 0.5797 0.5931 0.280 0.712 0.008
#> GSM1233137 1 0.7610 0.4503 0.564 0.388 0.048
#> GSM1233138 1 0.7156 0.4409 0.572 0.400 0.028
#> GSM1233140 1 0.6699 0.3888 0.744 0.092 0.164
#> GSM1233141 2 0.2400 0.8004 0.064 0.932 0.004
#> GSM1233142 2 0.2496 0.7981 0.068 0.928 0.004
#> GSM1233144 1 0.7389 0.4068 0.556 0.408 0.036
#> GSM1233147 2 0.4172 0.7616 0.156 0.840 0.004
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.152 0.73599 0.000 0.956 0.020 0.024
#> GSM1233002 2 0.546 0.15833 0.004 0.508 0.008 0.480
#> GSM1233003 4 0.881 -0.20630 0.296 0.056 0.224 0.424
#> GSM1233014 2 0.527 0.53762 0.000 0.640 0.020 0.340
#> GSM1233015 4 0.737 -0.41886 0.112 0.012 0.432 0.444
#> GSM1233016 4 0.633 0.45987 0.016 0.200 0.100 0.684
#> GSM1233024 2 0.336 0.73075 0.000 0.824 0.000 0.176
#> GSM1233049 1 0.172 0.68597 0.936 0.000 0.064 0.000
#> GSM1233064 2 0.284 0.75707 0.000 0.892 0.020 0.088
#> GSM1233068 4 0.689 0.16993 0.016 0.440 0.064 0.480
#> GSM1233073 4 0.645 0.12842 0.012 0.424 0.044 0.520
#> GSM1233093 1 0.104 0.70564 0.972 0.000 0.008 0.020
#> GSM1233115 4 0.858 -0.00614 0.092 0.124 0.296 0.488
#> GSM1232992 2 0.292 0.74344 0.000 0.860 0.000 0.140
#> GSM1232993 2 0.443 0.64340 0.000 0.720 0.004 0.276
#> GSM1233005 2 0.292 0.74344 0.000 0.860 0.000 0.140
#> GSM1233007 2 0.424 0.71484 0.000 0.784 0.020 0.196
#> GSM1233010 4 0.677 0.19989 0.000 0.408 0.096 0.496
#> GSM1233013 2 0.247 0.75592 0.000 0.900 0.004 0.096
#> GSM1233018 2 0.213 0.75584 0.000 0.920 0.004 0.076
#> GSM1233019 2 0.349 0.72530 0.000 0.812 0.000 0.188
#> GSM1233021 2 0.276 0.74759 0.000 0.872 0.000 0.128
#> GSM1233025 4 0.650 0.45090 0.024 0.184 0.108 0.684
#> GSM1233029 2 0.327 0.73191 0.000 0.832 0.000 0.168
#> GSM1233030 2 0.241 0.74841 0.000 0.908 0.008 0.084
#> GSM1233031 4 0.594 -0.04219 0.004 0.464 0.028 0.504
#> GSM1233032 3 0.833 0.39791 0.140 0.052 0.456 0.352
#> GSM1233035 4 0.614 0.13568 0.008 0.444 0.032 0.516
#> GSM1233038 1 0.491 0.70662 0.776 0.000 0.084 0.140
#> GSM1233039 2 0.284 0.75749 0.000 0.892 0.020 0.088
#> GSM1233042 2 0.499 0.23633 0.000 0.528 0.000 0.472
#> GSM1233043 2 0.499 0.23633 0.000 0.528 0.000 0.472
#> GSM1233044 4 0.672 0.15847 0.012 0.428 0.060 0.500
#> GSM1233046 4 0.571 0.48989 0.008 0.212 0.068 0.712
#> GSM1233051 4 0.834 -0.19338 0.108 0.084 0.304 0.504
#> GSM1233054 3 0.653 0.47488 0.076 0.096 0.716 0.112
#> GSM1233057 2 0.347 0.70472 0.000 0.868 0.072 0.060
#> GSM1233060 2 0.499 0.23633 0.000 0.528 0.000 0.472
#> GSM1233062 2 0.354 0.72669 0.000 0.820 0.004 0.176
#> GSM1233075 2 0.182 0.72841 0.000 0.944 0.020 0.036
#> GSM1233078 2 0.688 0.36142 0.000 0.596 0.192 0.212
#> GSM1233079 3 0.774 0.40239 0.132 0.020 0.432 0.416
#> GSM1233082 4 0.842 0.38500 0.048 0.304 0.176 0.472
#> GSM1233083 1 0.668 0.48601 0.576 0.000 0.112 0.312
#> GSM1233091 2 0.637 0.19470 0.000 0.540 0.068 0.392
#> GSM1233095 1 0.523 0.71626 0.752 0.000 0.152 0.096
#> GSM1233096 4 0.741 -0.41847 0.116 0.012 0.432 0.440
#> GSM1233101 1 0.591 0.69664 0.700 0.004 0.200 0.096
#> GSM1233105 4 0.658 0.20863 0.044 0.076 0.196 0.684
#> GSM1233117 2 0.182 0.74173 0.000 0.944 0.020 0.036
#> GSM1233118 2 0.177 0.75670 0.000 0.944 0.012 0.044
#> GSM1233001 2 0.104 0.73253 0.000 0.972 0.008 0.020
#> GSM1233006 2 0.361 0.72302 0.000 0.800 0.000 0.200
#> GSM1233008 2 0.220 0.76055 0.000 0.916 0.004 0.080
#> GSM1233009 2 0.198 0.74413 0.000 0.928 0.004 0.068
#> GSM1233017 2 0.310 0.74843 0.000 0.856 0.004 0.140
#> GSM1233020 2 0.220 0.75700 0.000 0.916 0.004 0.080
#> GSM1233022 2 0.527 0.48488 0.000 0.620 0.016 0.364
#> GSM1233026 4 0.689 0.23785 0.000 0.400 0.108 0.492
#> GSM1233028 2 0.621 0.03960 0.000 0.480 0.052 0.468
#> GSM1233034 2 0.202 0.75640 0.000 0.932 0.012 0.056
#> GSM1233040 3 0.763 0.25989 0.156 0.008 0.428 0.408
#> GSM1233048 1 0.808 0.22077 0.412 0.008 0.312 0.268
#> GSM1233056 1 0.106 0.69707 0.972 0.000 0.012 0.016
#> GSM1233058 4 0.673 0.18212 0.000 0.416 0.092 0.492
#> GSM1233059 1 0.595 0.67126 0.696 0.000 0.152 0.152
#> GSM1233066 2 0.390 0.72927 0.000 0.840 0.052 0.108
#> GSM1233071 2 0.453 0.66181 0.000 0.744 0.016 0.240
#> GSM1233074 2 0.182 0.72841 0.000 0.944 0.020 0.036
#> GSM1233076 2 0.504 0.69309 0.004 0.764 0.060 0.172
#> GSM1233080 1 0.408 0.72352 0.832 0.000 0.100 0.068
#> GSM1233088 2 0.321 0.75492 0.000 0.872 0.024 0.104
#> GSM1233090 1 0.485 0.71617 0.776 0.000 0.152 0.072
#> GSM1233092 4 0.651 0.20765 0.008 0.408 0.056 0.528
#> GSM1233094 2 0.542 0.40410 0.000 0.572 0.016 0.412
#> GSM1233097 2 0.584 0.22839 0.000 0.520 0.032 0.448
#> GSM1233100 2 0.548 0.30205 0.000 0.536 0.016 0.448
#> GSM1233104 2 0.584 0.24732 0.000 0.520 0.032 0.448
#> GSM1233106 4 0.877 -0.17425 0.100 0.128 0.316 0.456
#> GSM1233111 3 0.763 0.25989 0.156 0.008 0.428 0.408
#> GSM1233122 2 0.349 0.72881 0.000 0.812 0.000 0.188
#> GSM1233146 2 0.557 0.16095 0.004 0.504 0.012 0.480
#> GSM1232994 2 0.259 0.75363 0.000 0.892 0.004 0.104
#> GSM1232996 2 0.205 0.75597 0.000 0.924 0.004 0.072
#> GSM1232997 2 0.194 0.75093 0.000 0.936 0.012 0.052
#> GSM1232998 2 0.507 0.58049 0.000 0.664 0.016 0.320
#> GSM1232999 2 0.336 0.73230 0.000 0.824 0.000 0.176
#> GSM1233000 2 0.247 0.75407 0.000 0.900 0.004 0.096
#> GSM1233004 4 0.859 0.24532 0.072 0.192 0.232 0.504
#> GSM1233011 2 0.606 0.42735 0.000 0.604 0.060 0.336
#> GSM1233012 2 0.255 0.73659 0.000 0.912 0.028 0.060
#> GSM1233023 2 0.130 0.74535 0.000 0.956 0.000 0.044
#> GSM1233027 2 0.292 0.74344 0.000 0.860 0.000 0.140
#> GSM1233033 4 0.876 -0.20962 0.300 0.052 0.224 0.424
#> GSM1233036 2 0.439 0.70411 0.000 0.776 0.024 0.200
#> GSM1233037 2 0.436 0.66343 0.000 0.816 0.096 0.088
#> GSM1233041 1 0.568 0.69442 0.720 0.000 0.136 0.144
#> GSM1233045 4 0.673 0.18212 0.000 0.416 0.092 0.492
#> GSM1233047 3 0.698 0.53964 0.016 0.172 0.632 0.180
#> GSM1233050 1 0.770 0.45814 0.512 0.012 0.292 0.184
#> GSM1233052 4 0.765 0.45529 0.044 0.260 0.120 0.576
#> GSM1233053 3 0.653 0.47488 0.076 0.096 0.716 0.112
#> GSM1233055 1 0.118 0.69831 0.968 0.000 0.016 0.016
#> GSM1233061 2 0.512 0.66232 0.000 0.764 0.108 0.128
#> GSM1233063 4 0.798 -0.34550 0.172 0.020 0.352 0.456
#> GSM1233065 2 0.100 0.74768 0.000 0.972 0.004 0.024
#> GSM1233070 2 0.393 0.72102 0.000 0.792 0.008 0.200
#> GSM1233077 2 0.698 0.34012 0.000 0.584 0.204 0.212
#> GSM1233081 3 0.795 0.46066 0.116 0.040 0.468 0.376
#> GSM1233084 1 0.567 0.70020 0.720 0.000 0.148 0.132
#> GSM1233087 4 0.875 0.28042 0.212 0.164 0.112 0.512
#> GSM1233089 2 0.277 0.75662 0.000 0.880 0.004 0.116
#> GSM1233099 4 0.522 0.45149 0.040 0.132 0.044 0.784
#> GSM1233112 1 0.765 0.38881 0.456 0.000 0.232 0.312
#> GSM1233085 3 0.682 0.53214 0.008 0.172 0.632 0.188
#> GSM1233098 2 0.265 0.75896 0.000 0.880 0.000 0.120
#> GSM1233114 4 0.576 0.48138 0.024 0.200 0.052 0.724
#> GSM1233119 4 0.640 0.48742 0.012 0.228 0.096 0.664
#> GSM1233129 2 0.166 0.75677 0.000 0.944 0.004 0.052
#> GSM1233132 4 0.544 0.45027 0.040 0.136 0.052 0.772
#> GSM1233139 2 0.212 0.75104 0.000 0.924 0.008 0.068
#> GSM1233143 2 0.267 0.72594 0.000 0.908 0.044 0.048
#> GSM1233145 1 0.695 0.47381 0.516 0.000 0.120 0.364
#> GSM1233067 2 0.238 0.73048 0.000 0.920 0.028 0.052
#> GSM1233069 2 0.679 0.38064 0.000 0.608 0.200 0.192
#> GSM1233072 2 0.331 0.74574 0.000 0.840 0.004 0.156
#> GSM1233086 2 0.514 0.68396 0.000 0.744 0.064 0.192
#> GSM1233102 4 0.534 0.44334 0.044 0.128 0.048 0.780
#> GSM1233103 4 0.584 0.49782 0.012 0.248 0.052 0.688
#> GSM1233107 4 0.546 0.49319 0.000 0.256 0.052 0.692
#> GSM1233108 3 0.794 0.42609 0.128 0.032 0.436 0.404
#> GSM1233109 4 0.864 -0.19656 0.056 0.172 0.368 0.404
#> GSM1233110 2 0.702 0.31454 0.000 0.572 0.252 0.176
#> GSM1233113 2 0.172 0.72839 0.000 0.948 0.020 0.032
#> GSM1233116 2 0.191 0.73300 0.000 0.940 0.020 0.040
#> GSM1233120 4 0.522 0.45149 0.040 0.132 0.044 0.784
#> GSM1233121 2 0.698 0.34012 0.000 0.584 0.204 0.212
#> GSM1233123 2 0.639 0.47164 0.000 0.652 0.188 0.160
#> GSM1233124 2 0.533 0.66251 0.000 0.748 0.116 0.136
#> GSM1233125 4 0.914 -0.43328 0.176 0.096 0.360 0.368
#> GSM1233126 4 0.625 0.47632 0.008 0.232 0.092 0.668
#> GSM1233127 2 0.314 0.72817 0.000 0.860 0.008 0.132
#> GSM1233128 4 0.785 -0.37320 0.272 0.000 0.344 0.384
#> GSM1233130 2 0.709 0.35767 0.004 0.588 0.200 0.208
#> GSM1233131 4 0.580 0.49946 0.012 0.252 0.048 0.688
#> GSM1233133 3 0.737 0.42201 0.004 0.232 0.548 0.216
#> GSM1233134 2 0.430 0.65560 0.000 0.816 0.120 0.064
#> GSM1233135 2 0.211 0.73050 0.000 0.932 0.024 0.044
#> GSM1233136 2 0.675 0.43625 0.004 0.628 0.172 0.196
#> GSM1233137 3 0.600 0.50650 0.000 0.184 0.688 0.128
#> GSM1233138 4 0.622 0.48309 0.008 0.244 0.084 0.664
#> GSM1233140 3 0.835 0.36013 0.136 0.052 0.408 0.404
#> GSM1233141 2 0.314 0.72980 0.000 0.860 0.008 0.132
#> GSM1233142 2 0.314 0.72817 0.000 0.860 0.008 0.132
#> GSM1233144 3 0.739 0.41216 0.004 0.240 0.544 0.212
#> GSM1233147 2 0.532 0.66596 0.004 0.728 0.052 0.216
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.1403 0.70896 0.000 0.952 0.024 0.024 0.000
#> GSM1233002 4 0.5439 0.40229 0.040 0.392 0.012 0.556 0.000
#> GSM1233003 1 0.7320 0.35397 0.476 0.020 0.016 0.288 0.200
#> GSM1233014 4 0.4706 -0.03905 0.004 0.492 0.008 0.496 0.000
#> GSM1233015 1 0.5769 0.51400 0.684 0.004 0.096 0.184 0.032
#> GSM1233016 4 0.6631 0.39838 0.208 0.132 0.036 0.612 0.012
#> GSM1233024 2 0.3766 0.59906 0.000 0.728 0.004 0.268 0.000
#> GSM1233049 5 0.2270 0.66171 0.020 0.000 0.076 0.000 0.904
#> GSM1233064 2 0.2833 0.71501 0.004 0.864 0.012 0.120 0.000
#> GSM1233068 4 0.6422 0.50747 0.116 0.340 0.020 0.524 0.000
#> GSM1233073 4 0.5684 0.54394 0.064 0.288 0.016 0.628 0.004
#> GSM1233093 5 0.1569 0.68082 0.044 0.000 0.008 0.004 0.944
#> GSM1233115 1 0.8175 0.24216 0.388 0.072 0.136 0.368 0.036
#> GSM1232992 2 0.3395 0.64425 0.000 0.764 0.000 0.236 0.000
#> GSM1232993 2 0.4210 0.31523 0.000 0.588 0.000 0.412 0.000
#> GSM1233005 2 0.3366 0.64910 0.000 0.768 0.000 0.232 0.000
#> GSM1233007 2 0.4394 0.62015 0.016 0.716 0.012 0.256 0.000
#> GSM1233010 4 0.7083 0.47968 0.128 0.308 0.060 0.504 0.000
#> GSM1233013 2 0.2813 0.68989 0.000 0.832 0.000 0.168 0.000
#> GSM1233018 2 0.2806 0.70456 0.000 0.844 0.004 0.152 0.000
#> GSM1233019 2 0.3684 0.60355 0.000 0.720 0.000 0.280 0.000
#> GSM1233021 2 0.3274 0.66330 0.000 0.780 0.000 0.220 0.000
#> GSM1233025 4 0.6904 0.35883 0.216 0.108 0.048 0.604 0.024
#> GSM1233029 2 0.3534 0.62381 0.000 0.744 0.000 0.256 0.000
#> GSM1233030 2 0.2597 0.70074 0.004 0.872 0.004 0.120 0.000
#> GSM1233031 4 0.5982 0.43987 0.052 0.372 0.024 0.548 0.004
#> GSM1233032 1 0.7277 0.41196 0.588 0.032 0.192 0.128 0.060
#> GSM1233035 4 0.5967 0.47512 0.056 0.364 0.016 0.556 0.008
#> GSM1233038 5 0.5158 0.62832 0.148 0.000 0.036 0.080 0.736
#> GSM1233039 2 0.2833 0.71540 0.004 0.864 0.012 0.120 0.000
#> GSM1233042 4 0.5049 0.35689 0.028 0.408 0.004 0.560 0.000
#> GSM1233043 4 0.5049 0.35689 0.028 0.408 0.004 0.560 0.000
#> GSM1233044 4 0.6884 0.48311 0.092 0.348 0.052 0.504 0.004
#> GSM1233046 4 0.5086 0.49058 0.104 0.120 0.024 0.748 0.004
#> GSM1233051 1 0.7208 0.42103 0.524 0.056 0.076 0.316 0.028
#> GSM1233054 3 0.6045 0.55037 0.176 0.044 0.692 0.044 0.044
#> GSM1233057 2 0.3189 0.66125 0.020 0.868 0.080 0.032 0.000
#> GSM1233060 4 0.5049 0.35689 0.028 0.408 0.004 0.560 0.000
#> GSM1233062 2 0.3968 0.59154 0.004 0.716 0.004 0.276 0.000
#> GSM1233075 2 0.1469 0.69780 0.000 0.948 0.036 0.016 0.000
#> GSM1233078 2 0.7056 0.27833 0.064 0.552 0.172 0.212 0.000
#> GSM1233079 1 0.7828 0.24235 0.440 0.008 0.276 0.212 0.064
#> GSM1233082 4 0.7718 0.36989 0.280 0.232 0.056 0.428 0.004
#> GSM1233083 5 0.7200 0.35698 0.204 0.000 0.056 0.220 0.520
#> GSM1233091 2 0.6618 -0.24865 0.088 0.460 0.040 0.412 0.000
#> GSM1233095 5 0.5355 0.63898 0.216 0.000 0.064 0.028 0.692
#> GSM1233096 1 0.5801 0.51346 0.680 0.004 0.096 0.188 0.032
#> GSM1233101 5 0.5825 0.59397 0.272 0.004 0.052 0.036 0.636
#> GSM1233105 4 0.5746 -0.15486 0.348 0.024 0.024 0.588 0.016
#> GSM1233117 2 0.1661 0.71287 0.000 0.940 0.024 0.036 0.000
#> GSM1233118 2 0.2305 0.72630 0.000 0.896 0.012 0.092 0.000
#> GSM1233001 2 0.0451 0.70277 0.000 0.988 0.004 0.008 0.000
#> GSM1233006 2 0.3730 0.59909 0.000 0.712 0.000 0.288 0.000
#> GSM1233008 2 0.2674 0.72348 0.000 0.868 0.012 0.120 0.000
#> GSM1233009 2 0.2068 0.70380 0.000 0.904 0.004 0.092 0.000
#> GSM1233017 2 0.3398 0.65428 0.004 0.780 0.000 0.216 0.000
#> GSM1233020 2 0.2773 0.69746 0.000 0.836 0.000 0.164 0.000
#> GSM1233022 4 0.4702 0.06964 0.008 0.476 0.004 0.512 0.000
#> GSM1233026 4 0.7289 0.48177 0.144 0.300 0.068 0.488 0.000
#> GSM1233028 4 0.6553 0.42263 0.084 0.356 0.044 0.516 0.000
#> GSM1233034 2 0.2054 0.72359 0.004 0.916 0.008 0.072 0.000
#> GSM1233040 1 0.5490 0.51691 0.716 0.000 0.092 0.144 0.048
#> GSM1233048 1 0.7095 0.10434 0.512 0.004 0.068 0.100 0.316
#> GSM1233056 5 0.1179 0.67436 0.016 0.000 0.016 0.004 0.964
#> GSM1233058 4 0.7019 0.47636 0.124 0.316 0.056 0.504 0.000
#> GSM1233059 5 0.5735 0.52301 0.312 0.000 0.036 0.044 0.608
#> GSM1233066 2 0.4208 0.66936 0.008 0.784 0.056 0.152 0.000
#> GSM1233071 2 0.4579 0.49215 0.016 0.668 0.008 0.308 0.000
#> GSM1233074 2 0.1469 0.69780 0.000 0.948 0.036 0.016 0.000
#> GSM1233076 2 0.5165 0.60017 0.024 0.704 0.044 0.224 0.004
#> GSM1233080 5 0.4195 0.67240 0.140 0.000 0.040 0.024 0.796
#> GSM1233088 2 0.3124 0.70991 0.004 0.844 0.016 0.136 0.000
#> GSM1233090 5 0.4937 0.65109 0.172 0.000 0.060 0.028 0.740
#> GSM1233092 4 0.6787 0.45949 0.116 0.316 0.024 0.532 0.012
#> GSM1233094 4 0.4604 0.22026 0.012 0.428 0.000 0.560 0.000
#> GSM1233097 4 0.5826 0.36799 0.040 0.384 0.032 0.544 0.000
#> GSM1233100 4 0.4620 0.34103 0.016 0.392 0.000 0.592 0.000
#> GSM1233104 4 0.5826 0.35240 0.040 0.384 0.032 0.544 0.000
#> GSM1233106 1 0.7619 0.38798 0.496 0.096 0.080 0.304 0.024
#> GSM1233111 1 0.5490 0.51691 0.716 0.000 0.092 0.144 0.048
#> GSM1233122 2 0.3661 0.61206 0.000 0.724 0.000 0.276 0.000
#> GSM1233146 4 0.5338 0.39603 0.040 0.392 0.008 0.560 0.000
#> GSM1232994 2 0.2852 0.68561 0.000 0.828 0.000 0.172 0.000
#> GSM1232996 2 0.2806 0.70599 0.000 0.844 0.004 0.152 0.000
#> GSM1232997 2 0.2012 0.71910 0.000 0.920 0.020 0.060 0.000
#> GSM1232998 2 0.4700 0.12285 0.004 0.516 0.008 0.472 0.000
#> GSM1232999 2 0.3814 0.60271 0.000 0.720 0.004 0.276 0.000
#> GSM1233000 2 0.2732 0.69139 0.000 0.840 0.000 0.160 0.000
#> GSM1233004 4 0.8243 0.00347 0.284 0.116 0.144 0.436 0.020
#> GSM1233011 2 0.6316 0.16031 0.072 0.544 0.040 0.344 0.000
#> GSM1233012 2 0.2592 0.70525 0.000 0.892 0.052 0.056 0.000
#> GSM1233023 2 0.1484 0.71798 0.000 0.944 0.008 0.048 0.000
#> GSM1233027 2 0.3395 0.64425 0.000 0.764 0.000 0.236 0.000
#> GSM1233033 1 0.7273 0.34931 0.492 0.020 0.016 0.268 0.204
#> GSM1233036 2 0.4631 0.62554 0.024 0.728 0.024 0.224 0.000
#> GSM1233037 2 0.4154 0.61359 0.048 0.816 0.092 0.044 0.000
#> GSM1233041 5 0.4974 0.56196 0.316 0.000 0.004 0.040 0.640
#> GSM1233045 4 0.7019 0.47636 0.124 0.316 0.056 0.504 0.000
#> GSM1233047 3 0.6256 0.67598 0.144 0.108 0.668 0.076 0.004
#> GSM1233050 1 0.7089 -0.21589 0.440 0.004 0.080 0.072 0.404
#> GSM1233052 4 0.6469 0.44943 0.208 0.164 0.024 0.600 0.004
#> GSM1233053 3 0.6045 0.55037 0.176 0.044 0.692 0.044 0.044
#> GSM1233055 5 0.1787 0.67844 0.032 0.000 0.016 0.012 0.940
#> GSM1233061 2 0.5164 0.60170 0.020 0.728 0.120 0.132 0.000
#> GSM1233063 1 0.6510 0.54090 0.616 0.016 0.056 0.248 0.064
#> GSM1233065 2 0.1557 0.72017 0.000 0.940 0.008 0.052 0.000
#> GSM1233070 2 0.4088 0.60495 0.008 0.712 0.004 0.276 0.000
#> GSM1233077 2 0.7112 0.26522 0.064 0.544 0.180 0.212 0.000
#> GSM1233081 3 0.8186 -0.07673 0.336 0.028 0.380 0.200 0.056
#> GSM1233084 5 0.5106 0.59321 0.292 0.000 0.016 0.036 0.656
#> GSM1233087 4 0.8232 0.03046 0.208 0.084 0.052 0.500 0.156
#> GSM1233089 2 0.2813 0.70825 0.000 0.832 0.000 0.168 0.000
#> GSM1233099 4 0.2207 0.38416 0.044 0.012 0.012 0.924 0.008
#> GSM1233112 5 0.8408 0.21449 0.252 0.000 0.160 0.248 0.340
#> GSM1233085 3 0.5958 0.68691 0.120 0.112 0.688 0.080 0.000
#> GSM1233098 2 0.2970 0.70902 0.000 0.828 0.004 0.168 0.000
#> GSM1233114 4 0.3383 0.48009 0.028 0.076 0.028 0.864 0.004
#> GSM1233119 4 0.6653 0.45187 0.180 0.128 0.052 0.628 0.012
#> GSM1233129 2 0.2077 0.72378 0.000 0.908 0.008 0.084 0.000
#> GSM1233132 4 0.2253 0.38313 0.036 0.012 0.020 0.924 0.008
#> GSM1233139 2 0.2177 0.71537 0.004 0.908 0.008 0.080 0.000
#> GSM1233143 2 0.2673 0.69166 0.004 0.892 0.060 0.044 0.000
#> GSM1233145 5 0.7665 0.30554 0.236 0.000 0.068 0.256 0.440
#> GSM1233067 2 0.2536 0.69236 0.004 0.900 0.052 0.044 0.000
#> GSM1233069 2 0.6902 0.30954 0.056 0.568 0.180 0.196 0.000
#> GSM1233072 2 0.3366 0.66885 0.000 0.768 0.000 0.232 0.000
#> GSM1233086 2 0.5330 0.58448 0.024 0.688 0.064 0.224 0.000
#> GSM1233102 4 0.2498 0.36754 0.048 0.012 0.016 0.912 0.012
#> GSM1233103 4 0.4721 0.54273 0.072 0.140 0.024 0.764 0.000
#> GSM1233107 4 0.3734 0.55300 0.020 0.128 0.028 0.824 0.000
#> GSM1233108 1 0.8269 0.14089 0.376 0.020 0.300 0.236 0.068
#> GSM1233109 1 0.8748 -0.08450 0.296 0.136 0.264 0.288 0.016
#> GSM1233110 2 0.6993 0.21789 0.040 0.508 0.292 0.160 0.000
#> GSM1233113 2 0.1648 0.69318 0.000 0.940 0.040 0.020 0.000
#> GSM1233116 2 0.1911 0.69857 0.004 0.932 0.028 0.036 0.000
#> GSM1233120 4 0.2207 0.38416 0.044 0.012 0.012 0.924 0.008
#> GSM1233121 2 0.7112 0.26522 0.064 0.544 0.180 0.212 0.000
#> GSM1233123 2 0.6424 0.39812 0.036 0.608 0.200 0.156 0.000
#> GSM1233124 2 0.5185 0.56491 0.004 0.700 0.168 0.128 0.000
#> GSM1233125 1 0.7933 0.39713 0.552 0.076 0.132 0.172 0.068
#> GSM1233126 4 0.6619 0.45564 0.172 0.152 0.040 0.624 0.012
#> GSM1233127 2 0.3474 0.65682 0.004 0.796 0.008 0.192 0.000
#> GSM1233128 1 0.5652 0.44967 0.680 0.000 0.020 0.152 0.148
#> GSM1233130 2 0.7288 0.27186 0.068 0.540 0.180 0.208 0.004
#> GSM1233131 4 0.4746 0.54770 0.068 0.140 0.028 0.764 0.000
#> GSM1233133 3 0.6637 0.61588 0.084 0.164 0.620 0.132 0.000
#> GSM1233134 2 0.4271 0.57754 0.008 0.768 0.180 0.044 0.000
#> GSM1233135 2 0.2234 0.69173 0.004 0.916 0.044 0.036 0.000
#> GSM1233136 2 0.6894 0.33935 0.056 0.580 0.144 0.216 0.004
#> GSM1233137 3 0.4926 0.66819 0.064 0.116 0.764 0.056 0.000
#> GSM1233138 4 0.6518 0.47437 0.164 0.156 0.036 0.632 0.012
#> GSM1233140 1 0.6433 0.49764 0.664 0.036 0.108 0.160 0.032
#> GSM1233141 2 0.3544 0.65442 0.004 0.788 0.008 0.200 0.000
#> GSM1233142 2 0.3474 0.65682 0.004 0.796 0.008 0.192 0.000
#> GSM1233144 3 0.6663 0.60914 0.084 0.172 0.616 0.128 0.000
#> GSM1233147 2 0.5375 0.54605 0.024 0.664 0.040 0.268 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.1819 0.69218 0.000 0.932 0.032 0.024 0.004 0.008
#> GSM1233002 4 0.5404 0.44799 0.000 0.356 0.008 0.564 0.040 0.032
#> GSM1233003 5 0.8059 0.26694 0.168 0.020 0.008 0.208 0.376 0.220
#> GSM1233014 4 0.4442 0.10639 0.000 0.440 0.004 0.536 0.000 0.020
#> GSM1233015 5 0.2651 0.56601 0.000 0.004 0.016 0.084 0.880 0.016
#> GSM1233016 4 0.6166 0.30859 0.004 0.112 0.004 0.580 0.052 0.248
#> GSM1233024 2 0.3693 0.56837 0.000 0.708 0.004 0.280 0.000 0.008
#> GSM1233049 1 0.2322 0.70194 0.896 0.000 0.072 0.000 0.008 0.024
#> GSM1233064 2 0.3184 0.68724 0.000 0.828 0.008 0.140 0.004 0.020
#> GSM1233068 4 0.6411 0.52084 0.000 0.308 0.008 0.512 0.124 0.048
#> GSM1233073 4 0.5600 0.56077 0.000 0.256 0.008 0.624 0.064 0.048
#> GSM1233093 1 0.1523 0.72734 0.940 0.000 0.008 0.000 0.044 0.008
#> GSM1233115 6 0.6995 0.26461 0.016 0.024 0.016 0.304 0.184 0.456
#> GSM1232992 2 0.3337 0.61019 0.000 0.736 0.000 0.260 0.000 0.004
#> GSM1232993 2 0.4262 0.25604 0.000 0.560 0.004 0.424 0.000 0.012
#> GSM1233005 2 0.3314 0.61554 0.000 0.740 0.000 0.256 0.000 0.004
#> GSM1233007 2 0.4436 0.57378 0.000 0.676 0.008 0.272 0.000 0.044
#> GSM1233010 4 0.6840 0.49836 0.000 0.248 0.016 0.516 0.072 0.148
#> GSM1233013 2 0.2879 0.66513 0.000 0.816 0.000 0.176 0.004 0.004
#> GSM1233018 2 0.2805 0.67898 0.000 0.812 0.000 0.184 0.000 0.004
#> GSM1233019 2 0.3684 0.56981 0.000 0.692 0.004 0.300 0.000 0.004
#> GSM1233021 2 0.3126 0.62954 0.000 0.752 0.000 0.248 0.000 0.000
#> GSM1233025 4 0.6620 0.26254 0.012 0.096 0.008 0.556 0.076 0.252
#> GSM1233029 2 0.3405 0.59448 0.000 0.724 0.000 0.272 0.000 0.004
#> GSM1233030 2 0.2512 0.68097 0.000 0.868 0.008 0.116 0.000 0.008
#> GSM1233031 4 0.6066 0.48453 0.000 0.328 0.004 0.532 0.056 0.080
#> GSM1233032 5 0.6401 0.47561 0.036 0.016 0.152 0.052 0.640 0.104
#> GSM1233035 4 0.6121 0.46829 0.004 0.348 0.012 0.524 0.076 0.036
#> GSM1233038 1 0.5388 0.56867 0.664 0.000 0.004 0.064 0.060 0.208
#> GSM1233039 2 0.3144 0.68874 0.000 0.832 0.008 0.136 0.004 0.020
#> GSM1233042 4 0.5176 0.40657 0.000 0.372 0.008 0.564 0.036 0.020
#> GSM1233043 4 0.5176 0.40657 0.000 0.372 0.008 0.564 0.036 0.020
#> GSM1233044 4 0.6794 0.50511 0.004 0.300 0.036 0.504 0.032 0.124
#> GSM1233046 4 0.5726 0.47079 0.004 0.112 0.024 0.692 0.096 0.072
#> GSM1233051 5 0.7262 0.02665 0.004 0.040 0.024 0.220 0.408 0.304
#> GSM1233054 3 0.4257 0.59742 0.040 0.004 0.756 0.008 0.180 0.012
#> GSM1233057 2 0.3201 0.64012 0.000 0.856 0.084 0.016 0.028 0.016
#> GSM1233060 4 0.5176 0.40657 0.000 0.372 0.008 0.564 0.036 0.020
#> GSM1233062 2 0.3753 0.55974 0.000 0.696 0.004 0.292 0.000 0.008
#> GSM1233075 2 0.1793 0.68220 0.000 0.932 0.040 0.008 0.004 0.016
#> GSM1233078 2 0.7124 0.26111 0.000 0.508 0.156 0.168 0.012 0.156
#> GSM1233079 6 0.7662 0.19053 0.020 0.004 0.192 0.100 0.288 0.396
#> GSM1233082 4 0.7231 0.32332 0.000 0.196 0.004 0.412 0.288 0.100
#> GSM1233083 6 0.6466 -0.03937 0.396 0.000 0.000 0.164 0.040 0.400
#> GSM1233091 4 0.6576 0.29783 0.000 0.412 0.012 0.420 0.064 0.092
#> GSM1233095 1 0.5450 0.67730 0.632 0.000 0.012 0.004 0.180 0.172
#> GSM1233096 5 0.2753 0.56382 0.000 0.004 0.016 0.092 0.872 0.016
#> GSM1233101 1 0.5941 0.63283 0.588 0.004 0.016 0.008 0.232 0.152
#> GSM1233105 4 0.6383 -0.09806 0.008 0.020 0.008 0.516 0.296 0.152
#> GSM1233117 2 0.2010 0.69485 0.000 0.920 0.036 0.036 0.004 0.004
#> GSM1233118 2 0.2492 0.70906 0.000 0.876 0.004 0.100 0.000 0.020
#> GSM1233001 2 0.0582 0.68746 0.000 0.984 0.004 0.004 0.004 0.004
#> GSM1233006 2 0.3738 0.55590 0.000 0.680 0.004 0.312 0.000 0.004
#> GSM1233008 2 0.2976 0.70644 0.000 0.844 0.008 0.128 0.004 0.016
#> GSM1233009 2 0.2205 0.68281 0.000 0.896 0.008 0.088 0.004 0.004
#> GSM1233017 2 0.3426 0.62659 0.000 0.764 0.004 0.220 0.012 0.000
#> GSM1233020 2 0.2920 0.67831 0.000 0.820 0.000 0.168 0.004 0.008
#> GSM1233022 4 0.4538 0.17170 0.000 0.436 0.000 0.536 0.008 0.020
#> GSM1233026 4 0.7055 0.49067 0.000 0.240 0.020 0.496 0.076 0.168
#> GSM1233028 4 0.6185 0.47017 0.000 0.300 0.008 0.536 0.036 0.120
#> GSM1233034 2 0.2202 0.70780 0.000 0.904 0.004 0.072 0.008 0.012
#> GSM1233040 5 0.1426 0.56120 0.008 0.000 0.016 0.028 0.948 0.000
#> GSM1233048 5 0.5201 0.16462 0.284 0.004 0.020 0.032 0.640 0.020
#> GSM1233056 1 0.1225 0.71136 0.956 0.000 0.004 0.004 0.004 0.032
#> GSM1233058 4 0.6799 0.49707 0.000 0.256 0.016 0.516 0.068 0.144
#> GSM1233059 1 0.4454 0.51595 0.576 0.000 0.008 0.012 0.400 0.004
#> GSM1233066 2 0.4714 0.62767 0.000 0.728 0.068 0.160 0.000 0.044
#> GSM1233071 2 0.4424 0.47318 0.000 0.656 0.012 0.308 0.020 0.004
#> GSM1233074 2 0.1793 0.68220 0.000 0.932 0.040 0.008 0.004 0.016
#> GSM1233076 2 0.5299 0.55369 0.000 0.656 0.024 0.216 0.004 0.100
#> GSM1233080 1 0.4481 0.72369 0.736 0.000 0.008 0.004 0.152 0.100
#> GSM1233088 2 0.3300 0.68290 0.000 0.816 0.008 0.152 0.004 0.020
#> GSM1233090 1 0.5092 0.70043 0.684 0.000 0.020 0.008 0.200 0.088
#> GSM1233092 4 0.6197 0.45817 0.004 0.284 0.004 0.528 0.020 0.160
#> GSM1233094 4 0.4417 0.30597 0.000 0.384 0.000 0.588 0.004 0.024
#> GSM1233097 4 0.5283 0.42821 0.000 0.336 0.004 0.580 0.016 0.064
#> GSM1233100 4 0.4278 0.40059 0.000 0.352 0.000 0.624 0.008 0.016
#> GSM1233104 4 0.5319 0.42085 0.000 0.332 0.004 0.580 0.016 0.068
#> GSM1233106 5 0.6359 0.30346 0.000 0.096 0.028 0.224 0.592 0.060
#> GSM1233111 5 0.1426 0.56120 0.008 0.000 0.016 0.028 0.948 0.000
#> GSM1233122 2 0.3665 0.57378 0.000 0.696 0.004 0.296 0.000 0.004
#> GSM1233146 4 0.5247 0.43650 0.000 0.360 0.012 0.572 0.024 0.032
#> GSM1232994 2 0.3020 0.66055 0.000 0.812 0.004 0.176 0.004 0.004
#> GSM1232996 2 0.2805 0.68067 0.000 0.812 0.000 0.184 0.000 0.004
#> GSM1232997 2 0.2543 0.70323 0.000 0.892 0.024 0.064 0.004 0.016
#> GSM1232998 4 0.4532 -0.00511 0.000 0.464 0.004 0.508 0.000 0.024
#> GSM1232999 2 0.3802 0.54501 0.000 0.676 0.000 0.312 0.000 0.012
#> GSM1233000 2 0.2915 0.66684 0.000 0.824 0.004 0.164 0.004 0.004
#> GSM1233004 6 0.6722 0.23911 0.008 0.056 0.020 0.372 0.080 0.464
#> GSM1233011 2 0.6398 0.06035 0.000 0.492 0.024 0.348 0.028 0.108
#> GSM1233012 2 0.2788 0.68686 0.000 0.876 0.056 0.056 0.004 0.008
#> GSM1233023 2 0.2030 0.70181 0.000 0.920 0.016 0.048 0.004 0.012
#> GSM1233027 2 0.3337 0.61019 0.000 0.736 0.000 0.260 0.000 0.004
#> GSM1233033 5 0.8009 0.28934 0.172 0.020 0.008 0.196 0.392 0.212
#> GSM1233036 2 0.4947 0.58465 0.000 0.688 0.032 0.228 0.012 0.040
#> GSM1233037 2 0.4082 0.59124 0.000 0.804 0.092 0.024 0.060 0.020
#> GSM1233041 1 0.5058 0.55929 0.604 0.000 0.004 0.012 0.324 0.056
#> GSM1233045 4 0.6799 0.49707 0.000 0.256 0.016 0.516 0.068 0.144
#> GSM1233047 3 0.4684 0.70478 0.000 0.060 0.760 0.016 0.116 0.048
#> GSM1233050 5 0.5905 -0.16477 0.356 0.000 0.036 0.016 0.532 0.060
#> GSM1233052 4 0.6648 0.41036 0.000 0.140 0.008 0.552 0.204 0.096
#> GSM1233053 3 0.4257 0.59742 0.040 0.004 0.756 0.008 0.180 0.012
#> GSM1233055 1 0.2404 0.70274 0.880 0.000 0.004 0.004 0.008 0.104
#> GSM1233061 2 0.5465 0.56528 0.000 0.676 0.132 0.136 0.004 0.052
#> GSM1233063 5 0.6240 0.45877 0.040 0.016 0.008 0.152 0.616 0.168
#> GSM1233065 2 0.2338 0.70604 0.000 0.900 0.012 0.068 0.004 0.016
#> GSM1233070 2 0.3909 0.56912 0.000 0.688 0.004 0.296 0.004 0.008
#> GSM1233077 2 0.7174 0.24857 0.000 0.500 0.156 0.172 0.012 0.160
#> GSM1233081 6 0.8005 0.20779 0.020 0.020 0.304 0.112 0.172 0.372
#> GSM1233084 1 0.5434 0.61632 0.584 0.000 0.008 0.008 0.308 0.092
#> GSM1233087 4 0.6747 -0.12638 0.056 0.068 0.000 0.448 0.044 0.384
#> GSM1233089 2 0.3104 0.68178 0.000 0.800 0.000 0.184 0.000 0.016
#> GSM1233099 4 0.2788 0.35270 0.000 0.004 0.008 0.876 0.056 0.056
#> GSM1233112 6 0.5523 0.15371 0.128 0.000 0.044 0.128 0.016 0.684
#> GSM1233085 3 0.4145 0.71154 0.000 0.052 0.804 0.024 0.088 0.032
#> GSM1233098 2 0.3198 0.68469 0.000 0.796 0.008 0.188 0.000 0.008
#> GSM1233114 4 0.3696 0.43814 0.000 0.060 0.020 0.836 0.048 0.036
#> GSM1233119 4 0.5999 0.35123 0.004 0.096 0.004 0.620 0.068 0.208
#> GSM1233129 2 0.2619 0.70629 0.000 0.876 0.012 0.096 0.004 0.012
#> GSM1233132 4 0.2826 0.35270 0.000 0.004 0.012 0.876 0.052 0.056
#> GSM1233139 2 0.2257 0.69465 0.000 0.904 0.008 0.068 0.008 0.012
#> GSM1233143 2 0.2689 0.67224 0.000 0.876 0.080 0.036 0.004 0.004
#> GSM1233145 6 0.6679 0.01802 0.300 0.000 0.004 0.184 0.048 0.464
#> GSM1233067 2 0.2593 0.67615 0.000 0.884 0.068 0.036 0.000 0.012
#> GSM1233069 2 0.6992 0.29566 0.000 0.528 0.156 0.156 0.012 0.148
#> GSM1233072 2 0.3314 0.63501 0.000 0.740 0.000 0.256 0.000 0.004
#> GSM1233086 2 0.5396 0.53464 0.000 0.648 0.040 0.232 0.004 0.076
#> GSM1233102 4 0.2968 0.33621 0.000 0.004 0.008 0.864 0.060 0.064
#> GSM1233103 4 0.5203 0.51823 0.000 0.128 0.012 0.716 0.084 0.060
#> GSM1233107 4 0.4164 0.51184 0.000 0.108 0.020 0.796 0.048 0.028
#> GSM1233108 6 0.7896 0.30075 0.020 0.012 0.220 0.124 0.208 0.416
#> GSM1233109 6 0.8453 0.21747 0.000 0.100 0.224 0.188 0.132 0.356
#> GSM1233110 2 0.7057 0.19341 0.000 0.452 0.312 0.124 0.012 0.100
#> GSM1233113 2 0.1881 0.67522 0.000 0.924 0.052 0.016 0.004 0.004
#> GSM1233116 2 0.2313 0.68515 0.000 0.904 0.044 0.036 0.000 0.016
#> GSM1233120 4 0.2788 0.35270 0.000 0.004 0.008 0.876 0.056 0.056
#> GSM1233121 2 0.7174 0.24857 0.000 0.500 0.156 0.172 0.012 0.160
#> GSM1233123 2 0.6607 0.37131 0.000 0.560 0.200 0.128 0.008 0.104
#> GSM1233124 2 0.5360 0.52127 0.000 0.644 0.204 0.128 0.000 0.024
#> GSM1233125 5 0.7737 0.31750 0.024 0.044 0.164 0.080 0.500 0.188
#> GSM1233126 4 0.5996 0.36919 0.004 0.128 0.004 0.596 0.036 0.232
#> GSM1233127 2 0.3433 0.62535 0.000 0.780 0.008 0.200 0.004 0.008
#> GSM1233128 5 0.6116 0.46921 0.104 0.000 0.012 0.064 0.608 0.212
#> GSM1233130 2 0.7249 0.24594 0.000 0.488 0.160 0.168 0.012 0.172
#> GSM1233131 4 0.5184 0.51586 0.000 0.120 0.012 0.720 0.080 0.068
#> GSM1233133 3 0.6040 0.57448 0.000 0.108 0.672 0.072 0.072 0.076
#> GSM1233134 2 0.3910 0.55420 0.000 0.740 0.224 0.024 0.000 0.012
#> GSM1233135 2 0.2361 0.67727 0.000 0.896 0.064 0.032 0.000 0.008
#> GSM1233136 2 0.6909 0.29745 0.000 0.524 0.116 0.188 0.008 0.164
#> GSM1233137 3 0.1649 0.68784 0.000 0.040 0.936 0.008 0.016 0.000
#> GSM1233138 4 0.5908 0.38969 0.004 0.128 0.004 0.612 0.036 0.216
#> GSM1233140 5 0.6188 0.47287 0.008 0.020 0.092 0.064 0.636 0.180
#> GSM1233141 2 0.3492 0.62433 0.000 0.772 0.008 0.208 0.004 0.008
#> GSM1233142 2 0.3433 0.62535 0.000 0.780 0.008 0.200 0.004 0.008
#> GSM1233144 3 0.6069 0.56687 0.000 0.116 0.668 0.068 0.072 0.076
#> GSM1233147 2 0.5360 0.48719 0.000 0.616 0.024 0.268 0.000 0.092
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> SD:hclust 139 0.0585 0.386 0.471 2
#> SD:hclust 115 0.2240 0.590 0.552 3
#> SD:hclust 79 0.0302 0.590 0.519 4
#> SD:hclust 89 0.0136 0.191 0.375 5
#> SD:hclust 88 0.0244 0.172 0.239 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 51941 rows and 156 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.946 0.928 0.972 0.4689 0.533 0.533
#> 3 3 0.460 0.544 0.799 0.3888 0.668 0.448
#> 4 4 0.556 0.647 0.809 0.1303 0.750 0.411
#> 5 5 0.604 0.581 0.763 0.0652 0.894 0.634
#> 6 6 0.626 0.497 0.693 0.0399 0.951 0.782
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0000 0.9723 0.000 1.000
#> GSM1233002 2 0.1184 0.9577 0.016 0.984
#> GSM1233003 1 0.0000 0.9673 1.000 0.000
#> GSM1233014 2 0.0000 0.9723 0.000 1.000
#> GSM1233015 1 0.0672 0.9610 0.992 0.008
#> GSM1233016 2 0.1633 0.9503 0.024 0.976
#> GSM1233024 2 0.0000 0.9723 0.000 1.000
#> GSM1233049 1 0.0000 0.9673 1.000 0.000
#> GSM1233064 2 0.0000 0.9723 0.000 1.000
#> GSM1233068 1 0.9944 0.1528 0.544 0.456
#> GSM1233073 2 0.9732 0.3206 0.404 0.596
#> GSM1233093 1 0.0000 0.9673 1.000 0.000
#> GSM1233115 1 0.0000 0.9673 1.000 0.000
#> GSM1232992 2 0.0000 0.9723 0.000 1.000
#> GSM1232993 2 0.0000 0.9723 0.000 1.000
#> GSM1233005 2 0.0000 0.9723 0.000 1.000
#> GSM1233007 2 0.0000 0.9723 0.000 1.000
#> GSM1233010 2 0.8763 0.5742 0.296 0.704
#> GSM1233013 2 0.0000 0.9723 0.000 1.000
#> GSM1233018 2 0.0000 0.9723 0.000 1.000
#> GSM1233019 2 0.0000 0.9723 0.000 1.000
#> GSM1233021 2 0.0000 0.9723 0.000 1.000
#> GSM1233025 1 0.3879 0.8955 0.924 0.076
#> GSM1233029 2 0.0000 0.9723 0.000 1.000
#> GSM1233030 2 0.0000 0.9723 0.000 1.000
#> GSM1233031 2 0.0000 0.9723 0.000 1.000
#> GSM1233032 1 0.0000 0.9673 1.000 0.000
#> GSM1233035 1 0.9998 0.0172 0.508 0.492
#> GSM1233038 1 0.0000 0.9673 1.000 0.000
#> GSM1233039 2 0.0000 0.9723 0.000 1.000
#> GSM1233042 2 0.0000 0.9723 0.000 1.000
#> GSM1233043 2 0.0000 0.9723 0.000 1.000
#> GSM1233044 1 0.4431 0.8784 0.908 0.092
#> GSM1233046 1 0.0376 0.9642 0.996 0.004
#> GSM1233051 1 0.0000 0.9673 1.000 0.000
#> GSM1233054 2 0.9522 0.4055 0.372 0.628
#> GSM1233057 2 0.0000 0.9723 0.000 1.000
#> GSM1233060 2 0.0000 0.9723 0.000 1.000
#> GSM1233062 2 0.0000 0.9723 0.000 1.000
#> GSM1233075 2 0.0000 0.9723 0.000 1.000
#> GSM1233078 2 0.9661 0.3532 0.392 0.608
#> GSM1233079 1 0.0000 0.9673 1.000 0.000
#> GSM1233082 1 0.0376 0.9643 0.996 0.004
#> GSM1233083 1 0.0000 0.9673 1.000 0.000
#> GSM1233091 2 0.0000 0.9723 0.000 1.000
#> GSM1233095 1 0.0000 0.9673 1.000 0.000
#> GSM1233096 1 0.0000 0.9673 1.000 0.000
#> GSM1233101 1 0.0000 0.9673 1.000 0.000
#> GSM1233105 1 0.0000 0.9673 1.000 0.000
#> GSM1233117 2 0.0000 0.9723 0.000 1.000
#> GSM1233118 2 0.0000 0.9723 0.000 1.000
#> GSM1233001 2 0.0000 0.9723 0.000 1.000
#> GSM1233006 2 0.0000 0.9723 0.000 1.000
#> GSM1233008 2 0.0000 0.9723 0.000 1.000
#> GSM1233009 2 0.0000 0.9723 0.000 1.000
#> GSM1233017 2 0.0000 0.9723 0.000 1.000
#> GSM1233020 2 0.0000 0.9723 0.000 1.000
#> GSM1233022 2 0.0000 0.9723 0.000 1.000
#> GSM1233026 2 0.0000 0.9723 0.000 1.000
#> GSM1233028 2 0.0000 0.9723 0.000 1.000
#> GSM1233034 2 0.0000 0.9723 0.000 1.000
#> GSM1233040 1 0.0000 0.9673 1.000 0.000
#> GSM1233048 1 0.0000 0.9673 1.000 0.000
#> GSM1233056 1 0.0000 0.9673 1.000 0.000
#> GSM1233058 2 0.0000 0.9723 0.000 1.000
#> GSM1233059 1 0.0000 0.9673 1.000 0.000
#> GSM1233066 2 0.0000 0.9723 0.000 1.000
#> GSM1233071 2 0.0000 0.9723 0.000 1.000
#> GSM1233074 2 0.0000 0.9723 0.000 1.000
#> GSM1233076 2 0.0000 0.9723 0.000 1.000
#> GSM1233080 1 0.0000 0.9673 1.000 0.000
#> GSM1233088 2 0.0000 0.9723 0.000 1.000
#> GSM1233090 1 0.0000 0.9673 1.000 0.000
#> GSM1233092 2 0.0000 0.9723 0.000 1.000
#> GSM1233094 2 0.0000 0.9723 0.000 1.000
#> GSM1233097 2 0.0000 0.9723 0.000 1.000
#> GSM1233100 2 0.8608 0.5972 0.284 0.716
#> GSM1233104 2 0.0000 0.9723 0.000 1.000
#> GSM1233106 1 0.0672 0.9610 0.992 0.008
#> GSM1233111 1 0.0000 0.9673 1.000 0.000
#> GSM1233122 2 0.0000 0.9723 0.000 1.000
#> GSM1233146 2 0.0000 0.9723 0.000 1.000
#> GSM1232994 2 0.0000 0.9723 0.000 1.000
#> GSM1232996 2 0.0000 0.9723 0.000 1.000
#> GSM1232997 2 0.0000 0.9723 0.000 1.000
#> GSM1232998 2 0.0000 0.9723 0.000 1.000
#> GSM1232999 2 0.0000 0.9723 0.000 1.000
#> GSM1233000 2 0.0000 0.9723 0.000 1.000
#> GSM1233004 1 0.9983 0.0849 0.524 0.476
#> GSM1233011 2 0.0000 0.9723 0.000 1.000
#> GSM1233012 2 0.0000 0.9723 0.000 1.000
#> GSM1233023 2 0.0000 0.9723 0.000 1.000
#> GSM1233027 2 0.0000 0.9723 0.000 1.000
#> GSM1233033 1 0.0000 0.9673 1.000 0.000
#> GSM1233036 2 0.0000 0.9723 0.000 1.000
#> GSM1233037 2 0.0000 0.9723 0.000 1.000
#> GSM1233041 1 0.0000 0.9673 1.000 0.000
#> GSM1233045 2 0.0000 0.9723 0.000 1.000
#> GSM1233047 1 0.0000 0.9673 1.000 0.000
#> GSM1233050 1 0.0000 0.9673 1.000 0.000
#> GSM1233052 1 0.0000 0.9673 1.000 0.000
#> GSM1233053 1 0.0000 0.9673 1.000 0.000
#> GSM1233055 1 0.0000 0.9673 1.000 0.000
#> GSM1233061 2 0.0000 0.9723 0.000 1.000
#> GSM1233063 1 0.0000 0.9673 1.000 0.000
#> GSM1233065 2 0.0000 0.9723 0.000 1.000
#> GSM1233070 2 0.0000 0.9723 0.000 1.000
#> GSM1233077 2 0.0000 0.9723 0.000 1.000
#> GSM1233081 1 0.0000 0.9673 1.000 0.000
#> GSM1233084 1 0.0000 0.9673 1.000 0.000
#> GSM1233087 1 0.5842 0.8204 0.860 0.140
#> GSM1233089 2 0.0000 0.9723 0.000 1.000
#> GSM1233099 1 0.0000 0.9673 1.000 0.000
#> GSM1233112 1 0.0000 0.9673 1.000 0.000
#> GSM1233085 1 0.0000 0.9673 1.000 0.000
#> GSM1233098 2 0.0000 0.9723 0.000 1.000
#> GSM1233114 1 0.0000 0.9673 1.000 0.000
#> GSM1233119 2 0.6148 0.8061 0.152 0.848
#> GSM1233129 2 0.0000 0.9723 0.000 1.000
#> GSM1233132 1 0.0000 0.9673 1.000 0.000
#> GSM1233139 2 0.0000 0.9723 0.000 1.000
#> GSM1233143 2 0.0000 0.9723 0.000 1.000
#> GSM1233145 1 0.0000 0.9673 1.000 0.000
#> GSM1233067 2 0.0000 0.9723 0.000 1.000
#> GSM1233069 2 0.0000 0.9723 0.000 1.000
#> GSM1233072 2 0.0000 0.9723 0.000 1.000
#> GSM1233086 2 0.0000 0.9723 0.000 1.000
#> GSM1233102 1 0.0000 0.9673 1.000 0.000
#> GSM1233103 2 0.9209 0.4923 0.336 0.664
#> GSM1233107 2 0.8813 0.5658 0.300 0.700
#> GSM1233108 1 0.0000 0.9673 1.000 0.000
#> GSM1233109 1 0.0000 0.9673 1.000 0.000
#> GSM1233110 2 0.0000 0.9723 0.000 1.000
#> GSM1233113 2 0.0000 0.9723 0.000 1.000
#> GSM1233116 2 0.0000 0.9723 0.000 1.000
#> GSM1233120 1 0.0000 0.9673 1.000 0.000
#> GSM1233121 2 0.0000 0.9723 0.000 1.000
#> GSM1233123 2 0.0000 0.9723 0.000 1.000
#> GSM1233124 2 0.0000 0.9723 0.000 1.000
#> GSM1233125 1 0.0000 0.9673 1.000 0.000
#> GSM1233126 2 0.0000 0.9723 0.000 1.000
#> GSM1233127 2 0.0000 0.9723 0.000 1.000
#> GSM1233128 1 0.0000 0.9673 1.000 0.000
#> GSM1233130 2 0.0000 0.9723 0.000 1.000
#> GSM1233131 1 0.0000 0.9673 1.000 0.000
#> GSM1233133 1 0.0000 0.9673 1.000 0.000
#> GSM1233134 2 0.0000 0.9723 0.000 1.000
#> GSM1233135 2 0.0000 0.9723 0.000 1.000
#> GSM1233136 2 0.0000 0.9723 0.000 1.000
#> GSM1233137 1 0.0000 0.9673 1.000 0.000
#> GSM1233138 2 0.0000 0.9723 0.000 1.000
#> GSM1233140 1 0.0000 0.9673 1.000 0.000
#> GSM1233141 2 0.0000 0.9723 0.000 1.000
#> GSM1233142 2 0.0000 0.9723 0.000 1.000
#> GSM1233144 1 0.0000 0.9673 1.000 0.000
#> GSM1233147 2 0.0000 0.9723 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 3 0.4452 0.5513 0.000 0.192 0.808
#> GSM1233002 2 0.0237 0.6579 0.000 0.996 0.004
#> GSM1233003 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233014 2 0.4178 0.6358 0.000 0.828 0.172
#> GSM1233015 1 0.5926 0.5754 0.644 0.356 0.000
#> GSM1233016 2 0.0000 0.6588 0.000 1.000 0.000
#> GSM1233024 2 0.5431 0.5456 0.000 0.716 0.284
#> GSM1233049 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233064 3 0.5988 0.3759 0.000 0.368 0.632
#> GSM1233068 2 0.3375 0.5951 0.100 0.892 0.008
#> GSM1233073 2 0.0475 0.6569 0.004 0.992 0.004
#> GSM1233093 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233115 1 0.4931 0.7543 0.768 0.232 0.000
#> GSM1232992 3 0.6225 0.1810 0.000 0.432 0.568
#> GSM1232993 2 0.4974 0.5945 0.000 0.764 0.236
#> GSM1233005 3 0.6235 0.1689 0.000 0.436 0.564
#> GSM1233007 2 0.5882 0.3949 0.000 0.652 0.348
#> GSM1233010 2 0.0661 0.6554 0.008 0.988 0.004
#> GSM1233013 3 0.6225 0.1810 0.000 0.432 0.568
#> GSM1233018 3 0.6215 0.1912 0.000 0.428 0.572
#> GSM1233019 2 0.6215 0.2741 0.000 0.572 0.428
#> GSM1233021 3 0.6267 0.1164 0.000 0.452 0.548
#> GSM1233025 2 0.2772 0.6145 0.080 0.916 0.004
#> GSM1233029 2 0.5650 0.5072 0.000 0.688 0.312
#> GSM1233030 3 0.6302 0.0127 0.000 0.480 0.520
#> GSM1233031 2 0.0000 0.6588 0.000 1.000 0.000
#> GSM1233032 1 0.2066 0.8836 0.940 0.060 0.000
#> GSM1233035 2 0.0237 0.6582 0.004 0.996 0.000
#> GSM1233038 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233039 2 0.6204 0.0771 0.000 0.576 0.424
#> GSM1233042 2 0.3267 0.6590 0.000 0.884 0.116
#> GSM1233043 2 0.3412 0.6571 0.000 0.876 0.124
#> GSM1233044 2 0.8845 0.1993 0.184 0.576 0.240
#> GSM1233046 2 0.5905 0.1948 0.352 0.648 0.000
#> GSM1233051 1 0.3038 0.8638 0.896 0.104 0.000
#> GSM1233054 3 0.5220 0.5538 0.012 0.208 0.780
#> GSM1233057 3 0.3116 0.6240 0.000 0.108 0.892
#> GSM1233060 2 0.0237 0.6598 0.000 0.996 0.004
#> GSM1233062 2 0.4796 0.6065 0.000 0.780 0.220
#> GSM1233075 3 0.0000 0.6604 0.000 0.000 1.000
#> GSM1233078 3 0.5363 0.4963 0.000 0.276 0.724
#> GSM1233079 1 0.1964 0.8844 0.944 0.056 0.000
#> GSM1233082 2 0.6295 -0.1783 0.472 0.528 0.000
#> GSM1233083 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233091 2 0.4605 0.4581 0.000 0.796 0.204
#> GSM1233095 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233096 1 0.2537 0.8770 0.920 0.080 0.000
#> GSM1233101 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233105 2 0.6235 -0.0572 0.436 0.564 0.000
#> GSM1233117 3 0.5016 0.4987 0.000 0.240 0.760
#> GSM1233118 3 0.0747 0.6604 0.000 0.016 0.984
#> GSM1233001 3 0.4654 0.5328 0.000 0.208 0.792
#> GSM1233006 2 0.5254 0.5667 0.000 0.736 0.264
#> GSM1233008 3 0.6225 0.1810 0.000 0.432 0.568
#> GSM1233009 2 0.6215 0.2741 0.000 0.572 0.428
#> GSM1233017 2 0.6180 0.3042 0.000 0.584 0.416
#> GSM1233020 3 0.6192 0.2099 0.000 0.420 0.580
#> GSM1233022 2 0.4750 0.6093 0.000 0.784 0.216
#> GSM1233026 2 0.0237 0.6579 0.000 0.996 0.004
#> GSM1233028 2 0.0237 0.6579 0.000 0.996 0.004
#> GSM1233034 3 0.6192 0.2099 0.000 0.420 0.580
#> GSM1233040 1 0.2066 0.8836 0.940 0.060 0.000
#> GSM1233048 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233056 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233058 2 0.0237 0.6579 0.000 0.996 0.004
#> GSM1233059 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233066 3 0.4702 0.5671 0.000 0.212 0.788
#> GSM1233071 2 0.4291 0.6336 0.000 0.820 0.180
#> GSM1233074 3 0.0000 0.6604 0.000 0.000 1.000
#> GSM1233076 2 0.5678 0.4064 0.000 0.684 0.316
#> GSM1233080 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233088 3 0.6307 0.2788 0.000 0.488 0.512
#> GSM1233090 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233092 2 0.3551 0.6543 0.000 0.868 0.132
#> GSM1233094 2 0.3116 0.6604 0.000 0.892 0.108
#> GSM1233097 2 0.2066 0.6631 0.000 0.940 0.060
#> GSM1233100 2 0.0475 0.6569 0.004 0.992 0.004
#> GSM1233104 2 0.3412 0.6571 0.000 0.876 0.124
#> GSM1233106 1 0.6154 0.4733 0.592 0.408 0.000
#> GSM1233111 1 0.2537 0.8770 0.920 0.080 0.000
#> GSM1233122 3 0.6225 0.1810 0.000 0.432 0.568
#> GSM1233146 2 0.2066 0.6634 0.000 0.940 0.060
#> GSM1232994 2 0.5905 0.4416 0.000 0.648 0.352
#> GSM1232996 3 0.6192 0.2099 0.000 0.420 0.580
#> GSM1232997 3 0.0237 0.6607 0.000 0.004 0.996
#> GSM1232998 2 0.5363 0.5535 0.000 0.724 0.276
#> GSM1232999 2 0.5327 0.5580 0.000 0.728 0.272
#> GSM1233000 2 0.6215 0.2741 0.000 0.572 0.428
#> GSM1233004 3 0.7905 0.1863 0.056 0.444 0.500
#> GSM1233011 3 0.5810 0.4192 0.000 0.336 0.664
#> GSM1233012 3 0.1643 0.6523 0.000 0.044 0.956
#> GSM1233023 3 0.3038 0.6201 0.000 0.104 0.896
#> GSM1233027 2 0.5363 0.5535 0.000 0.724 0.276
#> GSM1233033 1 0.2261 0.8815 0.932 0.068 0.000
#> GSM1233036 3 0.2165 0.6510 0.000 0.064 0.936
#> GSM1233037 3 0.4291 0.6188 0.000 0.180 0.820
#> GSM1233041 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233045 2 0.2625 0.6613 0.000 0.916 0.084
#> GSM1233047 1 0.9001 0.4283 0.512 0.144 0.344
#> GSM1233050 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233052 2 0.6309 -0.2579 0.500 0.500 0.000
#> GSM1233053 1 0.2448 0.8788 0.924 0.076 0.000
#> GSM1233055 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233061 3 0.4555 0.5715 0.000 0.200 0.800
#> GSM1233063 1 0.2537 0.8770 0.920 0.080 0.000
#> GSM1233065 3 0.0592 0.6607 0.000 0.012 0.988
#> GSM1233070 2 0.4750 0.6028 0.000 0.784 0.216
#> GSM1233077 3 0.2537 0.6452 0.000 0.080 0.920
#> GSM1233081 1 0.7759 0.6979 0.676 0.144 0.180
#> GSM1233084 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233087 2 0.4110 0.5555 0.152 0.844 0.004
#> GSM1233089 3 0.6126 0.2466 0.000 0.400 0.600
#> GSM1233099 2 0.5016 0.4524 0.240 0.760 0.000
#> GSM1233112 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233085 1 0.7944 0.6669 0.656 0.132 0.212
#> GSM1233098 3 0.6225 0.1810 0.000 0.432 0.568
#> GSM1233114 1 0.4121 0.8198 0.832 0.168 0.000
#> GSM1233119 2 0.1129 0.6506 0.020 0.976 0.004
#> GSM1233129 3 0.0000 0.6604 0.000 0.000 1.000
#> GSM1233132 1 0.4121 0.8152 0.832 0.168 0.000
#> GSM1233139 2 0.6280 0.1792 0.000 0.540 0.460
#> GSM1233143 3 0.1529 0.6532 0.000 0.040 0.960
#> GSM1233145 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233067 3 0.0237 0.6599 0.000 0.004 0.996
#> GSM1233069 3 0.0592 0.6601 0.000 0.012 0.988
#> GSM1233072 3 0.6204 0.2007 0.000 0.424 0.576
#> GSM1233086 3 0.4842 0.5640 0.000 0.224 0.776
#> GSM1233102 2 0.6299 -0.0626 0.476 0.524 0.000
#> GSM1233103 2 0.0661 0.6550 0.004 0.988 0.008
#> GSM1233107 2 0.3340 0.5862 0.120 0.880 0.000
#> GSM1233108 1 0.5618 0.7827 0.796 0.048 0.156
#> GSM1233109 1 0.9462 0.2476 0.420 0.180 0.400
#> GSM1233110 3 0.4121 0.5965 0.000 0.168 0.832
#> GSM1233113 3 0.0747 0.6594 0.000 0.016 0.984
#> GSM1233116 3 0.0747 0.6594 0.000 0.016 0.984
#> GSM1233120 2 0.6291 -0.1171 0.468 0.532 0.000
#> GSM1233121 3 0.3267 0.6302 0.000 0.116 0.884
#> GSM1233123 3 0.4121 0.5965 0.000 0.168 0.832
#> GSM1233124 3 0.2959 0.6375 0.000 0.100 0.900
#> GSM1233125 1 0.5719 0.7819 0.792 0.052 0.156
#> GSM1233126 2 0.3482 0.6557 0.000 0.872 0.128
#> GSM1233127 2 0.5760 0.4828 0.000 0.672 0.328
#> GSM1233128 1 0.0000 0.8927 1.000 0.000 0.000
#> GSM1233130 3 0.4291 0.5901 0.000 0.180 0.820
#> GSM1233131 2 0.6252 -0.0961 0.444 0.556 0.000
#> GSM1233133 3 0.9152 -0.2746 0.428 0.144 0.428
#> GSM1233134 3 0.0424 0.6605 0.000 0.008 0.992
#> GSM1233135 3 0.0000 0.6604 0.000 0.000 1.000
#> GSM1233136 3 0.2537 0.6452 0.000 0.080 0.920
#> GSM1233137 3 0.9152 -0.2644 0.424 0.144 0.432
#> GSM1233138 2 0.3551 0.6543 0.000 0.868 0.132
#> GSM1233140 1 0.6109 0.7894 0.780 0.080 0.140
#> GSM1233141 2 0.6280 0.1791 0.000 0.540 0.460
#> GSM1233142 2 0.6244 0.2399 0.000 0.560 0.440
#> GSM1233144 3 0.9140 -0.2149 0.404 0.144 0.452
#> GSM1233147 2 0.6008 0.3316 0.000 0.628 0.372
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.1211 0.7404 0.000 0.960 0.040 0.000
#> GSM1233002 4 0.2773 0.7652 0.000 0.116 0.004 0.880
#> GSM1233003 1 0.2521 0.8504 0.912 0.000 0.024 0.064
#> GSM1233014 4 0.5409 -0.0496 0.000 0.492 0.012 0.496
#> GSM1233015 4 0.7957 0.2869 0.260 0.024 0.200 0.516
#> GSM1233016 4 0.3542 0.7539 0.000 0.120 0.028 0.852
#> GSM1233024 2 0.3306 0.7209 0.000 0.840 0.004 0.156
#> GSM1233049 1 0.0779 0.8717 0.980 0.000 0.016 0.004
#> GSM1233064 2 0.5160 0.6076 0.000 0.760 0.136 0.104
#> GSM1233068 4 0.6017 0.6737 0.020 0.084 0.180 0.716
#> GSM1233073 4 0.2266 0.7725 0.000 0.084 0.004 0.912
#> GSM1233093 1 0.0336 0.8734 0.992 0.000 0.008 0.000
#> GSM1233115 4 0.7114 0.3413 0.252 0.000 0.188 0.560
#> GSM1232992 2 0.0707 0.7715 0.000 0.980 0.000 0.020
#> GSM1232993 2 0.3172 0.7205 0.000 0.840 0.000 0.160
#> GSM1233005 2 0.0707 0.7715 0.000 0.980 0.000 0.020
#> GSM1233007 2 0.4690 0.5436 0.000 0.712 0.012 0.276
#> GSM1233010 4 0.1867 0.7761 0.000 0.072 0.000 0.928
#> GSM1233013 2 0.0707 0.7715 0.000 0.980 0.000 0.020
#> GSM1233018 2 0.0469 0.7694 0.000 0.988 0.000 0.012
#> GSM1233019 2 0.2011 0.7667 0.000 0.920 0.000 0.080
#> GSM1233021 2 0.0817 0.7718 0.000 0.976 0.000 0.024
#> GSM1233025 4 0.2400 0.7761 0.012 0.032 0.028 0.928
#> GSM1233029 2 0.2530 0.7584 0.000 0.888 0.000 0.112
#> GSM1233030 2 0.0921 0.7721 0.000 0.972 0.000 0.028
#> GSM1233031 4 0.2053 0.7763 0.000 0.072 0.004 0.924
#> GSM1233032 1 0.5325 0.7527 0.728 0.000 0.204 0.068
#> GSM1233035 4 0.3980 0.7599 0.008 0.052 0.092 0.848
#> GSM1233038 1 0.2222 0.8522 0.924 0.000 0.016 0.060
#> GSM1233039 2 0.6483 0.3674 0.000 0.584 0.092 0.324
#> GSM1233042 4 0.4744 0.5938 0.000 0.284 0.012 0.704
#> GSM1233043 4 0.4744 0.5938 0.000 0.284 0.012 0.704
#> GSM1233044 4 0.3801 0.6612 0.000 0.000 0.220 0.780
#> GSM1233046 4 0.4001 0.7230 0.036 0.008 0.116 0.840
#> GSM1233051 1 0.6262 0.7050 0.660 0.000 0.208 0.132
#> GSM1233054 3 0.2222 0.7218 0.004 0.032 0.932 0.032
#> GSM1233057 3 0.5306 0.5529 0.000 0.348 0.632 0.020
#> GSM1233060 4 0.3791 0.7127 0.000 0.200 0.004 0.796
#> GSM1233062 2 0.4720 0.5026 0.000 0.672 0.004 0.324
#> GSM1233075 3 0.4643 0.6015 0.000 0.344 0.656 0.000
#> GSM1233078 3 0.1256 0.7283 0.000 0.028 0.964 0.008
#> GSM1233079 1 0.5361 0.7509 0.724 0.000 0.208 0.068
#> GSM1233082 4 0.5504 0.6412 0.076 0.008 0.176 0.740
#> GSM1233083 1 0.2032 0.8633 0.936 0.000 0.028 0.036
#> GSM1233091 4 0.6262 0.6078 0.000 0.208 0.132 0.660
#> GSM1233095 1 0.0469 0.8731 0.988 0.000 0.012 0.000
#> GSM1233096 1 0.6149 0.7147 0.676 0.000 0.180 0.144
#> GSM1233101 1 0.0592 0.8725 0.984 0.000 0.016 0.000
#> GSM1233105 4 0.3840 0.7195 0.052 0.000 0.104 0.844
#> GSM1233117 2 0.1118 0.7443 0.000 0.964 0.036 0.000
#> GSM1233118 2 0.4500 0.3056 0.000 0.684 0.316 0.000
#> GSM1233001 2 0.1356 0.7419 0.000 0.960 0.032 0.008
#> GSM1233006 2 0.4546 0.6039 0.000 0.732 0.012 0.256
#> GSM1233008 2 0.0592 0.7707 0.000 0.984 0.000 0.016
#> GSM1233009 2 0.2149 0.7661 0.000 0.912 0.000 0.088
#> GSM1233017 2 0.2216 0.7646 0.000 0.908 0.000 0.092
#> GSM1233020 2 0.0188 0.7624 0.000 0.996 0.004 0.000
#> GSM1233022 2 0.5273 0.1737 0.000 0.536 0.008 0.456
#> GSM1233026 4 0.2402 0.7768 0.000 0.076 0.012 0.912
#> GSM1233028 4 0.2342 0.7750 0.000 0.080 0.008 0.912
#> GSM1233034 2 0.0817 0.7605 0.000 0.976 0.000 0.024
#> GSM1233040 1 0.5172 0.7580 0.744 0.000 0.188 0.068
#> GSM1233048 1 0.0524 0.8738 0.988 0.000 0.004 0.008
#> GSM1233056 1 0.1406 0.8685 0.960 0.000 0.016 0.024
#> GSM1233058 4 0.2480 0.7714 0.000 0.088 0.008 0.904
#> GSM1233059 1 0.0000 0.8733 1.000 0.000 0.000 0.000
#> GSM1233066 3 0.4568 0.7240 0.000 0.124 0.800 0.076
#> GSM1233071 2 0.4655 0.5259 0.000 0.684 0.004 0.312
#> GSM1233074 2 0.5000 -0.2978 0.000 0.504 0.496 0.000
#> GSM1233076 4 0.6696 0.1759 0.000 0.428 0.088 0.484
#> GSM1233080 1 0.0336 0.8734 0.992 0.000 0.008 0.000
#> GSM1233088 3 0.7661 0.2324 0.000 0.272 0.464 0.264
#> GSM1233090 1 0.0336 0.8734 0.992 0.000 0.008 0.000
#> GSM1233092 4 0.4516 0.6275 0.000 0.252 0.012 0.736
#> GSM1233094 4 0.4284 0.6654 0.000 0.224 0.012 0.764
#> GSM1233097 4 0.2988 0.7614 0.000 0.112 0.012 0.876
#> GSM1233100 4 0.2831 0.7647 0.000 0.120 0.004 0.876
#> GSM1233104 4 0.3718 0.7226 0.000 0.168 0.012 0.820
#> GSM1233106 4 0.6714 0.5673 0.108 0.024 0.208 0.660
#> GSM1233111 1 0.6075 0.7178 0.680 0.000 0.192 0.128
#> GSM1233122 2 0.0469 0.7697 0.000 0.988 0.000 0.012
#> GSM1233146 4 0.3377 0.7452 0.000 0.140 0.012 0.848
#> GSM1232994 2 0.2469 0.7583 0.000 0.892 0.000 0.108
#> GSM1232996 2 0.0336 0.7681 0.000 0.992 0.000 0.008
#> GSM1232997 2 0.4697 0.1890 0.000 0.644 0.356 0.000
#> GSM1232998 2 0.5300 0.3223 0.000 0.580 0.012 0.408
#> GSM1232999 2 0.4453 0.6201 0.000 0.744 0.012 0.244
#> GSM1233000 2 0.1940 0.7674 0.000 0.924 0.000 0.076
#> GSM1233004 4 0.6130 0.1085 0.000 0.048 0.440 0.512
#> GSM1233011 3 0.7905 0.0900 0.000 0.332 0.364 0.304
#> GSM1233012 2 0.3311 0.5831 0.000 0.828 0.172 0.000
#> GSM1233023 2 0.2412 0.6984 0.000 0.908 0.084 0.008
#> GSM1233027 2 0.4137 0.6661 0.000 0.780 0.012 0.208
#> GSM1233033 1 0.4673 0.8051 0.792 0.000 0.076 0.132
#> GSM1233036 3 0.4661 0.5900 0.000 0.348 0.652 0.000
#> GSM1233037 3 0.6493 0.4436 0.008 0.336 0.588 0.068
#> GSM1233041 1 0.0000 0.8733 1.000 0.000 0.000 0.000
#> GSM1233045 4 0.3636 0.7285 0.000 0.172 0.008 0.820
#> GSM1233047 3 0.2021 0.6913 0.040 0.000 0.936 0.024
#> GSM1233050 1 0.1059 0.8715 0.972 0.000 0.012 0.016
#> GSM1233052 4 0.5075 0.6696 0.100 0.004 0.120 0.776
#> GSM1233053 1 0.5203 0.7477 0.720 0.000 0.232 0.048
#> GSM1233055 1 0.1297 0.8696 0.964 0.000 0.016 0.020
#> GSM1233061 3 0.1716 0.7419 0.000 0.064 0.936 0.000
#> GSM1233063 1 0.5624 0.7518 0.720 0.000 0.172 0.108
#> GSM1233065 2 0.4624 0.2470 0.000 0.660 0.340 0.000
#> GSM1233070 2 0.4936 0.5049 0.000 0.672 0.012 0.316
#> GSM1233077 3 0.5070 0.7059 0.000 0.192 0.748 0.060
#> GSM1233081 3 0.3266 0.6170 0.108 0.000 0.868 0.024
#> GSM1233084 1 0.0188 0.8735 0.996 0.000 0.004 0.000
#> GSM1233087 4 0.2497 0.7762 0.016 0.040 0.020 0.924
#> GSM1233089 2 0.0469 0.7579 0.000 0.988 0.012 0.000
#> GSM1233099 4 0.2170 0.7705 0.036 0.012 0.016 0.936
#> GSM1233112 1 0.2124 0.8617 0.932 0.000 0.028 0.040
#> GSM1233085 3 0.2742 0.6583 0.076 0.000 0.900 0.024
#> GSM1233098 2 0.0524 0.7689 0.000 0.988 0.004 0.008
#> GSM1233114 4 0.6808 0.3856 0.236 0.000 0.164 0.600
#> GSM1233119 4 0.2261 0.7756 0.008 0.036 0.024 0.932
#> GSM1233129 3 0.5000 0.2814 0.000 0.496 0.504 0.000
#> GSM1233132 4 0.6457 0.3858 0.296 0.000 0.100 0.604
#> GSM1233139 2 0.1637 0.7702 0.000 0.940 0.000 0.060
#> GSM1233143 2 0.4222 0.4300 0.000 0.728 0.272 0.000
#> GSM1233145 1 0.3307 0.8130 0.868 0.000 0.028 0.104
#> GSM1233067 3 0.4585 0.6129 0.000 0.332 0.668 0.000
#> GSM1233069 3 0.4134 0.6875 0.000 0.260 0.740 0.000
#> GSM1233072 2 0.0376 0.7646 0.000 0.992 0.004 0.004
#> GSM1233086 3 0.6119 0.6399 0.000 0.152 0.680 0.168
#> GSM1233102 4 0.3523 0.7349 0.112 0.000 0.032 0.856
#> GSM1233103 4 0.3706 0.7489 0.000 0.040 0.112 0.848
#> GSM1233107 4 0.3333 0.7462 0.032 0.004 0.088 0.876
#> GSM1233108 3 0.5535 -0.1303 0.420 0.000 0.560 0.020
#> GSM1233109 3 0.1796 0.7021 0.032 0.004 0.948 0.016
#> GSM1233110 3 0.2530 0.7515 0.000 0.112 0.888 0.000
#> GSM1233113 2 0.4040 0.4545 0.000 0.752 0.248 0.000
#> GSM1233116 2 0.4761 0.1583 0.000 0.628 0.372 0.000
#> GSM1233120 4 0.3542 0.7258 0.120 0.000 0.028 0.852
#> GSM1233121 3 0.5070 0.7059 0.000 0.192 0.748 0.060
#> GSM1233123 3 0.2530 0.7515 0.000 0.112 0.888 0.000
#> GSM1233124 3 0.3975 0.6997 0.000 0.240 0.760 0.000
#> GSM1233125 3 0.5558 -0.1793 0.432 0.000 0.548 0.020
#> GSM1233126 4 0.4095 0.6822 0.000 0.192 0.016 0.792
#> GSM1233127 2 0.5055 0.4425 0.000 0.624 0.008 0.368
#> GSM1233128 1 0.1406 0.8678 0.960 0.000 0.016 0.024
#> GSM1233130 3 0.2773 0.7509 0.000 0.116 0.880 0.004
#> GSM1233131 4 0.4100 0.6972 0.048 0.000 0.128 0.824
#> GSM1233133 3 0.1584 0.7015 0.036 0.000 0.952 0.012
#> GSM1233134 3 0.3975 0.7009 0.000 0.240 0.760 0.000
#> GSM1233135 3 0.4103 0.6897 0.000 0.256 0.744 0.000
#> GSM1233136 3 0.5070 0.7059 0.000 0.192 0.748 0.060
#> GSM1233137 3 0.1677 0.7011 0.040 0.000 0.948 0.012
#> GSM1233138 4 0.4214 0.6725 0.000 0.204 0.016 0.780
#> GSM1233140 1 0.6491 0.4738 0.528 0.000 0.396 0.076
#> GSM1233141 2 0.4163 0.6960 0.000 0.792 0.020 0.188
#> GSM1233142 2 0.3681 0.7053 0.000 0.816 0.008 0.176
#> GSM1233144 3 0.1488 0.7044 0.032 0.000 0.956 0.012
#> GSM1233147 2 0.6995 0.1214 0.000 0.496 0.120 0.384
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.2046 0.7593 0.016 0.916 0.068 0.000 0.000
#> GSM1233002 4 0.3911 0.6852 0.084 0.100 0.004 0.812 0.000
#> GSM1233003 5 0.4599 0.7679 0.180 0.000 0.004 0.072 0.744
#> GSM1233014 4 0.4060 0.4580 0.000 0.360 0.000 0.640 0.000
#> GSM1233015 1 0.5204 0.5796 0.728 0.012 0.008 0.156 0.096
#> GSM1233016 4 0.3601 0.6272 0.128 0.052 0.000 0.820 0.000
#> GSM1233024 2 0.2966 0.7121 0.016 0.848 0.000 0.136 0.000
#> GSM1233049 5 0.0162 0.8988 0.004 0.000 0.000 0.000 0.996
#> GSM1233064 2 0.6143 0.5350 0.044 0.636 0.220 0.100 0.000
#> GSM1233068 1 0.5308 0.4353 0.620 0.028 0.008 0.332 0.012
#> GSM1233073 4 0.2378 0.6765 0.048 0.048 0.000 0.904 0.000
#> GSM1233093 5 0.0290 0.8997 0.008 0.000 0.000 0.000 0.992
#> GSM1233115 1 0.5726 0.4942 0.604 0.000 0.012 0.304 0.080
#> GSM1232992 2 0.0566 0.7752 0.000 0.984 0.004 0.012 0.000
#> GSM1232993 2 0.2249 0.7448 0.008 0.896 0.000 0.096 0.000
#> GSM1233005 2 0.0798 0.7750 0.000 0.976 0.008 0.016 0.000
#> GSM1233007 2 0.5554 0.0849 0.016 0.540 0.040 0.404 0.000
#> GSM1233010 4 0.4288 0.6242 0.180 0.052 0.004 0.764 0.000
#> GSM1233013 2 0.0451 0.7756 0.000 0.988 0.004 0.008 0.000
#> GSM1233018 2 0.0798 0.7767 0.000 0.976 0.016 0.008 0.000
#> GSM1233019 2 0.1908 0.7470 0.000 0.908 0.000 0.092 0.000
#> GSM1233021 2 0.0798 0.7750 0.000 0.976 0.008 0.016 0.000
#> GSM1233025 4 0.3511 0.5935 0.184 0.012 0.004 0.800 0.000
#> GSM1233029 2 0.2006 0.7554 0.012 0.916 0.000 0.072 0.000
#> GSM1233030 2 0.0609 0.7734 0.000 0.980 0.000 0.020 0.000
#> GSM1233031 4 0.4677 0.6192 0.196 0.068 0.004 0.732 0.000
#> GSM1233032 1 0.4733 0.3452 0.624 0.000 0.028 0.000 0.348
#> GSM1233035 4 0.5430 -0.2641 0.468 0.040 0.008 0.484 0.000
#> GSM1233038 5 0.3090 0.8480 0.104 0.000 0.000 0.040 0.856
#> GSM1233039 2 0.7881 0.1317 0.100 0.424 0.192 0.284 0.000
#> GSM1233042 4 0.3366 0.6575 0.000 0.232 0.000 0.768 0.000
#> GSM1233043 4 0.3366 0.6575 0.000 0.232 0.000 0.768 0.000
#> GSM1233044 4 0.5444 0.4528 0.160 0.000 0.180 0.660 0.000
#> GSM1233046 1 0.5097 0.2826 0.496 0.016 0.012 0.476 0.000
#> GSM1233051 1 0.4372 0.5102 0.752 0.000 0.008 0.040 0.200
#> GSM1233054 1 0.4891 -0.2157 0.500 0.016 0.480 0.000 0.004
#> GSM1233057 3 0.6448 0.2379 0.188 0.348 0.464 0.000 0.000
#> GSM1233060 4 0.5177 0.6295 0.132 0.180 0.000 0.688 0.000
#> GSM1233062 2 0.4014 0.5663 0.016 0.728 0.000 0.256 0.000
#> GSM1233075 3 0.4603 0.4670 0.032 0.300 0.668 0.000 0.000
#> GSM1233078 3 0.1557 0.7473 0.052 0.000 0.940 0.008 0.000
#> GSM1233079 1 0.4774 0.3331 0.612 0.000 0.028 0.000 0.360
#> GSM1233082 1 0.4787 0.4794 0.652 0.004 0.008 0.320 0.016
#> GSM1233083 5 0.3732 0.8172 0.120 0.000 0.004 0.056 0.820
#> GSM1233091 4 0.7162 0.2770 0.292 0.144 0.060 0.504 0.000
#> GSM1233095 5 0.0290 0.8997 0.008 0.000 0.000 0.000 0.992
#> GSM1233096 1 0.4900 0.4744 0.656 0.000 0.004 0.040 0.300
#> GSM1233101 5 0.0290 0.8997 0.008 0.000 0.000 0.000 0.992
#> GSM1233105 1 0.4702 0.2838 0.512 0.008 0.004 0.476 0.000
#> GSM1233117 2 0.2141 0.7622 0.016 0.916 0.064 0.004 0.000
#> GSM1233118 2 0.4731 0.4541 0.032 0.640 0.328 0.000 0.000
#> GSM1233001 2 0.3170 0.7257 0.036 0.856 0.104 0.004 0.000
#> GSM1233006 2 0.4166 0.3835 0.004 0.648 0.000 0.348 0.000
#> GSM1233008 2 0.0451 0.7756 0.000 0.988 0.004 0.008 0.000
#> GSM1233009 2 0.2390 0.7454 0.020 0.896 0.000 0.084 0.000
#> GSM1233017 2 0.2677 0.7297 0.016 0.872 0.000 0.112 0.000
#> GSM1233020 2 0.1041 0.7743 0.004 0.964 0.032 0.000 0.000
#> GSM1233022 4 0.4610 0.2666 0.012 0.432 0.000 0.556 0.000
#> GSM1233026 4 0.4692 0.5877 0.228 0.044 0.004 0.720 0.004
#> GSM1233028 4 0.4308 0.6429 0.168 0.060 0.004 0.768 0.000
#> GSM1233034 2 0.1750 0.7705 0.036 0.936 0.028 0.000 0.000
#> GSM1233040 1 0.4457 0.3508 0.620 0.000 0.012 0.000 0.368
#> GSM1233048 5 0.2424 0.7910 0.132 0.000 0.000 0.000 0.868
#> GSM1233056 5 0.1168 0.8921 0.032 0.000 0.000 0.008 0.960
#> GSM1233058 4 0.3971 0.6666 0.124 0.068 0.004 0.804 0.000
#> GSM1233059 5 0.0963 0.8905 0.036 0.000 0.000 0.000 0.964
#> GSM1233066 3 0.1596 0.7549 0.012 0.012 0.948 0.028 0.000
#> GSM1233071 2 0.4065 0.6582 0.048 0.772 0.000 0.180 0.000
#> GSM1233074 2 0.5003 0.2219 0.032 0.544 0.424 0.000 0.000
#> GSM1233076 4 0.7297 0.3560 0.052 0.252 0.204 0.492 0.000
#> GSM1233080 5 0.0290 0.8997 0.008 0.000 0.000 0.000 0.992
#> GSM1233088 1 0.7512 0.3021 0.504 0.168 0.232 0.096 0.000
#> GSM1233090 5 0.0609 0.8964 0.020 0.000 0.000 0.000 0.980
#> GSM1233092 4 0.3779 0.6455 0.012 0.236 0.000 0.752 0.000
#> GSM1233094 4 0.3333 0.6669 0.004 0.208 0.000 0.788 0.000
#> GSM1233097 4 0.3520 0.6845 0.080 0.076 0.004 0.840 0.000
#> GSM1233100 4 0.3731 0.6896 0.072 0.112 0.000 0.816 0.000
#> GSM1233104 4 0.3098 0.6889 0.016 0.148 0.000 0.836 0.000
#> GSM1233106 1 0.4647 0.5615 0.744 0.008 0.008 0.200 0.040
#> GSM1233111 1 0.4674 0.4389 0.656 0.000 0.004 0.024 0.316
#> GSM1233122 2 0.0960 0.7765 0.004 0.972 0.016 0.008 0.000
#> GSM1233146 4 0.2439 0.6934 0.004 0.120 0.000 0.876 0.000
#> GSM1232994 2 0.2727 0.7269 0.016 0.868 0.000 0.116 0.000
#> GSM1232996 2 0.0898 0.7769 0.000 0.972 0.020 0.008 0.000
#> GSM1232997 2 0.4620 0.4658 0.028 0.652 0.320 0.000 0.000
#> GSM1232998 4 0.4359 0.3344 0.000 0.412 0.004 0.584 0.000
#> GSM1232999 2 0.4359 0.1708 0.000 0.584 0.004 0.412 0.000
#> GSM1233000 2 0.1670 0.7604 0.012 0.936 0.000 0.052 0.000
#> GSM1233004 4 0.5809 0.2660 0.068 0.012 0.376 0.544 0.000
#> GSM1233011 3 0.6891 -0.0449 0.028 0.144 0.424 0.404 0.000
#> GSM1233012 2 0.3197 0.6994 0.024 0.836 0.140 0.000 0.000
#> GSM1233023 2 0.4218 0.6368 0.040 0.760 0.196 0.004 0.000
#> GSM1233027 2 0.3838 0.5050 0.000 0.716 0.004 0.280 0.000
#> GSM1233033 1 0.5793 0.2565 0.548 0.000 0.000 0.104 0.348
#> GSM1233036 3 0.4806 0.5267 0.060 0.252 0.688 0.000 0.000
#> GSM1233037 1 0.6225 0.1449 0.548 0.224 0.228 0.000 0.000
#> GSM1233041 5 0.1732 0.8750 0.080 0.000 0.000 0.000 0.920
#> GSM1233045 4 0.4658 0.6749 0.124 0.120 0.004 0.752 0.000
#> GSM1233047 3 0.4375 0.3722 0.420 0.000 0.576 0.000 0.004
#> GSM1233050 5 0.2020 0.8340 0.100 0.000 0.000 0.000 0.900
#> GSM1233052 1 0.5080 0.4243 0.596 0.004 0.012 0.372 0.016
#> GSM1233053 1 0.5351 0.3000 0.560 0.000 0.060 0.000 0.380
#> GSM1233055 5 0.1168 0.8928 0.032 0.000 0.000 0.008 0.960
#> GSM1233061 3 0.1357 0.7499 0.048 0.000 0.948 0.004 0.000
#> GSM1233063 1 0.4878 0.4703 0.676 0.000 0.000 0.060 0.264
#> GSM1233065 2 0.4854 0.4212 0.028 0.628 0.340 0.004 0.000
#> GSM1233070 2 0.4837 0.3485 0.016 0.628 0.012 0.344 0.000
#> GSM1233077 3 0.1954 0.7504 0.008 0.032 0.932 0.028 0.000
#> GSM1233081 3 0.4336 0.5687 0.280 0.000 0.700 0.008 0.012
#> GSM1233084 5 0.1043 0.8958 0.040 0.000 0.000 0.000 0.960
#> GSM1233087 4 0.2899 0.6520 0.100 0.020 0.008 0.872 0.000
#> GSM1233089 2 0.1788 0.7691 0.008 0.932 0.056 0.004 0.000
#> GSM1233099 4 0.3751 0.5255 0.212 0.000 0.012 0.772 0.004
#> GSM1233112 5 0.3985 0.8058 0.120 0.000 0.004 0.072 0.804
#> GSM1233085 3 0.4130 0.5621 0.292 0.000 0.696 0.000 0.012
#> GSM1233098 2 0.2165 0.7719 0.016 0.924 0.036 0.024 0.000
#> GSM1233114 1 0.5310 0.4611 0.616 0.000 0.012 0.328 0.044
#> GSM1233119 4 0.3202 0.6034 0.148 0.004 0.008 0.836 0.004
#> GSM1233129 2 0.4968 0.1309 0.028 0.516 0.456 0.000 0.000
#> GSM1233132 1 0.5828 0.3578 0.508 0.000 0.012 0.416 0.064
#> GSM1233139 2 0.2434 0.7706 0.048 0.908 0.008 0.036 0.000
#> GSM1233143 2 0.4775 0.5909 0.036 0.712 0.236 0.016 0.000
#> GSM1233145 5 0.4478 0.7627 0.144 0.000 0.004 0.088 0.764
#> GSM1233067 3 0.3882 0.5926 0.020 0.224 0.756 0.000 0.000
#> GSM1233069 3 0.1591 0.7513 0.004 0.052 0.940 0.004 0.000
#> GSM1233072 2 0.1281 0.7759 0.000 0.956 0.032 0.012 0.000
#> GSM1233086 3 0.4421 0.5899 0.020 0.024 0.748 0.208 0.000
#> GSM1233102 4 0.3961 0.5452 0.168 0.000 0.012 0.792 0.028
#> GSM1233103 1 0.5225 0.2266 0.508 0.028 0.008 0.456 0.000
#> GSM1233107 1 0.5058 0.2111 0.492 0.008 0.012 0.484 0.004
#> GSM1233108 3 0.6530 0.3714 0.280 0.000 0.532 0.012 0.176
#> GSM1233109 3 0.3461 0.6920 0.168 0.000 0.812 0.016 0.004
#> GSM1233110 3 0.1356 0.7560 0.028 0.012 0.956 0.004 0.000
#> GSM1233113 2 0.4243 0.5584 0.024 0.712 0.264 0.000 0.000
#> GSM1233116 3 0.4829 -0.0605 0.020 0.480 0.500 0.000 0.000
#> GSM1233120 4 0.4229 0.5177 0.208 0.000 0.012 0.756 0.024
#> GSM1233121 3 0.1954 0.7504 0.008 0.032 0.932 0.028 0.000
#> GSM1233123 3 0.1356 0.7560 0.028 0.012 0.956 0.004 0.000
#> GSM1233124 3 0.1990 0.7571 0.040 0.028 0.928 0.004 0.000
#> GSM1233125 3 0.6544 0.3780 0.264 0.000 0.536 0.012 0.188
#> GSM1233126 4 0.4300 0.6348 0.096 0.132 0.000 0.772 0.000
#> GSM1233127 2 0.5863 0.3893 0.096 0.580 0.008 0.316 0.000
#> GSM1233128 5 0.2621 0.8720 0.112 0.000 0.004 0.008 0.876
#> GSM1233130 3 0.1413 0.7555 0.012 0.020 0.956 0.012 0.000
#> GSM1233131 1 0.4504 0.3380 0.564 0.000 0.008 0.428 0.000
#> GSM1233133 3 0.3048 0.6864 0.176 0.000 0.820 0.000 0.004
#> GSM1233134 3 0.2074 0.7544 0.044 0.036 0.920 0.000 0.000
#> GSM1233135 3 0.1701 0.7494 0.016 0.048 0.936 0.000 0.000
#> GSM1233136 3 0.2234 0.7468 0.012 0.032 0.920 0.036 0.000
#> GSM1233137 3 0.3123 0.6834 0.184 0.000 0.812 0.000 0.004
#> GSM1233138 4 0.3904 0.6554 0.052 0.156 0.000 0.792 0.000
#> GSM1233140 1 0.5303 0.4438 0.688 0.000 0.172 0.004 0.136
#> GSM1233141 2 0.5538 0.5821 0.092 0.676 0.020 0.212 0.000
#> GSM1233142 2 0.5025 0.6236 0.092 0.716 0.008 0.184 0.000
#> GSM1233144 3 0.3048 0.6864 0.176 0.000 0.820 0.000 0.004
#> GSM1233147 4 0.6866 0.3256 0.016 0.252 0.240 0.492 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.2044 0.7337 0.000 0.920 0.028 0.004 0.008 0.040
#> GSM1233002 4 0.4629 0.4246 0.000 0.044 0.008 0.724 0.028 0.196
#> GSM1233003 1 0.6437 0.5060 0.536 0.000 0.000 0.076 0.244 0.144
#> GSM1233014 4 0.3329 0.4998 0.000 0.220 0.000 0.768 0.004 0.008
#> GSM1233015 5 0.5334 0.1003 0.024 0.000 0.000 0.076 0.596 0.304
#> GSM1233016 4 0.4602 0.3753 0.004 0.036 0.000 0.728 0.044 0.188
#> GSM1233024 2 0.3771 0.6454 0.000 0.776 0.000 0.172 0.008 0.044
#> GSM1233049 1 0.0547 0.8274 0.980 0.000 0.000 0.000 0.020 0.000
#> GSM1233064 2 0.6471 0.4235 0.000 0.576 0.236 0.096 0.028 0.064
#> GSM1233068 6 0.6570 0.4453 0.000 0.032 0.000 0.220 0.348 0.400
#> GSM1233073 4 0.3042 0.4531 0.000 0.032 0.000 0.836 0.004 0.128
#> GSM1233093 1 0.1075 0.8283 0.952 0.000 0.000 0.000 0.048 0.000
#> GSM1233115 6 0.6347 0.4881 0.012 0.000 0.008 0.204 0.316 0.460
#> GSM1232992 2 0.0547 0.7435 0.000 0.980 0.000 0.020 0.000 0.000
#> GSM1232993 2 0.3122 0.6739 0.000 0.816 0.000 0.160 0.004 0.020
#> GSM1233005 2 0.1003 0.7445 0.000 0.964 0.004 0.028 0.000 0.004
#> GSM1233007 4 0.5606 0.1357 0.000 0.452 0.040 0.460 0.004 0.044
#> GSM1233010 4 0.4738 0.2309 0.000 0.004 0.008 0.624 0.040 0.324
#> GSM1233013 2 0.0603 0.7441 0.000 0.980 0.000 0.016 0.000 0.004
#> GSM1233018 2 0.1096 0.7445 0.000 0.964 0.004 0.020 0.004 0.008
#> GSM1233019 2 0.2618 0.7042 0.000 0.860 0.000 0.116 0.000 0.024
#> GSM1233021 2 0.0858 0.7442 0.000 0.968 0.000 0.028 0.000 0.004
#> GSM1233025 4 0.4598 0.3155 0.012 0.000 0.008 0.696 0.044 0.240
#> GSM1233029 2 0.2563 0.7255 0.000 0.880 0.000 0.084 0.008 0.028
#> GSM1233030 2 0.1152 0.7402 0.000 0.952 0.000 0.044 0.000 0.004
#> GSM1233031 4 0.4868 0.0180 0.000 0.008 0.000 0.548 0.044 0.400
#> GSM1233032 5 0.2730 0.5333 0.124 0.000 0.004 0.004 0.856 0.012
#> GSM1233035 6 0.6329 0.5152 0.000 0.016 0.000 0.368 0.220 0.396
#> GSM1233038 1 0.3336 0.7844 0.840 0.000 0.000 0.024 0.052 0.084
#> GSM1233039 2 0.8080 -0.0264 0.000 0.372 0.184 0.264 0.052 0.128
#> GSM1233042 4 0.3014 0.5249 0.000 0.184 0.000 0.804 0.000 0.012
#> GSM1233043 4 0.3014 0.5249 0.000 0.184 0.000 0.804 0.000 0.012
#> GSM1233044 4 0.5809 0.2756 0.000 0.000 0.104 0.616 0.064 0.216
#> GSM1233046 6 0.6359 0.5003 0.008 0.008 0.000 0.324 0.224 0.436
#> GSM1233051 5 0.4560 0.4414 0.040 0.000 0.000 0.048 0.728 0.184
#> GSM1233054 5 0.6050 0.1376 0.000 0.032 0.348 0.004 0.508 0.108
#> GSM1233057 3 0.6994 0.3219 0.000 0.276 0.468 0.004 0.140 0.112
#> GSM1233060 4 0.5899 0.2048 0.000 0.160 0.000 0.528 0.016 0.296
#> GSM1233062 2 0.4628 0.5130 0.000 0.668 0.000 0.268 0.012 0.052
#> GSM1233075 3 0.5017 0.3973 0.000 0.312 0.612 0.000 0.016 0.060
#> GSM1233078 3 0.2412 0.6856 0.000 0.000 0.880 0.000 0.092 0.028
#> GSM1233079 5 0.2812 0.5356 0.108 0.000 0.004 0.004 0.860 0.024
#> GSM1233082 6 0.5818 0.4273 0.000 0.000 0.000 0.184 0.392 0.424
#> GSM1233083 1 0.4309 0.7377 0.768 0.000 0.000 0.044 0.060 0.128
#> GSM1233091 4 0.8080 -0.1337 0.000 0.092 0.068 0.348 0.192 0.300
#> GSM1233095 1 0.1075 0.8283 0.952 0.000 0.000 0.000 0.048 0.000
#> GSM1233096 5 0.5517 0.3403 0.088 0.000 0.000 0.048 0.632 0.232
#> GSM1233101 1 0.1007 0.8284 0.956 0.000 0.000 0.000 0.044 0.000
#> GSM1233105 6 0.6410 0.4438 0.016 0.004 0.000 0.324 0.220 0.436
#> GSM1233117 2 0.2339 0.7418 0.000 0.908 0.024 0.028 0.004 0.036
#> GSM1233118 2 0.5187 0.3557 0.000 0.588 0.332 0.004 0.012 0.064
#> GSM1233001 2 0.2908 0.7098 0.000 0.872 0.064 0.004 0.016 0.044
#> GSM1233006 2 0.4459 0.1138 0.000 0.516 0.000 0.460 0.004 0.020
#> GSM1233008 2 0.1262 0.7456 0.000 0.956 0.000 0.020 0.008 0.016
#> GSM1233009 2 0.3176 0.7018 0.000 0.840 0.000 0.100 0.008 0.052
#> GSM1233017 2 0.3505 0.6754 0.000 0.808 0.000 0.136 0.008 0.048
#> GSM1233020 2 0.0665 0.7445 0.000 0.980 0.008 0.000 0.004 0.008
#> GSM1233022 4 0.4743 0.2891 0.000 0.348 0.000 0.600 0.008 0.044
#> GSM1233026 4 0.5604 0.1775 0.000 0.008 0.008 0.556 0.104 0.324
#> GSM1233028 4 0.4718 0.2766 0.000 0.008 0.008 0.640 0.036 0.308
#> GSM1233034 2 0.2427 0.7323 0.000 0.904 0.012 0.012 0.028 0.044
#> GSM1233040 5 0.4468 0.5096 0.148 0.000 0.004 0.004 0.732 0.112
#> GSM1233048 1 0.3398 0.6369 0.740 0.000 0.000 0.000 0.252 0.008
#> GSM1233056 1 0.0692 0.8226 0.976 0.000 0.000 0.000 0.004 0.020
#> GSM1233058 4 0.4649 0.3351 0.000 0.008 0.008 0.656 0.036 0.292
#> GSM1233059 1 0.2048 0.7957 0.880 0.000 0.000 0.000 0.120 0.000
#> GSM1233066 3 0.1321 0.7247 0.000 0.004 0.952 0.000 0.024 0.020
#> GSM1233071 2 0.5340 0.4855 0.000 0.628 0.000 0.212 0.012 0.148
#> GSM1233074 2 0.5276 0.1225 0.000 0.500 0.424 0.000 0.016 0.060
#> GSM1233076 4 0.6731 0.3924 0.000 0.176 0.168 0.552 0.012 0.092
#> GSM1233080 1 0.1075 0.8283 0.952 0.000 0.000 0.000 0.048 0.000
#> GSM1233088 6 0.8369 0.0288 0.000 0.132 0.188 0.076 0.284 0.320
#> GSM1233090 1 0.1387 0.8226 0.932 0.000 0.000 0.000 0.068 0.000
#> GSM1233092 4 0.2810 0.5260 0.000 0.156 0.000 0.832 0.004 0.008
#> GSM1233094 4 0.2655 0.5283 0.000 0.140 0.000 0.848 0.004 0.008
#> GSM1233097 4 0.4292 0.4044 0.000 0.020 0.008 0.712 0.016 0.244
#> GSM1233100 4 0.4330 0.3865 0.000 0.052 0.000 0.708 0.008 0.232
#> GSM1233104 4 0.3370 0.5147 0.000 0.064 0.000 0.812 0.000 0.124
#> GSM1233106 5 0.5023 0.0449 0.000 0.004 0.000 0.084 0.600 0.312
#> GSM1233111 5 0.4914 0.4639 0.092 0.000 0.004 0.036 0.720 0.148
#> GSM1233122 2 0.0951 0.7447 0.000 0.968 0.004 0.020 0.000 0.008
#> GSM1233146 4 0.1989 0.5233 0.000 0.052 0.000 0.916 0.004 0.028
#> GSM1232994 2 0.3306 0.6799 0.000 0.820 0.000 0.136 0.008 0.036
#> GSM1232996 2 0.1198 0.7435 0.000 0.960 0.004 0.012 0.004 0.020
#> GSM1232997 2 0.5043 0.3908 0.000 0.612 0.312 0.000 0.020 0.056
#> GSM1232998 4 0.3888 0.4384 0.000 0.312 0.000 0.672 0.000 0.016
#> GSM1232999 4 0.4264 0.0476 0.000 0.484 0.000 0.500 0.000 0.016
#> GSM1233000 2 0.2065 0.7307 0.000 0.912 0.000 0.052 0.004 0.032
#> GSM1233004 4 0.6645 0.2443 0.000 0.016 0.264 0.480 0.024 0.216
#> GSM1233011 4 0.7226 0.1519 0.000 0.140 0.348 0.408 0.020 0.084
#> GSM1233012 2 0.3718 0.6708 0.000 0.808 0.116 0.004 0.012 0.060
#> GSM1233023 2 0.4603 0.5536 0.000 0.712 0.212 0.004 0.020 0.052
#> GSM1233027 2 0.3847 0.3719 0.000 0.644 0.000 0.348 0.000 0.008
#> GSM1233033 5 0.6892 0.2234 0.196 0.000 0.000 0.084 0.460 0.260
#> GSM1233036 3 0.5277 0.5337 0.000 0.236 0.656 0.008 0.028 0.072
#> GSM1233037 5 0.7385 0.2400 0.000 0.164 0.208 0.012 0.460 0.156
#> GSM1233041 1 0.3518 0.7093 0.732 0.000 0.000 0.000 0.256 0.012
#> GSM1233045 4 0.5408 0.3761 0.000 0.052 0.008 0.616 0.036 0.288
#> GSM1233047 5 0.5449 -0.0941 0.008 0.000 0.436 0.000 0.464 0.092
#> GSM1233050 1 0.2941 0.6949 0.780 0.000 0.000 0.000 0.220 0.000
#> GSM1233052 6 0.5871 0.5251 0.000 0.000 0.000 0.220 0.312 0.468
#> GSM1233053 5 0.5822 0.4394 0.248 0.000 0.068 0.000 0.600 0.084
#> GSM1233055 1 0.0692 0.8226 0.976 0.000 0.000 0.000 0.004 0.020
#> GSM1233061 3 0.1720 0.7199 0.000 0.000 0.928 0.000 0.040 0.032
#> GSM1233063 5 0.5302 0.4181 0.084 0.000 0.000 0.048 0.664 0.204
#> GSM1233065 2 0.5534 0.2656 0.000 0.548 0.356 0.008 0.016 0.072
#> GSM1233070 2 0.4608 0.1303 0.000 0.552 0.004 0.412 0.000 0.032
#> GSM1233077 3 0.2256 0.7121 0.000 0.032 0.908 0.004 0.008 0.048
#> GSM1233081 3 0.4937 0.3807 0.008 0.000 0.592 0.000 0.340 0.060
#> GSM1233084 1 0.2821 0.7941 0.832 0.000 0.000 0.000 0.152 0.016
#> GSM1233087 4 0.3855 0.3950 0.012 0.000 0.008 0.760 0.016 0.204
#> GSM1233089 2 0.1565 0.7405 0.000 0.940 0.028 0.004 0.000 0.028
#> GSM1233099 6 0.4220 0.1237 0.004 0.000 0.000 0.468 0.008 0.520
#> GSM1233112 1 0.4411 0.7316 0.760 0.000 0.000 0.048 0.060 0.132
#> GSM1233085 3 0.4972 0.3502 0.008 0.000 0.580 0.000 0.352 0.060
#> GSM1233098 2 0.2043 0.7333 0.000 0.912 0.012 0.064 0.000 0.012
#> GSM1233114 6 0.5365 0.5042 0.024 0.000 0.000 0.144 0.184 0.648
#> GSM1233119 4 0.4132 0.3050 0.004 0.000 0.008 0.632 0.004 0.352
#> GSM1233129 2 0.5415 0.0700 0.000 0.484 0.436 0.004 0.016 0.060
#> GSM1233132 6 0.5654 0.5702 0.040 0.000 0.000 0.192 0.140 0.628
#> GSM1233139 2 0.2867 0.7342 0.000 0.868 0.000 0.040 0.016 0.076
#> GSM1233143 2 0.5770 0.5987 0.000 0.656 0.184 0.052 0.020 0.088
#> GSM1233145 1 0.4847 0.6980 0.716 0.000 0.000 0.052 0.064 0.168
#> GSM1233067 3 0.3741 0.5985 0.000 0.208 0.756 0.000 0.004 0.032
#> GSM1233069 3 0.2078 0.7159 0.000 0.040 0.912 0.000 0.004 0.044
#> GSM1233072 2 0.1168 0.7465 0.000 0.956 0.000 0.016 0.000 0.028
#> GSM1233086 3 0.5326 0.5177 0.000 0.028 0.684 0.180 0.016 0.092
#> GSM1233102 4 0.5010 0.1556 0.032 0.000 0.000 0.592 0.032 0.344
#> GSM1233103 6 0.5848 0.5943 0.000 0.004 0.000 0.272 0.212 0.512
#> GSM1233107 6 0.4698 0.5325 0.008 0.000 0.000 0.240 0.076 0.676
#> GSM1233108 3 0.6042 0.0703 0.056 0.000 0.444 0.004 0.432 0.064
#> GSM1233109 3 0.4418 0.5703 0.000 0.000 0.716 0.008 0.204 0.072
#> GSM1233110 3 0.1245 0.7174 0.000 0.000 0.952 0.000 0.032 0.016
#> GSM1233113 2 0.4718 0.4815 0.000 0.664 0.264 0.000 0.012 0.060
#> GSM1233116 3 0.4862 0.1049 0.000 0.428 0.520 0.000 0.004 0.048
#> GSM1233120 6 0.4778 0.1169 0.028 0.000 0.000 0.452 0.012 0.508
#> GSM1233121 3 0.2180 0.7132 0.000 0.028 0.912 0.004 0.008 0.048
#> GSM1233123 3 0.0806 0.7214 0.000 0.000 0.972 0.000 0.020 0.008
#> GSM1233124 3 0.1777 0.7224 0.000 0.012 0.932 0.000 0.024 0.032
#> GSM1233125 5 0.6168 -0.1104 0.072 0.000 0.420 0.004 0.444 0.060
#> GSM1233126 4 0.4280 0.4519 0.004 0.080 0.000 0.752 0.008 0.156
#> GSM1233127 2 0.6034 0.3000 0.000 0.476 0.000 0.180 0.012 0.332
#> GSM1233128 1 0.4631 0.6858 0.700 0.000 0.000 0.008 0.200 0.092
#> GSM1233130 3 0.2057 0.7164 0.000 0.016 0.920 0.004 0.016 0.044
#> GSM1233131 6 0.5681 0.5968 0.004 0.000 0.000 0.232 0.212 0.552
#> GSM1233133 3 0.4039 0.5579 0.004 0.000 0.724 0.000 0.232 0.040
#> GSM1233134 3 0.1787 0.7219 0.000 0.016 0.932 0.000 0.020 0.032
#> GSM1233135 3 0.1261 0.7236 0.000 0.024 0.952 0.000 0.000 0.024
#> GSM1233136 3 0.2321 0.7107 0.000 0.032 0.904 0.004 0.008 0.052
#> GSM1233137 3 0.4188 0.5479 0.004 0.000 0.712 0.000 0.236 0.048
#> GSM1233138 4 0.3590 0.5027 0.000 0.116 0.000 0.804 0.004 0.076
#> GSM1233140 5 0.3707 0.5018 0.024 0.000 0.088 0.004 0.820 0.064
#> GSM1233141 2 0.5848 0.4258 0.000 0.544 0.008 0.144 0.008 0.296
#> GSM1233142 2 0.5676 0.4425 0.000 0.556 0.000 0.144 0.012 0.288
#> GSM1233144 3 0.3900 0.5610 0.000 0.000 0.728 0.000 0.232 0.040
#> GSM1233147 4 0.6554 0.3912 0.000 0.184 0.204 0.544 0.008 0.060
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> SD:kmeans 149 1.00e+00 0.737 0.7240 2
#> SD:kmeans 107 2.59e-03 0.657 0.0320 3
#> SD:kmeans 130 5.35e-06 0.102 0.0283 4
#> SD:kmeans 106 1.26e-05 0.346 0.0245 5
#> SD:kmeans 88 1.21e-05 0.133 0.0387 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 51941 rows and 156 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 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.972 0.952 0.980 0.4990 0.502 0.502
#> 3 3 0.705 0.830 0.916 0.3284 0.752 0.544
#> 4 4 0.655 0.712 0.860 0.1206 0.820 0.535
#> 5 5 0.634 0.584 0.767 0.0581 0.936 0.768
#> 6 6 0.622 0.501 0.712 0.0421 0.961 0.841
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0000 0.977 0.000 1.000
#> GSM1233002 1 0.6438 0.806 0.836 0.164
#> GSM1233003 1 0.0000 0.981 1.000 0.000
#> GSM1233014 2 0.0000 0.977 0.000 1.000
#> GSM1233015 1 0.0000 0.981 1.000 0.000
#> GSM1233016 1 0.0938 0.972 0.988 0.012
#> GSM1233024 2 0.0000 0.977 0.000 1.000
#> GSM1233049 1 0.0000 0.981 1.000 0.000
#> GSM1233064 2 0.0000 0.977 0.000 1.000
#> GSM1233068 1 0.0000 0.981 1.000 0.000
#> GSM1233073 1 0.1633 0.962 0.976 0.024
#> GSM1233093 1 0.0000 0.981 1.000 0.000
#> GSM1233115 1 0.0000 0.981 1.000 0.000
#> GSM1232992 2 0.0000 0.977 0.000 1.000
#> GSM1232993 2 0.0000 0.977 0.000 1.000
#> GSM1233005 2 0.0000 0.977 0.000 1.000
#> GSM1233007 2 0.0000 0.977 0.000 1.000
#> GSM1233010 1 0.0672 0.975 0.992 0.008
#> GSM1233013 2 0.0000 0.977 0.000 1.000
#> GSM1233018 2 0.0000 0.977 0.000 1.000
#> GSM1233019 2 0.0000 0.977 0.000 1.000
#> GSM1233021 2 0.0000 0.977 0.000 1.000
#> GSM1233025 1 0.0000 0.981 1.000 0.000
#> GSM1233029 2 0.0000 0.977 0.000 1.000
#> GSM1233030 2 0.0000 0.977 0.000 1.000
#> GSM1233031 1 0.4939 0.875 0.892 0.108
#> GSM1233032 1 0.0000 0.981 1.000 0.000
#> GSM1233035 1 0.0000 0.981 1.000 0.000
#> GSM1233038 1 0.0000 0.981 1.000 0.000
#> GSM1233039 2 0.0000 0.977 0.000 1.000
#> GSM1233042 2 0.0000 0.977 0.000 1.000
#> GSM1233043 2 0.0000 0.977 0.000 1.000
#> GSM1233044 1 0.0000 0.981 1.000 0.000
#> GSM1233046 1 0.0000 0.981 1.000 0.000
#> GSM1233051 1 0.0000 0.981 1.000 0.000
#> GSM1233054 1 0.4298 0.899 0.912 0.088
#> GSM1233057 2 0.0000 0.977 0.000 1.000
#> GSM1233060 2 0.8499 0.613 0.276 0.724
#> GSM1233062 2 0.0000 0.977 0.000 1.000
#> GSM1233075 2 0.0000 0.977 0.000 1.000
#> GSM1233078 1 0.2236 0.950 0.964 0.036
#> GSM1233079 1 0.0000 0.981 1.000 0.000
#> GSM1233082 1 0.0000 0.981 1.000 0.000
#> GSM1233083 1 0.0000 0.981 1.000 0.000
#> GSM1233091 2 0.9881 0.216 0.436 0.564
#> GSM1233095 1 0.0000 0.981 1.000 0.000
#> GSM1233096 1 0.0000 0.981 1.000 0.000
#> GSM1233101 1 0.0000 0.981 1.000 0.000
#> GSM1233105 1 0.0000 0.981 1.000 0.000
#> GSM1233117 2 0.0000 0.977 0.000 1.000
#> GSM1233118 2 0.0000 0.977 0.000 1.000
#> GSM1233001 2 0.0000 0.977 0.000 1.000
#> GSM1233006 2 0.0000 0.977 0.000 1.000
#> GSM1233008 2 0.0000 0.977 0.000 1.000
#> GSM1233009 2 0.0000 0.977 0.000 1.000
#> GSM1233017 2 0.0000 0.977 0.000 1.000
#> GSM1233020 2 0.0000 0.977 0.000 1.000
#> GSM1233022 2 0.0000 0.977 0.000 1.000
#> GSM1233026 1 0.9580 0.378 0.620 0.380
#> GSM1233028 2 0.7815 0.701 0.232 0.768
#> GSM1233034 2 0.0000 0.977 0.000 1.000
#> GSM1233040 1 0.0000 0.981 1.000 0.000
#> GSM1233048 1 0.0000 0.981 1.000 0.000
#> GSM1233056 1 0.0000 0.981 1.000 0.000
#> GSM1233058 1 0.8608 0.611 0.716 0.284
#> GSM1233059 1 0.0000 0.981 1.000 0.000
#> GSM1233066 2 0.0672 0.971 0.008 0.992
#> GSM1233071 2 0.0000 0.977 0.000 1.000
#> GSM1233074 2 0.0000 0.977 0.000 1.000
#> GSM1233076 2 0.0000 0.977 0.000 1.000
#> GSM1233080 1 0.0000 0.981 1.000 0.000
#> GSM1233088 2 0.9866 0.231 0.432 0.568
#> GSM1233090 1 0.0000 0.981 1.000 0.000
#> GSM1233092 2 0.0000 0.977 0.000 1.000
#> GSM1233094 2 0.0000 0.977 0.000 1.000
#> GSM1233097 2 0.3274 0.923 0.060 0.940
#> GSM1233100 1 0.5737 0.843 0.864 0.136
#> GSM1233104 2 0.0000 0.977 0.000 1.000
#> GSM1233106 1 0.0000 0.981 1.000 0.000
#> GSM1233111 1 0.0000 0.981 1.000 0.000
#> GSM1233122 2 0.0000 0.977 0.000 1.000
#> GSM1233146 2 0.0672 0.971 0.008 0.992
#> GSM1232994 2 0.0000 0.977 0.000 1.000
#> GSM1232996 2 0.0000 0.977 0.000 1.000
#> GSM1232997 2 0.0000 0.977 0.000 1.000
#> GSM1232998 2 0.0000 0.977 0.000 1.000
#> GSM1232999 2 0.0000 0.977 0.000 1.000
#> GSM1233000 2 0.0000 0.977 0.000 1.000
#> GSM1233004 1 0.0376 0.978 0.996 0.004
#> GSM1233011 2 0.0000 0.977 0.000 1.000
#> GSM1233012 2 0.0000 0.977 0.000 1.000
#> GSM1233023 2 0.0000 0.977 0.000 1.000
#> GSM1233027 2 0.0000 0.977 0.000 1.000
#> GSM1233033 1 0.0000 0.981 1.000 0.000
#> GSM1233036 2 0.0000 0.977 0.000 1.000
#> GSM1233037 2 0.0672 0.971 0.008 0.992
#> GSM1233041 1 0.0000 0.981 1.000 0.000
#> GSM1233045 2 0.0000 0.977 0.000 1.000
#> GSM1233047 1 0.0000 0.981 1.000 0.000
#> GSM1233050 1 0.0000 0.981 1.000 0.000
#> GSM1233052 1 0.0000 0.981 1.000 0.000
#> GSM1233053 1 0.0000 0.981 1.000 0.000
#> GSM1233055 1 0.0000 0.981 1.000 0.000
#> GSM1233061 2 0.7528 0.730 0.216 0.784
#> GSM1233063 1 0.0000 0.981 1.000 0.000
#> GSM1233065 2 0.0000 0.977 0.000 1.000
#> GSM1233070 2 0.0000 0.977 0.000 1.000
#> GSM1233077 2 0.0000 0.977 0.000 1.000
#> GSM1233081 1 0.0000 0.981 1.000 0.000
#> GSM1233084 1 0.0000 0.981 1.000 0.000
#> GSM1233087 1 0.0000 0.981 1.000 0.000
#> GSM1233089 2 0.0000 0.977 0.000 1.000
#> GSM1233099 1 0.0000 0.981 1.000 0.000
#> GSM1233112 1 0.0000 0.981 1.000 0.000
#> GSM1233085 1 0.0000 0.981 1.000 0.000
#> GSM1233098 2 0.0000 0.977 0.000 1.000
#> GSM1233114 1 0.0000 0.981 1.000 0.000
#> GSM1233119 1 0.0000 0.981 1.000 0.000
#> GSM1233129 2 0.0000 0.977 0.000 1.000
#> GSM1233132 1 0.0000 0.981 1.000 0.000
#> GSM1233139 2 0.0000 0.977 0.000 1.000
#> GSM1233143 2 0.0000 0.977 0.000 1.000
#> GSM1233145 1 0.0000 0.981 1.000 0.000
#> GSM1233067 2 0.0000 0.977 0.000 1.000
#> GSM1233069 2 0.0000 0.977 0.000 1.000
#> GSM1233072 2 0.0000 0.977 0.000 1.000
#> GSM1233086 2 0.0000 0.977 0.000 1.000
#> GSM1233102 1 0.0000 0.981 1.000 0.000
#> GSM1233103 1 0.0000 0.981 1.000 0.000
#> GSM1233107 1 0.0376 0.978 0.996 0.004
#> GSM1233108 1 0.0000 0.981 1.000 0.000
#> GSM1233109 1 0.0000 0.981 1.000 0.000
#> GSM1233110 2 0.4161 0.898 0.084 0.916
#> GSM1233113 2 0.0000 0.977 0.000 1.000
#> GSM1233116 2 0.0000 0.977 0.000 1.000
#> GSM1233120 1 0.0000 0.981 1.000 0.000
#> GSM1233121 2 0.0000 0.977 0.000 1.000
#> GSM1233123 2 0.2948 0.931 0.052 0.948
#> GSM1233124 2 0.0376 0.974 0.004 0.996
#> GSM1233125 1 0.0000 0.981 1.000 0.000
#> GSM1233126 2 0.3584 0.916 0.068 0.932
#> GSM1233127 2 0.0000 0.977 0.000 1.000
#> GSM1233128 1 0.0000 0.981 1.000 0.000
#> GSM1233130 2 0.0376 0.974 0.004 0.996
#> GSM1233131 1 0.0000 0.981 1.000 0.000
#> GSM1233133 1 0.0000 0.981 1.000 0.000
#> GSM1233134 2 0.0000 0.977 0.000 1.000
#> GSM1233135 2 0.0000 0.977 0.000 1.000
#> GSM1233136 2 0.0000 0.977 0.000 1.000
#> GSM1233137 1 0.0000 0.981 1.000 0.000
#> GSM1233138 2 0.0000 0.977 0.000 1.000
#> GSM1233140 1 0.0000 0.981 1.000 0.000
#> GSM1233141 2 0.0000 0.977 0.000 1.000
#> GSM1233142 2 0.0000 0.977 0.000 1.000
#> GSM1233144 1 0.0000 0.981 1.000 0.000
#> GSM1233147 2 0.0000 0.977 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.5397 0.7016 0.000 0.720 0.280
#> GSM1233002 2 0.5254 0.5805 0.264 0.736 0.000
#> GSM1233003 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233014 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233015 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233016 1 0.5760 0.5776 0.672 0.328 0.000
#> GSM1233024 2 0.2261 0.8873 0.000 0.932 0.068
#> GSM1233049 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233064 3 0.4702 0.6684 0.000 0.212 0.788
#> GSM1233068 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233073 1 0.6180 0.3855 0.584 0.416 0.000
#> GSM1233093 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233115 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1232992 2 0.3192 0.8773 0.000 0.888 0.112
#> GSM1232993 2 0.2165 0.8875 0.000 0.936 0.064
#> GSM1233005 2 0.3192 0.8773 0.000 0.888 0.112
#> GSM1233007 2 0.1860 0.8727 0.000 0.948 0.052
#> GSM1233010 1 0.4931 0.7314 0.768 0.232 0.000
#> GSM1233013 2 0.3192 0.8773 0.000 0.888 0.112
#> GSM1233018 2 0.3192 0.8773 0.000 0.888 0.112
#> GSM1233019 2 0.2625 0.8854 0.000 0.916 0.084
#> GSM1233021 2 0.3192 0.8773 0.000 0.888 0.112
#> GSM1233025 1 0.3116 0.8581 0.892 0.108 0.000
#> GSM1233029 2 0.2356 0.8871 0.000 0.928 0.072
#> GSM1233030 2 0.3116 0.8788 0.000 0.892 0.108
#> GSM1233031 2 0.4002 0.7489 0.160 0.840 0.000
#> GSM1233032 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233035 1 0.3619 0.8284 0.864 0.136 0.000
#> GSM1233038 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233039 3 0.5678 0.4799 0.000 0.316 0.684
#> GSM1233042 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233043 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233044 1 0.3349 0.8420 0.888 0.004 0.108
#> GSM1233046 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233051 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233054 3 0.3412 0.8095 0.124 0.000 0.876
#> GSM1233057 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233060 2 0.0592 0.8749 0.012 0.988 0.000
#> GSM1233062 2 0.1753 0.8870 0.000 0.952 0.048
#> GSM1233075 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233078 3 0.2878 0.8337 0.096 0.000 0.904
#> GSM1233079 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233082 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233083 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233091 3 0.6677 0.7227 0.088 0.168 0.744
#> GSM1233095 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233096 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233101 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233105 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233117 2 0.4750 0.7890 0.000 0.784 0.216
#> GSM1233118 3 0.0237 0.8981 0.000 0.004 0.996
#> GSM1233001 3 0.5760 0.4371 0.000 0.328 0.672
#> GSM1233006 2 0.0237 0.8805 0.000 0.996 0.004
#> GSM1233008 2 0.3192 0.8773 0.000 0.888 0.112
#> GSM1233009 2 0.2796 0.8835 0.000 0.908 0.092
#> GSM1233017 2 0.2625 0.8854 0.000 0.916 0.084
#> GSM1233020 2 0.3752 0.8566 0.000 0.856 0.144
#> GSM1233022 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233026 2 0.6081 0.4296 0.344 0.652 0.004
#> GSM1233028 2 0.2066 0.8459 0.060 0.940 0.000
#> GSM1233034 2 0.5178 0.7371 0.000 0.744 0.256
#> GSM1233040 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233048 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233056 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233058 2 0.4291 0.7171 0.180 0.820 0.000
#> GSM1233059 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233066 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233071 2 0.2537 0.8861 0.000 0.920 0.080
#> GSM1233074 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233076 2 0.6308 -0.0548 0.000 0.508 0.492
#> GSM1233080 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233088 3 0.3272 0.8400 0.016 0.080 0.904
#> GSM1233090 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233092 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233094 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233097 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233100 2 0.5968 0.3487 0.364 0.636 0.000
#> GSM1233104 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233106 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233111 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233122 2 0.3619 0.8624 0.000 0.864 0.136
#> GSM1233146 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1232994 2 0.2356 0.8871 0.000 0.928 0.072
#> GSM1232996 2 0.3192 0.8773 0.000 0.888 0.112
#> GSM1232997 3 0.0237 0.8981 0.000 0.004 0.996
#> GSM1232998 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1232999 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233000 2 0.2878 0.8825 0.000 0.904 0.096
#> GSM1233004 3 0.8322 0.0998 0.428 0.080 0.492
#> GSM1233011 3 0.5216 0.6703 0.000 0.260 0.740
#> GSM1233012 3 0.2448 0.8459 0.000 0.076 0.924
#> GSM1233023 3 0.0747 0.8922 0.000 0.016 0.984
#> GSM1233027 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233033 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233036 3 0.0237 0.8981 0.000 0.004 0.996
#> GSM1233037 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233041 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233045 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233047 1 0.6095 0.3387 0.608 0.000 0.392
#> GSM1233050 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233052 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233053 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233055 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233061 3 0.0237 0.8973 0.004 0.000 0.996
#> GSM1233063 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233065 3 0.0424 0.8967 0.000 0.008 0.992
#> GSM1233070 2 0.1289 0.8854 0.000 0.968 0.032
#> GSM1233077 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233081 1 0.4555 0.7330 0.800 0.000 0.200
#> GSM1233084 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233087 1 0.2796 0.8710 0.908 0.092 0.000
#> GSM1233089 2 0.5016 0.7568 0.000 0.760 0.240
#> GSM1233099 1 0.2356 0.8874 0.928 0.072 0.000
#> GSM1233112 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233085 1 0.5016 0.6726 0.760 0.000 0.240
#> GSM1233098 2 0.3816 0.8537 0.000 0.852 0.148
#> GSM1233114 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233119 1 0.5465 0.6394 0.712 0.288 0.000
#> GSM1233129 3 0.0237 0.8981 0.000 0.004 0.996
#> GSM1233132 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233139 2 0.3412 0.8717 0.000 0.876 0.124
#> GSM1233143 3 0.4654 0.6835 0.000 0.208 0.792
#> GSM1233145 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233067 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233069 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233072 2 0.3619 0.8624 0.000 0.864 0.136
#> GSM1233086 3 0.0892 0.8916 0.000 0.020 0.980
#> GSM1233102 1 0.2066 0.8955 0.940 0.060 0.000
#> GSM1233103 1 0.1031 0.9189 0.976 0.024 0.000
#> GSM1233107 1 0.7104 0.3787 0.608 0.360 0.032
#> GSM1233108 1 0.4452 0.7433 0.808 0.000 0.192
#> GSM1233109 3 0.6299 0.0946 0.476 0.000 0.524
#> GSM1233110 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233113 3 0.0424 0.8965 0.000 0.008 0.992
#> GSM1233116 3 0.0592 0.8945 0.000 0.012 0.988
#> GSM1233120 1 0.1163 0.9162 0.972 0.028 0.000
#> GSM1233121 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233123 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233124 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233125 1 0.4504 0.7380 0.804 0.000 0.196
#> GSM1233126 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233127 2 0.2625 0.8854 0.000 0.916 0.084
#> GSM1233128 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233130 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233131 1 0.0000 0.9324 1.000 0.000 0.000
#> GSM1233133 3 0.4974 0.6723 0.236 0.000 0.764
#> GSM1233134 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233135 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233136 3 0.0000 0.8991 0.000 0.000 1.000
#> GSM1233137 3 0.3752 0.7893 0.144 0.000 0.856
#> GSM1233138 2 0.0000 0.8796 0.000 1.000 0.000
#> GSM1233140 1 0.1860 0.8949 0.948 0.000 0.052
#> GSM1233141 2 0.4504 0.8048 0.000 0.804 0.196
#> GSM1233142 2 0.2878 0.8825 0.000 0.904 0.096
#> GSM1233144 3 0.3752 0.7893 0.144 0.000 0.856
#> GSM1233147 2 0.5948 0.4011 0.000 0.640 0.360
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.2149 0.7754 0.000 0.912 0.088 0.000
#> GSM1233002 4 0.3149 0.8078 0.032 0.088 0.000 0.880
#> GSM1233003 1 0.0188 0.9057 0.996 0.000 0.000 0.004
#> GSM1233014 4 0.3219 0.7800 0.000 0.164 0.000 0.836
#> GSM1233015 1 0.0524 0.9043 0.988 0.000 0.004 0.008
#> GSM1233016 4 0.3885 0.8053 0.064 0.092 0.000 0.844
#> GSM1233024 2 0.2530 0.7634 0.000 0.888 0.000 0.112
#> GSM1233049 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233064 2 0.4524 0.6521 0.000 0.768 0.204 0.028
#> GSM1233068 1 0.1617 0.8914 0.956 0.012 0.008 0.024
#> GSM1233073 4 0.2489 0.8093 0.068 0.020 0.000 0.912
#> GSM1233093 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233115 1 0.1637 0.8791 0.940 0.000 0.000 0.060
#> GSM1232992 2 0.0000 0.8156 0.000 1.000 0.000 0.000
#> GSM1232993 2 0.0707 0.8152 0.000 0.980 0.000 0.020
#> GSM1233005 2 0.0469 0.8158 0.000 0.988 0.012 0.000
#> GSM1233007 2 0.4426 0.6608 0.000 0.772 0.024 0.204
#> GSM1233010 4 0.1675 0.8068 0.044 0.004 0.004 0.948
#> GSM1233013 2 0.0000 0.8156 0.000 1.000 0.000 0.000
#> GSM1233018 2 0.0469 0.8158 0.000 0.988 0.012 0.000
#> GSM1233019 2 0.0921 0.8123 0.000 0.972 0.000 0.028
#> GSM1233021 2 0.0336 0.8159 0.000 0.992 0.008 0.000
#> GSM1233025 4 0.2408 0.7879 0.104 0.000 0.000 0.896
#> GSM1233029 2 0.0524 0.8156 0.000 0.988 0.004 0.008
#> GSM1233030 2 0.0336 0.8155 0.000 0.992 0.000 0.008
#> GSM1233031 4 0.1637 0.8131 0.000 0.060 0.000 0.940
#> GSM1233032 1 0.0188 0.9059 0.996 0.000 0.004 0.000
#> GSM1233035 1 0.5746 0.4312 0.612 0.040 0.000 0.348
#> GSM1233038 1 0.1716 0.8737 0.936 0.000 0.000 0.064
#> GSM1233039 2 0.5184 0.6361 0.000 0.736 0.204 0.060
#> GSM1233042 4 0.3801 0.7219 0.000 0.220 0.000 0.780
#> GSM1233043 4 0.3837 0.7188 0.000 0.224 0.000 0.776
#> GSM1233044 1 0.5339 0.7130 0.744 0.000 0.156 0.100
#> GSM1233046 1 0.3105 0.8125 0.856 0.004 0.000 0.140
#> GSM1233051 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233054 3 0.3852 0.6793 0.192 0.008 0.800 0.000
#> GSM1233057 3 0.4713 0.4340 0.000 0.360 0.640 0.000
#> GSM1233060 2 0.5404 -0.0551 0.012 0.512 0.000 0.476
#> GSM1233062 2 0.3486 0.6855 0.000 0.812 0.000 0.188
#> GSM1233075 3 0.3610 0.6890 0.000 0.200 0.800 0.000
#> GSM1233078 3 0.0376 0.8114 0.004 0.000 0.992 0.004
#> GSM1233079 1 0.0188 0.9059 0.996 0.000 0.004 0.000
#> GSM1233082 1 0.1211 0.8917 0.960 0.000 0.000 0.040
#> GSM1233083 1 0.0188 0.9057 0.996 0.000 0.000 0.004
#> GSM1233091 2 0.8817 -0.0435 0.064 0.392 0.360 0.184
#> GSM1233095 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233096 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233101 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233105 1 0.3764 0.7242 0.784 0.000 0.000 0.216
#> GSM1233117 2 0.1867 0.7862 0.000 0.928 0.072 0.000
#> GSM1233118 3 0.4999 0.0653 0.000 0.492 0.508 0.000
#> GSM1233001 2 0.2149 0.7745 0.000 0.912 0.088 0.000
#> GSM1233006 2 0.3764 0.6503 0.000 0.784 0.000 0.216
#> GSM1233008 2 0.0000 0.8156 0.000 1.000 0.000 0.000
#> GSM1233009 2 0.1389 0.8083 0.000 0.952 0.000 0.048
#> GSM1233017 2 0.1867 0.7915 0.000 0.928 0.000 0.072
#> GSM1233020 2 0.0469 0.8144 0.000 0.988 0.012 0.000
#> GSM1233022 4 0.4454 0.5995 0.000 0.308 0.000 0.692
#> GSM1233026 4 0.4304 0.7641 0.108 0.056 0.008 0.828
#> GSM1233028 4 0.1743 0.8146 0.000 0.056 0.004 0.940
#> GSM1233034 2 0.0592 0.8139 0.000 0.984 0.016 0.000
#> GSM1233040 1 0.0188 0.9059 0.996 0.000 0.004 0.000
#> GSM1233048 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233056 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233058 4 0.1139 0.8095 0.008 0.012 0.008 0.972
#> GSM1233059 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233066 3 0.0188 0.8130 0.000 0.004 0.996 0.000
#> GSM1233071 2 0.1557 0.8022 0.000 0.944 0.000 0.056
#> GSM1233074 3 0.4907 0.2942 0.000 0.420 0.580 0.000
#> GSM1233076 4 0.7398 0.2347 0.000 0.184 0.324 0.492
#> GSM1233080 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233088 3 0.6090 0.0979 0.012 0.452 0.512 0.024
#> GSM1233090 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233092 4 0.2589 0.8058 0.000 0.116 0.000 0.884
#> GSM1233094 4 0.3024 0.7919 0.000 0.148 0.000 0.852
#> GSM1233097 4 0.1109 0.8126 0.000 0.028 0.004 0.968
#> GSM1233100 4 0.3398 0.8116 0.068 0.060 0.000 0.872
#> GSM1233104 4 0.1389 0.8152 0.000 0.048 0.000 0.952
#> GSM1233106 1 0.0376 0.9055 0.992 0.000 0.004 0.004
#> GSM1233111 1 0.0188 0.9059 0.996 0.000 0.004 0.000
#> GSM1233122 2 0.0188 0.8154 0.000 0.996 0.004 0.000
#> GSM1233146 4 0.2704 0.8047 0.000 0.124 0.000 0.876
#> GSM1232994 2 0.2081 0.7840 0.000 0.916 0.000 0.084
#> GSM1232996 2 0.0469 0.8158 0.000 0.988 0.012 0.000
#> GSM1232997 2 0.4877 0.2503 0.000 0.592 0.408 0.000
#> GSM1232998 4 0.3710 0.7602 0.000 0.192 0.004 0.804
#> GSM1232999 2 0.5016 0.2236 0.000 0.600 0.004 0.396
#> GSM1233000 2 0.0469 0.8157 0.000 0.988 0.000 0.012
#> GSM1233004 3 0.6247 0.1592 0.056 0.000 0.516 0.428
#> GSM1233011 3 0.6391 0.3882 0.000 0.084 0.588 0.328
#> GSM1233012 2 0.4134 0.5718 0.000 0.740 0.260 0.000
#> GSM1233023 2 0.4018 0.6309 0.000 0.772 0.224 0.004
#> GSM1233027 2 0.4343 0.5530 0.000 0.732 0.004 0.264
#> GSM1233033 1 0.0336 0.9042 0.992 0.000 0.000 0.008
#> GSM1233036 3 0.3791 0.6935 0.000 0.200 0.796 0.004
#> GSM1233037 2 0.5732 0.3414 0.028 0.604 0.364 0.004
#> GSM1233041 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233045 4 0.3668 0.7150 0.000 0.188 0.004 0.808
#> GSM1233047 1 0.4888 0.3639 0.588 0.000 0.412 0.000
#> GSM1233050 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233052 1 0.1716 0.8785 0.936 0.000 0.000 0.064
#> GSM1233053 1 0.0336 0.9045 0.992 0.000 0.008 0.000
#> GSM1233055 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233061 3 0.0376 0.8125 0.004 0.004 0.992 0.000
#> GSM1233063 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233065 2 0.5167 -0.0373 0.000 0.508 0.488 0.004
#> GSM1233070 2 0.2805 0.7715 0.000 0.888 0.012 0.100
#> GSM1233077 3 0.0927 0.8110 0.000 0.008 0.976 0.016
#> GSM1233081 1 0.4889 0.4832 0.636 0.000 0.360 0.004
#> GSM1233084 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233087 4 0.2149 0.7919 0.088 0.000 0.000 0.912
#> GSM1233089 2 0.1389 0.8016 0.000 0.952 0.048 0.000
#> GSM1233099 4 0.4304 0.5356 0.284 0.000 0.000 0.716
#> GSM1233112 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233085 1 0.5097 0.3231 0.568 0.000 0.428 0.004
#> GSM1233098 2 0.1004 0.8123 0.000 0.972 0.024 0.004
#> GSM1233114 1 0.2704 0.8331 0.876 0.000 0.000 0.124
#> GSM1233119 4 0.0188 0.8058 0.004 0.000 0.000 0.996
#> GSM1233129 3 0.4817 0.3809 0.000 0.388 0.612 0.000
#> GSM1233132 1 0.3266 0.7933 0.832 0.000 0.000 0.168
#> GSM1233139 2 0.1284 0.8141 0.000 0.964 0.012 0.024
#> GSM1233143 2 0.4814 0.4602 0.000 0.676 0.316 0.008
#> GSM1233145 1 0.2760 0.8266 0.872 0.000 0.000 0.128
#> GSM1233067 3 0.2973 0.7436 0.000 0.144 0.856 0.000
#> GSM1233069 3 0.0804 0.8132 0.000 0.012 0.980 0.008
#> GSM1233072 2 0.0188 0.8154 0.000 0.996 0.004 0.000
#> GSM1233086 3 0.3088 0.7839 0.000 0.060 0.888 0.052
#> GSM1233102 4 0.3873 0.6528 0.228 0.000 0.000 0.772
#> GSM1233103 1 0.5047 0.5696 0.668 0.016 0.000 0.316
#> GSM1233107 4 0.7271 0.4526 0.216 0.244 0.000 0.540
#> GSM1233108 1 0.4699 0.5593 0.676 0.000 0.320 0.004
#> GSM1233109 3 0.4137 0.6332 0.208 0.000 0.780 0.012
#> GSM1233110 3 0.0376 0.8124 0.000 0.004 0.992 0.004
#> GSM1233113 2 0.4790 0.3254 0.000 0.620 0.380 0.000
#> GSM1233116 3 0.4331 0.5744 0.000 0.288 0.712 0.000
#> GSM1233120 4 0.5000 -0.0705 0.496 0.000 0.000 0.504
#> GSM1233121 3 0.0804 0.8120 0.000 0.008 0.980 0.012
#> GSM1233123 3 0.0188 0.8127 0.000 0.004 0.996 0.000
#> GSM1233124 3 0.0336 0.8133 0.000 0.008 0.992 0.000
#> GSM1233125 1 0.4522 0.5652 0.680 0.000 0.320 0.000
#> GSM1233126 4 0.2704 0.8008 0.000 0.124 0.000 0.876
#> GSM1233127 2 0.4843 0.3362 0.000 0.604 0.000 0.396
#> GSM1233128 1 0.0000 0.9068 1.000 0.000 0.000 0.000
#> GSM1233130 3 0.0927 0.8118 0.000 0.008 0.976 0.016
#> GSM1233131 1 0.3311 0.7902 0.828 0.000 0.000 0.172
#> GSM1233133 3 0.2888 0.7333 0.124 0.000 0.872 0.004
#> GSM1233134 3 0.0469 0.8133 0.000 0.012 0.988 0.000
#> GSM1233135 3 0.0336 0.8133 0.000 0.008 0.992 0.000
#> GSM1233136 3 0.0927 0.8110 0.000 0.008 0.976 0.016
#> GSM1233137 3 0.1716 0.7828 0.064 0.000 0.936 0.000
#> GSM1233138 4 0.2760 0.7992 0.000 0.128 0.000 0.872
#> GSM1233140 1 0.0707 0.8996 0.980 0.000 0.020 0.000
#> GSM1233141 2 0.4567 0.5885 0.000 0.716 0.008 0.276
#> GSM1233142 2 0.4103 0.6209 0.000 0.744 0.000 0.256
#> GSM1233144 3 0.2053 0.7762 0.072 0.000 0.924 0.004
#> GSM1233147 4 0.7165 0.2405 0.000 0.144 0.356 0.500
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.2208 0.7406 0.000 0.908 0.072 0.000 0.020
#> GSM1233002 4 0.5442 0.1683 0.020 0.036 0.000 0.592 0.352
#> GSM1233003 1 0.2124 0.8290 0.916 0.000 0.000 0.056 0.028
#> GSM1233014 4 0.2067 0.5155 0.000 0.048 0.000 0.920 0.032
#> GSM1233015 1 0.3544 0.7521 0.788 0.008 0.000 0.004 0.200
#> GSM1233016 4 0.2635 0.4877 0.016 0.008 0.000 0.888 0.088
#> GSM1233024 2 0.4998 0.6236 0.000 0.700 0.000 0.196 0.104
#> GSM1233049 1 0.0000 0.8524 1.000 0.000 0.000 0.000 0.000
#> GSM1233064 2 0.5294 0.6158 0.000 0.712 0.164 0.020 0.104
#> GSM1233068 1 0.2976 0.8007 0.852 0.012 0.000 0.004 0.132
#> GSM1233073 4 0.3210 0.4793 0.012 0.012 0.000 0.844 0.132
#> GSM1233093 1 0.0000 0.8524 1.000 0.000 0.000 0.000 0.000
#> GSM1233115 1 0.2970 0.7714 0.828 0.000 0.004 0.000 0.168
#> GSM1232992 2 0.1117 0.7482 0.000 0.964 0.000 0.016 0.020
#> GSM1232993 2 0.3992 0.7006 0.000 0.796 0.000 0.124 0.080
#> GSM1233005 2 0.2291 0.7455 0.000 0.908 0.000 0.036 0.056
#> GSM1233007 2 0.5857 0.4459 0.000 0.620 0.020 0.272 0.088
#> GSM1233010 5 0.4398 0.4922 0.008 0.008 0.000 0.312 0.672
#> GSM1233013 2 0.0807 0.7495 0.000 0.976 0.000 0.012 0.012
#> GSM1233018 2 0.1364 0.7502 0.000 0.952 0.000 0.012 0.036
#> GSM1233019 2 0.3595 0.7023 0.000 0.816 0.000 0.140 0.044
#> GSM1233021 2 0.2054 0.7473 0.000 0.920 0.000 0.028 0.052
#> GSM1233025 4 0.4832 0.3051 0.104 0.000 0.000 0.720 0.176
#> GSM1233029 2 0.3359 0.7341 0.000 0.840 0.000 0.052 0.108
#> GSM1233030 2 0.2209 0.7420 0.000 0.912 0.000 0.056 0.032
#> GSM1233031 5 0.4527 0.4127 0.000 0.036 0.000 0.272 0.692
#> GSM1233032 1 0.1412 0.8471 0.952 0.000 0.008 0.004 0.036
#> GSM1233035 4 0.7269 0.0216 0.196 0.036 0.000 0.424 0.344
#> GSM1233038 1 0.2291 0.8241 0.908 0.000 0.000 0.056 0.036
#> GSM1233039 2 0.6633 0.5224 0.000 0.616 0.104 0.092 0.188
#> GSM1233042 4 0.3410 0.5106 0.000 0.068 0.000 0.840 0.092
#> GSM1233043 4 0.3464 0.5092 0.000 0.068 0.000 0.836 0.096
#> GSM1233044 1 0.6905 0.4945 0.592 0.000 0.180 0.096 0.132
#> GSM1233046 1 0.6479 0.3580 0.540 0.008 0.000 0.240 0.212
#> GSM1233051 1 0.0794 0.8531 0.972 0.000 0.000 0.000 0.028
#> GSM1233054 3 0.6151 0.5362 0.200 0.036 0.648 0.004 0.112
#> GSM1233057 3 0.5958 0.0348 0.000 0.436 0.468 0.004 0.092
#> GSM1233060 4 0.6710 0.1408 0.000 0.264 0.000 0.420 0.316
#> GSM1233062 2 0.5580 0.5444 0.000 0.632 0.000 0.236 0.132
#> GSM1233075 3 0.4949 0.4950 0.000 0.296 0.656 0.004 0.044
#> GSM1233078 3 0.0963 0.7920 0.000 0.000 0.964 0.000 0.036
#> GSM1233079 1 0.0703 0.8503 0.976 0.000 0.000 0.000 0.024
#> GSM1233082 1 0.3300 0.7567 0.792 0.000 0.000 0.004 0.204
#> GSM1233083 1 0.1648 0.8394 0.940 0.000 0.000 0.040 0.020
#> GSM1233091 5 0.7879 0.1785 0.104 0.272 0.076 0.044 0.504
#> GSM1233095 1 0.0162 0.8524 0.996 0.000 0.000 0.000 0.004
#> GSM1233096 1 0.1831 0.8376 0.920 0.000 0.000 0.004 0.076
#> GSM1233101 1 0.0000 0.8524 1.000 0.000 0.000 0.000 0.000
#> GSM1233105 1 0.6020 0.3302 0.536 0.004 0.000 0.348 0.112
#> GSM1233117 2 0.3763 0.7451 0.000 0.840 0.080 0.044 0.036
#> GSM1233118 2 0.5185 0.3036 0.000 0.580 0.376 0.004 0.040
#> GSM1233001 2 0.2313 0.7392 0.000 0.912 0.044 0.004 0.040
#> GSM1233006 4 0.4942 0.0380 0.000 0.432 0.000 0.540 0.028
#> GSM1233008 2 0.1836 0.7548 0.000 0.936 0.008 0.016 0.040
#> GSM1233009 2 0.4648 0.6757 0.000 0.740 0.000 0.104 0.156
#> GSM1233017 2 0.4521 0.6599 0.000 0.748 0.000 0.164 0.088
#> GSM1233020 2 0.0960 0.7492 0.000 0.972 0.004 0.008 0.016
#> GSM1233022 4 0.4944 0.3530 0.000 0.208 0.000 0.700 0.092
#> GSM1233026 5 0.5127 0.4803 0.012 0.044 0.004 0.260 0.680
#> GSM1233028 5 0.4297 0.4917 0.000 0.020 0.000 0.288 0.692
#> GSM1233034 2 0.1518 0.7499 0.000 0.944 0.004 0.004 0.048
#> GSM1233040 1 0.1357 0.8477 0.948 0.000 0.000 0.004 0.048
#> GSM1233048 1 0.0451 0.8523 0.988 0.000 0.000 0.004 0.008
#> GSM1233056 1 0.0162 0.8525 0.996 0.000 0.000 0.000 0.004
#> GSM1233058 5 0.4298 0.4506 0.000 0.008 0.000 0.352 0.640
#> GSM1233059 1 0.0162 0.8524 0.996 0.000 0.000 0.000 0.004
#> GSM1233066 3 0.0566 0.7970 0.000 0.004 0.984 0.000 0.012
#> GSM1233071 2 0.5405 0.5812 0.000 0.660 0.000 0.204 0.136
#> GSM1233074 2 0.5365 0.1169 0.000 0.512 0.440 0.004 0.044
#> GSM1233076 4 0.8029 0.0542 0.000 0.140 0.236 0.436 0.188
#> GSM1233080 1 0.0000 0.8524 1.000 0.000 0.000 0.000 0.000
#> GSM1233088 3 0.7838 0.0949 0.040 0.356 0.372 0.016 0.216
#> GSM1233090 1 0.0162 0.8524 0.996 0.000 0.000 0.000 0.004
#> GSM1233092 4 0.1582 0.5177 0.000 0.028 0.000 0.944 0.028
#> GSM1233094 4 0.2754 0.5136 0.000 0.040 0.000 0.880 0.080
#> GSM1233097 5 0.4723 0.2995 0.000 0.016 0.000 0.448 0.536
#> GSM1233100 4 0.5461 0.3046 0.048 0.028 0.000 0.652 0.272
#> GSM1233104 4 0.4876 -0.0722 0.000 0.028 0.000 0.576 0.396
#> GSM1233106 1 0.2286 0.8250 0.888 0.000 0.000 0.004 0.108
#> GSM1233111 1 0.1638 0.8439 0.932 0.000 0.000 0.004 0.064
#> GSM1233122 2 0.1041 0.7499 0.000 0.964 0.000 0.032 0.004
#> GSM1233146 4 0.3731 0.4474 0.000 0.040 0.000 0.800 0.160
#> GSM1232994 2 0.4609 0.6578 0.000 0.744 0.000 0.152 0.104
#> GSM1232996 2 0.2032 0.7507 0.000 0.924 0.004 0.020 0.052
#> GSM1232997 2 0.4585 0.5841 0.000 0.728 0.216 0.004 0.052
#> GSM1232998 4 0.5008 0.3610 0.000 0.152 0.000 0.708 0.140
#> GSM1232999 2 0.6047 0.2674 0.000 0.532 0.000 0.332 0.136
#> GSM1233000 2 0.2708 0.7403 0.000 0.884 0.000 0.044 0.072
#> GSM1233004 5 0.7580 0.1559 0.048 0.004 0.368 0.192 0.388
#> GSM1233011 3 0.8024 0.2330 0.000 0.164 0.448 0.180 0.208
#> GSM1233012 2 0.4589 0.6831 0.000 0.764 0.160 0.020 0.056
#> GSM1233023 2 0.3916 0.6697 0.000 0.804 0.136 0.004 0.056
#> GSM1233027 2 0.5304 0.4837 0.000 0.628 0.000 0.292 0.080
#> GSM1233033 1 0.1701 0.8409 0.936 0.000 0.000 0.016 0.048
#> GSM1233036 3 0.5204 0.5727 0.000 0.228 0.684 0.008 0.080
#> GSM1233037 2 0.6631 0.3870 0.016 0.548 0.268 0.004 0.164
#> GSM1233041 1 0.0404 0.8517 0.988 0.000 0.000 0.000 0.012
#> GSM1233045 5 0.4748 0.4565 0.000 0.040 0.000 0.300 0.660
#> GSM1233047 1 0.4890 0.5009 0.628 0.000 0.332 0.000 0.040
#> GSM1233050 1 0.0451 0.8522 0.988 0.000 0.000 0.004 0.008
#> GSM1233052 1 0.3910 0.6634 0.720 0.000 0.000 0.008 0.272
#> GSM1233053 1 0.1934 0.8411 0.928 0.000 0.016 0.004 0.052
#> GSM1233055 1 0.0000 0.8524 1.000 0.000 0.000 0.000 0.000
#> GSM1233061 3 0.0992 0.7950 0.000 0.008 0.968 0.000 0.024
#> GSM1233063 1 0.0510 0.8519 0.984 0.000 0.000 0.000 0.016
#> GSM1233065 2 0.5503 0.4645 0.000 0.632 0.272 0.004 0.092
#> GSM1233070 2 0.4834 0.5790 0.000 0.692 0.004 0.252 0.052
#> GSM1233077 3 0.1787 0.7899 0.000 0.016 0.936 0.004 0.044
#> GSM1233081 1 0.4473 0.5445 0.656 0.000 0.324 0.000 0.020
#> GSM1233084 1 0.0000 0.8524 1.000 0.000 0.000 0.000 0.000
#> GSM1233087 4 0.5470 0.1102 0.092 0.000 0.000 0.612 0.296
#> GSM1233089 2 0.2581 0.7449 0.000 0.904 0.020 0.048 0.028
#> GSM1233099 5 0.5917 0.3326 0.132 0.000 0.000 0.304 0.564
#> GSM1233112 1 0.1195 0.8463 0.960 0.000 0.000 0.028 0.012
#> GSM1233085 1 0.4898 0.4231 0.592 0.000 0.376 0.000 0.032
#> GSM1233098 2 0.2713 0.7376 0.000 0.888 0.004 0.072 0.036
#> GSM1233114 1 0.4527 0.6189 0.692 0.000 0.000 0.036 0.272
#> GSM1233119 5 0.4555 0.2749 0.008 0.000 0.000 0.472 0.520
#> GSM1233129 2 0.5238 0.1319 0.000 0.520 0.440 0.004 0.036
#> GSM1233132 1 0.4907 0.5618 0.656 0.000 0.000 0.052 0.292
#> GSM1233139 2 0.3595 0.7241 0.000 0.816 0.000 0.044 0.140
#> GSM1233143 2 0.6855 0.4672 0.000 0.548 0.284 0.084 0.084
#> GSM1233145 1 0.4548 0.6870 0.748 0.000 0.000 0.156 0.096
#> GSM1233067 3 0.3538 0.6902 0.000 0.176 0.804 0.004 0.016
#> GSM1233069 3 0.1646 0.7925 0.000 0.020 0.944 0.004 0.032
#> GSM1233072 2 0.2312 0.7527 0.000 0.912 0.012 0.060 0.016
#> GSM1233086 3 0.5005 0.6646 0.000 0.072 0.740 0.028 0.160
#> GSM1233102 4 0.5435 0.2394 0.152 0.000 0.000 0.660 0.188
#> GSM1233103 5 0.5821 0.2336 0.276 0.008 0.000 0.108 0.608
#> GSM1233107 5 0.6833 0.1421 0.044 0.120 0.000 0.324 0.512
#> GSM1233108 1 0.4227 0.5987 0.692 0.000 0.292 0.000 0.016
#> GSM1233109 3 0.4400 0.5741 0.212 0.000 0.736 0.000 0.052
#> GSM1233110 3 0.0162 0.7950 0.000 0.000 0.996 0.000 0.004
#> GSM1233113 2 0.4552 0.5684 0.000 0.716 0.240 0.004 0.040
#> GSM1233116 3 0.4706 0.4221 0.000 0.344 0.632 0.004 0.020
#> GSM1233120 4 0.6821 -0.1392 0.324 0.000 0.000 0.352 0.324
#> GSM1233121 3 0.1787 0.7899 0.000 0.016 0.936 0.004 0.044
#> GSM1233123 3 0.0290 0.7951 0.000 0.000 0.992 0.000 0.008
#> GSM1233124 3 0.1012 0.7942 0.000 0.012 0.968 0.000 0.020
#> GSM1233125 1 0.4360 0.6140 0.692 0.000 0.284 0.000 0.024
#> GSM1233126 4 0.1740 0.5063 0.000 0.012 0.000 0.932 0.056
#> GSM1233127 2 0.6553 0.1460 0.000 0.432 0.000 0.204 0.364
#> GSM1233128 1 0.0404 0.8517 0.988 0.000 0.000 0.000 0.012
#> GSM1233130 3 0.1443 0.7904 0.000 0.004 0.948 0.004 0.044
#> GSM1233131 1 0.5185 0.4186 0.568 0.000 0.000 0.048 0.384
#> GSM1233133 3 0.2390 0.7385 0.084 0.000 0.896 0.000 0.020
#> GSM1233134 3 0.1106 0.7934 0.000 0.012 0.964 0.000 0.024
#> GSM1233135 3 0.0854 0.7967 0.000 0.012 0.976 0.004 0.008
#> GSM1233136 3 0.2467 0.7817 0.000 0.024 0.908 0.016 0.052
#> GSM1233137 3 0.2139 0.7653 0.052 0.000 0.916 0.000 0.032
#> GSM1233138 4 0.1522 0.5113 0.000 0.012 0.000 0.944 0.044
#> GSM1233140 1 0.1597 0.8486 0.940 0.000 0.012 0.000 0.048
#> GSM1233141 2 0.6244 0.4286 0.004 0.556 0.008 0.120 0.312
#> GSM1233142 2 0.5769 0.4205 0.000 0.556 0.000 0.104 0.340
#> GSM1233144 3 0.1943 0.7636 0.056 0.000 0.924 0.000 0.020
#> GSM1233147 4 0.7321 0.1230 0.000 0.100 0.284 0.504 0.112
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.2555 0.62697 0.000 0.888 0.064 0.016 0.000 0.032
#> GSM1233002 5 0.6308 0.14773 0.032 0.040 0.000 0.404 0.464 0.060
#> GSM1233003 1 0.3498 0.70714 0.828 0.000 0.000 0.056 0.024 0.092
#> GSM1233014 4 0.2220 0.61144 0.000 0.036 0.000 0.908 0.044 0.012
#> GSM1233015 1 0.5583 0.31675 0.480 0.000 0.004 0.000 0.124 0.392
#> GSM1233016 4 0.3436 0.56216 0.016 0.008 0.000 0.828 0.028 0.120
#> GSM1233024 2 0.6121 0.42105 0.000 0.520 0.000 0.268 0.024 0.188
#> GSM1233049 1 0.0405 0.73645 0.988 0.000 0.000 0.000 0.004 0.008
#> GSM1233064 2 0.5376 0.51172 0.000 0.720 0.084 0.036 0.060 0.100
#> GSM1233068 1 0.5517 0.49344 0.580 0.004 0.000 0.000 0.184 0.232
#> GSM1233073 4 0.4964 0.47430 0.060 0.004 0.000 0.724 0.140 0.072
#> GSM1233093 1 0.0146 0.73667 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM1233115 1 0.3884 0.58545 0.724 0.000 0.000 0.000 0.240 0.036
#> GSM1232992 2 0.2408 0.64190 0.000 0.892 0.000 0.052 0.004 0.052
#> GSM1232993 2 0.5218 0.54038 0.000 0.648 0.000 0.212 0.016 0.124
#> GSM1233005 2 0.2961 0.64010 0.000 0.868 0.000 0.052 0.052 0.028
#> GSM1233007 2 0.6427 0.17694 0.000 0.500 0.016 0.344 0.076 0.064
#> GSM1233010 5 0.2653 0.61627 0.004 0.000 0.000 0.056 0.876 0.064
#> GSM1233013 2 0.2066 0.64104 0.000 0.908 0.000 0.040 0.000 0.052
#> GSM1233018 2 0.1666 0.64190 0.000 0.936 0.000 0.020 0.036 0.008
#> GSM1233019 2 0.4732 0.57988 0.000 0.700 0.000 0.164 0.008 0.128
#> GSM1233021 2 0.3203 0.63641 0.000 0.852 0.000 0.056 0.064 0.028
#> GSM1233025 4 0.6645 0.20124 0.096 0.000 0.000 0.528 0.188 0.188
#> GSM1233029 2 0.4968 0.59444 0.000 0.724 0.000 0.088 0.080 0.108
#> GSM1233030 2 0.3517 0.62331 0.000 0.812 0.000 0.092 0.004 0.092
#> GSM1233031 5 0.5542 0.35398 0.004 0.008 0.000 0.124 0.580 0.284
#> GSM1233032 1 0.3601 0.69480 0.792 0.000 0.008 0.000 0.040 0.160
#> GSM1233035 6 0.5895 0.21564 0.064 0.020 0.000 0.328 0.032 0.556
#> GSM1233038 1 0.3470 0.69659 0.828 0.000 0.000 0.048 0.024 0.100
#> GSM1233039 2 0.7091 0.31987 0.000 0.556 0.056 0.088 0.144 0.156
#> GSM1233042 4 0.3453 0.58905 0.000 0.024 0.000 0.828 0.104 0.044
#> GSM1233043 4 0.3483 0.58949 0.000 0.028 0.000 0.828 0.100 0.044
#> GSM1233044 1 0.7367 0.37105 0.532 0.000 0.168 0.072 0.116 0.112
#> GSM1233046 6 0.6398 0.27910 0.240 0.004 0.004 0.212 0.024 0.516
#> GSM1233051 1 0.2504 0.73804 0.880 0.000 0.000 0.004 0.028 0.088
#> GSM1233054 3 0.7045 0.15732 0.164 0.036 0.440 0.000 0.036 0.324
#> GSM1233057 2 0.6801 0.00653 0.004 0.388 0.348 0.000 0.040 0.220
#> GSM1233060 4 0.6676 0.03494 0.000 0.132 0.000 0.412 0.076 0.380
#> GSM1233062 2 0.6695 0.31985 0.000 0.448 0.000 0.292 0.052 0.208
#> GSM1233075 3 0.5299 0.24984 0.000 0.372 0.540 0.000 0.012 0.076
#> GSM1233078 3 0.1801 0.74151 0.004 0.000 0.924 0.000 0.016 0.056
#> GSM1233079 1 0.2311 0.72642 0.880 0.000 0.000 0.000 0.016 0.104
#> GSM1233082 1 0.5388 0.52799 0.584 0.000 0.000 0.000 0.228 0.188
#> GSM1233083 1 0.3011 0.70357 0.852 0.000 0.000 0.036 0.012 0.100
#> GSM1233091 5 0.6175 0.31651 0.036 0.152 0.036 0.000 0.624 0.152
#> GSM1233095 1 0.0146 0.73629 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1233096 1 0.4339 0.62238 0.684 0.000 0.000 0.000 0.060 0.256
#> GSM1233101 1 0.0520 0.73760 0.984 0.000 0.000 0.000 0.008 0.008
#> GSM1233105 1 0.6653 0.22074 0.448 0.000 0.000 0.272 0.044 0.236
#> GSM1233117 2 0.3928 0.62653 0.000 0.808 0.088 0.064 0.004 0.036
#> GSM1233118 2 0.4634 0.42252 0.000 0.640 0.300 0.000 0.004 0.056
#> GSM1233001 2 0.2015 0.62275 0.000 0.916 0.016 0.000 0.012 0.056
#> GSM1233006 4 0.3934 0.43713 0.000 0.260 0.000 0.708 0.000 0.032
#> GSM1233008 2 0.2867 0.64584 0.000 0.868 0.000 0.040 0.016 0.076
#> GSM1233009 2 0.5767 0.48179 0.000 0.584 0.000 0.124 0.032 0.260
#> GSM1233017 2 0.5868 0.45113 0.000 0.556 0.000 0.228 0.016 0.200
#> GSM1233020 2 0.0665 0.63579 0.000 0.980 0.000 0.008 0.004 0.008
#> GSM1233022 4 0.4618 0.42935 0.000 0.124 0.000 0.720 0.012 0.144
#> GSM1233026 5 0.3239 0.59894 0.004 0.012 0.000 0.064 0.848 0.072
#> GSM1233028 5 0.3252 0.59481 0.000 0.008 0.000 0.048 0.832 0.112
#> GSM1233034 2 0.1956 0.63100 0.000 0.908 0.000 0.004 0.008 0.080
#> GSM1233040 1 0.3683 0.68692 0.768 0.000 0.000 0.000 0.048 0.184
#> GSM1233048 1 0.1806 0.73132 0.908 0.000 0.000 0.000 0.004 0.088
#> GSM1233056 1 0.1477 0.73073 0.940 0.000 0.000 0.004 0.008 0.048
#> GSM1233058 5 0.2467 0.64195 0.004 0.008 0.000 0.100 0.880 0.008
#> GSM1233059 1 0.1219 0.73740 0.948 0.000 0.000 0.000 0.004 0.048
#> GSM1233066 3 0.1680 0.74610 0.000 0.004 0.936 0.004 0.016 0.040
#> GSM1233071 2 0.6594 0.14224 0.000 0.360 0.000 0.288 0.024 0.328
#> GSM1233074 2 0.5127 0.31892 0.000 0.580 0.340 0.000 0.012 0.068
#> GSM1233076 4 0.8215 0.10828 0.000 0.136 0.128 0.400 0.236 0.100
#> GSM1233080 1 0.0000 0.73653 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233088 6 0.8011 0.17777 0.032 0.260 0.220 0.008 0.104 0.376
#> GSM1233090 1 0.0632 0.73720 0.976 0.000 0.000 0.000 0.000 0.024
#> GSM1233092 4 0.2015 0.60723 0.000 0.016 0.000 0.916 0.056 0.012
#> GSM1233094 4 0.2706 0.60749 0.000 0.028 0.000 0.880 0.068 0.024
#> GSM1233097 5 0.3376 0.58937 0.000 0.000 0.000 0.220 0.764 0.016
#> GSM1233100 4 0.6303 0.09883 0.056 0.000 0.000 0.496 0.328 0.120
#> GSM1233104 5 0.4467 0.17781 0.000 0.000 0.000 0.464 0.508 0.028
#> GSM1233106 1 0.4687 0.56694 0.632 0.000 0.000 0.000 0.072 0.296
#> GSM1233111 1 0.4059 0.65629 0.720 0.000 0.000 0.000 0.052 0.228
#> GSM1233122 2 0.2179 0.64305 0.000 0.900 0.000 0.064 0.000 0.036
#> GSM1233146 4 0.4708 0.51849 0.000 0.032 0.000 0.716 0.184 0.068
#> GSM1232994 2 0.5659 0.51693 0.000 0.620 0.000 0.160 0.032 0.188
#> GSM1232996 2 0.2036 0.64033 0.000 0.916 0.000 0.008 0.048 0.028
#> GSM1232997 2 0.4761 0.48521 0.000 0.688 0.212 0.000 0.012 0.088
#> GSM1232998 4 0.5337 0.40636 0.000 0.140 0.000 0.644 0.196 0.020
#> GSM1232999 2 0.6475 0.19563 0.000 0.468 0.000 0.288 0.208 0.036
#> GSM1233000 2 0.4438 0.59715 0.000 0.744 0.000 0.076 0.024 0.156
#> GSM1233004 5 0.6185 0.40585 0.052 0.004 0.216 0.048 0.624 0.056
#> GSM1233011 3 0.8061 0.07512 0.000 0.196 0.372 0.104 0.268 0.060
#> GSM1233012 2 0.4702 0.56907 0.000 0.732 0.156 0.028 0.004 0.080
#> GSM1233023 2 0.3516 0.58064 0.000 0.824 0.088 0.004 0.008 0.076
#> GSM1233027 2 0.6033 0.25418 0.000 0.496 0.000 0.364 0.092 0.048
#> GSM1233033 1 0.3590 0.71358 0.800 0.000 0.000 0.020 0.028 0.152
#> GSM1233036 3 0.5695 0.47770 0.000 0.220 0.620 0.000 0.048 0.112
#> GSM1233037 6 0.7317 0.05329 0.052 0.364 0.160 0.000 0.040 0.384
#> GSM1233041 1 0.1616 0.73812 0.932 0.000 0.000 0.000 0.020 0.048
#> GSM1233045 5 0.2986 0.63231 0.000 0.032 0.000 0.104 0.852 0.012
#> GSM1233047 1 0.6290 0.15395 0.440 0.000 0.356 0.000 0.024 0.180
#> GSM1233050 1 0.1204 0.73547 0.944 0.000 0.000 0.000 0.000 0.056
#> GSM1233052 1 0.5520 0.34985 0.532 0.000 0.000 0.000 0.312 0.156
#> GSM1233053 1 0.4158 0.64545 0.740 0.000 0.036 0.000 0.020 0.204
#> GSM1233055 1 0.1563 0.72992 0.932 0.000 0.000 0.000 0.012 0.056
#> GSM1233061 3 0.2301 0.72790 0.000 0.000 0.884 0.000 0.020 0.096
#> GSM1233063 1 0.2882 0.73030 0.848 0.000 0.000 0.004 0.028 0.120
#> GSM1233065 2 0.5082 0.47582 0.000 0.668 0.224 0.000 0.032 0.076
#> GSM1233070 2 0.5623 0.30655 0.000 0.540 0.000 0.356 0.048 0.056
#> GSM1233077 3 0.2965 0.72170 0.000 0.036 0.864 0.000 0.024 0.076
#> GSM1233081 1 0.5389 0.32603 0.548 0.000 0.356 0.000 0.016 0.080
#> GSM1233084 1 0.1138 0.73864 0.960 0.000 0.000 0.004 0.012 0.024
#> GSM1233087 5 0.7019 0.13437 0.172 0.000 0.000 0.356 0.380 0.092
#> GSM1233089 2 0.3441 0.61191 0.000 0.844 0.040 0.076 0.008 0.032
#> GSM1233099 5 0.6382 0.39946 0.132 0.000 0.000 0.124 0.576 0.168
#> GSM1233112 1 0.2790 0.70838 0.868 0.000 0.000 0.032 0.012 0.088
#> GSM1233085 3 0.5967 -0.06345 0.408 0.000 0.436 0.000 0.016 0.140
#> GSM1233098 2 0.3291 0.61328 0.000 0.832 0.016 0.124 0.004 0.024
#> GSM1233114 1 0.6030 0.46927 0.556 0.000 0.000 0.032 0.168 0.244
#> GSM1233119 5 0.5050 0.51487 0.004 0.000 0.000 0.260 0.628 0.108
#> GSM1233129 2 0.5091 0.26664 0.000 0.564 0.360 0.000 0.008 0.068
#> GSM1233132 1 0.6051 0.41167 0.556 0.000 0.000 0.032 0.180 0.232
#> GSM1233139 2 0.5152 0.51423 0.000 0.632 0.000 0.080 0.020 0.268
#> GSM1233143 2 0.7043 0.28992 0.000 0.456 0.284 0.112 0.004 0.144
#> GSM1233145 1 0.4276 0.64387 0.760 0.000 0.000 0.084 0.020 0.136
#> GSM1233067 3 0.3569 0.63362 0.000 0.164 0.792 0.000 0.008 0.036
#> GSM1233069 3 0.2613 0.72892 0.000 0.032 0.884 0.000 0.016 0.068
#> GSM1233072 2 0.3618 0.63838 0.000 0.820 0.024 0.112 0.004 0.040
#> GSM1233086 3 0.5580 0.56581 0.000 0.072 0.660 0.016 0.204 0.048
#> GSM1233102 4 0.6845 0.15487 0.232 0.000 0.000 0.496 0.116 0.156
#> GSM1233103 6 0.6282 0.11371 0.092 0.008 0.004 0.044 0.336 0.516
#> GSM1233107 6 0.6807 0.14876 0.016 0.044 0.000 0.224 0.220 0.496
#> GSM1233108 1 0.5036 0.44145 0.612 0.000 0.300 0.000 0.008 0.080
#> GSM1233109 3 0.5245 0.47304 0.232 0.000 0.648 0.000 0.028 0.092
#> GSM1233110 3 0.0632 0.74489 0.000 0.000 0.976 0.000 0.000 0.024
#> GSM1233113 2 0.4203 0.50784 0.000 0.720 0.220 0.000 0.004 0.056
#> GSM1233116 3 0.4658 0.32459 0.000 0.360 0.596 0.000 0.008 0.036
#> GSM1233120 1 0.7400 -0.04544 0.392 0.000 0.000 0.192 0.256 0.160
#> GSM1233121 3 0.2838 0.72728 0.000 0.032 0.872 0.000 0.024 0.072
#> GSM1233123 3 0.1010 0.74536 0.000 0.000 0.960 0.000 0.004 0.036
#> GSM1233124 3 0.1679 0.74330 0.000 0.016 0.936 0.000 0.012 0.036
#> GSM1233125 1 0.5269 0.44320 0.596 0.000 0.312 0.000 0.024 0.068
#> GSM1233126 4 0.1719 0.59981 0.000 0.008 0.000 0.928 0.008 0.056
#> GSM1233127 2 0.7753 -0.03369 0.000 0.336 0.008 0.176 0.200 0.280
#> GSM1233128 1 0.2666 0.72398 0.872 0.000 0.000 0.008 0.028 0.092
#> GSM1233130 3 0.2488 0.73174 0.000 0.016 0.888 0.000 0.020 0.076
#> GSM1233131 1 0.6441 0.19346 0.412 0.000 0.000 0.020 0.320 0.248
#> GSM1233133 3 0.3095 0.69640 0.052 0.000 0.856 0.000 0.020 0.072
#> GSM1233134 3 0.1726 0.73885 0.000 0.012 0.932 0.000 0.012 0.044
#> GSM1233135 3 0.1173 0.74514 0.000 0.016 0.960 0.000 0.008 0.016
#> GSM1233136 3 0.3858 0.69873 0.000 0.052 0.820 0.012 0.036 0.080
#> GSM1233137 3 0.3236 0.69466 0.036 0.000 0.840 0.000 0.020 0.104
#> GSM1233138 4 0.1773 0.61004 0.000 0.016 0.000 0.932 0.016 0.036
#> GSM1233140 1 0.4593 0.68611 0.728 0.000 0.044 0.000 0.048 0.180
#> GSM1233141 2 0.7449 0.23854 0.000 0.460 0.024 0.112 0.176 0.228
#> GSM1233142 2 0.6736 0.29037 0.000 0.488 0.000 0.076 0.192 0.244
#> GSM1233144 3 0.2725 0.70854 0.040 0.000 0.880 0.000 0.020 0.060
#> GSM1233147 4 0.7567 0.25196 0.000 0.116 0.200 0.500 0.104 0.080
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> SD:skmeans 153 8.72e-01 0.3179 0.8632 2
#> SD:skmeans 145 1.54e-03 0.3157 0.0347 3
#> SD:skmeans 132 2.75e-06 0.0757 0.0021 4
#> SD:skmeans 104 4.75e-06 0.1449 0.0231 5
#> SD:skmeans 93 1.78e-06 0.0785 0.0113 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 51941 rows and 156 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 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 0.245 0.634 0.825 0.4294 0.562 0.562
#> 3 3 0.308 0.590 0.760 0.4687 0.636 0.432
#> 4 4 0.465 0.595 0.758 0.1571 0.748 0.423
#> 5 5 0.547 0.455 0.693 0.0628 0.936 0.781
#> 6 6 0.589 0.483 0.704 0.0433 0.897 0.626
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
#> GSM1232995 2 0.1843 0.8069 0.028 0.972
#> GSM1233002 2 0.8499 0.6163 0.276 0.724
#> GSM1233003 1 0.8327 0.6207 0.736 0.264
#> GSM1233014 2 0.2603 0.8080 0.044 0.956
#> GSM1233015 2 0.9993 -0.0557 0.484 0.516
#> GSM1233016 2 0.7950 0.6406 0.240 0.760
#> GSM1233024 2 0.2603 0.8053 0.044 0.956
#> GSM1233049 1 0.4022 0.7190 0.920 0.080
#> GSM1233064 2 0.3584 0.7836 0.068 0.932
#> GSM1233068 2 0.9963 -0.1264 0.464 0.536
#> GSM1233073 2 0.9866 0.0711 0.432 0.568
#> GSM1233093 1 0.1414 0.7031 0.980 0.020
#> GSM1233115 1 0.5519 0.6976 0.872 0.128
#> GSM1232992 2 0.0000 0.8072 0.000 1.000
#> GSM1232993 2 0.0000 0.8072 0.000 1.000
#> GSM1233005 2 0.1184 0.8056 0.016 0.984
#> GSM1233007 2 0.4298 0.7757 0.088 0.912
#> GSM1233010 2 0.9087 0.5032 0.324 0.676
#> GSM1233013 2 0.0672 0.8076 0.008 0.992
#> GSM1233018 2 0.0938 0.8085 0.012 0.988
#> GSM1233019 2 0.1633 0.8031 0.024 0.976
#> GSM1233021 2 0.0938 0.8084 0.012 0.988
#> GSM1233025 2 0.8499 0.5999 0.276 0.724
#> GSM1233029 2 0.1184 0.8082 0.016 0.984
#> GSM1233030 2 0.0000 0.8072 0.000 1.000
#> GSM1233031 2 0.7299 0.6984 0.204 0.796
#> GSM1233032 1 0.5059 0.7164 0.888 0.112
#> GSM1233035 2 0.7453 0.6739 0.212 0.788
#> GSM1233038 1 0.3431 0.7186 0.936 0.064
#> GSM1233039 2 0.3733 0.7892 0.072 0.928
#> GSM1233042 2 0.5946 0.7406 0.144 0.856
#> GSM1233043 2 0.3114 0.8009 0.056 0.944
#> GSM1233044 1 0.9833 0.4330 0.576 0.424
#> GSM1233046 2 0.5946 0.7367 0.144 0.856
#> GSM1233051 1 0.9732 0.4564 0.596 0.404
#> GSM1233054 2 0.9087 0.4066 0.324 0.676
#> GSM1233057 2 0.3584 0.8005 0.068 0.932
#> GSM1233060 2 0.6712 0.7167 0.176 0.824
#> GSM1233062 2 0.1633 0.8073 0.024 0.976
#> GSM1233075 2 0.2043 0.8068 0.032 0.968
#> GSM1233078 1 0.9970 0.2491 0.532 0.468
#> GSM1233079 1 0.4431 0.7080 0.908 0.092
#> GSM1233082 2 1.0000 -0.2607 0.500 0.500
#> GSM1233083 1 0.5178 0.7064 0.884 0.116
#> GSM1233091 2 0.5842 0.7460 0.140 0.860
#> GSM1233095 1 0.0376 0.7086 0.996 0.004
#> GSM1233096 1 0.7950 0.6293 0.760 0.240
#> GSM1233101 1 0.4431 0.7165 0.908 0.092
#> GSM1233105 2 0.9795 0.1672 0.416 0.584
#> GSM1233117 2 0.1633 0.8073 0.024 0.976
#> GSM1233118 2 0.1184 0.8093 0.016 0.984
#> GSM1233001 2 0.2778 0.7957 0.048 0.952
#> GSM1233006 2 0.4161 0.7768 0.084 0.916
#> GSM1233008 2 0.1843 0.8069 0.028 0.972
#> GSM1233009 2 0.3584 0.7971 0.068 0.932
#> GSM1233017 2 0.0938 0.8087 0.012 0.988
#> GSM1233020 2 0.0672 0.8076 0.008 0.992
#> GSM1233022 2 0.3584 0.8008 0.068 0.932
#> GSM1233026 2 0.7528 0.6616 0.216 0.784
#> GSM1233028 2 0.4431 0.7869 0.092 0.908
#> GSM1233034 2 0.0000 0.8072 0.000 1.000
#> GSM1233040 1 0.5059 0.7149 0.888 0.112
#> GSM1233048 1 0.5842 0.7112 0.860 0.140
#> GSM1233056 1 0.0376 0.7067 0.996 0.004
#> GSM1233058 2 0.9248 0.5314 0.340 0.660
#> GSM1233059 1 0.3879 0.7196 0.924 0.076
#> GSM1233066 2 0.9922 -0.0814 0.448 0.552
#> GSM1233071 2 0.5059 0.7523 0.112 0.888
#> GSM1233074 2 0.0672 0.8076 0.008 0.992
#> GSM1233076 2 0.5178 0.7627 0.116 0.884
#> GSM1233080 1 0.1184 0.7045 0.984 0.016
#> GSM1233088 2 0.7745 0.6619 0.228 0.772
#> GSM1233090 1 0.2043 0.7146 0.968 0.032
#> GSM1233092 2 0.4431 0.7750 0.092 0.908
#> GSM1233094 2 0.6801 0.7245 0.180 0.820
#> GSM1233097 2 0.7376 0.6979 0.208 0.792
#> GSM1233100 2 0.6048 0.7360 0.148 0.852
#> GSM1233104 2 0.5059 0.7880 0.112 0.888
#> GSM1233106 1 0.9983 0.3326 0.524 0.476
#> GSM1233111 1 0.9896 0.2828 0.560 0.440
#> GSM1233122 2 0.4161 0.7768 0.084 0.916
#> GSM1233146 2 0.4298 0.7946 0.088 0.912
#> GSM1232994 2 0.3584 0.7964 0.068 0.932
#> GSM1232996 2 0.1414 0.8078 0.020 0.980
#> GSM1232997 2 0.1843 0.8074 0.028 0.972
#> GSM1232998 2 0.2778 0.8085 0.048 0.952
#> GSM1232999 2 0.1184 0.8085 0.016 0.984
#> GSM1233000 2 0.2603 0.8047 0.044 0.956
#> GSM1233004 1 0.9552 0.4703 0.624 0.376
#> GSM1233011 2 0.4022 0.8021 0.080 0.920
#> GSM1233012 2 0.1414 0.8081 0.020 0.980
#> GSM1233023 2 0.0672 0.8076 0.008 0.992
#> GSM1233027 2 0.4161 0.7768 0.084 0.916
#> GSM1233033 1 0.9775 0.3858 0.588 0.412
#> GSM1233036 2 0.3584 0.8016 0.068 0.932
#> GSM1233037 2 0.5178 0.7546 0.116 0.884
#> GSM1233041 1 0.3114 0.7205 0.944 0.056
#> GSM1233045 2 0.6247 0.7408 0.156 0.844
#> GSM1233047 1 0.9954 0.3662 0.540 0.460
#> GSM1233050 1 0.4690 0.7164 0.900 0.100
#> GSM1233052 1 0.9522 0.4958 0.628 0.372
#> GSM1233053 1 0.4815 0.7170 0.896 0.104
#> GSM1233055 1 0.0938 0.7092 0.988 0.012
#> GSM1233061 2 0.4562 0.7848 0.096 0.904
#> GSM1233063 1 0.8207 0.6314 0.744 0.256
#> GSM1233065 2 0.2603 0.8056 0.044 0.956
#> GSM1233070 2 0.2423 0.8047 0.040 0.960
#> GSM1233077 2 0.9661 0.2452 0.392 0.608
#> GSM1233081 1 0.9427 0.5038 0.640 0.360
#> GSM1233084 1 0.1633 0.7041 0.976 0.024
#> GSM1233087 2 0.9922 0.1465 0.448 0.552
#> GSM1233089 2 0.4431 0.7727 0.092 0.908
#> GSM1233099 1 0.9795 0.4007 0.584 0.416
#> GSM1233112 1 0.9815 0.3703 0.580 0.420
#> GSM1233085 1 0.9944 0.3713 0.544 0.456
#> GSM1233098 2 0.0938 0.8083 0.012 0.988
#> GSM1233114 1 0.9850 0.4425 0.572 0.428
#> GSM1233119 2 0.9833 0.2896 0.424 0.576
#> GSM1233129 2 0.2236 0.8081 0.036 0.964
#> GSM1233132 1 0.5294 0.7148 0.880 0.120
#> GSM1233139 2 0.1843 0.8094 0.028 0.972
#> GSM1233143 2 0.3431 0.7900 0.064 0.936
#> GSM1233145 1 0.3274 0.7185 0.940 0.060
#> GSM1233067 2 0.5519 0.7453 0.128 0.872
#> GSM1233069 2 0.9552 0.2601 0.376 0.624
#> GSM1233072 2 0.3114 0.7975 0.056 0.944
#> GSM1233086 2 0.6712 0.6913 0.176 0.824
#> GSM1233102 1 0.9661 0.4075 0.608 0.392
#> GSM1233103 2 0.7674 0.6513 0.224 0.776
#> GSM1233107 2 0.5178 0.7713 0.116 0.884
#> GSM1233108 1 0.4022 0.7162 0.920 0.080
#> GSM1233109 1 0.9977 0.2649 0.528 0.472
#> GSM1233110 2 0.9580 0.2689 0.380 0.620
#> GSM1233113 2 0.0938 0.8073 0.012 0.988
#> GSM1233116 2 0.2236 0.8069 0.036 0.964
#> GSM1233120 1 0.9170 0.5360 0.668 0.332
#> GSM1233121 2 0.9635 0.2554 0.388 0.612
#> GSM1233123 2 0.9170 0.3491 0.332 0.668
#> GSM1233124 2 0.9323 0.3054 0.348 0.652
#> GSM1233125 1 0.3274 0.7127 0.940 0.060
#> GSM1233126 2 0.7139 0.7050 0.196 0.804
#> GSM1233127 2 0.1184 0.8102 0.016 0.984
#> GSM1233128 1 0.0672 0.7080 0.992 0.008
#> GSM1233130 2 0.9686 0.2424 0.396 0.604
#> GSM1233131 1 0.9963 0.3159 0.536 0.464
#> GSM1233133 1 0.9963 0.3422 0.536 0.464
#> GSM1233134 2 0.6048 0.7265 0.148 0.852
#> GSM1233135 2 0.9552 0.2601 0.376 0.624
#> GSM1233136 2 0.9552 0.3018 0.376 0.624
#> GSM1233137 1 0.6973 0.6930 0.812 0.188
#> GSM1233138 2 0.4161 0.7790 0.084 0.916
#> GSM1233140 1 0.9661 0.4967 0.608 0.392
#> GSM1233141 2 0.2778 0.8064 0.048 0.952
#> GSM1233142 2 0.1184 0.8087 0.016 0.984
#> GSM1233144 1 0.9922 0.3896 0.552 0.448
#> GSM1233147 2 0.9522 0.3098 0.372 0.628
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.2066 0.7887 0.000 0.940 0.060
#> GSM1233002 2 0.4565 0.7349 0.064 0.860 0.076
#> GSM1233003 1 0.7591 -0.0313 0.544 0.044 0.412
#> GSM1233014 3 0.6793 0.4147 0.012 0.452 0.536
#> GSM1233015 2 0.4921 0.7017 0.164 0.816 0.020
#> GSM1233016 3 0.8405 0.5306 0.264 0.132 0.604
#> GSM1233024 2 0.2414 0.7944 0.020 0.940 0.040
#> GSM1233049 1 0.4291 0.7473 0.840 0.008 0.152
#> GSM1233064 2 0.1711 0.7884 0.008 0.960 0.032
#> GSM1233068 3 0.7222 0.6370 0.084 0.220 0.696
#> GSM1233073 3 0.7698 0.5665 0.072 0.304 0.624
#> GSM1233093 1 0.0747 0.7728 0.984 0.000 0.016
#> GSM1233115 1 0.8464 0.5605 0.592 0.128 0.280
#> GSM1232992 2 0.1031 0.7869 0.000 0.976 0.024
#> GSM1232993 2 0.0592 0.7920 0.000 0.988 0.012
#> GSM1233005 2 0.1453 0.7851 0.008 0.968 0.024
#> GSM1233007 2 0.4782 0.6594 0.016 0.820 0.164
#> GSM1233010 2 0.6192 0.6614 0.176 0.764 0.060
#> GSM1233013 2 0.0592 0.7923 0.000 0.988 0.012
#> GSM1233018 2 0.0592 0.7924 0.000 0.988 0.012
#> GSM1233019 2 0.2584 0.7717 0.008 0.928 0.064
#> GSM1233021 2 0.0592 0.7924 0.000 0.988 0.012
#> GSM1233025 3 0.7379 0.4477 0.336 0.048 0.616
#> GSM1233029 2 0.0592 0.7927 0.000 0.988 0.012
#> GSM1233030 2 0.2165 0.7737 0.000 0.936 0.064
#> GSM1233031 2 0.9290 -0.0564 0.164 0.464 0.372
#> GSM1233032 1 0.3587 0.7635 0.892 0.020 0.088
#> GSM1233035 3 0.9790 0.4241 0.308 0.260 0.432
#> GSM1233038 1 0.2625 0.7490 0.916 0.000 0.084
#> GSM1233039 2 0.2116 0.7931 0.012 0.948 0.040
#> GSM1233042 2 0.3791 0.7735 0.048 0.892 0.060
#> GSM1233043 2 0.1620 0.7866 0.012 0.964 0.024
#> GSM1233044 3 0.7923 0.5385 0.228 0.120 0.652
#> GSM1233046 3 0.8470 0.5228 0.104 0.344 0.552
#> GSM1233051 3 0.8544 0.5726 0.248 0.152 0.600
#> GSM1233054 2 0.8649 0.2427 0.112 0.528 0.360
#> GSM1233057 2 0.6374 0.7069 0.100 0.768 0.132
#> GSM1233060 2 0.5913 0.7178 0.144 0.788 0.068
#> GSM1233062 2 0.2878 0.7835 0.000 0.904 0.096
#> GSM1233075 2 0.4883 0.6872 0.004 0.788 0.208
#> GSM1233078 3 0.2796 0.5802 0.092 0.000 0.908
#> GSM1233079 1 0.7562 0.5784 0.628 0.064 0.308
#> GSM1233082 2 0.9626 -0.0367 0.204 0.404 0.392
#> GSM1233083 1 0.6659 0.5070 0.532 0.008 0.460
#> GSM1233091 2 0.3755 0.7692 0.008 0.872 0.120
#> GSM1233095 1 0.3784 0.7497 0.864 0.004 0.132
#> GSM1233096 1 0.3325 0.7387 0.904 0.076 0.020
#> GSM1233101 1 0.5378 0.6992 0.756 0.008 0.236
#> GSM1233105 1 0.9741 -0.1143 0.412 0.228 0.360
#> GSM1233117 2 0.5058 0.5774 0.000 0.756 0.244
#> GSM1233118 3 0.6295 0.3404 0.000 0.472 0.528
#> GSM1233001 2 0.2796 0.7713 0.000 0.908 0.092
#> GSM1233006 3 0.6654 0.4166 0.008 0.456 0.536
#> GSM1233008 2 0.2878 0.7786 0.000 0.904 0.096
#> GSM1233009 2 0.3690 0.7489 0.100 0.884 0.016
#> GSM1233017 2 0.2959 0.7681 0.000 0.900 0.100
#> GSM1233020 2 0.0424 0.7925 0.000 0.992 0.008
#> GSM1233022 2 0.4689 0.7766 0.052 0.852 0.096
#> GSM1233026 2 0.6783 0.6600 0.140 0.744 0.116
#> GSM1233028 2 0.6393 0.6831 0.112 0.768 0.120
#> GSM1233034 2 0.0000 0.7911 0.000 1.000 0.000
#> GSM1233040 1 0.2176 0.7700 0.948 0.020 0.032
#> GSM1233048 1 0.2806 0.7679 0.928 0.032 0.040
#> GSM1233056 1 0.0424 0.7754 0.992 0.000 0.008
#> GSM1233058 2 0.8265 0.5218 0.180 0.636 0.184
#> GSM1233059 1 0.1015 0.7758 0.980 0.008 0.012
#> GSM1233066 3 0.3791 0.5995 0.060 0.048 0.892
#> GSM1233071 3 0.7410 0.4850 0.040 0.384 0.576
#> GSM1233074 2 0.6252 -0.0360 0.000 0.556 0.444
#> GSM1233076 3 0.6696 0.5595 0.020 0.348 0.632
#> GSM1233080 1 0.3482 0.7535 0.872 0.000 0.128
#> GSM1233088 2 0.4994 0.7463 0.052 0.836 0.112
#> GSM1233090 1 0.0661 0.7761 0.988 0.008 0.004
#> GSM1233092 3 0.7287 0.4838 0.032 0.408 0.560
#> GSM1233094 3 0.7712 0.4902 0.052 0.392 0.556
#> GSM1233097 3 0.9217 0.3110 0.152 0.400 0.448
#> GSM1233100 2 0.4206 0.7658 0.040 0.872 0.088
#> GSM1233104 3 0.8742 0.5141 0.136 0.308 0.556
#> GSM1233106 3 0.6960 0.6366 0.116 0.152 0.732
#> GSM1233111 1 0.5639 0.5984 0.752 0.232 0.016
#> GSM1233122 3 0.6683 0.3058 0.008 0.492 0.500
#> GSM1233146 2 0.5060 0.7397 0.100 0.836 0.064
#> GSM1232994 2 0.2878 0.7624 0.096 0.904 0.000
#> GSM1232996 2 0.1289 0.7921 0.000 0.968 0.032
#> GSM1232997 2 0.3038 0.7808 0.000 0.896 0.104
#> GSM1232998 2 0.7278 -0.2082 0.028 0.516 0.456
#> GSM1232999 2 0.0747 0.7922 0.000 0.984 0.016
#> GSM1233000 2 0.0237 0.7911 0.004 0.996 0.000
#> GSM1233004 3 0.4821 0.5976 0.040 0.120 0.840
#> GSM1233011 3 0.6322 0.6084 0.024 0.276 0.700
#> GSM1233012 3 0.6204 0.4196 0.000 0.424 0.576
#> GSM1233023 2 0.3038 0.7705 0.000 0.896 0.104
#> GSM1233027 2 0.1453 0.7851 0.008 0.968 0.024
#> GSM1233033 3 0.6489 0.2650 0.456 0.004 0.540
#> GSM1233036 3 0.8395 0.5010 0.104 0.328 0.568
#> GSM1233037 2 0.6625 0.4263 0.024 0.660 0.316
#> GSM1233041 1 0.0661 0.7762 0.988 0.008 0.004
#> GSM1233045 2 0.5449 0.7206 0.116 0.816 0.068
#> GSM1233047 3 0.5028 0.5858 0.132 0.040 0.828
#> GSM1233050 1 0.4589 0.7435 0.820 0.008 0.172
#> GSM1233052 2 0.9485 0.1621 0.304 0.484 0.212
#> GSM1233053 1 0.5726 0.6994 0.760 0.024 0.216
#> GSM1233055 1 0.2165 0.7515 0.936 0.000 0.064
#> GSM1233061 3 0.6079 0.6300 0.036 0.216 0.748
#> GSM1233063 1 0.6540 0.1652 0.584 0.008 0.408
#> GSM1233065 2 0.4702 0.6908 0.000 0.788 0.212
#> GSM1233070 3 0.6598 0.4493 0.008 0.428 0.564
#> GSM1233077 3 0.4995 0.5940 0.092 0.068 0.840
#> GSM1233081 3 0.3686 0.5572 0.140 0.000 0.860
#> GSM1233084 1 0.1289 0.7715 0.968 0.000 0.032
#> GSM1233087 3 0.7297 0.5752 0.172 0.120 0.708
#> GSM1233089 2 0.6819 -0.3425 0.012 0.512 0.476
#> GSM1233099 3 0.7558 0.5551 0.188 0.124 0.688
#> GSM1233112 3 0.7757 0.5787 0.224 0.112 0.664
#> GSM1233085 3 0.4121 0.5729 0.108 0.024 0.868
#> GSM1233098 2 0.2860 0.7758 0.004 0.912 0.084
#> GSM1233114 3 0.6952 0.3172 0.480 0.016 0.504
#> GSM1233119 3 0.7504 0.5015 0.312 0.060 0.628
#> GSM1233129 2 0.3482 0.7632 0.000 0.872 0.128
#> GSM1233132 1 0.3832 0.7429 0.880 0.020 0.100
#> GSM1233139 2 0.3192 0.7669 0.000 0.888 0.112
#> GSM1233143 3 0.7462 0.5295 0.048 0.352 0.600
#> GSM1233145 1 0.3879 0.7058 0.848 0.000 0.152
#> GSM1233067 3 0.6887 0.6291 0.076 0.204 0.720
#> GSM1233069 3 0.4709 0.5886 0.092 0.056 0.852
#> GSM1233072 2 0.6680 -0.3514 0.008 0.508 0.484
#> GSM1233086 3 0.6723 0.6486 0.064 0.212 0.724
#> GSM1233102 3 0.5881 0.5187 0.256 0.016 0.728
#> GSM1233103 3 0.8869 0.5659 0.160 0.280 0.560
#> GSM1233107 3 0.8069 0.5882 0.120 0.244 0.636
#> GSM1233108 1 0.6215 0.5171 0.572 0.000 0.428
#> GSM1233109 3 0.3030 0.5799 0.092 0.004 0.904
#> GSM1233110 3 0.2945 0.5817 0.088 0.004 0.908
#> GSM1233113 2 0.3482 0.7489 0.000 0.872 0.128
#> GSM1233116 3 0.5650 0.5545 0.000 0.312 0.688
#> GSM1233120 3 0.7318 0.5147 0.264 0.068 0.668
#> GSM1233121 3 0.5093 0.5918 0.088 0.076 0.836
#> GSM1233123 3 0.4253 0.5938 0.080 0.048 0.872
#> GSM1233124 3 0.5625 0.6001 0.076 0.116 0.808
#> GSM1233125 1 0.4974 0.6763 0.764 0.000 0.236
#> GSM1233126 3 0.7824 0.5326 0.064 0.356 0.580
#> GSM1233127 3 0.6688 0.4761 0.012 0.408 0.580
#> GSM1233128 1 0.2625 0.7576 0.916 0.000 0.084
#> GSM1233130 3 0.2796 0.5802 0.092 0.000 0.908
#> GSM1233131 3 0.7325 0.3667 0.388 0.036 0.576
#> GSM1233133 3 0.3765 0.5828 0.084 0.028 0.888
#> GSM1233134 3 0.6336 0.6444 0.064 0.180 0.756
#> GSM1233135 3 0.4505 0.5902 0.092 0.048 0.860
#> GSM1233136 3 0.5004 0.5994 0.088 0.072 0.840
#> GSM1233137 1 0.6754 0.5066 0.556 0.012 0.432
#> GSM1233138 3 0.7158 0.5170 0.032 0.372 0.596
#> GSM1233140 3 0.7346 0.3207 0.432 0.032 0.536
#> GSM1233141 3 0.6696 0.5275 0.020 0.348 0.632
#> GSM1233142 3 0.7043 0.4109 0.020 0.448 0.532
#> GSM1233144 3 0.4045 0.5681 0.104 0.024 0.872
#> GSM1233147 3 0.5407 0.6392 0.040 0.156 0.804
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.2751 0.7777 0.000 0.904 0.040 0.056
#> GSM1233002 2 0.4998 0.0135 0.000 0.512 0.000 0.488
#> GSM1233003 4 0.7022 0.5581 0.228 0.012 0.148 0.612
#> GSM1233014 4 0.4728 0.6403 0.000 0.104 0.104 0.792
#> GSM1233015 2 0.2300 0.7772 0.016 0.920 0.000 0.064
#> GSM1233016 4 0.5063 0.6542 0.156 0.024 0.040 0.780
#> GSM1233024 2 0.1661 0.7899 0.000 0.944 0.004 0.052
#> GSM1233049 1 0.2281 0.8392 0.904 0.000 0.096 0.000
#> GSM1233064 2 0.1302 0.7845 0.000 0.956 0.000 0.044
#> GSM1233068 3 0.7150 0.4307 0.004 0.132 0.532 0.332
#> GSM1233073 4 0.4292 0.6456 0.000 0.080 0.100 0.820
#> GSM1233093 1 0.0000 0.8582 1.000 0.000 0.000 0.000
#> GSM1233115 4 0.8014 0.5109 0.184 0.064 0.176 0.576
#> GSM1232992 2 0.0817 0.7862 0.000 0.976 0.000 0.024
#> GSM1232993 2 0.0592 0.7890 0.000 0.984 0.000 0.016
#> GSM1233005 2 0.1118 0.7865 0.000 0.964 0.000 0.036
#> GSM1233007 2 0.3351 0.7535 0.000 0.844 0.008 0.148
#> GSM1233010 2 0.5584 0.6241 0.020 0.692 0.024 0.264
#> GSM1233013 2 0.1722 0.7836 0.000 0.944 0.008 0.048
#> GSM1233018 2 0.1118 0.7885 0.000 0.964 0.000 0.036
#> GSM1233019 2 0.1824 0.7799 0.000 0.936 0.004 0.060
#> GSM1233021 2 0.1211 0.7863 0.000 0.960 0.000 0.040
#> GSM1233025 4 0.4485 0.6502 0.176 0.012 0.020 0.792
#> GSM1233029 2 0.1118 0.7863 0.000 0.964 0.000 0.036
#> GSM1233030 2 0.1576 0.7825 0.000 0.948 0.004 0.048
#> GSM1233031 4 0.6039 0.5838 0.016 0.200 0.080 0.704
#> GSM1233032 1 0.4023 0.7821 0.840 0.004 0.104 0.052
#> GSM1233035 2 0.8387 0.4474 0.132 0.532 0.088 0.248
#> GSM1233038 1 0.2647 0.7878 0.880 0.000 0.000 0.120
#> GSM1233039 2 0.2714 0.7793 0.000 0.884 0.004 0.112
#> GSM1233042 2 0.4193 0.5772 0.000 0.732 0.000 0.268
#> GSM1233043 2 0.1792 0.7835 0.000 0.932 0.000 0.068
#> GSM1233044 4 0.6448 0.4611 0.012 0.056 0.344 0.588
#> GSM1233046 2 0.7272 0.4963 0.024 0.568 0.104 0.304
#> GSM1233051 4 0.7715 0.2517 0.064 0.064 0.384 0.488
#> GSM1233054 3 0.6708 0.5027 0.000 0.272 0.596 0.132
#> GSM1233057 3 0.7241 0.3479 0.004 0.364 0.500 0.132
#> GSM1233060 2 0.2839 0.7835 0.004 0.884 0.004 0.108
#> GSM1233062 2 0.5122 0.7086 0.000 0.756 0.080 0.164
#> GSM1233075 3 0.6233 0.3853 0.000 0.388 0.552 0.060
#> GSM1233078 3 0.2345 0.6206 0.000 0.000 0.900 0.100
#> GSM1233079 1 0.5689 0.6059 0.660 0.012 0.300 0.028
#> GSM1233082 4 0.7800 -0.0494 0.028 0.120 0.416 0.436
#> GSM1233083 4 0.6735 0.5346 0.132 0.004 0.248 0.616
#> GSM1233091 2 0.6868 0.3848 0.000 0.584 0.264 0.152
#> GSM1233095 1 0.2984 0.8349 0.888 0.000 0.084 0.028
#> GSM1233096 1 0.1888 0.8435 0.940 0.016 0.000 0.044
#> GSM1233101 1 0.4356 0.7900 0.804 0.000 0.148 0.048
#> GSM1233105 4 0.6266 0.6263 0.192 0.080 0.028 0.700
#> GSM1233117 2 0.2654 0.7711 0.000 0.888 0.004 0.108
#> GSM1233118 2 0.7329 0.1090 0.000 0.516 0.296 0.188
#> GSM1233001 2 0.2197 0.7802 0.000 0.928 0.024 0.048
#> GSM1233006 4 0.5858 0.0739 0.000 0.468 0.032 0.500
#> GSM1233008 2 0.4775 0.7035 0.000 0.784 0.076 0.140
#> GSM1233009 2 0.2142 0.7787 0.016 0.928 0.000 0.056
#> GSM1233017 2 0.2125 0.7852 0.000 0.920 0.004 0.076
#> GSM1233020 2 0.1389 0.7846 0.000 0.952 0.000 0.048
#> GSM1233022 2 0.5047 0.7141 0.004 0.744 0.040 0.212
#> GSM1233026 2 0.6353 0.6300 0.016 0.684 0.104 0.196
#> GSM1233028 2 0.7059 0.0979 0.016 0.468 0.076 0.440
#> GSM1233034 2 0.1118 0.7850 0.000 0.964 0.000 0.036
#> GSM1233040 1 0.0927 0.8567 0.976 0.000 0.008 0.016
#> GSM1233048 1 0.0707 0.8585 0.980 0.000 0.000 0.020
#> GSM1233056 1 0.0469 0.8584 0.988 0.000 0.012 0.000
#> GSM1233058 4 0.4739 0.6065 0.012 0.164 0.036 0.788
#> GSM1233059 1 0.0000 0.8582 1.000 0.000 0.000 0.000
#> GSM1233066 3 0.4214 0.6010 0.000 0.016 0.780 0.204
#> GSM1233071 3 0.7790 0.3553 0.000 0.316 0.420 0.264
#> GSM1233074 3 0.7464 0.4405 0.000 0.296 0.496 0.208
#> GSM1233076 4 0.4740 0.6360 0.000 0.132 0.080 0.788
#> GSM1233080 1 0.1792 0.8509 0.932 0.000 0.068 0.000
#> GSM1233088 2 0.6111 0.4391 0.000 0.652 0.256 0.092
#> GSM1233090 1 0.0524 0.8605 0.988 0.000 0.008 0.004
#> GSM1233092 4 0.4057 0.6344 0.000 0.152 0.032 0.816
#> GSM1233094 4 0.4274 0.6363 0.000 0.072 0.108 0.820
#> GSM1233097 4 0.4683 0.6369 0.012 0.096 0.080 0.812
#> GSM1233100 2 0.6396 0.3428 0.000 0.548 0.072 0.380
#> GSM1233104 4 0.4006 0.6553 0.008 0.084 0.060 0.848
#> GSM1233106 3 0.6512 0.4076 0.004 0.076 0.576 0.344
#> GSM1233111 1 0.5770 0.5787 0.708 0.228 0.024 0.040
#> GSM1233122 2 0.4707 0.6576 0.000 0.760 0.036 0.204
#> GSM1233146 2 0.4218 0.7156 0.008 0.796 0.012 0.184
#> GSM1232994 2 0.1302 0.7841 0.000 0.956 0.000 0.044
#> GSM1232996 2 0.1637 0.7858 0.000 0.940 0.000 0.060
#> GSM1232997 2 0.3088 0.7780 0.000 0.888 0.060 0.052
#> GSM1232998 4 0.5383 0.6295 0.000 0.160 0.100 0.740
#> GSM1232999 2 0.1474 0.7844 0.000 0.948 0.000 0.052
#> GSM1233000 2 0.1389 0.7840 0.000 0.952 0.000 0.048
#> GSM1233004 4 0.5746 0.3868 0.000 0.032 0.396 0.572
#> GSM1233011 4 0.6391 0.4634 0.004 0.084 0.292 0.620
#> GSM1233012 2 0.7696 -0.0610 0.000 0.436 0.332 0.232
#> GSM1233023 3 0.7113 0.3180 0.000 0.384 0.484 0.132
#> GSM1233027 2 0.1118 0.7856 0.000 0.964 0.000 0.036
#> GSM1233033 4 0.5219 0.6024 0.244 0.000 0.044 0.712
#> GSM1233036 3 0.7422 0.4809 0.012 0.180 0.564 0.244
#> GSM1233037 3 0.7341 0.4392 0.000 0.292 0.516 0.192
#> GSM1233041 1 0.0592 0.8561 0.984 0.000 0.000 0.016
#> GSM1233045 2 0.5283 0.6895 0.012 0.744 0.044 0.200
#> GSM1233047 3 0.2053 0.6412 0.000 0.004 0.924 0.072
#> GSM1233050 1 0.3266 0.8303 0.876 0.000 0.084 0.040
#> GSM1233052 2 0.9056 0.2584 0.256 0.444 0.092 0.208
#> GSM1233053 1 0.4072 0.8128 0.828 0.000 0.120 0.052
#> GSM1233055 1 0.0921 0.8572 0.972 0.000 0.000 0.028
#> GSM1233061 3 0.4538 0.5946 0.000 0.024 0.760 0.216
#> GSM1233063 4 0.6890 0.2818 0.392 0.008 0.084 0.516
#> GSM1233065 3 0.6741 0.1168 0.000 0.424 0.484 0.092
#> GSM1233070 4 0.5894 0.2252 0.000 0.392 0.040 0.568
#> GSM1233077 3 0.3157 0.6125 0.000 0.004 0.852 0.144
#> GSM1233081 3 0.2197 0.6210 0.004 0.000 0.916 0.080
#> GSM1233084 1 0.0592 0.8561 0.984 0.000 0.000 0.016
#> GSM1233087 4 0.3665 0.6713 0.016 0.060 0.052 0.872
#> GSM1233089 2 0.4617 0.6549 0.000 0.764 0.032 0.204
#> GSM1233099 4 0.3240 0.6677 0.016 0.056 0.036 0.892
#> GSM1233112 4 0.5714 0.5693 0.004 0.056 0.256 0.684
#> GSM1233085 3 0.3801 0.6261 0.076 0.004 0.856 0.064
#> GSM1233098 2 0.5213 0.5467 0.000 0.724 0.224 0.052
#> GSM1233114 1 0.6203 0.2282 0.580 0.008 0.044 0.368
#> GSM1233119 4 0.2837 0.6722 0.028 0.024 0.036 0.912
#> GSM1233129 3 0.6988 0.3389 0.000 0.380 0.500 0.120
#> GSM1233132 1 0.2238 0.8417 0.920 0.004 0.004 0.072
#> GSM1233139 2 0.2363 0.7848 0.000 0.920 0.024 0.056
#> GSM1233143 3 0.7145 0.4271 0.000 0.144 0.508 0.348
#> GSM1233145 4 0.5614 0.4439 0.336 0.000 0.036 0.628
#> GSM1233067 3 0.5267 0.6046 0.000 0.076 0.740 0.184
#> GSM1233069 3 0.2714 0.6307 0.000 0.004 0.884 0.112
#> GSM1233072 2 0.4692 0.6469 0.000 0.756 0.032 0.212
#> GSM1233086 3 0.4453 0.5930 0.000 0.012 0.744 0.244
#> GSM1233102 4 0.4353 0.6592 0.060 0.004 0.116 0.820
#> GSM1233103 2 0.7218 0.4897 0.020 0.576 0.112 0.292
#> GSM1233107 4 0.6776 0.3576 0.016 0.308 0.080 0.596
#> GSM1233108 3 0.5663 0.2818 0.264 0.000 0.676 0.060
#> GSM1233109 3 0.2281 0.6160 0.000 0.000 0.904 0.096
#> GSM1233110 3 0.1940 0.6238 0.000 0.000 0.924 0.076
#> GSM1233113 2 0.2214 0.7804 0.000 0.928 0.028 0.044
#> GSM1233116 3 0.7687 0.1753 0.000 0.348 0.428 0.224
#> GSM1233120 4 0.5191 0.6542 0.072 0.032 0.104 0.792
#> GSM1233121 3 0.2706 0.6265 0.000 0.020 0.900 0.080
#> GSM1233123 3 0.0817 0.6440 0.000 0.000 0.976 0.024
#> GSM1233124 3 0.3695 0.6192 0.000 0.016 0.828 0.156
#> GSM1233125 1 0.6451 0.2893 0.476 0.000 0.456 0.068
#> GSM1233126 4 0.4093 0.6478 0.012 0.120 0.032 0.836
#> GSM1233127 4 0.6393 -0.0307 0.000 0.456 0.064 0.480
#> GSM1233128 1 0.3166 0.8140 0.868 0.000 0.116 0.016
#> GSM1233130 3 0.2530 0.6129 0.000 0.000 0.888 0.112
#> GSM1233131 4 0.6363 0.6126 0.200 0.008 0.120 0.672
#> GSM1233133 3 0.0336 0.6419 0.000 0.000 0.992 0.008
#> GSM1233134 3 0.2861 0.6422 0.000 0.016 0.888 0.096
#> GSM1233135 3 0.3523 0.6349 0.000 0.032 0.856 0.112
#> GSM1233136 3 0.5220 0.2250 0.000 0.016 0.632 0.352
#> GSM1233137 3 0.4220 0.4730 0.248 0.000 0.748 0.004
#> GSM1233138 4 0.2797 0.6542 0.000 0.068 0.032 0.900
#> GSM1233140 3 0.6752 0.4311 0.180 0.012 0.648 0.160
#> GSM1233141 4 0.7437 0.0945 0.004 0.172 0.312 0.512
#> GSM1233142 2 0.6326 0.5310 0.008 0.624 0.068 0.300
#> GSM1233144 3 0.0000 0.6403 0.000 0.000 1.000 0.000
#> GSM1233147 4 0.5417 0.5166 0.000 0.040 0.284 0.676
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.3398 0.5732 0.000 0.780 0.000 0.004 0.216
#> GSM1233002 4 0.5087 0.3624 0.000 0.292 0.000 0.644 0.064
#> GSM1233003 4 0.5820 0.2888 0.424 0.012 0.020 0.516 0.028
#> GSM1233014 4 0.4622 0.6476 0.000 0.092 0.036 0.784 0.088
#> GSM1233015 2 0.1893 0.6994 0.000 0.928 0.000 0.024 0.048
#> GSM1233016 4 0.6298 0.5375 0.236 0.016 0.024 0.628 0.096
#> GSM1233024 2 0.1082 0.7153 0.000 0.964 0.000 0.028 0.008
#> GSM1233049 1 0.4401 0.5516 0.656 0.000 0.016 0.000 0.328
#> GSM1233064 2 0.1282 0.7155 0.000 0.952 0.000 0.044 0.004
#> GSM1233068 3 0.6367 0.4309 0.000 0.020 0.492 0.100 0.388
#> GSM1233073 4 0.3241 0.6609 0.000 0.052 0.036 0.872 0.040
#> GSM1233093 1 0.3913 0.5572 0.676 0.000 0.000 0.000 0.324
#> GSM1233115 4 0.7794 0.4672 0.156 0.064 0.068 0.564 0.148
#> GSM1232992 2 0.0510 0.7132 0.000 0.984 0.000 0.016 0.000
#> GSM1232993 2 0.0290 0.7171 0.000 0.992 0.000 0.008 0.000
#> GSM1233005 2 0.0510 0.7132 0.000 0.984 0.000 0.016 0.000
#> GSM1233007 2 0.3146 0.6937 0.000 0.856 0.000 0.092 0.052
#> GSM1233010 2 0.5652 0.4717 0.004 0.684 0.016 0.124 0.172
#> GSM1233013 2 0.1569 0.7146 0.000 0.944 0.004 0.044 0.008
#> GSM1233018 2 0.0324 0.7159 0.000 0.992 0.000 0.004 0.004
#> GSM1233019 2 0.1557 0.7116 0.000 0.940 0.000 0.052 0.008
#> GSM1233021 2 0.0671 0.7128 0.000 0.980 0.000 0.016 0.004
#> GSM1233025 4 0.4690 0.6459 0.128 0.012 0.004 0.768 0.088
#> GSM1233029 2 0.0671 0.7128 0.000 0.980 0.000 0.016 0.004
#> GSM1233030 2 0.1484 0.7120 0.000 0.944 0.000 0.048 0.008
#> GSM1233031 4 0.5979 0.5504 0.000 0.168 0.016 0.636 0.180
#> GSM1233032 5 0.5378 -0.4058 0.392 0.000 0.060 0.000 0.548
#> GSM1233035 2 0.8354 -0.2469 0.276 0.332 0.016 0.076 0.300
#> GSM1233038 1 0.3779 0.3641 0.776 0.000 0.000 0.200 0.024
#> GSM1233039 2 0.2448 0.7044 0.000 0.892 0.000 0.088 0.020
#> GSM1233042 2 0.4327 0.3182 0.000 0.632 0.000 0.360 0.008
#> GSM1233043 2 0.1965 0.6871 0.000 0.904 0.000 0.096 0.000
#> GSM1233044 4 0.7709 0.1458 0.004 0.064 0.180 0.400 0.352
#> GSM1233046 2 0.7479 0.1755 0.016 0.476 0.044 0.148 0.316
#> GSM1233051 1 0.8770 -0.1627 0.316 0.028 0.108 0.300 0.248
#> GSM1233054 3 0.6400 0.4465 0.000 0.124 0.524 0.016 0.336
#> GSM1233057 3 0.6629 0.4130 0.000 0.176 0.504 0.012 0.308
#> GSM1233060 2 0.2777 0.6874 0.000 0.864 0.000 0.120 0.016
#> GSM1233062 2 0.5077 0.5082 0.000 0.692 0.016 0.052 0.240
#> GSM1233075 3 0.6108 0.4573 0.000 0.212 0.644 0.048 0.096
#> GSM1233078 3 0.4010 0.5435 0.000 0.000 0.784 0.056 0.160
#> GSM1233079 1 0.6741 0.3867 0.464 0.000 0.136 0.024 0.376
#> GSM1233082 3 0.7870 0.1934 0.016 0.036 0.368 0.252 0.328
#> GSM1233083 4 0.4900 0.6204 0.060 0.004 0.096 0.776 0.064
#> GSM1233091 2 0.7493 -0.0838 0.000 0.416 0.240 0.044 0.300
#> GSM1233095 1 0.4618 0.5438 0.636 0.000 0.016 0.004 0.344
#> GSM1233096 1 0.2173 0.4586 0.920 0.016 0.000 0.012 0.052
#> GSM1233101 1 0.5396 0.5090 0.588 0.000 0.032 0.020 0.360
#> GSM1233105 4 0.4078 0.6113 0.160 0.028 0.000 0.792 0.020
#> GSM1233117 2 0.2754 0.6977 0.000 0.884 0.004 0.032 0.080
#> GSM1233118 2 0.7584 0.1053 0.000 0.472 0.288 0.108 0.132
#> GSM1233001 2 0.2217 0.7067 0.000 0.920 0.024 0.044 0.012
#> GSM1233006 4 0.6010 0.1045 0.000 0.404 0.024 0.512 0.060
#> GSM1233008 2 0.4644 0.4892 0.000 0.708 0.016 0.024 0.252
#> GSM1233009 2 0.0898 0.7117 0.000 0.972 0.000 0.020 0.008
#> GSM1233017 2 0.1774 0.7132 0.000 0.932 0.000 0.052 0.016
#> GSM1233020 2 0.1408 0.7152 0.000 0.948 0.000 0.044 0.008
#> GSM1233022 2 0.4527 0.6128 0.000 0.752 0.004 0.172 0.072
#> GSM1233026 2 0.6266 0.2449 0.000 0.560 0.040 0.072 0.328
#> GSM1233028 2 0.6968 -0.0863 0.000 0.448 0.016 0.216 0.320
#> GSM1233034 2 0.1043 0.7155 0.000 0.960 0.000 0.040 0.000
#> GSM1233040 1 0.0162 0.4958 0.996 0.000 0.000 0.000 0.004
#> GSM1233048 1 0.4101 0.5565 0.664 0.000 0.000 0.004 0.332
#> GSM1233056 1 0.3913 0.5572 0.676 0.000 0.000 0.000 0.324
#> GSM1233058 4 0.5389 0.5679 0.000 0.100 0.012 0.684 0.204
#> GSM1233059 1 0.3913 0.5572 0.676 0.000 0.000 0.000 0.324
#> GSM1233066 3 0.4873 0.5307 0.000 0.000 0.644 0.044 0.312
#> GSM1233071 3 0.8119 0.2836 0.000 0.228 0.424 0.152 0.196
#> GSM1233074 3 0.7311 0.4353 0.000 0.148 0.520 0.084 0.248
#> GSM1233076 4 0.3942 0.6486 0.000 0.028 0.064 0.828 0.080
#> GSM1233080 1 0.4066 0.5568 0.672 0.000 0.004 0.000 0.324
#> GSM1233088 2 0.5806 0.3192 0.000 0.600 0.316 0.052 0.032
#> GSM1233090 1 0.3949 0.5557 0.668 0.000 0.000 0.000 0.332
#> GSM1233092 4 0.3732 0.6447 0.000 0.060 0.024 0.840 0.076
#> GSM1233094 4 0.3949 0.6395 0.000 0.048 0.036 0.828 0.088
#> GSM1233097 4 0.4696 0.6033 0.000 0.080 0.016 0.760 0.144
#> GSM1233100 2 0.6986 -0.0560 0.000 0.444 0.016 0.320 0.220
#> GSM1233104 4 0.4497 0.6521 0.000 0.092 0.012 0.776 0.120
#> GSM1233106 3 0.6405 0.4497 0.000 0.016 0.512 0.120 0.352
#> GSM1233111 1 0.5219 0.1334 0.672 0.268 0.020 0.004 0.036
#> GSM1233122 2 0.4660 0.6035 0.000 0.772 0.028 0.132 0.068
#> GSM1233146 2 0.4705 0.5690 0.000 0.744 0.008 0.172 0.076
#> GSM1232994 2 0.0609 0.7123 0.000 0.980 0.000 0.020 0.000
#> GSM1232996 2 0.1386 0.7107 0.000 0.952 0.000 0.016 0.032
#> GSM1232997 2 0.3592 0.6292 0.000 0.808 0.012 0.012 0.168
#> GSM1232998 4 0.4868 0.6293 0.000 0.136 0.020 0.752 0.092
#> GSM1232999 2 0.0671 0.7128 0.000 0.980 0.000 0.016 0.004
#> GSM1233000 2 0.1121 0.7153 0.000 0.956 0.000 0.044 0.000
#> GSM1233004 3 0.7049 -0.1326 0.000 0.024 0.404 0.388 0.184
#> GSM1233011 4 0.7396 0.3109 0.000 0.060 0.180 0.472 0.288
#> GSM1233012 2 0.8277 -0.2015 0.000 0.316 0.312 0.124 0.248
#> GSM1233023 3 0.7209 0.3924 0.000 0.208 0.504 0.048 0.240
#> GSM1233027 2 0.0510 0.7132 0.000 0.984 0.000 0.016 0.000
#> GSM1233033 1 0.6247 -0.2869 0.432 0.000 0.000 0.424 0.144
#> GSM1233036 3 0.6394 0.4589 0.000 0.060 0.524 0.052 0.364
#> GSM1233037 3 0.6991 0.4462 0.000 0.088 0.508 0.080 0.324
#> GSM1233041 1 0.0000 0.4970 1.000 0.000 0.000 0.000 0.000
#> GSM1233045 2 0.5634 0.4564 0.000 0.656 0.008 0.132 0.204
#> GSM1233047 3 0.4288 0.5332 0.000 0.000 0.664 0.012 0.324
#> GSM1233050 1 0.4505 0.5283 0.620 0.000 0.008 0.004 0.368
#> GSM1233052 5 0.7313 0.2301 0.036 0.292 0.016 0.152 0.504
#> GSM1233053 1 0.5044 0.5317 0.608 0.000 0.036 0.004 0.352
#> GSM1233055 1 0.4235 0.5526 0.656 0.000 0.000 0.008 0.336
#> GSM1233061 3 0.4965 0.5274 0.000 0.000 0.644 0.052 0.304
#> GSM1233063 1 0.7450 0.0261 0.496 0.004 0.060 0.256 0.184
#> GSM1233065 3 0.6717 0.0615 0.000 0.340 0.440 0.004 0.216
#> GSM1233070 4 0.6573 0.1225 0.000 0.340 0.024 0.512 0.124
#> GSM1233077 3 0.4902 0.5115 0.000 0.004 0.724 0.100 0.172
#> GSM1233081 3 0.1493 0.5870 0.000 0.000 0.948 0.028 0.024
#> GSM1233084 1 0.1410 0.5140 0.940 0.000 0.000 0.000 0.060
#> GSM1233087 4 0.3627 0.6431 0.000 0.064 0.008 0.836 0.092
#> GSM1233089 2 0.4451 0.6087 0.000 0.784 0.024 0.132 0.060
#> GSM1233099 4 0.3521 0.6259 0.000 0.012 0.008 0.808 0.172
#> GSM1233112 4 0.5023 0.5807 0.008 0.020 0.100 0.756 0.116
#> GSM1233085 3 0.5190 0.5271 0.024 0.000 0.612 0.020 0.344
#> GSM1233098 2 0.5566 0.3806 0.000 0.644 0.276 0.044 0.036
#> GSM1233114 1 0.6279 0.1129 0.532 0.000 0.000 0.200 0.268
#> GSM1233119 4 0.3430 0.6436 0.000 0.004 0.000 0.776 0.220
#> GSM1233129 3 0.6599 0.4146 0.000 0.168 0.504 0.012 0.316
#> GSM1233132 1 0.5458 0.4216 0.476 0.000 0.000 0.060 0.464
#> GSM1233139 2 0.2444 0.7085 0.000 0.912 0.024 0.036 0.028
#> GSM1233143 3 0.6744 0.4179 0.000 0.020 0.440 0.144 0.396
#> GSM1233145 4 0.5489 0.2949 0.420 0.000 0.012 0.528 0.040
#> GSM1233067 3 0.5252 0.5645 0.000 0.024 0.716 0.088 0.172
#> GSM1233069 3 0.1267 0.5910 0.000 0.004 0.960 0.024 0.012
#> GSM1233072 2 0.4702 0.5894 0.000 0.760 0.024 0.156 0.060
#> GSM1233086 3 0.5027 0.5535 0.000 0.012 0.720 0.084 0.184
#> GSM1233102 4 0.2713 0.6566 0.004 0.000 0.036 0.888 0.072
#> GSM1233103 2 0.6699 0.0996 0.000 0.464 0.036 0.104 0.396
#> GSM1233107 5 0.7460 -0.0402 0.000 0.284 0.032 0.324 0.360
#> GSM1233108 3 0.5490 0.2452 0.020 0.000 0.576 0.036 0.368
#> GSM1233109 3 0.3779 0.5363 0.000 0.000 0.804 0.052 0.144
#> GSM1233110 3 0.2625 0.5610 0.000 0.000 0.876 0.016 0.108
#> GSM1233113 2 0.2355 0.7063 0.000 0.916 0.024 0.036 0.024
#> GSM1233116 3 0.7693 0.0124 0.000 0.308 0.436 0.088 0.168
#> GSM1233120 4 0.2648 0.6313 0.000 0.000 0.000 0.848 0.152
#> GSM1233121 3 0.3870 0.5485 0.000 0.024 0.816 0.028 0.132
#> GSM1233123 3 0.2179 0.5644 0.000 0.000 0.888 0.000 0.112
#> GSM1233124 3 0.4964 0.5566 0.000 0.020 0.712 0.048 0.220
#> GSM1233125 3 0.6454 0.0678 0.392 0.000 0.468 0.012 0.128
#> GSM1233126 4 0.3033 0.6512 0.000 0.032 0.024 0.880 0.064
#> GSM1233127 2 0.7192 -0.0877 0.000 0.408 0.024 0.344 0.224
#> GSM1233128 1 0.4135 0.4069 0.808 0.000 0.080 0.016 0.096
#> GSM1233130 3 0.4466 0.5136 0.000 0.000 0.748 0.076 0.176
#> GSM1233131 1 0.7139 -0.0392 0.412 0.000 0.032 0.176 0.380
#> GSM1233133 3 0.2773 0.5788 0.000 0.000 0.836 0.000 0.164
#> GSM1233134 3 0.3409 0.5903 0.000 0.000 0.824 0.032 0.144
#> GSM1233135 3 0.1978 0.5934 0.000 0.004 0.928 0.024 0.044
#> GSM1233136 3 0.6259 0.2618 0.000 0.004 0.556 0.260 0.180
#> GSM1233137 3 0.4679 0.5083 0.136 0.000 0.740 0.000 0.124
#> GSM1233138 4 0.3110 0.6516 0.000 0.024 0.024 0.872 0.080
#> GSM1233140 1 0.7890 -0.1482 0.392 0.016 0.248 0.040 0.304
#> GSM1233141 4 0.8291 -0.0406 0.000 0.132 0.292 0.340 0.236
#> GSM1233142 2 0.6665 0.2052 0.000 0.504 0.024 0.136 0.336
#> GSM1233144 3 0.2605 0.5762 0.000 0.000 0.852 0.000 0.148
#> GSM1233147 4 0.5673 0.4989 0.000 0.020 0.276 0.632 0.072
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.3843 0.63673 0.000 0.740 0.008 0.016 0.004 0.232
#> GSM1233002 4 0.7265 0.38752 0.000 0.252 0.156 0.484 0.064 0.044
#> GSM1233003 5 0.4228 0.44557 0.032 0.000 0.000 0.252 0.704 0.012
#> GSM1233014 4 0.3593 0.56850 0.000 0.048 0.008 0.828 0.020 0.096
#> GSM1233015 2 0.2209 0.73029 0.000 0.900 0.000 0.004 0.072 0.024
#> GSM1233016 4 0.4301 0.28922 0.024 0.000 0.008 0.696 0.264 0.008
#> GSM1233024 2 0.0260 0.75719 0.000 0.992 0.000 0.008 0.000 0.000
#> GSM1233049 1 0.0000 0.85117 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233064 2 0.1492 0.75764 0.000 0.940 0.000 0.036 0.000 0.024
#> GSM1233068 6 0.1442 0.58687 0.000 0.000 0.004 0.040 0.012 0.944
#> GSM1233073 4 0.4164 0.54984 0.000 0.020 0.004 0.780 0.116 0.080
#> GSM1233093 1 0.0000 0.85117 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233115 3 0.8005 -0.31199 0.184 0.020 0.376 0.312 0.044 0.064
#> GSM1232992 2 0.0000 0.75649 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232993 2 0.1010 0.75908 0.000 0.960 0.000 0.036 0.000 0.004
#> GSM1233005 2 0.0725 0.75594 0.000 0.976 0.012 0.012 0.000 0.000
#> GSM1233007 2 0.3766 0.71008 0.000 0.796 0.020 0.148 0.004 0.032
#> GSM1233010 2 0.7407 0.26692 0.000 0.500 0.232 0.076 0.076 0.116
#> GSM1233013 2 0.1572 0.75716 0.000 0.936 0.000 0.036 0.000 0.028
#> GSM1233018 2 0.1053 0.75923 0.000 0.964 0.012 0.020 0.000 0.004
#> GSM1233019 2 0.1549 0.75615 0.000 0.936 0.000 0.044 0.000 0.020
#> GSM1233021 2 0.0725 0.75594 0.000 0.976 0.012 0.012 0.000 0.000
#> GSM1233025 4 0.4770 0.51432 0.012 0.036 0.092 0.748 0.112 0.000
#> GSM1233029 2 0.0547 0.75606 0.000 0.980 0.000 0.020 0.000 0.000
#> GSM1233030 2 0.1367 0.75686 0.000 0.944 0.000 0.044 0.000 0.012
#> GSM1233031 4 0.7181 0.45033 0.000 0.156 0.084 0.552 0.072 0.136
#> GSM1233032 1 0.3874 0.42627 0.636 0.000 0.000 0.000 0.008 0.356
#> GSM1233035 5 0.7857 0.13435 0.024 0.240 0.000 0.168 0.388 0.180
#> GSM1233038 5 0.4086 0.56186 0.124 0.000 0.000 0.124 0.752 0.000
#> GSM1233039 2 0.2681 0.73410 0.000 0.880 0.072 0.028 0.000 0.020
#> GSM1233042 2 0.4961 0.26734 0.000 0.584 0.008 0.348 0.060 0.000
#> GSM1233043 2 0.3176 0.68998 0.000 0.840 0.008 0.100 0.052 0.000
#> GSM1233044 6 0.6952 0.14911 0.004 0.024 0.096 0.296 0.080 0.500
#> GSM1233046 2 0.7504 0.14084 0.004 0.360 0.004 0.304 0.104 0.224
#> GSM1233051 3 0.7269 0.03118 0.004 0.004 0.428 0.260 0.216 0.088
#> GSM1233054 6 0.1965 0.59420 0.000 0.024 0.008 0.040 0.004 0.924
#> GSM1233057 6 0.1615 0.59088 0.000 0.064 0.000 0.004 0.004 0.928
#> GSM1233060 2 0.3235 0.70161 0.000 0.848 0.004 0.076 0.060 0.012
#> GSM1233062 2 0.4139 0.60764 0.000 0.732 0.000 0.048 0.008 0.212
#> GSM1233075 6 0.4556 0.46966 0.000 0.120 0.096 0.036 0.000 0.748
#> GSM1233078 3 0.4580 0.60442 0.000 0.000 0.708 0.120 0.004 0.168
#> GSM1233079 1 0.4233 0.60596 0.736 0.000 0.080 0.004 0.000 0.180
#> GSM1233082 6 0.6834 0.13864 0.000 0.004 0.176 0.212 0.096 0.512
#> GSM1233083 4 0.6198 0.42623 0.080 0.000 0.168 0.588 0.164 0.000
#> GSM1233091 6 0.6561 0.09032 0.000 0.344 0.136 0.040 0.012 0.468
#> GSM1233095 1 0.0146 0.85055 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM1233096 5 0.4803 0.37825 0.360 0.020 0.000 0.012 0.596 0.012
#> GSM1233101 1 0.2176 0.77059 0.896 0.000 0.080 0.000 0.000 0.024
#> GSM1233105 4 0.4507 0.26866 0.020 0.012 0.000 0.596 0.372 0.000
#> GSM1233117 2 0.3324 0.71329 0.000 0.824 0.000 0.112 0.004 0.060
#> GSM1233118 6 0.5951 0.24700 0.000 0.332 0.000 0.200 0.004 0.464
#> GSM1233001 2 0.1863 0.75512 0.000 0.920 0.000 0.036 0.000 0.044
#> GSM1233006 4 0.4302 0.18524 0.000 0.368 0.000 0.608 0.004 0.020
#> GSM1233008 2 0.4362 0.56293 0.000 0.688 0.000 0.036 0.012 0.264
#> GSM1233009 2 0.0458 0.75794 0.000 0.984 0.000 0.000 0.016 0.000
#> GSM1233017 2 0.1719 0.75642 0.000 0.924 0.000 0.060 0.000 0.016
#> GSM1233020 2 0.1564 0.75741 0.000 0.936 0.000 0.040 0.000 0.024
#> GSM1233022 2 0.4361 0.61337 0.000 0.724 0.000 0.196 0.008 0.072
#> GSM1233026 2 0.7948 0.05643 0.000 0.352 0.272 0.060 0.072 0.244
#> GSM1233028 2 0.8576 -0.17718 0.000 0.292 0.140 0.224 0.092 0.252
#> GSM1233034 2 0.1320 0.75759 0.000 0.948 0.000 0.036 0.000 0.016
#> GSM1233040 5 0.3868 0.14258 0.496 0.000 0.000 0.000 0.504 0.000
#> GSM1233048 1 0.0260 0.84730 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM1233056 1 0.0000 0.85117 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233058 4 0.8065 0.39256 0.000 0.092 0.220 0.424 0.104 0.160
#> GSM1233059 1 0.0000 0.85117 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233066 6 0.3189 0.55776 0.000 0.000 0.096 0.056 0.008 0.840
#> GSM1233071 6 0.5898 0.35714 0.000 0.200 0.000 0.308 0.004 0.488
#> GSM1233074 6 0.3020 0.56554 0.000 0.076 0.000 0.080 0.000 0.844
#> GSM1233076 4 0.3068 0.56681 0.000 0.016 0.124 0.840 0.000 0.020
#> GSM1233080 1 0.0000 0.85117 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233088 2 0.6121 0.27464 0.000 0.548 0.088 0.044 0.012 0.308
#> GSM1233090 1 0.0146 0.85055 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM1233092 4 0.2443 0.56414 0.000 0.004 0.096 0.880 0.000 0.020
#> GSM1233094 4 0.3536 0.55759 0.000 0.004 0.004 0.812 0.056 0.124
#> GSM1233097 4 0.6984 0.43381 0.000 0.060 0.144 0.568 0.076 0.152
#> GSM1233100 2 0.8319 -0.10062 0.000 0.340 0.136 0.260 0.068 0.196
#> GSM1233104 4 0.3219 0.57536 0.000 0.056 0.060 0.852 0.000 0.032
#> GSM1233106 6 0.1926 0.59321 0.000 0.000 0.000 0.068 0.020 0.912
#> GSM1233111 5 0.5737 0.46828 0.196 0.164 0.024 0.004 0.612 0.000
#> GSM1233122 2 0.4224 0.56454 0.000 0.684 0.000 0.276 0.004 0.036
#> GSM1233146 2 0.5225 0.56562 0.000 0.696 0.016 0.184 0.044 0.060
#> GSM1232994 2 0.0000 0.75649 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232996 2 0.1180 0.75631 0.000 0.960 0.012 0.016 0.000 0.012
#> GSM1232997 2 0.3373 0.63266 0.000 0.744 0.000 0.008 0.000 0.248
#> GSM1232998 4 0.4411 0.54928 0.000 0.160 0.016 0.740 0.000 0.084
#> GSM1232999 2 0.1151 0.75138 0.000 0.956 0.012 0.032 0.000 0.000
#> GSM1233000 2 0.1480 0.75719 0.000 0.940 0.000 0.040 0.000 0.020
#> GSM1233004 3 0.1933 0.55847 0.000 0.000 0.920 0.032 0.004 0.044
#> GSM1233011 4 0.6722 0.27994 0.000 0.036 0.244 0.496 0.016 0.208
#> GSM1233012 6 0.6132 0.23569 0.000 0.316 0.000 0.256 0.004 0.424
#> GSM1233023 6 0.2263 0.57095 0.000 0.100 0.000 0.016 0.000 0.884
#> GSM1233027 2 0.0632 0.75572 0.000 0.976 0.000 0.024 0.000 0.000
#> GSM1233033 5 0.4717 0.47388 0.032 0.012 0.004 0.272 0.672 0.008
#> GSM1233036 6 0.2958 0.58644 0.000 0.012 0.004 0.096 0.028 0.860
#> GSM1233037 6 0.1297 0.59467 0.000 0.012 0.000 0.040 0.000 0.948
#> GSM1233041 5 0.3847 0.23100 0.456 0.000 0.000 0.000 0.544 0.000
#> GSM1233045 2 0.7800 0.28540 0.000 0.484 0.140 0.132 0.088 0.156
#> GSM1233047 6 0.1549 0.57901 0.000 0.000 0.044 0.020 0.000 0.936
#> GSM1233050 1 0.0405 0.84642 0.988 0.000 0.000 0.008 0.000 0.004
#> GSM1233052 6 0.9824 -0.10338 0.128 0.200 0.140 0.136 0.148 0.248
#> GSM1233053 1 0.0837 0.83800 0.972 0.000 0.020 0.004 0.004 0.000
#> GSM1233055 1 0.0146 0.85021 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1233061 6 0.4038 0.50350 0.000 0.000 0.156 0.072 0.008 0.764
#> GSM1233063 5 0.6045 0.55032 0.088 0.004 0.088 0.192 0.624 0.004
#> GSM1233065 6 0.6875 0.18975 0.000 0.272 0.272 0.036 0.008 0.412
#> GSM1233070 4 0.5742 0.40407 0.000 0.252 0.092 0.608 0.004 0.044
#> GSM1233077 3 0.2962 0.64783 0.000 0.000 0.848 0.084 0.000 0.068
#> GSM1233081 3 0.3868 0.08144 0.000 0.000 0.508 0.000 0.000 0.492
#> GSM1233084 1 0.3862 -0.16179 0.524 0.000 0.000 0.000 0.476 0.000
#> GSM1233087 4 0.5535 0.54203 0.000 0.060 0.132 0.700 0.076 0.032
#> GSM1233089 2 0.3977 0.56397 0.000 0.692 0.000 0.284 0.004 0.020
#> GSM1233099 5 0.6366 -0.29505 0.000 0.000 0.148 0.372 0.440 0.040
#> GSM1233112 4 0.5901 0.36339 0.000 0.000 0.268 0.548 0.164 0.020
#> GSM1233085 3 0.7017 0.38852 0.032 0.000 0.484 0.072 0.112 0.300
#> GSM1233098 2 0.4667 0.31599 0.000 0.576 0.004 0.040 0.000 0.380
#> GSM1233114 5 0.1663 0.48165 0.000 0.000 0.000 0.088 0.912 0.000
#> GSM1233119 4 0.6562 0.40439 0.000 0.004 0.180 0.488 0.284 0.044
#> GSM1233129 6 0.1141 0.59002 0.000 0.052 0.000 0.000 0.000 0.948
#> GSM1233132 1 0.4682 0.30531 0.540 0.000 0.000 0.036 0.420 0.004
#> GSM1233139 2 0.1765 0.75779 0.000 0.924 0.000 0.024 0.000 0.052
#> GSM1233143 6 0.3555 0.48933 0.000 0.000 0.000 0.280 0.008 0.712
#> GSM1233145 5 0.3986 0.32733 0.020 0.000 0.000 0.316 0.664 0.000
#> GSM1233067 6 0.5983 0.35394 0.000 0.020 0.172 0.244 0.004 0.560
#> GSM1233069 6 0.4089 -0.07773 0.000 0.000 0.468 0.008 0.000 0.524
#> GSM1233072 2 0.4106 0.53176 0.000 0.664 0.000 0.312 0.004 0.020
#> GSM1233086 6 0.6418 0.16739 0.000 0.000 0.300 0.280 0.016 0.404
#> GSM1233102 4 0.3883 0.51382 0.000 0.000 0.044 0.752 0.200 0.004
#> GSM1233103 2 0.7850 -0.00796 0.000 0.316 0.008 0.220 0.256 0.200
#> GSM1233107 4 0.7209 0.14114 0.000 0.272 0.000 0.332 0.312 0.084
#> GSM1233108 3 0.2852 0.63773 0.080 0.000 0.856 0.000 0.000 0.064
#> GSM1233109 3 0.2581 0.65539 0.000 0.000 0.856 0.016 0.000 0.128
#> GSM1233110 3 0.3050 0.60925 0.000 0.000 0.764 0.000 0.000 0.236
#> GSM1233113 2 0.1908 0.75445 0.000 0.916 0.000 0.028 0.000 0.056
#> GSM1233116 3 0.7452 0.01330 0.000 0.276 0.348 0.284 0.012 0.080
#> GSM1233120 4 0.6135 0.38114 0.000 0.000 0.128 0.512 0.320 0.040
#> GSM1233121 3 0.3728 0.64607 0.000 0.004 0.784 0.060 0.000 0.152
#> GSM1233123 3 0.3050 0.60925 0.000 0.000 0.764 0.000 0.000 0.236
#> GSM1233124 6 0.5947 0.29505 0.000 0.004 0.280 0.168 0.012 0.536
#> GSM1233125 3 0.3215 0.48606 0.004 0.000 0.756 0.000 0.240 0.000
#> GSM1233126 4 0.1969 0.56680 0.000 0.004 0.052 0.920 0.004 0.020
#> GSM1233127 4 0.6365 0.02617 0.000 0.368 0.000 0.384 0.232 0.016
#> GSM1233128 5 0.5336 0.44468 0.244 0.000 0.168 0.000 0.588 0.000
#> GSM1233130 3 0.2912 0.65496 0.000 0.000 0.852 0.072 0.000 0.076
#> GSM1233131 5 0.6462 0.44408 0.028 0.000 0.152 0.104 0.612 0.104
#> GSM1233133 3 0.3592 0.50234 0.000 0.000 0.656 0.000 0.000 0.344
#> GSM1233134 6 0.3284 0.45218 0.000 0.000 0.196 0.020 0.000 0.784
#> GSM1233135 6 0.4491 0.10984 0.000 0.000 0.388 0.036 0.000 0.576
#> GSM1233136 3 0.2667 0.62756 0.000 0.000 0.852 0.128 0.000 0.020
#> GSM1233137 6 0.4308 0.39619 0.120 0.000 0.152 0.000 0.000 0.728
#> GSM1233138 4 0.2698 0.56693 0.000 0.016 0.092 0.872 0.000 0.020
#> GSM1233140 5 0.4308 0.23874 0.008 0.000 0.008 0.000 0.532 0.452
#> GSM1233141 4 0.7426 -0.04043 0.000 0.132 0.000 0.360 0.240 0.268
#> GSM1233142 2 0.7247 0.06233 0.000 0.372 0.008 0.296 0.256 0.068
#> GSM1233144 3 0.3288 0.58768 0.000 0.000 0.724 0.000 0.000 0.276
#> GSM1233147 4 0.4178 0.32914 0.000 0.000 0.372 0.608 0.000 0.020
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> SD:pam 118 9.19e-01 0.9459 1.0000 2
#> SD:pam 126 8.68e-07 0.3338 0.0630 3
#> SD:pam 114 5.61e-06 0.2370 0.0433 4
#> SD:pam 93 1.62e-07 0.0734 0.0275 5
#> SD:pam 89 2.96e-06 0.1674 0.0539 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 51941 rows and 156 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 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.410 0.822 0.864 0.4152 0.581 0.581
#> 3 3 0.299 0.472 0.705 0.4087 0.718 0.571
#> 4 4 0.524 0.599 0.748 0.2148 0.714 0.425
#> 5 5 0.628 0.564 0.789 0.0789 0.794 0.418
#> 6 6 0.648 0.553 0.753 0.0472 0.917 0.682
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.5294 0.8626 0.120 0.880
#> GSM1233002 2 0.1414 0.8727 0.020 0.980
#> GSM1233003 1 0.7602 0.8919 0.780 0.220
#> GSM1233014 2 0.1414 0.8727 0.020 0.980
#> GSM1233015 2 0.9635 -0.0276 0.388 0.612
#> GSM1233016 2 0.2778 0.8717 0.048 0.952
#> GSM1233024 2 0.1414 0.8727 0.020 0.980
#> GSM1233049 1 0.6148 0.8624 0.848 0.152
#> GSM1233064 2 0.4690 0.8694 0.100 0.900
#> GSM1233068 2 0.2948 0.8708 0.052 0.948
#> GSM1233073 2 0.1414 0.8727 0.020 0.980
#> GSM1233093 1 0.7528 0.8939 0.784 0.216
#> GSM1233115 1 0.7602 0.8919 0.780 0.220
#> GSM1232992 2 0.1633 0.8784 0.024 0.976
#> GSM1232993 2 0.1414 0.8727 0.020 0.980
#> GSM1233005 2 0.3584 0.8769 0.068 0.932
#> GSM1233007 2 0.3584 0.8759 0.068 0.932
#> GSM1233010 2 0.1414 0.8727 0.020 0.980
#> GSM1233013 2 0.2778 0.8774 0.048 0.952
#> GSM1233018 2 0.3733 0.8754 0.072 0.928
#> GSM1233019 2 0.1414 0.8727 0.020 0.980
#> GSM1233021 2 0.1633 0.8784 0.024 0.976
#> GSM1233025 2 0.1843 0.8734 0.028 0.972
#> GSM1233029 2 0.0938 0.8762 0.012 0.988
#> GSM1233030 2 0.1414 0.8784 0.020 0.980
#> GSM1233031 2 0.1414 0.8727 0.020 0.980
#> GSM1233032 1 0.4939 0.8291 0.892 0.108
#> GSM1233035 2 0.1414 0.8727 0.020 0.980
#> GSM1233038 1 0.7745 0.8874 0.772 0.228
#> GSM1233039 2 0.4431 0.8717 0.092 0.908
#> GSM1233042 2 0.1414 0.8727 0.020 0.980
#> GSM1233043 2 0.1414 0.8727 0.020 0.980
#> GSM1233044 2 0.4690 0.8754 0.100 0.900
#> GSM1233046 2 0.2043 0.8732 0.032 0.968
#> GSM1233051 1 0.7745 0.8835 0.772 0.228
#> GSM1233054 2 0.6712 0.8334 0.176 0.824
#> GSM1233057 2 0.6531 0.8376 0.168 0.832
#> GSM1233060 2 0.1414 0.8727 0.020 0.980
#> GSM1233062 2 0.1414 0.8727 0.020 0.980
#> GSM1233075 2 0.7883 0.7901 0.236 0.764
#> GSM1233078 2 0.8081 0.7801 0.248 0.752
#> GSM1233079 1 0.4562 0.8095 0.904 0.096
#> GSM1233082 2 0.9833 -0.0742 0.424 0.576
#> GSM1233083 1 0.7528 0.8939 0.784 0.216
#> GSM1233091 2 0.3114 0.8766 0.056 0.944
#> GSM1233095 1 0.7528 0.8939 0.784 0.216
#> GSM1233096 1 0.7950 0.8790 0.760 0.240
#> GSM1233101 1 0.7453 0.8928 0.788 0.212
#> GSM1233105 1 0.8267 0.8699 0.740 0.260
#> GSM1233117 2 0.5059 0.8656 0.112 0.888
#> GSM1233118 2 0.6712 0.8334 0.176 0.824
#> GSM1233001 2 0.6623 0.8355 0.172 0.828
#> GSM1233006 2 0.1414 0.8727 0.020 0.980
#> GSM1233008 2 0.4815 0.8682 0.104 0.896
#> GSM1233009 2 0.0672 0.8758 0.008 0.992
#> GSM1233017 2 0.1414 0.8727 0.020 0.980
#> GSM1233020 2 0.4815 0.8682 0.104 0.896
#> GSM1233022 2 0.1414 0.8727 0.020 0.980
#> GSM1233026 2 0.2778 0.8719 0.048 0.952
#> GSM1233028 2 0.1633 0.8726 0.024 0.976
#> GSM1233034 2 0.3114 0.8766 0.056 0.944
#> GSM1233040 1 0.6343 0.8671 0.840 0.160
#> GSM1233048 1 0.7528 0.8939 0.784 0.216
#> GSM1233056 1 0.7528 0.8939 0.784 0.216
#> GSM1233058 2 0.1414 0.8727 0.020 0.980
#> GSM1233059 1 0.7528 0.8939 0.784 0.216
#> GSM1233066 2 0.8081 0.7801 0.248 0.752
#> GSM1233071 2 0.1414 0.8727 0.020 0.980
#> GSM1233074 2 0.7056 0.8231 0.192 0.808
#> GSM1233076 2 0.4562 0.8708 0.096 0.904
#> GSM1233080 1 0.7528 0.8939 0.784 0.216
#> GSM1233088 2 0.5294 0.8636 0.120 0.880
#> GSM1233090 1 0.7528 0.8939 0.784 0.216
#> GSM1233092 2 0.1414 0.8727 0.020 0.980
#> GSM1233094 2 0.1414 0.8727 0.020 0.980
#> GSM1233097 2 0.1414 0.8727 0.020 0.980
#> GSM1233100 2 0.1414 0.8727 0.020 0.980
#> GSM1233104 2 0.1414 0.8727 0.020 0.980
#> GSM1233106 2 0.9850 -0.0925 0.428 0.572
#> GSM1233111 1 0.7528 0.8939 0.784 0.216
#> GSM1233122 2 0.3114 0.8771 0.056 0.944
#> GSM1233146 2 0.1414 0.8727 0.020 0.980
#> GSM1232994 2 0.2778 0.8719 0.048 0.952
#> GSM1232996 2 0.4815 0.8682 0.104 0.896
#> GSM1232997 2 0.6973 0.8259 0.188 0.812
#> GSM1232998 2 0.1414 0.8727 0.020 0.980
#> GSM1232999 2 0.1414 0.8727 0.020 0.980
#> GSM1233000 2 0.1414 0.8727 0.020 0.980
#> GSM1233004 2 0.5842 0.8541 0.140 0.860
#> GSM1233011 2 0.5408 0.8609 0.124 0.876
#> GSM1233012 2 0.6623 0.8355 0.172 0.828
#> GSM1233023 2 0.6623 0.8355 0.172 0.828
#> GSM1233027 2 0.1414 0.8727 0.020 0.980
#> GSM1233033 1 0.8016 0.8758 0.756 0.244
#> GSM1233036 2 0.6531 0.8376 0.168 0.832
#> GSM1233037 2 0.5178 0.8638 0.116 0.884
#> GSM1233041 1 0.7528 0.8939 0.784 0.216
#> GSM1233045 2 0.1414 0.8727 0.020 0.980
#> GSM1233047 1 0.7528 0.6452 0.784 0.216
#> GSM1233050 1 0.7528 0.8939 0.784 0.216
#> GSM1233052 1 0.9635 0.7001 0.612 0.388
#> GSM1233053 1 0.4562 0.8095 0.904 0.096
#> GSM1233055 1 0.7528 0.8939 0.784 0.216
#> GSM1233061 2 0.8081 0.7801 0.248 0.752
#> GSM1233063 1 0.7528 0.8939 0.784 0.216
#> GSM1233065 2 0.7376 0.8119 0.208 0.792
#> GSM1233070 2 0.1843 0.8735 0.028 0.972
#> GSM1233077 2 0.8081 0.7801 0.248 0.752
#> GSM1233081 1 0.1414 0.7534 0.980 0.020
#> GSM1233084 1 0.7528 0.8939 0.784 0.216
#> GSM1233087 2 0.5059 0.8022 0.112 0.888
#> GSM1233089 2 0.4815 0.8682 0.104 0.896
#> GSM1233099 2 0.1414 0.8727 0.020 0.980
#> GSM1233112 1 0.7528 0.8939 0.784 0.216
#> GSM1233085 1 0.1414 0.7534 0.980 0.020
#> GSM1233098 2 0.4431 0.8718 0.092 0.908
#> GSM1233114 1 0.7528 0.8939 0.784 0.216
#> GSM1233119 2 0.1414 0.8727 0.020 0.980
#> GSM1233129 2 0.6712 0.8333 0.176 0.824
#> GSM1233132 1 0.8016 0.8758 0.756 0.244
#> GSM1233139 2 0.3274 0.8766 0.060 0.940
#> GSM1233143 2 0.6887 0.8286 0.184 0.816
#> GSM1233145 1 0.7745 0.8874 0.772 0.228
#> GSM1233067 2 0.8081 0.7801 0.248 0.752
#> GSM1233069 2 0.8081 0.7801 0.248 0.752
#> GSM1233072 2 0.4815 0.8682 0.104 0.896
#> GSM1233086 2 0.7674 0.8001 0.224 0.776
#> GSM1233102 1 0.8081 0.8752 0.752 0.248
#> GSM1233103 2 0.2603 0.8723 0.044 0.956
#> GSM1233107 2 0.1414 0.8727 0.020 0.980
#> GSM1233108 1 0.1414 0.7534 0.980 0.020
#> GSM1233109 1 0.6247 0.6613 0.844 0.156
#> GSM1233110 2 0.8081 0.7801 0.248 0.752
#> GSM1233113 2 0.8016 0.7835 0.244 0.756
#> GSM1233116 2 0.8081 0.7801 0.248 0.752
#> GSM1233120 1 0.8016 0.8758 0.756 0.244
#> GSM1233121 2 0.8081 0.7801 0.248 0.752
#> GSM1233123 2 0.8081 0.7801 0.248 0.752
#> GSM1233124 2 0.8081 0.7801 0.248 0.752
#> GSM1233125 1 0.1414 0.7534 0.980 0.020
#> GSM1233126 2 0.1414 0.8727 0.020 0.980
#> GSM1233127 2 0.1633 0.8726 0.024 0.976
#> GSM1233128 1 0.7528 0.8939 0.784 0.216
#> GSM1233130 2 0.8081 0.7801 0.248 0.752
#> GSM1233131 1 0.8861 0.8277 0.696 0.304
#> GSM1233133 1 0.2236 0.7508 0.964 0.036
#> GSM1233134 2 0.8081 0.7801 0.248 0.752
#> GSM1233135 2 0.8081 0.7801 0.248 0.752
#> GSM1233136 2 0.8081 0.7801 0.248 0.752
#> GSM1233137 1 0.9710 0.0284 0.600 0.400
#> GSM1233138 2 0.1414 0.8727 0.020 0.980
#> GSM1233140 1 0.5059 0.8038 0.888 0.112
#> GSM1233141 2 0.4431 0.8749 0.092 0.908
#> GSM1233142 2 0.1843 0.8765 0.028 0.972
#> GSM1233144 1 0.9881 -0.1169 0.564 0.436
#> GSM1233147 2 0.4690 0.8739 0.100 0.900
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.6174 0.524142 0.168 0.768 0.064
#> GSM1233002 2 0.5926 0.484508 0.356 0.644 0.000
#> GSM1233003 1 0.9812 0.772680 0.412 0.248 0.340
#> GSM1233014 2 0.3192 0.642253 0.112 0.888 0.000
#> GSM1233015 2 0.9329 -0.241006 0.180 0.488 0.332
#> GSM1233016 2 0.6126 0.468568 0.400 0.600 0.000
#> GSM1233024 2 0.0892 0.665559 0.020 0.980 0.000
#> GSM1233049 1 0.7169 0.765431 0.568 0.028 0.404
#> GSM1233064 2 0.5688 0.547241 0.168 0.788 0.044
#> GSM1233068 2 0.3966 0.644190 0.100 0.876 0.024
#> GSM1233073 2 0.6215 0.450872 0.428 0.572 0.000
#> GSM1233093 1 0.9243 0.892853 0.492 0.168 0.340
#> GSM1233115 1 0.9281 0.828774 0.488 0.172 0.340
#> GSM1232992 2 0.1964 0.658865 0.056 0.944 0.000
#> GSM1232993 2 0.0424 0.667044 0.008 0.992 0.000
#> GSM1233005 2 0.1964 0.659665 0.056 0.944 0.000
#> GSM1233007 2 0.4110 0.619637 0.152 0.844 0.004
#> GSM1233010 2 0.6008 0.479330 0.372 0.628 0.000
#> GSM1233013 2 0.1964 0.658891 0.056 0.944 0.000
#> GSM1233018 2 0.2356 0.654081 0.072 0.928 0.000
#> GSM1233019 2 0.1031 0.665954 0.024 0.976 0.000
#> GSM1233021 2 0.1163 0.667175 0.028 0.972 0.000
#> GSM1233025 2 0.6442 0.452159 0.432 0.564 0.004
#> GSM1233029 2 0.1031 0.665433 0.024 0.976 0.000
#> GSM1233030 2 0.0747 0.666996 0.016 0.984 0.000
#> GSM1233031 2 0.0747 0.668042 0.016 0.984 0.000
#> GSM1233032 3 0.6906 -0.251056 0.324 0.032 0.644
#> GSM1233035 2 0.1453 0.667795 0.008 0.968 0.024
#> GSM1233038 1 0.9579 0.706428 0.452 0.208 0.340
#> GSM1233039 2 0.4465 0.596892 0.176 0.820 0.004
#> GSM1233042 2 0.6215 0.450872 0.428 0.572 0.000
#> GSM1233043 2 0.6126 0.481526 0.400 0.600 0.000
#> GSM1233044 2 0.7759 0.508298 0.180 0.676 0.144
#> GSM1233046 2 0.6601 0.278277 0.028 0.676 0.296
#> GSM1233051 1 0.9162 0.829042 0.500 0.160 0.340
#> GSM1233054 3 0.9734 0.404100 0.224 0.376 0.400
#> GSM1233057 2 0.9425 -0.346489 0.176 0.432 0.392
#> GSM1233060 2 0.0592 0.667456 0.012 0.988 0.000
#> GSM1233062 2 0.0592 0.667012 0.012 0.988 0.000
#> GSM1233075 3 0.6510 0.587417 0.012 0.364 0.624
#> GSM1233078 3 0.6129 0.610140 0.008 0.324 0.668
#> GSM1233079 3 0.6541 -0.186197 0.304 0.024 0.672
#> GSM1233082 2 0.8288 0.047145 0.096 0.572 0.332
#> GSM1233083 1 0.8173 0.820279 0.552 0.080 0.368
#> GSM1233091 2 0.4465 0.596892 0.176 0.820 0.004
#> GSM1233095 1 0.8683 0.882789 0.540 0.120 0.340
#> GSM1233096 1 0.9550 0.863396 0.456 0.204 0.340
#> GSM1233101 1 0.8261 0.850592 0.568 0.092 0.340
#> GSM1233105 2 0.8288 0.020178 0.096 0.572 0.332
#> GSM1233117 2 0.4749 0.589849 0.172 0.816 0.012
#> GSM1233118 2 0.9317 -0.315275 0.164 0.448 0.388
#> GSM1233001 2 0.9243 -0.198771 0.168 0.492 0.340
#> GSM1233006 2 0.2959 0.643177 0.100 0.900 0.000
#> GSM1233008 2 0.2711 0.646819 0.088 0.912 0.000
#> GSM1233009 2 0.0829 0.666538 0.012 0.984 0.004
#> GSM1233017 2 0.0237 0.666690 0.004 0.996 0.000
#> GSM1233020 2 0.4062 0.596537 0.164 0.836 0.000
#> GSM1233022 2 0.2537 0.649896 0.080 0.920 0.000
#> GSM1233026 2 0.5902 0.555942 0.316 0.680 0.004
#> GSM1233028 2 0.2066 0.666428 0.060 0.940 0.000
#> GSM1233034 2 0.3752 0.614112 0.144 0.856 0.000
#> GSM1233040 1 0.8043 0.834150 0.556 0.072 0.372
#> GSM1233048 1 0.9457 0.871607 0.468 0.192 0.340
#> GSM1233056 1 0.8261 0.874528 0.568 0.092 0.340
#> GSM1233058 2 0.6079 0.475041 0.388 0.612 0.000
#> GSM1233059 1 0.9243 0.892853 0.492 0.168 0.340
#> GSM1233066 3 0.8716 0.534678 0.120 0.348 0.532
#> GSM1233071 2 0.0237 0.666376 0.000 0.996 0.004
#> GSM1233074 3 0.8754 0.497157 0.116 0.376 0.508
#> GSM1233076 2 0.4521 0.601789 0.180 0.816 0.004
#> GSM1233080 1 0.9032 0.894353 0.512 0.148 0.340
#> GSM1233088 2 0.8792 0.092293 0.176 0.580 0.244
#> GSM1233090 1 0.8683 0.882508 0.540 0.120 0.340
#> GSM1233092 2 0.3267 0.641717 0.116 0.884 0.000
#> GSM1233094 2 0.6215 0.450872 0.428 0.572 0.000
#> GSM1233097 2 0.6225 0.451216 0.432 0.568 0.000
#> GSM1233100 2 0.5882 0.493338 0.348 0.652 0.000
#> GSM1233104 2 0.5016 0.595622 0.240 0.760 0.000
#> GSM1233106 2 0.9306 -0.221071 0.176 0.488 0.336
#> GSM1233111 1 0.9203 0.894578 0.496 0.164 0.340
#> GSM1233122 2 0.2261 0.653017 0.068 0.932 0.000
#> GSM1233146 2 0.6026 0.476828 0.376 0.624 0.000
#> GSM1232994 2 0.0892 0.665098 0.020 0.980 0.000
#> GSM1232996 2 0.2959 0.643345 0.100 0.900 0.000
#> GSM1232997 2 0.9302 -0.381213 0.160 0.424 0.416
#> GSM1232998 2 0.3116 0.642237 0.108 0.892 0.000
#> GSM1232999 2 0.2261 0.652397 0.068 0.932 0.000
#> GSM1233000 2 0.0237 0.666690 0.004 0.996 0.000
#> GSM1233004 3 0.8638 -0.172714 0.184 0.216 0.600
#> GSM1233011 2 0.6318 0.528684 0.172 0.760 0.068
#> GSM1233012 2 0.9167 -0.144433 0.168 0.512 0.320
#> GSM1233023 2 0.9256 -0.210075 0.168 0.488 0.344
#> GSM1233027 2 0.2356 0.651405 0.072 0.928 0.000
#> GSM1233033 2 0.9967 -0.662267 0.296 0.364 0.340
#> GSM1233036 2 0.8907 -0.000332 0.168 0.560 0.272
#> GSM1233037 2 0.9702 -0.287895 0.232 0.440 0.328
#> GSM1233041 1 0.9243 0.892853 0.492 0.168 0.340
#> GSM1233045 2 0.5621 0.544855 0.308 0.692 0.000
#> GSM1233047 3 0.5803 0.075957 0.212 0.028 0.760
#> GSM1233050 1 0.8790 0.887879 0.532 0.128 0.340
#> GSM1233052 2 0.7001 0.101807 0.032 0.628 0.340
#> GSM1233053 3 0.6819 -0.253341 0.328 0.028 0.644
#> GSM1233055 1 0.9077 0.856049 0.508 0.152 0.340
#> GSM1233061 3 0.8836 0.523533 0.128 0.352 0.520
#> GSM1233063 1 0.9203 0.894578 0.496 0.164 0.340
#> GSM1233065 3 0.9149 0.397957 0.144 0.416 0.440
#> GSM1233070 2 0.0237 0.666904 0.004 0.996 0.000
#> GSM1233077 3 0.5810 0.611360 0.000 0.336 0.664
#> GSM1233081 3 0.2448 0.281966 0.076 0.000 0.924
#> GSM1233084 1 0.9203 0.895188 0.496 0.164 0.340
#> GSM1233087 2 0.8994 0.263330 0.184 0.556 0.260
#> GSM1233089 2 0.4062 0.596537 0.164 0.836 0.000
#> GSM1233099 2 0.7203 0.435763 0.416 0.556 0.028
#> GSM1233112 1 0.8213 0.855530 0.568 0.088 0.344
#> GSM1233085 3 0.2165 0.291444 0.064 0.000 0.936
#> GSM1233098 2 0.4062 0.596537 0.164 0.836 0.000
#> GSM1233114 1 0.9579 0.830367 0.452 0.208 0.340
#> GSM1233119 2 0.5835 0.545447 0.340 0.660 0.000
#> GSM1233129 2 0.9282 -0.263790 0.164 0.468 0.368
#> GSM1233132 2 0.9752 -0.456299 0.236 0.424 0.340
#> GSM1233139 2 0.2400 0.654126 0.064 0.932 0.004
#> GSM1233143 2 0.9331 -0.210958 0.176 0.480 0.344
#> GSM1233145 3 0.9999 -0.582200 0.332 0.328 0.340
#> GSM1233067 3 0.6404 0.605320 0.012 0.344 0.644
#> GSM1233069 3 0.5810 0.611360 0.000 0.336 0.664
#> GSM1233072 2 0.4062 0.596537 0.164 0.836 0.000
#> GSM1233086 2 0.9046 -0.137123 0.152 0.516 0.332
#> GSM1233102 2 0.9268 -0.049915 0.172 0.492 0.336
#> GSM1233103 2 0.1878 0.665506 0.044 0.952 0.004
#> GSM1233107 2 0.2400 0.663877 0.064 0.932 0.004
#> GSM1233108 3 0.1643 0.291600 0.044 0.000 0.956
#> GSM1233109 3 0.1129 0.330895 0.020 0.004 0.976
#> GSM1233110 3 0.5810 0.611360 0.000 0.336 0.664
#> GSM1233113 3 0.6651 0.606130 0.020 0.340 0.640
#> GSM1233116 3 0.6566 0.598749 0.016 0.348 0.636
#> GSM1233120 2 0.9399 -0.085928 0.188 0.480 0.332
#> GSM1233121 3 0.5810 0.611360 0.000 0.336 0.664
#> GSM1233123 3 0.5810 0.611360 0.000 0.336 0.664
#> GSM1233124 3 0.7724 0.573002 0.060 0.352 0.588
#> GSM1233125 3 0.1643 0.291600 0.044 0.000 0.956
#> GSM1233126 2 0.5058 0.597439 0.244 0.756 0.000
#> GSM1233127 2 0.1529 0.663555 0.040 0.960 0.000
#> GSM1233128 1 0.8261 0.855113 0.568 0.092 0.340
#> GSM1233130 3 0.6008 0.610402 0.004 0.332 0.664
#> GSM1233131 2 0.8013 0.004341 0.080 0.588 0.332
#> GSM1233133 3 0.0983 0.335184 0.016 0.004 0.980
#> GSM1233134 3 0.5810 0.611360 0.000 0.336 0.664
#> GSM1233135 3 0.5810 0.611360 0.000 0.336 0.664
#> GSM1233136 3 0.5810 0.611360 0.000 0.336 0.664
#> GSM1233137 3 0.0661 0.342703 0.008 0.004 0.988
#> GSM1233138 2 0.4121 0.628029 0.168 0.832 0.000
#> GSM1233140 3 0.6539 -0.138507 0.288 0.028 0.684
#> GSM1233141 2 0.4178 0.616482 0.172 0.828 0.000
#> GSM1233142 2 0.1031 0.668203 0.024 0.976 0.000
#> GSM1233144 3 0.0237 0.350116 0.000 0.004 0.996
#> GSM1233147 2 0.4978 0.602710 0.216 0.780 0.004
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.7024 0.4292 0.128 0.512 0.360 0.000
#> GSM1233002 4 0.4713 0.4292 0.000 0.360 0.000 0.640
#> GSM1233003 1 0.4134 0.6745 0.740 0.000 0.000 0.260
#> GSM1233014 4 0.0895 0.7592 0.000 0.020 0.004 0.976
#> GSM1233015 2 0.7968 0.4907 0.280 0.416 0.004 0.300
#> GSM1233016 4 0.2101 0.7469 0.012 0.060 0.000 0.928
#> GSM1233024 2 0.4564 0.5893 0.000 0.672 0.000 0.328
#> GSM1233049 1 0.1022 0.8162 0.968 0.000 0.032 0.000
#> GSM1233064 2 0.6951 0.4904 0.132 0.544 0.324 0.000
#> GSM1233068 2 0.8048 0.6205 0.148 0.536 0.048 0.268
#> GSM1233073 4 0.1389 0.7584 0.000 0.048 0.000 0.952
#> GSM1233093 1 0.0000 0.8332 1.000 0.000 0.000 0.000
#> GSM1233115 1 0.0707 0.8259 0.980 0.020 0.000 0.000
#> GSM1232992 2 0.5668 0.6492 0.048 0.652 0.000 0.300
#> GSM1232993 2 0.4608 0.6231 0.000 0.692 0.004 0.304
#> GSM1233005 2 0.5157 0.6373 0.016 0.676 0.004 0.304
#> GSM1233007 2 0.8068 0.5277 0.088 0.552 0.264 0.096
#> GSM1233010 4 0.4643 0.4640 0.000 0.344 0.000 0.656
#> GSM1233013 2 0.5883 0.6500 0.060 0.640 0.000 0.300
#> GSM1233018 2 0.6937 0.6361 0.124 0.572 0.004 0.300
#> GSM1233019 2 0.4454 0.6165 0.000 0.692 0.000 0.308
#> GSM1233021 2 0.4584 0.6290 0.004 0.696 0.000 0.300
#> GSM1233025 4 0.0188 0.7540 0.000 0.004 0.000 0.996
#> GSM1233029 2 0.4406 0.6249 0.000 0.700 0.000 0.300
#> GSM1233030 2 0.4406 0.6249 0.000 0.700 0.000 0.300
#> GSM1233031 2 0.5661 0.3185 0.008 0.544 0.012 0.436
#> GSM1233032 1 0.4730 0.1914 0.636 0.000 0.364 0.000
#> GSM1233035 2 0.5304 0.6247 0.012 0.672 0.012 0.304
#> GSM1233038 4 0.0817 0.7490 0.024 0.000 0.000 0.976
#> GSM1233039 2 0.7164 0.4727 0.156 0.524 0.320 0.000
#> GSM1233042 4 0.2469 0.7366 0.000 0.108 0.000 0.892
#> GSM1233043 4 0.3311 0.6840 0.000 0.172 0.000 0.828
#> GSM1233044 2 0.7129 0.4340 0.140 0.504 0.356 0.000
#> GSM1233046 2 0.5774 0.6286 0.040 0.640 0.004 0.316
#> GSM1233051 1 0.0895 0.8247 0.976 0.020 0.004 0.000
#> GSM1233054 3 0.3356 0.6065 0.176 0.000 0.824 0.000
#> GSM1233057 3 0.3688 0.5808 0.208 0.000 0.792 0.000
#> GSM1233060 2 0.5068 0.6219 0.004 0.676 0.012 0.308
#> GSM1233062 2 0.4431 0.6210 0.000 0.696 0.000 0.304
#> GSM1233075 3 0.6141 0.6928 0.076 0.300 0.624 0.000
#> GSM1233078 3 0.4584 0.7037 0.004 0.300 0.696 0.000
#> GSM1233079 3 0.7474 0.5421 0.280 0.220 0.500 0.000
#> GSM1233082 2 0.7521 0.5580 0.220 0.488 0.000 0.292
#> GSM1233083 1 0.5165 0.3007 0.512 0.000 0.004 0.484
#> GSM1233091 2 0.7164 0.4727 0.156 0.524 0.320 0.000
#> GSM1233095 1 0.0000 0.8332 1.000 0.000 0.000 0.000
#> GSM1233096 1 0.4584 0.3772 0.696 0.004 0.000 0.300
#> GSM1233101 1 0.0000 0.8332 1.000 0.000 0.000 0.000
#> GSM1233105 4 0.2596 0.7530 0.024 0.068 0.000 0.908
#> GSM1233117 2 0.7538 0.4501 0.112 0.512 0.352 0.024
#> GSM1233118 3 0.3088 0.6289 0.128 0.008 0.864 0.000
#> GSM1233001 3 0.5003 0.5664 0.148 0.084 0.768 0.000
#> GSM1233006 4 0.4855 0.4422 0.000 0.352 0.004 0.644
#> GSM1233008 2 0.6892 0.6377 0.120 0.576 0.004 0.300
#> GSM1233009 2 0.5657 0.6456 0.032 0.660 0.008 0.300
#> GSM1233017 2 0.4406 0.6249 0.000 0.700 0.000 0.300
#> GSM1233020 2 0.6955 0.5155 0.124 0.568 0.304 0.004
#> GSM1233022 4 0.3208 0.7017 0.004 0.148 0.000 0.848
#> GSM1233026 2 0.6876 0.6037 0.116 0.532 0.000 0.352
#> GSM1233028 2 0.4819 0.5824 0.004 0.652 0.000 0.344
#> GSM1233034 2 0.8172 0.5372 0.156 0.536 0.252 0.056
#> GSM1233040 1 0.0000 0.8332 1.000 0.000 0.000 0.000
#> GSM1233048 1 0.4008 0.5270 0.756 0.000 0.000 0.244
#> GSM1233056 1 0.2760 0.7834 0.872 0.000 0.000 0.128
#> GSM1233058 4 0.4679 0.4477 0.000 0.352 0.000 0.648
#> GSM1233059 1 0.0000 0.8332 1.000 0.000 0.000 0.000
#> GSM1233066 3 0.1557 0.6659 0.056 0.000 0.944 0.000
#> GSM1233071 2 0.5022 0.6294 0.004 0.684 0.012 0.300
#> GSM1233074 3 0.4458 0.6646 0.116 0.076 0.808 0.000
#> GSM1233076 3 0.9516 -0.3288 0.120 0.324 0.336 0.220
#> GSM1233080 1 0.0000 0.8332 1.000 0.000 0.000 0.000
#> GSM1233088 3 0.5657 0.5185 0.160 0.120 0.720 0.000
#> GSM1233090 1 0.0000 0.8332 1.000 0.000 0.000 0.000
#> GSM1233092 4 0.0937 0.7556 0.000 0.012 0.012 0.976
#> GSM1233094 4 0.1867 0.7522 0.000 0.072 0.000 0.928
#> GSM1233097 4 0.2589 0.7281 0.000 0.116 0.000 0.884
#> GSM1233100 4 0.4872 0.4416 0.004 0.356 0.000 0.640
#> GSM1233104 4 0.0817 0.7595 0.000 0.024 0.000 0.976
#> GSM1233106 1 0.6939 -0.0498 0.540 0.332 0.000 0.128
#> GSM1233111 1 0.0336 0.8318 0.992 0.000 0.000 0.008
#> GSM1233122 2 0.6737 0.6135 0.024 0.668 0.140 0.168
#> GSM1233146 4 0.4713 0.4029 0.000 0.360 0.000 0.640
#> GSM1232994 2 0.4624 0.5683 0.000 0.660 0.000 0.340
#> GSM1232996 2 0.7069 0.6360 0.124 0.568 0.008 0.300
#> GSM1232997 3 0.2944 0.6302 0.128 0.004 0.868 0.000
#> GSM1232998 4 0.1593 0.7558 0.004 0.024 0.016 0.956
#> GSM1232999 4 0.4866 0.3355 0.000 0.404 0.000 0.596
#> GSM1233000 2 0.4406 0.6249 0.000 0.700 0.000 0.300
#> GSM1233004 3 0.8227 0.3102 0.128 0.088 0.556 0.228
#> GSM1233011 2 0.7143 0.3359 0.132 0.460 0.408 0.000
#> GSM1233012 3 0.5624 0.5186 0.128 0.148 0.724 0.000
#> GSM1233023 3 0.5280 0.5520 0.128 0.120 0.752 0.000
#> GSM1233027 4 0.4804 0.3971 0.000 0.384 0.000 0.616
#> GSM1233033 4 0.6309 0.4009 0.336 0.076 0.000 0.588
#> GSM1233036 3 0.6685 0.2695 0.132 0.268 0.600 0.000
#> GSM1233037 3 0.3873 0.5609 0.228 0.000 0.772 0.000
#> GSM1233041 1 0.0000 0.8332 1.000 0.000 0.000 0.000
#> GSM1233045 4 0.4830 0.3347 0.000 0.392 0.000 0.608
#> GSM1233047 3 0.3311 0.6191 0.172 0.000 0.828 0.000
#> GSM1233050 1 0.0000 0.8332 1.000 0.000 0.000 0.000
#> GSM1233052 2 0.7249 0.4221 0.156 0.496 0.000 0.348
#> GSM1233053 1 0.4961 -0.0747 0.552 0.000 0.448 0.000
#> GSM1233055 1 0.3024 0.7703 0.852 0.000 0.000 0.148
#> GSM1233061 3 0.2345 0.6500 0.100 0.000 0.900 0.000
#> GSM1233063 1 0.0188 0.8328 0.996 0.000 0.000 0.004
#> GSM1233065 3 0.4100 0.6085 0.128 0.048 0.824 0.000
#> GSM1233070 2 0.4891 0.6267 0.000 0.680 0.012 0.308
#> GSM1233077 3 0.4584 0.7037 0.004 0.300 0.696 0.000
#> GSM1233081 3 0.5161 0.6926 0.024 0.300 0.676 0.000
#> GSM1233084 1 0.0000 0.8332 1.000 0.000 0.000 0.000
#> GSM1233087 4 0.1174 0.7593 0.012 0.020 0.000 0.968
#> GSM1233089 2 0.7138 0.5045 0.124 0.552 0.316 0.008
#> GSM1233099 4 0.1209 0.7597 0.004 0.032 0.000 0.964
#> GSM1233112 1 0.3443 0.7781 0.848 0.000 0.016 0.136
#> GSM1233085 3 0.5161 0.6926 0.024 0.300 0.676 0.000
#> GSM1233098 2 0.6807 0.5242 0.108 0.576 0.312 0.004
#> GSM1233114 1 0.4008 0.6643 0.756 0.000 0.000 0.244
#> GSM1233119 4 0.0000 0.7518 0.000 0.000 0.000 1.000
#> GSM1233129 3 0.2814 0.6306 0.132 0.000 0.868 0.000
#> GSM1233132 4 0.4284 0.5894 0.200 0.020 0.000 0.780
#> GSM1233139 2 0.7185 0.6349 0.124 0.564 0.012 0.300
#> GSM1233143 3 0.5104 0.5791 0.116 0.088 0.784 0.012
#> GSM1233145 4 0.0817 0.7490 0.024 0.000 0.000 0.976
#> GSM1233067 3 0.4194 0.7072 0.008 0.228 0.764 0.000
#> GSM1233069 3 0.4584 0.7037 0.004 0.300 0.696 0.000
#> GSM1233072 2 0.7203 0.5234 0.116 0.568 0.300 0.016
#> GSM1233086 3 0.6558 0.2069 0.108 0.296 0.596 0.000
#> GSM1233102 4 0.0817 0.7490 0.024 0.000 0.000 0.976
#> GSM1233103 2 0.6490 0.6466 0.064 0.620 0.016 0.300
#> GSM1233107 4 0.5683 -0.2587 0.008 0.452 0.012 0.528
#> GSM1233108 3 0.5161 0.6926 0.024 0.300 0.676 0.000
#> GSM1233109 3 0.4957 0.6975 0.016 0.300 0.684 0.000
#> GSM1233110 3 0.4584 0.7037 0.004 0.300 0.696 0.000
#> GSM1233113 3 0.4353 0.7075 0.012 0.232 0.756 0.000
#> GSM1233116 3 0.3032 0.6975 0.008 0.124 0.868 0.000
#> GSM1233120 4 0.0817 0.7490 0.024 0.000 0.000 0.976
#> GSM1233121 3 0.4584 0.7037 0.004 0.300 0.696 0.000
#> GSM1233123 3 0.4584 0.7037 0.004 0.300 0.696 0.000
#> GSM1233124 3 0.1545 0.6858 0.008 0.040 0.952 0.000
#> GSM1233125 3 0.5161 0.6926 0.024 0.300 0.676 0.000
#> GSM1233126 4 0.0000 0.7518 0.000 0.000 0.000 1.000
#> GSM1233127 2 0.5168 0.3435 0.004 0.504 0.000 0.492
#> GSM1233128 1 0.2408 0.7973 0.896 0.000 0.000 0.104
#> GSM1233130 3 0.4584 0.7037 0.004 0.300 0.696 0.000
#> GSM1233131 2 0.6799 0.3533 0.096 0.464 0.000 0.440
#> GSM1233133 3 0.4957 0.6975 0.016 0.300 0.684 0.000
#> GSM1233134 3 0.4584 0.7037 0.004 0.300 0.696 0.000
#> GSM1233135 3 0.4584 0.7037 0.004 0.300 0.696 0.000
#> GSM1233136 3 0.4584 0.7037 0.004 0.300 0.696 0.000
#> GSM1233137 3 0.4722 0.7020 0.008 0.300 0.692 0.000
#> GSM1233138 4 0.0336 0.7551 0.000 0.008 0.000 0.992
#> GSM1233140 3 0.4679 0.4526 0.352 0.000 0.648 0.000
#> GSM1233141 2 0.8644 0.5410 0.104 0.504 0.132 0.260
#> GSM1233142 2 0.5793 0.6354 0.048 0.628 0.000 0.324
#> GSM1233144 3 0.4584 0.7037 0.004 0.300 0.696 0.000
#> GSM1233147 4 0.9347 -0.0701 0.100 0.220 0.320 0.360
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.2719 0.79784 0.000 0.884 0.048 0.068 0.000
#> GSM1233002 4 0.4201 -0.04040 0.000 0.000 0.000 0.592 0.408
#> GSM1233003 1 0.3855 0.69992 0.748 0.004 0.000 0.008 0.240
#> GSM1233014 4 0.4242 -0.04377 0.000 0.000 0.000 0.572 0.428
#> GSM1233015 4 0.7096 -0.11581 0.212 0.024 0.000 0.448 0.316
#> GSM1233016 5 0.4201 0.57316 0.000 0.000 0.000 0.408 0.592
#> GSM1233024 4 0.2104 0.61716 0.000 0.060 0.000 0.916 0.024
#> GSM1233049 1 0.2897 0.80202 0.884 0.024 0.020 0.000 0.072
#> GSM1233064 2 0.2230 0.79579 0.000 0.884 0.000 0.116 0.000
#> GSM1233068 4 0.6863 0.10234 0.044 0.132 0.000 0.524 0.300
#> GSM1233073 4 0.4307 -0.33231 0.000 0.000 0.000 0.504 0.496
#> GSM1233093 1 0.0290 0.82240 0.992 0.008 0.000 0.000 0.000
#> GSM1233115 1 0.2899 0.80526 0.888 0.032 0.000 0.024 0.056
#> GSM1232992 4 0.1952 0.60860 0.000 0.084 0.000 0.912 0.004
#> GSM1232993 4 0.1544 0.61666 0.000 0.068 0.000 0.932 0.000
#> GSM1233005 4 0.2676 0.61597 0.000 0.080 0.000 0.884 0.036
#> GSM1233007 2 0.4390 0.38314 0.000 0.568 0.000 0.428 0.004
#> GSM1233010 4 0.4192 -0.02618 0.000 0.000 0.000 0.596 0.404
#> GSM1233013 4 0.2389 0.59104 0.000 0.116 0.000 0.880 0.004
#> GSM1233018 4 0.3132 0.54780 0.000 0.172 0.000 0.820 0.008
#> GSM1233019 4 0.2104 0.61747 0.000 0.060 0.000 0.916 0.024
#> GSM1233021 4 0.2046 0.61772 0.000 0.068 0.000 0.916 0.016
#> GSM1233025 5 0.3857 0.68300 0.000 0.000 0.000 0.312 0.688
#> GSM1233029 4 0.1544 0.61666 0.000 0.068 0.000 0.932 0.000
#> GSM1233030 4 0.1704 0.61524 0.000 0.068 0.000 0.928 0.004
#> GSM1233031 4 0.2068 0.56935 0.004 0.000 0.000 0.904 0.092
#> GSM1233032 1 0.7025 0.45088 0.552 0.236 0.068 0.000 0.144
#> GSM1233035 4 0.3333 0.46282 0.004 0.000 0.000 0.788 0.208
#> GSM1233038 5 0.3960 0.63468 0.060 0.024 0.000 0.092 0.824
#> GSM1233039 2 0.1965 0.79814 0.000 0.904 0.000 0.096 0.000
#> GSM1233042 4 0.3906 0.32053 0.004 0.000 0.000 0.704 0.292
#> GSM1233043 4 0.3884 0.33108 0.004 0.000 0.000 0.708 0.288
#> GSM1233044 2 0.4246 0.78740 0.008 0.800 0.040 0.136 0.016
#> GSM1233046 4 0.4182 0.17660 0.000 0.004 0.000 0.644 0.352
#> GSM1233051 1 0.3455 0.79326 0.860 0.040 0.000 0.040 0.060
#> GSM1233054 2 0.4630 0.66662 0.000 0.744 0.116 0.000 0.140
#> GSM1233057 2 0.2925 0.77636 0.000 0.884 0.064 0.016 0.036
#> GSM1233060 4 0.1478 0.58818 0.000 0.000 0.000 0.936 0.064
#> GSM1233062 4 0.1809 0.61771 0.000 0.060 0.000 0.928 0.012
#> GSM1233075 3 0.1478 0.85507 0.000 0.064 0.936 0.000 0.000
#> GSM1233078 3 0.0162 0.89501 0.000 0.004 0.996 0.000 0.000
#> GSM1233079 3 0.8340 -0.08646 0.316 0.224 0.316 0.000 0.144
#> GSM1233082 4 0.5965 0.00593 0.080 0.012 0.000 0.528 0.380
#> GSM1233083 1 0.4558 0.72195 0.740 0.080 0.000 0.000 0.180
#> GSM1233091 2 0.2674 0.79094 0.000 0.856 0.000 0.140 0.004
#> GSM1233095 1 0.0290 0.82240 0.992 0.008 0.000 0.000 0.000
#> GSM1233096 4 0.7192 -0.20840 0.220 0.024 0.000 0.392 0.364
#> GSM1233101 1 0.0451 0.82205 0.988 0.008 0.000 0.000 0.004
#> GSM1233105 5 0.4219 0.48839 0.000 0.000 0.000 0.416 0.584
#> GSM1233117 2 0.3727 0.78469 0.000 0.824 0.068 0.104 0.004
#> GSM1233118 2 0.1965 0.78521 0.000 0.904 0.096 0.000 0.000
#> GSM1233001 2 0.1386 0.79883 0.000 0.952 0.016 0.032 0.000
#> GSM1233006 4 0.3086 0.50030 0.000 0.004 0.000 0.816 0.180
#> GSM1233008 4 0.3814 0.43403 0.000 0.276 0.000 0.720 0.004
#> GSM1233009 4 0.1544 0.61666 0.000 0.068 0.000 0.932 0.000
#> GSM1233017 4 0.1478 0.61698 0.000 0.064 0.000 0.936 0.000
#> GSM1233020 2 0.3266 0.72771 0.000 0.796 0.000 0.200 0.004
#> GSM1233022 4 0.4242 0.48175 0.004 0.036 0.000 0.752 0.208
#> GSM1233026 4 0.4644 0.28332 0.000 0.040 0.000 0.680 0.280
#> GSM1233028 4 0.1851 0.57264 0.000 0.000 0.000 0.912 0.088
#> GSM1233034 2 0.2930 0.74577 0.000 0.832 0.000 0.164 0.004
#> GSM1233040 1 0.2645 0.80203 0.888 0.044 0.000 0.000 0.068
#> GSM1233048 1 0.6901 -0.10132 0.404 0.016 0.000 0.184 0.396
#> GSM1233056 1 0.3495 0.75250 0.812 0.028 0.000 0.000 0.160
#> GSM1233058 4 0.4045 0.13883 0.000 0.000 0.000 0.644 0.356
#> GSM1233059 1 0.0290 0.82240 0.992 0.008 0.000 0.000 0.000
#> GSM1233066 2 0.3707 0.63101 0.000 0.716 0.284 0.000 0.000
#> GSM1233071 4 0.1544 0.61666 0.000 0.068 0.000 0.932 0.000
#> GSM1233074 2 0.3730 0.56583 0.000 0.712 0.288 0.000 0.000
#> GSM1233076 2 0.3318 0.78005 0.000 0.808 0.012 0.180 0.000
#> GSM1233080 1 0.0290 0.82240 0.992 0.008 0.000 0.000 0.000
#> GSM1233088 2 0.2308 0.78758 0.000 0.912 0.004 0.036 0.048
#> GSM1233090 1 0.0290 0.82240 0.992 0.008 0.000 0.000 0.000
#> GSM1233092 4 0.4410 -0.08285 0.004 0.000 0.000 0.556 0.440
#> GSM1233094 4 0.4009 0.26820 0.004 0.000 0.000 0.684 0.312
#> GSM1233097 4 0.3774 0.31898 0.000 0.000 0.000 0.704 0.296
#> GSM1233100 4 0.3966 0.20129 0.000 0.000 0.000 0.664 0.336
#> GSM1233104 4 0.4350 0.00857 0.004 0.000 0.000 0.588 0.408
#> GSM1233106 1 0.7761 -0.06333 0.352 0.056 0.000 0.308 0.284
#> GSM1233111 1 0.4093 0.74212 0.816 0.024 0.000 0.072 0.088
#> GSM1233122 4 0.4127 0.40822 0.000 0.312 0.000 0.680 0.008
#> GSM1233146 4 0.2852 0.50369 0.000 0.000 0.000 0.828 0.172
#> GSM1232994 4 0.2012 0.61717 0.000 0.060 0.000 0.920 0.020
#> GSM1232996 4 0.4141 0.48433 0.000 0.236 0.000 0.736 0.028
#> GSM1232997 2 0.1965 0.77738 0.000 0.904 0.096 0.000 0.000
#> GSM1232998 4 0.4367 0.00400 0.000 0.004 0.000 0.580 0.416
#> GSM1232999 4 0.3146 0.60124 0.000 0.052 0.000 0.856 0.092
#> GSM1233000 4 0.1544 0.61666 0.000 0.068 0.000 0.932 0.000
#> GSM1233004 2 0.4381 0.74021 0.012 0.776 0.152 0.060 0.000
#> GSM1233011 2 0.3535 0.78988 0.000 0.832 0.088 0.080 0.000
#> GSM1233012 2 0.1981 0.80179 0.000 0.924 0.028 0.048 0.000
#> GSM1233023 2 0.1195 0.79793 0.000 0.960 0.012 0.028 0.000
#> GSM1233027 4 0.3911 0.57535 0.000 0.060 0.000 0.796 0.144
#> GSM1233033 5 0.5253 0.40832 0.036 0.008 0.000 0.384 0.572
#> GSM1233036 2 0.1444 0.79720 0.000 0.948 0.040 0.012 0.000
#> GSM1233037 2 0.4428 0.71981 0.012 0.792 0.044 0.016 0.136
#> GSM1233041 1 0.0290 0.82240 0.992 0.008 0.000 0.000 0.000
#> GSM1233045 4 0.2848 0.51942 0.000 0.004 0.000 0.840 0.156
#> GSM1233047 2 0.8315 0.13694 0.256 0.360 0.240 0.000 0.144
#> GSM1233050 1 0.1845 0.80923 0.928 0.016 0.000 0.000 0.056
#> GSM1233052 4 0.4420 -0.01833 0.000 0.004 0.000 0.548 0.448
#> GSM1233053 1 0.7166 0.42384 0.536 0.244 0.076 0.000 0.144
#> GSM1233055 1 0.3495 0.75087 0.812 0.028 0.000 0.000 0.160
#> GSM1233061 2 0.4608 0.53449 0.000 0.640 0.336 0.000 0.024
#> GSM1233063 1 0.2241 0.80486 0.908 0.008 0.000 0.008 0.076
#> GSM1233065 2 0.2127 0.77310 0.000 0.892 0.108 0.000 0.000
#> GSM1233070 4 0.2171 0.60372 0.000 0.024 0.000 0.912 0.064
#> GSM1233077 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233081 3 0.2079 0.85077 0.000 0.020 0.916 0.000 0.064
#> GSM1233084 1 0.0290 0.82240 0.992 0.008 0.000 0.000 0.000
#> GSM1233087 5 0.3966 0.67191 0.000 0.000 0.000 0.336 0.664
#> GSM1233089 2 0.2377 0.77669 0.000 0.872 0.000 0.128 0.000
#> GSM1233099 5 0.4074 0.64398 0.000 0.000 0.000 0.364 0.636
#> GSM1233112 1 0.4748 0.71786 0.728 0.100 0.000 0.000 0.172
#> GSM1233085 3 0.1908 0.84316 0.000 0.000 0.908 0.000 0.092
#> GSM1233098 2 0.3300 0.72517 0.000 0.792 0.000 0.204 0.004
#> GSM1233114 1 0.5330 0.38375 0.484 0.028 0.000 0.012 0.476
#> GSM1233119 5 0.4273 0.30928 0.000 0.000 0.000 0.448 0.552
#> GSM1233129 2 0.1628 0.79281 0.000 0.936 0.056 0.008 0.000
#> GSM1233132 5 0.3607 0.66281 0.000 0.004 0.000 0.244 0.752
#> GSM1233139 4 0.2970 0.55417 0.000 0.168 0.000 0.828 0.004
#> GSM1233143 2 0.2389 0.77936 0.000 0.880 0.116 0.004 0.000
#> GSM1233145 5 0.3969 0.63043 0.064 0.024 0.000 0.088 0.824
#> GSM1233067 3 0.3932 0.45590 0.000 0.328 0.672 0.000 0.000
#> GSM1233069 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233072 2 0.3196 0.73856 0.000 0.804 0.000 0.192 0.004
#> GSM1233086 2 0.3608 0.75514 0.000 0.812 0.148 0.040 0.000
#> GSM1233102 5 0.2848 0.67376 0.000 0.004 0.000 0.156 0.840
#> GSM1233103 4 0.4108 0.24431 0.000 0.008 0.000 0.684 0.308
#> GSM1233107 4 0.3210 0.41546 0.000 0.000 0.000 0.788 0.212
#> GSM1233108 3 0.1197 0.87128 0.048 0.000 0.952 0.000 0.000
#> GSM1233109 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233110 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233113 3 0.3895 0.47037 0.000 0.320 0.680 0.000 0.000
#> GSM1233116 3 0.4227 0.19582 0.000 0.420 0.580 0.000 0.000
#> GSM1233120 5 0.3123 0.68899 0.000 0.004 0.000 0.184 0.812
#> GSM1233121 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233123 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233124 2 0.4273 0.29594 0.000 0.552 0.448 0.000 0.000
#> GSM1233125 3 0.1341 0.86550 0.056 0.000 0.944 0.000 0.000
#> GSM1233126 4 0.4300 -0.17020 0.000 0.000 0.000 0.524 0.476
#> GSM1233127 4 0.3825 0.53470 0.000 0.060 0.000 0.804 0.136
#> GSM1233128 1 0.2879 0.78570 0.868 0.032 0.000 0.000 0.100
#> GSM1233130 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233131 4 0.4549 -0.07254 0.000 0.008 0.000 0.528 0.464
#> GSM1233133 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233134 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233135 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233136 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233137 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233138 4 0.4278 -0.10773 0.000 0.000 0.000 0.548 0.452
#> GSM1233140 2 0.7884 0.02664 0.324 0.408 0.124 0.000 0.144
#> GSM1233141 2 0.5956 0.06720 0.000 0.476 0.000 0.416 0.108
#> GSM1233142 4 0.1768 0.61699 0.000 0.072 0.000 0.924 0.004
#> GSM1233144 3 0.0000 0.89693 0.000 0.000 1.000 0.000 0.000
#> GSM1233147 2 0.4269 0.73090 0.000 0.776 0.000 0.108 0.116
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 6 0.2443 0.69954 0.000 0.096 0.020 0.000 0.004 0.880
#> GSM1233002 2 0.4175 0.01986 0.000 0.524 0.000 0.464 0.012 0.000
#> GSM1233003 1 0.3835 0.64663 0.768 0.004 0.000 0.184 0.040 0.004
#> GSM1233014 4 0.3965 0.52950 0.000 0.388 0.000 0.604 0.008 0.000
#> GSM1233015 2 0.7696 0.11366 0.196 0.380 0.000 0.212 0.204 0.008
#> GSM1233016 4 0.3244 0.54670 0.000 0.268 0.000 0.732 0.000 0.000
#> GSM1233024 2 0.2178 0.54228 0.000 0.868 0.000 0.132 0.000 0.000
#> GSM1233049 1 0.4100 0.50462 0.600 0.000 0.004 0.000 0.388 0.008
#> GSM1233064 6 0.3768 0.69248 0.004 0.112 0.004 0.028 0.036 0.816
#> GSM1233068 2 0.8271 0.21498 0.144 0.416 0.000 0.168 0.160 0.112
#> GSM1233073 4 0.2912 0.62054 0.000 0.216 0.000 0.784 0.000 0.000
#> GSM1233093 1 0.0000 0.73740 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233115 1 0.3810 0.71956 0.780 0.016 0.000 0.008 0.176 0.020
#> GSM1232992 2 0.1720 0.62221 0.000 0.928 0.000 0.000 0.032 0.040
#> GSM1232993 2 0.0405 0.63736 0.000 0.988 0.000 0.008 0.000 0.004
#> GSM1233005 2 0.1864 0.62306 0.000 0.924 0.000 0.004 0.032 0.040
#> GSM1233007 6 0.5321 0.35022 0.000 0.372 0.000 0.048 0.032 0.548
#> GSM1233010 4 0.4179 0.10242 0.000 0.472 0.000 0.516 0.012 0.000
#> GSM1233013 2 0.1984 0.61387 0.000 0.912 0.000 0.000 0.032 0.056
#> GSM1233018 2 0.2815 0.57382 0.000 0.848 0.000 0.000 0.032 0.120
#> GSM1233019 2 0.1007 0.62155 0.000 0.956 0.000 0.044 0.000 0.000
#> GSM1233021 2 0.1168 0.63205 0.000 0.956 0.000 0.000 0.028 0.016
#> GSM1233025 4 0.1910 0.62798 0.000 0.108 0.000 0.892 0.000 0.000
#> GSM1233029 2 0.0405 0.63736 0.000 0.988 0.000 0.008 0.000 0.004
#> GSM1233030 2 0.0964 0.63675 0.000 0.968 0.000 0.004 0.016 0.012
#> GSM1233031 2 0.3141 0.47239 0.000 0.788 0.000 0.200 0.012 0.000
#> GSM1233032 5 0.4618 0.58492 0.236 0.000 0.020 0.000 0.692 0.052
#> GSM1233035 2 0.3777 0.53605 0.004 0.776 0.000 0.164 0.056 0.000
#> GSM1233038 4 0.3525 0.47200 0.068 0.004 0.000 0.808 0.120 0.000
#> GSM1233039 6 0.3682 0.68878 0.000 0.080 0.004 0.028 0.064 0.824
#> GSM1233042 4 0.3872 0.52578 0.000 0.392 0.000 0.604 0.004 0.000
#> GSM1233043 4 0.3975 0.43854 0.000 0.452 0.000 0.544 0.004 0.000
#> GSM1233044 6 0.4742 0.65106 0.060 0.080 0.028 0.064 0.000 0.768
#> GSM1233046 2 0.5669 0.33782 0.020 0.600 0.000 0.248 0.128 0.004
#> GSM1233051 1 0.2913 0.71664 0.812 0.004 0.000 0.000 0.180 0.004
#> GSM1233054 5 0.4684 0.19023 0.000 0.008 0.028 0.000 0.520 0.444
#> GSM1233057 6 0.4617 -0.06298 0.000 0.016 0.016 0.000 0.424 0.544
#> GSM1233060 2 0.2933 0.52728 0.000 0.796 0.000 0.200 0.004 0.000
#> GSM1233062 2 0.0692 0.63191 0.000 0.976 0.000 0.020 0.004 0.000
#> GSM1233075 3 0.2830 0.80752 0.000 0.000 0.836 0.000 0.020 0.144
#> GSM1233078 3 0.0632 0.87109 0.000 0.000 0.976 0.000 0.000 0.024
#> GSM1233079 5 0.5549 0.62049 0.172 0.000 0.124 0.000 0.652 0.052
#> GSM1233082 2 0.7511 0.19559 0.184 0.440 0.000 0.188 0.176 0.012
#> GSM1233083 1 0.6227 0.57481 0.584 0.004 0.000 0.092 0.224 0.096
#> GSM1233091 6 0.4581 0.66405 0.016 0.100 0.000 0.036 0.080 0.768
#> GSM1233095 1 0.2300 0.73185 0.856 0.000 0.000 0.000 0.144 0.000
#> GSM1233096 2 0.7463 0.10862 0.196 0.392 0.000 0.212 0.200 0.000
#> GSM1233101 1 0.2703 0.72605 0.824 0.000 0.000 0.000 0.172 0.004
#> GSM1233105 4 0.4020 0.56917 0.008 0.204 0.000 0.744 0.044 0.000
#> GSM1233117 6 0.3415 0.67885 0.000 0.152 0.028 0.000 0.012 0.808
#> GSM1233118 6 0.2911 0.67262 0.000 0.024 0.036 0.000 0.072 0.868
#> GSM1233001 6 0.3756 0.63583 0.000 0.052 0.008 0.000 0.156 0.784
#> GSM1233006 2 0.3659 0.06312 0.000 0.636 0.000 0.364 0.000 0.000
#> GSM1233008 2 0.4216 0.40208 0.000 0.676 0.000 0.004 0.032 0.288
#> GSM1233009 2 0.0436 0.63799 0.000 0.988 0.000 0.004 0.004 0.004
#> GSM1233017 2 0.0146 0.63694 0.000 0.996 0.000 0.004 0.000 0.000
#> GSM1233020 6 0.3348 0.63341 0.000 0.216 0.000 0.000 0.016 0.768
#> GSM1233022 2 0.3857 -0.33308 0.000 0.532 0.000 0.468 0.000 0.000
#> GSM1233026 2 0.4693 0.41502 0.008 0.656 0.000 0.292 0.016 0.028
#> GSM1233028 2 0.3012 0.52523 0.000 0.796 0.000 0.196 0.008 0.000
#> GSM1233034 6 0.4132 0.64281 0.008 0.180 0.000 0.000 0.064 0.748
#> GSM1233040 1 0.3835 0.32472 0.656 0.000 0.004 0.000 0.336 0.004
#> GSM1233048 1 0.5995 0.44142 0.608 0.100 0.000 0.092 0.200 0.000
#> GSM1233056 1 0.4525 0.68285 0.700 0.000 0.000 0.072 0.220 0.008
#> GSM1233058 4 0.3997 0.09582 0.000 0.488 0.000 0.508 0.004 0.000
#> GSM1233059 1 0.0547 0.73494 0.980 0.000 0.000 0.000 0.020 0.000
#> GSM1233066 6 0.4153 0.58430 0.000 0.000 0.148 0.004 0.096 0.752
#> GSM1233071 2 0.0748 0.63763 0.000 0.976 0.000 0.016 0.004 0.004
#> GSM1233074 6 0.5552 0.13841 0.000 0.004 0.328 0.000 0.136 0.532
#> GSM1233076 6 0.3204 0.67662 0.004 0.112 0.000 0.052 0.000 0.832
#> GSM1233080 1 0.1814 0.74250 0.900 0.000 0.000 0.000 0.100 0.000
#> GSM1233088 6 0.4017 0.59069 0.004 0.032 0.008 0.000 0.212 0.744
#> GSM1233090 1 0.2300 0.73397 0.856 0.000 0.000 0.000 0.144 0.000
#> GSM1233092 4 0.3911 0.54852 0.000 0.368 0.000 0.624 0.008 0.000
#> GSM1233094 4 0.3789 0.50696 0.000 0.416 0.000 0.584 0.000 0.000
#> GSM1233097 4 0.3915 0.48178 0.000 0.412 0.000 0.584 0.004 0.000
#> GSM1233100 4 0.4183 0.11599 0.000 0.480 0.000 0.508 0.012 0.000
#> GSM1233104 4 0.3727 0.53153 0.000 0.388 0.000 0.612 0.000 0.000
#> GSM1233106 1 0.7005 0.34319 0.536 0.148 0.000 0.040 0.208 0.068
#> GSM1233111 1 0.3301 0.62736 0.772 0.008 0.000 0.004 0.216 0.000
#> GSM1233122 2 0.4454 0.29501 0.000 0.616 0.000 0.004 0.032 0.348
#> GSM1233146 2 0.3405 0.41613 0.000 0.724 0.000 0.272 0.004 0.000
#> GSM1232994 2 0.2631 0.47390 0.000 0.820 0.000 0.180 0.000 0.000
#> GSM1232996 2 0.3713 0.47910 0.000 0.744 0.000 0.000 0.032 0.224
#> GSM1232997 6 0.2806 0.61893 0.000 0.008 0.008 0.000 0.144 0.840
#> GSM1232998 4 0.3975 0.52509 0.000 0.392 0.000 0.600 0.008 0.000
#> GSM1232999 2 0.2933 0.45237 0.000 0.796 0.000 0.200 0.000 0.004
#> GSM1233000 2 0.0291 0.63755 0.000 0.992 0.000 0.004 0.000 0.004
#> GSM1233004 6 0.4893 0.61363 0.024 0.008 0.104 0.040 0.064 0.760
#> GSM1233011 6 0.2713 0.69583 0.000 0.040 0.040 0.036 0.000 0.884
#> GSM1233012 6 0.3133 0.68923 0.000 0.064 0.016 0.000 0.068 0.852
#> GSM1233023 6 0.3395 0.65051 0.000 0.048 0.004 0.000 0.136 0.812
#> GSM1233027 2 0.3446 0.18583 0.000 0.692 0.000 0.308 0.000 0.000
#> GSM1233033 4 0.6469 0.00502 0.068 0.408 0.000 0.412 0.112 0.000
#> GSM1233036 6 0.3172 0.67124 0.000 0.040 0.016 0.000 0.100 0.844
#> GSM1233037 5 0.4876 0.20646 0.016 0.012 0.012 0.000 0.520 0.440
#> GSM1233041 1 0.0260 0.73657 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM1233045 2 0.3398 0.40638 0.000 0.740 0.000 0.252 0.008 0.000
#> GSM1233047 5 0.5766 0.64353 0.120 0.000 0.132 0.000 0.648 0.100
#> GSM1233050 1 0.2762 0.71809 0.804 0.000 0.000 0.000 0.196 0.000
#> GSM1233052 2 0.5972 0.28752 0.032 0.560 0.000 0.256 0.152 0.000
#> GSM1233053 5 0.4752 0.60211 0.236 0.000 0.024 0.000 0.684 0.056
#> GSM1233055 1 0.3225 0.69249 0.828 0.000 0.000 0.092 0.080 0.000
#> GSM1233061 6 0.5550 0.26784 0.000 0.000 0.228 0.000 0.216 0.556
#> GSM1233063 1 0.2501 0.70258 0.872 0.016 0.000 0.004 0.108 0.000
#> GSM1233065 6 0.3313 0.63050 0.000 0.024 0.016 0.000 0.140 0.820
#> GSM1233070 2 0.1918 0.60800 0.000 0.904 0.000 0.088 0.008 0.000
#> GSM1233077 3 0.1444 0.87463 0.000 0.000 0.928 0.000 0.000 0.072
#> GSM1233081 3 0.2609 0.76986 0.000 0.000 0.868 0.000 0.096 0.036
#> GSM1233084 1 0.2234 0.73754 0.872 0.004 0.000 0.000 0.124 0.000
#> GSM1233087 4 0.2389 0.62726 0.000 0.128 0.000 0.864 0.008 0.000
#> GSM1233089 6 0.2632 0.67874 0.000 0.164 0.000 0.000 0.004 0.832
#> GSM1233099 4 0.2346 0.63111 0.008 0.124 0.000 0.868 0.000 0.000
#> GSM1233112 1 0.6247 0.54891 0.572 0.000 0.000 0.092 0.224 0.112
#> GSM1233085 3 0.2402 0.76144 0.000 0.000 0.856 0.000 0.140 0.004
#> GSM1233098 6 0.4040 0.57092 0.000 0.280 0.000 0.000 0.032 0.688
#> GSM1233114 1 0.5479 0.55489 0.612 0.012 0.000 0.180 0.196 0.000
#> GSM1233119 4 0.2402 0.63519 0.000 0.140 0.000 0.856 0.004 0.000
#> GSM1233129 6 0.2615 0.62896 0.000 0.008 0.004 0.000 0.136 0.852
#> GSM1233132 4 0.5631 0.41870 0.028 0.232 0.000 0.608 0.132 0.000
#> GSM1233139 2 0.2726 0.57986 0.000 0.856 0.000 0.000 0.032 0.112
#> GSM1233143 6 0.3603 0.67817 0.000 0.044 0.064 0.000 0.064 0.828
#> GSM1233145 4 0.4015 0.48987 0.076 0.020 0.000 0.784 0.120 0.000
#> GSM1233067 3 0.4161 0.44084 0.000 0.008 0.612 0.000 0.008 0.372
#> GSM1233069 3 0.1501 0.87343 0.000 0.000 0.924 0.000 0.000 0.076
#> GSM1233072 6 0.3454 0.63896 0.000 0.208 0.000 0.000 0.024 0.768
#> GSM1233086 6 0.3893 0.66109 0.004 0.008 0.096 0.028 0.048 0.816
#> GSM1233102 4 0.1767 0.57633 0.012 0.020 0.000 0.932 0.036 0.000
#> GSM1233103 2 0.5555 0.38249 0.008 0.628 0.000 0.216 0.132 0.016
#> GSM1233107 2 0.3918 0.21315 0.004 0.632 0.000 0.360 0.004 0.000
#> GSM1233108 3 0.0260 0.86387 0.000 0.000 0.992 0.000 0.008 0.000
#> GSM1233109 3 0.0260 0.86387 0.000 0.000 0.992 0.000 0.008 0.000
#> GSM1233110 3 0.0937 0.87421 0.000 0.000 0.960 0.000 0.000 0.040
#> GSM1233113 3 0.3965 0.41334 0.000 0.008 0.604 0.000 0.000 0.388
#> GSM1233116 3 0.4684 0.19554 0.000 0.008 0.520 0.000 0.028 0.444
#> GSM1233120 4 0.2833 0.61175 0.008 0.088 0.000 0.864 0.040 0.000
#> GSM1233121 3 0.1501 0.87359 0.000 0.000 0.924 0.000 0.000 0.076
#> GSM1233123 3 0.1387 0.87446 0.000 0.000 0.932 0.000 0.000 0.068
#> GSM1233124 6 0.4767 0.37409 0.000 0.000 0.304 0.000 0.076 0.620
#> GSM1233125 3 0.0622 0.86106 0.012 0.000 0.980 0.000 0.008 0.000
#> GSM1233126 4 0.3528 0.59457 0.000 0.296 0.000 0.700 0.004 0.000
#> GSM1233127 2 0.2697 0.46324 0.000 0.812 0.000 0.188 0.000 0.000
#> GSM1233128 1 0.4120 0.69250 0.724 0.000 0.000 0.040 0.228 0.008
#> GSM1233130 3 0.1444 0.87463 0.000 0.000 0.928 0.000 0.000 0.072
#> GSM1233131 2 0.5598 0.27711 0.024 0.576 0.000 0.296 0.104 0.000
#> GSM1233133 3 0.0146 0.86453 0.000 0.000 0.996 0.000 0.004 0.000
#> GSM1233134 3 0.1556 0.87237 0.000 0.000 0.920 0.000 0.000 0.080
#> GSM1233135 3 0.1556 0.87237 0.000 0.000 0.920 0.000 0.000 0.080
#> GSM1233136 3 0.1556 0.87229 0.000 0.000 0.920 0.000 0.000 0.080
#> GSM1233137 3 0.0146 0.86537 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM1233138 4 0.3934 0.54078 0.000 0.376 0.000 0.616 0.008 0.000
#> GSM1233140 5 0.5045 0.66140 0.148 0.000 0.032 0.000 0.696 0.124
#> GSM1233141 6 0.5727 0.03538 0.000 0.444 0.000 0.076 0.032 0.448
#> GSM1233142 2 0.1180 0.63766 0.000 0.960 0.000 0.016 0.012 0.012
#> GSM1233144 3 0.0146 0.86453 0.000 0.000 0.996 0.000 0.004 0.000
#> GSM1233147 6 0.3248 0.65907 0.004 0.052 0.000 0.116 0.000 0.828
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> SD:mclust 151 7.32e-01 1.0000 1.0000 2
#> SD:mclust 101 1.06e-05 0.0796 0.0153 3
#> SD:mclust 122 5.01e-04 0.2022 0.0134 4
#> SD:mclust 109 1.18e-07 0.0122 0.0542 5
#> SD:mclust 110 5.76e-06 0.0505 0.0263 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 51941 rows and 156 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'SD' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.683 0.851 0.936 0.4805 0.527 0.527
#> 3 3 0.463 0.598 0.817 0.3686 0.706 0.489
#> 4 4 0.476 0.481 0.711 0.1257 0.751 0.403
#> 5 5 0.582 0.566 0.760 0.0714 0.852 0.507
#> 6 6 0.581 0.434 0.660 0.0419 0.923 0.655
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0000 0.9388 0.000 1.000
#> GSM1233002 1 0.0000 0.9237 1.000 0.000
#> GSM1233003 1 0.0000 0.9237 1.000 0.000
#> GSM1233014 1 0.0000 0.9237 1.000 0.000
#> GSM1233015 1 0.5294 0.8420 0.880 0.120
#> GSM1233016 1 0.0000 0.9237 1.000 0.000
#> GSM1233024 1 0.0000 0.9237 1.000 0.000
#> GSM1233049 2 0.0000 0.9388 0.000 1.000
#> GSM1233064 2 0.5629 0.8157 0.132 0.868
#> GSM1233068 1 0.3879 0.8784 0.924 0.076
#> GSM1233073 1 0.0000 0.9237 1.000 0.000
#> GSM1233093 1 0.0000 0.9237 1.000 0.000
#> GSM1233115 1 0.0000 0.9237 1.000 0.000
#> GSM1232992 1 0.6887 0.7766 0.816 0.184
#> GSM1232993 1 0.0376 0.9221 0.996 0.004
#> GSM1233005 1 0.2603 0.9007 0.956 0.044
#> GSM1233007 1 0.0000 0.9237 1.000 0.000
#> GSM1233010 1 0.0000 0.9237 1.000 0.000
#> GSM1233013 1 0.8661 0.6260 0.712 0.288
#> GSM1233018 1 0.8386 0.6591 0.732 0.268
#> GSM1233019 1 0.0376 0.9221 0.996 0.004
#> GSM1233021 1 0.3584 0.8841 0.932 0.068
#> GSM1233025 1 0.0000 0.9237 1.000 0.000
#> GSM1233029 1 0.0000 0.9237 1.000 0.000
#> GSM1233030 1 0.6438 0.7993 0.836 0.164
#> GSM1233031 1 0.0000 0.9237 1.000 0.000
#> GSM1233032 2 0.0000 0.9388 0.000 1.000
#> GSM1233035 1 0.0000 0.9237 1.000 0.000
#> GSM1233038 1 0.0000 0.9237 1.000 0.000
#> GSM1233039 2 0.9970 0.0512 0.468 0.532
#> GSM1233042 1 0.0000 0.9237 1.000 0.000
#> GSM1233043 1 0.0000 0.9237 1.000 0.000
#> GSM1233044 1 0.9522 0.3996 0.628 0.372
#> GSM1233046 1 0.0672 0.9203 0.992 0.008
#> GSM1233051 1 0.6048 0.8067 0.852 0.148
#> GSM1233054 2 0.0000 0.9388 0.000 1.000
#> GSM1233057 2 0.0000 0.9388 0.000 1.000
#> GSM1233060 1 0.0000 0.9237 1.000 0.000
#> GSM1233062 1 0.0000 0.9237 1.000 0.000
#> GSM1233075 2 0.0000 0.9388 0.000 1.000
#> GSM1233078 2 0.0000 0.9388 0.000 1.000
#> GSM1233079 2 0.0000 0.9388 0.000 1.000
#> GSM1233082 1 0.0000 0.9237 1.000 0.000
#> GSM1233083 1 0.2236 0.9023 0.964 0.036
#> GSM1233091 1 0.9970 0.1870 0.532 0.468
#> GSM1233095 1 0.2423 0.8999 0.960 0.040
#> GSM1233096 1 0.0000 0.9237 1.000 0.000
#> GSM1233101 2 0.9635 0.3821 0.388 0.612
#> GSM1233105 1 0.0000 0.9237 1.000 0.000
#> GSM1233117 2 0.0000 0.9388 0.000 1.000
#> GSM1233118 2 0.0000 0.9388 0.000 1.000
#> GSM1233001 2 0.0000 0.9388 0.000 1.000
#> GSM1233006 1 0.0000 0.9237 1.000 0.000
#> GSM1233008 1 0.9491 0.4746 0.632 0.368
#> GSM1233009 1 0.5946 0.8198 0.856 0.144
#> GSM1233017 1 0.1633 0.9124 0.976 0.024
#> GSM1233020 2 0.5946 0.8026 0.144 0.856
#> GSM1233022 1 0.0000 0.9237 1.000 0.000
#> GSM1233026 1 0.0000 0.9237 1.000 0.000
#> GSM1233028 1 0.0000 0.9237 1.000 0.000
#> GSM1233034 2 0.9970 0.0343 0.468 0.532
#> GSM1233040 2 0.3431 0.8862 0.064 0.936
#> GSM1233048 1 0.0000 0.9237 1.000 0.000
#> GSM1233056 1 0.2603 0.8964 0.956 0.044
#> GSM1233058 1 0.0000 0.9237 1.000 0.000
#> GSM1233059 1 0.0000 0.9237 1.000 0.000
#> GSM1233066 2 0.0000 0.9388 0.000 1.000
#> GSM1233071 1 0.2236 0.9057 0.964 0.036
#> GSM1233074 2 0.0000 0.9388 0.000 1.000
#> GSM1233076 1 0.8144 0.6466 0.748 0.252
#> GSM1233080 1 0.0000 0.9237 1.000 0.000
#> GSM1233088 2 0.6623 0.7633 0.172 0.828
#> GSM1233090 1 0.9954 0.1995 0.540 0.460
#> GSM1233092 1 0.0000 0.9237 1.000 0.000
#> GSM1233094 1 0.0000 0.9237 1.000 0.000
#> GSM1233097 1 0.0000 0.9237 1.000 0.000
#> GSM1233100 1 0.0000 0.9237 1.000 0.000
#> GSM1233104 1 0.0000 0.9237 1.000 0.000
#> GSM1233106 1 0.6801 0.7835 0.820 0.180
#> GSM1233111 1 0.3431 0.8882 0.936 0.064
#> GSM1233122 1 0.6712 0.7868 0.824 0.176
#> GSM1233146 1 0.0000 0.9237 1.000 0.000
#> GSM1232994 1 0.0000 0.9237 1.000 0.000
#> GSM1232996 1 0.6531 0.7990 0.832 0.168
#> GSM1232997 2 0.0000 0.9388 0.000 1.000
#> GSM1232998 1 0.0000 0.9237 1.000 0.000
#> GSM1232999 1 0.0000 0.9237 1.000 0.000
#> GSM1233000 1 0.5408 0.8384 0.876 0.124
#> GSM1233004 2 0.9608 0.3929 0.384 0.616
#> GSM1233011 2 0.9427 0.4462 0.360 0.640
#> GSM1233012 2 0.0000 0.9388 0.000 1.000
#> GSM1233023 2 0.0000 0.9388 0.000 1.000
#> GSM1233027 1 0.0000 0.9237 1.000 0.000
#> GSM1233033 1 0.0000 0.9237 1.000 0.000
#> GSM1233036 2 0.0000 0.9388 0.000 1.000
#> GSM1233037 2 0.1633 0.9206 0.024 0.976
#> GSM1233041 1 0.0000 0.9237 1.000 0.000
#> GSM1233045 1 0.0000 0.9237 1.000 0.000
#> GSM1233047 2 0.0000 0.9388 0.000 1.000
#> GSM1233050 2 0.5629 0.8163 0.132 0.868
#> GSM1233052 1 0.0000 0.9237 1.000 0.000
#> GSM1233053 2 0.0000 0.9388 0.000 1.000
#> GSM1233055 1 0.0000 0.9237 1.000 0.000
#> GSM1233061 2 0.0000 0.9388 0.000 1.000
#> GSM1233063 1 0.0000 0.9237 1.000 0.000
#> GSM1233065 2 0.0000 0.9388 0.000 1.000
#> GSM1233070 1 0.0000 0.9237 1.000 0.000
#> GSM1233077 2 0.0000 0.9388 0.000 1.000
#> GSM1233081 2 0.0000 0.9388 0.000 1.000
#> GSM1233084 1 0.0000 0.9237 1.000 0.000
#> GSM1233087 1 0.0000 0.9237 1.000 0.000
#> GSM1233089 2 0.5629 0.8196 0.132 0.868
#> GSM1233099 1 0.0000 0.9237 1.000 0.000
#> GSM1233112 2 0.9170 0.5141 0.332 0.668
#> GSM1233085 2 0.0000 0.9388 0.000 1.000
#> GSM1233098 1 0.6887 0.7803 0.816 0.184
#> GSM1233114 1 0.0000 0.9237 1.000 0.000
#> GSM1233119 1 0.0000 0.9237 1.000 0.000
#> GSM1233129 2 0.0000 0.9388 0.000 1.000
#> GSM1233132 1 0.0000 0.9237 1.000 0.000
#> GSM1233139 1 0.9710 0.3906 0.600 0.400
#> GSM1233143 2 0.0000 0.9388 0.000 1.000
#> GSM1233145 1 0.0000 0.9237 1.000 0.000
#> GSM1233067 2 0.0000 0.9388 0.000 1.000
#> GSM1233069 2 0.0000 0.9388 0.000 1.000
#> GSM1233072 1 0.8909 0.6013 0.692 0.308
#> GSM1233086 2 0.0376 0.9359 0.004 0.996
#> GSM1233102 1 0.0000 0.9237 1.000 0.000
#> GSM1233103 1 0.0376 0.9221 0.996 0.004
#> GSM1233107 1 0.1414 0.9145 0.980 0.020
#> GSM1233108 2 0.0000 0.9388 0.000 1.000
#> GSM1233109 2 0.0000 0.9388 0.000 1.000
#> GSM1233110 2 0.0000 0.9388 0.000 1.000
#> GSM1233113 2 0.0000 0.9388 0.000 1.000
#> GSM1233116 2 0.0000 0.9388 0.000 1.000
#> GSM1233120 1 0.0000 0.9237 1.000 0.000
#> GSM1233121 2 0.0000 0.9388 0.000 1.000
#> GSM1233123 2 0.0000 0.9388 0.000 1.000
#> GSM1233124 2 0.0000 0.9388 0.000 1.000
#> GSM1233125 2 0.0000 0.9388 0.000 1.000
#> GSM1233126 1 0.0000 0.9237 1.000 0.000
#> GSM1233127 1 0.1843 0.9102 0.972 0.028
#> GSM1233128 1 0.9866 0.2126 0.568 0.432
#> GSM1233130 2 0.0000 0.9388 0.000 1.000
#> GSM1233131 1 0.0000 0.9237 1.000 0.000
#> GSM1233133 2 0.0000 0.9388 0.000 1.000
#> GSM1233134 2 0.0000 0.9388 0.000 1.000
#> GSM1233135 2 0.0000 0.9388 0.000 1.000
#> GSM1233136 2 0.0000 0.9388 0.000 1.000
#> GSM1233137 2 0.0000 0.9388 0.000 1.000
#> GSM1233138 1 0.0000 0.9237 1.000 0.000
#> GSM1233140 2 0.0000 0.9388 0.000 1.000
#> GSM1233141 1 0.9552 0.4552 0.624 0.376
#> GSM1233142 1 0.6623 0.7906 0.828 0.172
#> GSM1233144 2 0.0000 0.9388 0.000 1.000
#> GSM1233147 1 0.9963 0.1015 0.536 0.464
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.6192 0.1331 0.000 0.580 0.420
#> GSM1233002 1 0.6215 0.3449 0.572 0.428 0.000
#> GSM1233003 1 0.0747 0.7204 0.984 0.000 0.016
#> GSM1233014 1 0.2356 0.7276 0.928 0.072 0.000
#> GSM1233015 2 0.0237 0.7216 0.004 0.996 0.000
#> GSM1233016 1 0.0237 0.7245 0.996 0.000 0.004
#> GSM1233024 2 0.5835 0.4585 0.340 0.660 0.000
#> GSM1233049 3 0.0000 0.8396 0.000 0.000 1.000
#> GSM1233064 2 0.5968 0.2608 0.000 0.636 0.364
#> GSM1233068 2 0.0747 0.7212 0.016 0.984 0.000
#> GSM1233073 1 0.2261 0.7289 0.932 0.068 0.000
#> GSM1233093 1 0.6192 0.3174 0.580 0.420 0.000
#> GSM1233115 1 0.6180 0.3170 0.584 0.416 0.000
#> GSM1232992 2 0.0424 0.7226 0.008 0.992 0.000
#> GSM1232993 2 0.0592 0.7225 0.012 0.988 0.000
#> GSM1233005 2 0.4346 0.6448 0.184 0.816 0.000
#> GSM1233007 1 0.3551 0.7186 0.868 0.132 0.000
#> GSM1233010 1 0.5529 0.5534 0.704 0.296 0.000
#> GSM1233013 2 0.0892 0.7243 0.020 0.980 0.000
#> GSM1233018 2 0.0424 0.7231 0.008 0.992 0.000
#> GSM1233019 2 0.6095 0.3558 0.392 0.608 0.000
#> GSM1233021 2 0.1643 0.7209 0.044 0.956 0.000
#> GSM1233025 1 0.0237 0.7245 0.996 0.000 0.004
#> GSM1233029 2 0.0892 0.7204 0.020 0.980 0.000
#> GSM1233030 2 0.0000 0.7212 0.000 1.000 0.000
#> GSM1233031 2 0.5785 0.4047 0.332 0.668 0.000
#> GSM1233032 3 0.6308 0.0308 0.000 0.492 0.508
#> GSM1233035 2 0.3816 0.6780 0.148 0.852 0.000
#> GSM1233038 1 0.0000 0.7259 1.000 0.000 0.000
#> GSM1233039 2 0.1529 0.7114 0.000 0.960 0.040
#> GSM1233042 1 0.3879 0.7006 0.848 0.152 0.000
#> GSM1233043 1 0.3816 0.7022 0.852 0.148 0.000
#> GSM1233044 1 0.8202 0.2405 0.544 0.080 0.376
#> GSM1233046 2 0.5254 0.5617 0.264 0.736 0.000
#> GSM1233051 2 0.9596 0.0171 0.200 0.416 0.384
#> GSM1233054 3 0.6260 0.2939 0.000 0.448 0.552
#> GSM1233057 2 0.5465 0.4623 0.000 0.712 0.288
#> GSM1233060 2 0.3116 0.6731 0.108 0.892 0.000
#> GSM1233062 2 0.4346 0.6518 0.184 0.816 0.000
#> GSM1233075 3 0.1964 0.8278 0.000 0.056 0.944
#> GSM1233078 3 0.0000 0.8396 0.000 0.000 1.000
#> GSM1233079 3 0.1753 0.8156 0.000 0.048 0.952
#> GSM1233082 2 0.4702 0.5326 0.212 0.788 0.000
#> GSM1233083 1 0.2625 0.6863 0.916 0.000 0.084
#> GSM1233091 2 0.0000 0.7212 0.000 1.000 0.000
#> GSM1233095 1 0.7890 0.3295 0.564 0.372 0.064
#> GSM1233096 2 0.2356 0.6972 0.072 0.928 0.000
#> GSM1233101 3 0.4605 0.6925 0.204 0.000 0.796
#> GSM1233105 1 0.4887 0.6426 0.772 0.228 0.000
#> GSM1233117 3 0.6307 0.1714 0.000 0.488 0.512
#> GSM1233118 3 0.3551 0.7816 0.000 0.132 0.868
#> GSM1233001 2 0.5760 0.3783 0.000 0.672 0.328
#> GSM1233006 1 0.4750 0.6464 0.784 0.216 0.000
#> GSM1233008 2 0.6488 0.6198 0.160 0.756 0.084
#> GSM1233009 2 0.0237 0.7216 0.004 0.996 0.000
#> GSM1233017 2 0.5397 0.5420 0.280 0.720 0.000
#> GSM1233020 2 0.7310 0.2823 0.040 0.600 0.360
#> GSM1233022 1 0.5835 0.4353 0.660 0.340 0.000
#> GSM1233026 2 0.6111 0.1016 0.396 0.604 0.000
#> GSM1233028 2 0.5178 0.5812 0.256 0.744 0.000
#> GSM1233034 2 0.0000 0.7212 0.000 1.000 0.000
#> GSM1233040 2 0.2625 0.6934 0.000 0.916 0.084
#> GSM1233048 2 0.1860 0.7077 0.052 0.948 0.000
#> GSM1233056 1 0.1753 0.7072 0.952 0.000 0.048
#> GSM1233058 1 0.2959 0.7249 0.900 0.100 0.000
#> GSM1233059 2 0.4750 0.5401 0.216 0.784 0.000
#> GSM1233066 3 0.0237 0.8402 0.000 0.004 0.996
#> GSM1233071 2 0.1643 0.7209 0.044 0.956 0.000
#> GSM1233074 3 0.3192 0.7959 0.000 0.112 0.888
#> GSM1233076 1 0.5926 0.3095 0.644 0.000 0.356
#> GSM1233080 1 0.7030 0.3298 0.580 0.396 0.024
#> GSM1233088 2 0.3879 0.6357 0.000 0.848 0.152
#> GSM1233090 2 0.6814 0.3069 0.020 0.608 0.372
#> GSM1233092 1 0.1163 0.7301 0.972 0.028 0.000
#> GSM1233094 1 0.4399 0.6756 0.812 0.188 0.000
#> GSM1233097 1 0.4062 0.6931 0.836 0.164 0.000
#> GSM1233100 2 0.6302 -0.0269 0.480 0.520 0.000
#> GSM1233104 1 0.4235 0.6848 0.824 0.176 0.000
#> GSM1233106 2 0.1182 0.7206 0.012 0.976 0.012
#> GSM1233111 2 0.2703 0.7006 0.056 0.928 0.016
#> GSM1233122 2 0.6111 0.3476 0.396 0.604 0.000
#> GSM1233146 1 0.4504 0.6695 0.804 0.196 0.000
#> GSM1232994 2 0.5650 0.4989 0.312 0.688 0.000
#> GSM1232996 2 0.5573 0.6534 0.160 0.796 0.044
#> GSM1232997 3 0.5216 0.6518 0.000 0.260 0.740
#> GSM1232998 1 0.4178 0.6859 0.828 0.172 0.000
#> GSM1232999 1 0.5733 0.4816 0.676 0.324 0.000
#> GSM1233000 2 0.0892 0.7231 0.020 0.980 0.000
#> GSM1233004 3 0.5138 0.6345 0.252 0.000 0.748
#> GSM1233011 3 0.4887 0.6663 0.228 0.000 0.772
#> GSM1233012 3 0.5948 0.4925 0.000 0.360 0.640
#> GSM1233023 3 0.6154 0.3936 0.000 0.408 0.592
#> GSM1233027 1 0.4654 0.6652 0.792 0.208 0.000
#> GSM1233033 1 0.5244 0.5903 0.756 0.240 0.004
#> GSM1233036 3 0.6260 0.2874 0.000 0.448 0.552
#> GSM1233037 2 0.2356 0.6925 0.000 0.928 0.072
#> GSM1233041 1 0.7067 0.2007 0.512 0.468 0.020
#> GSM1233045 2 0.5988 0.2911 0.368 0.632 0.000
#> GSM1233047 3 0.2448 0.8181 0.000 0.076 0.924
#> GSM1233050 2 0.3340 0.6658 0.000 0.880 0.120
#> GSM1233052 2 0.3482 0.6427 0.128 0.872 0.000
#> GSM1233053 2 0.6286 -0.0403 0.000 0.536 0.464
#> GSM1233055 1 0.0000 0.7259 1.000 0.000 0.000
#> GSM1233061 3 0.1163 0.8378 0.000 0.028 0.972
#> GSM1233063 1 0.6654 0.2424 0.536 0.456 0.008
#> GSM1233065 3 0.5591 0.5908 0.000 0.304 0.696
#> GSM1233070 1 0.6126 0.3327 0.600 0.400 0.000
#> GSM1233077 3 0.0000 0.8396 0.000 0.000 1.000
#> GSM1233081 3 0.0000 0.8396 0.000 0.000 1.000
#> GSM1233084 1 0.7820 0.4092 0.604 0.324 0.072
#> GSM1233087 1 0.0237 0.7271 0.996 0.004 0.000
#> GSM1233089 3 0.7770 0.5494 0.088 0.272 0.640
#> GSM1233099 1 0.4931 0.6281 0.768 0.232 0.000
#> GSM1233112 3 0.5835 0.4589 0.340 0.000 0.660
#> GSM1233085 3 0.0237 0.8402 0.000 0.004 0.996
#> GSM1233098 2 0.6482 0.5416 0.244 0.716 0.040
#> GSM1233114 1 0.4654 0.6577 0.792 0.208 0.000
#> GSM1233119 1 0.0424 0.7280 0.992 0.008 0.000
#> GSM1233129 3 0.5397 0.6246 0.000 0.280 0.720
#> GSM1233132 1 0.5785 0.4533 0.668 0.332 0.000
#> GSM1233139 2 0.0237 0.7216 0.000 0.996 0.004
#> GSM1233143 3 0.6244 0.3138 0.000 0.440 0.560
#> GSM1233145 1 0.0000 0.7259 1.000 0.000 0.000
#> GSM1233067 3 0.2165 0.8245 0.000 0.064 0.936
#> GSM1233069 3 0.0424 0.8401 0.000 0.008 0.992
#> GSM1233072 1 0.8398 0.0193 0.476 0.440 0.084
#> GSM1233086 3 0.0747 0.8401 0.000 0.016 0.984
#> GSM1233102 1 0.0000 0.7259 1.000 0.000 0.000
#> GSM1233103 2 0.2878 0.7051 0.096 0.904 0.000
#> GSM1233107 2 0.6168 0.3113 0.412 0.588 0.000
#> GSM1233108 3 0.0424 0.8373 0.008 0.000 0.992
#> GSM1233109 3 0.0424 0.8373 0.008 0.000 0.992
#> GSM1233110 3 0.0237 0.8402 0.000 0.004 0.996
#> GSM1233113 3 0.4291 0.7396 0.000 0.180 0.820
#> GSM1233116 3 0.1411 0.8356 0.000 0.036 0.964
#> GSM1233120 1 0.0424 0.7280 0.992 0.008 0.000
#> GSM1233121 3 0.0237 0.8402 0.000 0.004 0.996
#> GSM1233123 3 0.0424 0.8401 0.000 0.008 0.992
#> GSM1233124 3 0.0892 0.8391 0.000 0.020 0.980
#> GSM1233125 3 0.0592 0.8357 0.012 0.000 0.988
#> GSM1233126 1 0.0747 0.7292 0.984 0.016 0.000
#> GSM1233127 2 0.6267 0.2020 0.452 0.548 0.000
#> GSM1233128 3 0.6460 0.2618 0.440 0.004 0.556
#> GSM1233130 3 0.0000 0.8396 0.000 0.000 1.000
#> GSM1233131 1 0.4931 0.6467 0.768 0.232 0.000
#> GSM1233133 3 0.0000 0.8396 0.000 0.000 1.000
#> GSM1233134 3 0.1860 0.8295 0.000 0.052 0.948
#> GSM1233135 3 0.0237 0.8402 0.000 0.004 0.996
#> GSM1233136 3 0.0237 0.8387 0.004 0.000 0.996
#> GSM1233137 3 0.1031 0.8386 0.000 0.024 0.976
#> GSM1233138 1 0.1289 0.7304 0.968 0.032 0.000
#> GSM1233140 3 0.0237 0.8394 0.000 0.004 0.996
#> GSM1233141 2 0.6079 0.3553 0.388 0.612 0.000
#> GSM1233142 2 0.6095 0.3521 0.392 0.608 0.000
#> GSM1233144 3 0.0237 0.8402 0.000 0.004 0.996
#> GSM1233147 1 0.6180 0.1438 0.584 0.000 0.416
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.3577 0.5573 0.000 0.832 0.156 0.012
#> GSM1233002 2 0.6840 0.0356 0.100 0.468 0.000 0.432
#> GSM1233003 4 0.6922 0.3499 0.308 0.060 0.036 0.596
#> GSM1233014 4 0.4605 0.4978 0.000 0.336 0.000 0.664
#> GSM1233015 1 0.3801 0.6349 0.780 0.220 0.000 0.000
#> GSM1233016 4 0.5982 0.5479 0.204 0.112 0.000 0.684
#> GSM1233024 2 0.4669 0.5590 0.104 0.796 0.000 0.100
#> GSM1233049 3 0.1398 0.8076 0.004 0.000 0.956 0.040
#> GSM1233064 2 0.9209 0.2570 0.224 0.440 0.224 0.112
#> GSM1233068 1 0.4304 0.5771 0.716 0.284 0.000 0.000
#> GSM1233073 4 0.6050 0.5854 0.112 0.212 0.000 0.676
#> GSM1233093 1 0.2973 0.5995 0.856 0.000 0.000 0.144
#> GSM1233115 4 0.6692 0.1724 0.376 0.052 0.020 0.552
#> GSM1232992 2 0.3942 0.4350 0.236 0.764 0.000 0.000
#> GSM1232993 2 0.4897 0.2735 0.332 0.660 0.000 0.008
#> GSM1233005 2 0.4485 0.5164 0.028 0.772 0.000 0.200
#> GSM1233007 4 0.5047 0.4171 0.016 0.316 0.000 0.668
#> GSM1233010 1 0.4678 0.4919 0.744 0.024 0.000 0.232
#> GSM1233013 2 0.2662 0.5704 0.084 0.900 0.016 0.000
#> GSM1233018 2 0.2981 0.5692 0.092 0.888 0.016 0.004
#> GSM1233019 2 0.2329 0.5841 0.012 0.916 0.000 0.072
#> GSM1233021 2 0.3229 0.6023 0.072 0.880 0.000 0.048
#> GSM1233025 4 0.4399 0.5204 0.212 0.020 0.000 0.768
#> GSM1233029 1 0.5165 0.1893 0.512 0.484 0.000 0.004
#> GSM1233030 2 0.4713 0.2008 0.360 0.640 0.000 0.000
#> GSM1233031 1 0.5271 0.4865 0.656 0.320 0.000 0.024
#> GSM1233032 1 0.6242 0.4437 0.612 0.080 0.308 0.000
#> GSM1233035 1 0.5742 0.5909 0.664 0.276 0.000 0.060
#> GSM1233038 4 0.5716 0.4802 0.252 0.068 0.000 0.680
#> GSM1233039 1 0.6556 0.4700 0.604 0.320 0.020 0.056
#> GSM1233042 4 0.4564 0.5063 0.000 0.328 0.000 0.672
#> GSM1233043 4 0.4500 0.5125 0.000 0.316 0.000 0.684
#> GSM1233044 2 0.7500 -0.0584 0.000 0.416 0.180 0.404
#> GSM1233046 2 0.5979 0.4250 0.136 0.692 0.000 0.172
#> GSM1233051 1 0.3958 0.5889 0.824 0.000 0.032 0.144
#> GSM1233054 3 0.6615 0.2593 0.084 0.404 0.512 0.000
#> GSM1233057 2 0.6429 0.3652 0.160 0.648 0.192 0.000
#> GSM1233060 1 0.4382 0.5743 0.704 0.296 0.000 0.000
#> GSM1233062 2 0.4939 0.4594 0.220 0.740 0.000 0.040
#> GSM1233075 3 0.2081 0.8068 0.000 0.084 0.916 0.000
#> GSM1233078 3 0.0188 0.8212 0.000 0.000 0.996 0.004
#> GSM1233079 3 0.3117 0.7644 0.092 0.000 0.880 0.028
#> GSM1233082 1 0.1557 0.6922 0.944 0.056 0.000 0.000
#> GSM1233083 4 0.2670 0.6037 0.024 0.000 0.072 0.904
#> GSM1233091 1 0.6011 0.4004 0.588 0.372 0.012 0.028
#> GSM1233095 4 0.6878 0.1767 0.348 0.008 0.092 0.552
#> GSM1233096 1 0.2081 0.6912 0.916 0.084 0.000 0.000
#> GSM1233101 3 0.5838 0.2938 0.016 0.012 0.560 0.412
#> GSM1233105 1 0.6016 0.2878 0.632 0.068 0.000 0.300
#> GSM1233117 2 0.5106 0.4945 0.000 0.720 0.240 0.040
#> GSM1233118 3 0.4454 0.5827 0.000 0.308 0.692 0.000
#> GSM1233001 2 0.6724 0.3092 0.224 0.612 0.164 0.000
#> GSM1233006 4 0.4843 0.3907 0.000 0.396 0.000 0.604
#> GSM1233008 2 0.2207 0.5907 0.040 0.932 0.024 0.004
#> GSM1233009 2 0.4720 0.2682 0.324 0.672 0.004 0.000
#> GSM1233017 2 0.2021 0.5948 0.040 0.936 0.000 0.024
#> GSM1233020 2 0.3984 0.5623 0.000 0.828 0.040 0.132
#> GSM1233022 2 0.6561 0.1125 0.092 0.564 0.000 0.344
#> GSM1233026 1 0.4008 0.6305 0.820 0.148 0.000 0.032
#> GSM1233028 2 0.3959 0.5934 0.092 0.840 0.000 0.068
#> GSM1233034 1 0.5168 0.1936 0.504 0.492 0.004 0.000
#> GSM1233040 1 0.1940 0.6921 0.924 0.076 0.000 0.000
#> GSM1233048 1 0.2530 0.6856 0.888 0.112 0.000 0.000
#> GSM1233056 4 0.5485 0.5888 0.096 0.048 0.076 0.780
#> GSM1233058 4 0.4866 0.3066 0.000 0.404 0.000 0.596
#> GSM1233059 1 0.0817 0.6874 0.976 0.024 0.000 0.000
#> GSM1233066 3 0.0707 0.8239 0.000 0.020 0.980 0.000
#> GSM1233071 1 0.5080 0.4086 0.576 0.420 0.000 0.004
#> GSM1233074 3 0.3539 0.7339 0.004 0.176 0.820 0.000
#> GSM1233076 4 0.4919 0.5166 0.000 0.048 0.200 0.752
#> GSM1233080 1 0.4678 0.4986 0.744 0.000 0.024 0.232
#> GSM1233088 1 0.6307 0.4939 0.620 0.288 0.092 0.000
#> GSM1233090 1 0.1631 0.6853 0.956 0.020 0.016 0.008
#> GSM1233092 4 0.3942 0.5889 0.000 0.236 0.000 0.764
#> GSM1233094 4 0.5626 0.4162 0.028 0.384 0.000 0.588
#> GSM1233097 2 0.4999 -0.1508 0.000 0.508 0.000 0.492
#> GSM1233100 2 0.7883 0.1248 0.300 0.384 0.000 0.316
#> GSM1233104 2 0.4994 -0.1729 0.000 0.520 0.000 0.480
#> GSM1233106 1 0.2469 0.6869 0.892 0.108 0.000 0.000
#> GSM1233111 1 0.1637 0.6922 0.940 0.060 0.000 0.000
#> GSM1233122 2 0.2081 0.5714 0.000 0.916 0.000 0.084
#> GSM1233146 4 0.6498 0.3239 0.072 0.440 0.000 0.488
#> GSM1232994 2 0.2759 0.5970 0.044 0.904 0.000 0.052
#> GSM1232996 2 0.3789 0.5630 0.020 0.836 0.004 0.140
#> GSM1232997 3 0.5088 0.3539 0.004 0.424 0.572 0.000
#> GSM1232998 2 0.4994 -0.1322 0.000 0.520 0.000 0.480
#> GSM1232999 2 0.5339 0.1819 0.016 0.600 0.000 0.384
#> GSM1233000 2 0.3636 0.5077 0.172 0.820 0.000 0.008
#> GSM1233004 4 0.7067 0.3517 0.000 0.160 0.288 0.552
#> GSM1233011 3 0.6299 0.1988 0.000 0.060 0.520 0.420
#> GSM1233012 3 0.5143 0.2656 0.004 0.456 0.540 0.000
#> GSM1233023 2 0.6126 0.3177 0.064 0.632 0.300 0.004
#> GSM1233027 4 0.5693 0.0972 0.024 0.472 0.000 0.504
#> GSM1233033 1 0.5630 0.2528 0.608 0.032 0.000 0.360
#> GSM1233036 2 0.5407 -0.1535 0.012 0.504 0.484 0.000
#> GSM1233037 2 0.6079 -0.1660 0.464 0.492 0.044 0.000
#> GSM1233041 1 0.2466 0.6275 0.900 0.000 0.004 0.096
#> GSM1233045 2 0.5997 0.2216 0.048 0.576 0.000 0.376
#> GSM1233047 3 0.2530 0.7906 0.000 0.112 0.888 0.000
#> GSM1233050 1 0.4883 0.5723 0.696 0.288 0.016 0.000
#> GSM1233052 1 0.4328 0.6161 0.748 0.244 0.000 0.008
#> GSM1233053 3 0.6857 0.2240 0.104 0.404 0.492 0.000
#> GSM1233055 4 0.2088 0.6177 0.064 0.004 0.004 0.928
#> GSM1233061 3 0.1302 0.8222 0.000 0.044 0.956 0.000
#> GSM1233063 1 0.2530 0.6257 0.896 0.000 0.004 0.100
#> GSM1233065 2 0.6337 0.1778 0.000 0.568 0.360 0.072
#> GSM1233070 2 0.6737 0.0891 0.092 0.488 0.000 0.420
#> GSM1233077 3 0.1970 0.8047 0.000 0.008 0.932 0.060
#> GSM1233081 3 0.0469 0.8186 0.000 0.000 0.988 0.012
#> GSM1233084 1 0.6120 0.1643 0.540 0.004 0.040 0.416
#> GSM1233087 4 0.1716 0.6248 0.000 0.064 0.000 0.936
#> GSM1233089 2 0.6762 0.2142 0.000 0.536 0.104 0.360
#> GSM1233099 2 0.4955 -0.0771 0.000 0.556 0.000 0.444
#> GSM1233112 4 0.5837 0.2234 0.000 0.036 0.400 0.564
#> GSM1233085 3 0.0188 0.8229 0.000 0.004 0.996 0.000
#> GSM1233098 2 0.8065 0.3576 0.208 0.496 0.024 0.272
#> GSM1233114 2 0.7901 -0.2712 0.316 0.372 0.000 0.312
#> GSM1233119 4 0.5113 0.5389 0.024 0.292 0.000 0.684
#> GSM1233129 3 0.5167 0.1956 0.004 0.488 0.508 0.000
#> GSM1233132 2 0.7661 -0.0286 0.272 0.464 0.000 0.264
#> GSM1233139 2 0.4267 0.4647 0.188 0.788 0.024 0.000
#> GSM1233143 2 0.4898 0.1023 0.000 0.584 0.416 0.000
#> GSM1233145 4 0.3679 0.6293 0.060 0.084 0.000 0.856
#> GSM1233067 3 0.2216 0.8036 0.000 0.092 0.908 0.000
#> GSM1233069 3 0.0469 0.8241 0.000 0.012 0.988 0.000
#> GSM1233072 2 0.3895 0.4919 0.000 0.804 0.012 0.184
#> GSM1233086 3 0.6037 0.5782 0.000 0.160 0.688 0.152
#> GSM1233102 4 0.3707 0.6320 0.028 0.132 0.000 0.840
#> GSM1233103 1 0.5125 0.4759 0.604 0.388 0.000 0.008
#> GSM1233107 2 0.3108 0.5593 0.016 0.872 0.000 0.112
#> GSM1233108 3 0.1302 0.8085 0.000 0.000 0.956 0.044
#> GSM1233109 3 0.1557 0.8031 0.000 0.000 0.944 0.056
#> GSM1233110 3 0.0336 0.8239 0.000 0.008 0.992 0.000
#> GSM1233113 3 0.4679 0.4976 0.000 0.352 0.648 0.000
#> GSM1233116 3 0.1890 0.8205 0.000 0.056 0.936 0.008
#> GSM1233120 4 0.3636 0.6236 0.008 0.172 0.000 0.820
#> GSM1233121 3 0.1545 0.8144 0.000 0.008 0.952 0.040
#> GSM1233123 3 0.0469 0.8238 0.000 0.012 0.988 0.000
#> GSM1233124 3 0.1557 0.8203 0.000 0.056 0.944 0.000
#> GSM1233125 3 0.1807 0.7990 0.008 0.000 0.940 0.052
#> GSM1233126 4 0.4281 0.6215 0.028 0.180 0.000 0.792
#> GSM1233127 2 0.3024 0.5301 0.000 0.852 0.000 0.148
#> GSM1233128 4 0.7638 0.1693 0.308 0.000 0.232 0.460
#> GSM1233130 3 0.1211 0.8107 0.000 0.000 0.960 0.040
#> GSM1233131 1 0.6964 0.2296 0.584 0.188 0.000 0.228
#> GSM1233133 3 0.0000 0.8221 0.000 0.000 1.000 0.000
#> GSM1233134 3 0.2216 0.8030 0.000 0.092 0.908 0.000
#> GSM1233135 3 0.0469 0.8238 0.000 0.012 0.988 0.000
#> GSM1233136 3 0.4035 0.7023 0.000 0.020 0.804 0.176
#> GSM1233137 3 0.1474 0.8202 0.000 0.052 0.948 0.000
#> GSM1233138 4 0.5111 0.6116 0.056 0.204 0.000 0.740
#> GSM1233140 3 0.4418 0.6708 0.184 0.000 0.784 0.032
#> GSM1233141 2 0.2048 0.5850 0.000 0.928 0.008 0.064
#> GSM1233142 2 0.1356 0.5962 0.008 0.960 0.000 0.032
#> GSM1233144 3 0.0188 0.8229 0.000 0.004 0.996 0.000
#> GSM1233147 4 0.5466 0.4964 0.000 0.068 0.220 0.712
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.3003 0.64597 0.000 0.872 0.092 0.016 0.020
#> GSM1233002 5 0.5341 0.63129 0.124 0.212 0.000 0.000 0.664
#> GSM1233003 4 0.3012 0.64397 0.072 0.000 0.004 0.872 0.052
#> GSM1233014 4 0.3876 0.66380 0.000 0.192 0.000 0.776 0.032
#> GSM1233015 1 0.1851 0.75420 0.912 0.088 0.000 0.000 0.000
#> GSM1233016 4 0.1331 0.69765 0.008 0.040 0.000 0.952 0.000
#> GSM1233024 2 0.4080 0.45742 0.020 0.728 0.000 0.252 0.000
#> GSM1233049 3 0.0727 0.83531 0.004 0.000 0.980 0.012 0.004
#> GSM1233064 5 0.5955 0.57612 0.172 0.216 0.004 0.000 0.608
#> GSM1233068 1 0.2674 0.73848 0.868 0.120 0.000 0.000 0.012
#> GSM1233073 4 0.3346 0.69696 0.000 0.092 0.000 0.844 0.064
#> GSM1233093 1 0.3752 0.68702 0.812 0.004 0.000 0.044 0.140
#> GSM1233115 5 0.1818 0.69523 0.044 0.024 0.000 0.000 0.932
#> GSM1232992 2 0.4104 0.55903 0.220 0.748 0.000 0.000 0.032
#> GSM1232993 2 0.4201 0.41279 0.328 0.664 0.000 0.000 0.008
#> GSM1233005 5 0.4798 0.28248 0.012 0.472 0.000 0.004 0.512
#> GSM1233007 5 0.2068 0.70689 0.000 0.092 0.000 0.004 0.904
#> GSM1233010 1 0.3812 0.70191 0.828 0.012 0.000 0.080 0.080
#> GSM1233013 2 0.1644 0.66469 0.048 0.940 0.004 0.000 0.008
#> GSM1233018 2 0.3991 0.53984 0.048 0.780 0.000 0.000 0.172
#> GSM1233019 2 0.2612 0.60811 0.000 0.868 0.000 0.124 0.008
#> GSM1233021 2 0.4498 0.37790 0.032 0.688 0.000 0.000 0.280
#> GSM1233025 4 0.4161 0.58020 0.040 0.000 0.000 0.752 0.208
#> GSM1233029 1 0.4288 0.36366 0.612 0.384 0.000 0.000 0.004
#> GSM1233030 2 0.3123 0.62858 0.160 0.828 0.000 0.012 0.000
#> GSM1233031 1 0.6170 0.23840 0.492 0.384 0.000 0.120 0.004
#> GSM1233032 1 0.4591 0.41215 0.648 0.008 0.332 0.012 0.000
#> GSM1233035 4 0.5809 0.34364 0.084 0.384 0.004 0.528 0.000
#> GSM1233038 4 0.3255 0.62908 0.052 0.000 0.000 0.848 0.100
#> GSM1233039 1 0.5996 0.20559 0.512 0.120 0.000 0.000 0.368
#> GSM1233042 5 0.6096 0.33569 0.000 0.148 0.000 0.316 0.536
#> GSM1233043 5 0.6218 0.22714 0.000 0.148 0.000 0.364 0.488
#> GSM1233044 2 0.7877 -0.10450 0.000 0.332 0.268 0.332 0.068
#> GSM1233046 4 0.4306 0.12214 0.000 0.492 0.000 0.508 0.000
#> GSM1233051 1 0.4242 0.66099 0.796 0.000 0.032 0.136 0.036
#> GSM1233054 3 0.6273 0.02778 0.128 0.428 0.440 0.000 0.004
#> GSM1233057 2 0.4740 0.55833 0.204 0.728 0.060 0.000 0.008
#> GSM1233060 1 0.2605 0.72735 0.852 0.148 0.000 0.000 0.000
#> GSM1233062 2 0.4075 0.61960 0.096 0.800 0.000 0.100 0.004
#> GSM1233075 3 0.1671 0.82794 0.000 0.076 0.924 0.000 0.000
#> GSM1233078 3 0.0451 0.83969 0.000 0.004 0.988 0.000 0.008
#> GSM1233079 3 0.4552 0.65674 0.176 0.000 0.760 0.024 0.040
#> GSM1233082 1 0.1484 0.76358 0.944 0.048 0.000 0.008 0.000
#> GSM1233083 5 0.4455 0.45282 0.012 0.000 0.032 0.216 0.740
#> GSM1233091 1 0.5449 0.48092 0.636 0.108 0.000 0.000 0.256
#> GSM1233095 5 0.3222 0.63835 0.108 0.000 0.004 0.036 0.852
#> GSM1233096 1 0.1469 0.76165 0.948 0.036 0.000 0.016 0.000
#> GSM1233101 5 0.4082 0.61862 0.036 0.000 0.164 0.012 0.788
#> GSM1233105 4 0.2426 0.68622 0.064 0.036 0.000 0.900 0.000
#> GSM1233117 2 0.4915 0.52272 0.000 0.696 0.236 0.064 0.004
#> GSM1233118 3 0.4323 0.51128 0.000 0.332 0.656 0.000 0.012
#> GSM1233001 2 0.5496 0.46496 0.256 0.660 0.028 0.000 0.056
#> GSM1233006 4 0.4883 0.53600 0.000 0.300 0.000 0.652 0.048
#> GSM1233008 2 0.1405 0.66024 0.016 0.956 0.008 0.000 0.020
#> GSM1233009 2 0.2806 0.63373 0.152 0.844 0.000 0.004 0.000
#> GSM1233017 2 0.2929 0.58816 0.008 0.840 0.000 0.152 0.000
#> GSM1233020 2 0.3491 0.49089 0.000 0.768 0.000 0.004 0.228
#> GSM1233022 4 0.3715 0.61419 0.004 0.260 0.000 0.736 0.000
#> GSM1233026 1 0.5411 0.59946 0.692 0.072 0.000 0.028 0.208
#> GSM1233028 2 0.3437 0.60553 0.048 0.832 0.000 0.000 0.120
#> GSM1233034 1 0.4674 0.25310 0.568 0.416 0.000 0.000 0.016
#> GSM1233040 1 0.1461 0.75291 0.952 0.016 0.004 0.028 0.000
#> GSM1233048 1 0.1732 0.75664 0.920 0.080 0.000 0.000 0.000
#> GSM1233056 4 0.5601 0.37471 0.028 0.000 0.040 0.600 0.332
#> GSM1233058 5 0.2513 0.70816 0.008 0.116 0.000 0.000 0.876
#> GSM1233059 1 0.0566 0.75919 0.984 0.012 0.000 0.004 0.000
#> GSM1233066 3 0.0404 0.84228 0.000 0.012 0.988 0.000 0.000
#> GSM1233071 2 0.4822 0.46745 0.288 0.664 0.000 0.048 0.000
#> GSM1233074 3 0.3109 0.72082 0.000 0.200 0.800 0.000 0.000
#> GSM1233076 5 0.0932 0.67974 0.000 0.004 0.004 0.020 0.972
#> GSM1233080 1 0.4210 0.65380 0.780 0.000 0.000 0.096 0.124
#> GSM1233088 1 0.3326 0.71126 0.824 0.152 0.000 0.000 0.024
#> GSM1233090 1 0.0451 0.75532 0.988 0.000 0.000 0.008 0.004
#> GSM1233092 4 0.5254 0.51695 0.000 0.084 0.000 0.644 0.272
#> GSM1233094 4 0.4221 0.62779 0.000 0.236 0.000 0.732 0.032
#> GSM1233097 5 0.3366 0.66800 0.000 0.232 0.000 0.000 0.768
#> GSM1233100 1 0.6298 0.52631 0.608 0.200 0.000 0.024 0.168
#> GSM1233104 2 0.6191 -0.20866 0.000 0.440 0.000 0.136 0.424
#> GSM1233106 1 0.1195 0.76125 0.960 0.028 0.000 0.012 0.000
#> GSM1233111 1 0.1485 0.76065 0.948 0.032 0.000 0.020 0.000
#> GSM1233122 2 0.2270 0.63668 0.000 0.904 0.000 0.076 0.020
#> GSM1233146 4 0.6631 0.32934 0.000 0.324 0.000 0.440 0.236
#> GSM1232994 2 0.2032 0.64958 0.004 0.924 0.000 0.052 0.020
#> GSM1232996 2 0.4457 0.28561 0.012 0.656 0.000 0.004 0.328
#> GSM1232997 2 0.6082 0.26326 0.024 0.556 0.344 0.000 0.076
#> GSM1232998 5 0.5252 0.56232 0.000 0.292 0.000 0.076 0.632
#> GSM1232999 5 0.4627 0.36439 0.000 0.444 0.000 0.012 0.544
#> GSM1233000 2 0.2519 0.65816 0.100 0.884 0.000 0.000 0.016
#> GSM1233004 5 0.1443 0.69843 0.004 0.044 0.004 0.000 0.948
#> GSM1233011 5 0.4371 0.61084 0.000 0.028 0.164 0.032 0.776
#> GSM1233012 3 0.4420 0.24503 0.000 0.448 0.548 0.004 0.000
#> GSM1233023 2 0.5475 0.54074 0.092 0.720 0.052 0.000 0.136
#> GSM1233027 5 0.4758 0.61610 0.012 0.288 0.000 0.024 0.676
#> GSM1233033 4 0.3355 0.59568 0.184 0.000 0.000 0.804 0.012
#> GSM1233036 3 0.4448 0.14861 0.000 0.480 0.516 0.000 0.004
#> GSM1233037 2 0.4538 0.36321 0.348 0.636 0.012 0.000 0.004
#> GSM1233041 1 0.4184 0.58906 0.740 0.000 0.004 0.232 0.024
#> GSM1233045 5 0.4024 0.67262 0.028 0.220 0.000 0.000 0.752
#> GSM1233047 3 0.1851 0.82231 0.000 0.088 0.912 0.000 0.000
#> GSM1233050 1 0.2305 0.75401 0.896 0.092 0.000 0.000 0.012
#> GSM1233052 1 0.2727 0.74051 0.868 0.116 0.000 0.000 0.016
#> GSM1233053 3 0.5928 0.35266 0.124 0.328 0.548 0.000 0.000
#> GSM1233055 5 0.3484 0.56045 0.024 0.000 0.004 0.152 0.820
#> GSM1233061 3 0.1043 0.84081 0.000 0.040 0.960 0.000 0.000
#> GSM1233063 1 0.5050 0.49929 0.664 0.000 0.008 0.280 0.048
#> GSM1233065 2 0.5499 -0.22890 0.020 0.480 0.028 0.000 0.472
#> GSM1233070 5 0.6338 0.43535 0.140 0.332 0.000 0.008 0.520
#> GSM1233077 3 0.3333 0.67915 0.000 0.004 0.788 0.000 0.208
#> GSM1233081 3 0.0404 0.83754 0.000 0.000 0.988 0.000 0.012
#> GSM1233084 1 0.6400 0.39891 0.580 0.000 0.032 0.272 0.116
#> GSM1233087 5 0.1862 0.66991 0.004 0.016 0.000 0.048 0.932
#> GSM1233089 5 0.4879 0.60076 0.000 0.276 0.024 0.020 0.680
#> GSM1233099 2 0.6081 -0.00969 0.000 0.496 0.000 0.128 0.376
#> GSM1233112 4 0.6509 0.31972 0.000 0.008 0.340 0.492 0.160
#> GSM1233085 3 0.0290 0.84181 0.000 0.008 0.992 0.000 0.000
#> GSM1233098 5 0.6106 0.56296 0.176 0.236 0.000 0.004 0.584
#> GSM1233114 4 0.4318 0.57022 0.008 0.296 0.000 0.688 0.008
#> GSM1233119 4 0.5325 0.54567 0.000 0.088 0.000 0.636 0.276
#> GSM1233129 2 0.4648 -0.01875 0.000 0.524 0.464 0.000 0.012
#> GSM1233132 4 0.4253 0.52955 0.004 0.332 0.000 0.660 0.004
#> GSM1233139 2 0.2520 0.66183 0.096 0.888 0.004 0.012 0.000
#> GSM1233143 2 0.5865 0.23754 0.000 0.532 0.360 0.108 0.000
#> GSM1233145 4 0.3106 0.66688 0.000 0.020 0.000 0.840 0.140
#> GSM1233067 3 0.2377 0.79253 0.000 0.128 0.872 0.000 0.000
#> GSM1233069 3 0.0579 0.84092 0.000 0.008 0.984 0.000 0.008
#> GSM1233072 2 0.3879 0.54342 0.000 0.784 0.012 0.188 0.016
#> GSM1233086 5 0.6086 0.49427 0.000 0.152 0.304 0.000 0.544
#> GSM1233102 4 0.2592 0.69306 0.000 0.052 0.000 0.892 0.056
#> GSM1233103 1 0.5199 0.28369 0.548 0.412 0.000 0.036 0.004
#> GSM1233107 2 0.4593 -0.17373 0.004 0.512 0.000 0.480 0.004
#> GSM1233108 3 0.2162 0.80720 0.008 0.000 0.916 0.012 0.064
#> GSM1233109 3 0.2193 0.79441 0.000 0.000 0.900 0.008 0.092
#> GSM1233110 3 0.0290 0.84177 0.000 0.008 0.992 0.000 0.000
#> GSM1233113 3 0.4415 0.39266 0.000 0.388 0.604 0.000 0.008
#> GSM1233116 3 0.1211 0.84171 0.000 0.024 0.960 0.000 0.016
#> GSM1233120 4 0.5181 0.38305 0.000 0.052 0.000 0.588 0.360
#> GSM1233121 3 0.3318 0.70074 0.000 0.012 0.808 0.000 0.180
#> GSM1233123 3 0.0290 0.84177 0.000 0.008 0.992 0.000 0.000
#> GSM1233124 3 0.1197 0.83987 0.000 0.048 0.952 0.000 0.000
#> GSM1233125 3 0.2765 0.79155 0.024 0.000 0.896 0.036 0.044
#> GSM1233126 4 0.2248 0.70213 0.000 0.088 0.000 0.900 0.012
#> GSM1233127 2 0.4046 0.37272 0.000 0.696 0.000 0.296 0.008
#> GSM1233128 4 0.7817 0.31264 0.116 0.000 0.200 0.468 0.216
#> GSM1233130 3 0.1502 0.82163 0.000 0.004 0.940 0.000 0.056
#> GSM1233131 4 0.6546 0.49510 0.240 0.192 0.000 0.552 0.016
#> GSM1233133 3 0.0162 0.84114 0.000 0.004 0.996 0.000 0.000
#> GSM1233134 3 0.1792 0.82379 0.000 0.084 0.916 0.000 0.000
#> GSM1233135 3 0.0404 0.84194 0.000 0.012 0.988 0.000 0.000
#> GSM1233136 5 0.4455 0.54568 0.000 0.036 0.260 0.000 0.704
#> GSM1233137 3 0.1410 0.83565 0.000 0.060 0.940 0.000 0.000
#> GSM1233138 4 0.2824 0.70405 0.000 0.096 0.000 0.872 0.032
#> GSM1233140 3 0.3919 0.72330 0.100 0.000 0.816 0.076 0.008
#> GSM1233141 2 0.3060 0.60507 0.000 0.848 0.000 0.128 0.024
#> GSM1233142 2 0.2488 0.60883 0.000 0.872 0.000 0.124 0.004
#> GSM1233144 3 0.0000 0.84004 0.000 0.000 1.000 0.000 0.000
#> GSM1233147 5 0.1904 0.68596 0.000 0.020 0.016 0.028 0.936
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.2898 0.50857 0.000 0.868 0.060 0.000 0.056 0.016
#> GSM1233002 6 0.5819 0.38202 0.112 0.344 0.000 0.008 0.012 0.524
#> GSM1233003 4 0.3373 0.57325 0.032 0.000 0.000 0.816 0.140 0.012
#> GSM1233014 4 0.3007 0.60941 0.000 0.080 0.000 0.860 0.040 0.020
#> GSM1233015 1 0.1908 0.67875 0.916 0.056 0.000 0.000 0.028 0.000
#> GSM1233016 4 0.2914 0.58572 0.008 0.004 0.000 0.832 0.152 0.004
#> GSM1233024 2 0.6101 0.04107 0.028 0.536 0.000 0.184 0.252 0.000
#> GSM1233049 3 0.3090 0.74669 0.008 0.000 0.864 0.060 0.052 0.016
#> GSM1233064 6 0.5874 0.21679 0.120 0.400 0.012 0.000 0.004 0.464
#> GSM1233068 1 0.2783 0.64511 0.836 0.148 0.000 0.000 0.000 0.016
#> GSM1233073 4 0.2307 0.61881 0.012 0.020 0.000 0.904 0.060 0.004
#> GSM1233093 1 0.4448 0.61191 0.756 0.000 0.000 0.032 0.112 0.100
#> GSM1233115 6 0.3323 0.55308 0.020 0.028 0.000 0.004 0.112 0.836
#> GSM1232992 2 0.4244 0.47037 0.188 0.732 0.004 0.000 0.000 0.076
#> GSM1232993 2 0.4982 0.25678 0.368 0.580 0.000 0.012 0.024 0.016
#> GSM1233005 6 0.5717 0.28827 0.024 0.440 0.000 0.000 0.088 0.448
#> GSM1233007 6 0.4650 0.46433 0.044 0.288 0.004 0.008 0.000 0.656
#> GSM1233010 5 0.5176 0.25373 0.236 0.004 0.000 0.016 0.652 0.092
#> GSM1233013 2 0.1972 0.53784 0.056 0.916 0.004 0.000 0.000 0.024
#> GSM1233018 2 0.4117 0.43484 0.096 0.756 0.000 0.000 0.004 0.144
#> GSM1233019 2 0.3315 0.48742 0.008 0.836 0.000 0.116 0.024 0.016
#> GSM1233021 2 0.4867 0.17767 0.044 0.640 0.000 0.000 0.024 0.292
#> GSM1233025 5 0.6791 -0.07905 0.032 0.000 0.004 0.316 0.380 0.268
#> GSM1233029 1 0.4582 0.46171 0.652 0.296 0.000 0.000 0.040 0.012
#> GSM1233030 2 0.3641 0.47835 0.224 0.748 0.000 0.000 0.028 0.000
#> GSM1233031 5 0.5652 0.45501 0.120 0.220 0.000 0.040 0.620 0.000
#> GSM1233032 1 0.5067 0.39650 0.596 0.000 0.312 0.004 0.088 0.000
#> GSM1233035 5 0.6867 0.26898 0.048 0.308 0.000 0.272 0.372 0.000
#> GSM1233038 4 0.4492 0.49129 0.032 0.000 0.000 0.712 0.220 0.036
#> GSM1233039 6 0.6361 0.21225 0.324 0.208 0.004 0.000 0.016 0.448
#> GSM1233042 4 0.6199 0.50134 0.024 0.108 0.000 0.636 0.088 0.144
#> GSM1233043 4 0.5801 0.52860 0.016 0.100 0.000 0.668 0.080 0.136
#> GSM1233044 5 0.8127 0.24002 0.000 0.208 0.264 0.080 0.364 0.084
#> GSM1233046 4 0.5666 0.00887 0.000 0.388 0.000 0.456 0.156 0.000
#> GSM1233051 1 0.6732 0.50057 0.568 0.028 0.004 0.060 0.208 0.132
#> GSM1233054 3 0.6392 0.23266 0.220 0.284 0.472 0.000 0.020 0.004
#> GSM1233057 2 0.4335 0.52393 0.176 0.752 0.044 0.000 0.016 0.012
#> GSM1233060 1 0.2993 0.66297 0.844 0.120 0.000 0.008 0.028 0.000
#> GSM1233062 2 0.6256 -0.01901 0.112 0.496 0.000 0.056 0.336 0.000
#> GSM1233075 3 0.3904 0.64130 0.000 0.232 0.732 0.000 0.004 0.032
#> GSM1233078 3 0.1010 0.78847 0.000 0.004 0.960 0.000 0.000 0.036
#> GSM1233079 3 0.5173 0.55982 0.220 0.000 0.668 0.004 0.028 0.080
#> GSM1233082 1 0.3037 0.63995 0.808 0.016 0.000 0.000 0.176 0.000
#> GSM1233083 6 0.5210 0.29644 0.004 0.000 0.020 0.228 0.092 0.656
#> GSM1233091 1 0.5802 0.45088 0.624 0.140 0.000 0.000 0.056 0.180
#> GSM1233095 6 0.6147 0.41642 0.136 0.004 0.012 0.028 0.236 0.584
#> GSM1233096 1 0.1657 0.67865 0.928 0.016 0.000 0.000 0.056 0.000
#> GSM1233101 6 0.7672 0.48394 0.064 0.080 0.112 0.024 0.200 0.520
#> GSM1233105 4 0.3843 0.55011 0.104 0.004 0.000 0.784 0.108 0.000
#> GSM1233117 2 0.4617 0.43586 0.000 0.732 0.164 0.036 0.068 0.000
#> GSM1233118 3 0.3991 0.62974 0.000 0.240 0.724 0.000 0.028 0.008
#> GSM1233001 2 0.4862 0.43925 0.128 0.704 0.020 0.000 0.000 0.148
#> GSM1233006 4 0.5438 0.37003 0.000 0.284 0.000 0.572 0.004 0.140
#> GSM1233008 2 0.2902 0.48708 0.016 0.864 0.004 0.004 0.100 0.012
#> GSM1233009 2 0.4881 0.15051 0.076 0.588 0.000 0.000 0.336 0.000
#> GSM1233017 2 0.4632 0.24419 0.004 0.668 0.000 0.072 0.256 0.000
#> GSM1233020 2 0.4085 0.35246 0.016 0.712 0.012 0.004 0.000 0.256
#> GSM1233022 4 0.5569 0.13858 0.000 0.280 0.000 0.540 0.180 0.000
#> GSM1233026 5 0.5572 0.23653 0.236 0.020 0.000 0.004 0.616 0.124
#> GSM1233028 5 0.5512 0.13870 0.020 0.408 0.000 0.000 0.496 0.076
#> GSM1233034 2 0.4651 0.04481 0.476 0.484 0.000 0.000 0.000 0.040
#> GSM1233040 1 0.3290 0.57261 0.744 0.000 0.000 0.004 0.252 0.000
#> GSM1233048 1 0.2885 0.67220 0.872 0.068 0.000 0.008 0.044 0.008
#> GSM1233056 4 0.4636 0.55305 0.024 0.000 0.008 0.748 0.104 0.116
#> GSM1233058 6 0.4572 0.45970 0.000 0.040 0.000 0.008 0.316 0.636
#> GSM1233059 1 0.1863 0.66804 0.896 0.000 0.000 0.000 0.104 0.000
#> GSM1233066 3 0.1974 0.79157 0.000 0.048 0.920 0.000 0.012 0.020
#> GSM1233071 1 0.5459 0.09748 0.496 0.416 0.000 0.024 0.064 0.000
#> GSM1233074 3 0.4397 0.38223 0.000 0.376 0.596 0.000 0.004 0.024
#> GSM1233076 6 0.2316 0.55529 0.000 0.024 0.012 0.020 0.032 0.912
#> GSM1233080 1 0.5315 0.57574 0.696 0.000 0.008 0.052 0.148 0.096
#> GSM1233088 1 0.4930 0.51822 0.676 0.136 0.008 0.000 0.000 0.180
#> GSM1233090 1 0.3627 0.65052 0.816 0.000 0.024 0.020 0.128 0.012
#> GSM1233092 4 0.4214 0.56936 0.000 0.036 0.000 0.732 0.020 0.212
#> GSM1233094 4 0.3296 0.60130 0.004 0.068 0.000 0.836 0.088 0.004
#> GSM1233097 6 0.5751 0.37533 0.008 0.088 0.000 0.016 0.380 0.508
#> GSM1233100 1 0.7842 0.31450 0.468 0.152 0.000 0.116 0.184 0.080
#> GSM1233104 5 0.6485 0.16813 0.000 0.172 0.000 0.048 0.480 0.300
#> GSM1233106 1 0.2009 0.67791 0.908 0.024 0.000 0.000 0.068 0.000
#> GSM1233111 1 0.2859 0.64813 0.828 0.016 0.000 0.000 0.156 0.000
#> GSM1233122 2 0.4484 0.44350 0.004 0.748 0.008 0.064 0.012 0.164
#> GSM1233146 4 0.7589 -0.02185 0.004 0.244 0.000 0.312 0.132 0.308
#> GSM1232994 2 0.4581 0.22711 0.020 0.656 0.000 0.016 0.300 0.008
#> GSM1232996 2 0.5728 -0.07320 0.016 0.532 0.000 0.000 0.124 0.328
#> GSM1232997 2 0.6042 0.34615 0.080 0.608 0.140 0.000 0.000 0.172
#> GSM1232998 6 0.5829 0.50120 0.000 0.224 0.000 0.020 0.184 0.572
#> GSM1232999 6 0.5809 0.46110 0.000 0.324 0.000 0.004 0.176 0.496
#> GSM1233000 2 0.2975 0.53287 0.132 0.840 0.000 0.000 0.012 0.016
#> GSM1233004 6 0.3594 0.55323 0.000 0.040 0.008 0.004 0.144 0.804
#> GSM1233011 6 0.5584 0.40333 0.000 0.020 0.096 0.008 0.272 0.604
#> GSM1233012 2 0.4753 -0.03395 0.000 0.496 0.456 0.000 0.048 0.000
#> GSM1233023 2 0.5041 0.39499 0.112 0.684 0.024 0.000 0.000 0.180
#> GSM1233027 6 0.4933 0.50716 0.004 0.308 0.000 0.020 0.040 0.628
#> GSM1233033 4 0.6317 0.03911 0.308 0.000 0.000 0.376 0.308 0.008
#> GSM1233036 3 0.5989 -0.01666 0.004 0.376 0.424 0.000 0.196 0.000
#> GSM1233037 2 0.4337 0.27297 0.388 0.592 0.008 0.000 0.004 0.008
#> GSM1233041 1 0.4871 0.45038 0.616 0.000 0.000 0.072 0.308 0.004
#> GSM1233045 6 0.5495 0.51175 0.016 0.128 0.000 0.000 0.256 0.600
#> GSM1233047 3 0.1719 0.78613 0.000 0.060 0.924 0.000 0.016 0.000
#> GSM1233050 1 0.3321 0.61257 0.796 0.180 0.000 0.000 0.008 0.016
#> GSM1233052 1 0.4385 0.64049 0.772 0.068 0.000 0.008 0.120 0.032
#> GSM1233053 3 0.5923 0.55048 0.136 0.168 0.628 0.004 0.064 0.000
#> GSM1233055 6 0.5465 0.42091 0.028 0.000 0.004 0.088 0.256 0.624
#> GSM1233061 3 0.1225 0.79226 0.000 0.036 0.952 0.000 0.000 0.012
#> GSM1233063 1 0.5670 0.20323 0.460 0.000 0.000 0.060 0.440 0.040
#> GSM1233065 2 0.5448 -0.26945 0.020 0.464 0.004 0.000 0.056 0.456
#> GSM1233070 6 0.5889 0.17943 0.128 0.412 0.000 0.016 0.000 0.444
#> GSM1233077 3 0.4624 0.49680 0.000 0.032 0.616 0.000 0.012 0.340
#> GSM1233081 3 0.0458 0.78692 0.000 0.000 0.984 0.000 0.000 0.016
#> GSM1233084 1 0.7463 0.29688 0.456 0.000 0.028 0.124 0.256 0.136
#> GSM1233087 6 0.3724 0.53550 0.008 0.012 0.000 0.040 0.136 0.804
#> GSM1233089 6 0.5310 0.24094 0.004 0.416 0.036 0.016 0.008 0.520
#> GSM1233099 5 0.6672 0.33255 0.008 0.192 0.000 0.076 0.540 0.184
#> GSM1233112 4 0.4414 0.54978 0.000 0.008 0.032 0.732 0.024 0.204
#> GSM1233085 3 0.0260 0.78696 0.000 0.000 0.992 0.000 0.008 0.000
#> GSM1233098 2 0.6344 -0.19105 0.120 0.432 0.016 0.016 0.004 0.412
#> GSM1233114 5 0.5436 0.35977 0.004 0.148 0.000 0.240 0.604 0.004
#> GSM1233119 5 0.5886 0.24699 0.000 0.016 0.000 0.160 0.532 0.292
#> GSM1233129 2 0.4581 0.23319 0.000 0.592 0.372 0.000 0.012 0.024
#> GSM1233132 5 0.5701 0.34678 0.004 0.196 0.000 0.256 0.544 0.000
#> GSM1233139 2 0.4094 0.29667 0.032 0.700 0.004 0.000 0.264 0.000
#> GSM1233143 2 0.5834 0.22959 0.000 0.552 0.304 0.032 0.112 0.000
#> GSM1233145 4 0.3509 0.58828 0.000 0.000 0.000 0.804 0.084 0.112
#> GSM1233067 3 0.2909 0.74049 0.000 0.136 0.836 0.000 0.028 0.000
#> GSM1233069 3 0.3370 0.73383 0.000 0.044 0.812 0.000 0.004 0.140
#> GSM1233072 2 0.5534 0.44257 0.000 0.676 0.008 0.128 0.052 0.136
#> GSM1233086 6 0.6034 0.21954 0.000 0.044 0.092 0.000 0.412 0.452
#> GSM1233102 4 0.1448 0.62684 0.000 0.016 0.000 0.948 0.024 0.012
#> GSM1233103 5 0.6071 0.36336 0.236 0.252 0.000 0.012 0.500 0.000
#> GSM1233107 5 0.5854 0.21925 0.000 0.392 0.000 0.192 0.416 0.000
#> GSM1233108 3 0.2536 0.75222 0.000 0.000 0.864 0.000 0.020 0.116
#> GSM1233109 3 0.3541 0.67574 0.000 0.000 0.748 0.000 0.020 0.232
#> GSM1233110 3 0.0692 0.78964 0.000 0.004 0.976 0.000 0.000 0.020
#> GSM1233113 2 0.5264 0.31376 0.000 0.588 0.304 0.000 0.008 0.100
#> GSM1233116 3 0.4418 0.73195 0.000 0.080 0.772 0.004 0.044 0.100
#> GSM1233120 4 0.6430 0.04951 0.008 0.016 0.000 0.412 0.376 0.188
#> GSM1233121 3 0.3686 0.66972 0.000 0.032 0.748 0.000 0.000 0.220
#> GSM1233123 3 0.0603 0.78919 0.000 0.004 0.980 0.000 0.000 0.016
#> GSM1233124 3 0.2888 0.75001 0.000 0.092 0.852 0.000 0.056 0.000
#> GSM1233125 3 0.4911 0.56041 0.008 0.000 0.676 0.012 0.236 0.068
#> GSM1233126 4 0.1794 0.62609 0.000 0.028 0.000 0.932 0.024 0.016
#> GSM1233127 2 0.5503 -0.11408 0.000 0.484 0.000 0.132 0.384 0.000
#> GSM1233128 5 0.8169 0.09976 0.068 0.000 0.184 0.128 0.388 0.232
#> GSM1233130 3 0.3761 0.67294 0.000 0.008 0.744 0.000 0.020 0.228
#> GSM1233131 5 0.5217 0.37460 0.152 0.032 0.000 0.124 0.688 0.004
#> GSM1233133 3 0.0405 0.78733 0.000 0.004 0.988 0.000 0.008 0.000
#> GSM1233134 3 0.2383 0.76759 0.000 0.096 0.880 0.000 0.024 0.000
#> GSM1233135 3 0.0870 0.79073 0.000 0.012 0.972 0.000 0.004 0.012
#> GSM1233136 6 0.4654 0.47201 0.000 0.080 0.176 0.000 0.024 0.720
#> GSM1233137 3 0.1779 0.78289 0.000 0.064 0.920 0.000 0.016 0.000
#> GSM1233138 4 0.4183 0.58836 0.000 0.040 0.000 0.772 0.140 0.048
#> GSM1233140 3 0.5569 0.44236 0.096 0.000 0.612 0.028 0.260 0.004
#> GSM1233141 2 0.4910 0.08260 0.000 0.584 0.004 0.052 0.356 0.004
#> GSM1233142 2 0.4868 -0.00682 0.000 0.548 0.004 0.052 0.396 0.000
#> GSM1233144 3 0.0291 0.78703 0.000 0.004 0.992 0.000 0.004 0.000
#> GSM1233147 6 0.3229 0.55438 0.000 0.060 0.012 0.044 0.024 0.860
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> SD:NMF 143 1.46e-03 0.62232 0.02911 2
#> SD:NMF 111 1.25e-05 0.29103 0.00503 3
#> SD:NMF 86 2.80e-05 0.03877 0.02155 4
#> SD:NMF 110 1.64e-05 0.01626 0.00159 5
#> SD:NMF 71 8.97e-05 0.00959 0.00293 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 51941 rows and 156 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 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.299 0.689 0.841 0.4467 0.530 0.530
#> 3 3 0.231 0.474 0.723 0.3517 0.752 0.581
#> 4 4 0.299 0.468 0.679 0.1291 0.847 0.657
#> 5 5 0.379 0.403 0.652 0.0745 0.959 0.884
#> 6 6 0.436 0.452 0.624 0.0497 0.883 0.655
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0938 0.80331 0.012 0.988
#> GSM1233002 2 0.9393 0.54099 0.356 0.644
#> GSM1233003 1 0.2043 0.82535 0.968 0.032
#> GSM1233014 2 0.4939 0.80911 0.108 0.892
#> GSM1233015 1 0.2423 0.82386 0.960 0.040
#> GSM1233016 2 0.8955 0.63402 0.312 0.688
#> GSM1233024 2 0.3114 0.81884 0.056 0.944
#> GSM1233049 1 0.0938 0.81946 0.988 0.012
#> GSM1233064 2 0.4022 0.81741 0.080 0.920
#> GSM1233068 1 0.9393 0.45669 0.644 0.356
#> GSM1233073 1 0.9866 0.20980 0.568 0.432
#> GSM1233093 1 0.0938 0.81946 0.988 0.012
#> GSM1233115 1 0.5737 0.78619 0.864 0.136
#> GSM1232992 2 0.0938 0.80686 0.012 0.988
#> GSM1232993 2 0.6531 0.77744 0.168 0.832
#> GSM1233005 2 0.0938 0.80686 0.012 0.988
#> GSM1233007 2 0.3733 0.81818 0.072 0.928
#> GSM1233010 2 0.9963 0.24497 0.464 0.536
#> GSM1233013 2 0.0938 0.79819 0.012 0.988
#> GSM1233018 2 0.0376 0.80260 0.004 0.996
#> GSM1233019 2 0.2778 0.81858 0.048 0.952
#> GSM1233021 2 0.0938 0.80686 0.012 0.988
#> GSM1233025 2 0.9977 0.21590 0.472 0.528
#> GSM1233029 2 0.2948 0.81902 0.052 0.948
#> GSM1233030 2 0.0938 0.79227 0.012 0.988
#> GSM1233031 2 0.9909 0.29619 0.444 0.556
#> GSM1233032 1 0.3733 0.82007 0.928 0.072
#> GSM1233035 2 0.9909 0.29141 0.444 0.556
#> GSM1233038 1 0.1184 0.82138 0.984 0.016
#> GSM1233039 2 0.3879 0.81830 0.076 0.924
#> GSM1233042 2 0.9170 0.58214 0.332 0.668
#> GSM1233043 2 0.9170 0.58214 0.332 0.668
#> GSM1233044 1 0.9732 0.29749 0.596 0.404
#> GSM1233046 1 0.8813 0.57299 0.700 0.300
#> GSM1233051 1 0.3114 0.82323 0.944 0.056
#> GSM1233054 1 0.2948 0.82334 0.948 0.052
#> GSM1233057 2 0.6973 0.76657 0.188 0.812
#> GSM1233060 2 0.9170 0.58052 0.332 0.668
#> GSM1233062 2 0.3879 0.81704 0.076 0.924
#> GSM1233075 2 0.1843 0.81020 0.028 0.972
#> GSM1233078 2 0.9427 0.54407 0.360 0.640
#> GSM1233079 1 0.3879 0.81779 0.924 0.076
#> GSM1233082 1 0.6712 0.75256 0.824 0.176
#> GSM1233083 1 0.1633 0.82400 0.976 0.024
#> GSM1233091 1 0.9983 0.00992 0.524 0.476
#> GSM1233095 1 0.1184 0.82071 0.984 0.016
#> GSM1233096 1 0.1843 0.82374 0.972 0.028
#> GSM1233101 1 0.1414 0.82249 0.980 0.020
#> GSM1233105 1 0.8661 0.59235 0.712 0.288
#> GSM1233117 2 0.0938 0.79227 0.012 0.988
#> GSM1233118 2 0.2778 0.81845 0.048 0.952
#> GSM1233001 2 0.0938 0.79227 0.012 0.988
#> GSM1233006 2 0.3431 0.81861 0.064 0.936
#> GSM1233008 2 0.3584 0.81989 0.068 0.932
#> GSM1233009 2 0.0376 0.80288 0.004 0.996
#> GSM1233017 2 0.2423 0.81695 0.040 0.960
#> GSM1233020 2 0.0376 0.80260 0.004 0.996
#> GSM1233022 2 0.5294 0.80434 0.120 0.880
#> GSM1233026 2 0.9795 0.39965 0.416 0.584
#> GSM1233028 2 0.9944 0.26097 0.456 0.544
#> GSM1233034 2 0.3584 0.81986 0.068 0.932
#> GSM1233040 1 0.1843 0.82374 0.972 0.028
#> GSM1233048 1 0.1184 0.82138 0.984 0.016
#> GSM1233056 1 0.0938 0.81946 0.988 0.012
#> GSM1233058 2 0.9977 0.22212 0.472 0.528
#> GSM1233059 1 0.0938 0.81946 0.988 0.012
#> GSM1233066 2 0.9000 0.61938 0.316 0.684
#> GSM1233071 2 0.5946 0.79448 0.144 0.856
#> GSM1233074 2 0.1843 0.81020 0.028 0.972
#> GSM1233076 2 0.3274 0.81922 0.060 0.940
#> GSM1233080 1 0.0938 0.81946 0.988 0.012
#> GSM1233088 2 0.6623 0.77939 0.172 0.828
#> GSM1233090 1 0.0938 0.81946 0.988 0.012
#> GSM1233092 2 0.5737 0.79961 0.136 0.864
#> GSM1233094 2 0.7745 0.73402 0.228 0.772
#> GSM1233097 2 0.9909 0.30515 0.444 0.556
#> GSM1233100 2 0.9850 0.35008 0.428 0.572
#> GSM1233104 2 0.8267 0.69449 0.260 0.740
#> GSM1233106 1 0.5408 0.79527 0.876 0.124
#> GSM1233111 1 0.1843 0.82374 0.972 0.028
#> GSM1233122 2 0.3274 0.81800 0.060 0.940
#> GSM1233146 2 0.9286 0.56404 0.344 0.656
#> GSM1232994 2 0.1184 0.80846 0.016 0.984
#> GSM1232996 2 0.0938 0.80681 0.012 0.988
#> GSM1232997 2 0.3114 0.81916 0.056 0.944
#> GSM1232998 2 0.4022 0.81586 0.080 0.920
#> GSM1232999 2 0.2423 0.81813 0.040 0.960
#> GSM1233000 2 0.1414 0.81084 0.020 0.980
#> GSM1233004 1 0.9286 0.48844 0.656 0.344
#> GSM1233011 2 0.8016 0.71360 0.244 0.756
#> GSM1233012 2 0.2236 0.81633 0.036 0.964
#> GSM1233023 2 0.2948 0.81879 0.052 0.948
#> GSM1233027 2 0.2236 0.81478 0.036 0.964
#> GSM1233033 1 0.1633 0.82409 0.976 0.024
#> GSM1233036 2 0.6048 0.79230 0.148 0.852
#> GSM1233037 2 0.7056 0.76363 0.192 0.808
#> GSM1233041 1 0.0938 0.81946 0.988 0.012
#> GSM1233045 2 0.9970 0.23800 0.468 0.532
#> GSM1233047 1 0.4562 0.81108 0.904 0.096
#> GSM1233050 1 0.1184 0.82071 0.984 0.016
#> GSM1233052 1 0.6801 0.75223 0.820 0.180
#> GSM1233053 1 0.2948 0.82334 0.948 0.052
#> GSM1233055 1 0.0938 0.81946 0.988 0.012
#> GSM1233061 2 0.9795 0.41459 0.416 0.584
#> GSM1233063 1 0.2236 0.82502 0.964 0.036
#> GSM1233065 2 0.2948 0.81909 0.052 0.948
#> GSM1233070 2 0.4022 0.81672 0.080 0.920
#> GSM1233077 2 0.9087 0.60568 0.324 0.676
#> GSM1233081 1 0.6438 0.76818 0.836 0.164
#> GSM1233084 1 0.0938 0.81946 0.988 0.012
#> GSM1233087 1 0.4431 0.81241 0.908 0.092
#> GSM1233089 2 0.2423 0.81628 0.040 0.960
#> GSM1233099 1 0.7883 0.68174 0.764 0.236
#> GSM1233112 1 0.0938 0.81946 0.988 0.012
#> GSM1233085 1 0.6887 0.74701 0.816 0.184
#> GSM1233098 2 0.2778 0.81856 0.048 0.952
#> GSM1233114 1 0.9996 -0.06112 0.512 0.488
#> GSM1233119 2 0.9944 0.27174 0.456 0.544
#> GSM1233129 2 0.2948 0.81903 0.052 0.948
#> GSM1233132 1 0.7376 0.71746 0.792 0.208
#> GSM1233139 2 0.2778 0.82008 0.048 0.952
#> GSM1233143 2 0.1414 0.79509 0.020 0.980
#> GSM1233145 1 0.2423 0.82481 0.960 0.040
#> GSM1233067 2 0.0938 0.80206 0.012 0.988
#> GSM1233069 2 0.8813 0.63322 0.300 0.700
#> GSM1233072 2 0.3431 0.81793 0.064 0.936
#> GSM1233086 2 0.7528 0.74094 0.216 0.784
#> GSM1233102 1 0.7745 0.68991 0.772 0.228
#> GSM1233103 1 0.9795 0.27067 0.584 0.416
#> GSM1233107 2 0.5946 0.78912 0.144 0.856
#> GSM1233108 1 0.6148 0.77697 0.848 0.152
#> GSM1233109 1 0.9881 0.16240 0.564 0.436
#> GSM1233110 2 0.9580 0.49896 0.380 0.620
#> GSM1233113 2 0.0938 0.79227 0.012 0.988
#> GSM1233116 2 0.0938 0.79227 0.012 0.988
#> GSM1233120 1 0.7815 0.68788 0.768 0.232
#> GSM1233121 2 0.9170 0.59178 0.332 0.668
#> GSM1233123 2 0.9552 0.50810 0.376 0.624
#> GSM1233124 2 0.9552 0.50382 0.376 0.624
#> GSM1233125 1 0.5737 0.78758 0.864 0.136
#> GSM1233126 2 0.7883 0.72865 0.236 0.764
#> GSM1233127 2 0.2043 0.81191 0.032 0.968
#> GSM1233128 1 0.1633 0.82372 0.976 0.024
#> GSM1233130 2 0.9044 0.61419 0.320 0.680
#> GSM1233131 1 0.9754 0.29868 0.592 0.408
#> GSM1233133 1 0.9983 -0.02237 0.524 0.476
#> GSM1233134 2 0.5294 0.80585 0.120 0.880
#> GSM1233135 2 0.1184 0.79943 0.016 0.984
#> GSM1233136 2 0.7602 0.73867 0.220 0.780
#> GSM1233137 1 0.9983 -0.01723 0.524 0.476
#> GSM1233138 2 0.7815 0.73256 0.232 0.768
#> GSM1233140 1 0.4562 0.81119 0.904 0.096
#> GSM1233141 2 0.0938 0.80613 0.012 0.988
#> GSM1233142 2 0.2043 0.81191 0.032 0.968
#> GSM1233144 2 1.0000 0.12751 0.496 0.504
#> GSM1233147 2 0.4690 0.81152 0.100 0.900
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 3 0.5397 0.70898 0.000 0.280 0.720
#> GSM1233002 2 0.6696 0.51427 0.188 0.736 0.076
#> GSM1233003 1 0.1529 0.84073 0.960 0.040 0.000
#> GSM1233014 2 0.7124 0.25148 0.048 0.656 0.296
#> GSM1233015 1 0.3295 0.83684 0.896 0.096 0.008
#> GSM1233016 2 0.6902 0.50837 0.168 0.732 0.100
#> GSM1233024 2 0.6264 0.02039 0.004 0.616 0.380
#> GSM1233049 1 0.0000 0.83601 1.000 0.000 0.000
#> GSM1233064 2 0.6507 0.29707 0.028 0.688 0.284
#> GSM1233068 1 0.7493 0.10993 0.484 0.480 0.036
#> GSM1233073 2 0.6896 0.19914 0.392 0.588 0.020
#> GSM1233093 1 0.0000 0.83601 1.000 0.000 0.000
#> GSM1233115 1 0.5803 0.72236 0.736 0.248 0.016
#> GSM1232992 3 0.6299 0.41517 0.000 0.476 0.524
#> GSM1232993 2 0.5355 0.43619 0.032 0.800 0.168
#> GSM1233005 3 0.6299 0.41429 0.000 0.476 0.524
#> GSM1233007 2 0.6019 0.27157 0.012 0.700 0.288
#> GSM1233010 2 0.7124 0.49775 0.272 0.672 0.056
#> GSM1233013 3 0.5529 0.66550 0.000 0.296 0.704
#> GSM1233018 3 0.6154 0.52774 0.000 0.408 0.592
#> GSM1233019 2 0.6180 -0.12961 0.000 0.584 0.416
#> GSM1233021 3 0.6280 0.44544 0.000 0.460 0.540
#> GSM1233025 2 0.7453 0.46063 0.292 0.644 0.064
#> GSM1233029 2 0.6228 0.03725 0.004 0.624 0.372
#> GSM1233030 3 0.4062 0.67593 0.000 0.164 0.836
#> GSM1233031 2 0.8238 0.45732 0.300 0.596 0.104
#> GSM1233032 1 0.4261 0.82177 0.848 0.140 0.012
#> GSM1233035 2 0.8625 0.42837 0.316 0.560 0.124
#> GSM1233038 1 0.1031 0.83954 0.976 0.024 0.000
#> GSM1233039 2 0.6441 0.30702 0.028 0.696 0.276
#> GSM1233042 2 0.6829 0.50968 0.168 0.736 0.096
#> GSM1233043 2 0.6829 0.50968 0.168 0.736 0.096
#> GSM1233044 2 0.6763 0.06421 0.436 0.552 0.012
#> GSM1233046 1 0.6793 0.32109 0.536 0.452 0.012
#> GSM1233051 1 0.3826 0.82811 0.868 0.124 0.008
#> GSM1233054 1 0.3966 0.82710 0.876 0.100 0.024
#> GSM1233057 2 0.6559 0.38615 0.040 0.708 0.252
#> GSM1233060 2 0.7027 0.50844 0.172 0.724 0.104
#> GSM1233062 2 0.6357 0.16479 0.012 0.652 0.336
#> GSM1233075 3 0.5882 0.62348 0.000 0.348 0.652
#> GSM1233078 2 0.6865 0.49548 0.160 0.736 0.104
#> GSM1233079 1 0.4862 0.80785 0.820 0.160 0.020
#> GSM1233082 1 0.6113 0.64465 0.688 0.300 0.012
#> GSM1233083 1 0.1753 0.84218 0.952 0.048 0.000
#> GSM1233091 2 0.8034 0.27731 0.392 0.540 0.068
#> GSM1233095 1 0.0237 0.83635 0.996 0.004 0.000
#> GSM1233096 1 0.2860 0.83864 0.912 0.084 0.004
#> GSM1233101 1 0.0747 0.83939 0.984 0.016 0.000
#> GSM1233105 1 0.6724 0.41753 0.568 0.420 0.012
#> GSM1233117 3 0.4002 0.69100 0.000 0.160 0.840
#> GSM1233118 2 0.6495 -0.27709 0.004 0.536 0.460
#> GSM1233001 3 0.3619 0.67306 0.000 0.136 0.864
#> GSM1233006 2 0.5982 0.19156 0.004 0.668 0.328
#> GSM1233008 2 0.6849 0.05586 0.020 0.600 0.380
#> GSM1233009 3 0.6244 0.42083 0.000 0.440 0.560
#> GSM1233017 2 0.6274 -0.28479 0.000 0.544 0.456
#> GSM1233020 3 0.5560 0.68250 0.000 0.300 0.700
#> GSM1233022 2 0.6839 0.29009 0.044 0.684 0.272
#> GSM1233026 2 0.6981 0.51930 0.228 0.704 0.068
#> GSM1233028 2 0.7112 0.49638 0.260 0.680 0.060
#> GSM1233034 2 0.6627 0.19804 0.020 0.644 0.336
#> GSM1233040 1 0.2860 0.83864 0.912 0.084 0.004
#> GSM1233048 1 0.0424 0.83824 0.992 0.008 0.000
#> GSM1233056 1 0.0000 0.83601 1.000 0.000 0.000
#> GSM1233058 2 0.7277 0.48350 0.280 0.660 0.060
#> GSM1233059 1 0.0000 0.83601 1.000 0.000 0.000
#> GSM1233066 2 0.6856 0.50020 0.132 0.740 0.128
#> GSM1233071 2 0.6633 0.34162 0.040 0.700 0.260
#> GSM1233074 3 0.5882 0.62348 0.000 0.348 0.652
#> GSM1233076 2 0.6597 0.24390 0.024 0.664 0.312
#> GSM1233080 1 0.0000 0.83601 1.000 0.000 0.000
#> GSM1233088 2 0.7677 0.39195 0.092 0.656 0.252
#> GSM1233090 1 0.0000 0.83601 1.000 0.000 0.000
#> GSM1233092 2 0.6124 0.38940 0.036 0.744 0.220
#> GSM1233094 2 0.5243 0.49345 0.072 0.828 0.100
#> GSM1233097 2 0.6913 0.50199 0.248 0.696 0.056
#> GSM1233100 2 0.6950 0.50391 0.252 0.692 0.056
#> GSM1233104 2 0.7361 0.49313 0.124 0.704 0.172
#> GSM1233106 1 0.5115 0.74908 0.768 0.228 0.004
#> GSM1233111 1 0.2860 0.83864 0.912 0.084 0.004
#> GSM1233122 2 0.5988 0.09460 0.000 0.632 0.368
#> GSM1233146 2 0.6757 0.51403 0.180 0.736 0.084
#> GSM1232994 2 0.6307 -0.31127 0.000 0.512 0.488
#> GSM1232996 3 0.6432 0.48966 0.004 0.428 0.568
#> GSM1232997 2 0.6359 0.10111 0.008 0.628 0.364
#> GSM1232998 2 0.7271 0.11267 0.040 0.608 0.352
#> GSM1232999 2 0.6140 -0.03831 0.000 0.596 0.404
#> GSM1233000 2 0.6302 -0.28862 0.000 0.520 0.480
#> GSM1233004 2 0.7997 -0.18284 0.468 0.472 0.060
#> GSM1233011 2 0.7283 0.49317 0.116 0.708 0.176
#> GSM1233012 3 0.6079 0.58505 0.000 0.388 0.612
#> GSM1233023 2 0.6298 0.00887 0.004 0.608 0.388
#> GSM1233027 2 0.6386 -0.10699 0.004 0.584 0.412
#> GSM1233033 1 0.1289 0.84083 0.968 0.032 0.000
#> GSM1233036 2 0.7308 0.26974 0.056 0.648 0.296
#> GSM1233037 2 0.7157 0.36464 0.056 0.668 0.276
#> GSM1233041 1 0.0000 0.83601 1.000 0.000 0.000
#> GSM1233045 2 0.7246 0.49120 0.276 0.664 0.060
#> GSM1233047 1 0.5178 0.79693 0.808 0.164 0.028
#> GSM1233050 1 0.0829 0.83863 0.984 0.012 0.004
#> GSM1233052 1 0.6018 0.63791 0.684 0.308 0.008
#> GSM1233053 1 0.3966 0.82710 0.876 0.100 0.024
#> GSM1233055 1 0.0000 0.83601 1.000 0.000 0.000
#> GSM1233061 2 0.6527 0.50135 0.188 0.744 0.068
#> GSM1233063 1 0.3573 0.83025 0.876 0.120 0.004
#> GSM1233065 2 0.6398 -0.05160 0.004 0.580 0.416
#> GSM1233070 2 0.5956 0.31452 0.016 0.720 0.264
#> GSM1233077 2 0.6111 0.48927 0.112 0.784 0.104
#> GSM1233081 1 0.6099 0.73384 0.740 0.228 0.032
#> GSM1233084 1 0.0000 0.83601 1.000 0.000 0.000
#> GSM1233087 1 0.3851 0.81284 0.860 0.136 0.004
#> GSM1233089 2 0.6008 0.17381 0.004 0.664 0.332
#> GSM1233099 1 0.6584 0.50385 0.608 0.380 0.012
#> GSM1233112 1 0.0000 0.83601 1.000 0.000 0.000
#> GSM1233085 1 0.6703 0.67214 0.692 0.268 0.040
#> GSM1233098 2 0.6345 -0.05699 0.004 0.596 0.400
#> GSM1233114 2 0.7961 0.33984 0.336 0.588 0.076
#> GSM1233119 2 0.7416 0.48482 0.276 0.656 0.068
#> GSM1233129 2 0.6468 -0.24651 0.004 0.552 0.444
#> GSM1233132 1 0.6470 0.55842 0.632 0.356 0.012
#> GSM1233139 2 0.6608 -0.15311 0.008 0.560 0.432
#> GSM1233143 3 0.4062 0.69504 0.000 0.164 0.836
#> GSM1233145 1 0.2200 0.83806 0.940 0.056 0.004
#> GSM1233067 3 0.4796 0.70852 0.000 0.220 0.780
#> GSM1233069 2 0.6590 0.47496 0.112 0.756 0.132
#> GSM1233072 2 0.5835 0.16182 0.000 0.660 0.340
#> GSM1233086 2 0.6543 0.47373 0.076 0.748 0.176
#> GSM1233102 1 0.6448 0.54264 0.636 0.352 0.012
#> GSM1233103 2 0.7250 0.14907 0.396 0.572 0.032
#> GSM1233107 2 0.6155 0.26717 0.008 0.664 0.328
#> GSM1233108 1 0.6148 0.72265 0.728 0.244 0.028
#> GSM1233109 2 0.7768 0.23599 0.344 0.592 0.064
#> GSM1233110 2 0.6975 0.48263 0.144 0.732 0.124
#> GSM1233113 3 0.4002 0.69642 0.000 0.160 0.840
#> GSM1233116 3 0.3752 0.68382 0.000 0.144 0.856
#> GSM1233120 1 0.6566 0.51392 0.612 0.376 0.012
#> GSM1233121 2 0.6100 0.49125 0.120 0.784 0.096
#> GSM1233123 2 0.6752 0.48796 0.152 0.744 0.104
#> GSM1233124 2 0.8125 0.46222 0.176 0.648 0.176
#> GSM1233125 1 0.5551 0.75852 0.768 0.212 0.020
#> GSM1233126 2 0.5863 0.48795 0.084 0.796 0.120
#> GSM1233127 3 0.5365 0.67532 0.004 0.252 0.744
#> GSM1233128 1 0.2173 0.84344 0.944 0.048 0.008
#> GSM1233130 2 0.6039 0.49227 0.108 0.788 0.104
#> GSM1233131 2 0.7263 0.12979 0.400 0.568 0.032
#> GSM1233133 2 0.7925 0.32244 0.316 0.604 0.080
#> GSM1233134 3 0.6518 0.17550 0.004 0.484 0.512
#> GSM1233135 3 0.4842 0.70657 0.000 0.224 0.776
#> GSM1233136 2 0.6264 0.46219 0.068 0.764 0.168
#> GSM1233137 2 0.7916 0.35361 0.292 0.620 0.088
#> GSM1233138 2 0.5780 0.48531 0.080 0.800 0.120
#> GSM1233140 1 0.4634 0.80449 0.824 0.164 0.012
#> GSM1233141 3 0.5178 0.68917 0.000 0.256 0.744
#> GSM1233142 3 0.5365 0.67532 0.004 0.252 0.744
#> GSM1233144 2 0.7770 0.39497 0.272 0.640 0.088
#> GSM1233147 2 0.6839 0.32516 0.044 0.684 0.272
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.6275 0.65558 0.000 0.596 0.076 0.328
#> GSM1233002 4 0.7393 0.30523 0.184 0.032 0.172 0.612
#> GSM1233003 1 0.1721 0.78867 0.952 0.008 0.012 0.028
#> GSM1233014 4 0.5128 0.48140 0.032 0.132 0.048 0.788
#> GSM1233015 1 0.3093 0.78032 0.892 0.004 0.064 0.040
#> GSM1233016 4 0.7093 0.34380 0.148 0.056 0.132 0.664
#> GSM1233024 4 0.4544 0.41628 0.000 0.164 0.048 0.788
#> GSM1233049 1 0.1151 0.78092 0.968 0.008 0.024 0.000
#> GSM1233064 4 0.6546 0.40289 0.012 0.128 0.196 0.664
#> GSM1233068 1 0.7571 0.18902 0.476 0.012 0.140 0.372
#> GSM1233073 4 0.8031 0.03657 0.388 0.024 0.160 0.428
#> GSM1233093 1 0.1151 0.78092 0.968 0.008 0.024 0.000
#> GSM1233115 1 0.5857 0.65496 0.712 0.004 0.172 0.112
#> GSM1232992 4 0.5466 0.18521 0.000 0.292 0.040 0.668
#> GSM1232993 4 0.4447 0.47320 0.028 0.036 0.108 0.828
#> GSM1233005 4 0.5466 0.18530 0.000 0.292 0.040 0.668
#> GSM1233007 4 0.5232 0.48001 0.016 0.096 0.108 0.780
#> GSM1233010 4 0.8107 0.13521 0.260 0.024 0.224 0.492
#> GSM1233013 2 0.5933 0.39664 0.000 0.500 0.036 0.464
#> GSM1233018 4 0.5558 0.01491 0.000 0.364 0.028 0.608
#> GSM1233019 4 0.4348 0.37691 0.000 0.196 0.024 0.780
#> GSM1233021 4 0.5475 0.16411 0.000 0.308 0.036 0.656
#> GSM1233025 4 0.8417 0.12892 0.264 0.040 0.220 0.476
#> GSM1233029 4 0.4485 0.42568 0.000 0.152 0.052 0.796
#> GSM1233030 2 0.5497 0.68461 0.000 0.672 0.044 0.284
#> GSM1233031 4 0.7783 0.23262 0.284 0.040 0.128 0.548
#> GSM1233032 1 0.4173 0.75835 0.828 0.004 0.120 0.048
#> GSM1233035 4 0.7698 0.23794 0.304 0.040 0.112 0.544
#> GSM1233038 1 0.1394 0.78663 0.964 0.008 0.016 0.012
#> GSM1233039 4 0.6413 0.41152 0.016 0.120 0.180 0.684
#> GSM1233042 4 0.6911 0.34948 0.164 0.024 0.160 0.652
#> GSM1233043 4 0.6911 0.34948 0.164 0.024 0.160 0.652
#> GSM1233044 1 0.8239 0.00352 0.408 0.016 0.244 0.332
#> GSM1233046 1 0.7680 0.34448 0.528 0.024 0.140 0.308
#> GSM1233051 1 0.3687 0.76861 0.856 0.000 0.080 0.064
#> GSM1233054 1 0.3712 0.74488 0.832 0.004 0.152 0.012
#> GSM1233057 3 0.7372 0.15943 0.024 0.092 0.504 0.380
#> GSM1233060 4 0.6809 0.34818 0.172 0.020 0.152 0.656
#> GSM1233062 4 0.4371 0.46557 0.008 0.124 0.048 0.820
#> GSM1233075 2 0.7035 0.59786 0.000 0.572 0.244 0.184
#> GSM1233078 3 0.7500 0.66585 0.100 0.040 0.568 0.292
#> GSM1233079 1 0.4462 0.73207 0.792 0.000 0.164 0.044
#> GSM1233082 1 0.6241 0.60324 0.684 0.008 0.116 0.192
#> GSM1233083 1 0.1994 0.78884 0.936 0.004 0.052 0.008
#> GSM1233091 4 0.8284 -0.00387 0.384 0.028 0.188 0.400
#> GSM1233095 1 0.1339 0.78190 0.964 0.008 0.024 0.004
#> GSM1233096 1 0.2731 0.78222 0.908 0.004 0.060 0.028
#> GSM1233101 1 0.1639 0.78569 0.952 0.004 0.036 0.008
#> GSM1233105 1 0.7669 0.40288 0.556 0.032 0.136 0.276
#> GSM1233117 2 0.5070 0.74160 0.000 0.748 0.060 0.192
#> GSM1233118 4 0.7517 -0.02087 0.000 0.304 0.212 0.484
#> GSM1233001 2 0.5156 0.71025 0.000 0.720 0.044 0.236
#> GSM1233006 4 0.3612 0.47160 0.000 0.100 0.044 0.856
#> GSM1233008 4 0.7225 0.32204 0.016 0.196 0.184 0.604
#> GSM1233009 4 0.7170 0.00274 0.000 0.288 0.172 0.540
#> GSM1233017 4 0.4706 0.31239 0.000 0.224 0.028 0.748
#> GSM1233020 2 0.6206 0.49541 0.000 0.540 0.056 0.404
#> GSM1233022 4 0.4741 0.50080 0.032 0.104 0.048 0.816
#> GSM1233026 4 0.7885 0.17887 0.212 0.024 0.232 0.532
#> GSM1233028 4 0.8021 0.17225 0.252 0.024 0.216 0.508
#> GSM1233034 4 0.6223 0.43724 0.016 0.128 0.152 0.704
#> GSM1233040 1 0.2731 0.78222 0.908 0.004 0.060 0.028
#> GSM1233048 1 0.1191 0.78372 0.968 0.004 0.024 0.004
#> GSM1233056 1 0.1151 0.78092 0.968 0.008 0.024 0.000
#> GSM1233058 4 0.8292 0.10715 0.264 0.028 0.240 0.468
#> GSM1233059 1 0.1151 0.78092 0.968 0.008 0.024 0.000
#> GSM1233066 3 0.7458 0.54787 0.080 0.040 0.532 0.348
#> GSM1233071 4 0.5197 0.50760 0.040 0.080 0.084 0.796
#> GSM1233074 2 0.7035 0.59786 0.000 0.572 0.244 0.184
#> GSM1233076 4 0.6415 0.41769 0.020 0.128 0.160 0.692
#> GSM1233080 1 0.1151 0.78092 0.968 0.008 0.024 0.000
#> GSM1233088 4 0.7596 0.37628 0.080 0.112 0.184 0.624
#> GSM1233090 1 0.1151 0.78092 0.968 0.008 0.024 0.000
#> GSM1233092 4 0.4620 0.49794 0.024 0.080 0.072 0.824
#> GSM1233094 4 0.5437 0.42912 0.068 0.036 0.120 0.776
#> GSM1233097 4 0.7953 0.18987 0.244 0.024 0.212 0.520
#> GSM1233100 4 0.7548 0.22028 0.248 0.028 0.148 0.576
#> GSM1233104 4 0.6926 0.41569 0.120 0.068 0.128 0.684
#> GSM1233106 1 0.5379 0.69469 0.760 0.008 0.104 0.128
#> GSM1233111 1 0.2731 0.78222 0.908 0.004 0.060 0.028
#> GSM1233122 4 0.3895 0.44304 0.000 0.132 0.036 0.832
#> GSM1233146 4 0.7406 0.32197 0.176 0.036 0.172 0.616
#> GSM1232994 4 0.5727 0.26506 0.000 0.228 0.080 0.692
#> GSM1232996 4 0.5806 0.08918 0.004 0.340 0.036 0.620
#> GSM1232997 4 0.6908 0.31065 0.000 0.188 0.220 0.592
#> GSM1232998 4 0.5464 0.44302 0.028 0.184 0.040 0.748
#> GSM1232999 4 0.4348 0.40636 0.000 0.196 0.024 0.780
#> GSM1233000 4 0.5967 0.26230 0.004 0.236 0.080 0.680
#> GSM1233004 1 0.8039 -0.03671 0.428 0.012 0.344 0.216
#> GSM1233011 4 0.8243 0.09674 0.088 0.092 0.316 0.504
#> GSM1233012 2 0.7260 0.50773 0.000 0.464 0.148 0.388
#> GSM1233023 4 0.7036 0.25581 0.000 0.208 0.216 0.576
#> GSM1233027 4 0.4281 0.38774 0.000 0.180 0.028 0.792
#> GSM1233033 1 0.1509 0.78786 0.960 0.008 0.012 0.020
#> GSM1233036 4 0.8241 0.20172 0.052 0.160 0.272 0.516
#> GSM1233037 3 0.7690 0.11976 0.040 0.092 0.488 0.380
#> GSM1233041 1 0.0672 0.78372 0.984 0.008 0.008 0.000
#> GSM1233045 4 0.8276 0.11216 0.260 0.028 0.240 0.472
#> GSM1233047 1 0.4742 0.69611 0.760 0.004 0.208 0.028
#> GSM1233050 1 0.1396 0.78413 0.960 0.004 0.032 0.004
#> GSM1233052 1 0.6257 0.59908 0.684 0.012 0.100 0.204
#> GSM1233053 1 0.3712 0.74488 0.832 0.004 0.152 0.012
#> GSM1233055 1 0.1151 0.78092 0.968 0.008 0.024 0.000
#> GSM1233061 3 0.6961 0.67062 0.132 0.012 0.612 0.244
#> GSM1233063 1 0.3705 0.77296 0.868 0.012 0.060 0.060
#> GSM1233065 4 0.6826 0.27193 0.000 0.228 0.172 0.600
#> GSM1233070 4 0.4784 0.49081 0.016 0.072 0.104 0.808
#> GSM1233077 3 0.6546 0.66674 0.048 0.032 0.628 0.292
#> GSM1233081 1 0.5517 0.61286 0.684 0.004 0.272 0.040
#> GSM1233084 1 0.0927 0.78226 0.976 0.008 0.016 0.000
#> GSM1233087 1 0.4265 0.75692 0.840 0.016 0.076 0.068
#> GSM1233089 4 0.5812 0.40881 0.000 0.156 0.136 0.708
#> GSM1233099 1 0.7358 0.47948 0.596 0.028 0.132 0.244
#> GSM1233112 1 0.1452 0.78083 0.956 0.008 0.036 0.000
#> GSM1233085 1 0.5677 0.51316 0.628 0.000 0.332 0.040
#> GSM1233098 4 0.6646 0.29506 0.000 0.224 0.156 0.620
#> GSM1233114 4 0.8686 0.05255 0.324 0.072 0.156 0.448
#> GSM1233119 4 0.8343 0.15319 0.248 0.040 0.220 0.492
#> GSM1233129 4 0.7412 0.03416 0.000 0.296 0.200 0.504
#> GSM1233132 1 0.7130 0.52777 0.624 0.028 0.124 0.224
#> GSM1233139 4 0.6519 0.31294 0.012 0.204 0.120 0.664
#> GSM1233143 2 0.5410 0.73881 0.000 0.728 0.080 0.192
#> GSM1233145 1 0.2616 0.78175 0.920 0.028 0.036 0.016
#> GSM1233067 2 0.5897 0.71305 0.000 0.700 0.136 0.164
#> GSM1233069 3 0.7069 0.65882 0.048 0.068 0.616 0.268
#> GSM1233072 4 0.3427 0.46271 0.000 0.112 0.028 0.860
#> GSM1233086 4 0.7796 -0.06808 0.052 0.084 0.380 0.484
#> GSM1233102 1 0.6971 0.52056 0.628 0.020 0.124 0.228
#> GSM1233103 4 0.8189 0.04104 0.384 0.028 0.172 0.416
#> GSM1233107 4 0.7421 0.20933 0.004 0.220 0.236 0.540
#> GSM1233108 1 0.5546 0.60061 0.680 0.000 0.268 0.052
#> GSM1233109 3 0.7309 0.56211 0.268 0.004 0.548 0.180
#> GSM1233110 3 0.6381 0.69754 0.076 0.036 0.696 0.192
#> GSM1233113 2 0.4839 0.74385 0.000 0.764 0.052 0.184
#> GSM1233116 2 0.4756 0.73188 0.000 0.772 0.052 0.176
#> GSM1233120 1 0.7332 0.48738 0.600 0.028 0.132 0.240
#> GSM1233121 3 0.6557 0.67703 0.056 0.028 0.632 0.284
#> GSM1233123 3 0.6687 0.70479 0.092 0.028 0.660 0.220
#> GSM1233124 3 0.7820 0.67126 0.112 0.084 0.600 0.204
#> GSM1233125 1 0.5188 0.65823 0.716 0.000 0.240 0.044
#> GSM1233126 4 0.6002 0.41464 0.064 0.060 0.132 0.744
#> GSM1233127 2 0.6705 0.58576 0.000 0.608 0.148 0.244
#> GSM1233128 1 0.2652 0.78580 0.912 0.004 0.056 0.028
#> GSM1233130 3 0.6766 0.64664 0.052 0.036 0.608 0.304
#> GSM1233131 4 0.8191 0.02014 0.388 0.028 0.172 0.412
#> GSM1233133 3 0.7044 0.59319 0.240 0.016 0.612 0.132
#> GSM1233134 3 0.7568 -0.19235 0.000 0.404 0.404 0.192
#> GSM1233135 2 0.5938 0.71059 0.000 0.696 0.136 0.168
#> GSM1233136 4 0.7397 -0.17471 0.036 0.072 0.404 0.488
#> GSM1233137 3 0.6680 0.62097 0.204 0.024 0.664 0.108
#> GSM1233138 4 0.5930 0.41926 0.060 0.060 0.132 0.748
#> GSM1233140 1 0.4770 0.72277 0.780 0.004 0.168 0.048
#> GSM1233141 2 0.6578 0.60138 0.000 0.620 0.136 0.244
#> GSM1233142 2 0.6705 0.58576 0.000 0.608 0.148 0.244
#> GSM1233144 3 0.6898 0.64074 0.196 0.020 0.644 0.140
#> GSM1233147 4 0.6772 0.35936 0.028 0.116 0.192 0.664
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.572 0.56454 0.000 0.612 0.044 0.308 0.036
#> GSM1233002 4 0.767 0.17689 0.140 0.016 0.132 0.548 0.164
#> GSM1233003 1 0.258 0.68786 0.904 0.000 0.024 0.024 0.048
#> GSM1233014 4 0.489 0.47668 0.004 0.100 0.012 0.752 0.132
#> GSM1233015 1 0.388 0.67616 0.832 0.000 0.064 0.028 0.076
#> GSM1233016 4 0.708 0.04558 0.104 0.012 0.052 0.532 0.300
#> GSM1233024 4 0.459 0.46453 0.000 0.100 0.004 0.756 0.140
#> GSM1233049 1 0.167 0.67653 0.944 0.008 0.032 0.000 0.016
#> GSM1233064 4 0.591 0.45068 0.004 0.120 0.160 0.680 0.036
#> GSM1233068 1 0.778 -0.05008 0.420 0.000 0.120 0.328 0.132
#> GSM1233073 4 0.825 -0.25294 0.328 0.004 0.108 0.340 0.220
#> GSM1233093 1 0.150 0.67692 0.952 0.008 0.024 0.000 0.016
#> GSM1233115 1 0.641 0.52607 0.648 0.000 0.140 0.096 0.116
#> GSM1232992 4 0.517 0.32754 0.000 0.248 0.008 0.676 0.068
#> GSM1232993 4 0.474 0.41262 0.016 0.008 0.052 0.760 0.164
#> GSM1233005 4 0.517 0.33312 0.000 0.240 0.008 0.680 0.072
#> GSM1233007 4 0.471 0.52008 0.008 0.080 0.092 0.788 0.032
#> GSM1233010 4 0.814 0.00316 0.200 0.004 0.152 0.448 0.196
#> GSM1233013 4 0.577 -0.19906 0.000 0.432 0.000 0.480 0.088
#> GSM1233018 4 0.555 0.22056 0.000 0.292 0.004 0.616 0.088
#> GSM1233019 4 0.429 0.46679 0.000 0.152 0.000 0.768 0.080
#> GSM1233021 4 0.525 0.32251 0.000 0.252 0.008 0.668 0.072
#> GSM1233025 4 0.810 -0.17501 0.200 0.000 0.124 0.396 0.280
#> GSM1233029 4 0.427 0.47607 0.000 0.092 0.004 0.784 0.120
#> GSM1233030 2 0.523 0.60121 0.000 0.648 0.000 0.268 0.084
#> GSM1233031 4 0.779 -0.07797 0.232 0.012 0.060 0.468 0.228
#> GSM1233032 1 0.440 0.66128 0.780 0.000 0.148 0.020 0.052
#> GSM1233035 4 0.781 -0.06899 0.252 0.016 0.056 0.468 0.208
#> GSM1233038 1 0.228 0.68842 0.920 0.004 0.020 0.012 0.044
#> GSM1233039 4 0.579 0.45235 0.008 0.112 0.152 0.696 0.032
#> GSM1233042 4 0.716 0.22188 0.124 0.008 0.120 0.592 0.156
#> GSM1233043 4 0.716 0.22188 0.124 0.008 0.120 0.592 0.156
#> GSM1233044 1 0.838 -0.23182 0.340 0.000 0.224 0.280 0.156
#> GSM1233046 1 0.765 0.03401 0.456 0.000 0.076 0.212 0.256
#> GSM1233051 1 0.455 0.66076 0.792 0.000 0.076 0.044 0.088
#> GSM1233054 1 0.448 0.63319 0.748 0.004 0.200 0.004 0.044
#> GSM1233057 3 0.795 0.24553 0.012 0.064 0.420 0.296 0.208
#> GSM1233060 4 0.735 0.20429 0.128 0.016 0.116 0.584 0.156
#> GSM1233062 4 0.438 0.46778 0.004 0.076 0.004 0.780 0.136
#> GSM1233075 2 0.675 0.56153 0.000 0.600 0.184 0.144 0.072
#> GSM1233078 3 0.615 0.66358 0.048 0.052 0.656 0.224 0.020
#> GSM1233079 1 0.459 0.63066 0.732 0.000 0.208 0.004 0.056
#> GSM1233082 1 0.661 0.45458 0.624 0.000 0.092 0.168 0.116
#> GSM1233083 1 0.230 0.69239 0.908 0.000 0.044 0.000 0.048
#> GSM1233091 4 0.827 -0.15769 0.340 0.008 0.140 0.364 0.148
#> GSM1233095 1 0.166 0.67878 0.948 0.008 0.024 0.004 0.016
#> GSM1233096 1 0.348 0.68023 0.852 0.000 0.056 0.016 0.076
#> GSM1233101 1 0.232 0.68867 0.916 0.004 0.052 0.008 0.020
#> GSM1233105 1 0.736 0.11856 0.504 0.000 0.076 0.160 0.260
#> GSM1233117 2 0.389 0.69885 0.000 0.804 0.040 0.148 0.008
#> GSM1233118 4 0.738 0.08619 0.000 0.284 0.172 0.480 0.064
#> GSM1233001 2 0.481 0.65539 0.000 0.712 0.000 0.204 0.084
#> GSM1233006 4 0.366 0.51548 0.000 0.080 0.024 0.844 0.052
#> GSM1233008 4 0.677 0.39355 0.008 0.152 0.140 0.624 0.076
#> GSM1233009 4 0.674 0.02331 0.000 0.172 0.012 0.444 0.372
#> GSM1233017 4 0.476 0.42530 0.000 0.168 0.000 0.728 0.104
#> GSM1233020 2 0.603 0.29395 0.000 0.500 0.024 0.416 0.060
#> GSM1233022 4 0.442 0.45610 0.004 0.048 0.008 0.768 0.172
#> GSM1233026 4 0.790 0.10152 0.148 0.004 0.164 0.488 0.196
#> GSM1233028 4 0.800 -0.01543 0.184 0.000 0.144 0.444 0.228
#> GSM1233034 4 0.591 0.48922 0.012 0.108 0.112 0.708 0.060
#> GSM1233040 1 0.348 0.68023 0.852 0.000 0.056 0.016 0.076
#> GSM1233048 1 0.181 0.68780 0.940 0.004 0.024 0.004 0.028
#> GSM1233056 1 0.167 0.67653 0.944 0.008 0.032 0.000 0.016
#> GSM1233058 4 0.822 0.00799 0.196 0.004 0.172 0.436 0.192
#> GSM1233059 1 0.150 0.67692 0.952 0.008 0.024 0.000 0.016
#> GSM1233066 3 0.678 0.56459 0.028 0.056 0.576 0.288 0.052
#> GSM1233071 4 0.521 0.44003 0.028 0.044 0.020 0.740 0.168
#> GSM1233074 2 0.675 0.56153 0.000 0.600 0.184 0.144 0.072
#> GSM1233076 4 0.552 0.46027 0.008 0.124 0.136 0.712 0.020
#> GSM1233080 1 0.150 0.67692 0.952 0.008 0.024 0.000 0.016
#> GSM1233088 4 0.736 0.43817 0.056 0.104 0.156 0.608 0.076
#> GSM1233090 1 0.159 0.67660 0.948 0.008 0.028 0.000 0.016
#> GSM1233092 4 0.532 0.43656 0.012 0.040 0.040 0.724 0.184
#> GSM1233094 4 0.551 0.33621 0.036 0.004 0.064 0.700 0.196
#> GSM1233097 4 0.788 0.00128 0.172 0.000 0.136 0.464 0.228
#> GSM1233100 4 0.764 -0.02285 0.204 0.004 0.076 0.488 0.228
#> GSM1233104 4 0.671 0.32326 0.076 0.032 0.072 0.648 0.172
#> GSM1233106 1 0.595 0.56327 0.688 0.000 0.080 0.104 0.128
#> GSM1233111 1 0.348 0.68023 0.852 0.000 0.056 0.016 0.076
#> GSM1233122 4 0.387 0.50689 0.000 0.104 0.016 0.824 0.056
#> GSM1233146 4 0.757 0.20711 0.132 0.016 0.132 0.560 0.160
#> GSM1232994 4 0.553 0.36000 0.000 0.160 0.004 0.664 0.172
#> GSM1232996 4 0.545 0.27127 0.000 0.272 0.004 0.636 0.088
#> GSM1232997 4 0.678 0.36665 0.000 0.152 0.172 0.600 0.076
#> GSM1232998 4 0.502 0.49283 0.000 0.132 0.012 0.732 0.124
#> GSM1232999 4 0.445 0.48431 0.000 0.140 0.008 0.772 0.080
#> GSM1233000 4 0.575 0.35372 0.000 0.168 0.008 0.648 0.176
#> GSM1233004 1 0.843 -0.05951 0.368 0.016 0.312 0.196 0.108
#> GSM1233011 4 0.787 0.22774 0.036 0.084 0.280 0.496 0.104
#> GSM1233012 2 0.716 0.43586 0.000 0.476 0.104 0.344 0.076
#> GSM1233023 4 0.700 0.31489 0.000 0.184 0.168 0.572 0.076
#> GSM1233027 4 0.398 0.46852 0.000 0.128 0.000 0.796 0.076
#> GSM1233033 1 0.230 0.68750 0.916 0.000 0.016 0.020 0.048
#> GSM1233036 4 0.800 0.27352 0.028 0.140 0.220 0.508 0.104
#> GSM1233037 3 0.827 0.17574 0.028 0.056 0.372 0.312 0.232
#> GSM1233041 1 0.125 0.68581 0.964 0.008 0.008 0.004 0.016
#> GSM1233045 4 0.820 0.01387 0.196 0.004 0.172 0.440 0.188
#> GSM1233047 1 0.491 0.57067 0.664 0.000 0.288 0.004 0.044
#> GSM1233050 1 0.172 0.68688 0.944 0.004 0.028 0.004 0.020
#> GSM1233052 1 0.654 0.42499 0.624 0.000 0.072 0.128 0.176
#> GSM1233053 1 0.448 0.63319 0.748 0.004 0.200 0.004 0.044
#> GSM1233055 1 0.167 0.67653 0.944 0.008 0.032 0.000 0.016
#> GSM1233061 3 0.535 0.66695 0.056 0.016 0.728 0.172 0.028
#> GSM1233063 1 0.418 0.66695 0.816 0.000 0.056 0.044 0.084
#> GSM1233065 4 0.668 0.34564 0.000 0.184 0.136 0.608 0.072
#> GSM1233070 4 0.459 0.51304 0.012 0.060 0.076 0.804 0.048
#> GSM1233077 3 0.496 0.67407 0.004 0.048 0.712 0.224 0.012
#> GSM1233081 1 0.527 0.48307 0.588 0.000 0.360 0.004 0.048
#> GSM1233084 1 0.150 0.67934 0.952 0.008 0.020 0.000 0.020
#> GSM1233087 1 0.475 0.63454 0.776 0.000 0.056 0.056 0.112
#> GSM1233089 4 0.523 0.46482 0.000 0.152 0.116 0.716 0.016
#> GSM1233099 1 0.697 0.23250 0.552 0.000 0.068 0.128 0.252
#> GSM1233112 1 0.218 0.67535 0.920 0.008 0.048 0.000 0.024
#> GSM1233085 1 0.562 0.33954 0.512 0.004 0.428 0.004 0.052
#> GSM1233098 4 0.647 0.37299 0.000 0.200 0.132 0.616 0.052
#> GSM1233114 5 0.802 0.31103 0.292 0.008 0.072 0.228 0.400
#> GSM1233119 4 0.806 -0.16503 0.180 0.000 0.128 0.404 0.288
#> GSM1233129 4 0.720 0.15920 0.000 0.276 0.164 0.504 0.056
#> GSM1233132 1 0.670 0.30080 0.576 0.000 0.060 0.112 0.252
#> GSM1233139 4 0.691 0.36787 0.008 0.172 0.068 0.604 0.148
#> GSM1233143 2 0.423 0.69751 0.000 0.788 0.056 0.144 0.012
#> GSM1233145 1 0.316 0.67657 0.864 0.000 0.032 0.012 0.092
#> GSM1233067 2 0.484 0.67421 0.000 0.748 0.116 0.124 0.012
#> GSM1233069 3 0.541 0.66913 0.004 0.084 0.696 0.200 0.016
#> GSM1233072 4 0.338 0.51417 0.000 0.084 0.016 0.856 0.044
#> GSM1233086 4 0.734 0.06192 0.020 0.072 0.348 0.484 0.076
#> GSM1233102 1 0.686 0.28494 0.572 0.000 0.064 0.136 0.228
#> GSM1233103 1 0.801 -0.29384 0.324 0.000 0.080 0.308 0.288
#> GSM1233107 5 0.691 0.28446 0.000 0.128 0.064 0.252 0.556
#> GSM1233108 1 0.543 0.45365 0.568 0.000 0.376 0.008 0.048
#> GSM1233109 3 0.580 0.52413 0.164 0.012 0.700 0.088 0.036
#> GSM1233110 3 0.422 0.65936 0.008 0.052 0.820 0.088 0.032
#> GSM1233113 2 0.392 0.69970 0.000 0.804 0.044 0.144 0.008
#> GSM1233116 2 0.396 0.68489 0.000 0.820 0.036 0.112 0.032
#> GSM1233120 1 0.693 0.24539 0.556 0.000 0.068 0.124 0.252
#> GSM1233121 3 0.481 0.68188 0.004 0.048 0.732 0.204 0.012
#> GSM1233123 3 0.462 0.69402 0.028 0.040 0.784 0.136 0.012
#> GSM1233124 3 0.647 0.63340 0.044 0.096 0.680 0.128 0.052
#> GSM1233125 1 0.536 0.52660 0.616 0.000 0.320 0.008 0.056
#> GSM1233126 4 0.597 0.20962 0.028 0.012 0.048 0.612 0.300
#> GSM1233127 2 0.636 0.37205 0.000 0.528 0.020 0.108 0.344
#> GSM1233128 1 0.338 0.68701 0.852 0.000 0.096 0.012 0.040
#> GSM1233130 3 0.533 0.65230 0.008 0.048 0.680 0.248 0.016
#> GSM1233131 1 0.800 -0.27446 0.328 0.000 0.080 0.308 0.284
#> GSM1233133 3 0.553 0.54668 0.156 0.020 0.728 0.056 0.040
#> GSM1233134 2 0.662 0.16768 0.000 0.444 0.424 0.100 0.032
#> GSM1233135 2 0.489 0.67119 0.000 0.744 0.124 0.120 0.012
#> GSM1233136 4 0.636 -0.12586 0.008 0.072 0.432 0.468 0.020
#> GSM1233137 3 0.418 0.52263 0.092 0.024 0.816 0.004 0.064
#> GSM1233138 4 0.589 0.21830 0.024 0.012 0.048 0.616 0.300
#> GSM1233140 1 0.500 0.61649 0.708 0.000 0.220 0.016 0.056
#> GSM1233141 2 0.624 0.39209 0.000 0.544 0.016 0.108 0.332
#> GSM1233142 2 0.636 0.37205 0.000 0.528 0.020 0.108 0.344
#> GSM1233144 3 0.512 0.58628 0.116 0.024 0.768 0.052 0.040
#> GSM1233147 4 0.589 0.39639 0.008 0.112 0.204 0.660 0.016
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 6 0.5184 0.49907 0.000 0.300 0.032 0.012 0.032 0.624
#> GSM1233002 2 0.6640 -0.20997 0.084 0.428 0.056 0.412 0.008 0.012
#> GSM1233003 1 0.3318 0.69421 0.828 0.016 0.008 0.132 0.016 0.000
#> GSM1233014 2 0.5140 0.51110 0.000 0.680 0.004 0.192 0.024 0.100
#> GSM1233015 1 0.4927 0.62617 0.680 0.004 0.020 0.244 0.044 0.008
#> GSM1233016 4 0.7078 0.09715 0.064 0.384 0.016 0.432 0.076 0.028
#> GSM1233024 2 0.5348 0.50074 0.000 0.696 0.004 0.096 0.128 0.076
#> GSM1233049 1 0.0508 0.70524 0.984 0.000 0.004 0.000 0.012 0.000
#> GSM1233064 2 0.6044 0.50642 0.004 0.652 0.148 0.084 0.016 0.096
#> GSM1233068 4 0.7081 0.42934 0.324 0.220 0.040 0.400 0.012 0.004
#> GSM1233073 4 0.7001 0.57282 0.244 0.240 0.032 0.460 0.020 0.004
#> GSM1233093 1 0.0260 0.70596 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM1233115 1 0.6388 0.35784 0.544 0.048 0.068 0.308 0.028 0.004
#> GSM1232992 2 0.4605 0.42715 0.000 0.704 0.000 0.020 0.060 0.216
#> GSM1232993 2 0.4469 0.36179 0.000 0.648 0.008 0.316 0.020 0.008
#> GSM1233005 2 0.4600 0.42840 0.000 0.708 0.000 0.024 0.056 0.212
#> GSM1233007 2 0.5014 0.56630 0.004 0.740 0.088 0.096 0.008 0.064
#> GSM1233010 4 0.7305 0.47959 0.120 0.308 0.076 0.460 0.028 0.008
#> GSM1233013 2 0.5977 -0.13095 0.000 0.468 0.004 0.036 0.084 0.408
#> GSM1233018 2 0.5296 0.32268 0.000 0.624 0.004 0.028 0.064 0.280
#> GSM1233019 2 0.4622 0.53862 0.000 0.756 0.004 0.064 0.060 0.116
#> GSM1233021 2 0.4752 0.41457 0.000 0.692 0.000 0.028 0.056 0.224
#> GSM1233025 4 0.7111 0.50600 0.112 0.260 0.052 0.516 0.056 0.004
#> GSM1233029 2 0.4923 0.52101 0.000 0.732 0.004 0.096 0.112 0.056
#> GSM1233030 6 0.5254 0.44199 0.000 0.236 0.000 0.048 0.064 0.652
#> GSM1233031 4 0.7387 0.40785 0.164 0.324 0.020 0.424 0.052 0.016
#> GSM1233032 1 0.5647 0.62847 0.648 0.004 0.116 0.192 0.036 0.004
#> GSM1233035 4 0.7526 0.37023 0.192 0.332 0.020 0.388 0.052 0.016
#> GSM1233038 1 0.2734 0.70125 0.860 0.004 0.004 0.116 0.016 0.000
#> GSM1233039 2 0.5898 0.50494 0.004 0.668 0.148 0.080 0.020 0.080
#> GSM1233042 2 0.6060 -0.12397 0.068 0.464 0.040 0.416 0.012 0.000
#> GSM1233043 2 0.6060 -0.12397 0.068 0.464 0.040 0.416 0.012 0.000
#> GSM1233044 4 0.7943 0.49787 0.268 0.180 0.176 0.356 0.016 0.004
#> GSM1233046 4 0.6069 0.31633 0.360 0.104 0.008 0.504 0.020 0.004
#> GSM1233051 1 0.4983 0.61006 0.668 0.012 0.020 0.260 0.036 0.004
#> GSM1233054 1 0.5778 0.60850 0.660 0.004 0.140 0.124 0.068 0.004
#> GSM1233057 3 0.7770 0.24975 0.008 0.260 0.460 0.096 0.112 0.064
#> GSM1233060 2 0.6404 -0.13100 0.068 0.452 0.040 0.412 0.024 0.004
#> GSM1233062 2 0.5390 0.51655 0.004 0.692 0.004 0.148 0.100 0.052
#> GSM1233075 6 0.6106 0.52145 0.000 0.124 0.192 0.016 0.052 0.616
#> GSM1233078 3 0.6052 0.67707 0.032 0.176 0.648 0.092 0.004 0.048
#> GSM1233079 1 0.5892 0.59404 0.608 0.004 0.172 0.180 0.036 0.000
#> GSM1233082 1 0.6558 0.18676 0.496 0.084 0.036 0.348 0.032 0.004
#> GSM1233083 1 0.3260 0.69875 0.824 0.000 0.012 0.136 0.028 0.000
#> GSM1233091 4 0.7796 0.51963 0.256 0.268 0.084 0.364 0.016 0.012
#> GSM1233095 1 0.0551 0.70818 0.984 0.004 0.000 0.004 0.008 0.000
#> GSM1233096 1 0.4775 0.63752 0.696 0.004 0.016 0.232 0.044 0.008
#> GSM1233101 1 0.1957 0.71626 0.928 0.008 0.028 0.024 0.012 0.000
#> GSM1233105 4 0.6637 0.17310 0.384 0.060 0.012 0.460 0.072 0.012
#> GSM1233117 6 0.3354 0.60045 0.000 0.128 0.028 0.000 0.020 0.824
#> GSM1233118 2 0.7013 0.13802 0.000 0.476 0.176 0.024 0.052 0.272
#> GSM1233001 6 0.4741 0.51488 0.000 0.184 0.000 0.044 0.056 0.716
#> GSM1233006 2 0.4334 0.57340 0.000 0.776 0.024 0.120 0.012 0.068
#> GSM1233008 2 0.6236 0.45427 0.004 0.632 0.152 0.032 0.044 0.136
#> GSM1233009 5 0.7150 0.02201 0.000 0.384 0.036 0.088 0.404 0.088
#> GSM1233017 2 0.5252 0.49209 0.000 0.704 0.004 0.068 0.100 0.124
#> GSM1233020 6 0.5626 0.19734 0.000 0.436 0.020 0.012 0.056 0.476
#> GSM1233022 2 0.5433 0.47931 0.000 0.652 0.004 0.224 0.064 0.056
#> GSM1233026 4 0.7055 0.37596 0.076 0.360 0.080 0.448 0.028 0.008
#> GSM1233028 4 0.6643 0.48839 0.092 0.292 0.048 0.536 0.020 0.012
#> GSM1233034 2 0.5676 0.54584 0.004 0.696 0.116 0.072 0.024 0.088
#> GSM1233040 1 0.4750 0.64034 0.700 0.004 0.016 0.228 0.044 0.008
#> GSM1233048 1 0.1410 0.71571 0.944 0.000 0.004 0.044 0.008 0.000
#> GSM1233056 1 0.0508 0.70524 0.984 0.000 0.004 0.000 0.012 0.000
#> GSM1233058 4 0.7435 0.48500 0.120 0.304 0.084 0.452 0.032 0.008
#> GSM1233059 1 0.0405 0.70554 0.988 0.000 0.000 0.004 0.008 0.000
#> GSM1233066 3 0.6870 0.55806 0.004 0.228 0.548 0.128 0.032 0.060
#> GSM1233071 2 0.5858 0.45719 0.008 0.628 0.012 0.216 0.112 0.024
#> GSM1233074 6 0.6106 0.52145 0.000 0.124 0.192 0.016 0.052 0.616
#> GSM1233076 2 0.5707 0.51478 0.004 0.684 0.128 0.064 0.016 0.104
#> GSM1233080 1 0.0260 0.70596 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM1233088 2 0.7503 0.43515 0.028 0.532 0.132 0.184 0.032 0.092
#> GSM1233090 1 0.0405 0.70580 0.988 0.000 0.004 0.000 0.008 0.000
#> GSM1233092 2 0.5593 0.43803 0.004 0.640 0.016 0.248 0.052 0.040
#> GSM1233094 2 0.5149 0.22131 0.008 0.568 0.004 0.372 0.036 0.012
#> GSM1233097 4 0.6523 0.46834 0.088 0.312 0.044 0.528 0.020 0.008
#> GSM1233100 4 0.6443 0.39098 0.120 0.352 0.012 0.484 0.024 0.008
#> GSM1233104 2 0.5846 0.11117 0.028 0.528 0.016 0.380 0.016 0.032
#> GSM1233106 1 0.6195 0.39392 0.544 0.052 0.032 0.332 0.032 0.008
#> GSM1233111 1 0.4750 0.64034 0.700 0.004 0.016 0.228 0.044 0.008
#> GSM1233122 2 0.4396 0.57806 0.000 0.780 0.016 0.092 0.028 0.084
#> GSM1233146 2 0.6605 -0.15232 0.076 0.444 0.060 0.400 0.008 0.012
#> GSM1232994 2 0.5794 0.42140 0.000 0.660 0.020 0.052 0.164 0.104
#> GSM1232996 2 0.5427 0.37666 0.000 0.632 0.004 0.040 0.068 0.256
#> GSM1232997 2 0.6376 0.41852 0.000 0.612 0.168 0.044 0.044 0.132
#> GSM1232998 2 0.5271 0.54725 0.000 0.692 0.004 0.136 0.044 0.124
#> GSM1232999 2 0.4802 0.55671 0.000 0.736 0.004 0.084 0.044 0.132
#> GSM1233000 2 0.6003 0.40155 0.000 0.640 0.028 0.048 0.180 0.104
#> GSM1233004 4 0.8467 0.30321 0.280 0.136 0.216 0.312 0.040 0.016
#> GSM1233011 2 0.7564 0.20168 0.000 0.404 0.236 0.256 0.032 0.072
#> GSM1233012 6 0.6840 0.39290 0.000 0.324 0.100 0.032 0.060 0.484
#> GSM1233023 2 0.6445 0.38041 0.000 0.592 0.160 0.040 0.036 0.172
#> GSM1233027 2 0.4463 0.53848 0.000 0.772 0.004 0.060 0.072 0.092
#> GSM1233033 1 0.2851 0.69773 0.844 0.004 0.000 0.132 0.020 0.000
#> GSM1233036 2 0.8038 0.31750 0.020 0.460 0.212 0.124 0.048 0.136
#> GSM1233037 3 0.8211 0.20570 0.016 0.268 0.408 0.128 0.120 0.060
#> GSM1233041 1 0.0935 0.71362 0.964 0.000 0.000 0.032 0.004 0.000
#> GSM1233045 4 0.7444 0.48231 0.120 0.308 0.084 0.448 0.032 0.008
#> GSM1233047 1 0.6287 0.52900 0.572 0.004 0.240 0.124 0.056 0.004
#> GSM1233050 1 0.1375 0.71467 0.952 0.004 0.008 0.028 0.008 0.000
#> GSM1233052 1 0.5890 0.16433 0.516 0.068 0.012 0.372 0.032 0.000
#> GSM1233053 1 0.5778 0.60850 0.660 0.004 0.140 0.124 0.068 0.004
#> GSM1233055 1 0.0508 0.70524 0.984 0.000 0.004 0.000 0.012 0.000
#> GSM1233061 3 0.5433 0.69222 0.024 0.140 0.704 0.100 0.012 0.020
#> GSM1233063 1 0.4860 0.62747 0.704 0.016 0.016 0.220 0.036 0.008
#> GSM1233065 2 0.6308 0.40934 0.000 0.604 0.140 0.032 0.040 0.184
#> GSM1233070 2 0.4942 0.54756 0.004 0.740 0.068 0.132 0.012 0.044
#> GSM1233077 3 0.5338 0.66603 0.000 0.180 0.688 0.064 0.012 0.056
#> GSM1233081 1 0.6445 0.42984 0.488 0.004 0.328 0.128 0.052 0.000
#> GSM1233084 1 0.0363 0.71086 0.988 0.000 0.000 0.012 0.000 0.000
#> GSM1233087 1 0.5213 0.59466 0.688 0.032 0.020 0.212 0.044 0.004
#> GSM1233089 2 0.5489 0.51436 0.000 0.696 0.108 0.052 0.020 0.124
#> GSM1233099 4 0.5310 -0.04279 0.456 0.040 0.000 0.472 0.032 0.000
#> GSM1233112 1 0.1931 0.69725 0.924 0.000 0.004 0.040 0.028 0.004
#> GSM1233085 1 0.6715 0.28866 0.424 0.004 0.384 0.124 0.060 0.004
#> GSM1233098 2 0.6146 0.43521 0.000 0.620 0.132 0.040 0.028 0.180
#> GSM1233114 4 0.6956 0.31188 0.252 0.068 0.004 0.452 0.224 0.000
#> GSM1233119 4 0.6800 0.49560 0.100 0.268 0.052 0.532 0.048 0.000
#> GSM1233129 2 0.6864 0.21245 0.000 0.500 0.164 0.024 0.048 0.264
#> GSM1233132 1 0.5132 0.06661 0.484 0.032 0.000 0.456 0.028 0.000
#> GSM1233139 2 0.6899 0.43258 0.004 0.588 0.088 0.048 0.128 0.144
#> GSM1233143 6 0.3683 0.60432 0.000 0.124 0.040 0.000 0.028 0.808
#> GSM1233145 1 0.3734 0.67344 0.776 0.004 0.008 0.184 0.028 0.000
#> GSM1233067 6 0.3957 0.59334 0.000 0.100 0.100 0.004 0.008 0.788
#> GSM1233069 3 0.5571 0.65368 0.000 0.168 0.676 0.052 0.016 0.088
#> GSM1233072 2 0.4125 0.57967 0.000 0.796 0.016 0.100 0.020 0.068
#> GSM1233086 2 0.7337 0.09159 0.000 0.420 0.308 0.180 0.032 0.060
#> GSM1233102 1 0.5531 -0.00638 0.468 0.052 0.004 0.448 0.028 0.000
#> GSM1233103 4 0.6209 0.56132 0.224 0.172 0.012 0.568 0.020 0.004
#> GSM1233107 5 0.5344 0.33703 0.000 0.088 0.004 0.324 0.576 0.008
#> GSM1233108 1 0.6539 0.40793 0.464 0.004 0.332 0.156 0.044 0.000
#> GSM1233109 3 0.6248 0.57172 0.116 0.044 0.656 0.132 0.032 0.020
#> GSM1233110 3 0.3527 0.64805 0.000 0.060 0.844 0.016 0.028 0.052
#> GSM1233113 6 0.3058 0.60577 0.000 0.124 0.024 0.000 0.012 0.840
#> GSM1233116 6 0.2763 0.54661 0.000 0.072 0.024 0.000 0.028 0.876
#> GSM1233120 4 0.5254 -0.06199 0.460 0.036 0.000 0.472 0.032 0.000
#> GSM1233121 3 0.5208 0.67596 0.000 0.164 0.704 0.068 0.012 0.052
#> GSM1233123 3 0.5006 0.69403 0.020 0.096 0.760 0.064 0.024 0.036
#> GSM1233124 3 0.6034 0.62138 0.024 0.088 0.692 0.072 0.036 0.088
#> GSM1233125 1 0.6634 0.46604 0.496 0.004 0.280 0.172 0.044 0.004
#> GSM1233126 2 0.6379 0.09626 0.012 0.448 0.016 0.420 0.072 0.032
#> GSM1233127 5 0.5764 0.49888 0.000 0.056 0.000 0.052 0.480 0.412
#> GSM1233128 1 0.4702 0.68858 0.744 0.004 0.064 0.148 0.036 0.004
#> GSM1233130 3 0.5737 0.64545 0.004 0.204 0.652 0.076 0.012 0.052
#> GSM1233131 4 0.6320 0.56740 0.224 0.176 0.008 0.560 0.024 0.008
#> GSM1233133 3 0.5263 0.58321 0.112 0.028 0.736 0.076 0.032 0.016
#> GSM1233134 6 0.6310 0.20792 0.000 0.092 0.416 0.008 0.048 0.436
#> GSM1233135 6 0.4002 0.58886 0.000 0.100 0.104 0.004 0.008 0.784
#> GSM1233136 2 0.6753 -0.14576 0.004 0.416 0.412 0.080 0.016 0.072
#> GSM1233137 3 0.4792 0.51413 0.060 0.000 0.764 0.064 0.084 0.028
#> GSM1233138 2 0.6293 0.10817 0.008 0.452 0.016 0.420 0.072 0.032
#> GSM1233140 1 0.6279 0.56480 0.576 0.004 0.184 0.188 0.044 0.004
#> GSM1233141 5 0.5609 0.46850 0.000 0.060 0.000 0.036 0.476 0.428
#> GSM1233142 5 0.5764 0.49888 0.000 0.056 0.000 0.052 0.480 0.412
#> GSM1233144 3 0.4745 0.61353 0.080 0.028 0.780 0.064 0.028 0.020
#> GSM1233147 2 0.6157 0.45481 0.004 0.628 0.184 0.064 0.016 0.104
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> CV:hclust 131 3.26e-01 0.7771 1.0000 2
#> CV:hclust 74 1.66e-02 0.1349 0.1362 3
#> CV:hclust 74 8.91e-04 0.0403 0.0284 4
#> CV:hclust 66 2.82e-04 0.0877 0.1705 5
#> CV:hclust 79 1.24e-05 0.0576 0.2831 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 51941 rows and 156 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.999 0.958 0.982 0.5001 0.500 0.500
#> 3 3 0.450 0.454 0.750 0.3212 0.714 0.487
#> 4 4 0.655 0.716 0.850 0.1306 0.778 0.443
#> 5 5 0.633 0.521 0.724 0.0607 0.918 0.706
#> 6 6 0.657 0.536 0.720 0.0409 0.890 0.572
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0000 0.984 0.000 1.000
#> GSM1233002 1 0.3431 0.924 0.936 0.064
#> GSM1233003 1 0.0000 0.979 1.000 0.000
#> GSM1233014 2 0.0000 0.984 0.000 1.000
#> GSM1233015 1 0.0000 0.979 1.000 0.000
#> GSM1233016 1 0.9635 0.368 0.612 0.388
#> GSM1233024 2 0.0000 0.984 0.000 1.000
#> GSM1233049 1 0.0000 0.979 1.000 0.000
#> GSM1233064 2 0.0000 0.984 0.000 1.000
#> GSM1233068 1 0.0000 0.979 1.000 0.000
#> GSM1233073 1 0.0000 0.979 1.000 0.000
#> GSM1233093 1 0.0000 0.979 1.000 0.000
#> GSM1233115 1 0.0000 0.979 1.000 0.000
#> GSM1232992 2 0.0000 0.984 0.000 1.000
#> GSM1232993 2 0.0000 0.984 0.000 1.000
#> GSM1233005 2 0.0000 0.984 0.000 1.000
#> GSM1233007 2 0.0000 0.984 0.000 1.000
#> GSM1233010 1 0.0000 0.979 1.000 0.000
#> GSM1233013 2 0.0000 0.984 0.000 1.000
#> GSM1233018 2 0.0000 0.984 0.000 1.000
#> GSM1233019 2 0.0000 0.984 0.000 1.000
#> GSM1233021 2 0.0000 0.984 0.000 1.000
#> GSM1233025 1 0.0000 0.979 1.000 0.000
#> GSM1233029 2 0.0000 0.984 0.000 1.000
#> GSM1233030 2 0.0000 0.984 0.000 1.000
#> GSM1233031 1 0.3879 0.912 0.924 0.076
#> GSM1233032 1 0.0000 0.979 1.000 0.000
#> GSM1233035 1 0.0938 0.970 0.988 0.012
#> GSM1233038 1 0.0000 0.979 1.000 0.000
#> GSM1233039 2 0.0000 0.984 0.000 1.000
#> GSM1233042 2 0.0000 0.984 0.000 1.000
#> GSM1233043 2 0.0000 0.984 0.000 1.000
#> GSM1233044 1 0.0000 0.979 1.000 0.000
#> GSM1233046 1 0.0000 0.979 1.000 0.000
#> GSM1233051 1 0.0000 0.979 1.000 0.000
#> GSM1233054 1 0.0000 0.979 1.000 0.000
#> GSM1233057 2 0.0000 0.984 0.000 1.000
#> GSM1233060 2 0.9552 0.389 0.376 0.624
#> GSM1233062 2 0.0000 0.984 0.000 1.000
#> GSM1233075 2 0.0000 0.984 0.000 1.000
#> GSM1233078 1 0.2603 0.943 0.956 0.044
#> GSM1233079 1 0.0000 0.979 1.000 0.000
#> GSM1233082 1 0.0000 0.979 1.000 0.000
#> GSM1233083 1 0.0000 0.979 1.000 0.000
#> GSM1233091 1 0.0000 0.979 1.000 0.000
#> GSM1233095 1 0.0000 0.979 1.000 0.000
#> GSM1233096 1 0.0000 0.979 1.000 0.000
#> GSM1233101 1 0.0000 0.979 1.000 0.000
#> GSM1233105 1 0.0000 0.979 1.000 0.000
#> GSM1233117 2 0.0000 0.984 0.000 1.000
#> GSM1233118 2 0.0000 0.984 0.000 1.000
#> GSM1233001 2 0.0000 0.984 0.000 1.000
#> GSM1233006 2 0.0000 0.984 0.000 1.000
#> GSM1233008 2 0.0000 0.984 0.000 1.000
#> GSM1233009 2 0.0000 0.984 0.000 1.000
#> GSM1233017 2 0.0000 0.984 0.000 1.000
#> GSM1233020 2 0.0000 0.984 0.000 1.000
#> GSM1233022 2 0.0000 0.984 0.000 1.000
#> GSM1233026 2 0.9608 0.372 0.384 0.616
#> GSM1233028 1 0.9754 0.316 0.592 0.408
#> GSM1233034 2 0.0000 0.984 0.000 1.000
#> GSM1233040 1 0.0000 0.979 1.000 0.000
#> GSM1233048 1 0.0000 0.979 1.000 0.000
#> GSM1233056 1 0.0000 0.979 1.000 0.000
#> GSM1233058 1 0.2603 0.944 0.956 0.044
#> GSM1233059 1 0.0000 0.979 1.000 0.000
#> GSM1233066 2 0.0672 0.977 0.008 0.992
#> GSM1233071 2 0.0000 0.984 0.000 1.000
#> GSM1233074 2 0.0000 0.984 0.000 1.000
#> GSM1233076 2 0.0000 0.984 0.000 1.000
#> GSM1233080 1 0.0000 0.979 1.000 0.000
#> GSM1233088 2 0.4431 0.893 0.092 0.908
#> GSM1233090 1 0.0000 0.979 1.000 0.000
#> GSM1233092 2 0.0000 0.984 0.000 1.000
#> GSM1233094 2 0.3879 0.910 0.076 0.924
#> GSM1233097 1 0.8327 0.642 0.736 0.264
#> GSM1233100 1 0.0000 0.979 1.000 0.000
#> GSM1233104 2 0.0000 0.984 0.000 1.000
#> GSM1233106 1 0.0000 0.979 1.000 0.000
#> GSM1233111 1 0.0000 0.979 1.000 0.000
#> GSM1233122 2 0.0000 0.984 0.000 1.000
#> GSM1233146 2 0.3274 0.928 0.060 0.940
#> GSM1232994 2 0.0000 0.984 0.000 1.000
#> GSM1232996 2 0.0000 0.984 0.000 1.000
#> GSM1232997 2 0.0000 0.984 0.000 1.000
#> GSM1232998 2 0.0000 0.984 0.000 1.000
#> GSM1232999 2 0.0000 0.984 0.000 1.000
#> GSM1233000 2 0.0000 0.984 0.000 1.000
#> GSM1233004 1 0.1184 0.967 0.984 0.016
#> GSM1233011 2 0.0000 0.984 0.000 1.000
#> GSM1233012 2 0.0000 0.984 0.000 1.000
#> GSM1233023 2 0.0000 0.984 0.000 1.000
#> GSM1233027 2 0.0000 0.984 0.000 1.000
#> GSM1233033 1 0.0000 0.979 1.000 0.000
#> GSM1233036 2 0.0000 0.984 0.000 1.000
#> GSM1233037 2 0.0672 0.977 0.008 0.992
#> GSM1233041 1 0.0000 0.979 1.000 0.000
#> GSM1233045 2 0.0000 0.984 0.000 1.000
#> GSM1233047 1 0.0000 0.979 1.000 0.000
#> GSM1233050 1 0.0000 0.979 1.000 0.000
#> GSM1233052 1 0.0000 0.979 1.000 0.000
#> GSM1233053 1 0.0000 0.979 1.000 0.000
#> GSM1233055 1 0.0000 0.979 1.000 0.000
#> GSM1233061 1 0.3584 0.919 0.932 0.068
#> GSM1233063 1 0.0000 0.979 1.000 0.000
#> GSM1233065 2 0.0000 0.984 0.000 1.000
#> GSM1233070 2 0.0000 0.984 0.000 1.000
#> GSM1233077 2 0.0000 0.984 0.000 1.000
#> GSM1233081 1 0.0000 0.979 1.000 0.000
#> GSM1233084 1 0.0000 0.979 1.000 0.000
#> GSM1233087 1 0.0000 0.979 1.000 0.000
#> GSM1233089 2 0.0000 0.984 0.000 1.000
#> GSM1233099 1 0.0000 0.979 1.000 0.000
#> GSM1233112 1 0.0000 0.979 1.000 0.000
#> GSM1233085 1 0.0000 0.979 1.000 0.000
#> GSM1233098 2 0.0000 0.984 0.000 1.000
#> GSM1233114 1 0.0000 0.979 1.000 0.000
#> GSM1233119 1 0.2948 0.935 0.948 0.052
#> GSM1233129 2 0.0000 0.984 0.000 1.000
#> GSM1233132 1 0.0000 0.979 1.000 0.000
#> GSM1233139 2 0.0000 0.984 0.000 1.000
#> GSM1233143 2 0.0000 0.984 0.000 1.000
#> GSM1233145 1 0.0000 0.979 1.000 0.000
#> GSM1233067 2 0.0000 0.984 0.000 1.000
#> GSM1233069 2 0.0000 0.984 0.000 1.000
#> GSM1233072 2 0.0000 0.984 0.000 1.000
#> GSM1233086 2 0.0000 0.984 0.000 1.000
#> GSM1233102 1 0.0000 0.979 1.000 0.000
#> GSM1233103 1 0.1184 0.967 0.984 0.016
#> GSM1233107 2 0.7139 0.755 0.196 0.804
#> GSM1233108 1 0.0000 0.979 1.000 0.000
#> GSM1233109 1 0.0000 0.979 1.000 0.000
#> GSM1233110 2 0.0000 0.984 0.000 1.000
#> GSM1233113 2 0.0000 0.984 0.000 1.000
#> GSM1233116 2 0.0000 0.984 0.000 1.000
#> GSM1233120 1 0.0000 0.979 1.000 0.000
#> GSM1233121 2 0.0000 0.984 0.000 1.000
#> GSM1233123 2 0.4562 0.888 0.096 0.904
#> GSM1233124 2 0.0000 0.984 0.000 1.000
#> GSM1233125 1 0.0000 0.979 1.000 0.000
#> GSM1233126 2 0.0000 0.984 0.000 1.000
#> GSM1233127 2 0.0000 0.984 0.000 1.000
#> GSM1233128 1 0.0000 0.979 1.000 0.000
#> GSM1233130 2 0.0000 0.984 0.000 1.000
#> GSM1233131 1 0.0000 0.979 1.000 0.000
#> GSM1233133 1 0.0000 0.979 1.000 0.000
#> GSM1233134 2 0.0000 0.984 0.000 1.000
#> GSM1233135 2 0.0000 0.984 0.000 1.000
#> GSM1233136 2 0.0000 0.984 0.000 1.000
#> GSM1233137 1 0.0000 0.979 1.000 0.000
#> GSM1233138 2 0.0000 0.984 0.000 1.000
#> GSM1233140 1 0.0000 0.979 1.000 0.000
#> GSM1233141 2 0.0000 0.984 0.000 1.000
#> GSM1233142 2 0.0000 0.984 0.000 1.000
#> GSM1233144 1 0.0000 0.979 1.000 0.000
#> GSM1233147 2 0.0000 0.984 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 3 0.5327 0.4928 0.000 0.272 0.728
#> GSM1233002 2 0.3941 0.5435 0.156 0.844 0.000
#> GSM1233003 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233014 2 0.4291 0.3681 0.000 0.820 0.180
#> GSM1233015 1 0.4002 0.7628 0.840 0.160 0.000
#> GSM1233016 2 0.3941 0.5422 0.156 0.844 0.000
#> GSM1233024 2 0.6305 -0.2559 0.000 0.516 0.484
#> GSM1233049 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233064 2 0.6111 0.1193 0.000 0.604 0.396
#> GSM1233068 2 0.6305 -0.1057 0.484 0.516 0.000
#> GSM1233073 2 0.5706 0.3520 0.320 0.680 0.000
#> GSM1233093 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233115 1 0.2066 0.8320 0.940 0.060 0.000
#> GSM1232992 3 0.6244 0.3759 0.000 0.440 0.560
#> GSM1232993 2 0.0892 0.5260 0.000 0.980 0.020
#> GSM1233005 3 0.6244 0.3759 0.000 0.440 0.560
#> GSM1233007 2 0.2959 0.4960 0.000 0.900 0.100
#> GSM1233010 2 0.5621 0.3776 0.308 0.692 0.000
#> GSM1233013 3 0.6244 0.3759 0.000 0.440 0.560
#> GSM1233018 3 0.6244 0.3759 0.000 0.440 0.560
#> GSM1233019 3 0.6307 0.2875 0.000 0.488 0.512
#> GSM1233021 3 0.6244 0.3759 0.000 0.440 0.560
#> GSM1233025 2 0.6215 0.0675 0.428 0.572 0.000
#> GSM1233029 2 0.6307 -0.2629 0.000 0.512 0.488
#> GSM1233030 3 0.6244 0.3759 0.000 0.440 0.560
#> GSM1233031 2 0.3412 0.5496 0.124 0.876 0.000
#> GSM1233032 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233035 2 0.4178 0.5387 0.172 0.828 0.000
#> GSM1233038 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233039 2 0.4452 0.4306 0.000 0.808 0.192
#> GSM1233042 2 0.0237 0.5325 0.000 0.996 0.004
#> GSM1233043 2 0.0592 0.5292 0.000 0.988 0.012
#> GSM1233044 1 0.6308 0.1458 0.508 0.492 0.000
#> GSM1233046 1 0.5621 0.5671 0.692 0.308 0.000
#> GSM1233051 1 0.1031 0.8479 0.976 0.024 0.000
#> GSM1233054 1 0.8842 0.5157 0.580 0.208 0.212
#> GSM1233057 3 0.4399 0.3933 0.000 0.188 0.812
#> GSM1233060 2 0.1765 0.5460 0.040 0.956 0.004
#> GSM1233062 2 0.6192 -0.1435 0.000 0.580 0.420
#> GSM1233075 3 0.0000 0.5364 0.000 0.000 1.000
#> GSM1233078 3 0.8142 -0.0574 0.068 0.464 0.468
#> GSM1233079 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233082 1 0.4605 0.7156 0.796 0.204 0.000
#> GSM1233083 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233091 2 0.7748 0.2403 0.340 0.596 0.064
#> GSM1233095 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233096 1 0.0892 0.8484 0.980 0.020 0.000
#> GSM1233101 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233105 1 0.6252 0.2785 0.556 0.444 0.000
#> GSM1233117 3 0.4291 0.5263 0.000 0.180 0.820
#> GSM1233118 3 0.1031 0.5433 0.000 0.024 0.976
#> GSM1233001 3 0.5529 0.4799 0.000 0.296 0.704
#> GSM1233006 2 0.4121 0.3851 0.000 0.832 0.168
#> GSM1233008 3 0.6260 0.3636 0.000 0.448 0.552
#> GSM1233009 2 0.6309 -0.2802 0.000 0.504 0.496
#> GSM1233017 2 0.6309 -0.2881 0.000 0.500 0.500
#> GSM1233020 3 0.5835 0.4532 0.000 0.340 0.660
#> GSM1233022 2 0.6260 -0.1891 0.000 0.552 0.448
#> GSM1233026 2 0.4056 0.5468 0.092 0.876 0.032
#> GSM1233028 2 0.3120 0.5505 0.080 0.908 0.012
#> GSM1233034 3 0.6267 0.3621 0.000 0.452 0.548
#> GSM1233040 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233048 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233056 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233058 2 0.4353 0.5423 0.156 0.836 0.008
#> GSM1233059 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233066 3 0.6274 0.0402 0.000 0.456 0.544
#> GSM1233071 2 0.1860 0.5063 0.000 0.948 0.052
#> GSM1233074 3 0.0892 0.5428 0.000 0.020 0.980
#> GSM1233076 2 0.5948 0.2207 0.000 0.640 0.360
#> GSM1233080 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233088 2 0.5450 0.3927 0.012 0.760 0.228
#> GSM1233090 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233092 2 0.3941 0.4013 0.000 0.844 0.156
#> GSM1233094 2 0.0829 0.5380 0.012 0.984 0.004
#> GSM1233097 2 0.4963 0.5232 0.200 0.792 0.008
#> GSM1233100 2 0.5760 0.3381 0.328 0.672 0.000
#> GSM1233104 2 0.1031 0.5240 0.000 0.976 0.024
#> GSM1233106 1 0.3879 0.7687 0.848 0.152 0.000
#> GSM1233111 1 0.0592 0.8513 0.988 0.012 0.000
#> GSM1233122 3 0.6235 0.3796 0.000 0.436 0.564
#> GSM1233146 2 0.0661 0.5351 0.004 0.988 0.008
#> GSM1232994 2 0.6307 -0.2633 0.000 0.512 0.488
#> GSM1232996 3 0.6244 0.3759 0.000 0.440 0.560
#> GSM1232997 3 0.1860 0.5317 0.000 0.052 0.948
#> GSM1232998 2 0.6307 -0.2629 0.000 0.512 0.488
#> GSM1232999 2 0.5560 0.1335 0.000 0.700 0.300
#> GSM1233000 3 0.6309 0.2599 0.000 0.500 0.500
#> GSM1233004 2 0.9517 0.1524 0.280 0.488 0.232
#> GSM1233011 3 0.6244 0.1088 0.000 0.440 0.560
#> GSM1233012 3 0.2711 0.5440 0.000 0.088 0.912
#> GSM1233023 3 0.4002 0.5236 0.000 0.160 0.840
#> GSM1233027 2 0.6307 -0.2629 0.000 0.512 0.488
#> GSM1233033 1 0.0747 0.8500 0.984 0.016 0.000
#> GSM1233036 3 0.4931 0.3762 0.000 0.232 0.768
#> GSM1233037 2 0.5591 0.2818 0.000 0.696 0.304
#> GSM1233041 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233045 2 0.0892 0.5327 0.000 0.980 0.020
#> GSM1233047 1 0.3031 0.8189 0.912 0.076 0.012
#> GSM1233050 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233052 1 0.3816 0.7722 0.852 0.148 0.000
#> GSM1233053 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233055 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233061 2 0.8737 0.0690 0.108 0.464 0.428
#> GSM1233063 1 0.0424 0.8521 0.992 0.008 0.000
#> GSM1233065 3 0.1289 0.5422 0.000 0.032 0.968
#> GSM1233070 2 0.4062 0.3906 0.000 0.836 0.164
#> GSM1233077 3 0.5529 0.2623 0.000 0.296 0.704
#> GSM1233081 1 0.5538 0.7605 0.812 0.072 0.116
#> GSM1233084 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233087 2 0.6307 -0.1168 0.488 0.512 0.000
#> GSM1233089 3 0.5363 0.4892 0.000 0.276 0.724
#> GSM1233099 1 0.6305 0.1665 0.516 0.484 0.000
#> GSM1233112 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233085 1 0.6424 0.7031 0.752 0.068 0.180
#> GSM1233098 3 0.6008 0.4291 0.000 0.372 0.628
#> GSM1233114 1 0.1860 0.8366 0.948 0.052 0.000
#> GSM1233119 2 0.4291 0.5360 0.180 0.820 0.000
#> GSM1233129 3 0.1031 0.5421 0.000 0.024 0.976
#> GSM1233132 1 0.0892 0.8484 0.980 0.020 0.000
#> GSM1233139 3 0.6280 0.3434 0.000 0.460 0.540
#> GSM1233143 3 0.3482 0.5375 0.000 0.128 0.872
#> GSM1233145 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233067 3 0.0592 0.5401 0.000 0.012 0.988
#> GSM1233069 3 0.0592 0.5320 0.000 0.012 0.988
#> GSM1233072 3 0.6225 0.3830 0.000 0.432 0.568
#> GSM1233086 3 0.6235 0.0763 0.000 0.436 0.564
#> GSM1233102 1 0.5968 0.4446 0.636 0.364 0.000
#> GSM1233103 2 0.4399 0.5324 0.188 0.812 0.000
#> GSM1233107 2 0.2651 0.5452 0.060 0.928 0.012
#> GSM1233108 1 0.3879 0.7501 0.848 0.000 0.152
#> GSM1233109 1 0.8925 0.4068 0.504 0.132 0.364
#> GSM1233110 3 0.6410 0.1020 0.004 0.420 0.576
#> GSM1233113 3 0.2448 0.5450 0.000 0.076 0.924
#> GSM1233116 3 0.2165 0.5447 0.000 0.064 0.936
#> GSM1233120 1 0.5905 0.4758 0.648 0.352 0.000
#> GSM1233121 3 0.6154 0.1194 0.000 0.408 0.592
#> GSM1233123 3 0.6421 0.0958 0.004 0.424 0.572
#> GSM1233124 3 0.6235 0.0781 0.000 0.436 0.564
#> GSM1233125 1 0.4002 0.7434 0.840 0.000 0.160
#> GSM1233126 2 0.3816 0.4110 0.000 0.852 0.148
#> GSM1233127 2 0.6308 -0.2792 0.000 0.508 0.492
#> GSM1233128 1 0.0000 0.8537 1.000 0.000 0.000
#> GSM1233130 3 0.6180 0.1101 0.000 0.416 0.584
#> GSM1233131 2 0.6286 -0.0446 0.464 0.536 0.000
#> GSM1233133 1 0.8655 0.4097 0.512 0.108 0.380
#> GSM1233134 3 0.0237 0.5352 0.000 0.004 0.996
#> GSM1233135 3 0.0237 0.5352 0.000 0.004 0.996
#> GSM1233136 3 0.5591 0.2510 0.000 0.304 0.696
#> GSM1233137 1 0.8740 0.3063 0.460 0.108 0.432
#> GSM1233138 2 0.4062 0.3910 0.000 0.836 0.164
#> GSM1233140 1 0.2537 0.8188 0.920 0.080 0.000
#> GSM1233141 3 0.6260 0.3691 0.000 0.448 0.552
#> GSM1233142 3 0.6291 0.3352 0.000 0.468 0.532
#> GSM1233144 1 0.9088 0.3410 0.464 0.140 0.396
#> GSM1233147 3 0.6140 0.1288 0.000 0.404 0.596
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.0921 0.8523 0.000 0.972 0.028 0.000
#> GSM1233002 4 0.1174 0.8147 0.000 0.012 0.020 0.968
#> GSM1233003 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233014 4 0.5435 0.1701 0.000 0.420 0.016 0.564
#> GSM1233015 1 0.6380 0.1833 0.500 0.000 0.064 0.436
#> GSM1233016 4 0.1516 0.8099 0.008 0.016 0.016 0.960
#> GSM1233024 2 0.3356 0.8006 0.000 0.824 0.000 0.176
#> GSM1233049 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233064 3 0.6860 0.5649 0.000 0.244 0.592 0.164
#> GSM1233068 4 0.4565 0.7196 0.140 0.000 0.064 0.796
#> GSM1233073 4 0.0992 0.8166 0.012 0.004 0.008 0.976
#> GSM1233093 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233115 1 0.4508 0.7223 0.780 0.000 0.036 0.184
#> GSM1232992 2 0.1109 0.8716 0.000 0.968 0.004 0.028
#> GSM1232993 4 0.3972 0.7087 0.000 0.204 0.008 0.788
#> GSM1233005 2 0.1209 0.8727 0.000 0.964 0.004 0.032
#> GSM1233007 4 0.7017 0.4386 0.000 0.236 0.188 0.576
#> GSM1233010 4 0.1151 0.8142 0.008 0.000 0.024 0.968
#> GSM1233013 2 0.1209 0.8727 0.000 0.964 0.004 0.032
#> GSM1233018 2 0.1209 0.8727 0.000 0.964 0.004 0.032
#> GSM1233019 2 0.1474 0.8714 0.000 0.948 0.000 0.052
#> GSM1233021 2 0.1209 0.8727 0.000 0.964 0.004 0.032
#> GSM1233025 4 0.1452 0.8076 0.036 0.000 0.008 0.956
#> GSM1233029 2 0.3583 0.7921 0.000 0.816 0.004 0.180
#> GSM1233030 2 0.1209 0.8727 0.000 0.964 0.004 0.032
#> GSM1233031 4 0.0921 0.8136 0.000 0.000 0.028 0.972
#> GSM1233032 1 0.1398 0.8627 0.956 0.000 0.040 0.004
#> GSM1233035 4 0.1545 0.8123 0.000 0.008 0.040 0.952
#> GSM1233038 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233039 4 0.7205 0.2722 0.000 0.168 0.304 0.528
#> GSM1233042 4 0.2775 0.7833 0.000 0.084 0.020 0.896
#> GSM1233043 4 0.2775 0.7833 0.000 0.084 0.020 0.896
#> GSM1233044 4 0.4906 0.7008 0.140 0.000 0.084 0.776
#> GSM1233046 4 0.5524 0.5328 0.276 0.000 0.048 0.676
#> GSM1233051 1 0.2032 0.8593 0.936 0.000 0.036 0.028
#> GSM1233054 3 0.5067 0.6409 0.116 0.000 0.768 0.116
#> GSM1233057 3 0.3219 0.7735 0.000 0.112 0.868 0.020
#> GSM1233060 4 0.2385 0.8034 0.000 0.052 0.028 0.920
#> GSM1233062 2 0.4252 0.6934 0.000 0.744 0.004 0.252
#> GSM1233075 3 0.4730 0.5565 0.000 0.364 0.636 0.000
#> GSM1233078 3 0.0927 0.7934 0.008 0.000 0.976 0.016
#> GSM1233079 1 0.1209 0.8644 0.964 0.000 0.032 0.004
#> GSM1233082 4 0.6340 0.1244 0.408 0.000 0.064 0.528
#> GSM1233083 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233091 4 0.5174 0.6882 0.092 0.000 0.152 0.756
#> GSM1233095 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233096 1 0.2775 0.8333 0.896 0.000 0.020 0.084
#> GSM1233101 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233105 4 0.3501 0.7530 0.132 0.000 0.020 0.848
#> GSM1233117 2 0.2011 0.8122 0.000 0.920 0.080 0.000
#> GSM1233118 3 0.4933 0.4342 0.000 0.432 0.568 0.000
#> GSM1233001 2 0.0817 0.8540 0.000 0.976 0.024 0.000
#> GSM1233006 4 0.5478 0.1554 0.000 0.444 0.016 0.540
#> GSM1233008 2 0.1489 0.8728 0.000 0.952 0.004 0.044
#> GSM1233009 2 0.2466 0.8572 0.000 0.900 0.004 0.096
#> GSM1233017 2 0.2530 0.8482 0.000 0.888 0.000 0.112
#> GSM1233020 2 0.0592 0.8582 0.000 0.984 0.016 0.000
#> GSM1233022 2 0.4661 0.5480 0.000 0.652 0.000 0.348
#> GSM1233026 4 0.0707 0.8143 0.000 0.000 0.020 0.980
#> GSM1233028 4 0.0921 0.8136 0.000 0.000 0.028 0.972
#> GSM1233034 2 0.1545 0.8724 0.000 0.952 0.008 0.040
#> GSM1233040 1 0.1398 0.8627 0.956 0.000 0.040 0.004
#> GSM1233048 1 0.0188 0.8717 0.996 0.000 0.000 0.004
#> GSM1233056 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233058 4 0.0817 0.8141 0.000 0.000 0.024 0.976
#> GSM1233059 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233066 3 0.0707 0.7946 0.000 0.000 0.980 0.020
#> GSM1233071 4 0.3852 0.7161 0.000 0.180 0.012 0.808
#> GSM1233074 3 0.4877 0.4823 0.000 0.408 0.592 0.000
#> GSM1233076 3 0.6042 0.3494 0.000 0.048 0.560 0.392
#> GSM1233080 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233088 3 0.7044 0.0792 0.000 0.120 0.452 0.428
#> GSM1233090 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233092 4 0.5003 0.4720 0.000 0.308 0.016 0.676
#> GSM1233094 4 0.0779 0.8120 0.000 0.016 0.004 0.980
#> GSM1233097 4 0.0592 0.8142 0.000 0.000 0.016 0.984
#> GSM1233100 4 0.1796 0.8132 0.016 0.004 0.032 0.948
#> GSM1233104 4 0.1576 0.7992 0.000 0.048 0.004 0.948
#> GSM1233106 1 0.6387 0.1565 0.492 0.000 0.064 0.444
#> GSM1233111 1 0.2830 0.8437 0.900 0.000 0.040 0.060
#> GSM1233122 2 0.1042 0.8688 0.000 0.972 0.008 0.020
#> GSM1233146 4 0.0657 0.8119 0.000 0.004 0.012 0.984
#> GSM1232994 2 0.2530 0.8481 0.000 0.888 0.000 0.112
#> GSM1232996 2 0.1209 0.8727 0.000 0.964 0.004 0.032
#> GSM1232997 3 0.4624 0.5975 0.000 0.340 0.660 0.000
#> GSM1232998 2 0.4606 0.6988 0.000 0.724 0.012 0.264
#> GSM1232999 2 0.4663 0.6538 0.000 0.716 0.012 0.272
#> GSM1233000 2 0.1661 0.8716 0.000 0.944 0.004 0.052
#> GSM1233004 3 0.5355 0.3742 0.020 0.000 0.620 0.360
#> GSM1233011 3 0.5356 0.6864 0.000 0.072 0.728 0.200
#> GSM1233012 2 0.2921 0.7441 0.000 0.860 0.140 0.000
#> GSM1233023 2 0.4992 -0.2538 0.000 0.524 0.476 0.000
#> GSM1233027 2 0.3810 0.7816 0.000 0.804 0.008 0.188
#> GSM1233033 1 0.2053 0.8421 0.924 0.000 0.004 0.072
#> GSM1233036 3 0.3812 0.7552 0.000 0.140 0.832 0.028
#> GSM1233037 3 0.7347 0.4657 0.000 0.244 0.528 0.228
#> GSM1233041 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233045 4 0.0707 0.8143 0.000 0.000 0.020 0.980
#> GSM1233047 1 0.3672 0.7756 0.824 0.000 0.164 0.012
#> GSM1233050 1 0.0188 0.8717 0.996 0.000 0.000 0.004
#> GSM1233052 1 0.6299 0.2341 0.520 0.000 0.060 0.420
#> GSM1233053 1 0.1302 0.8623 0.956 0.000 0.044 0.000
#> GSM1233055 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233061 3 0.1004 0.7906 0.004 0.000 0.972 0.024
#> GSM1233063 1 0.2089 0.8545 0.932 0.000 0.020 0.048
#> GSM1233065 3 0.4941 0.4294 0.000 0.436 0.564 0.000
#> GSM1233070 4 0.5597 0.1412 0.000 0.464 0.020 0.516
#> GSM1233077 3 0.2413 0.7882 0.000 0.064 0.916 0.020
#> GSM1233081 1 0.5099 0.4858 0.612 0.000 0.380 0.008
#> GSM1233084 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233087 4 0.3047 0.7690 0.116 0.000 0.012 0.872
#> GSM1233089 2 0.1022 0.8548 0.000 0.968 0.032 0.000
#> GSM1233099 4 0.3863 0.7298 0.144 0.000 0.028 0.828
#> GSM1233112 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233085 1 0.5285 0.2856 0.524 0.000 0.468 0.008
#> GSM1233098 2 0.1004 0.8597 0.000 0.972 0.024 0.004
#> GSM1233114 1 0.5403 0.4845 0.628 0.000 0.024 0.348
#> GSM1233119 4 0.0524 0.8122 0.004 0.000 0.008 0.988
#> GSM1233129 3 0.4817 0.5188 0.000 0.388 0.612 0.000
#> GSM1233132 1 0.4391 0.6426 0.740 0.000 0.008 0.252
#> GSM1233139 2 0.1661 0.8720 0.000 0.944 0.004 0.052
#> GSM1233143 2 0.2760 0.7574 0.000 0.872 0.128 0.000
#> GSM1233145 1 0.0921 0.8614 0.972 0.000 0.000 0.028
#> GSM1233067 3 0.4713 0.5255 0.000 0.360 0.640 0.000
#> GSM1233069 3 0.2334 0.7808 0.000 0.088 0.908 0.004
#> GSM1233072 2 0.1059 0.8676 0.000 0.972 0.012 0.016
#> GSM1233086 3 0.2480 0.7788 0.000 0.008 0.904 0.088
#> GSM1233102 4 0.3444 0.7060 0.184 0.000 0.000 0.816
#> GSM1233103 4 0.1302 0.8106 0.000 0.000 0.044 0.956
#> GSM1233107 4 0.1471 0.8126 0.004 0.012 0.024 0.960
#> GSM1233108 1 0.4643 0.5377 0.656 0.000 0.344 0.000
#> GSM1233109 3 0.1722 0.7747 0.048 0.000 0.944 0.008
#> GSM1233110 3 0.0927 0.7952 0.000 0.008 0.976 0.016
#> GSM1233113 2 0.3400 0.6818 0.000 0.820 0.180 0.000
#> GSM1233116 2 0.4193 0.5558 0.000 0.732 0.268 0.000
#> GSM1233120 4 0.3688 0.6731 0.208 0.000 0.000 0.792
#> GSM1233121 3 0.1733 0.7943 0.000 0.024 0.948 0.028
#> GSM1233123 3 0.0657 0.7947 0.000 0.004 0.984 0.012
#> GSM1233124 3 0.0927 0.7946 0.000 0.008 0.976 0.016
#> GSM1233125 1 0.4730 0.5013 0.636 0.000 0.364 0.000
#> GSM1233126 4 0.4908 0.5041 0.000 0.292 0.016 0.692
#> GSM1233127 2 0.3764 0.8069 0.000 0.816 0.012 0.172
#> GSM1233128 1 0.0000 0.8726 1.000 0.000 0.000 0.000
#> GSM1233130 3 0.1182 0.7950 0.000 0.016 0.968 0.016
#> GSM1233131 4 0.3266 0.7745 0.084 0.000 0.040 0.876
#> GSM1233133 3 0.1635 0.7748 0.044 0.000 0.948 0.008
#> GSM1233134 3 0.2216 0.7775 0.000 0.092 0.908 0.000
#> GSM1233135 3 0.2408 0.7760 0.000 0.104 0.896 0.000
#> GSM1233136 3 0.2466 0.7897 0.000 0.056 0.916 0.028
#> GSM1233137 3 0.1452 0.7804 0.036 0.000 0.956 0.008
#> GSM1233138 4 0.5269 0.3398 0.000 0.364 0.016 0.620
#> GSM1233140 1 0.3554 0.7990 0.844 0.000 0.136 0.020
#> GSM1233141 2 0.2805 0.8457 0.000 0.888 0.012 0.100
#> GSM1233142 2 0.3479 0.8221 0.000 0.840 0.012 0.148
#> GSM1233144 3 0.1584 0.7793 0.036 0.000 0.952 0.012
#> GSM1233147 3 0.5297 0.5633 0.000 0.032 0.676 0.292
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.2616 0.67454 0.000 0.888 0.036 0.000 0.076
#> GSM1233002 4 0.1894 0.63794 0.000 0.008 0.000 0.920 0.072
#> GSM1233003 1 0.0510 0.85508 0.984 0.000 0.000 0.000 0.016
#> GSM1233014 5 0.6796 0.79120 0.000 0.304 0.000 0.316 0.380
#> GSM1233015 4 0.5513 0.53370 0.180 0.000 0.000 0.652 0.168
#> GSM1233016 4 0.4449 0.01540 0.004 0.004 0.000 0.604 0.388
#> GSM1233024 2 0.4468 0.46541 0.000 0.728 0.004 0.040 0.228
#> GSM1233049 1 0.0162 0.85644 0.996 0.000 0.000 0.000 0.004
#> GSM1233064 3 0.7719 0.29607 0.000 0.200 0.496 0.148 0.156
#> GSM1233068 4 0.4444 0.60788 0.064 0.004 0.000 0.756 0.176
#> GSM1233073 4 0.2068 0.62446 0.004 0.000 0.000 0.904 0.092
#> GSM1233093 1 0.0000 0.85731 1.000 0.000 0.000 0.000 0.000
#> GSM1233115 4 0.6030 0.06340 0.420 0.000 0.000 0.464 0.116
#> GSM1232992 2 0.0000 0.69485 0.000 1.000 0.000 0.000 0.000
#> GSM1232993 4 0.6443 -0.34236 0.000 0.248 0.000 0.504 0.248
#> GSM1233005 2 0.0510 0.69544 0.000 0.984 0.000 0.000 0.016
#> GSM1233007 5 0.8131 0.45352 0.000 0.212 0.116 0.304 0.368
#> GSM1233010 4 0.1043 0.64847 0.000 0.000 0.000 0.960 0.040
#> GSM1233013 2 0.0290 0.69448 0.000 0.992 0.000 0.000 0.008
#> GSM1233018 2 0.0404 0.69524 0.000 0.988 0.000 0.000 0.012
#> GSM1233019 2 0.2672 0.64025 0.000 0.872 0.004 0.008 0.116
#> GSM1233021 2 0.0510 0.69544 0.000 0.984 0.000 0.000 0.016
#> GSM1233025 4 0.2970 0.54690 0.004 0.000 0.000 0.828 0.168
#> GSM1233029 2 0.4303 0.50322 0.000 0.752 0.000 0.056 0.192
#> GSM1233030 2 0.0290 0.69448 0.000 0.992 0.000 0.000 0.008
#> GSM1233031 4 0.0703 0.64289 0.000 0.000 0.000 0.976 0.024
#> GSM1233032 1 0.2516 0.81278 0.860 0.000 0.000 0.000 0.140
#> GSM1233035 4 0.2074 0.64964 0.000 0.000 0.000 0.896 0.104
#> GSM1233038 1 0.0162 0.85703 0.996 0.000 0.000 0.000 0.004
#> GSM1233039 4 0.7970 -0.00824 0.000 0.128 0.244 0.440 0.188
#> GSM1233042 4 0.5519 -0.17151 0.000 0.084 0.000 0.584 0.332
#> GSM1233043 4 0.5566 -0.18983 0.000 0.088 0.000 0.580 0.332
#> GSM1233044 4 0.4539 0.62326 0.048 0.000 0.036 0.780 0.136
#> GSM1233046 4 0.5032 0.58572 0.168 0.000 0.000 0.704 0.128
#> GSM1233051 1 0.4577 0.72651 0.748 0.000 0.000 0.108 0.144
#> GSM1233054 3 0.7121 0.37845 0.024 0.000 0.428 0.208 0.340
#> GSM1233057 3 0.6421 0.61271 0.000 0.108 0.616 0.056 0.220
#> GSM1233060 4 0.2325 0.62976 0.000 0.028 0.000 0.904 0.068
#> GSM1233062 2 0.5040 0.29495 0.000 0.660 0.000 0.068 0.272
#> GSM1233075 3 0.5928 0.14183 0.000 0.392 0.500 0.000 0.108
#> GSM1233078 3 0.3171 0.67418 0.000 0.000 0.816 0.008 0.176
#> GSM1233079 1 0.2561 0.81173 0.856 0.000 0.000 0.000 0.144
#> GSM1233082 4 0.5198 0.56005 0.164 0.000 0.000 0.688 0.148
#> GSM1233083 1 0.0794 0.85148 0.972 0.000 0.000 0.000 0.028
#> GSM1233091 4 0.4900 0.59464 0.028 0.008 0.032 0.740 0.192
#> GSM1233095 1 0.0000 0.85731 1.000 0.000 0.000 0.000 0.000
#> GSM1233096 1 0.5740 0.52618 0.612 0.000 0.000 0.244 0.144
#> GSM1233101 1 0.0000 0.85731 1.000 0.000 0.000 0.000 0.000
#> GSM1233105 4 0.3193 0.65096 0.028 0.000 0.000 0.840 0.132
#> GSM1233117 2 0.3697 0.65203 0.000 0.820 0.080 0.000 0.100
#> GSM1233118 3 0.5952 0.08860 0.000 0.412 0.480 0.000 0.108
#> GSM1233001 2 0.3767 0.62700 0.000 0.812 0.120 0.000 0.068
#> GSM1233006 5 0.6708 0.69575 0.000 0.376 0.000 0.244 0.380
#> GSM1233008 2 0.1082 0.69494 0.000 0.964 0.000 0.008 0.028
#> GSM1233009 2 0.2787 0.66407 0.000 0.880 0.004 0.028 0.088
#> GSM1233017 2 0.3396 0.61467 0.000 0.832 0.004 0.028 0.136
#> GSM1233020 2 0.2378 0.67707 0.000 0.904 0.048 0.000 0.048
#> GSM1233022 2 0.6405 -0.40624 0.000 0.460 0.000 0.176 0.364
#> GSM1233026 4 0.1608 0.64131 0.000 0.000 0.000 0.928 0.072
#> GSM1233028 4 0.1121 0.64633 0.000 0.000 0.000 0.956 0.044
#> GSM1233034 2 0.3554 0.63231 0.000 0.848 0.024 0.040 0.088
#> GSM1233040 1 0.2966 0.80660 0.848 0.000 0.000 0.016 0.136
#> GSM1233048 1 0.0609 0.85491 0.980 0.000 0.000 0.000 0.020
#> GSM1233056 1 0.0162 0.85644 0.996 0.000 0.000 0.000 0.004
#> GSM1233058 4 0.1478 0.63524 0.000 0.000 0.000 0.936 0.064
#> GSM1233059 1 0.0000 0.85731 1.000 0.000 0.000 0.000 0.000
#> GSM1233066 3 0.2886 0.67804 0.000 0.000 0.844 0.008 0.148
#> GSM1233071 4 0.6204 -0.21991 0.000 0.176 0.000 0.536 0.288
#> GSM1233074 3 0.5985 0.09652 0.000 0.408 0.480 0.000 0.112
#> GSM1233076 3 0.7641 -0.16462 0.000 0.064 0.392 0.196 0.348
#> GSM1233080 1 0.0000 0.85731 1.000 0.000 0.000 0.000 0.000
#> GSM1233088 4 0.7362 0.29864 0.000 0.084 0.228 0.520 0.168
#> GSM1233090 1 0.0000 0.85731 1.000 0.000 0.000 0.000 0.000
#> GSM1233092 5 0.6705 0.80384 0.000 0.244 0.000 0.364 0.392
#> GSM1233094 4 0.4418 0.09690 0.000 0.016 0.000 0.652 0.332
#> GSM1233097 4 0.1851 0.61587 0.000 0.000 0.000 0.912 0.088
#> GSM1233100 4 0.1478 0.64736 0.000 0.000 0.000 0.936 0.064
#> GSM1233104 4 0.5912 -0.41221 0.000 0.116 0.000 0.536 0.348
#> GSM1233106 4 0.5567 0.52986 0.196 0.000 0.000 0.644 0.160
#> GSM1233111 1 0.5664 0.56489 0.628 0.000 0.000 0.220 0.152
#> GSM1233122 2 0.0703 0.69537 0.000 0.976 0.000 0.000 0.024
#> GSM1233146 4 0.3508 0.34810 0.000 0.000 0.000 0.748 0.252
#> GSM1232994 2 0.3523 0.61207 0.000 0.824 0.004 0.032 0.140
#> GSM1232996 2 0.0510 0.69580 0.000 0.984 0.000 0.000 0.016
#> GSM1232997 3 0.5904 0.31812 0.000 0.312 0.572 0.004 0.112
#> GSM1232998 2 0.5862 -0.12432 0.000 0.544 0.000 0.112 0.344
#> GSM1232999 2 0.5659 -0.07378 0.000 0.580 0.000 0.100 0.320
#> GSM1233000 2 0.1630 0.68719 0.000 0.944 0.004 0.016 0.036
#> GSM1233004 3 0.5641 0.05016 0.000 0.000 0.488 0.436 0.076
#> GSM1233011 3 0.5797 0.43693 0.000 0.040 0.652 0.068 0.240
#> GSM1233012 2 0.5295 0.51540 0.000 0.664 0.224 0.000 0.112
#> GSM1233023 2 0.6042 0.08943 0.000 0.484 0.396 0.000 0.120
#> GSM1233027 2 0.4638 0.22500 0.000 0.648 0.000 0.028 0.324
#> GSM1233033 1 0.5127 0.64635 0.692 0.000 0.000 0.184 0.124
#> GSM1233036 3 0.5730 0.64281 0.000 0.096 0.684 0.040 0.180
#> GSM1233037 3 0.8497 0.15061 0.000 0.172 0.296 0.268 0.264
#> GSM1233041 1 0.0000 0.85731 1.000 0.000 0.000 0.000 0.000
#> GSM1233045 4 0.1671 0.63072 0.000 0.000 0.000 0.924 0.076
#> GSM1233047 1 0.7071 0.40139 0.496 0.000 0.188 0.036 0.280
#> GSM1233050 1 0.0510 0.85541 0.984 0.000 0.000 0.000 0.016
#> GSM1233052 4 0.5504 0.52045 0.224 0.000 0.000 0.644 0.132
#> GSM1233053 1 0.3053 0.79909 0.828 0.000 0.008 0.000 0.164
#> GSM1233055 1 0.0000 0.85731 1.000 0.000 0.000 0.000 0.000
#> GSM1233061 3 0.3727 0.66421 0.000 0.000 0.768 0.016 0.216
#> GSM1233063 1 0.4887 0.69148 0.720 0.000 0.000 0.148 0.132
#> GSM1233065 2 0.5932 -0.01921 0.000 0.456 0.440 0.000 0.104
#> GSM1233070 2 0.7161 -0.61819 0.000 0.384 0.020 0.232 0.364
#> GSM1233077 3 0.1845 0.66810 0.000 0.016 0.928 0.000 0.056
#> GSM1233081 3 0.7096 0.10823 0.308 0.000 0.420 0.016 0.256
#> GSM1233084 1 0.0000 0.85731 1.000 0.000 0.000 0.000 0.000
#> GSM1233087 4 0.2712 0.63073 0.032 0.000 0.000 0.880 0.088
#> GSM1233089 2 0.4647 0.57554 0.000 0.732 0.184 0.000 0.084
#> GSM1233099 4 0.2653 0.64306 0.024 0.000 0.000 0.880 0.096
#> GSM1233112 1 0.0880 0.84977 0.968 0.000 0.000 0.000 0.032
#> GSM1233085 3 0.6682 0.33157 0.224 0.000 0.516 0.012 0.248
#> GSM1233098 2 0.5461 0.52053 0.000 0.672 0.160 0.004 0.164
#> GSM1233114 4 0.6188 0.38924 0.284 0.000 0.000 0.540 0.176
#> GSM1233119 4 0.3210 0.53218 0.000 0.000 0.000 0.788 0.212
#> GSM1233129 3 0.5938 0.18919 0.000 0.376 0.512 0.000 0.112
#> GSM1233132 4 0.6219 0.06515 0.424 0.000 0.000 0.436 0.140
#> GSM1233139 2 0.2568 0.68376 0.000 0.888 0.004 0.016 0.092
#> GSM1233143 2 0.5307 0.58491 0.000 0.676 0.156 0.000 0.168
#> GSM1233145 1 0.1997 0.82280 0.924 0.000 0.000 0.036 0.040
#> GSM1233067 3 0.5569 0.28530 0.000 0.320 0.588 0.000 0.092
#> GSM1233069 3 0.1981 0.66640 0.000 0.016 0.920 0.000 0.064
#> GSM1233072 2 0.2172 0.68821 0.000 0.908 0.016 0.000 0.076
#> GSM1233086 3 0.2291 0.67234 0.000 0.000 0.908 0.036 0.056
#> GSM1233102 4 0.3780 0.60164 0.072 0.000 0.000 0.812 0.116
#> GSM1233103 4 0.2280 0.64739 0.000 0.000 0.000 0.880 0.120
#> GSM1233107 4 0.3826 0.51325 0.000 0.004 0.008 0.752 0.236
#> GSM1233108 1 0.6661 0.09075 0.412 0.000 0.356 0.000 0.232
#> GSM1233109 3 0.3783 0.65970 0.004 0.000 0.768 0.012 0.216
#> GSM1233110 3 0.2843 0.67866 0.000 0.000 0.848 0.008 0.144
#> GSM1233113 2 0.5404 0.45194 0.000 0.636 0.264 0.000 0.100
#> GSM1233116 2 0.5751 0.29104 0.000 0.540 0.364 0.000 0.096
#> GSM1233120 4 0.3754 0.61655 0.084 0.000 0.000 0.816 0.100
#> GSM1233121 3 0.1168 0.67618 0.000 0.000 0.960 0.008 0.032
#> GSM1233123 3 0.2843 0.67866 0.000 0.000 0.848 0.008 0.144
#> GSM1233124 3 0.2929 0.67933 0.000 0.000 0.840 0.008 0.152
#> GSM1233125 1 0.6673 0.01282 0.388 0.000 0.380 0.000 0.232
#> GSM1233126 5 0.6616 0.76393 0.000 0.216 0.000 0.380 0.404
#> GSM1233127 2 0.5448 0.50734 0.000 0.676 0.012 0.100 0.212
#> GSM1233128 1 0.0162 0.85715 0.996 0.000 0.000 0.000 0.004
#> GSM1233130 3 0.1251 0.68127 0.000 0.000 0.956 0.008 0.036
#> GSM1233131 4 0.2574 0.64977 0.012 0.000 0.000 0.876 0.112
#> GSM1233133 3 0.3845 0.65545 0.004 0.000 0.760 0.012 0.224
#> GSM1233134 3 0.3203 0.68273 0.000 0.012 0.820 0.000 0.168
#> GSM1233135 3 0.2351 0.65796 0.000 0.016 0.896 0.000 0.088
#> GSM1233136 3 0.1981 0.66697 0.000 0.016 0.920 0.000 0.064
#> GSM1233137 3 0.3686 0.66401 0.004 0.000 0.780 0.012 0.204
#> GSM1233138 5 0.6749 0.81401 0.000 0.264 0.000 0.348 0.388
#> GSM1233140 1 0.7344 0.48335 0.508 0.000 0.124 0.096 0.272
#> GSM1233141 2 0.4784 0.58537 0.000 0.736 0.016 0.056 0.192
#> GSM1233142 2 0.5198 0.53905 0.000 0.704 0.012 0.092 0.192
#> GSM1233144 3 0.3719 0.66079 0.004 0.000 0.776 0.012 0.208
#> GSM1233147 3 0.6352 0.16887 0.000 0.016 0.540 0.124 0.320
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.3915 0.4628 0.000 0.692 0.004 0.000 0.016 0.288
#> GSM1233002 4 0.2806 0.6394 0.000 0.004 0.000 0.844 0.136 0.016
#> GSM1233003 1 0.2574 0.8218 0.896 0.000 0.020 0.008 0.048 0.028
#> GSM1233014 5 0.4959 0.6321 0.000 0.216 0.000 0.124 0.656 0.004
#> GSM1233015 4 0.5136 0.5946 0.080 0.000 0.072 0.740 0.032 0.076
#> GSM1233016 5 0.4004 0.4714 0.000 0.004 0.004 0.296 0.684 0.012
#> GSM1233024 2 0.3680 0.5855 0.000 0.756 0.000 0.008 0.216 0.020
#> GSM1233049 1 0.0146 0.8463 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM1233064 6 0.8013 0.2560 0.000 0.144 0.088 0.116 0.216 0.436
#> GSM1233068 4 0.3772 0.6403 0.020 0.000 0.056 0.832 0.048 0.044
#> GSM1233073 4 0.3003 0.6256 0.000 0.000 0.000 0.812 0.172 0.016
#> GSM1233093 1 0.0000 0.8470 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233115 4 0.5246 0.5148 0.232 0.000 0.064 0.664 0.028 0.012
#> GSM1232992 2 0.1152 0.7324 0.000 0.952 0.000 0.000 0.004 0.044
#> GSM1232993 5 0.6772 0.3751 0.000 0.260 0.000 0.336 0.364 0.040
#> GSM1233005 2 0.1007 0.7325 0.000 0.956 0.000 0.000 0.000 0.044
#> GSM1233007 5 0.6575 0.5228 0.000 0.160 0.004 0.116 0.564 0.156
#> GSM1233010 4 0.1926 0.6635 0.000 0.000 0.000 0.912 0.068 0.020
#> GSM1233013 2 0.0713 0.7357 0.000 0.972 0.000 0.000 0.000 0.028
#> GSM1233018 2 0.1075 0.7290 0.000 0.952 0.000 0.000 0.000 0.048
#> GSM1233019 2 0.2006 0.7179 0.000 0.892 0.000 0.000 0.104 0.004
#> GSM1233021 2 0.0937 0.7319 0.000 0.960 0.000 0.000 0.000 0.040
#> GSM1233025 4 0.4654 0.3459 0.004 0.000 0.004 0.564 0.400 0.028
#> GSM1233029 2 0.4205 0.5984 0.000 0.760 0.000 0.040 0.164 0.036
#> GSM1233030 2 0.0458 0.7374 0.000 0.984 0.000 0.000 0.000 0.016
#> GSM1233031 4 0.2163 0.6597 0.000 0.000 0.000 0.892 0.092 0.016
#> GSM1233032 1 0.5243 0.6801 0.712 0.000 0.156 0.060 0.032 0.040
#> GSM1233035 4 0.2796 0.6652 0.000 0.000 0.012 0.872 0.068 0.048
#> GSM1233038 1 0.0912 0.8436 0.972 0.000 0.004 0.004 0.008 0.012
#> GSM1233039 4 0.7855 -0.1212 0.000 0.100 0.032 0.344 0.284 0.240
#> GSM1233042 5 0.4983 0.5332 0.000 0.064 0.000 0.312 0.612 0.012
#> GSM1233043 5 0.5018 0.5404 0.000 0.068 0.000 0.308 0.612 0.012
#> GSM1233044 4 0.5457 0.5727 0.028 0.000 0.200 0.668 0.084 0.020
#> GSM1233046 4 0.5184 0.6213 0.120 0.000 0.028 0.728 0.072 0.052
#> GSM1233051 1 0.7105 0.4427 0.504 0.000 0.120 0.264 0.048 0.064
#> GSM1233054 3 0.4560 0.5556 0.004 0.000 0.740 0.160 0.024 0.072
#> GSM1233057 3 0.6759 0.3127 0.000 0.060 0.524 0.068 0.056 0.292
#> GSM1233060 4 0.3458 0.6302 0.000 0.032 0.000 0.824 0.116 0.028
#> GSM1233062 2 0.4282 0.5445 0.000 0.736 0.000 0.036 0.200 0.028
#> GSM1233075 6 0.4405 0.6159 0.000 0.240 0.072 0.000 0.000 0.688
#> GSM1233078 3 0.2748 0.6552 0.000 0.000 0.848 0.000 0.024 0.128
#> GSM1233079 1 0.5595 0.6366 0.664 0.000 0.204 0.060 0.028 0.044
#> GSM1233082 4 0.3776 0.6368 0.044 0.000 0.064 0.832 0.028 0.032
#> GSM1233083 1 0.2228 0.8226 0.912 0.000 0.016 0.004 0.044 0.024
#> GSM1233091 4 0.4601 0.6133 0.008 0.000 0.064 0.764 0.104 0.060
#> GSM1233095 1 0.0000 0.8470 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233096 4 0.6557 -0.0689 0.400 0.000 0.072 0.444 0.024 0.060
#> GSM1233101 1 0.0146 0.8463 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM1233105 4 0.3381 0.6637 0.008 0.000 0.008 0.836 0.096 0.052
#> GSM1233117 2 0.4614 0.3440 0.000 0.624 0.016 0.000 0.028 0.332
#> GSM1233118 6 0.4491 0.6124 0.000 0.240 0.068 0.000 0.004 0.688
#> GSM1233001 2 0.4332 0.2621 0.000 0.644 0.000 0.000 0.040 0.316
#> GSM1233006 5 0.5023 0.5880 0.000 0.256 0.000 0.068 0.652 0.024
#> GSM1233008 2 0.1549 0.7381 0.000 0.936 0.000 0.000 0.020 0.044
#> GSM1233009 2 0.2686 0.7238 0.000 0.876 0.000 0.012 0.080 0.032
#> GSM1233017 2 0.2844 0.7034 0.000 0.856 0.000 0.012 0.112 0.020
#> GSM1233020 2 0.2841 0.6255 0.000 0.824 0.000 0.000 0.012 0.164
#> GSM1233022 5 0.5045 0.2645 0.000 0.412 0.000 0.056 0.524 0.008
#> GSM1233026 4 0.2540 0.6485 0.000 0.004 0.000 0.872 0.104 0.020
#> GSM1233028 4 0.2526 0.6591 0.000 0.004 0.000 0.876 0.096 0.024
#> GSM1233034 2 0.4720 0.5770 0.000 0.744 0.000 0.076 0.072 0.108
#> GSM1233040 1 0.5271 0.6947 0.720 0.000 0.112 0.092 0.024 0.052
#> GSM1233048 1 0.0893 0.8412 0.972 0.000 0.004 0.004 0.004 0.016
#> GSM1233056 1 0.0291 0.8463 0.992 0.000 0.004 0.000 0.000 0.004
#> GSM1233058 4 0.2809 0.6364 0.000 0.004 0.000 0.848 0.128 0.020
#> GSM1233059 1 0.0000 0.8470 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233066 3 0.2744 0.6391 0.000 0.000 0.840 0.000 0.016 0.144
#> GSM1233071 4 0.6855 -0.3517 0.000 0.232 0.000 0.360 0.356 0.052
#> GSM1233074 6 0.4377 0.6137 0.000 0.244 0.068 0.000 0.000 0.688
#> GSM1233076 5 0.6473 0.3045 0.000 0.020 0.088 0.068 0.548 0.276
#> GSM1233080 1 0.0000 0.8470 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233088 4 0.6949 0.3242 0.000 0.052 0.048 0.544 0.176 0.180
#> GSM1233090 1 0.0000 0.8470 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233092 5 0.4806 0.6645 0.000 0.164 0.000 0.148 0.684 0.004
#> GSM1233094 5 0.4090 0.3884 0.000 0.008 0.000 0.384 0.604 0.004
#> GSM1233097 4 0.3590 0.6010 0.000 0.004 0.000 0.776 0.188 0.032
#> GSM1233100 4 0.2420 0.6642 0.004 0.000 0.000 0.888 0.076 0.032
#> GSM1233104 5 0.5673 0.5070 0.000 0.120 0.000 0.320 0.544 0.016
#> GSM1233106 4 0.4614 0.6088 0.064 0.000 0.084 0.776 0.028 0.048
#> GSM1233111 1 0.6601 0.1275 0.428 0.000 0.076 0.412 0.024 0.060
#> GSM1233122 2 0.2875 0.6884 0.000 0.852 0.000 0.000 0.052 0.096
#> GSM1233146 4 0.4097 -0.0827 0.000 0.000 0.000 0.500 0.492 0.008
#> GSM1232994 2 0.3135 0.6918 0.000 0.836 0.000 0.012 0.124 0.028
#> GSM1232996 2 0.1219 0.7307 0.000 0.948 0.000 0.000 0.004 0.048
#> GSM1232997 6 0.6361 0.5620 0.000 0.256 0.084 0.008 0.092 0.560
#> GSM1232998 5 0.4825 0.2081 0.000 0.432 0.000 0.032 0.524 0.012
#> GSM1232999 2 0.4689 0.1441 0.000 0.580 0.000 0.020 0.380 0.020
#> GSM1233000 2 0.1350 0.7381 0.000 0.952 0.000 0.008 0.020 0.020
#> GSM1233004 3 0.7219 0.0449 0.000 0.000 0.376 0.332 0.164 0.128
#> GSM1233011 6 0.7016 0.2576 0.000 0.040 0.208 0.028 0.252 0.472
#> GSM1233012 6 0.5000 0.3089 0.000 0.432 0.044 0.000 0.012 0.512
#> GSM1233023 6 0.5679 0.4161 0.000 0.392 0.020 0.008 0.072 0.508
#> GSM1233027 2 0.4093 0.1526 0.000 0.584 0.000 0.000 0.404 0.012
#> GSM1233033 1 0.6976 0.1761 0.436 0.000 0.056 0.376 0.068 0.064
#> GSM1233036 3 0.6147 0.2700 0.000 0.056 0.536 0.036 0.036 0.336
#> GSM1233037 4 0.8365 -0.0543 0.000 0.144 0.308 0.316 0.088 0.144
#> GSM1233041 1 0.0508 0.8462 0.984 0.000 0.000 0.000 0.004 0.012
#> GSM1233045 4 0.3206 0.6238 0.000 0.004 0.000 0.816 0.152 0.028
#> GSM1233047 3 0.5049 0.5021 0.192 0.000 0.704 0.048 0.016 0.040
#> GSM1233050 1 0.0696 0.8435 0.980 0.000 0.004 0.004 0.008 0.004
#> GSM1233052 4 0.4092 0.6256 0.100 0.000 0.060 0.800 0.016 0.024
#> GSM1233053 1 0.5040 0.5085 0.620 0.000 0.316 0.024 0.012 0.028
#> GSM1233055 1 0.0291 0.8463 0.992 0.000 0.004 0.000 0.000 0.004
#> GSM1233061 3 0.1624 0.6908 0.000 0.000 0.936 0.008 0.012 0.044
#> GSM1233063 1 0.7005 0.3959 0.508 0.000 0.080 0.284 0.060 0.068
#> GSM1233065 6 0.5871 0.5155 0.000 0.356 0.056 0.000 0.068 0.520
#> GSM1233070 5 0.5767 0.5424 0.000 0.256 0.000 0.100 0.596 0.048
#> GSM1233077 6 0.4675 0.2085 0.000 0.000 0.368 0.000 0.052 0.580
#> GSM1233081 3 0.2767 0.6558 0.068 0.000 0.880 0.020 0.004 0.028
#> GSM1233084 1 0.0146 0.8468 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM1233087 4 0.4231 0.5967 0.008 0.000 0.012 0.728 0.224 0.028
#> GSM1233089 6 0.5481 0.2158 0.000 0.436 0.000 0.000 0.124 0.440
#> GSM1233099 4 0.4241 0.6249 0.016 0.000 0.000 0.756 0.152 0.076
#> GSM1233112 1 0.2407 0.8184 0.904 0.000 0.016 0.008 0.048 0.024
#> GSM1233085 3 0.1693 0.6760 0.032 0.000 0.936 0.012 0.000 0.020
#> GSM1233098 2 0.5690 -0.0746 0.000 0.480 0.000 0.000 0.168 0.352
#> GSM1233114 4 0.6791 0.5383 0.144 0.000 0.060 0.596 0.100 0.100
#> GSM1233119 4 0.5121 0.4357 0.000 0.000 0.004 0.580 0.328 0.088
#> GSM1233129 6 0.5163 0.6044 0.000 0.252 0.088 0.000 0.020 0.640
#> GSM1233132 4 0.6881 0.3756 0.280 0.000 0.036 0.516 0.076 0.092
#> GSM1233139 2 0.3424 0.7066 0.000 0.828 0.000 0.012 0.080 0.080
#> GSM1233143 2 0.5812 0.2724 0.000 0.552 0.036 0.000 0.100 0.312
#> GSM1233145 1 0.3274 0.7897 0.856 0.000 0.016 0.020 0.072 0.036
#> GSM1233067 6 0.5355 0.6038 0.000 0.204 0.136 0.000 0.020 0.640
#> GSM1233069 6 0.4728 0.2660 0.000 0.004 0.340 0.000 0.052 0.604
#> GSM1233072 2 0.3832 0.7016 0.000 0.776 0.000 0.000 0.120 0.104
#> GSM1233086 3 0.5807 0.0389 0.000 0.004 0.452 0.024 0.084 0.436
#> GSM1233102 4 0.5319 0.5465 0.020 0.000 0.012 0.652 0.236 0.080
#> GSM1233103 4 0.1755 0.6714 0.000 0.000 0.008 0.932 0.032 0.028
#> GSM1233107 4 0.5977 0.4185 0.000 0.044 0.000 0.544 0.304 0.108
#> GSM1233108 3 0.3130 0.6379 0.124 0.000 0.840 0.008 0.008 0.020
#> GSM1233109 3 0.2436 0.6643 0.000 0.000 0.880 0.000 0.032 0.088
#> GSM1233110 3 0.2790 0.6414 0.000 0.000 0.840 0.000 0.020 0.140
#> GSM1233113 6 0.4947 0.3485 0.000 0.416 0.036 0.000 0.016 0.532
#> GSM1233116 6 0.5319 0.5397 0.000 0.300 0.076 0.000 0.024 0.600
#> GSM1233120 4 0.5139 0.5949 0.032 0.000 0.012 0.700 0.176 0.080
#> GSM1233121 6 0.4797 -0.0157 0.000 0.000 0.444 0.000 0.052 0.504
#> GSM1233123 3 0.2581 0.6513 0.000 0.000 0.856 0.000 0.016 0.128
#> GSM1233124 3 0.2520 0.6402 0.000 0.000 0.844 0.000 0.004 0.152
#> GSM1233125 3 0.3211 0.6395 0.108 0.000 0.844 0.008 0.012 0.028
#> GSM1233126 5 0.4371 0.6344 0.000 0.100 0.000 0.168 0.728 0.004
#> GSM1233127 2 0.5614 0.5361 0.000 0.612 0.000 0.032 0.236 0.120
#> GSM1233128 1 0.1710 0.8364 0.936 0.000 0.020 0.000 0.016 0.028
#> GSM1233130 3 0.4800 0.0918 0.000 0.000 0.500 0.000 0.052 0.448
#> GSM1233131 4 0.2982 0.6665 0.016 0.000 0.012 0.872 0.064 0.036
#> GSM1233133 3 0.0547 0.6904 0.000 0.000 0.980 0.000 0.000 0.020
#> GSM1233134 3 0.4315 0.0411 0.000 0.004 0.496 0.000 0.012 0.488
#> GSM1233135 6 0.4244 0.3272 0.000 0.008 0.320 0.000 0.020 0.652
#> GSM1233136 6 0.5227 0.2459 0.000 0.004 0.336 0.000 0.096 0.564
#> GSM1233137 3 0.1219 0.6879 0.000 0.000 0.948 0.000 0.004 0.048
#> GSM1233138 5 0.4799 0.6632 0.000 0.172 0.000 0.140 0.684 0.004
#> GSM1233140 3 0.6346 0.4080 0.172 0.000 0.620 0.104 0.036 0.068
#> GSM1233141 2 0.5129 0.5889 0.000 0.668 0.000 0.020 0.192 0.120
#> GSM1233142 2 0.5292 0.5754 0.000 0.652 0.000 0.028 0.212 0.108
#> GSM1233144 3 0.0713 0.6904 0.000 0.000 0.972 0.000 0.000 0.028
#> GSM1233147 5 0.5934 0.1576 0.000 0.012 0.108 0.016 0.528 0.336
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> CV:kmeans 152 0.502633 0.597 0.8697 2
#> CV:kmeans 79 0.023596 0.632 0.0862 3
#> CV:kmeans 134 0.000548 0.165 0.0545 4
#> CV:kmeans 112 0.000045 0.197 0.0451 5
#> CV:kmeans 110 0.003776 0.658 0.3782 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 51941 rows and 156 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 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.961 0.984 0.5031 0.497 0.497
#> 3 3 0.695 0.811 0.908 0.3043 0.773 0.575
#> 4 4 0.616 0.651 0.827 0.1174 0.820 0.546
#> 5 5 0.595 0.555 0.762 0.0604 0.955 0.838
#> 6 6 0.604 0.442 0.696 0.0388 0.958 0.838
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0000 0.987 0.000 1.000
#> GSM1233002 1 0.1184 0.967 0.984 0.016
#> GSM1233003 1 0.0000 0.980 1.000 0.000
#> GSM1233014 2 0.0000 0.987 0.000 1.000
#> GSM1233015 1 0.0000 0.980 1.000 0.000
#> GSM1233016 1 0.4562 0.884 0.904 0.096
#> GSM1233024 2 0.0000 0.987 0.000 1.000
#> GSM1233049 1 0.0000 0.980 1.000 0.000
#> GSM1233064 2 0.0000 0.987 0.000 1.000
#> GSM1233068 1 0.0000 0.980 1.000 0.000
#> GSM1233073 1 0.0000 0.980 1.000 0.000
#> GSM1233093 1 0.0000 0.980 1.000 0.000
#> GSM1233115 1 0.0000 0.980 1.000 0.000
#> GSM1232992 2 0.0000 0.987 0.000 1.000
#> GSM1232993 2 0.0000 0.987 0.000 1.000
#> GSM1233005 2 0.0000 0.987 0.000 1.000
#> GSM1233007 2 0.0000 0.987 0.000 1.000
#> GSM1233010 1 0.0000 0.980 1.000 0.000
#> GSM1233013 2 0.0000 0.987 0.000 1.000
#> GSM1233018 2 0.0000 0.987 0.000 1.000
#> GSM1233019 2 0.0000 0.987 0.000 1.000
#> GSM1233021 2 0.0000 0.987 0.000 1.000
#> GSM1233025 1 0.0000 0.980 1.000 0.000
#> GSM1233029 2 0.0000 0.987 0.000 1.000
#> GSM1233030 2 0.0000 0.987 0.000 1.000
#> GSM1233031 1 0.0000 0.980 1.000 0.000
#> GSM1233032 1 0.0000 0.980 1.000 0.000
#> GSM1233035 1 0.0000 0.980 1.000 0.000
#> GSM1233038 1 0.0000 0.980 1.000 0.000
#> GSM1233039 2 0.0000 0.987 0.000 1.000
#> GSM1233042 2 0.1633 0.965 0.024 0.976
#> GSM1233043 2 0.0000 0.987 0.000 1.000
#> GSM1233044 1 0.0000 0.980 1.000 0.000
#> GSM1233046 1 0.0000 0.980 1.000 0.000
#> GSM1233051 1 0.0000 0.980 1.000 0.000
#> GSM1233054 1 0.0000 0.980 1.000 0.000
#> GSM1233057 2 0.0000 0.987 0.000 1.000
#> GSM1233060 1 0.7453 0.732 0.788 0.212
#> GSM1233062 2 0.0000 0.987 0.000 1.000
#> GSM1233075 2 0.0000 0.987 0.000 1.000
#> GSM1233078 1 0.0000 0.980 1.000 0.000
#> GSM1233079 1 0.0000 0.980 1.000 0.000
#> GSM1233082 1 0.0000 0.980 1.000 0.000
#> GSM1233083 1 0.0000 0.980 1.000 0.000
#> GSM1233091 1 0.0000 0.980 1.000 0.000
#> GSM1233095 1 0.0000 0.980 1.000 0.000
#> GSM1233096 1 0.0000 0.980 1.000 0.000
#> GSM1233101 1 0.0000 0.980 1.000 0.000
#> GSM1233105 1 0.0000 0.980 1.000 0.000
#> GSM1233117 2 0.0000 0.987 0.000 1.000
#> GSM1233118 2 0.0000 0.987 0.000 1.000
#> GSM1233001 2 0.0000 0.987 0.000 1.000
#> GSM1233006 2 0.0000 0.987 0.000 1.000
#> GSM1233008 2 0.0000 0.987 0.000 1.000
#> GSM1233009 2 0.0000 0.987 0.000 1.000
#> GSM1233017 2 0.0000 0.987 0.000 1.000
#> GSM1233020 2 0.0000 0.987 0.000 1.000
#> GSM1233022 2 0.0000 0.987 0.000 1.000
#> GSM1233026 1 0.8386 0.635 0.732 0.268
#> GSM1233028 1 0.0938 0.970 0.988 0.012
#> GSM1233034 2 0.0000 0.987 0.000 1.000
#> GSM1233040 1 0.0000 0.980 1.000 0.000
#> GSM1233048 1 0.0000 0.980 1.000 0.000
#> GSM1233056 1 0.0000 0.980 1.000 0.000
#> GSM1233058 1 0.0000 0.980 1.000 0.000
#> GSM1233059 1 0.0000 0.980 1.000 0.000
#> GSM1233066 2 0.1184 0.973 0.016 0.984
#> GSM1233071 2 0.0000 0.987 0.000 1.000
#> GSM1233074 2 0.0000 0.987 0.000 1.000
#> GSM1233076 2 0.0000 0.987 0.000 1.000
#> GSM1233080 1 0.0000 0.980 1.000 0.000
#> GSM1233088 1 0.9393 0.459 0.644 0.356
#> GSM1233090 1 0.0000 0.980 1.000 0.000
#> GSM1233092 2 0.0000 0.987 0.000 1.000
#> GSM1233094 2 0.7376 0.735 0.208 0.792
#> GSM1233097 1 0.1184 0.967 0.984 0.016
#> GSM1233100 1 0.0000 0.980 1.000 0.000
#> GSM1233104 2 0.0000 0.987 0.000 1.000
#> GSM1233106 1 0.0000 0.980 1.000 0.000
#> GSM1233111 1 0.0000 0.980 1.000 0.000
#> GSM1233122 2 0.0000 0.987 0.000 1.000
#> GSM1233146 2 0.9922 0.174 0.448 0.552
#> GSM1232994 2 0.0000 0.987 0.000 1.000
#> GSM1232996 2 0.0000 0.987 0.000 1.000
#> GSM1232997 2 0.0000 0.987 0.000 1.000
#> GSM1232998 2 0.0000 0.987 0.000 1.000
#> GSM1232999 2 0.0000 0.987 0.000 1.000
#> GSM1233000 2 0.0000 0.987 0.000 1.000
#> GSM1233004 1 0.0000 0.980 1.000 0.000
#> GSM1233011 2 0.0000 0.987 0.000 1.000
#> GSM1233012 2 0.0000 0.987 0.000 1.000
#> GSM1233023 2 0.0000 0.987 0.000 1.000
#> GSM1233027 2 0.0000 0.987 0.000 1.000
#> GSM1233033 1 0.0000 0.980 1.000 0.000
#> GSM1233036 2 0.0000 0.987 0.000 1.000
#> GSM1233037 2 0.2778 0.941 0.048 0.952
#> GSM1233041 1 0.0000 0.980 1.000 0.000
#> GSM1233045 2 0.1414 0.969 0.020 0.980
#> GSM1233047 1 0.0000 0.980 1.000 0.000
#> GSM1233050 1 0.0000 0.980 1.000 0.000
#> GSM1233052 1 0.0000 0.980 1.000 0.000
#> GSM1233053 1 0.0000 0.980 1.000 0.000
#> GSM1233055 1 0.0000 0.980 1.000 0.000
#> GSM1233061 1 0.2043 0.952 0.968 0.032
#> GSM1233063 1 0.0000 0.980 1.000 0.000
#> GSM1233065 2 0.0000 0.987 0.000 1.000
#> GSM1233070 2 0.0000 0.987 0.000 1.000
#> GSM1233077 2 0.0000 0.987 0.000 1.000
#> GSM1233081 1 0.0000 0.980 1.000 0.000
#> GSM1233084 1 0.0000 0.980 1.000 0.000
#> GSM1233087 1 0.0000 0.980 1.000 0.000
#> GSM1233089 2 0.0000 0.987 0.000 1.000
#> GSM1233099 1 0.0000 0.980 1.000 0.000
#> GSM1233112 1 0.0000 0.980 1.000 0.000
#> GSM1233085 1 0.0000 0.980 1.000 0.000
#> GSM1233098 2 0.0000 0.987 0.000 1.000
#> GSM1233114 1 0.0000 0.980 1.000 0.000
#> GSM1233119 1 0.0000 0.980 1.000 0.000
#> GSM1233129 2 0.0000 0.987 0.000 1.000
#> GSM1233132 1 0.0000 0.980 1.000 0.000
#> GSM1233139 2 0.0000 0.987 0.000 1.000
#> GSM1233143 2 0.0000 0.987 0.000 1.000
#> GSM1233145 1 0.0000 0.980 1.000 0.000
#> GSM1233067 2 0.0000 0.987 0.000 1.000
#> GSM1233069 2 0.0000 0.987 0.000 1.000
#> GSM1233072 2 0.0000 0.987 0.000 1.000
#> GSM1233086 2 0.0000 0.987 0.000 1.000
#> GSM1233102 1 0.0000 0.980 1.000 0.000
#> GSM1233103 1 0.0000 0.980 1.000 0.000
#> GSM1233107 2 0.7815 0.696 0.232 0.768
#> GSM1233108 1 0.0000 0.980 1.000 0.000
#> GSM1233109 1 0.0000 0.980 1.000 0.000
#> GSM1233110 2 0.1633 0.966 0.024 0.976
#> GSM1233113 2 0.0000 0.987 0.000 1.000
#> GSM1233116 2 0.0000 0.987 0.000 1.000
#> GSM1233120 1 0.0000 0.980 1.000 0.000
#> GSM1233121 2 0.0000 0.987 0.000 1.000
#> GSM1233123 1 0.9866 0.253 0.568 0.432
#> GSM1233124 2 0.0000 0.987 0.000 1.000
#> GSM1233125 1 0.0000 0.980 1.000 0.000
#> GSM1233126 2 0.0000 0.987 0.000 1.000
#> GSM1233127 2 0.0000 0.987 0.000 1.000
#> GSM1233128 1 0.0000 0.980 1.000 0.000
#> GSM1233130 2 0.0000 0.987 0.000 1.000
#> GSM1233131 1 0.0000 0.980 1.000 0.000
#> GSM1233133 1 0.0000 0.980 1.000 0.000
#> GSM1233134 2 0.0000 0.987 0.000 1.000
#> GSM1233135 2 0.0000 0.987 0.000 1.000
#> GSM1233136 2 0.0000 0.987 0.000 1.000
#> GSM1233137 1 0.0000 0.980 1.000 0.000
#> GSM1233138 2 0.0000 0.987 0.000 1.000
#> GSM1233140 1 0.0000 0.980 1.000 0.000
#> GSM1233141 2 0.0000 0.987 0.000 1.000
#> GSM1233142 2 0.0000 0.987 0.000 1.000
#> GSM1233144 1 0.0000 0.980 1.000 0.000
#> GSM1233147 2 0.0000 0.987 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.4750 0.7580 0.000 0.784 0.216
#> GSM1233002 1 0.5178 0.6824 0.744 0.256 0.000
#> GSM1233003 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233014 2 0.0000 0.8606 0.000 1.000 0.000
#> GSM1233015 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233016 2 0.6267 0.1124 0.452 0.548 0.000
#> GSM1233024 2 0.1289 0.8682 0.000 0.968 0.032
#> GSM1233049 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233064 3 0.4178 0.7559 0.000 0.172 0.828
#> GSM1233068 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233073 1 0.2537 0.8834 0.920 0.080 0.000
#> GSM1233093 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233115 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1232992 2 0.3340 0.8503 0.000 0.880 0.120
#> GSM1232993 2 0.0424 0.8634 0.000 0.992 0.008
#> GSM1233005 2 0.3267 0.8524 0.000 0.884 0.116
#> GSM1233007 2 0.4452 0.7556 0.000 0.808 0.192
#> GSM1233010 1 0.2261 0.8931 0.932 0.068 0.000
#> GSM1233013 2 0.3340 0.8503 0.000 0.880 0.120
#> GSM1233018 2 0.3340 0.8503 0.000 0.880 0.120
#> GSM1233019 2 0.1529 0.8691 0.000 0.960 0.040
#> GSM1233021 2 0.3267 0.8524 0.000 0.884 0.116
#> GSM1233025 1 0.2165 0.8952 0.936 0.064 0.000
#> GSM1233029 2 0.1643 0.8690 0.000 0.956 0.044
#> GSM1233030 2 0.3192 0.8543 0.000 0.888 0.112
#> GSM1233031 1 0.6295 0.2068 0.528 0.472 0.000
#> GSM1233032 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233035 1 0.5363 0.6558 0.724 0.276 0.000
#> GSM1233038 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233039 3 0.5988 0.4109 0.000 0.368 0.632
#> GSM1233042 2 0.0000 0.8606 0.000 1.000 0.000
#> GSM1233043 2 0.0000 0.8606 0.000 1.000 0.000
#> GSM1233044 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233046 1 0.0237 0.9308 0.996 0.004 0.000
#> GSM1233051 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233054 1 0.6079 0.3704 0.612 0.000 0.388
#> GSM1233057 3 0.0000 0.8721 0.000 0.000 1.000
#> GSM1233060 2 0.4504 0.6659 0.196 0.804 0.000
#> GSM1233062 2 0.1163 0.8680 0.000 0.972 0.028
#> GSM1233075 3 0.0000 0.8721 0.000 0.000 1.000
#> GSM1233078 3 0.3267 0.7969 0.116 0.000 0.884
#> GSM1233079 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233082 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233083 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233091 1 0.2590 0.8799 0.924 0.004 0.072
#> GSM1233095 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233096 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233101 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233105 1 0.0592 0.9272 0.988 0.012 0.000
#> GSM1233117 2 0.5497 0.6489 0.000 0.708 0.292
#> GSM1233118 3 0.2165 0.8519 0.000 0.064 0.936
#> GSM1233001 2 0.6126 0.4230 0.000 0.600 0.400
#> GSM1233006 2 0.0424 0.8636 0.000 0.992 0.008
#> GSM1233008 2 0.3340 0.8503 0.000 0.880 0.120
#> GSM1233009 2 0.2165 0.8673 0.000 0.936 0.064
#> GSM1233017 2 0.1964 0.8683 0.000 0.944 0.056
#> GSM1233020 2 0.3941 0.8222 0.000 0.844 0.156
#> GSM1233022 2 0.0237 0.8617 0.000 0.996 0.004
#> GSM1233026 2 0.6168 0.2235 0.412 0.588 0.000
#> GSM1233028 2 0.6260 0.0759 0.448 0.552 0.000
#> GSM1233034 2 0.4002 0.8214 0.000 0.840 0.160
#> GSM1233040 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233048 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233056 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233058 1 0.4750 0.7541 0.784 0.216 0.000
#> GSM1233059 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233066 3 0.1015 0.8666 0.008 0.012 0.980
#> GSM1233071 2 0.1529 0.8689 0.000 0.960 0.040
#> GSM1233074 3 0.0747 0.8704 0.000 0.016 0.984
#> GSM1233076 3 0.4002 0.7991 0.000 0.160 0.840
#> GSM1233080 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233088 3 0.2810 0.8559 0.036 0.036 0.928
#> GSM1233090 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233092 2 0.0000 0.8606 0.000 1.000 0.000
#> GSM1233094 2 0.2066 0.8241 0.060 0.940 0.000
#> GSM1233097 1 0.6126 0.3884 0.600 0.400 0.000
#> GSM1233100 1 0.1753 0.9069 0.952 0.048 0.000
#> GSM1233104 2 0.0000 0.8606 0.000 1.000 0.000
#> GSM1233106 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233111 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233122 2 0.3340 0.8503 0.000 0.880 0.120
#> GSM1233146 2 0.1411 0.8390 0.036 0.964 0.000
#> GSM1232994 2 0.1163 0.8677 0.000 0.972 0.028
#> GSM1232996 2 0.3340 0.8503 0.000 0.880 0.120
#> GSM1232997 3 0.0747 0.8704 0.000 0.016 0.984
#> GSM1232998 2 0.0592 0.8647 0.000 0.988 0.012
#> GSM1232999 2 0.0424 0.8636 0.000 0.992 0.008
#> GSM1233000 2 0.2537 0.8647 0.000 0.920 0.080
#> GSM1233004 1 0.5896 0.5771 0.700 0.008 0.292
#> GSM1233011 3 0.3941 0.7906 0.000 0.156 0.844
#> GSM1233012 3 0.6008 0.3465 0.000 0.372 0.628
#> GSM1233023 3 0.3619 0.7960 0.000 0.136 0.864
#> GSM1233027 2 0.0892 0.8666 0.000 0.980 0.020
#> GSM1233033 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233036 3 0.1529 0.8646 0.000 0.040 0.960
#> GSM1233037 3 0.6193 0.5156 0.016 0.292 0.692
#> GSM1233041 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233045 2 0.0000 0.8606 0.000 1.000 0.000
#> GSM1233047 1 0.2165 0.8847 0.936 0.000 0.064
#> GSM1233050 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233052 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233053 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233055 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233061 3 0.3619 0.7847 0.136 0.000 0.864
#> GSM1233063 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233065 3 0.2261 0.8498 0.000 0.068 0.932
#> GSM1233070 2 0.2261 0.8660 0.000 0.932 0.068
#> GSM1233077 3 0.0237 0.8717 0.000 0.004 0.996
#> GSM1233081 1 0.4346 0.7554 0.816 0.000 0.184
#> GSM1233084 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233087 1 0.0747 0.9253 0.984 0.016 0.000
#> GSM1233089 2 0.6260 0.2810 0.000 0.552 0.448
#> GSM1233099 1 0.0424 0.9292 0.992 0.008 0.000
#> GSM1233112 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233085 1 0.5058 0.6706 0.756 0.000 0.244
#> GSM1233098 2 0.5327 0.6818 0.000 0.728 0.272
#> GSM1233114 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233119 1 0.5098 0.7036 0.752 0.248 0.000
#> GSM1233129 3 0.1753 0.8602 0.000 0.048 0.952
#> GSM1233132 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233139 2 0.2796 0.8614 0.000 0.908 0.092
#> GSM1233143 2 0.6215 0.3400 0.000 0.572 0.428
#> GSM1233145 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233067 3 0.0592 0.8718 0.000 0.012 0.988
#> GSM1233069 3 0.0000 0.8721 0.000 0.000 1.000
#> GSM1233072 2 0.3482 0.8451 0.000 0.872 0.128
#> GSM1233086 3 0.0892 0.8715 0.000 0.020 0.980
#> GSM1233102 1 0.0892 0.9231 0.980 0.020 0.000
#> GSM1233103 1 0.3038 0.8631 0.896 0.104 0.000
#> GSM1233107 2 0.5092 0.7085 0.176 0.804 0.020
#> GSM1233108 1 0.4605 0.7286 0.796 0.000 0.204
#> GSM1233109 3 0.6180 0.2747 0.416 0.000 0.584
#> GSM1233110 3 0.0000 0.8721 0.000 0.000 1.000
#> GSM1233113 3 0.4002 0.7697 0.000 0.160 0.840
#> GSM1233116 3 0.3482 0.8036 0.000 0.128 0.872
#> GSM1233120 1 0.0592 0.9274 0.988 0.012 0.000
#> GSM1233121 3 0.0237 0.8717 0.000 0.004 0.996
#> GSM1233123 3 0.0747 0.8661 0.016 0.000 0.984
#> GSM1233124 3 0.0000 0.8721 0.000 0.000 1.000
#> GSM1233125 1 0.4555 0.7340 0.800 0.000 0.200
#> GSM1233126 2 0.0000 0.8606 0.000 1.000 0.000
#> GSM1233127 2 0.2066 0.8683 0.000 0.940 0.060
#> GSM1233128 1 0.0000 0.9325 1.000 0.000 0.000
#> GSM1233130 3 0.0237 0.8717 0.000 0.004 0.996
#> GSM1233131 1 0.0237 0.9308 0.996 0.004 0.000
#> GSM1233133 3 0.5859 0.4572 0.344 0.000 0.656
#> GSM1233134 3 0.0000 0.8721 0.000 0.000 1.000
#> GSM1233135 3 0.0000 0.8721 0.000 0.000 1.000
#> GSM1233136 3 0.0237 0.8717 0.000 0.004 0.996
#> GSM1233137 3 0.4121 0.7514 0.168 0.000 0.832
#> GSM1233138 2 0.0000 0.8606 0.000 1.000 0.000
#> GSM1233140 1 0.0237 0.9303 0.996 0.000 0.004
#> GSM1233141 2 0.3116 0.8559 0.000 0.892 0.108
#> GSM1233142 2 0.2261 0.8667 0.000 0.932 0.068
#> GSM1233144 3 0.5098 0.6407 0.248 0.000 0.752
#> GSM1233147 3 0.4887 0.7239 0.000 0.228 0.772
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.1978 0.7581 0.000 0.928 0.068 0.004
#> GSM1233002 4 0.6417 0.3104 0.388 0.072 0.000 0.540
#> GSM1233003 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233014 4 0.4722 0.5439 0.000 0.300 0.008 0.692
#> GSM1233015 1 0.2011 0.8465 0.920 0.000 0.000 0.080
#> GSM1233016 4 0.4560 0.7178 0.092 0.084 0.008 0.816
#> GSM1233024 2 0.3448 0.6733 0.000 0.828 0.004 0.168
#> GSM1233049 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233064 2 0.5337 0.2676 0.000 0.564 0.424 0.012
#> GSM1233068 1 0.1474 0.8632 0.948 0.000 0.000 0.052
#> GSM1233073 4 0.4713 0.3920 0.360 0.000 0.000 0.640
#> GSM1233093 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233115 1 0.0592 0.8790 0.984 0.000 0.000 0.016
#> GSM1232992 2 0.0376 0.7648 0.000 0.992 0.004 0.004
#> GSM1232993 2 0.3982 0.6066 0.000 0.776 0.004 0.220
#> GSM1233005 2 0.0779 0.7655 0.000 0.980 0.004 0.016
#> GSM1233007 2 0.6835 0.4028 0.000 0.576 0.136 0.288
#> GSM1233010 4 0.4697 0.3748 0.356 0.000 0.000 0.644
#> GSM1233013 2 0.0336 0.7640 0.000 0.992 0.000 0.008
#> GSM1233018 2 0.0779 0.7655 0.000 0.980 0.004 0.016
#> GSM1233019 2 0.1743 0.7455 0.000 0.940 0.004 0.056
#> GSM1233021 2 0.0779 0.7655 0.000 0.980 0.004 0.016
#> GSM1233025 4 0.4194 0.6318 0.228 0.000 0.008 0.764
#> GSM1233029 2 0.2281 0.7322 0.000 0.904 0.000 0.096
#> GSM1233030 2 0.0469 0.7633 0.000 0.988 0.000 0.012
#> GSM1233031 4 0.3668 0.6970 0.116 0.028 0.004 0.852
#> GSM1233032 1 0.0336 0.8788 0.992 0.000 0.000 0.008
#> GSM1233035 4 0.5966 0.3253 0.384 0.036 0.004 0.576
#> GSM1233038 1 0.0336 0.8798 0.992 0.000 0.000 0.008
#> GSM1233039 2 0.7358 0.1082 0.000 0.448 0.392 0.160
#> GSM1233042 4 0.4158 0.6466 0.000 0.224 0.008 0.768
#> GSM1233043 4 0.4262 0.6366 0.000 0.236 0.008 0.756
#> GSM1233044 1 0.1888 0.8659 0.940 0.000 0.016 0.044
#> GSM1233046 1 0.1637 0.8571 0.940 0.000 0.000 0.060
#> GSM1233051 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233054 1 0.5331 0.4684 0.644 0.000 0.332 0.024
#> GSM1233057 3 0.5007 0.3530 0.000 0.356 0.636 0.008
#> GSM1233060 4 0.6363 0.6480 0.144 0.184 0.004 0.668
#> GSM1233062 2 0.3539 0.6631 0.000 0.820 0.004 0.176
#> GSM1233075 3 0.5070 0.1954 0.000 0.416 0.580 0.004
#> GSM1233078 3 0.1059 0.7673 0.016 0.000 0.972 0.012
#> GSM1233079 1 0.0524 0.8775 0.988 0.000 0.004 0.008
#> GSM1233082 1 0.1716 0.8580 0.936 0.000 0.000 0.064
#> GSM1233083 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233091 1 0.5531 0.6758 0.732 0.000 0.128 0.140
#> GSM1233095 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233096 1 0.0817 0.8755 0.976 0.000 0.000 0.024
#> GSM1233101 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233105 1 0.4103 0.6515 0.744 0.000 0.000 0.256
#> GSM1233117 2 0.2944 0.7216 0.000 0.868 0.128 0.004
#> GSM1233118 2 0.4972 0.2047 0.000 0.544 0.456 0.000
#> GSM1233001 2 0.2921 0.7108 0.000 0.860 0.140 0.000
#> GSM1233006 2 0.5161 0.2147 0.000 0.592 0.008 0.400
#> GSM1233008 2 0.0592 0.7646 0.000 0.984 0.000 0.016
#> GSM1233009 2 0.2281 0.7368 0.000 0.904 0.000 0.096
#> GSM1233017 2 0.2647 0.7145 0.000 0.880 0.000 0.120
#> GSM1233020 2 0.0469 0.7655 0.000 0.988 0.012 0.000
#> GSM1233022 4 0.5050 0.3622 0.000 0.408 0.004 0.588
#> GSM1233026 4 0.3927 0.7137 0.072 0.060 0.012 0.856
#> GSM1233028 4 0.4205 0.7079 0.096 0.068 0.004 0.832
#> GSM1233034 2 0.1452 0.7648 0.000 0.956 0.036 0.008
#> GSM1233040 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233048 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233056 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233058 4 0.3727 0.6688 0.164 0.004 0.008 0.824
#> GSM1233059 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233066 3 0.1182 0.7694 0.000 0.016 0.968 0.016
#> GSM1233071 2 0.3636 0.6744 0.000 0.820 0.008 0.172
#> GSM1233074 2 0.5119 0.2386 0.000 0.556 0.440 0.004
#> GSM1233076 3 0.6013 0.4915 0.000 0.072 0.640 0.288
#> GSM1233080 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233088 3 0.6778 0.5405 0.056 0.224 0.660 0.060
#> GSM1233090 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233092 4 0.4391 0.6147 0.000 0.252 0.008 0.740
#> GSM1233094 4 0.3208 0.6925 0.000 0.148 0.004 0.848
#> GSM1233097 4 0.1411 0.7082 0.020 0.020 0.000 0.960
#> GSM1233100 1 0.4905 0.4429 0.632 0.004 0.000 0.364
#> GSM1233104 4 0.2589 0.7052 0.000 0.116 0.000 0.884
#> GSM1233106 1 0.1118 0.8712 0.964 0.000 0.000 0.036
#> GSM1233111 1 0.0469 0.8790 0.988 0.000 0.000 0.012
#> GSM1233122 2 0.0804 0.7651 0.000 0.980 0.012 0.008
#> GSM1233146 4 0.2310 0.7125 0.004 0.068 0.008 0.920
#> GSM1232994 2 0.3105 0.6929 0.000 0.856 0.004 0.140
#> GSM1232996 2 0.0779 0.7655 0.000 0.980 0.004 0.016
#> GSM1232997 2 0.4907 0.3114 0.000 0.580 0.420 0.000
#> GSM1232998 4 0.5244 0.2339 0.000 0.436 0.008 0.556
#> GSM1232999 2 0.5099 0.2735 0.000 0.612 0.008 0.380
#> GSM1233000 2 0.0921 0.7619 0.000 0.972 0.000 0.028
#> GSM1233004 3 0.6972 0.2689 0.356 0.000 0.520 0.124
#> GSM1233011 3 0.6936 0.3563 0.000 0.292 0.564 0.144
#> GSM1233012 2 0.3764 0.6472 0.000 0.784 0.216 0.000
#> GSM1233023 2 0.4283 0.5847 0.000 0.740 0.256 0.004
#> GSM1233027 2 0.4673 0.4801 0.000 0.700 0.008 0.292
#> GSM1233033 1 0.0817 0.8748 0.976 0.000 0.000 0.024
#> GSM1233036 3 0.5285 0.0300 0.000 0.468 0.524 0.008
#> GSM1233037 2 0.6378 0.5300 0.048 0.672 0.240 0.040
#> GSM1233041 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233045 4 0.2654 0.7021 0.000 0.108 0.004 0.888
#> GSM1233047 1 0.1888 0.8507 0.940 0.000 0.044 0.016
#> GSM1233050 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233052 1 0.1637 0.8614 0.940 0.000 0.000 0.060
#> GSM1233053 1 0.1059 0.8701 0.972 0.000 0.012 0.016
#> GSM1233055 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233061 3 0.3501 0.7056 0.132 0.000 0.848 0.020
#> GSM1233063 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233065 2 0.5004 0.3589 0.000 0.604 0.392 0.004
#> GSM1233070 2 0.4095 0.6349 0.000 0.792 0.016 0.192
#> GSM1233077 3 0.0895 0.7677 0.000 0.020 0.976 0.004
#> GSM1233081 1 0.4630 0.6248 0.732 0.000 0.252 0.016
#> GSM1233084 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233087 1 0.4356 0.5926 0.708 0.000 0.000 0.292
#> GSM1233089 2 0.3625 0.6960 0.000 0.828 0.160 0.012
#> GSM1233099 1 0.4855 0.3779 0.600 0.000 0.000 0.400
#> GSM1233112 1 0.0188 0.8804 0.996 0.000 0.000 0.004
#> GSM1233085 1 0.5417 0.2797 0.572 0.000 0.412 0.016
#> GSM1233098 2 0.2197 0.7495 0.000 0.916 0.080 0.004
#> GSM1233114 1 0.2647 0.8109 0.880 0.000 0.000 0.120
#> GSM1233119 4 0.1585 0.7052 0.040 0.004 0.004 0.952
#> GSM1233129 2 0.5088 0.2826 0.000 0.572 0.424 0.004
#> GSM1233132 1 0.2011 0.8443 0.920 0.000 0.000 0.080
#> GSM1233139 2 0.0592 0.7642 0.000 0.984 0.000 0.016
#> GSM1233143 2 0.3810 0.6702 0.000 0.804 0.188 0.008
#> GSM1233145 1 0.1867 0.8490 0.928 0.000 0.000 0.072
#> GSM1233067 3 0.5028 0.2313 0.000 0.400 0.596 0.004
#> GSM1233069 3 0.1022 0.7652 0.000 0.032 0.968 0.000
#> GSM1233072 2 0.0937 0.7663 0.000 0.976 0.012 0.012
#> GSM1233086 3 0.4633 0.6487 0.000 0.172 0.780 0.048
#> GSM1233102 1 0.4948 0.2278 0.560 0.000 0.000 0.440
#> GSM1233103 4 0.5946 -0.0156 0.472 0.028 0.004 0.496
#> GSM1233107 4 0.4730 0.4171 0.000 0.364 0.000 0.636
#> GSM1233108 1 0.5269 0.4053 0.620 0.000 0.364 0.016
#> GSM1233109 3 0.4567 0.5917 0.244 0.000 0.740 0.016
#> GSM1233110 3 0.0672 0.7691 0.000 0.008 0.984 0.008
#> GSM1233113 2 0.4522 0.5049 0.000 0.680 0.320 0.000
#> GSM1233116 2 0.4996 0.1203 0.000 0.516 0.484 0.000
#> GSM1233120 1 0.4605 0.5088 0.664 0.000 0.000 0.336
#> GSM1233121 3 0.0657 0.7685 0.000 0.012 0.984 0.004
#> GSM1233123 3 0.1082 0.7680 0.004 0.004 0.972 0.020
#> GSM1233124 3 0.1520 0.7681 0.000 0.024 0.956 0.020
#> GSM1233125 1 0.5253 0.4136 0.624 0.000 0.360 0.016
#> GSM1233126 4 0.4262 0.6286 0.000 0.236 0.008 0.756
#> GSM1233127 2 0.4134 0.5643 0.000 0.740 0.000 0.260
#> GSM1233128 1 0.0000 0.8816 1.000 0.000 0.000 0.000
#> GSM1233130 3 0.0376 0.7687 0.000 0.004 0.992 0.004
#> GSM1233131 1 0.4564 0.5364 0.672 0.000 0.000 0.328
#> GSM1233133 3 0.4675 0.5974 0.244 0.000 0.736 0.020
#> GSM1233134 3 0.2124 0.7505 0.000 0.068 0.924 0.008
#> GSM1233135 3 0.1489 0.7619 0.000 0.044 0.952 0.004
#> GSM1233136 3 0.1042 0.7671 0.000 0.020 0.972 0.008
#> GSM1233137 3 0.3757 0.6870 0.152 0.000 0.828 0.020
#> GSM1233138 4 0.4452 0.6013 0.000 0.260 0.008 0.732
#> GSM1233140 1 0.1510 0.8611 0.956 0.000 0.028 0.016
#> GSM1233141 2 0.2760 0.7149 0.000 0.872 0.000 0.128
#> GSM1233142 2 0.3649 0.6399 0.000 0.796 0.000 0.204
#> GSM1233144 3 0.4079 0.6623 0.180 0.000 0.800 0.020
#> GSM1233147 3 0.5705 0.5320 0.000 0.064 0.676 0.260
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.2270 0.71242 0.000 0.916 0.052 0.020 0.012
#> GSM1233002 4 0.7055 0.35182 0.208 0.016 0.004 0.460 0.312
#> GSM1233003 1 0.0324 0.81800 0.992 0.000 0.000 0.004 0.004
#> GSM1233014 5 0.3477 0.58640 0.000 0.136 0.000 0.040 0.824
#> GSM1233015 1 0.4306 0.52892 0.660 0.000 0.000 0.328 0.012
#> GSM1233016 5 0.3114 0.51854 0.036 0.016 0.000 0.076 0.872
#> GSM1233024 2 0.5090 0.54791 0.000 0.688 0.000 0.104 0.208
#> GSM1233049 1 0.0162 0.81742 0.996 0.000 0.000 0.004 0.000
#> GSM1233064 2 0.7264 0.34138 0.000 0.532 0.244 0.100 0.124
#> GSM1233068 1 0.4001 0.69123 0.764 0.000 0.004 0.208 0.024
#> GSM1233073 5 0.6318 -0.11363 0.240 0.004 0.000 0.204 0.552
#> GSM1233093 1 0.0000 0.81729 1.000 0.000 0.000 0.000 0.000
#> GSM1233115 1 0.1851 0.79832 0.912 0.000 0.000 0.088 0.000
#> GSM1232992 2 0.1403 0.71315 0.000 0.952 0.000 0.024 0.024
#> GSM1232993 2 0.5666 0.37155 0.000 0.592 0.000 0.108 0.300
#> GSM1233005 2 0.1725 0.71336 0.000 0.936 0.000 0.020 0.044
#> GSM1233007 5 0.6890 0.38135 0.000 0.284 0.060 0.116 0.540
#> GSM1233010 4 0.4247 0.56779 0.132 0.000 0.000 0.776 0.092
#> GSM1233013 2 0.1211 0.71405 0.000 0.960 0.000 0.016 0.024
#> GSM1233018 2 0.1117 0.71512 0.000 0.964 0.000 0.020 0.016
#> GSM1233019 2 0.3412 0.65884 0.000 0.820 0.000 0.028 0.152
#> GSM1233021 2 0.1579 0.71335 0.000 0.944 0.000 0.024 0.032
#> GSM1233025 5 0.6287 -0.10356 0.196 0.000 0.000 0.276 0.528
#> GSM1233029 2 0.4840 0.60257 0.000 0.724 0.000 0.152 0.124
#> GSM1233030 2 0.1725 0.70879 0.000 0.936 0.000 0.020 0.044
#> GSM1233031 4 0.4054 0.51001 0.008 0.012 0.000 0.744 0.236
#> GSM1233032 1 0.1153 0.81507 0.964 0.000 0.004 0.024 0.008
#> GSM1233035 4 0.6721 0.43885 0.208 0.016 0.000 0.520 0.256
#> GSM1233038 1 0.0510 0.81677 0.984 0.000 0.000 0.016 0.000
#> GSM1233039 2 0.8350 0.05271 0.000 0.376 0.180 0.236 0.208
#> GSM1233042 5 0.3849 0.55117 0.000 0.080 0.000 0.112 0.808
#> GSM1233043 5 0.3849 0.55117 0.000 0.080 0.000 0.112 0.808
#> GSM1233044 1 0.4401 0.72651 0.800 0.000 0.048 0.100 0.052
#> GSM1233046 1 0.3193 0.75573 0.840 0.000 0.000 0.132 0.028
#> GSM1233051 1 0.0671 0.81866 0.980 0.000 0.000 0.016 0.004
#> GSM1233054 1 0.6200 0.36175 0.552 0.000 0.336 0.088 0.024
#> GSM1233057 3 0.6475 -0.03116 0.000 0.436 0.444 0.092 0.028
#> GSM1233060 4 0.7011 0.17067 0.060 0.104 0.000 0.464 0.372
#> GSM1233062 2 0.5322 0.52822 0.000 0.672 0.000 0.140 0.188
#> GSM1233075 2 0.5707 0.13928 0.000 0.496 0.444 0.032 0.028
#> GSM1233078 3 0.2072 0.72149 0.020 0.000 0.928 0.036 0.016
#> GSM1233079 1 0.0960 0.81615 0.972 0.000 0.004 0.016 0.008
#> GSM1233082 1 0.3171 0.74136 0.816 0.000 0.000 0.176 0.008
#> GSM1233083 1 0.1059 0.81594 0.968 0.000 0.004 0.020 0.008
#> GSM1233091 1 0.6485 0.09991 0.484 0.008 0.060 0.412 0.036
#> GSM1233095 1 0.0000 0.81729 1.000 0.000 0.000 0.000 0.000
#> GSM1233096 1 0.2971 0.75313 0.836 0.000 0.000 0.156 0.008
#> GSM1233101 1 0.0000 0.81729 1.000 0.000 0.000 0.000 0.000
#> GSM1233105 1 0.6114 0.30520 0.564 0.000 0.000 0.244 0.192
#> GSM1233117 2 0.3444 0.69997 0.000 0.848 0.104 0.024 0.024
#> GSM1233118 2 0.5208 0.44332 0.000 0.624 0.328 0.028 0.020
#> GSM1233001 2 0.2722 0.70441 0.000 0.896 0.056 0.020 0.028
#> GSM1233006 5 0.3727 0.54934 0.000 0.216 0.000 0.016 0.768
#> GSM1233008 2 0.1310 0.71741 0.000 0.956 0.000 0.020 0.024
#> GSM1233009 2 0.4096 0.65309 0.000 0.784 0.000 0.144 0.072
#> GSM1233017 2 0.4393 0.61862 0.000 0.756 0.000 0.076 0.168
#> GSM1233020 2 0.2006 0.71353 0.000 0.932 0.020 0.024 0.024
#> GSM1233022 5 0.5552 0.39747 0.000 0.328 0.000 0.088 0.584
#> GSM1233026 4 0.4324 0.51190 0.016 0.052 0.008 0.800 0.124
#> GSM1233028 4 0.4423 0.53753 0.024 0.048 0.000 0.780 0.148
#> GSM1233034 2 0.2529 0.71519 0.000 0.900 0.004 0.056 0.040
#> GSM1233040 1 0.1430 0.81047 0.944 0.000 0.000 0.052 0.004
#> GSM1233048 1 0.0898 0.81629 0.972 0.000 0.000 0.020 0.008
#> GSM1233056 1 0.0162 0.81707 0.996 0.000 0.000 0.004 0.000
#> GSM1233058 4 0.4532 0.53555 0.048 0.004 0.008 0.756 0.184
#> GSM1233059 1 0.0162 0.81734 0.996 0.000 0.000 0.004 0.000
#> GSM1233066 3 0.2015 0.72818 0.004 0.008 0.932 0.036 0.020
#> GSM1233071 2 0.6127 0.34092 0.000 0.552 0.000 0.172 0.276
#> GSM1233074 2 0.5439 0.39238 0.000 0.596 0.348 0.032 0.024
#> GSM1233076 5 0.7091 -0.12481 0.000 0.056 0.404 0.116 0.424
#> GSM1233080 1 0.0162 0.81734 0.996 0.000 0.000 0.004 0.000
#> GSM1233088 3 0.8780 0.17001 0.032 0.180 0.344 0.316 0.128
#> GSM1233090 1 0.0162 0.81734 0.996 0.000 0.000 0.004 0.000
#> GSM1233092 5 0.2712 0.60198 0.000 0.088 0.000 0.032 0.880
#> GSM1233094 5 0.3950 0.52857 0.000 0.068 0.000 0.136 0.796
#> GSM1233097 4 0.4551 0.41018 0.008 0.008 0.000 0.636 0.348
#> GSM1233100 1 0.6662 -0.00938 0.468 0.008 0.000 0.340 0.184
#> GSM1233104 5 0.5652 0.13962 0.000 0.088 0.000 0.360 0.552
#> GSM1233106 1 0.2909 0.76734 0.848 0.000 0.000 0.140 0.012
#> GSM1233111 1 0.2563 0.77895 0.872 0.000 0.000 0.120 0.008
#> GSM1233122 2 0.1883 0.71706 0.000 0.932 0.008 0.012 0.048
#> GSM1233146 5 0.4106 0.39852 0.000 0.020 0.000 0.256 0.724
#> GSM1232994 2 0.4801 0.59866 0.000 0.728 0.000 0.124 0.148
#> GSM1232996 2 0.1012 0.71682 0.000 0.968 0.000 0.012 0.020
#> GSM1232997 2 0.5423 0.42363 0.000 0.616 0.324 0.036 0.024
#> GSM1232998 5 0.5375 0.34599 0.000 0.368 0.000 0.064 0.568
#> GSM1232999 2 0.5896 0.27975 0.000 0.564 0.000 0.128 0.308
#> GSM1233000 2 0.2922 0.69432 0.000 0.872 0.000 0.072 0.056
#> GSM1233004 3 0.7593 0.08900 0.332 0.000 0.380 0.240 0.048
#> GSM1233011 3 0.7306 0.39015 0.000 0.252 0.524 0.104 0.120
#> GSM1233012 2 0.4461 0.63930 0.000 0.756 0.192 0.028 0.024
#> GSM1233023 2 0.4704 0.60905 0.000 0.744 0.192 0.032 0.032
#> GSM1233027 2 0.5386 0.20084 0.000 0.544 0.000 0.060 0.396
#> GSM1233033 1 0.2293 0.79464 0.900 0.000 0.000 0.084 0.016
#> GSM1233036 3 0.6270 0.05407 0.000 0.408 0.484 0.088 0.020
#> GSM1233037 2 0.7041 0.46387 0.032 0.604 0.160 0.164 0.040
#> GSM1233041 1 0.0162 0.81734 0.996 0.000 0.000 0.004 0.000
#> GSM1233045 4 0.4915 0.41976 0.000 0.064 0.004 0.696 0.236
#> GSM1233047 1 0.3371 0.74726 0.848 0.000 0.104 0.040 0.008
#> GSM1233050 1 0.0404 0.81746 0.988 0.000 0.000 0.012 0.000
#> GSM1233052 1 0.3171 0.73884 0.816 0.000 0.000 0.176 0.008
#> GSM1233053 1 0.1996 0.80106 0.928 0.000 0.032 0.036 0.004
#> GSM1233055 1 0.0000 0.81729 1.000 0.000 0.000 0.000 0.000
#> GSM1233061 3 0.4162 0.64164 0.132 0.000 0.800 0.048 0.020
#> GSM1233063 1 0.0880 0.81652 0.968 0.000 0.000 0.032 0.000
#> GSM1233065 2 0.5173 0.53513 0.000 0.684 0.248 0.044 0.024
#> GSM1233070 2 0.5471 0.13211 0.000 0.516 0.004 0.052 0.428
#> GSM1233077 3 0.2853 0.71982 0.000 0.036 0.892 0.044 0.028
#> GSM1233081 1 0.4751 0.55925 0.692 0.000 0.264 0.036 0.008
#> GSM1233084 1 0.0000 0.81729 1.000 0.000 0.000 0.000 0.000
#> GSM1233087 1 0.5466 0.46845 0.656 0.000 0.000 0.152 0.192
#> GSM1233089 2 0.4612 0.67138 0.000 0.780 0.108 0.028 0.084
#> GSM1233099 4 0.6100 0.19276 0.428 0.000 0.000 0.448 0.124
#> GSM1233112 1 0.0727 0.81652 0.980 0.000 0.004 0.012 0.004
#> GSM1233085 1 0.5628 0.09750 0.492 0.000 0.452 0.036 0.020
#> GSM1233098 2 0.3658 0.69921 0.000 0.844 0.044 0.028 0.084
#> GSM1233114 1 0.3934 0.61608 0.740 0.000 0.000 0.244 0.016
#> GSM1233119 4 0.4688 0.23083 0.008 0.004 0.000 0.532 0.456
#> GSM1233129 2 0.5256 0.41310 0.000 0.608 0.344 0.032 0.016
#> GSM1233132 1 0.3427 0.69656 0.796 0.000 0.000 0.192 0.012
#> GSM1233139 2 0.2899 0.70367 0.000 0.872 0.004 0.096 0.028
#> GSM1233143 2 0.4569 0.67147 0.000 0.760 0.172 0.020 0.048
#> GSM1233145 1 0.3033 0.75808 0.864 0.000 0.000 0.084 0.052
#> GSM1233067 3 0.5204 0.29509 0.000 0.348 0.608 0.024 0.020
#> GSM1233069 3 0.2853 0.71984 0.000 0.044 0.892 0.036 0.028
#> GSM1233072 2 0.3784 0.69988 0.000 0.820 0.024 0.024 0.132
#> GSM1233086 3 0.5380 0.65160 0.000 0.092 0.736 0.096 0.076
#> GSM1233102 1 0.6387 0.07610 0.516 0.000 0.000 0.248 0.236
#> GSM1233103 4 0.5157 0.55309 0.160 0.020 0.004 0.732 0.084
#> GSM1233107 4 0.6948 0.10864 0.012 0.204 0.004 0.468 0.312
#> GSM1233108 1 0.4998 0.45382 0.632 0.000 0.328 0.032 0.008
#> GSM1233109 3 0.4930 0.54726 0.228 0.000 0.708 0.048 0.016
#> GSM1233110 3 0.0912 0.72514 0.000 0.000 0.972 0.016 0.012
#> GSM1233113 2 0.4473 0.60968 0.000 0.748 0.204 0.028 0.020
#> GSM1233116 2 0.5419 0.29257 0.000 0.548 0.404 0.032 0.016
#> GSM1233120 1 0.5570 0.34410 0.608 0.000 0.000 0.288 0.104
#> GSM1233121 3 0.2333 0.72400 0.000 0.016 0.916 0.040 0.028
#> GSM1233123 3 0.1195 0.72532 0.000 0.000 0.960 0.028 0.012
#> GSM1233124 3 0.2351 0.72151 0.000 0.028 0.916 0.036 0.020
#> GSM1233125 1 0.5368 0.36891 0.592 0.000 0.356 0.036 0.016
#> GSM1233126 5 0.2482 0.60154 0.000 0.084 0.000 0.024 0.892
#> GSM1233127 2 0.5804 0.50049 0.000 0.628 0.004 0.208 0.160
#> GSM1233128 1 0.0290 0.81742 0.992 0.000 0.000 0.008 0.000
#> GSM1233130 3 0.1948 0.72596 0.000 0.008 0.932 0.036 0.024
#> GSM1233131 4 0.5603 0.07122 0.452 0.000 0.000 0.476 0.072
#> GSM1233133 3 0.4629 0.57020 0.204 0.000 0.740 0.036 0.020
#> GSM1233134 3 0.2585 0.71354 0.000 0.072 0.896 0.024 0.008
#> GSM1233135 3 0.2897 0.71557 0.000 0.072 0.884 0.020 0.024
#> GSM1233136 3 0.3316 0.71378 0.000 0.044 0.868 0.052 0.036
#> GSM1233137 3 0.3892 0.65584 0.120 0.000 0.820 0.036 0.024
#> GSM1233138 5 0.2824 0.60197 0.000 0.096 0.000 0.032 0.872
#> GSM1233140 1 0.3040 0.78551 0.876 0.000 0.044 0.068 0.012
#> GSM1233141 2 0.4093 0.67775 0.000 0.808 0.012 0.088 0.092
#> GSM1233142 2 0.5135 0.59509 0.000 0.704 0.004 0.172 0.120
#> GSM1233144 3 0.4326 0.61889 0.160 0.000 0.780 0.036 0.024
#> GSM1233147 3 0.6308 0.12226 0.000 0.028 0.456 0.076 0.440
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.4133 0.5262 0.000 0.748 0.048 0.008 0.004 0.192
#> GSM1233002 5 0.7820 0.2655 0.200 0.016 0.000 0.256 0.364 0.164
#> GSM1233003 1 0.1080 0.7674 0.960 0.000 0.000 0.004 0.004 0.032
#> GSM1233014 4 0.3338 0.5442 0.000 0.172 0.000 0.800 0.020 0.008
#> GSM1233015 1 0.6537 0.1858 0.460 0.000 0.000 0.036 0.244 0.260
#> GSM1233016 4 0.2874 0.5030 0.048 0.016 0.000 0.880 0.044 0.012
#> GSM1233024 2 0.4352 0.5327 0.000 0.768 0.000 0.120 0.060 0.052
#> GSM1233049 1 0.0405 0.7671 0.988 0.000 0.004 0.000 0.000 0.008
#> GSM1233064 6 0.7331 0.4561 0.000 0.312 0.124 0.080 0.040 0.444
#> GSM1233068 1 0.5916 0.5510 0.624 0.000 0.012 0.036 0.160 0.168
#> GSM1233073 4 0.7238 -0.0912 0.216 0.008 0.000 0.456 0.212 0.108
#> GSM1233093 1 0.0146 0.7668 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM1233115 1 0.2373 0.7513 0.888 0.000 0.000 0.004 0.084 0.024
#> GSM1232992 2 0.1515 0.6031 0.000 0.944 0.000 0.020 0.008 0.028
#> GSM1232993 2 0.6033 0.2692 0.000 0.608 0.000 0.184 0.084 0.124
#> GSM1233005 2 0.2024 0.6068 0.000 0.920 0.000 0.016 0.028 0.036
#> GSM1233007 4 0.7184 -0.1025 0.000 0.280 0.032 0.424 0.036 0.228
#> GSM1233010 5 0.3803 0.5908 0.056 0.004 0.000 0.048 0.820 0.072
#> GSM1233013 2 0.0806 0.6049 0.000 0.972 0.000 0.008 0.000 0.020
#> GSM1233018 2 0.1555 0.6054 0.000 0.940 0.000 0.008 0.012 0.040
#> GSM1233019 2 0.2151 0.5909 0.000 0.904 0.000 0.072 0.008 0.016
#> GSM1233021 2 0.1700 0.6030 0.000 0.936 0.000 0.012 0.028 0.024
#> GSM1233025 4 0.6343 -0.0703 0.168 0.000 0.000 0.496 0.296 0.040
#> GSM1233029 2 0.3798 0.5498 0.000 0.812 0.000 0.060 0.040 0.088
#> GSM1233030 2 0.0976 0.6033 0.000 0.968 0.000 0.016 0.008 0.008
#> GSM1233031 5 0.5028 0.5587 0.008 0.032 0.000 0.116 0.716 0.128
#> GSM1233032 1 0.2488 0.7579 0.892 0.000 0.016 0.004 0.016 0.072
#> GSM1233035 5 0.8443 0.3350 0.140 0.060 0.008 0.192 0.352 0.248
#> GSM1233038 1 0.1053 0.7649 0.964 0.000 0.000 0.004 0.012 0.020
#> GSM1233039 6 0.7887 0.5021 0.000 0.192 0.092 0.140 0.112 0.464
#> GSM1233042 4 0.4326 0.5367 0.000 0.092 0.000 0.776 0.064 0.068
#> GSM1233043 4 0.4261 0.5399 0.000 0.096 0.000 0.780 0.064 0.060
#> GSM1233044 1 0.5437 0.6498 0.720 0.000 0.080 0.048 0.088 0.064
#> GSM1233046 1 0.4484 0.6891 0.772 0.000 0.008 0.044 0.092 0.084
#> GSM1233051 1 0.1442 0.7691 0.944 0.000 0.004 0.000 0.012 0.040
#> GSM1233054 3 0.6580 0.0079 0.360 0.000 0.424 0.008 0.028 0.180
#> GSM1233057 3 0.6927 -0.1651 0.000 0.236 0.388 0.004 0.048 0.324
#> GSM1233060 4 0.8041 -0.0991 0.024 0.156 0.000 0.300 0.252 0.268
#> GSM1233062 2 0.4474 0.5209 0.000 0.760 0.000 0.112 0.048 0.080
#> GSM1233075 2 0.6331 -0.0203 0.000 0.384 0.284 0.004 0.004 0.324
#> GSM1233078 3 0.2368 0.5222 0.008 0.000 0.888 0.004 0.008 0.092
#> GSM1233079 1 0.2613 0.7567 0.892 0.000 0.040 0.008 0.012 0.048
#> GSM1233082 1 0.5204 0.5804 0.660 0.000 0.000 0.020 0.192 0.128
#> GSM1233083 1 0.2164 0.7571 0.916 0.000 0.012 0.008 0.020 0.044
#> GSM1233091 1 0.8032 -0.2384 0.328 0.008 0.072 0.048 0.320 0.224
#> GSM1233095 1 0.0260 0.7672 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM1233096 1 0.4624 0.6574 0.732 0.000 0.000 0.024 0.104 0.140
#> GSM1233101 1 0.0260 0.7674 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM1233105 1 0.6980 0.2453 0.484 0.000 0.000 0.196 0.192 0.128
#> GSM1233117 2 0.4487 0.5206 0.000 0.732 0.064 0.016 0.004 0.184
#> GSM1233118 2 0.6192 0.1846 0.000 0.476 0.232 0.008 0.004 0.280
#> GSM1233001 2 0.3560 0.5151 0.000 0.772 0.012 0.008 0.004 0.204
#> GSM1233006 4 0.3915 0.4581 0.000 0.228 0.000 0.736 0.008 0.028
#> GSM1233008 2 0.2449 0.6069 0.000 0.888 0.000 0.020 0.012 0.080
#> GSM1233009 2 0.4361 0.5384 0.000 0.768 0.000 0.040 0.096 0.096
#> GSM1233017 2 0.3181 0.5763 0.000 0.852 0.000 0.076 0.028 0.044
#> GSM1233020 2 0.2615 0.5740 0.000 0.852 0.000 0.008 0.004 0.136
#> GSM1233022 4 0.5544 0.1661 0.000 0.408 0.000 0.500 0.056 0.036
#> GSM1233026 5 0.4845 0.5316 0.004 0.048 0.000 0.068 0.728 0.152
#> GSM1233028 5 0.4398 0.5646 0.004 0.056 0.000 0.068 0.776 0.096
#> GSM1233034 2 0.3399 0.5498 0.000 0.820 0.000 0.024 0.024 0.132
#> GSM1233040 1 0.2753 0.7498 0.876 0.000 0.004 0.012 0.028 0.080
#> GSM1233048 1 0.1410 0.7656 0.944 0.000 0.000 0.004 0.008 0.044
#> GSM1233056 1 0.0653 0.7672 0.980 0.000 0.004 0.000 0.004 0.012
#> GSM1233058 5 0.4013 0.5760 0.024 0.012 0.004 0.072 0.812 0.076
#> GSM1233059 1 0.0837 0.7676 0.972 0.000 0.000 0.004 0.004 0.020
#> GSM1233066 3 0.2760 0.5342 0.004 0.000 0.868 0.012 0.016 0.100
#> GSM1233071 2 0.6463 0.1812 0.000 0.540 0.000 0.184 0.072 0.204
#> GSM1233074 2 0.6118 0.1455 0.000 0.456 0.212 0.004 0.004 0.324
#> GSM1233076 4 0.7623 -0.2046 0.000 0.040 0.220 0.380 0.064 0.296
#> GSM1233080 1 0.0260 0.7672 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM1233088 6 0.8028 0.3910 0.020 0.064 0.208 0.092 0.148 0.468
#> GSM1233090 1 0.0363 0.7676 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM1233092 4 0.2009 0.5688 0.000 0.084 0.000 0.904 0.004 0.008
#> GSM1233094 4 0.4435 0.4930 0.004 0.076 0.000 0.768 0.112 0.040
#> GSM1233097 5 0.4341 0.5147 0.012 0.012 0.000 0.188 0.744 0.044
#> GSM1233100 1 0.7573 -0.0257 0.408 0.012 0.000 0.204 0.240 0.136
#> GSM1233104 4 0.6625 0.0543 0.000 0.168 0.000 0.408 0.372 0.052
#> GSM1233106 1 0.5207 0.6164 0.684 0.000 0.008 0.020 0.128 0.160
#> GSM1233111 1 0.4211 0.6935 0.772 0.000 0.000 0.028 0.076 0.124
#> GSM1233122 2 0.3366 0.5731 0.000 0.824 0.000 0.092 0.004 0.080
#> GSM1233146 4 0.5515 0.3275 0.004 0.028 0.000 0.608 0.276 0.084
#> GSM1232994 2 0.4228 0.5450 0.000 0.784 0.000 0.080 0.076 0.060
#> GSM1232996 2 0.2000 0.6075 0.000 0.916 0.000 0.004 0.032 0.048
#> GSM1232997 2 0.5769 0.0501 0.000 0.460 0.180 0.000 0.000 0.360
#> GSM1232998 2 0.5706 -0.0863 0.000 0.452 0.000 0.440 0.080 0.028
#> GSM1232999 2 0.5526 0.3565 0.000 0.644 0.000 0.196 0.116 0.044
#> GSM1233000 2 0.2672 0.5950 0.000 0.884 0.000 0.020 0.048 0.048
#> GSM1233004 1 0.8104 -0.2529 0.292 0.000 0.244 0.024 0.260 0.180
#> GSM1233011 3 0.8363 -0.2235 0.000 0.216 0.308 0.112 0.080 0.284
#> GSM1233012 2 0.5672 0.4080 0.000 0.616 0.140 0.024 0.004 0.216
#> GSM1233023 2 0.5369 0.2661 0.000 0.568 0.088 0.004 0.008 0.332
#> GSM1233027 2 0.4887 0.4078 0.000 0.680 0.000 0.232 0.040 0.048
#> GSM1233033 1 0.3210 0.7380 0.852 0.000 0.000 0.032 0.068 0.048
#> GSM1233036 3 0.6976 -0.1179 0.000 0.332 0.388 0.004 0.056 0.220
#> GSM1233037 6 0.7763 0.3309 0.012 0.340 0.144 0.040 0.076 0.388
#> GSM1233041 1 0.0508 0.7682 0.984 0.000 0.000 0.000 0.004 0.012
#> GSM1233045 5 0.5012 0.5016 0.000 0.076 0.000 0.100 0.720 0.104
#> GSM1233047 1 0.4003 0.6363 0.740 0.000 0.208 0.000 0.004 0.048
#> GSM1233050 1 0.0777 0.7673 0.972 0.000 0.000 0.000 0.004 0.024
#> GSM1233052 1 0.4687 0.6330 0.704 0.000 0.000 0.008 0.168 0.120
#> GSM1233053 1 0.2442 0.7477 0.884 0.000 0.068 0.000 0.000 0.048
#> GSM1233055 1 0.0622 0.7662 0.980 0.000 0.000 0.000 0.008 0.012
#> GSM1233061 3 0.3900 0.4892 0.096 0.000 0.796 0.000 0.020 0.088
#> GSM1233063 1 0.2051 0.7653 0.916 0.000 0.000 0.008 0.040 0.036
#> GSM1233065 2 0.5909 0.2257 0.000 0.532 0.132 0.008 0.012 0.316
#> GSM1233070 2 0.6117 -0.0122 0.000 0.468 0.008 0.388 0.024 0.112
#> GSM1233077 3 0.4241 0.4232 0.000 0.008 0.652 0.008 0.008 0.324
#> GSM1233081 1 0.4317 0.4826 0.636 0.000 0.336 0.000 0.012 0.016
#> GSM1233084 1 0.0363 0.7671 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM1233087 1 0.5819 0.4481 0.612 0.000 0.000 0.184 0.160 0.044
#> GSM1233089 2 0.6194 0.2170 0.000 0.556 0.040 0.128 0.008 0.268
#> GSM1233099 5 0.5939 0.4394 0.288 0.000 0.000 0.088 0.564 0.060
#> GSM1233112 1 0.1621 0.7643 0.944 0.000 0.016 0.012 0.008 0.020
#> GSM1233085 3 0.4705 -0.0321 0.440 0.000 0.520 0.000 0.004 0.036
#> GSM1233098 2 0.5259 0.4281 0.000 0.668 0.032 0.088 0.004 0.208
#> GSM1233114 1 0.5149 0.3999 0.596 0.000 0.000 0.036 0.328 0.040
#> GSM1233119 5 0.4609 0.3570 0.008 0.000 0.000 0.344 0.612 0.036
#> GSM1233129 2 0.6143 0.1728 0.000 0.464 0.236 0.004 0.004 0.292
#> GSM1233132 1 0.4080 0.6020 0.724 0.000 0.000 0.020 0.236 0.020
#> GSM1233139 2 0.4225 0.5594 0.000 0.768 0.004 0.028 0.048 0.152
#> GSM1233143 2 0.5932 0.4324 0.000 0.624 0.140 0.040 0.012 0.184
#> GSM1233145 1 0.3737 0.6945 0.816 0.000 0.000 0.064 0.084 0.036
#> GSM1233067 3 0.6313 -0.0296 0.000 0.320 0.428 0.008 0.004 0.240
#> GSM1233069 3 0.4245 0.4190 0.000 0.012 0.648 0.004 0.008 0.328
#> GSM1233072 2 0.3943 0.5714 0.000 0.788 0.004 0.116 0.008 0.084
#> GSM1233086 3 0.7095 0.2523 0.000 0.096 0.528 0.040 0.112 0.224
#> GSM1233102 1 0.6713 0.0817 0.464 0.000 0.000 0.240 0.240 0.056
#> GSM1233103 5 0.6144 0.5488 0.076 0.020 0.008 0.080 0.644 0.172
#> GSM1233107 5 0.6814 0.2885 0.004 0.132 0.004 0.264 0.508 0.088
#> GSM1233108 1 0.4528 0.3209 0.564 0.000 0.404 0.000 0.004 0.028
#> GSM1233109 3 0.4473 0.4407 0.156 0.000 0.732 0.000 0.012 0.100
#> GSM1233110 3 0.1204 0.5460 0.000 0.000 0.944 0.000 0.000 0.056
#> GSM1233113 2 0.5641 0.3343 0.000 0.568 0.136 0.008 0.004 0.284
#> GSM1233116 2 0.6462 0.1250 0.000 0.444 0.260 0.012 0.008 0.276
#> GSM1233120 1 0.5909 0.2398 0.532 0.000 0.000 0.092 0.332 0.044
#> GSM1233121 3 0.3977 0.4547 0.000 0.008 0.692 0.004 0.008 0.288
#> GSM1233123 3 0.1411 0.5440 0.000 0.000 0.936 0.000 0.004 0.060
#> GSM1233124 3 0.2568 0.5278 0.000 0.024 0.880 0.004 0.004 0.088
#> GSM1233125 1 0.4546 0.2404 0.528 0.000 0.444 0.000 0.008 0.020
#> GSM1233126 4 0.1957 0.5651 0.000 0.072 0.000 0.912 0.008 0.008
#> GSM1233127 2 0.6158 0.3251 0.000 0.568 0.000 0.108 0.248 0.076
#> GSM1233128 1 0.0717 0.7673 0.976 0.000 0.000 0.000 0.008 0.016
#> GSM1233130 3 0.3437 0.4795 0.000 0.000 0.752 0.004 0.008 0.236
#> GSM1233131 5 0.5705 0.0913 0.408 0.000 0.000 0.044 0.488 0.060
#> GSM1233133 3 0.3204 0.4795 0.144 0.000 0.820 0.000 0.004 0.032
#> GSM1233134 3 0.4085 0.4656 0.000 0.052 0.748 0.004 0.004 0.192
#> GSM1233135 3 0.4183 0.4384 0.000 0.036 0.692 0.000 0.004 0.268
#> GSM1233136 3 0.5054 0.3327 0.000 0.012 0.588 0.036 0.012 0.352
#> GSM1233137 3 0.2889 0.5119 0.096 0.000 0.856 0.000 0.004 0.044
#> GSM1233138 4 0.2062 0.5676 0.000 0.088 0.000 0.900 0.008 0.004
#> GSM1233140 1 0.4411 0.6587 0.736 0.000 0.172 0.000 0.016 0.076
#> GSM1233141 2 0.5129 0.5370 0.000 0.716 0.004 0.068 0.096 0.116
#> GSM1233142 2 0.5096 0.4803 0.000 0.692 0.000 0.052 0.180 0.076
#> GSM1233144 3 0.3054 0.4938 0.116 0.000 0.840 0.000 0.004 0.040
#> GSM1233147 4 0.7192 -0.2000 0.000 0.040 0.288 0.376 0.020 0.276
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> CV:skmeans 153 3.95e-01 0.740 0.5292 2
#> CV:skmeans 143 2.87e-03 0.739 0.0962 3
#> CV:skmeans 122 3.08e-06 0.246 0.0193 4
#> CV:skmeans 108 1.13e-05 0.267 0.0430 5
#> CV:skmeans 85 2.02e-02 0.270 0.7967 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 51941 rows and 156 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 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.929 0.937 0.971 0.4711 0.530 0.530
#> 3 3 0.485 0.560 0.789 0.3789 0.771 0.586
#> 4 4 0.653 0.739 0.866 0.1316 0.813 0.532
#> 5 5 0.656 0.577 0.784 0.0677 0.945 0.798
#> 6 6 0.693 0.502 0.741 0.0461 0.901 0.607
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0000 0.972 0.000 1.000
#> GSM1233002 2 0.0672 0.968 0.008 0.992
#> GSM1233003 1 0.0000 0.966 1.000 0.000
#> GSM1233014 2 0.1843 0.957 0.028 0.972
#> GSM1233015 1 0.9286 0.483 0.656 0.344
#> GSM1233016 2 0.3733 0.922 0.072 0.928
#> GSM1233024 2 0.0000 0.972 0.000 1.000
#> GSM1233049 1 0.0000 0.966 1.000 0.000
#> GSM1233064 2 0.0000 0.972 0.000 1.000
#> GSM1233068 1 0.5519 0.849 0.872 0.128
#> GSM1233073 2 0.2603 0.946 0.044 0.956
#> GSM1233093 1 0.0000 0.966 1.000 0.000
#> GSM1233115 1 0.0000 0.966 1.000 0.000
#> GSM1232992 2 0.0000 0.972 0.000 1.000
#> GSM1232993 2 0.0000 0.972 0.000 1.000
#> GSM1233005 2 0.0000 0.972 0.000 1.000
#> GSM1233007 2 0.0000 0.972 0.000 1.000
#> GSM1233010 2 0.9608 0.405 0.384 0.616
#> GSM1233013 2 0.0000 0.972 0.000 1.000
#> GSM1233018 2 0.0000 0.972 0.000 1.000
#> GSM1233019 2 0.0000 0.972 0.000 1.000
#> GSM1233021 2 0.0000 0.972 0.000 1.000
#> GSM1233025 1 0.9970 0.102 0.532 0.468
#> GSM1233029 2 0.0000 0.972 0.000 1.000
#> GSM1233030 2 0.0000 0.972 0.000 1.000
#> GSM1233031 2 0.4562 0.900 0.096 0.904
#> GSM1233032 1 0.0000 0.966 1.000 0.000
#> GSM1233035 2 0.4815 0.891 0.104 0.896
#> GSM1233038 1 0.0000 0.966 1.000 0.000
#> GSM1233039 2 0.0000 0.972 0.000 1.000
#> GSM1233042 2 0.1633 0.959 0.024 0.976
#> GSM1233043 2 0.0000 0.972 0.000 1.000
#> GSM1233044 1 0.3733 0.910 0.928 0.072
#> GSM1233046 1 0.0938 0.959 0.988 0.012
#> GSM1233051 1 0.0000 0.966 1.000 0.000
#> GSM1233054 1 0.2603 0.937 0.956 0.044
#> GSM1233057 2 0.0376 0.970 0.004 0.996
#> GSM1233060 2 0.0000 0.972 0.000 1.000
#> GSM1233062 2 0.0000 0.972 0.000 1.000
#> GSM1233075 2 0.0000 0.972 0.000 1.000
#> GSM1233078 2 0.7602 0.736 0.220 0.780
#> GSM1233079 1 0.0000 0.966 1.000 0.000
#> GSM1233082 1 0.0000 0.966 1.000 0.000
#> GSM1233083 1 0.0000 0.966 1.000 0.000
#> GSM1233091 2 0.4939 0.885 0.108 0.892
#> GSM1233095 1 0.0000 0.966 1.000 0.000
#> GSM1233096 1 0.0000 0.966 1.000 0.000
#> GSM1233101 1 0.0000 0.966 1.000 0.000
#> GSM1233105 1 0.2043 0.944 0.968 0.032
#> GSM1233117 2 0.0000 0.972 0.000 1.000
#> GSM1233118 2 0.0000 0.972 0.000 1.000
#> GSM1233001 2 0.0000 0.972 0.000 1.000
#> GSM1233006 2 0.0000 0.972 0.000 1.000
#> GSM1233008 2 0.0000 0.972 0.000 1.000
#> GSM1233009 2 0.0000 0.972 0.000 1.000
#> GSM1233017 2 0.0000 0.972 0.000 1.000
#> GSM1233020 2 0.0000 0.972 0.000 1.000
#> GSM1233022 2 0.0000 0.972 0.000 1.000
#> GSM1233026 2 0.2603 0.944 0.044 0.956
#> GSM1233028 2 0.0938 0.967 0.012 0.988
#> GSM1233034 2 0.0000 0.972 0.000 1.000
#> GSM1233040 1 0.0000 0.966 1.000 0.000
#> GSM1233048 1 0.0000 0.966 1.000 0.000
#> GSM1233056 1 0.0000 0.966 1.000 0.000
#> GSM1233058 2 0.2423 0.949 0.040 0.960
#> GSM1233059 1 0.0000 0.966 1.000 0.000
#> GSM1233066 2 0.4161 0.909 0.084 0.916
#> GSM1233071 2 0.0000 0.972 0.000 1.000
#> GSM1233074 2 0.0000 0.972 0.000 1.000
#> GSM1233076 2 0.0000 0.972 0.000 1.000
#> GSM1233080 1 0.0000 0.966 1.000 0.000
#> GSM1233088 2 0.0000 0.972 0.000 1.000
#> GSM1233090 1 0.0000 0.966 1.000 0.000
#> GSM1233092 2 0.1184 0.964 0.016 0.984
#> GSM1233094 2 0.2423 0.949 0.040 0.960
#> GSM1233097 2 0.8661 0.621 0.288 0.712
#> GSM1233100 2 0.8327 0.660 0.264 0.736
#> GSM1233104 2 0.1633 0.959 0.024 0.976
#> GSM1233106 1 0.4298 0.894 0.912 0.088
#> GSM1233111 1 0.0376 0.964 0.996 0.004
#> GSM1233122 2 0.0000 0.972 0.000 1.000
#> GSM1233146 2 0.0672 0.968 0.008 0.992
#> GSM1232994 2 0.0000 0.972 0.000 1.000
#> GSM1232996 2 0.0000 0.972 0.000 1.000
#> GSM1232997 2 0.0000 0.972 0.000 1.000
#> GSM1232998 2 0.0000 0.972 0.000 1.000
#> GSM1232999 2 0.0000 0.972 0.000 1.000
#> GSM1233000 2 0.0000 0.972 0.000 1.000
#> GSM1233004 1 0.2603 0.936 0.956 0.044
#> GSM1233011 2 0.0000 0.972 0.000 1.000
#> GSM1233012 2 0.0000 0.972 0.000 1.000
#> GSM1233023 2 0.0000 0.972 0.000 1.000
#> GSM1233027 2 0.0000 0.972 0.000 1.000
#> GSM1233033 1 0.0000 0.966 1.000 0.000
#> GSM1233036 2 0.1843 0.956 0.028 0.972
#> GSM1233037 2 0.0000 0.972 0.000 1.000
#> GSM1233041 1 0.0000 0.966 1.000 0.000
#> GSM1233045 2 0.1843 0.956 0.028 0.972
#> GSM1233047 1 0.0672 0.962 0.992 0.008
#> GSM1233050 1 0.0000 0.966 1.000 0.000
#> GSM1233052 1 0.0000 0.966 1.000 0.000
#> GSM1233053 1 0.0000 0.966 1.000 0.000
#> GSM1233055 1 0.0000 0.966 1.000 0.000
#> GSM1233061 1 0.9833 0.273 0.576 0.424
#> GSM1233063 1 0.0000 0.966 1.000 0.000
#> GSM1233065 2 0.0000 0.972 0.000 1.000
#> GSM1233070 2 0.0000 0.972 0.000 1.000
#> GSM1233077 2 0.0000 0.972 0.000 1.000
#> GSM1233081 1 0.0000 0.966 1.000 0.000
#> GSM1233084 1 0.0000 0.966 1.000 0.000
#> GSM1233087 1 0.0376 0.964 0.996 0.004
#> GSM1233089 2 0.0000 0.972 0.000 1.000
#> GSM1233099 1 0.0376 0.964 0.996 0.004
#> GSM1233112 1 0.0000 0.966 1.000 0.000
#> GSM1233085 1 0.0000 0.966 1.000 0.000
#> GSM1233098 2 0.0000 0.972 0.000 1.000
#> GSM1233114 1 0.0000 0.966 1.000 0.000
#> GSM1233119 2 0.8144 0.682 0.252 0.748
#> GSM1233129 2 0.0000 0.972 0.000 1.000
#> GSM1233132 1 0.0000 0.966 1.000 0.000
#> GSM1233139 2 0.0000 0.972 0.000 1.000
#> GSM1233143 2 0.0000 0.972 0.000 1.000
#> GSM1233145 1 0.0000 0.966 1.000 0.000
#> GSM1233067 2 0.0000 0.972 0.000 1.000
#> GSM1233069 2 0.0000 0.972 0.000 1.000
#> GSM1233072 2 0.0000 0.972 0.000 1.000
#> GSM1233086 2 0.0000 0.972 0.000 1.000
#> GSM1233102 1 0.0000 0.966 1.000 0.000
#> GSM1233103 2 0.2948 0.938 0.052 0.948
#> GSM1233107 2 0.5059 0.883 0.112 0.888
#> GSM1233108 1 0.0000 0.966 1.000 0.000
#> GSM1233109 1 0.0000 0.966 1.000 0.000
#> GSM1233110 2 0.2778 0.941 0.048 0.952
#> GSM1233113 2 0.0000 0.972 0.000 1.000
#> GSM1233116 2 0.0000 0.972 0.000 1.000
#> GSM1233120 1 0.0000 0.966 1.000 0.000
#> GSM1233121 2 0.0376 0.970 0.004 0.996
#> GSM1233123 2 0.4815 0.888 0.104 0.896
#> GSM1233124 2 0.2778 0.941 0.048 0.952
#> GSM1233125 1 0.0000 0.966 1.000 0.000
#> GSM1233126 2 0.1843 0.957 0.028 0.972
#> GSM1233127 2 0.0000 0.972 0.000 1.000
#> GSM1233128 1 0.0000 0.966 1.000 0.000
#> GSM1233130 2 0.0000 0.972 0.000 1.000
#> GSM1233131 1 0.2948 0.929 0.948 0.052
#> GSM1233133 1 0.0672 0.962 0.992 0.008
#> GSM1233134 2 0.0000 0.972 0.000 1.000
#> GSM1233135 2 0.0000 0.972 0.000 1.000
#> GSM1233136 2 0.0000 0.972 0.000 1.000
#> GSM1233137 1 0.0376 0.964 0.996 0.004
#> GSM1233138 2 0.1633 0.959 0.024 0.976
#> GSM1233140 1 0.4161 0.898 0.916 0.084
#> GSM1233141 2 0.0000 0.972 0.000 1.000
#> GSM1233142 2 0.0000 0.972 0.000 1.000
#> GSM1233144 1 0.2948 0.929 0.948 0.052
#> GSM1233147 2 0.0000 0.972 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.2796 0.7654 0.000 0.908 0.092
#> GSM1233002 2 0.6451 0.2944 0.008 0.608 0.384
#> GSM1233003 1 0.5905 0.5409 0.648 0.000 0.352
#> GSM1233014 3 0.6952 -0.1882 0.016 0.480 0.504
#> GSM1233015 1 0.7032 0.2434 0.604 0.368 0.028
#> GSM1233016 3 0.2998 0.5746 0.016 0.068 0.916
#> GSM1233024 2 0.2165 0.7645 0.000 0.936 0.064
#> GSM1233049 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233064 2 0.0892 0.7639 0.000 0.980 0.020
#> GSM1233068 3 0.3193 0.5275 0.100 0.004 0.896
#> GSM1233073 3 0.6935 0.1207 0.024 0.372 0.604
#> GSM1233093 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233115 1 0.0237 0.8345 0.996 0.000 0.004
#> GSM1232992 2 0.0000 0.7652 0.000 1.000 0.000
#> GSM1232993 2 0.0424 0.7674 0.000 0.992 0.008
#> GSM1233005 2 0.0592 0.7660 0.000 0.988 0.012
#> GSM1233007 2 0.3038 0.7198 0.000 0.896 0.104
#> GSM1233010 3 0.7412 0.4658 0.192 0.112 0.696
#> GSM1233013 2 0.0000 0.7652 0.000 1.000 0.000
#> GSM1233018 2 0.0000 0.7652 0.000 1.000 0.000
#> GSM1233019 2 0.0000 0.7652 0.000 1.000 0.000
#> GSM1233021 2 0.2711 0.7581 0.000 0.912 0.088
#> GSM1233025 3 0.5764 0.5021 0.124 0.076 0.800
#> GSM1233029 2 0.2959 0.7538 0.000 0.900 0.100
#> GSM1233030 2 0.0000 0.7652 0.000 1.000 0.000
#> GSM1233031 3 0.6819 -0.1910 0.012 0.476 0.512
#> GSM1233032 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233035 2 0.7186 0.1940 0.024 0.500 0.476
#> GSM1233038 1 0.0237 0.8348 0.996 0.000 0.004
#> GSM1233039 2 0.5859 0.3015 0.000 0.656 0.344
#> GSM1233042 2 0.6753 0.3133 0.016 0.596 0.388
#> GSM1233043 2 0.5988 0.3645 0.000 0.632 0.368
#> GSM1233044 3 0.5365 0.3702 0.252 0.004 0.744
#> GSM1233046 1 0.5560 0.5792 0.700 0.000 0.300
#> GSM1233051 1 0.5291 0.6590 0.732 0.000 0.268
#> GSM1233054 3 0.6280 -0.1886 0.460 0.000 0.540
#> GSM1233057 2 0.4235 0.7230 0.000 0.824 0.176
#> GSM1233060 2 0.5905 0.4094 0.000 0.648 0.352
#> GSM1233062 2 0.4178 0.7237 0.000 0.828 0.172
#> GSM1233075 2 0.0237 0.7665 0.000 0.996 0.004
#> GSM1233078 3 0.2903 0.5725 0.028 0.048 0.924
#> GSM1233079 1 0.1411 0.8221 0.964 0.000 0.036
#> GSM1233082 1 0.2878 0.7946 0.904 0.000 0.096
#> GSM1233083 1 0.0424 0.8345 0.992 0.000 0.008
#> GSM1233091 3 0.7186 0.2483 0.040 0.336 0.624
#> GSM1233095 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233096 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233101 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233105 1 0.6541 0.5462 0.672 0.024 0.304
#> GSM1233117 2 0.0237 0.7666 0.000 0.996 0.004
#> GSM1233118 2 0.0592 0.7676 0.000 0.988 0.012
#> GSM1233001 2 0.0237 0.7638 0.000 0.996 0.004
#> GSM1233006 2 0.5254 0.5048 0.000 0.736 0.264
#> GSM1233008 2 0.4291 0.7200 0.000 0.820 0.180
#> GSM1233009 2 0.2711 0.7589 0.000 0.912 0.088
#> GSM1233017 2 0.2448 0.7608 0.000 0.924 0.076
#> GSM1233020 2 0.0000 0.7652 0.000 1.000 0.000
#> GSM1233022 2 0.3551 0.7495 0.000 0.868 0.132
#> GSM1233026 2 0.6260 0.2390 0.000 0.552 0.448
#> GSM1233028 2 0.6235 0.3818 0.000 0.564 0.436
#> GSM1233034 2 0.1163 0.7690 0.000 0.972 0.028
#> GSM1233040 1 0.0747 0.8278 0.984 0.000 0.016
#> GSM1233048 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233056 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233058 3 0.4634 0.5219 0.012 0.164 0.824
#> GSM1233059 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233066 3 0.0592 0.5720 0.000 0.012 0.988
#> GSM1233071 2 0.5760 0.5008 0.000 0.672 0.328
#> GSM1233074 2 0.3267 0.7542 0.000 0.884 0.116
#> GSM1233076 3 0.5254 0.5135 0.000 0.264 0.736
#> GSM1233080 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233088 2 0.5431 0.3570 0.000 0.716 0.284
#> GSM1233090 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233092 2 0.6498 0.2976 0.008 0.596 0.396
#> GSM1233094 3 0.6783 0.0577 0.016 0.396 0.588
#> GSM1233097 3 0.7885 0.1768 0.072 0.336 0.592
#> GSM1233100 3 0.8447 0.0553 0.092 0.392 0.516
#> GSM1233104 3 0.6936 -0.1606 0.016 0.460 0.524
#> GSM1233106 1 0.6521 0.1745 0.504 0.004 0.492
#> GSM1233111 1 0.0424 0.8324 0.992 0.000 0.008
#> GSM1233122 2 0.0000 0.7652 0.000 1.000 0.000
#> GSM1233146 3 0.6672 -0.1888 0.008 0.472 0.520
#> GSM1232994 2 0.1031 0.7651 0.000 0.976 0.024
#> GSM1232996 2 0.3116 0.7559 0.000 0.892 0.108
#> GSM1232997 2 0.3686 0.7450 0.000 0.860 0.140
#> GSM1232998 2 0.5138 0.6773 0.000 0.748 0.252
#> GSM1232999 2 0.3686 0.7457 0.000 0.860 0.140
#> GSM1233000 2 0.0000 0.7652 0.000 1.000 0.000
#> GSM1233004 3 0.4062 0.4587 0.164 0.000 0.836
#> GSM1233011 3 0.6215 0.1621 0.000 0.428 0.572
#> GSM1233012 2 0.3551 0.7467 0.000 0.868 0.132
#> GSM1233023 2 0.2711 0.7558 0.000 0.912 0.088
#> GSM1233027 2 0.0000 0.7652 0.000 1.000 0.000
#> GSM1233033 1 0.2356 0.8030 0.928 0.000 0.072
#> GSM1233036 2 0.5158 0.6798 0.004 0.764 0.232
#> GSM1233037 2 0.5178 0.6534 0.000 0.744 0.256
#> GSM1233041 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233045 2 0.6305 0.2470 0.000 0.516 0.484
#> GSM1233047 1 0.6192 0.3456 0.580 0.000 0.420
#> GSM1233050 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233052 1 0.0592 0.8314 0.988 0.000 0.012
#> GSM1233053 1 0.0424 0.8323 0.992 0.000 0.008
#> GSM1233055 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233061 3 0.2711 0.5310 0.088 0.000 0.912
#> GSM1233063 1 0.0592 0.8322 0.988 0.000 0.012
#> GSM1233065 2 0.4555 0.7082 0.000 0.800 0.200
#> GSM1233070 2 0.4002 0.7034 0.000 0.840 0.160
#> GSM1233077 3 0.6309 0.2403 0.000 0.496 0.504
#> GSM1233081 1 0.3412 0.7639 0.876 0.000 0.124
#> GSM1233084 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233087 1 0.5988 0.4857 0.632 0.000 0.368
#> GSM1233089 2 0.1163 0.7616 0.000 0.972 0.028
#> GSM1233099 1 0.5591 0.5763 0.696 0.000 0.304
#> GSM1233112 1 0.6095 0.4902 0.608 0.000 0.392
#> GSM1233085 1 0.5254 0.6105 0.736 0.000 0.264
#> GSM1233098 2 0.0000 0.7652 0.000 1.000 0.000
#> GSM1233114 1 0.0237 0.8348 0.996 0.000 0.004
#> GSM1233119 3 0.3237 0.5709 0.032 0.056 0.912
#> GSM1233129 2 0.4062 0.7262 0.000 0.836 0.164
#> GSM1233132 1 0.0237 0.8348 0.996 0.000 0.004
#> GSM1233139 2 0.3412 0.7511 0.000 0.876 0.124
#> GSM1233143 2 0.4842 0.6476 0.000 0.776 0.224
#> GSM1233145 1 0.2261 0.8041 0.932 0.000 0.068
#> GSM1233067 2 0.4750 0.6580 0.000 0.784 0.216
#> GSM1233069 2 0.6299 -0.2429 0.000 0.524 0.476
#> GSM1233072 2 0.1860 0.7524 0.000 0.948 0.052
#> GSM1233086 3 0.5216 0.4478 0.000 0.260 0.740
#> GSM1233102 1 0.6260 0.3872 0.552 0.000 0.448
#> GSM1233103 3 0.6286 -0.1088 0.000 0.464 0.536
#> GSM1233107 2 0.8128 0.1055 0.068 0.492 0.440
#> GSM1233108 1 0.6299 0.2318 0.524 0.000 0.476
#> GSM1233109 3 0.6305 -0.1972 0.484 0.000 0.516
#> GSM1233110 3 0.7099 0.3726 0.028 0.384 0.588
#> GSM1233113 2 0.0237 0.7638 0.000 0.996 0.004
#> GSM1233116 2 0.4291 0.5888 0.000 0.820 0.180
#> GSM1233120 1 0.5560 0.5840 0.700 0.000 0.300
#> GSM1233121 3 0.4887 0.4951 0.000 0.228 0.772
#> GSM1233123 3 0.6852 0.4179 0.036 0.300 0.664
#> GSM1233124 3 0.5202 0.4990 0.008 0.220 0.772
#> GSM1233125 1 0.6291 0.2470 0.532 0.000 0.468
#> GSM1233126 2 0.6944 0.1287 0.016 0.516 0.468
#> GSM1233127 2 0.3816 0.7296 0.000 0.852 0.148
#> GSM1233128 1 0.0000 0.8354 1.000 0.000 0.000
#> GSM1233130 3 0.5497 0.4421 0.000 0.292 0.708
#> GSM1233131 3 0.4796 0.3981 0.220 0.000 0.780
#> GSM1233133 1 0.6307 0.2022 0.512 0.000 0.488
#> GSM1233134 3 0.6026 0.3255 0.000 0.376 0.624
#> GSM1233135 3 0.6244 0.3116 0.000 0.440 0.560
#> GSM1233136 3 0.6295 0.2828 0.000 0.472 0.528
#> GSM1233137 1 0.2448 0.7972 0.924 0.000 0.076
#> GSM1233138 2 0.6824 0.2631 0.016 0.576 0.408
#> GSM1233140 3 0.6104 0.2140 0.348 0.004 0.648
#> GSM1233141 2 0.3941 0.7262 0.000 0.844 0.156
#> GSM1233142 2 0.2878 0.7593 0.000 0.904 0.096
#> GSM1233144 3 0.6244 -0.0364 0.440 0.000 0.560
#> GSM1233147 3 0.3686 0.5590 0.000 0.140 0.860
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.1474 0.8767 0.000 0.948 0.000 0.052
#> GSM1233002 4 0.4193 0.6642 0.000 0.268 0.000 0.732
#> GSM1233003 4 0.5392 0.5132 0.280 0.000 0.040 0.680
#> GSM1233014 4 0.1302 0.7668 0.000 0.044 0.000 0.956
#> GSM1233015 1 0.6028 0.3147 0.584 0.364 0.000 0.052
#> GSM1233016 4 0.1716 0.7651 0.000 0.064 0.000 0.936
#> GSM1233024 2 0.0469 0.8809 0.000 0.988 0.000 0.012
#> GSM1233049 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233064 2 0.0592 0.8780 0.000 0.984 0.000 0.016
#> GSM1233068 4 0.5429 0.6002 0.072 0.000 0.208 0.720
#> GSM1233073 4 0.1822 0.7661 0.004 0.044 0.008 0.944
#> GSM1233093 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233115 1 0.0336 0.8710 0.992 0.000 0.000 0.008
#> GSM1232992 2 0.0000 0.8802 0.000 1.000 0.000 0.000
#> GSM1232993 2 0.0000 0.8802 0.000 1.000 0.000 0.000
#> GSM1233005 2 0.0469 0.8798 0.000 0.988 0.000 0.012
#> GSM1233007 2 0.3505 0.8134 0.000 0.864 0.088 0.048
#> GSM1233010 4 0.8094 0.3049 0.120 0.052 0.332 0.496
#> GSM1233013 2 0.0000 0.8802 0.000 1.000 0.000 0.000
#> GSM1233018 2 0.0188 0.8804 0.000 0.996 0.000 0.004
#> GSM1233019 2 0.0000 0.8802 0.000 1.000 0.000 0.000
#> GSM1233021 2 0.1022 0.8785 0.000 0.968 0.000 0.032
#> GSM1233025 4 0.5202 0.7066 0.048 0.040 0.124 0.788
#> GSM1233029 2 0.1940 0.8585 0.000 0.924 0.000 0.076
#> GSM1233030 2 0.0000 0.8802 0.000 1.000 0.000 0.000
#> GSM1233031 4 0.2888 0.7429 0.004 0.124 0.000 0.872
#> GSM1233032 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233035 4 0.3636 0.7317 0.008 0.172 0.000 0.820
#> GSM1233038 1 0.3610 0.7438 0.800 0.000 0.000 0.200
#> GSM1233039 2 0.6386 0.2545 0.000 0.552 0.376 0.072
#> GSM1233042 4 0.3024 0.7482 0.000 0.148 0.000 0.852
#> GSM1233043 4 0.4500 0.5938 0.000 0.316 0.000 0.684
#> GSM1233044 4 0.6508 0.5482 0.168 0.000 0.192 0.640
#> GSM1233046 4 0.3907 0.6167 0.232 0.000 0.000 0.768
#> GSM1233051 1 0.5866 0.3551 0.624 0.000 0.052 0.324
#> GSM1233054 3 0.7728 0.0766 0.352 0.000 0.416 0.232
#> GSM1233057 2 0.3372 0.8533 0.000 0.868 0.036 0.096
#> GSM1233060 4 0.4713 0.5287 0.000 0.360 0.000 0.640
#> GSM1233062 2 0.2408 0.8590 0.000 0.896 0.000 0.104
#> GSM1233075 2 0.0188 0.8807 0.000 0.996 0.000 0.004
#> GSM1233078 3 0.0000 0.8632 0.000 0.000 1.000 0.000
#> GSM1233079 1 0.0336 0.8715 0.992 0.000 0.008 0.000
#> GSM1233082 1 0.4509 0.6388 0.708 0.000 0.004 0.288
#> GSM1233083 1 0.3710 0.7499 0.804 0.000 0.004 0.192
#> GSM1233091 4 0.6779 0.6438 0.044 0.168 0.108 0.680
#> GSM1233095 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233096 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233101 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233105 4 0.3649 0.6467 0.204 0.000 0.000 0.796
#> GSM1233117 2 0.0188 0.8806 0.000 0.996 0.000 0.004
#> GSM1233118 2 0.0592 0.8817 0.000 0.984 0.000 0.016
#> GSM1233001 2 0.0000 0.8802 0.000 1.000 0.000 0.000
#> GSM1233006 2 0.4961 -0.0208 0.000 0.552 0.000 0.448
#> GSM1233008 2 0.2647 0.8539 0.000 0.880 0.000 0.120
#> GSM1233009 2 0.1716 0.8657 0.000 0.936 0.000 0.064
#> GSM1233017 2 0.0592 0.8805 0.000 0.984 0.000 0.016
#> GSM1233020 2 0.0000 0.8802 0.000 1.000 0.000 0.000
#> GSM1233022 2 0.2589 0.8464 0.000 0.884 0.000 0.116
#> GSM1233026 2 0.7388 0.3452 0.000 0.504 0.304 0.192
#> GSM1233028 4 0.4933 0.0854 0.000 0.432 0.000 0.568
#> GSM1233034 2 0.0188 0.8804 0.000 0.996 0.000 0.004
#> GSM1233040 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233048 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233056 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233058 4 0.3389 0.7272 0.004 0.024 0.104 0.868
#> GSM1233059 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233066 3 0.2281 0.8198 0.000 0.000 0.904 0.096
#> GSM1233071 4 0.4972 0.1351 0.000 0.456 0.000 0.544
#> GSM1233074 2 0.2149 0.8622 0.000 0.912 0.000 0.088
#> GSM1233076 3 0.3691 0.7759 0.000 0.068 0.856 0.076
#> GSM1233080 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233088 2 0.5364 0.4876 0.000 0.652 0.320 0.028
#> GSM1233090 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233092 4 0.3311 0.7417 0.000 0.172 0.000 0.828
#> GSM1233094 4 0.1576 0.7665 0.000 0.048 0.004 0.948
#> GSM1233097 4 0.0592 0.7592 0.016 0.000 0.000 0.984
#> GSM1233100 4 0.1305 0.7665 0.004 0.036 0.000 0.960
#> GSM1233104 4 0.0000 0.7565 0.000 0.000 0.000 1.000
#> GSM1233106 1 0.7450 0.1254 0.424 0.000 0.172 0.404
#> GSM1233111 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233122 2 0.0000 0.8802 0.000 1.000 0.000 0.000
#> GSM1233146 4 0.3266 0.7037 0.000 0.168 0.000 0.832
#> GSM1232994 2 0.1474 0.8661 0.000 0.948 0.000 0.052
#> GSM1232996 2 0.2011 0.8644 0.000 0.920 0.000 0.080
#> GSM1232997 2 0.3149 0.8589 0.000 0.880 0.032 0.088
#> GSM1232998 2 0.3942 0.7789 0.000 0.764 0.000 0.236
#> GSM1232999 2 0.2868 0.8461 0.000 0.864 0.000 0.136
#> GSM1233000 2 0.0000 0.8802 0.000 1.000 0.000 0.000
#> GSM1233004 3 0.4290 0.6660 0.016 0.000 0.772 0.212
#> GSM1233011 3 0.6393 0.5501 0.000 0.188 0.652 0.160
#> GSM1233012 2 0.2909 0.8576 0.000 0.888 0.020 0.092
#> GSM1233023 2 0.2011 0.8642 0.000 0.920 0.000 0.080
#> GSM1233027 2 0.0000 0.8802 0.000 1.000 0.000 0.000
#> GSM1233033 1 0.4477 0.5973 0.688 0.000 0.000 0.312
#> GSM1233036 2 0.4804 0.7898 0.000 0.776 0.064 0.160
#> GSM1233037 2 0.5272 0.7475 0.000 0.752 0.112 0.136
#> GSM1233041 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233045 4 0.3873 0.6399 0.000 0.228 0.000 0.772
#> GSM1233047 3 0.4567 0.5604 0.276 0.000 0.716 0.008
#> GSM1233050 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233052 1 0.1022 0.8553 0.968 0.000 0.000 0.032
#> GSM1233053 1 0.0188 0.8731 0.996 0.000 0.004 0.000
#> GSM1233055 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233061 3 0.2676 0.8206 0.012 0.000 0.896 0.092
#> GSM1233063 1 0.3123 0.7838 0.844 0.000 0.000 0.156
#> GSM1233065 2 0.4322 0.8161 0.000 0.804 0.044 0.152
#> GSM1233070 2 0.3688 0.7428 0.000 0.792 0.000 0.208
#> GSM1233077 3 0.0000 0.8632 0.000 0.000 1.000 0.000
#> GSM1233081 1 0.3710 0.7136 0.804 0.000 0.192 0.004
#> GSM1233084 1 0.0000 0.8747 1.000 0.000 0.000 0.000
#> GSM1233087 4 0.2647 0.7175 0.120 0.000 0.000 0.880
#> GSM1233089 2 0.1151 0.8768 0.000 0.968 0.008 0.024
#> GSM1233099 4 0.3311 0.6745 0.172 0.000 0.000 0.828
#> GSM1233112 4 0.6482 0.5402 0.208 0.000 0.152 0.640
#> GSM1233085 1 0.4933 0.2379 0.568 0.000 0.432 0.000
#> GSM1233098 2 0.0000 0.8802 0.000 1.000 0.000 0.000
#> GSM1233114 1 0.3610 0.7438 0.800 0.000 0.000 0.200
#> GSM1233119 4 0.5776 0.1808 0.012 0.016 0.388 0.584
#> GSM1233129 2 0.2281 0.8596 0.000 0.904 0.000 0.096
#> GSM1233132 1 0.3486 0.7547 0.812 0.000 0.000 0.188
#> GSM1233139 2 0.2053 0.8746 0.000 0.924 0.004 0.072
#> GSM1233143 2 0.5574 0.7104 0.000 0.728 0.148 0.124
#> GSM1233145 1 0.4304 0.6511 0.716 0.000 0.000 0.284
#> GSM1233067 2 0.5085 0.6046 0.000 0.676 0.304 0.020
#> GSM1233069 3 0.0000 0.8632 0.000 0.000 1.000 0.000
#> GSM1233072 2 0.1792 0.8551 0.000 0.932 0.000 0.068
#> GSM1233086 3 0.2530 0.8135 0.000 0.000 0.888 0.112
#> GSM1233102 4 0.2805 0.7243 0.100 0.000 0.012 0.888
#> GSM1233103 2 0.7186 0.1230 0.000 0.444 0.136 0.420
#> GSM1233107 4 0.2919 0.7723 0.044 0.060 0.000 0.896
#> GSM1233108 3 0.0000 0.8632 0.000 0.000 1.000 0.000
#> GSM1233109 3 0.0000 0.8632 0.000 0.000 1.000 0.000
#> GSM1233110 3 0.0000 0.8632 0.000 0.000 1.000 0.000
#> GSM1233113 2 0.0000 0.8802 0.000 1.000 0.000 0.000
#> GSM1233116 3 0.4996 -0.0494 0.000 0.484 0.516 0.000
#> GSM1233120 4 0.3688 0.6398 0.208 0.000 0.000 0.792
#> GSM1233121 3 0.0000 0.8632 0.000 0.000 1.000 0.000
#> GSM1233123 3 0.0000 0.8632 0.000 0.000 1.000 0.000
#> GSM1233124 3 0.2149 0.8247 0.000 0.000 0.912 0.088
#> GSM1233125 3 0.0469 0.8587 0.012 0.000 0.988 0.000
#> GSM1233126 4 0.2197 0.7639 0.000 0.080 0.004 0.916
#> GSM1233127 2 0.3074 0.8257 0.000 0.848 0.000 0.152
#> GSM1233128 1 0.0336 0.8719 0.992 0.000 0.000 0.008
#> GSM1233130 3 0.0000 0.8632 0.000 0.000 1.000 0.000
#> GSM1233131 3 0.6862 0.1564 0.104 0.000 0.488 0.408
#> GSM1233133 3 0.0000 0.8632 0.000 0.000 1.000 0.000
#> GSM1233134 3 0.2081 0.8271 0.000 0.000 0.916 0.084
#> GSM1233135 3 0.0000 0.8632 0.000 0.000 1.000 0.000
#> GSM1233136 3 0.0592 0.8564 0.000 0.016 0.984 0.000
#> GSM1233137 1 0.1867 0.8310 0.928 0.000 0.072 0.000
#> GSM1233138 4 0.2149 0.7647 0.000 0.088 0.000 0.912
#> GSM1233140 3 0.4235 0.7735 0.084 0.000 0.824 0.092
#> GSM1233141 2 0.3074 0.8253 0.000 0.848 0.000 0.152
#> GSM1233142 2 0.2081 0.8673 0.000 0.916 0.000 0.084
#> GSM1233144 3 0.0000 0.8632 0.000 0.000 1.000 0.000
#> GSM1233147 3 0.0188 0.8618 0.000 0.000 0.996 0.004
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.2230 0.7858 0.000 0.884 0.000 0.000 0.116
#> GSM1233002 4 0.3667 0.5402 0.000 0.140 0.000 0.812 0.048
#> GSM1233003 4 0.6934 0.1564 0.232 0.000 0.016 0.472 0.280
#> GSM1233014 4 0.2970 0.5492 0.000 0.004 0.000 0.828 0.168
#> GSM1233015 1 0.7638 -0.1146 0.400 0.284 0.000 0.052 0.264
#> GSM1233016 4 0.4430 0.4160 0.000 0.012 0.000 0.628 0.360
#> GSM1233024 2 0.1121 0.7967 0.000 0.956 0.000 0.000 0.044
#> GSM1233049 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233064 2 0.1018 0.7991 0.000 0.968 0.000 0.016 0.016
#> GSM1233068 4 0.6545 0.0654 0.028 0.000 0.100 0.456 0.416
#> GSM1233073 4 0.3663 0.5359 0.000 0.016 0.000 0.776 0.208
#> GSM1233093 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233115 1 0.0324 0.8337 0.992 0.000 0.000 0.004 0.004
#> GSM1232992 2 0.0162 0.8002 0.000 0.996 0.000 0.000 0.004
#> GSM1232993 2 0.0000 0.8004 0.000 1.000 0.000 0.000 0.000
#> GSM1233005 2 0.0324 0.8004 0.000 0.992 0.000 0.004 0.004
#> GSM1233007 2 0.4216 0.7238 0.000 0.812 0.088 0.036 0.064
#> GSM1233010 5 0.7667 0.0699 0.060 0.016 0.132 0.368 0.424
#> GSM1233013 2 0.0510 0.8012 0.000 0.984 0.000 0.000 0.016
#> GSM1233018 2 0.0162 0.8002 0.000 0.996 0.000 0.000 0.004
#> GSM1233019 2 0.0404 0.8006 0.000 0.988 0.000 0.000 0.012
#> GSM1233021 2 0.1197 0.7958 0.000 0.952 0.000 0.000 0.048
#> GSM1233025 4 0.5096 0.1257 0.000 0.012 0.016 0.500 0.472
#> GSM1233029 2 0.1282 0.7894 0.000 0.952 0.000 0.044 0.004
#> GSM1233030 2 0.0000 0.8004 0.000 1.000 0.000 0.000 0.000
#> GSM1233031 4 0.4338 0.4150 0.000 0.024 0.000 0.696 0.280
#> GSM1233032 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233035 5 0.5683 -0.0364 0.004 0.068 0.000 0.428 0.500
#> GSM1233038 1 0.5778 0.4428 0.592 0.000 0.000 0.128 0.280
#> GSM1233039 2 0.5441 0.2209 0.000 0.572 0.376 0.032 0.020
#> GSM1233042 4 0.2573 0.5743 0.000 0.104 0.000 0.880 0.016
#> GSM1233043 4 0.3527 0.5171 0.000 0.172 0.000 0.804 0.024
#> GSM1233044 5 0.7627 0.0756 0.108 0.000 0.136 0.292 0.464
#> GSM1233046 4 0.5345 0.4057 0.196 0.000 0.000 0.668 0.136
#> GSM1233051 1 0.5243 0.3108 0.596 0.000 0.048 0.352 0.004
#> GSM1233054 3 0.7711 0.0831 0.312 0.000 0.400 0.224 0.064
#> GSM1233057 2 0.4273 0.4818 0.000 0.552 0.000 0.000 0.448
#> GSM1233060 4 0.3835 0.4598 0.000 0.244 0.000 0.744 0.012
#> GSM1233062 2 0.3774 0.6366 0.000 0.704 0.000 0.000 0.296
#> GSM1233075 2 0.2813 0.7340 0.000 0.832 0.000 0.000 0.168
#> GSM1233078 3 0.0000 0.7980 0.000 0.000 1.000 0.000 0.000
#> GSM1233079 1 0.0162 0.8357 0.996 0.000 0.004 0.000 0.000
#> GSM1233082 5 0.6436 0.1000 0.344 0.000 0.004 0.164 0.488
#> GSM1233083 1 0.4757 0.6058 0.732 0.000 0.000 0.120 0.148
#> GSM1233091 4 0.6077 0.2580 0.012 0.032 0.044 0.588 0.324
#> GSM1233095 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233096 1 0.0609 0.8303 0.980 0.000 0.000 0.000 0.020
#> GSM1233101 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233105 4 0.6192 0.0913 0.136 0.000 0.000 0.432 0.432
#> GSM1233117 2 0.0000 0.8004 0.000 1.000 0.000 0.000 0.000
#> GSM1233118 2 0.3160 0.7319 0.000 0.808 0.000 0.004 0.188
#> GSM1233001 2 0.0000 0.8004 0.000 1.000 0.000 0.000 0.000
#> GSM1233006 4 0.5458 0.0501 0.000 0.464 0.000 0.476 0.060
#> GSM1233008 2 0.3895 0.6151 0.000 0.680 0.000 0.000 0.320
#> GSM1233009 2 0.1310 0.7958 0.000 0.956 0.000 0.024 0.020
#> GSM1233017 2 0.1197 0.7958 0.000 0.952 0.000 0.000 0.048
#> GSM1233020 2 0.1270 0.7928 0.000 0.948 0.000 0.000 0.052
#> GSM1233022 2 0.4237 0.7173 0.000 0.772 0.000 0.076 0.152
#> GSM1233026 5 0.7025 0.3519 0.000 0.224 0.152 0.068 0.556
#> GSM1233028 5 0.6406 0.2556 0.000 0.240 0.000 0.248 0.512
#> GSM1233034 2 0.0404 0.8012 0.000 0.988 0.000 0.000 0.012
#> GSM1233040 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233048 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233056 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233058 4 0.3809 0.4393 0.000 0.000 0.008 0.736 0.256
#> GSM1233059 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233066 3 0.3586 0.6365 0.000 0.000 0.736 0.000 0.264
#> GSM1233071 4 0.6343 0.1404 0.000 0.284 0.000 0.516 0.200
#> GSM1233074 2 0.4114 0.6104 0.000 0.624 0.000 0.000 0.376
#> GSM1233076 3 0.3826 0.7094 0.000 0.032 0.836 0.080 0.052
#> GSM1233080 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233088 2 0.5397 0.3940 0.000 0.624 0.316 0.028 0.032
#> GSM1233090 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233092 4 0.3176 0.5689 0.000 0.080 0.000 0.856 0.064
#> GSM1233094 4 0.2463 0.5824 0.000 0.008 0.004 0.888 0.100
#> GSM1233097 4 0.2536 0.5751 0.004 0.000 0.000 0.868 0.128
#> GSM1233100 4 0.3435 0.5627 0.004 0.020 0.000 0.820 0.156
#> GSM1233104 4 0.4242 0.2491 0.000 0.000 0.000 0.572 0.428
#> GSM1233106 5 0.4522 0.3335 0.096 0.000 0.040 0.072 0.792
#> GSM1233111 1 0.2074 0.7849 0.896 0.000 0.000 0.000 0.104
#> GSM1233122 2 0.1197 0.7925 0.000 0.952 0.000 0.000 0.048
#> GSM1233146 4 0.3507 0.5425 0.000 0.052 0.000 0.828 0.120
#> GSM1232994 2 0.1205 0.7914 0.000 0.956 0.000 0.040 0.004
#> GSM1232996 2 0.1410 0.7956 0.000 0.940 0.000 0.000 0.060
#> GSM1232997 2 0.3109 0.7342 0.000 0.800 0.000 0.000 0.200
#> GSM1232998 2 0.5470 0.5741 0.000 0.628 0.000 0.104 0.268
#> GSM1232999 2 0.2439 0.7782 0.000 0.876 0.000 0.004 0.120
#> GSM1233000 2 0.1197 0.7951 0.000 0.952 0.000 0.000 0.048
#> GSM1233004 3 0.4240 0.5675 0.004 0.000 0.732 0.240 0.024
#> GSM1233011 3 0.6334 0.3336 0.000 0.128 0.528 0.012 0.332
#> GSM1233012 2 0.4489 0.5498 0.000 0.572 0.008 0.000 0.420
#> GSM1233023 2 0.4390 0.5232 0.000 0.568 0.004 0.000 0.428
#> GSM1233027 2 0.0451 0.8001 0.000 0.988 0.000 0.008 0.004
#> GSM1233033 5 0.6589 0.1257 0.312 0.000 0.000 0.232 0.456
#> GSM1233036 5 0.4975 0.0853 0.000 0.316 0.012 0.028 0.644
#> GSM1233037 5 0.5957 -0.3287 0.000 0.408 0.068 0.016 0.508
#> GSM1233041 1 0.1908 0.7920 0.908 0.000 0.000 0.000 0.092
#> GSM1233045 4 0.4119 0.5098 0.000 0.068 0.000 0.780 0.152
#> GSM1233047 3 0.4086 0.5213 0.284 0.000 0.704 0.000 0.012
#> GSM1233050 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233052 1 0.1386 0.8078 0.952 0.000 0.000 0.032 0.016
#> GSM1233053 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233055 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233061 3 0.4130 0.5842 0.012 0.000 0.696 0.000 0.292
#> GSM1233063 1 0.6177 0.1383 0.464 0.000 0.000 0.136 0.400
#> GSM1233065 2 0.5080 0.4060 0.000 0.504 0.008 0.020 0.468
#> GSM1233070 2 0.4909 0.6394 0.000 0.716 0.000 0.164 0.120
#> GSM1233077 3 0.0000 0.7980 0.000 0.000 1.000 0.000 0.000
#> GSM1233081 1 0.3123 0.6852 0.812 0.000 0.184 0.004 0.000
#> GSM1233084 1 0.0000 0.8376 1.000 0.000 0.000 0.000 0.000
#> GSM1233087 4 0.1195 0.5885 0.028 0.000 0.000 0.960 0.012
#> GSM1233089 2 0.2267 0.7858 0.000 0.916 0.008 0.028 0.048
#> GSM1233099 4 0.4736 0.4770 0.072 0.000 0.000 0.712 0.216
#> GSM1233112 4 0.7535 0.2867 0.180 0.000 0.144 0.524 0.152
#> GSM1233085 1 0.4249 0.2255 0.568 0.000 0.432 0.000 0.000
#> GSM1233098 2 0.1792 0.7882 0.000 0.916 0.000 0.000 0.084
#> GSM1233114 1 0.5783 0.4582 0.612 0.000 0.000 0.160 0.228
#> GSM1233119 5 0.5674 0.1869 0.000 0.008 0.080 0.316 0.596
#> GSM1233129 2 0.4302 0.4567 0.000 0.520 0.000 0.000 0.480
#> GSM1233132 1 0.4588 0.6264 0.748 0.000 0.000 0.116 0.136
#> GSM1233139 2 0.1952 0.7902 0.000 0.912 0.000 0.004 0.084
#> GSM1233143 2 0.5586 0.3807 0.000 0.480 0.044 0.012 0.464
#> GSM1233145 1 0.6578 0.1985 0.468 0.000 0.000 0.248 0.284
#> GSM1233067 2 0.6271 0.4073 0.000 0.532 0.272 0.000 0.196
#> GSM1233069 3 0.0000 0.7980 0.000 0.000 1.000 0.000 0.000
#> GSM1233072 2 0.2863 0.7633 0.000 0.876 0.000 0.064 0.060
#> GSM1233086 3 0.4416 0.5378 0.000 0.000 0.632 0.012 0.356
#> GSM1233102 4 0.3081 0.5400 0.012 0.000 0.000 0.832 0.156
#> GSM1233103 5 0.7040 0.3107 0.000 0.280 0.052 0.148 0.520
#> GSM1233107 5 0.5771 -0.0795 0.028 0.036 0.000 0.440 0.496
#> GSM1233108 3 0.0000 0.7980 0.000 0.000 1.000 0.000 0.000
#> GSM1233109 3 0.0000 0.7980 0.000 0.000 1.000 0.000 0.000
#> GSM1233110 3 0.0000 0.7980 0.000 0.000 1.000 0.000 0.000
#> GSM1233113 2 0.0404 0.8007 0.000 0.988 0.000 0.000 0.012
#> GSM1233116 3 0.4658 -0.0495 0.000 0.484 0.504 0.000 0.012
#> GSM1233120 4 0.4872 0.4760 0.120 0.000 0.000 0.720 0.160
#> GSM1233121 3 0.0000 0.7980 0.000 0.000 1.000 0.000 0.000
#> GSM1233123 3 0.0000 0.7980 0.000 0.000 1.000 0.000 0.000
#> GSM1233124 3 0.3730 0.6244 0.000 0.000 0.712 0.000 0.288
#> GSM1233125 3 0.1557 0.7696 0.008 0.000 0.940 0.000 0.052
#> GSM1233126 4 0.2588 0.5803 0.000 0.048 0.000 0.892 0.060
#> GSM1233127 2 0.4907 0.6128 0.000 0.656 0.000 0.052 0.292
#> GSM1233128 1 0.2707 0.7576 0.860 0.000 0.000 0.008 0.132
#> GSM1233130 3 0.0000 0.7980 0.000 0.000 1.000 0.000 0.000
#> GSM1233131 5 0.7581 0.2125 0.068 0.000 0.200 0.280 0.452
#> GSM1233133 3 0.0000 0.7980 0.000 0.000 1.000 0.000 0.000
#> GSM1233134 3 0.3932 0.6000 0.000 0.000 0.672 0.000 0.328
#> GSM1233135 3 0.2648 0.7217 0.000 0.000 0.848 0.000 0.152
#> GSM1233136 3 0.1205 0.7790 0.000 0.004 0.956 0.000 0.040
#> GSM1233137 1 0.1768 0.7908 0.924 0.000 0.072 0.000 0.004
#> GSM1233138 4 0.2719 0.5805 0.000 0.048 0.000 0.884 0.068
#> GSM1233140 3 0.4854 0.5509 0.044 0.000 0.648 0.000 0.308
#> GSM1233141 2 0.4849 0.5671 0.000 0.608 0.000 0.032 0.360
#> GSM1233142 2 0.4249 0.6476 0.000 0.688 0.000 0.016 0.296
#> GSM1233144 3 0.0000 0.7980 0.000 0.000 1.000 0.000 0.000
#> GSM1233147 3 0.0404 0.7940 0.000 0.000 0.988 0.000 0.012
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.2191 0.79376 0.000 0.876 0.000 0.000 0.004 0.120
#> GSM1233002 5 0.4262 -0.07799 0.000 0.016 0.000 0.476 0.508 0.000
#> GSM1233003 4 0.5525 0.15471 0.156 0.000 0.008 0.584 0.252 0.000
#> GSM1233014 4 0.5070 0.10955 0.000 0.000 0.000 0.576 0.328 0.096
#> GSM1233015 1 0.6471 -0.07239 0.376 0.248 0.000 0.020 0.356 0.000
#> GSM1233016 4 0.5248 0.11722 0.000 0.004 0.000 0.508 0.404 0.084
#> GSM1233024 2 0.0458 0.83430 0.000 0.984 0.000 0.000 0.000 0.016
#> GSM1233049 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233064 2 0.1766 0.82782 0.000 0.936 0.004 0.016 0.016 0.028
#> GSM1233068 6 0.7303 -0.10772 0.020 0.000 0.060 0.256 0.252 0.412
#> GSM1233073 4 0.1151 0.29446 0.000 0.000 0.000 0.956 0.012 0.032
#> GSM1233093 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233115 1 0.0713 0.83628 0.972 0.000 0.000 0.000 0.028 0.000
#> GSM1232992 2 0.0000 0.83589 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232993 2 0.0000 0.83589 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233005 2 0.0146 0.83567 0.000 0.996 0.000 0.004 0.000 0.000
#> GSM1233007 2 0.4778 0.72239 0.000 0.764 0.088 0.052 0.028 0.068
#> GSM1233010 5 0.5740 0.04881 0.020 0.008 0.120 0.256 0.596 0.000
#> GSM1233013 2 0.0520 0.83582 0.000 0.984 0.000 0.000 0.008 0.008
#> GSM1233018 2 0.0000 0.83589 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233019 2 0.0993 0.83096 0.000 0.964 0.000 0.000 0.012 0.024
#> GSM1233021 2 0.0547 0.83289 0.000 0.980 0.000 0.000 0.000 0.020
#> GSM1233025 4 0.3993 0.07246 0.000 0.004 0.000 0.520 0.476 0.000
#> GSM1233029 2 0.0622 0.83245 0.000 0.980 0.000 0.012 0.008 0.000
#> GSM1233030 2 0.0000 0.83589 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233031 5 0.3337 0.03310 0.000 0.000 0.000 0.260 0.736 0.004
#> GSM1233032 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233035 5 0.4720 0.08826 0.000 0.044 0.000 0.128 0.736 0.092
#> GSM1233038 4 0.6033 0.03371 0.364 0.000 0.000 0.388 0.248 0.000
#> GSM1233039 2 0.4754 0.24811 0.000 0.584 0.376 0.008 0.020 0.012
#> GSM1233042 4 0.4264 0.00153 0.000 0.016 0.000 0.500 0.484 0.000
#> GSM1233043 5 0.4594 -0.08072 0.000 0.036 0.000 0.480 0.484 0.000
#> GSM1233044 4 0.7932 0.01746 0.092 0.000 0.148 0.432 0.088 0.240
#> GSM1233046 5 0.5757 -0.12090 0.180 0.000 0.000 0.352 0.468 0.000
#> GSM1233051 1 0.6144 0.20516 0.544 0.000 0.036 0.244 0.176 0.000
#> GSM1233054 3 0.8145 0.09360 0.296 0.000 0.368 0.108 0.092 0.136
#> GSM1233057 6 0.1663 0.67138 0.000 0.088 0.000 0.000 0.000 0.912
#> GSM1233060 4 0.5627 0.01797 0.000 0.148 0.000 0.452 0.400 0.000
#> GSM1233062 2 0.3360 0.62880 0.000 0.732 0.000 0.000 0.004 0.264
#> GSM1233075 6 0.3758 0.53984 0.000 0.324 0.000 0.000 0.008 0.668
#> GSM1233078 3 0.0000 0.79504 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233079 1 0.0146 0.84898 0.996 0.000 0.004 0.000 0.000 0.000
#> GSM1233082 5 0.5699 -0.07755 0.172 0.000 0.000 0.344 0.484 0.000
#> GSM1233083 1 0.3647 0.42707 0.640 0.000 0.000 0.360 0.000 0.000
#> GSM1233091 4 0.7257 -0.05227 0.004 0.032 0.020 0.340 0.308 0.296
#> GSM1233095 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233096 1 0.0937 0.83389 0.960 0.000 0.000 0.000 0.040 0.000
#> GSM1233101 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233105 4 0.5238 0.08463 0.096 0.000 0.000 0.496 0.408 0.000
#> GSM1233117 2 0.0000 0.83589 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233118 6 0.4633 0.33405 0.000 0.392 0.000 0.004 0.036 0.568
#> GSM1233001 2 0.0000 0.83589 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233006 2 0.6898 -0.05610 0.000 0.384 0.000 0.336 0.220 0.060
#> GSM1233008 2 0.3668 0.54586 0.000 0.668 0.000 0.000 0.004 0.328
#> GSM1233009 2 0.0508 0.83478 0.000 0.984 0.000 0.004 0.000 0.012
#> GSM1233017 2 0.0547 0.83289 0.000 0.980 0.000 0.000 0.000 0.020
#> GSM1233020 2 0.1895 0.81299 0.000 0.912 0.000 0.000 0.016 0.072
#> GSM1233022 2 0.4368 0.71711 0.000 0.760 0.000 0.092 0.028 0.120
#> GSM1233026 5 0.7676 0.06575 0.000 0.200 0.140 0.020 0.416 0.224
#> GSM1233028 5 0.7538 0.11100 0.000 0.220 0.000 0.168 0.352 0.260
#> GSM1233034 2 0.0000 0.83589 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233040 1 0.0458 0.84508 0.984 0.000 0.000 0.000 0.016 0.000
#> GSM1233048 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233056 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233058 5 0.4141 -0.04501 0.000 0.000 0.000 0.432 0.556 0.012
#> GSM1233059 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233066 3 0.3528 0.54770 0.000 0.000 0.700 0.000 0.004 0.296
#> GSM1233071 6 0.7402 0.18307 0.000 0.184 0.000 0.184 0.228 0.404
#> GSM1233074 6 0.1958 0.67491 0.000 0.100 0.000 0.000 0.004 0.896
#> GSM1233076 3 0.3971 0.68847 0.000 0.020 0.816 0.076 0.032 0.056
#> GSM1233080 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233088 2 0.5304 0.38097 0.000 0.584 0.324 0.004 0.076 0.012
#> GSM1233090 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233092 4 0.5427 0.10753 0.000 0.028 0.000 0.532 0.380 0.060
#> GSM1233094 4 0.4832 0.12592 0.000 0.000 0.004 0.608 0.324 0.064
#> GSM1233097 4 0.4260 0.13087 0.004 0.000 0.000 0.640 0.332 0.024
#> GSM1233100 4 0.3124 0.24202 0.004 0.004 0.000 0.816 0.164 0.012
#> GSM1233104 4 0.4000 0.16977 0.000 0.000 0.000 0.724 0.228 0.048
#> GSM1233106 5 0.7687 0.02404 0.060 0.000 0.044 0.264 0.368 0.264
#> GSM1233111 1 0.2703 0.73223 0.824 0.000 0.000 0.004 0.172 0.000
#> GSM1233122 2 0.1719 0.81544 0.000 0.924 0.000 0.000 0.016 0.060
#> GSM1233146 5 0.4227 -0.07991 0.000 0.004 0.000 0.488 0.500 0.008
#> GSM1232994 2 0.0520 0.83389 0.000 0.984 0.000 0.008 0.008 0.000
#> GSM1232996 2 0.0713 0.83205 0.000 0.972 0.000 0.000 0.000 0.028
#> GSM1232997 2 0.2823 0.71975 0.000 0.796 0.000 0.000 0.000 0.204
#> GSM1232998 2 0.5544 0.57584 0.000 0.640 0.000 0.104 0.048 0.208
#> GSM1232999 2 0.2420 0.79223 0.000 0.876 0.000 0.008 0.008 0.108
#> GSM1233000 2 0.1657 0.81765 0.000 0.928 0.000 0.000 0.016 0.056
#> GSM1233004 3 0.4602 0.56442 0.004 0.000 0.708 0.148 0.140 0.000
#> GSM1233011 3 0.6511 0.31293 0.000 0.132 0.528 0.012 0.052 0.276
#> GSM1233012 6 0.3429 0.55807 0.000 0.252 0.004 0.000 0.004 0.740
#> GSM1233023 6 0.1391 0.67760 0.000 0.040 0.000 0.000 0.016 0.944
#> GSM1233027 2 0.0405 0.83465 0.000 0.988 0.000 0.004 0.008 0.000
#> GSM1233033 4 0.5296 0.05302 0.100 0.000 0.000 0.452 0.448 0.000
#> GSM1233036 6 0.2420 0.63922 0.000 0.032 0.000 0.004 0.076 0.888
#> GSM1233037 6 0.0000 0.66770 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233041 1 0.2520 0.75131 0.844 0.000 0.000 0.004 0.152 0.000
#> GSM1233045 5 0.4863 -0.06683 0.000 0.016 0.000 0.460 0.496 0.028
#> GSM1233047 3 0.3855 0.54160 0.272 0.000 0.704 0.000 0.000 0.024
#> GSM1233050 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233052 1 0.1152 0.82264 0.952 0.000 0.000 0.004 0.044 0.000
#> GSM1233053 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233055 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233061 3 0.3565 0.55647 0.004 0.000 0.716 0.000 0.004 0.276
#> GSM1233063 5 0.5989 -0.07334 0.248 0.000 0.000 0.320 0.432 0.000
#> GSM1233065 6 0.4001 0.52784 0.000 0.260 0.000 0.004 0.028 0.708
#> GSM1233070 2 0.5496 0.63478 0.000 0.676 0.000 0.120 0.104 0.100
#> GSM1233077 3 0.0000 0.79504 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233081 1 0.2838 0.70217 0.808 0.000 0.188 0.000 0.004 0.000
#> GSM1233084 1 0.0000 0.85069 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233087 4 0.4118 0.13320 0.020 0.000 0.000 0.628 0.352 0.000
#> GSM1233089 2 0.3060 0.79631 0.000 0.868 0.012 0.044 0.016 0.060
#> GSM1233099 4 0.3014 0.26070 0.036 0.000 0.000 0.832 0.132 0.000
#> GSM1233112 4 0.4707 0.21003 0.152 0.000 0.148 0.696 0.004 0.000
#> GSM1233085 1 0.3804 0.25637 0.576 0.000 0.424 0.000 0.000 0.000
#> GSM1233098 2 0.3345 0.69379 0.000 0.776 0.000 0.000 0.020 0.204
#> GSM1233114 1 0.5452 0.03389 0.444 0.000 0.000 0.436 0.120 0.000
#> GSM1233119 4 0.4303 0.07313 0.000 0.004 0.000 0.524 0.460 0.012
#> GSM1233129 6 0.0713 0.67280 0.000 0.028 0.000 0.000 0.000 0.972
#> GSM1233132 1 0.3607 0.45229 0.652 0.000 0.000 0.348 0.000 0.000
#> GSM1233139 2 0.1444 0.81611 0.000 0.928 0.000 0.000 0.000 0.072
#> GSM1233143 6 0.1176 0.67160 0.000 0.020 0.000 0.000 0.024 0.956
#> GSM1233145 4 0.5684 0.11294 0.228 0.000 0.000 0.528 0.244 0.000
#> GSM1233067 6 0.4838 0.58647 0.000 0.100 0.180 0.000 0.020 0.700
#> GSM1233069 3 0.0146 0.79429 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM1233072 2 0.3504 0.77170 0.000 0.832 0.000 0.076 0.032 0.060
#> GSM1233086 6 0.4490 0.24251 0.000 0.000 0.372 0.008 0.024 0.596
#> GSM1233102 4 0.0146 0.29543 0.000 0.000 0.000 0.996 0.004 0.000
#> GSM1233103 5 0.7782 0.01157 0.000 0.276 0.040 0.072 0.340 0.272
#> GSM1233107 4 0.5511 0.12434 0.008 0.016 0.000 0.616 0.256 0.104
#> GSM1233108 3 0.0146 0.79418 0.004 0.000 0.996 0.000 0.000 0.000
#> GSM1233109 3 0.0000 0.79504 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233110 3 0.0000 0.79504 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233113 2 0.1074 0.83503 0.000 0.960 0.000 0.000 0.028 0.012
#> GSM1233116 3 0.4732 -0.04544 0.000 0.476 0.488 0.000 0.020 0.016
#> GSM1233120 4 0.2361 0.28276 0.088 0.000 0.000 0.884 0.028 0.000
#> GSM1233121 3 0.0000 0.79504 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233123 3 0.0000 0.79504 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233124 3 0.4105 0.42441 0.000 0.000 0.632 0.000 0.020 0.348
#> GSM1233125 3 0.2006 0.74041 0.004 0.000 0.892 0.000 0.104 0.000
#> GSM1233126 4 0.5253 0.12486 0.000 0.020 0.000 0.556 0.364 0.060
#> GSM1233127 2 0.5450 0.56150 0.000 0.620 0.000 0.068 0.048 0.264
#> GSM1233128 1 0.3641 0.63245 0.732 0.000 0.000 0.020 0.248 0.000
#> GSM1233130 3 0.0000 0.79504 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233131 5 0.6313 0.05608 0.028 0.000 0.152 0.256 0.548 0.016
#> GSM1233133 3 0.0692 0.78901 0.000 0.000 0.976 0.000 0.020 0.004
#> GSM1233134 6 0.3053 0.61340 0.000 0.000 0.168 0.000 0.020 0.812
#> GSM1233135 6 0.4034 0.40958 0.000 0.000 0.328 0.000 0.020 0.652
#> GSM1233136 3 0.1075 0.76984 0.000 0.000 0.952 0.000 0.000 0.048
#> GSM1233137 1 0.2602 0.78423 0.884 0.000 0.072 0.000 0.020 0.024
#> GSM1233138 4 0.5223 0.13157 0.000 0.020 0.000 0.568 0.352 0.060
#> GSM1233140 3 0.6061 0.40669 0.012 0.000 0.540 0.008 0.252 0.188
#> GSM1233141 2 0.5544 0.39253 0.000 0.536 0.000 0.044 0.052 0.368
#> GSM1233142 2 0.5028 0.58229 0.000 0.636 0.000 0.004 0.112 0.248
#> GSM1233144 3 0.0436 0.79312 0.004 0.000 0.988 0.000 0.004 0.004
#> GSM1233147 3 0.0363 0.79119 0.000 0.000 0.988 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)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> CV:pam 152 1.00e+00 1.000 0.6397 2
#> CV:pam 103 9.57e-01 0.921 0.2781 3
#> CV:pam 140 5.14e-06 0.289 0.0309 4
#> CV:pam 109 1.94e-06 0.203 0.0143 5
#> CV:pam 93 1.68e-04 0.368 0.1424 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 51941 rows and 156 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 0.200 0.560 0.787 0.4417 0.507 0.507
#> 3 3 0.373 0.592 0.783 0.3266 0.657 0.450
#> 4 4 0.521 0.567 0.769 0.2358 0.775 0.485
#> 5 5 0.565 0.607 0.742 0.0654 0.841 0.480
#> 6 6 0.697 0.677 0.783 0.0596 0.896 0.565
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 6
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
#> GSM1232995 2 0.8386 0.55451 0.268 0.732
#> GSM1233002 1 0.3114 0.70588 0.944 0.056
#> GSM1233003 1 0.9323 0.35793 0.652 0.348
#> GSM1233014 1 0.4815 0.72946 0.896 0.104
#> GSM1233015 1 0.6148 0.64287 0.848 0.152
#> GSM1233016 1 0.4815 0.72946 0.896 0.104
#> GSM1233024 1 0.5519 0.72899 0.872 0.128
#> GSM1233049 2 0.7883 0.64638 0.236 0.764
#> GSM1233064 2 0.9087 0.45994 0.324 0.676
#> GSM1233068 1 0.9732 0.17897 0.596 0.404
#> GSM1233073 1 0.0000 0.70725 1.000 0.000
#> GSM1233093 1 0.9323 0.35793 0.652 0.348
#> GSM1233115 1 0.9460 0.31559 0.636 0.364
#> GSM1232992 1 0.9850 0.33569 0.572 0.428
#> GSM1232993 1 0.4815 0.72946 0.896 0.104
#> GSM1233005 1 0.9896 0.30157 0.560 0.440
#> GSM1233007 2 0.9970 0.01424 0.468 0.532
#> GSM1233010 1 0.0000 0.70725 1.000 0.000
#> GSM1233013 1 0.9710 0.40478 0.600 0.400
#> GSM1233018 1 0.9909 0.29077 0.556 0.444
#> GSM1233019 1 0.4939 0.73002 0.892 0.108
#> GSM1233021 1 0.9358 0.49920 0.648 0.352
#> GSM1233025 1 0.0000 0.70725 1.000 0.000
#> GSM1233029 1 0.4815 0.72946 0.896 0.104
#> GSM1233030 1 0.8207 0.62918 0.744 0.256
#> GSM1233031 1 0.5178 0.73023 0.884 0.116
#> GSM1233032 2 0.8499 0.61568 0.276 0.724
#> GSM1233035 1 0.3274 0.72729 0.940 0.060
#> GSM1233038 1 0.3879 0.69930 0.924 0.076
#> GSM1233039 2 0.9710 0.25046 0.400 0.600
#> GSM1233042 1 0.4815 0.72946 0.896 0.104
#> GSM1233043 1 0.4815 0.72946 0.896 0.104
#> GSM1233044 1 0.9996 -0.16758 0.512 0.488
#> GSM1233046 1 0.3114 0.70516 0.944 0.056
#> GSM1233051 1 0.9833 0.10267 0.576 0.424
#> GSM1233054 2 0.7299 0.67847 0.204 0.796
#> GSM1233057 2 0.3274 0.71388 0.060 0.940
#> GSM1233060 1 0.4815 0.72946 0.896 0.104
#> GSM1233062 1 0.4939 0.73011 0.892 0.108
#> GSM1233075 2 0.0000 0.71154 0.000 1.000
#> GSM1233078 2 0.4815 0.67925 0.104 0.896
#> GSM1233079 2 0.6343 0.68832 0.160 0.840
#> GSM1233082 1 0.9170 0.39231 0.668 0.332
#> GSM1233083 2 0.9996 0.23036 0.488 0.512
#> GSM1233091 2 1.0000 0.11396 0.496 0.504
#> GSM1233095 1 0.9552 0.28280 0.624 0.376
#> GSM1233096 1 0.6801 0.61891 0.820 0.180
#> GSM1233101 1 0.9998 -0.17830 0.508 0.492
#> GSM1233105 1 0.0000 0.70725 1.000 0.000
#> GSM1233117 2 0.9087 0.45921 0.324 0.676
#> GSM1233118 2 0.2778 0.71499 0.048 0.952
#> GSM1233001 2 0.4939 0.69551 0.108 0.892
#> GSM1233006 1 0.4815 0.72946 0.896 0.104
#> GSM1233008 2 0.9881 0.13862 0.436 0.564
#> GSM1233009 1 0.5408 0.72982 0.876 0.124
#> GSM1233017 1 0.5294 0.73002 0.880 0.120
#> GSM1233020 2 0.9248 0.42383 0.340 0.660
#> GSM1233022 1 0.6048 0.72362 0.852 0.148
#> GSM1233026 1 0.5842 0.72626 0.860 0.140
#> GSM1233028 1 0.5059 0.73064 0.888 0.112
#> GSM1233034 2 0.9922 0.08005 0.448 0.552
#> GSM1233040 1 0.9393 0.33769 0.644 0.356
#> GSM1233048 1 0.9000 0.42407 0.684 0.316
#> GSM1233056 1 0.9635 0.24362 0.612 0.388
#> GSM1233058 1 0.3879 0.72562 0.924 0.076
#> GSM1233059 1 0.9323 0.35793 0.652 0.348
#> GSM1233066 2 0.0672 0.71323 0.008 0.992
#> GSM1233071 1 0.6801 0.70978 0.820 0.180
#> GSM1233074 2 0.0938 0.71383 0.012 0.988
#> GSM1233076 2 0.9087 0.45921 0.324 0.676
#> GSM1233080 1 0.9358 0.34851 0.648 0.352
#> GSM1233088 2 0.9129 0.45256 0.328 0.672
#> GSM1233090 1 0.9608 0.25770 0.616 0.384
#> GSM1233092 1 0.4815 0.72946 0.896 0.104
#> GSM1233094 1 0.4815 0.72946 0.896 0.104
#> GSM1233097 1 0.4815 0.72946 0.896 0.104
#> GSM1233100 1 0.0000 0.70725 1.000 0.000
#> GSM1233104 1 0.4939 0.73002 0.892 0.108
#> GSM1233106 1 0.9248 0.37558 0.660 0.340
#> GSM1233111 1 0.8861 0.44620 0.696 0.304
#> GSM1233122 2 0.9977 0.00777 0.472 0.528
#> GSM1233146 1 0.4815 0.72946 0.896 0.104
#> GSM1232994 1 0.9460 0.50044 0.636 0.364
#> GSM1232996 1 0.9909 0.29079 0.556 0.444
#> GSM1232997 2 0.3274 0.71396 0.060 0.940
#> GSM1232998 1 0.4815 0.72946 0.896 0.104
#> GSM1232999 1 0.4815 0.72946 0.896 0.104
#> GSM1233000 1 0.7299 0.69286 0.796 0.204
#> GSM1233004 2 0.9815 0.42084 0.420 0.580
#> GSM1233011 2 0.9087 0.45921 0.324 0.676
#> GSM1233012 2 0.8016 0.58407 0.244 0.756
#> GSM1233023 2 0.4298 0.70530 0.088 0.912
#> GSM1233027 1 0.4815 0.72946 0.896 0.104
#> GSM1233033 1 0.0000 0.70725 1.000 0.000
#> GSM1233036 2 0.8499 0.54323 0.276 0.724
#> GSM1233037 2 0.8608 0.51969 0.284 0.716
#> GSM1233041 1 0.9323 0.35793 0.652 0.348
#> GSM1233045 1 0.5059 0.73060 0.888 0.112
#> GSM1233047 2 0.6148 0.68853 0.152 0.848
#> GSM1233050 1 0.9358 0.34806 0.648 0.352
#> GSM1233052 1 0.6247 0.64543 0.844 0.156
#> GSM1233053 2 0.8267 0.63705 0.260 0.740
#> GSM1233055 1 0.9393 0.33867 0.644 0.356
#> GSM1233061 2 0.4431 0.70822 0.092 0.908
#> GSM1233063 1 0.9323 0.35793 0.652 0.348
#> GSM1233065 2 0.3584 0.71206 0.068 0.932
#> GSM1233070 1 0.9850 0.33858 0.572 0.428
#> GSM1233077 2 0.0000 0.71154 0.000 1.000
#> GSM1233081 2 0.5178 0.68317 0.116 0.884
#> GSM1233084 1 0.9323 0.35793 0.652 0.348
#> GSM1233087 1 0.3114 0.70679 0.944 0.056
#> GSM1233089 2 0.9087 0.45921 0.324 0.676
#> GSM1233099 1 0.0000 0.70725 1.000 0.000
#> GSM1233112 2 0.9933 0.34135 0.452 0.548
#> GSM1233085 2 0.4815 0.67925 0.104 0.896
#> GSM1233098 2 0.9323 0.40430 0.348 0.652
#> GSM1233114 1 0.7815 0.55784 0.768 0.232
#> GSM1233119 1 0.4690 0.72992 0.900 0.100
#> GSM1233129 2 0.3274 0.71388 0.060 0.940
#> GSM1233132 1 0.0672 0.70890 0.992 0.008
#> GSM1233139 2 1.0000 -0.11098 0.496 0.504
#> GSM1233143 2 0.8327 0.55342 0.264 0.736
#> GSM1233145 1 0.0000 0.70725 1.000 0.000
#> GSM1233067 2 0.0000 0.71154 0.000 1.000
#> GSM1233069 2 0.0000 0.71154 0.000 1.000
#> GSM1233072 2 0.9795 0.22366 0.416 0.584
#> GSM1233086 2 0.8555 0.53455 0.280 0.720
#> GSM1233102 1 0.0000 0.70725 1.000 0.000
#> GSM1233103 1 0.7056 0.69238 0.808 0.192
#> GSM1233107 1 0.4815 0.72946 0.896 0.104
#> GSM1233108 2 0.4815 0.67925 0.104 0.896
#> GSM1233109 2 0.4815 0.67925 0.104 0.896
#> GSM1233110 2 0.0000 0.71154 0.000 1.000
#> GSM1233113 2 0.0000 0.71154 0.000 1.000
#> GSM1233116 2 0.0000 0.71154 0.000 1.000
#> GSM1233120 1 0.0000 0.70725 1.000 0.000
#> GSM1233121 2 0.0000 0.71154 0.000 1.000
#> GSM1233123 2 0.0000 0.71154 0.000 1.000
#> GSM1233124 2 0.0000 0.71154 0.000 1.000
#> GSM1233125 2 0.4815 0.67925 0.104 0.896
#> GSM1233126 1 0.4815 0.72946 0.896 0.104
#> GSM1233127 1 0.5408 0.72159 0.876 0.124
#> GSM1233128 1 0.9775 0.15842 0.588 0.412
#> GSM1233130 2 0.0000 0.71154 0.000 1.000
#> GSM1233131 1 0.0672 0.70866 0.992 0.008
#> GSM1233133 2 0.4815 0.67925 0.104 0.896
#> GSM1233134 2 0.0000 0.71154 0.000 1.000
#> GSM1233135 2 0.0000 0.71154 0.000 1.000
#> GSM1233136 2 0.0000 0.71154 0.000 1.000
#> GSM1233137 2 0.4815 0.67925 0.104 0.896
#> GSM1233138 1 0.4815 0.72946 0.896 0.104
#> GSM1233140 2 0.7219 0.68083 0.200 0.800
#> GSM1233141 2 0.9988 -0.02733 0.480 0.520
#> GSM1233142 1 0.6531 0.69707 0.832 0.168
#> GSM1233144 2 0.4815 0.67925 0.104 0.896
#> GSM1233147 2 0.8861 0.49456 0.304 0.696
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.9926 -0.2685 0.328 0.388 0.284
#> GSM1233002 2 0.0424 0.7758 0.008 0.992 0.000
#> GSM1233003 1 0.6452 0.7808 0.712 0.252 0.036
#> GSM1233014 2 0.5741 0.6735 0.188 0.776 0.036
#> GSM1233015 2 0.5156 0.5661 0.216 0.776 0.008
#> GSM1233016 2 0.4099 0.7058 0.140 0.852 0.008
#> GSM1233024 2 0.2663 0.7765 0.024 0.932 0.044
#> GSM1233049 1 0.6902 0.6424 0.732 0.100 0.168
#> GSM1233064 2 0.9994 -0.3746 0.340 0.344 0.316
#> GSM1233068 2 0.7396 0.2913 0.296 0.644 0.060
#> GSM1233073 2 0.0000 0.7752 0.000 1.000 0.000
#> GSM1233093 1 0.6180 0.7702 0.716 0.260 0.024
#> GSM1233115 1 0.6539 0.7422 0.684 0.288 0.028
#> GSM1232992 2 0.4658 0.7432 0.076 0.856 0.068
#> GSM1232993 2 0.1411 0.7767 0.000 0.964 0.036
#> GSM1233005 2 0.4749 0.7395 0.076 0.852 0.072
#> GSM1233007 2 0.7044 0.5420 0.168 0.724 0.108
#> GSM1233010 2 0.0000 0.7752 0.000 1.000 0.000
#> GSM1233013 2 0.4745 0.7404 0.080 0.852 0.068
#> GSM1233018 2 0.5153 0.7232 0.100 0.832 0.068
#> GSM1233019 2 0.2926 0.7774 0.036 0.924 0.040
#> GSM1233021 2 0.4194 0.7559 0.064 0.876 0.060
#> GSM1233025 2 0.3619 0.7250 0.136 0.864 0.000
#> GSM1233029 2 0.2297 0.7775 0.020 0.944 0.036
#> GSM1233030 2 0.3039 0.7754 0.036 0.920 0.044
#> GSM1233031 2 0.0592 0.7770 0.000 0.988 0.012
#> GSM1233032 1 0.6462 0.6914 0.764 0.120 0.116
#> GSM1233035 2 0.1411 0.7777 0.000 0.964 0.036
#> GSM1233038 2 0.5982 0.3379 0.328 0.668 0.004
#> GSM1233039 2 0.8535 0.1239 0.332 0.556 0.112
#> GSM1233042 2 0.2878 0.7348 0.096 0.904 0.000
#> GSM1233043 2 0.3845 0.7243 0.116 0.872 0.012
#> GSM1233044 1 0.8250 0.5261 0.528 0.392 0.080
#> GSM1233046 2 0.2165 0.7604 0.064 0.936 0.000
#> GSM1233051 1 0.5982 0.7864 0.744 0.228 0.028
#> GSM1233054 1 0.8511 0.0243 0.480 0.092 0.428
#> GSM1233057 3 0.8196 0.3250 0.356 0.084 0.560
#> GSM1233060 2 0.0000 0.7752 0.000 1.000 0.000
#> GSM1233062 2 0.1832 0.7774 0.008 0.956 0.036
#> GSM1233075 3 0.1315 0.7536 0.020 0.008 0.972
#> GSM1233078 3 0.0983 0.7566 0.016 0.004 0.980
#> GSM1233079 1 0.7581 -0.1252 0.496 0.040 0.464
#> GSM1233082 2 0.7636 -0.0536 0.396 0.556 0.048
#> GSM1233083 1 0.7059 0.7315 0.724 0.164 0.112
#> GSM1233091 1 0.8606 0.5133 0.528 0.364 0.108
#> GSM1233095 1 0.6012 0.7849 0.748 0.220 0.032
#> GSM1233096 2 0.6600 0.0813 0.384 0.604 0.012
#> GSM1233101 1 0.5678 0.7680 0.776 0.192 0.032
#> GSM1233105 2 0.0237 0.7748 0.004 0.996 0.000
#> GSM1233117 2 0.9528 0.0238 0.288 0.484 0.228
#> GSM1233118 3 0.6016 0.5825 0.256 0.020 0.724
#> GSM1233001 3 0.8530 0.3356 0.344 0.108 0.548
#> GSM1233006 2 0.5047 0.7121 0.140 0.824 0.036
#> GSM1233008 2 0.6410 0.6392 0.144 0.764 0.092
#> GSM1233009 2 0.2636 0.7766 0.020 0.932 0.048
#> GSM1233017 2 0.2550 0.7767 0.024 0.936 0.040
#> GSM1233020 2 0.8571 0.1307 0.340 0.548 0.112
#> GSM1233022 2 0.3267 0.7777 0.044 0.912 0.044
#> GSM1233026 2 0.0424 0.7760 0.008 0.992 0.000
#> GSM1233028 2 0.0237 0.7757 0.004 0.996 0.000
#> GSM1233034 2 0.6181 0.6421 0.116 0.780 0.104
#> GSM1233040 1 0.6056 0.7860 0.744 0.224 0.032
#> GSM1233048 1 0.7145 0.4215 0.536 0.440 0.024
#> GSM1233056 1 0.6203 0.7657 0.760 0.184 0.056
#> GSM1233058 2 0.0237 0.7757 0.004 0.996 0.000
#> GSM1233059 1 0.6287 0.7580 0.704 0.272 0.024
#> GSM1233066 3 0.5247 0.6314 0.224 0.008 0.768
#> GSM1233071 2 0.2269 0.7749 0.016 0.944 0.040
#> GSM1233074 3 0.3690 0.7225 0.100 0.016 0.884
#> GSM1233076 2 0.9303 0.0337 0.316 0.500 0.184
#> GSM1233080 1 0.5982 0.7862 0.744 0.228 0.028
#> GSM1233088 1 0.9921 0.3204 0.396 0.308 0.296
#> GSM1233090 1 0.5939 0.7859 0.748 0.224 0.028
#> GSM1233092 2 0.5741 0.6735 0.188 0.776 0.036
#> GSM1233094 2 0.0747 0.7739 0.016 0.984 0.000
#> GSM1233097 2 0.1411 0.7681 0.036 0.964 0.000
#> GSM1233100 2 0.0000 0.7752 0.000 1.000 0.000
#> GSM1233104 2 0.4930 0.7333 0.120 0.836 0.044
#> GSM1233106 1 0.7841 0.5301 0.536 0.408 0.056
#> GSM1233111 1 0.7396 0.3131 0.488 0.480 0.032
#> GSM1233122 2 0.5500 0.7081 0.100 0.816 0.084
#> GSM1233146 2 0.0237 0.7748 0.004 0.996 0.000
#> GSM1232994 2 0.4058 0.7585 0.044 0.880 0.076
#> GSM1232996 2 0.4838 0.7375 0.076 0.848 0.076
#> GSM1232997 3 0.7885 0.3952 0.336 0.072 0.592
#> GSM1232998 2 0.5741 0.6735 0.188 0.776 0.036
#> GSM1232999 2 0.1647 0.7775 0.004 0.960 0.036
#> GSM1233000 2 0.2550 0.7766 0.024 0.936 0.040
#> GSM1233004 1 0.9252 0.2645 0.468 0.160 0.372
#> GSM1233011 2 0.9151 0.0909 0.292 0.528 0.180
#> GSM1233012 3 0.9608 0.0344 0.300 0.232 0.468
#> GSM1233023 3 0.8683 0.2912 0.340 0.120 0.540
#> GSM1233027 2 0.4960 0.7262 0.128 0.832 0.040
#> GSM1233033 2 0.2066 0.7620 0.060 0.940 0.000
#> GSM1233036 2 0.9996 -0.3587 0.324 0.348 0.328
#> GSM1233037 3 0.9907 -0.2258 0.356 0.268 0.376
#> GSM1233041 1 0.6451 0.7335 0.684 0.292 0.024
#> GSM1233045 2 0.0237 0.7757 0.004 0.996 0.000
#> GSM1233047 1 0.7918 -0.0836 0.484 0.056 0.460
#> GSM1233050 1 0.5939 0.7859 0.748 0.224 0.028
#> GSM1233052 2 0.5982 0.3057 0.328 0.668 0.004
#> GSM1233053 1 0.6511 0.6657 0.760 0.104 0.136
#> GSM1233055 1 0.6295 0.7848 0.728 0.236 0.036
#> GSM1233061 3 0.6217 0.5759 0.264 0.024 0.712
#> GSM1233063 1 0.6651 0.6968 0.656 0.320 0.024
#> GSM1233065 3 0.7091 0.4854 0.320 0.040 0.640
#> GSM1233070 2 0.4058 0.7499 0.044 0.880 0.076
#> GSM1233077 3 0.0475 0.7574 0.004 0.004 0.992
#> GSM1233081 3 0.4834 0.6695 0.204 0.004 0.792
#> GSM1233084 1 0.6025 0.7858 0.740 0.232 0.028
#> GSM1233087 2 0.2860 0.7667 0.084 0.912 0.004
#> GSM1233089 2 0.9822 -0.1206 0.292 0.428 0.280
#> GSM1233099 2 0.1031 0.7718 0.024 0.976 0.000
#> GSM1233112 1 0.7552 0.7125 0.692 0.168 0.140
#> GSM1233085 3 0.2165 0.7412 0.064 0.000 0.936
#> GSM1233098 2 0.8592 0.1356 0.332 0.552 0.116
#> GSM1233114 2 0.7067 0.2144 0.376 0.596 0.028
#> GSM1233119 2 0.4921 0.6881 0.164 0.816 0.020
#> GSM1233129 3 0.7529 0.4518 0.316 0.060 0.624
#> GSM1233132 2 0.5058 0.5470 0.244 0.756 0.000
#> GSM1233139 2 0.5889 0.6734 0.108 0.796 0.096
#> GSM1233143 3 0.9908 -0.1130 0.276 0.332 0.392
#> GSM1233145 2 0.5178 0.5625 0.256 0.744 0.000
#> GSM1233067 3 0.0237 0.7563 0.004 0.000 0.996
#> GSM1233069 3 0.0424 0.7568 0.008 0.000 0.992
#> GSM1233072 2 0.7909 0.4353 0.240 0.648 0.112
#> GSM1233086 3 0.9846 -0.0863 0.276 0.304 0.420
#> GSM1233102 2 0.3941 0.7244 0.156 0.844 0.000
#> GSM1233103 2 0.2806 0.7661 0.032 0.928 0.040
#> GSM1233107 2 0.1877 0.7729 0.032 0.956 0.012
#> GSM1233108 3 0.1643 0.7389 0.044 0.000 0.956
#> GSM1233109 3 0.1643 0.7389 0.044 0.000 0.956
#> GSM1233110 3 0.0475 0.7574 0.004 0.004 0.992
#> GSM1233113 3 0.0237 0.7563 0.004 0.000 0.996
#> GSM1233116 3 0.0237 0.7563 0.004 0.000 0.996
#> GSM1233120 2 0.3340 0.7434 0.120 0.880 0.000
#> GSM1233121 3 0.0237 0.7569 0.000 0.004 0.996
#> GSM1233123 3 0.0475 0.7574 0.004 0.004 0.992
#> GSM1233124 3 0.3644 0.7105 0.124 0.004 0.872
#> GSM1233125 3 0.1860 0.7411 0.052 0.000 0.948
#> GSM1233126 2 0.5689 0.6739 0.184 0.780 0.036
#> GSM1233127 2 0.3155 0.7745 0.044 0.916 0.040
#> GSM1233128 1 0.6158 0.7680 0.760 0.188 0.052
#> GSM1233130 3 0.0475 0.7574 0.004 0.004 0.992
#> GSM1233131 2 0.0424 0.7758 0.008 0.992 0.000
#> GSM1233133 3 0.1753 0.7402 0.048 0.000 0.952
#> GSM1233134 3 0.0424 0.7568 0.008 0.000 0.992
#> GSM1233135 3 0.0237 0.7563 0.004 0.000 0.996
#> GSM1233136 3 0.0237 0.7569 0.000 0.004 0.996
#> GSM1233137 3 0.1643 0.7389 0.044 0.000 0.956
#> GSM1233138 2 0.5741 0.6735 0.188 0.776 0.036
#> GSM1233140 1 0.7458 0.6080 0.692 0.112 0.196
#> GSM1233141 2 0.5848 0.7198 0.124 0.796 0.080
#> GSM1233142 2 0.3572 0.7740 0.060 0.900 0.040
#> GSM1233144 3 0.1643 0.7389 0.044 0.000 0.956
#> GSM1233147 3 0.9926 -0.1307 0.276 0.348 0.376
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.4799 0.41740 0.224 0.744 0.032 0.000
#> GSM1233002 4 0.5137 0.24154 0.000 0.452 0.004 0.544
#> GSM1233003 1 0.0524 0.78140 0.988 0.008 0.000 0.004
#> GSM1233014 4 0.0000 0.72361 0.000 0.000 0.000 1.000
#> GSM1233015 1 0.7602 -0.14175 0.420 0.380 0.000 0.200
#> GSM1233016 4 0.0000 0.72361 0.000 0.000 0.000 1.000
#> GSM1233024 2 0.3123 0.62855 0.000 0.844 0.000 0.156
#> GSM1233049 1 0.3399 0.73124 0.868 0.092 0.040 0.000
#> GSM1233064 3 0.7784 0.26912 0.244 0.364 0.392 0.000
#> GSM1233068 1 0.4281 0.65247 0.792 0.180 0.000 0.028
#> GSM1233073 4 0.4456 0.57587 0.000 0.280 0.004 0.716
#> GSM1233093 1 0.0336 0.78007 0.992 0.008 0.000 0.000
#> GSM1233115 1 0.0707 0.77862 0.980 0.020 0.000 0.000
#> GSM1232992 2 0.3497 0.63924 0.024 0.852 0.000 0.124
#> GSM1232993 2 0.4040 0.56068 0.000 0.752 0.000 0.248
#> GSM1233005 2 0.3962 0.63892 0.044 0.832 0.000 0.124
#> GSM1233007 4 0.8655 0.00764 0.212 0.344 0.044 0.400
#> GSM1233010 4 0.5132 0.25405 0.000 0.448 0.004 0.548
#> GSM1233013 2 0.3497 0.63911 0.024 0.852 0.000 0.124
#> GSM1233018 2 0.4127 0.63679 0.052 0.824 0.000 0.124
#> GSM1233019 2 0.3311 0.61983 0.000 0.828 0.000 0.172
#> GSM1233021 2 0.2999 0.63482 0.004 0.864 0.000 0.132
#> GSM1233025 4 0.0000 0.72361 0.000 0.000 0.000 1.000
#> GSM1233029 2 0.3569 0.60335 0.000 0.804 0.000 0.196
#> GSM1233030 2 0.3591 0.62571 0.008 0.824 0.000 0.168
#> GSM1233031 2 0.4917 0.43921 0.008 0.656 0.000 0.336
#> GSM1233032 1 0.3308 0.73678 0.872 0.092 0.036 0.000
#> GSM1233035 2 0.4360 0.56425 0.008 0.744 0.000 0.248
#> GSM1233038 4 0.3325 0.67159 0.112 0.024 0.000 0.864
#> GSM1233039 2 0.6008 0.36630 0.284 0.656 0.048 0.012
#> GSM1233042 4 0.2704 0.69830 0.000 0.124 0.000 0.876
#> GSM1233043 4 0.2647 0.69929 0.000 0.120 0.000 0.880
#> GSM1233044 1 0.2845 0.76911 0.896 0.076 0.000 0.028
#> GSM1233046 2 0.7506 0.30855 0.220 0.492 0.000 0.288
#> GSM1233051 1 0.0524 0.78054 0.988 0.008 0.004 0.000
#> GSM1233054 1 0.6845 0.26147 0.564 0.128 0.308 0.000
#> GSM1233057 3 0.7114 0.53123 0.232 0.204 0.564 0.000
#> GSM1233060 2 0.4428 0.52336 0.000 0.720 0.004 0.276
#> GSM1233062 2 0.3873 0.57897 0.000 0.772 0.000 0.228
#> GSM1233075 3 0.0937 0.81903 0.012 0.012 0.976 0.000
#> GSM1233078 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233079 1 0.5977 0.53573 0.688 0.120 0.192 0.000
#> GSM1233082 1 0.4998 0.58760 0.748 0.200 0.000 0.052
#> GSM1233083 1 0.8118 0.26271 0.452 0.112 0.052 0.384
#> GSM1233091 1 0.3749 0.73567 0.840 0.128 0.032 0.000
#> GSM1233095 1 0.0188 0.77957 0.996 0.004 0.000 0.000
#> GSM1233096 1 0.6977 0.33826 0.584 0.212 0.000 0.204
#> GSM1233101 1 0.1305 0.77291 0.960 0.036 0.004 0.000
#> GSM1233105 4 0.4905 0.44902 0.000 0.364 0.004 0.632
#> GSM1233117 2 0.5533 0.38750 0.220 0.708 0.072 0.000
#> GSM1233118 3 0.6885 0.56986 0.208 0.196 0.596 0.000
#> GSM1233001 3 0.7536 0.43662 0.220 0.296 0.484 0.000
#> GSM1233006 4 0.2216 0.70937 0.000 0.092 0.000 0.908
#> GSM1233008 2 0.4297 0.62126 0.084 0.820 0.000 0.096
#> GSM1233009 2 0.4012 0.62067 0.016 0.800 0.000 0.184
#> GSM1233017 2 0.3219 0.62326 0.000 0.836 0.000 0.164
#> GSM1233020 2 0.4609 0.42333 0.224 0.752 0.024 0.000
#> GSM1233022 4 0.4972 0.07609 0.000 0.456 0.000 0.544
#> GSM1233026 2 0.4655 0.46406 0.000 0.684 0.004 0.312
#> GSM1233028 2 0.4401 0.53084 0.000 0.724 0.004 0.272
#> GSM1233034 2 0.4470 0.57809 0.172 0.792 0.004 0.032
#> GSM1233040 1 0.0524 0.78054 0.988 0.008 0.004 0.000
#> GSM1233048 1 0.4149 0.64929 0.812 0.152 0.000 0.036
#> GSM1233056 1 0.1635 0.76728 0.948 0.044 0.008 0.000
#> GSM1233058 4 0.5513 0.38234 0.016 0.384 0.004 0.596
#> GSM1233059 1 0.0336 0.78007 0.992 0.008 0.000 0.000
#> GSM1233066 3 0.6393 0.61973 0.188 0.160 0.652 0.000
#> GSM1233071 2 0.4228 0.58342 0.008 0.760 0.000 0.232
#> GSM1233074 3 0.4700 0.72545 0.124 0.084 0.792 0.000
#> GSM1233076 4 0.8872 0.04875 0.256 0.172 0.096 0.476
#> GSM1233080 1 0.0188 0.77957 0.996 0.004 0.000 0.000
#> GSM1233088 1 0.7453 0.32085 0.508 0.260 0.232 0.000
#> GSM1233090 1 0.0188 0.77957 0.996 0.004 0.000 0.000
#> GSM1233092 4 0.0000 0.72361 0.000 0.000 0.000 1.000
#> GSM1233094 4 0.2714 0.70452 0.000 0.112 0.004 0.884
#> GSM1233097 4 0.2999 0.69249 0.000 0.132 0.004 0.864
#> GSM1233100 2 0.5168 -0.09612 0.000 0.504 0.004 0.492
#> GSM1233104 4 0.2408 0.70640 0.000 0.104 0.000 0.896
#> GSM1233106 1 0.3501 0.70533 0.848 0.132 0.000 0.020
#> GSM1233111 1 0.4418 0.63338 0.784 0.184 0.000 0.032
#> GSM1233122 2 0.4956 0.61321 0.108 0.776 0.000 0.116
#> GSM1233146 4 0.5030 0.44833 0.004 0.352 0.004 0.640
#> GSM1232994 2 0.2868 0.63259 0.000 0.864 0.000 0.136
#> GSM1232996 2 0.3392 0.63892 0.020 0.856 0.000 0.124
#> GSM1232997 3 0.7091 0.53875 0.224 0.208 0.568 0.000
#> GSM1232998 4 0.0188 0.72283 0.000 0.004 0.000 0.996
#> GSM1232999 2 0.4981 0.02379 0.000 0.536 0.000 0.464
#> GSM1233000 2 0.3257 0.63121 0.004 0.844 0.000 0.152
#> GSM1233004 1 0.9518 -0.03208 0.356 0.124 0.304 0.216
#> GSM1233011 2 0.7358 0.30097 0.232 0.608 0.124 0.036
#> GSM1233012 2 0.7147 0.16984 0.224 0.560 0.216 0.000
#> GSM1233023 3 0.7480 0.45685 0.224 0.276 0.500 0.000
#> GSM1233027 4 0.4431 0.55315 0.000 0.304 0.000 0.696
#> GSM1233033 4 0.6615 0.53267 0.148 0.208 0.004 0.640
#> GSM1233036 2 0.6770 0.26655 0.236 0.604 0.160 0.000
#> GSM1233037 1 0.7536 0.25622 0.492 0.264 0.244 0.000
#> GSM1233041 1 0.0336 0.78007 0.992 0.008 0.000 0.000
#> GSM1233045 2 0.5112 0.12769 0.000 0.560 0.004 0.436
#> GSM1233047 1 0.5902 0.55736 0.696 0.120 0.184 0.000
#> GSM1233050 1 0.0336 0.78052 0.992 0.008 0.000 0.000
#> GSM1233052 1 0.7348 0.22693 0.528 0.240 0.000 0.232
#> GSM1233053 1 0.3612 0.72384 0.856 0.100 0.044 0.000
#> GSM1233055 1 0.0336 0.78052 0.992 0.008 0.000 0.000
#> GSM1233061 3 0.6656 0.54677 0.256 0.136 0.608 0.000
#> GSM1233063 1 0.1174 0.77824 0.968 0.020 0.000 0.012
#> GSM1233065 3 0.7004 0.55193 0.220 0.200 0.580 0.000
#> GSM1233070 2 0.5202 0.41999 0.016 0.668 0.004 0.312
#> GSM1233077 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233081 3 0.5624 0.66480 0.172 0.108 0.720 0.000
#> GSM1233084 1 0.0188 0.77957 0.996 0.004 0.000 0.000
#> GSM1233087 4 0.0927 0.72164 0.016 0.008 0.000 0.976
#> GSM1233089 2 0.8100 -0.15146 0.224 0.452 0.308 0.016
#> GSM1233099 4 0.2999 0.69094 0.000 0.132 0.004 0.864
#> GSM1233112 1 0.5036 0.68702 0.792 0.112 0.080 0.016
#> GSM1233085 3 0.0469 0.82379 0.012 0.000 0.988 0.000
#> GSM1233098 2 0.4799 0.41732 0.224 0.744 0.032 0.000
#> GSM1233114 1 0.5565 0.41395 0.624 0.032 0.000 0.344
#> GSM1233119 4 0.0000 0.72361 0.000 0.000 0.000 1.000
#> GSM1233129 3 0.7034 0.54823 0.220 0.204 0.576 0.000
#> GSM1233132 1 0.7192 0.05337 0.472 0.140 0.000 0.388
#> GSM1233139 2 0.4665 0.62579 0.088 0.804 0.004 0.104
#> GSM1233143 2 0.6133 0.35914 0.204 0.672 0.124 0.000
#> GSM1233145 4 0.0336 0.72196 0.008 0.000 0.000 0.992
#> GSM1233067 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233069 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233072 2 0.5875 0.51074 0.224 0.684 0.000 0.092
#> GSM1233086 2 0.7717 -0.32733 0.224 0.388 0.388 0.000
#> GSM1233102 4 0.0000 0.72361 0.000 0.000 0.000 1.000
#> GSM1233103 2 0.4567 0.57616 0.016 0.740 0.000 0.244
#> GSM1233107 4 0.4992 -0.14903 0.000 0.476 0.000 0.524
#> GSM1233108 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233109 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233110 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233113 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233116 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233120 4 0.0188 0.72327 0.004 0.000 0.000 0.996
#> GSM1233121 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233123 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233124 3 0.4608 0.73581 0.096 0.104 0.800 0.000
#> GSM1233125 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233126 4 0.0000 0.72361 0.000 0.000 0.000 1.000
#> GSM1233127 2 0.4977 0.27036 0.000 0.540 0.000 0.460
#> GSM1233128 1 0.0524 0.77690 0.988 0.008 0.004 0.000
#> GSM1233130 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233131 4 0.6044 0.23192 0.036 0.416 0.004 0.544
#> GSM1233133 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233134 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233135 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233136 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233137 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233138 4 0.0188 0.72283 0.000 0.004 0.000 0.996
#> GSM1233140 1 0.4072 0.70419 0.828 0.120 0.052 0.000
#> GSM1233141 2 0.6139 0.53482 0.100 0.656 0.000 0.244
#> GSM1233142 2 0.4356 0.52534 0.000 0.708 0.000 0.292
#> GSM1233144 3 0.0188 0.82651 0.004 0.000 0.996 0.000
#> GSM1233147 4 0.8996 0.07693 0.228 0.184 0.112 0.476
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 5 0.4065 0.68385 0.000 0.264 0.016 0.000 0.720
#> GSM1233002 2 0.7229 0.17123 0.024 0.452 0.216 0.304 0.004
#> GSM1233003 1 0.3102 0.82623 0.876 0.008 0.032 0.008 0.076
#> GSM1233014 4 0.0854 0.65125 0.004 0.000 0.012 0.976 0.008
#> GSM1233015 2 0.8052 0.22930 0.272 0.436 0.016 0.204 0.072
#> GSM1233016 4 0.1314 0.65680 0.024 0.004 0.008 0.960 0.004
#> GSM1233024 2 0.2929 0.54475 0.000 0.820 0.000 0.180 0.000
#> GSM1233049 1 0.4696 0.49891 0.616 0.000 0.024 0.000 0.360
#> GSM1233064 5 0.2283 0.77903 0.036 0.040 0.000 0.008 0.916
#> GSM1233068 1 0.5011 0.75106 0.764 0.120 0.020 0.016 0.080
#> GSM1233073 4 0.6958 0.32722 0.024 0.264 0.216 0.496 0.000
#> GSM1233093 1 0.1484 0.82518 0.944 0.000 0.008 0.000 0.048
#> GSM1233115 1 0.2853 0.82434 0.888 0.012 0.016 0.008 0.076
#> GSM1232992 2 0.1356 0.58900 0.012 0.956 0.004 0.000 0.028
#> GSM1232993 2 0.4682 0.48532 0.000 0.708 0.032 0.248 0.012
#> GSM1233005 2 0.1399 0.58892 0.028 0.952 0.000 0.000 0.020
#> GSM1233007 5 0.7078 0.25802 0.208 0.372 0.000 0.020 0.400
#> GSM1233010 4 0.7182 0.00295 0.024 0.376 0.216 0.384 0.000
#> GSM1233013 2 0.1168 0.59052 0.008 0.960 0.000 0.000 0.032
#> GSM1233018 2 0.1960 0.57942 0.020 0.928 0.004 0.000 0.048
#> GSM1233019 2 0.2773 0.55791 0.000 0.836 0.000 0.164 0.000
#> GSM1233021 2 0.1467 0.59645 0.008 0.956 0.004 0.016 0.016
#> GSM1233025 4 0.2411 0.66083 0.052 0.008 0.024 0.912 0.004
#> GSM1233029 2 0.3492 0.55608 0.000 0.796 0.000 0.188 0.016
#> GSM1233030 2 0.1960 0.60121 0.004 0.928 0.000 0.048 0.020
#> GSM1233031 2 0.6528 0.09712 0.008 0.456 0.152 0.384 0.000
#> GSM1233032 5 0.4508 0.27812 0.332 0.000 0.020 0.000 0.648
#> GSM1233035 2 0.6893 0.30693 0.112 0.548 0.044 0.288 0.008
#> GSM1233038 4 0.4685 0.57867 0.232 0.012 0.024 0.724 0.008
#> GSM1233039 5 0.6014 0.51780 0.288 0.080 0.016 0.008 0.608
#> GSM1233042 4 0.4000 0.58122 0.016 0.180 0.020 0.784 0.000
#> GSM1233043 4 0.3242 0.59616 0.012 0.172 0.000 0.816 0.000
#> GSM1233044 1 0.4329 0.79950 0.800 0.020 0.036 0.012 0.132
#> GSM1233046 2 0.8694 0.10423 0.132 0.376 0.136 0.316 0.040
#> GSM1233051 1 0.2741 0.82529 0.892 0.008 0.016 0.008 0.076
#> GSM1233054 5 0.2027 0.76484 0.040 0.008 0.024 0.000 0.928
#> GSM1233057 5 0.1405 0.77219 0.016 0.020 0.008 0.000 0.956
#> GSM1233060 2 0.6802 0.24647 0.004 0.492 0.208 0.288 0.008
#> GSM1233062 2 0.3707 0.45899 0.000 0.716 0.000 0.284 0.000
#> GSM1233075 3 0.3988 0.94575 0.000 0.016 0.732 0.000 0.252
#> GSM1233078 3 0.3452 0.94674 0.000 0.000 0.756 0.000 0.244
#> GSM1233079 5 0.3669 0.71828 0.128 0.000 0.056 0.000 0.816
#> GSM1233082 1 0.5804 0.61106 0.672 0.220 0.020 0.016 0.072
#> GSM1233083 1 0.5519 0.40760 0.556 0.012 0.036 0.004 0.392
#> GSM1233091 1 0.5462 0.45319 0.596 0.044 0.016 0.000 0.344
#> GSM1233095 1 0.1697 0.82449 0.932 0.000 0.008 0.000 0.060
#> GSM1233096 2 0.8071 0.22230 0.288 0.432 0.020 0.192 0.068
#> GSM1233101 1 0.3409 0.78789 0.824 0.000 0.032 0.000 0.144
#> GSM1233105 4 0.7233 0.16620 0.016 0.328 0.216 0.432 0.008
#> GSM1233117 5 0.5875 0.59845 0.048 0.332 0.036 0.000 0.584
#> GSM1233118 5 0.3578 0.73033 0.000 0.132 0.048 0.000 0.820
#> GSM1233001 5 0.3648 0.73063 0.024 0.156 0.008 0.000 0.812
#> GSM1233006 4 0.2831 0.63358 0.004 0.116 0.004 0.868 0.008
#> GSM1233008 2 0.2782 0.55628 0.048 0.880 0.000 0.000 0.072
#> GSM1233009 2 0.2771 0.58834 0.000 0.860 0.000 0.128 0.012
#> GSM1233017 2 0.2280 0.58316 0.000 0.880 0.000 0.120 0.000
#> GSM1233020 5 0.5328 0.57359 0.064 0.352 0.000 0.000 0.584
#> GSM1233022 4 0.4630 0.19749 0.004 0.416 0.000 0.572 0.008
#> GSM1233026 2 0.7147 0.24857 0.024 0.480 0.216 0.276 0.004
#> GSM1233028 2 0.6768 0.23448 0.012 0.488 0.208 0.292 0.000
#> GSM1233034 2 0.4906 0.43470 0.092 0.720 0.000 0.004 0.184
#> GSM1233040 1 0.3098 0.80184 0.836 0.000 0.016 0.000 0.148
#> GSM1233048 1 0.5604 0.67142 0.712 0.176 0.020 0.028 0.064
#> GSM1233056 1 0.2915 0.80054 0.860 0.000 0.024 0.000 0.116
#> GSM1233058 2 0.7444 0.03380 0.032 0.392 0.216 0.356 0.004
#> GSM1233059 1 0.1484 0.82518 0.944 0.000 0.008 0.000 0.048
#> GSM1233066 5 0.2517 0.72099 0.004 0.008 0.104 0.000 0.884
#> GSM1233071 2 0.4338 0.51251 0.004 0.736 0.004 0.232 0.024
#> GSM1233074 3 0.5691 0.55313 0.000 0.084 0.516 0.000 0.400
#> GSM1233076 5 0.3740 0.75973 0.056 0.056 0.024 0.012 0.852
#> GSM1233080 1 0.1484 0.82518 0.944 0.000 0.008 0.000 0.048
#> GSM1233088 5 0.2312 0.76511 0.060 0.012 0.016 0.000 0.912
#> GSM1233090 1 0.1830 0.82261 0.924 0.000 0.008 0.000 0.068
#> GSM1233092 4 0.0854 0.65125 0.004 0.000 0.012 0.976 0.008
#> GSM1233094 4 0.5349 0.60077 0.016 0.120 0.144 0.716 0.004
#> GSM1233097 4 0.5611 0.58913 0.032 0.104 0.172 0.692 0.000
#> GSM1233100 2 0.7073 0.09779 0.008 0.428 0.216 0.340 0.008
#> GSM1233104 4 0.2077 0.65374 0.000 0.084 0.000 0.908 0.008
#> GSM1233106 1 0.5444 0.71340 0.724 0.156 0.020 0.016 0.084
#> GSM1233111 1 0.5518 0.69493 0.716 0.164 0.016 0.020 0.084
#> GSM1233122 2 0.2630 0.55981 0.012 0.892 0.000 0.016 0.080
#> GSM1233146 4 0.7078 0.22844 0.024 0.308 0.212 0.456 0.000
#> GSM1232994 2 0.2966 0.54041 0.000 0.816 0.000 0.184 0.000
#> GSM1232996 2 0.0693 0.59153 0.008 0.980 0.000 0.000 0.012
#> GSM1232997 5 0.1503 0.76974 0.008 0.020 0.020 0.000 0.952
#> GSM1232998 4 0.1404 0.64662 0.004 0.004 0.008 0.956 0.028
#> GSM1232999 2 0.4367 0.24176 0.000 0.580 0.000 0.416 0.004
#> GSM1233000 2 0.1981 0.60208 0.000 0.920 0.000 0.064 0.016
#> GSM1233004 5 0.4056 0.74937 0.092 0.020 0.048 0.012 0.828
#> GSM1233011 5 0.3818 0.76033 0.052 0.072 0.024 0.008 0.844
#> GSM1233012 5 0.3134 0.75056 0.000 0.120 0.032 0.000 0.848
#> GSM1233023 5 0.1695 0.77518 0.008 0.044 0.008 0.000 0.940
#> GSM1233027 4 0.4520 0.37819 0.000 0.340 0.008 0.644 0.008
#> GSM1233033 4 0.7278 0.45931 0.208 0.184 0.044 0.548 0.016
#> GSM1233036 5 0.1646 0.77254 0.004 0.032 0.020 0.000 0.944
#> GSM1233037 5 0.4179 0.69406 0.140 0.044 0.020 0.000 0.796
#> GSM1233041 1 0.1484 0.82518 0.944 0.000 0.008 0.000 0.048
#> GSM1233045 2 0.6923 0.11691 0.016 0.440 0.196 0.348 0.000
#> GSM1233047 5 0.2446 0.75560 0.044 0.000 0.056 0.000 0.900
#> GSM1233050 1 0.2233 0.82631 0.904 0.000 0.016 0.000 0.080
#> GSM1233052 2 0.7791 0.21824 0.284 0.444 0.020 0.212 0.040
#> GSM1233053 5 0.4661 0.36037 0.312 0.000 0.032 0.000 0.656
#> GSM1233055 1 0.2208 0.82313 0.908 0.000 0.020 0.000 0.072
#> GSM1233061 5 0.2482 0.73947 0.024 0.000 0.084 0.000 0.892
#> GSM1233063 1 0.2852 0.82583 0.892 0.008 0.024 0.012 0.064
#> GSM1233065 5 0.2388 0.76535 0.000 0.072 0.028 0.000 0.900
#> GSM1233070 2 0.3292 0.58563 0.008 0.836 0.000 0.140 0.016
#> GSM1233077 3 0.3480 0.95546 0.000 0.000 0.752 0.000 0.248
#> GSM1233081 5 0.4599 0.17929 0.020 0.000 0.356 0.000 0.624
#> GSM1233084 1 0.1484 0.82518 0.944 0.000 0.008 0.000 0.048
#> GSM1233087 4 0.4295 0.60442 0.200 0.008 0.028 0.760 0.004
#> GSM1233089 5 0.3615 0.76292 0.048 0.084 0.016 0.004 0.848
#> GSM1233099 4 0.6270 0.58084 0.044 0.080 0.220 0.644 0.012
#> GSM1233112 1 0.5635 0.17130 0.476 0.008 0.044 0.004 0.468
#> GSM1233085 3 0.3980 0.89699 0.008 0.000 0.708 0.000 0.284
#> GSM1233098 5 0.5028 0.65431 0.072 0.260 0.000 0.000 0.668
#> GSM1233114 1 0.7508 -0.02735 0.452 0.148 0.032 0.344 0.024
#> GSM1233119 4 0.0486 0.65642 0.004 0.004 0.000 0.988 0.004
#> GSM1233129 5 0.1661 0.76716 0.000 0.036 0.024 0.000 0.940
#> GSM1233132 4 0.7329 0.38627 0.240 0.196 0.032 0.516 0.016
#> GSM1233139 2 0.2929 0.56925 0.044 0.880 0.000 0.008 0.068
#> GSM1233143 5 0.4441 0.68443 0.000 0.236 0.044 0.000 0.720
#> GSM1233145 4 0.4309 0.58525 0.228 0.004 0.024 0.740 0.004
#> GSM1233067 3 0.3961 0.94840 0.000 0.016 0.736 0.000 0.248
#> GSM1233069 3 0.3480 0.95546 0.000 0.000 0.752 0.000 0.248
#> GSM1233072 2 0.5592 0.08854 0.024 0.628 0.016 0.024 0.308
#> GSM1233086 5 0.3524 0.75742 0.052 0.036 0.040 0.008 0.864
#> GSM1233102 4 0.3682 0.62890 0.156 0.004 0.024 0.812 0.004
#> GSM1233103 2 0.7436 0.25163 0.168 0.504 0.048 0.268 0.012
#> GSM1233107 4 0.6159 0.46599 0.012 0.192 0.192 0.604 0.000
#> GSM1233108 3 0.3849 0.93940 0.016 0.000 0.752 0.000 0.232
#> GSM1233109 3 0.3700 0.93700 0.008 0.000 0.752 0.000 0.240
#> GSM1233110 3 0.3480 0.95546 0.000 0.000 0.752 0.000 0.248
#> GSM1233113 3 0.3961 0.94840 0.000 0.016 0.736 0.000 0.248
#> GSM1233116 3 0.3992 0.93890 0.000 0.012 0.720 0.000 0.268
#> GSM1233120 4 0.4244 0.59994 0.204 0.004 0.024 0.760 0.008
#> GSM1233121 3 0.3480 0.95546 0.000 0.000 0.752 0.000 0.248
#> GSM1233123 3 0.3480 0.95546 0.000 0.000 0.752 0.000 0.248
#> GSM1233124 5 0.3756 0.44908 0.000 0.008 0.248 0.000 0.744
#> GSM1233125 3 0.3934 0.93403 0.016 0.000 0.740 0.000 0.244
#> GSM1233126 4 0.0854 0.65125 0.004 0.000 0.012 0.976 0.008
#> GSM1233127 4 0.4576 0.07429 0.004 0.456 0.000 0.536 0.004
#> GSM1233128 1 0.3060 0.79682 0.848 0.000 0.024 0.000 0.128
#> GSM1233130 3 0.3480 0.95546 0.000 0.000 0.752 0.000 0.248
#> GSM1233131 4 0.7575 0.05844 0.028 0.356 0.216 0.388 0.012
#> GSM1233133 3 0.3671 0.93824 0.008 0.000 0.756 0.000 0.236
#> GSM1233134 3 0.3756 0.95233 0.000 0.008 0.744 0.000 0.248
#> GSM1233135 3 0.3480 0.95546 0.000 0.000 0.752 0.000 0.248
#> GSM1233136 3 0.3480 0.95546 0.000 0.000 0.752 0.000 0.248
#> GSM1233137 3 0.3491 0.94581 0.004 0.000 0.768 0.000 0.228
#> GSM1233138 4 0.0854 0.65125 0.004 0.000 0.012 0.976 0.008
#> GSM1233140 5 0.2951 0.74088 0.112 0.000 0.028 0.000 0.860
#> GSM1233141 2 0.4741 0.41958 0.000 0.724 0.004 0.204 0.068
#> GSM1233142 2 0.3895 0.45957 0.004 0.728 0.000 0.264 0.004
#> GSM1233144 3 0.3671 0.93824 0.008 0.000 0.756 0.000 0.236
#> GSM1233147 5 0.3853 0.75272 0.052 0.052 0.036 0.012 0.848
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 6 0.5408 0.0137 0.016 0.424 0.052 0.000 0.008 0.500
#> GSM1233002 5 0.2876 0.7482 0.000 0.056 0.000 0.080 0.860 0.004
#> GSM1233003 1 0.2430 0.8581 0.900 0.048 0.012 0.004 0.000 0.036
#> GSM1233014 4 0.0260 0.8324 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM1233015 5 0.5332 0.6033 0.136 0.096 0.000 0.016 0.704 0.048
#> GSM1233016 4 0.2252 0.8335 0.000 0.044 0.000 0.908 0.020 0.028
#> GSM1233024 5 0.3469 0.7486 0.000 0.088 0.000 0.104 0.808 0.000
#> GSM1233049 6 0.6004 0.3558 0.320 0.112 0.040 0.000 0.000 0.528
#> GSM1233064 6 0.4540 0.3394 0.040 0.308 0.008 0.000 0.000 0.644
#> GSM1233068 1 0.3971 0.8099 0.808 0.080 0.000 0.004 0.052 0.056
#> GSM1233073 5 0.4306 0.4028 0.000 0.032 0.000 0.344 0.624 0.000
#> GSM1233093 1 0.0405 0.8625 0.988 0.008 0.000 0.000 0.000 0.004
#> GSM1233115 1 0.1738 0.8613 0.928 0.016 0.004 0.000 0.000 0.052
#> GSM1232992 2 0.4874 0.4506 0.008 0.580 0.000 0.004 0.368 0.040
#> GSM1232993 5 0.3315 0.7353 0.004 0.092 0.000 0.036 0.844 0.024
#> GSM1233005 2 0.4642 0.4065 0.012 0.560 0.000 0.004 0.408 0.016
#> GSM1233007 2 0.6443 0.5628 0.060 0.600 0.004 0.020 0.184 0.132
#> GSM1233010 5 0.3108 0.7221 0.000 0.044 0.000 0.128 0.828 0.000
#> GSM1233013 2 0.5019 0.3576 0.008 0.532 0.000 0.004 0.412 0.044
#> GSM1233018 2 0.5122 0.4833 0.012 0.584 0.000 0.004 0.344 0.056
#> GSM1233019 5 0.3469 0.7492 0.000 0.088 0.000 0.104 0.808 0.000
#> GSM1233021 5 0.4518 0.2969 0.000 0.336 0.000 0.008 0.624 0.032
#> GSM1233025 4 0.2772 0.8320 0.004 0.048 0.000 0.884 0.036 0.028
#> GSM1233029 5 0.3294 0.7255 0.004 0.084 0.000 0.032 0.848 0.032
#> GSM1233030 5 0.3690 0.6882 0.004 0.128 0.000 0.016 0.808 0.044
#> GSM1233031 5 0.1908 0.7558 0.000 0.004 0.000 0.096 0.900 0.000
#> GSM1233032 6 0.4136 0.6293 0.192 0.076 0.000 0.000 0.000 0.732
#> GSM1233035 5 0.1225 0.7678 0.000 0.012 0.000 0.036 0.952 0.000
#> GSM1233038 4 0.4039 0.8135 0.012 0.068 0.000 0.808 0.076 0.036
#> GSM1233039 2 0.5554 0.3813 0.124 0.552 0.004 0.000 0.004 0.316
#> GSM1233042 4 0.3518 0.6782 0.000 0.012 0.000 0.732 0.256 0.000
#> GSM1233043 4 0.3240 0.6827 0.000 0.004 0.000 0.752 0.244 0.000
#> GSM1233044 1 0.3895 0.8147 0.816 0.060 0.040 0.000 0.008 0.076
#> GSM1233046 5 0.3879 0.7222 0.044 0.076 0.000 0.072 0.808 0.000
#> GSM1233051 1 0.1349 0.8618 0.940 0.000 0.004 0.000 0.000 0.056
#> GSM1233054 6 0.1732 0.7375 0.072 0.004 0.004 0.000 0.000 0.920
#> GSM1233057 6 0.1722 0.7376 0.036 0.016 0.008 0.004 0.000 0.936
#> GSM1233060 5 0.2085 0.7596 0.000 0.056 0.000 0.024 0.912 0.008
#> GSM1233062 5 0.3017 0.7510 0.000 0.084 0.000 0.072 0.844 0.000
#> GSM1233075 3 0.0363 0.9435 0.000 0.000 0.988 0.000 0.000 0.012
#> GSM1233078 3 0.1141 0.9260 0.000 0.000 0.948 0.000 0.000 0.052
#> GSM1233079 6 0.4259 0.6914 0.112 0.084 0.032 0.000 0.000 0.772
#> GSM1233082 1 0.4422 0.7694 0.772 0.084 0.000 0.004 0.096 0.044
#> GSM1233083 1 0.5695 0.6390 0.632 0.220 0.056 0.004 0.000 0.088
#> GSM1233091 1 0.6163 0.0867 0.456 0.300 0.004 0.000 0.004 0.236
#> GSM1233095 1 0.1168 0.8620 0.956 0.028 0.000 0.000 0.000 0.016
#> GSM1233096 5 0.5299 0.6002 0.144 0.100 0.000 0.012 0.700 0.044
#> GSM1233101 1 0.3571 0.8106 0.816 0.096 0.012 0.000 0.000 0.076
#> GSM1233105 5 0.3745 0.6055 0.000 0.028 0.000 0.240 0.732 0.000
#> GSM1233117 2 0.5639 0.2924 0.020 0.536 0.084 0.004 0.000 0.356
#> GSM1233118 6 0.3150 0.7256 0.008 0.060 0.088 0.000 0.000 0.844
#> GSM1233001 6 0.2515 0.7233 0.024 0.072 0.016 0.000 0.000 0.888
#> GSM1233006 4 0.2945 0.7559 0.000 0.020 0.000 0.824 0.156 0.000
#> GSM1233008 2 0.5615 0.5505 0.044 0.592 0.000 0.004 0.296 0.064
#> GSM1233009 5 0.2741 0.7302 0.000 0.092 0.000 0.032 0.868 0.008
#> GSM1233017 5 0.3006 0.7465 0.000 0.092 0.000 0.064 0.844 0.000
#> GSM1233020 2 0.4996 0.4179 0.032 0.604 0.008 0.004 0.012 0.340
#> GSM1233022 4 0.2783 0.7567 0.000 0.016 0.000 0.836 0.148 0.000
#> GSM1233026 5 0.2771 0.7625 0.004 0.060 0.000 0.068 0.868 0.000
#> GSM1233028 5 0.1320 0.7665 0.000 0.016 0.000 0.036 0.948 0.000
#> GSM1233034 2 0.5741 0.5793 0.056 0.624 0.004 0.000 0.228 0.088
#> GSM1233040 1 0.3084 0.8137 0.832 0.032 0.004 0.000 0.000 0.132
#> GSM1233048 1 0.3789 0.8136 0.820 0.064 0.000 0.004 0.072 0.040
#> GSM1233056 1 0.4014 0.7926 0.784 0.136 0.036 0.000 0.000 0.044
#> GSM1233058 5 0.3416 0.7123 0.000 0.056 0.000 0.140 0.804 0.000
#> GSM1233059 1 0.0748 0.8617 0.976 0.016 0.000 0.004 0.000 0.004
#> GSM1233066 6 0.2933 0.7294 0.008 0.032 0.108 0.000 0.000 0.852
#> GSM1233071 5 0.3117 0.7330 0.000 0.100 0.000 0.032 0.848 0.020
#> GSM1233074 3 0.2734 0.7878 0.008 0.004 0.840 0.000 0.000 0.148
#> GSM1233076 2 0.5606 0.3065 0.024 0.548 0.076 0.004 0.000 0.348
#> GSM1233080 1 0.0717 0.8627 0.976 0.016 0.000 0.000 0.000 0.008
#> GSM1233088 6 0.2882 0.7121 0.060 0.076 0.004 0.000 0.000 0.860
#> GSM1233090 1 0.0909 0.8631 0.968 0.012 0.000 0.000 0.000 0.020
#> GSM1233092 4 0.0260 0.8324 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM1233094 4 0.4047 0.5678 0.000 0.028 0.000 0.676 0.296 0.000
#> GSM1233097 4 0.5401 0.4037 0.000 0.080 0.000 0.568 0.332 0.020
#> GSM1233100 5 0.2653 0.7653 0.004 0.064 0.000 0.056 0.876 0.000
#> GSM1233104 4 0.1501 0.8255 0.000 0.000 0.000 0.924 0.076 0.000
#> GSM1233106 1 0.3732 0.8136 0.824 0.076 0.000 0.004 0.052 0.044
#> GSM1233111 1 0.4434 0.7777 0.776 0.092 0.000 0.008 0.080 0.044
#> GSM1233122 2 0.4466 0.4897 0.016 0.628 0.000 0.012 0.340 0.004
#> GSM1233146 5 0.4066 0.5947 0.000 0.036 0.000 0.272 0.692 0.000
#> GSM1232994 5 0.4003 0.7220 0.000 0.092 0.000 0.152 0.756 0.000
#> GSM1232996 2 0.4144 0.4133 0.000 0.580 0.000 0.004 0.408 0.008
#> GSM1232997 6 0.1959 0.7406 0.020 0.032 0.024 0.000 0.000 0.924
#> GSM1232998 4 0.0260 0.8324 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM1232999 5 0.4382 0.6546 0.000 0.076 0.000 0.228 0.696 0.000
#> GSM1233000 5 0.3022 0.7131 0.000 0.112 0.000 0.020 0.848 0.020
#> GSM1233004 6 0.7226 0.0636 0.216 0.328 0.084 0.004 0.000 0.368
#> GSM1233011 2 0.5536 0.2938 0.024 0.540 0.080 0.000 0.000 0.356
#> GSM1233012 6 0.4436 0.6197 0.012 0.180 0.080 0.000 0.000 0.728
#> GSM1233023 6 0.2226 0.7251 0.028 0.060 0.008 0.000 0.000 0.904
#> GSM1233027 4 0.4389 0.4952 0.000 0.052 0.000 0.660 0.288 0.000
#> GSM1233033 5 0.4766 0.4297 0.000 0.060 0.000 0.320 0.616 0.004
#> GSM1233036 6 0.3618 0.7316 0.032 0.076 0.068 0.000 0.000 0.824
#> GSM1233037 6 0.3851 0.6563 0.120 0.060 0.004 0.000 0.016 0.800
#> GSM1233041 1 0.0748 0.8622 0.976 0.016 0.000 0.004 0.000 0.004
#> GSM1233045 5 0.2679 0.7593 0.000 0.040 0.000 0.096 0.864 0.000
#> GSM1233047 6 0.3837 0.7324 0.052 0.076 0.060 0.000 0.000 0.812
#> GSM1233050 1 0.1429 0.8617 0.940 0.004 0.004 0.000 0.000 0.052
#> GSM1233052 5 0.5180 0.5704 0.200 0.080 0.000 0.016 0.684 0.020
#> GSM1233053 6 0.4837 0.6393 0.184 0.084 0.028 0.000 0.000 0.704
#> GSM1233055 1 0.2071 0.8602 0.916 0.044 0.012 0.000 0.000 0.028
#> GSM1233061 6 0.2752 0.7345 0.012 0.020 0.104 0.000 0.000 0.864
#> GSM1233063 1 0.2710 0.8605 0.892 0.036 0.004 0.004 0.028 0.036
#> GSM1233065 6 0.2670 0.7418 0.020 0.044 0.052 0.000 0.000 0.884
#> GSM1233070 5 0.4765 0.3641 0.016 0.320 0.000 0.040 0.624 0.000
#> GSM1233077 3 0.0000 0.9488 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233081 6 0.4495 0.5953 0.000 0.072 0.256 0.000 0.000 0.672
#> GSM1233084 1 0.0520 0.8631 0.984 0.008 0.000 0.000 0.000 0.008
#> GSM1233087 4 0.4340 0.7904 0.012 0.060 0.000 0.776 0.124 0.028
#> GSM1233089 2 0.5693 0.3133 0.024 0.548 0.072 0.004 0.004 0.348
#> GSM1233099 4 0.5392 0.5809 0.000 0.084 0.000 0.620 0.264 0.032
#> GSM1233112 1 0.6148 0.5519 0.580 0.240 0.064 0.004 0.000 0.112
#> GSM1233085 3 0.3446 0.5516 0.000 0.000 0.692 0.000 0.000 0.308
#> GSM1233098 2 0.5067 0.3746 0.040 0.572 0.008 0.000 0.012 0.368
#> GSM1233114 5 0.7626 0.1641 0.232 0.080 0.000 0.236 0.416 0.036
#> GSM1233119 4 0.0547 0.8335 0.000 0.000 0.000 0.980 0.020 0.000
#> GSM1233129 6 0.2685 0.7407 0.016 0.036 0.068 0.000 0.000 0.880
#> GSM1233132 5 0.5828 0.4116 0.012 0.080 0.000 0.300 0.576 0.032
#> GSM1233139 2 0.5628 0.4181 0.036 0.520 0.004 0.004 0.392 0.044
#> GSM1233143 6 0.5449 -0.0533 0.008 0.436 0.092 0.000 0.000 0.464
#> GSM1233145 4 0.3155 0.8261 0.008 0.056 0.000 0.864 0.040 0.032
#> GSM1233067 3 0.0146 0.9478 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM1233069 3 0.0000 0.9488 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233072 2 0.6112 0.4954 0.028 0.636 0.028 0.028 0.064 0.216
#> GSM1233086 2 0.5737 0.0927 0.020 0.464 0.084 0.004 0.000 0.428
#> GSM1233102 4 0.2632 0.8296 0.000 0.048 0.000 0.888 0.032 0.032
#> GSM1233103 5 0.2257 0.7508 0.016 0.060 0.000 0.020 0.904 0.000
#> GSM1233107 5 0.4331 0.2965 0.000 0.020 0.000 0.464 0.516 0.000
#> GSM1233108 3 0.0790 0.9396 0.000 0.000 0.968 0.000 0.000 0.032
#> GSM1233109 3 0.0790 0.9396 0.000 0.000 0.968 0.000 0.000 0.032
#> GSM1233110 3 0.0000 0.9488 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233113 3 0.0146 0.9478 0.000 0.000 0.996 0.000 0.000 0.004
#> GSM1233116 3 0.1531 0.9011 0.000 0.004 0.928 0.000 0.000 0.068
#> GSM1233120 4 0.3479 0.8228 0.004 0.060 0.000 0.840 0.064 0.032
#> GSM1233121 3 0.0260 0.9479 0.000 0.000 0.992 0.000 0.000 0.008
#> GSM1233123 3 0.0000 0.9488 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233124 6 0.3812 0.6354 0.012 0.012 0.248 0.000 0.000 0.728
#> GSM1233125 3 0.2996 0.7085 0.000 0.000 0.772 0.000 0.000 0.228
#> GSM1233126 4 0.0260 0.8324 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM1233127 5 0.4550 0.4009 0.000 0.036 0.000 0.420 0.544 0.000
#> GSM1233128 1 0.3948 0.7977 0.784 0.144 0.028 0.000 0.000 0.044
#> GSM1233130 3 0.0000 0.9488 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233131 5 0.3618 0.6621 0.000 0.040 0.000 0.192 0.768 0.000
#> GSM1233133 3 0.0713 0.9413 0.000 0.000 0.972 0.000 0.000 0.028
#> GSM1233134 3 0.0000 0.9488 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233135 3 0.0000 0.9488 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233136 3 0.0000 0.9488 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233137 3 0.0000 0.9488 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233138 4 0.0260 0.8324 0.000 0.000 0.000 0.992 0.008 0.000
#> GSM1233140 6 0.3879 0.7289 0.076 0.072 0.044 0.000 0.000 0.808
#> GSM1233141 2 0.6653 0.5002 0.012 0.544 0.008 0.212 0.184 0.040
#> GSM1233142 5 0.4249 0.6358 0.000 0.052 0.000 0.260 0.688 0.000
#> GSM1233144 3 0.0790 0.9396 0.000 0.000 0.968 0.000 0.000 0.032
#> GSM1233147 2 0.5620 0.2983 0.020 0.544 0.084 0.004 0.000 0.348
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> CV:mclust 105 5.30e-03 0.37938 0.0184 2
#> CV:mclust 121 2.31e-07 0.04441 0.0226 3
#> CV:mclust 113 3.13e-06 0.11565 0.0458 4
#> CV:mclust 114 7.10e-09 0.00868 0.0341 5
#> CV:mclust 123 3.80e-09 0.00910 0.0338 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 51941 rows and 156 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'CV' method.
#> Subgroups are detected by 'NMF' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.919 0.932 0.971 0.4753 0.527 0.527
#> 3 3 0.437 0.461 0.731 0.3912 0.768 0.576
#> 4 4 0.544 0.607 0.795 0.1336 0.757 0.410
#> 5 5 0.594 0.544 0.744 0.0684 0.854 0.502
#> 6 6 0.625 0.528 0.720 0.0407 0.888 0.526
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0000 0.9661 0.000 1.000
#> GSM1233002 1 0.0000 0.9720 1.000 0.000
#> GSM1233003 1 0.0376 0.9691 0.996 0.004
#> GSM1233014 1 0.0000 0.9720 1.000 0.000
#> GSM1233015 1 0.0000 0.9720 1.000 0.000
#> GSM1233016 1 0.0000 0.9720 1.000 0.000
#> GSM1233024 1 0.0000 0.9720 1.000 0.000
#> GSM1233049 2 0.0000 0.9661 0.000 1.000
#> GSM1233064 2 0.1633 0.9484 0.024 0.976
#> GSM1233068 1 0.0000 0.9720 1.000 0.000
#> GSM1233073 1 0.0000 0.9720 1.000 0.000
#> GSM1233093 1 0.0000 0.9720 1.000 0.000
#> GSM1233115 1 0.0000 0.9720 1.000 0.000
#> GSM1232992 1 0.0000 0.9720 1.000 0.000
#> GSM1232993 1 0.0000 0.9720 1.000 0.000
#> GSM1233005 1 0.0000 0.9720 1.000 0.000
#> GSM1233007 1 0.0000 0.9720 1.000 0.000
#> GSM1233010 1 0.0000 0.9720 1.000 0.000
#> GSM1233013 1 0.1184 0.9601 0.984 0.016
#> GSM1233018 1 0.0672 0.9662 0.992 0.008
#> GSM1233019 1 0.0000 0.9720 1.000 0.000
#> GSM1233021 1 0.0000 0.9720 1.000 0.000
#> GSM1233025 1 0.0000 0.9720 1.000 0.000
#> GSM1233029 1 0.0000 0.9720 1.000 0.000
#> GSM1233030 1 0.0000 0.9720 1.000 0.000
#> GSM1233031 1 0.0000 0.9720 1.000 0.000
#> GSM1233032 2 0.0000 0.9661 0.000 1.000
#> GSM1233035 1 0.0000 0.9720 1.000 0.000
#> GSM1233038 1 0.0000 0.9720 1.000 0.000
#> GSM1233039 1 0.6623 0.7937 0.828 0.172
#> GSM1233042 1 0.0000 0.9720 1.000 0.000
#> GSM1233043 1 0.0000 0.9720 1.000 0.000
#> GSM1233044 1 0.8081 0.6761 0.752 0.248
#> GSM1233046 1 0.0000 0.9720 1.000 0.000
#> GSM1233051 1 0.4161 0.8993 0.916 0.084
#> GSM1233054 2 0.0000 0.9661 0.000 1.000
#> GSM1233057 2 0.0000 0.9661 0.000 1.000
#> GSM1233060 1 0.0000 0.9720 1.000 0.000
#> GSM1233062 1 0.0000 0.9720 1.000 0.000
#> GSM1233075 2 0.0000 0.9661 0.000 1.000
#> GSM1233078 2 0.0000 0.9661 0.000 1.000
#> GSM1233079 2 0.0000 0.9661 0.000 1.000
#> GSM1233082 1 0.0000 0.9720 1.000 0.000
#> GSM1233083 2 0.8909 0.5677 0.308 0.692
#> GSM1233091 1 0.8267 0.6586 0.740 0.260
#> GSM1233095 1 0.3879 0.9065 0.924 0.076
#> GSM1233096 1 0.0000 0.9720 1.000 0.000
#> GSM1233101 2 0.0938 0.9583 0.012 0.988
#> GSM1233105 1 0.0000 0.9720 1.000 0.000
#> GSM1233117 2 0.0000 0.9661 0.000 1.000
#> GSM1233118 2 0.0000 0.9661 0.000 1.000
#> GSM1233001 2 0.1414 0.9516 0.020 0.980
#> GSM1233006 1 0.0000 0.9720 1.000 0.000
#> GSM1233008 1 0.2778 0.9336 0.952 0.048
#> GSM1233009 1 0.0000 0.9720 1.000 0.000
#> GSM1233017 1 0.0000 0.9720 1.000 0.000
#> GSM1233020 2 0.5294 0.8506 0.120 0.880
#> GSM1233022 1 0.0000 0.9720 1.000 0.000
#> GSM1233026 1 0.0000 0.9720 1.000 0.000
#> GSM1233028 1 0.0000 0.9720 1.000 0.000
#> GSM1233034 1 0.4298 0.8951 0.912 0.088
#> GSM1233040 1 0.6343 0.8108 0.840 0.160
#> GSM1233048 1 0.0000 0.9720 1.000 0.000
#> GSM1233056 2 0.9944 0.1773 0.456 0.544
#> GSM1233058 1 0.0000 0.9720 1.000 0.000
#> GSM1233059 1 0.0000 0.9720 1.000 0.000
#> GSM1233066 2 0.0000 0.9661 0.000 1.000
#> GSM1233071 1 0.0000 0.9720 1.000 0.000
#> GSM1233074 2 0.0000 0.9661 0.000 1.000
#> GSM1233076 2 0.6148 0.8158 0.152 0.848
#> GSM1233080 1 0.0000 0.9720 1.000 0.000
#> GSM1233088 2 0.8813 0.5691 0.300 0.700
#> GSM1233090 1 0.5178 0.8648 0.884 0.116
#> GSM1233092 1 0.0000 0.9720 1.000 0.000
#> GSM1233094 1 0.0000 0.9720 1.000 0.000
#> GSM1233097 1 0.0000 0.9720 1.000 0.000
#> GSM1233100 1 0.0000 0.9720 1.000 0.000
#> GSM1233104 1 0.0000 0.9720 1.000 0.000
#> GSM1233106 1 0.0000 0.9720 1.000 0.000
#> GSM1233111 1 0.0000 0.9720 1.000 0.000
#> GSM1233122 1 0.0000 0.9720 1.000 0.000
#> GSM1233146 1 0.0000 0.9720 1.000 0.000
#> GSM1232994 1 0.0000 0.9720 1.000 0.000
#> GSM1232996 1 0.0376 0.9691 0.996 0.004
#> GSM1232997 2 0.0000 0.9661 0.000 1.000
#> GSM1232998 1 0.0000 0.9720 1.000 0.000
#> GSM1232999 1 0.0000 0.9720 1.000 0.000
#> GSM1233000 1 0.0000 0.9720 1.000 0.000
#> GSM1233004 2 0.0376 0.9635 0.004 0.996
#> GSM1233011 2 0.2603 0.9320 0.044 0.956
#> GSM1233012 2 0.0000 0.9661 0.000 1.000
#> GSM1233023 2 0.0376 0.9635 0.004 0.996
#> GSM1233027 1 0.0000 0.9720 1.000 0.000
#> GSM1233033 1 0.0000 0.9720 1.000 0.000
#> GSM1233036 2 0.0000 0.9661 0.000 1.000
#> GSM1233037 2 0.9522 0.4024 0.372 0.628
#> GSM1233041 1 0.0000 0.9720 1.000 0.000
#> GSM1233045 1 0.0000 0.9720 1.000 0.000
#> GSM1233047 2 0.0000 0.9661 0.000 1.000
#> GSM1233050 1 0.8955 0.5585 0.688 0.312
#> GSM1233052 1 0.0000 0.9720 1.000 0.000
#> GSM1233053 2 0.0000 0.9661 0.000 1.000
#> GSM1233055 1 0.0000 0.9720 1.000 0.000
#> GSM1233061 2 0.0000 0.9661 0.000 1.000
#> GSM1233063 1 0.0000 0.9720 1.000 0.000
#> GSM1233065 2 0.0000 0.9661 0.000 1.000
#> GSM1233070 1 0.0000 0.9720 1.000 0.000
#> GSM1233077 2 0.0000 0.9661 0.000 1.000
#> GSM1233081 2 0.0000 0.9661 0.000 1.000
#> GSM1233084 1 0.0000 0.9720 1.000 0.000
#> GSM1233087 1 0.0000 0.9720 1.000 0.000
#> GSM1233089 2 0.0000 0.9661 0.000 1.000
#> GSM1233099 1 0.0000 0.9720 1.000 0.000
#> GSM1233112 2 0.1414 0.9520 0.020 0.980
#> GSM1233085 2 0.0000 0.9661 0.000 1.000
#> GSM1233098 1 1.0000 -0.0104 0.500 0.500
#> GSM1233114 1 0.0000 0.9720 1.000 0.000
#> GSM1233119 1 0.0000 0.9720 1.000 0.000
#> GSM1233129 2 0.0000 0.9661 0.000 1.000
#> GSM1233132 1 0.0000 0.9720 1.000 0.000
#> GSM1233139 1 0.2948 0.9305 0.948 0.052
#> GSM1233143 2 0.0000 0.9661 0.000 1.000
#> GSM1233145 1 0.0000 0.9720 1.000 0.000
#> GSM1233067 2 0.0000 0.9661 0.000 1.000
#> GSM1233069 2 0.0000 0.9661 0.000 1.000
#> GSM1233072 1 0.1414 0.9572 0.980 0.020
#> GSM1233086 2 0.0000 0.9661 0.000 1.000
#> GSM1233102 1 0.0000 0.9720 1.000 0.000
#> GSM1233103 1 0.0000 0.9720 1.000 0.000
#> GSM1233107 1 0.0000 0.9720 1.000 0.000
#> GSM1233108 2 0.0000 0.9661 0.000 1.000
#> GSM1233109 2 0.0000 0.9661 0.000 1.000
#> GSM1233110 2 0.0000 0.9661 0.000 1.000
#> GSM1233113 2 0.0000 0.9661 0.000 1.000
#> GSM1233116 2 0.0000 0.9661 0.000 1.000
#> GSM1233120 1 0.0000 0.9720 1.000 0.000
#> GSM1233121 2 0.0000 0.9661 0.000 1.000
#> GSM1233123 2 0.0000 0.9661 0.000 1.000
#> GSM1233124 2 0.0000 0.9661 0.000 1.000
#> GSM1233125 2 0.0000 0.9661 0.000 1.000
#> GSM1233126 1 0.0000 0.9720 1.000 0.000
#> GSM1233127 1 0.0000 0.9720 1.000 0.000
#> GSM1233128 1 0.9491 0.4072 0.632 0.368
#> GSM1233130 2 0.0000 0.9661 0.000 1.000
#> GSM1233131 1 0.0000 0.9720 1.000 0.000
#> GSM1233133 2 0.0000 0.9661 0.000 1.000
#> GSM1233134 2 0.0000 0.9661 0.000 1.000
#> GSM1233135 2 0.0000 0.9661 0.000 1.000
#> GSM1233136 2 0.0000 0.9661 0.000 1.000
#> GSM1233137 2 0.0000 0.9661 0.000 1.000
#> GSM1233138 1 0.0000 0.9720 1.000 0.000
#> GSM1233140 2 0.0000 0.9661 0.000 1.000
#> GSM1233141 1 0.3274 0.9236 0.940 0.060
#> GSM1233142 1 0.0000 0.9720 1.000 0.000
#> GSM1233144 2 0.0000 0.9661 0.000 1.000
#> GSM1233147 2 0.3114 0.9202 0.056 0.944
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 3 0.6451 0.4802 0.004 0.436 0.560
#> GSM1233002 1 0.5810 0.2693 0.664 0.336 0.000
#> GSM1233003 1 0.7114 -0.3447 0.584 0.388 0.028
#> GSM1233014 2 0.6192 0.4947 0.420 0.580 0.000
#> GSM1233015 1 0.6267 0.4854 0.548 0.452 0.000
#> GSM1233016 2 0.6305 0.4541 0.484 0.516 0.000
#> GSM1233024 2 0.4062 0.4115 0.164 0.836 0.000
#> GSM1233049 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233064 3 0.4526 0.7928 0.040 0.104 0.856
#> GSM1233068 1 0.6095 0.5063 0.608 0.392 0.000
#> GSM1233073 2 0.6225 0.4892 0.432 0.568 0.000
#> GSM1233093 1 0.0747 0.4202 0.984 0.016 0.000
#> GSM1233115 1 0.1031 0.4134 0.976 0.024 0.000
#> GSM1232992 1 0.6308 0.4571 0.508 0.492 0.000
#> GSM1232993 1 0.6267 0.4757 0.548 0.452 0.000
#> GSM1233005 2 0.3752 0.3215 0.144 0.856 0.000
#> GSM1233007 1 0.5517 -0.0906 0.728 0.268 0.004
#> GSM1233010 1 0.4750 0.2757 0.784 0.216 0.000
#> GSM1233013 2 0.6267 -0.4273 0.452 0.548 0.000
#> GSM1233018 2 0.6274 -0.4320 0.456 0.544 0.000
#> GSM1233019 2 0.2959 0.4179 0.100 0.900 0.000
#> GSM1233021 2 0.5785 -0.1913 0.332 0.668 0.000
#> GSM1233025 2 0.6309 0.4389 0.500 0.500 0.000
#> GSM1233029 1 0.6204 0.4858 0.576 0.424 0.000
#> GSM1233030 1 0.6309 0.4556 0.504 0.496 0.000
#> GSM1233031 2 0.5948 0.3005 0.360 0.640 0.000
#> GSM1233032 3 0.9305 0.0966 0.380 0.164 0.456
#> GSM1233035 2 0.6302 -0.3863 0.480 0.520 0.000
#> GSM1233038 1 0.6309 -0.4582 0.504 0.496 0.000
#> GSM1233039 1 0.7975 0.4804 0.660 0.180 0.160
#> GSM1233042 2 0.6295 0.4743 0.472 0.528 0.000
#> GSM1233043 2 0.6180 0.5032 0.416 0.584 0.000
#> GSM1233044 2 0.6962 0.4678 0.184 0.724 0.092
#> GSM1233046 2 0.4842 0.3409 0.224 0.776 0.000
#> GSM1233051 1 0.4662 0.4409 0.844 0.032 0.124
#> GSM1233054 3 0.7941 0.5805 0.096 0.276 0.628
#> GSM1233057 3 0.7567 0.5026 0.048 0.376 0.576
#> GSM1233060 1 0.5810 0.5121 0.664 0.336 0.000
#> GSM1233062 2 0.6260 -0.2899 0.448 0.552 0.000
#> GSM1233075 3 0.2066 0.8223 0.000 0.060 0.940
#> GSM1233078 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233079 3 0.0592 0.8294 0.012 0.000 0.988
#> GSM1233082 1 0.5327 0.5211 0.728 0.272 0.000
#> GSM1233083 3 0.9813 0.0607 0.316 0.260 0.424
#> GSM1233091 1 0.6672 0.4729 0.520 0.472 0.008
#> GSM1233095 1 0.3618 0.3840 0.884 0.012 0.104
#> GSM1233096 1 0.5859 0.5274 0.656 0.344 0.000
#> GSM1233101 3 0.1753 0.8181 0.048 0.000 0.952
#> GSM1233105 1 0.3619 0.3367 0.864 0.136 0.000
#> GSM1233117 3 0.6274 0.4611 0.000 0.456 0.544
#> GSM1233118 3 0.2165 0.8219 0.000 0.064 0.936
#> GSM1233001 3 0.9692 0.1743 0.224 0.344 0.432
#> GSM1233006 2 0.6111 0.5078 0.396 0.604 0.000
#> GSM1233008 2 0.4121 0.1693 0.168 0.832 0.000
#> GSM1233009 2 0.6235 -0.4000 0.436 0.564 0.000
#> GSM1233017 2 0.3116 0.3635 0.108 0.892 0.000
#> GSM1233020 2 0.6527 -0.1917 0.008 0.588 0.404
#> GSM1233022 2 0.4555 0.4997 0.200 0.800 0.000
#> GSM1233026 1 0.4452 0.4390 0.808 0.192 0.000
#> GSM1233028 2 0.3686 0.3893 0.140 0.860 0.000
#> GSM1233034 1 0.6518 0.4659 0.512 0.484 0.004
#> GSM1233040 1 0.6664 0.4789 0.528 0.464 0.008
#> GSM1233048 1 0.5760 0.5246 0.672 0.328 0.000
#> GSM1233056 3 0.9353 0.1476 0.388 0.168 0.444
#> GSM1233058 2 0.6215 0.4996 0.428 0.572 0.000
#> GSM1233059 1 0.4291 0.5042 0.820 0.180 0.000
#> GSM1233066 3 0.0237 0.8313 0.000 0.004 0.996
#> GSM1233071 1 0.6225 0.4875 0.568 0.432 0.000
#> GSM1233074 3 0.3267 0.8023 0.000 0.116 0.884
#> GSM1233076 3 0.8576 0.4607 0.240 0.160 0.600
#> GSM1233080 1 0.0829 0.4029 0.984 0.012 0.004
#> GSM1233088 1 0.9546 0.2820 0.472 0.216 0.312
#> GSM1233090 1 0.6856 0.4880 0.740 0.128 0.132
#> GSM1233092 2 0.6295 0.4627 0.472 0.528 0.000
#> GSM1233094 2 0.5733 0.5240 0.324 0.676 0.000
#> GSM1233097 2 0.5859 0.5222 0.344 0.656 0.000
#> GSM1233100 1 0.5216 0.5004 0.740 0.260 0.000
#> GSM1233104 2 0.5465 0.5205 0.288 0.712 0.000
#> GSM1233106 1 0.5810 0.5266 0.664 0.336 0.000
#> GSM1233111 1 0.5560 0.5312 0.700 0.300 0.000
#> GSM1233122 2 0.2878 0.4679 0.096 0.904 0.000
#> GSM1233146 2 0.6026 0.5135 0.376 0.624 0.000
#> GSM1232994 2 0.3551 0.3983 0.132 0.868 0.000
#> GSM1232996 2 0.2261 0.3607 0.068 0.932 0.000
#> GSM1232997 3 0.4351 0.7729 0.004 0.168 0.828
#> GSM1232998 2 0.5785 0.5251 0.332 0.668 0.000
#> GSM1232999 2 0.4842 0.4841 0.224 0.776 0.000
#> GSM1233000 2 0.6299 -0.4440 0.476 0.524 0.000
#> GSM1233004 3 0.4994 0.7425 0.112 0.052 0.836
#> GSM1233011 3 0.3572 0.7920 0.040 0.060 0.900
#> GSM1233012 3 0.5497 0.6717 0.000 0.292 0.708
#> GSM1233023 3 0.5318 0.7425 0.016 0.204 0.780
#> GSM1233027 2 0.6062 0.5129 0.384 0.616 0.000
#> GSM1233033 1 0.5835 -0.2408 0.660 0.340 0.000
#> GSM1233036 3 0.7099 0.5206 0.028 0.384 0.588
#> GSM1233037 1 0.7584 0.4466 0.488 0.472 0.040
#> GSM1233041 1 0.0892 0.4238 0.980 0.020 0.000
#> GSM1233045 2 0.6204 0.3075 0.424 0.576 0.000
#> GSM1233047 3 0.3619 0.7934 0.000 0.136 0.864
#> GSM1233050 1 0.6672 0.4729 0.520 0.472 0.008
#> GSM1233052 1 0.5905 0.5107 0.648 0.352 0.000
#> GSM1233053 3 0.7564 0.5922 0.068 0.296 0.636
#> GSM1233055 1 0.6505 -0.4322 0.528 0.468 0.004
#> GSM1233061 3 0.0747 0.8307 0.000 0.016 0.984
#> GSM1233063 1 0.2165 0.4046 0.936 0.064 0.000
#> GSM1233065 3 0.4733 0.7565 0.004 0.196 0.800
#> GSM1233070 1 0.6309 -0.3787 0.504 0.496 0.000
#> GSM1233077 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233081 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233084 1 0.2176 0.3790 0.948 0.032 0.020
#> GSM1233087 2 0.6307 0.4501 0.488 0.512 0.000
#> GSM1233089 3 0.4994 0.7425 0.024 0.160 0.816
#> GSM1233099 2 0.5859 0.5203 0.344 0.656 0.000
#> GSM1233112 3 0.6662 0.6684 0.120 0.128 0.752
#> GSM1233085 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233098 3 0.7079 0.6622 0.176 0.104 0.720
#> GSM1233114 2 0.6062 0.5097 0.384 0.616 0.000
#> GSM1233119 2 0.6295 0.4627 0.472 0.528 0.000
#> GSM1233129 3 0.5325 0.7138 0.004 0.248 0.748
#> GSM1233132 2 0.5291 0.4799 0.268 0.732 0.000
#> GSM1233139 2 0.6235 -0.4097 0.436 0.564 0.000
#> GSM1233143 3 0.6267 0.4791 0.000 0.452 0.548
#> GSM1233145 2 0.6305 0.4541 0.484 0.516 0.000
#> GSM1233067 3 0.1289 0.8285 0.000 0.032 0.968
#> GSM1233069 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233072 2 0.4504 0.5078 0.196 0.804 0.000
#> GSM1233086 3 0.0237 0.8311 0.000 0.004 0.996
#> GSM1233102 2 0.6305 0.4541 0.484 0.516 0.000
#> GSM1233103 2 0.6299 -0.3955 0.476 0.524 0.000
#> GSM1233107 2 0.3340 0.4807 0.120 0.880 0.000
#> GSM1233108 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233109 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233110 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233113 3 0.3116 0.8063 0.000 0.108 0.892
#> GSM1233116 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233120 2 0.6305 0.4541 0.484 0.516 0.000
#> GSM1233121 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233123 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233124 3 0.0892 0.8302 0.000 0.020 0.980
#> GSM1233125 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233126 2 0.6295 0.4627 0.472 0.528 0.000
#> GSM1233127 2 0.2796 0.4682 0.092 0.908 0.000
#> GSM1233128 3 0.8876 0.2278 0.412 0.120 0.468
#> GSM1233130 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233131 2 0.6225 0.4732 0.432 0.568 0.000
#> GSM1233133 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233134 3 0.2625 0.8149 0.000 0.084 0.916
#> GSM1233135 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233136 3 0.0237 0.8307 0.000 0.004 0.996
#> GSM1233137 3 0.1411 0.8278 0.000 0.036 0.964
#> GSM1233138 2 0.6295 0.4627 0.472 0.528 0.000
#> GSM1233140 3 0.1585 0.8245 0.028 0.008 0.964
#> GSM1233141 2 0.0592 0.3962 0.012 0.988 0.000
#> GSM1233142 2 0.1643 0.4008 0.044 0.956 0.000
#> GSM1233144 3 0.0000 0.8315 0.000 0.000 1.000
#> GSM1233147 3 0.7618 0.5916 0.156 0.156 0.688
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.2334 0.6694 0.000 0.908 0.088 0.004
#> GSM1233002 4 0.7076 0.1622 0.416 0.124 0.000 0.460
#> GSM1233003 4 0.4724 0.5821 0.136 0.000 0.076 0.788
#> GSM1233014 4 0.4543 0.5469 0.000 0.324 0.000 0.676
#> GSM1233015 1 0.1557 0.8121 0.944 0.056 0.000 0.000
#> GSM1233016 4 0.1411 0.7014 0.020 0.020 0.000 0.960
#> GSM1233024 2 0.4877 0.5361 0.044 0.752 0.000 0.204
#> GSM1233049 3 0.1209 0.8260 0.004 0.000 0.964 0.032
#> GSM1233064 3 0.6202 0.6386 0.056 0.244 0.676 0.024
#> GSM1233068 1 0.1716 0.8118 0.936 0.064 0.000 0.000
#> GSM1233073 4 0.5374 0.6297 0.052 0.244 0.000 0.704
#> GSM1233093 1 0.2831 0.7806 0.876 0.000 0.004 0.120
#> GSM1233115 1 0.3780 0.7629 0.832 0.004 0.016 0.148
#> GSM1232992 2 0.3710 0.6129 0.192 0.804 0.000 0.004
#> GSM1232993 2 0.5217 0.3189 0.380 0.608 0.000 0.012
#> GSM1233005 2 0.2589 0.6416 0.000 0.884 0.000 0.116
#> GSM1233007 4 0.4827 0.6173 0.164 0.040 0.012 0.784
#> GSM1233010 1 0.3219 0.7489 0.836 0.000 0.000 0.164
#> GSM1233013 2 0.1492 0.6845 0.036 0.956 0.004 0.004
#> GSM1233018 2 0.2365 0.6833 0.064 0.920 0.004 0.012
#> GSM1233019 2 0.3539 0.5888 0.004 0.820 0.000 0.176
#> GSM1233021 2 0.1837 0.6812 0.028 0.944 0.000 0.028
#> GSM1233025 4 0.1661 0.6860 0.052 0.000 0.004 0.944
#> GSM1233029 1 0.4606 0.5874 0.724 0.264 0.000 0.012
#> GSM1233030 2 0.4188 0.5531 0.244 0.752 0.000 0.004
#> GSM1233031 1 0.7379 0.0631 0.452 0.384 0.000 0.164
#> GSM1233032 1 0.4292 0.7557 0.820 0.100 0.080 0.000
#> GSM1233035 1 0.5279 0.6257 0.716 0.232 0.000 0.052
#> GSM1233038 4 0.2867 0.6683 0.104 0.012 0.000 0.884
#> GSM1233039 1 0.4597 0.7808 0.828 0.032 0.080 0.060
#> GSM1233042 4 0.2530 0.7093 0.004 0.100 0.000 0.896
#> GSM1233043 4 0.2654 0.7080 0.004 0.108 0.000 0.888
#> GSM1233044 2 0.4576 0.4434 0.000 0.728 0.012 0.260
#> GSM1233046 2 0.6236 0.4675 0.152 0.668 0.000 0.180
#> GSM1233051 1 0.4440 0.7531 0.804 0.000 0.060 0.136
#> GSM1233054 3 0.7167 0.2426 0.136 0.396 0.468 0.000
#> GSM1233057 2 0.5873 0.4115 0.076 0.668 0.256 0.000
#> GSM1233060 1 0.1978 0.8105 0.928 0.068 0.000 0.004
#> GSM1233062 2 0.5520 0.5520 0.244 0.696 0.000 0.060
#> GSM1233075 3 0.3528 0.7556 0.000 0.192 0.808 0.000
#> GSM1233078 3 0.0000 0.8383 0.000 0.000 1.000 0.000
#> GSM1233079 3 0.2099 0.8180 0.040 0.004 0.936 0.020
#> GSM1233082 1 0.0469 0.8201 0.988 0.012 0.000 0.000
#> GSM1233083 4 0.4074 0.5944 0.008 0.004 0.196 0.792
#> GSM1233091 1 0.3266 0.7422 0.832 0.168 0.000 0.000
#> GSM1233095 1 0.7148 0.4984 0.580 0.004 0.216 0.200
#> GSM1233096 1 0.0707 0.8196 0.980 0.020 0.000 0.000
#> GSM1233101 3 0.2441 0.8074 0.020 0.004 0.920 0.056
#> GSM1233105 1 0.3942 0.6782 0.764 0.000 0.000 0.236
#> GSM1233117 2 0.4153 0.6490 0.000 0.820 0.132 0.048
#> GSM1233118 3 0.4250 0.6741 0.000 0.276 0.724 0.000
#> GSM1233001 2 0.6673 0.3521 0.140 0.608 0.252 0.000
#> GSM1233006 4 0.3400 0.6819 0.000 0.180 0.000 0.820
#> GSM1233008 2 0.0672 0.6812 0.008 0.984 0.000 0.008
#> GSM1233009 2 0.3172 0.6442 0.160 0.840 0.000 0.000
#> GSM1233017 2 0.3099 0.6488 0.020 0.876 0.000 0.104
#> GSM1233020 2 0.3312 0.6691 0.000 0.876 0.072 0.052
#> GSM1233022 2 0.5244 0.0121 0.008 0.556 0.000 0.436
#> GSM1233026 1 0.1209 0.8174 0.964 0.004 0.000 0.032
#> GSM1233028 2 0.3205 0.6457 0.024 0.872 0.000 0.104
#> GSM1233034 1 0.4866 0.3267 0.596 0.404 0.000 0.000
#> GSM1233040 1 0.1302 0.8163 0.956 0.044 0.000 0.000
#> GSM1233048 1 0.1022 0.8178 0.968 0.032 0.000 0.000
#> GSM1233056 4 0.5883 0.4435 0.064 0.000 0.288 0.648
#> GSM1233058 4 0.3300 0.7038 0.008 0.144 0.000 0.848
#> GSM1233059 1 0.0336 0.8186 0.992 0.000 0.000 0.008
#> GSM1233066 3 0.1389 0.8340 0.000 0.048 0.952 0.000
#> GSM1233071 1 0.2469 0.7869 0.892 0.108 0.000 0.000
#> GSM1233074 3 0.4605 0.5859 0.000 0.336 0.664 0.000
#> GSM1233076 4 0.4773 0.4865 0.004 0.008 0.280 0.708
#> GSM1233080 1 0.4054 0.7295 0.796 0.000 0.016 0.188
#> GSM1233088 1 0.5142 0.6721 0.744 0.064 0.192 0.000
#> GSM1233090 1 0.0672 0.8180 0.984 0.000 0.008 0.008
#> GSM1233092 4 0.2589 0.7069 0.000 0.116 0.000 0.884
#> GSM1233094 4 0.4830 0.4378 0.000 0.392 0.000 0.608
#> GSM1233097 4 0.4761 0.4838 0.000 0.372 0.000 0.628
#> GSM1233100 1 0.2335 0.8163 0.920 0.060 0.000 0.020
#> GSM1233104 4 0.4955 0.3419 0.000 0.444 0.000 0.556
#> GSM1233106 1 0.0707 0.8198 0.980 0.020 0.000 0.000
#> GSM1233111 1 0.0188 0.8196 0.996 0.004 0.000 0.000
#> GSM1233122 2 0.4164 0.4639 0.000 0.736 0.000 0.264
#> GSM1233146 4 0.4037 0.7002 0.040 0.136 0.000 0.824
#> GSM1232994 2 0.4004 0.5953 0.024 0.812 0.000 0.164
#> GSM1232996 2 0.1302 0.6725 0.000 0.956 0.000 0.044
#> GSM1232997 3 0.5080 0.4254 0.004 0.420 0.576 0.000
#> GSM1232998 4 0.4925 0.3801 0.000 0.428 0.000 0.572
#> GSM1232999 2 0.4843 0.1229 0.000 0.604 0.000 0.396
#> GSM1233000 2 0.2867 0.6755 0.104 0.884 0.000 0.012
#> GSM1233004 3 0.5550 0.2020 0.000 0.020 0.552 0.428
#> GSM1233011 3 0.4701 0.6862 0.000 0.056 0.780 0.164
#> GSM1233012 2 0.5277 -0.0912 0.008 0.532 0.460 0.000
#> GSM1233023 2 0.5774 -0.1708 0.028 0.508 0.464 0.000
#> GSM1233027 4 0.3810 0.6757 0.008 0.188 0.000 0.804
#> GSM1233033 1 0.5000 0.1710 0.504 0.000 0.000 0.496
#> GSM1233036 2 0.4353 0.5067 0.012 0.756 0.232 0.000
#> GSM1233037 2 0.5360 0.1050 0.436 0.552 0.012 0.000
#> GSM1233041 1 0.2053 0.8010 0.924 0.000 0.004 0.072
#> GSM1233045 4 0.6716 0.2830 0.092 0.404 0.000 0.504
#> GSM1233047 3 0.4134 0.6859 0.000 0.260 0.740 0.000
#> GSM1233050 1 0.2760 0.7749 0.872 0.128 0.000 0.000
#> GSM1233052 1 0.1792 0.8134 0.932 0.068 0.000 0.000
#> GSM1233053 3 0.7149 0.4456 0.184 0.264 0.552 0.000
#> GSM1233055 4 0.4155 0.6213 0.100 0.000 0.072 0.828
#> GSM1233061 3 0.1474 0.8316 0.000 0.052 0.948 0.000
#> GSM1233063 1 0.4454 0.5963 0.692 0.000 0.000 0.308
#> GSM1233065 2 0.5105 -0.0413 0.000 0.564 0.432 0.004
#> GSM1233070 4 0.4488 0.6852 0.096 0.096 0.000 0.808
#> GSM1233077 3 0.0524 0.8378 0.000 0.004 0.988 0.008
#> GSM1233081 3 0.0188 0.8393 0.000 0.004 0.996 0.000
#> GSM1233084 1 0.5442 0.5960 0.672 0.000 0.040 0.288
#> GSM1233087 4 0.0336 0.6964 0.008 0.000 0.000 0.992
#> GSM1233089 4 0.6779 0.3386 0.000 0.116 0.324 0.560
#> GSM1233099 4 0.4877 0.5390 0.008 0.328 0.000 0.664
#> GSM1233112 4 0.4916 0.1973 0.000 0.000 0.424 0.576
#> GSM1233085 3 0.0469 0.8392 0.000 0.012 0.988 0.000
#> GSM1233098 3 0.8251 0.4545 0.080 0.236 0.548 0.136
#> GSM1233114 4 0.5566 0.6413 0.072 0.224 0.000 0.704
#> GSM1233119 4 0.3355 0.6910 0.004 0.160 0.000 0.836
#> GSM1233129 2 0.4624 0.2695 0.000 0.660 0.340 0.000
#> GSM1233132 4 0.7800 0.2102 0.248 0.372 0.000 0.380
#> GSM1233139 2 0.2053 0.6808 0.072 0.924 0.004 0.000
#> GSM1233143 2 0.4579 0.5625 0.004 0.764 0.212 0.020
#> GSM1233145 4 0.1388 0.7035 0.012 0.028 0.000 0.960
#> GSM1233067 3 0.3726 0.7372 0.000 0.212 0.788 0.000
#> GSM1233069 3 0.0188 0.8389 0.000 0.004 0.996 0.000
#> GSM1233072 4 0.4999 0.1867 0.000 0.492 0.000 0.508
#> GSM1233086 3 0.1798 0.8346 0.000 0.040 0.944 0.016
#> GSM1233102 4 0.2714 0.7075 0.004 0.112 0.000 0.884
#> GSM1233103 1 0.4610 0.6611 0.744 0.236 0.000 0.020
#> GSM1233107 2 0.5364 0.1499 0.016 0.592 0.000 0.392
#> GSM1233108 3 0.0707 0.8324 0.000 0.000 0.980 0.020
#> GSM1233109 3 0.1211 0.8244 0.000 0.000 0.960 0.040
#> GSM1233110 3 0.0469 0.8392 0.000 0.012 0.988 0.000
#> GSM1233113 3 0.4898 0.4369 0.000 0.416 0.584 0.000
#> GSM1233116 3 0.1557 0.8321 0.000 0.056 0.944 0.000
#> GSM1233120 4 0.2021 0.7092 0.012 0.056 0.000 0.932
#> GSM1233121 3 0.0188 0.8389 0.000 0.004 0.996 0.000
#> GSM1233123 3 0.0336 0.8393 0.000 0.008 0.992 0.000
#> GSM1233124 3 0.3311 0.7701 0.000 0.172 0.828 0.000
#> GSM1233125 3 0.1004 0.8296 0.004 0.000 0.972 0.024
#> GSM1233126 4 0.1867 0.7090 0.000 0.072 0.000 0.928
#> GSM1233127 2 0.5028 0.1456 0.004 0.596 0.000 0.400
#> GSM1233128 4 0.7185 0.3157 0.176 0.000 0.284 0.540
#> GSM1233130 3 0.0524 0.8374 0.000 0.004 0.988 0.008
#> GSM1233131 4 0.7292 0.3172 0.352 0.160 0.000 0.488
#> GSM1233133 3 0.0336 0.8393 0.000 0.008 0.992 0.000
#> GSM1233134 3 0.4134 0.6870 0.000 0.260 0.740 0.000
#> GSM1233135 3 0.0336 0.8393 0.000 0.008 0.992 0.000
#> GSM1233136 3 0.1854 0.8193 0.000 0.012 0.940 0.048
#> GSM1233137 3 0.2216 0.8138 0.000 0.092 0.908 0.000
#> GSM1233138 4 0.2589 0.7062 0.000 0.116 0.000 0.884
#> GSM1233140 3 0.4645 0.6679 0.204 0.008 0.768 0.020
#> GSM1233141 2 0.2704 0.6356 0.000 0.876 0.000 0.124
#> GSM1233142 2 0.3450 0.6120 0.008 0.836 0.000 0.156
#> GSM1233144 3 0.0469 0.8392 0.000 0.012 0.988 0.000
#> GSM1233147 4 0.4957 0.4233 0.000 0.012 0.320 0.668
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.3277 0.561978 0.000 0.856 0.072 0.004 0.068
#> GSM1233002 5 0.4503 0.594118 0.124 0.120 0.000 0.000 0.756
#> GSM1233003 4 0.4320 0.579383 0.016 0.016 0.040 0.804 0.124
#> GSM1233014 4 0.4810 0.619961 0.000 0.204 0.000 0.712 0.084
#> GSM1233015 1 0.0162 0.836134 0.996 0.004 0.000 0.000 0.000
#> GSM1233016 4 0.1914 0.668749 0.000 0.016 0.000 0.924 0.060
#> GSM1233024 2 0.4235 -0.005171 0.000 0.576 0.000 0.424 0.000
#> GSM1233049 3 0.1314 0.828758 0.000 0.012 0.960 0.012 0.016
#> GSM1233064 5 0.4618 0.554836 0.048 0.188 0.016 0.000 0.748
#> GSM1233068 1 0.2378 0.804992 0.904 0.048 0.000 0.000 0.048
#> GSM1233073 4 0.3876 0.672505 0.004 0.116 0.000 0.812 0.068
#> GSM1233093 1 0.3302 0.785603 0.864 0.020 0.000 0.044 0.072
#> GSM1233115 5 0.4860 0.470541 0.292 0.028 0.000 0.012 0.668
#> GSM1232992 2 0.6015 0.355091 0.144 0.584 0.000 0.004 0.268
#> GSM1232993 2 0.5258 0.000748 0.472 0.488 0.000 0.004 0.036
#> GSM1233005 5 0.4196 0.365155 0.004 0.356 0.000 0.000 0.640
#> GSM1233007 5 0.2270 0.668480 0.012 0.052 0.000 0.020 0.916
#> GSM1233010 1 0.3778 0.755321 0.824 0.024 0.000 0.124 0.028
#> GSM1233013 2 0.3450 0.552234 0.060 0.848 0.000 0.008 0.084
#> GSM1233018 2 0.5357 0.278874 0.068 0.588 0.000 0.000 0.344
#> GSM1233019 2 0.3930 0.485677 0.000 0.792 0.000 0.152 0.056
#> GSM1233021 2 0.5283 0.054646 0.048 0.508 0.000 0.000 0.444
#> GSM1233025 4 0.3759 0.536763 0.000 0.016 0.000 0.764 0.220
#> GSM1233029 1 0.2482 0.793811 0.892 0.084 0.000 0.000 0.024
#> GSM1233030 2 0.4768 0.353192 0.344 0.632 0.004 0.016 0.004
#> GSM1233031 4 0.6626 0.375615 0.156 0.324 0.000 0.504 0.016
#> GSM1233032 1 0.4223 0.602529 0.724 0.028 0.248 0.000 0.000
#> GSM1233035 4 0.6691 0.346183 0.192 0.296 0.012 0.500 0.000
#> GSM1233038 4 0.2208 0.654179 0.012 0.012 0.000 0.916 0.060
#> GSM1233039 5 0.4316 0.575984 0.208 0.040 0.000 0.004 0.748
#> GSM1233042 5 0.3752 0.653211 0.000 0.048 0.000 0.148 0.804
#> GSM1233043 5 0.4238 0.621574 0.000 0.052 0.000 0.192 0.756
#> GSM1233044 2 0.5735 -0.047764 0.000 0.508 0.064 0.420 0.008
#> GSM1233046 4 0.4419 0.459434 0.008 0.344 0.004 0.644 0.000
#> GSM1233051 1 0.5015 0.716470 0.760 0.020 0.016 0.068 0.136
#> GSM1233054 3 0.6036 0.393646 0.144 0.308 0.548 0.000 0.000
#> GSM1233057 2 0.6368 0.482526 0.124 0.644 0.160 0.000 0.072
#> GSM1233060 1 0.0566 0.835500 0.984 0.012 0.000 0.000 0.004
#> GSM1233062 2 0.6177 0.393822 0.240 0.600 0.000 0.144 0.016
#> GSM1233075 3 0.4134 0.716212 0.000 0.196 0.760 0.000 0.044
#> GSM1233078 3 0.1197 0.825621 0.000 0.000 0.952 0.000 0.048
#> GSM1233079 3 0.2839 0.803600 0.036 0.024 0.892 0.000 0.048
#> GSM1233082 1 0.0324 0.836415 0.992 0.004 0.000 0.000 0.004
#> GSM1233083 5 0.5455 0.499655 0.004 0.024 0.064 0.220 0.688
#> GSM1233091 1 0.4783 0.624618 0.724 0.100 0.000 0.000 0.176
#> GSM1233095 5 0.6331 0.277292 0.364 0.028 0.028 0.036 0.544
#> GSM1233096 1 0.0162 0.836134 0.996 0.004 0.000 0.000 0.000
#> GSM1233101 5 0.6548 0.174358 0.080 0.028 0.380 0.008 0.504
#> GSM1233105 4 0.3578 0.586287 0.204 0.004 0.000 0.784 0.008
#> GSM1233117 2 0.3664 0.550043 0.000 0.840 0.096 0.040 0.024
#> GSM1233118 3 0.4339 0.608361 0.000 0.296 0.684 0.000 0.020
#> GSM1233001 2 0.6534 0.277563 0.164 0.520 0.012 0.000 0.304
#> GSM1233006 5 0.5616 0.219060 0.000 0.084 0.000 0.364 0.552
#> GSM1233008 2 0.2376 0.569950 0.024 0.916 0.012 0.004 0.044
#> GSM1233009 2 0.4573 0.513681 0.164 0.756 0.000 0.072 0.008
#> GSM1233017 2 0.3989 0.368814 0.004 0.728 0.000 0.260 0.008
#> GSM1233020 2 0.4841 0.068072 0.008 0.520 0.004 0.004 0.464
#> GSM1233022 4 0.4182 0.480531 0.000 0.352 0.000 0.644 0.004
#> GSM1233026 1 0.2338 0.818680 0.916 0.016 0.000 0.036 0.032
#> GSM1233028 2 0.4508 0.495800 0.032 0.784 0.000 0.128 0.056
#> GSM1233034 1 0.4767 0.607893 0.720 0.192 0.000 0.000 0.088
#> GSM1233040 1 0.1082 0.832840 0.964 0.008 0.000 0.028 0.000
#> GSM1233048 1 0.0324 0.835843 0.992 0.004 0.000 0.000 0.004
#> GSM1233056 4 0.7181 0.132589 0.004 0.024 0.208 0.464 0.300
#> GSM1233058 5 0.3323 0.665865 0.000 0.100 0.000 0.056 0.844
#> GSM1233059 1 0.0290 0.835852 0.992 0.000 0.000 0.008 0.000
#> GSM1233066 3 0.1043 0.832469 0.000 0.040 0.960 0.000 0.000
#> GSM1233071 1 0.1041 0.831031 0.964 0.032 0.000 0.000 0.004
#> GSM1233074 3 0.4969 0.434584 0.000 0.376 0.588 0.000 0.036
#> GSM1233076 5 0.3857 0.625259 0.000 0.016 0.044 0.120 0.820
#> GSM1233080 1 0.5095 0.706364 0.768 0.024 0.024 0.100 0.084
#> GSM1233088 1 0.3942 0.656823 0.748 0.020 0.000 0.000 0.232
#> GSM1233090 1 0.1117 0.830904 0.964 0.016 0.000 0.020 0.000
#> GSM1233092 4 0.4930 0.272097 0.000 0.032 0.000 0.580 0.388
#> GSM1233094 4 0.4904 0.593686 0.000 0.240 0.000 0.688 0.072
#> GSM1233097 5 0.6031 0.378428 0.000 0.268 0.000 0.164 0.568
#> GSM1233100 1 0.1547 0.829986 0.948 0.032 0.000 0.004 0.016
#> GSM1233104 4 0.6582 0.278562 0.000 0.376 0.000 0.416 0.208
#> GSM1233106 1 0.0451 0.836146 0.988 0.004 0.000 0.008 0.000
#> GSM1233111 1 0.0324 0.836227 0.992 0.004 0.000 0.004 0.000
#> GSM1233122 2 0.5083 0.108132 0.000 0.532 0.000 0.036 0.432
#> GSM1233146 4 0.4737 0.583131 0.004 0.056 0.000 0.712 0.228
#> GSM1232994 2 0.4588 0.436485 0.024 0.756 0.000 0.180 0.040
#> GSM1232996 2 0.4504 0.095310 0.008 0.564 0.000 0.000 0.428
#> GSM1232997 2 0.6937 0.059110 0.036 0.424 0.132 0.000 0.408
#> GSM1232998 5 0.5917 0.369997 0.000 0.304 0.000 0.132 0.564
#> GSM1232999 5 0.5128 0.327692 0.004 0.380 0.000 0.036 0.580
#> GSM1233000 2 0.4723 0.501563 0.128 0.736 0.000 0.000 0.136
#> GSM1233004 5 0.1710 0.672999 0.000 0.020 0.024 0.012 0.944
#> GSM1233011 3 0.6065 0.199406 0.000 0.072 0.516 0.020 0.392
#> GSM1233012 3 0.4803 0.150812 0.000 0.492 0.492 0.012 0.004
#> GSM1233023 2 0.6752 0.196760 0.052 0.484 0.088 0.000 0.376
#> GSM1233027 5 0.4229 0.656848 0.004 0.104 0.000 0.104 0.788
#> GSM1233033 4 0.3038 0.649388 0.088 0.016 0.000 0.872 0.024
#> GSM1233036 2 0.5049 0.077185 0.000 0.560 0.408 0.028 0.004
#> GSM1233037 1 0.5238 0.112313 0.520 0.440 0.004 0.000 0.036
#> GSM1233041 1 0.4106 0.620142 0.724 0.020 0.000 0.256 0.000
#> GSM1233045 5 0.5245 0.537753 0.064 0.224 0.000 0.020 0.692
#> GSM1233047 3 0.3143 0.736673 0.000 0.204 0.796 0.000 0.000
#> GSM1233050 1 0.1386 0.828078 0.952 0.032 0.000 0.000 0.016
#> GSM1233052 1 0.1978 0.823883 0.932 0.032 0.000 0.024 0.012
#> GSM1233053 3 0.4521 0.705901 0.088 0.164 0.748 0.000 0.000
#> GSM1233055 5 0.5905 0.353992 0.016 0.024 0.040 0.312 0.608
#> GSM1233061 3 0.1205 0.832991 0.000 0.040 0.956 0.000 0.004
#> GSM1233063 4 0.6655 0.079973 0.384 0.020 0.004 0.476 0.116
#> GSM1233065 5 0.5695 0.219415 0.020 0.372 0.048 0.000 0.560
#> GSM1233070 5 0.2710 0.670471 0.008 0.064 0.000 0.036 0.892
#> GSM1233077 3 0.3366 0.686704 0.000 0.000 0.768 0.000 0.232
#> GSM1233081 3 0.0703 0.830920 0.000 0.000 0.976 0.000 0.024
#> GSM1233084 1 0.7289 0.344253 0.528 0.024 0.036 0.276 0.136
#> GSM1233087 5 0.4492 0.449805 0.004 0.020 0.000 0.296 0.680
#> GSM1233089 5 0.2416 0.668708 0.000 0.060 0.016 0.016 0.908
#> GSM1233099 4 0.5739 0.525056 0.000 0.280 0.000 0.596 0.124
#> GSM1233112 5 0.6621 0.291385 0.000 0.020 0.156 0.296 0.528
#> GSM1233085 3 0.0609 0.834457 0.000 0.020 0.980 0.000 0.000
#> GSM1233098 5 0.3915 0.610549 0.024 0.136 0.028 0.000 0.812
#> GSM1233114 4 0.3812 0.619710 0.000 0.204 0.000 0.772 0.024
#> GSM1233119 4 0.3543 0.670885 0.000 0.112 0.000 0.828 0.060
#> GSM1233129 2 0.5192 0.358029 0.000 0.644 0.280 0.000 0.076
#> GSM1233132 4 0.4338 0.566393 0.008 0.264 0.000 0.712 0.016
#> GSM1233139 2 0.3443 0.545710 0.040 0.860 0.036 0.064 0.000
#> GSM1233143 2 0.5828 0.377912 0.000 0.608 0.260 0.128 0.004
#> GSM1233145 4 0.3011 0.629887 0.000 0.016 0.000 0.844 0.140
#> GSM1233067 3 0.2929 0.758209 0.000 0.180 0.820 0.000 0.000
#> GSM1233069 3 0.1830 0.824886 0.000 0.008 0.924 0.000 0.068
#> GSM1233072 2 0.6615 -0.180140 0.000 0.408 0.000 0.376 0.216
#> GSM1233086 3 0.5012 0.609776 0.000 0.048 0.696 0.016 0.240
#> GSM1233102 4 0.3409 0.673039 0.000 0.052 0.000 0.836 0.112
#> GSM1233103 1 0.6877 0.079694 0.456 0.332 0.004 0.200 0.008
#> GSM1233107 4 0.4588 0.435305 0.000 0.380 0.000 0.604 0.016
#> GSM1233108 3 0.2079 0.812333 0.000 0.020 0.916 0.000 0.064
#> GSM1233109 3 0.2464 0.797541 0.000 0.016 0.888 0.000 0.096
#> GSM1233110 3 0.0912 0.835264 0.000 0.016 0.972 0.000 0.012
#> GSM1233113 2 0.5884 0.167468 0.000 0.536 0.352 0.000 0.112
#> GSM1233116 3 0.1331 0.835278 0.000 0.040 0.952 0.000 0.008
#> GSM1233120 4 0.4969 0.522127 0.004 0.056 0.000 0.676 0.264
#> GSM1233121 3 0.3366 0.690577 0.000 0.000 0.768 0.000 0.232
#> GSM1233123 3 0.0693 0.834866 0.000 0.012 0.980 0.000 0.008
#> GSM1233124 3 0.2230 0.804427 0.000 0.116 0.884 0.000 0.000
#> GSM1233125 3 0.1862 0.818270 0.000 0.016 0.932 0.004 0.048
#> GSM1233126 4 0.3888 0.655833 0.000 0.064 0.000 0.800 0.136
#> GSM1233127 2 0.4830 -0.234983 0.000 0.492 0.000 0.488 0.020
#> GSM1233128 4 0.7557 0.261350 0.044 0.024 0.224 0.520 0.188
#> GSM1233130 3 0.2471 0.781826 0.000 0.000 0.864 0.000 0.136
#> GSM1233131 4 0.3895 0.640399 0.044 0.132 0.000 0.812 0.012
#> GSM1233133 3 0.0609 0.834457 0.000 0.020 0.980 0.000 0.000
#> GSM1233134 3 0.3003 0.751427 0.000 0.188 0.812 0.000 0.000
#> GSM1233135 3 0.1041 0.834318 0.000 0.032 0.964 0.000 0.004
#> GSM1233136 5 0.3001 0.620731 0.000 0.004 0.144 0.008 0.844
#> GSM1233137 3 0.1410 0.826333 0.000 0.060 0.940 0.000 0.000
#> GSM1233138 4 0.3416 0.678575 0.000 0.072 0.000 0.840 0.088
#> GSM1233140 3 0.2640 0.805690 0.032 0.016 0.900 0.052 0.000
#> GSM1233141 2 0.3656 0.452893 0.000 0.800 0.000 0.168 0.032
#> GSM1233142 2 0.4380 0.286916 0.000 0.688 0.004 0.292 0.016
#> GSM1233144 3 0.0510 0.834757 0.000 0.016 0.984 0.000 0.000
#> GSM1233147 5 0.3467 0.629767 0.000 0.004 0.036 0.128 0.832
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.2830 0.5683 0.000 0.864 0.064 0.000 0.068 0.004
#> GSM1233002 6 0.5341 0.4353 0.148 0.228 0.000 0.008 0.000 0.616
#> GSM1233003 4 0.2244 0.7586 0.016 0.012 0.000 0.912 0.048 0.012
#> GSM1233014 4 0.2444 0.7498 0.000 0.028 0.000 0.892 0.068 0.012
#> GSM1233015 1 0.1261 0.7690 0.952 0.024 0.000 0.000 0.024 0.000
#> GSM1233016 4 0.1340 0.7633 0.008 0.000 0.000 0.948 0.040 0.004
#> GSM1233024 5 0.6293 0.3341 0.004 0.312 0.000 0.272 0.408 0.004
#> GSM1233049 3 0.1741 0.8109 0.004 0.012 0.940 0.004 0.020 0.020
#> GSM1233064 6 0.4976 0.2369 0.052 0.400 0.008 0.000 0.000 0.540
#> GSM1233068 1 0.2613 0.7279 0.848 0.140 0.000 0.000 0.000 0.012
#> GSM1233073 4 0.0865 0.7606 0.000 0.000 0.000 0.964 0.036 0.000
#> GSM1233093 1 0.3725 0.6987 0.804 0.012 0.000 0.004 0.052 0.128
#> GSM1233115 6 0.3505 0.5639 0.096 0.008 0.000 0.004 0.068 0.824
#> GSM1232992 2 0.4390 0.5136 0.148 0.720 0.000 0.000 0.000 0.132
#> GSM1232993 2 0.4601 0.1181 0.436 0.536 0.000 0.012 0.004 0.012
#> GSM1233005 6 0.5231 0.2285 0.000 0.392 0.004 0.000 0.084 0.520
#> GSM1233007 6 0.5118 0.4822 0.020 0.252 0.000 0.084 0.000 0.644
#> GSM1233010 5 0.4840 0.4701 0.152 0.000 0.000 0.004 0.680 0.164
#> GSM1233013 2 0.2201 0.5940 0.048 0.912 0.000 0.004 0.024 0.012
#> GSM1233018 2 0.4315 0.4623 0.016 0.736 0.004 0.000 0.044 0.200
#> GSM1233019 2 0.4522 0.4811 0.000 0.700 0.000 0.236 0.036 0.028
#> GSM1233021 2 0.5029 0.0776 0.000 0.544 0.000 0.000 0.080 0.376
#> GSM1233025 4 0.6141 0.5552 0.024 0.016 0.004 0.596 0.156 0.204
#> GSM1233029 1 0.2758 0.7548 0.860 0.112 0.000 0.000 0.016 0.012
#> GSM1233030 2 0.3935 0.4330 0.292 0.688 0.000 0.004 0.016 0.000
#> GSM1233031 5 0.3834 0.6194 0.100 0.048 0.000 0.036 0.812 0.004
#> GSM1233032 1 0.4632 0.6328 0.724 0.080 0.176 0.000 0.016 0.004
#> GSM1233035 5 0.7304 0.1589 0.316 0.092 0.000 0.224 0.364 0.004
#> GSM1233038 4 0.3951 0.7024 0.040 0.012 0.000 0.792 0.140 0.016
#> GSM1233039 6 0.4962 0.4883 0.152 0.180 0.000 0.000 0.004 0.664
#> GSM1233042 4 0.5121 0.4571 0.000 0.052 0.000 0.624 0.032 0.292
#> GSM1233043 4 0.4890 0.5250 0.004 0.044 0.000 0.660 0.024 0.268
#> GSM1233044 5 0.7243 0.3578 0.000 0.224 0.156 0.096 0.496 0.028
#> GSM1233046 4 0.4861 0.5446 0.012 0.108 0.000 0.700 0.176 0.004
#> GSM1233051 1 0.5679 0.6005 0.676 0.084 0.000 0.076 0.016 0.148
#> GSM1233054 3 0.5893 0.2712 0.152 0.312 0.520 0.000 0.016 0.000
#> GSM1233057 2 0.4142 0.5945 0.068 0.800 0.084 0.000 0.036 0.012
#> GSM1233060 1 0.2199 0.7634 0.892 0.088 0.000 0.000 0.020 0.000
#> GSM1233062 1 0.6481 -0.1326 0.356 0.308 0.000 0.016 0.320 0.000
#> GSM1233075 3 0.4131 0.3927 0.000 0.356 0.624 0.000 0.000 0.020
#> GSM1233078 3 0.0865 0.8158 0.000 0.000 0.964 0.000 0.000 0.036
#> GSM1233079 3 0.3606 0.7564 0.084 0.020 0.832 0.000 0.012 0.052
#> GSM1233082 1 0.1434 0.7647 0.940 0.012 0.000 0.000 0.048 0.000
#> GSM1233083 6 0.4818 0.4772 0.004 0.008 0.040 0.168 0.048 0.732
#> GSM1233091 1 0.5171 0.5894 0.668 0.144 0.000 0.000 0.020 0.168
#> GSM1233095 6 0.5760 0.4369 0.200 0.012 0.012 0.012 0.128 0.636
#> GSM1233096 1 0.1151 0.7649 0.956 0.012 0.000 0.000 0.032 0.000
#> GSM1233101 6 0.7056 0.1887 0.052 0.024 0.352 0.008 0.120 0.444
#> GSM1233105 4 0.3090 0.7127 0.140 0.000 0.000 0.828 0.028 0.004
#> GSM1233117 2 0.4606 0.5069 0.000 0.748 0.108 0.044 0.100 0.000
#> GSM1233118 3 0.4605 0.5110 0.000 0.296 0.652 0.000 0.036 0.016
#> GSM1233001 2 0.4905 0.4938 0.140 0.688 0.012 0.000 0.000 0.160
#> GSM1233006 4 0.3439 0.6757 0.000 0.072 0.000 0.808 0.000 0.120
#> GSM1233008 2 0.2611 0.5592 0.016 0.876 0.004 0.000 0.096 0.008
#> GSM1233009 5 0.4963 0.3922 0.060 0.392 0.000 0.000 0.544 0.004
#> GSM1233017 2 0.5440 0.1443 0.000 0.576 0.000 0.200 0.224 0.000
#> GSM1233020 2 0.3919 0.4165 0.016 0.708 0.008 0.000 0.000 0.268
#> GSM1233022 4 0.4233 0.5926 0.000 0.088 0.000 0.740 0.168 0.004
#> GSM1233026 5 0.5115 0.4553 0.156 0.008 0.000 0.004 0.668 0.164
#> GSM1233028 5 0.4527 0.5881 0.020 0.164 0.000 0.000 0.732 0.084
#> GSM1233034 1 0.4641 0.2208 0.552 0.404 0.000 0.000 0.000 0.044
#> GSM1233040 1 0.2551 0.7313 0.872 0.012 0.004 0.000 0.108 0.004
#> GSM1233048 1 0.2044 0.7623 0.908 0.076 0.000 0.004 0.008 0.004
#> GSM1233056 4 0.7030 0.3382 0.008 0.016 0.228 0.496 0.048 0.204
#> GSM1233058 6 0.4620 0.0848 0.004 0.032 0.000 0.000 0.420 0.544
#> GSM1233059 1 0.1931 0.7489 0.916 0.008 0.000 0.004 0.068 0.004
#> GSM1233066 3 0.1644 0.8142 0.000 0.040 0.932 0.000 0.028 0.000
#> GSM1233071 1 0.2531 0.7432 0.860 0.128 0.000 0.004 0.008 0.000
#> GSM1233074 2 0.4326 0.3201 0.008 0.608 0.368 0.000 0.000 0.016
#> GSM1233076 6 0.2787 0.5902 0.000 0.016 0.020 0.072 0.012 0.880
#> GSM1233080 1 0.5127 0.6220 0.704 0.012 0.008 0.012 0.100 0.164
#> GSM1233088 1 0.5446 0.3308 0.540 0.120 0.000 0.000 0.004 0.336
#> GSM1233090 1 0.4258 0.6832 0.776 0.016 0.012 0.004 0.144 0.048
#> GSM1233092 4 0.1897 0.7508 0.000 0.004 0.000 0.908 0.004 0.084
#> GSM1233094 4 0.1845 0.7521 0.000 0.028 0.000 0.920 0.052 0.000
#> GSM1233097 5 0.4934 0.2301 0.000 0.040 0.000 0.016 0.568 0.376
#> GSM1233100 1 0.3690 0.7593 0.824 0.080 0.000 0.020 0.068 0.008
#> GSM1233104 5 0.5558 0.4780 0.000 0.096 0.000 0.048 0.632 0.224
#> GSM1233106 1 0.1562 0.7703 0.940 0.032 0.000 0.000 0.024 0.004
#> GSM1233111 1 0.1578 0.7642 0.936 0.012 0.000 0.000 0.048 0.004
#> GSM1233122 2 0.5680 0.3401 0.012 0.592 0.000 0.160 0.004 0.232
#> GSM1233146 4 0.6039 0.4972 0.036 0.016 0.000 0.596 0.240 0.112
#> GSM1232994 5 0.5057 0.3964 0.012 0.404 0.000 0.024 0.544 0.016
#> GSM1232996 2 0.5292 0.1502 0.000 0.560 0.004 0.000 0.104 0.332
#> GSM1232997 2 0.4815 0.4552 0.044 0.692 0.044 0.000 0.000 0.220
#> GSM1232998 6 0.7036 0.3241 0.000 0.224 0.000 0.116 0.196 0.464
#> GSM1232999 6 0.6410 0.2588 0.000 0.296 0.000 0.020 0.252 0.432
#> GSM1233000 2 0.3673 0.5755 0.124 0.808 0.000 0.000 0.024 0.044
#> GSM1233004 6 0.3204 0.5557 0.000 0.052 0.004 0.000 0.112 0.832
#> GSM1233011 6 0.7000 0.1616 0.000 0.048 0.268 0.008 0.264 0.412
#> GSM1233012 2 0.5147 0.0808 0.000 0.512 0.424 0.020 0.044 0.000
#> GSM1233023 2 0.4720 0.4544 0.052 0.692 0.028 0.000 0.000 0.228
#> GSM1233027 6 0.5390 0.5467 0.008 0.180 0.000 0.096 0.040 0.676
#> GSM1233033 4 0.4721 0.6464 0.076 0.016 0.000 0.720 0.180 0.008
#> GSM1233036 5 0.6112 0.1268 0.000 0.332 0.300 0.000 0.368 0.000
#> GSM1233037 2 0.4249 0.1857 0.416 0.568 0.004 0.000 0.000 0.012
#> GSM1233041 1 0.4753 0.6128 0.728 0.020 0.000 0.072 0.168 0.012
#> GSM1233045 6 0.5184 0.1100 0.004 0.076 0.000 0.000 0.420 0.500
#> GSM1233047 3 0.2744 0.7512 0.000 0.144 0.840 0.000 0.016 0.000
#> GSM1233050 1 0.2695 0.7300 0.844 0.144 0.000 0.000 0.008 0.004
#> GSM1233052 1 0.4784 0.3328 0.584 0.028 0.000 0.004 0.372 0.012
#> GSM1233053 3 0.4464 0.7305 0.068 0.100 0.776 0.004 0.048 0.004
#> GSM1233055 6 0.6300 0.3912 0.040 0.012 0.036 0.080 0.212 0.620
#> GSM1233061 3 0.0632 0.8189 0.000 0.024 0.976 0.000 0.000 0.000
#> GSM1233063 5 0.7254 -0.0266 0.368 0.020 0.004 0.072 0.396 0.140
#> GSM1233065 2 0.4874 -0.0575 0.000 0.496 0.008 0.000 0.040 0.456
#> GSM1233070 6 0.5899 0.4246 0.036 0.268 0.000 0.128 0.000 0.568
#> GSM1233077 3 0.4405 0.4050 0.000 0.020 0.604 0.000 0.008 0.368
#> GSM1233081 3 0.0547 0.8182 0.000 0.000 0.980 0.000 0.000 0.020
#> GSM1233084 1 0.6141 0.5474 0.644 0.024 0.008 0.104 0.052 0.168
#> GSM1233087 6 0.4372 0.4357 0.004 0.008 0.000 0.236 0.044 0.708
#> GSM1233089 6 0.4433 0.5279 0.000 0.200 0.012 0.068 0.000 0.720
#> GSM1233099 5 0.4335 0.5529 0.000 0.016 0.000 0.096 0.752 0.136
#> GSM1233112 4 0.4438 0.4984 0.000 0.000 0.020 0.640 0.016 0.324
#> GSM1233085 3 0.0146 0.8202 0.000 0.004 0.996 0.000 0.000 0.000
#> GSM1233098 6 0.6080 0.0652 0.056 0.440 0.004 0.056 0.004 0.440
#> GSM1233114 5 0.3767 0.5973 0.004 0.040 0.000 0.152 0.792 0.012
#> GSM1233119 5 0.4302 0.5476 0.000 0.000 0.000 0.116 0.728 0.156
#> GSM1233129 2 0.3663 0.5535 0.000 0.776 0.180 0.000 0.040 0.004
#> GSM1233132 5 0.3691 0.6185 0.020 0.044 0.000 0.120 0.812 0.004
#> GSM1233139 2 0.4426 0.2228 0.028 0.664 0.004 0.008 0.296 0.000
#> GSM1233143 2 0.6706 0.1970 0.000 0.480 0.288 0.084 0.148 0.000
#> GSM1233145 4 0.1074 0.7665 0.000 0.000 0.000 0.960 0.012 0.028
#> GSM1233067 3 0.3210 0.7208 0.000 0.168 0.804 0.000 0.028 0.000
#> GSM1233069 3 0.3073 0.7276 0.000 0.016 0.816 0.000 0.004 0.164
#> GSM1233072 4 0.5614 0.2999 0.000 0.328 0.000 0.540 0.012 0.120
#> GSM1233086 5 0.5549 0.3367 0.000 0.036 0.080 0.000 0.588 0.296
#> GSM1233102 4 0.2462 0.7340 0.000 0.000 0.000 0.876 0.096 0.028
#> GSM1233103 5 0.4355 0.5865 0.176 0.076 0.000 0.012 0.736 0.000
#> GSM1233107 5 0.4465 0.5988 0.000 0.144 0.000 0.144 0.712 0.000
#> GSM1233108 3 0.1820 0.8041 0.000 0.012 0.924 0.000 0.008 0.056
#> GSM1233109 3 0.3025 0.7338 0.000 0.004 0.820 0.004 0.008 0.164
#> GSM1233110 3 0.0146 0.8201 0.000 0.004 0.996 0.000 0.000 0.000
#> GSM1233113 2 0.4761 0.5181 0.000 0.688 0.212 0.000 0.012 0.088
#> GSM1233116 3 0.2245 0.8127 0.000 0.040 0.908 0.000 0.036 0.016
#> GSM1233120 5 0.5641 0.2705 0.004 0.000 0.000 0.144 0.512 0.340
#> GSM1233121 3 0.3852 0.5118 0.000 0.012 0.664 0.000 0.000 0.324
#> GSM1233123 3 0.0000 0.8199 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233124 3 0.2956 0.7685 0.000 0.088 0.848 0.000 0.064 0.000
#> GSM1233125 3 0.2809 0.7869 0.008 0.016 0.880 0.000 0.064 0.032
#> GSM1233126 4 0.0603 0.7643 0.000 0.000 0.000 0.980 0.016 0.004
#> GSM1233127 5 0.4599 0.6040 0.000 0.192 0.000 0.104 0.700 0.004
#> GSM1233128 3 0.9035 -0.0758 0.096 0.020 0.292 0.164 0.208 0.220
#> GSM1233130 3 0.3429 0.6367 0.000 0.004 0.740 0.000 0.004 0.252
#> GSM1233131 5 0.3852 0.5755 0.080 0.000 0.000 0.108 0.796 0.016
#> GSM1233133 3 0.0146 0.8202 0.000 0.004 0.996 0.000 0.000 0.000
#> GSM1233134 3 0.2872 0.7557 0.000 0.140 0.836 0.000 0.024 0.000
#> GSM1233135 3 0.0547 0.8193 0.000 0.020 0.980 0.000 0.000 0.000
#> GSM1233136 6 0.3982 0.5609 0.000 0.052 0.124 0.016 0.012 0.796
#> GSM1233137 3 0.1563 0.8071 0.000 0.056 0.932 0.000 0.012 0.000
#> GSM1233138 4 0.1082 0.7626 0.000 0.004 0.000 0.956 0.040 0.000
#> GSM1233140 3 0.3753 0.7547 0.036 0.016 0.824 0.012 0.104 0.008
#> GSM1233141 5 0.4488 0.3876 0.000 0.420 0.000 0.032 0.548 0.000
#> GSM1233142 5 0.4412 0.5720 0.000 0.256 0.000 0.048 0.688 0.008
#> GSM1233144 3 0.0146 0.8201 0.000 0.004 0.996 0.000 0.000 0.000
#> GSM1233147 6 0.3683 0.5752 0.000 0.040 0.024 0.108 0.008 0.820
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> CV:NMF 152 1.22e-03 0.4169 0.01874 2
#> CV:NMF 70 5.13e-03 0.0261 0.00104 3
#> CV:NMF 116 4.34e-06 0.0978 0.03117 4
#> CV:NMF 99 6.29e-06 0.0215 0.00195 5
#> CV:NMF 94 5.52e-06 0.0524 0.02997 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 51941 rows and 156 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 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.339 0.785 0.881 0.4100 0.587 0.587
#> 3 3 0.300 0.628 0.777 0.2781 0.949 0.914
#> 4 4 0.321 0.494 0.678 0.1992 0.763 0.574
#> 5 5 0.354 0.484 0.684 0.1010 0.918 0.772
#> 6 6 0.400 0.487 0.694 0.0308 0.975 0.920
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0000 0.87572 0.000 1.000
#> GSM1233002 2 0.6343 0.81743 0.160 0.840
#> GSM1233003 1 0.5519 0.81419 0.872 0.128
#> GSM1233014 2 0.2948 0.87259 0.052 0.948
#> GSM1233015 1 0.4690 0.83170 0.900 0.100
#> GSM1233016 2 0.9552 0.46203 0.376 0.624
#> GSM1233024 2 0.0938 0.87665 0.012 0.988
#> GSM1233049 1 0.0000 0.81487 1.000 0.000
#> GSM1233064 2 0.1184 0.87710 0.016 0.984
#> GSM1233068 2 0.8386 0.69303 0.268 0.732
#> GSM1233073 2 0.7950 0.73917 0.240 0.760
#> GSM1233093 1 0.0000 0.81487 1.000 0.000
#> GSM1233115 1 0.8555 0.68125 0.720 0.280
#> GSM1232992 2 0.0000 0.87572 0.000 1.000
#> GSM1232993 2 0.4022 0.86467 0.080 0.920
#> GSM1233005 2 0.0000 0.87572 0.000 1.000
#> GSM1233007 2 0.2603 0.87488 0.044 0.956
#> GSM1233010 2 0.7376 0.76881 0.208 0.792
#> GSM1233013 2 0.0000 0.87572 0.000 1.000
#> GSM1233018 2 0.0000 0.87572 0.000 1.000
#> GSM1233019 2 0.0376 0.87658 0.004 0.996
#> GSM1233021 2 0.0000 0.87572 0.000 1.000
#> GSM1233025 2 0.9286 0.54544 0.344 0.656
#> GSM1233029 2 0.0938 0.87665 0.012 0.988
#> GSM1233030 2 0.0000 0.87572 0.000 1.000
#> GSM1233031 2 0.5294 0.84796 0.120 0.880
#> GSM1233032 1 0.4431 0.83514 0.908 0.092
#> GSM1233035 2 0.5408 0.83873 0.124 0.876
#> GSM1233038 1 0.1414 0.82477 0.980 0.020
#> GSM1233039 2 0.1184 0.87710 0.016 0.984
#> GSM1233042 2 0.5946 0.82766 0.144 0.856
#> GSM1233043 2 0.5946 0.82766 0.144 0.856
#> GSM1233044 2 0.8144 0.71938 0.252 0.748
#> GSM1233046 2 0.8661 0.65137 0.288 0.712
#> GSM1233051 1 0.7815 0.74397 0.768 0.232
#> GSM1233054 1 0.8327 0.71280 0.736 0.264
#> GSM1233057 2 0.3431 0.86983 0.064 0.936
#> GSM1233060 2 0.5946 0.82766 0.144 0.856
#> GSM1233062 2 0.0938 0.87665 0.012 0.988
#> GSM1233075 2 0.0000 0.87572 0.000 1.000
#> GSM1233078 2 0.7376 0.75992 0.208 0.792
#> GSM1233079 1 0.6887 0.78505 0.816 0.184
#> GSM1233082 2 0.9988 -0.00861 0.480 0.520
#> GSM1233083 1 0.4022 0.83270 0.920 0.080
#> GSM1233091 2 0.6623 0.81333 0.172 0.828
#> GSM1233095 1 0.1184 0.82412 0.984 0.016
#> GSM1233096 1 0.4562 0.83247 0.904 0.096
#> GSM1233101 1 0.2043 0.83076 0.968 0.032
#> GSM1233105 1 0.9954 0.17772 0.540 0.460
#> GSM1233117 2 0.0000 0.87572 0.000 1.000
#> GSM1233118 2 0.0376 0.87593 0.004 0.996
#> GSM1233001 2 0.0000 0.87572 0.000 1.000
#> GSM1233006 2 0.0376 0.87658 0.004 0.996
#> GSM1233008 2 0.0376 0.87607 0.004 0.996
#> GSM1233009 2 0.0000 0.87572 0.000 1.000
#> GSM1233017 2 0.0376 0.87657 0.004 0.996
#> GSM1233020 2 0.0000 0.87572 0.000 1.000
#> GSM1233022 2 0.3114 0.87208 0.056 0.944
#> GSM1233026 2 0.7883 0.73034 0.236 0.764
#> GSM1233028 2 0.6531 0.81784 0.168 0.832
#> GSM1233034 2 0.0376 0.87580 0.004 0.996
#> GSM1233040 1 0.3274 0.83589 0.940 0.060
#> GSM1233048 1 0.2603 0.83419 0.956 0.044
#> GSM1233056 1 0.0000 0.81487 1.000 0.000
#> GSM1233058 2 0.6973 0.79286 0.188 0.812
#> GSM1233059 1 0.1843 0.82924 0.972 0.028
#> GSM1233066 2 0.3274 0.86461 0.060 0.940
#> GSM1233071 2 0.2948 0.87209 0.052 0.948
#> GSM1233074 2 0.0000 0.87572 0.000 1.000
#> GSM1233076 2 0.4022 0.86534 0.080 0.920
#> GSM1233080 1 0.0000 0.81487 1.000 0.000
#> GSM1233088 2 0.1633 0.87729 0.024 0.976
#> GSM1233090 1 0.0000 0.81487 1.000 0.000
#> GSM1233092 2 0.7299 0.77912 0.204 0.796
#> GSM1233094 2 0.5178 0.84752 0.116 0.884
#> GSM1233097 2 0.6048 0.82962 0.148 0.852
#> GSM1233100 2 0.6801 0.80168 0.180 0.820
#> GSM1233104 2 0.5059 0.85048 0.112 0.888
#> GSM1233106 1 0.8763 0.66949 0.704 0.296
#> GSM1233111 1 0.3274 0.83589 0.940 0.060
#> GSM1233122 2 0.0376 0.87658 0.004 0.996
#> GSM1233146 2 0.6148 0.82321 0.152 0.848
#> GSM1232994 2 0.0000 0.87572 0.000 1.000
#> GSM1232996 2 0.0000 0.87572 0.000 1.000
#> GSM1232997 2 0.0376 0.87643 0.004 0.996
#> GSM1232998 2 0.2778 0.87267 0.048 0.952
#> GSM1232999 2 0.0376 0.87658 0.004 0.996
#> GSM1233000 2 0.0000 0.87572 0.000 1.000
#> GSM1233004 1 0.9491 0.52024 0.632 0.368
#> GSM1233011 2 0.5946 0.83219 0.144 0.856
#> GSM1233012 2 0.0000 0.87572 0.000 1.000
#> GSM1233023 2 0.0000 0.87572 0.000 1.000
#> GSM1233027 2 0.0376 0.87658 0.004 0.996
#> GSM1233033 1 0.4690 0.82587 0.900 0.100
#> GSM1233036 2 0.3114 0.87234 0.056 0.944
#> GSM1233037 2 0.3733 0.86752 0.072 0.928
#> GSM1233041 1 0.0376 0.81741 0.996 0.004
#> GSM1233045 2 0.6438 0.81604 0.164 0.836
#> GSM1233047 1 0.9248 0.59115 0.660 0.340
#> GSM1233050 1 0.2236 0.83182 0.964 0.036
#> GSM1233052 2 0.8763 0.64027 0.296 0.704
#> GSM1233053 1 0.8327 0.71280 0.736 0.264
#> GSM1233055 1 0.0000 0.81487 1.000 0.000
#> GSM1233061 2 0.4298 0.85627 0.088 0.912
#> GSM1233063 1 0.4431 0.83508 0.908 0.092
#> GSM1233065 2 0.0000 0.87572 0.000 1.000
#> GSM1233070 2 0.0672 0.87689 0.008 0.992
#> GSM1233077 2 0.6973 0.78047 0.188 0.812
#> GSM1233081 1 0.7602 0.75574 0.780 0.220
#> GSM1233084 1 0.0376 0.81741 0.996 0.004
#> GSM1233087 1 0.9850 0.33224 0.572 0.428
#> GSM1233089 2 0.0376 0.87658 0.004 0.996
#> GSM1233099 2 0.8955 0.60728 0.312 0.688
#> GSM1233112 1 0.4815 0.83090 0.896 0.104
#> GSM1233085 1 0.9358 0.56638 0.648 0.352
#> GSM1233098 2 0.0376 0.87658 0.004 0.996
#> GSM1233114 2 0.8608 0.65357 0.284 0.716
#> GSM1233119 2 0.9209 0.56103 0.336 0.664
#> GSM1233129 2 0.0376 0.87593 0.004 0.996
#> GSM1233132 2 0.8861 0.61638 0.304 0.696
#> GSM1233139 2 0.0376 0.87657 0.004 0.996
#> GSM1233143 2 0.0000 0.87572 0.000 1.000
#> GSM1233145 1 0.3733 0.83580 0.928 0.072
#> GSM1233067 2 0.0000 0.87572 0.000 1.000
#> GSM1233069 2 0.6343 0.81012 0.160 0.840
#> GSM1233072 2 0.0376 0.87658 0.004 0.996
#> GSM1233086 2 0.3274 0.86796 0.060 0.940
#> GSM1233102 2 0.9491 0.48449 0.368 0.632
#> GSM1233103 2 0.8763 0.63441 0.296 0.704
#> GSM1233107 2 0.7602 0.74916 0.220 0.780
#> GSM1233108 1 0.6973 0.78216 0.812 0.188
#> GSM1233109 1 0.9710 0.42388 0.600 0.400
#> GSM1233110 2 0.8081 0.70736 0.248 0.752
#> GSM1233113 2 0.0000 0.87572 0.000 1.000
#> GSM1233116 2 0.0000 0.87572 0.000 1.000
#> GSM1233120 2 0.9286 0.53924 0.344 0.656
#> GSM1233121 2 0.6887 0.78520 0.184 0.816
#> GSM1233123 2 0.6343 0.81460 0.160 0.840
#> GSM1233124 2 0.3584 0.86773 0.068 0.932
#> GSM1233125 1 0.5408 0.82452 0.876 0.124
#> GSM1233126 2 0.9044 0.59544 0.320 0.680
#> GSM1233127 2 0.0000 0.87572 0.000 1.000
#> GSM1233128 1 0.2043 0.83082 0.968 0.032
#> GSM1233130 2 0.7139 0.76872 0.196 0.804
#> GSM1233131 2 0.8763 0.63441 0.296 0.704
#> GSM1233133 1 0.9896 0.31611 0.560 0.440
#> GSM1233134 2 0.2043 0.87515 0.032 0.968
#> GSM1233135 2 0.0000 0.87572 0.000 1.000
#> GSM1233136 2 0.7056 0.77407 0.192 0.808
#> GSM1233137 1 0.9323 0.57387 0.652 0.348
#> GSM1233138 2 0.9000 0.60383 0.316 0.684
#> GSM1233140 1 0.3879 0.83694 0.924 0.076
#> GSM1233141 2 0.0000 0.87572 0.000 1.000
#> GSM1233142 2 0.0000 0.87572 0.000 1.000
#> GSM1233144 1 0.9922 0.28813 0.552 0.448
#> GSM1233147 2 0.3879 0.86690 0.076 0.924
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.1015 0.8050 0.012 0.980 0.008
#> GSM1233002 2 0.5690 0.7055 0.288 0.708 0.004
#> GSM1233003 1 0.8199 0.1115 0.488 0.072 0.440
#> GSM1233014 2 0.3482 0.7946 0.128 0.872 0.000
#> GSM1233015 1 0.5763 0.3291 0.716 0.008 0.276
#> GSM1233016 2 0.8355 0.3525 0.408 0.508 0.084
#> GSM1233024 2 0.1643 0.8118 0.044 0.956 0.000
#> GSM1233049 3 0.1529 0.6875 0.040 0.000 0.960
#> GSM1233064 2 0.2400 0.8121 0.064 0.932 0.004
#> GSM1233068 2 0.7368 0.5650 0.352 0.604 0.044
#> GSM1233073 2 0.7107 0.6111 0.340 0.624 0.036
#> GSM1233093 3 0.1643 0.6891 0.044 0.000 0.956
#> GSM1233115 1 0.8520 0.3963 0.588 0.132 0.280
#> GSM1232992 2 0.0592 0.8100 0.012 0.988 0.000
#> GSM1232993 2 0.4235 0.7818 0.176 0.824 0.000
#> GSM1233005 2 0.0592 0.8100 0.012 0.988 0.000
#> GSM1233007 2 0.3267 0.8062 0.116 0.884 0.000
#> GSM1233010 2 0.6026 0.6128 0.376 0.624 0.000
#> GSM1233013 2 0.1015 0.8050 0.012 0.980 0.008
#> GSM1233018 2 0.1315 0.8070 0.020 0.972 0.008
#> GSM1233019 2 0.1289 0.8116 0.032 0.968 0.000
#> GSM1233021 2 0.0747 0.8103 0.016 0.984 0.000
#> GSM1233025 2 0.7382 0.3874 0.456 0.512 0.032
#> GSM1233029 2 0.1411 0.8123 0.036 0.964 0.000
#> GSM1233030 2 0.1170 0.8058 0.016 0.976 0.008
#> GSM1233031 2 0.5156 0.7571 0.216 0.776 0.008
#> GSM1233032 1 0.7084 0.2923 0.628 0.036 0.336
#> GSM1233035 2 0.5503 0.7511 0.208 0.772 0.020
#> GSM1233038 3 0.4452 0.6492 0.192 0.000 0.808
#> GSM1233039 2 0.2400 0.8121 0.064 0.932 0.004
#> GSM1233042 2 0.5404 0.7261 0.256 0.740 0.004
#> GSM1233043 2 0.5404 0.7261 0.256 0.740 0.004
#> GSM1233044 2 0.6994 0.5922 0.360 0.612 0.028
#> GSM1233046 2 0.7610 0.4861 0.388 0.564 0.048
#> GSM1233051 1 0.7814 0.4815 0.652 0.104 0.244
#> GSM1233054 1 0.6222 0.4994 0.776 0.092 0.132
#> GSM1233057 2 0.4099 0.7922 0.140 0.852 0.008
#> GSM1233060 2 0.5365 0.7287 0.252 0.744 0.004
#> GSM1233062 2 0.1753 0.8118 0.048 0.952 0.000
#> GSM1233075 2 0.1453 0.8063 0.024 0.968 0.008
#> GSM1233078 2 0.6318 0.5789 0.356 0.636 0.008
#> GSM1233079 1 0.6714 0.3546 0.672 0.032 0.296
#> GSM1233082 1 0.8792 0.2096 0.492 0.392 0.116
#> GSM1233083 3 0.6653 0.5042 0.288 0.032 0.680
#> GSM1233091 2 0.6161 0.7016 0.288 0.696 0.016
#> GSM1233095 3 0.5058 0.6614 0.244 0.000 0.756
#> GSM1233096 1 0.5623 0.3198 0.716 0.004 0.280
#> GSM1233101 3 0.5553 0.6319 0.272 0.004 0.724
#> GSM1233105 1 0.9028 0.3811 0.540 0.292 0.168
#> GSM1233117 2 0.1015 0.8050 0.012 0.980 0.008
#> GSM1233118 2 0.1170 0.8054 0.016 0.976 0.008
#> GSM1233001 2 0.1170 0.8049 0.016 0.976 0.008
#> GSM1233006 2 0.1964 0.8115 0.056 0.944 0.000
#> GSM1233008 2 0.1267 0.8112 0.024 0.972 0.004
#> GSM1233009 2 0.1170 0.8061 0.016 0.976 0.008
#> GSM1233017 2 0.1411 0.8127 0.036 0.964 0.000
#> GSM1233020 2 0.1015 0.8050 0.012 0.980 0.008
#> GSM1233022 2 0.3686 0.7941 0.140 0.860 0.000
#> GSM1233026 2 0.6154 0.5470 0.408 0.592 0.000
#> GSM1233028 2 0.5754 0.7095 0.296 0.700 0.004
#> GSM1233034 2 0.1399 0.8077 0.028 0.968 0.004
#> GSM1233040 1 0.5982 0.2414 0.668 0.004 0.328
#> GSM1233048 1 0.6518 -0.2280 0.512 0.004 0.484
#> GSM1233056 3 0.1163 0.6840 0.028 0.000 0.972
#> GSM1233058 2 0.6081 0.6513 0.344 0.652 0.004
#> GSM1233059 3 0.6008 0.5169 0.372 0.000 0.628
#> GSM1233066 2 0.3349 0.7968 0.108 0.888 0.004
#> GSM1233071 2 0.3826 0.8025 0.124 0.868 0.008
#> GSM1233074 2 0.1453 0.8063 0.024 0.968 0.008
#> GSM1233076 2 0.4293 0.7899 0.164 0.832 0.004
#> GSM1233080 3 0.3412 0.7003 0.124 0.000 0.876
#> GSM1233088 2 0.2772 0.8120 0.080 0.916 0.004
#> GSM1233090 3 0.4002 0.6965 0.160 0.000 0.840
#> GSM1233092 2 0.6420 0.6783 0.288 0.688 0.024
#> GSM1233094 2 0.4931 0.7496 0.232 0.768 0.000
#> GSM1233097 2 0.5553 0.7240 0.272 0.724 0.004
#> GSM1233100 2 0.6255 0.6676 0.320 0.668 0.012
#> GSM1233104 2 0.4702 0.7605 0.212 0.788 0.000
#> GSM1233106 1 0.8726 0.4811 0.592 0.196 0.212
#> GSM1233111 1 0.5982 0.2414 0.668 0.004 0.328
#> GSM1233122 2 0.1964 0.8115 0.056 0.944 0.000
#> GSM1233146 2 0.5623 0.7126 0.280 0.716 0.004
#> GSM1232994 2 0.0747 0.8081 0.016 0.984 0.000
#> GSM1232996 2 0.1315 0.8070 0.020 0.972 0.008
#> GSM1232997 2 0.1647 0.8105 0.036 0.960 0.004
#> GSM1232998 2 0.3412 0.7948 0.124 0.876 0.000
#> GSM1232999 2 0.1031 0.8114 0.024 0.976 0.000
#> GSM1233000 2 0.1170 0.8061 0.016 0.976 0.008
#> GSM1233004 1 0.9084 0.4061 0.552 0.216 0.232
#> GSM1233011 2 0.4842 0.7570 0.224 0.776 0.000
#> GSM1233012 2 0.1015 0.8050 0.012 0.980 0.008
#> GSM1233023 2 0.1585 0.8069 0.028 0.964 0.008
#> GSM1233027 2 0.0892 0.8109 0.020 0.980 0.000
#> GSM1233033 3 0.7920 -0.0248 0.468 0.056 0.476
#> GSM1233036 2 0.3267 0.8086 0.116 0.884 0.000
#> GSM1233037 2 0.4228 0.7889 0.148 0.844 0.008
#> GSM1233041 3 0.5810 0.5767 0.336 0.000 0.664
#> GSM1233045 2 0.5873 0.6877 0.312 0.684 0.004
#> GSM1233047 1 0.6561 0.5218 0.756 0.144 0.100
#> GSM1233050 3 0.6518 0.2623 0.484 0.004 0.512
#> GSM1233052 2 0.7337 0.4508 0.428 0.540 0.032
#> GSM1233053 1 0.6222 0.4994 0.776 0.092 0.132
#> GSM1233055 3 0.1031 0.6838 0.024 0.000 0.976
#> GSM1233061 2 0.4514 0.7767 0.156 0.832 0.012
#> GSM1233063 1 0.6702 0.2827 0.648 0.024 0.328
#> GSM1233065 2 0.1711 0.8076 0.032 0.960 0.008
#> GSM1233070 2 0.2066 0.8124 0.060 0.940 0.000
#> GSM1233077 2 0.6104 0.6009 0.348 0.648 0.004
#> GSM1233081 1 0.7053 0.4415 0.692 0.064 0.244
#> GSM1233084 3 0.5760 0.6033 0.328 0.000 0.672
#> GSM1233087 1 0.9911 0.2969 0.400 0.296 0.304
#> GSM1233089 2 0.1878 0.8125 0.044 0.952 0.004
#> GSM1233099 2 0.7283 0.3825 0.460 0.512 0.028
#> GSM1233112 3 0.6843 0.4081 0.332 0.028 0.640
#> GSM1233085 1 0.6605 0.5211 0.752 0.152 0.096
#> GSM1233098 2 0.1411 0.8118 0.036 0.964 0.000
#> GSM1233114 2 0.7248 0.4285 0.436 0.536 0.028
#> GSM1233119 2 0.7169 0.4069 0.456 0.520 0.024
#> GSM1233129 2 0.1525 0.8084 0.032 0.964 0.004
#> GSM1233132 2 0.7283 0.3704 0.460 0.512 0.028
#> GSM1233139 2 0.1315 0.8073 0.020 0.972 0.008
#> GSM1233143 2 0.1015 0.8050 0.012 0.980 0.008
#> GSM1233145 3 0.6172 0.4952 0.308 0.012 0.680
#> GSM1233067 2 0.1015 0.8050 0.012 0.980 0.008
#> GSM1233069 2 0.5785 0.6630 0.300 0.696 0.004
#> GSM1233072 2 0.1964 0.8115 0.056 0.944 0.000
#> GSM1233086 2 0.3349 0.8032 0.108 0.888 0.004
#> GSM1233102 2 0.8141 0.2671 0.460 0.472 0.068
#> GSM1233103 2 0.7049 0.4157 0.452 0.528 0.020
#> GSM1233107 2 0.6584 0.5679 0.380 0.608 0.012
#> GSM1233108 1 0.6684 0.3568 0.676 0.032 0.292
#> GSM1233109 1 0.7772 0.4806 0.672 0.196 0.132
#> GSM1233110 2 0.6647 0.4980 0.396 0.592 0.012
#> GSM1233113 2 0.1170 0.8049 0.016 0.976 0.008
#> GSM1233116 2 0.1585 0.8051 0.028 0.964 0.008
#> GSM1233120 2 0.7839 0.3065 0.464 0.484 0.052
#> GSM1233121 2 0.6081 0.6079 0.344 0.652 0.004
#> GSM1233123 2 0.5919 0.6833 0.276 0.712 0.012
#> GSM1233124 2 0.3715 0.7959 0.128 0.868 0.004
#> GSM1233125 1 0.7787 0.3325 0.588 0.064 0.348
#> GSM1233126 2 0.7464 0.4808 0.400 0.560 0.040
#> GSM1233127 2 0.1015 0.8050 0.012 0.980 0.008
#> GSM1233128 1 0.6168 0.0556 0.588 0.000 0.412
#> GSM1233130 2 0.6275 0.5895 0.348 0.644 0.008
#> GSM1233131 2 0.7054 0.4104 0.456 0.524 0.020
#> GSM1233133 1 0.7184 0.4817 0.688 0.240 0.072
#> GSM1233134 2 0.3295 0.7975 0.096 0.896 0.008
#> GSM1233135 2 0.1170 0.8049 0.016 0.976 0.008
#> GSM1233136 2 0.6252 0.5970 0.344 0.648 0.008
#> GSM1233137 1 0.6349 0.5201 0.764 0.156 0.080
#> GSM1233138 2 0.7366 0.4887 0.400 0.564 0.036
#> GSM1233140 1 0.6696 0.2535 0.632 0.020 0.348
#> GSM1233141 2 0.1015 0.8050 0.012 0.980 0.008
#> GSM1233142 2 0.1015 0.8050 0.012 0.980 0.008
#> GSM1233144 1 0.7259 0.4760 0.680 0.248 0.072
#> GSM1233147 2 0.4293 0.7909 0.164 0.832 0.004
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.1302 0.717088 0.000 0.956 0.000 0.044
#> GSM1233002 4 0.5650 0.444829 0.000 0.432 0.024 0.544
#> GSM1233003 3 0.8716 0.126361 0.352 0.040 0.364 0.244
#> GSM1233014 2 0.4761 0.279223 0.000 0.628 0.000 0.372
#> GSM1233015 3 0.6449 0.504529 0.152 0.000 0.644 0.204
#> GSM1233016 4 0.6891 0.594649 0.036 0.248 0.080 0.636
#> GSM1233024 2 0.4018 0.624293 0.000 0.772 0.004 0.224
#> GSM1233049 1 0.1610 0.650379 0.952 0.000 0.032 0.016
#> GSM1233064 2 0.3335 0.693474 0.000 0.856 0.016 0.128
#> GSM1233068 4 0.7278 0.558436 0.012 0.364 0.112 0.512
#> GSM1233073 4 0.6102 0.598194 0.008 0.324 0.048 0.620
#> GSM1233093 1 0.0927 0.651273 0.976 0.000 0.016 0.008
#> GSM1233115 4 0.8530 -0.490372 0.188 0.044 0.344 0.424
#> GSM1232992 2 0.3444 0.669426 0.000 0.816 0.000 0.184
#> GSM1232993 2 0.5300 0.135942 0.000 0.580 0.012 0.408
#> GSM1233005 2 0.3444 0.669426 0.000 0.816 0.000 0.184
#> GSM1233007 2 0.5088 0.495387 0.000 0.688 0.024 0.288
#> GSM1233010 4 0.7002 0.456453 0.000 0.388 0.120 0.492
#> GSM1233013 2 0.1716 0.714771 0.000 0.936 0.000 0.064
#> GSM1233018 2 0.2345 0.715475 0.000 0.900 0.000 0.100
#> GSM1233019 2 0.3688 0.639773 0.000 0.792 0.000 0.208
#> GSM1233021 2 0.3219 0.687759 0.000 0.836 0.000 0.164
#> GSM1233025 4 0.6831 0.608430 0.012 0.260 0.112 0.616
#> GSM1233029 2 0.3945 0.639041 0.000 0.780 0.004 0.216
#> GSM1233030 2 0.1792 0.714113 0.000 0.932 0.000 0.068
#> GSM1233031 2 0.6198 -0.000205 0.008 0.560 0.040 0.392
#> GSM1233032 3 0.7072 0.484755 0.212 0.020 0.624 0.144
#> GSM1233035 2 0.6236 -0.028272 0.012 0.560 0.036 0.392
#> GSM1233038 1 0.5180 0.601710 0.740 0.000 0.064 0.196
#> GSM1233039 2 0.3443 0.690480 0.000 0.848 0.016 0.136
#> GSM1233042 4 0.5500 0.364562 0.000 0.464 0.016 0.520
#> GSM1233043 4 0.5500 0.364562 0.000 0.464 0.016 0.520
#> GSM1233044 4 0.7347 0.532018 0.012 0.376 0.116 0.496
#> GSM1233046 4 0.7029 0.620140 0.020 0.284 0.100 0.596
#> GSM1233051 3 0.8041 0.439795 0.132 0.044 0.504 0.320
#> GSM1233054 3 0.5219 0.498820 0.048 0.036 0.784 0.132
#> GSM1233057 2 0.4300 0.585203 0.000 0.820 0.092 0.088
#> GSM1233060 4 0.5399 0.356117 0.000 0.468 0.012 0.520
#> GSM1233062 2 0.4122 0.607175 0.000 0.760 0.004 0.236
#> GSM1233075 2 0.0657 0.703131 0.000 0.984 0.004 0.012
#> GSM1233078 2 0.7330 0.012847 0.000 0.512 0.184 0.304
#> GSM1233079 3 0.7464 0.370396 0.208 0.000 0.496 0.296
#> GSM1233082 4 0.8859 0.259433 0.060 0.236 0.276 0.428
#> GSM1233083 1 0.6595 0.495422 0.604 0.000 0.120 0.276
#> GSM1233091 4 0.6609 0.422874 0.004 0.440 0.068 0.488
#> GSM1233095 1 0.5809 0.542832 0.692 0.000 0.216 0.092
#> GSM1233096 3 0.6457 0.502261 0.156 0.000 0.644 0.200
#> GSM1233101 1 0.6396 0.484242 0.644 0.004 0.248 0.104
#> GSM1233105 4 0.7734 0.170195 0.088 0.096 0.212 0.604
#> GSM1233117 2 0.1302 0.717088 0.000 0.956 0.000 0.044
#> GSM1233118 2 0.1004 0.715457 0.000 0.972 0.004 0.024
#> GSM1233001 2 0.0188 0.704877 0.000 0.996 0.000 0.004
#> GSM1233006 2 0.4049 0.621917 0.000 0.780 0.008 0.212
#> GSM1233008 2 0.2530 0.717144 0.000 0.896 0.004 0.100
#> GSM1233009 2 0.2334 0.708289 0.000 0.908 0.004 0.088
#> GSM1233017 2 0.2760 0.708667 0.000 0.872 0.000 0.128
#> GSM1233020 2 0.1716 0.714771 0.000 0.936 0.000 0.064
#> GSM1233022 2 0.4661 0.369608 0.000 0.652 0.000 0.348
#> GSM1233026 4 0.7325 0.442577 0.000 0.368 0.160 0.472
#> GSM1233028 4 0.5921 0.412280 0.000 0.448 0.036 0.516
#> GSM1233034 2 0.1576 0.719185 0.000 0.948 0.004 0.048
#> GSM1233040 3 0.6407 0.466312 0.204 0.000 0.648 0.148
#> GSM1233048 3 0.6988 0.168457 0.380 0.000 0.500 0.120
#> GSM1233056 1 0.0804 0.646977 0.980 0.000 0.008 0.012
#> GSM1233058 4 0.6686 0.479655 0.000 0.388 0.092 0.520
#> GSM1233059 1 0.6561 0.289947 0.564 0.000 0.344 0.092
#> GSM1233066 2 0.4964 0.613021 0.000 0.764 0.068 0.168
#> GSM1233071 2 0.4839 0.541316 0.004 0.724 0.016 0.256
#> GSM1233074 2 0.0657 0.703131 0.000 0.984 0.004 0.012
#> GSM1233076 2 0.5678 0.410158 0.000 0.640 0.044 0.316
#> GSM1233080 1 0.3523 0.645413 0.856 0.000 0.112 0.032
#> GSM1233088 2 0.3278 0.695345 0.000 0.864 0.020 0.116
#> GSM1233090 1 0.4105 0.625591 0.812 0.000 0.156 0.032
#> GSM1233092 4 0.5773 0.401479 0.008 0.440 0.016 0.536
#> GSM1233094 4 0.4985 0.325457 0.000 0.468 0.000 0.532
#> GSM1233097 4 0.5564 0.409091 0.000 0.436 0.020 0.544
#> GSM1233100 4 0.5467 0.545771 0.000 0.364 0.024 0.612
#> GSM1233104 2 0.5281 -0.148564 0.000 0.528 0.008 0.464
#> GSM1233106 3 0.8738 0.429574 0.120 0.124 0.496 0.260
#> GSM1233111 3 0.6407 0.466312 0.204 0.000 0.648 0.148
#> GSM1233122 2 0.4086 0.618837 0.000 0.776 0.008 0.216
#> GSM1233146 4 0.5576 0.420689 0.000 0.444 0.020 0.536
#> GSM1232994 2 0.2469 0.713242 0.000 0.892 0.000 0.108
#> GSM1232996 2 0.2408 0.714103 0.000 0.896 0.000 0.104
#> GSM1232997 2 0.1576 0.711597 0.000 0.948 0.004 0.048
#> GSM1232998 2 0.4746 0.287294 0.000 0.632 0.000 0.368
#> GSM1232999 2 0.3801 0.635877 0.000 0.780 0.000 0.220
#> GSM1233000 2 0.2408 0.710503 0.000 0.896 0.000 0.104
#> GSM1233004 4 0.9227 -0.285252 0.168 0.116 0.312 0.404
#> GSM1233011 2 0.6309 0.131178 0.000 0.588 0.076 0.336
#> GSM1233012 2 0.0895 0.715543 0.000 0.976 0.004 0.020
#> GSM1233023 2 0.0895 0.706010 0.000 0.976 0.004 0.020
#> GSM1233027 2 0.3528 0.663325 0.000 0.808 0.000 0.192
#> GSM1233033 1 0.8390 -0.096383 0.392 0.024 0.352 0.232
#> GSM1233036 2 0.4904 0.579853 0.000 0.744 0.040 0.216
#> GSM1233037 2 0.4424 0.574240 0.000 0.812 0.100 0.088
#> GSM1233041 1 0.6367 0.350414 0.584 0.000 0.336 0.080
#> GSM1233045 4 0.6575 0.443146 0.000 0.412 0.080 0.508
#> GSM1233047 3 0.5937 0.494131 0.024 0.068 0.720 0.188
#> GSM1233050 3 0.6895 0.080903 0.400 0.000 0.492 0.108
#> GSM1233052 4 0.6554 0.628540 0.008 0.268 0.096 0.628
#> GSM1233053 3 0.5219 0.498820 0.048 0.036 0.784 0.132
#> GSM1233055 1 0.1297 0.653777 0.964 0.000 0.020 0.016
#> GSM1233061 2 0.5452 0.551695 0.000 0.736 0.108 0.156
#> GSM1233063 3 0.7141 0.468674 0.208 0.012 0.604 0.176
#> GSM1233065 2 0.2342 0.716943 0.000 0.912 0.008 0.080
#> GSM1233070 2 0.4248 0.612979 0.000 0.768 0.012 0.220
#> GSM1233077 2 0.7268 0.021367 0.000 0.516 0.172 0.312
#> GSM1233081 3 0.7442 0.449971 0.156 0.020 0.576 0.248
#> GSM1233084 1 0.6280 0.412270 0.604 0.000 0.316 0.080
#> GSM1233087 4 0.8876 0.227561 0.236 0.152 0.120 0.492
#> GSM1233089 2 0.3448 0.663782 0.000 0.828 0.004 0.168
#> GSM1233099 4 0.5279 0.632290 0.008 0.196 0.052 0.744
#> GSM1233112 1 0.7222 0.417792 0.528 0.000 0.172 0.300
#> GSM1233085 3 0.6095 0.492433 0.024 0.080 0.712 0.184
#> GSM1233098 2 0.2921 0.686063 0.000 0.860 0.000 0.140
#> GSM1233114 4 0.5610 0.628135 0.008 0.208 0.064 0.720
#> GSM1233119 4 0.6990 0.587297 0.008 0.284 0.124 0.584
#> GSM1233129 2 0.0927 0.710011 0.000 0.976 0.008 0.016
#> GSM1233132 4 0.5519 0.622471 0.008 0.184 0.072 0.736
#> GSM1233139 2 0.2334 0.707482 0.000 0.908 0.004 0.088
#> GSM1233143 2 0.0524 0.709102 0.000 0.988 0.004 0.008
#> GSM1233145 1 0.6603 0.475324 0.572 0.000 0.100 0.328
#> GSM1233067 2 0.0188 0.707573 0.000 0.996 0.000 0.004
#> GSM1233069 2 0.6836 0.163664 0.000 0.580 0.140 0.280
#> GSM1233072 2 0.3972 0.630116 0.000 0.788 0.008 0.204
#> GSM1233086 2 0.4996 0.606702 0.000 0.752 0.056 0.192
#> GSM1233102 4 0.6005 0.612267 0.032 0.176 0.068 0.724
#> GSM1233103 4 0.6181 0.629527 0.008 0.216 0.096 0.680
#> GSM1233107 4 0.5921 0.603931 0.004 0.288 0.056 0.652
#> GSM1233108 3 0.7468 0.364504 0.204 0.000 0.492 0.304
#> GSM1233109 3 0.8297 0.339478 0.076 0.096 0.432 0.396
#> GSM1233110 2 0.7606 -0.069890 0.000 0.476 0.248 0.276
#> GSM1233113 2 0.0000 0.706787 0.000 1.000 0.000 0.000
#> GSM1233116 2 0.1256 0.711518 0.000 0.964 0.008 0.028
#> GSM1233120 4 0.5665 0.624035 0.028 0.180 0.052 0.740
#> GSM1233121 2 0.7250 0.022686 0.000 0.516 0.168 0.316
#> GSM1233123 2 0.6798 0.215956 0.000 0.604 0.172 0.224
#> GSM1233124 2 0.5412 0.573359 0.000 0.736 0.096 0.168
#> GSM1233125 3 0.8059 0.460684 0.232 0.052 0.552 0.164
#> GSM1233126 4 0.6024 0.583425 0.012 0.300 0.044 0.644
#> GSM1233127 2 0.1302 0.714887 0.000 0.956 0.000 0.044
#> GSM1233128 3 0.7086 0.329469 0.292 0.000 0.548 0.160
#> GSM1233130 2 0.7268 0.035889 0.000 0.516 0.172 0.312
#> GSM1233131 4 0.6147 0.628717 0.008 0.212 0.096 0.684
#> GSM1233133 3 0.7143 0.430141 0.016 0.152 0.608 0.224
#> GSM1233134 2 0.3037 0.644812 0.000 0.888 0.076 0.036
#> GSM1233135 2 0.0188 0.709224 0.000 0.996 0.000 0.004
#> GSM1233136 2 0.7221 0.055599 0.000 0.524 0.168 0.308
#> GSM1233137 3 0.5693 0.484030 0.012 0.080 0.732 0.176
#> GSM1233138 4 0.6046 0.580794 0.012 0.304 0.044 0.640
#> GSM1233140 3 0.7043 0.470701 0.216 0.016 0.620 0.148
#> GSM1233141 2 0.1389 0.715211 0.000 0.952 0.000 0.048
#> GSM1233142 2 0.1302 0.714887 0.000 0.956 0.000 0.044
#> GSM1233144 3 0.7230 0.421630 0.016 0.164 0.600 0.220
#> GSM1233147 2 0.5678 0.405910 0.000 0.640 0.044 0.316
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.1768 0.6905 0.000 0.924 0.004 0.072 0.000
#> GSM1233002 4 0.4482 0.6019 0.004 0.252 0.032 0.712 0.000
#> GSM1233003 1 0.7521 0.3934 0.548 0.012 0.092 0.180 0.168
#> GSM1233014 4 0.4702 0.1831 0.000 0.432 0.016 0.552 0.000
#> GSM1233015 1 0.2733 0.5468 0.872 0.000 0.012 0.112 0.004
#> GSM1233016 4 0.7227 0.5682 0.068 0.132 0.116 0.624 0.060
#> GSM1233024 2 0.4298 0.4769 0.000 0.640 0.008 0.352 0.000
#> GSM1233049 5 0.2740 0.6594 0.096 0.000 0.028 0.000 0.876
#> GSM1233064 2 0.3454 0.6627 0.000 0.816 0.028 0.156 0.000
#> GSM1233068 4 0.6578 0.6111 0.096 0.224 0.064 0.612 0.004
#> GSM1233073 4 0.4836 0.6613 0.032 0.156 0.036 0.764 0.012
#> GSM1233093 5 0.2389 0.6580 0.116 0.000 0.004 0.000 0.880
#> GSM1233115 3 0.7964 0.2283 0.256 0.008 0.440 0.216 0.080
#> GSM1232992 2 0.3816 0.5677 0.000 0.696 0.000 0.304 0.000
#> GSM1232993 4 0.4730 0.2252 0.004 0.416 0.012 0.568 0.000
#> GSM1233005 2 0.3837 0.5634 0.000 0.692 0.000 0.308 0.000
#> GSM1233007 2 0.5524 0.2527 0.008 0.536 0.040 0.412 0.004
#> GSM1233010 4 0.7241 0.5102 0.076 0.268 0.140 0.516 0.000
#> GSM1233013 2 0.2389 0.6812 0.000 0.880 0.004 0.116 0.000
#> GSM1233018 2 0.3196 0.6710 0.000 0.804 0.004 0.192 0.000
#> GSM1233019 2 0.4151 0.5002 0.000 0.652 0.004 0.344 0.000
#> GSM1233021 2 0.3661 0.6073 0.000 0.724 0.000 0.276 0.000
#> GSM1233025 4 0.7332 0.5575 0.072 0.132 0.172 0.592 0.032
#> GSM1233029 2 0.4183 0.5260 0.000 0.668 0.008 0.324 0.000
#> GSM1233030 2 0.2230 0.6823 0.000 0.884 0.000 0.116 0.000
#> GSM1233031 4 0.6099 0.2594 0.028 0.416 0.060 0.496 0.000
#> GSM1233032 1 0.4734 0.5007 0.776 0.000 0.116 0.056 0.052
#> GSM1233035 4 0.5779 0.1486 0.036 0.456 0.028 0.480 0.000
#> GSM1233038 5 0.6257 0.5723 0.116 0.000 0.104 0.116 0.664
#> GSM1233039 2 0.3574 0.6573 0.000 0.804 0.028 0.168 0.000
#> GSM1233042 4 0.4138 0.5705 0.000 0.276 0.016 0.708 0.000
#> GSM1233043 4 0.4138 0.5705 0.000 0.276 0.016 0.708 0.000
#> GSM1233044 4 0.6917 0.5982 0.096 0.248 0.092 0.564 0.000
#> GSM1233046 4 0.5854 0.6177 0.080 0.124 0.064 0.716 0.016
#> GSM1233051 1 0.6964 0.1374 0.572 0.016 0.224 0.156 0.032
#> GSM1233054 1 0.6192 -0.2926 0.456 0.004 0.456 0.060 0.024
#> GSM1233057 2 0.4372 0.5790 0.020 0.800 0.104 0.072 0.004
#> GSM1233060 4 0.4161 0.5673 0.000 0.280 0.016 0.704 0.000
#> GSM1233062 2 0.4354 0.4418 0.000 0.624 0.008 0.368 0.000
#> GSM1233075 2 0.0798 0.6784 0.000 0.976 0.016 0.008 0.000
#> GSM1233078 2 0.7619 0.1258 0.040 0.440 0.256 0.256 0.008
#> GSM1233079 3 0.7516 0.1773 0.392 0.000 0.396 0.104 0.108
#> GSM1233082 4 0.7799 0.1416 0.336 0.148 0.092 0.420 0.004
#> GSM1233083 5 0.7094 0.4848 0.104 0.000 0.200 0.128 0.568
#> GSM1233091 4 0.6295 0.5462 0.040 0.296 0.084 0.580 0.000
#> GSM1233095 5 0.6487 0.4883 0.268 0.000 0.192 0.008 0.532
#> GSM1233096 1 0.2681 0.5510 0.876 0.000 0.012 0.108 0.004
#> GSM1233101 5 0.7118 0.4435 0.268 0.004 0.216 0.024 0.488
#> GSM1233105 4 0.7035 0.1439 0.232 0.016 0.100 0.584 0.068
#> GSM1233117 2 0.1768 0.6905 0.000 0.924 0.004 0.072 0.000
#> GSM1233118 2 0.1894 0.6961 0.000 0.920 0.008 0.072 0.000
#> GSM1233001 2 0.0162 0.6785 0.000 0.996 0.000 0.004 0.000
#> GSM1233006 2 0.4416 0.4528 0.000 0.632 0.012 0.356 0.000
#> GSM1233008 2 0.3462 0.6584 0.000 0.792 0.012 0.196 0.000
#> GSM1233009 2 0.2470 0.6773 0.000 0.884 0.012 0.104 0.000
#> GSM1233017 2 0.3003 0.6652 0.000 0.812 0.000 0.188 0.000
#> GSM1233020 2 0.2389 0.6812 0.000 0.880 0.004 0.116 0.000
#> GSM1233022 2 0.4803 0.0307 0.004 0.496 0.012 0.488 0.000
#> GSM1233026 4 0.7744 0.4625 0.096 0.252 0.192 0.460 0.000
#> GSM1233028 4 0.5727 0.5664 0.028 0.288 0.060 0.624 0.000
#> GSM1233034 2 0.1956 0.6958 0.000 0.916 0.008 0.076 0.000
#> GSM1233040 1 0.1764 0.5750 0.928 0.000 0.000 0.064 0.008
#> GSM1233048 1 0.4946 0.4892 0.700 0.000 0.008 0.060 0.232
#> GSM1233056 5 0.2136 0.6604 0.088 0.000 0.008 0.000 0.904
#> GSM1233058 4 0.6839 0.5471 0.064 0.260 0.116 0.560 0.000
#> GSM1233059 1 0.5184 0.1384 0.556 0.000 0.004 0.036 0.404
#> GSM1233066 2 0.5672 0.5550 0.024 0.668 0.096 0.212 0.000
#> GSM1233071 2 0.4947 0.4640 0.008 0.644 0.032 0.316 0.000
#> GSM1233074 2 0.0798 0.6784 0.000 0.976 0.016 0.008 0.000
#> GSM1233076 2 0.6388 0.1747 0.020 0.496 0.068 0.404 0.012
#> GSM1233080 5 0.4480 0.6162 0.220 0.000 0.044 0.004 0.732
#> GSM1233088 2 0.3409 0.6668 0.000 0.824 0.032 0.144 0.000
#> GSM1233090 5 0.4513 0.5619 0.284 0.000 0.024 0.004 0.688
#> GSM1233092 4 0.6046 0.5459 0.032 0.272 0.064 0.624 0.008
#> GSM1233094 4 0.4039 0.5639 0.004 0.268 0.008 0.720 0.000
#> GSM1233097 4 0.4952 0.5819 0.012 0.268 0.040 0.680 0.000
#> GSM1233100 4 0.3982 0.6493 0.012 0.172 0.020 0.792 0.004
#> GSM1233104 4 0.4972 0.4471 0.004 0.352 0.032 0.612 0.000
#> GSM1233106 1 0.6324 0.2229 0.636 0.084 0.060 0.216 0.004
#> GSM1233111 1 0.1764 0.5750 0.928 0.000 0.000 0.064 0.008
#> GSM1233122 2 0.4402 0.4627 0.000 0.636 0.012 0.352 0.000
#> GSM1233146 4 0.4479 0.5917 0.004 0.264 0.028 0.704 0.000
#> GSM1232994 2 0.2690 0.6745 0.000 0.844 0.000 0.156 0.000
#> GSM1232996 2 0.3231 0.6686 0.000 0.800 0.004 0.196 0.000
#> GSM1232997 2 0.2006 0.6892 0.000 0.916 0.012 0.072 0.000
#> GSM1232998 4 0.4617 0.1771 0.000 0.436 0.012 0.552 0.000
#> GSM1232999 2 0.4101 0.4570 0.000 0.628 0.000 0.372 0.000
#> GSM1233000 2 0.2674 0.6732 0.000 0.856 0.004 0.140 0.000
#> GSM1233004 3 0.8501 0.2701 0.176 0.048 0.440 0.252 0.084
#> GSM1233011 2 0.6700 -0.1222 0.040 0.448 0.096 0.416 0.000
#> GSM1233012 2 0.1251 0.6910 0.000 0.956 0.008 0.036 0.000
#> GSM1233023 2 0.1168 0.6850 0.000 0.960 0.008 0.032 0.000
#> GSM1233027 2 0.3876 0.5535 0.000 0.684 0.000 0.316 0.000
#> GSM1233033 1 0.7433 0.3826 0.544 0.008 0.084 0.164 0.200
#> GSM1233036 2 0.5201 0.4631 0.016 0.636 0.036 0.312 0.000
#> GSM1233037 2 0.4546 0.5702 0.028 0.792 0.104 0.072 0.004
#> GSM1233041 1 0.5399 0.1262 0.524 0.000 0.024 0.020 0.432
#> GSM1233045 4 0.6663 0.5348 0.052 0.276 0.108 0.564 0.000
#> GSM1233047 3 0.6871 0.3963 0.340 0.036 0.516 0.096 0.012
#> GSM1233050 1 0.5121 0.4499 0.692 0.000 0.024 0.044 0.240
#> GSM1233052 4 0.5746 0.6080 0.104 0.128 0.048 0.712 0.008
#> GSM1233053 3 0.6192 0.1854 0.456 0.004 0.456 0.060 0.024
#> GSM1233055 5 0.3267 0.6719 0.112 0.000 0.044 0.000 0.844
#> GSM1233061 2 0.5916 0.5444 0.028 0.672 0.128 0.168 0.004
#> GSM1233063 1 0.4291 0.5620 0.808 0.004 0.048 0.108 0.032
#> GSM1233065 2 0.2915 0.6928 0.000 0.860 0.024 0.116 0.000
#> GSM1233070 2 0.4387 0.4763 0.000 0.640 0.012 0.348 0.000
#> GSM1233077 2 0.7544 0.1368 0.036 0.448 0.252 0.256 0.008
#> GSM1233081 3 0.7564 0.2903 0.392 0.012 0.416 0.100 0.080
#> GSM1233084 1 0.5804 -0.0341 0.492 0.000 0.048 0.020 0.440
#> GSM1233087 4 0.8827 0.0942 0.096 0.072 0.196 0.432 0.204
#> GSM1233089 2 0.4025 0.5435 0.000 0.700 0.008 0.292 0.000
#> GSM1233099 4 0.3195 0.5577 0.052 0.016 0.040 0.880 0.012
#> GSM1233112 5 0.7381 0.4136 0.072 0.000 0.316 0.144 0.468
#> GSM1233085 3 0.6903 0.4063 0.328 0.040 0.524 0.096 0.012
#> GSM1233098 2 0.3395 0.6113 0.000 0.764 0.000 0.236 0.000
#> GSM1233114 4 0.3783 0.5580 0.056 0.028 0.060 0.848 0.008
#> GSM1233119 4 0.7749 0.5552 0.084 0.168 0.168 0.548 0.032
#> GSM1233129 2 0.1522 0.6902 0.000 0.944 0.012 0.044 0.000
#> GSM1233132 4 0.3362 0.5268 0.060 0.008 0.060 0.864 0.008
#> GSM1233139 2 0.2522 0.6752 0.000 0.880 0.012 0.108 0.000
#> GSM1233143 2 0.0992 0.6855 0.000 0.968 0.008 0.024 0.000
#> GSM1233145 5 0.7605 0.4442 0.120 0.000 0.192 0.180 0.508
#> GSM1233067 2 0.0566 0.6824 0.000 0.984 0.004 0.012 0.000
#> GSM1233069 2 0.7107 0.2475 0.032 0.516 0.220 0.228 0.004
#> GSM1233072 2 0.4356 0.4799 0.000 0.648 0.012 0.340 0.000
#> GSM1233086 2 0.5497 0.5202 0.016 0.652 0.072 0.260 0.000
#> GSM1233102 4 0.3884 0.5176 0.048 0.008 0.060 0.844 0.040
#> GSM1233103 4 0.4442 0.5686 0.088 0.052 0.060 0.800 0.000
#> GSM1233107 4 0.4522 0.6241 0.040 0.116 0.056 0.788 0.000
#> GSM1233108 3 0.7477 0.1904 0.376 0.000 0.416 0.104 0.104
#> GSM1233109 3 0.8401 0.3549 0.244 0.068 0.428 0.220 0.040
#> GSM1233110 2 0.8107 0.0603 0.084 0.408 0.264 0.236 0.008
#> GSM1233113 2 0.0451 0.6804 0.000 0.988 0.004 0.008 0.000
#> GSM1233116 2 0.1661 0.6905 0.000 0.940 0.024 0.036 0.000
#> GSM1233120 4 0.3629 0.5371 0.052 0.012 0.044 0.860 0.032
#> GSM1233121 2 0.7494 0.1372 0.032 0.448 0.252 0.260 0.008
#> GSM1233123 2 0.7027 0.3189 0.048 0.556 0.216 0.176 0.004
#> GSM1233124 2 0.5875 0.5361 0.036 0.660 0.096 0.208 0.000
#> GSM1233125 1 0.5904 0.4463 0.688 0.028 0.196 0.052 0.036
#> GSM1233126 4 0.6496 0.6106 0.036 0.164 0.104 0.660 0.036
#> GSM1233127 2 0.2144 0.6859 0.000 0.912 0.020 0.068 0.000
#> GSM1233128 1 0.5090 0.5472 0.752 0.000 0.112 0.048 0.088
#> GSM1233130 2 0.7620 0.1489 0.044 0.452 0.240 0.256 0.008
#> GSM1233131 4 0.4437 0.5695 0.088 0.048 0.064 0.800 0.000
#> GSM1233133 3 0.7886 0.4502 0.272 0.100 0.464 0.156 0.008
#> GSM1233134 2 0.3399 0.6405 0.024 0.864 0.072 0.036 0.004
#> GSM1233135 2 0.0671 0.6841 0.000 0.980 0.004 0.016 0.000
#> GSM1233136 2 0.7546 0.1647 0.040 0.460 0.240 0.252 0.008
#> GSM1233137 3 0.7106 0.3693 0.348 0.044 0.496 0.096 0.016
#> GSM1233138 4 0.6530 0.6100 0.036 0.168 0.104 0.656 0.036
#> GSM1233140 1 0.4286 0.5467 0.804 0.000 0.104 0.060 0.032
#> GSM1233141 2 0.2236 0.6855 0.000 0.908 0.024 0.068 0.000
#> GSM1233142 2 0.2144 0.6859 0.000 0.912 0.020 0.068 0.000
#> GSM1233144 3 0.7973 0.4446 0.268 0.108 0.456 0.160 0.008
#> GSM1233147 2 0.6310 0.1697 0.016 0.496 0.068 0.408 0.012
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.1700 0.6820 0.000 0.916 0.000 0.080 0.000 0.004
#> GSM1233002 4 0.4127 0.5921 0.000 0.236 0.004 0.716 0.000 0.044
#> GSM1233003 5 0.7169 0.3927 0.160 0.012 0.020 0.132 0.548 0.128
#> GSM1233014 4 0.4317 0.2334 0.000 0.408 0.004 0.572 0.000 0.016
#> GSM1233015 5 0.2022 0.6295 0.000 0.000 0.024 0.052 0.916 0.008
#> GSM1233016 4 0.6751 0.5039 0.020 0.124 0.056 0.604 0.032 0.164
#> GSM1233024 2 0.4034 0.4384 0.000 0.624 0.004 0.364 0.000 0.008
#> GSM1233049 1 0.1692 0.6502 0.932 0.000 0.048 0.000 0.008 0.012
#> GSM1233064 2 0.3488 0.6442 0.000 0.800 0.012 0.160 0.000 0.028
#> GSM1233068 4 0.6375 0.5943 0.000 0.212 0.020 0.592 0.104 0.072
#> GSM1233073 4 0.4479 0.6451 0.004 0.148 0.012 0.764 0.032 0.040
#> GSM1233093 1 0.1268 0.6533 0.952 0.000 0.004 0.000 0.036 0.008
#> GSM1233115 6 0.6044 0.5500 0.012 0.004 0.032 0.164 0.172 0.616
#> GSM1232992 2 0.3601 0.5417 0.000 0.684 0.000 0.312 0.000 0.004
#> GSM1232993 4 0.4269 0.2573 0.000 0.404 0.004 0.580 0.004 0.008
#> GSM1233005 2 0.3619 0.5371 0.000 0.680 0.000 0.316 0.000 0.004
#> GSM1233007 2 0.5244 0.1872 0.000 0.512 0.020 0.416 0.000 0.052
#> GSM1233010 4 0.6877 0.5073 0.000 0.236 0.020 0.504 0.052 0.188
#> GSM1233013 2 0.2191 0.6704 0.000 0.876 0.000 0.120 0.000 0.004
#> GSM1233018 2 0.3043 0.6566 0.000 0.792 0.000 0.200 0.000 0.008
#> GSM1233019 2 0.3887 0.4614 0.000 0.632 0.000 0.360 0.000 0.008
#> GSM1233021 2 0.3448 0.5876 0.000 0.716 0.000 0.280 0.000 0.004
#> GSM1233025 4 0.6195 0.4697 0.012 0.112 0.016 0.564 0.016 0.280
#> GSM1233029 2 0.3925 0.4947 0.000 0.656 0.004 0.332 0.000 0.008
#> GSM1233030 2 0.2048 0.6727 0.000 0.880 0.000 0.120 0.000 0.000
#> GSM1233031 4 0.5707 0.2833 0.000 0.404 0.004 0.492 0.024 0.076
#> GSM1233032 5 0.4653 0.5676 0.040 0.000 0.164 0.020 0.744 0.032
#> GSM1233035 4 0.5646 0.1529 0.000 0.448 0.024 0.468 0.040 0.020
#> GSM1233038 1 0.6401 0.5053 0.604 0.000 0.036 0.096 0.064 0.200
#> GSM1233039 2 0.3593 0.6374 0.000 0.788 0.012 0.172 0.000 0.028
#> GSM1233042 4 0.3927 0.5647 0.000 0.260 0.004 0.712 0.000 0.024
#> GSM1233043 4 0.3927 0.5647 0.000 0.260 0.004 0.712 0.000 0.024
#> GSM1233044 4 0.6833 0.5905 0.000 0.216 0.036 0.548 0.060 0.140
#> GSM1233046 4 0.5867 0.5917 0.016 0.120 0.068 0.696 0.064 0.036
#> GSM1233051 5 0.6034 0.0942 0.004 0.012 0.016 0.108 0.536 0.324
#> GSM1233054 3 0.4077 0.6451 0.012 0.004 0.748 0.024 0.208 0.004
#> GSM1233057 2 0.3708 0.5741 0.000 0.800 0.136 0.052 0.008 0.004
#> GSM1233060 4 0.3950 0.5614 0.000 0.264 0.004 0.708 0.000 0.024
#> GSM1233062 2 0.4079 0.3999 0.000 0.608 0.004 0.380 0.000 0.008
#> GSM1233075 2 0.0717 0.6712 0.000 0.976 0.016 0.008 0.000 0.000
#> GSM1233078 2 0.7484 0.0896 0.000 0.404 0.124 0.220 0.008 0.244
#> GSM1233079 6 0.7133 0.4359 0.032 0.000 0.144 0.064 0.288 0.472
#> GSM1233082 4 0.7421 0.1060 0.000 0.144 0.036 0.388 0.356 0.076
#> GSM1233083 1 0.7029 0.2749 0.428 0.000 0.048 0.112 0.044 0.368
#> GSM1233091 4 0.6001 0.5401 0.000 0.284 0.024 0.580 0.032 0.080
#> GSM1233095 1 0.6256 0.4679 0.508 0.000 0.020 0.008 0.168 0.296
#> GSM1233096 5 0.1957 0.6313 0.000 0.000 0.024 0.048 0.920 0.008
#> GSM1233101 1 0.6545 0.3881 0.460 0.004 0.008 0.020 0.184 0.324
#> GSM1233105 4 0.7092 0.0627 0.028 0.016 0.068 0.548 0.212 0.128
#> GSM1233117 2 0.1644 0.6808 0.000 0.920 0.000 0.076 0.000 0.004
#> GSM1233118 2 0.1802 0.6882 0.000 0.916 0.000 0.072 0.000 0.012
#> GSM1233001 2 0.0146 0.6714 0.000 0.996 0.000 0.004 0.000 0.000
#> GSM1233006 2 0.4302 0.4046 0.000 0.608 0.004 0.368 0.000 0.020
#> GSM1233008 2 0.3345 0.6403 0.000 0.776 0.000 0.204 0.000 0.020
#> GSM1233009 2 0.2266 0.6680 0.000 0.880 0.012 0.108 0.000 0.000
#> GSM1233017 2 0.2762 0.6498 0.000 0.804 0.000 0.196 0.000 0.000
#> GSM1233020 2 0.2191 0.6704 0.000 0.876 0.000 0.120 0.000 0.004
#> GSM1233022 4 0.4394 -0.0133 0.000 0.484 0.004 0.496 0.000 0.016
#> GSM1233026 4 0.7210 0.4543 0.000 0.212 0.024 0.444 0.056 0.264
#> GSM1233028 4 0.5293 0.5648 0.000 0.264 0.008 0.632 0.016 0.080
#> GSM1233034 2 0.1812 0.6877 0.000 0.912 0.008 0.080 0.000 0.000
#> GSM1233040 5 0.0881 0.6428 0.008 0.000 0.012 0.008 0.972 0.000
#> GSM1233048 5 0.4450 0.5323 0.216 0.000 0.016 0.016 0.724 0.028
#> GSM1233056 1 0.1167 0.6550 0.960 0.000 0.012 0.000 0.008 0.020
#> GSM1233058 4 0.6476 0.5431 0.000 0.232 0.016 0.552 0.044 0.156
#> GSM1233059 5 0.4262 0.2195 0.424 0.000 0.004 0.000 0.560 0.012
#> GSM1233066 2 0.5696 0.5150 0.000 0.640 0.064 0.216 0.008 0.072
#> GSM1233071 2 0.4777 0.4316 0.000 0.632 0.032 0.316 0.008 0.012
#> GSM1233074 2 0.0717 0.6712 0.000 0.976 0.016 0.008 0.000 0.000
#> GSM1233076 2 0.5927 0.1000 0.000 0.472 0.020 0.396 0.004 0.108
#> GSM1233080 1 0.4765 0.6145 0.720 0.000 0.016 0.004 0.144 0.116
#> GSM1233088 2 0.3468 0.6499 0.000 0.808 0.016 0.148 0.000 0.028
#> GSM1233090 1 0.5013 0.5644 0.684 0.000 0.020 0.004 0.204 0.088
#> GSM1233092 4 0.5421 0.5372 0.004 0.256 0.028 0.628 0.000 0.084
#> GSM1233094 4 0.3470 0.5642 0.000 0.248 0.000 0.740 0.000 0.012
#> GSM1233097 4 0.4550 0.5790 0.000 0.248 0.008 0.692 0.008 0.044
#> GSM1233100 4 0.3811 0.6346 0.000 0.160 0.008 0.788 0.012 0.032
#> GSM1233104 4 0.4569 0.4635 0.000 0.332 0.008 0.624 0.000 0.036
#> GSM1233106 5 0.5994 0.3528 0.000 0.084 0.060 0.176 0.648 0.032
#> GSM1233111 5 0.0881 0.6428 0.008 0.000 0.012 0.008 0.972 0.000
#> GSM1233122 2 0.4290 0.4159 0.000 0.612 0.004 0.364 0.000 0.020
#> GSM1233146 4 0.4038 0.5856 0.000 0.244 0.000 0.712 0.000 0.044
#> GSM1232994 2 0.2491 0.6613 0.000 0.836 0.000 0.164 0.000 0.000
#> GSM1232996 2 0.3073 0.6539 0.000 0.788 0.000 0.204 0.000 0.008
#> GSM1232997 2 0.1951 0.6804 0.000 0.908 0.016 0.076 0.000 0.000
#> GSM1232998 4 0.4192 0.2282 0.000 0.412 0.000 0.572 0.000 0.016
#> GSM1232999 2 0.3872 0.4090 0.000 0.604 0.000 0.392 0.000 0.004
#> GSM1233000 2 0.2442 0.6625 0.000 0.852 0.004 0.144 0.000 0.000
#> GSM1233004 6 0.5742 0.4852 0.008 0.016 0.028 0.212 0.088 0.648
#> GSM1233011 4 0.6143 0.1812 0.000 0.412 0.004 0.420 0.016 0.148
#> GSM1233012 2 0.1334 0.6821 0.000 0.948 0.020 0.032 0.000 0.000
#> GSM1233023 2 0.1124 0.6776 0.000 0.956 0.008 0.036 0.000 0.000
#> GSM1233027 2 0.3652 0.5265 0.000 0.672 0.000 0.324 0.000 0.004
#> GSM1233033 5 0.7026 0.4138 0.196 0.008 0.016 0.128 0.544 0.108
#> GSM1233036 2 0.4948 0.4017 0.000 0.612 0.004 0.324 0.012 0.048
#> GSM1233037 2 0.3845 0.5660 0.000 0.792 0.140 0.052 0.012 0.004
#> GSM1233041 5 0.4580 0.2517 0.440 0.000 0.004 0.000 0.528 0.028
#> GSM1233045 4 0.6315 0.5353 0.000 0.248 0.016 0.560 0.036 0.140
#> GSM1233047 3 0.4358 0.7055 0.000 0.016 0.784 0.036 0.104 0.060
#> GSM1233050 5 0.4524 0.4983 0.228 0.000 0.020 0.004 0.708 0.040
#> GSM1233052 4 0.5657 0.5705 0.000 0.120 0.020 0.684 0.112 0.064
#> GSM1233053 3 0.4077 0.6451 0.012 0.004 0.748 0.024 0.208 0.004
#> GSM1233055 1 0.2586 0.6627 0.880 0.000 0.008 0.000 0.032 0.080
#> GSM1233061 2 0.5940 0.5072 0.000 0.640 0.120 0.156 0.008 0.076
#> GSM1233063 5 0.3839 0.6246 0.024 0.000 0.016 0.056 0.820 0.084
#> GSM1233065 2 0.2933 0.6818 0.000 0.848 0.012 0.120 0.000 0.020
#> GSM1233070 2 0.4303 0.4295 0.000 0.616 0.008 0.360 0.000 0.016
#> GSM1233077 2 0.7407 0.0920 0.000 0.408 0.108 0.224 0.008 0.252
#> GSM1233081 3 0.7462 -0.0914 0.016 0.008 0.388 0.064 0.204 0.320
#> GSM1233084 5 0.5383 0.0672 0.440 0.000 0.012 0.000 0.472 0.076
#> GSM1233087 4 0.7730 -0.0868 0.092 0.060 0.040 0.424 0.044 0.340
#> GSM1233089 2 0.3784 0.5031 0.000 0.680 0.000 0.308 0.000 0.012
#> GSM1233099 4 0.3313 0.5065 0.004 0.004 0.032 0.856 0.044 0.060
#> GSM1233112 6 0.6525 -0.2632 0.260 0.000 0.112 0.072 0.012 0.544
#> GSM1233085 3 0.4042 0.7020 0.000 0.020 0.812 0.036 0.076 0.056
#> GSM1233098 2 0.3290 0.5819 0.000 0.744 0.000 0.252 0.000 0.004
#> GSM1233114 4 0.3849 0.5133 0.004 0.020 0.056 0.832 0.044 0.044
#> GSM1233119 4 0.6630 0.4697 0.012 0.136 0.016 0.536 0.032 0.268
#> GSM1233129 2 0.1590 0.6825 0.000 0.936 0.008 0.048 0.000 0.008
#> GSM1233132 4 0.3590 0.4841 0.004 0.004 0.056 0.840 0.052 0.044
#> GSM1233139 2 0.2312 0.6657 0.000 0.876 0.012 0.112 0.000 0.000
#> GSM1233143 2 0.1176 0.6766 0.000 0.956 0.020 0.024 0.000 0.000
#> GSM1233145 1 0.7504 0.2486 0.380 0.000 0.056 0.152 0.056 0.356
#> GSM1233067 2 0.0820 0.6750 0.000 0.972 0.016 0.012 0.000 0.000
#> GSM1233069 2 0.7130 0.2033 0.000 0.480 0.108 0.200 0.008 0.204
#> GSM1233072 2 0.4254 0.4326 0.000 0.624 0.004 0.352 0.000 0.020
#> GSM1233086 2 0.5604 0.4588 0.000 0.612 0.024 0.268 0.012 0.084
#> GSM1233102 4 0.3969 0.4627 0.028 0.000 0.036 0.820 0.048 0.068
#> GSM1233103 4 0.4691 0.5236 0.000 0.048 0.056 0.772 0.088 0.036
#> GSM1233107 4 0.4508 0.5798 0.000 0.108 0.056 0.776 0.036 0.024
#> GSM1233108 6 0.6976 0.4609 0.028 0.000 0.148 0.060 0.264 0.500
#> GSM1233109 6 0.7521 0.3991 0.004 0.032 0.168 0.164 0.136 0.496
#> GSM1233110 2 0.7743 0.0297 0.000 0.364 0.212 0.192 0.008 0.224
#> GSM1233113 2 0.0405 0.6716 0.000 0.988 0.008 0.004 0.000 0.000
#> GSM1233116 2 0.2036 0.6831 0.000 0.916 0.008 0.048 0.000 0.028
#> GSM1233120 4 0.3770 0.4837 0.024 0.000 0.036 0.832 0.044 0.064
#> GSM1233121 2 0.7390 0.0917 0.000 0.408 0.104 0.228 0.008 0.252
#> GSM1233123 2 0.6995 0.2702 0.000 0.516 0.144 0.148 0.008 0.184
#> GSM1233124 2 0.5688 0.5105 0.000 0.644 0.108 0.196 0.008 0.044
#> GSM1233125 5 0.5791 0.4780 0.028 0.016 0.104 0.012 0.660 0.180
#> GSM1233126 4 0.5811 0.5517 0.008 0.152 0.052 0.644 0.000 0.144
#> GSM1233127 2 0.2282 0.6742 0.000 0.900 0.020 0.068 0.000 0.012
#> GSM1233128 5 0.4150 0.5855 0.084 0.000 0.004 0.004 0.760 0.148
#> GSM1233130 2 0.7441 0.0894 0.000 0.400 0.096 0.228 0.012 0.264
#> GSM1233131 4 0.4695 0.5252 0.000 0.044 0.056 0.772 0.088 0.040
#> GSM1233133 3 0.6291 0.5314 0.000 0.060 0.640 0.096 0.060 0.144
#> GSM1233134 2 0.2723 0.6229 0.000 0.852 0.128 0.016 0.000 0.004
#> GSM1233135 2 0.1036 0.6787 0.000 0.964 0.008 0.024 0.000 0.004
#> GSM1233136 2 0.7399 0.1008 0.000 0.408 0.092 0.228 0.012 0.260
#> GSM1233137 3 0.2899 0.6961 0.000 0.020 0.872 0.032 0.072 0.004
#> GSM1233138 4 0.5777 0.5532 0.008 0.152 0.052 0.648 0.000 0.140
#> GSM1233140 5 0.4142 0.6026 0.016 0.000 0.084 0.020 0.796 0.084
#> GSM1233141 2 0.2375 0.6737 0.000 0.896 0.020 0.068 0.000 0.016
#> GSM1233142 2 0.2282 0.6742 0.000 0.900 0.020 0.068 0.000 0.012
#> GSM1233144 3 0.6349 0.5142 0.000 0.068 0.636 0.100 0.056 0.140
#> GSM1233147 2 0.5897 0.0940 0.000 0.472 0.020 0.400 0.004 0.104
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> MAD:hclust 148 0.2405 0.513 0.863 2
#> MAD:hclust 111 0.0259 0.713 0.762 3
#> MAD:hclust 87 0.0227 0.077 0.419 4
#> MAD:hclust 96 0.3988 0.604 0.182 5
#> MAD:hclust 97 0.2387 0.817 0.175 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 51941 rows and 156 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'MAD' method.
#> Subgroups are detected by 'kmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.931 0.972 0.4789 0.518 0.518
#> 3 3 0.448 0.560 0.758 0.3643 0.714 0.498
#> 4 4 0.593 0.631 0.810 0.1306 0.831 0.558
#> 5 5 0.648 0.651 0.794 0.0654 0.910 0.680
#> 6 6 0.648 0.482 0.717 0.0396 0.994 0.974
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0000 0.981 0.000 1.000
#> GSM1233002 2 0.9686 0.297 0.396 0.604
#> GSM1233003 1 0.0000 0.956 1.000 0.000
#> GSM1233014 2 0.0000 0.981 0.000 1.000
#> GSM1233015 1 0.0000 0.956 1.000 0.000
#> GSM1233016 2 0.7139 0.740 0.196 0.804
#> GSM1233024 2 0.0000 0.981 0.000 1.000
#> GSM1233049 1 0.0000 0.956 1.000 0.000
#> GSM1233064 2 0.0000 0.981 0.000 1.000
#> GSM1233068 1 0.7745 0.711 0.772 0.228
#> GSM1233073 1 0.9552 0.438 0.624 0.376
#> GSM1233093 1 0.0000 0.956 1.000 0.000
#> GSM1233115 1 0.0000 0.956 1.000 0.000
#> GSM1232992 2 0.0000 0.981 0.000 1.000
#> GSM1232993 2 0.0000 0.981 0.000 1.000
#> GSM1233005 2 0.0000 0.981 0.000 1.000
#> GSM1233007 2 0.0000 0.981 0.000 1.000
#> GSM1233010 1 0.9286 0.510 0.656 0.344
#> GSM1233013 2 0.0000 0.981 0.000 1.000
#> GSM1233018 2 0.0000 0.981 0.000 1.000
#> GSM1233019 2 0.0000 0.981 0.000 1.000
#> GSM1233021 2 0.0000 0.981 0.000 1.000
#> GSM1233025 1 0.0376 0.953 0.996 0.004
#> GSM1233029 2 0.0000 0.981 0.000 1.000
#> GSM1233030 2 0.0000 0.981 0.000 1.000
#> GSM1233031 2 0.0000 0.981 0.000 1.000
#> GSM1233032 1 0.0000 0.956 1.000 0.000
#> GSM1233035 1 0.7602 0.723 0.780 0.220
#> GSM1233038 1 0.0000 0.956 1.000 0.000
#> GSM1233039 2 0.0000 0.981 0.000 1.000
#> GSM1233042 2 0.0000 0.981 0.000 1.000
#> GSM1233043 2 0.0000 0.981 0.000 1.000
#> GSM1233044 1 0.0000 0.956 1.000 0.000
#> GSM1233046 1 0.0000 0.956 1.000 0.000
#> GSM1233051 1 0.0000 0.956 1.000 0.000
#> GSM1233054 1 0.9427 0.477 0.640 0.360
#> GSM1233057 2 0.0000 0.981 0.000 1.000
#> GSM1233060 2 0.0000 0.981 0.000 1.000
#> GSM1233062 2 0.0000 0.981 0.000 1.000
#> GSM1233075 2 0.0000 0.981 0.000 1.000
#> GSM1233078 1 0.9522 0.449 0.628 0.372
#> GSM1233079 1 0.0000 0.956 1.000 0.000
#> GSM1233082 1 0.0376 0.953 0.996 0.004
#> GSM1233083 1 0.0000 0.956 1.000 0.000
#> GSM1233091 2 0.0000 0.981 0.000 1.000
#> GSM1233095 1 0.0000 0.956 1.000 0.000
#> GSM1233096 1 0.0000 0.956 1.000 0.000
#> GSM1233101 1 0.0000 0.956 1.000 0.000
#> GSM1233105 1 0.0000 0.956 1.000 0.000
#> GSM1233117 2 0.0000 0.981 0.000 1.000
#> GSM1233118 2 0.0000 0.981 0.000 1.000
#> GSM1233001 2 0.0000 0.981 0.000 1.000
#> GSM1233006 2 0.0000 0.981 0.000 1.000
#> GSM1233008 2 0.0000 0.981 0.000 1.000
#> GSM1233009 2 0.0000 0.981 0.000 1.000
#> GSM1233017 2 0.0000 0.981 0.000 1.000
#> GSM1233020 2 0.0000 0.981 0.000 1.000
#> GSM1233022 2 0.0000 0.981 0.000 1.000
#> GSM1233026 2 0.0000 0.981 0.000 1.000
#> GSM1233028 2 0.0000 0.981 0.000 1.000
#> GSM1233034 2 0.0000 0.981 0.000 1.000
#> GSM1233040 1 0.0000 0.956 1.000 0.000
#> GSM1233048 1 0.0000 0.956 1.000 0.000
#> GSM1233056 1 0.0000 0.956 1.000 0.000
#> GSM1233058 2 0.0000 0.981 0.000 1.000
#> GSM1233059 1 0.0000 0.956 1.000 0.000
#> GSM1233066 2 0.0000 0.981 0.000 1.000
#> GSM1233071 2 0.0000 0.981 0.000 1.000
#> GSM1233074 2 0.0000 0.981 0.000 1.000
#> GSM1233076 2 0.0000 0.981 0.000 1.000
#> GSM1233080 1 0.0000 0.956 1.000 0.000
#> GSM1233088 2 0.0000 0.981 0.000 1.000
#> GSM1233090 1 0.0000 0.956 1.000 0.000
#> GSM1233092 2 0.0000 0.981 0.000 1.000
#> GSM1233094 2 0.0000 0.981 0.000 1.000
#> GSM1233097 2 0.0000 0.981 0.000 1.000
#> GSM1233100 1 0.9866 0.290 0.568 0.432
#> GSM1233104 2 0.0000 0.981 0.000 1.000
#> GSM1233106 1 0.0000 0.956 1.000 0.000
#> GSM1233111 1 0.0000 0.956 1.000 0.000
#> GSM1233122 2 0.0000 0.981 0.000 1.000
#> GSM1233146 2 0.0000 0.981 0.000 1.000
#> GSM1232994 2 0.0000 0.981 0.000 1.000
#> GSM1232996 2 0.0000 0.981 0.000 1.000
#> GSM1232997 2 0.0000 0.981 0.000 1.000
#> GSM1232998 2 0.0000 0.981 0.000 1.000
#> GSM1232999 2 0.0000 0.981 0.000 1.000
#> GSM1233000 2 0.0000 0.981 0.000 1.000
#> GSM1233004 1 0.8267 0.662 0.740 0.260
#> GSM1233011 2 0.0000 0.981 0.000 1.000
#> GSM1233012 2 0.0000 0.981 0.000 1.000
#> GSM1233023 2 0.0000 0.981 0.000 1.000
#> GSM1233027 2 0.0000 0.981 0.000 1.000
#> GSM1233033 1 0.0000 0.956 1.000 0.000
#> GSM1233036 2 0.0000 0.981 0.000 1.000
#> GSM1233037 2 0.0000 0.981 0.000 1.000
#> GSM1233041 1 0.0000 0.956 1.000 0.000
#> GSM1233045 2 0.0000 0.981 0.000 1.000
#> GSM1233047 1 0.0000 0.956 1.000 0.000
#> GSM1233050 1 0.0000 0.956 1.000 0.000
#> GSM1233052 1 0.0000 0.956 1.000 0.000
#> GSM1233053 1 0.0000 0.956 1.000 0.000
#> GSM1233055 1 0.0000 0.956 1.000 0.000
#> GSM1233061 2 0.1414 0.962 0.020 0.980
#> GSM1233063 1 0.0000 0.956 1.000 0.000
#> GSM1233065 2 0.0000 0.981 0.000 1.000
#> GSM1233070 2 0.0000 0.981 0.000 1.000
#> GSM1233077 2 0.0000 0.981 0.000 1.000
#> GSM1233081 1 0.0000 0.956 1.000 0.000
#> GSM1233084 1 0.0000 0.956 1.000 0.000
#> GSM1233087 1 0.0376 0.953 0.996 0.004
#> GSM1233089 2 0.0000 0.981 0.000 1.000
#> GSM1233099 1 0.0000 0.956 1.000 0.000
#> GSM1233112 1 0.0000 0.956 1.000 0.000
#> GSM1233085 1 0.0000 0.956 1.000 0.000
#> GSM1233098 2 0.0000 0.981 0.000 1.000
#> GSM1233114 1 0.0000 0.956 1.000 0.000
#> GSM1233119 2 0.7745 0.691 0.228 0.772
#> GSM1233129 2 0.0000 0.981 0.000 1.000
#> GSM1233132 1 0.0000 0.956 1.000 0.000
#> GSM1233139 2 0.0000 0.981 0.000 1.000
#> GSM1233143 2 0.0000 0.981 0.000 1.000
#> GSM1233145 1 0.0000 0.956 1.000 0.000
#> GSM1233067 2 0.0000 0.981 0.000 1.000
#> GSM1233069 2 0.0000 0.981 0.000 1.000
#> GSM1233072 2 0.0000 0.981 0.000 1.000
#> GSM1233086 2 0.0000 0.981 0.000 1.000
#> GSM1233102 1 0.0000 0.956 1.000 0.000
#> GSM1233103 2 0.9983 0.022 0.476 0.524
#> GSM1233107 2 0.9393 0.431 0.356 0.644
#> GSM1233108 1 0.0000 0.956 1.000 0.000
#> GSM1233109 1 0.0000 0.956 1.000 0.000
#> GSM1233110 2 0.0938 0.970 0.012 0.988
#> GSM1233113 2 0.0000 0.981 0.000 1.000
#> GSM1233116 2 0.0000 0.981 0.000 1.000
#> GSM1233120 1 0.0000 0.956 1.000 0.000
#> GSM1233121 2 0.0000 0.981 0.000 1.000
#> GSM1233123 2 0.0000 0.981 0.000 1.000
#> GSM1233124 2 0.0000 0.981 0.000 1.000
#> GSM1233125 1 0.0000 0.956 1.000 0.000
#> GSM1233126 2 0.0376 0.977 0.004 0.996
#> GSM1233127 2 0.0000 0.981 0.000 1.000
#> GSM1233128 1 0.0000 0.956 1.000 0.000
#> GSM1233130 2 0.0000 0.981 0.000 1.000
#> GSM1233131 1 0.0000 0.956 1.000 0.000
#> GSM1233133 1 0.0000 0.956 1.000 0.000
#> GSM1233134 2 0.0000 0.981 0.000 1.000
#> GSM1233135 2 0.0000 0.981 0.000 1.000
#> GSM1233136 2 0.0000 0.981 0.000 1.000
#> GSM1233137 1 0.0000 0.956 1.000 0.000
#> GSM1233138 2 0.0000 0.981 0.000 1.000
#> GSM1233140 1 0.0000 0.956 1.000 0.000
#> GSM1233141 2 0.0000 0.981 0.000 1.000
#> GSM1233142 2 0.0000 0.981 0.000 1.000
#> GSM1233144 1 0.0000 0.956 1.000 0.000
#> GSM1233147 2 0.0000 0.981 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.0237 0.7191 0.000 0.996 0.004
#> GSM1233002 3 0.5731 0.6022 0.020 0.228 0.752
#> GSM1233003 1 0.0237 0.8569 0.996 0.000 0.004
#> GSM1233014 2 0.6308 -0.1640 0.000 0.508 0.492
#> GSM1233015 1 0.5926 0.5881 0.644 0.000 0.356
#> GSM1233016 3 0.5726 0.6057 0.024 0.216 0.760
#> GSM1233024 2 0.4702 0.5320 0.000 0.788 0.212
#> GSM1233049 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233064 2 0.6008 0.4096 0.000 0.628 0.372
#> GSM1233068 3 0.5772 0.4922 0.220 0.024 0.756
#> GSM1233073 3 0.5967 0.6065 0.032 0.216 0.752
#> GSM1233093 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233115 1 0.5760 0.6209 0.672 0.000 0.328
#> GSM1232992 2 0.0000 0.7191 0.000 1.000 0.000
#> GSM1232993 2 0.5859 0.2919 0.000 0.656 0.344
#> GSM1233005 2 0.0000 0.7191 0.000 1.000 0.000
#> GSM1233007 2 0.5785 0.2074 0.000 0.668 0.332
#> GSM1233010 3 0.6049 0.6096 0.040 0.204 0.756
#> GSM1233013 2 0.0237 0.7183 0.000 0.996 0.004
#> GSM1233018 2 0.0000 0.7191 0.000 1.000 0.000
#> GSM1233019 2 0.2878 0.6681 0.000 0.904 0.096
#> GSM1233021 2 0.0000 0.7191 0.000 1.000 0.000
#> GSM1233025 3 0.5493 0.4915 0.232 0.012 0.756
#> GSM1233029 2 0.2878 0.6699 0.000 0.904 0.096
#> GSM1233030 2 0.1031 0.7105 0.000 0.976 0.024
#> GSM1233031 3 0.5058 0.5905 0.000 0.244 0.756
#> GSM1233032 1 0.3116 0.8488 0.892 0.000 0.108
#> GSM1233035 3 0.5842 0.6090 0.036 0.196 0.768
#> GSM1233038 1 0.0237 0.8569 0.996 0.000 0.004
#> GSM1233039 3 0.6215 0.1469 0.000 0.428 0.572
#> GSM1233042 3 0.6180 0.3660 0.000 0.416 0.584
#> GSM1233043 3 0.6244 0.3135 0.000 0.440 0.560
#> GSM1233044 3 0.5722 0.3691 0.292 0.004 0.704
#> GSM1233046 3 0.5291 0.4288 0.268 0.000 0.732
#> GSM1233051 1 0.3879 0.8260 0.848 0.000 0.152
#> GSM1233054 3 0.6621 0.2757 0.032 0.284 0.684
#> GSM1233057 2 0.6305 0.2168 0.000 0.516 0.484
#> GSM1233060 3 0.5058 0.5905 0.000 0.244 0.756
#> GSM1233062 2 0.5968 0.2420 0.000 0.636 0.364
#> GSM1233075 2 0.4931 0.6235 0.000 0.768 0.232
#> GSM1233078 3 0.4682 0.4155 0.004 0.192 0.804
#> GSM1233079 1 0.2711 0.8524 0.912 0.000 0.088
#> GSM1233082 3 0.6062 0.1706 0.384 0.000 0.616
#> GSM1233083 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233091 3 0.3816 0.4962 0.000 0.148 0.852
#> GSM1233095 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233096 1 0.3267 0.8433 0.884 0.000 0.116
#> GSM1233101 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233105 3 0.5882 0.2849 0.348 0.000 0.652
#> GSM1233117 2 0.0237 0.7191 0.000 0.996 0.004
#> GSM1233118 2 0.4399 0.6536 0.000 0.812 0.188
#> GSM1233001 2 0.3879 0.6711 0.000 0.848 0.152
#> GSM1233006 2 0.5363 0.4289 0.000 0.724 0.276
#> GSM1233008 2 0.0237 0.7183 0.000 0.996 0.004
#> GSM1233009 2 0.2878 0.6681 0.000 0.904 0.096
#> GSM1233017 2 0.2878 0.6681 0.000 0.904 0.096
#> GSM1233020 2 0.0000 0.7191 0.000 1.000 0.000
#> GSM1233022 2 0.5948 0.2525 0.000 0.640 0.360
#> GSM1233026 3 0.4931 0.5980 0.000 0.232 0.768
#> GSM1233028 3 0.4931 0.5966 0.000 0.232 0.768
#> GSM1233034 2 0.3340 0.6860 0.000 0.880 0.120
#> GSM1233040 1 0.3116 0.8476 0.892 0.000 0.108
#> GSM1233048 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233056 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233058 3 0.4974 0.5966 0.000 0.236 0.764
#> GSM1233059 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233066 3 0.4974 0.3728 0.000 0.236 0.764
#> GSM1233071 2 0.6095 0.1457 0.000 0.608 0.392
#> GSM1233074 2 0.4842 0.6301 0.000 0.776 0.224
#> GSM1233076 3 0.6095 0.2574 0.000 0.392 0.608
#> GSM1233080 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233088 3 0.5397 0.3186 0.000 0.280 0.720
#> GSM1233090 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233092 3 0.6309 0.1699 0.000 0.496 0.504
#> GSM1233094 3 0.6079 0.4128 0.000 0.388 0.612
#> GSM1233097 3 0.5905 0.4754 0.000 0.352 0.648
#> GSM1233100 3 0.5816 0.6038 0.024 0.224 0.752
#> GSM1233104 3 0.6225 0.3322 0.000 0.432 0.568
#> GSM1233106 1 0.6244 0.3869 0.560 0.000 0.440
#> GSM1233111 1 0.3412 0.8416 0.876 0.000 0.124
#> GSM1233122 2 0.0000 0.7191 0.000 1.000 0.000
#> GSM1233146 3 0.5733 0.5091 0.000 0.324 0.676
#> GSM1232994 2 0.3340 0.6458 0.000 0.880 0.120
#> GSM1232996 2 0.0000 0.7191 0.000 1.000 0.000
#> GSM1232997 2 0.4796 0.6333 0.000 0.780 0.220
#> GSM1232998 2 0.5706 0.3436 0.000 0.680 0.320
#> GSM1232999 2 0.5560 0.3868 0.000 0.700 0.300
#> GSM1233000 2 0.2878 0.6681 0.000 0.904 0.096
#> GSM1233004 3 0.4189 0.5321 0.056 0.068 0.876
#> GSM1233011 3 0.6299 -0.0647 0.000 0.476 0.524
#> GSM1233012 2 0.4121 0.6665 0.000 0.832 0.168
#> GSM1233023 2 0.4702 0.6391 0.000 0.788 0.212
#> GSM1233027 2 0.4235 0.5845 0.000 0.824 0.176
#> GSM1233033 1 0.2165 0.8555 0.936 0.000 0.064
#> GSM1233036 2 0.6215 0.3511 0.000 0.572 0.428
#> GSM1233037 2 0.6307 0.2071 0.000 0.512 0.488
#> GSM1233041 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233045 3 0.5926 0.4667 0.000 0.356 0.644
#> GSM1233047 1 0.6095 0.6188 0.608 0.000 0.392
#> GSM1233050 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233052 3 0.5926 0.2576 0.356 0.000 0.644
#> GSM1233053 1 0.3816 0.8286 0.852 0.000 0.148
#> GSM1233055 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233061 3 0.5497 0.2761 0.000 0.292 0.708
#> GSM1233063 1 0.3267 0.8433 0.884 0.000 0.116
#> GSM1233065 2 0.4702 0.6391 0.000 0.788 0.212
#> GSM1233070 2 0.6008 0.2013 0.000 0.628 0.372
#> GSM1233077 2 0.6204 0.3894 0.000 0.576 0.424
#> GSM1233081 1 0.5760 0.6873 0.672 0.000 0.328
#> GSM1233084 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233087 3 0.6154 0.5334 0.204 0.044 0.752
#> GSM1233089 2 0.0592 0.7180 0.000 0.988 0.012
#> GSM1233099 3 0.5987 0.5247 0.208 0.036 0.756
#> GSM1233112 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233085 1 0.5810 0.6855 0.664 0.000 0.336
#> GSM1233098 2 0.0000 0.7191 0.000 1.000 0.000
#> GSM1233114 1 0.4399 0.7949 0.812 0.000 0.188
#> GSM1233119 3 0.5967 0.6072 0.032 0.216 0.752
#> GSM1233129 2 0.4796 0.6334 0.000 0.780 0.220
#> GSM1233132 1 0.4654 0.7706 0.792 0.000 0.208
#> GSM1233139 2 0.0592 0.7186 0.000 0.988 0.012
#> GSM1233143 2 0.1753 0.7111 0.000 0.952 0.048
#> GSM1233145 1 0.0237 0.8569 0.996 0.000 0.004
#> GSM1233067 2 0.4750 0.6361 0.000 0.784 0.216
#> GSM1233069 2 0.4974 0.6206 0.000 0.764 0.236
#> GSM1233072 2 0.0000 0.7191 0.000 1.000 0.000
#> GSM1233086 3 0.6062 0.1422 0.000 0.384 0.616
#> GSM1233102 3 0.6045 0.3635 0.380 0.000 0.620
#> GSM1233103 3 0.5219 0.6086 0.016 0.196 0.788
#> GSM1233107 3 0.6372 0.6096 0.084 0.152 0.764
#> GSM1233108 1 0.3192 0.8479 0.888 0.000 0.112
#> GSM1233109 1 0.6095 0.6091 0.608 0.000 0.392
#> GSM1233110 3 0.5988 0.1330 0.000 0.368 0.632
#> GSM1233113 2 0.4504 0.6491 0.000 0.804 0.196
#> GSM1233116 2 0.4504 0.6497 0.000 0.804 0.196
#> GSM1233120 3 0.5465 0.4519 0.288 0.000 0.712
#> GSM1233121 3 0.6252 -0.0704 0.000 0.444 0.556
#> GSM1233123 3 0.6026 0.1156 0.000 0.376 0.624
#> GSM1233124 3 0.6295 -0.1413 0.000 0.472 0.528
#> GSM1233125 1 0.3267 0.8472 0.884 0.000 0.116
#> GSM1233126 3 0.6521 0.1779 0.004 0.492 0.504
#> GSM1233127 2 0.3941 0.6053 0.000 0.844 0.156
#> GSM1233128 1 0.0000 0.8581 1.000 0.000 0.000
#> GSM1233130 3 0.5785 0.2094 0.000 0.332 0.668
#> GSM1233131 3 0.6252 -0.0231 0.444 0.000 0.556
#> GSM1233133 1 0.6079 0.6247 0.612 0.000 0.388
#> GSM1233134 2 0.5138 0.6096 0.000 0.748 0.252
#> GSM1233135 2 0.4931 0.6235 0.000 0.768 0.232
#> GSM1233136 2 0.6204 0.3894 0.000 0.576 0.424
#> GSM1233137 1 0.6274 0.5254 0.544 0.000 0.456
#> GSM1233138 3 0.6309 0.1699 0.000 0.496 0.504
#> GSM1233140 1 0.3482 0.8413 0.872 0.000 0.128
#> GSM1233141 2 0.2959 0.6700 0.000 0.900 0.100
#> GSM1233142 2 0.2878 0.6681 0.000 0.904 0.096
#> GSM1233144 1 0.6678 0.4665 0.512 0.008 0.480
#> GSM1233147 2 0.6235 0.1111 0.000 0.564 0.436
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.0524 0.8213 0.000 0.988 0.008 0.004
#> GSM1233002 4 0.1488 0.7320 0.000 0.032 0.012 0.956
#> GSM1233003 1 0.2300 0.8196 0.924 0.000 0.028 0.048
#> GSM1233014 4 0.4677 0.4234 0.000 0.316 0.004 0.680
#> GSM1233015 4 0.8017 0.0588 0.272 0.004 0.348 0.376
#> GSM1233016 4 0.2032 0.7305 0.000 0.028 0.036 0.936
#> GSM1233024 2 0.2999 0.7590 0.000 0.864 0.004 0.132
#> GSM1233049 1 0.0000 0.8356 1.000 0.000 0.000 0.000
#> GSM1233064 2 0.7679 -0.1170 0.000 0.424 0.356 0.220
#> GSM1233068 4 0.4969 0.5479 0.008 0.004 0.312 0.676
#> GSM1233073 4 0.1297 0.7325 0.000 0.020 0.016 0.964
#> GSM1233093 1 0.0188 0.8369 0.996 0.000 0.000 0.004
#> GSM1233115 4 0.7918 -0.0544 0.316 0.000 0.332 0.352
#> GSM1232992 2 0.0672 0.8222 0.000 0.984 0.008 0.008
#> GSM1232993 2 0.3208 0.7502 0.000 0.848 0.004 0.148
#> GSM1233005 2 0.0672 0.8222 0.000 0.984 0.008 0.008
#> GSM1233007 2 0.5723 0.3477 0.000 0.580 0.032 0.388
#> GSM1233010 4 0.1284 0.7312 0.000 0.012 0.024 0.964
#> GSM1233013 2 0.0336 0.8211 0.000 0.992 0.000 0.008
#> GSM1233018 2 0.0524 0.8213 0.000 0.988 0.008 0.004
#> GSM1233019 2 0.1109 0.8165 0.000 0.968 0.004 0.028
#> GSM1233021 2 0.0672 0.8222 0.000 0.984 0.008 0.008
#> GSM1233025 4 0.1209 0.7268 0.004 0.000 0.032 0.964
#> GSM1233029 2 0.1305 0.8147 0.000 0.960 0.004 0.036
#> GSM1233030 2 0.0469 0.8205 0.000 0.988 0.000 0.012
#> GSM1233031 4 0.2111 0.7326 0.000 0.044 0.024 0.932
#> GSM1233032 1 0.5193 0.6591 0.656 0.000 0.324 0.020
#> GSM1233035 4 0.4936 0.5761 0.000 0.020 0.280 0.700
#> GSM1233038 1 0.2124 0.8207 0.932 0.000 0.028 0.040
#> GSM1233039 3 0.7878 0.2796 0.000 0.284 0.376 0.340
#> GSM1233042 4 0.3105 0.6840 0.000 0.140 0.004 0.856
#> GSM1233043 4 0.3105 0.6840 0.000 0.140 0.004 0.856
#> GSM1233044 4 0.2737 0.7004 0.008 0.000 0.104 0.888
#> GSM1233046 4 0.5326 0.5481 0.012 0.012 0.308 0.668
#> GSM1233051 1 0.6039 0.6216 0.596 0.000 0.348 0.056
#> GSM1233054 3 0.1690 0.6635 0.008 0.008 0.952 0.032
#> GSM1233057 3 0.5271 0.4846 0.000 0.340 0.640 0.020
#> GSM1233060 4 0.3279 0.7203 0.000 0.096 0.032 0.872
#> GSM1233062 2 0.4819 0.4902 0.000 0.652 0.004 0.344
#> GSM1233075 3 0.4996 0.1640 0.000 0.484 0.516 0.000
#> GSM1233078 3 0.1388 0.6713 0.000 0.012 0.960 0.028
#> GSM1233079 1 0.5069 0.6645 0.664 0.000 0.320 0.016
#> GSM1233082 4 0.5717 0.5049 0.044 0.000 0.324 0.632
#> GSM1233083 1 0.1520 0.8295 0.956 0.000 0.020 0.024
#> GSM1233091 4 0.6558 0.3077 0.000 0.108 0.296 0.596
#> GSM1233095 1 0.0188 0.8369 0.996 0.000 0.000 0.004
#> GSM1233096 1 0.5745 0.6729 0.656 0.000 0.288 0.056
#> GSM1233101 1 0.0188 0.8369 0.996 0.000 0.000 0.004
#> GSM1233105 4 0.5877 0.5531 0.068 0.000 0.276 0.656
#> GSM1233117 2 0.0672 0.8222 0.000 0.984 0.008 0.008
#> GSM1233118 2 0.3024 0.7193 0.000 0.852 0.148 0.000
#> GSM1233001 2 0.2011 0.7796 0.000 0.920 0.080 0.000
#> GSM1233006 2 0.4483 0.6044 0.000 0.712 0.004 0.284
#> GSM1233008 2 0.0672 0.8222 0.000 0.984 0.008 0.008
#> GSM1233009 2 0.0921 0.8174 0.000 0.972 0.000 0.028
#> GSM1233017 2 0.0921 0.8174 0.000 0.972 0.000 0.028
#> GSM1233020 2 0.0336 0.8199 0.000 0.992 0.008 0.000
#> GSM1233022 2 0.4964 0.4153 0.000 0.616 0.004 0.380
#> GSM1233026 4 0.1284 0.7307 0.000 0.024 0.012 0.964
#> GSM1233028 4 0.1388 0.7318 0.000 0.028 0.012 0.960
#> GSM1233034 2 0.2125 0.7810 0.000 0.920 0.076 0.004
#> GSM1233040 1 0.5130 0.6696 0.668 0.000 0.312 0.020
#> GSM1233048 1 0.0469 0.8365 0.988 0.000 0.000 0.012
#> GSM1233056 1 0.0336 0.8364 0.992 0.000 0.000 0.008
#> GSM1233058 4 0.1004 0.7308 0.000 0.024 0.004 0.972
#> GSM1233059 1 0.0188 0.8369 0.996 0.000 0.000 0.004
#> GSM1233066 3 0.5524 0.5250 0.000 0.048 0.676 0.276
#> GSM1233071 2 0.4840 0.6359 0.000 0.732 0.028 0.240
#> GSM1233074 2 0.4134 0.5558 0.000 0.740 0.260 0.000
#> GSM1233076 4 0.6798 0.3185 0.000 0.172 0.224 0.604
#> GSM1233080 1 0.0188 0.8369 0.996 0.000 0.000 0.004
#> GSM1233088 3 0.3731 0.6505 0.000 0.120 0.844 0.036
#> GSM1233090 1 0.0188 0.8369 0.996 0.000 0.000 0.004
#> GSM1233092 4 0.3945 0.6081 0.000 0.216 0.004 0.780
#> GSM1233094 4 0.2546 0.7117 0.000 0.092 0.008 0.900
#> GSM1233097 4 0.1661 0.7262 0.000 0.052 0.004 0.944
#> GSM1233100 4 0.1624 0.7329 0.000 0.028 0.020 0.952
#> GSM1233104 4 0.2401 0.7112 0.000 0.092 0.004 0.904
#> GSM1233106 4 0.6952 0.3676 0.120 0.000 0.364 0.516
#> GSM1233111 1 0.5793 0.6504 0.628 0.000 0.324 0.048
#> GSM1233122 2 0.0672 0.8222 0.000 0.984 0.008 0.008
#> GSM1233146 4 0.1970 0.7237 0.000 0.060 0.008 0.932
#> GSM1232994 2 0.1109 0.8165 0.000 0.968 0.004 0.028
#> GSM1232996 2 0.0524 0.8213 0.000 0.988 0.008 0.004
#> GSM1232997 2 0.4277 0.5152 0.000 0.720 0.280 0.000
#> GSM1232998 2 0.5161 0.1800 0.000 0.520 0.004 0.476
#> GSM1232999 2 0.4800 0.4915 0.000 0.656 0.004 0.340
#> GSM1233000 2 0.0921 0.8174 0.000 0.972 0.000 0.028
#> GSM1233004 4 0.5099 0.2249 0.000 0.008 0.380 0.612
#> GSM1233011 4 0.7661 0.0323 0.000 0.272 0.264 0.464
#> GSM1233012 2 0.1940 0.7834 0.000 0.924 0.076 0.000
#> GSM1233023 2 0.3172 0.7060 0.000 0.840 0.160 0.000
#> GSM1233027 2 0.4049 0.6823 0.000 0.780 0.008 0.212
#> GSM1233033 1 0.5070 0.7441 0.748 0.000 0.192 0.060
#> GSM1233036 3 0.5517 0.3398 0.000 0.412 0.568 0.020
#> GSM1233037 3 0.4004 0.6474 0.000 0.164 0.812 0.024
#> GSM1233041 1 0.0657 0.8367 0.984 0.000 0.012 0.004
#> GSM1233045 4 0.2334 0.7147 0.000 0.088 0.004 0.908
#> GSM1233047 3 0.3198 0.6001 0.080 0.000 0.880 0.040
#> GSM1233050 1 0.0188 0.8369 0.996 0.000 0.000 0.004
#> GSM1233052 4 0.6098 0.5139 0.076 0.000 0.292 0.632
#> GSM1233053 1 0.5149 0.6381 0.648 0.000 0.336 0.016
#> GSM1233055 1 0.0336 0.8364 0.992 0.000 0.000 0.008
#> GSM1233061 3 0.1388 0.6717 0.000 0.012 0.960 0.028
#> GSM1233063 1 0.5712 0.6692 0.644 0.000 0.308 0.048
#> GSM1233065 2 0.3710 0.6635 0.000 0.804 0.192 0.004
#> GSM1233070 2 0.5007 0.4601 0.000 0.636 0.008 0.356
#> GSM1233077 3 0.6621 0.5402 0.000 0.140 0.616 0.244
#> GSM1233081 3 0.3557 0.5718 0.108 0.000 0.856 0.036
#> GSM1233084 1 0.0779 0.8364 0.980 0.000 0.016 0.004
#> GSM1233087 4 0.1114 0.7271 0.016 0.004 0.008 0.972
#> GSM1233089 2 0.0592 0.8167 0.000 0.984 0.016 0.000
#> GSM1233099 4 0.1284 0.7276 0.012 0.000 0.024 0.964
#> GSM1233112 1 0.1297 0.8309 0.964 0.000 0.016 0.020
#> GSM1233085 3 0.3984 0.5339 0.132 0.000 0.828 0.040
#> GSM1233098 2 0.0927 0.8212 0.000 0.976 0.016 0.008
#> GSM1233114 4 0.7923 -0.1192 0.324 0.000 0.332 0.344
#> GSM1233119 4 0.0992 0.7299 0.004 0.008 0.012 0.976
#> GSM1233129 2 0.4277 0.5185 0.000 0.720 0.280 0.000
#> GSM1233132 4 0.7646 0.1978 0.292 0.000 0.244 0.464
#> GSM1233139 2 0.1284 0.8196 0.000 0.964 0.012 0.024
#> GSM1233143 2 0.1151 0.8160 0.000 0.968 0.024 0.008
#> GSM1233145 1 0.2546 0.8066 0.912 0.000 0.028 0.060
#> GSM1233067 2 0.4454 0.4921 0.000 0.692 0.308 0.000
#> GSM1233069 3 0.5070 0.4178 0.000 0.372 0.620 0.008
#> GSM1233072 2 0.0672 0.8222 0.000 0.984 0.008 0.008
#> GSM1233086 3 0.6637 0.3739 0.000 0.092 0.540 0.368
#> GSM1233102 4 0.3056 0.7068 0.072 0.000 0.040 0.888
#> GSM1233103 4 0.5013 0.5649 0.000 0.020 0.292 0.688
#> GSM1233107 4 0.4952 0.5861 0.008 0.012 0.268 0.712
#> GSM1233108 3 0.5408 -0.4313 0.488 0.000 0.500 0.012
#> GSM1233109 3 0.3215 0.5890 0.092 0.000 0.876 0.032
#> GSM1233110 3 0.2174 0.6820 0.000 0.052 0.928 0.020
#> GSM1233113 2 0.2281 0.7672 0.000 0.904 0.096 0.000
#> GSM1233116 2 0.3052 0.7362 0.000 0.860 0.136 0.004
#> GSM1233120 4 0.2871 0.7090 0.072 0.000 0.032 0.896
#> GSM1233121 3 0.6351 0.5309 0.000 0.104 0.628 0.268
#> GSM1233123 3 0.2089 0.6811 0.000 0.048 0.932 0.020
#> GSM1233124 3 0.6303 0.5991 0.000 0.192 0.660 0.148
#> GSM1233125 1 0.5407 0.4249 0.504 0.000 0.484 0.012
#> GSM1233126 4 0.3498 0.6592 0.000 0.160 0.008 0.832
#> GSM1233127 2 0.3649 0.6969 0.000 0.796 0.000 0.204
#> GSM1233128 1 0.1284 0.8337 0.964 0.000 0.024 0.012
#> GSM1233130 3 0.4224 0.6430 0.000 0.044 0.812 0.144
#> GSM1233131 4 0.6013 0.5146 0.064 0.000 0.312 0.624
#> GSM1233133 3 0.2593 0.5981 0.080 0.000 0.904 0.016
#> GSM1233134 3 0.4661 0.4556 0.000 0.348 0.652 0.000
#> GSM1233135 3 0.4776 0.4097 0.000 0.376 0.624 0.000
#> GSM1233136 3 0.6621 0.5402 0.000 0.140 0.616 0.244
#> GSM1233137 3 0.2949 0.6121 0.088 0.000 0.888 0.024
#> GSM1233138 4 0.3545 0.6559 0.000 0.164 0.008 0.828
#> GSM1233140 1 0.6016 0.5375 0.544 0.000 0.412 0.044
#> GSM1233141 2 0.3311 0.7279 0.000 0.828 0.000 0.172
#> GSM1233142 2 0.1940 0.7985 0.000 0.924 0.000 0.076
#> GSM1233144 3 0.2111 0.6429 0.044 0.000 0.932 0.024
#> GSM1233147 4 0.7028 0.3318 0.000 0.228 0.196 0.576
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.0566 0.8325 0.004 0.984 0.012 0.000 0.000
#> GSM1233002 4 0.2756 0.7665 0.096 0.012 0.012 0.880 0.000
#> GSM1233003 5 0.3876 0.7601 0.192 0.000 0.000 0.032 0.776
#> GSM1233014 4 0.3443 0.6952 0.012 0.164 0.008 0.816 0.000
#> GSM1233015 1 0.5223 0.6217 0.748 0.000 0.076 0.092 0.084
#> GSM1233016 4 0.3681 0.6916 0.184 0.008 0.008 0.796 0.004
#> GSM1233024 2 0.3059 0.7872 0.028 0.860 0.004 0.108 0.000
#> GSM1233049 5 0.0404 0.8844 0.012 0.000 0.000 0.000 0.988
#> GSM1233064 3 0.6927 0.2806 0.056 0.336 0.500 0.108 0.000
#> GSM1233068 1 0.5375 0.3956 0.568 0.000 0.044 0.380 0.008
#> GSM1233073 4 0.1809 0.7698 0.060 0.012 0.000 0.928 0.000
#> GSM1233093 5 0.0404 0.8845 0.012 0.000 0.000 0.000 0.988
#> GSM1233115 1 0.6267 0.5824 0.616 0.000 0.044 0.240 0.100
#> GSM1232992 2 0.0000 0.8330 0.000 1.000 0.000 0.000 0.000
#> GSM1232993 2 0.3651 0.7456 0.028 0.808 0.004 0.160 0.000
#> GSM1233005 2 0.0740 0.8338 0.008 0.980 0.004 0.008 0.000
#> GSM1233007 4 0.6375 0.4645 0.020 0.284 0.132 0.564 0.000
#> GSM1233010 4 0.3239 0.7279 0.156 0.004 0.012 0.828 0.000
#> GSM1233013 2 0.0162 0.8329 0.000 0.996 0.000 0.004 0.000
#> GSM1233018 2 0.0740 0.8329 0.008 0.980 0.008 0.004 0.000
#> GSM1233019 2 0.0771 0.8316 0.004 0.976 0.000 0.020 0.000
#> GSM1233021 2 0.0740 0.8338 0.008 0.980 0.004 0.008 0.000
#> GSM1233025 4 0.3578 0.6903 0.204 0.000 0.008 0.784 0.004
#> GSM1233029 2 0.1547 0.8293 0.016 0.948 0.004 0.032 0.000
#> GSM1233030 2 0.0162 0.8329 0.000 0.996 0.000 0.004 0.000
#> GSM1233031 4 0.3561 0.6946 0.188 0.008 0.008 0.796 0.000
#> GSM1233032 1 0.5426 0.4226 0.608 0.000 0.084 0.000 0.308
#> GSM1233035 1 0.5636 0.3283 0.524 0.016 0.044 0.416 0.000
#> GSM1233038 5 0.2171 0.8513 0.064 0.000 0.000 0.024 0.912
#> GSM1233039 3 0.7344 0.3789 0.076 0.176 0.516 0.232 0.000
#> GSM1233042 4 0.2645 0.7518 0.012 0.096 0.008 0.884 0.000
#> GSM1233043 4 0.2645 0.7518 0.012 0.096 0.008 0.884 0.000
#> GSM1233044 4 0.4045 0.6870 0.148 0.000 0.056 0.792 0.004
#> GSM1233046 1 0.5853 0.3895 0.540 0.004 0.052 0.388 0.016
#> GSM1233051 1 0.4671 0.5199 0.712 0.000 0.040 0.008 0.240
#> GSM1233054 3 0.4114 0.4748 0.376 0.000 0.624 0.000 0.000
#> GSM1233057 3 0.4879 0.6396 0.124 0.156 0.720 0.000 0.000
#> GSM1233060 4 0.4978 0.6787 0.156 0.092 0.016 0.736 0.000
#> GSM1233062 2 0.4958 0.4377 0.032 0.616 0.004 0.348 0.000
#> GSM1233075 3 0.4639 0.3455 0.020 0.368 0.612 0.000 0.000
#> GSM1233078 3 0.0880 0.7246 0.032 0.000 0.968 0.000 0.000
#> GSM1233079 1 0.5405 0.4076 0.596 0.000 0.076 0.000 0.328
#> GSM1233082 1 0.4810 0.5782 0.692 0.000 0.024 0.264 0.020
#> GSM1233083 5 0.2505 0.8358 0.092 0.000 0.000 0.020 0.888
#> GSM1233091 4 0.7017 0.2921 0.180 0.028 0.324 0.468 0.000
#> GSM1233095 5 0.0609 0.8846 0.020 0.000 0.000 0.000 0.980
#> GSM1233096 1 0.4358 0.5177 0.696 0.000 0.008 0.012 0.284
#> GSM1233101 5 0.0703 0.8844 0.024 0.000 0.000 0.000 0.976
#> GSM1233105 1 0.4972 0.4585 0.612 0.004 0.000 0.352 0.032
#> GSM1233117 2 0.0727 0.8340 0.004 0.980 0.004 0.012 0.000
#> GSM1233118 2 0.3882 0.6592 0.020 0.756 0.224 0.000 0.000
#> GSM1233001 2 0.2408 0.7876 0.016 0.892 0.092 0.000 0.000
#> GSM1233006 2 0.4220 0.5490 0.008 0.688 0.004 0.300 0.000
#> GSM1233008 2 0.0162 0.8332 0.000 0.996 0.004 0.000 0.000
#> GSM1233009 2 0.1547 0.8271 0.032 0.948 0.004 0.016 0.000
#> GSM1233017 2 0.1564 0.8256 0.024 0.948 0.004 0.024 0.000
#> GSM1233020 2 0.0566 0.8321 0.004 0.984 0.012 0.000 0.000
#> GSM1233022 2 0.5377 0.1083 0.044 0.496 0.004 0.456 0.000
#> GSM1233026 4 0.3504 0.7368 0.160 0.008 0.016 0.816 0.000
#> GSM1233028 4 0.2753 0.7608 0.104 0.008 0.012 0.876 0.000
#> GSM1233034 2 0.2775 0.7914 0.036 0.884 0.076 0.004 0.000
#> GSM1233040 1 0.4854 0.4646 0.648 0.000 0.044 0.000 0.308
#> GSM1233048 5 0.1792 0.8426 0.084 0.000 0.000 0.000 0.916
#> GSM1233056 5 0.0671 0.8800 0.016 0.000 0.000 0.004 0.980
#> GSM1233058 4 0.2748 0.7630 0.096 0.008 0.016 0.880 0.000
#> GSM1233059 5 0.0880 0.8807 0.032 0.000 0.000 0.000 0.968
#> GSM1233066 3 0.2162 0.7169 0.012 0.008 0.916 0.064 0.000
#> GSM1233071 2 0.5287 0.6533 0.092 0.708 0.020 0.180 0.000
#> GSM1233074 2 0.4437 0.5106 0.020 0.664 0.316 0.000 0.000
#> GSM1233076 4 0.5784 0.5267 0.056 0.040 0.268 0.636 0.000
#> GSM1233080 5 0.0510 0.8844 0.016 0.000 0.000 0.000 0.984
#> GSM1233088 3 0.5698 0.4873 0.308 0.052 0.612 0.028 0.000
#> GSM1233090 5 0.0794 0.8824 0.028 0.000 0.000 0.000 0.972
#> GSM1233092 4 0.3018 0.7364 0.012 0.116 0.012 0.860 0.000
#> GSM1233094 4 0.2130 0.7599 0.012 0.080 0.000 0.908 0.000
#> GSM1233097 4 0.2270 0.7744 0.052 0.020 0.012 0.916 0.000
#> GSM1233100 4 0.2395 0.7704 0.072 0.016 0.008 0.904 0.000
#> GSM1233104 4 0.1695 0.7756 0.008 0.044 0.008 0.940 0.000
#> GSM1233106 1 0.5407 0.6281 0.728 0.000 0.076 0.132 0.064
#> GSM1233111 1 0.4573 0.5029 0.688 0.000 0.028 0.004 0.280
#> GSM1233122 2 0.0324 0.8335 0.004 0.992 0.004 0.000 0.000
#> GSM1233146 4 0.1356 0.7753 0.012 0.028 0.004 0.956 0.000
#> GSM1232994 2 0.1646 0.8252 0.020 0.944 0.004 0.032 0.000
#> GSM1232996 2 0.0740 0.8329 0.008 0.980 0.008 0.004 0.000
#> GSM1232997 2 0.4584 0.5064 0.028 0.660 0.312 0.000 0.000
#> GSM1232998 4 0.4353 0.4746 0.004 0.328 0.008 0.660 0.000
#> GSM1232999 2 0.4816 -0.0551 0.008 0.496 0.008 0.488 0.000
#> GSM1233000 2 0.0510 0.8327 0.000 0.984 0.000 0.016 0.000
#> GSM1233004 4 0.5492 0.5033 0.076 0.000 0.312 0.608 0.004
#> GSM1233011 4 0.6432 0.4199 0.032 0.112 0.288 0.568 0.000
#> GSM1233012 2 0.1830 0.8153 0.012 0.932 0.052 0.004 0.000
#> GSM1233023 2 0.4024 0.6561 0.028 0.752 0.220 0.000 0.000
#> GSM1233027 2 0.3561 0.7084 0.008 0.796 0.008 0.188 0.000
#> GSM1233033 1 0.4946 0.3112 0.596 0.000 0.000 0.036 0.368
#> GSM1233036 3 0.5065 0.5335 0.048 0.264 0.676 0.012 0.000
#> GSM1233037 3 0.5297 0.4664 0.360 0.060 0.580 0.000 0.000
#> GSM1233041 5 0.2329 0.8217 0.124 0.000 0.000 0.000 0.876
#> GSM1233045 4 0.3113 0.7648 0.100 0.020 0.016 0.864 0.000
#> GSM1233047 3 0.5107 0.3872 0.356 0.000 0.596 0.000 0.048
#> GSM1233050 5 0.2020 0.8317 0.100 0.000 0.000 0.000 0.900
#> GSM1233052 1 0.5762 0.3996 0.544 0.000 0.040 0.388 0.028
#> GSM1233053 1 0.5928 0.4013 0.548 0.000 0.124 0.000 0.328
#> GSM1233055 5 0.0671 0.8799 0.016 0.000 0.000 0.004 0.980
#> GSM1233061 3 0.1121 0.7225 0.044 0.000 0.956 0.000 0.000
#> GSM1233063 1 0.4455 0.4969 0.692 0.000 0.008 0.016 0.284
#> GSM1233065 2 0.4248 0.6312 0.032 0.728 0.240 0.000 0.000
#> GSM1233070 2 0.5270 0.3297 0.016 0.584 0.028 0.372 0.000
#> GSM1233077 3 0.3046 0.7067 0.020 0.028 0.876 0.076 0.000
#> GSM1233081 3 0.4645 0.5236 0.268 0.000 0.688 0.000 0.044
#> GSM1233084 5 0.0963 0.8820 0.036 0.000 0.000 0.000 0.964
#> GSM1233087 4 0.1857 0.7697 0.060 0.000 0.008 0.928 0.004
#> GSM1233089 2 0.0798 0.8322 0.008 0.976 0.016 0.000 0.000
#> GSM1233099 4 0.3419 0.7068 0.180 0.000 0.016 0.804 0.000
#> GSM1233112 5 0.2305 0.8411 0.092 0.000 0.000 0.012 0.896
#> GSM1233085 3 0.5066 0.3976 0.344 0.000 0.608 0.000 0.048
#> GSM1233098 2 0.2047 0.8232 0.012 0.928 0.020 0.040 0.000
#> GSM1233114 1 0.4881 0.6117 0.744 0.000 0.012 0.132 0.112
#> GSM1233119 4 0.2563 0.7614 0.120 0.000 0.008 0.872 0.000
#> GSM1233129 2 0.4747 0.4207 0.028 0.620 0.352 0.000 0.000
#> GSM1233132 1 0.6189 0.5494 0.596 0.000 0.024 0.268 0.112
#> GSM1233139 2 0.1492 0.8287 0.040 0.948 0.004 0.008 0.000
#> GSM1233143 2 0.2263 0.8235 0.036 0.920 0.020 0.024 0.000
#> GSM1233145 5 0.3134 0.8051 0.120 0.000 0.000 0.032 0.848
#> GSM1233067 2 0.4147 0.5483 0.008 0.676 0.316 0.000 0.000
#> GSM1233069 3 0.2727 0.7055 0.016 0.116 0.868 0.000 0.000
#> GSM1233072 2 0.0290 0.8328 0.000 0.992 0.008 0.000 0.000
#> GSM1233086 3 0.5313 0.2590 0.024 0.024 0.596 0.356 0.000
#> GSM1233102 4 0.3764 0.7001 0.156 0.000 0.000 0.800 0.044
#> GSM1233103 1 0.5157 0.2954 0.520 0.000 0.040 0.440 0.000
#> GSM1233107 1 0.5419 0.3186 0.560 0.008 0.036 0.392 0.004
#> GSM1233108 1 0.6955 0.0356 0.352 0.000 0.320 0.004 0.324
#> GSM1233109 3 0.4114 0.6259 0.176 0.000 0.776 0.004 0.044
#> GSM1233110 3 0.0963 0.7248 0.036 0.000 0.964 0.000 0.000
#> GSM1233113 2 0.2522 0.7793 0.012 0.880 0.108 0.000 0.000
#> GSM1233116 2 0.3391 0.7135 0.012 0.800 0.188 0.000 0.000
#> GSM1233120 4 0.4290 0.6735 0.196 0.000 0.004 0.756 0.044
#> GSM1233121 3 0.2861 0.7079 0.016 0.024 0.884 0.076 0.000
#> GSM1233123 3 0.0880 0.7253 0.032 0.000 0.968 0.000 0.000
#> GSM1233124 3 0.2434 0.7296 0.024 0.040 0.912 0.024 0.000
#> GSM1233125 5 0.6942 -0.0890 0.348 0.000 0.296 0.004 0.352
#> GSM1233126 4 0.3460 0.7428 0.088 0.048 0.008 0.852 0.004
#> GSM1233127 2 0.4675 0.7026 0.088 0.744 0.004 0.164 0.000
#> GSM1233128 5 0.2583 0.8157 0.132 0.000 0.000 0.004 0.864
#> GSM1233130 3 0.1200 0.7273 0.016 0.008 0.964 0.012 0.000
#> GSM1233131 1 0.4946 0.5004 0.636 0.000 0.012 0.328 0.024
#> GSM1233133 3 0.4355 0.5744 0.224 0.000 0.732 0.000 0.044
#> GSM1233134 3 0.2654 0.7205 0.032 0.084 0.884 0.000 0.000
#> GSM1233135 3 0.2563 0.7056 0.008 0.120 0.872 0.000 0.000
#> GSM1233136 3 0.3046 0.7067 0.020 0.028 0.876 0.076 0.000
#> GSM1233137 3 0.4233 0.5988 0.208 0.000 0.748 0.000 0.044
#> GSM1233138 4 0.3209 0.7510 0.068 0.060 0.008 0.864 0.000
#> GSM1233140 1 0.5420 0.4921 0.664 0.000 0.112 0.004 0.220
#> GSM1233141 2 0.4181 0.7428 0.076 0.788 0.004 0.132 0.000
#> GSM1233142 2 0.3338 0.7878 0.068 0.852 0.004 0.076 0.000
#> GSM1233144 3 0.3456 0.6389 0.184 0.000 0.800 0.000 0.016
#> GSM1233147 4 0.5161 0.5472 0.020 0.040 0.272 0.668 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.1003 0.77081 0.000 0.964 0.016 0.000 0.000 0.020
#> GSM1233002 4 0.2152 0.59556 0.000 0.004 0.000 0.904 0.068 0.024
#> GSM1233003 1 0.6506 0.42081 0.492 0.000 0.000 0.048 0.196 0.264
#> GSM1233014 4 0.4854 0.52291 0.000 0.152 0.000 0.664 0.000 0.184
#> GSM1233015 5 0.2639 0.28436 0.008 0.000 0.000 0.084 0.876 0.032
#> GSM1233016 4 0.5827 0.22189 0.008 0.008 0.004 0.472 0.096 0.412
#> GSM1233024 2 0.3857 0.67581 0.000 0.768 0.000 0.080 0.000 0.152
#> GSM1233049 1 0.0603 0.84847 0.980 0.000 0.000 0.000 0.016 0.004
#> GSM1233064 3 0.6341 0.12971 0.000 0.372 0.464 0.124 0.012 0.028
#> GSM1233068 5 0.4763 -0.16476 0.000 0.000 0.004 0.440 0.516 0.040
#> GSM1233073 4 0.3043 0.58241 0.000 0.008 0.000 0.832 0.020 0.140
#> GSM1233093 1 0.0713 0.84910 0.972 0.000 0.000 0.000 0.028 0.000
#> GSM1233115 5 0.6612 0.00195 0.032 0.000 0.032 0.328 0.492 0.116
#> GSM1232992 2 0.0146 0.77179 0.000 0.996 0.000 0.004 0.000 0.000
#> GSM1232993 2 0.4693 0.57002 0.000 0.684 0.000 0.176 0.000 0.140
#> GSM1233005 2 0.0603 0.77270 0.000 0.980 0.004 0.016 0.000 0.000
#> GSM1233007 4 0.6663 0.35395 0.000 0.288 0.136 0.488 0.000 0.088
#> GSM1233010 4 0.3210 0.49807 0.000 0.000 0.000 0.812 0.152 0.036
#> GSM1233013 2 0.0291 0.77136 0.000 0.992 0.000 0.004 0.000 0.004
#> GSM1233018 2 0.0551 0.77244 0.000 0.984 0.004 0.008 0.000 0.004
#> GSM1233019 2 0.1196 0.76557 0.000 0.952 0.000 0.008 0.000 0.040
#> GSM1233021 2 0.0603 0.77270 0.000 0.980 0.004 0.016 0.000 0.000
#> GSM1233025 4 0.5526 0.26147 0.008 0.000 0.004 0.552 0.104 0.332
#> GSM1233029 2 0.1856 0.75838 0.000 0.920 0.000 0.032 0.000 0.048
#> GSM1233030 2 0.1124 0.76679 0.000 0.956 0.000 0.008 0.000 0.036
#> GSM1233031 4 0.4663 0.30325 0.000 0.000 0.000 0.684 0.192 0.124
#> GSM1233032 5 0.4828 0.39635 0.108 0.000 0.004 0.000 0.668 0.220
#> GSM1233035 5 0.6104 -0.74430 0.000 0.008 0.000 0.216 0.452 0.324
#> GSM1233038 1 0.3186 0.80024 0.824 0.000 0.000 0.016 0.016 0.144
#> GSM1233039 3 0.7025 0.29226 0.000 0.160 0.500 0.252 0.056 0.032
#> GSM1233042 4 0.4199 0.57768 0.000 0.100 0.000 0.736 0.000 0.164
#> GSM1233043 4 0.4199 0.57768 0.000 0.100 0.000 0.736 0.000 0.164
#> GSM1233044 4 0.4301 0.47584 0.000 0.000 0.020 0.760 0.096 0.124
#> GSM1233046 5 0.6103 -0.68301 0.004 0.000 0.008 0.188 0.476 0.324
#> GSM1233051 5 0.4086 0.40246 0.036 0.000 0.000 0.024 0.756 0.184
#> GSM1233054 3 0.6141 0.33513 0.000 0.000 0.452 0.012 0.336 0.200
#> GSM1233057 3 0.5836 0.58649 0.000 0.116 0.652 0.004 0.120 0.108
#> GSM1233060 4 0.6459 0.25329 0.000 0.080 0.000 0.548 0.188 0.184
#> GSM1233062 2 0.5734 0.34317 0.000 0.536 0.000 0.264 0.004 0.196
#> GSM1233075 3 0.4702 0.29078 0.000 0.332 0.612 0.000 0.004 0.052
#> GSM1233078 3 0.1895 0.68750 0.000 0.000 0.912 0.000 0.016 0.072
#> GSM1233079 5 0.4893 0.40132 0.128 0.000 0.004 0.000 0.668 0.200
#> GSM1233082 5 0.4038 0.06956 0.000 0.000 0.000 0.244 0.712 0.044
#> GSM1233083 1 0.2980 0.78705 0.808 0.000 0.000 0.000 0.012 0.180
#> GSM1233091 4 0.6177 0.22277 0.000 0.008 0.236 0.572 0.144 0.040
#> GSM1233095 1 0.1124 0.84804 0.956 0.000 0.000 0.000 0.036 0.008
#> GSM1233096 5 0.2563 0.36346 0.084 0.000 0.000 0.028 0.880 0.008
#> GSM1233101 1 0.1245 0.84941 0.952 0.000 0.000 0.000 0.032 0.016
#> GSM1233105 5 0.6096 -0.43496 0.024 0.000 0.000 0.156 0.496 0.324
#> GSM1233117 2 0.1003 0.77392 0.000 0.964 0.004 0.004 0.000 0.028
#> GSM1233118 2 0.4617 0.45577 0.000 0.624 0.324 0.000 0.004 0.048
#> GSM1233001 2 0.2668 0.72633 0.000 0.872 0.096 0.004 0.004 0.024
#> GSM1233006 2 0.5602 0.24989 0.000 0.536 0.000 0.276 0.000 0.188
#> GSM1233008 2 0.0653 0.77368 0.000 0.980 0.004 0.004 0.000 0.012
#> GSM1233009 2 0.2488 0.74251 0.000 0.864 0.000 0.008 0.004 0.124
#> GSM1233017 2 0.2212 0.74152 0.000 0.880 0.000 0.008 0.000 0.112
#> GSM1233020 2 0.0405 0.77197 0.000 0.988 0.008 0.000 0.000 0.004
#> GSM1233022 2 0.6079 -0.08788 0.000 0.380 0.000 0.348 0.000 0.272
#> GSM1233026 4 0.3939 0.50559 0.000 0.000 0.020 0.784 0.140 0.056
#> GSM1233028 4 0.2586 0.55521 0.000 0.000 0.000 0.868 0.100 0.032
#> GSM1233034 2 0.2425 0.74476 0.000 0.900 0.060 0.016 0.008 0.016
#> GSM1233040 5 0.4124 0.41167 0.120 0.000 0.000 0.000 0.748 0.132
#> GSM1233048 1 0.2593 0.78995 0.844 0.000 0.000 0.000 0.148 0.008
#> GSM1233056 1 0.0858 0.84323 0.968 0.000 0.000 0.000 0.004 0.028
#> GSM1233058 4 0.2186 0.58607 0.000 0.000 0.012 0.908 0.056 0.024
#> GSM1233059 1 0.1958 0.82455 0.896 0.000 0.000 0.000 0.100 0.004
#> GSM1233066 3 0.1293 0.69703 0.000 0.004 0.956 0.020 0.004 0.016
#> GSM1233071 2 0.6454 0.36086 0.000 0.540 0.000 0.096 0.120 0.244
#> GSM1233074 2 0.4861 0.31762 0.000 0.552 0.392 0.000 0.004 0.052
#> GSM1233076 4 0.5928 0.43687 0.000 0.024 0.272 0.592 0.028 0.084
#> GSM1233080 1 0.0790 0.84848 0.968 0.000 0.000 0.000 0.032 0.000
#> GSM1233088 3 0.6203 0.41167 0.000 0.024 0.576 0.088 0.268 0.044
#> GSM1233090 1 0.1644 0.83642 0.920 0.000 0.000 0.000 0.076 0.004
#> GSM1233092 4 0.4762 0.55153 0.000 0.120 0.004 0.684 0.000 0.192
#> GSM1233094 4 0.3996 0.58282 0.000 0.080 0.000 0.752 0.000 0.168
#> GSM1233097 4 0.1448 0.60986 0.000 0.012 0.000 0.948 0.016 0.024
#> GSM1233100 4 0.2456 0.58386 0.000 0.008 0.000 0.892 0.052 0.048
#> GSM1233104 4 0.2488 0.61924 0.000 0.044 0.000 0.880 0.000 0.076
#> GSM1233106 5 0.2282 0.28475 0.000 0.000 0.000 0.088 0.888 0.024
#> GSM1233111 5 0.3419 0.40690 0.088 0.000 0.000 0.012 0.828 0.072
#> GSM1233122 2 0.0291 0.77264 0.000 0.992 0.004 0.000 0.000 0.004
#> GSM1233146 4 0.3166 0.60481 0.000 0.024 0.000 0.816 0.004 0.156
#> GSM1232994 2 0.2432 0.74154 0.000 0.876 0.000 0.024 0.000 0.100
#> GSM1232996 2 0.0748 0.77273 0.000 0.976 0.004 0.016 0.000 0.004
#> GSM1232997 2 0.4456 0.38650 0.000 0.596 0.372 0.000 0.004 0.028
#> GSM1232998 4 0.4887 0.43469 0.000 0.280 0.000 0.624 0.000 0.096
#> GSM1232999 2 0.5027 -0.03035 0.000 0.488 0.000 0.440 0.000 0.072
#> GSM1233000 2 0.1080 0.77069 0.000 0.960 0.000 0.004 0.004 0.032
#> GSM1233004 4 0.4739 0.45655 0.000 0.004 0.208 0.708 0.032 0.048
#> GSM1233011 4 0.6254 0.33997 0.000 0.072 0.328 0.516 0.004 0.080
#> GSM1233012 2 0.3039 0.73140 0.000 0.848 0.088 0.000 0.004 0.060
#> GSM1233023 2 0.4506 0.46089 0.000 0.636 0.324 0.004 0.004 0.032
#> GSM1233027 2 0.4307 0.53460 0.000 0.704 0.000 0.224 0.000 0.072
#> GSM1233033 5 0.5779 0.22272 0.192 0.000 0.000 0.008 0.544 0.256
#> GSM1233036 3 0.5766 0.53506 0.000 0.192 0.648 0.024 0.032 0.104
#> GSM1233037 3 0.6630 0.39188 0.000 0.068 0.472 0.004 0.328 0.128
#> GSM1233041 1 0.4328 0.69389 0.716 0.000 0.000 0.000 0.192 0.092
#> GSM1233045 4 0.2542 0.59085 0.000 0.012 0.012 0.896 0.056 0.024
#> GSM1233047 3 0.6364 0.19458 0.016 0.000 0.388 0.000 0.364 0.232
#> GSM1233050 1 0.2631 0.78383 0.840 0.000 0.000 0.000 0.152 0.008
#> GSM1233052 5 0.4972 -0.21798 0.000 0.000 0.000 0.392 0.536 0.072
#> GSM1233053 5 0.6495 0.30935 0.180 0.000 0.068 0.000 0.528 0.224
#> GSM1233055 1 0.0935 0.84276 0.964 0.000 0.000 0.000 0.004 0.032
#> GSM1233061 3 0.1984 0.69135 0.000 0.000 0.912 0.000 0.032 0.056
#> GSM1233063 5 0.4239 0.37630 0.088 0.000 0.000 0.008 0.748 0.156
#> GSM1233065 2 0.4860 0.40439 0.000 0.596 0.352 0.012 0.004 0.036
#> GSM1233070 2 0.5630 0.14567 0.000 0.524 0.028 0.368 0.000 0.080
#> GSM1233077 3 0.1714 0.68722 0.000 0.024 0.936 0.016 0.000 0.024
#> GSM1233081 3 0.6293 0.32635 0.020 0.000 0.472 0.000 0.272 0.236
#> GSM1233084 1 0.2794 0.82417 0.860 0.000 0.000 0.000 0.080 0.060
#> GSM1233087 4 0.1644 0.60745 0.004 0.000 0.000 0.932 0.012 0.052
#> GSM1233089 2 0.0891 0.76975 0.000 0.968 0.024 0.000 0.000 0.008
#> GSM1233099 4 0.4969 0.18912 0.000 0.000 0.000 0.648 0.156 0.196
#> GSM1233112 1 0.3110 0.77865 0.792 0.000 0.000 0.000 0.012 0.196
#> GSM1233085 3 0.6351 0.21866 0.016 0.000 0.408 0.000 0.344 0.232
#> GSM1233098 2 0.2188 0.76239 0.000 0.912 0.032 0.020 0.000 0.036
#> GSM1233114 5 0.5455 -0.14664 0.044 0.000 0.000 0.080 0.628 0.248
#> GSM1233119 4 0.2968 0.57566 0.000 0.000 0.000 0.816 0.016 0.168
#> GSM1233129 2 0.4780 0.28798 0.000 0.544 0.408 0.000 0.004 0.044
#> GSM1233132 5 0.6490 -0.44745 0.052 0.000 0.000 0.204 0.508 0.236
#> GSM1233139 2 0.2975 0.74069 0.000 0.832 0.012 0.004 0.004 0.148
#> GSM1233143 2 0.3667 0.71960 0.000 0.776 0.032 0.008 0.000 0.184
#> GSM1233145 1 0.4133 0.72341 0.724 0.000 0.000 0.024 0.020 0.232
#> GSM1233067 2 0.4816 0.24985 0.000 0.516 0.436 0.000 0.004 0.044
#> GSM1233069 3 0.1405 0.69077 0.000 0.024 0.948 0.004 0.000 0.024
#> GSM1233072 2 0.0748 0.77332 0.000 0.976 0.004 0.004 0.000 0.016
#> GSM1233086 3 0.4230 0.34752 0.000 0.004 0.648 0.324 0.000 0.024
#> GSM1233102 4 0.5219 0.22335 0.036 0.000 0.000 0.552 0.036 0.376
#> GSM1233103 5 0.5849 -0.44571 0.000 0.000 0.004 0.332 0.484 0.180
#> GSM1233107 6 0.5795 0.00000 0.000 0.000 0.000 0.184 0.364 0.452
#> GSM1233108 5 0.7361 0.19661 0.132 0.000 0.204 0.000 0.372 0.292
#> GSM1233109 3 0.5560 0.51426 0.020 0.000 0.636 0.008 0.132 0.204
#> GSM1233110 3 0.1367 0.69418 0.000 0.000 0.944 0.000 0.012 0.044
#> GSM1233113 2 0.3183 0.70061 0.000 0.828 0.128 0.000 0.004 0.040
#> GSM1233116 2 0.4177 0.54584 0.000 0.684 0.280 0.004 0.000 0.032
#> GSM1233120 4 0.5818 0.07460 0.036 0.000 0.000 0.564 0.108 0.292
#> GSM1233121 3 0.1458 0.68982 0.000 0.016 0.948 0.016 0.000 0.020
#> GSM1233123 3 0.1367 0.69438 0.000 0.000 0.944 0.000 0.012 0.044
#> GSM1233124 3 0.1674 0.69483 0.000 0.000 0.924 0.004 0.004 0.068
#> GSM1233125 5 0.7267 0.23649 0.128 0.000 0.184 0.000 0.392 0.296
#> GSM1233126 4 0.5190 0.48042 0.008 0.052 0.004 0.592 0.008 0.336
#> GSM1233127 2 0.5261 0.57891 0.000 0.644 0.004 0.100 0.016 0.236
#> GSM1233128 1 0.4854 0.63366 0.664 0.000 0.000 0.000 0.184 0.152
#> GSM1233130 3 0.1053 0.69267 0.000 0.004 0.964 0.012 0.000 0.020
#> GSM1233131 5 0.5150 -0.25580 0.000 0.000 0.000 0.188 0.624 0.188
#> GSM1233133 3 0.5873 0.42617 0.012 0.000 0.544 0.000 0.216 0.228
#> GSM1233134 3 0.2715 0.68569 0.000 0.028 0.872 0.000 0.012 0.088
#> GSM1233135 3 0.1408 0.69259 0.000 0.020 0.944 0.000 0.000 0.036
#> GSM1233136 3 0.1714 0.68722 0.000 0.024 0.936 0.016 0.000 0.024
#> GSM1233137 3 0.5730 0.47050 0.012 0.000 0.568 0.000 0.184 0.236
#> GSM1233138 4 0.4893 0.52015 0.000 0.060 0.004 0.636 0.008 0.292
#> GSM1233140 5 0.5041 0.39061 0.048 0.000 0.028 0.004 0.648 0.272
#> GSM1233141 2 0.4875 0.62722 0.000 0.680 0.004 0.092 0.008 0.216
#> GSM1233142 2 0.4130 0.68144 0.000 0.744 0.004 0.044 0.008 0.200
#> GSM1233144 3 0.5422 0.49127 0.004 0.000 0.596 0.000 0.176 0.224
#> GSM1233147 4 0.6174 0.42651 0.000 0.060 0.280 0.544 0.000 0.116
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> MAD:kmeans 149 0.97868 0.577 0.73183 2
#> MAD:kmeans 103 0.47572 0.909 0.39974 3
#> MAD:kmeans 127 0.00457 0.532 0.25566 4
#> MAD:kmeans 122 0.00121 0.237 0.00886 5
#> MAD:kmeans 86 0.00187 0.116 0.00119 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 51941 rows and 156 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 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.960 0.950 0.980 0.5002 0.500 0.500
#> 3 3 0.681 0.678 0.847 0.3160 0.737 0.525
#> 4 4 0.694 0.725 0.866 0.1181 0.790 0.485
#> 5 5 0.616 0.561 0.753 0.0592 0.953 0.829
#> 6 6 0.630 0.528 0.711 0.0411 0.952 0.813
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0000 0.982 0.000 1.000
#> GSM1233002 1 0.7376 0.745 0.792 0.208
#> GSM1233003 1 0.0000 0.975 1.000 0.000
#> GSM1233014 2 0.0000 0.982 0.000 1.000
#> GSM1233015 1 0.0000 0.975 1.000 0.000
#> GSM1233016 1 0.0000 0.975 1.000 0.000
#> GSM1233024 2 0.0000 0.982 0.000 1.000
#> GSM1233049 1 0.0000 0.975 1.000 0.000
#> GSM1233064 2 0.0000 0.982 0.000 1.000
#> GSM1233068 1 0.0000 0.975 1.000 0.000
#> GSM1233073 1 0.0376 0.971 0.996 0.004
#> GSM1233093 1 0.0000 0.975 1.000 0.000
#> GSM1233115 1 0.0000 0.975 1.000 0.000
#> GSM1232992 2 0.0000 0.982 0.000 1.000
#> GSM1232993 2 0.0000 0.982 0.000 1.000
#> GSM1233005 2 0.0000 0.982 0.000 1.000
#> GSM1233007 2 0.0000 0.982 0.000 1.000
#> GSM1233010 1 0.0000 0.975 1.000 0.000
#> GSM1233013 2 0.0000 0.982 0.000 1.000
#> GSM1233018 2 0.0000 0.982 0.000 1.000
#> GSM1233019 2 0.0000 0.982 0.000 1.000
#> GSM1233021 2 0.0000 0.982 0.000 1.000
#> GSM1233025 1 0.0000 0.975 1.000 0.000
#> GSM1233029 2 0.0000 0.982 0.000 1.000
#> GSM1233030 2 0.0000 0.982 0.000 1.000
#> GSM1233031 1 0.6247 0.815 0.844 0.156
#> GSM1233032 1 0.0000 0.975 1.000 0.000
#> GSM1233035 1 0.0000 0.975 1.000 0.000
#> GSM1233038 1 0.0000 0.975 1.000 0.000
#> GSM1233039 2 0.0000 0.982 0.000 1.000
#> GSM1233042 2 0.0000 0.982 0.000 1.000
#> GSM1233043 2 0.0000 0.982 0.000 1.000
#> GSM1233044 1 0.0000 0.975 1.000 0.000
#> GSM1233046 1 0.0000 0.975 1.000 0.000
#> GSM1233051 1 0.0000 0.975 1.000 0.000
#> GSM1233054 1 0.0672 0.968 0.992 0.008
#> GSM1233057 2 0.0000 0.982 0.000 1.000
#> GSM1233060 2 0.9661 0.330 0.392 0.608
#> GSM1233062 2 0.0000 0.982 0.000 1.000
#> GSM1233075 2 0.0000 0.982 0.000 1.000
#> GSM1233078 1 0.0376 0.971 0.996 0.004
#> GSM1233079 1 0.0000 0.975 1.000 0.000
#> GSM1233082 1 0.0000 0.975 1.000 0.000
#> GSM1233083 1 0.0000 0.975 1.000 0.000
#> GSM1233091 1 0.9580 0.413 0.620 0.380
#> GSM1233095 1 0.0000 0.975 1.000 0.000
#> GSM1233096 1 0.0000 0.975 1.000 0.000
#> GSM1233101 1 0.0000 0.975 1.000 0.000
#> GSM1233105 1 0.0000 0.975 1.000 0.000
#> GSM1233117 2 0.0000 0.982 0.000 1.000
#> GSM1233118 2 0.0000 0.982 0.000 1.000
#> GSM1233001 2 0.0000 0.982 0.000 1.000
#> GSM1233006 2 0.0000 0.982 0.000 1.000
#> GSM1233008 2 0.0000 0.982 0.000 1.000
#> GSM1233009 2 0.0000 0.982 0.000 1.000
#> GSM1233017 2 0.0000 0.982 0.000 1.000
#> GSM1233020 2 0.0000 0.982 0.000 1.000
#> GSM1233022 2 0.0000 0.982 0.000 1.000
#> GSM1233026 1 0.8555 0.628 0.720 0.280
#> GSM1233028 2 0.5519 0.847 0.128 0.872
#> GSM1233034 2 0.0000 0.982 0.000 1.000
#> GSM1233040 1 0.0000 0.975 1.000 0.000
#> GSM1233048 1 0.0000 0.975 1.000 0.000
#> GSM1233056 1 0.0000 0.975 1.000 0.000
#> GSM1233058 1 0.7453 0.739 0.788 0.212
#> GSM1233059 1 0.0000 0.975 1.000 0.000
#> GSM1233066 2 0.0672 0.976 0.008 0.992
#> GSM1233071 2 0.0000 0.982 0.000 1.000
#> GSM1233074 2 0.0000 0.982 0.000 1.000
#> GSM1233076 2 0.0000 0.982 0.000 1.000
#> GSM1233080 1 0.0000 0.975 1.000 0.000
#> GSM1233088 1 0.9833 0.289 0.576 0.424
#> GSM1233090 1 0.0000 0.975 1.000 0.000
#> GSM1233092 2 0.0000 0.982 0.000 1.000
#> GSM1233094 2 0.0000 0.982 0.000 1.000
#> GSM1233097 2 0.0376 0.979 0.004 0.996
#> GSM1233100 1 0.2603 0.936 0.956 0.044
#> GSM1233104 2 0.0000 0.982 0.000 1.000
#> GSM1233106 1 0.0000 0.975 1.000 0.000
#> GSM1233111 1 0.0000 0.975 1.000 0.000
#> GSM1233122 2 0.0000 0.982 0.000 1.000
#> GSM1233146 2 0.0000 0.982 0.000 1.000
#> GSM1232994 2 0.0000 0.982 0.000 1.000
#> GSM1232996 2 0.0000 0.982 0.000 1.000
#> GSM1232997 2 0.0000 0.982 0.000 1.000
#> GSM1232998 2 0.0000 0.982 0.000 1.000
#> GSM1232999 2 0.0000 0.982 0.000 1.000
#> GSM1233000 2 0.0000 0.982 0.000 1.000
#> GSM1233004 1 0.0000 0.975 1.000 0.000
#> GSM1233011 2 0.0000 0.982 0.000 1.000
#> GSM1233012 2 0.0000 0.982 0.000 1.000
#> GSM1233023 2 0.0000 0.982 0.000 1.000
#> GSM1233027 2 0.0000 0.982 0.000 1.000
#> GSM1233033 1 0.0000 0.975 1.000 0.000
#> GSM1233036 2 0.0000 0.982 0.000 1.000
#> GSM1233037 2 0.0376 0.979 0.004 0.996
#> GSM1233041 1 0.0000 0.975 1.000 0.000
#> GSM1233045 2 0.0000 0.982 0.000 1.000
#> GSM1233047 1 0.0000 0.975 1.000 0.000
#> GSM1233050 1 0.0000 0.975 1.000 0.000
#> GSM1233052 1 0.0000 0.975 1.000 0.000
#> GSM1233053 1 0.0000 0.975 1.000 0.000
#> GSM1233055 1 0.0000 0.975 1.000 0.000
#> GSM1233061 2 0.9977 0.107 0.472 0.528
#> GSM1233063 1 0.0000 0.975 1.000 0.000
#> GSM1233065 2 0.0000 0.982 0.000 1.000
#> GSM1233070 2 0.0000 0.982 0.000 1.000
#> GSM1233077 2 0.0000 0.982 0.000 1.000
#> GSM1233081 1 0.0000 0.975 1.000 0.000
#> GSM1233084 1 0.0000 0.975 1.000 0.000
#> GSM1233087 1 0.0000 0.975 1.000 0.000
#> GSM1233089 2 0.0000 0.982 0.000 1.000
#> GSM1233099 1 0.0000 0.975 1.000 0.000
#> GSM1233112 1 0.0000 0.975 1.000 0.000
#> GSM1233085 1 0.0000 0.975 1.000 0.000
#> GSM1233098 2 0.0000 0.982 0.000 1.000
#> GSM1233114 1 0.0000 0.975 1.000 0.000
#> GSM1233119 1 0.0000 0.975 1.000 0.000
#> GSM1233129 2 0.0000 0.982 0.000 1.000
#> GSM1233132 1 0.0000 0.975 1.000 0.000
#> GSM1233139 2 0.0000 0.982 0.000 1.000
#> GSM1233143 2 0.0000 0.982 0.000 1.000
#> GSM1233145 1 0.0000 0.975 1.000 0.000
#> GSM1233067 2 0.0000 0.982 0.000 1.000
#> GSM1233069 2 0.0000 0.982 0.000 1.000
#> GSM1233072 2 0.0000 0.982 0.000 1.000
#> GSM1233086 2 0.0000 0.982 0.000 1.000
#> GSM1233102 1 0.0000 0.975 1.000 0.000
#> GSM1233103 1 0.0000 0.975 1.000 0.000
#> GSM1233107 1 0.2948 0.928 0.948 0.052
#> GSM1233108 1 0.0000 0.975 1.000 0.000
#> GSM1233109 1 0.0000 0.975 1.000 0.000
#> GSM1233110 2 0.7056 0.759 0.192 0.808
#> GSM1233113 2 0.0000 0.982 0.000 1.000
#> GSM1233116 2 0.0000 0.982 0.000 1.000
#> GSM1233120 1 0.0000 0.975 1.000 0.000
#> GSM1233121 2 0.0000 0.982 0.000 1.000
#> GSM1233123 2 0.4161 0.899 0.084 0.916
#> GSM1233124 2 0.0000 0.982 0.000 1.000
#> GSM1233125 1 0.0000 0.975 1.000 0.000
#> GSM1233126 2 0.5059 0.866 0.112 0.888
#> GSM1233127 2 0.0000 0.982 0.000 1.000
#> GSM1233128 1 0.0000 0.975 1.000 0.000
#> GSM1233130 2 0.0938 0.972 0.012 0.988
#> GSM1233131 1 0.0000 0.975 1.000 0.000
#> GSM1233133 1 0.0000 0.975 1.000 0.000
#> GSM1233134 2 0.0000 0.982 0.000 1.000
#> GSM1233135 2 0.0000 0.982 0.000 1.000
#> GSM1233136 2 0.0000 0.982 0.000 1.000
#> GSM1233137 1 0.0000 0.975 1.000 0.000
#> GSM1233138 2 0.0000 0.982 0.000 1.000
#> GSM1233140 1 0.0000 0.975 1.000 0.000
#> GSM1233141 2 0.0000 0.982 0.000 1.000
#> GSM1233142 2 0.0000 0.982 0.000 1.000
#> GSM1233144 1 0.0000 0.975 1.000 0.000
#> GSM1233147 2 0.0000 0.982 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.6280 0.45158 0.000 0.540 0.460
#> GSM1233002 2 0.4504 0.48661 0.196 0.804 0.000
#> GSM1233003 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233014 2 0.0000 0.61265 0.000 1.000 0.000
#> GSM1233015 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233016 2 0.6299 -0.16370 0.476 0.524 0.000
#> GSM1233024 2 0.5706 0.53800 0.000 0.680 0.320
#> GSM1233049 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233064 3 0.1964 0.82148 0.000 0.056 0.944
#> GSM1233068 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233073 2 0.5465 0.34835 0.288 0.712 0.000
#> GSM1233093 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233115 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1232992 2 0.6274 0.45684 0.000 0.544 0.456
#> GSM1232993 2 0.5905 0.52356 0.000 0.648 0.352
#> GSM1233005 2 0.6274 0.45684 0.000 0.544 0.456
#> GSM1233007 2 0.3752 0.59276 0.000 0.856 0.144
#> GSM1233010 2 0.6305 -0.19629 0.484 0.516 0.000
#> GSM1233013 2 0.6280 0.45158 0.000 0.540 0.460
#> GSM1233018 2 0.6280 0.45158 0.000 0.540 0.460
#> GSM1233019 2 0.6252 0.46805 0.000 0.556 0.444
#> GSM1233021 2 0.6274 0.45684 0.000 0.544 0.456
#> GSM1233025 1 0.6260 0.34307 0.552 0.448 0.000
#> GSM1233029 2 0.6140 0.49453 0.000 0.596 0.404
#> GSM1233030 2 0.6274 0.45684 0.000 0.544 0.456
#> GSM1233031 2 0.1163 0.60392 0.028 0.972 0.000
#> GSM1233032 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233035 1 0.2356 0.88017 0.928 0.072 0.000
#> GSM1233038 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233039 3 0.2448 0.81903 0.000 0.076 0.924
#> GSM1233042 2 0.0000 0.61265 0.000 1.000 0.000
#> GSM1233043 2 0.0000 0.61265 0.000 1.000 0.000
#> GSM1233044 1 0.0892 0.92994 0.980 0.020 0.000
#> GSM1233046 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233051 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233054 3 0.6280 0.04278 0.460 0.000 0.540
#> GSM1233057 3 0.0000 0.85366 0.000 0.000 1.000
#> GSM1233060 2 0.1315 0.61307 0.008 0.972 0.020
#> GSM1233062 2 0.5138 0.56423 0.000 0.748 0.252
#> GSM1233075 3 0.0000 0.85366 0.000 0.000 1.000
#> GSM1233078 3 0.6267 0.06928 0.452 0.000 0.548
#> GSM1233079 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233082 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233083 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233091 3 0.8525 0.40329 0.200 0.188 0.612
#> GSM1233095 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233096 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233101 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233105 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233117 2 0.6280 0.45158 0.000 0.540 0.460
#> GSM1233118 3 0.1411 0.83733 0.000 0.036 0.964
#> GSM1233001 3 0.2261 0.80441 0.000 0.068 0.932
#> GSM1233006 2 0.3482 0.59990 0.000 0.872 0.128
#> GSM1233008 2 0.6280 0.45158 0.000 0.540 0.460
#> GSM1233009 2 0.6252 0.46805 0.000 0.556 0.444
#> GSM1233017 2 0.6252 0.46805 0.000 0.556 0.444
#> GSM1233020 2 0.6280 0.45158 0.000 0.540 0.460
#> GSM1233022 2 0.1860 0.61108 0.000 0.948 0.052
#> GSM1233026 2 0.7360 0.39393 0.212 0.692 0.096
#> GSM1233028 2 0.0747 0.60712 0.016 0.984 0.000
#> GSM1233034 3 0.3482 0.71471 0.000 0.128 0.872
#> GSM1233040 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233048 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233056 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233058 2 0.3816 0.52275 0.148 0.852 0.000
#> GSM1233059 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233066 3 0.2066 0.81552 0.000 0.060 0.940
#> GSM1233071 2 0.6252 0.46805 0.000 0.556 0.444
#> GSM1233074 3 0.0000 0.85366 0.000 0.000 1.000
#> GSM1233076 2 0.6111 0.10638 0.000 0.604 0.396
#> GSM1233080 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233088 3 0.2165 0.79845 0.064 0.000 0.936
#> GSM1233090 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233092 2 0.0000 0.61265 0.000 1.000 0.000
#> GSM1233094 2 0.0000 0.61265 0.000 1.000 0.000
#> GSM1233097 2 0.0000 0.61265 0.000 1.000 0.000
#> GSM1233100 2 0.5254 0.42143 0.264 0.736 0.000
#> GSM1233104 2 0.0000 0.61265 0.000 1.000 0.000
#> GSM1233106 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233111 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233122 2 0.6280 0.45158 0.000 0.540 0.460
#> GSM1233146 2 0.0000 0.61265 0.000 1.000 0.000
#> GSM1232994 2 0.6204 0.48256 0.000 0.576 0.424
#> GSM1232996 2 0.6280 0.45158 0.000 0.540 0.460
#> GSM1232997 3 0.0592 0.85185 0.000 0.012 0.988
#> GSM1232998 2 0.0000 0.61265 0.000 1.000 0.000
#> GSM1232999 2 0.0000 0.61265 0.000 1.000 0.000
#> GSM1233000 2 0.6267 0.46096 0.000 0.548 0.452
#> GSM1233004 2 0.9927 0.00435 0.316 0.392 0.292
#> GSM1233011 2 0.6215 0.04376 0.000 0.572 0.428
#> GSM1233012 3 0.2796 0.77310 0.000 0.092 0.908
#> GSM1233023 3 0.1031 0.84598 0.000 0.024 0.976
#> GSM1233027 2 0.0237 0.61283 0.000 0.996 0.004
#> GSM1233033 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233036 3 0.0592 0.85203 0.000 0.012 0.988
#> GSM1233037 3 0.0000 0.85366 0.000 0.000 1.000
#> GSM1233041 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233045 2 0.0000 0.61265 0.000 1.000 0.000
#> GSM1233047 1 0.2625 0.87803 0.916 0.000 0.084
#> GSM1233050 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233052 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233053 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233055 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233061 3 0.3686 0.70145 0.140 0.000 0.860
#> GSM1233063 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233065 3 0.0892 0.84810 0.000 0.020 0.980
#> GSM1233070 2 0.5882 0.52314 0.000 0.652 0.348
#> GSM1233077 3 0.1411 0.83692 0.000 0.036 0.964
#> GSM1233081 1 0.1289 0.92280 0.968 0.000 0.032
#> GSM1233084 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233087 1 0.6168 0.41496 0.588 0.412 0.000
#> GSM1233089 2 0.6299 0.42059 0.000 0.524 0.476
#> GSM1233099 1 0.5363 0.64530 0.724 0.276 0.000
#> GSM1233112 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233085 1 0.1860 0.90731 0.948 0.000 0.052
#> GSM1233098 2 0.6280 0.45189 0.000 0.540 0.460
#> GSM1233114 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233119 2 0.6260 -0.09167 0.448 0.552 0.000
#> GSM1233129 3 0.0424 0.85279 0.000 0.008 0.992
#> GSM1233132 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233139 3 0.6286 -0.29756 0.000 0.464 0.536
#> GSM1233143 3 0.6008 0.01720 0.000 0.372 0.628
#> GSM1233145 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233067 3 0.0592 0.85172 0.000 0.012 0.988
#> GSM1233069 3 0.0000 0.85366 0.000 0.000 1.000
#> GSM1233072 2 0.6280 0.45158 0.000 0.540 0.460
#> GSM1233086 3 0.4399 0.67746 0.000 0.188 0.812
#> GSM1233102 1 0.5465 0.62670 0.712 0.288 0.000
#> GSM1233103 1 0.0237 0.94057 0.996 0.004 0.000
#> GSM1233107 1 0.8118 0.45401 0.648 0.188 0.164
#> GSM1233108 1 0.1031 0.92815 0.976 0.000 0.024
#> GSM1233109 1 0.2165 0.89792 0.936 0.000 0.064
#> GSM1233110 3 0.0000 0.85366 0.000 0.000 1.000
#> GSM1233113 3 0.1289 0.84064 0.000 0.032 0.968
#> GSM1233116 3 0.1964 0.81983 0.000 0.056 0.944
#> GSM1233120 1 0.2448 0.88261 0.924 0.076 0.000
#> GSM1233121 3 0.1753 0.82689 0.000 0.048 0.952
#> GSM1233123 3 0.0000 0.85366 0.000 0.000 1.000
#> GSM1233124 3 0.0000 0.85366 0.000 0.000 1.000
#> GSM1233125 1 0.0892 0.93079 0.980 0.000 0.020
#> GSM1233126 2 0.0592 0.60863 0.012 0.988 0.000
#> GSM1233127 2 0.6260 0.46410 0.000 0.552 0.448
#> GSM1233128 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233130 3 0.1399 0.84038 0.004 0.028 0.968
#> GSM1233131 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233133 1 0.2537 0.88334 0.920 0.000 0.080
#> GSM1233134 3 0.0000 0.85366 0.000 0.000 1.000
#> GSM1233135 3 0.0000 0.85366 0.000 0.000 1.000
#> GSM1233136 3 0.1411 0.83692 0.000 0.036 0.964
#> GSM1233137 1 0.5706 0.53220 0.680 0.000 0.320
#> GSM1233138 2 0.0000 0.61265 0.000 1.000 0.000
#> GSM1233140 1 0.0000 0.94313 1.000 0.000 0.000
#> GSM1233141 2 0.6280 0.45158 0.000 0.540 0.460
#> GSM1233142 2 0.6274 0.45648 0.000 0.544 0.456
#> GSM1233144 1 0.6252 0.23401 0.556 0.000 0.444
#> GSM1233147 2 0.4504 0.45488 0.000 0.804 0.196
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.1004 0.8263 0.000 0.972 0.024 0.004
#> GSM1233002 4 0.2317 0.8000 0.032 0.036 0.004 0.928
#> GSM1233003 1 0.0817 0.9387 0.976 0.000 0.000 0.024
#> GSM1233014 4 0.3808 0.7580 0.000 0.176 0.012 0.812
#> GSM1233015 1 0.0000 0.9457 1.000 0.000 0.000 0.000
#> GSM1233016 4 0.5769 0.6687 0.212 0.064 0.012 0.712
#> GSM1233024 2 0.1716 0.8037 0.000 0.936 0.000 0.064
#> GSM1233049 1 0.0188 0.9456 0.996 0.000 0.004 0.000
#> GSM1233064 2 0.4936 0.4465 0.000 0.624 0.372 0.004
#> GSM1233068 1 0.1474 0.9200 0.948 0.000 0.000 0.052
#> GSM1233073 4 0.1004 0.7949 0.024 0.004 0.000 0.972
#> GSM1233093 1 0.0188 0.9456 0.996 0.000 0.004 0.000
#> GSM1233115 1 0.2124 0.9075 0.924 0.000 0.008 0.068
#> GSM1232992 2 0.0469 0.8280 0.000 0.988 0.012 0.000
#> GSM1232993 2 0.1211 0.8177 0.000 0.960 0.000 0.040
#> GSM1233005 2 0.0927 0.8285 0.000 0.976 0.016 0.008
#> GSM1233007 2 0.6397 0.5351 0.000 0.648 0.144 0.208
#> GSM1233010 4 0.1661 0.7885 0.052 0.000 0.004 0.944
#> GSM1233013 2 0.0469 0.8280 0.000 0.988 0.012 0.000
#> GSM1233018 2 0.0707 0.8276 0.000 0.980 0.020 0.000
#> GSM1233019 2 0.0188 0.8264 0.000 0.996 0.000 0.004
#> GSM1233021 2 0.0779 0.8283 0.000 0.980 0.016 0.004
#> GSM1233025 4 0.4019 0.6948 0.196 0.000 0.012 0.792
#> GSM1233029 2 0.0376 0.8276 0.000 0.992 0.004 0.004
#> GSM1233030 2 0.0188 0.8278 0.000 0.996 0.004 0.000
#> GSM1233031 4 0.1151 0.7996 0.008 0.024 0.000 0.968
#> GSM1233032 1 0.0188 0.9456 0.996 0.000 0.004 0.000
#> GSM1233035 1 0.4257 0.7924 0.812 0.048 0.000 0.140
#> GSM1233038 1 0.1637 0.9205 0.940 0.000 0.000 0.060
#> GSM1233039 3 0.5576 0.0370 0.000 0.444 0.536 0.020
#> GSM1233042 4 0.3088 0.7889 0.000 0.128 0.008 0.864
#> GSM1233043 4 0.3088 0.7889 0.000 0.128 0.008 0.864
#> GSM1233044 1 0.2741 0.8802 0.892 0.000 0.012 0.096
#> GSM1233046 1 0.1909 0.9232 0.940 0.008 0.004 0.048
#> GSM1233051 1 0.0000 0.9457 1.000 0.000 0.000 0.000
#> GSM1233054 3 0.4837 0.4433 0.348 0.000 0.648 0.004
#> GSM1233057 3 0.4720 0.4409 0.000 0.324 0.672 0.004
#> GSM1233060 4 0.6237 0.2366 0.044 0.448 0.004 0.504
#> GSM1233062 2 0.3024 0.7358 0.000 0.852 0.000 0.148
#> GSM1233075 3 0.4677 0.4531 0.000 0.316 0.680 0.004
#> GSM1233078 3 0.1792 0.7178 0.068 0.000 0.932 0.000
#> GSM1233079 1 0.0188 0.9456 0.996 0.000 0.004 0.000
#> GSM1233082 1 0.0707 0.9398 0.980 0.000 0.000 0.020
#> GSM1233083 1 0.1004 0.9408 0.972 0.000 0.004 0.024
#> GSM1233091 3 0.7828 0.4310 0.060 0.120 0.576 0.244
#> GSM1233095 1 0.0188 0.9456 0.996 0.000 0.004 0.000
#> GSM1233096 1 0.0000 0.9457 1.000 0.000 0.000 0.000
#> GSM1233101 1 0.0376 0.9453 0.992 0.000 0.004 0.004
#> GSM1233105 1 0.2011 0.9035 0.920 0.000 0.000 0.080
#> GSM1233117 2 0.0707 0.8280 0.000 0.980 0.020 0.000
#> GSM1233118 2 0.4677 0.5278 0.000 0.680 0.316 0.004
#> GSM1233001 2 0.3052 0.7512 0.000 0.860 0.136 0.004
#> GSM1233006 2 0.3142 0.7445 0.000 0.860 0.008 0.132
#> GSM1233008 2 0.0469 0.8280 0.000 0.988 0.012 0.000
#> GSM1233009 2 0.0188 0.8272 0.000 0.996 0.004 0.000
#> GSM1233017 2 0.0188 0.8264 0.000 0.996 0.000 0.004
#> GSM1233020 2 0.0817 0.8270 0.000 0.976 0.024 0.000
#> GSM1233022 2 0.5158 -0.0420 0.000 0.524 0.004 0.472
#> GSM1233026 4 0.3669 0.7788 0.040 0.032 0.052 0.876
#> GSM1233028 4 0.1256 0.7995 0.000 0.028 0.008 0.964
#> GSM1233034 2 0.2266 0.7935 0.000 0.912 0.084 0.004
#> GSM1233040 1 0.0000 0.9457 1.000 0.000 0.000 0.000
#> GSM1233048 1 0.0188 0.9456 0.996 0.000 0.004 0.000
#> GSM1233056 1 0.0376 0.9455 0.992 0.000 0.004 0.004
#> GSM1233058 4 0.1247 0.7959 0.004 0.012 0.016 0.968
#> GSM1233059 1 0.0000 0.9457 1.000 0.000 0.000 0.000
#> GSM1233066 3 0.0804 0.7410 0.000 0.008 0.980 0.012
#> GSM1233071 2 0.0779 0.8244 0.000 0.980 0.004 0.016
#> GSM1233074 2 0.5070 0.3120 0.000 0.580 0.416 0.004
#> GSM1233076 4 0.6489 0.3689 0.000 0.080 0.372 0.548
#> GSM1233080 1 0.0188 0.9456 0.996 0.000 0.004 0.000
#> GSM1233088 3 0.3852 0.6524 0.012 0.180 0.808 0.000
#> GSM1233090 1 0.0188 0.9456 0.996 0.000 0.004 0.000
#> GSM1233092 4 0.3743 0.7696 0.000 0.160 0.016 0.824
#> GSM1233094 4 0.2944 0.7879 0.000 0.128 0.004 0.868
#> GSM1233097 4 0.0779 0.7963 0.000 0.016 0.004 0.980
#> GSM1233100 4 0.2593 0.7801 0.080 0.016 0.000 0.904
#> GSM1233104 4 0.1109 0.7991 0.000 0.028 0.004 0.968
#> GSM1233106 1 0.0000 0.9457 1.000 0.000 0.000 0.000
#> GSM1233111 1 0.0000 0.9457 1.000 0.000 0.000 0.000
#> GSM1233122 2 0.0592 0.8279 0.000 0.984 0.016 0.000
#> GSM1233146 4 0.3217 0.7884 0.000 0.128 0.012 0.860
#> GSM1232994 2 0.1022 0.8186 0.000 0.968 0.000 0.032
#> GSM1232996 2 0.1004 0.8286 0.000 0.972 0.024 0.004
#> GSM1232997 2 0.4872 0.4543 0.000 0.640 0.356 0.004
#> GSM1232998 4 0.4364 0.7102 0.000 0.220 0.016 0.764
#> GSM1232999 2 0.5452 0.0931 0.000 0.556 0.016 0.428
#> GSM1233000 2 0.0188 0.8274 0.000 0.996 0.004 0.000
#> GSM1233004 4 0.5808 0.2560 0.032 0.000 0.424 0.544
#> GSM1233011 4 0.7500 0.1030 0.000 0.180 0.408 0.412
#> GSM1233012 2 0.2053 0.8022 0.000 0.924 0.072 0.004
#> GSM1233023 2 0.4428 0.5942 0.000 0.720 0.276 0.004
#> GSM1233027 2 0.4253 0.6341 0.000 0.776 0.016 0.208
#> GSM1233033 1 0.0469 0.9428 0.988 0.000 0.000 0.012
#> GSM1233036 2 0.5168 0.0704 0.000 0.504 0.492 0.004
#> GSM1233037 3 0.5212 0.2545 0.004 0.404 0.588 0.004
#> GSM1233041 1 0.0000 0.9457 1.000 0.000 0.000 0.000
#> GSM1233045 4 0.2522 0.7901 0.000 0.076 0.016 0.908
#> GSM1233047 1 0.4103 0.6528 0.744 0.000 0.256 0.000
#> GSM1233050 1 0.0188 0.9456 0.996 0.000 0.004 0.000
#> GSM1233052 1 0.2773 0.8701 0.880 0.000 0.004 0.116
#> GSM1233053 1 0.0188 0.9456 0.996 0.000 0.004 0.000
#> GSM1233055 1 0.0376 0.9455 0.992 0.000 0.004 0.004
#> GSM1233061 3 0.1610 0.7421 0.032 0.016 0.952 0.000
#> GSM1233063 1 0.0000 0.9457 1.000 0.000 0.000 0.000
#> GSM1233065 2 0.4950 0.4263 0.000 0.620 0.376 0.004
#> GSM1233070 2 0.2919 0.7951 0.000 0.896 0.044 0.060
#> GSM1233077 3 0.0376 0.7386 0.000 0.004 0.992 0.004
#> GSM1233081 1 0.4382 0.5769 0.704 0.000 0.296 0.000
#> GSM1233084 1 0.0188 0.9456 0.996 0.000 0.004 0.000
#> GSM1233087 4 0.1716 0.7817 0.064 0.000 0.000 0.936
#> GSM1233089 2 0.1302 0.8242 0.000 0.956 0.044 0.000
#> GSM1233099 4 0.3801 0.6485 0.220 0.000 0.000 0.780
#> GSM1233112 1 0.0524 0.9446 0.988 0.000 0.004 0.008
#> GSM1233085 1 0.4072 0.6597 0.748 0.000 0.252 0.000
#> GSM1233098 2 0.1474 0.8222 0.000 0.948 0.052 0.000
#> GSM1233114 1 0.0707 0.9403 0.980 0.000 0.000 0.020
#> GSM1233119 4 0.0376 0.7935 0.004 0.000 0.004 0.992
#> GSM1233129 2 0.5039 0.3485 0.000 0.592 0.404 0.004
#> GSM1233132 1 0.1302 0.9303 0.956 0.000 0.000 0.044
#> GSM1233139 2 0.0524 0.8278 0.000 0.988 0.008 0.004
#> GSM1233143 2 0.1256 0.8244 0.000 0.964 0.028 0.008
#> GSM1233145 1 0.1716 0.9179 0.936 0.000 0.000 0.064
#> GSM1233067 3 0.5151 0.0171 0.000 0.464 0.532 0.004
#> GSM1233069 3 0.0592 0.7441 0.000 0.016 0.984 0.000
#> GSM1233072 2 0.0707 0.8284 0.000 0.980 0.020 0.000
#> GSM1233086 3 0.5293 0.6021 0.000 0.100 0.748 0.152
#> GSM1233102 4 0.3801 0.6609 0.220 0.000 0.000 0.780
#> GSM1233103 1 0.4044 0.8123 0.820 0.024 0.004 0.152
#> GSM1233107 2 0.8034 -0.1130 0.320 0.384 0.004 0.292
#> GSM1233108 1 0.3486 0.7613 0.812 0.000 0.188 0.000
#> GSM1233109 3 0.4948 0.1660 0.440 0.000 0.560 0.000
#> GSM1233110 3 0.0469 0.7439 0.000 0.012 0.988 0.000
#> GSM1233113 2 0.3870 0.6815 0.000 0.788 0.208 0.004
#> GSM1233116 2 0.4819 0.4959 0.000 0.652 0.344 0.004
#> GSM1233120 4 0.4855 0.3014 0.400 0.000 0.000 0.600
#> GSM1233121 3 0.0336 0.7369 0.000 0.000 0.992 0.008
#> GSM1233123 3 0.0592 0.7443 0.000 0.016 0.984 0.000
#> GSM1233124 3 0.2401 0.7307 0.000 0.092 0.904 0.004
#> GSM1233125 1 0.2868 0.8244 0.864 0.000 0.136 0.000
#> GSM1233126 4 0.3718 0.7631 0.000 0.168 0.012 0.820
#> GSM1233127 2 0.3494 0.7168 0.000 0.824 0.004 0.172
#> GSM1233128 1 0.0000 0.9457 1.000 0.000 0.000 0.000
#> GSM1233130 3 0.0000 0.7400 0.000 0.000 1.000 0.000
#> GSM1233131 1 0.1474 0.9263 0.948 0.000 0.000 0.052
#> GSM1233133 3 0.5000 -0.0114 0.496 0.000 0.504 0.000
#> GSM1233134 3 0.2530 0.7226 0.000 0.100 0.896 0.004
#> GSM1233135 3 0.1305 0.7434 0.000 0.036 0.960 0.004
#> GSM1233136 3 0.0188 0.7389 0.000 0.000 0.996 0.004
#> GSM1233137 3 0.4781 0.4613 0.336 0.000 0.660 0.004
#> GSM1233138 4 0.3625 0.7666 0.000 0.160 0.012 0.828
#> GSM1233140 1 0.0188 0.9450 0.996 0.000 0.004 0.000
#> GSM1233141 2 0.3032 0.7642 0.000 0.868 0.008 0.124
#> GSM1233142 2 0.1489 0.8163 0.000 0.952 0.004 0.044
#> GSM1233144 3 0.4008 0.5968 0.244 0.000 0.756 0.000
#> GSM1233147 4 0.6725 0.4533 0.000 0.104 0.348 0.548
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.1179 0.78092 0.000 0.964 0.016 0.004 0.016
#> GSM1233002 4 0.4971 0.31083 0.052 0.020 0.000 0.716 0.212
#> GSM1233003 1 0.2674 0.83152 0.856 0.000 0.000 0.004 0.140
#> GSM1233014 5 0.5556 0.16114 0.000 0.068 0.000 0.456 0.476
#> GSM1233015 1 0.4407 0.76986 0.760 0.004 0.000 0.064 0.172
#> GSM1233016 5 0.5135 0.27069 0.080 0.012 0.000 0.204 0.704
#> GSM1233024 2 0.4364 0.65121 0.000 0.736 0.000 0.048 0.216
#> GSM1233049 1 0.0000 0.85997 1.000 0.000 0.000 0.000 0.000
#> GSM1233064 2 0.6151 0.47642 0.000 0.612 0.268 0.052 0.068
#> GSM1233068 1 0.4599 0.73995 0.744 0.000 0.000 0.156 0.100
#> GSM1233073 4 0.4718 -0.00825 0.016 0.000 0.000 0.540 0.444
#> GSM1233093 1 0.0162 0.86007 0.996 0.000 0.000 0.000 0.004
#> GSM1233115 1 0.3359 0.77139 0.816 0.000 0.000 0.164 0.020
#> GSM1232992 2 0.0324 0.77924 0.000 0.992 0.004 0.000 0.004
#> GSM1232993 2 0.3506 0.72599 0.000 0.824 0.000 0.044 0.132
#> GSM1233005 2 0.2026 0.77362 0.000 0.924 0.012 0.056 0.008
#> GSM1233007 2 0.7496 0.12669 0.000 0.480 0.068 0.240 0.212
#> GSM1233010 4 0.3412 0.36882 0.028 0.000 0.000 0.820 0.152
#> GSM1233013 2 0.0566 0.77926 0.000 0.984 0.004 0.000 0.012
#> GSM1233018 2 0.1095 0.77947 0.000 0.968 0.012 0.012 0.008
#> GSM1233019 2 0.2189 0.76296 0.000 0.904 0.000 0.012 0.084
#> GSM1233021 2 0.1883 0.77551 0.000 0.932 0.012 0.048 0.008
#> GSM1233025 5 0.6339 0.11701 0.188 0.000 0.000 0.304 0.508
#> GSM1233029 2 0.1725 0.77757 0.000 0.936 0.000 0.044 0.020
#> GSM1233030 2 0.1341 0.77380 0.000 0.944 0.000 0.000 0.056
#> GSM1233031 4 0.4638 0.24041 0.000 0.028 0.000 0.648 0.324
#> GSM1233032 1 0.1638 0.85596 0.932 0.000 0.004 0.000 0.064
#> GSM1233035 5 0.5964 0.04619 0.344 0.032 0.000 0.056 0.568
#> GSM1233038 1 0.3012 0.82727 0.852 0.000 0.000 0.024 0.124
#> GSM1233039 2 0.7696 0.02662 0.000 0.416 0.344 0.136 0.104
#> GSM1233042 4 0.5232 -0.13485 0.000 0.044 0.000 0.500 0.456
#> GSM1233043 4 0.5232 -0.13485 0.000 0.044 0.000 0.500 0.456
#> GSM1233044 1 0.5494 0.71574 0.716 0.000 0.044 0.108 0.132
#> GSM1233046 1 0.5302 0.44752 0.556 0.008 0.004 0.028 0.404
#> GSM1233051 1 0.2017 0.85990 0.912 0.000 0.000 0.008 0.080
#> GSM1233054 3 0.6101 0.44163 0.304 0.004 0.568 0.004 0.120
#> GSM1233057 3 0.6154 0.22649 0.008 0.372 0.528 0.008 0.084
#> GSM1233060 5 0.6362 0.17644 0.016 0.204 0.000 0.196 0.584
#> GSM1233062 2 0.5245 0.53747 0.000 0.640 0.000 0.080 0.280
#> GSM1233075 3 0.5010 0.18952 0.000 0.392 0.572 0.000 0.036
#> GSM1233078 3 0.1872 0.71307 0.052 0.000 0.928 0.000 0.020
#> GSM1233079 1 0.0955 0.85939 0.968 0.000 0.004 0.000 0.028
#> GSM1233082 1 0.3906 0.81834 0.800 0.000 0.000 0.068 0.132
#> GSM1233083 1 0.2193 0.84172 0.900 0.000 0.000 0.008 0.092
#> GSM1233091 4 0.8399 0.23280 0.116 0.112 0.152 0.520 0.100
#> GSM1233095 1 0.0290 0.86013 0.992 0.000 0.000 0.000 0.008
#> GSM1233096 1 0.2358 0.85011 0.888 0.000 0.000 0.008 0.104
#> GSM1233101 1 0.0290 0.86013 0.992 0.000 0.000 0.000 0.008
#> GSM1233105 1 0.4639 0.59071 0.632 0.000 0.000 0.024 0.344
#> GSM1233117 2 0.1787 0.78348 0.000 0.936 0.016 0.004 0.044
#> GSM1233118 2 0.4295 0.62267 0.000 0.724 0.248 0.004 0.024
#> GSM1233001 2 0.2570 0.75423 0.000 0.888 0.084 0.000 0.028
#> GSM1233006 2 0.6158 -0.06383 0.000 0.452 0.000 0.132 0.416
#> GSM1233008 2 0.1483 0.78238 0.000 0.952 0.012 0.008 0.028
#> GSM1233009 2 0.2886 0.74411 0.000 0.844 0.000 0.008 0.148
#> GSM1233017 2 0.2806 0.73813 0.000 0.844 0.000 0.004 0.152
#> GSM1233020 2 0.0960 0.77899 0.000 0.972 0.016 0.004 0.008
#> GSM1233022 5 0.6188 0.20251 0.000 0.284 0.000 0.176 0.540
#> GSM1233026 4 0.4603 0.35418 0.008 0.028 0.008 0.732 0.224
#> GSM1233028 4 0.2358 0.39690 0.000 0.008 0.000 0.888 0.104
#> GSM1233034 2 0.1549 0.77873 0.000 0.944 0.040 0.000 0.016
#> GSM1233040 1 0.1851 0.85786 0.912 0.000 0.000 0.000 0.088
#> GSM1233048 1 0.0404 0.86101 0.988 0.000 0.000 0.000 0.012
#> GSM1233056 1 0.0963 0.85867 0.964 0.000 0.000 0.000 0.036
#> GSM1233058 4 0.0324 0.41639 0.000 0.004 0.000 0.992 0.004
#> GSM1233059 1 0.0162 0.86061 0.996 0.000 0.000 0.000 0.004
#> GSM1233066 3 0.1830 0.71736 0.000 0.004 0.932 0.052 0.012
#> GSM1233071 2 0.4016 0.64527 0.000 0.716 0.000 0.012 0.272
#> GSM1233074 2 0.4677 0.54027 0.000 0.664 0.300 0.000 0.036
#> GSM1233076 4 0.7902 0.14889 0.000 0.076 0.272 0.380 0.272
#> GSM1233080 1 0.0290 0.86013 0.992 0.000 0.000 0.000 0.008
#> GSM1233088 3 0.7602 0.49831 0.048 0.180 0.568 0.060 0.144
#> GSM1233090 1 0.0000 0.85997 1.000 0.000 0.000 0.000 0.000
#> GSM1233092 5 0.5238 0.12992 0.000 0.044 0.000 0.472 0.484
#> GSM1233094 4 0.5049 -0.16645 0.000 0.032 0.000 0.488 0.480
#> GSM1233097 4 0.1831 0.39530 0.000 0.004 0.000 0.920 0.076
#> GSM1233100 4 0.5162 0.21080 0.064 0.000 0.000 0.628 0.308
#> GSM1233104 4 0.3690 0.26848 0.000 0.012 0.000 0.764 0.224
#> GSM1233106 1 0.2573 0.84874 0.880 0.000 0.000 0.016 0.104
#> GSM1233111 1 0.2179 0.85437 0.896 0.000 0.000 0.004 0.100
#> GSM1233122 2 0.1041 0.78089 0.000 0.964 0.004 0.000 0.032
#> GSM1233146 5 0.5459 0.14458 0.000 0.060 0.000 0.468 0.472
#> GSM1232994 2 0.3016 0.74142 0.000 0.848 0.000 0.020 0.132
#> GSM1232996 2 0.1883 0.77620 0.000 0.932 0.012 0.048 0.008
#> GSM1232997 2 0.4302 0.61448 0.000 0.720 0.248 0.000 0.032
#> GSM1232998 4 0.6260 -0.07777 0.000 0.172 0.000 0.516 0.312
#> GSM1232999 2 0.6254 0.03968 0.000 0.480 0.000 0.368 0.152
#> GSM1233000 2 0.1484 0.77635 0.000 0.944 0.000 0.008 0.048
#> GSM1233004 4 0.6395 0.30514 0.084 0.000 0.216 0.624 0.076
#> GSM1233011 4 0.8103 0.13636 0.000 0.184 0.288 0.396 0.132
#> GSM1233012 2 0.2992 0.77587 0.000 0.868 0.068 0.000 0.064
#> GSM1233023 2 0.4000 0.69132 0.000 0.788 0.164 0.004 0.044
#> GSM1233027 2 0.5700 0.42335 0.000 0.628 0.000 0.196 0.176
#> GSM1233033 1 0.2561 0.83819 0.856 0.000 0.000 0.000 0.144
#> GSM1233036 2 0.6616 0.08964 0.000 0.440 0.436 0.048 0.076
#> GSM1233037 3 0.6422 0.07753 0.008 0.416 0.456 0.004 0.116
#> GSM1233041 1 0.1121 0.86024 0.956 0.000 0.000 0.000 0.044
#> GSM1233045 4 0.1648 0.41250 0.000 0.040 0.000 0.940 0.020
#> GSM1233047 1 0.4355 0.65674 0.732 0.000 0.224 0.000 0.044
#> GSM1233050 1 0.0290 0.86064 0.992 0.000 0.000 0.000 0.008
#> GSM1233052 1 0.4678 0.66471 0.712 0.000 0.000 0.224 0.064
#> GSM1233053 1 0.2209 0.84521 0.912 0.000 0.032 0.000 0.056
#> GSM1233055 1 0.1205 0.85829 0.956 0.000 0.000 0.004 0.040
#> GSM1233061 3 0.1626 0.72545 0.016 0.000 0.940 0.000 0.044
#> GSM1233063 1 0.1341 0.85964 0.944 0.000 0.000 0.000 0.056
#> GSM1233065 2 0.5043 0.59029 0.000 0.688 0.252 0.020 0.040
#> GSM1233070 2 0.4436 0.66277 0.000 0.768 0.004 0.088 0.140
#> GSM1233077 3 0.2086 0.71948 0.000 0.008 0.924 0.020 0.048
#> GSM1233081 1 0.4250 0.62544 0.720 0.000 0.252 0.000 0.028
#> GSM1233084 1 0.0609 0.86176 0.980 0.000 0.000 0.000 0.020
#> GSM1233087 4 0.5700 0.18470 0.120 0.000 0.000 0.600 0.280
#> GSM1233089 2 0.1911 0.77898 0.000 0.932 0.028 0.004 0.036
#> GSM1233099 4 0.5631 0.22693 0.164 0.000 0.000 0.636 0.200
#> GSM1233112 1 0.1410 0.85447 0.940 0.000 0.000 0.000 0.060
#> GSM1233085 1 0.4655 0.61430 0.700 0.000 0.248 0.000 0.052
#> GSM1233098 2 0.2482 0.76964 0.000 0.904 0.016 0.016 0.064
#> GSM1233114 1 0.3460 0.82470 0.828 0.000 0.000 0.044 0.128
#> GSM1233119 4 0.3274 0.35535 0.000 0.000 0.000 0.780 0.220
#> GSM1233129 2 0.4911 0.52578 0.000 0.652 0.308 0.008 0.032
#> GSM1233132 1 0.4280 0.76663 0.772 0.000 0.000 0.088 0.140
#> GSM1233139 2 0.2674 0.75408 0.000 0.856 0.004 0.000 0.140
#> GSM1233143 2 0.3731 0.74149 0.000 0.800 0.040 0.000 0.160
#> GSM1233145 1 0.3764 0.78663 0.800 0.000 0.000 0.044 0.156
#> GSM1233067 2 0.4904 0.20116 0.000 0.504 0.472 0.000 0.024
#> GSM1233069 3 0.1630 0.72662 0.000 0.016 0.944 0.004 0.036
#> GSM1233072 2 0.1704 0.77922 0.000 0.928 0.004 0.000 0.068
#> GSM1233086 3 0.6911 0.38659 0.000 0.120 0.568 0.236 0.076
#> GSM1233102 5 0.6642 0.05465 0.228 0.000 0.000 0.352 0.420
#> GSM1233103 1 0.7142 0.01995 0.376 0.008 0.004 0.272 0.340
#> GSM1233107 5 0.7591 0.12919 0.144 0.184 0.000 0.156 0.516
#> GSM1233108 1 0.3412 0.76417 0.820 0.000 0.152 0.000 0.028
#> GSM1233109 3 0.5133 0.29212 0.388 0.000 0.568 0.000 0.044
#> GSM1233110 3 0.0290 0.72951 0.000 0.000 0.992 0.000 0.008
#> GSM1233113 2 0.3449 0.70735 0.000 0.812 0.164 0.000 0.024
#> GSM1233116 2 0.4853 0.56511 0.000 0.664 0.296 0.008 0.032
#> GSM1233120 4 0.6767 -0.04620 0.328 0.000 0.000 0.392 0.280
#> GSM1233121 3 0.1934 0.72303 0.000 0.008 0.932 0.020 0.040
#> GSM1233123 3 0.0162 0.72945 0.000 0.000 0.996 0.000 0.004
#> GSM1233124 3 0.2347 0.71369 0.000 0.056 0.912 0.016 0.016
#> GSM1233125 1 0.3759 0.78646 0.808 0.000 0.136 0.000 0.056
#> GSM1233126 5 0.5016 0.24232 0.000 0.044 0.000 0.348 0.608
#> GSM1233127 2 0.4986 0.62802 0.000 0.688 0.000 0.084 0.228
#> GSM1233128 1 0.1410 0.85883 0.940 0.000 0.000 0.000 0.060
#> GSM1233130 3 0.1522 0.72487 0.000 0.000 0.944 0.012 0.044
#> GSM1233131 1 0.4971 0.72633 0.708 0.000 0.000 0.116 0.176
#> GSM1233133 3 0.5221 0.23134 0.400 0.000 0.552 0.000 0.048
#> GSM1233134 3 0.1914 0.71458 0.000 0.060 0.924 0.000 0.016
#> GSM1233135 3 0.1117 0.73137 0.000 0.020 0.964 0.000 0.016
#> GSM1233136 3 0.2178 0.71755 0.000 0.008 0.920 0.024 0.048
#> GSM1233137 3 0.4960 0.53025 0.268 0.000 0.668 0.000 0.064
#> GSM1233138 5 0.5044 0.20444 0.000 0.036 0.000 0.408 0.556
#> GSM1233140 1 0.2616 0.85278 0.880 0.000 0.020 0.000 0.100
#> GSM1233141 2 0.4691 0.68006 0.000 0.736 0.004 0.076 0.184
#> GSM1233142 2 0.3863 0.72228 0.000 0.796 0.000 0.052 0.152
#> GSM1233144 3 0.4204 0.59970 0.196 0.000 0.756 0.000 0.048
#> GSM1233147 4 0.7567 0.09509 0.000 0.040 0.276 0.348 0.336
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.1010 0.7424 0.000 0.960 0.000 0.004 0.000 0.036
#> GSM1233002 5 0.6678 0.2118 0.100 0.024 0.004 0.376 0.456 0.040
#> GSM1233003 1 0.4082 0.7195 0.792 0.000 0.000 0.064 0.048 0.096
#> GSM1233014 4 0.2532 0.5358 0.000 0.052 0.000 0.884 0.060 0.004
#> GSM1233015 1 0.5446 0.3467 0.504 0.000 0.004 0.004 0.092 0.396
#> GSM1233016 4 0.4842 0.3812 0.040 0.000 0.000 0.720 0.092 0.148
#> GSM1233024 2 0.5174 0.5720 0.000 0.660 0.000 0.140 0.016 0.184
#> GSM1233049 1 0.0260 0.7611 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM1233064 2 0.6738 0.4145 0.000 0.576 0.200 0.040 0.096 0.088
#> GSM1233068 1 0.5577 0.4933 0.588 0.000 0.004 0.004 0.176 0.228
#> GSM1233073 4 0.5276 0.3951 0.044 0.004 0.000 0.688 0.160 0.104
#> GSM1233093 1 0.0547 0.7617 0.980 0.000 0.000 0.000 0.000 0.020
#> GSM1233115 1 0.3642 0.6478 0.760 0.000 0.000 0.000 0.204 0.036
#> GSM1232992 2 0.0291 0.7405 0.000 0.992 0.000 0.004 0.000 0.004
#> GSM1232993 2 0.4870 0.5908 0.000 0.696 0.000 0.168 0.016 0.120
#> GSM1233005 2 0.1116 0.7395 0.000 0.960 0.000 0.008 0.028 0.004
#> GSM1233007 2 0.7361 -0.0722 0.000 0.416 0.088 0.348 0.104 0.044
#> GSM1233010 5 0.4585 0.5392 0.044 0.000 0.000 0.124 0.748 0.084
#> GSM1233013 2 0.0777 0.7410 0.000 0.972 0.000 0.004 0.000 0.024
#> GSM1233018 2 0.0806 0.7406 0.000 0.972 0.000 0.000 0.020 0.008
#> GSM1233019 2 0.1984 0.7350 0.000 0.912 0.000 0.032 0.000 0.056
#> GSM1233021 2 0.0858 0.7398 0.000 0.968 0.000 0.000 0.028 0.004
#> GSM1233025 4 0.6831 0.1371 0.148 0.000 0.000 0.512 0.196 0.144
#> GSM1233029 2 0.1492 0.7445 0.000 0.940 0.000 0.000 0.024 0.036
#> GSM1233030 2 0.1701 0.7346 0.000 0.920 0.000 0.008 0.000 0.072
#> GSM1233031 5 0.5714 0.2040 0.000 0.000 0.000 0.176 0.484 0.340
#> GSM1233032 1 0.3773 0.7194 0.788 0.000 0.012 0.008 0.028 0.164
#> GSM1233035 6 0.5573 0.4588 0.084 0.016 0.000 0.160 0.060 0.680
#> GSM1233038 1 0.4071 0.7124 0.792 0.000 0.000 0.060 0.048 0.100
#> GSM1233039 2 0.8050 -0.1203 0.000 0.340 0.264 0.040 0.236 0.120
#> GSM1233042 4 0.3792 0.5047 0.000 0.044 0.000 0.792 0.144 0.020
#> GSM1233043 4 0.3792 0.5047 0.000 0.044 0.000 0.792 0.144 0.020
#> GSM1233044 1 0.7131 0.4874 0.564 0.000 0.068 0.124 0.116 0.128
#> GSM1233046 6 0.5927 0.2325 0.324 0.000 0.004 0.108 0.028 0.536
#> GSM1233051 1 0.3076 0.7610 0.840 0.000 0.000 0.004 0.044 0.112
#> GSM1233054 3 0.6902 0.2117 0.212 0.000 0.428 0.004 0.056 0.300
#> GSM1233057 3 0.6871 0.1599 0.000 0.280 0.396 0.000 0.052 0.272
#> GSM1233060 6 0.7118 0.0853 0.008 0.116 0.000 0.344 0.120 0.412
#> GSM1233062 2 0.6411 0.3767 0.000 0.524 0.000 0.172 0.056 0.248
#> GSM1233075 3 0.5786 -0.0558 0.000 0.432 0.444 0.000 0.020 0.104
#> GSM1233078 3 0.3277 0.6611 0.020 0.000 0.856 0.012 0.056 0.056
#> GSM1233079 1 0.2820 0.7478 0.860 0.000 0.008 0.008 0.012 0.112
#> GSM1233082 1 0.4719 0.6717 0.692 0.000 0.000 0.008 0.100 0.200
#> GSM1233083 1 0.3089 0.7356 0.856 0.000 0.000 0.040 0.024 0.080
#> GSM1233091 5 0.6973 0.3851 0.052 0.056 0.120 0.028 0.604 0.140
#> GSM1233095 1 0.0363 0.7612 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM1233096 1 0.3909 0.7011 0.748 0.000 0.004 0.004 0.032 0.212
#> GSM1233101 1 0.0858 0.7617 0.968 0.000 0.000 0.000 0.004 0.028
#> GSM1233105 1 0.6553 0.4121 0.512 0.000 0.000 0.160 0.072 0.256
#> GSM1233117 2 0.1398 0.7429 0.000 0.940 0.000 0.008 0.000 0.052
#> GSM1233118 2 0.3595 0.6841 0.000 0.796 0.144 0.000 0.004 0.056
#> GSM1233001 2 0.2784 0.7188 0.000 0.880 0.032 0.004 0.020 0.064
#> GSM1233006 4 0.4527 0.2731 0.000 0.360 0.000 0.604 0.008 0.028
#> GSM1233008 2 0.1124 0.7436 0.000 0.956 0.000 0.000 0.008 0.036
#> GSM1233009 2 0.4274 0.5836 0.000 0.676 0.000 0.024 0.012 0.288
#> GSM1233017 2 0.4224 0.6048 0.000 0.700 0.000 0.036 0.008 0.256
#> GSM1233020 2 0.0291 0.7403 0.000 0.992 0.000 0.004 0.004 0.000
#> GSM1233022 4 0.5617 0.2194 0.000 0.184 0.000 0.608 0.020 0.188
#> GSM1233026 5 0.4123 0.5434 0.008 0.012 0.004 0.120 0.788 0.068
#> GSM1233028 5 0.4355 0.5495 0.000 0.008 0.000 0.164 0.736 0.092
#> GSM1233034 2 0.2758 0.7229 0.000 0.872 0.008 0.004 0.028 0.088
#> GSM1233040 1 0.3908 0.7186 0.764 0.000 0.004 0.008 0.036 0.188
#> GSM1233048 1 0.1333 0.7632 0.944 0.000 0.000 0.000 0.008 0.048
#> GSM1233056 1 0.1577 0.7572 0.940 0.000 0.000 0.016 0.008 0.036
#> GSM1233058 5 0.3530 0.5409 0.004 0.012 0.000 0.200 0.776 0.008
#> GSM1233059 1 0.1082 0.7614 0.956 0.000 0.000 0.000 0.004 0.040
#> GSM1233066 3 0.3051 0.6537 0.000 0.016 0.872 0.032 0.056 0.024
#> GSM1233071 2 0.5545 0.3284 0.000 0.492 0.000 0.096 0.012 0.400
#> GSM1233074 2 0.5128 0.5637 0.000 0.660 0.216 0.000 0.020 0.104
#> GSM1233076 4 0.7895 -0.0193 0.000 0.080 0.256 0.356 0.260 0.048
#> GSM1233080 1 0.0260 0.7616 0.992 0.000 0.000 0.000 0.000 0.008
#> GSM1233088 3 0.7439 0.2410 0.028 0.068 0.448 0.012 0.140 0.304
#> GSM1233090 1 0.0865 0.7609 0.964 0.000 0.000 0.000 0.000 0.036
#> GSM1233092 4 0.2340 0.5368 0.000 0.044 0.000 0.896 0.056 0.004
#> GSM1233094 4 0.3594 0.5125 0.000 0.028 0.000 0.820 0.104 0.048
#> GSM1233097 5 0.4246 0.4069 0.000 0.012 0.000 0.340 0.636 0.012
#> GSM1233100 4 0.6623 -0.0151 0.088 0.004 0.000 0.456 0.356 0.096
#> GSM1233104 4 0.4426 0.1151 0.000 0.020 0.000 0.596 0.376 0.008
#> GSM1233106 1 0.4571 0.6597 0.680 0.000 0.008 0.004 0.048 0.260
#> GSM1233111 1 0.4054 0.7227 0.752 0.000 0.004 0.004 0.052 0.188
#> GSM1233122 2 0.1579 0.7419 0.000 0.944 0.004 0.020 0.008 0.024
#> GSM1233146 4 0.4189 0.5111 0.000 0.044 0.004 0.784 0.120 0.048
#> GSM1232994 2 0.3964 0.6600 0.000 0.764 0.000 0.048 0.012 0.176
#> GSM1232996 2 0.0972 0.7401 0.000 0.964 0.000 0.000 0.028 0.008
#> GSM1232997 2 0.4966 0.6091 0.000 0.700 0.168 0.000 0.032 0.100
#> GSM1232998 4 0.5203 0.3607 0.000 0.152 0.004 0.656 0.180 0.008
#> GSM1232999 2 0.5950 0.1380 0.000 0.516 0.004 0.300 0.172 0.008
#> GSM1233000 2 0.2466 0.7242 0.000 0.872 0.000 0.008 0.008 0.112
#> GSM1233004 5 0.6120 0.4159 0.096 0.000 0.172 0.044 0.640 0.048
#> GSM1233011 5 0.8162 0.0918 0.000 0.196 0.224 0.248 0.304 0.028
#> GSM1233012 2 0.3447 0.7203 0.000 0.816 0.036 0.008 0.004 0.136
#> GSM1233023 2 0.4192 0.6654 0.000 0.780 0.116 0.004 0.024 0.076
#> GSM1233027 2 0.4864 0.3958 0.000 0.624 0.000 0.308 0.056 0.012
#> GSM1233033 1 0.4942 0.6858 0.704 0.000 0.000 0.052 0.064 0.180
#> GSM1233036 3 0.7253 0.0300 0.000 0.360 0.364 0.008 0.092 0.176
#> GSM1233037 6 0.7104 -0.0734 0.012 0.220 0.276 0.000 0.060 0.432
#> GSM1233041 1 0.2575 0.7582 0.880 0.000 0.000 0.004 0.044 0.072
#> GSM1233045 5 0.3719 0.5368 0.000 0.028 0.000 0.200 0.764 0.008
#> GSM1233047 1 0.5787 0.4626 0.604 0.000 0.204 0.004 0.024 0.164
#> GSM1233050 1 0.1152 0.7604 0.952 0.000 0.000 0.000 0.004 0.044
#> GSM1233052 1 0.4834 0.5413 0.660 0.000 0.000 0.000 0.212 0.128
#> GSM1233053 1 0.4449 0.6546 0.736 0.000 0.048 0.004 0.024 0.188
#> GSM1233055 1 0.1503 0.7579 0.944 0.000 0.000 0.016 0.008 0.032
#> GSM1233061 3 0.4038 0.6320 0.032 0.004 0.796 0.004 0.040 0.124
#> GSM1233063 1 0.3160 0.7509 0.840 0.000 0.000 0.008 0.048 0.104
#> GSM1233065 2 0.5002 0.6253 0.000 0.712 0.144 0.000 0.056 0.088
#> GSM1233070 2 0.5025 0.5599 0.000 0.688 0.008 0.216 0.036 0.052
#> GSM1233077 3 0.3352 0.6491 0.000 0.012 0.840 0.008 0.096 0.044
#> GSM1233081 1 0.5537 0.4848 0.632 0.000 0.236 0.004 0.036 0.092
#> GSM1233084 1 0.1251 0.7634 0.956 0.000 0.000 0.008 0.012 0.024
#> GSM1233087 4 0.7056 -0.0752 0.212 0.000 0.000 0.380 0.328 0.080
#> GSM1233089 2 0.1921 0.7357 0.000 0.928 0.004 0.032 0.012 0.024
#> GSM1233099 5 0.7257 0.2388 0.172 0.000 0.000 0.192 0.440 0.196
#> GSM1233112 1 0.2867 0.7382 0.868 0.000 0.000 0.040 0.016 0.076
#> GSM1233085 1 0.6135 0.3613 0.548 0.000 0.264 0.008 0.024 0.156
#> GSM1233098 2 0.2755 0.7204 0.000 0.884 0.012 0.064 0.016 0.024
#> GSM1233114 1 0.5037 0.6475 0.676 0.000 0.000 0.040 0.064 0.220
#> GSM1233119 5 0.5152 0.3248 0.012 0.000 0.004 0.376 0.556 0.052
#> GSM1233129 2 0.4849 0.5946 0.000 0.692 0.200 0.000 0.020 0.088
#> GSM1233132 1 0.5260 0.5599 0.660 0.000 0.000 0.048 0.072 0.220
#> GSM1233139 2 0.4473 0.5728 0.000 0.644 0.004 0.020 0.012 0.320
#> GSM1233143 2 0.5460 0.5483 0.000 0.612 0.060 0.052 0.000 0.276
#> GSM1233145 1 0.4514 0.6803 0.756 0.000 0.000 0.092 0.044 0.108
#> GSM1233067 2 0.5034 0.2779 0.000 0.520 0.404 0.000 0.000 0.076
#> GSM1233069 3 0.2898 0.6580 0.000 0.016 0.872 0.004 0.068 0.040
#> GSM1233072 2 0.2065 0.7430 0.000 0.912 0.000 0.032 0.004 0.052
#> GSM1233086 3 0.6975 0.2571 0.000 0.104 0.496 0.060 0.296 0.044
#> GSM1233102 4 0.6343 0.1838 0.232 0.000 0.000 0.556 0.084 0.128
#> GSM1233103 6 0.5416 0.3406 0.104 0.000 0.000 0.032 0.228 0.636
#> GSM1233107 6 0.6899 0.4081 0.032 0.104 0.004 0.180 0.108 0.572
#> GSM1233108 1 0.4701 0.6215 0.728 0.000 0.180 0.008 0.032 0.052
#> GSM1233109 3 0.6051 0.3296 0.316 0.000 0.548 0.008 0.064 0.064
#> GSM1233110 3 0.1693 0.6692 0.000 0.004 0.932 0.000 0.020 0.044
#> GSM1233113 2 0.3196 0.7052 0.000 0.836 0.096 0.000 0.004 0.064
#> GSM1233116 2 0.4007 0.6564 0.000 0.760 0.184 0.000 0.020 0.036
#> GSM1233120 1 0.7366 -0.2059 0.344 0.000 0.000 0.332 0.184 0.140
#> GSM1233121 3 0.3166 0.6531 0.000 0.012 0.852 0.008 0.092 0.036
#> GSM1233123 3 0.1628 0.6690 0.000 0.008 0.940 0.004 0.012 0.036
#> GSM1233124 3 0.3836 0.6357 0.000 0.056 0.820 0.008 0.040 0.076
#> GSM1233125 1 0.5198 0.6618 0.704 0.000 0.156 0.008 0.052 0.080
#> GSM1233126 4 0.1542 0.5326 0.000 0.016 0.000 0.944 0.016 0.024
#> GSM1233127 2 0.6053 0.4427 0.000 0.556 0.000 0.108 0.056 0.280
#> GSM1233128 1 0.2945 0.7532 0.864 0.000 0.000 0.016 0.048 0.072
#> GSM1233130 3 0.3044 0.6548 0.000 0.012 0.860 0.008 0.088 0.032
#> GSM1233131 1 0.5696 0.5818 0.604 0.000 0.000 0.028 0.148 0.220
#> GSM1233133 3 0.5801 0.4076 0.248 0.000 0.604 0.008 0.032 0.108
#> GSM1233134 3 0.3550 0.6253 0.000 0.072 0.828 0.004 0.016 0.080
#> GSM1233135 3 0.1262 0.6692 0.000 0.016 0.956 0.000 0.008 0.020
#> GSM1233136 3 0.3792 0.6386 0.000 0.016 0.816 0.016 0.104 0.048
#> GSM1233137 3 0.5386 0.4947 0.164 0.000 0.660 0.004 0.024 0.148
#> GSM1233138 4 0.2002 0.5333 0.000 0.020 0.000 0.916 0.056 0.008
#> GSM1233140 1 0.5013 0.7172 0.708 0.000 0.028 0.016 0.064 0.184
#> GSM1233141 2 0.5636 0.5425 0.000 0.620 0.000 0.080 0.060 0.240
#> GSM1233142 2 0.5452 0.5441 0.000 0.628 0.000 0.064 0.056 0.252
#> GSM1233144 3 0.4731 0.5559 0.132 0.000 0.732 0.004 0.024 0.108
#> GSM1233147 4 0.6890 0.2621 0.000 0.064 0.192 0.560 0.136 0.048
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> MAD:skmeans 152 0.759265 0.389 0.8497 2
#> MAD:skmeans 111 0.011603 0.276 0.2045 3
#> MAD:skmeans 130 0.000364 0.450 0.0611 4
#> MAD:skmeans 102 0.000262 0.256 0.0548 5
#> MAD:skmeans 104 0.002420 0.231 0.1247 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 51941 rows and 156 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 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 0.403 0.713 0.863 0.4439 0.524 0.524
#> 3 3 0.305 0.581 0.789 0.4452 0.648 0.427
#> 4 4 0.505 0.652 0.776 0.1458 0.807 0.524
#> 5 5 0.577 0.556 0.753 0.0583 0.954 0.832
#> 6 6 0.663 0.604 0.770 0.0444 0.911 0.654
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
#> GSM1232995 2 0.1843 0.857 0.028 0.972
#> GSM1233002 2 0.7674 0.629 0.224 0.776
#> GSM1233003 1 0.2236 0.773 0.964 0.036
#> GSM1233014 2 0.1184 0.855 0.016 0.984
#> GSM1233015 1 0.9850 0.223 0.572 0.428
#> GSM1233016 1 0.9608 0.567 0.616 0.384
#> GSM1233024 2 0.0376 0.856 0.004 0.996
#> GSM1233049 1 0.0376 0.766 0.996 0.004
#> GSM1233064 2 0.2043 0.856 0.032 0.968
#> GSM1233068 1 0.9795 0.474 0.584 0.416
#> GSM1233073 1 0.9815 0.505 0.580 0.420
#> GSM1233093 1 0.1843 0.759 0.972 0.028
#> GSM1233115 1 0.5737 0.752 0.864 0.136
#> GSM1232992 2 0.0000 0.856 0.000 1.000
#> GSM1232993 2 0.2236 0.858 0.036 0.964
#> GSM1233005 2 0.0376 0.856 0.004 0.996
#> GSM1233007 2 0.0672 0.855 0.008 0.992
#> GSM1233010 2 0.8713 0.497 0.292 0.708
#> GSM1233013 2 0.1843 0.857 0.028 0.972
#> GSM1233018 2 0.0000 0.856 0.000 1.000
#> GSM1233019 2 0.0376 0.856 0.004 0.996
#> GSM1233021 2 0.0000 0.856 0.000 1.000
#> GSM1233025 2 0.9881 0.105 0.436 0.564
#> GSM1233029 2 0.0000 0.856 0.000 1.000
#> GSM1233030 2 0.1414 0.858 0.020 0.980
#> GSM1233031 2 0.8267 0.556 0.260 0.740
#> GSM1233032 1 0.3879 0.767 0.924 0.076
#> GSM1233035 2 0.8763 0.525 0.296 0.704
#> GSM1233038 1 0.2043 0.760 0.968 0.032
#> GSM1233039 2 0.0672 0.857 0.008 0.992
#> GSM1233042 2 0.2948 0.836 0.052 0.948
#> GSM1233043 2 0.0672 0.855 0.008 0.992
#> GSM1233044 1 0.9522 0.584 0.628 0.372
#> GSM1233046 2 0.8763 0.525 0.296 0.704
#> GSM1233051 1 0.9170 0.622 0.668 0.332
#> GSM1233054 1 0.9944 0.355 0.544 0.456
#> GSM1233057 2 0.2043 0.856 0.032 0.968
#> GSM1233060 2 0.8081 0.573 0.248 0.752
#> GSM1233062 2 0.0376 0.856 0.004 0.996
#> GSM1233075 2 0.1843 0.857 0.028 0.972
#> GSM1233078 1 0.9635 0.531 0.612 0.388
#> GSM1233079 1 0.0672 0.766 0.992 0.008
#> GSM1233082 1 0.9170 0.627 0.668 0.332
#> GSM1233083 1 0.1843 0.759 0.972 0.028
#> GSM1233091 2 0.3879 0.839 0.076 0.924
#> GSM1233095 1 0.0000 0.766 1.000 0.000
#> GSM1233096 1 0.2043 0.767 0.968 0.032
#> GSM1233101 1 0.3733 0.768 0.928 0.072
#> GSM1233105 1 0.8267 0.692 0.740 0.260
#> GSM1233117 2 0.1843 0.857 0.028 0.972
#> GSM1233118 2 0.1843 0.857 0.028 0.972
#> GSM1233001 2 0.2043 0.856 0.032 0.968
#> GSM1233006 2 0.0938 0.854 0.012 0.988
#> GSM1233008 2 0.1414 0.859 0.020 0.980
#> GSM1233009 2 0.1843 0.857 0.028 0.972
#> GSM1233017 2 0.0376 0.856 0.004 0.996
#> GSM1233020 2 0.0000 0.856 0.000 1.000
#> GSM1233022 2 0.0376 0.856 0.004 0.996
#> GSM1233026 2 0.7376 0.655 0.208 0.792
#> GSM1233028 2 0.1843 0.852 0.028 0.972
#> GSM1233034 2 0.1843 0.857 0.028 0.972
#> GSM1233040 1 0.1184 0.768 0.984 0.016
#> GSM1233048 1 0.0672 0.766 0.992 0.008
#> GSM1233056 1 0.0000 0.766 1.000 0.000
#> GSM1233058 2 0.8713 0.501 0.292 0.708
#> GSM1233059 1 0.0000 0.766 1.000 0.000
#> GSM1233066 1 0.9710 0.507 0.600 0.400
#> GSM1233071 2 0.8386 0.569 0.268 0.732
#> GSM1233074 2 0.1843 0.857 0.028 0.972
#> GSM1233076 2 0.3879 0.818 0.076 0.924
#> GSM1233080 1 0.0000 0.766 1.000 0.000
#> GSM1233088 2 0.9686 0.238 0.396 0.604
#> GSM1233090 1 0.0376 0.766 0.996 0.004
#> GSM1233092 2 0.1184 0.854 0.016 0.984
#> GSM1233094 2 0.8327 0.551 0.264 0.736
#> GSM1233097 2 0.2778 0.844 0.048 0.952
#> GSM1233100 2 0.8267 0.553 0.260 0.740
#> GSM1233104 2 0.4161 0.814 0.084 0.916
#> GSM1233106 1 0.9635 0.535 0.612 0.388
#> GSM1233111 1 0.5629 0.707 0.868 0.132
#> GSM1233122 2 0.2043 0.856 0.032 0.968
#> GSM1233146 2 0.4022 0.813 0.080 0.920
#> GSM1232994 2 0.0672 0.855 0.008 0.992
#> GSM1232996 2 0.0000 0.856 0.000 1.000
#> GSM1232997 2 0.1843 0.857 0.028 0.972
#> GSM1232998 2 0.0672 0.855 0.008 0.992
#> GSM1232999 2 0.0376 0.856 0.004 0.996
#> GSM1233000 2 0.1843 0.857 0.028 0.972
#> GSM1233004 1 0.9661 0.550 0.608 0.392
#> GSM1233011 2 0.0938 0.857 0.012 0.988
#> GSM1233012 2 0.1843 0.857 0.028 0.972
#> GSM1233023 2 0.1843 0.857 0.028 0.972
#> GSM1233027 2 0.0938 0.854 0.012 0.988
#> GSM1233033 1 0.4431 0.767 0.908 0.092
#> GSM1233036 2 0.2236 0.855 0.036 0.964
#> GSM1233037 2 0.3733 0.840 0.072 0.928
#> GSM1233041 1 0.0376 0.766 0.996 0.004
#> GSM1233045 2 0.1633 0.852 0.024 0.976
#> GSM1233047 1 0.9460 0.573 0.636 0.364
#> GSM1233050 1 0.1633 0.770 0.976 0.024
#> GSM1233052 1 0.7139 0.741 0.804 0.196
#> GSM1233053 1 0.1633 0.770 0.976 0.024
#> GSM1233055 1 0.1843 0.759 0.972 0.028
#> GSM1233061 2 0.5629 0.789 0.132 0.868
#> GSM1233063 1 0.5519 0.760 0.872 0.128
#> GSM1233065 2 0.1843 0.857 0.028 0.972
#> GSM1233070 2 0.0672 0.856 0.008 0.992
#> GSM1233077 2 0.9248 0.378 0.340 0.660
#> GSM1233081 1 0.9393 0.585 0.644 0.356
#> GSM1233084 1 0.0000 0.766 1.000 0.000
#> GSM1233087 1 0.9866 0.479 0.568 0.432
#> GSM1233089 2 0.0376 0.856 0.004 0.996
#> GSM1233099 1 0.9732 0.534 0.596 0.404
#> GSM1233112 1 0.7815 0.708 0.768 0.232
#> GSM1233085 1 0.9129 0.630 0.672 0.328
#> GSM1233098 2 0.1843 0.857 0.028 0.972
#> GSM1233114 1 0.6973 0.738 0.812 0.188
#> GSM1233119 1 0.9754 0.527 0.592 0.408
#> GSM1233129 2 0.2423 0.854 0.040 0.960
#> GSM1233132 1 0.1184 0.768 0.984 0.016
#> GSM1233139 2 0.1843 0.857 0.028 0.972
#> GSM1233143 2 0.2603 0.853 0.044 0.956
#> GSM1233145 1 0.2423 0.764 0.960 0.040
#> GSM1233067 2 0.3114 0.846 0.056 0.944
#> GSM1233069 2 0.9323 0.356 0.348 0.652
#> GSM1233072 2 0.0672 0.857 0.008 0.992
#> GSM1233086 2 0.5737 0.774 0.136 0.864
#> GSM1233102 1 0.9044 0.654 0.680 0.320
#> GSM1233103 2 1.0000 -0.179 0.496 0.504
#> GSM1233107 2 0.8267 0.603 0.260 0.740
#> GSM1233108 1 0.2043 0.772 0.968 0.032
#> GSM1233109 1 0.9427 0.580 0.640 0.360
#> GSM1233110 2 0.9460 0.314 0.364 0.636
#> GSM1233113 2 0.1843 0.857 0.028 0.972
#> GSM1233116 2 0.0672 0.857 0.008 0.992
#> GSM1233120 1 0.8555 0.687 0.720 0.280
#> GSM1233121 2 0.9427 0.320 0.360 0.640
#> GSM1233123 2 0.9393 0.329 0.356 0.644
#> GSM1233124 2 0.9491 0.299 0.368 0.632
#> GSM1233125 1 0.0672 0.766 0.992 0.008
#> GSM1233126 2 0.8207 0.578 0.256 0.744
#> GSM1233127 2 0.2236 0.857 0.036 0.964
#> GSM1233128 1 0.1843 0.759 0.972 0.028
#> GSM1233130 2 0.9393 0.331 0.356 0.644
#> GSM1233131 1 0.8327 0.700 0.736 0.264
#> GSM1233133 1 0.9248 0.613 0.660 0.340
#> GSM1233134 2 0.5408 0.787 0.124 0.876
#> GSM1233135 2 0.9044 0.435 0.320 0.680
#> GSM1233136 2 0.9358 0.342 0.352 0.648
#> GSM1233137 1 0.6531 0.739 0.832 0.168
#> GSM1233138 2 0.1414 0.854 0.020 0.980
#> GSM1233140 1 0.7376 0.729 0.792 0.208
#> GSM1233141 2 0.2043 0.859 0.032 0.968
#> GSM1233142 2 0.0376 0.857 0.004 0.996
#> GSM1233144 1 0.9129 0.630 0.672 0.328
#> GSM1233147 2 0.8016 0.577 0.244 0.756
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.6095 0.1679 0.000 0.608 0.392
#> GSM1233002 2 0.3921 0.6838 0.036 0.884 0.080
#> GSM1233003 1 0.4399 0.7553 0.812 0.000 0.188
#> GSM1233014 2 0.3879 0.6837 0.000 0.848 0.152
#> GSM1233015 2 0.7922 -0.0771 0.060 0.532 0.408
#> GSM1233016 1 0.8796 0.4323 0.508 0.120 0.372
#> GSM1233024 2 0.1753 0.7009 0.000 0.952 0.048
#> GSM1233049 1 0.2261 0.7923 0.932 0.000 0.068
#> GSM1233064 2 0.4974 0.4898 0.000 0.764 0.236
#> GSM1233068 3 0.1989 0.7168 0.004 0.048 0.948
#> GSM1233073 2 0.9390 0.3238 0.184 0.476 0.340
#> GSM1233093 1 0.0000 0.7977 1.000 0.000 0.000
#> GSM1233115 3 0.9172 0.1831 0.296 0.180 0.524
#> GSM1232992 2 0.0000 0.7027 0.000 1.000 0.000
#> GSM1232993 2 0.4842 0.5007 0.000 0.776 0.224
#> GSM1233005 2 0.0000 0.7027 0.000 1.000 0.000
#> GSM1233007 2 0.3340 0.7005 0.000 0.880 0.120
#> GSM1233010 2 0.6810 0.6138 0.068 0.720 0.212
#> GSM1233013 2 0.5882 0.2191 0.000 0.652 0.348
#> GSM1233018 2 0.0000 0.7027 0.000 1.000 0.000
#> GSM1233019 2 0.1529 0.7024 0.000 0.960 0.040
#> GSM1233021 2 0.0000 0.7027 0.000 1.000 0.000
#> GSM1233025 1 0.9749 0.2339 0.444 0.296 0.260
#> GSM1233029 2 0.0000 0.7027 0.000 1.000 0.000
#> GSM1233030 2 0.4504 0.5985 0.000 0.804 0.196
#> GSM1233031 2 0.5207 0.6889 0.052 0.824 0.124
#> GSM1233032 1 0.6252 0.2136 0.556 0.000 0.444
#> GSM1233035 3 0.9621 0.3326 0.252 0.276 0.472
#> GSM1233038 1 0.0000 0.7977 1.000 0.000 0.000
#> GSM1233039 2 0.3192 0.6977 0.000 0.888 0.112
#> GSM1233042 2 0.0592 0.7037 0.012 0.988 0.000
#> GSM1233043 2 0.0000 0.7027 0.000 1.000 0.000
#> GSM1233044 3 0.7295 0.3557 0.072 0.252 0.676
#> GSM1233046 3 0.7337 0.6676 0.140 0.152 0.708
#> GSM1233051 3 0.4883 0.4877 0.208 0.004 0.788
#> GSM1233054 3 0.4883 0.6880 0.004 0.208 0.788
#> GSM1233057 3 0.5560 0.6132 0.000 0.300 0.700
#> GSM1233060 2 0.3253 0.7033 0.036 0.912 0.052
#> GSM1233062 2 0.3551 0.6993 0.000 0.868 0.132
#> GSM1233075 3 0.5835 0.5653 0.000 0.340 0.660
#> GSM1233078 3 0.0000 0.7185 0.000 0.000 1.000
#> GSM1233079 3 0.6168 0.2005 0.412 0.000 0.588
#> GSM1233082 3 0.2703 0.7078 0.056 0.016 0.928
#> GSM1233083 1 0.4399 0.7599 0.812 0.000 0.188
#> GSM1233091 3 0.5591 0.6090 0.000 0.304 0.696
#> GSM1233095 1 0.2261 0.7923 0.932 0.000 0.068
#> GSM1233096 1 0.3816 0.7141 0.852 0.000 0.148
#> GSM1233101 1 0.3573 0.7726 0.876 0.004 0.120
#> GSM1233105 1 0.7916 0.5784 0.636 0.100 0.264
#> GSM1233117 2 0.5785 0.3560 0.000 0.668 0.332
#> GSM1233118 3 0.5882 0.5028 0.000 0.348 0.652
#> GSM1233001 2 0.6286 -0.1232 0.000 0.536 0.464
#> GSM1233006 2 0.3340 0.6898 0.000 0.880 0.120
#> GSM1233008 2 0.6079 0.2813 0.000 0.612 0.388
#> GSM1233009 2 0.4605 0.5378 0.000 0.796 0.204
#> GSM1233017 2 0.1753 0.7009 0.000 0.952 0.048
#> GSM1233020 2 0.2066 0.6888 0.000 0.940 0.060
#> GSM1233022 2 0.2959 0.7076 0.000 0.900 0.100
#> GSM1233026 2 0.6348 0.6263 0.048 0.740 0.212
#> GSM1233028 2 0.3359 0.6981 0.016 0.900 0.084
#> GSM1233034 2 0.4555 0.5518 0.000 0.800 0.200
#> GSM1233040 1 0.3941 0.7109 0.844 0.000 0.156
#> GSM1233048 1 0.0000 0.7977 1.000 0.000 0.000
#> GSM1233056 1 0.0747 0.7982 0.984 0.000 0.016
#> GSM1233058 2 0.6446 0.6260 0.052 0.736 0.212
#> GSM1233059 1 0.0237 0.7983 0.996 0.000 0.004
#> GSM1233066 3 0.0000 0.7185 0.000 0.000 1.000
#> GSM1233071 3 0.4834 0.6838 0.004 0.204 0.792
#> GSM1233074 3 0.5760 0.5795 0.000 0.328 0.672
#> GSM1233076 2 0.5363 0.6085 0.000 0.724 0.276
#> GSM1233080 1 0.1964 0.7952 0.944 0.000 0.056
#> GSM1233088 3 0.5012 0.6625 0.008 0.204 0.788
#> GSM1233090 1 0.0424 0.7991 0.992 0.000 0.008
#> GSM1233092 2 0.4931 0.6402 0.000 0.768 0.232
#> GSM1233094 2 0.6079 0.6308 0.036 0.748 0.216
#> GSM1233097 2 0.5506 0.6501 0.016 0.764 0.220
#> GSM1233100 2 0.5377 0.6664 0.112 0.820 0.068
#> GSM1233104 2 0.5585 0.6574 0.024 0.772 0.204
#> GSM1233106 3 0.1031 0.7147 0.024 0.000 0.976
#> GSM1233111 1 0.3879 0.7141 0.848 0.000 0.152
#> GSM1233122 3 0.6267 0.2505 0.000 0.452 0.548
#> GSM1233146 2 0.2955 0.7027 0.008 0.912 0.080
#> GSM1232994 2 0.0000 0.7027 0.000 1.000 0.000
#> GSM1232996 2 0.0000 0.7027 0.000 1.000 0.000
#> GSM1232997 2 0.6126 0.1377 0.000 0.600 0.400
#> GSM1232998 2 0.3879 0.6837 0.000 0.848 0.152
#> GSM1232999 2 0.0000 0.7027 0.000 1.000 0.000
#> GSM1233000 2 0.4750 0.5170 0.000 0.784 0.216
#> GSM1233004 2 0.9234 0.3312 0.160 0.476 0.364
#> GSM1233011 2 0.6192 0.4123 0.000 0.580 0.420
#> GSM1233012 3 0.5926 0.4568 0.000 0.356 0.644
#> GSM1233023 3 0.5785 0.5865 0.000 0.332 0.668
#> GSM1233027 2 0.0000 0.7027 0.000 1.000 0.000
#> GSM1233033 1 0.3295 0.7871 0.896 0.008 0.096
#> GSM1233036 3 0.4897 0.6946 0.016 0.172 0.812
#> GSM1233037 3 0.4887 0.6674 0.000 0.228 0.772
#> GSM1233041 1 0.0000 0.7977 1.000 0.000 0.000
#> GSM1233045 2 0.2711 0.7074 0.000 0.912 0.088
#> GSM1233047 3 0.1267 0.7247 0.024 0.004 0.972
#> GSM1233050 1 0.2711 0.7886 0.912 0.000 0.088
#> GSM1233052 2 0.9192 0.3978 0.180 0.520 0.300
#> GSM1233053 1 0.6291 0.1513 0.532 0.000 0.468
#> GSM1233055 1 0.0000 0.7977 1.000 0.000 0.000
#> GSM1233061 3 0.3192 0.7250 0.000 0.112 0.888
#> GSM1233063 1 0.4931 0.7114 0.768 0.000 0.232
#> GSM1233065 2 0.6235 0.0854 0.000 0.564 0.436
#> GSM1233070 2 0.5882 0.5514 0.000 0.652 0.348
#> GSM1233077 3 0.2537 0.7025 0.000 0.080 0.920
#> GSM1233081 3 0.0424 0.7198 0.008 0.000 0.992
#> GSM1233084 1 0.0892 0.7980 0.980 0.000 0.020
#> GSM1233087 2 0.9355 0.3561 0.188 0.492 0.320
#> GSM1233089 2 0.3192 0.6969 0.000 0.888 0.112
#> GSM1233099 2 0.9441 0.3388 0.200 0.484 0.316
#> GSM1233112 1 0.5948 0.6034 0.640 0.000 0.360
#> GSM1233085 3 0.3340 0.6876 0.120 0.000 0.880
#> GSM1233098 3 0.6235 0.4185 0.000 0.436 0.564
#> GSM1233114 1 0.4702 0.7125 0.788 0.000 0.212
#> GSM1233119 2 0.9830 0.2521 0.264 0.420 0.316
#> GSM1233129 3 0.5621 0.6037 0.000 0.308 0.692
#> GSM1233132 1 0.0592 0.7992 0.988 0.000 0.012
#> GSM1233139 2 0.6302 -0.1497 0.000 0.520 0.480
#> GSM1233143 3 0.4399 0.6861 0.000 0.188 0.812
#> GSM1233145 1 0.3551 0.7721 0.868 0.000 0.132
#> GSM1233067 3 0.4504 0.6842 0.000 0.196 0.804
#> GSM1233069 3 0.3686 0.7123 0.000 0.140 0.860
#> GSM1233072 2 0.4291 0.6630 0.000 0.820 0.180
#> GSM1233086 3 0.4178 0.6380 0.000 0.172 0.828
#> GSM1233102 1 0.9520 0.3869 0.452 0.196 0.352
#> GSM1233103 3 0.5835 0.6980 0.052 0.164 0.784
#> GSM1233107 3 0.8231 0.5871 0.156 0.208 0.636
#> GSM1233108 3 0.6305 -0.2134 0.484 0.000 0.516
#> GSM1233109 3 0.0592 0.7196 0.012 0.000 0.988
#> GSM1233110 3 0.0000 0.7185 0.000 0.000 1.000
#> GSM1233113 2 0.6299 -0.1370 0.000 0.524 0.476
#> GSM1233116 2 0.5431 0.5980 0.000 0.716 0.284
#> GSM1233120 1 0.9842 0.2732 0.420 0.272 0.308
#> GSM1233121 3 0.3038 0.6729 0.000 0.104 0.896
#> GSM1233123 3 0.3038 0.7257 0.000 0.104 0.896
#> GSM1233124 3 0.2356 0.7309 0.000 0.072 0.928
#> GSM1233125 1 0.4504 0.7620 0.804 0.000 0.196
#> GSM1233126 2 0.8776 0.4801 0.144 0.560 0.296
#> GSM1233127 2 0.6192 0.3334 0.000 0.580 0.420
#> GSM1233128 1 0.0892 0.7994 0.980 0.000 0.020
#> GSM1233130 3 0.0000 0.7185 0.000 0.000 1.000
#> GSM1233131 1 0.8435 0.5400 0.592 0.124 0.284
#> GSM1233133 3 0.0592 0.7210 0.012 0.000 0.988
#> GSM1233134 3 0.3879 0.7103 0.000 0.152 0.848
#> GSM1233135 3 0.4121 0.7136 0.000 0.168 0.832
#> GSM1233136 3 0.5291 0.4672 0.000 0.268 0.732
#> GSM1233137 3 0.5138 0.5400 0.252 0.000 0.748
#> GSM1233138 2 0.6341 0.5908 0.016 0.672 0.312
#> GSM1233140 3 0.5650 0.3090 0.312 0.000 0.688
#> GSM1233141 3 0.6280 0.1111 0.000 0.460 0.540
#> GSM1233142 2 0.4555 0.6650 0.000 0.800 0.200
#> GSM1233144 3 0.0892 0.7202 0.020 0.000 0.980
#> GSM1233147 2 0.5397 0.5992 0.000 0.720 0.280
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.3249 0.7589 0.000 0.852 0.140 0.008
#> GSM1233002 4 0.4679 0.4807 0.000 0.352 0.000 0.648
#> GSM1233003 4 0.6176 0.4004 0.368 0.000 0.060 0.572
#> GSM1233014 2 0.7128 0.4056 0.000 0.528 0.152 0.320
#> GSM1233015 2 0.3264 0.7650 0.004 0.876 0.096 0.024
#> GSM1233016 4 0.5506 0.5562 0.268 0.016 0.024 0.692
#> GSM1233024 2 0.2345 0.7845 0.000 0.900 0.000 0.100
#> GSM1233049 1 0.1724 0.8296 0.948 0.000 0.032 0.020
#> GSM1233064 2 0.0817 0.7909 0.000 0.976 0.024 0.000
#> GSM1233068 3 0.1722 0.7882 0.000 0.008 0.944 0.048
#> GSM1233073 4 0.5276 0.6599 0.004 0.084 0.156 0.756
#> GSM1233093 1 0.0000 0.8392 1.000 0.000 0.000 0.000
#> GSM1233115 4 0.6405 0.6273 0.092 0.072 0.112 0.724
#> GSM1232992 2 0.0000 0.7892 0.000 1.000 0.000 0.000
#> GSM1232993 2 0.0927 0.7910 0.000 0.976 0.008 0.016
#> GSM1233005 2 0.0000 0.7892 0.000 1.000 0.000 0.000
#> GSM1233007 2 0.3610 0.7213 0.000 0.800 0.000 0.200
#> GSM1233010 4 0.7897 0.5311 0.036 0.300 0.140 0.524
#> GSM1233013 2 0.1389 0.7866 0.000 0.952 0.048 0.000
#> GSM1233018 2 0.0000 0.7892 0.000 1.000 0.000 0.000
#> GSM1233019 2 0.1716 0.7858 0.000 0.936 0.000 0.064
#> GSM1233021 2 0.0000 0.7892 0.000 1.000 0.000 0.000
#> GSM1233025 4 0.5563 0.5844 0.248 0.028 0.020 0.704
#> GSM1233029 2 0.1118 0.7836 0.000 0.964 0.000 0.036
#> GSM1233030 2 0.2334 0.7787 0.000 0.908 0.004 0.088
#> GSM1233031 2 0.5878 0.5675 0.000 0.632 0.056 0.312
#> GSM1233032 1 0.4936 0.5630 0.700 0.000 0.280 0.020
#> GSM1233035 2 0.8644 0.3973 0.076 0.464 0.312 0.148
#> GSM1233038 1 0.1389 0.8276 0.952 0.000 0.000 0.048
#> GSM1233039 2 0.4855 0.2128 0.000 0.600 0.000 0.400
#> GSM1233042 2 0.3074 0.7343 0.000 0.848 0.000 0.152
#> GSM1233043 2 0.3172 0.7311 0.000 0.840 0.000 0.160
#> GSM1233044 3 0.5057 0.5480 0.004 0.044 0.748 0.204
#> GSM1233046 3 0.5517 0.6524 0.020 0.036 0.724 0.220
#> GSM1233051 4 0.7437 0.4138 0.136 0.008 0.380 0.476
#> GSM1233054 3 0.1929 0.7999 0.000 0.024 0.940 0.036
#> GSM1233057 3 0.2266 0.7861 0.000 0.084 0.912 0.004
#> GSM1233060 2 0.3569 0.7507 0.000 0.804 0.000 0.196
#> GSM1233062 2 0.5369 0.7225 0.000 0.744 0.144 0.112
#> GSM1233075 3 0.4879 0.7582 0.000 0.092 0.780 0.128
#> GSM1233078 3 0.3942 0.7309 0.000 0.000 0.764 0.236
#> GSM1233079 1 0.6813 0.4024 0.576 0.000 0.292 0.132
#> GSM1233082 3 0.4594 0.4021 0.008 0.000 0.712 0.280
#> GSM1233083 4 0.5772 0.5116 0.260 0.000 0.068 0.672
#> GSM1233091 3 0.2480 0.7793 0.000 0.088 0.904 0.008
#> GSM1233095 1 0.3523 0.7713 0.856 0.000 0.032 0.112
#> GSM1233096 1 0.1109 0.8357 0.968 0.000 0.004 0.028
#> GSM1233101 1 0.5923 0.5966 0.696 0.000 0.176 0.128
#> GSM1233105 4 0.6402 0.4936 0.292 0.012 0.068 0.628
#> GSM1233117 2 0.3149 0.7786 0.000 0.880 0.032 0.088
#> GSM1233118 3 0.6584 0.3809 0.000 0.336 0.568 0.096
#> GSM1233001 2 0.2976 0.7588 0.000 0.872 0.120 0.008
#> GSM1233006 2 0.4194 0.7161 0.000 0.764 0.008 0.228
#> GSM1233008 2 0.4595 0.7247 0.000 0.780 0.176 0.044
#> GSM1233009 2 0.0469 0.7911 0.000 0.988 0.012 0.000
#> GSM1233017 2 0.2149 0.7788 0.000 0.912 0.000 0.088
#> GSM1233020 2 0.0524 0.7916 0.000 0.988 0.004 0.008
#> GSM1233022 2 0.5132 0.7377 0.000 0.748 0.068 0.184
#> GSM1233026 4 0.7354 0.4411 0.000 0.352 0.168 0.480
#> GSM1233028 2 0.5905 0.6296 0.000 0.700 0.144 0.156
#> GSM1233034 2 0.1629 0.7927 0.000 0.952 0.024 0.024
#> GSM1233040 1 0.0779 0.8386 0.980 0.000 0.004 0.016
#> GSM1233048 1 0.1867 0.8180 0.928 0.000 0.000 0.072
#> GSM1233056 1 0.0000 0.8392 1.000 0.000 0.000 0.000
#> GSM1233058 4 0.5770 0.6575 0.000 0.140 0.148 0.712
#> GSM1233059 1 0.0000 0.8392 1.000 0.000 0.000 0.000
#> GSM1233066 3 0.1474 0.7911 0.000 0.000 0.948 0.052
#> GSM1233071 3 0.4174 0.7549 0.000 0.044 0.816 0.140
#> GSM1233074 3 0.3991 0.7335 0.000 0.172 0.808 0.020
#> GSM1233076 4 0.3962 0.6442 0.000 0.152 0.028 0.820
#> GSM1233080 1 0.0817 0.8366 0.976 0.000 0.024 0.000
#> GSM1233088 3 0.4514 0.7592 0.000 0.056 0.796 0.148
#> GSM1233090 1 0.0000 0.8392 1.000 0.000 0.000 0.000
#> GSM1233092 4 0.3893 0.6070 0.000 0.196 0.008 0.796
#> GSM1233094 2 0.7599 0.2802 0.000 0.448 0.208 0.344
#> GSM1233097 4 0.7243 0.0161 0.000 0.404 0.144 0.452
#> GSM1233100 2 0.6696 0.5042 0.004 0.604 0.112 0.280
#> GSM1233104 2 0.7268 0.2530 0.000 0.476 0.152 0.372
#> GSM1233106 3 0.0921 0.7888 0.000 0.000 0.972 0.028
#> GSM1233111 1 0.1256 0.8350 0.964 0.000 0.008 0.028
#> GSM1233122 2 0.3907 0.7623 0.000 0.836 0.044 0.120
#> GSM1233146 2 0.5630 0.6691 0.000 0.724 0.140 0.136
#> GSM1232994 2 0.0000 0.7892 0.000 1.000 0.000 0.000
#> GSM1232996 2 0.0469 0.7881 0.000 0.988 0.000 0.012
#> GSM1232997 2 0.3870 0.7276 0.000 0.788 0.208 0.004
#> GSM1232998 2 0.6719 0.5151 0.000 0.608 0.152 0.240
#> GSM1232999 2 0.1118 0.7836 0.000 0.964 0.000 0.036
#> GSM1233000 2 0.0592 0.7906 0.000 0.984 0.016 0.000
#> GSM1233004 4 0.4525 0.6511 0.000 0.116 0.080 0.804
#> GSM1233011 4 0.6547 0.6017 0.000 0.124 0.260 0.616
#> GSM1233012 2 0.7113 0.3035 0.000 0.484 0.384 0.132
#> GSM1233023 3 0.2888 0.7726 0.000 0.124 0.872 0.004
#> GSM1233027 2 0.1118 0.7836 0.000 0.964 0.000 0.036
#> GSM1233033 1 0.5060 0.1189 0.584 0.000 0.004 0.412
#> GSM1233036 3 0.3080 0.7755 0.000 0.024 0.880 0.096
#> GSM1233037 3 0.3439 0.8016 0.000 0.048 0.868 0.084
#> GSM1233041 1 0.0188 0.8388 0.996 0.000 0.000 0.004
#> GSM1233045 2 0.5070 0.6618 0.000 0.748 0.060 0.192
#> GSM1233047 3 0.0921 0.7911 0.000 0.000 0.972 0.028
#> GSM1233050 1 0.2473 0.8046 0.908 0.000 0.080 0.012
#> GSM1233052 4 0.8168 0.6064 0.056 0.196 0.200 0.548
#> GSM1233053 1 0.5141 0.7032 0.756 0.000 0.160 0.084
#> GSM1233055 1 0.1940 0.8124 0.924 0.000 0.000 0.076
#> GSM1233061 3 0.1970 0.7907 0.000 0.008 0.932 0.060
#> GSM1233063 4 0.6064 0.2680 0.444 0.000 0.044 0.512
#> GSM1233065 2 0.5184 0.5866 0.000 0.672 0.304 0.024
#> GSM1233070 4 0.6871 0.4853 0.000 0.240 0.168 0.592
#> GSM1233077 4 0.4624 0.2638 0.000 0.000 0.340 0.660
#> GSM1233081 3 0.3688 0.7152 0.000 0.000 0.792 0.208
#> GSM1233084 1 0.0188 0.8388 0.996 0.000 0.000 0.004
#> GSM1233087 4 0.4890 0.6673 0.000 0.080 0.144 0.776
#> GSM1233089 2 0.2918 0.7701 0.000 0.876 0.008 0.116
#> GSM1233099 4 0.5596 0.6586 0.004 0.088 0.180 0.728
#> GSM1233112 4 0.5142 0.5803 0.192 0.000 0.064 0.744
#> GSM1233085 3 0.3105 0.7698 0.004 0.000 0.856 0.140
#> GSM1233098 2 0.5132 0.0899 0.000 0.548 0.448 0.004
#> GSM1233114 1 0.5953 0.4452 0.656 0.000 0.076 0.268
#> GSM1233119 4 0.4825 0.6660 0.020 0.036 0.152 0.792
#> GSM1233129 3 0.2271 0.7825 0.000 0.076 0.916 0.008
#> GSM1233132 1 0.2401 0.8145 0.904 0.000 0.004 0.092
#> GSM1233139 2 0.3142 0.7530 0.000 0.860 0.132 0.008
#> GSM1233143 3 0.3606 0.7517 0.000 0.024 0.844 0.132
#> GSM1233145 4 0.5592 0.3641 0.404 0.000 0.024 0.572
#> GSM1233067 3 0.3958 0.7641 0.000 0.024 0.816 0.160
#> GSM1233069 3 0.3266 0.7633 0.000 0.000 0.832 0.168
#> GSM1233072 2 0.3161 0.7669 0.000 0.864 0.012 0.124
#> GSM1233086 3 0.4094 0.7582 0.000 0.056 0.828 0.116
#> GSM1233102 4 0.5134 0.6400 0.120 0.004 0.104 0.772
#> GSM1233103 3 0.6703 0.4685 0.000 0.232 0.612 0.156
#> GSM1233107 3 0.7359 0.2515 0.000 0.184 0.504 0.312
#> GSM1233108 4 0.7007 0.3676 0.144 0.000 0.308 0.548
#> GSM1233109 4 0.4955 0.1513 0.000 0.000 0.444 0.556
#> GSM1233110 3 0.2921 0.7556 0.000 0.000 0.860 0.140
#> GSM1233113 2 0.3156 0.7755 0.000 0.884 0.068 0.048
#> GSM1233116 2 0.6490 0.6578 0.000 0.640 0.156 0.204
#> GSM1233120 4 0.4562 0.6136 0.152 0.000 0.056 0.792
#> GSM1233121 3 0.4624 0.7532 0.000 0.052 0.784 0.164
#> GSM1233123 3 0.2921 0.7591 0.000 0.000 0.860 0.140
#> GSM1233124 3 0.2011 0.7874 0.000 0.000 0.920 0.080
#> GSM1233125 1 0.6395 0.0166 0.472 0.000 0.064 0.464
#> GSM1233126 4 0.4254 0.6687 0.032 0.024 0.108 0.836
#> GSM1233127 2 0.6388 0.6503 0.000 0.652 0.156 0.192
#> GSM1233128 1 0.0672 0.8381 0.984 0.000 0.008 0.008
#> GSM1233130 4 0.4776 0.2581 0.000 0.000 0.376 0.624
#> GSM1233131 4 0.5519 0.5005 0.316 0.004 0.028 0.652
#> GSM1233133 3 0.1302 0.7954 0.000 0.000 0.956 0.044
#> GSM1233134 3 0.2334 0.8018 0.000 0.004 0.908 0.088
#> GSM1233135 3 0.3681 0.7681 0.000 0.008 0.816 0.176
#> GSM1233136 4 0.5198 0.4310 0.000 0.040 0.252 0.708
#> GSM1233137 3 0.3760 0.7489 0.028 0.000 0.836 0.136
#> GSM1233138 4 0.5080 0.6525 0.000 0.092 0.144 0.764
#> GSM1233140 3 0.4635 0.5673 0.268 0.000 0.720 0.012
#> GSM1233141 3 0.6984 0.4017 0.000 0.236 0.580 0.184
#> GSM1233142 2 0.5812 0.6930 0.000 0.708 0.156 0.136
#> GSM1233144 3 0.2814 0.7607 0.000 0.000 0.868 0.132
#> GSM1233147 4 0.2775 0.6621 0.000 0.084 0.020 0.896
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.1478 0.7582 0.000 0.936 0.064 0.000 0.000
#> GSM1233002 4 0.6304 0.3032 0.000 0.156 0.000 0.460 0.384
#> GSM1233003 5 0.3837 0.3482 0.164 0.000 0.024 0.012 0.800
#> GSM1233014 2 0.7466 0.3591 0.000 0.460 0.056 0.212 0.272
#> GSM1233015 2 0.3590 0.7299 0.000 0.828 0.080 0.000 0.092
#> GSM1233016 5 0.6024 0.2219 0.116 0.000 0.000 0.412 0.472
#> GSM1233024 2 0.3074 0.7328 0.000 0.804 0.000 0.196 0.000
#> GSM1233049 1 0.0867 0.7460 0.976 0.000 0.008 0.008 0.008
#> GSM1233064 2 0.0404 0.7619 0.000 0.988 0.012 0.000 0.000
#> GSM1233068 3 0.0963 0.7997 0.000 0.000 0.964 0.000 0.036
#> GSM1233073 5 0.6364 -0.2397 0.004 0.032 0.064 0.416 0.484
#> GSM1233093 1 0.0404 0.7538 0.988 0.000 0.000 0.000 0.012
#> GSM1233115 4 0.7074 0.4560 0.120 0.052 0.044 0.620 0.164
#> GSM1232992 2 0.0000 0.7611 0.000 1.000 0.000 0.000 0.000
#> GSM1232993 2 0.0000 0.7611 0.000 1.000 0.000 0.000 0.000
#> GSM1233005 2 0.0000 0.7611 0.000 1.000 0.000 0.000 0.000
#> GSM1233007 2 0.4367 0.5367 0.000 0.620 0.000 0.372 0.008
#> GSM1233010 4 0.6294 0.5169 0.000 0.188 0.076 0.644 0.092
#> GSM1233013 2 0.0609 0.7610 0.000 0.980 0.020 0.000 0.000
#> GSM1233018 2 0.0000 0.7611 0.000 1.000 0.000 0.000 0.000
#> GSM1233019 2 0.1608 0.7544 0.000 0.928 0.000 0.072 0.000
#> GSM1233021 2 0.0162 0.7614 0.000 0.996 0.000 0.004 0.000
#> GSM1233025 4 0.4294 0.4980 0.112 0.008 0.000 0.788 0.092
#> GSM1233029 2 0.2471 0.7247 0.000 0.864 0.000 0.136 0.000
#> GSM1233030 2 0.2077 0.7506 0.000 0.908 0.008 0.084 0.000
#> GSM1233031 2 0.6747 0.5167 0.000 0.540 0.024 0.208 0.228
#> GSM1233032 1 0.4477 0.5099 0.708 0.000 0.252 0.000 0.040
#> GSM1233035 2 0.9034 0.2376 0.064 0.392 0.228 0.120 0.196
#> GSM1233038 5 0.3534 0.2518 0.256 0.000 0.000 0.000 0.744
#> GSM1233039 4 0.4283 0.2145 0.000 0.456 0.000 0.544 0.000
#> GSM1233042 2 0.5117 0.5685 0.000 0.652 0.000 0.072 0.276
#> GSM1233043 2 0.5578 0.5357 0.000 0.616 0.000 0.112 0.272
#> GSM1233044 3 0.5850 0.5165 0.004 0.028 0.680 0.156 0.132
#> GSM1233046 3 0.6646 0.4246 0.024 0.008 0.568 0.132 0.268
#> GSM1233051 4 0.7293 0.2484 0.044 0.000 0.324 0.448 0.184
#> GSM1233054 3 0.0992 0.8071 0.000 0.008 0.968 0.024 0.000
#> GSM1233057 3 0.1282 0.8026 0.000 0.044 0.952 0.004 0.000
#> GSM1233060 2 0.5009 0.5972 0.000 0.652 0.000 0.060 0.288
#> GSM1233062 2 0.4537 0.7200 0.000 0.740 0.076 0.184 0.000
#> GSM1233075 3 0.2661 0.7966 0.000 0.056 0.888 0.056 0.000
#> GSM1233078 3 0.4288 0.7305 0.012 0.000 0.732 0.240 0.016
#> GSM1233079 1 0.5015 0.4711 0.684 0.000 0.252 0.056 0.008
#> GSM1233082 3 0.5414 0.3260 0.000 0.000 0.624 0.284 0.092
#> GSM1233083 4 0.6617 0.3015 0.116 0.000 0.036 0.540 0.308
#> GSM1233091 3 0.1549 0.7996 0.000 0.016 0.944 0.000 0.040
#> GSM1233095 1 0.1538 0.7319 0.948 0.000 0.008 0.008 0.036
#> GSM1233096 1 0.4235 0.4514 0.576 0.000 0.000 0.000 0.424
#> GSM1233101 1 0.3794 0.6628 0.832 0.000 0.080 0.016 0.072
#> GSM1233105 5 0.3818 0.3680 0.144 0.000 0.016 0.028 0.812
#> GSM1233117 2 0.2305 0.7507 0.000 0.896 0.012 0.092 0.000
#> GSM1233118 3 0.5525 0.4382 0.000 0.288 0.612 0.100 0.000
#> GSM1233001 2 0.2280 0.7337 0.000 0.880 0.120 0.000 0.000
#> GSM1233006 2 0.4088 0.7137 0.000 0.776 0.000 0.168 0.056
#> GSM1233008 2 0.3409 0.7170 0.000 0.816 0.160 0.024 0.000
#> GSM1233009 2 0.0162 0.7618 0.000 0.996 0.004 0.000 0.000
#> GSM1233017 2 0.1792 0.7511 0.000 0.916 0.000 0.084 0.000
#> GSM1233020 2 0.0000 0.7611 0.000 1.000 0.000 0.000 0.000
#> GSM1233022 2 0.5816 0.6537 0.000 0.652 0.032 0.232 0.084
#> GSM1233026 4 0.5640 0.5459 0.000 0.156 0.080 0.704 0.060
#> GSM1233028 2 0.6543 0.5838 0.000 0.628 0.076 0.140 0.156
#> GSM1233034 2 0.1012 0.7625 0.000 0.968 0.020 0.012 0.000
#> GSM1233040 1 0.4227 0.4560 0.580 0.000 0.000 0.000 0.420
#> GSM1233048 1 0.1410 0.7424 0.940 0.000 0.000 0.000 0.060
#> GSM1233056 1 0.0404 0.7538 0.988 0.000 0.000 0.000 0.012
#> GSM1233058 4 0.6092 0.5411 0.000 0.096 0.072 0.668 0.164
#> GSM1233059 1 0.0404 0.7538 0.988 0.000 0.000 0.000 0.012
#> GSM1233066 3 0.0880 0.8026 0.000 0.000 0.968 0.032 0.000
#> GSM1233071 3 0.3370 0.7495 0.000 0.028 0.824 0.148 0.000
#> GSM1233074 3 0.1965 0.7833 0.000 0.096 0.904 0.000 0.000
#> GSM1233076 4 0.2450 0.5787 0.000 0.028 0.000 0.896 0.076
#> GSM1233080 1 0.0162 0.7522 0.996 0.000 0.004 0.000 0.000
#> GSM1233088 3 0.4751 0.7285 0.000 0.044 0.752 0.172 0.032
#> GSM1233090 1 0.0404 0.7538 0.988 0.000 0.000 0.000 0.012
#> GSM1233092 4 0.3688 0.5568 0.000 0.060 0.000 0.816 0.124
#> GSM1233094 2 0.7889 0.2052 0.000 0.376 0.140 0.124 0.360
#> GSM1233097 5 0.7707 -0.1412 0.000 0.356 0.064 0.212 0.368
#> GSM1233100 2 0.6731 0.3755 0.000 0.480 0.056 0.080 0.384
#> GSM1233104 2 0.7611 0.2895 0.000 0.432 0.060 0.228 0.280
#> GSM1233106 3 0.0794 0.8003 0.000 0.000 0.972 0.000 0.028
#> GSM1233111 1 0.4262 0.4287 0.560 0.000 0.000 0.000 0.440
#> GSM1233122 2 0.3098 0.7332 0.000 0.836 0.016 0.148 0.000
#> GSM1233146 2 0.7032 0.4696 0.000 0.528 0.056 0.144 0.272
#> GSM1232994 2 0.0000 0.7611 0.000 1.000 0.000 0.000 0.000
#> GSM1232996 2 0.1544 0.7531 0.000 0.932 0.000 0.068 0.000
#> GSM1232997 2 0.3274 0.6785 0.000 0.780 0.220 0.000 0.000
#> GSM1232998 2 0.6324 0.5830 0.000 0.628 0.056 0.212 0.104
#> GSM1232999 2 0.2471 0.7247 0.000 0.864 0.000 0.136 0.000
#> GSM1233000 2 0.0162 0.7612 0.000 0.996 0.004 0.000 0.000
#> GSM1233004 4 0.3784 0.5541 0.000 0.088 0.016 0.832 0.064
#> GSM1233011 4 0.4651 0.5520 0.000 0.092 0.156 0.748 0.004
#> GSM1233012 2 0.6257 0.2518 0.000 0.460 0.392 0.148 0.000
#> GSM1233023 3 0.1478 0.7980 0.000 0.064 0.936 0.000 0.000
#> GSM1233027 2 0.2471 0.7247 0.000 0.864 0.000 0.136 0.000
#> GSM1233033 5 0.5163 0.1408 0.296 0.000 0.000 0.068 0.636
#> GSM1233036 3 0.2193 0.7861 0.000 0.000 0.900 0.092 0.008
#> GSM1233037 3 0.1753 0.8078 0.000 0.032 0.936 0.032 0.000
#> GSM1233041 1 0.4138 0.4741 0.616 0.000 0.000 0.000 0.384
#> GSM1233045 2 0.6771 0.4326 0.000 0.544 0.028 0.196 0.232
#> GSM1233047 3 0.0579 0.8046 0.000 0.000 0.984 0.008 0.008
#> GSM1233050 1 0.1485 0.7433 0.948 0.000 0.020 0.000 0.032
#> GSM1233052 4 0.8295 0.2632 0.048 0.124 0.076 0.396 0.356
#> GSM1233053 1 0.3272 0.7004 0.860 0.000 0.072 0.008 0.060
#> GSM1233055 1 0.0609 0.7518 0.980 0.000 0.000 0.000 0.020
#> GSM1233061 3 0.1831 0.8077 0.000 0.000 0.920 0.076 0.004
#> GSM1233063 5 0.7058 0.1465 0.264 0.000 0.036 0.196 0.504
#> GSM1233065 2 0.5051 0.5850 0.000 0.680 0.248 0.068 0.004
#> GSM1233070 4 0.5314 0.5105 0.000 0.124 0.080 0.736 0.060
#> GSM1233077 4 0.3013 0.4645 0.000 0.000 0.160 0.832 0.008
#> GSM1233081 3 0.4774 0.5714 0.012 0.000 0.644 0.328 0.016
#> GSM1233084 1 0.3966 0.5298 0.664 0.000 0.000 0.000 0.336
#> GSM1233087 4 0.6180 0.3369 0.000 0.048 0.044 0.504 0.404
#> GSM1233089 2 0.2516 0.7386 0.000 0.860 0.000 0.140 0.000
#> GSM1233099 5 0.4863 -0.1937 0.000 0.016 0.008 0.384 0.592
#> GSM1233112 5 0.6627 -0.1118 0.096 0.000 0.036 0.400 0.468
#> GSM1233085 3 0.3170 0.7840 0.012 0.000 0.852 0.120 0.016
#> GSM1233098 2 0.4440 0.0580 0.000 0.528 0.468 0.004 0.000
#> GSM1233114 5 0.6058 -0.0142 0.292 0.000 0.036 0.072 0.600
#> GSM1233119 4 0.3720 0.5526 0.000 0.000 0.012 0.760 0.228
#> GSM1233129 3 0.0963 0.8008 0.000 0.036 0.964 0.000 0.000
#> GSM1233132 1 0.4009 0.5614 0.684 0.000 0.004 0.000 0.312
#> GSM1233139 2 0.2690 0.7178 0.000 0.844 0.156 0.000 0.000
#> GSM1233143 3 0.2605 0.7512 0.000 0.000 0.852 0.148 0.000
#> GSM1233145 5 0.4323 0.3366 0.196 0.000 0.024 0.020 0.760
#> GSM1233067 3 0.2806 0.7531 0.000 0.004 0.844 0.152 0.000
#> GSM1233069 3 0.3246 0.7538 0.000 0.000 0.808 0.184 0.008
#> GSM1233072 2 0.2605 0.7353 0.000 0.852 0.000 0.148 0.000
#> GSM1233086 3 0.4238 0.7267 0.000 0.052 0.756 0.192 0.000
#> GSM1233102 5 0.5433 -0.1866 0.016 0.000 0.032 0.412 0.540
#> GSM1233103 3 0.7412 0.2729 0.000 0.300 0.480 0.136 0.084
#> GSM1233107 5 0.8179 -0.0954 0.000 0.168 0.340 0.148 0.344
#> GSM1233108 4 0.5966 0.3819 0.120 0.000 0.128 0.684 0.068
#> GSM1233109 4 0.4493 0.3889 0.012 0.000 0.272 0.700 0.016
#> GSM1233110 3 0.3209 0.7523 0.000 0.000 0.812 0.180 0.008
#> GSM1233113 2 0.2370 0.7533 0.000 0.904 0.040 0.056 0.000
#> GSM1233116 2 0.5674 0.5548 0.000 0.536 0.072 0.388 0.004
#> GSM1233120 5 0.4884 -0.1944 0.020 0.000 0.004 0.404 0.572
#> GSM1233121 3 0.5134 0.7187 0.012 0.052 0.724 0.196 0.016
#> GSM1233123 3 0.3280 0.7558 0.000 0.000 0.812 0.176 0.012
#> GSM1233124 3 0.2011 0.8024 0.000 0.000 0.908 0.088 0.004
#> GSM1233125 5 0.7382 0.0535 0.224 0.000 0.036 0.340 0.400
#> GSM1233126 4 0.4151 0.3934 0.000 0.004 0.000 0.652 0.344
#> GSM1233127 2 0.5990 0.6495 0.000 0.668 0.044 0.156 0.132
#> GSM1233128 1 0.4434 0.3642 0.536 0.000 0.004 0.000 0.460
#> GSM1233130 4 0.3806 0.4544 0.012 0.000 0.180 0.792 0.016
#> GSM1233131 5 0.6635 0.3334 0.156 0.000 0.020 0.300 0.524
#> GSM1233133 3 0.1569 0.8036 0.012 0.000 0.948 0.032 0.008
#> GSM1233134 3 0.1341 0.8073 0.000 0.000 0.944 0.056 0.000
#> GSM1233135 3 0.2843 0.7932 0.000 0.000 0.848 0.144 0.008
#> GSM1233136 4 0.2644 0.5136 0.012 0.000 0.088 0.888 0.012
#> GSM1233137 3 0.2208 0.7958 0.020 0.000 0.908 0.072 0.000
#> GSM1233138 4 0.3653 0.5545 0.000 0.012 0.016 0.808 0.164
#> GSM1233140 3 0.5715 0.1635 0.076 0.000 0.536 0.004 0.384
#> GSM1233141 3 0.8007 0.2317 0.000 0.200 0.444 0.216 0.140
#> GSM1233142 2 0.5118 0.7017 0.000 0.732 0.036 0.168 0.064
#> GSM1233144 3 0.3769 0.7453 0.012 0.000 0.796 0.176 0.016
#> GSM1233147 4 0.2110 0.5797 0.000 0.016 0.000 0.912 0.072
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.1148 0.7701 0.000 0.960 0.020 0.016 0.004 0.000
#> GSM1233002 4 0.2912 0.6712 0.000 0.076 0.000 0.852 0.000 0.072
#> GSM1233003 5 0.4518 0.7116 0.104 0.000 0.000 0.200 0.696 0.000
#> GSM1233014 4 0.5198 0.4364 0.000 0.056 0.016 0.628 0.012 0.288
#> GSM1233015 2 0.2559 0.7528 0.000 0.896 0.052 0.024 0.020 0.008
#> GSM1233016 5 0.6237 0.5904 0.088 0.004 0.000 0.124 0.596 0.188
#> GSM1233024 2 0.3674 0.6173 0.000 0.716 0.000 0.016 0.000 0.268
#> GSM1233049 1 0.0146 0.8496 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM1233064 2 0.0551 0.7719 0.000 0.984 0.008 0.004 0.000 0.004
#> GSM1233068 3 0.0935 0.8032 0.000 0.000 0.964 0.032 0.004 0.000
#> GSM1233073 4 0.2565 0.6549 0.000 0.004 0.012 0.892 0.040 0.052
#> GSM1233093 1 0.0000 0.8507 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233115 6 0.6586 0.3060 0.120 0.028 0.004 0.284 0.032 0.532
#> GSM1232992 2 0.0146 0.7709 0.000 0.996 0.000 0.004 0.000 0.000
#> GSM1232993 2 0.0146 0.7709 0.000 0.996 0.000 0.004 0.000 0.000
#> GSM1233005 2 0.0508 0.7701 0.000 0.984 0.000 0.012 0.000 0.004
#> GSM1233007 2 0.4341 0.3587 0.000 0.564 0.000 0.024 0.000 0.412
#> GSM1233010 6 0.5269 0.4516 0.000 0.212 0.020 0.068 0.024 0.676
#> GSM1233013 2 0.0436 0.7719 0.000 0.988 0.004 0.004 0.000 0.004
#> GSM1233018 2 0.0363 0.7702 0.000 0.988 0.000 0.012 0.000 0.000
#> GSM1233019 2 0.1285 0.7649 0.000 0.944 0.000 0.004 0.000 0.052
#> GSM1233021 2 0.0458 0.7701 0.000 0.984 0.000 0.016 0.000 0.000
#> GSM1233025 6 0.5354 0.4669 0.072 0.004 0.000 0.144 0.088 0.692
#> GSM1233029 2 0.3534 0.5861 0.000 0.740 0.000 0.016 0.000 0.244
#> GSM1233030 2 0.1349 0.7637 0.000 0.940 0.000 0.004 0.000 0.056
#> GSM1233031 2 0.7041 0.0552 0.000 0.368 0.008 0.280 0.044 0.300
#> GSM1233032 1 0.3163 0.6074 0.764 0.000 0.232 0.000 0.004 0.000
#> GSM1233035 2 0.8573 0.1390 0.064 0.392 0.148 0.064 0.264 0.068
#> GSM1233038 5 0.4496 0.7230 0.136 0.000 0.000 0.156 0.708 0.000
#> GSM1233039 6 0.4172 0.1013 0.000 0.460 0.000 0.012 0.000 0.528
#> GSM1233042 4 0.3641 0.6003 0.000 0.248 0.000 0.732 0.000 0.020
#> GSM1233043 4 0.3830 0.6220 0.000 0.212 0.000 0.744 0.000 0.044
#> GSM1233044 3 0.6180 0.4128 0.000 0.020 0.608 0.124 0.048 0.200
#> GSM1233046 4 0.6815 0.3277 0.020 0.024 0.296 0.528 0.052 0.080
#> GSM1233051 6 0.7331 0.1854 0.016 0.000 0.256 0.064 0.276 0.388
#> GSM1233054 3 0.0260 0.8079 0.000 0.000 0.992 0.000 0.000 0.008
#> GSM1233057 3 0.0405 0.8070 0.000 0.008 0.988 0.000 0.000 0.004
#> GSM1233060 4 0.3778 0.5489 0.000 0.288 0.000 0.696 0.000 0.016
#> GSM1233062 2 0.4433 0.6471 0.000 0.716 0.020 0.036 0.004 0.224
#> GSM1233075 3 0.0806 0.8072 0.000 0.008 0.972 0.000 0.000 0.020
#> GSM1233078 3 0.4637 0.7232 0.000 0.004 0.728 0.028 0.060 0.180
#> GSM1233079 1 0.3948 0.5799 0.728 0.000 0.240 0.024 0.004 0.004
#> GSM1233082 3 0.4745 0.5001 0.000 0.000 0.676 0.056 0.020 0.248
#> GSM1233083 4 0.5526 -0.1031 0.036 0.000 0.008 0.492 0.036 0.428
#> GSM1233091 3 0.2313 0.7886 0.000 0.016 0.904 0.060 0.004 0.016
#> GSM1233095 1 0.0858 0.8320 0.968 0.000 0.000 0.028 0.000 0.004
#> GSM1233096 5 0.3965 0.6157 0.388 0.000 0.000 0.008 0.604 0.000
#> GSM1233101 1 0.4598 0.5568 0.680 0.000 0.016 0.268 0.012 0.024
#> GSM1233105 5 0.5241 0.3381 0.080 0.000 0.000 0.444 0.472 0.004
#> GSM1233117 2 0.1750 0.7642 0.000 0.928 0.008 0.004 0.004 0.056
#> GSM1233118 3 0.4684 0.4980 0.000 0.268 0.664 0.000 0.012 0.056
#> GSM1233001 2 0.1814 0.7470 0.000 0.900 0.100 0.000 0.000 0.000
#> GSM1233006 2 0.4139 0.6839 0.000 0.772 0.000 0.104 0.016 0.108
#> GSM1233008 2 0.3514 0.6941 0.000 0.812 0.140 0.032 0.004 0.012
#> GSM1233009 2 0.0291 0.7717 0.000 0.992 0.004 0.004 0.000 0.000
#> GSM1233017 2 0.1349 0.7637 0.000 0.940 0.000 0.004 0.000 0.056
#> GSM1233020 2 0.0291 0.7714 0.000 0.992 0.000 0.004 0.000 0.004
#> GSM1233022 2 0.5831 0.4015 0.000 0.532 0.008 0.152 0.004 0.304
#> GSM1233026 6 0.4635 0.5106 0.000 0.120 0.020 0.084 0.020 0.756
#> GSM1233028 2 0.7563 0.1685 0.000 0.424 0.020 0.168 0.128 0.260
#> GSM1233034 2 0.0806 0.7710 0.000 0.972 0.020 0.000 0.000 0.008
#> GSM1233040 5 0.3841 0.6288 0.380 0.000 0.000 0.004 0.616 0.000
#> GSM1233048 1 0.0291 0.8479 0.992 0.000 0.000 0.004 0.004 0.000
#> GSM1233056 1 0.0260 0.8461 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM1233058 6 0.5187 0.4393 0.000 0.068 0.020 0.224 0.016 0.672
#> GSM1233059 1 0.0000 0.8507 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233066 3 0.1036 0.8035 0.000 0.000 0.964 0.024 0.004 0.008
#> GSM1233071 3 0.2846 0.7646 0.000 0.012 0.864 0.004 0.020 0.100
#> GSM1233074 3 0.0713 0.8036 0.000 0.028 0.972 0.000 0.000 0.000
#> GSM1233076 6 0.2402 0.5387 0.000 0.004 0.000 0.140 0.000 0.856
#> GSM1233080 1 0.0000 0.8507 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233088 3 0.3652 0.7364 0.000 0.048 0.796 0.004 0.004 0.148
#> GSM1233090 1 0.0000 0.8507 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233092 6 0.3801 0.4519 0.000 0.012 0.000 0.232 0.016 0.740
#> GSM1233094 4 0.2867 0.6677 0.000 0.040 0.016 0.868 0.000 0.076
#> GSM1233097 4 0.3067 0.6624 0.000 0.064 0.012 0.860 0.004 0.060
#> GSM1233100 4 0.3191 0.6723 0.000 0.096 0.016 0.844 0.000 0.044
#> GSM1233104 4 0.5295 0.4272 0.000 0.060 0.012 0.628 0.020 0.280
#> GSM1233106 3 0.0146 0.8073 0.000 0.000 0.996 0.004 0.000 0.000
#> GSM1233111 5 0.3652 0.6735 0.324 0.000 0.000 0.004 0.672 0.000
#> GSM1233122 2 0.2660 0.7420 0.000 0.872 0.008 0.004 0.016 0.100
#> GSM1233146 4 0.6323 0.0866 0.000 0.368 0.012 0.376 0.000 0.244
#> GSM1232994 2 0.0146 0.7709 0.000 0.996 0.000 0.004 0.000 0.000
#> GSM1232996 2 0.2301 0.7280 0.000 0.884 0.000 0.020 0.000 0.096
#> GSM1232997 2 0.3163 0.6274 0.000 0.764 0.232 0.004 0.000 0.000
#> GSM1232998 2 0.6664 0.2026 0.000 0.456 0.016 0.220 0.020 0.288
#> GSM1232999 2 0.3695 0.5801 0.000 0.732 0.000 0.024 0.000 0.244
#> GSM1233000 2 0.0291 0.7714 0.000 0.992 0.000 0.004 0.000 0.004
#> GSM1233004 6 0.3755 0.5120 0.000 0.052 0.000 0.100 0.036 0.812
#> GSM1233011 6 0.5038 0.5203 0.000 0.060 0.140 0.056 0.016 0.728
#> GSM1233012 2 0.5772 0.1427 0.000 0.460 0.424 0.004 0.016 0.096
#> GSM1233023 3 0.0458 0.8066 0.000 0.016 0.984 0.000 0.000 0.000
#> GSM1233027 2 0.3695 0.5801 0.000 0.732 0.000 0.024 0.000 0.244
#> GSM1233033 5 0.5081 0.7327 0.156 0.000 0.000 0.128 0.688 0.028
#> GSM1233036 3 0.2335 0.7915 0.000 0.000 0.904 0.028 0.024 0.044
#> GSM1233037 3 0.0806 0.8072 0.000 0.008 0.972 0.000 0.000 0.020
#> GSM1233041 5 0.3620 0.6548 0.352 0.000 0.000 0.000 0.648 0.000
#> GSM1233045 4 0.5756 0.4379 0.000 0.180 0.008 0.544 0.000 0.268
#> GSM1233047 3 0.0653 0.8078 0.000 0.000 0.980 0.012 0.004 0.004
#> GSM1233050 1 0.0146 0.8495 0.996 0.000 0.000 0.004 0.000 0.000
#> GSM1233052 4 0.4563 0.6401 0.024 0.084 0.020 0.792 0.044 0.036
#> GSM1233053 1 0.2650 0.7851 0.880 0.000 0.040 0.072 0.004 0.004
#> GSM1233055 1 0.0146 0.8500 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1233061 3 0.2265 0.8042 0.000 0.000 0.900 0.024 0.008 0.068
#> GSM1233063 5 0.4957 0.7076 0.172 0.000 0.004 0.020 0.700 0.104
#> GSM1233065 2 0.5575 0.4984 0.000 0.644 0.204 0.040 0.004 0.108
#> GSM1233070 6 0.5516 0.4653 0.000 0.136 0.052 0.100 0.020 0.692
#> GSM1233077 6 0.4014 0.3842 0.000 0.000 0.240 0.000 0.044 0.716
#> GSM1233081 3 0.4498 0.5683 0.000 0.000 0.640 0.024 0.016 0.320
#> GSM1233084 5 0.4096 0.4391 0.484 0.000 0.000 0.008 0.508 0.000
#> GSM1233087 4 0.2695 0.6232 0.000 0.004 0.008 0.844 0.000 0.144
#> GSM1233089 2 0.2203 0.7517 0.000 0.896 0.000 0.004 0.016 0.084
#> GSM1233099 4 0.4034 0.5450 0.000 0.004 0.000 0.692 0.280 0.024
#> GSM1233112 4 0.3389 0.6180 0.036 0.000 0.008 0.848 0.072 0.036
#> GSM1233085 3 0.3717 0.7756 0.000 0.004 0.820 0.024 0.076 0.076
#> GSM1233098 2 0.3989 0.0863 0.000 0.528 0.468 0.004 0.000 0.000
#> GSM1233114 5 0.1672 0.6259 0.016 0.000 0.000 0.048 0.932 0.004
#> GSM1233119 6 0.4658 0.4717 0.000 0.000 0.008 0.092 0.204 0.696
#> GSM1233129 3 0.0260 0.8063 0.000 0.008 0.992 0.000 0.000 0.000
#> GSM1233132 1 0.5925 0.2810 0.444 0.000 0.000 0.224 0.332 0.000
#> GSM1233139 2 0.2378 0.7145 0.000 0.848 0.152 0.000 0.000 0.000
#> GSM1233143 3 0.2942 0.7624 0.000 0.004 0.856 0.004 0.036 0.100
#> GSM1233145 5 0.4560 0.7121 0.108 0.000 0.000 0.200 0.692 0.000
#> GSM1233067 3 0.2548 0.7690 0.000 0.004 0.876 0.004 0.016 0.100
#> GSM1233069 3 0.3046 0.7332 0.000 0.000 0.800 0.000 0.012 0.188
#> GSM1233072 2 0.2405 0.7436 0.000 0.880 0.000 0.004 0.016 0.100
#> GSM1233086 3 0.4933 0.6887 0.000 0.036 0.708 0.036 0.020 0.200
#> GSM1233102 4 0.2251 0.6428 0.000 0.000 0.008 0.904 0.052 0.036
#> GSM1233103 3 0.7729 0.3027 0.000 0.176 0.432 0.048 0.248 0.096
#> GSM1233107 3 0.8384 0.1248 0.000 0.184 0.336 0.112 0.272 0.096
#> GSM1233108 6 0.6099 0.4295 0.164 0.000 0.128 0.024 0.052 0.632
#> GSM1233109 6 0.4926 0.2984 0.000 0.000 0.292 0.024 0.048 0.636
#> GSM1233110 3 0.4193 0.6837 0.000 0.000 0.724 0.008 0.048 0.220
#> GSM1233113 2 0.1723 0.7660 0.000 0.928 0.036 0.000 0.000 0.036
#> GSM1233116 6 0.5763 -0.2738 0.000 0.428 0.032 0.040 0.020 0.480
#> GSM1233120 4 0.2907 0.6195 0.000 0.000 0.000 0.828 0.152 0.020
#> GSM1233121 3 0.5292 0.6509 0.000 0.028 0.672 0.028 0.048 0.224
#> GSM1233123 3 0.4053 0.7035 0.000 0.000 0.744 0.008 0.048 0.200
#> GSM1233124 3 0.3201 0.7918 0.000 0.000 0.852 0.044 0.032 0.072
#> GSM1233125 5 0.4299 0.4875 0.004 0.000 0.008 0.016 0.652 0.320
#> GSM1233126 4 0.4633 0.3379 0.000 0.004 0.000 0.568 0.036 0.392
#> GSM1233127 2 0.5928 0.5254 0.000 0.600 0.008 0.044 0.244 0.104
#> GSM1233128 5 0.4140 0.6993 0.280 0.000 0.000 0.024 0.688 0.008
#> GSM1233130 6 0.4613 0.3851 0.000 0.000 0.232 0.024 0.048 0.696
#> GSM1233131 5 0.4360 0.6906 0.104 0.004 0.000 0.032 0.772 0.088
#> GSM1233133 3 0.2620 0.7878 0.000 0.000 0.888 0.024 0.040 0.048
#> GSM1233134 3 0.0363 0.8072 0.000 0.000 0.988 0.000 0.000 0.012
#> GSM1233135 3 0.1462 0.8044 0.000 0.000 0.936 0.000 0.008 0.056
#> GSM1233136 6 0.3918 0.5000 0.000 0.000 0.160 0.016 0.048 0.776
#> GSM1233137 3 0.0914 0.8068 0.016 0.000 0.968 0.000 0.000 0.016
#> GSM1233138 6 0.4033 0.4600 0.000 0.004 0.004 0.220 0.036 0.736
#> GSM1233140 5 0.3634 0.4706 0.000 0.000 0.356 0.000 0.644 0.000
#> GSM1233141 3 0.8272 0.0500 0.000 0.188 0.336 0.048 0.244 0.184
#> GSM1233142 2 0.6188 0.5118 0.000 0.576 0.008 0.052 0.244 0.120
#> GSM1233144 3 0.4502 0.6884 0.000 0.000 0.720 0.028 0.048 0.204
#> GSM1233147 6 0.2377 0.5445 0.000 0.004 0.000 0.124 0.004 0.868
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> MAD:pam 139 0.370157 0.559 1.000 2
#> MAD:pam 118 0.000247 0.113 0.117 3
#> MAD:pam 126 0.001511 0.281 0.409 4
#> MAD:pam 105 0.003118 0.246 0.340 5
#> MAD:pam 114 0.007466 0.355 0.722 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 51941 rows and 156 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 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.990 0.958 0.957 0.4233 0.562 0.562
#> 3 3 0.496 0.626 0.811 0.3590 0.872 0.777
#> 4 4 0.398 0.422 0.683 0.2096 0.684 0.402
#> 5 5 0.548 0.451 0.667 0.0992 0.789 0.415
#> 6 6 0.610 0.580 0.729 0.0518 0.908 0.640
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0000 0.977 0.000 1.000
#> GSM1233002 2 0.0376 0.976 0.004 0.996
#> GSM1233003 1 0.4022 0.974 0.920 0.080
#> GSM1233014 2 0.2236 0.960 0.036 0.964
#> GSM1233015 1 0.7376 0.839 0.792 0.208
#> GSM1233016 2 0.0376 0.976 0.004 0.996
#> GSM1233024 2 0.0376 0.976 0.004 0.996
#> GSM1233049 1 0.4022 0.974 0.920 0.080
#> GSM1233064 2 0.0376 0.976 0.004 0.996
#> GSM1233068 2 0.0376 0.976 0.004 0.996
#> GSM1233073 2 0.1184 0.972 0.016 0.984
#> GSM1233093 1 0.4022 0.974 0.920 0.080
#> GSM1233115 1 0.4161 0.972 0.916 0.084
#> GSM1232992 2 0.0376 0.976 0.004 0.996
#> GSM1232993 2 0.0376 0.976 0.004 0.996
#> GSM1233005 2 0.0000 0.977 0.000 1.000
#> GSM1233007 2 0.0000 0.977 0.000 1.000
#> GSM1233010 2 0.0376 0.976 0.004 0.996
#> GSM1233013 2 0.0376 0.976 0.004 0.996
#> GSM1233018 2 0.0000 0.977 0.000 1.000
#> GSM1233019 2 0.0376 0.976 0.004 0.996
#> GSM1233021 2 0.0000 0.977 0.000 1.000
#> GSM1233025 2 0.2236 0.953 0.036 0.964
#> GSM1233029 2 0.0376 0.976 0.004 0.996
#> GSM1233030 2 0.0376 0.976 0.004 0.996
#> GSM1233031 2 0.0376 0.976 0.004 0.996
#> GSM1233032 1 0.3879 0.969 0.924 0.076
#> GSM1233035 2 0.0376 0.976 0.004 0.996
#> GSM1233038 1 0.4022 0.974 0.920 0.080
#> GSM1233039 2 0.0000 0.977 0.000 1.000
#> GSM1233042 2 0.2236 0.960 0.036 0.964
#> GSM1233043 2 0.2236 0.960 0.036 0.964
#> GSM1233044 2 0.4562 0.885 0.096 0.904
#> GSM1233046 2 0.4562 0.886 0.096 0.904
#> GSM1233051 1 0.4022 0.974 0.920 0.080
#> GSM1233054 2 0.0672 0.975 0.008 0.992
#> GSM1233057 2 0.0672 0.975 0.008 0.992
#> GSM1233060 2 0.0376 0.976 0.004 0.996
#> GSM1233062 2 0.0376 0.976 0.004 0.996
#> GSM1233075 2 0.2043 0.962 0.032 0.968
#> GSM1233078 2 0.2778 0.951 0.048 0.952
#> GSM1233079 1 0.3879 0.969 0.924 0.076
#> GSM1233082 1 0.7950 0.793 0.760 0.240
#> GSM1233083 1 0.4022 0.974 0.920 0.080
#> GSM1233091 2 0.0000 0.977 0.000 1.000
#> GSM1233095 1 0.4022 0.974 0.920 0.080
#> GSM1233096 1 0.4022 0.974 0.920 0.080
#> GSM1233101 1 0.4022 0.974 0.920 0.080
#> GSM1233105 1 0.4022 0.974 0.920 0.080
#> GSM1233117 2 0.0000 0.977 0.000 1.000
#> GSM1233118 2 0.0672 0.975 0.008 0.992
#> GSM1233001 2 0.0672 0.975 0.008 0.992
#> GSM1233006 2 0.2043 0.963 0.032 0.968
#> GSM1233008 2 0.0000 0.977 0.000 1.000
#> GSM1233009 2 0.0376 0.976 0.004 0.996
#> GSM1233017 2 0.0376 0.976 0.004 0.996
#> GSM1233020 2 0.0000 0.977 0.000 1.000
#> GSM1233022 2 0.0376 0.976 0.004 0.996
#> GSM1233026 2 0.0376 0.976 0.004 0.996
#> GSM1233028 2 0.0376 0.976 0.004 0.996
#> GSM1233034 2 0.0000 0.977 0.000 1.000
#> GSM1233040 1 0.3733 0.970 0.928 0.072
#> GSM1233048 1 0.4022 0.974 0.920 0.080
#> GSM1233056 1 0.4022 0.974 0.920 0.080
#> GSM1233058 2 0.1843 0.966 0.028 0.972
#> GSM1233059 1 0.4022 0.974 0.920 0.080
#> GSM1233066 2 0.2603 0.954 0.044 0.956
#> GSM1233071 2 0.0376 0.976 0.004 0.996
#> GSM1233074 2 0.0672 0.975 0.008 0.992
#> GSM1233076 2 0.0000 0.977 0.000 1.000
#> GSM1233080 1 0.4022 0.974 0.920 0.080
#> GSM1233088 2 0.0672 0.975 0.008 0.992
#> GSM1233090 1 0.4022 0.974 0.920 0.080
#> GSM1233092 2 0.1414 0.970 0.020 0.980
#> GSM1233094 2 0.2236 0.960 0.036 0.964
#> GSM1233097 2 0.2236 0.960 0.036 0.964
#> GSM1233100 2 0.0376 0.976 0.004 0.996
#> GSM1233104 2 0.2236 0.960 0.036 0.964
#> GSM1233106 1 0.7528 0.828 0.784 0.216
#> GSM1233111 1 0.4022 0.974 0.920 0.080
#> GSM1233122 2 0.0000 0.977 0.000 1.000
#> GSM1233146 2 0.0376 0.976 0.004 0.996
#> GSM1232994 2 0.0376 0.976 0.004 0.996
#> GSM1232996 2 0.0000 0.977 0.000 1.000
#> GSM1232997 2 0.0672 0.975 0.008 0.992
#> GSM1232998 2 0.0376 0.976 0.004 0.996
#> GSM1232999 2 0.2236 0.960 0.036 0.964
#> GSM1233000 2 0.0376 0.976 0.004 0.996
#> GSM1233004 2 0.9732 0.295 0.404 0.596
#> GSM1233011 2 0.0672 0.975 0.008 0.992
#> GSM1233012 2 0.0672 0.975 0.008 0.992
#> GSM1233023 2 0.0672 0.975 0.008 0.992
#> GSM1233027 2 0.1184 0.973 0.016 0.984
#> GSM1233033 1 0.4022 0.974 0.920 0.080
#> GSM1233036 2 0.0672 0.975 0.008 0.992
#> GSM1233037 2 0.0672 0.975 0.008 0.992
#> GSM1233041 1 0.4022 0.974 0.920 0.080
#> GSM1233045 2 0.2043 0.963 0.032 0.968
#> GSM1233047 1 0.3879 0.967 0.924 0.076
#> GSM1233050 1 0.4022 0.974 0.920 0.080
#> GSM1233052 1 0.4815 0.955 0.896 0.104
#> GSM1233053 1 0.3879 0.969 0.924 0.076
#> GSM1233055 1 0.4022 0.974 0.920 0.080
#> GSM1233061 2 0.0672 0.975 0.008 0.992
#> GSM1233063 1 0.4022 0.974 0.920 0.080
#> GSM1233065 2 0.1414 0.969 0.020 0.980
#> GSM1233070 2 0.0376 0.976 0.004 0.996
#> GSM1233077 2 0.2778 0.951 0.048 0.952
#> GSM1233081 1 0.2236 0.942 0.964 0.036
#> GSM1233084 1 0.4022 0.974 0.920 0.080
#> GSM1233087 1 0.9000 0.662 0.684 0.316
#> GSM1233089 2 0.0000 0.977 0.000 1.000
#> GSM1233099 2 0.5408 0.847 0.124 0.876
#> GSM1233112 1 0.4022 0.974 0.920 0.080
#> GSM1233085 1 0.2236 0.942 0.964 0.036
#> GSM1233098 2 0.0000 0.977 0.000 1.000
#> GSM1233114 1 0.4022 0.974 0.920 0.080
#> GSM1233119 2 0.2236 0.960 0.036 0.964
#> GSM1233129 2 0.0672 0.975 0.008 0.992
#> GSM1233132 1 0.4022 0.974 0.920 0.080
#> GSM1233139 2 0.0376 0.976 0.004 0.996
#> GSM1233143 2 0.0000 0.977 0.000 1.000
#> GSM1233145 1 0.4022 0.974 0.920 0.080
#> GSM1233067 2 0.2778 0.951 0.048 0.952
#> GSM1233069 2 0.2778 0.951 0.048 0.952
#> GSM1233072 2 0.0000 0.977 0.000 1.000
#> GSM1233086 2 0.2778 0.951 0.048 0.952
#> GSM1233102 1 0.4022 0.974 0.920 0.080
#> GSM1233103 2 0.0376 0.976 0.004 0.996
#> GSM1233107 2 0.0672 0.975 0.008 0.992
#> GSM1233108 1 0.2236 0.942 0.964 0.036
#> GSM1233109 1 0.2236 0.942 0.964 0.036
#> GSM1233110 2 0.2778 0.951 0.048 0.952
#> GSM1233113 2 0.2778 0.951 0.048 0.952
#> GSM1233116 2 0.2778 0.951 0.048 0.952
#> GSM1233120 1 0.4022 0.974 0.920 0.080
#> GSM1233121 2 0.2778 0.951 0.048 0.952
#> GSM1233123 2 0.2778 0.951 0.048 0.952
#> GSM1233124 2 0.2778 0.951 0.048 0.952
#> GSM1233125 1 0.2236 0.942 0.964 0.036
#> GSM1233126 2 0.2236 0.960 0.036 0.964
#> GSM1233127 2 0.0376 0.976 0.004 0.996
#> GSM1233128 1 0.4022 0.974 0.920 0.080
#> GSM1233130 2 0.2778 0.951 0.048 0.952
#> GSM1233131 1 0.4022 0.974 0.920 0.080
#> GSM1233133 1 0.2236 0.942 0.964 0.036
#> GSM1233134 2 0.2778 0.951 0.048 0.952
#> GSM1233135 2 0.2778 0.951 0.048 0.952
#> GSM1233136 2 0.2778 0.951 0.048 0.952
#> GSM1233137 1 0.2423 0.943 0.960 0.040
#> GSM1233138 2 0.2236 0.960 0.036 0.964
#> GSM1233140 1 0.3879 0.969 0.924 0.076
#> GSM1233141 2 0.0376 0.976 0.004 0.996
#> GSM1233142 2 0.0376 0.976 0.004 0.996
#> GSM1233144 1 0.4022 0.930 0.920 0.080
#> GSM1233147 2 0.0000 0.977 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.1337 0.68372 0.012 0.972 0.016
#> GSM1233002 3 0.7674 0.83951 0.044 0.476 0.480
#> GSM1233003 1 0.2703 0.88442 0.928 0.056 0.016
#> GSM1233014 2 0.4146 0.62018 0.044 0.876 0.080
#> GSM1233015 1 0.3234 0.87990 0.908 0.072 0.020
#> GSM1233016 3 0.8068 0.84292 0.064 0.456 0.480
#> GSM1233024 2 0.2443 0.66203 0.032 0.940 0.028
#> GSM1233049 1 0.2550 0.89270 0.936 0.024 0.040
#> GSM1233064 2 0.2903 0.67894 0.028 0.924 0.048
#> GSM1233068 2 0.7411 0.14353 0.256 0.668 0.076
#> GSM1233073 3 0.7835 0.84600 0.052 0.456 0.492
#> GSM1233093 1 0.2297 0.89128 0.944 0.020 0.036
#> GSM1233115 1 0.1647 0.89474 0.960 0.036 0.004
#> GSM1232992 2 0.1015 0.68149 0.008 0.980 0.012
#> GSM1232993 2 0.2903 0.64798 0.028 0.924 0.048
#> GSM1233005 2 0.1015 0.68330 0.008 0.980 0.012
#> GSM1233007 2 0.2793 0.66819 0.028 0.928 0.044
#> GSM1233010 3 0.7996 0.83081 0.060 0.464 0.476
#> GSM1233013 2 0.1337 0.68173 0.012 0.972 0.016
#> GSM1233018 2 0.1015 0.68382 0.008 0.980 0.012
#> GSM1233019 2 0.2031 0.67370 0.032 0.952 0.016
#> GSM1233021 2 0.1337 0.68256 0.016 0.972 0.012
#> GSM1233025 3 0.8774 0.78079 0.112 0.412 0.476
#> GSM1233029 2 0.1399 0.67561 0.028 0.968 0.004
#> GSM1233030 2 0.1751 0.67519 0.028 0.960 0.012
#> GSM1233031 2 0.3764 0.62963 0.040 0.892 0.068
#> GSM1233032 1 0.2116 0.88714 0.948 0.040 0.012
#> GSM1233035 2 0.7557 0.00510 0.264 0.656 0.080
#> GSM1233038 1 0.3649 0.87347 0.896 0.068 0.036
#> GSM1233039 2 0.2903 0.67578 0.028 0.924 0.048
#> GSM1233042 3 0.7585 0.82863 0.040 0.476 0.484
#> GSM1233043 2 0.7487 -0.80350 0.036 0.500 0.464
#> GSM1233044 1 0.7876 0.34673 0.612 0.308 0.080
#> GSM1233046 1 0.8071 0.12643 0.564 0.360 0.076
#> GSM1233051 1 0.1711 0.89318 0.960 0.032 0.008
#> GSM1233054 2 0.9315 0.19086 0.220 0.520 0.260
#> GSM1233057 2 0.6728 0.51804 0.080 0.736 0.184
#> GSM1233060 2 0.3669 0.63338 0.040 0.896 0.064
#> GSM1233062 2 0.3028 0.64580 0.032 0.920 0.048
#> GSM1233075 2 0.6962 0.33808 0.020 0.568 0.412
#> GSM1233078 3 0.9442 -0.00522 0.216 0.288 0.496
#> GSM1233079 1 0.2681 0.88717 0.932 0.040 0.028
#> GSM1233082 1 0.5173 0.78893 0.816 0.148 0.036
#> GSM1233083 1 0.3253 0.88173 0.912 0.052 0.036
#> GSM1233091 2 0.3899 0.66539 0.056 0.888 0.056
#> GSM1233095 1 0.2152 0.89110 0.948 0.016 0.036
#> GSM1233096 1 0.1525 0.89393 0.964 0.032 0.004
#> GSM1233101 1 0.2918 0.88584 0.924 0.044 0.032
#> GSM1233105 1 0.4256 0.84995 0.868 0.096 0.036
#> GSM1233117 2 0.1482 0.68388 0.020 0.968 0.012
#> GSM1233118 2 0.3337 0.67047 0.032 0.908 0.060
#> GSM1233001 2 0.4137 0.65123 0.032 0.872 0.096
#> GSM1233006 2 0.3764 0.63120 0.040 0.892 0.068
#> GSM1233008 2 0.1015 0.68382 0.008 0.980 0.012
#> GSM1233009 2 0.1643 0.67692 0.044 0.956 0.000
#> GSM1233017 2 0.1877 0.67429 0.032 0.956 0.012
#> GSM1233020 2 0.1781 0.68493 0.020 0.960 0.020
#> GSM1233022 2 0.3472 0.63525 0.040 0.904 0.056
#> GSM1233026 2 0.6211 0.20534 0.036 0.736 0.228
#> GSM1233028 2 0.6000 0.30481 0.040 0.760 0.200
#> GSM1233034 2 0.1267 0.68735 0.024 0.972 0.004
#> GSM1233040 1 0.1765 0.88804 0.956 0.040 0.004
#> GSM1233048 1 0.1399 0.89442 0.968 0.028 0.004
#> GSM1233056 1 0.1529 0.88701 0.960 0.000 0.040
#> GSM1233058 3 0.7396 0.83929 0.032 0.480 0.488
#> GSM1233059 1 0.2434 0.89265 0.940 0.024 0.036
#> GSM1233066 2 0.5826 0.59041 0.032 0.764 0.204
#> GSM1233071 2 0.2926 0.65573 0.036 0.924 0.040
#> GSM1233074 2 0.5778 0.55871 0.032 0.768 0.200
#> GSM1233076 2 0.3649 0.67231 0.036 0.896 0.068
#> GSM1233080 1 0.2152 0.89110 0.948 0.016 0.036
#> GSM1233088 2 0.4658 0.65132 0.076 0.856 0.068
#> GSM1233090 1 0.2297 0.89230 0.944 0.020 0.036
#> GSM1233092 2 0.5105 0.53641 0.048 0.828 0.124
#> GSM1233094 3 0.7585 0.82909 0.040 0.476 0.484
#> GSM1233097 3 0.7493 0.83328 0.036 0.476 0.488
#> GSM1233100 3 0.7839 0.84626 0.052 0.464 0.484
#> GSM1233104 2 0.6956 -0.20700 0.040 0.660 0.300
#> GSM1233106 1 0.2743 0.88755 0.928 0.052 0.020
#> GSM1233111 1 0.1315 0.89426 0.972 0.020 0.008
#> GSM1233122 2 0.1482 0.68407 0.020 0.968 0.012
#> GSM1233146 2 0.7755 -0.81627 0.048 0.492 0.460
#> GSM1232994 2 0.2176 0.67118 0.032 0.948 0.020
#> GSM1232996 2 0.1015 0.68382 0.008 0.980 0.012
#> GSM1232997 2 0.5778 0.56555 0.032 0.768 0.200
#> GSM1232998 2 0.3899 0.63817 0.056 0.888 0.056
#> GSM1232999 2 0.3337 0.64377 0.032 0.908 0.060
#> GSM1233000 2 0.1751 0.67519 0.028 0.960 0.012
#> GSM1233004 1 0.8350 0.56880 0.600 0.120 0.280
#> GSM1233011 2 0.3623 0.67438 0.032 0.896 0.072
#> GSM1233012 2 0.2681 0.68052 0.028 0.932 0.040
#> GSM1233023 2 0.3802 0.65617 0.032 0.888 0.080
#> GSM1233027 2 0.2689 0.66439 0.036 0.932 0.032
#> GSM1233033 1 0.2400 0.88565 0.932 0.064 0.004
#> GSM1233036 2 0.2564 0.68237 0.028 0.936 0.036
#> GSM1233037 2 0.6622 0.53061 0.088 0.748 0.164
#> GSM1233041 1 0.2434 0.89265 0.940 0.024 0.036
#> GSM1233045 2 0.7129 -0.59678 0.028 0.580 0.392
#> GSM1233047 1 0.4689 0.85538 0.852 0.052 0.096
#> GSM1233050 1 0.1315 0.89461 0.972 0.020 0.008
#> GSM1233052 1 0.4324 0.84750 0.860 0.112 0.028
#> GSM1233053 1 0.2269 0.88720 0.944 0.040 0.016
#> GSM1233055 1 0.1832 0.89019 0.956 0.008 0.036
#> GSM1233061 2 0.6668 0.51866 0.040 0.696 0.264
#> GSM1233063 1 0.1315 0.89426 0.972 0.020 0.008
#> GSM1233065 2 0.6012 0.55656 0.032 0.748 0.220
#> GSM1233070 2 0.3375 0.64542 0.044 0.908 0.048
#> GSM1233077 2 0.6944 0.30037 0.016 0.516 0.468
#> GSM1233081 1 0.4539 0.84098 0.836 0.016 0.148
#> GSM1233084 1 0.2152 0.89110 0.948 0.016 0.036
#> GSM1233087 1 0.7485 0.52756 0.680 0.224 0.096
#> GSM1233089 2 0.1877 0.68552 0.032 0.956 0.012
#> GSM1233099 2 0.9522 -0.68003 0.188 0.412 0.400
#> GSM1233112 1 0.1950 0.89141 0.952 0.040 0.008
#> GSM1233085 1 0.4326 0.84472 0.844 0.012 0.144
#> GSM1233098 2 0.1453 0.68661 0.024 0.968 0.008
#> GSM1233114 1 0.2301 0.88560 0.936 0.060 0.004
#> GSM1233119 3 0.7987 0.84317 0.060 0.448 0.492
#> GSM1233129 2 0.3713 0.65816 0.032 0.892 0.076
#> GSM1233132 1 0.3031 0.87250 0.912 0.076 0.012
#> GSM1233139 2 0.0892 0.68619 0.020 0.980 0.000
#> GSM1233143 2 0.2050 0.68440 0.028 0.952 0.020
#> GSM1233145 1 0.3649 0.87347 0.896 0.068 0.036
#> GSM1233067 2 0.6108 0.54670 0.028 0.732 0.240
#> GSM1233069 2 0.6919 0.30037 0.016 0.536 0.448
#> GSM1233072 2 0.1337 0.68390 0.016 0.972 0.012
#> GSM1233086 2 0.5803 0.59043 0.028 0.760 0.212
#> GSM1233102 1 0.4821 0.84582 0.848 0.088 0.064
#> GSM1233103 2 0.4658 0.59570 0.076 0.856 0.068
#> GSM1233107 2 0.5722 0.48625 0.132 0.800 0.068
#> GSM1233108 1 0.4233 0.84185 0.836 0.004 0.160
#> GSM1233109 1 0.5062 0.81860 0.800 0.016 0.184
#> GSM1233110 2 0.6950 0.29356 0.016 0.508 0.476
#> GSM1233113 2 0.6148 0.54458 0.028 0.728 0.244
#> GSM1233116 2 0.5849 0.56983 0.028 0.756 0.216
#> GSM1233120 1 0.4423 0.84295 0.864 0.088 0.048
#> GSM1233121 2 0.6888 0.35019 0.016 0.552 0.432
#> GSM1233123 2 0.6931 0.31058 0.016 0.528 0.456
#> GSM1233124 2 0.6226 0.54904 0.028 0.720 0.252
#> GSM1233125 1 0.3851 0.85333 0.860 0.004 0.136
#> GSM1233126 2 0.7652 -0.75797 0.044 0.512 0.444
#> GSM1233127 2 0.2663 0.66706 0.044 0.932 0.024
#> GSM1233128 1 0.2434 0.88604 0.940 0.024 0.036
#> GSM1233130 2 0.6954 0.28966 0.016 0.500 0.484
#> GSM1233131 1 0.3966 0.86032 0.876 0.100 0.024
#> GSM1233133 1 0.5008 0.81910 0.804 0.016 0.180
#> GSM1233134 2 0.6888 0.31945 0.016 0.552 0.432
#> GSM1233135 2 0.6919 0.30037 0.016 0.536 0.448
#> GSM1233136 2 0.6954 0.28966 0.016 0.500 0.484
#> GSM1233137 1 0.6369 0.69692 0.668 0.016 0.316
#> GSM1233138 2 0.6936 -0.11366 0.044 0.672 0.284
#> GSM1233140 1 0.2269 0.88720 0.944 0.040 0.016
#> GSM1233141 2 0.1774 0.68182 0.024 0.960 0.016
#> GSM1233142 2 0.1877 0.67472 0.032 0.956 0.012
#> GSM1233144 1 0.5843 0.75929 0.732 0.016 0.252
#> GSM1233147 2 0.4206 0.66558 0.040 0.872 0.088
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.0707 0.45395 0.000 0.980 0.000 0.020
#> GSM1233002 4 0.4035 0.63511 0.000 0.176 0.020 0.804
#> GSM1233003 1 0.4799 0.66051 0.704 0.004 0.008 0.284
#> GSM1233014 4 0.4428 0.62493 0.004 0.116 0.064 0.816
#> GSM1233015 4 0.8502 0.33964 0.348 0.084 0.112 0.456
#> GSM1233016 4 0.2360 0.66361 0.004 0.052 0.020 0.924
#> GSM1233024 4 0.5606 0.24490 0.000 0.480 0.020 0.500
#> GSM1233049 1 0.0895 0.77366 0.976 0.004 0.020 0.000
#> GSM1233064 2 0.3946 0.44633 0.000 0.812 0.168 0.020
#> GSM1233068 2 0.8486 0.16398 0.088 0.528 0.152 0.232
#> GSM1233073 4 0.2363 0.66476 0.000 0.056 0.024 0.920
#> GSM1233093 1 0.1743 0.75830 0.940 0.004 0.056 0.000
#> GSM1233115 1 0.3728 0.76281 0.864 0.008 0.064 0.064
#> GSM1232992 2 0.5028 -0.05681 0.000 0.596 0.004 0.400
#> GSM1232993 2 0.6360 -0.10422 0.000 0.516 0.064 0.420
#> GSM1233005 2 0.4866 -0.05798 0.000 0.596 0.000 0.404
#> GSM1233007 2 0.4879 0.45889 0.000 0.780 0.128 0.092
#> GSM1233010 4 0.3862 0.64395 0.000 0.152 0.024 0.824
#> GSM1233013 2 0.5028 -0.05681 0.000 0.596 0.004 0.400
#> GSM1233018 2 0.4776 -0.00994 0.000 0.624 0.000 0.376
#> GSM1233019 2 0.5105 -0.12610 0.000 0.564 0.004 0.432
#> GSM1233021 2 0.4866 -0.05798 0.000 0.596 0.000 0.404
#> GSM1233025 4 0.1697 0.65310 0.004 0.016 0.028 0.952
#> GSM1233029 2 0.5193 -0.06526 0.000 0.580 0.008 0.412
#> GSM1233030 2 0.5039 -0.06197 0.000 0.592 0.004 0.404
#> GSM1233031 4 0.7548 0.46214 0.036 0.288 0.112 0.564
#> GSM1233032 1 0.5835 0.57731 0.688 0.008 0.244 0.060
#> GSM1233035 4 0.8760 0.42931 0.100 0.256 0.152 0.492
#> GSM1233038 4 0.4897 0.50405 0.332 0.000 0.008 0.660
#> GSM1233039 2 0.4850 0.43703 0.004 0.776 0.168 0.052
#> GSM1233042 4 0.2216 0.66086 0.000 0.092 0.000 0.908
#> GSM1233043 4 0.2469 0.65836 0.000 0.108 0.000 0.892
#> GSM1233044 2 0.8556 0.15952 0.124 0.508 0.100 0.268
#> GSM1233046 4 0.8758 0.45090 0.112 0.236 0.148 0.504
#> GSM1233051 1 0.3652 0.76222 0.868 0.008 0.064 0.060
#> GSM1233054 2 0.8532 -0.22365 0.132 0.412 0.388 0.068
#> GSM1233057 2 0.6570 0.13643 0.072 0.580 0.340 0.008
#> GSM1233060 4 0.7314 0.22345 0.008 0.400 0.120 0.472
#> GSM1233062 2 0.5971 -0.11615 0.000 0.532 0.040 0.428
#> GSM1233075 3 0.3032 0.73784 0.000 0.124 0.868 0.008
#> GSM1233078 3 0.2956 0.75378 0.048 0.012 0.904 0.036
#> GSM1233079 3 0.6215 0.40949 0.304 0.008 0.628 0.060
#> GSM1233082 4 0.9163 0.39345 0.276 0.236 0.084 0.404
#> GSM1233083 1 0.4540 0.64474 0.740 0.004 0.008 0.248
#> GSM1233091 2 0.6375 0.36776 0.028 0.688 0.204 0.080
#> GSM1233095 1 0.1743 0.75830 0.940 0.004 0.056 0.000
#> GSM1233096 1 0.6687 -0.13434 0.472 0.008 0.064 0.456
#> GSM1233101 1 0.0524 0.77841 0.988 0.004 0.008 0.000
#> GSM1233105 4 0.5875 0.55779 0.204 0.024 0.056 0.716
#> GSM1233117 2 0.3751 0.28713 0.000 0.800 0.004 0.196
#> GSM1233118 2 0.4594 0.28919 0.000 0.712 0.280 0.008
#> GSM1233001 2 0.4343 0.27988 0.004 0.732 0.264 0.000
#> GSM1233006 4 0.5754 0.48887 0.000 0.316 0.048 0.636
#> GSM1233008 2 0.4936 -0.00625 0.000 0.624 0.004 0.372
#> GSM1233009 2 0.6278 -0.07943 0.000 0.532 0.060 0.408
#> GSM1233017 2 0.5039 -0.06197 0.000 0.592 0.004 0.404
#> GSM1233020 2 0.1004 0.47040 0.000 0.972 0.024 0.004
#> GSM1233022 4 0.5646 0.50638 0.000 0.296 0.048 0.656
#> GSM1233026 4 0.6302 0.36701 0.000 0.368 0.068 0.564
#> GSM1233028 4 0.5543 0.42576 0.000 0.360 0.028 0.612
#> GSM1233034 2 0.3231 0.46193 0.004 0.868 0.116 0.012
#> GSM1233040 1 0.5350 0.65996 0.744 0.008 0.188 0.060
#> GSM1233048 1 0.5507 0.63962 0.720 0.004 0.064 0.212
#> GSM1233056 1 0.3851 0.73398 0.852 0.004 0.056 0.088
#> GSM1233058 4 0.4323 0.61489 0.000 0.204 0.020 0.776
#> GSM1233059 1 0.0376 0.77737 0.992 0.004 0.004 0.000
#> GSM1233066 2 0.6087 0.08940 0.000 0.540 0.412 0.048
#> GSM1233071 2 0.6826 -0.11511 0.000 0.484 0.100 0.416
#> GSM1233074 2 0.5212 0.08966 0.000 0.572 0.420 0.008
#> GSM1233076 2 0.5412 0.41927 0.000 0.736 0.168 0.096
#> GSM1233080 1 0.1743 0.75830 0.940 0.004 0.056 0.000
#> GSM1233088 2 0.6786 0.13048 0.052 0.572 0.348 0.028
#> GSM1233090 1 0.0336 0.77813 0.992 0.008 0.000 0.000
#> GSM1233092 4 0.4626 0.61804 0.004 0.120 0.072 0.804
#> GSM1233094 4 0.1792 0.65820 0.000 0.068 0.000 0.932
#> GSM1233097 4 0.2197 0.66145 0.000 0.080 0.004 0.916
#> GSM1233100 4 0.3143 0.66478 0.000 0.100 0.024 0.876
#> GSM1233104 4 0.2053 0.65709 0.004 0.072 0.000 0.924
#> GSM1233106 1 0.6057 0.69450 0.748 0.072 0.096 0.084
#> GSM1233111 1 0.3652 0.76222 0.868 0.008 0.064 0.060
#> GSM1233122 2 0.4122 0.23284 0.000 0.760 0.004 0.236
#> GSM1233146 4 0.3925 0.63693 0.000 0.176 0.016 0.808
#> GSM1232994 2 0.5161 -0.22104 0.000 0.520 0.004 0.476
#> GSM1232996 2 0.4761 -0.00326 0.000 0.628 0.000 0.372
#> GSM1232997 2 0.5172 0.12308 0.000 0.588 0.404 0.008
#> GSM1232998 4 0.5886 0.54232 0.004 0.160 0.124 0.712
#> GSM1232999 4 0.5833 0.31076 0.000 0.440 0.032 0.528
#> GSM1233000 2 0.5039 -0.06197 0.000 0.592 0.004 0.404
#> GSM1233004 3 0.8285 0.45813 0.072 0.248 0.536 0.144
#> GSM1233011 2 0.5288 0.37930 0.000 0.720 0.224 0.056
#> GSM1233012 2 0.3088 0.43458 0.000 0.864 0.128 0.008
#> GSM1233023 2 0.5112 0.23448 0.004 0.648 0.340 0.008
#> GSM1233027 4 0.5643 0.34088 0.000 0.428 0.024 0.548
#> GSM1233033 4 0.6314 0.43330 0.288 0.012 0.064 0.636
#> GSM1233036 2 0.4019 0.42513 0.000 0.792 0.196 0.012
#> GSM1233037 2 0.7926 -0.10571 0.084 0.472 0.384 0.060
#> GSM1233041 1 0.0895 0.77366 0.976 0.004 0.020 0.000
#> GSM1233045 4 0.4539 0.55167 0.000 0.272 0.008 0.720
#> GSM1233047 1 0.7668 0.12279 0.484 0.064 0.392 0.060
#> GSM1233050 1 0.3255 0.76894 0.888 0.008 0.048 0.056
#> GSM1233052 4 0.8697 0.47119 0.224 0.216 0.072 0.488
#> GSM1233053 1 0.5742 0.59730 0.700 0.008 0.232 0.060
#> GSM1233055 1 0.3272 0.73870 0.860 0.004 0.008 0.128
#> GSM1233061 2 0.6099 -0.06001 0.004 0.500 0.460 0.036
#> GSM1233063 1 0.3508 0.76299 0.872 0.004 0.064 0.060
#> GSM1233065 2 0.5085 0.14220 0.000 0.616 0.376 0.008
#> GSM1233070 2 0.6435 -0.04843 0.000 0.532 0.072 0.396
#> GSM1233077 3 0.3105 0.73942 0.000 0.120 0.868 0.012
#> GSM1233081 3 0.5030 0.62990 0.188 0.000 0.752 0.060
#> GSM1233084 1 0.1743 0.75830 0.940 0.004 0.056 0.000
#> GSM1233087 4 0.4737 0.62470 0.136 0.012 0.052 0.800
#> GSM1233089 2 0.1452 0.47557 0.000 0.956 0.036 0.008
#> GSM1233099 4 0.2845 0.66151 0.032 0.028 0.028 0.912
#> GSM1233112 1 0.4331 0.75353 0.808 0.004 0.036 0.152
#> GSM1233085 3 0.5030 0.63009 0.188 0.000 0.752 0.060
#> GSM1233098 2 0.3323 0.45928 0.000 0.876 0.064 0.060
#> GSM1233114 1 0.6559 0.09974 0.480 0.004 0.064 0.452
#> GSM1233119 4 0.2485 0.66143 0.004 0.064 0.016 0.916
#> GSM1233129 2 0.5007 0.21555 0.000 0.636 0.356 0.008
#> GSM1233132 4 0.5706 0.49153 0.236 0.004 0.064 0.696
#> GSM1233139 2 0.6837 -0.04754 0.000 0.504 0.104 0.392
#> GSM1233143 2 0.3320 0.45520 0.000 0.876 0.056 0.068
#> GSM1233145 4 0.4917 0.49631 0.336 0.000 0.008 0.656
#> GSM1233067 2 0.4964 0.11893 0.000 0.616 0.380 0.004
#> GSM1233069 3 0.3032 0.73784 0.000 0.124 0.868 0.008
#> GSM1233072 2 0.3024 0.35025 0.000 0.852 0.000 0.148
#> GSM1233086 2 0.5658 0.25218 0.000 0.632 0.328 0.040
#> GSM1233102 4 0.4360 0.57213 0.248 0.000 0.008 0.744
#> GSM1233103 4 0.8800 0.39124 0.088 0.284 0.160 0.468
#> GSM1233107 4 0.7551 0.51169 0.052 0.244 0.108 0.596
#> GSM1233108 3 0.5169 0.58242 0.272 0.000 0.696 0.032
#> GSM1233109 3 0.4663 0.67732 0.148 0.000 0.788 0.064
#> GSM1233110 3 0.3043 0.74843 0.004 0.112 0.876 0.008
#> GSM1233113 2 0.5060 0.07363 0.000 0.584 0.412 0.004
#> GSM1233116 2 0.4781 0.19409 0.000 0.660 0.336 0.004
#> GSM1233120 4 0.4137 0.58065 0.208 0.000 0.012 0.780
#> GSM1233121 3 0.3421 0.73909 0.000 0.088 0.868 0.044
#> GSM1233123 3 0.2918 0.74530 0.000 0.116 0.876 0.008
#> GSM1233124 2 0.5345 0.08486 0.000 0.560 0.428 0.012
#> GSM1233125 3 0.5025 0.59144 0.252 0.000 0.716 0.032
#> GSM1233126 4 0.1824 0.65417 0.004 0.060 0.000 0.936
#> GSM1233127 2 0.5105 -0.10784 0.000 0.564 0.004 0.432
#> GSM1233128 1 0.3504 0.74172 0.872 0.004 0.056 0.068
#> GSM1233130 3 0.3382 0.74824 0.004 0.080 0.876 0.040
#> GSM1233131 4 0.7944 0.50681 0.272 0.096 0.076 0.556
#> GSM1233133 3 0.4907 0.64622 0.176 0.000 0.764 0.060
#> GSM1233134 3 0.3032 0.73784 0.000 0.124 0.868 0.008
#> GSM1233135 3 0.3032 0.73784 0.000 0.124 0.868 0.008
#> GSM1233136 3 0.3399 0.74036 0.000 0.092 0.868 0.040
#> GSM1233137 3 0.3840 0.72065 0.104 0.000 0.844 0.052
#> GSM1233138 4 0.2125 0.65731 0.004 0.076 0.000 0.920
#> GSM1233140 1 0.6098 0.53900 0.664 0.012 0.264 0.060
#> GSM1233141 2 0.5004 -0.03799 0.000 0.604 0.004 0.392
#> GSM1233142 2 0.5039 -0.06197 0.000 0.592 0.004 0.404
#> GSM1233144 3 0.4114 0.71100 0.112 0.000 0.828 0.060
#> GSM1233147 2 0.6275 0.36771 0.000 0.660 0.136 0.204
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.4906 -0.0182 0.000 0.640 0.008 0.324 0.028
#> GSM1233002 4 0.6824 -0.4603 0.000 0.340 0.000 0.340 0.320
#> GSM1233003 1 0.5973 0.2754 0.552 0.024 0.000 0.064 0.360
#> GSM1233014 2 0.6446 0.2791 0.000 0.492 0.016 0.372 0.120
#> GSM1233015 5 0.5766 0.5138 0.096 0.176 0.000 0.044 0.684
#> GSM1233016 5 0.6630 0.3600 0.000 0.220 0.000 0.376 0.404
#> GSM1233024 2 0.1907 0.6104 0.000 0.928 0.000 0.044 0.028
#> GSM1233049 1 0.0290 0.7518 0.992 0.000 0.000 0.000 0.008
#> GSM1233064 4 0.5537 0.5497 0.000 0.264 0.112 0.624 0.000
#> GSM1233068 4 0.6824 -0.0996 0.012 0.188 0.000 0.428 0.372
#> GSM1233073 4 0.6802 -0.4728 0.000 0.300 0.000 0.372 0.328
#> GSM1233093 1 0.1671 0.7374 0.924 0.000 0.000 0.000 0.076
#> GSM1233115 1 0.4317 0.6010 0.668 0.000 0.004 0.008 0.320
#> GSM1232992 2 0.1954 0.5928 0.000 0.932 0.008 0.032 0.028
#> GSM1232993 2 0.2629 0.5875 0.000 0.860 0.000 0.136 0.004
#> GSM1233005 2 0.1780 0.5969 0.000 0.940 0.008 0.024 0.028
#> GSM1233007 4 0.3710 0.3644 0.000 0.192 0.000 0.784 0.024
#> GSM1233010 2 0.6824 -0.2409 0.000 0.344 0.000 0.332 0.324
#> GSM1233013 2 0.1579 0.5919 0.000 0.944 0.000 0.032 0.024
#> GSM1233018 2 0.2193 0.5846 0.000 0.920 0.008 0.044 0.028
#> GSM1233019 2 0.0865 0.6066 0.000 0.972 0.000 0.004 0.024
#> GSM1233021 2 0.1588 0.6014 0.000 0.948 0.008 0.016 0.028
#> GSM1233025 5 0.6482 0.3823 0.000 0.188 0.000 0.372 0.440
#> GSM1233029 2 0.0162 0.6116 0.000 0.996 0.000 0.004 0.000
#> GSM1233030 2 0.0865 0.6043 0.000 0.972 0.000 0.004 0.024
#> GSM1233031 2 0.4225 0.4194 0.000 0.632 0.000 0.364 0.004
#> GSM1233032 1 0.5890 0.5066 0.496 0.000 0.028 0.044 0.432
#> GSM1233035 2 0.5486 -0.1964 0.004 0.500 0.000 0.052 0.444
#> GSM1233038 5 0.7407 0.3756 0.348 0.188 0.000 0.048 0.416
#> GSM1233039 4 0.3950 0.5425 0.000 0.136 0.068 0.796 0.000
#> GSM1233042 2 0.5727 0.3512 0.000 0.556 0.016 0.372 0.056
#> GSM1233043 2 0.5609 0.3598 0.000 0.564 0.016 0.372 0.048
#> GSM1233044 4 0.6016 0.0335 0.020 0.148 0.000 0.636 0.196
#> GSM1233046 5 0.5243 0.4990 0.004 0.352 0.000 0.048 0.596
#> GSM1233051 1 0.4370 0.5924 0.656 0.004 0.000 0.008 0.332
#> GSM1233054 4 0.5014 0.2677 0.004 0.000 0.024 0.540 0.432
#> GSM1233057 4 0.6890 0.5113 0.000 0.168 0.176 0.584 0.072
#> GSM1233060 2 0.6046 0.2437 0.000 0.524 0.000 0.344 0.132
#> GSM1233062 2 0.1965 0.6128 0.000 0.924 0.000 0.052 0.024
#> GSM1233075 3 0.3239 0.7319 0.000 0.068 0.852 0.080 0.000
#> GSM1233078 3 0.0703 0.8223 0.000 0.000 0.976 0.024 0.000
#> GSM1233079 3 0.7000 0.2945 0.112 0.000 0.444 0.052 0.392
#> GSM1233082 5 0.4728 0.5171 0.060 0.240 0.000 0.000 0.700
#> GSM1233083 1 0.3030 0.6795 0.868 0.004 0.000 0.040 0.088
#> GSM1233091 4 0.2696 0.4926 0.000 0.040 0.028 0.900 0.032
#> GSM1233095 1 0.0000 0.7521 1.000 0.000 0.000 0.000 0.000
#> GSM1233096 5 0.5301 0.4511 0.176 0.148 0.000 0.000 0.676
#> GSM1233101 1 0.0000 0.7521 1.000 0.000 0.000 0.000 0.000
#> GSM1233105 5 0.6568 0.5508 0.028 0.248 0.000 0.156 0.568
#> GSM1233117 2 0.4140 0.3203 0.000 0.764 0.008 0.200 0.028
#> GSM1233118 4 0.5285 0.5418 0.000 0.356 0.060 0.584 0.000
#> GSM1233001 4 0.5704 0.5627 0.000 0.328 0.064 0.592 0.016
#> GSM1233006 2 0.4581 0.4165 0.000 0.624 0.004 0.360 0.012
#> GSM1233008 2 0.2036 0.5790 0.000 0.920 0.000 0.056 0.024
#> GSM1233009 2 0.1403 0.6024 0.000 0.952 0.000 0.024 0.024
#> GSM1233017 2 0.0703 0.6057 0.000 0.976 0.000 0.000 0.024
#> GSM1233020 2 0.5222 -0.3397 0.000 0.512 0.008 0.452 0.028
#> GSM1233022 2 0.4577 0.5189 0.000 0.740 0.000 0.176 0.084
#> GSM1233026 4 0.6798 -0.4109 0.000 0.324 0.000 0.376 0.300
#> GSM1233028 2 0.5523 0.3422 0.000 0.572 0.000 0.348 0.080
#> GSM1233034 4 0.5085 0.5313 0.000 0.344 0.004 0.612 0.040
#> GSM1233040 5 0.5573 -0.5385 0.460 0.000 0.024 0.028 0.488
#> GSM1233048 5 0.5336 0.1372 0.288 0.084 0.000 0.000 0.628
#> GSM1233056 1 0.1410 0.7299 0.940 0.000 0.000 0.000 0.060
#> GSM1233058 2 0.6822 -0.2283 0.000 0.344 0.000 0.340 0.316
#> GSM1233059 1 0.1851 0.7352 0.912 0.000 0.000 0.000 0.088
#> GSM1233066 4 0.4211 0.3133 0.000 0.000 0.360 0.636 0.004
#> GSM1233071 2 0.1579 0.6068 0.000 0.944 0.000 0.032 0.024
#> GSM1233074 4 0.5703 0.5715 0.000 0.316 0.092 0.588 0.004
#> GSM1233076 4 0.2983 0.4369 0.000 0.096 0.040 0.864 0.000
#> GSM1233080 1 0.0000 0.7521 1.000 0.000 0.000 0.000 0.000
#> GSM1233088 4 0.6225 0.3974 0.000 0.028 0.160 0.624 0.188
#> GSM1233090 1 0.0404 0.7521 0.988 0.000 0.000 0.000 0.012
#> GSM1233092 2 0.6299 0.2891 0.000 0.496 0.012 0.380 0.112
#> GSM1233094 2 0.5990 0.3275 0.000 0.536 0.016 0.372 0.076
#> GSM1233097 2 0.5784 0.3518 0.000 0.552 0.016 0.372 0.060
#> GSM1233100 2 0.6747 -0.1153 0.000 0.376 0.000 0.364 0.260
#> GSM1233104 2 0.6374 0.2920 0.000 0.500 0.016 0.372 0.112
#> GSM1233106 5 0.6235 -0.0958 0.276 0.048 0.000 0.076 0.600
#> GSM1233111 1 0.5061 0.5359 0.528 0.008 0.000 0.020 0.444
#> GSM1233122 2 0.3563 0.4437 0.000 0.824 0.008 0.140 0.028
#> GSM1233146 2 0.4696 0.4095 0.000 0.616 0.000 0.360 0.024
#> GSM1232994 2 0.1195 0.6075 0.000 0.960 0.000 0.012 0.028
#> GSM1232996 2 0.2409 0.5728 0.000 0.908 0.008 0.056 0.028
#> GSM1232997 4 0.6017 0.5761 0.000 0.292 0.132 0.572 0.004
#> GSM1232998 2 0.5928 0.2998 0.000 0.500 0.000 0.392 0.108
#> GSM1232999 2 0.3048 0.5628 0.000 0.820 0.000 0.176 0.004
#> GSM1233000 2 0.0671 0.6100 0.000 0.980 0.000 0.004 0.016
#> GSM1233004 3 0.4825 0.3647 0.024 0.000 0.568 0.408 0.000
#> GSM1233011 4 0.4078 0.4996 0.000 0.128 0.072 0.796 0.004
#> GSM1233012 4 0.4664 0.4561 0.000 0.436 0.004 0.552 0.008
#> GSM1233023 4 0.5635 0.5671 0.000 0.320 0.068 0.600 0.012
#> GSM1233027 2 0.1364 0.6122 0.000 0.952 0.000 0.036 0.012
#> GSM1233033 5 0.5670 0.5851 0.096 0.224 0.000 0.020 0.660
#> GSM1233036 4 0.4637 0.4775 0.000 0.420 0.008 0.568 0.004
#> GSM1233037 4 0.5206 0.2816 0.000 0.004 0.036 0.544 0.416
#> GSM1233041 1 0.1792 0.7349 0.916 0.000 0.000 0.000 0.084
#> GSM1233045 2 0.4915 0.4404 0.000 0.660 0.016 0.300 0.024
#> GSM1233047 1 0.7302 0.4411 0.416 0.000 0.104 0.084 0.396
#> GSM1233050 1 0.3876 0.6111 0.684 0.000 0.000 0.000 0.316
#> GSM1233052 5 0.5769 0.5270 0.032 0.340 0.000 0.044 0.584
#> GSM1233053 1 0.5890 0.5066 0.496 0.000 0.028 0.044 0.432
#> GSM1233055 1 0.2690 0.7047 0.844 0.000 0.000 0.000 0.156
#> GSM1233061 4 0.5420 0.2068 0.000 0.000 0.416 0.524 0.060
#> GSM1233063 1 0.4219 0.5557 0.584 0.000 0.000 0.000 0.416
#> GSM1233065 4 0.5944 0.5732 0.000 0.312 0.116 0.568 0.004
#> GSM1233070 2 0.4086 0.5270 0.000 0.736 0.000 0.240 0.024
#> GSM1233077 3 0.0703 0.8223 0.000 0.000 0.976 0.024 0.000
#> GSM1233081 3 0.4374 0.6416 0.028 0.000 0.700 0.000 0.272
#> GSM1233084 1 0.0000 0.7521 1.000 0.000 0.000 0.000 0.000
#> GSM1233087 5 0.7064 0.3907 0.020 0.204 0.000 0.376 0.400
#> GSM1233089 4 0.4807 0.4168 0.000 0.464 0.008 0.520 0.008
#> GSM1233099 5 0.6696 0.3340 0.000 0.240 0.000 0.372 0.388
#> GSM1233112 1 0.1732 0.7319 0.920 0.000 0.000 0.000 0.080
#> GSM1233085 3 0.5107 0.5599 0.044 0.000 0.620 0.004 0.332
#> GSM1233098 2 0.5040 -0.3276 0.000 0.516 0.004 0.456 0.024
#> GSM1233114 5 0.4854 0.3651 0.184 0.088 0.000 0.004 0.724
#> GSM1233119 4 0.6696 -0.4933 0.000 0.240 0.000 0.388 0.372
#> GSM1233129 4 0.5575 0.5683 0.000 0.320 0.080 0.596 0.004
#> GSM1233132 5 0.5523 0.5955 0.048 0.224 0.000 0.048 0.680
#> GSM1233139 2 0.2325 0.5843 0.000 0.904 0.000 0.068 0.028
#> GSM1233143 2 0.5019 -0.2879 0.000 0.536 0.004 0.436 0.024
#> GSM1233145 5 0.7366 0.3756 0.348 0.180 0.000 0.048 0.424
#> GSM1233067 4 0.6358 0.5502 0.000 0.328 0.180 0.492 0.000
#> GSM1233069 3 0.0703 0.8223 0.000 0.000 0.976 0.024 0.000
#> GSM1233072 2 0.4415 0.2412 0.000 0.728 0.008 0.236 0.028
#> GSM1233086 4 0.4782 0.4371 0.000 0.052 0.244 0.700 0.004
#> GSM1233102 5 0.7146 0.4043 0.028 0.192 0.000 0.368 0.412
#> GSM1233103 5 0.5774 0.4876 0.004 0.336 0.000 0.092 0.568
#> GSM1233107 2 0.6407 0.2261 0.004 0.500 0.000 0.332 0.164
#> GSM1233108 3 0.4382 0.5869 0.288 0.000 0.688 0.000 0.024
#> GSM1233109 3 0.1186 0.8156 0.020 0.000 0.964 0.008 0.008
#> GSM1233110 3 0.0703 0.8223 0.000 0.000 0.976 0.024 0.000
#> GSM1233113 4 0.6311 0.5529 0.000 0.320 0.176 0.504 0.000
#> GSM1233116 4 0.6406 0.5490 0.000 0.328 0.188 0.484 0.000
#> GSM1233120 5 0.7107 0.4077 0.028 0.184 0.000 0.368 0.420
#> GSM1233121 3 0.0703 0.8223 0.000 0.000 0.976 0.024 0.000
#> GSM1233123 3 0.0703 0.8223 0.000 0.000 0.976 0.024 0.000
#> GSM1233124 4 0.5708 0.2978 0.000 0.084 0.412 0.504 0.000
#> GSM1233125 3 0.4506 0.5730 0.296 0.000 0.676 0.000 0.028
#> GSM1233126 2 0.6514 0.2688 0.000 0.484 0.016 0.372 0.128
#> GSM1233127 2 0.1082 0.6159 0.000 0.964 0.000 0.028 0.008
#> GSM1233128 1 0.1331 0.7378 0.952 0.000 0.008 0.000 0.040
#> GSM1233130 3 0.0703 0.8223 0.000 0.000 0.976 0.024 0.000
#> GSM1233131 5 0.6023 0.5700 0.068 0.296 0.000 0.036 0.600
#> GSM1233133 3 0.4374 0.6417 0.028 0.000 0.700 0.000 0.272
#> GSM1233134 3 0.1582 0.8020 0.000 0.028 0.944 0.028 0.000
#> GSM1233135 3 0.0794 0.8203 0.000 0.000 0.972 0.028 0.000
#> GSM1233136 3 0.0703 0.8223 0.000 0.000 0.976 0.024 0.000
#> GSM1233137 3 0.4351 0.6885 0.004 0.000 0.724 0.028 0.244
#> GSM1233138 2 0.6480 0.2754 0.000 0.488 0.016 0.372 0.124
#> GSM1233140 1 0.6201 0.4991 0.480 0.000 0.040 0.052 0.428
#> GSM1233141 2 0.1579 0.5993 0.000 0.944 0.000 0.032 0.024
#> GSM1233142 2 0.0865 0.6043 0.000 0.972 0.000 0.004 0.024
#> GSM1233144 3 0.3106 0.7801 0.008 0.000 0.856 0.020 0.116
#> GSM1233147 4 0.3055 0.4107 0.000 0.072 0.000 0.864 0.064
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.4757 0.0327 0.000 0.508 0.004 0.008 0.024 0.456
#> GSM1233002 4 0.2703 0.6545 0.000 0.172 0.000 0.824 0.000 0.004
#> GSM1233003 1 0.7210 0.0403 0.372 0.096 0.000 0.304 0.228 0.000
#> GSM1233014 2 0.4669 0.4627 0.004 0.504 0.008 0.468 0.004 0.012
#> GSM1233015 4 0.4832 0.2164 0.000 0.044 0.000 0.492 0.460 0.004
#> GSM1233016 4 0.2420 0.6676 0.004 0.128 0.000 0.864 0.000 0.004
#> GSM1233024 2 0.0692 0.7029 0.000 0.976 0.000 0.020 0.004 0.000
#> GSM1233049 1 0.0790 0.7813 0.968 0.000 0.000 0.000 0.032 0.000
#> GSM1233064 6 0.3594 0.7468 0.000 0.068 0.024 0.060 0.012 0.836
#> GSM1233068 4 0.6984 0.1844 0.008 0.072 0.000 0.408 0.156 0.356
#> GSM1233073 4 0.2482 0.6374 0.000 0.148 0.000 0.848 0.004 0.000
#> GSM1233093 1 0.2135 0.7337 0.872 0.000 0.000 0.000 0.128 0.000
#> GSM1233115 1 0.4288 0.4551 0.744 0.000 0.048 0.016 0.188 0.004
#> GSM1232992 2 0.3622 0.6483 0.000 0.792 0.004 0.012 0.024 0.168
#> GSM1232993 2 0.2218 0.6837 0.000 0.884 0.000 0.104 0.000 0.012
#> GSM1233005 2 0.4125 0.6813 0.000 0.776 0.004 0.068 0.016 0.136
#> GSM1233007 6 0.5269 0.6205 0.000 0.112 0.004 0.204 0.020 0.660
#> GSM1233010 4 0.2454 0.6588 0.000 0.160 0.000 0.840 0.000 0.000
#> GSM1233013 2 0.3124 0.6608 0.000 0.828 0.000 0.008 0.024 0.140
#> GSM1233018 2 0.4022 0.6249 0.000 0.756 0.004 0.020 0.024 0.196
#> GSM1233019 2 0.0725 0.7052 0.000 0.976 0.000 0.012 0.000 0.012
#> GSM1233021 2 0.3536 0.6942 0.000 0.820 0.004 0.048 0.012 0.116
#> GSM1233025 4 0.1471 0.6523 0.004 0.064 0.000 0.932 0.000 0.000
#> GSM1233029 2 0.1257 0.7077 0.000 0.952 0.000 0.020 0.000 0.028
#> GSM1233030 2 0.1194 0.7063 0.000 0.956 0.000 0.008 0.004 0.032
#> GSM1233031 2 0.3730 0.5764 0.000 0.740 0.000 0.236 0.008 0.016
#> GSM1233032 5 0.4027 0.5832 0.216 0.000 0.024 0.000 0.740 0.020
#> GSM1233035 2 0.5672 -0.0773 0.000 0.528 0.000 0.260 0.212 0.000
#> GSM1233038 4 0.4070 0.4029 0.248 0.004 0.000 0.716 0.028 0.004
#> GSM1233039 6 0.3907 0.7218 0.000 0.036 0.008 0.128 0.028 0.800
#> GSM1233042 2 0.4400 0.4008 0.000 0.560 0.008 0.420 0.004 0.008
#> GSM1233043 2 0.4261 0.5049 0.000 0.620 0.008 0.360 0.004 0.008
#> GSM1233044 4 0.6008 0.1843 0.036 0.032 0.000 0.516 0.044 0.372
#> GSM1233046 4 0.5646 0.5276 0.000 0.220 0.000 0.536 0.244 0.000
#> GSM1233051 5 0.4348 0.1186 0.464 0.000 0.004 0.004 0.520 0.008
#> GSM1233054 5 0.4246 0.0358 0.000 0.000 0.020 0.000 0.580 0.400
#> GSM1233057 6 0.3710 0.6273 0.000 0.012 0.024 0.000 0.196 0.768
#> GSM1233060 2 0.4393 0.0148 0.000 0.500 0.000 0.480 0.004 0.016
#> GSM1233062 2 0.0935 0.7041 0.000 0.964 0.000 0.032 0.000 0.004
#> GSM1233075 3 0.3349 0.7959 0.000 0.008 0.748 0.000 0.000 0.244
#> GSM1233078 3 0.1866 0.8301 0.000 0.000 0.908 0.000 0.008 0.084
#> GSM1233079 3 0.5364 0.2136 0.068 0.000 0.496 0.000 0.420 0.016
#> GSM1233082 4 0.6455 0.4437 0.016 0.132 0.000 0.496 0.324 0.032
#> GSM1233083 1 0.3161 0.7126 0.856 0.004 0.036 0.080 0.024 0.000
#> GSM1233091 6 0.4732 0.6734 0.000 0.012 0.004 0.160 0.108 0.716
#> GSM1233095 1 0.0146 0.7829 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1233096 4 0.6382 0.3408 0.100 0.080 0.000 0.500 0.320 0.000
#> GSM1233101 1 0.0713 0.7813 0.972 0.000 0.000 0.000 0.028 0.000
#> GSM1233105 4 0.4745 0.6088 0.000 0.136 0.000 0.676 0.188 0.000
#> GSM1233117 2 0.4808 0.2863 0.000 0.580 0.004 0.016 0.024 0.376
#> GSM1233118 6 0.2597 0.7269 0.000 0.176 0.000 0.000 0.000 0.824
#> GSM1233001 6 0.4579 0.7242 0.000 0.180 0.012 0.000 0.092 0.716
#> GSM1233006 2 0.3512 0.5804 0.000 0.720 0.000 0.272 0.000 0.008
#> GSM1233008 2 0.3384 0.6351 0.000 0.800 0.000 0.008 0.024 0.168
#> GSM1233009 2 0.0837 0.7057 0.000 0.972 0.000 0.004 0.004 0.020
#> GSM1233017 2 0.0436 0.7037 0.000 0.988 0.000 0.004 0.004 0.004
#> GSM1233020 6 0.4130 0.5777 0.000 0.300 0.004 0.000 0.024 0.672
#> GSM1233022 2 0.2624 0.6778 0.000 0.844 0.000 0.148 0.004 0.004
#> GSM1233026 4 0.4082 0.5746 0.000 0.068 0.000 0.764 0.012 0.156
#> GSM1233028 4 0.4178 0.0833 0.000 0.428 0.000 0.560 0.004 0.008
#> GSM1233034 6 0.4883 0.7010 0.000 0.240 0.000 0.008 0.092 0.660
#> GSM1233040 5 0.1843 0.5973 0.080 0.000 0.004 0.000 0.912 0.004
#> GSM1233048 5 0.5929 0.2991 0.160 0.024 0.000 0.264 0.552 0.000
#> GSM1233056 1 0.0622 0.7794 0.980 0.000 0.000 0.012 0.008 0.000
#> GSM1233058 4 0.2989 0.6488 0.000 0.176 0.000 0.812 0.008 0.004
#> GSM1233059 1 0.3547 0.5658 0.668 0.000 0.000 0.000 0.332 0.000
#> GSM1233066 6 0.4298 0.6742 0.000 0.004 0.176 0.088 0.000 0.732
#> GSM1233071 2 0.1970 0.6958 0.000 0.912 0.000 0.060 0.000 0.028
#> GSM1233074 6 0.3648 0.6826 0.000 0.024 0.128 0.000 0.040 0.808
#> GSM1233076 6 0.4502 0.6801 0.008 0.020 0.068 0.156 0.000 0.748
#> GSM1233080 1 0.0260 0.7837 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM1233088 6 0.3735 0.6120 0.000 0.008 0.020 0.000 0.224 0.748
#> GSM1233090 1 0.2340 0.7180 0.852 0.000 0.000 0.000 0.148 0.000
#> GSM1233092 2 0.4722 0.4611 0.004 0.504 0.004 0.464 0.004 0.020
#> GSM1233094 2 0.4192 0.5012 0.000 0.612 0.008 0.372 0.004 0.004
#> GSM1233097 2 0.4400 0.3883 0.000 0.560 0.008 0.420 0.004 0.008
#> GSM1233100 4 0.2912 0.6001 0.000 0.216 0.000 0.784 0.000 0.000
#> GSM1233104 2 0.4583 0.4596 0.004 0.504 0.008 0.472 0.004 0.008
#> GSM1233106 5 0.4287 0.4597 0.040 0.008 0.000 0.216 0.728 0.008
#> GSM1233111 5 0.2320 0.5760 0.132 0.000 0.000 0.000 0.864 0.004
#> GSM1233122 2 0.4540 0.5096 0.000 0.672 0.004 0.020 0.024 0.280
#> GSM1233146 2 0.4222 0.2365 0.000 0.516 0.000 0.472 0.004 0.008
#> GSM1232994 2 0.0692 0.7029 0.000 0.976 0.000 0.020 0.004 0.000
#> GSM1232996 2 0.4340 0.6388 0.000 0.744 0.004 0.048 0.020 0.184
#> GSM1232997 6 0.4236 0.7039 0.000 0.072 0.148 0.000 0.020 0.760
#> GSM1232998 2 0.4350 0.5231 0.004 0.552 0.000 0.428 0.000 0.016
#> GSM1232999 2 0.2613 0.6812 0.000 0.848 0.000 0.140 0.000 0.012
#> GSM1233000 2 0.1148 0.7065 0.000 0.960 0.000 0.016 0.004 0.020
#> GSM1233004 3 0.6155 0.5248 0.156 0.000 0.628 0.076 0.016 0.124
#> GSM1233011 6 0.3909 0.6736 0.000 0.020 0.012 0.200 0.008 0.760
#> GSM1233012 6 0.3323 0.6938 0.000 0.240 0.000 0.000 0.008 0.752
#> GSM1233023 6 0.4031 0.7397 0.000 0.112 0.020 0.000 0.084 0.784
#> GSM1233027 2 0.2094 0.7016 0.000 0.900 0.000 0.080 0.000 0.020
#> GSM1233033 4 0.6214 0.5220 0.052 0.148 0.000 0.548 0.252 0.000
#> GSM1233036 6 0.3183 0.7241 0.000 0.200 0.004 0.000 0.008 0.788
#> GSM1233037 6 0.4323 0.3608 0.000 0.004 0.020 0.000 0.376 0.600
#> GSM1233041 1 0.3515 0.5744 0.676 0.000 0.000 0.000 0.324 0.000
#> GSM1233045 2 0.4798 0.3901 0.000 0.564 0.008 0.396 0.012 0.020
#> GSM1233047 5 0.6033 0.4934 0.200 0.000 0.128 0.000 0.600 0.072
#> GSM1233050 1 0.3899 0.2304 0.628 0.000 0.008 0.000 0.364 0.000
#> GSM1233052 4 0.5420 0.5535 0.000 0.172 0.000 0.572 0.256 0.000
#> GSM1233053 5 0.3626 0.5995 0.184 0.000 0.020 0.000 0.780 0.016
#> GSM1233055 1 0.3089 0.7038 0.800 0.004 0.000 0.008 0.188 0.000
#> GSM1233061 6 0.3440 0.6085 0.000 0.000 0.196 0.000 0.028 0.776
#> GSM1233063 5 0.4838 0.1925 0.372 0.000 0.000 0.064 0.564 0.000
#> GSM1233065 6 0.4215 0.7099 0.000 0.092 0.148 0.000 0.008 0.752
#> GSM1233070 2 0.5525 0.5558 0.000 0.628 0.000 0.168 0.024 0.180
#> GSM1233077 3 0.1714 0.8280 0.000 0.000 0.908 0.000 0.000 0.092
#> GSM1233081 3 0.3056 0.7527 0.016 0.000 0.832 0.000 0.140 0.012
#> GSM1233084 1 0.0260 0.7837 0.992 0.000 0.000 0.000 0.008 0.000
#> GSM1233087 4 0.2476 0.6631 0.000 0.092 0.004 0.880 0.024 0.000
#> GSM1233089 6 0.3487 0.6876 0.000 0.224 0.000 0.000 0.020 0.756
#> GSM1233099 4 0.2234 0.6640 0.000 0.124 0.000 0.872 0.004 0.000
#> GSM1233112 1 0.2077 0.7624 0.920 0.000 0.012 0.032 0.032 0.004
#> GSM1233085 3 0.4512 0.6556 0.028 0.000 0.708 0.000 0.224 0.040
#> GSM1233098 6 0.4159 0.5850 0.000 0.300 0.000 0.008 0.020 0.672
#> GSM1233114 4 0.6179 0.0383 0.200 0.012 0.000 0.420 0.368 0.000
#> GSM1233119 4 0.1026 0.6165 0.004 0.012 0.000 0.968 0.008 0.008
#> GSM1233129 6 0.3557 0.7478 0.000 0.092 0.024 0.000 0.060 0.824
#> GSM1233132 4 0.5627 0.5497 0.016 0.144 0.000 0.584 0.256 0.000
#> GSM1233139 2 0.3425 0.6422 0.000 0.800 0.000 0.008 0.028 0.164
#> GSM1233143 6 0.4714 0.3641 0.000 0.416 0.004 0.008 0.024 0.548
#> GSM1233145 4 0.4139 0.3724 0.260 0.000 0.000 0.700 0.036 0.004
#> GSM1233067 6 0.4243 0.7030 0.000 0.104 0.164 0.000 0.000 0.732
#> GSM1233069 3 0.2738 0.8195 0.000 0.004 0.820 0.000 0.000 0.176
#> GSM1233072 2 0.4910 0.1151 0.000 0.520 0.004 0.016 0.024 0.436
#> GSM1233086 6 0.4528 0.6660 0.000 0.004 0.148 0.132 0.000 0.716
#> GSM1233102 4 0.1096 0.6173 0.008 0.004 0.000 0.964 0.020 0.004
#> GSM1233103 4 0.6280 0.5332 0.000 0.196 0.000 0.544 0.212 0.048
#> GSM1233107 2 0.5132 0.3201 0.000 0.600 0.000 0.316 0.068 0.016
#> GSM1233108 3 0.2848 0.7673 0.104 0.000 0.856 0.000 0.036 0.004
#> GSM1233109 3 0.0777 0.8089 0.000 0.000 0.972 0.000 0.024 0.004
#> GSM1233110 3 0.2006 0.8318 0.000 0.000 0.892 0.000 0.004 0.104
#> GSM1233113 6 0.4482 0.7054 0.000 0.124 0.168 0.000 0.000 0.708
#> GSM1233116 6 0.4704 0.7128 0.000 0.160 0.156 0.000 0.000 0.684
#> GSM1233120 4 0.0922 0.6223 0.004 0.004 0.000 0.968 0.024 0.000
#> GSM1233121 3 0.1908 0.8277 0.000 0.004 0.900 0.000 0.000 0.096
#> GSM1233123 3 0.3109 0.8094 0.000 0.000 0.772 0.000 0.004 0.224
#> GSM1233124 6 0.3658 0.6389 0.000 0.016 0.188 0.020 0.000 0.776
#> GSM1233125 3 0.3419 0.7348 0.152 0.000 0.804 0.000 0.040 0.004
#> GSM1233126 4 0.4579 -0.4296 0.004 0.464 0.008 0.512 0.004 0.008
#> GSM1233127 2 0.1007 0.6993 0.000 0.956 0.000 0.044 0.000 0.000
#> GSM1233128 1 0.0291 0.7819 0.992 0.000 0.004 0.000 0.004 0.000
#> GSM1233130 3 0.1908 0.8292 0.000 0.000 0.900 0.000 0.004 0.096
#> GSM1233131 4 0.5680 0.5418 0.012 0.160 0.000 0.568 0.260 0.000
#> GSM1233133 3 0.3202 0.7530 0.000 0.000 0.816 0.000 0.144 0.040
#> GSM1233134 3 0.3512 0.7690 0.000 0.008 0.720 0.000 0.000 0.272
#> GSM1233135 3 0.3081 0.8099 0.000 0.004 0.776 0.000 0.000 0.220
#> GSM1233136 3 0.1714 0.8280 0.000 0.000 0.908 0.000 0.000 0.092
#> GSM1233137 3 0.3261 0.7866 0.000 0.000 0.824 0.000 0.104 0.072
#> GSM1233138 2 0.4583 0.4596 0.004 0.504 0.008 0.472 0.004 0.008
#> GSM1233140 5 0.3946 0.5882 0.208 0.000 0.032 0.000 0.748 0.012
#> GSM1233141 2 0.2969 0.6846 0.000 0.852 0.004 0.008 0.024 0.112
#> GSM1233142 2 0.1155 0.7060 0.000 0.956 0.000 0.004 0.004 0.036
#> GSM1233144 3 0.2842 0.7882 0.000 0.000 0.852 0.000 0.104 0.044
#> GSM1233147 6 0.4776 0.6482 0.012 0.012 0.056 0.204 0.004 0.712
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> MAD:mclust 155 7.13e-01 1.00000 1.00000 2
#> MAD:mclust 130 3.15e-01 0.79764 0.03656 3
#> MAD:mclust 74 1.42e-06 0.00567 0.00667 4
#> MAD:mclust 87 3.40e-06 0.04095 0.16562 5
#> MAD:mclust 120 3.37e-05 0.08218 0.13668 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 51941 rows and 156 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 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.545 0.783 0.908 0.4974 0.497 0.497
#> 3 3 0.330 0.483 0.742 0.3153 0.682 0.445
#> 4 4 0.427 0.542 0.741 0.1284 0.813 0.515
#> 5 5 0.544 0.572 0.758 0.0706 0.888 0.606
#> 6 6 0.553 0.414 0.640 0.0418 0.891 0.557
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0672 0.9041 0.008 0.992
#> GSM1233002 1 0.0000 0.8758 1.000 0.000
#> GSM1233003 1 0.0000 0.8758 1.000 0.000
#> GSM1233014 1 0.0000 0.8758 1.000 0.000
#> GSM1233015 2 0.4939 0.8319 0.108 0.892
#> GSM1233016 1 0.0000 0.8758 1.000 0.000
#> GSM1233024 1 0.5519 0.7906 0.872 0.128
#> GSM1233049 2 0.3114 0.8680 0.056 0.944
#> GSM1233064 2 0.0000 0.9072 0.000 1.000
#> GSM1233068 2 0.9087 0.5335 0.324 0.676
#> GSM1233073 1 0.0000 0.8758 1.000 0.000
#> GSM1233093 1 0.0000 0.8758 1.000 0.000
#> GSM1233115 1 0.6973 0.7298 0.812 0.188
#> GSM1232992 2 0.7815 0.6854 0.232 0.768
#> GSM1232993 1 0.9209 0.4983 0.664 0.336
#> GSM1233005 1 0.8909 0.5538 0.692 0.308
#> GSM1233007 1 0.1184 0.8711 0.984 0.016
#> GSM1233010 1 0.0000 0.8758 1.000 0.000
#> GSM1233013 2 0.6343 0.7766 0.160 0.840
#> GSM1233018 2 0.3584 0.8655 0.068 0.932
#> GSM1233019 1 0.9393 0.4552 0.644 0.356
#> GSM1233021 1 0.9954 0.1582 0.540 0.460
#> GSM1233025 1 0.0000 0.8758 1.000 0.000
#> GSM1233029 1 0.9552 0.4081 0.624 0.376
#> GSM1233030 2 0.9580 0.3946 0.380 0.620
#> GSM1233031 1 0.0000 0.8758 1.000 0.000
#> GSM1233032 2 0.0000 0.9072 0.000 1.000
#> GSM1233035 1 0.9491 0.4283 0.632 0.368
#> GSM1233038 1 0.0000 0.8758 1.000 0.000
#> GSM1233039 2 0.0376 0.9057 0.004 0.996
#> GSM1233042 1 0.0000 0.8758 1.000 0.000
#> GSM1233043 1 0.0000 0.8758 1.000 0.000
#> GSM1233044 1 0.4298 0.8259 0.912 0.088
#> GSM1233046 2 0.9993 0.0461 0.484 0.516
#> GSM1233051 1 0.9998 0.0899 0.508 0.492
#> GSM1233054 2 0.0000 0.9072 0.000 1.000
#> GSM1233057 2 0.0000 0.9072 0.000 1.000
#> GSM1233060 1 0.0672 0.8730 0.992 0.008
#> GSM1233062 1 0.7219 0.7130 0.800 0.200
#> GSM1233075 2 0.0000 0.9072 0.000 1.000
#> GSM1233078 2 0.0000 0.9072 0.000 1.000
#> GSM1233079 2 0.0376 0.9053 0.004 0.996
#> GSM1233082 1 0.1843 0.8652 0.972 0.028
#> GSM1233083 1 0.0000 0.8758 1.000 0.000
#> GSM1233091 2 0.0938 0.9015 0.012 0.988
#> GSM1233095 1 0.7299 0.7081 0.796 0.204
#> GSM1233096 1 0.9323 0.4682 0.652 0.348
#> GSM1233101 1 0.9248 0.4894 0.660 0.340
#> GSM1233105 1 0.0000 0.8758 1.000 0.000
#> GSM1233117 2 0.5519 0.8116 0.128 0.872
#> GSM1233118 2 0.0000 0.9072 0.000 1.000
#> GSM1233001 2 0.0000 0.9072 0.000 1.000
#> GSM1233006 1 0.0672 0.8730 0.992 0.008
#> GSM1233008 2 0.3431 0.8688 0.064 0.936
#> GSM1233009 2 0.9393 0.4547 0.356 0.644
#> GSM1233017 2 0.9983 0.0779 0.476 0.524
#> GSM1233020 2 0.0376 0.9057 0.004 0.996
#> GSM1233022 1 0.0000 0.8758 1.000 0.000
#> GSM1233026 1 0.1843 0.8638 0.972 0.028
#> GSM1233028 1 0.5059 0.8048 0.888 0.112
#> GSM1233034 2 0.0000 0.9072 0.000 1.000
#> GSM1233040 2 0.0000 0.9072 0.000 1.000
#> GSM1233048 1 0.7815 0.6717 0.768 0.232
#> GSM1233056 1 0.0000 0.8758 1.000 0.000
#> GSM1233058 1 0.0000 0.8758 1.000 0.000
#> GSM1233059 1 0.6438 0.7695 0.836 0.164
#> GSM1233066 2 0.0000 0.9072 0.000 1.000
#> GSM1233071 2 0.9580 0.3949 0.380 0.620
#> GSM1233074 2 0.0000 0.9072 0.000 1.000
#> GSM1233076 1 0.6343 0.7588 0.840 0.160
#> GSM1233080 1 0.4815 0.8120 0.896 0.104
#> GSM1233088 2 0.0000 0.9072 0.000 1.000
#> GSM1233090 2 0.4022 0.8497 0.080 0.920
#> GSM1233092 1 0.0000 0.8758 1.000 0.000
#> GSM1233094 1 0.0000 0.8758 1.000 0.000
#> GSM1233097 1 0.0000 0.8758 1.000 0.000
#> GSM1233100 1 0.0000 0.8758 1.000 0.000
#> GSM1233104 1 0.0000 0.8758 1.000 0.000
#> GSM1233106 2 0.1633 0.8970 0.024 0.976
#> GSM1233111 2 0.2043 0.8920 0.032 0.968
#> GSM1233122 2 0.9129 0.5172 0.328 0.672
#> GSM1233146 1 0.0000 0.8758 1.000 0.000
#> GSM1232994 1 0.9248 0.4894 0.660 0.340
#> GSM1232996 2 0.7453 0.7140 0.212 0.788
#> GSM1232997 2 0.0000 0.9072 0.000 1.000
#> GSM1232998 1 0.0000 0.8758 1.000 0.000
#> GSM1232999 1 0.0000 0.8758 1.000 0.000
#> GSM1233000 2 0.9323 0.4735 0.348 0.652
#> GSM1233004 1 0.8386 0.6186 0.732 0.268
#> GSM1233011 1 0.8661 0.5893 0.712 0.288
#> GSM1233012 2 0.0000 0.9072 0.000 1.000
#> GSM1233023 2 0.0000 0.9072 0.000 1.000
#> GSM1233027 1 0.0000 0.8758 1.000 0.000
#> GSM1233033 1 0.0000 0.8758 1.000 0.000
#> GSM1233036 2 0.0000 0.9072 0.000 1.000
#> GSM1233037 2 0.0000 0.9072 0.000 1.000
#> GSM1233041 1 0.0672 0.8728 0.992 0.008
#> GSM1233045 1 0.0000 0.8758 1.000 0.000
#> GSM1233047 2 0.0000 0.9072 0.000 1.000
#> GSM1233050 2 0.0000 0.9072 0.000 1.000
#> GSM1233052 1 0.0000 0.8758 1.000 0.000
#> GSM1233053 2 0.0000 0.9072 0.000 1.000
#> GSM1233055 1 0.0000 0.8758 1.000 0.000
#> GSM1233061 2 0.0000 0.9072 0.000 1.000
#> GSM1233063 1 0.3274 0.8446 0.940 0.060
#> GSM1233065 2 0.0000 0.9072 0.000 1.000
#> GSM1233070 1 0.4562 0.8184 0.904 0.096
#> GSM1233077 2 0.0000 0.9072 0.000 1.000
#> GSM1233081 2 0.0000 0.9072 0.000 1.000
#> GSM1233084 1 0.0376 0.8743 0.996 0.004
#> GSM1233087 1 0.0000 0.8758 1.000 0.000
#> GSM1233089 2 0.3584 0.8667 0.068 0.932
#> GSM1233099 1 0.0000 0.8758 1.000 0.000
#> GSM1233112 1 0.0672 0.8728 0.992 0.008
#> GSM1233085 2 0.0000 0.9072 0.000 1.000
#> GSM1233098 1 0.9983 0.1163 0.524 0.476
#> GSM1233114 1 0.1414 0.8676 0.980 0.020
#> GSM1233119 1 0.0000 0.8758 1.000 0.000
#> GSM1233129 2 0.0000 0.9072 0.000 1.000
#> GSM1233132 1 0.0000 0.8758 1.000 0.000
#> GSM1233139 2 0.0376 0.9058 0.004 0.996
#> GSM1233143 2 0.0376 0.9058 0.004 0.996
#> GSM1233145 1 0.0000 0.8758 1.000 0.000
#> GSM1233067 2 0.0000 0.9072 0.000 1.000
#> GSM1233069 2 0.0000 0.9072 0.000 1.000
#> GSM1233072 2 0.8207 0.6458 0.256 0.744
#> GSM1233086 2 0.5842 0.7857 0.140 0.860
#> GSM1233102 1 0.0000 0.8758 1.000 0.000
#> GSM1233103 1 0.9977 0.1200 0.528 0.472
#> GSM1233107 1 0.9970 0.1301 0.532 0.468
#> GSM1233108 2 0.6247 0.7566 0.156 0.844
#> GSM1233109 2 0.5946 0.7739 0.144 0.856
#> GSM1233110 2 0.0000 0.9072 0.000 1.000
#> GSM1233113 2 0.0000 0.9072 0.000 1.000
#> GSM1233116 2 0.0000 0.9072 0.000 1.000
#> GSM1233120 1 0.0000 0.8758 1.000 0.000
#> GSM1233121 2 0.0000 0.9072 0.000 1.000
#> GSM1233123 2 0.0000 0.9072 0.000 1.000
#> GSM1233124 2 0.0000 0.9072 0.000 1.000
#> GSM1233125 2 0.8499 0.5571 0.276 0.724
#> GSM1233126 1 0.0000 0.8758 1.000 0.000
#> GSM1233127 1 0.9909 0.2132 0.556 0.444
#> GSM1233128 1 0.6973 0.7286 0.812 0.188
#> GSM1233130 2 0.0000 0.9072 0.000 1.000
#> GSM1233131 1 0.0000 0.8758 1.000 0.000
#> GSM1233133 2 0.0000 0.9072 0.000 1.000
#> GSM1233134 2 0.0000 0.9072 0.000 1.000
#> GSM1233135 2 0.0000 0.9072 0.000 1.000
#> GSM1233136 2 0.0672 0.9033 0.008 0.992
#> GSM1233137 2 0.0000 0.9072 0.000 1.000
#> GSM1233138 1 0.0000 0.8758 1.000 0.000
#> GSM1233140 2 0.1184 0.8983 0.016 0.984
#> GSM1233141 2 0.7815 0.6852 0.232 0.768
#> GSM1233142 2 0.9552 0.4056 0.376 0.624
#> GSM1233144 2 0.0000 0.9072 0.000 1.000
#> GSM1233147 1 0.5629 0.7872 0.868 0.132
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.6027 0.4449 0.016 0.712 0.272
#> GSM1233002 1 0.5810 0.5630 0.664 0.336 0.000
#> GSM1233003 1 0.4934 0.6084 0.820 0.024 0.156
#> GSM1233014 1 0.4178 0.6587 0.828 0.172 0.000
#> GSM1233015 2 0.2496 0.6001 0.004 0.928 0.068
#> GSM1233016 1 0.3263 0.6784 0.912 0.048 0.040
#> GSM1233024 2 0.5835 0.3781 0.340 0.660 0.000
#> GSM1233049 3 0.2879 0.6722 0.052 0.024 0.924
#> GSM1233064 2 0.6008 0.1331 0.000 0.628 0.372
#> GSM1233068 2 0.3043 0.5943 0.008 0.908 0.084
#> GSM1233073 1 0.3619 0.6800 0.864 0.136 0.000
#> GSM1233093 1 0.5903 0.5521 0.744 0.232 0.024
#> GSM1233115 1 0.9507 0.1039 0.432 0.188 0.380
#> GSM1232992 2 0.1315 0.6457 0.008 0.972 0.020
#> GSM1232993 2 0.2400 0.6339 0.064 0.932 0.004
#> GSM1233005 2 0.5815 0.4673 0.304 0.692 0.004
#> GSM1233007 1 0.4733 0.6353 0.800 0.196 0.004
#> GSM1233010 1 0.4475 0.6667 0.840 0.144 0.016
#> GSM1233013 2 0.4007 0.6591 0.084 0.880 0.036
#> GSM1233018 2 0.3967 0.6496 0.044 0.884 0.072
#> GSM1233019 2 0.5541 0.5469 0.252 0.740 0.008
#> GSM1233021 2 0.4589 0.6141 0.172 0.820 0.008
#> GSM1233025 1 0.1905 0.6750 0.956 0.016 0.028
#> GSM1233029 2 0.1529 0.6366 0.040 0.960 0.000
#> GSM1233030 2 0.2414 0.6382 0.020 0.940 0.040
#> GSM1233031 2 0.6489 -0.1016 0.456 0.540 0.004
#> GSM1233032 3 0.4931 0.5538 0.000 0.232 0.768
#> GSM1233035 2 0.2313 0.6448 0.032 0.944 0.024
#> GSM1233038 1 0.1337 0.6736 0.972 0.016 0.012
#> GSM1233039 3 0.6260 0.4025 0.000 0.448 0.552
#> GSM1233042 1 0.5497 0.5609 0.708 0.292 0.000
#> GSM1233043 1 0.5431 0.5715 0.716 0.284 0.000
#> GSM1233044 1 0.5931 0.6566 0.792 0.124 0.084
#> GSM1233046 2 0.4782 0.6240 0.164 0.820 0.016
#> GSM1233051 3 0.7569 0.4548 0.092 0.240 0.668
#> GSM1233054 3 0.6045 0.4426 0.000 0.380 0.620
#> GSM1233057 2 0.6286 -0.1026 0.000 0.536 0.464
#> GSM1233060 2 0.4291 0.4653 0.180 0.820 0.000
#> GSM1233062 2 0.5623 0.4802 0.280 0.716 0.004
#> GSM1233075 3 0.4931 0.6324 0.000 0.232 0.768
#> GSM1233078 3 0.1129 0.7040 0.004 0.020 0.976
#> GSM1233079 3 0.3083 0.6689 0.024 0.060 0.916
#> GSM1233082 2 0.9282 -0.1591 0.368 0.468 0.164
#> GSM1233083 1 0.2066 0.6628 0.940 0.000 0.060
#> GSM1233091 2 0.6126 0.1273 0.004 0.644 0.352
#> GSM1233095 1 0.9021 0.3397 0.552 0.184 0.264
#> GSM1233096 2 0.5728 0.4916 0.032 0.772 0.196
#> GSM1233101 3 0.6460 0.1861 0.440 0.004 0.556
#> GSM1233105 1 0.6066 0.6062 0.728 0.248 0.024
#> GSM1233117 2 0.7202 0.5840 0.124 0.716 0.160
#> GSM1233118 3 0.6095 0.4251 0.000 0.392 0.608
#> GSM1233001 2 0.6308 -0.1347 0.000 0.508 0.492
#> GSM1233006 1 0.5988 0.4397 0.632 0.368 0.000
#> GSM1233008 2 0.6590 0.6235 0.112 0.756 0.132
#> GSM1233009 2 0.1989 0.6266 0.004 0.948 0.048
#> GSM1233017 2 0.4755 0.6078 0.184 0.808 0.008
#> GSM1233020 2 0.6200 0.3665 0.012 0.676 0.312
#> GSM1233022 1 0.6518 0.1471 0.512 0.484 0.004
#> GSM1233026 1 0.8204 0.4620 0.588 0.316 0.096
#> GSM1233028 2 0.5948 0.3023 0.360 0.640 0.000
#> GSM1233034 2 0.3816 0.5410 0.000 0.852 0.148
#> GSM1233040 3 0.6204 0.2768 0.000 0.424 0.576
#> GSM1233048 2 0.3356 0.6215 0.036 0.908 0.056
#> GSM1233056 1 0.1585 0.6700 0.964 0.008 0.028
#> GSM1233058 1 0.3551 0.6790 0.868 0.132 0.000
#> GSM1233059 2 0.8550 0.2720 0.176 0.608 0.216
#> GSM1233066 3 0.3116 0.6980 0.000 0.108 0.892
#> GSM1233071 2 0.2982 0.6321 0.024 0.920 0.056
#> GSM1233074 3 0.5810 0.5134 0.000 0.336 0.664
#> GSM1233076 1 0.6180 0.3603 0.660 0.008 0.332
#> GSM1233080 1 0.9431 0.2994 0.500 0.220 0.280
#> GSM1233088 2 0.6252 -0.1652 0.000 0.556 0.444
#> GSM1233090 3 0.7459 0.3114 0.044 0.372 0.584
#> GSM1233092 1 0.2959 0.6827 0.900 0.100 0.000
#> GSM1233094 1 0.5363 0.5853 0.724 0.276 0.000
#> GSM1233097 1 0.5058 0.6114 0.756 0.244 0.000
#> GSM1233100 1 0.5706 0.5837 0.680 0.320 0.000
#> GSM1233104 1 0.5363 0.5837 0.724 0.276 0.000
#> GSM1233106 2 0.6126 0.1492 0.000 0.600 0.400
#> GSM1233111 2 0.6813 -0.0505 0.012 0.520 0.468
#> GSM1233122 2 0.5366 0.5945 0.208 0.776 0.016
#> GSM1233146 1 0.5560 0.5607 0.700 0.300 0.000
#> GSM1232994 2 0.5285 0.5545 0.244 0.752 0.004
#> GSM1232996 2 0.6283 0.6117 0.176 0.760 0.064
#> GSM1232997 3 0.6126 0.4057 0.000 0.400 0.600
#> GSM1232998 1 0.5178 0.5957 0.744 0.256 0.000
#> GSM1232999 1 0.5835 0.4978 0.660 0.340 0.000
#> GSM1233000 2 0.1781 0.6502 0.020 0.960 0.020
#> GSM1233004 1 0.7248 0.1203 0.536 0.028 0.436
#> GSM1233011 1 0.6763 0.1265 0.552 0.012 0.436
#> GSM1233012 2 0.6308 -0.1291 0.000 0.508 0.492
#> GSM1233023 3 0.6295 0.2268 0.000 0.472 0.528
#> GSM1233027 1 0.5785 0.5158 0.668 0.332 0.000
#> GSM1233033 1 0.7731 0.5493 0.664 0.228 0.108
#> GSM1233036 2 0.6295 -0.0610 0.000 0.528 0.472
#> GSM1233037 2 0.5968 0.1731 0.000 0.636 0.364
#> GSM1233041 1 0.9904 0.2603 0.400 0.316 0.284
#> GSM1233045 1 0.6307 0.3184 0.512 0.488 0.000
#> GSM1233047 3 0.4452 0.6594 0.000 0.192 0.808
#> GSM1233050 3 0.6154 0.3309 0.000 0.408 0.592
#> GSM1233052 2 0.5560 0.1575 0.300 0.700 0.000
#> GSM1233053 2 0.6267 -0.0452 0.000 0.548 0.452
#> GSM1233055 1 0.1163 0.6804 0.972 0.028 0.000
#> GSM1233061 3 0.4702 0.6469 0.000 0.212 0.788
#> GSM1233063 1 0.9968 0.2105 0.368 0.332 0.300
#> GSM1233065 3 0.6244 0.3064 0.000 0.440 0.560
#> GSM1233070 2 0.6518 -0.0490 0.484 0.512 0.004
#> GSM1233077 3 0.2050 0.7040 0.020 0.028 0.952
#> GSM1233081 3 0.0661 0.6992 0.008 0.004 0.988
#> GSM1233084 1 0.9359 0.3061 0.508 0.208 0.284
#> GSM1233087 1 0.1860 0.6838 0.948 0.052 0.000
#> GSM1233089 2 0.8157 0.3498 0.096 0.596 0.308
#> GSM1233099 1 0.5948 0.4674 0.640 0.360 0.000
#> GSM1233112 1 0.6034 0.5790 0.752 0.036 0.212
#> GSM1233085 3 0.1031 0.7051 0.000 0.024 0.976
#> GSM1233098 2 0.6630 0.4492 0.300 0.672 0.028
#> GSM1233114 2 0.7674 -0.0257 0.472 0.484 0.044
#> GSM1233119 1 0.1643 0.6832 0.956 0.044 0.000
#> GSM1233129 3 0.6302 0.2010 0.000 0.480 0.520
#> GSM1233132 1 0.6468 0.3037 0.552 0.444 0.004
#> GSM1233139 2 0.3551 0.5871 0.000 0.868 0.132
#> GSM1233143 2 0.6553 0.3729 0.020 0.656 0.324
#> GSM1233145 1 0.0424 0.6781 0.992 0.008 0.000
#> GSM1233067 3 0.6062 0.4361 0.000 0.384 0.616
#> GSM1233069 3 0.3038 0.7003 0.000 0.104 0.896
#> GSM1233072 2 0.7447 0.5873 0.160 0.700 0.140
#> GSM1233086 3 0.7860 0.4760 0.088 0.284 0.628
#> GSM1233102 1 0.1964 0.6835 0.944 0.056 0.000
#> GSM1233103 2 0.4289 0.6552 0.092 0.868 0.040
#> GSM1233107 2 0.5247 0.5809 0.224 0.768 0.008
#> GSM1233108 3 0.2356 0.6712 0.072 0.000 0.928
#> GSM1233109 3 0.2772 0.6703 0.080 0.004 0.916
#> GSM1233110 3 0.1753 0.7069 0.000 0.048 0.952
#> GSM1233113 3 0.6309 0.1515 0.000 0.496 0.504
#> GSM1233116 3 0.5733 0.5314 0.000 0.324 0.676
#> GSM1233120 1 0.2878 0.6832 0.904 0.096 0.000
#> GSM1233121 3 0.2680 0.7073 0.008 0.068 0.924
#> GSM1233123 3 0.2796 0.7033 0.000 0.092 0.908
#> GSM1233124 3 0.5706 0.5369 0.000 0.320 0.680
#> GSM1233125 3 0.3193 0.6512 0.100 0.004 0.896
#> GSM1233126 1 0.3412 0.6790 0.876 0.124 0.000
#> GSM1233127 2 0.5502 0.5563 0.248 0.744 0.008
#> GSM1233128 3 0.6796 0.2442 0.368 0.020 0.612
#> GSM1233130 3 0.0848 0.7004 0.008 0.008 0.984
#> GSM1233131 1 0.6292 0.6125 0.740 0.216 0.044
#> GSM1233133 3 0.0424 0.7020 0.000 0.008 0.992
#> GSM1233134 3 0.5178 0.6106 0.000 0.256 0.744
#> GSM1233135 3 0.2796 0.7031 0.000 0.092 0.908
#> GSM1233136 3 0.2918 0.6969 0.044 0.032 0.924
#> GSM1233137 3 0.5098 0.6195 0.000 0.248 0.752
#> GSM1233138 1 0.3412 0.6808 0.876 0.124 0.000
#> GSM1233140 3 0.2443 0.6792 0.032 0.028 0.940
#> GSM1233141 2 0.5633 0.5970 0.208 0.768 0.024
#> GSM1233142 2 0.5318 0.5966 0.204 0.780 0.016
#> GSM1233144 3 0.0747 0.7040 0.000 0.016 0.984
#> GSM1233147 1 0.7128 0.5209 0.684 0.064 0.252
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.321 0.70302 0.000 0.876 0.092 0.032
#> GSM1233002 4 0.606 0.63795 0.088 0.232 0.004 0.676
#> GSM1233003 4 0.713 0.02955 0.444 0.024 0.068 0.464
#> GSM1233014 4 0.388 0.69781 0.016 0.172 0.000 0.812
#> GSM1233015 1 0.439 0.59530 0.740 0.252 0.008 0.000
#> GSM1233016 4 0.702 0.23120 0.412 0.092 0.008 0.488
#> GSM1233024 2 0.576 0.51677 0.128 0.712 0.000 0.160
#> GSM1233049 3 0.232 0.72081 0.036 0.000 0.924 0.040
#> GSM1233064 2 0.853 0.35363 0.156 0.504 0.264 0.076
#> GSM1233068 1 0.486 0.49141 0.668 0.324 0.008 0.000
#> GSM1233073 4 0.525 0.63792 0.148 0.100 0.000 0.752
#> GSM1233093 1 0.445 0.51917 0.744 0.000 0.012 0.244
#> GSM1233115 4 0.830 0.23722 0.188 0.036 0.304 0.472
#> GSM1232992 2 0.247 0.67816 0.108 0.892 0.000 0.000
#> GSM1232993 2 0.467 0.59516 0.200 0.764 0.000 0.036
#> GSM1233005 2 0.463 0.50855 0.012 0.740 0.004 0.244
#> GSM1233007 4 0.442 0.67826 0.000 0.160 0.044 0.796
#> GSM1233010 1 0.518 0.52623 0.732 0.056 0.000 0.212
#> GSM1233013 2 0.117 0.70835 0.020 0.968 0.012 0.000
#> GSM1233018 2 0.250 0.71061 0.028 0.924 0.012 0.036
#> GSM1233019 2 0.286 0.66264 0.008 0.880 0.000 0.112
#> GSM1233021 2 0.340 0.68329 0.032 0.864 0.000 0.104
#> GSM1233025 4 0.553 0.26391 0.388 0.004 0.016 0.592
#> GSM1233029 2 0.515 0.43986 0.316 0.664 0.000 0.020
#> GSM1233030 2 0.381 0.61846 0.176 0.812 0.000 0.012
#> GSM1233031 1 0.630 0.39795 0.548 0.388 0.000 0.064
#> GSM1233032 1 0.584 0.21211 0.524 0.032 0.444 0.000
#> GSM1233035 1 0.523 0.57503 0.676 0.296 0.000 0.028
#> GSM1233038 4 0.511 0.39372 0.328 0.016 0.000 0.656
#> GSM1233039 3 0.891 0.14971 0.288 0.256 0.400 0.056
#> GSM1233042 4 0.383 0.69388 0.004 0.204 0.000 0.792
#> GSM1233043 4 0.371 0.69423 0.004 0.192 0.000 0.804
#> GSM1233044 4 0.597 0.68264 0.016 0.148 0.112 0.724
#> GSM1233046 2 0.607 0.45311 0.172 0.684 0.000 0.144
#> GSM1233051 1 0.435 0.59669 0.780 0.000 0.196 0.024
#> GSM1233054 3 0.628 0.00582 0.056 0.468 0.476 0.000
#> GSM1233057 2 0.627 0.48323 0.096 0.632 0.272 0.000
#> GSM1233060 1 0.544 0.38576 0.596 0.384 0.000 0.020
#> GSM1233062 2 0.565 0.50243 0.192 0.712 0.000 0.096
#> GSM1233075 3 0.402 0.65229 0.004 0.224 0.772 0.000
#> GSM1233078 3 0.141 0.75238 0.000 0.020 0.960 0.020
#> GSM1233079 3 0.385 0.59850 0.180 0.000 0.808 0.012
#> GSM1233082 1 0.168 0.68866 0.948 0.044 0.004 0.004
#> GSM1233083 4 0.349 0.62389 0.044 0.000 0.092 0.864
#> GSM1233091 1 0.922 0.12474 0.420 0.284 0.184 0.112
#> GSM1233095 4 0.730 0.32379 0.220 0.000 0.244 0.536
#> GSM1233096 1 0.247 0.69732 0.900 0.096 0.004 0.000
#> GSM1233101 3 0.603 0.04306 0.032 0.004 0.496 0.468
#> GSM1233105 1 0.514 0.54391 0.744 0.064 0.000 0.192
#> GSM1233117 2 0.298 0.70955 0.000 0.892 0.068 0.040
#> GSM1233118 2 0.597 0.11476 0.000 0.532 0.428 0.040
#> GSM1233001 2 0.508 0.55551 0.036 0.716 0.248 0.000
#> GSM1233006 4 0.510 0.51588 0.008 0.380 0.000 0.612
#> GSM1233008 2 0.112 0.71064 0.000 0.964 0.036 0.000
#> GSM1233009 2 0.393 0.60425 0.196 0.796 0.004 0.004
#> GSM1233017 2 0.203 0.68767 0.036 0.936 0.000 0.028
#> GSM1233020 2 0.422 0.68434 0.000 0.824 0.104 0.072
#> GSM1233022 2 0.683 0.23554 0.144 0.584 0.000 0.272
#> GSM1233026 1 0.437 0.64708 0.808 0.148 0.004 0.040
#> GSM1233028 2 0.444 0.60353 0.060 0.804 0.000 0.136
#> GSM1233034 2 0.463 0.51223 0.268 0.720 0.012 0.000
#> GSM1233040 1 0.362 0.69479 0.860 0.064 0.076 0.000
#> GSM1233048 1 0.354 0.67268 0.828 0.164 0.000 0.008
#> GSM1233056 4 0.370 0.63768 0.064 0.012 0.056 0.868
#> GSM1233058 4 0.386 0.68593 0.004 0.176 0.008 0.812
#> GSM1233059 1 0.205 0.69483 0.928 0.064 0.008 0.000
#> GSM1233066 3 0.305 0.74280 0.000 0.108 0.876 0.016
#> GSM1233071 2 0.524 0.29182 0.356 0.628 0.000 0.016
#> GSM1233074 3 0.503 0.33865 0.004 0.400 0.596 0.000
#> GSM1233076 4 0.560 0.49531 0.008 0.040 0.264 0.688
#> GSM1233080 1 0.591 0.54531 0.700 0.000 0.148 0.152
#> GSM1233088 1 0.790 0.02461 0.372 0.304 0.324 0.000
#> GSM1233090 1 0.384 0.63655 0.816 0.016 0.168 0.000
#> GSM1233092 4 0.241 0.69933 0.000 0.104 0.000 0.896
#> GSM1233094 4 0.483 0.66866 0.032 0.228 0.000 0.740
#> GSM1233097 4 0.469 0.64647 0.004 0.288 0.004 0.704
#> GSM1233100 4 0.642 0.57128 0.216 0.140 0.000 0.644
#> GSM1233104 4 0.481 0.62659 0.008 0.316 0.000 0.676
#> GSM1233106 1 0.340 0.69727 0.864 0.104 0.032 0.000
#> GSM1233111 1 0.272 0.69860 0.904 0.064 0.032 0.000
#> GSM1233122 2 0.233 0.69605 0.000 0.916 0.012 0.072
#> GSM1233146 4 0.703 0.47294 0.132 0.348 0.000 0.520
#> GSM1232994 2 0.289 0.67321 0.036 0.896 0.000 0.068
#> GSM1232996 2 0.378 0.65443 0.004 0.832 0.016 0.148
#> GSM1232997 2 0.528 0.02808 0.000 0.524 0.468 0.008
#> GSM1232998 4 0.461 0.63927 0.000 0.304 0.004 0.692
#> GSM1232999 4 0.489 0.48151 0.000 0.412 0.000 0.588
#> GSM1233000 2 0.327 0.66001 0.132 0.856 0.000 0.012
#> GSM1233004 4 0.647 0.45592 0.004 0.096 0.276 0.624
#> GSM1233011 4 0.603 0.43520 0.020 0.036 0.292 0.652
#> GSM1233012 2 0.484 0.49127 0.012 0.688 0.300 0.000
#> GSM1233023 2 0.496 0.50489 0.020 0.696 0.284 0.000
#> GSM1233027 4 0.478 0.55015 0.000 0.376 0.000 0.624
#> GSM1233033 1 0.406 0.57352 0.808 0.016 0.004 0.172
#> GSM1233036 2 0.446 0.60555 0.024 0.768 0.208 0.000
#> GSM1233037 2 0.647 0.53834 0.164 0.644 0.192 0.000
#> GSM1233041 1 0.232 0.65863 0.924 0.000 0.036 0.040
#> GSM1233045 4 0.613 0.54672 0.056 0.328 0.004 0.612
#> GSM1233047 3 0.340 0.71469 0.008 0.152 0.840 0.000
#> GSM1233050 1 0.633 0.56623 0.656 0.144 0.200 0.000
#> GSM1233052 1 0.579 0.54036 0.656 0.284 0.000 0.060
#> GSM1233053 2 0.676 0.30180 0.108 0.548 0.344 0.000
#> GSM1233055 4 0.200 0.65679 0.044 0.000 0.020 0.936
#> GSM1233061 3 0.398 0.65569 0.004 0.220 0.776 0.000
#> GSM1233063 1 0.149 0.67015 0.956 0.000 0.032 0.012
#> GSM1233065 2 0.609 0.32486 0.000 0.596 0.344 0.060
#> GSM1233070 2 0.557 -0.19401 0.012 0.516 0.004 0.468
#> GSM1233077 3 0.281 0.73753 0.000 0.024 0.896 0.080
#> GSM1233081 3 0.112 0.74342 0.012 0.004 0.972 0.012
#> GSM1233084 1 0.639 0.47853 0.648 0.000 0.140 0.212
#> GSM1233087 4 0.111 0.66923 0.016 0.004 0.008 0.972
#> GSM1233089 2 0.661 0.45104 0.000 0.620 0.144 0.236
#> GSM1233099 4 0.537 0.44570 0.012 0.444 0.000 0.544
#> GSM1233112 4 0.492 0.57585 0.000 0.036 0.228 0.736
#> GSM1233085 3 0.209 0.75358 0.020 0.048 0.932 0.000
#> GSM1233098 4 0.812 0.04738 0.084 0.408 0.072 0.436
#> GSM1233114 1 0.734 0.27424 0.460 0.380 0.000 0.160
#> GSM1233119 4 0.556 0.67517 0.124 0.132 0.004 0.740
#> GSM1233129 2 0.472 0.44457 0.000 0.672 0.324 0.004
#> GSM1233132 1 0.772 0.23675 0.408 0.364 0.000 0.228
#> GSM1233139 2 0.331 0.68302 0.092 0.872 0.036 0.000
#> GSM1233143 2 0.317 0.66983 0.000 0.840 0.160 0.000
#> GSM1233145 4 0.391 0.64935 0.104 0.040 0.008 0.848
#> GSM1233067 3 0.516 0.10387 0.000 0.476 0.520 0.004
#> GSM1233069 3 0.202 0.75910 0.000 0.056 0.932 0.012
#> GSM1233072 2 0.337 0.69059 0.000 0.872 0.048 0.080
#> GSM1233086 3 0.616 0.50261 0.000 0.092 0.644 0.264
#> GSM1233102 4 0.346 0.68251 0.056 0.076 0.000 0.868
#> GSM1233103 1 0.538 0.30517 0.536 0.452 0.000 0.012
#> GSM1233107 2 0.340 0.65725 0.068 0.872 0.000 0.060
#> GSM1233108 3 0.259 0.70990 0.044 0.000 0.912 0.044
#> GSM1233109 3 0.245 0.71273 0.016 0.000 0.912 0.072
#> GSM1233110 3 0.156 0.75785 0.000 0.056 0.944 0.000
#> GSM1233113 2 0.495 0.40004 0.000 0.648 0.344 0.008
#> GSM1233116 3 0.564 0.48337 0.000 0.324 0.636 0.040
#> GSM1233120 4 0.291 0.69506 0.020 0.092 0.000 0.888
#> GSM1233121 3 0.281 0.73965 0.000 0.024 0.896 0.080
#> GSM1233123 3 0.190 0.75707 0.004 0.064 0.932 0.000
#> GSM1233124 3 0.519 0.40210 0.000 0.372 0.616 0.012
#> GSM1233125 3 0.365 0.65908 0.108 0.000 0.852 0.040
#> GSM1233126 4 0.425 0.68600 0.064 0.116 0.000 0.820
#> GSM1233127 2 0.261 0.67392 0.012 0.900 0.000 0.088
#> GSM1233128 3 0.760 -0.05744 0.380 0.000 0.420 0.200
#> GSM1233130 3 0.115 0.74751 0.000 0.008 0.968 0.024
#> GSM1233131 1 0.520 0.58584 0.752 0.088 0.000 0.160
#> GSM1233133 3 0.183 0.74944 0.024 0.032 0.944 0.000
#> GSM1233134 3 0.472 0.54654 0.008 0.300 0.692 0.000
#> GSM1233135 3 0.179 0.75761 0.000 0.068 0.932 0.000
#> GSM1233136 3 0.415 0.68345 0.000 0.032 0.808 0.160
#> GSM1233137 3 0.412 0.65383 0.008 0.220 0.772 0.000
#> GSM1233138 4 0.553 0.65174 0.136 0.132 0.000 0.732
#> GSM1233140 3 0.474 0.38370 0.328 0.000 0.668 0.004
#> GSM1233141 2 0.139 0.70841 0.000 0.960 0.012 0.028
#> GSM1233142 2 0.149 0.69813 0.012 0.956 0.000 0.032
#> GSM1233144 3 0.131 0.75611 0.004 0.036 0.960 0.000
#> GSM1233147 4 0.487 0.53655 0.000 0.028 0.244 0.728
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.2054 0.7191 0.000 0.916 0.072 0.008 0.004
#> GSM1233002 4 0.4221 0.6704 0.112 0.108 0.000 0.780 0.000
#> GSM1233003 5 0.3241 0.6248 0.104 0.000 0.028 0.012 0.856
#> GSM1233014 5 0.3953 0.6731 0.000 0.148 0.000 0.060 0.792
#> GSM1233015 1 0.2424 0.6967 0.868 0.132 0.000 0.000 0.000
#> GSM1233016 5 0.1547 0.6969 0.016 0.032 0.004 0.000 0.948
#> GSM1233024 2 0.4683 0.3131 0.012 0.624 0.000 0.008 0.356
#> GSM1233049 3 0.2506 0.7585 0.036 0.000 0.904 0.008 0.052
#> GSM1233064 4 0.7137 0.3254 0.216 0.296 0.028 0.460 0.000
#> GSM1233068 1 0.3051 0.6964 0.852 0.120 0.000 0.028 0.000
#> GSM1233073 5 0.3780 0.6581 0.000 0.060 0.000 0.132 0.808
#> GSM1233093 1 0.3948 0.6243 0.768 0.012 0.000 0.208 0.012
#> GSM1233115 4 0.2264 0.7030 0.060 0.004 0.024 0.912 0.000
#> GSM1232992 2 0.2550 0.7089 0.084 0.892 0.004 0.020 0.000
#> GSM1232993 2 0.4477 0.5491 0.252 0.708 0.000 0.040 0.000
#> GSM1233005 4 0.4696 0.3807 0.012 0.400 0.000 0.584 0.004
#> GSM1233007 4 0.1267 0.7117 0.000 0.024 0.004 0.960 0.012
#> GSM1233010 1 0.4560 0.6511 0.784 0.016 0.004 0.092 0.104
#> GSM1233013 2 0.0968 0.7214 0.012 0.972 0.012 0.004 0.000
#> GSM1233018 2 0.3844 0.6570 0.064 0.804 0.000 0.132 0.000
#> GSM1233019 2 0.2358 0.6731 0.000 0.888 0.000 0.008 0.104
#> GSM1233021 2 0.4693 0.5228 0.056 0.700 0.000 0.244 0.000
#> GSM1233025 5 0.2804 0.6745 0.048 0.000 0.008 0.056 0.888
#> GSM1233029 2 0.4904 0.0829 0.472 0.504 0.000 0.024 0.000
#> GSM1233030 2 0.2172 0.7171 0.060 0.916 0.004 0.000 0.020
#> GSM1233031 1 0.5801 0.3116 0.532 0.380 0.000 0.004 0.084
#> GSM1233032 1 0.4977 0.1408 0.532 0.008 0.444 0.000 0.016
#> GSM1233035 5 0.6923 0.1405 0.284 0.340 0.004 0.000 0.372
#> GSM1233038 5 0.2938 0.6448 0.084 0.000 0.008 0.032 0.876
#> GSM1233039 1 0.7254 0.0264 0.400 0.164 0.044 0.392 0.000
#> GSM1233042 4 0.5475 0.5407 0.000 0.124 0.000 0.644 0.232
#> GSM1233043 4 0.5673 0.5049 0.000 0.132 0.000 0.616 0.252
#> GSM1233044 5 0.6646 0.5359 0.000 0.120 0.180 0.084 0.616
#> GSM1233046 2 0.4937 0.1241 0.028 0.544 0.000 0.000 0.428
#> GSM1233051 1 0.6062 0.5042 0.632 0.000 0.160 0.020 0.188
#> GSM1233054 2 0.7014 0.2188 0.252 0.420 0.316 0.012 0.000
#> GSM1233057 2 0.4677 0.6691 0.104 0.756 0.132 0.008 0.000
#> GSM1233060 1 0.4382 0.5445 0.700 0.276 0.000 0.020 0.004
#> GSM1233062 2 0.4354 0.6092 0.068 0.768 0.000 0.004 0.160
#> GSM1233075 3 0.3003 0.7391 0.000 0.188 0.812 0.000 0.000
#> GSM1233078 3 0.0798 0.8077 0.000 0.008 0.976 0.016 0.000
#> GSM1233079 3 0.3898 0.6495 0.160 0.000 0.800 0.024 0.016
#> GSM1233082 1 0.0807 0.7114 0.976 0.012 0.000 0.000 0.012
#> GSM1233083 4 0.4436 0.5930 0.008 0.000 0.068 0.768 0.156
#> GSM1233091 1 0.5697 0.1944 0.512 0.084 0.000 0.404 0.000
#> GSM1233095 4 0.3619 0.6572 0.124 0.000 0.040 0.828 0.008
#> GSM1233096 1 0.1386 0.7134 0.952 0.032 0.000 0.000 0.016
#> GSM1233101 4 0.2234 0.7004 0.016 0.004 0.060 0.916 0.004
#> GSM1233105 5 0.2756 0.6612 0.092 0.024 0.004 0.000 0.880
#> GSM1233117 2 0.3567 0.6885 0.000 0.832 0.112 0.004 0.052
#> GSM1233118 3 0.4747 0.0594 0.000 0.484 0.500 0.016 0.000
#> GSM1233001 2 0.4115 0.6792 0.036 0.796 0.148 0.020 0.000
#> GSM1233006 5 0.5294 0.3831 0.000 0.380 0.000 0.056 0.564
#> GSM1233008 2 0.1186 0.7214 0.008 0.964 0.020 0.008 0.000
#> GSM1233009 2 0.2773 0.6654 0.164 0.836 0.000 0.000 0.000
#> GSM1233017 2 0.2249 0.6842 0.008 0.896 0.000 0.000 0.096
#> GSM1233020 2 0.3372 0.6747 0.000 0.840 0.036 0.120 0.004
#> GSM1233022 5 0.3611 0.6614 0.004 0.208 0.000 0.008 0.780
#> GSM1233026 1 0.6046 0.5548 0.652 0.032 0.004 0.208 0.104
#> GSM1233028 2 0.5060 0.5421 0.104 0.692 0.000 0.204 0.000
#> GSM1233034 2 0.4527 0.3322 0.392 0.596 0.000 0.012 0.000
#> GSM1233040 1 0.2104 0.7047 0.924 0.024 0.008 0.000 0.044
#> GSM1233048 1 0.2408 0.7070 0.892 0.092 0.000 0.016 0.000
#> GSM1233056 5 0.5411 0.2284 0.008 0.000 0.044 0.396 0.552
#> GSM1233058 4 0.1757 0.7154 0.012 0.048 0.000 0.936 0.004
#> GSM1233059 1 0.0566 0.7122 0.984 0.012 0.000 0.004 0.000
#> GSM1233066 3 0.2339 0.8013 0.000 0.100 0.892 0.004 0.004
#> GSM1233071 2 0.4888 0.6053 0.188 0.720 0.004 0.000 0.088
#> GSM1233074 3 0.4045 0.4763 0.000 0.356 0.644 0.000 0.000
#> GSM1233076 4 0.2193 0.6942 0.000 0.000 0.060 0.912 0.028
#> GSM1233080 1 0.5260 0.6196 0.736 0.000 0.052 0.136 0.076
#> GSM1233088 1 0.5154 0.5673 0.696 0.224 0.064 0.016 0.000
#> GSM1233090 1 0.0833 0.7092 0.976 0.000 0.016 0.004 0.004
#> GSM1233092 5 0.5770 0.2694 0.000 0.096 0.000 0.372 0.532
#> GSM1233094 5 0.5048 0.6182 0.000 0.152 0.000 0.144 0.704
#> GSM1233097 4 0.2237 0.7133 0.004 0.084 0.000 0.904 0.008
#> GSM1233100 1 0.6798 0.1258 0.460 0.116 0.000 0.388 0.036
#> GSM1233104 4 0.5240 0.5815 0.000 0.216 0.000 0.672 0.112
#> GSM1233106 1 0.1579 0.7120 0.944 0.032 0.000 0.000 0.024
#> GSM1233111 1 0.1914 0.6959 0.928 0.008 0.008 0.000 0.056
#> GSM1233122 2 0.2700 0.6882 0.000 0.884 0.024 0.004 0.088
#> GSM1233146 5 0.6619 0.3519 0.004 0.320 0.000 0.204 0.472
#> GSM1232994 2 0.2515 0.6961 0.020 0.908 0.000 0.032 0.040
#> GSM1232996 2 0.4347 0.3526 0.004 0.636 0.000 0.356 0.004
#> GSM1232997 2 0.5455 0.2295 0.012 0.548 0.400 0.040 0.000
#> GSM1232998 4 0.4926 0.6166 0.000 0.152 0.000 0.716 0.132
#> GSM1232999 4 0.4163 0.6611 0.000 0.228 0.000 0.740 0.032
#> GSM1233000 2 0.2669 0.6967 0.104 0.876 0.000 0.020 0.000
#> GSM1233004 4 0.1442 0.7063 0.000 0.004 0.032 0.952 0.012
#> GSM1233011 4 0.5455 0.5364 0.000 0.008 0.176 0.680 0.136
#> GSM1233012 2 0.4235 0.4386 0.000 0.656 0.336 0.000 0.008
#> GSM1233023 2 0.4365 0.6647 0.024 0.776 0.164 0.036 0.000
#> GSM1233027 4 0.5683 0.5206 0.000 0.304 0.000 0.588 0.108
#> GSM1233033 5 0.3530 0.5347 0.204 0.000 0.012 0.000 0.784
#> GSM1233036 2 0.4335 0.6165 0.036 0.740 0.220 0.004 0.000
#> GSM1233037 2 0.4503 0.6742 0.120 0.756 0.124 0.000 0.000
#> GSM1233041 1 0.4430 0.5499 0.720 0.000 0.032 0.004 0.244
#> GSM1233045 4 0.3527 0.6985 0.056 0.116 0.000 0.828 0.000
#> GSM1233047 3 0.2439 0.7899 0.004 0.120 0.876 0.000 0.000
#> GSM1233050 1 0.2625 0.7066 0.876 0.108 0.000 0.016 0.000
#> GSM1233052 1 0.3849 0.6756 0.808 0.112 0.000 0.080 0.000
#> GSM1233053 2 0.6993 0.2464 0.248 0.428 0.312 0.012 0.000
#> GSM1233055 4 0.3351 0.6449 0.020 0.000 0.004 0.828 0.148
#> GSM1233061 3 0.2852 0.7540 0.000 0.172 0.828 0.000 0.000
#> GSM1233063 1 0.4957 0.4926 0.664 0.000 0.040 0.008 0.288
#> GSM1233065 2 0.5892 -0.0316 0.016 0.472 0.060 0.452 0.000
#> GSM1233070 4 0.6215 0.1488 0.048 0.452 0.000 0.456 0.044
#> GSM1233077 3 0.2674 0.7630 0.000 0.012 0.868 0.120 0.000
#> GSM1233081 3 0.0880 0.8002 0.000 0.000 0.968 0.032 0.000
#> GSM1233084 1 0.6931 0.3358 0.512 0.000 0.148 0.040 0.300
#> GSM1233087 4 0.2088 0.6949 0.004 0.004 0.004 0.916 0.072
#> GSM1233089 2 0.6211 0.4250 0.000 0.592 0.080 0.288 0.040
#> GSM1233099 4 0.5238 0.4362 0.012 0.396 0.000 0.564 0.028
#> GSM1233112 5 0.6248 0.4618 0.000 0.024 0.256 0.124 0.596
#> GSM1233085 3 0.0963 0.8138 0.000 0.036 0.964 0.000 0.000
#> GSM1233098 4 0.5446 0.6120 0.068 0.236 0.016 0.676 0.004
#> GSM1233114 5 0.4064 0.6579 0.024 0.216 0.004 0.000 0.756
#> GSM1233119 5 0.4728 0.5534 0.000 0.060 0.000 0.240 0.700
#> GSM1233129 2 0.3906 0.5200 0.000 0.704 0.292 0.004 0.000
#> GSM1233132 5 0.6124 0.4868 0.200 0.236 0.000 0.000 0.564
#> GSM1233139 2 0.2595 0.7132 0.080 0.888 0.032 0.000 0.000
#> GSM1233143 2 0.4496 0.6495 0.000 0.752 0.156 0.000 0.092
#> GSM1233145 5 0.2393 0.6838 0.004 0.016 0.000 0.080 0.900
#> GSM1233067 3 0.4350 0.3361 0.000 0.408 0.588 0.000 0.004
#> GSM1233069 3 0.1484 0.8152 0.000 0.048 0.944 0.008 0.000
#> GSM1233072 2 0.4087 0.6207 0.000 0.784 0.040 0.008 0.168
#> GSM1233086 4 0.4636 0.4786 0.000 0.024 0.308 0.664 0.004
#> GSM1233102 5 0.3201 0.6797 0.000 0.052 0.000 0.096 0.852
#> GSM1233103 1 0.4151 0.4433 0.652 0.344 0.000 0.000 0.004
#> GSM1233107 2 0.4126 0.2614 0.000 0.620 0.000 0.000 0.380
#> GSM1233108 3 0.2409 0.7702 0.012 0.000 0.908 0.060 0.020
#> GSM1233109 3 0.1877 0.7782 0.000 0.000 0.924 0.064 0.012
#> GSM1233110 3 0.1205 0.8144 0.000 0.040 0.956 0.004 0.000
#> GSM1233113 2 0.4066 0.4655 0.000 0.672 0.324 0.000 0.004
#> GSM1233116 3 0.5595 0.5440 0.000 0.276 0.632 0.080 0.012
#> GSM1233120 4 0.5131 0.3056 0.000 0.048 0.000 0.588 0.364
#> GSM1233121 3 0.2674 0.7628 0.000 0.012 0.868 0.120 0.000
#> GSM1233123 3 0.1502 0.8133 0.000 0.056 0.940 0.004 0.000
#> GSM1233124 3 0.3895 0.5504 0.000 0.320 0.680 0.000 0.000
#> GSM1233125 3 0.3584 0.7183 0.060 0.000 0.852 0.032 0.056
#> GSM1233126 5 0.2653 0.6975 0.000 0.096 0.000 0.024 0.880
#> GSM1233127 2 0.3809 0.5188 0.000 0.736 0.000 0.008 0.256
#> GSM1233128 5 0.7599 0.0913 0.184 0.000 0.372 0.064 0.380
#> GSM1233130 3 0.1041 0.8017 0.000 0.004 0.964 0.032 0.000
#> GSM1233131 1 0.5396 0.1929 0.532 0.048 0.004 0.000 0.416
#> GSM1233133 3 0.0510 0.8102 0.000 0.016 0.984 0.000 0.000
#> GSM1233134 3 0.3177 0.7177 0.000 0.208 0.792 0.000 0.000
#> GSM1233135 3 0.1991 0.8090 0.000 0.076 0.916 0.004 0.004
#> GSM1233136 3 0.4680 0.1392 0.000 0.008 0.540 0.448 0.004
#> GSM1233137 3 0.2773 0.7606 0.000 0.164 0.836 0.000 0.000
#> GSM1233138 5 0.2540 0.7001 0.000 0.088 0.000 0.024 0.888
#> GSM1233140 3 0.5087 0.5349 0.152 0.000 0.700 0.000 0.148
#> GSM1233141 2 0.2708 0.6922 0.000 0.892 0.016 0.020 0.072
#> GSM1233142 2 0.1282 0.7057 0.000 0.952 0.000 0.004 0.044
#> GSM1233144 3 0.0609 0.8110 0.000 0.020 0.980 0.000 0.000
#> GSM1233147 4 0.2459 0.6972 0.000 0.004 0.052 0.904 0.040
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.3409 0.62699 0.004 0.844 0.076 0.004 0.016 0.056
#> GSM1233002 6 0.4811 0.50501 0.180 0.120 0.000 0.004 0.004 0.692
#> GSM1233003 4 0.4316 0.32177 0.012 0.000 0.004 0.628 0.348 0.008
#> GSM1233014 4 0.4725 0.56686 0.000 0.104 0.000 0.732 0.128 0.036
#> GSM1233015 1 0.3268 0.54406 0.824 0.076 0.000 0.000 0.100 0.000
#> GSM1233016 4 0.4011 0.43671 0.000 0.024 0.000 0.672 0.304 0.000
#> GSM1233024 2 0.4959 0.46141 0.020 0.664 0.000 0.240 0.076 0.000
#> GSM1233049 3 0.5441 0.56338 0.080 0.012 0.720 0.120 0.028 0.040
#> GSM1233064 6 0.6160 0.31521 0.172 0.240 0.040 0.000 0.000 0.548
#> GSM1233068 1 0.2999 0.57477 0.860 0.084 0.000 0.000 0.024 0.032
#> GSM1233073 4 0.1794 0.60628 0.024 0.008 0.000 0.936 0.020 0.012
#> GSM1233093 1 0.5271 0.42603 0.680 0.000 0.004 0.052 0.072 0.192
#> GSM1233115 6 0.4016 0.55595 0.044 0.012 0.008 0.012 0.124 0.800
#> GSM1232992 2 0.4617 0.53666 0.104 0.716 0.012 0.000 0.000 0.168
#> GSM1232993 1 0.6087 0.06680 0.448 0.436 0.000 0.028 0.028 0.060
#> GSM1233005 6 0.5742 0.27620 0.028 0.364 0.000 0.000 0.092 0.516
#> GSM1233007 6 0.2603 0.57005 0.016 0.064 0.020 0.004 0.004 0.892
#> GSM1233010 5 0.4082 0.39508 0.204 0.008 0.000 0.000 0.740 0.048
#> GSM1233013 2 0.2614 0.62224 0.060 0.884 0.012 0.000 0.000 0.044
#> GSM1233018 2 0.4427 0.48725 0.048 0.716 0.004 0.000 0.012 0.220
#> GSM1233019 2 0.3518 0.62493 0.016 0.824 0.000 0.112 0.004 0.044
#> GSM1233021 2 0.5687 0.21549 0.052 0.548 0.000 0.000 0.060 0.340
#> GSM1233025 5 0.5242 0.21836 0.012 0.000 0.004 0.284 0.616 0.084
#> GSM1233029 1 0.5344 0.23901 0.520 0.400 0.000 0.000 0.024 0.056
#> GSM1233030 2 0.2611 0.62459 0.092 0.880 0.004 0.012 0.008 0.004
#> GSM1233031 5 0.6805 0.01389 0.252 0.328 0.000 0.028 0.384 0.008
#> GSM1233032 3 0.6141 -0.01222 0.292 0.008 0.456 0.000 0.244 0.000
#> GSM1233035 2 0.7560 -0.04754 0.176 0.388 0.004 0.192 0.240 0.000
#> GSM1233038 4 0.4572 0.12472 0.012 0.000 0.000 0.512 0.460 0.016
#> GSM1233039 6 0.5494 0.38452 0.244 0.084 0.016 0.000 0.020 0.636
#> GSM1233042 4 0.6395 0.29129 0.068 0.048 0.000 0.536 0.036 0.312
#> GSM1233043 4 0.6219 0.30644 0.044 0.064 0.000 0.552 0.032 0.308
#> GSM1233044 5 0.7174 0.23812 0.000 0.112 0.096 0.096 0.564 0.132
#> GSM1233046 4 0.5530 0.00785 0.028 0.444 0.004 0.472 0.052 0.000
#> GSM1233051 1 0.6324 -0.08106 0.440 0.000 0.064 0.004 0.408 0.084
#> GSM1233054 3 0.6379 0.28193 0.288 0.232 0.460 0.000 0.016 0.004
#> GSM1233057 2 0.4948 0.56278 0.124 0.700 0.156 0.000 0.004 0.016
#> GSM1233060 1 0.3879 0.52420 0.748 0.220 0.000 0.012 0.012 0.008
#> GSM1233062 2 0.5542 0.46356 0.064 0.648 0.000 0.068 0.216 0.004
#> GSM1233075 3 0.3387 0.68140 0.000 0.164 0.796 0.000 0.000 0.040
#> GSM1233078 3 0.2076 0.69665 0.016 0.000 0.912 0.000 0.012 0.060
#> GSM1233079 3 0.5450 0.44444 0.228 0.000 0.640 0.000 0.084 0.048
#> GSM1233082 1 0.3711 0.38869 0.720 0.020 0.000 0.000 0.260 0.000
#> GSM1233083 6 0.6176 0.14128 0.020 0.000 0.036 0.300 0.092 0.552
#> GSM1233091 1 0.5726 0.35496 0.600 0.072 0.004 0.000 0.052 0.272
#> GSM1233095 6 0.7621 0.36266 0.216 0.000 0.048 0.088 0.192 0.456
#> GSM1233096 1 0.3455 0.47996 0.784 0.036 0.000 0.000 0.180 0.000
#> GSM1233101 6 0.7739 0.44549 0.128 0.016 0.064 0.072 0.236 0.484
#> GSM1233105 4 0.4690 0.46145 0.056 0.032 0.000 0.708 0.204 0.000
#> GSM1233117 2 0.3784 0.62111 0.000 0.812 0.120 0.032 0.020 0.016
#> GSM1233118 3 0.4510 0.37599 0.000 0.380 0.588 0.000 0.008 0.024
#> GSM1233001 2 0.5848 0.46450 0.036 0.600 0.124 0.000 0.004 0.236
#> GSM1233006 4 0.5488 0.45260 0.004 0.176 0.000 0.604 0.004 0.212
#> GSM1233008 2 0.2808 0.62879 0.012 0.880 0.008 0.000 0.056 0.044
#> GSM1233009 2 0.3493 0.57206 0.136 0.800 0.000 0.000 0.064 0.000
#> GSM1233017 2 0.2767 0.61981 0.004 0.868 0.000 0.072 0.056 0.000
#> GSM1233020 2 0.5062 0.40126 0.012 0.600 0.068 0.000 0.000 0.320
#> GSM1233022 4 0.5547 0.27479 0.000 0.344 0.000 0.508 0.148 0.000
#> GSM1233026 5 0.3695 0.41863 0.176 0.004 0.000 0.000 0.776 0.044
#> GSM1233028 2 0.6699 0.03624 0.044 0.420 0.000 0.000 0.312 0.224
#> GSM1233034 1 0.5552 0.01975 0.452 0.436 0.000 0.000 0.008 0.104
#> GSM1233040 1 0.4719 0.10635 0.564 0.016 0.024 0.000 0.396 0.000
#> GSM1233048 1 0.2131 0.57069 0.916 0.048 0.004 0.004 0.004 0.024
#> GSM1233056 4 0.4630 0.52622 0.076 0.000 0.020 0.772 0.052 0.080
#> GSM1233058 6 0.5309 0.51981 0.016 0.052 0.000 0.016 0.308 0.608
#> GSM1233059 1 0.2651 0.52638 0.860 0.028 0.000 0.000 0.112 0.000
#> GSM1233066 3 0.5158 0.64545 0.000 0.144 0.700 0.000 0.064 0.092
#> GSM1233071 2 0.5618 0.37728 0.276 0.604 0.004 0.076 0.040 0.000
#> GSM1233074 3 0.4092 0.45720 0.000 0.344 0.636 0.000 0.000 0.020
#> GSM1233076 6 0.3026 0.53510 0.004 0.000 0.036 0.020 0.076 0.864
#> GSM1233080 1 0.6346 0.36605 0.636 0.000 0.044 0.096 0.092 0.132
#> GSM1233088 1 0.5934 0.43768 0.604 0.132 0.036 0.000 0.008 0.220
#> GSM1233090 1 0.3788 0.50981 0.828 0.000 0.040 0.036 0.076 0.020
#> GSM1233092 4 0.4475 0.54649 0.000 0.032 0.000 0.708 0.032 0.228
#> GSM1233094 4 0.3064 0.60538 0.004 0.068 0.000 0.860 0.056 0.012
#> GSM1233097 6 0.6133 0.51730 0.044 0.052 0.000 0.040 0.292 0.572
#> GSM1233100 1 0.7604 0.20807 0.500 0.048 0.004 0.128 0.144 0.176
#> GSM1233104 6 0.6974 0.43414 0.012 0.152 0.000 0.072 0.308 0.456
#> GSM1233106 1 0.3440 0.46500 0.776 0.028 0.000 0.000 0.196 0.000
#> GSM1233111 1 0.3820 0.25476 0.660 0.004 0.004 0.000 0.332 0.000
#> GSM1233122 2 0.5593 0.52335 0.012 0.648 0.040 0.084 0.000 0.216
#> GSM1233146 2 0.7961 -0.03721 0.028 0.332 0.000 0.268 0.128 0.244
#> GSM1232994 2 0.3585 0.62680 0.032 0.844 0.000 0.048 0.052 0.024
#> GSM1232996 2 0.5807 -0.11772 0.012 0.456 0.000 0.000 0.128 0.404
#> GSM1232997 2 0.6071 0.37550 0.012 0.524 0.252 0.000 0.004 0.208
#> GSM1232998 6 0.6050 0.51874 0.000 0.132 0.000 0.044 0.268 0.556
#> GSM1232999 6 0.5603 0.53068 0.004 0.168 0.000 0.004 0.244 0.580
#> GSM1233000 2 0.3737 0.56216 0.168 0.780 0.000 0.000 0.008 0.044
#> GSM1233004 6 0.4063 0.53452 0.004 0.012 0.008 0.004 0.260 0.712
#> GSM1233011 5 0.5453 -0.26867 0.000 0.012 0.048 0.016 0.488 0.436
#> GSM1233012 2 0.4151 0.18422 0.000 0.576 0.412 0.004 0.008 0.000
#> GSM1233023 2 0.5691 0.45963 0.032 0.600 0.124 0.000 0.000 0.244
#> GSM1233027 6 0.4769 0.46965 0.008 0.248 0.000 0.028 0.032 0.684
#> GSM1233033 5 0.5469 0.26412 0.144 0.000 0.000 0.324 0.532 0.000
#> GSM1233036 2 0.5953 0.46880 0.024 0.588 0.220 0.000 0.160 0.008
#> GSM1233037 2 0.5126 0.52672 0.196 0.668 0.120 0.000 0.004 0.012
#> GSM1233041 5 0.4730 0.07997 0.468 0.000 0.016 0.020 0.496 0.000
#> GSM1233045 6 0.5749 0.54756 0.052 0.064 0.000 0.012 0.256 0.616
#> GSM1233047 3 0.2068 0.71070 0.008 0.080 0.904 0.000 0.008 0.000
#> GSM1233050 1 0.2796 0.57359 0.872 0.068 0.000 0.000 0.048 0.012
#> GSM1233052 1 0.3889 0.55566 0.816 0.080 0.000 0.008 0.040 0.056
#> GSM1233053 3 0.6429 0.36314 0.276 0.204 0.488 0.000 0.028 0.004
#> GSM1233055 6 0.7092 0.37184 0.108 0.004 0.008 0.192 0.180 0.508
#> GSM1233061 3 0.3102 0.69369 0.000 0.156 0.816 0.000 0.000 0.028
#> GSM1233063 5 0.4634 0.24699 0.376 0.000 0.008 0.024 0.588 0.004
#> GSM1233065 6 0.6192 0.26362 0.024 0.356 0.028 0.000 0.084 0.508
#> GSM1233070 6 0.5689 0.07819 0.060 0.380 0.004 0.028 0.004 0.524
#> GSM1233077 3 0.4379 0.48960 0.000 0.008 0.632 0.000 0.024 0.336
#> GSM1233081 3 0.1976 0.69513 0.024 0.008 0.928 0.000 0.020 0.020
#> GSM1233084 5 0.7236 0.11921 0.388 0.000 0.056 0.096 0.396 0.064
#> GSM1233087 6 0.4722 0.51868 0.020 0.000 0.000 0.104 0.160 0.716
#> GSM1233089 2 0.5644 0.22246 0.008 0.472 0.080 0.012 0.000 0.428
#> GSM1233099 2 0.8586 -0.18749 0.132 0.288 0.000 0.104 0.276 0.200
#> GSM1233112 4 0.4805 0.51654 0.024 0.004 0.036 0.716 0.016 0.204
#> GSM1233085 3 0.1777 0.70228 0.012 0.032 0.932 0.000 0.024 0.000
#> GSM1233098 6 0.6132 0.30418 0.092 0.260 0.060 0.004 0.004 0.580
#> GSM1233114 5 0.6167 -0.05404 0.004 0.288 0.000 0.292 0.416 0.000
#> GSM1233119 5 0.5893 0.17530 0.000 0.032 0.004 0.132 0.588 0.244
#> GSM1233129 2 0.4788 0.42578 0.008 0.652 0.288 0.000 0.012 0.040
#> GSM1233132 2 0.7517 -0.14263 0.148 0.328 0.000 0.292 0.232 0.000
#> GSM1233139 2 0.3037 0.62785 0.056 0.872 0.032 0.012 0.028 0.000
#> GSM1233143 2 0.4278 0.58468 0.000 0.760 0.152 0.056 0.032 0.000
#> GSM1233145 4 0.3144 0.57357 0.000 0.004 0.000 0.808 0.172 0.016
#> GSM1233067 3 0.3841 0.38791 0.000 0.380 0.616 0.000 0.004 0.000
#> GSM1233069 3 0.4098 0.62290 0.000 0.036 0.732 0.000 0.012 0.220
#> GSM1233072 2 0.5560 0.57533 0.000 0.680 0.044 0.128 0.016 0.132
#> GSM1233086 6 0.6451 0.40215 0.012 0.020 0.124 0.012 0.332 0.500
#> GSM1233102 4 0.1003 0.61164 0.000 0.016 0.000 0.964 0.020 0.000
#> GSM1233103 1 0.6250 0.16599 0.432 0.324 0.012 0.000 0.232 0.000
#> GSM1233107 2 0.5215 0.40284 0.000 0.620 0.004 0.236 0.140 0.000
#> GSM1233108 3 0.3864 0.63081 0.016 0.000 0.796 0.000 0.092 0.096
#> GSM1233109 3 0.4613 0.59072 0.012 0.000 0.704 0.000 0.080 0.204
#> GSM1233110 3 0.0748 0.70657 0.000 0.004 0.976 0.000 0.004 0.016
#> GSM1233113 2 0.5219 0.40875 0.000 0.604 0.272 0.000 0.004 0.120
#> GSM1233116 3 0.7375 0.26101 0.000 0.220 0.412 0.000 0.184 0.184
#> GSM1233120 4 0.5870 0.47835 0.088 0.004 0.004 0.652 0.096 0.156
#> GSM1233121 3 0.3343 0.67324 0.004 0.008 0.816 0.000 0.024 0.148
#> GSM1233123 3 0.1605 0.71489 0.000 0.044 0.936 0.000 0.004 0.016
#> GSM1233124 3 0.5137 0.39629 0.000 0.328 0.584 0.000 0.080 0.008
#> GSM1233125 3 0.4693 0.13532 0.012 0.000 0.532 0.000 0.432 0.024
#> GSM1233126 4 0.3063 0.60479 0.000 0.052 0.000 0.856 0.076 0.016
#> GSM1233127 2 0.4444 0.51345 0.000 0.708 0.000 0.184 0.108 0.000
#> GSM1233128 5 0.6132 0.40486 0.048 0.000 0.188 0.056 0.636 0.072
#> GSM1233130 3 0.3960 0.61334 0.000 0.004 0.736 0.000 0.040 0.220
#> GSM1233131 5 0.5622 0.38334 0.236 0.068 0.000 0.072 0.624 0.000
#> GSM1233133 3 0.1461 0.69878 0.000 0.016 0.940 0.000 0.044 0.000
#> GSM1233134 3 0.3023 0.62154 0.000 0.232 0.768 0.000 0.000 0.000
#> GSM1233135 3 0.2265 0.71506 0.000 0.068 0.900 0.000 0.008 0.024
#> GSM1233136 6 0.5071 0.05313 0.000 0.012 0.376 0.000 0.056 0.556
#> GSM1233137 3 0.2100 0.70803 0.000 0.112 0.884 0.000 0.004 0.000
#> GSM1233138 4 0.5081 0.50349 0.000 0.072 0.000 0.664 0.232 0.032
#> GSM1233140 5 0.5343 0.06723 0.072 0.000 0.444 0.012 0.472 0.000
#> GSM1233141 2 0.3893 0.62440 0.000 0.820 0.024 0.052 0.080 0.024
#> GSM1233142 2 0.3413 0.60393 0.004 0.820 0.004 0.048 0.124 0.000
#> GSM1233144 3 0.0820 0.70379 0.000 0.012 0.972 0.000 0.016 0.000
#> GSM1233147 6 0.3651 0.53239 0.000 0.012 0.052 0.040 0.060 0.836
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> MAD:NMF 136 1.28e-02 0.24475 0.18363 2
#> MAD:NMF 96 8.47e-04 0.31453 0.03595 3
#> MAD:NMF 109 4.41e-05 0.04471 0.04316 4
#> MAD:NMF 116 3.24e-06 0.00866 0.00761 5
#> MAD:NMF 70 2.48e-03 0.06671 0.06669 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 51941 rows and 156 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'hclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.708 0.873 0.935 0.4618 0.518 0.518
#> 3 3 0.540 0.680 0.825 0.2568 0.847 0.720
#> 4 4 0.661 0.809 0.888 0.2030 0.803 0.573
#> 5 5 0.724 0.776 0.868 0.0743 0.941 0.811
#> 6 6 0.716 0.713 0.773 0.0370 0.985 0.944
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.0000 0.9456 0.000 1.000
#> GSM1233002 1 0.3274 0.8792 0.940 0.060
#> GSM1233003 1 0.0000 0.8973 1.000 0.000
#> GSM1233014 2 0.2423 0.9374 0.040 0.960
#> GSM1233015 1 0.8016 0.7348 0.756 0.244
#> GSM1233016 2 0.7139 0.7792 0.196 0.804
#> GSM1233024 2 0.0000 0.9456 0.000 1.000
#> GSM1233049 1 0.0000 0.8973 1.000 0.000
#> GSM1233064 2 0.3431 0.9256 0.064 0.936
#> GSM1233068 2 0.5059 0.8858 0.112 0.888
#> GSM1233073 2 0.9970 0.0364 0.468 0.532
#> GSM1233093 1 0.0000 0.8973 1.000 0.000
#> GSM1233115 1 0.1414 0.8942 0.980 0.020
#> GSM1232992 2 0.0000 0.9456 0.000 1.000
#> GSM1232993 2 0.3274 0.9279 0.060 0.940
#> GSM1233005 2 0.0000 0.9456 0.000 1.000
#> GSM1233007 2 0.3114 0.9301 0.056 0.944
#> GSM1233010 1 0.9963 0.2237 0.536 0.464
#> GSM1233013 2 0.0000 0.9456 0.000 1.000
#> GSM1233018 2 0.0000 0.9456 0.000 1.000
#> GSM1233019 2 0.0000 0.9456 0.000 1.000
#> GSM1233021 2 0.0000 0.9456 0.000 1.000
#> GSM1233025 1 0.7745 0.7536 0.772 0.228
#> GSM1233029 2 0.1843 0.9411 0.028 0.972
#> GSM1233030 2 0.0000 0.9456 0.000 1.000
#> GSM1233031 2 0.7299 0.7665 0.204 0.796
#> GSM1233032 1 0.0000 0.8973 1.000 0.000
#> GSM1233035 2 0.4562 0.9014 0.096 0.904
#> GSM1233038 1 0.0000 0.8973 1.000 0.000
#> GSM1233039 2 0.3879 0.9176 0.076 0.924
#> GSM1233042 2 0.3584 0.9233 0.068 0.932
#> GSM1233043 2 0.3584 0.9233 0.068 0.932
#> GSM1233044 1 0.6343 0.8140 0.840 0.160
#> GSM1233046 1 0.9170 0.5907 0.668 0.332
#> GSM1233051 1 0.1414 0.8942 0.980 0.020
#> GSM1233054 1 0.8713 0.6637 0.708 0.292
#> GSM1233057 2 0.3879 0.9176 0.076 0.924
#> GSM1233060 2 0.4562 0.9010 0.096 0.904
#> GSM1233062 2 0.1843 0.9411 0.028 0.972
#> GSM1233075 2 0.0000 0.9456 0.000 1.000
#> GSM1233078 2 0.9896 0.1545 0.440 0.560
#> GSM1233079 1 0.0000 0.8973 1.000 0.000
#> GSM1233082 1 0.7883 0.7446 0.764 0.236
#> GSM1233083 1 0.0000 0.8973 1.000 0.000
#> GSM1233091 1 0.9000 0.6220 0.684 0.316
#> GSM1233095 1 0.0000 0.8973 1.000 0.000
#> GSM1233096 1 0.0000 0.8973 1.000 0.000
#> GSM1233101 1 0.0000 0.8973 1.000 0.000
#> GSM1233105 1 0.7745 0.7536 0.772 0.228
#> GSM1233117 2 0.0000 0.9456 0.000 1.000
#> GSM1233118 2 0.0000 0.9456 0.000 1.000
#> GSM1233001 2 0.0000 0.9456 0.000 1.000
#> GSM1233006 2 0.0000 0.9456 0.000 1.000
#> GSM1233008 2 0.0000 0.9456 0.000 1.000
#> GSM1233009 2 0.0000 0.9456 0.000 1.000
#> GSM1233017 2 0.0000 0.9456 0.000 1.000
#> GSM1233020 2 0.0000 0.9456 0.000 1.000
#> GSM1233022 2 0.2043 0.9401 0.032 0.968
#> GSM1233026 2 0.7299 0.7667 0.204 0.796
#> GSM1233028 2 0.8144 0.6817 0.252 0.748
#> GSM1233034 2 0.0000 0.9456 0.000 1.000
#> GSM1233040 1 0.0000 0.8973 1.000 0.000
#> GSM1233048 1 0.0000 0.8973 1.000 0.000
#> GSM1233056 1 0.0000 0.8973 1.000 0.000
#> GSM1233058 2 0.7602 0.7405 0.220 0.780
#> GSM1233059 1 0.0000 0.8973 1.000 0.000
#> GSM1233066 2 0.4161 0.9113 0.084 0.916
#> GSM1233071 2 0.2043 0.9401 0.032 0.968
#> GSM1233074 2 0.0000 0.9456 0.000 1.000
#> GSM1233076 2 0.2043 0.9401 0.032 0.968
#> GSM1233080 1 0.0000 0.8973 1.000 0.000
#> GSM1233088 2 0.4562 0.9010 0.096 0.904
#> GSM1233090 1 0.0000 0.8973 1.000 0.000
#> GSM1233092 2 0.0000 0.9456 0.000 1.000
#> GSM1233094 2 0.3274 0.9279 0.060 0.940
#> GSM1233097 2 0.3431 0.9256 0.064 0.936
#> GSM1233100 1 0.8207 0.7186 0.744 0.256
#> GSM1233104 2 0.2423 0.9374 0.040 0.960
#> GSM1233106 1 0.8081 0.7297 0.752 0.248
#> GSM1233111 1 0.0000 0.8973 1.000 0.000
#> GSM1233122 2 0.0000 0.9456 0.000 1.000
#> GSM1233146 2 0.4022 0.9145 0.080 0.920
#> GSM1232994 2 0.0000 0.9456 0.000 1.000
#> GSM1232996 2 0.0000 0.9456 0.000 1.000
#> GSM1232997 2 0.0000 0.9456 0.000 1.000
#> GSM1232998 2 0.0000 0.9456 0.000 1.000
#> GSM1232999 2 0.0000 0.9456 0.000 1.000
#> GSM1233000 2 0.0000 0.9456 0.000 1.000
#> GSM1233004 1 0.2236 0.8892 0.964 0.036
#> GSM1233011 2 0.2423 0.9374 0.040 0.960
#> GSM1233012 2 0.0000 0.9456 0.000 1.000
#> GSM1233023 2 0.0000 0.9456 0.000 1.000
#> GSM1233027 2 0.0000 0.9456 0.000 1.000
#> GSM1233033 1 0.0000 0.8973 1.000 0.000
#> GSM1233036 2 0.3114 0.9303 0.056 0.944
#> GSM1233037 2 0.7376 0.7591 0.208 0.792
#> GSM1233041 1 0.0000 0.8973 1.000 0.000
#> GSM1233045 2 0.3431 0.9256 0.064 0.936
#> GSM1233047 1 0.2778 0.8846 0.952 0.048
#> GSM1233050 1 0.0000 0.8973 1.000 0.000
#> GSM1233052 1 0.1184 0.8950 0.984 0.016
#> GSM1233053 1 0.0000 0.8973 1.000 0.000
#> GSM1233055 1 0.0000 0.8973 1.000 0.000
#> GSM1233061 1 0.9129 0.5989 0.672 0.328
#> GSM1233063 1 0.0000 0.8973 1.000 0.000
#> GSM1233065 2 0.0000 0.9456 0.000 1.000
#> GSM1233070 2 0.0000 0.9456 0.000 1.000
#> GSM1233077 2 0.1843 0.9411 0.028 0.972
#> GSM1233081 1 0.7745 0.7537 0.772 0.228
#> GSM1233084 1 0.0000 0.8973 1.000 0.000
#> GSM1233087 1 0.7950 0.7398 0.760 0.240
#> GSM1233089 2 0.0000 0.9456 0.000 1.000
#> GSM1233099 1 0.9000 0.6220 0.684 0.316
#> GSM1233112 1 0.0000 0.8973 1.000 0.000
#> GSM1233085 1 0.2423 0.8878 0.960 0.040
#> GSM1233098 2 0.0000 0.9456 0.000 1.000
#> GSM1233114 1 0.0000 0.8973 1.000 0.000
#> GSM1233119 1 0.9933 0.2661 0.548 0.452
#> GSM1233129 2 0.0000 0.9456 0.000 1.000
#> GSM1233132 1 0.2948 0.8828 0.948 0.052
#> GSM1233139 2 0.0000 0.9456 0.000 1.000
#> GSM1233143 2 0.0000 0.9456 0.000 1.000
#> GSM1233145 1 0.0000 0.8973 1.000 0.000
#> GSM1233067 2 0.0000 0.9456 0.000 1.000
#> GSM1233069 2 0.0000 0.9456 0.000 1.000
#> GSM1233072 2 0.0000 0.9456 0.000 1.000
#> GSM1233086 2 0.2423 0.9374 0.040 0.960
#> GSM1233102 1 0.0672 0.8964 0.992 0.008
#> GSM1233103 2 0.4562 0.9013 0.096 0.904
#> GSM1233107 2 0.4161 0.9113 0.084 0.916
#> GSM1233108 1 0.0000 0.8973 1.000 0.000
#> GSM1233109 1 0.1414 0.8942 0.980 0.020
#> GSM1233110 2 0.5629 0.8631 0.132 0.868
#> GSM1233113 2 0.0000 0.9456 0.000 1.000
#> GSM1233116 2 0.0000 0.9456 0.000 1.000
#> GSM1233120 1 0.7950 0.7400 0.760 0.240
#> GSM1233121 2 0.2423 0.9374 0.040 0.960
#> GSM1233123 2 0.5178 0.8808 0.116 0.884
#> GSM1233124 2 0.3431 0.9258 0.064 0.936
#> GSM1233125 1 0.0000 0.8973 1.000 0.000
#> GSM1233126 2 0.2043 0.9401 0.032 0.968
#> GSM1233127 2 0.0000 0.9456 0.000 1.000
#> GSM1233128 1 0.0000 0.8973 1.000 0.000
#> GSM1233130 2 0.4690 0.8972 0.100 0.900
#> GSM1233131 1 0.7745 0.7536 0.772 0.228
#> GSM1233133 1 0.2778 0.8846 0.952 0.048
#> GSM1233134 2 0.0000 0.9456 0.000 1.000
#> GSM1233135 2 0.0672 0.9447 0.008 0.992
#> GSM1233136 2 0.2043 0.9401 0.032 0.968
#> GSM1233137 1 0.5294 0.8435 0.880 0.120
#> GSM1233138 2 0.0672 0.9447 0.008 0.992
#> GSM1233140 1 0.0376 0.8968 0.996 0.004
#> GSM1233141 2 0.0000 0.9456 0.000 1.000
#> GSM1233142 2 0.0000 0.9456 0.000 1.000
#> GSM1233144 1 0.5294 0.8435 0.880 0.120
#> GSM1233147 2 0.0376 0.9452 0.004 0.996
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233002 1 0.5254 0.576 0.736 0.000 0.264
#> GSM1233003 3 0.0424 0.947 0.008 0.000 0.992
#> GSM1233014 2 0.5497 0.814 0.292 0.708 0.000
#> GSM1233015 1 0.2496 0.630 0.928 0.004 0.068
#> GSM1233016 1 0.6309 -0.559 0.504 0.496 0.000
#> GSM1233024 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1233049 3 0.0000 0.949 0.000 0.000 1.000
#> GSM1233064 2 0.5988 0.763 0.368 0.632 0.000
#> GSM1233068 2 0.6192 0.703 0.420 0.580 0.000
#> GSM1233073 1 0.4842 0.289 0.776 0.224 0.000
#> GSM1233093 3 0.0000 0.949 0.000 0.000 1.000
#> GSM1233115 1 0.5678 0.533 0.684 0.000 0.316
#> GSM1232992 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1232993 2 0.5926 0.773 0.356 0.644 0.000
#> GSM1233005 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233007 2 0.5905 0.776 0.352 0.648 0.000
#> GSM1233010 1 0.5627 0.446 0.780 0.188 0.032
#> GSM1233013 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233018 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233019 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233021 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233025 1 0.2625 0.632 0.916 0.000 0.084
#> GSM1233029 2 0.5138 0.830 0.252 0.748 0.000
#> GSM1233030 2 0.0000 0.779 0.000 1.000 0.000
#> GSM1233031 1 0.6307 -0.538 0.512 0.488 0.000
#> GSM1233032 3 0.2356 0.879 0.072 0.000 0.928
#> GSM1233035 2 0.6140 0.726 0.404 0.596 0.000
#> GSM1233038 3 0.0000 0.949 0.000 0.000 1.000
#> GSM1233039 2 0.6045 0.751 0.380 0.620 0.000
#> GSM1233042 2 0.6026 0.756 0.376 0.624 0.000
#> GSM1233043 2 0.6026 0.756 0.376 0.624 0.000
#> GSM1233044 1 0.3879 0.619 0.848 0.000 0.152
#> GSM1233046 1 0.1031 0.590 0.976 0.024 0.000
#> GSM1233051 1 0.5650 0.537 0.688 0.000 0.312
#> GSM1233054 1 0.1453 0.610 0.968 0.008 0.024
#> GSM1233057 2 0.6062 0.747 0.384 0.616 0.000
#> GSM1233060 2 0.6140 0.724 0.404 0.596 0.000
#> GSM1233062 2 0.5397 0.821 0.280 0.720 0.000
#> GSM1233075 2 0.4178 0.841 0.172 0.828 0.000
#> GSM1233078 1 0.6161 0.202 0.708 0.272 0.020
#> GSM1233079 1 0.5926 0.484 0.644 0.000 0.356
#> GSM1233082 1 0.2448 0.631 0.924 0.000 0.076
#> GSM1233083 1 0.6307 0.203 0.512 0.000 0.488
#> GSM1233091 1 0.0829 0.599 0.984 0.012 0.004
#> GSM1233095 3 0.0000 0.949 0.000 0.000 1.000
#> GSM1233096 1 0.5926 0.484 0.644 0.000 0.356
#> GSM1233101 3 0.5560 0.468 0.300 0.000 0.700
#> GSM1233105 1 0.2625 0.632 0.916 0.000 0.084
#> GSM1233117 2 0.0237 0.781 0.004 0.996 0.000
#> GSM1233118 2 0.0237 0.781 0.004 0.996 0.000
#> GSM1233001 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233006 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1233008 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1233009 2 0.3412 0.827 0.124 0.876 0.000
#> GSM1233017 2 0.0237 0.781 0.004 0.996 0.000
#> GSM1233020 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233022 2 0.5138 0.830 0.252 0.748 0.000
#> GSM1233026 1 0.6307 -0.540 0.512 0.488 0.000
#> GSM1233028 1 0.6244 -0.424 0.560 0.440 0.000
#> GSM1233034 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1233040 3 0.0424 0.947 0.008 0.000 0.992
#> GSM1233048 3 0.0424 0.947 0.008 0.000 0.992
#> GSM1233056 3 0.0000 0.949 0.000 0.000 1.000
#> GSM1233058 1 0.6295 -0.502 0.528 0.472 0.000
#> GSM1233059 3 0.0000 0.949 0.000 0.000 1.000
#> GSM1233066 2 0.6095 0.739 0.392 0.608 0.000
#> GSM1233071 2 0.5138 0.830 0.252 0.748 0.000
#> GSM1233074 2 0.4291 0.842 0.180 0.820 0.000
#> GSM1233076 2 0.5216 0.828 0.260 0.740 0.000
#> GSM1233080 3 0.0000 0.949 0.000 0.000 1.000
#> GSM1233088 2 0.6140 0.724 0.404 0.596 0.000
#> GSM1233090 3 0.0000 0.949 0.000 0.000 1.000
#> GSM1233092 2 0.4452 0.843 0.192 0.808 0.000
#> GSM1233094 2 0.5968 0.767 0.364 0.636 0.000
#> GSM1233097 2 0.5988 0.763 0.368 0.632 0.000
#> GSM1233100 1 0.2200 0.626 0.940 0.004 0.056
#> GSM1233104 2 0.5560 0.810 0.300 0.700 0.000
#> GSM1233106 1 0.2165 0.629 0.936 0.000 0.064
#> GSM1233111 1 0.5926 0.484 0.644 0.000 0.356
#> GSM1233122 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233146 2 0.6079 0.743 0.388 0.612 0.000
#> GSM1232994 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1232996 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1232997 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1232998 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1232999 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1233000 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1233004 1 0.5497 0.557 0.708 0.000 0.292
#> GSM1233011 2 0.5497 0.814 0.292 0.708 0.000
#> GSM1233012 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1233023 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1233027 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233033 1 0.5810 0.501 0.664 0.000 0.336
#> GSM1233036 2 0.5835 0.785 0.340 0.660 0.000
#> GSM1233037 1 0.6305 -0.528 0.516 0.484 0.000
#> GSM1233041 3 0.0000 0.949 0.000 0.000 1.000
#> GSM1233045 2 0.5988 0.763 0.368 0.632 0.000
#> GSM1233047 1 0.5291 0.573 0.732 0.000 0.268
#> GSM1233050 3 0.0424 0.947 0.008 0.000 0.992
#> GSM1233052 1 0.5706 0.525 0.680 0.000 0.320
#> GSM1233053 1 0.6168 0.391 0.588 0.000 0.412
#> GSM1233055 3 0.0424 0.947 0.008 0.000 0.992
#> GSM1233061 1 0.1267 0.592 0.972 0.024 0.004
#> GSM1233063 1 0.5926 0.484 0.644 0.000 0.356
#> GSM1233065 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233070 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1233077 2 0.5058 0.832 0.244 0.756 0.000
#> GSM1233081 1 0.2625 0.631 0.916 0.000 0.084
#> GSM1233084 3 0.0000 0.949 0.000 0.000 1.000
#> GSM1233087 1 0.2356 0.631 0.928 0.000 0.072
#> GSM1233089 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233099 1 0.0829 0.599 0.984 0.012 0.004
#> GSM1233112 1 0.6154 0.401 0.592 0.000 0.408
#> GSM1233085 1 0.5363 0.566 0.724 0.000 0.276
#> GSM1233098 2 0.3879 0.836 0.152 0.848 0.000
#> GSM1233114 1 0.5926 0.484 0.644 0.000 0.356
#> GSM1233119 1 0.5467 0.470 0.792 0.176 0.032
#> GSM1233129 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1233132 1 0.5216 0.578 0.740 0.000 0.260
#> GSM1233139 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1233143 2 0.4346 0.843 0.184 0.816 0.000
#> GSM1233145 3 0.5497 0.489 0.292 0.000 0.708
#> GSM1233067 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233069 2 0.4291 0.842 0.180 0.820 0.000
#> GSM1233072 2 0.0000 0.779 0.000 1.000 0.000
#> GSM1233086 2 0.5560 0.810 0.300 0.700 0.000
#> GSM1233102 1 0.5835 0.505 0.660 0.000 0.340
#> GSM1233103 2 0.6140 0.725 0.404 0.596 0.000
#> GSM1233107 2 0.6095 0.739 0.392 0.608 0.000
#> GSM1233108 1 0.5926 0.484 0.644 0.000 0.356
#> GSM1233109 1 0.5621 0.539 0.692 0.000 0.308
#> GSM1233110 2 0.6244 0.669 0.440 0.560 0.000
#> GSM1233113 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233116 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233120 1 0.2356 0.631 0.928 0.000 0.072
#> GSM1233121 2 0.5560 0.810 0.300 0.700 0.000
#> GSM1233123 2 0.6204 0.696 0.424 0.576 0.000
#> GSM1233124 2 0.6008 0.760 0.372 0.628 0.000
#> GSM1233125 1 0.6079 0.431 0.612 0.000 0.388
#> GSM1233126 2 0.5216 0.828 0.260 0.740 0.000
#> GSM1233127 2 0.4346 0.843 0.184 0.816 0.000
#> GSM1233128 3 0.0000 0.949 0.000 0.000 1.000
#> GSM1233130 2 0.6154 0.719 0.408 0.592 0.000
#> GSM1233131 1 0.2625 0.632 0.916 0.000 0.084
#> GSM1233133 1 0.5254 0.575 0.736 0.000 0.264
#> GSM1233134 2 0.4399 0.843 0.188 0.812 0.000
#> GSM1233135 2 0.4605 0.842 0.204 0.796 0.000
#> GSM1233136 2 0.5098 0.831 0.248 0.752 0.000
#> GSM1233137 1 0.4452 0.608 0.808 0.000 0.192
#> GSM1233138 2 0.4605 0.842 0.204 0.796 0.000
#> GSM1233140 1 0.5905 0.491 0.648 0.000 0.352
#> GSM1233141 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233142 2 0.0237 0.777 0.004 0.996 0.000
#> GSM1233144 1 0.4452 0.609 0.808 0.000 0.192
#> GSM1233147 2 0.4452 0.843 0.192 0.808 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233002 4 0.2411 0.79513 0.040 0.000 0.040 0.920
#> GSM1233003 1 0.0707 0.92660 0.980 0.000 0.000 0.020
#> GSM1233014 3 0.2011 0.85404 0.000 0.080 0.920 0.000
#> GSM1233015 4 0.3764 0.75437 0.000 0.000 0.216 0.784
#> GSM1233016 3 0.3219 0.70811 0.000 0.000 0.836 0.164
#> GSM1233024 3 0.3649 0.81197 0.000 0.204 0.796 0.000
#> GSM1233049 1 0.0000 0.93209 1.000 0.000 0.000 0.000
#> GSM1233064 3 0.0376 0.84033 0.000 0.004 0.992 0.004
#> GSM1233068 3 0.1716 0.80951 0.000 0.000 0.936 0.064
#> GSM1233073 3 0.4977 -0.11334 0.000 0.000 0.540 0.460
#> GSM1233093 1 0.0000 0.93209 1.000 0.000 0.000 0.000
#> GSM1233115 4 0.1792 0.78165 0.068 0.000 0.000 0.932
#> GSM1232992 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1232993 3 0.0779 0.84503 0.000 0.016 0.980 0.004
#> GSM1233005 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233007 3 0.0707 0.84680 0.000 0.020 0.980 0.000
#> GSM1233010 4 0.4977 0.35178 0.000 0.000 0.460 0.540
#> GSM1233013 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233018 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233019 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233021 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233025 4 0.3569 0.76478 0.000 0.000 0.196 0.804
#> GSM1233029 3 0.2647 0.84789 0.000 0.120 0.880 0.000
#> GSM1233030 2 0.1474 0.93494 0.000 0.948 0.052 0.000
#> GSM1233031 3 0.3311 0.69989 0.000 0.000 0.828 0.172
#> GSM1233032 1 0.2589 0.83468 0.884 0.000 0.000 0.116
#> GSM1233035 3 0.1211 0.82441 0.000 0.000 0.960 0.040
#> GSM1233038 1 0.0000 0.93209 1.000 0.000 0.000 0.000
#> GSM1233039 3 0.0779 0.83660 0.000 0.004 0.980 0.016
#> GSM1233042 3 0.0188 0.83901 0.000 0.000 0.996 0.004
#> GSM1233043 3 0.0188 0.83901 0.000 0.000 0.996 0.004
#> GSM1233044 4 0.2469 0.78494 0.000 0.000 0.108 0.892
#> GSM1233046 4 0.4585 0.65053 0.000 0.000 0.332 0.668
#> GSM1233051 4 0.1716 0.78369 0.064 0.000 0.000 0.936
#> GSM1233054 4 0.4250 0.70590 0.000 0.000 0.276 0.724
#> GSM1233057 3 0.0707 0.83284 0.000 0.000 0.980 0.020
#> GSM1233060 3 0.1474 0.81721 0.000 0.000 0.948 0.052
#> GSM1233062 3 0.2216 0.85392 0.000 0.092 0.908 0.000
#> GSM1233075 3 0.4277 0.73657 0.000 0.280 0.720 0.000
#> GSM1233078 3 0.4941 -0.00303 0.000 0.000 0.564 0.436
#> GSM1233079 4 0.2469 0.76282 0.108 0.000 0.000 0.892
#> GSM1233082 4 0.3649 0.76126 0.000 0.000 0.204 0.796
#> GSM1233083 4 0.4134 0.58624 0.260 0.000 0.000 0.740
#> GSM1233091 4 0.4454 0.67830 0.000 0.000 0.308 0.692
#> GSM1233095 1 0.0000 0.93209 1.000 0.000 0.000 0.000
#> GSM1233096 4 0.2469 0.76282 0.108 0.000 0.000 0.892
#> GSM1233101 1 0.4967 0.17147 0.548 0.000 0.000 0.452
#> GSM1233105 4 0.3569 0.76478 0.000 0.000 0.196 0.804
#> GSM1233117 2 0.1389 0.94104 0.000 0.952 0.048 0.000
#> GSM1233118 2 0.1389 0.94104 0.000 0.952 0.048 0.000
#> GSM1233001 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233006 3 0.3486 0.82173 0.000 0.188 0.812 0.000
#> GSM1233008 3 0.3649 0.81197 0.000 0.204 0.796 0.000
#> GSM1233009 3 0.4713 0.61910 0.000 0.360 0.640 0.000
#> GSM1233017 2 0.1389 0.94178 0.000 0.952 0.048 0.000
#> GSM1233020 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233022 3 0.2647 0.84750 0.000 0.120 0.880 0.000
#> GSM1233026 3 0.3356 0.69241 0.000 0.000 0.824 0.176
#> GSM1233028 3 0.3837 0.61028 0.000 0.000 0.776 0.224
#> GSM1233034 3 0.3569 0.81731 0.000 0.196 0.804 0.000
#> GSM1233040 1 0.0817 0.92527 0.976 0.000 0.000 0.024
#> GSM1233048 1 0.0817 0.92527 0.976 0.000 0.000 0.024
#> GSM1233056 1 0.0000 0.93209 1.000 0.000 0.000 0.000
#> GSM1233058 3 0.3610 0.65608 0.000 0.000 0.800 0.200
#> GSM1233059 1 0.0000 0.93209 1.000 0.000 0.000 0.000
#> GSM1233066 3 0.1211 0.82427 0.000 0.000 0.960 0.040
#> GSM1233071 3 0.2647 0.84750 0.000 0.120 0.880 0.000
#> GSM1233074 3 0.4040 0.77257 0.000 0.248 0.752 0.000
#> GSM1233076 3 0.2714 0.85038 0.000 0.112 0.884 0.004
#> GSM1233080 1 0.0000 0.93209 1.000 0.000 0.000 0.000
#> GSM1233088 3 0.1557 0.81497 0.000 0.000 0.944 0.056
#> GSM1233090 1 0.0000 0.93209 1.000 0.000 0.000 0.000
#> GSM1233092 3 0.3444 0.82429 0.000 0.184 0.816 0.000
#> GSM1233094 3 0.0524 0.84191 0.000 0.008 0.988 0.004
#> GSM1233097 3 0.0376 0.84033 0.000 0.004 0.992 0.004
#> GSM1233100 4 0.3873 0.74571 0.000 0.000 0.228 0.772
#> GSM1233104 3 0.1867 0.85439 0.000 0.072 0.928 0.000
#> GSM1233106 4 0.3764 0.75450 0.000 0.000 0.216 0.784
#> GSM1233111 4 0.2469 0.76282 0.108 0.000 0.000 0.892
#> GSM1233122 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233146 3 0.0921 0.82962 0.000 0.000 0.972 0.028
#> GSM1232994 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1232996 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1232997 3 0.3569 0.81731 0.000 0.196 0.804 0.000
#> GSM1232998 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1232999 3 0.3444 0.82352 0.000 0.184 0.816 0.000
#> GSM1233000 3 0.3486 0.82173 0.000 0.188 0.812 0.000
#> GSM1233004 4 0.1302 0.78695 0.044 0.000 0.000 0.956
#> GSM1233011 3 0.2011 0.85404 0.000 0.080 0.920 0.000
#> GSM1233012 3 0.3764 0.80316 0.000 0.216 0.784 0.000
#> GSM1233023 3 0.3649 0.81197 0.000 0.204 0.796 0.000
#> GSM1233027 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233033 4 0.2149 0.77275 0.088 0.000 0.000 0.912
#> GSM1233036 3 0.1022 0.85059 0.000 0.032 0.968 0.000
#> GSM1233037 3 0.3356 0.68833 0.000 0.000 0.824 0.176
#> GSM1233041 1 0.0000 0.93209 1.000 0.000 0.000 0.000
#> GSM1233045 3 0.0376 0.84033 0.000 0.004 0.992 0.004
#> GSM1233047 4 0.0707 0.78895 0.020 0.000 0.000 0.980
#> GSM1233050 1 0.0817 0.92527 0.976 0.000 0.000 0.024
#> GSM1233052 4 0.1867 0.77847 0.072 0.000 0.000 0.928
#> GSM1233053 4 0.3400 0.69852 0.180 0.000 0.000 0.820
#> GSM1233055 1 0.0817 0.92527 0.976 0.000 0.000 0.024
#> GSM1233061 4 0.4564 0.65735 0.000 0.000 0.328 0.672
#> GSM1233063 4 0.2469 0.76282 0.108 0.000 0.000 0.892
#> GSM1233065 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233070 3 0.3486 0.82173 0.000 0.188 0.812 0.000
#> GSM1233077 3 0.2760 0.84515 0.000 0.128 0.872 0.000
#> GSM1233081 4 0.3751 0.76607 0.004 0.000 0.196 0.800
#> GSM1233084 1 0.0000 0.93209 1.000 0.000 0.000 0.000
#> GSM1233087 4 0.3688 0.75918 0.000 0.000 0.208 0.792
#> GSM1233089 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233099 4 0.4454 0.67830 0.000 0.000 0.308 0.692
#> GSM1233112 4 0.3356 0.70386 0.176 0.000 0.000 0.824
#> GSM1233085 4 0.0921 0.78863 0.028 0.000 0.000 0.972
#> GSM1233098 3 0.4661 0.63284 0.000 0.348 0.652 0.000
#> GSM1233114 4 0.2469 0.76282 0.108 0.000 0.000 0.892
#> GSM1233119 4 0.4955 0.39563 0.000 0.000 0.444 0.556
#> GSM1233129 3 0.3610 0.81461 0.000 0.200 0.800 0.000
#> GSM1233132 4 0.0469 0.78905 0.012 0.000 0.000 0.988
#> GSM1233139 3 0.3444 0.82352 0.000 0.184 0.816 0.000
#> GSM1233143 3 0.3801 0.79977 0.000 0.220 0.780 0.000
#> GSM1233145 1 0.4948 0.20896 0.560 0.000 0.000 0.440
#> GSM1233067 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233069 3 0.4134 0.76074 0.000 0.260 0.740 0.000
#> GSM1233072 2 0.0188 0.98507 0.000 0.996 0.004 0.000
#> GSM1233086 3 0.1867 0.85439 0.000 0.072 0.928 0.000
#> GSM1233102 4 0.2216 0.77091 0.092 0.000 0.000 0.908
#> GSM1233103 3 0.1474 0.81816 0.000 0.000 0.948 0.052
#> GSM1233107 3 0.1118 0.82615 0.000 0.000 0.964 0.036
#> GSM1233108 4 0.2469 0.76282 0.108 0.000 0.000 0.892
#> GSM1233109 4 0.1637 0.78437 0.060 0.000 0.000 0.940
#> GSM1233110 3 0.2216 0.78675 0.000 0.000 0.908 0.092
#> GSM1233113 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233116 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233120 4 0.3688 0.75947 0.000 0.000 0.208 0.792
#> GSM1233121 3 0.1867 0.85439 0.000 0.072 0.928 0.000
#> GSM1233123 3 0.1940 0.79992 0.000 0.000 0.924 0.076
#> GSM1233124 3 0.0657 0.83847 0.000 0.004 0.984 0.012
#> GSM1233125 4 0.3172 0.71845 0.160 0.000 0.000 0.840
#> GSM1233126 3 0.2530 0.84986 0.000 0.112 0.888 0.000
#> GSM1233127 3 0.3801 0.79977 0.000 0.220 0.780 0.000
#> GSM1233128 1 0.0000 0.93209 1.000 0.000 0.000 0.000
#> GSM1233130 3 0.1557 0.81512 0.000 0.000 0.944 0.056
#> GSM1233131 4 0.3569 0.76475 0.000 0.000 0.196 0.804
#> GSM1233133 4 0.0592 0.78921 0.016 0.000 0.000 0.984
#> GSM1233134 3 0.3688 0.80908 0.000 0.208 0.792 0.000
#> GSM1233135 3 0.3266 0.83104 0.000 0.168 0.832 0.000
#> GSM1233136 3 0.2704 0.84625 0.000 0.124 0.876 0.000
#> GSM1233137 4 0.1557 0.79186 0.000 0.000 0.056 0.944
#> GSM1233138 3 0.3266 0.83104 0.000 0.168 0.832 0.000
#> GSM1233140 4 0.2408 0.76496 0.104 0.000 0.000 0.896
#> GSM1233141 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233142 2 0.0000 0.98907 0.000 1.000 0.000 0.000
#> GSM1233144 4 0.1557 0.79207 0.000 0.000 0.056 0.944
#> GSM1233147 3 0.3569 0.81779 0.000 0.196 0.804 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.0000 0.9828 0.000 1.000 0.000 0.000 0.000
#> GSM1233002 1 0.4182 0.5202 0.600 0.000 0.000 0.400 0.000
#> GSM1233003 5 0.1608 0.9306 0.072 0.000 0.000 0.000 0.928
#> GSM1233014 3 0.1792 0.8192 0.000 0.000 0.916 0.084 0.000
#> GSM1233015 4 0.1430 0.7761 0.052 0.000 0.004 0.944 0.000
#> GSM1233016 3 0.4171 0.5694 0.000 0.000 0.604 0.396 0.000
#> GSM1233024 3 0.1671 0.7971 0.000 0.076 0.924 0.000 0.000
#> GSM1233049 5 0.0162 0.9581 0.000 0.000 0.000 0.004 0.996
#> GSM1233064 3 0.3003 0.7926 0.000 0.000 0.812 0.188 0.000
#> GSM1233068 3 0.3774 0.7136 0.000 0.000 0.704 0.296 0.000
#> GSM1233073 4 0.3949 0.4277 0.004 0.000 0.300 0.696 0.000
#> GSM1233093 5 0.0162 0.9581 0.000 0.000 0.000 0.004 0.996
#> GSM1233115 1 0.3242 0.7223 0.784 0.000 0.000 0.216 0.000
#> GSM1232992 2 0.0000 0.9828 0.000 1.000 0.000 0.000 0.000
#> GSM1232993 3 0.3010 0.8014 0.000 0.004 0.824 0.172 0.000
#> GSM1233005 2 0.0162 0.9827 0.000 0.996 0.004 0.000 0.000
#> GSM1233007 3 0.2930 0.8041 0.000 0.004 0.832 0.164 0.000
#> GSM1233010 4 0.4029 0.6001 0.024 0.000 0.232 0.744 0.000
#> GSM1233013 2 0.0000 0.9828 0.000 1.000 0.000 0.000 0.000
#> GSM1233018 2 0.0000 0.9828 0.000 1.000 0.000 0.000 0.000
#> GSM1233019 2 0.0000 0.9828 0.000 1.000 0.000 0.000 0.000
#> GSM1233021 2 0.0162 0.9827 0.000 0.996 0.004 0.000 0.000
#> GSM1233025 4 0.1608 0.7671 0.072 0.000 0.000 0.928 0.000
#> GSM1233029 3 0.0955 0.8182 0.000 0.004 0.968 0.028 0.000
#> GSM1233030 2 0.1908 0.8977 0.000 0.908 0.092 0.000 0.000
#> GSM1233031 3 0.4235 0.5307 0.000 0.000 0.576 0.424 0.000
#> GSM1233032 5 0.2690 0.8435 0.156 0.000 0.000 0.000 0.844
#> GSM1233035 3 0.3612 0.7416 0.000 0.000 0.732 0.268 0.000
#> GSM1233038 5 0.0000 0.9587 0.000 0.000 0.000 0.000 1.000
#> GSM1233039 3 0.3210 0.7815 0.000 0.000 0.788 0.212 0.000
#> GSM1233042 3 0.2929 0.7978 0.000 0.000 0.820 0.180 0.000
#> GSM1233043 3 0.2929 0.7978 0.000 0.000 0.820 0.180 0.000
#> GSM1233044 4 0.3766 0.4433 0.268 0.000 0.004 0.728 0.000
#> GSM1233046 4 0.1892 0.7462 0.004 0.000 0.080 0.916 0.000
#> GSM1233051 1 0.3210 0.7231 0.788 0.000 0.000 0.212 0.000
#> GSM1233054 4 0.1997 0.7696 0.036 0.000 0.040 0.924 0.000
#> GSM1233057 3 0.3424 0.7630 0.000 0.000 0.760 0.240 0.000
#> GSM1233060 3 0.3636 0.7395 0.000 0.000 0.728 0.272 0.000
#> GSM1233062 3 0.1638 0.8214 0.000 0.004 0.932 0.064 0.000
#> GSM1233075 3 0.2690 0.7408 0.000 0.156 0.844 0.000 0.000
#> GSM1233078 4 0.4251 0.3547 0.012 0.000 0.316 0.672 0.000
#> GSM1233079 1 0.0794 0.7620 0.972 0.000 0.000 0.028 0.000
#> GSM1233082 4 0.1704 0.7719 0.068 0.000 0.004 0.928 0.000
#> GSM1233083 1 0.3278 0.6752 0.824 0.000 0.000 0.020 0.156
#> GSM1233091 4 0.1502 0.7604 0.004 0.000 0.056 0.940 0.000
#> GSM1233095 5 0.0000 0.9587 0.000 0.000 0.000 0.000 1.000
#> GSM1233096 1 0.0794 0.7620 0.972 0.000 0.000 0.028 0.000
#> GSM1233101 1 0.4489 0.1494 0.572 0.000 0.000 0.008 0.420
#> GSM1233105 4 0.1608 0.7671 0.072 0.000 0.000 0.928 0.000
#> GSM1233117 2 0.1544 0.9231 0.000 0.932 0.068 0.000 0.000
#> GSM1233118 2 0.1544 0.9231 0.000 0.932 0.068 0.000 0.000
#> GSM1233001 2 0.0162 0.9816 0.000 0.996 0.004 0.000 0.000
#> GSM1233006 3 0.1410 0.8041 0.000 0.060 0.940 0.000 0.000
#> GSM1233008 3 0.1671 0.7971 0.000 0.076 0.924 0.000 0.000
#> GSM1233009 3 0.3395 0.6689 0.000 0.236 0.764 0.000 0.000
#> GSM1233017 2 0.1608 0.9195 0.000 0.928 0.072 0.000 0.000
#> GSM1233020 2 0.0000 0.9828 0.000 1.000 0.000 0.000 0.000
#> GSM1233022 3 0.0671 0.8167 0.000 0.004 0.980 0.016 0.000
#> GSM1233026 3 0.4210 0.5381 0.000 0.000 0.588 0.412 0.000
#> GSM1233028 3 0.4294 0.4093 0.000 0.000 0.532 0.468 0.000
#> GSM1233034 3 0.1544 0.8010 0.000 0.068 0.932 0.000 0.000
#> GSM1233040 5 0.1792 0.9241 0.084 0.000 0.000 0.000 0.916
#> GSM1233048 5 0.2127 0.9107 0.108 0.000 0.000 0.000 0.892
#> GSM1233056 5 0.0162 0.9581 0.000 0.000 0.000 0.004 0.996
#> GSM1233058 3 0.4256 0.4868 0.000 0.000 0.564 0.436 0.000
#> GSM1233059 5 0.0000 0.9587 0.000 0.000 0.000 0.000 1.000
#> GSM1233066 3 0.3612 0.7408 0.000 0.000 0.732 0.268 0.000
#> GSM1233071 3 0.0671 0.8167 0.000 0.004 0.980 0.016 0.000
#> GSM1233074 3 0.2280 0.7679 0.000 0.120 0.880 0.000 0.000
#> GSM1233076 3 0.1430 0.8203 0.000 0.004 0.944 0.052 0.000
#> GSM1233080 5 0.0000 0.9587 0.000 0.000 0.000 0.000 1.000
#> GSM1233088 3 0.3684 0.7322 0.000 0.000 0.720 0.280 0.000
#> GSM1233090 5 0.0000 0.9587 0.000 0.000 0.000 0.000 1.000
#> GSM1233092 3 0.1341 0.8053 0.000 0.056 0.944 0.000 0.000
#> GSM1233094 3 0.3177 0.7837 0.000 0.000 0.792 0.208 0.000
#> GSM1233097 3 0.3039 0.7908 0.000 0.000 0.808 0.192 0.000
#> GSM1233100 4 0.1331 0.7772 0.040 0.000 0.008 0.952 0.000
#> GSM1233104 3 0.2020 0.8175 0.000 0.000 0.900 0.100 0.000
#> GSM1233106 4 0.1740 0.7778 0.056 0.000 0.012 0.932 0.000
#> GSM1233111 1 0.0703 0.7606 0.976 0.000 0.000 0.024 0.000
#> GSM1233122 2 0.0000 0.9828 0.000 1.000 0.000 0.000 0.000
#> GSM1233146 3 0.3508 0.7538 0.000 0.000 0.748 0.252 0.000
#> GSM1232994 2 0.0162 0.9827 0.000 0.996 0.004 0.000 0.000
#> GSM1232996 2 0.0000 0.9828 0.000 1.000 0.000 0.000 0.000
#> GSM1232997 3 0.1544 0.8010 0.000 0.068 0.932 0.000 0.000
#> GSM1232998 2 0.0162 0.9827 0.000 0.996 0.004 0.000 0.000
#> GSM1232999 3 0.1341 0.8052 0.000 0.056 0.944 0.000 0.000
#> GSM1233000 3 0.1410 0.8041 0.000 0.060 0.940 0.000 0.000
#> GSM1233004 1 0.4150 0.5639 0.612 0.000 0.000 0.388 0.000
#> GSM1233011 3 0.1792 0.8192 0.000 0.000 0.916 0.084 0.000
#> GSM1233012 3 0.1851 0.7904 0.000 0.088 0.912 0.000 0.000
#> GSM1233023 3 0.1671 0.7971 0.000 0.076 0.924 0.000 0.000
#> GSM1233027 2 0.0404 0.9772 0.000 0.988 0.012 0.000 0.000
#> GSM1233033 1 0.1270 0.7606 0.948 0.000 0.000 0.052 0.000
#> GSM1233036 3 0.2732 0.8060 0.000 0.000 0.840 0.160 0.000
#> GSM1233037 3 0.4210 0.5342 0.000 0.000 0.588 0.412 0.000
#> GSM1233041 5 0.0162 0.9581 0.000 0.000 0.000 0.004 0.996
#> GSM1233045 3 0.3039 0.7908 0.000 0.000 0.808 0.192 0.000
#> GSM1233047 1 0.4283 0.4380 0.544 0.000 0.000 0.456 0.000
#> GSM1233050 5 0.2127 0.9107 0.108 0.000 0.000 0.000 0.892
#> GSM1233052 1 0.3796 0.6569 0.700 0.000 0.000 0.300 0.000
#> GSM1233053 1 0.4065 0.7173 0.772 0.000 0.000 0.180 0.048
#> GSM1233055 5 0.2439 0.9018 0.120 0.000 0.000 0.004 0.876
#> GSM1233061 4 0.1831 0.7491 0.004 0.000 0.076 0.920 0.000
#> GSM1233063 1 0.0794 0.7620 0.972 0.000 0.000 0.028 0.000
#> GSM1233065 2 0.0162 0.9827 0.000 0.996 0.004 0.000 0.000
#> GSM1233070 3 0.1410 0.8041 0.000 0.060 0.940 0.000 0.000
#> GSM1233077 3 0.0566 0.8158 0.000 0.004 0.984 0.012 0.000
#> GSM1233081 4 0.2068 0.7527 0.092 0.000 0.004 0.904 0.000
#> GSM1233084 5 0.0000 0.9587 0.000 0.000 0.000 0.000 1.000
#> GSM1233087 4 0.1704 0.7726 0.068 0.000 0.004 0.928 0.000
#> GSM1233089 2 0.0162 0.9827 0.000 0.996 0.004 0.000 0.000
#> GSM1233099 4 0.1502 0.7604 0.004 0.000 0.056 0.940 0.000
#> GSM1233112 1 0.3991 0.7208 0.780 0.000 0.000 0.172 0.048
#> GSM1233085 1 0.4268 0.4619 0.556 0.000 0.000 0.444 0.000
#> GSM1233098 3 0.3305 0.6676 0.000 0.224 0.776 0.000 0.000
#> GSM1233114 1 0.0703 0.7606 0.976 0.000 0.000 0.024 0.000
#> GSM1233119 4 0.3877 0.6230 0.024 0.000 0.212 0.764 0.000
#> GSM1233129 3 0.1608 0.7990 0.000 0.072 0.928 0.000 0.000
#> GSM1233132 1 0.4291 0.4082 0.536 0.000 0.000 0.464 0.000
#> GSM1233139 3 0.1341 0.8052 0.000 0.056 0.944 0.000 0.000
#> GSM1233143 3 0.1908 0.7900 0.000 0.092 0.908 0.000 0.000
#> GSM1233145 1 0.4287 0.0277 0.540 0.000 0.000 0.000 0.460
#> GSM1233067 2 0.0162 0.9827 0.000 0.996 0.004 0.000 0.000
#> GSM1233069 3 0.2424 0.7588 0.000 0.132 0.868 0.000 0.000
#> GSM1233072 2 0.0290 0.9802 0.000 0.992 0.008 0.000 0.000
#> GSM1233086 3 0.1908 0.8185 0.000 0.000 0.908 0.092 0.000
#> GSM1233102 1 0.2329 0.7554 0.876 0.000 0.000 0.124 0.000
#> GSM1233103 3 0.3636 0.7383 0.000 0.000 0.728 0.272 0.000
#> GSM1233107 3 0.3586 0.7442 0.000 0.000 0.736 0.264 0.000
#> GSM1233108 1 0.0794 0.7620 0.972 0.000 0.000 0.028 0.000
#> GSM1233109 1 0.3612 0.6858 0.732 0.000 0.000 0.268 0.000
#> GSM1233110 3 0.3932 0.6754 0.000 0.000 0.672 0.328 0.000
#> GSM1233113 2 0.0000 0.9828 0.000 1.000 0.000 0.000 0.000
#> GSM1233116 2 0.0000 0.9828 0.000 1.000 0.000 0.000 0.000
#> GSM1233120 4 0.1956 0.7716 0.076 0.000 0.008 0.916 0.000
#> GSM1233121 3 0.1965 0.8182 0.000 0.000 0.904 0.096 0.000
#> GSM1233123 3 0.3857 0.6924 0.000 0.000 0.688 0.312 0.000
#> GSM1233124 3 0.3305 0.7742 0.000 0.000 0.776 0.224 0.000
#> GSM1233125 1 0.2054 0.7443 0.920 0.000 0.000 0.028 0.052
#> GSM1233126 3 0.1205 0.8201 0.000 0.004 0.956 0.040 0.000
#> GSM1233127 3 0.1908 0.7900 0.000 0.092 0.908 0.000 0.000
#> GSM1233128 5 0.0162 0.9581 0.000 0.000 0.000 0.004 0.996
#> GSM1233130 3 0.3636 0.7381 0.000 0.000 0.728 0.272 0.000
#> GSM1233131 4 0.2068 0.7558 0.092 0.000 0.004 0.904 0.000
#> GSM1233133 1 0.4302 0.3785 0.520 0.000 0.000 0.480 0.000
#> GSM1233134 3 0.1732 0.7949 0.000 0.080 0.920 0.000 0.000
#> GSM1233135 3 0.1408 0.8103 0.000 0.044 0.948 0.008 0.000
#> GSM1233136 3 0.0671 0.8169 0.000 0.004 0.980 0.016 0.000
#> GSM1233137 4 0.4015 0.1885 0.348 0.000 0.000 0.652 0.000
#> GSM1233138 3 0.1408 0.8103 0.000 0.044 0.948 0.008 0.000
#> GSM1233140 1 0.1121 0.7610 0.956 0.000 0.000 0.044 0.000
#> GSM1233141 2 0.0000 0.9828 0.000 1.000 0.000 0.000 0.000
#> GSM1233142 2 0.0000 0.9828 0.000 1.000 0.000 0.000 0.000
#> GSM1233144 4 0.3983 0.2162 0.340 0.000 0.000 0.660 0.000
#> GSM1233147 3 0.1544 0.8015 0.000 0.068 0.932 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.0146 9.77e-01 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM1233002 3 0.5774 4.24e-01 0.000 0.000 0.456 0.364 0.180 0.000
#> GSM1233003 1 0.1779 8.88e-01 0.920 0.000 0.064 0.000 0.016 0.000
#> GSM1233014 6 0.1549 7.68e-01 0.000 0.000 0.000 0.044 0.020 0.936
#> GSM1233015 4 0.0603 7.42e-01 0.000 0.000 0.016 0.980 0.000 0.004
#> GSM1233016 6 0.5296 4.98e-01 0.000 0.000 0.000 0.308 0.128 0.564
#> GSM1233024 6 0.2859 7.39e-01 0.000 0.016 0.000 0.000 0.156 0.828
#> GSM1233049 1 0.0458 9.12e-01 0.984 0.000 0.000 0.000 0.016 0.000
#> GSM1233064 6 0.3468 7.33e-01 0.000 0.000 0.000 0.128 0.068 0.804
#> GSM1233068 6 0.4823 6.32e-01 0.000 0.000 0.000 0.216 0.124 0.660
#> GSM1233073 4 0.4934 4.67e-01 0.000 0.000 0.000 0.628 0.108 0.264
#> GSM1233093 1 0.0458 9.12e-01 0.984 0.000 0.000 0.000 0.016 0.000
#> GSM1233115 3 0.5688 3.73e-02 0.000 0.000 0.496 0.176 0.328 0.000
#> GSM1232992 2 0.0000 9.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232993 6 0.3252 7.46e-01 0.000 0.000 0.000 0.108 0.068 0.824
#> GSM1233005 2 0.0146 9.78e-01 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM1233007 6 0.2937 7.49e-01 0.000 0.000 0.000 0.096 0.056 0.848
#> GSM1233010 4 0.4338 5.69e-01 0.000 0.000 0.004 0.716 0.072 0.208
#> GSM1233013 2 0.0146 9.77e-01 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM1233018 2 0.0146 9.77e-01 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM1233019 2 0.0146 9.77e-01 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM1233021 2 0.0146 9.78e-01 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM1233025 4 0.1049 7.31e-01 0.000 0.000 0.032 0.960 0.008 0.000
#> GSM1233029 6 0.1007 7.68e-01 0.000 0.000 0.000 0.000 0.044 0.956
#> GSM1233030 2 0.2740 8.48e-01 0.000 0.864 0.000 0.000 0.076 0.060
#> GSM1233031 6 0.5314 4.78e-01 0.000 0.000 0.000 0.336 0.120 0.544
#> GSM1233032 1 0.3013 8.13e-01 0.844 0.000 0.088 0.000 0.068 0.000
#> GSM1233035 6 0.4585 6.66e-01 0.000 0.000 0.000 0.192 0.116 0.692
#> GSM1233038 1 0.0000 9.14e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233039 6 0.3717 7.22e-01 0.000 0.000 0.000 0.148 0.072 0.780
#> GSM1233042 6 0.3611 7.33e-01 0.000 0.000 0.000 0.108 0.096 0.796
#> GSM1233043 6 0.3611 7.33e-01 0.000 0.000 0.000 0.108 0.096 0.796
#> GSM1233044 4 0.3309 3.70e-01 0.000 0.000 0.280 0.720 0.000 0.000
#> GSM1233046 4 0.2846 7.06e-01 0.000 0.000 0.000 0.856 0.060 0.084
#> GSM1233051 3 0.5625 -8.36e-05 0.000 0.000 0.504 0.164 0.332 0.000
#> GSM1233054 4 0.3043 7.27e-01 0.000 0.000 0.040 0.864 0.040 0.056
#> GSM1233057 6 0.4371 6.80e-01 0.000 0.000 0.000 0.180 0.104 0.716
#> GSM1233060 6 0.4545 6.67e-01 0.000 0.000 0.000 0.192 0.112 0.696
#> GSM1233062 6 0.1700 7.72e-01 0.000 0.000 0.000 0.004 0.080 0.916
#> GSM1233075 6 0.4059 6.86e-01 0.000 0.100 0.000 0.000 0.148 0.752
#> GSM1233078 4 0.4959 3.75e-01 0.000 0.000 0.008 0.616 0.072 0.304
#> GSM1233079 5 0.3971 9.55e-01 0.000 0.000 0.448 0.004 0.548 0.000
#> GSM1233082 4 0.0790 7.36e-01 0.000 0.000 0.032 0.968 0.000 0.000
#> GSM1233083 3 0.5790 -6.48e-01 0.140 0.000 0.464 0.008 0.388 0.000
#> GSM1233091 4 0.2711 7.20e-01 0.000 0.000 0.004 0.872 0.056 0.068
#> GSM1233095 1 0.0000 9.14e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233096 5 0.3971 9.55e-01 0.000 0.000 0.448 0.004 0.548 0.000
#> GSM1233101 3 0.4566 3.75e-03 0.364 0.000 0.596 0.004 0.036 0.000
#> GSM1233105 4 0.1049 7.31e-01 0.000 0.000 0.032 0.960 0.008 0.000
#> GSM1233117 2 0.1845 9.11e-01 0.000 0.920 0.000 0.000 0.028 0.052
#> GSM1233118 2 0.1845 9.11e-01 0.000 0.920 0.000 0.000 0.028 0.052
#> GSM1233001 2 0.0291 9.75e-01 0.000 0.992 0.000 0.000 0.004 0.004
#> GSM1233006 6 0.2613 7.47e-01 0.000 0.012 0.000 0.000 0.140 0.848
#> GSM1233008 6 0.2859 7.39e-01 0.000 0.016 0.000 0.000 0.156 0.828
#> GSM1233009 6 0.4425 6.42e-01 0.000 0.176 0.000 0.000 0.112 0.712
#> GSM1233017 2 0.1930 9.07e-01 0.000 0.916 0.000 0.000 0.036 0.048
#> GSM1233020 2 0.0146 9.77e-01 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM1233022 6 0.1204 7.66e-01 0.000 0.000 0.000 0.000 0.056 0.944
#> GSM1233026 6 0.5313 4.73e-01 0.000 0.000 0.000 0.324 0.124 0.552
#> GSM1233028 6 0.5380 3.46e-01 0.000 0.000 0.000 0.384 0.116 0.500
#> GSM1233034 6 0.2631 7.44e-01 0.000 0.008 0.000 0.000 0.152 0.840
#> GSM1233040 1 0.2432 8.71e-01 0.876 0.000 0.100 0.000 0.024 0.000
#> GSM1233048 1 0.2909 8.48e-01 0.836 0.000 0.136 0.000 0.028 0.000
#> GSM1233056 1 0.0458 9.12e-01 0.984 0.000 0.000 0.000 0.016 0.000
#> GSM1233058 6 0.5344 4.18e-01 0.000 0.000 0.000 0.348 0.120 0.532
#> GSM1233059 1 0.0000 9.14e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233066 6 0.4613 6.58e-01 0.000 0.000 0.000 0.196 0.116 0.688
#> GSM1233071 6 0.1204 7.66e-01 0.000 0.000 0.000 0.000 0.056 0.944
#> GSM1233074 6 0.3681 7.10e-01 0.000 0.064 0.000 0.000 0.156 0.780
#> GSM1233076 6 0.0891 7.71e-01 0.000 0.000 0.000 0.008 0.024 0.968
#> GSM1233080 1 0.0000 9.14e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233088 6 0.4601 6.60e-01 0.000 0.000 0.000 0.200 0.112 0.688
#> GSM1233090 1 0.0000 9.14e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233092 6 0.2613 7.47e-01 0.000 0.012 0.000 0.000 0.140 0.848
#> GSM1233094 6 0.3680 7.24e-01 0.000 0.000 0.000 0.144 0.072 0.784
#> GSM1233097 6 0.3412 7.34e-01 0.000 0.000 0.000 0.128 0.064 0.808
#> GSM1233100 4 0.0665 7.44e-01 0.000 0.000 0.008 0.980 0.008 0.004
#> GSM1233104 6 0.1984 7.65e-01 0.000 0.000 0.000 0.056 0.032 0.912
#> GSM1233106 4 0.0881 7.45e-01 0.000 0.000 0.012 0.972 0.008 0.008
#> GSM1233111 5 0.3966 9.54e-01 0.000 0.000 0.444 0.004 0.552 0.000
#> GSM1233122 2 0.0000 9.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233146 6 0.4496 6.72e-01 0.000 0.000 0.000 0.180 0.116 0.704
#> GSM1232994 2 0.0146 9.78e-01 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM1232996 2 0.0146 9.77e-01 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM1232997 6 0.2669 7.43e-01 0.000 0.008 0.000 0.000 0.156 0.836
#> GSM1232998 2 0.0146 9.78e-01 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM1232999 6 0.2473 7.49e-01 0.000 0.008 0.000 0.000 0.136 0.856
#> GSM1233000 6 0.2653 7.46e-01 0.000 0.012 0.000 0.000 0.144 0.844
#> GSM1233004 3 0.4720 5.37e-01 0.000 0.000 0.624 0.304 0.072 0.000
#> GSM1233011 6 0.1644 7.68e-01 0.000 0.000 0.000 0.040 0.028 0.932
#> GSM1233012 6 0.3102 7.33e-01 0.000 0.028 0.000 0.000 0.156 0.816
#> GSM1233023 6 0.2859 7.39e-01 0.000 0.016 0.000 0.000 0.156 0.828
#> GSM1233027 2 0.0363 9.73e-01 0.000 0.988 0.000 0.000 0.000 0.012
#> GSM1233033 5 0.3789 8.11e-01 0.000 0.000 0.332 0.008 0.660 0.000
#> GSM1233036 6 0.3520 7.43e-01 0.000 0.000 0.000 0.096 0.100 0.804
#> GSM1233037 6 0.5279 4.67e-01 0.000 0.000 0.000 0.324 0.120 0.556
#> GSM1233041 1 0.0458 9.12e-01 0.984 0.000 0.000 0.000 0.016 0.000
#> GSM1233045 6 0.3468 7.33e-01 0.000 0.000 0.000 0.128 0.068 0.804
#> GSM1233047 3 0.3841 4.98e-01 0.000 0.000 0.616 0.380 0.004 0.000
#> GSM1233050 1 0.2909 8.48e-01 0.836 0.000 0.136 0.000 0.028 0.000
#> GSM1233052 3 0.2871 5.06e-01 0.000 0.000 0.804 0.192 0.004 0.000
#> GSM1233053 3 0.1867 3.81e-01 0.000 0.000 0.916 0.064 0.020 0.000
#> GSM1233055 1 0.3101 8.38e-01 0.820 0.000 0.148 0.000 0.032 0.000
#> GSM1233061 4 0.2988 7.08e-01 0.000 0.000 0.004 0.852 0.060 0.084
#> GSM1233063 5 0.3971 9.55e-01 0.000 0.000 0.448 0.004 0.548 0.000
#> GSM1233065 2 0.0146 9.78e-01 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM1233070 6 0.2653 7.46e-01 0.000 0.012 0.000 0.000 0.144 0.844
#> GSM1233077 6 0.0937 7.70e-01 0.000 0.000 0.000 0.000 0.040 0.960
#> GSM1233081 4 0.1141 7.25e-01 0.000 0.000 0.052 0.948 0.000 0.000
#> GSM1233084 1 0.0000 9.14e-01 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233087 4 0.0790 7.38e-01 0.000 0.000 0.032 0.968 0.000 0.000
#> GSM1233089 2 0.0146 9.78e-01 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM1233099 4 0.2711 7.20e-01 0.000 0.000 0.004 0.872 0.056 0.068
#> GSM1233112 3 0.1769 3.77e-01 0.004 0.000 0.924 0.060 0.012 0.000
#> GSM1233085 3 0.3647 5.28e-01 0.000 0.000 0.640 0.360 0.000 0.000
#> GSM1233098 6 0.4732 6.15e-01 0.000 0.172 0.000 0.000 0.148 0.680
#> GSM1233114 5 0.3966 9.54e-01 0.000 0.000 0.444 0.004 0.552 0.000
#> GSM1233119 4 0.4337 5.81e-01 0.000 0.000 0.008 0.724 0.068 0.200
#> GSM1233129 6 0.2768 7.41e-01 0.000 0.012 0.000 0.000 0.156 0.832
#> GSM1233132 3 0.3695 4.78e-01 0.000 0.000 0.624 0.376 0.000 0.000
#> GSM1233139 6 0.2513 7.48e-01 0.000 0.008 0.000 0.000 0.140 0.852
#> GSM1233143 6 0.3139 7.33e-01 0.000 0.032 0.000 0.000 0.152 0.816
#> GSM1233145 1 0.5940 -1.22e-01 0.440 0.000 0.332 0.000 0.228 0.000
#> GSM1233067 2 0.0146 9.78e-01 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM1233069 6 0.3806 7.03e-01 0.000 0.076 0.000 0.000 0.152 0.772
#> GSM1233072 2 0.0260 9.76e-01 0.000 0.992 0.000 0.000 0.000 0.008
#> GSM1233086 6 0.1845 7.66e-01 0.000 0.000 0.000 0.052 0.028 0.920
#> GSM1233102 3 0.5082 -5.58e-01 0.000 0.000 0.512 0.080 0.408 0.000
#> GSM1233103 6 0.4596 6.64e-01 0.000 0.000 0.000 0.188 0.120 0.692
#> GSM1233107 6 0.4585 6.62e-01 0.000 0.000 0.000 0.192 0.116 0.692
#> GSM1233108 5 0.3971 9.55e-01 0.000 0.000 0.448 0.004 0.548 0.000
#> GSM1233109 3 0.5701 3.34e-01 0.000 0.000 0.524 0.228 0.248 0.000
#> GSM1233110 6 0.4963 6.04e-01 0.000 0.000 0.000 0.240 0.124 0.636
#> GSM1233113 2 0.0146 9.77e-01 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM1233116 2 0.0146 9.77e-01 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM1233120 4 0.1082 7.38e-01 0.000 0.000 0.040 0.956 0.000 0.004
#> GSM1233121 6 0.1921 7.66e-01 0.000 0.000 0.000 0.052 0.032 0.916
#> GSM1233123 6 0.4944 6.11e-01 0.000 0.000 0.000 0.224 0.132 0.644
#> GSM1233124 6 0.4026 7.05e-01 0.000 0.000 0.000 0.160 0.088 0.752
#> GSM1233125 5 0.4815 8.68e-01 0.048 0.000 0.396 0.004 0.552 0.000
#> GSM1233126 6 0.1204 7.72e-01 0.000 0.000 0.000 0.000 0.056 0.944
#> GSM1233127 6 0.3139 7.33e-01 0.000 0.032 0.000 0.000 0.152 0.816
#> GSM1233128 1 0.0458 9.12e-01 0.984 0.000 0.000 0.000 0.016 0.000
#> GSM1233130 6 0.4596 6.64e-01 0.000 0.000 0.000 0.188 0.120 0.692
#> GSM1233131 4 0.1349 7.20e-01 0.000 0.000 0.056 0.940 0.004 0.000
#> GSM1233133 3 0.3899 4.48e-01 0.000 0.000 0.592 0.404 0.004 0.000
#> GSM1233134 6 0.2945 7.37e-01 0.000 0.020 0.000 0.000 0.156 0.824
#> GSM1233135 6 0.2165 7.56e-01 0.000 0.008 0.000 0.000 0.108 0.884
#> GSM1233136 6 0.1075 7.70e-01 0.000 0.000 0.000 0.000 0.048 0.952
#> GSM1233137 4 0.3774 -1.44e-04 0.000 0.000 0.408 0.592 0.000 0.000
#> GSM1233138 6 0.2165 7.56e-01 0.000 0.008 0.000 0.000 0.108 0.884
#> GSM1233140 5 0.4229 9.35e-01 0.000 0.000 0.436 0.016 0.548 0.000
#> GSM1233141 2 0.0000 9.78e-01 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233142 2 0.0146 9.77e-01 0.000 0.996 0.000 0.000 0.004 0.000
#> GSM1233144 4 0.3717 7.17e-02 0.000 0.000 0.384 0.616 0.000 0.000
#> GSM1233147 6 0.2730 7.43e-01 0.000 0.012 0.000 0.000 0.152 0.836
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> ATC:hclust 152 0.798 0.901 0.8243 2
#> ATC:hclust 133 0.109 0.229 0.1149 3
#> ATC:hclust 150 0.179 0.355 0.0248 4
#> ATC:hclust 143 0.231 0.621 0.0817 5
#> ATC:hclust 132 0.183 0.634 0.2077 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 51941 rows and 156 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 1.000 0.985 0.994 0.4743 0.524 0.524
#> 3 3 1.000 0.954 0.984 0.3956 0.679 0.458
#> 4 4 0.731 0.653 0.853 0.1134 0.784 0.477
#> 5 5 0.863 0.840 0.921 0.0695 0.825 0.466
#> 6 6 0.871 0.862 0.918 0.0502 0.889 0.545
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
#> GSM1232995 2 0.000 1.000 0.000 1.000
#> GSM1233002 1 0.000 0.985 1.000 0.000
#> GSM1233003 1 0.000 0.985 1.000 0.000
#> GSM1233014 2 0.000 1.000 0.000 1.000
#> GSM1233015 1 0.000 0.985 1.000 0.000
#> GSM1233016 2 0.000 1.000 0.000 1.000
#> GSM1233024 2 0.000 1.000 0.000 1.000
#> GSM1233049 1 0.000 0.985 1.000 0.000
#> GSM1233064 2 0.000 1.000 0.000 1.000
#> GSM1233068 2 0.000 1.000 0.000 1.000
#> GSM1233073 2 0.000 1.000 0.000 1.000
#> GSM1233093 1 0.000 0.985 1.000 0.000
#> GSM1233115 1 0.000 0.985 1.000 0.000
#> GSM1232992 2 0.000 1.000 0.000 1.000
#> GSM1232993 2 0.000 1.000 0.000 1.000
#> GSM1233005 2 0.000 1.000 0.000 1.000
#> GSM1233007 2 0.000 1.000 0.000 1.000
#> GSM1233010 1 0.000 0.985 1.000 0.000
#> GSM1233013 2 0.000 1.000 0.000 1.000
#> GSM1233018 2 0.000 1.000 0.000 1.000
#> GSM1233019 2 0.000 1.000 0.000 1.000
#> GSM1233021 2 0.000 1.000 0.000 1.000
#> GSM1233025 1 0.000 0.985 1.000 0.000
#> GSM1233029 2 0.000 1.000 0.000 1.000
#> GSM1233030 2 0.000 1.000 0.000 1.000
#> GSM1233031 2 0.000 1.000 0.000 1.000
#> GSM1233032 1 0.000 0.985 1.000 0.000
#> GSM1233035 2 0.000 1.000 0.000 1.000
#> GSM1233038 1 0.000 0.985 1.000 0.000
#> GSM1233039 2 0.000 1.000 0.000 1.000
#> GSM1233042 2 0.000 1.000 0.000 1.000
#> GSM1233043 2 0.000 1.000 0.000 1.000
#> GSM1233044 1 0.000 0.985 1.000 0.000
#> GSM1233046 1 0.978 0.307 0.588 0.412
#> GSM1233051 1 0.000 0.985 1.000 0.000
#> GSM1233054 1 0.000 0.985 1.000 0.000
#> GSM1233057 2 0.000 1.000 0.000 1.000
#> GSM1233060 2 0.000 1.000 0.000 1.000
#> GSM1233062 2 0.000 1.000 0.000 1.000
#> GSM1233075 2 0.000 1.000 0.000 1.000
#> GSM1233078 2 0.000 1.000 0.000 1.000
#> GSM1233079 1 0.000 0.985 1.000 0.000
#> GSM1233082 1 0.000 0.985 1.000 0.000
#> GSM1233083 1 0.000 0.985 1.000 0.000
#> GSM1233091 2 0.000 1.000 0.000 1.000
#> GSM1233095 1 0.000 0.985 1.000 0.000
#> GSM1233096 1 0.000 0.985 1.000 0.000
#> GSM1233101 1 0.000 0.985 1.000 0.000
#> GSM1233105 1 0.000 0.985 1.000 0.000
#> GSM1233117 2 0.000 1.000 0.000 1.000
#> GSM1233118 2 0.000 1.000 0.000 1.000
#> GSM1233001 2 0.000 1.000 0.000 1.000
#> GSM1233006 2 0.000 1.000 0.000 1.000
#> GSM1233008 2 0.000 1.000 0.000 1.000
#> GSM1233009 2 0.000 1.000 0.000 1.000
#> GSM1233017 2 0.000 1.000 0.000 1.000
#> GSM1233020 2 0.000 1.000 0.000 1.000
#> GSM1233022 2 0.000 1.000 0.000 1.000
#> GSM1233026 2 0.000 1.000 0.000 1.000
#> GSM1233028 2 0.000 1.000 0.000 1.000
#> GSM1233034 2 0.000 1.000 0.000 1.000
#> GSM1233040 1 0.000 0.985 1.000 0.000
#> GSM1233048 1 0.000 0.985 1.000 0.000
#> GSM1233056 1 0.000 0.985 1.000 0.000
#> GSM1233058 2 0.000 1.000 0.000 1.000
#> GSM1233059 1 0.000 0.985 1.000 0.000
#> GSM1233066 2 0.000 1.000 0.000 1.000
#> GSM1233071 2 0.000 1.000 0.000 1.000
#> GSM1233074 2 0.000 1.000 0.000 1.000
#> GSM1233076 2 0.000 1.000 0.000 1.000
#> GSM1233080 1 0.000 0.985 1.000 0.000
#> GSM1233088 2 0.000 1.000 0.000 1.000
#> GSM1233090 1 0.000 0.985 1.000 0.000
#> GSM1233092 2 0.000 1.000 0.000 1.000
#> GSM1233094 2 0.000 1.000 0.000 1.000
#> GSM1233097 2 0.000 1.000 0.000 1.000
#> GSM1233100 1 0.000 0.985 1.000 0.000
#> GSM1233104 2 0.000 1.000 0.000 1.000
#> GSM1233106 1 0.000 0.985 1.000 0.000
#> GSM1233111 1 0.000 0.985 1.000 0.000
#> GSM1233122 2 0.000 1.000 0.000 1.000
#> GSM1233146 2 0.000 1.000 0.000 1.000
#> GSM1232994 2 0.000 1.000 0.000 1.000
#> GSM1232996 2 0.000 1.000 0.000 1.000
#> GSM1232997 2 0.000 1.000 0.000 1.000
#> GSM1232998 2 0.000 1.000 0.000 1.000
#> GSM1232999 2 0.000 1.000 0.000 1.000
#> GSM1233000 2 0.000 1.000 0.000 1.000
#> GSM1233004 1 0.000 0.985 1.000 0.000
#> GSM1233011 2 0.000 1.000 0.000 1.000
#> GSM1233012 2 0.000 1.000 0.000 1.000
#> GSM1233023 2 0.000 1.000 0.000 1.000
#> GSM1233027 2 0.000 1.000 0.000 1.000
#> GSM1233033 1 0.000 0.985 1.000 0.000
#> GSM1233036 2 0.000 1.000 0.000 1.000
#> GSM1233037 2 0.000 1.000 0.000 1.000
#> GSM1233041 1 0.000 0.985 1.000 0.000
#> GSM1233045 2 0.000 1.000 0.000 1.000
#> GSM1233047 1 0.000 0.985 1.000 0.000
#> GSM1233050 1 0.000 0.985 1.000 0.000
#> GSM1233052 1 0.000 0.985 1.000 0.000
#> GSM1233053 1 0.000 0.985 1.000 0.000
#> GSM1233055 1 0.000 0.985 1.000 0.000
#> GSM1233061 2 0.000 1.000 0.000 1.000
#> GSM1233063 1 0.000 0.985 1.000 0.000
#> GSM1233065 2 0.000 1.000 0.000 1.000
#> GSM1233070 2 0.000 1.000 0.000 1.000
#> GSM1233077 2 0.000 1.000 0.000 1.000
#> GSM1233081 1 0.000 0.985 1.000 0.000
#> GSM1233084 1 0.000 0.985 1.000 0.000
#> GSM1233087 1 0.000 0.985 1.000 0.000
#> GSM1233089 2 0.000 1.000 0.000 1.000
#> GSM1233099 1 0.000 0.985 1.000 0.000
#> GSM1233112 1 0.000 0.985 1.000 0.000
#> GSM1233085 1 0.000 0.985 1.000 0.000
#> GSM1233098 2 0.000 1.000 0.000 1.000
#> GSM1233114 1 0.000 0.985 1.000 0.000
#> GSM1233119 1 0.992 0.198 0.552 0.448
#> GSM1233129 2 0.000 1.000 0.000 1.000
#> GSM1233132 1 0.000 0.985 1.000 0.000
#> GSM1233139 2 0.000 1.000 0.000 1.000
#> GSM1233143 2 0.000 1.000 0.000 1.000
#> GSM1233145 1 0.000 0.985 1.000 0.000
#> GSM1233067 2 0.000 1.000 0.000 1.000
#> GSM1233069 2 0.000 1.000 0.000 1.000
#> GSM1233072 2 0.000 1.000 0.000 1.000
#> GSM1233086 2 0.000 1.000 0.000 1.000
#> GSM1233102 1 0.000 0.985 1.000 0.000
#> GSM1233103 2 0.000 1.000 0.000 1.000
#> GSM1233107 2 0.000 1.000 0.000 1.000
#> GSM1233108 1 0.000 0.985 1.000 0.000
#> GSM1233109 1 0.000 0.985 1.000 0.000
#> GSM1233110 2 0.000 1.000 0.000 1.000
#> GSM1233113 2 0.000 1.000 0.000 1.000
#> GSM1233116 2 0.000 1.000 0.000 1.000
#> GSM1233120 1 0.000 0.985 1.000 0.000
#> GSM1233121 2 0.000 1.000 0.000 1.000
#> GSM1233123 2 0.000 1.000 0.000 1.000
#> GSM1233124 2 0.000 1.000 0.000 1.000
#> GSM1233125 1 0.000 0.985 1.000 0.000
#> GSM1233126 2 0.000 1.000 0.000 1.000
#> GSM1233127 2 0.000 1.000 0.000 1.000
#> GSM1233128 1 0.000 0.985 1.000 0.000
#> GSM1233130 2 0.000 1.000 0.000 1.000
#> GSM1233131 1 0.000 0.985 1.000 0.000
#> GSM1233133 1 0.000 0.985 1.000 0.000
#> GSM1233134 2 0.000 1.000 0.000 1.000
#> GSM1233135 2 0.000 1.000 0.000 1.000
#> GSM1233136 2 0.000 1.000 0.000 1.000
#> GSM1233137 1 0.000 0.985 1.000 0.000
#> GSM1233138 2 0.000 1.000 0.000 1.000
#> GSM1233140 1 0.000 0.985 1.000 0.000
#> GSM1233141 2 0.000 1.000 0.000 1.000
#> GSM1233142 2 0.000 1.000 0.000 1.000
#> GSM1233144 1 0.000 0.985 1.000 0.000
#> GSM1233147 2 0.000 1.000 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233002 2 0.6095 0.340 0.392 0.608 0.000
#> GSM1233003 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233014 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233015 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233016 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233024 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233049 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233064 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233068 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233073 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233093 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233115 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1232992 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1232993 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233005 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233007 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233010 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233013 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233018 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233019 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233021 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233025 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233029 3 0.4750 0.713 0.000 0.216 0.784
#> GSM1233030 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233031 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233032 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233035 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233038 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233039 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233042 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233043 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233044 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233046 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233051 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233054 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233057 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233060 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233062 2 0.6215 0.225 0.000 0.572 0.428
#> GSM1233075 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233078 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233079 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233082 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233083 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233091 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233095 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233096 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233101 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233105 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233117 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233118 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233001 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233006 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233008 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233009 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233017 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233020 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233022 3 0.6295 0.110 0.000 0.472 0.528
#> GSM1233026 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233028 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233034 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233040 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233048 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233056 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233058 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233059 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233066 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233071 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233074 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233076 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233080 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233088 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233090 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233092 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233094 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233097 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233100 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233104 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233106 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233111 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233122 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233146 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1232994 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1232996 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1232997 3 0.0747 0.959 0.000 0.016 0.984
#> GSM1232998 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1232999 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233000 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233004 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233011 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233012 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233023 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233027 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233033 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233036 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233037 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233041 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233045 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233047 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233050 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233052 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233053 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233055 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233061 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233063 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233065 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233070 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233077 3 0.6280 0.151 0.000 0.460 0.540
#> GSM1233081 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233084 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233087 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233089 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233099 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233112 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233085 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233098 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233114 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233119 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233129 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233132 1 0.3752 0.825 0.856 0.144 0.000
#> GSM1233139 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233143 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233145 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233067 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233069 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233072 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233086 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233102 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233103 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233107 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233108 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233109 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233110 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233113 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233116 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233120 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233121 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233123 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233124 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233125 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233126 2 0.0237 0.974 0.000 0.996 0.004
#> GSM1233127 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233128 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233130 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233131 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233133 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233134 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233135 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233136 2 0.6235 0.199 0.000 0.564 0.436
#> GSM1233137 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233138 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233140 1 0.0000 0.996 1.000 0.000 0.000
#> GSM1233141 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233142 3 0.0000 0.975 0.000 0.000 1.000
#> GSM1233144 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233147 3 0.0000 0.975 0.000 0.000 1.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233002 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233003 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233014 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233015 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233016 4 0.4804 0.4935 0.000 0.000 0.384 0.616
#> GSM1233024 2 0.4406 0.6447 0.000 0.700 0.000 0.300
#> GSM1233049 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233064 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233068 4 0.4730 0.5182 0.000 0.000 0.364 0.636
#> GSM1233073 4 0.4996 0.3451 0.000 0.000 0.484 0.516
#> GSM1233093 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233115 3 0.4382 0.5007 0.296 0.000 0.704 0.000
#> GSM1232992 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1232993 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233005 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233007 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233010 3 0.4955 -0.1953 0.000 0.000 0.556 0.444
#> GSM1233013 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233018 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233019 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233021 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233025 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233029 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233030 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233031 4 0.4996 0.3451 0.000 0.000 0.484 0.516
#> GSM1233032 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233035 4 0.2921 0.7113 0.000 0.000 0.140 0.860
#> GSM1233038 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233039 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233042 4 0.1211 0.7576 0.000 0.000 0.040 0.960
#> GSM1233043 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233044 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233046 4 0.4998 0.3360 0.000 0.000 0.488 0.512
#> GSM1233051 3 0.4843 0.3734 0.396 0.000 0.604 0.000
#> GSM1233054 3 0.3266 0.5322 0.000 0.000 0.832 0.168
#> GSM1233057 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233060 4 0.3569 0.6755 0.000 0.000 0.196 0.804
#> GSM1233062 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233075 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233078 4 0.4996 0.3451 0.000 0.000 0.484 0.516
#> GSM1233079 3 0.4996 0.2168 0.484 0.000 0.516 0.000
#> GSM1233082 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233083 3 0.4999 0.1942 0.492 0.000 0.508 0.000
#> GSM1233091 4 0.4996 0.3451 0.000 0.000 0.484 0.516
#> GSM1233095 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233096 3 0.4996 0.2168 0.484 0.000 0.516 0.000
#> GSM1233101 1 0.2011 0.8642 0.920 0.000 0.080 0.000
#> GSM1233105 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233117 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233118 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233001 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233006 4 0.4454 0.3140 0.000 0.308 0.000 0.692
#> GSM1233008 2 0.3172 0.7888 0.000 0.840 0.000 0.160
#> GSM1233009 2 0.1022 0.8769 0.000 0.968 0.000 0.032
#> GSM1233017 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233020 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233022 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233026 4 0.4989 0.3656 0.000 0.000 0.472 0.528
#> GSM1233028 4 0.4996 0.3451 0.000 0.000 0.484 0.516
#> GSM1233034 4 0.4985 -0.1912 0.000 0.468 0.000 0.532
#> GSM1233040 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233048 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233056 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233058 4 0.4989 0.3653 0.000 0.000 0.472 0.528
#> GSM1233059 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233066 4 0.4193 0.6187 0.000 0.000 0.268 0.732
#> GSM1233071 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233074 2 0.4040 0.7092 0.000 0.752 0.000 0.248
#> GSM1233076 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233080 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233088 4 0.3837 0.6550 0.000 0.000 0.224 0.776
#> GSM1233090 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233092 2 0.4996 0.3027 0.000 0.516 0.000 0.484
#> GSM1233094 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233097 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233100 3 0.3311 0.5253 0.000 0.000 0.828 0.172
#> GSM1233104 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233106 3 0.0336 0.7160 0.000 0.000 0.992 0.008
#> GSM1233111 3 0.4996 0.2168 0.484 0.000 0.516 0.000
#> GSM1233122 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233146 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1232994 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1232996 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1232997 4 0.0188 0.7693 0.000 0.004 0.000 0.996
#> GSM1232998 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1232999 4 0.0188 0.7693 0.000 0.004 0.000 0.996
#> GSM1233000 2 0.4103 0.7004 0.000 0.744 0.000 0.256
#> GSM1233004 3 0.1302 0.7000 0.044 0.000 0.956 0.000
#> GSM1233011 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233012 2 0.4916 0.4374 0.000 0.576 0.000 0.424
#> GSM1233023 2 0.4888 0.4610 0.000 0.588 0.000 0.412
#> GSM1233027 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233033 3 0.4996 0.2168 0.484 0.000 0.516 0.000
#> GSM1233036 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233037 4 0.4994 0.3521 0.000 0.000 0.480 0.520
#> GSM1233041 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233045 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233047 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233050 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233052 3 0.4193 0.5303 0.268 0.000 0.732 0.000
#> GSM1233053 3 0.4948 0.3013 0.440 0.000 0.560 0.000
#> GSM1233055 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233061 4 0.4996 0.3451 0.000 0.000 0.484 0.516
#> GSM1233063 3 0.4996 0.2168 0.484 0.000 0.516 0.000
#> GSM1233065 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233070 4 0.4961 -0.1262 0.000 0.448 0.000 0.552
#> GSM1233077 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233081 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233084 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233087 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233089 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233099 3 0.3400 0.5112 0.000 0.000 0.820 0.180
#> GSM1233112 3 0.4996 0.2168 0.484 0.000 0.516 0.000
#> GSM1233085 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233098 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233114 3 0.4996 0.2168 0.484 0.000 0.516 0.000
#> GSM1233119 3 0.4992 -0.2787 0.000 0.000 0.524 0.476
#> GSM1233129 2 0.5000 0.2698 0.000 0.504 0.000 0.496
#> GSM1233132 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233139 4 0.4981 -0.1786 0.000 0.464 0.000 0.536
#> GSM1233143 2 0.3975 0.7174 0.000 0.760 0.000 0.240
#> GSM1233145 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233067 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233069 2 0.4193 0.6866 0.000 0.732 0.000 0.268
#> GSM1233072 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233086 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233102 3 0.4972 0.2728 0.456 0.000 0.544 0.000
#> GSM1233103 4 0.2345 0.7317 0.000 0.000 0.100 0.900
#> GSM1233107 4 0.3975 0.6421 0.000 0.000 0.240 0.760
#> GSM1233108 3 0.4996 0.2168 0.484 0.000 0.516 0.000
#> GSM1233109 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233110 4 0.4564 0.5597 0.000 0.000 0.328 0.672
#> GSM1233113 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233116 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233120 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233121 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233123 4 0.4356 0.5968 0.000 0.000 0.292 0.708
#> GSM1233124 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233125 1 0.4972 -0.0941 0.544 0.000 0.456 0.000
#> GSM1233126 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233127 2 0.1211 0.8726 0.000 0.960 0.000 0.040
#> GSM1233128 1 0.0000 0.9630 1.000 0.000 0.000 0.000
#> GSM1233130 4 0.3074 0.7048 0.000 0.000 0.152 0.848
#> GSM1233131 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233133 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233134 2 0.4999 0.2811 0.000 0.508 0.000 0.492
#> GSM1233135 4 0.4916 -0.0436 0.000 0.424 0.000 0.576
#> GSM1233136 4 0.0000 0.7715 0.000 0.000 0.000 1.000
#> GSM1233137 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233138 4 0.4624 0.2307 0.000 0.340 0.000 0.660
#> GSM1233140 3 0.4746 0.4145 0.368 0.000 0.632 0.000
#> GSM1233141 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233142 2 0.0000 0.8923 0.000 1.000 0.000 0.000
#> GSM1233144 3 0.0000 0.7211 0.000 0.000 1.000 0.000
#> GSM1233147 4 0.4925 -0.0592 0.000 0.428 0.000 0.572
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233002 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233003 5 0.1121 0.9487 0.000 0.000 0.044 0.000 0.956
#> GSM1233014 3 0.2605 0.8289 0.000 0.000 0.852 0.148 0.000
#> GSM1233015 4 0.4074 0.2888 0.364 0.000 0.000 0.636 0.000
#> GSM1233016 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233024 3 0.1478 0.8918 0.000 0.064 0.936 0.000 0.000
#> GSM1233049 5 0.0000 0.9577 0.000 0.000 0.000 0.000 1.000
#> GSM1233064 4 0.4268 0.1825 0.000 0.000 0.444 0.556 0.000
#> GSM1233068 4 0.0290 0.8584 0.000 0.000 0.008 0.992 0.000
#> GSM1233073 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233093 5 0.0000 0.9577 0.000 0.000 0.000 0.000 1.000
#> GSM1233115 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1232992 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1232993 3 0.3395 0.7123 0.000 0.000 0.764 0.236 0.000
#> GSM1233005 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233007 3 0.2813 0.8088 0.000 0.000 0.832 0.168 0.000
#> GSM1233010 4 0.1197 0.8248 0.048 0.000 0.000 0.952 0.000
#> GSM1233013 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233018 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233019 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233021 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233025 4 0.4291 -0.0594 0.464 0.000 0.000 0.536 0.000
#> GSM1233029 3 0.1341 0.8896 0.000 0.000 0.944 0.056 0.000
#> GSM1233030 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233031 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233032 5 0.1121 0.9487 0.000 0.000 0.044 0.000 0.956
#> GSM1233035 4 0.0290 0.8584 0.000 0.000 0.008 0.992 0.000
#> GSM1233038 5 0.0000 0.9577 0.000 0.000 0.000 0.000 1.000
#> GSM1233039 4 0.3707 0.5645 0.000 0.000 0.284 0.716 0.000
#> GSM1233042 4 0.1410 0.8277 0.000 0.000 0.060 0.940 0.000
#> GSM1233043 4 0.4302 0.0511 0.000 0.000 0.480 0.520 0.000
#> GSM1233044 1 0.3932 0.5962 0.672 0.000 0.000 0.328 0.000
#> GSM1233046 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233051 1 0.0404 0.9113 0.988 0.000 0.012 0.000 0.000
#> GSM1233054 4 0.1197 0.8248 0.048 0.000 0.000 0.952 0.000
#> GSM1233057 4 0.3661 0.5778 0.000 0.000 0.276 0.724 0.000
#> GSM1233060 4 0.0290 0.8584 0.000 0.000 0.008 0.992 0.000
#> GSM1233062 3 0.1341 0.8896 0.000 0.000 0.944 0.056 0.000
#> GSM1233075 2 0.2179 0.8653 0.000 0.888 0.112 0.000 0.000
#> GSM1233078 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233079 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233082 1 0.2891 0.8020 0.824 0.000 0.000 0.176 0.000
#> GSM1233083 1 0.1341 0.8873 0.944 0.000 0.056 0.000 0.000
#> GSM1233091 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233095 5 0.0000 0.9577 0.000 0.000 0.000 0.000 1.000
#> GSM1233096 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233101 5 0.5406 0.1265 0.464 0.000 0.056 0.000 0.480
#> GSM1233105 1 0.2891 0.8020 0.824 0.000 0.000 0.176 0.000
#> GSM1233117 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233118 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233001 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233006 3 0.1568 0.8958 0.000 0.036 0.944 0.020 0.000
#> GSM1233008 3 0.2179 0.8588 0.000 0.112 0.888 0.000 0.000
#> GSM1233009 3 0.3966 0.5271 0.000 0.336 0.664 0.000 0.000
#> GSM1233017 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233020 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233022 3 0.1341 0.8896 0.000 0.000 0.944 0.056 0.000
#> GSM1233026 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233028 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233034 3 0.1341 0.8949 0.000 0.056 0.944 0.000 0.000
#> GSM1233040 5 0.1121 0.9487 0.000 0.000 0.044 0.000 0.956
#> GSM1233048 5 0.2209 0.9230 0.032 0.000 0.056 0.000 0.912
#> GSM1233056 5 0.0000 0.9577 0.000 0.000 0.000 0.000 1.000
#> GSM1233058 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233059 5 0.0000 0.9577 0.000 0.000 0.000 0.000 1.000
#> GSM1233066 4 0.0290 0.8584 0.000 0.000 0.008 0.992 0.000
#> GSM1233071 3 0.1341 0.8896 0.000 0.000 0.944 0.056 0.000
#> GSM1233074 3 0.1792 0.8805 0.000 0.084 0.916 0.000 0.000
#> GSM1233076 3 0.2732 0.8187 0.000 0.000 0.840 0.160 0.000
#> GSM1233080 5 0.0000 0.9577 0.000 0.000 0.000 0.000 1.000
#> GSM1233088 4 0.0290 0.8584 0.000 0.000 0.008 0.992 0.000
#> GSM1233090 5 0.0000 0.9577 0.000 0.000 0.000 0.000 1.000
#> GSM1233092 3 0.1341 0.8949 0.000 0.056 0.944 0.000 0.000
#> GSM1233094 4 0.3999 0.4508 0.000 0.000 0.344 0.656 0.000
#> GSM1233097 4 0.4305 0.0233 0.000 0.000 0.488 0.512 0.000
#> GSM1233100 4 0.1197 0.8248 0.048 0.000 0.000 0.952 0.000
#> GSM1233104 3 0.2230 0.8559 0.000 0.000 0.884 0.116 0.000
#> GSM1233106 4 0.1608 0.8020 0.072 0.000 0.000 0.928 0.000
#> GSM1233111 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233122 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233146 4 0.3336 0.6480 0.000 0.000 0.228 0.772 0.000
#> GSM1232994 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1232996 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1232997 3 0.1341 0.8896 0.000 0.000 0.944 0.056 0.000
#> GSM1232998 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1232999 3 0.1341 0.8896 0.000 0.000 0.944 0.056 0.000
#> GSM1233000 3 0.1478 0.8918 0.000 0.064 0.936 0.000 0.000
#> GSM1233004 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233011 3 0.2813 0.8085 0.000 0.000 0.832 0.168 0.000
#> GSM1233012 3 0.1410 0.8934 0.000 0.060 0.940 0.000 0.000
#> GSM1233023 3 0.1478 0.8918 0.000 0.064 0.936 0.000 0.000
#> GSM1233027 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233033 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233036 3 0.2852 0.8040 0.000 0.000 0.828 0.172 0.000
#> GSM1233037 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233041 5 0.0000 0.9577 0.000 0.000 0.000 0.000 1.000
#> GSM1233045 3 0.4256 0.2294 0.000 0.000 0.564 0.436 0.000
#> GSM1233047 1 0.0404 0.9113 0.988 0.000 0.012 0.000 0.000
#> GSM1233050 5 0.1121 0.9487 0.000 0.000 0.044 0.000 0.956
#> GSM1233052 1 0.1270 0.8898 0.948 0.000 0.052 0.000 0.000
#> GSM1233053 1 0.1270 0.8898 0.948 0.000 0.052 0.000 0.000
#> GSM1233055 5 0.0880 0.9517 0.000 0.000 0.032 0.000 0.968
#> GSM1233061 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233063 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233065 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233070 3 0.1341 0.8949 0.000 0.056 0.944 0.000 0.000
#> GSM1233077 3 0.1341 0.8896 0.000 0.000 0.944 0.056 0.000
#> GSM1233081 1 0.2377 0.8392 0.872 0.000 0.000 0.128 0.000
#> GSM1233084 5 0.0000 0.9577 0.000 0.000 0.000 0.000 1.000
#> GSM1233087 1 0.3983 0.5720 0.660 0.000 0.000 0.340 0.000
#> GSM1233089 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233099 4 0.1197 0.8248 0.048 0.000 0.000 0.952 0.000
#> GSM1233112 1 0.1270 0.8898 0.948 0.000 0.052 0.000 0.000
#> GSM1233085 1 0.0404 0.9113 0.988 0.000 0.012 0.000 0.000
#> GSM1233098 3 0.4262 0.2592 0.000 0.440 0.560 0.000 0.000
#> GSM1233114 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233119 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233129 3 0.1341 0.8949 0.000 0.056 0.944 0.000 0.000
#> GSM1233132 1 0.0566 0.9118 0.984 0.000 0.012 0.004 0.000
#> GSM1233139 3 0.1341 0.8949 0.000 0.056 0.944 0.000 0.000
#> GSM1233143 3 0.1792 0.8805 0.000 0.084 0.916 0.000 0.000
#> GSM1233145 5 0.2153 0.9237 0.040 0.000 0.044 0.000 0.916
#> GSM1233067 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233069 3 0.1671 0.8857 0.000 0.076 0.924 0.000 0.000
#> GSM1233072 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233086 3 0.2280 0.8524 0.000 0.000 0.880 0.120 0.000
#> GSM1233102 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233103 4 0.0404 0.8568 0.000 0.000 0.012 0.988 0.000
#> GSM1233107 4 0.0290 0.8584 0.000 0.000 0.008 0.992 0.000
#> GSM1233108 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233109 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233110 4 0.0000 0.8589 0.000 0.000 0.000 1.000 0.000
#> GSM1233113 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233116 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233120 4 0.3752 0.4683 0.292 0.000 0.000 0.708 0.000
#> GSM1233121 3 0.2605 0.8293 0.000 0.000 0.852 0.148 0.000
#> GSM1233123 4 0.0290 0.8584 0.000 0.000 0.008 0.992 0.000
#> GSM1233124 4 0.4015 0.4418 0.000 0.000 0.348 0.652 0.000
#> GSM1233125 1 0.1502 0.8847 0.940 0.000 0.056 0.000 0.004
#> GSM1233126 3 0.1341 0.8896 0.000 0.000 0.944 0.056 0.000
#> GSM1233127 3 0.3684 0.6373 0.000 0.280 0.720 0.000 0.000
#> GSM1233128 5 0.0000 0.9577 0.000 0.000 0.000 0.000 1.000
#> GSM1233130 4 0.0609 0.8529 0.000 0.000 0.020 0.980 0.000
#> GSM1233131 1 0.3395 0.7362 0.764 0.000 0.000 0.236 0.000
#> GSM1233133 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233134 3 0.1341 0.8949 0.000 0.056 0.944 0.000 0.000
#> GSM1233135 3 0.1341 0.8949 0.000 0.056 0.944 0.000 0.000
#> GSM1233136 3 0.1341 0.8896 0.000 0.000 0.944 0.056 0.000
#> GSM1233137 1 0.3816 0.6368 0.696 0.000 0.000 0.304 0.000
#> GSM1233138 3 0.1568 0.8958 0.000 0.036 0.944 0.020 0.000
#> GSM1233140 1 0.0000 0.9147 1.000 0.000 0.000 0.000 0.000
#> GSM1233141 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233142 2 0.0000 0.9951 0.000 1.000 0.000 0.000 0.000
#> GSM1233144 1 0.3274 0.7551 0.780 0.000 0.000 0.220 0.000
#> GSM1233147 3 0.1522 0.8959 0.000 0.044 0.944 0.012 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233002 4 0.3464 0.3023 0.000 0.000 0.000 0.688 0.312 0.000
#> GSM1233003 1 0.2039 0.9300 0.908 0.000 0.000 0.004 0.072 0.016
#> GSM1233014 6 0.2697 0.7849 0.000 0.000 0.188 0.000 0.000 0.812
#> GSM1233015 4 0.1391 0.8341 0.000 0.000 0.000 0.944 0.016 0.040
#> GSM1233016 6 0.3547 0.3562 0.000 0.000 0.000 0.332 0.000 0.668
#> GSM1233024 3 0.0458 0.9310 0.000 0.000 0.984 0.016 0.000 0.000
#> GSM1233049 1 0.0000 0.9570 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233064 6 0.1327 0.8618 0.000 0.000 0.064 0.000 0.000 0.936
#> GSM1233068 6 0.1501 0.8158 0.000 0.000 0.000 0.076 0.000 0.924
#> GSM1233073 4 0.3547 0.6491 0.000 0.000 0.000 0.668 0.000 0.332
#> GSM1233093 1 0.0000 0.9570 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233115 5 0.1556 0.9193 0.000 0.000 0.000 0.080 0.920 0.000
#> GSM1232992 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232993 6 0.1910 0.8442 0.000 0.000 0.108 0.000 0.000 0.892
#> GSM1233005 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233007 6 0.2597 0.7983 0.000 0.000 0.176 0.000 0.000 0.824
#> GSM1233010 4 0.2300 0.8298 0.000 0.000 0.000 0.856 0.000 0.144
#> GSM1233013 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233018 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233019 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233021 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233025 4 0.0914 0.8279 0.000 0.000 0.000 0.968 0.016 0.016
#> GSM1233029 3 0.1204 0.9032 0.000 0.000 0.944 0.000 0.000 0.056
#> GSM1233030 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233031 4 0.3706 0.5548 0.000 0.000 0.000 0.620 0.000 0.380
#> GSM1233032 1 0.1738 0.9390 0.928 0.000 0.000 0.004 0.052 0.016
#> GSM1233035 6 0.0632 0.8559 0.000 0.000 0.000 0.024 0.000 0.976
#> GSM1233038 1 0.0000 0.9570 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233039 6 0.0713 0.8632 0.000 0.000 0.028 0.000 0.000 0.972
#> GSM1233042 6 0.0717 0.8592 0.000 0.000 0.008 0.016 0.000 0.976
#> GSM1233043 6 0.1444 0.8600 0.000 0.000 0.072 0.000 0.000 0.928
#> GSM1233044 4 0.0909 0.8264 0.000 0.000 0.000 0.968 0.020 0.012
#> GSM1233046 4 0.2969 0.7785 0.000 0.000 0.000 0.776 0.000 0.224
#> GSM1233051 5 0.1327 0.9171 0.000 0.000 0.000 0.064 0.936 0.000
#> GSM1233054 4 0.2135 0.8364 0.000 0.000 0.000 0.872 0.000 0.128
#> GSM1233057 6 0.0937 0.8641 0.000 0.000 0.040 0.000 0.000 0.960
#> GSM1233060 6 0.0632 0.8559 0.000 0.000 0.000 0.024 0.000 0.976
#> GSM1233062 3 0.3483 0.6832 0.000 0.000 0.748 0.016 0.000 0.236
#> GSM1233075 3 0.2941 0.6938 0.000 0.220 0.780 0.000 0.000 0.000
#> GSM1233078 4 0.3023 0.7695 0.000 0.000 0.000 0.768 0.000 0.232
#> GSM1233079 5 0.1501 0.9201 0.000 0.000 0.000 0.076 0.924 0.000
#> GSM1233082 4 0.1007 0.8055 0.000 0.000 0.000 0.956 0.044 0.000
#> GSM1233083 5 0.0725 0.8760 0.000 0.000 0.000 0.012 0.976 0.012
#> GSM1233091 4 0.3499 0.6676 0.000 0.000 0.000 0.680 0.000 0.320
#> GSM1233095 1 0.0000 0.9570 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233096 5 0.1501 0.9201 0.000 0.000 0.000 0.076 0.924 0.000
#> GSM1233101 5 0.2123 0.8321 0.052 0.000 0.000 0.012 0.912 0.024
#> GSM1233105 4 0.1007 0.8055 0.000 0.000 0.000 0.956 0.044 0.000
#> GSM1233117 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233118 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233001 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233006 3 0.0000 0.9350 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233008 3 0.0603 0.9298 0.000 0.004 0.980 0.016 0.000 0.000
#> GSM1233009 3 0.1007 0.9021 0.000 0.044 0.956 0.000 0.000 0.000
#> GSM1233017 2 0.0547 0.9778 0.000 0.980 0.020 0.000 0.000 0.000
#> GSM1233020 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233022 3 0.1141 0.9064 0.000 0.000 0.948 0.000 0.000 0.052
#> GSM1233026 6 0.3823 -0.0108 0.000 0.000 0.000 0.436 0.000 0.564
#> GSM1233028 4 0.3531 0.6556 0.000 0.000 0.000 0.672 0.000 0.328
#> GSM1233034 3 0.0458 0.9310 0.000 0.000 0.984 0.016 0.000 0.000
#> GSM1233040 1 0.1863 0.9356 0.920 0.000 0.000 0.004 0.060 0.016
#> GSM1233048 1 0.3550 0.8261 0.788 0.000 0.000 0.012 0.176 0.024
#> GSM1233056 1 0.0000 0.9570 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233058 6 0.2941 0.6084 0.000 0.000 0.000 0.220 0.000 0.780
#> GSM1233059 1 0.0000 0.9570 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233066 6 0.0713 0.8539 0.000 0.000 0.000 0.028 0.000 0.972
#> GSM1233071 3 0.3330 0.6032 0.000 0.000 0.716 0.000 0.000 0.284
#> GSM1233074 3 0.0603 0.9298 0.000 0.004 0.980 0.016 0.000 0.000
#> GSM1233076 6 0.2730 0.7799 0.000 0.000 0.192 0.000 0.000 0.808
#> GSM1233080 1 0.0000 0.9570 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233088 6 0.0632 0.8559 0.000 0.000 0.000 0.024 0.000 0.976
#> GSM1233090 1 0.0000 0.9570 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233092 3 0.0000 0.9350 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233094 6 0.1141 0.8638 0.000 0.000 0.052 0.000 0.000 0.948
#> GSM1233097 6 0.1501 0.8587 0.000 0.000 0.076 0.000 0.000 0.924
#> GSM1233100 4 0.2135 0.8364 0.000 0.000 0.000 0.872 0.000 0.128
#> GSM1233104 6 0.2697 0.7852 0.000 0.000 0.188 0.000 0.000 0.812
#> GSM1233106 4 0.1501 0.8400 0.000 0.000 0.000 0.924 0.000 0.076
#> GSM1233111 5 0.1501 0.9201 0.000 0.000 0.000 0.076 0.924 0.000
#> GSM1233122 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233146 6 0.0717 0.8612 0.000 0.000 0.016 0.008 0.000 0.976
#> GSM1232994 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232996 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232997 3 0.1003 0.9241 0.000 0.000 0.964 0.016 0.000 0.020
#> GSM1232998 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232999 3 0.0000 0.9350 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233000 3 0.0000 0.9350 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233004 5 0.2964 0.8559 0.000 0.000 0.000 0.204 0.792 0.004
#> GSM1233011 6 0.2562 0.8019 0.000 0.000 0.172 0.000 0.000 0.828
#> GSM1233012 3 0.0000 0.9350 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233023 3 0.0458 0.9310 0.000 0.000 0.984 0.016 0.000 0.000
#> GSM1233027 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233033 5 0.1501 0.9201 0.000 0.000 0.000 0.076 0.924 0.000
#> GSM1233036 6 0.2664 0.8211 0.000 0.000 0.136 0.016 0.000 0.848
#> GSM1233037 6 0.3797 0.0559 0.000 0.000 0.000 0.420 0.000 0.580
#> GSM1233041 1 0.0000 0.9570 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233045 6 0.1556 0.8571 0.000 0.000 0.080 0.000 0.000 0.920
#> GSM1233047 5 0.3349 0.8229 0.000 0.000 0.000 0.244 0.748 0.008
#> GSM1233050 1 0.1863 0.9356 0.920 0.000 0.000 0.004 0.060 0.016
#> GSM1233052 5 0.2212 0.8708 0.000 0.000 0.000 0.112 0.880 0.008
#> GSM1233053 5 0.0972 0.8879 0.000 0.000 0.000 0.028 0.964 0.008
#> GSM1233055 1 0.1801 0.9372 0.924 0.000 0.000 0.004 0.056 0.016
#> GSM1233061 4 0.3499 0.6685 0.000 0.000 0.000 0.680 0.000 0.320
#> GSM1233063 5 0.1501 0.9201 0.000 0.000 0.000 0.076 0.924 0.000
#> GSM1233065 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233070 3 0.0000 0.9350 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233077 3 0.1863 0.8602 0.000 0.000 0.896 0.000 0.000 0.104
#> GSM1233081 4 0.1007 0.8055 0.000 0.000 0.000 0.956 0.044 0.000
#> GSM1233084 1 0.0000 0.9570 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233087 4 0.0806 0.8245 0.000 0.000 0.000 0.972 0.020 0.008
#> GSM1233089 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233099 4 0.2135 0.8364 0.000 0.000 0.000 0.872 0.000 0.128
#> GSM1233112 5 0.0520 0.8838 0.000 0.000 0.000 0.008 0.984 0.008
#> GSM1233085 5 0.3323 0.8268 0.000 0.000 0.000 0.240 0.752 0.008
#> GSM1233098 3 0.1267 0.8860 0.000 0.060 0.940 0.000 0.000 0.000
#> GSM1233114 5 0.1501 0.9201 0.000 0.000 0.000 0.076 0.924 0.000
#> GSM1233119 4 0.2762 0.7996 0.000 0.000 0.000 0.804 0.000 0.196
#> GSM1233129 3 0.0000 0.9350 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233132 5 0.3634 0.7604 0.000 0.000 0.000 0.296 0.696 0.008
#> GSM1233139 3 0.0000 0.9350 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233143 3 0.0146 0.9336 0.000 0.004 0.996 0.000 0.000 0.000
#> GSM1233145 1 0.3855 0.7075 0.704 0.000 0.000 0.004 0.276 0.016
#> GSM1233067 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233069 3 0.0146 0.9336 0.000 0.004 0.996 0.000 0.000 0.000
#> GSM1233072 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233086 6 0.2697 0.7853 0.000 0.000 0.188 0.000 0.000 0.812
#> GSM1233102 5 0.1501 0.9201 0.000 0.000 0.000 0.076 0.924 0.000
#> GSM1233103 6 0.0692 0.8577 0.000 0.000 0.004 0.020 0.000 0.976
#> GSM1233107 6 0.0632 0.8559 0.000 0.000 0.000 0.024 0.000 0.976
#> GSM1233108 5 0.1556 0.9190 0.000 0.000 0.000 0.080 0.920 0.000
#> GSM1233109 5 0.3023 0.8400 0.000 0.000 0.000 0.232 0.768 0.000
#> GSM1233110 6 0.1141 0.8372 0.000 0.000 0.000 0.052 0.000 0.948
#> GSM1233113 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233116 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233120 4 0.1075 0.8377 0.000 0.000 0.000 0.952 0.000 0.048
#> GSM1233121 6 0.2527 0.8056 0.000 0.000 0.168 0.000 0.000 0.832
#> GSM1233123 6 0.0713 0.8539 0.000 0.000 0.000 0.028 0.000 0.972
#> GSM1233124 6 0.1141 0.8638 0.000 0.000 0.052 0.000 0.000 0.948
#> GSM1233125 5 0.0622 0.8793 0.000 0.000 0.000 0.008 0.980 0.012
#> GSM1233126 3 0.3782 0.2863 0.000 0.000 0.588 0.000 0.000 0.412
#> GSM1233127 3 0.0458 0.9265 0.000 0.016 0.984 0.000 0.000 0.000
#> GSM1233128 1 0.0000 0.9570 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233130 6 0.0692 0.8577 0.000 0.000 0.004 0.020 0.000 0.976
#> GSM1233131 4 0.1151 0.8189 0.000 0.000 0.000 0.956 0.032 0.012
#> GSM1233133 5 0.3360 0.8042 0.000 0.000 0.000 0.264 0.732 0.004
#> GSM1233134 3 0.0000 0.9350 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233135 3 0.0000 0.9350 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233136 3 0.1957 0.8525 0.000 0.000 0.888 0.000 0.000 0.112
#> GSM1233137 4 0.0891 0.8246 0.000 0.000 0.000 0.968 0.024 0.008
#> GSM1233138 3 0.0000 0.9350 0.000 0.000 1.000 0.000 0.000 0.000
#> GSM1233140 5 0.1501 0.9201 0.000 0.000 0.000 0.076 0.924 0.000
#> GSM1233141 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233142 2 0.0000 0.9991 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233144 4 0.1151 0.8189 0.000 0.000 0.000 0.956 0.032 0.012
#> GSM1233147 3 0.0000 0.9350 0.000 0.000 1.000 0.000 0.000 0.000
Heatmaps for the consensus matrix. It visualizes the probability of two samples to be in a same group.
consensus_heatmap(res, k = 2)
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> ATC:kmeans 154 1.000 0.939 0.9763 2
#> ATC:kmeans 151 0.667 0.627 0.8708 3
#> ATC:kmeans 117 0.374 0.631 0.3250 4
#> ATC:kmeans 145 0.152 0.358 0.0332 5
#> ATC:kmeans 151 0.298 0.462 0.0753 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 51941 rows and 156 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'skmeans' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 3.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.991 0.997 0.4991 0.502 0.502
#> 3 3 0.957 0.936 0.971 0.1126 0.936 0.874
#> 4 4 0.883 0.844 0.939 0.0596 0.991 0.980
#> 5 5 0.863 0.816 0.915 0.0405 0.973 0.937
#> 6 6 0.866 0.779 0.897 0.0312 0.992 0.981
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
#> GSM1232995 2 0.0000 0.994 0.000 1.000
#> GSM1233002 1 0.0000 1.000 1.000 0.000
#> GSM1233003 1 0.0000 1.000 1.000 0.000
#> GSM1233014 2 0.0000 0.994 0.000 1.000
#> GSM1233015 1 0.0000 1.000 1.000 0.000
#> GSM1233016 1 0.0000 1.000 1.000 0.000
#> GSM1233024 2 0.0000 0.994 0.000 1.000
#> GSM1233049 1 0.0000 1.000 1.000 0.000
#> GSM1233064 2 0.0000 0.994 0.000 1.000
#> GSM1233068 2 0.9909 0.204 0.444 0.556
#> GSM1233073 1 0.0000 1.000 1.000 0.000
#> GSM1233093 1 0.0000 1.000 1.000 0.000
#> GSM1233115 1 0.0000 1.000 1.000 0.000
#> GSM1232992 2 0.0000 0.994 0.000 1.000
#> GSM1232993 2 0.0000 0.994 0.000 1.000
#> GSM1233005 2 0.0000 0.994 0.000 1.000
#> GSM1233007 2 0.0000 0.994 0.000 1.000
#> GSM1233010 1 0.0000 1.000 1.000 0.000
#> GSM1233013 2 0.0000 0.994 0.000 1.000
#> GSM1233018 2 0.0000 0.994 0.000 1.000
#> GSM1233019 2 0.0000 0.994 0.000 1.000
#> GSM1233021 2 0.0000 0.994 0.000 1.000
#> GSM1233025 1 0.0000 1.000 1.000 0.000
#> GSM1233029 2 0.0000 0.994 0.000 1.000
#> GSM1233030 2 0.0000 0.994 0.000 1.000
#> GSM1233031 1 0.0000 1.000 1.000 0.000
#> GSM1233032 1 0.0000 1.000 1.000 0.000
#> GSM1233035 2 0.0000 0.994 0.000 1.000
#> GSM1233038 1 0.0000 1.000 1.000 0.000
#> GSM1233039 2 0.0000 0.994 0.000 1.000
#> GSM1233042 2 0.0000 0.994 0.000 1.000
#> GSM1233043 2 0.0000 0.994 0.000 1.000
#> GSM1233044 1 0.0000 1.000 1.000 0.000
#> GSM1233046 1 0.0000 1.000 1.000 0.000
#> GSM1233051 1 0.0000 1.000 1.000 0.000
#> GSM1233054 1 0.0000 1.000 1.000 0.000
#> GSM1233057 2 0.0000 0.994 0.000 1.000
#> GSM1233060 2 0.0000 0.994 0.000 1.000
#> GSM1233062 2 0.0000 0.994 0.000 1.000
#> GSM1233075 2 0.0000 0.994 0.000 1.000
#> GSM1233078 1 0.0000 1.000 1.000 0.000
#> GSM1233079 1 0.0000 1.000 1.000 0.000
#> GSM1233082 1 0.0000 1.000 1.000 0.000
#> GSM1233083 1 0.0000 1.000 1.000 0.000
#> GSM1233091 1 0.0000 1.000 1.000 0.000
#> GSM1233095 1 0.0000 1.000 1.000 0.000
#> GSM1233096 1 0.0000 1.000 1.000 0.000
#> GSM1233101 1 0.0000 1.000 1.000 0.000
#> GSM1233105 1 0.0000 1.000 1.000 0.000
#> GSM1233117 2 0.0000 0.994 0.000 1.000
#> GSM1233118 2 0.0000 0.994 0.000 1.000
#> GSM1233001 2 0.0000 0.994 0.000 1.000
#> GSM1233006 2 0.0000 0.994 0.000 1.000
#> GSM1233008 2 0.0000 0.994 0.000 1.000
#> GSM1233009 2 0.0000 0.994 0.000 1.000
#> GSM1233017 2 0.0000 0.994 0.000 1.000
#> GSM1233020 2 0.0000 0.994 0.000 1.000
#> GSM1233022 2 0.0000 0.994 0.000 1.000
#> GSM1233026 1 0.0000 1.000 1.000 0.000
#> GSM1233028 1 0.0000 1.000 1.000 0.000
#> GSM1233034 2 0.0000 0.994 0.000 1.000
#> GSM1233040 1 0.0000 1.000 1.000 0.000
#> GSM1233048 1 0.0000 1.000 1.000 0.000
#> GSM1233056 1 0.0000 1.000 1.000 0.000
#> GSM1233058 1 0.0000 1.000 1.000 0.000
#> GSM1233059 1 0.0000 1.000 1.000 0.000
#> GSM1233066 2 0.0000 0.994 0.000 1.000
#> GSM1233071 2 0.0000 0.994 0.000 1.000
#> GSM1233074 2 0.0000 0.994 0.000 1.000
#> GSM1233076 2 0.0000 0.994 0.000 1.000
#> GSM1233080 1 0.0000 1.000 1.000 0.000
#> GSM1233088 2 0.0000 0.994 0.000 1.000
#> GSM1233090 1 0.0000 1.000 1.000 0.000
#> GSM1233092 2 0.0000 0.994 0.000 1.000
#> GSM1233094 2 0.0000 0.994 0.000 1.000
#> GSM1233097 2 0.0000 0.994 0.000 1.000
#> GSM1233100 1 0.0000 1.000 1.000 0.000
#> GSM1233104 2 0.0000 0.994 0.000 1.000
#> GSM1233106 1 0.0000 1.000 1.000 0.000
#> GSM1233111 1 0.0000 1.000 1.000 0.000
#> GSM1233122 2 0.0000 0.994 0.000 1.000
#> GSM1233146 2 0.0000 0.994 0.000 1.000
#> GSM1232994 2 0.0000 0.994 0.000 1.000
#> GSM1232996 2 0.0000 0.994 0.000 1.000
#> GSM1232997 2 0.0000 0.994 0.000 1.000
#> GSM1232998 2 0.0000 0.994 0.000 1.000
#> GSM1232999 2 0.0000 0.994 0.000 1.000
#> GSM1233000 2 0.0000 0.994 0.000 1.000
#> GSM1233004 1 0.0000 1.000 1.000 0.000
#> GSM1233011 2 0.0000 0.994 0.000 1.000
#> GSM1233012 2 0.0000 0.994 0.000 1.000
#> GSM1233023 2 0.0000 0.994 0.000 1.000
#> GSM1233027 2 0.0000 0.994 0.000 1.000
#> GSM1233033 1 0.0000 1.000 1.000 0.000
#> GSM1233036 2 0.0000 0.994 0.000 1.000
#> GSM1233037 1 0.0000 1.000 1.000 0.000
#> GSM1233041 1 0.0000 1.000 1.000 0.000
#> GSM1233045 2 0.0000 0.994 0.000 1.000
#> GSM1233047 1 0.0000 1.000 1.000 0.000
#> GSM1233050 1 0.0000 1.000 1.000 0.000
#> GSM1233052 1 0.0000 1.000 1.000 0.000
#> GSM1233053 1 0.0000 1.000 1.000 0.000
#> GSM1233055 1 0.0000 1.000 1.000 0.000
#> GSM1233061 1 0.0000 1.000 1.000 0.000
#> GSM1233063 1 0.0000 1.000 1.000 0.000
#> GSM1233065 2 0.0000 0.994 0.000 1.000
#> GSM1233070 2 0.0000 0.994 0.000 1.000
#> GSM1233077 2 0.0000 0.994 0.000 1.000
#> GSM1233081 1 0.0000 1.000 1.000 0.000
#> GSM1233084 1 0.0000 1.000 1.000 0.000
#> GSM1233087 1 0.0000 1.000 1.000 0.000
#> GSM1233089 2 0.0000 0.994 0.000 1.000
#> GSM1233099 1 0.0000 1.000 1.000 0.000
#> GSM1233112 1 0.0000 1.000 1.000 0.000
#> GSM1233085 1 0.0000 1.000 1.000 0.000
#> GSM1233098 2 0.0000 0.994 0.000 1.000
#> GSM1233114 1 0.0000 1.000 1.000 0.000
#> GSM1233119 1 0.0000 1.000 1.000 0.000
#> GSM1233129 2 0.0000 0.994 0.000 1.000
#> GSM1233132 1 0.0000 1.000 1.000 0.000
#> GSM1233139 2 0.0000 0.994 0.000 1.000
#> GSM1233143 2 0.0000 0.994 0.000 1.000
#> GSM1233145 1 0.0000 1.000 1.000 0.000
#> GSM1233067 2 0.0000 0.994 0.000 1.000
#> GSM1233069 2 0.0000 0.994 0.000 1.000
#> GSM1233072 2 0.0000 0.994 0.000 1.000
#> GSM1233086 2 0.0000 0.994 0.000 1.000
#> GSM1233102 1 0.0000 1.000 1.000 0.000
#> GSM1233103 2 0.0000 0.994 0.000 1.000
#> GSM1233107 2 0.0000 0.994 0.000 1.000
#> GSM1233108 1 0.0000 1.000 1.000 0.000
#> GSM1233109 1 0.0000 1.000 1.000 0.000
#> GSM1233110 2 0.3879 0.914 0.076 0.924
#> GSM1233113 2 0.0000 0.994 0.000 1.000
#> GSM1233116 2 0.0000 0.994 0.000 1.000
#> GSM1233120 1 0.0000 1.000 1.000 0.000
#> GSM1233121 2 0.0000 0.994 0.000 1.000
#> GSM1233123 2 0.0672 0.986 0.008 0.992
#> GSM1233124 2 0.0000 0.994 0.000 1.000
#> GSM1233125 1 0.0000 1.000 1.000 0.000
#> GSM1233126 2 0.0000 0.994 0.000 1.000
#> GSM1233127 2 0.0000 0.994 0.000 1.000
#> GSM1233128 1 0.0000 1.000 1.000 0.000
#> GSM1233130 2 0.0000 0.994 0.000 1.000
#> GSM1233131 1 0.0000 1.000 1.000 0.000
#> GSM1233133 1 0.0000 1.000 1.000 0.000
#> GSM1233134 2 0.0000 0.994 0.000 1.000
#> GSM1233135 2 0.0000 0.994 0.000 1.000
#> GSM1233136 2 0.0000 0.994 0.000 1.000
#> GSM1233137 1 0.0000 1.000 1.000 0.000
#> GSM1233138 2 0.0000 0.994 0.000 1.000
#> GSM1233140 1 0.0000 1.000 1.000 0.000
#> GSM1233141 2 0.0000 0.994 0.000 1.000
#> GSM1233142 2 0.0000 0.994 0.000 1.000
#> GSM1233144 1 0.0000 1.000 1.000 0.000
#> GSM1233147 2 0.0000 0.994 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233002 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233003 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233014 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233015 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233016 3 0.0892 0.706 0.020 0.000 0.980
#> GSM1233024 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233049 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233064 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233068 3 0.3587 0.703 0.088 0.020 0.892
#> GSM1233073 1 0.5733 0.450 0.676 0.000 0.324
#> GSM1233093 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233115 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1232992 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1232993 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233005 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233007 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233010 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233013 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233018 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233019 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233021 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233025 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233029 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233030 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233031 1 0.4062 0.778 0.836 0.000 0.164
#> GSM1233032 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233035 3 0.1860 0.724 0.000 0.052 0.948
#> GSM1233038 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233039 2 0.2165 0.920 0.000 0.936 0.064
#> GSM1233042 2 0.4702 0.700 0.000 0.788 0.212
#> GSM1233043 2 0.0237 0.979 0.000 0.996 0.004
#> GSM1233044 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233046 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233051 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233054 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233057 2 0.3816 0.810 0.000 0.852 0.148
#> GSM1233060 2 0.3340 0.851 0.000 0.880 0.120
#> GSM1233062 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233075 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233078 1 0.1163 0.958 0.972 0.000 0.028
#> GSM1233079 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233082 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233083 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233091 1 0.0237 0.982 0.996 0.000 0.004
#> GSM1233095 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233096 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233101 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233105 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233117 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233118 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233001 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233006 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233008 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233009 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233017 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233020 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233022 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233026 3 0.5810 0.468 0.336 0.000 0.664
#> GSM1233028 1 0.4555 0.713 0.800 0.000 0.200
#> GSM1233034 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233040 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233048 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233056 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233058 3 0.6302 0.133 0.480 0.000 0.520
#> GSM1233059 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233066 3 0.2448 0.728 0.000 0.076 0.924
#> GSM1233071 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233074 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233076 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233080 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233088 2 0.1860 0.933 0.000 0.948 0.052
#> GSM1233090 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233092 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233094 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233097 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233100 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233104 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233106 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233111 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233122 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233146 2 0.6180 0.187 0.000 0.584 0.416
#> GSM1232994 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1232996 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1232997 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1232998 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1232999 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233000 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233004 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233011 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233012 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233023 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233027 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233033 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233036 2 0.0892 0.965 0.000 0.980 0.020
#> GSM1233037 3 0.6215 0.288 0.428 0.000 0.572
#> GSM1233041 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233045 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233047 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233050 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233052 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233053 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233055 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233061 1 0.1163 0.958 0.972 0.000 0.028
#> GSM1233063 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233065 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233070 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233077 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233081 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233084 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233087 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233089 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233099 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233112 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233085 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233098 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233114 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233119 1 0.2165 0.916 0.936 0.000 0.064
#> GSM1233129 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233132 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233139 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233143 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233145 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233067 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233069 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233072 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233086 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233102 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233103 2 0.1753 0.938 0.000 0.952 0.048
#> GSM1233107 3 0.5058 0.615 0.000 0.244 0.756
#> GSM1233108 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233109 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233110 3 0.7044 0.467 0.032 0.348 0.620
#> GSM1233113 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233116 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233120 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233121 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233123 3 0.6421 0.280 0.004 0.424 0.572
#> GSM1233124 2 0.0237 0.979 0.000 0.996 0.004
#> GSM1233125 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233126 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233127 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233128 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233130 2 0.3340 0.853 0.000 0.880 0.120
#> GSM1233131 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233133 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233134 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233135 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233136 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233137 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233138 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233140 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233141 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233142 2 0.0000 0.983 0.000 1.000 0.000
#> GSM1233144 1 0.0000 0.986 1.000 0.000 0.000
#> GSM1233147 2 0.0000 0.983 0.000 1.000 0.000
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233002 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233003 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233014 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233015 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233016 4 0.5186 -0.1307 0.016 0.000 0.344 0.640
#> GSM1233024 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233049 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233064 2 0.1151 0.9249 0.000 0.968 0.024 0.008
#> GSM1233068 4 0.2131 0.1488 0.040 0.008 0.016 0.936
#> GSM1233073 1 0.6805 0.3249 0.592 0.000 0.260 0.148
#> GSM1233093 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233115 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1232992 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1232993 2 0.0188 0.9464 0.000 0.996 0.000 0.004
#> GSM1233005 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233007 2 0.0188 0.9464 0.000 0.996 0.000 0.004
#> GSM1233010 1 0.0188 0.9669 0.996 0.000 0.004 0.000
#> GSM1233013 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233018 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233019 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233021 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233025 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233029 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233030 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233031 1 0.6187 0.3363 0.596 0.000 0.336 0.068
#> GSM1233032 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233035 4 0.3117 0.0922 0.000 0.028 0.092 0.880
#> GSM1233038 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233039 2 0.5085 0.5872 0.000 0.708 0.032 0.260
#> GSM1233042 4 0.7047 -0.0888 0.000 0.436 0.120 0.444
#> GSM1233043 2 0.4312 0.7581 0.000 0.812 0.056 0.132
#> GSM1233044 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233046 1 0.1940 0.9016 0.924 0.000 0.076 0.000
#> GSM1233051 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233054 1 0.0188 0.9669 0.996 0.000 0.004 0.000
#> GSM1233057 2 0.4920 0.6656 0.000 0.756 0.052 0.192
#> GSM1233060 2 0.7323 -0.1462 0.000 0.456 0.388 0.156
#> GSM1233062 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233075 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233078 1 0.3168 0.8580 0.884 0.000 0.060 0.056
#> GSM1233079 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233082 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233083 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233091 1 0.4050 0.7794 0.820 0.000 0.144 0.036
#> GSM1233095 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233096 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233101 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233105 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233117 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233118 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233001 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233006 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233008 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233009 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233017 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233020 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233022 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233026 3 0.6653 0.1534 0.180 0.000 0.624 0.196
#> GSM1233028 1 0.5250 0.6558 0.744 0.000 0.080 0.176
#> GSM1233034 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233040 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233048 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233056 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233058 4 0.6690 0.0479 0.188 0.000 0.192 0.620
#> GSM1233059 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233066 4 0.6135 -0.2159 0.000 0.068 0.324 0.608
#> GSM1233071 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233074 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233076 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233080 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233088 2 0.6919 0.1173 0.000 0.528 0.352 0.120
#> GSM1233090 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233092 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233094 2 0.2775 0.8584 0.000 0.896 0.084 0.020
#> GSM1233097 2 0.1938 0.8976 0.000 0.936 0.012 0.052
#> GSM1233100 1 0.0188 0.9668 0.996 0.000 0.004 0.000
#> GSM1233104 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233106 1 0.0336 0.9637 0.992 0.000 0.000 0.008
#> GSM1233111 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233122 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233146 2 0.7438 -0.0142 0.000 0.512 0.244 0.244
#> GSM1232994 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1232996 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1232997 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1232998 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1232999 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233000 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233004 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233011 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233012 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233023 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233027 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233033 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233036 2 0.2281 0.8649 0.000 0.904 0.000 0.096
#> GSM1233037 4 0.5998 0.0701 0.240 0.000 0.092 0.668
#> GSM1233041 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233045 2 0.2363 0.8827 0.000 0.920 0.024 0.056
#> GSM1233047 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233050 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233052 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233053 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233055 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233061 1 0.5022 0.5995 0.708 0.000 0.264 0.028
#> GSM1233063 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233065 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233070 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233077 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233081 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233084 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233087 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233089 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233099 1 0.0376 0.9638 0.992 0.000 0.004 0.004
#> GSM1233112 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233085 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233098 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233114 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233119 1 0.3090 0.8604 0.888 0.000 0.056 0.056
#> GSM1233129 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233132 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233139 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233143 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233145 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233067 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233069 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233072 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233086 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233102 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233103 2 0.6757 0.1131 0.000 0.524 0.376 0.100
#> GSM1233107 3 0.7003 0.1760 0.000 0.116 0.460 0.424
#> GSM1233108 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233109 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233110 3 0.3667 0.4108 0.000 0.056 0.856 0.088
#> GSM1233113 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233116 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233120 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233121 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233123 3 0.6215 0.2922 0.000 0.128 0.664 0.208
#> GSM1233124 2 0.3545 0.7712 0.000 0.828 0.164 0.008
#> GSM1233125 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233126 2 0.0188 0.9464 0.000 0.996 0.000 0.004
#> GSM1233127 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233128 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233130 2 0.6383 0.2362 0.000 0.568 0.356 0.076
#> GSM1233131 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233133 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233134 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233135 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233136 2 0.0469 0.9404 0.000 0.988 0.012 0.000
#> GSM1233137 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233138 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233140 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233141 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233142 2 0.0000 0.9493 0.000 1.000 0.000 0.000
#> GSM1233144 1 0.0000 0.9699 1.000 0.000 0.000 0.000
#> GSM1233147 2 0.0000 0.9493 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233002 1 0.0486 0.9398 0.988 0.000 0.004 0.004 0.004
#> GSM1233003 1 0.0451 0.9418 0.988 0.000 0.000 0.004 0.008
#> GSM1233014 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233015 1 0.0854 0.9348 0.976 0.000 0.004 0.012 0.008
#> GSM1233016 4 0.3242 0.4599 0.000 0.000 0.076 0.852 0.072
#> GSM1233024 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233049 1 0.0290 0.9411 0.992 0.000 0.000 0.000 0.008
#> GSM1233064 2 0.2388 0.8447 0.000 0.900 0.072 0.000 0.028
#> GSM1233068 4 0.6076 0.2446 0.012 0.004 0.072 0.492 0.420
#> GSM1233073 1 0.7848 -0.0130 0.476 0.000 0.148 0.172 0.204
#> GSM1233093 1 0.0290 0.9411 0.992 0.000 0.000 0.000 0.008
#> GSM1233115 1 0.0000 0.9418 1.000 0.000 0.000 0.000 0.000
#> GSM1232992 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1232993 2 0.0579 0.9395 0.000 0.984 0.008 0.000 0.008
#> GSM1233005 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233007 2 0.0955 0.9242 0.000 0.968 0.028 0.000 0.004
#> GSM1233010 1 0.1393 0.9223 0.956 0.000 0.012 0.008 0.024
#> GSM1233013 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233018 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233019 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233021 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233025 1 0.0727 0.9367 0.980 0.000 0.004 0.012 0.004
#> GSM1233029 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233030 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233031 1 0.7204 0.1840 0.524 0.000 0.224 0.060 0.192
#> GSM1233032 1 0.0324 0.9410 0.992 0.000 0.000 0.004 0.004
#> GSM1233035 4 0.5503 0.3994 0.000 0.028 0.052 0.652 0.268
#> GSM1233038 1 0.0324 0.9410 0.992 0.000 0.000 0.004 0.004
#> GSM1233039 2 0.6533 0.2483 0.000 0.636 0.096 0.136 0.132
#> GSM1233042 5 0.7604 -0.3496 0.000 0.232 0.272 0.060 0.436
#> GSM1233043 2 0.6107 0.1251 0.000 0.604 0.232 0.012 0.152
#> GSM1233044 1 0.0162 0.9416 0.996 0.000 0.000 0.004 0.000
#> GSM1233046 1 0.4558 0.7299 0.780 0.000 0.076 0.024 0.120
#> GSM1233051 1 0.0000 0.9418 1.000 0.000 0.000 0.000 0.000
#> GSM1233054 1 0.1764 0.8975 0.928 0.000 0.008 0.000 0.064
#> GSM1233057 2 0.6972 0.0756 0.000 0.592 0.124 0.156 0.128
#> GSM1233060 3 0.7531 0.4095 0.000 0.252 0.476 0.072 0.200
#> GSM1233062 2 0.0162 0.9492 0.000 0.996 0.000 0.004 0.000
#> GSM1233075 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233078 1 0.5384 0.6575 0.736 0.000 0.080 0.096 0.088
#> GSM1233079 1 0.0324 0.9410 0.992 0.000 0.000 0.004 0.004
#> GSM1233082 1 0.0613 0.9384 0.984 0.000 0.004 0.004 0.008
#> GSM1233083 1 0.0162 0.9417 0.996 0.000 0.000 0.000 0.004
#> GSM1233091 1 0.5870 0.3999 0.604 0.000 0.072 0.024 0.300
#> GSM1233095 1 0.0162 0.9416 0.996 0.000 0.000 0.000 0.004
#> GSM1233096 1 0.0324 0.9410 0.992 0.000 0.000 0.004 0.004
#> GSM1233101 1 0.0290 0.9411 0.992 0.000 0.000 0.000 0.008
#> GSM1233105 1 0.0613 0.9384 0.984 0.000 0.004 0.004 0.008
#> GSM1233117 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233118 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233001 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233006 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233008 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233009 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233017 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233020 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233022 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233026 4 0.7627 0.0799 0.200 0.000 0.280 0.448 0.072
#> GSM1233028 1 0.6231 0.3012 0.576 0.000 0.048 0.064 0.312
#> GSM1233034 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233040 1 0.0290 0.9411 0.992 0.000 0.000 0.000 0.008
#> GSM1233048 1 0.0404 0.9402 0.988 0.000 0.000 0.000 0.012
#> GSM1233056 1 0.0000 0.9418 1.000 0.000 0.000 0.000 0.000
#> GSM1233058 5 0.4397 0.0631 0.044 0.000 0.056 0.100 0.800
#> GSM1233059 1 0.0290 0.9411 0.992 0.000 0.000 0.000 0.008
#> GSM1233066 4 0.4864 0.4429 0.000 0.056 0.080 0.772 0.092
#> GSM1233071 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233074 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233076 2 0.0703 0.9317 0.000 0.976 0.024 0.000 0.000
#> GSM1233080 1 0.0000 0.9418 1.000 0.000 0.000 0.000 0.000
#> GSM1233088 3 0.6929 0.4725 0.000 0.260 0.536 0.044 0.160
#> GSM1233090 1 0.0290 0.9411 0.992 0.000 0.000 0.000 0.008
#> GSM1233092 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233094 2 0.4251 0.6771 0.000 0.796 0.132 0.024 0.048
#> GSM1233097 2 0.3579 0.7382 0.000 0.828 0.100 0.000 0.072
#> GSM1233100 1 0.1522 0.9109 0.944 0.000 0.012 0.000 0.044
#> GSM1233104 2 0.0162 0.9492 0.000 0.996 0.004 0.000 0.000
#> GSM1233106 1 0.0613 0.9384 0.984 0.000 0.004 0.004 0.008
#> GSM1233111 1 0.0486 0.9398 0.988 0.000 0.004 0.004 0.004
#> GSM1233122 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233146 2 0.5849 -0.0946 0.000 0.560 0.068 0.356 0.016
#> GSM1232994 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1232996 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1232997 2 0.0162 0.9492 0.000 0.996 0.004 0.000 0.000
#> GSM1232998 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1232999 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233000 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233004 1 0.0290 0.9411 0.992 0.000 0.000 0.000 0.008
#> GSM1233011 2 0.0324 0.9462 0.000 0.992 0.004 0.004 0.000
#> GSM1233012 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233023 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233027 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233033 1 0.0613 0.9384 0.984 0.000 0.004 0.004 0.008
#> GSM1233036 2 0.4401 0.6805 0.000 0.800 0.036 0.084 0.080
#> GSM1233037 5 0.6873 -0.0133 0.172 0.000 0.060 0.192 0.576
#> GSM1233041 1 0.0324 0.9410 0.992 0.000 0.000 0.004 0.004
#> GSM1233045 2 0.3493 0.7432 0.000 0.832 0.108 0.000 0.060
#> GSM1233047 1 0.0404 0.9402 0.988 0.000 0.000 0.000 0.012
#> GSM1233050 1 0.0290 0.9411 0.992 0.000 0.000 0.000 0.008
#> GSM1233052 1 0.0404 0.9402 0.988 0.000 0.000 0.000 0.012
#> GSM1233053 1 0.0404 0.9402 0.988 0.000 0.000 0.000 0.012
#> GSM1233055 1 0.0290 0.9411 0.992 0.000 0.000 0.000 0.008
#> GSM1233061 1 0.7180 0.1277 0.508 0.000 0.152 0.060 0.280
#> GSM1233063 1 0.0324 0.9410 0.992 0.000 0.000 0.004 0.004
#> GSM1233065 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233070 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233077 2 0.0162 0.9492 0.000 0.996 0.004 0.000 0.000
#> GSM1233081 1 0.0162 0.9418 0.996 0.000 0.000 0.000 0.004
#> GSM1233084 1 0.0324 0.9410 0.992 0.000 0.000 0.004 0.004
#> GSM1233087 1 0.0162 0.9417 0.996 0.000 0.004 0.000 0.000
#> GSM1233089 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233099 1 0.2305 0.8686 0.896 0.000 0.012 0.000 0.092
#> GSM1233112 1 0.0290 0.9411 0.992 0.000 0.000 0.000 0.008
#> GSM1233085 1 0.0290 0.9411 0.992 0.000 0.000 0.000 0.008
#> GSM1233098 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233114 1 0.0486 0.9398 0.988 0.000 0.004 0.004 0.004
#> GSM1233119 1 0.4031 0.7629 0.808 0.000 0.024 0.132 0.036
#> GSM1233129 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233132 1 0.0609 0.9367 0.980 0.000 0.000 0.000 0.020
#> GSM1233139 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233143 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233145 1 0.0000 0.9418 1.000 0.000 0.000 0.000 0.000
#> GSM1233067 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233069 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233072 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233086 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233102 1 0.0324 0.9410 0.992 0.000 0.000 0.004 0.004
#> GSM1233103 3 0.5848 0.4964 0.000 0.280 0.616 0.020 0.084
#> GSM1233107 4 0.5357 0.3324 0.000 0.116 0.124 0.724 0.036
#> GSM1233108 1 0.0324 0.9410 0.992 0.000 0.000 0.004 0.004
#> GSM1233109 1 0.0000 0.9418 1.000 0.000 0.000 0.000 0.000
#> GSM1233110 3 0.5774 -0.3452 0.004 0.008 0.604 0.304 0.080
#> GSM1233113 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233116 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233120 1 0.0671 0.9371 0.980 0.000 0.004 0.000 0.016
#> GSM1233121 2 0.0404 0.9427 0.000 0.988 0.012 0.000 0.000
#> GSM1233123 5 0.7155 0.0248 0.000 0.072 0.348 0.108 0.472
#> GSM1233124 2 0.3523 0.7358 0.000 0.832 0.120 0.044 0.004
#> GSM1233125 1 0.0324 0.9410 0.992 0.000 0.000 0.004 0.004
#> GSM1233126 2 0.0771 0.9320 0.000 0.976 0.020 0.000 0.004
#> GSM1233127 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233128 1 0.0324 0.9410 0.992 0.000 0.000 0.004 0.004
#> GSM1233130 3 0.7412 0.4550 0.000 0.272 0.500 0.132 0.096
#> GSM1233131 1 0.0404 0.9411 0.988 0.000 0.000 0.000 0.012
#> GSM1233133 1 0.0290 0.9411 0.992 0.000 0.000 0.000 0.008
#> GSM1233134 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233135 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233136 2 0.0963 0.9197 0.000 0.964 0.036 0.000 0.000
#> GSM1233137 1 0.0404 0.9402 0.988 0.000 0.000 0.000 0.012
#> GSM1233138 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233140 1 0.0324 0.9410 0.992 0.000 0.000 0.004 0.004
#> GSM1233141 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233142 2 0.0000 0.9522 0.000 1.000 0.000 0.000 0.000
#> GSM1233144 1 0.0404 0.9417 0.988 0.000 0.000 0.000 0.012
#> GSM1233147 2 0.0000 0.9522 0.000 1.000 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
#> GSM1232995 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233002 1 0.0909 0.9091 0.968 0.000 0.000 0.000 0.020 0.012
#> GSM1233003 1 0.0146 0.9130 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1233014 2 0.0508 0.9326 0.000 0.984 0.000 0.012 0.004 0.000
#> GSM1233015 1 0.2434 0.8674 0.892 0.000 0.008 0.000 0.064 0.036
#> GSM1233016 3 0.5010 0.3082 0.004 0.000 0.592 0.020 0.348 0.036
#> GSM1233024 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233049 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233064 2 0.3128 0.7515 0.000 0.836 0.008 0.132 0.016 0.008
#> GSM1233068 3 0.5679 0.2764 0.000 0.004 0.660 0.128 0.068 0.140
#> GSM1233073 1 0.8122 -0.4048 0.352 0.000 0.096 0.076 0.176 0.300
#> GSM1233093 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233115 1 0.0291 0.9130 0.992 0.000 0.000 0.000 0.004 0.004
#> GSM1232992 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232993 2 0.1261 0.9072 0.000 0.956 0.004 0.028 0.004 0.008
#> GSM1233005 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233007 2 0.1718 0.8826 0.000 0.932 0.000 0.044 0.008 0.016
#> GSM1233010 1 0.3239 0.8199 0.840 0.000 0.016 0.000 0.100 0.044
#> GSM1233013 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233018 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233019 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233021 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233025 1 0.1838 0.8836 0.916 0.000 0.000 0.000 0.068 0.016
#> GSM1233029 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233030 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233031 1 0.7422 -0.0199 0.476 0.000 0.048 0.068 0.216 0.192
#> GSM1233032 1 0.0692 0.9111 0.976 0.000 0.000 0.000 0.020 0.004
#> GSM1233035 3 0.2820 0.4759 0.000 0.032 0.884 0.052 0.016 0.016
#> GSM1233038 1 0.0692 0.9111 0.976 0.000 0.000 0.000 0.020 0.004
#> GSM1233039 2 0.6703 -0.0564 0.000 0.556 0.204 0.160 0.036 0.044
#> GSM1233042 4 0.5879 -0.0567 0.000 0.076 0.116 0.660 0.016 0.132
#> GSM1233043 4 0.5654 0.3518 0.000 0.416 0.076 0.480 0.000 0.028
#> GSM1233044 1 0.0405 0.9135 0.988 0.000 0.000 0.000 0.008 0.004
#> GSM1233046 1 0.4803 0.6059 0.716 0.000 0.020 0.012 0.064 0.188
#> GSM1233051 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233054 1 0.2002 0.8559 0.908 0.000 0.004 0.000 0.012 0.076
#> GSM1233057 2 0.7474 -0.2388 0.000 0.508 0.180 0.156 0.068 0.088
#> GSM1233060 4 0.7149 0.3933 0.000 0.164 0.056 0.552 0.116 0.112
#> GSM1233062 2 0.0146 0.9410 0.000 0.996 0.000 0.000 0.000 0.004
#> GSM1233075 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233078 1 0.6704 0.3801 0.580 0.000 0.044 0.056 0.160 0.160
#> GSM1233079 1 0.0993 0.9081 0.964 0.000 0.000 0.000 0.024 0.012
#> GSM1233082 1 0.1765 0.8879 0.924 0.000 0.000 0.000 0.052 0.024
#> GSM1233083 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233091 1 0.6070 0.1703 0.540 0.000 0.024 0.056 0.044 0.336
#> GSM1233095 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233096 1 0.0806 0.9102 0.972 0.000 0.000 0.000 0.020 0.008
#> GSM1233101 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233105 1 0.1745 0.8880 0.924 0.000 0.000 0.000 0.056 0.020
#> GSM1233117 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233118 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233001 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233006 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233008 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233009 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233017 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233020 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233022 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233026 5 0.6767 0.1714 0.112 0.000 0.160 0.036 0.584 0.108
#> GSM1233028 1 0.7822 -0.1480 0.456 0.000 0.140 0.096 0.084 0.224
#> GSM1233034 2 0.0260 0.9380 0.000 0.992 0.008 0.000 0.000 0.000
#> GSM1233040 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233048 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233056 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233058 6 0.6459 0.2854 0.044 0.000 0.160 0.196 0.024 0.576
#> GSM1233059 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233066 3 0.6530 0.4255 0.000 0.040 0.580 0.060 0.228 0.092
#> GSM1233071 2 0.0146 0.9409 0.000 0.996 0.000 0.004 0.000 0.000
#> GSM1233074 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233076 2 0.1364 0.8957 0.000 0.944 0.004 0.048 0.004 0.000
#> GSM1233080 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233088 4 0.7392 0.4168 0.000 0.180 0.068 0.520 0.144 0.088
#> GSM1233090 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233092 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233094 2 0.4012 0.6994 0.000 0.804 0.012 0.096 0.064 0.024
#> GSM1233097 2 0.3877 0.6531 0.000 0.780 0.024 0.168 0.004 0.024
#> GSM1233100 1 0.2431 0.8234 0.872 0.000 0.004 0.004 0.004 0.116
#> GSM1233104 2 0.0146 0.9410 0.000 0.996 0.000 0.004 0.000 0.000
#> GSM1233106 1 0.2547 0.8558 0.880 0.000 0.004 0.000 0.080 0.036
#> GSM1233111 1 0.1245 0.9032 0.952 0.000 0.000 0.000 0.032 0.016
#> GSM1233122 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233146 2 0.7315 -0.4423 0.000 0.432 0.256 0.080 0.216 0.016
#> GSM1232994 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232996 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232997 2 0.0260 0.9377 0.000 0.992 0.000 0.008 0.000 0.000
#> GSM1232998 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232999 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233000 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233004 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233011 2 0.0405 0.9356 0.000 0.988 0.000 0.008 0.004 0.000
#> GSM1233012 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233023 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233027 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233033 1 0.1682 0.8903 0.928 0.000 0.000 0.000 0.052 0.020
#> GSM1233036 2 0.4041 0.6136 0.000 0.764 0.164 0.060 0.000 0.012
#> GSM1233037 6 0.8459 0.1902 0.136 0.000 0.284 0.192 0.084 0.304
#> GSM1233041 1 0.0692 0.9111 0.976 0.000 0.000 0.000 0.020 0.004
#> GSM1233045 2 0.3905 0.4914 0.000 0.712 0.012 0.264 0.000 0.012
#> GSM1233047 1 0.0146 0.9118 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM1233050 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233052 1 0.0508 0.9080 0.984 0.000 0.000 0.000 0.004 0.012
#> GSM1233053 1 0.0146 0.9118 0.996 0.000 0.000 0.000 0.000 0.004
#> GSM1233055 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233061 1 0.6970 -0.2885 0.404 0.000 0.040 0.024 0.164 0.368
#> GSM1233063 1 0.0777 0.9107 0.972 0.000 0.000 0.000 0.024 0.004
#> GSM1233065 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233070 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233077 2 0.0458 0.9321 0.000 0.984 0.000 0.016 0.000 0.000
#> GSM1233081 1 0.0458 0.9129 0.984 0.000 0.000 0.000 0.000 0.016
#> GSM1233084 1 0.0692 0.9111 0.976 0.000 0.000 0.000 0.020 0.004
#> GSM1233087 1 0.1003 0.9085 0.964 0.000 0.000 0.000 0.016 0.020
#> GSM1233089 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233099 1 0.2615 0.7987 0.852 0.000 0.000 0.004 0.008 0.136
#> GSM1233112 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233085 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233098 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233114 1 0.1408 0.8991 0.944 0.000 0.000 0.000 0.036 0.020
#> GSM1233119 1 0.5299 0.5998 0.684 0.000 0.052 0.004 0.176 0.084
#> GSM1233129 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233132 1 0.0363 0.9094 0.988 0.000 0.000 0.000 0.000 0.012
#> GSM1233139 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233143 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233145 1 0.0692 0.9111 0.976 0.000 0.000 0.000 0.020 0.004
#> GSM1233067 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233069 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233072 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233086 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233102 1 0.0806 0.9102 0.972 0.000 0.000 0.000 0.020 0.008
#> GSM1233103 4 0.6733 0.4592 0.000 0.184 0.020 0.560 0.156 0.080
#> GSM1233107 3 0.6579 0.2549 0.000 0.072 0.464 0.036 0.380 0.048
#> GSM1233108 1 0.0993 0.9080 0.964 0.000 0.000 0.000 0.024 0.012
#> GSM1233109 1 0.0820 0.9107 0.972 0.000 0.000 0.000 0.016 0.012
#> GSM1233110 5 0.5366 0.1197 0.000 0.008 0.028 0.176 0.672 0.116
#> GSM1233113 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233116 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233120 1 0.0922 0.9016 0.968 0.000 0.000 0.004 0.004 0.024
#> GSM1233121 2 0.1340 0.8999 0.000 0.948 0.000 0.040 0.008 0.004
#> GSM1233123 6 0.7392 -0.0193 0.000 0.052 0.080 0.156 0.216 0.496
#> GSM1233124 2 0.5124 0.5157 0.000 0.724 0.016 0.056 0.132 0.072
#> GSM1233125 1 0.0603 0.9118 0.980 0.000 0.000 0.000 0.016 0.004
#> GSM1233126 2 0.1116 0.9119 0.000 0.960 0.008 0.028 0.000 0.004
#> GSM1233127 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233128 1 0.0806 0.9102 0.972 0.000 0.000 0.000 0.020 0.008
#> GSM1233130 4 0.7268 0.3821 0.000 0.176 0.052 0.488 0.232 0.052
#> GSM1233131 1 0.0622 0.9111 0.980 0.000 0.000 0.000 0.012 0.008
#> GSM1233133 1 0.0000 0.9128 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233134 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233135 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233136 2 0.1956 0.8526 0.000 0.908 0.000 0.080 0.008 0.004
#> GSM1233137 1 0.0508 0.9080 0.984 0.000 0.000 0.000 0.004 0.012
#> GSM1233138 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233140 1 0.1074 0.9067 0.960 0.000 0.000 0.000 0.028 0.012
#> GSM1233141 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233142 2 0.0000 0.9437 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233144 1 0.0405 0.9128 0.988 0.000 0.000 0.000 0.008 0.004
#> GSM1233147 2 0.0000 0.9437 0.000 1.000 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)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> ATC:skmeans 155 0.370 1.000 0.728 2
#> ATC:skmeans 149 0.782 0.608 0.421 3
#> ATC:skmeans 138 0.799 0.746 1.000 4
#> ATC:skmeans 132 0.816 0.497 1.000 5
#> ATC:skmeans 130 0.822 0.611 1.000 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 51941 rows and 156 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 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 0.978 0.990 0.4677 0.530 0.530
#> 3 3 0.999 0.967 0.985 0.3734 0.642 0.425
#> 4 4 0.806 0.815 0.919 0.1279 0.778 0.480
#> 5 5 0.911 0.840 0.940 0.0917 0.837 0.493
#> 6 6 0.859 0.831 0.912 0.0359 0.935 0.712
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
#> GSM1232995 2 0.0000 0.995 0.000 1.000
#> GSM1233002 1 0.0000 0.979 1.000 0.000
#> GSM1233003 1 0.0000 0.979 1.000 0.000
#> GSM1233014 2 0.0000 0.995 0.000 1.000
#> GSM1233015 1 0.5519 0.856 0.872 0.128
#> GSM1233016 2 0.0000 0.995 0.000 1.000
#> GSM1233024 2 0.0000 0.995 0.000 1.000
#> GSM1233049 1 0.0000 0.979 1.000 0.000
#> GSM1233064 2 0.0000 0.995 0.000 1.000
#> GSM1233068 2 0.0000 0.995 0.000 1.000
#> GSM1233073 2 0.0672 0.988 0.008 0.992
#> GSM1233093 1 0.0000 0.979 1.000 0.000
#> GSM1233115 1 0.0000 0.979 1.000 0.000
#> GSM1232992 2 0.0000 0.995 0.000 1.000
#> GSM1232993 2 0.0000 0.995 0.000 1.000
#> GSM1233005 2 0.0000 0.995 0.000 1.000
#> GSM1233007 2 0.0000 0.995 0.000 1.000
#> GSM1233010 1 0.8207 0.678 0.744 0.256
#> GSM1233013 2 0.0000 0.995 0.000 1.000
#> GSM1233018 2 0.0000 0.995 0.000 1.000
#> GSM1233019 2 0.0000 0.995 0.000 1.000
#> GSM1233021 2 0.0000 0.995 0.000 1.000
#> GSM1233025 1 0.0672 0.973 0.992 0.008
#> GSM1233029 2 0.0000 0.995 0.000 1.000
#> GSM1233030 2 0.0000 0.995 0.000 1.000
#> GSM1233031 2 0.0000 0.995 0.000 1.000
#> GSM1233032 1 0.0000 0.979 1.000 0.000
#> GSM1233035 2 0.0000 0.995 0.000 1.000
#> GSM1233038 1 0.0000 0.979 1.000 0.000
#> GSM1233039 2 0.0000 0.995 0.000 1.000
#> GSM1233042 2 0.0000 0.995 0.000 1.000
#> GSM1233043 2 0.0000 0.995 0.000 1.000
#> GSM1233044 1 0.0000 0.979 1.000 0.000
#> GSM1233046 2 0.7674 0.703 0.224 0.776
#> GSM1233051 1 0.0000 0.979 1.000 0.000
#> GSM1233054 1 0.7056 0.779 0.808 0.192
#> GSM1233057 2 0.0000 0.995 0.000 1.000
#> GSM1233060 2 0.0000 0.995 0.000 1.000
#> GSM1233062 2 0.0000 0.995 0.000 1.000
#> GSM1233075 2 0.0000 0.995 0.000 1.000
#> GSM1233078 2 0.3733 0.920 0.072 0.928
#> GSM1233079 1 0.0000 0.979 1.000 0.000
#> GSM1233082 1 0.0000 0.979 1.000 0.000
#> GSM1233083 1 0.0000 0.979 1.000 0.000
#> GSM1233091 2 0.1843 0.968 0.028 0.972
#> GSM1233095 1 0.0000 0.979 1.000 0.000
#> GSM1233096 1 0.0000 0.979 1.000 0.000
#> GSM1233101 1 0.0000 0.979 1.000 0.000
#> GSM1233105 1 0.0000 0.979 1.000 0.000
#> GSM1233117 2 0.0000 0.995 0.000 1.000
#> GSM1233118 2 0.0000 0.995 0.000 1.000
#> GSM1233001 2 0.0000 0.995 0.000 1.000
#> GSM1233006 2 0.0000 0.995 0.000 1.000
#> GSM1233008 2 0.0000 0.995 0.000 1.000
#> GSM1233009 2 0.0000 0.995 0.000 1.000
#> GSM1233017 2 0.0000 0.995 0.000 1.000
#> GSM1233020 2 0.0000 0.995 0.000 1.000
#> GSM1233022 2 0.0000 0.995 0.000 1.000
#> GSM1233026 2 0.0000 0.995 0.000 1.000
#> GSM1233028 2 0.0376 0.992 0.004 0.996
#> GSM1233034 2 0.0000 0.995 0.000 1.000
#> GSM1233040 1 0.0000 0.979 1.000 0.000
#> GSM1233048 1 0.0000 0.979 1.000 0.000
#> GSM1233056 1 0.0000 0.979 1.000 0.000
#> GSM1233058 2 0.0000 0.995 0.000 1.000
#> GSM1233059 1 0.0000 0.979 1.000 0.000
#> GSM1233066 2 0.0000 0.995 0.000 1.000
#> GSM1233071 2 0.0000 0.995 0.000 1.000
#> GSM1233074 2 0.0000 0.995 0.000 1.000
#> GSM1233076 2 0.0000 0.995 0.000 1.000
#> GSM1233080 1 0.0000 0.979 1.000 0.000
#> GSM1233088 2 0.0000 0.995 0.000 1.000
#> GSM1233090 1 0.0000 0.979 1.000 0.000
#> GSM1233092 2 0.0000 0.995 0.000 1.000
#> GSM1233094 2 0.0000 0.995 0.000 1.000
#> GSM1233097 2 0.0000 0.995 0.000 1.000
#> GSM1233100 1 0.7056 0.779 0.808 0.192
#> GSM1233104 2 0.0000 0.995 0.000 1.000
#> GSM1233106 1 0.7056 0.779 0.808 0.192
#> GSM1233111 1 0.0000 0.979 1.000 0.000
#> GSM1233122 2 0.0000 0.995 0.000 1.000
#> GSM1233146 2 0.0000 0.995 0.000 1.000
#> GSM1232994 2 0.0000 0.995 0.000 1.000
#> GSM1232996 2 0.0000 0.995 0.000 1.000
#> GSM1232997 2 0.0000 0.995 0.000 1.000
#> GSM1232998 2 0.0000 0.995 0.000 1.000
#> GSM1232999 2 0.0000 0.995 0.000 1.000
#> GSM1233000 2 0.0000 0.995 0.000 1.000
#> GSM1233004 1 0.0000 0.979 1.000 0.000
#> GSM1233011 2 0.0000 0.995 0.000 1.000
#> GSM1233012 2 0.0000 0.995 0.000 1.000
#> GSM1233023 2 0.0000 0.995 0.000 1.000
#> GSM1233027 2 0.0000 0.995 0.000 1.000
#> GSM1233033 1 0.0000 0.979 1.000 0.000
#> GSM1233036 2 0.0000 0.995 0.000 1.000
#> GSM1233037 2 0.0000 0.995 0.000 1.000
#> GSM1233041 1 0.0000 0.979 1.000 0.000
#> GSM1233045 2 0.0000 0.995 0.000 1.000
#> GSM1233047 1 0.0000 0.979 1.000 0.000
#> GSM1233050 1 0.0000 0.979 1.000 0.000
#> GSM1233052 1 0.0000 0.979 1.000 0.000
#> GSM1233053 1 0.0000 0.979 1.000 0.000
#> GSM1233055 1 0.0000 0.979 1.000 0.000
#> GSM1233061 2 0.0000 0.995 0.000 1.000
#> GSM1233063 1 0.0000 0.979 1.000 0.000
#> GSM1233065 2 0.0000 0.995 0.000 1.000
#> GSM1233070 2 0.0000 0.995 0.000 1.000
#> GSM1233077 2 0.0000 0.995 0.000 1.000
#> GSM1233081 1 0.0000 0.979 1.000 0.000
#> GSM1233084 1 0.0000 0.979 1.000 0.000
#> GSM1233087 1 0.0000 0.979 1.000 0.000
#> GSM1233089 2 0.0000 0.995 0.000 1.000
#> GSM1233099 1 0.7056 0.779 0.808 0.192
#> GSM1233112 1 0.0000 0.979 1.000 0.000
#> GSM1233085 1 0.0000 0.979 1.000 0.000
#> GSM1233098 2 0.0000 0.995 0.000 1.000
#> GSM1233114 1 0.0000 0.979 1.000 0.000
#> GSM1233119 2 0.4431 0.897 0.092 0.908
#> GSM1233129 2 0.0000 0.995 0.000 1.000
#> GSM1233132 1 0.0000 0.979 1.000 0.000
#> GSM1233139 2 0.0000 0.995 0.000 1.000
#> GSM1233143 2 0.0000 0.995 0.000 1.000
#> GSM1233145 1 0.0000 0.979 1.000 0.000
#> GSM1233067 2 0.0000 0.995 0.000 1.000
#> GSM1233069 2 0.0000 0.995 0.000 1.000
#> GSM1233072 2 0.0000 0.995 0.000 1.000
#> GSM1233086 2 0.0000 0.995 0.000 1.000
#> GSM1233102 1 0.0000 0.979 1.000 0.000
#> GSM1233103 2 0.0000 0.995 0.000 1.000
#> GSM1233107 2 0.0000 0.995 0.000 1.000
#> GSM1233108 1 0.0000 0.979 1.000 0.000
#> GSM1233109 1 0.0000 0.979 1.000 0.000
#> GSM1233110 2 0.0000 0.995 0.000 1.000
#> GSM1233113 2 0.0000 0.995 0.000 1.000
#> GSM1233116 2 0.0000 0.995 0.000 1.000
#> GSM1233120 1 0.0000 0.979 1.000 0.000
#> GSM1233121 2 0.0000 0.995 0.000 1.000
#> GSM1233123 2 0.0000 0.995 0.000 1.000
#> GSM1233124 2 0.0000 0.995 0.000 1.000
#> GSM1233125 1 0.0000 0.979 1.000 0.000
#> GSM1233126 2 0.0000 0.995 0.000 1.000
#> GSM1233127 2 0.0000 0.995 0.000 1.000
#> GSM1233128 1 0.0000 0.979 1.000 0.000
#> GSM1233130 2 0.0000 0.995 0.000 1.000
#> GSM1233131 1 0.0000 0.979 1.000 0.000
#> GSM1233133 1 0.0000 0.979 1.000 0.000
#> GSM1233134 2 0.0000 0.995 0.000 1.000
#> GSM1233135 2 0.0000 0.995 0.000 1.000
#> GSM1233136 2 0.0000 0.995 0.000 1.000
#> GSM1233137 1 0.0000 0.979 1.000 0.000
#> GSM1233138 2 0.0000 0.995 0.000 1.000
#> GSM1233140 1 0.0000 0.979 1.000 0.000
#> GSM1233141 2 0.0000 0.995 0.000 1.000
#> GSM1233142 2 0.0000 0.995 0.000 1.000
#> GSM1233144 1 0.0000 0.979 1.000 0.000
#> GSM1233147 2 0.0000 0.995 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233002 2 0.0237 0.976 0.004 0.996 0.000
#> GSM1233003 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233014 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233015 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233016 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233024 3 0.0424 0.987 0.000 0.008 0.992
#> GSM1233049 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233064 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233068 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233073 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233093 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233115 1 0.3267 0.874 0.884 0.116 0.000
#> GSM1232992 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1232993 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233005 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233007 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233010 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233013 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233018 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233019 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233021 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233025 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233029 2 0.5098 0.682 0.000 0.752 0.248
#> GSM1233030 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233031 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233032 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233035 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233038 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233039 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233042 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233043 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233044 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233046 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233051 1 0.3192 0.878 0.888 0.112 0.000
#> GSM1233054 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233057 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233060 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233062 2 0.4654 0.746 0.000 0.792 0.208
#> GSM1233075 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233078 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233079 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233082 2 0.0237 0.976 0.004 0.996 0.000
#> GSM1233083 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233091 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233095 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233096 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233101 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233105 2 0.0237 0.976 0.004 0.996 0.000
#> GSM1233117 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233118 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233001 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233006 3 0.2625 0.906 0.000 0.084 0.916
#> GSM1233008 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233009 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233017 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233020 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233022 2 0.4452 0.769 0.000 0.808 0.192
#> GSM1233026 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233028 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233034 3 0.0592 0.984 0.000 0.012 0.988
#> GSM1233040 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233048 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233056 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233058 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233059 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233066 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233071 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233074 3 0.0237 0.989 0.000 0.004 0.996
#> GSM1233076 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233080 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233088 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233090 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233092 3 0.0424 0.987 0.000 0.008 0.992
#> GSM1233094 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233097 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233100 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233104 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233106 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233111 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233122 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233146 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1232994 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1232996 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1232997 2 0.5968 0.450 0.000 0.636 0.364
#> GSM1232998 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1232999 3 0.1753 0.948 0.000 0.048 0.952
#> GSM1233000 3 0.0424 0.987 0.000 0.008 0.992
#> GSM1233004 2 0.2261 0.914 0.068 0.932 0.000
#> GSM1233011 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233012 3 0.0424 0.987 0.000 0.008 0.992
#> GSM1233023 3 0.0424 0.987 0.000 0.008 0.992
#> GSM1233027 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233033 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233036 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233037 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233041 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233045 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233047 2 0.0892 0.963 0.020 0.980 0.000
#> GSM1233050 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233052 1 0.4796 0.736 0.780 0.220 0.000
#> GSM1233053 1 0.2356 0.918 0.928 0.072 0.000
#> GSM1233055 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233061 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233063 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233065 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233070 3 0.1163 0.970 0.000 0.028 0.972
#> GSM1233077 2 0.3686 0.838 0.000 0.860 0.140
#> GSM1233081 2 0.0237 0.976 0.004 0.996 0.000
#> GSM1233084 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233087 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233089 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233099 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233112 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233085 2 0.0424 0.973 0.008 0.992 0.000
#> GSM1233098 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233114 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233119 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233129 3 0.0424 0.987 0.000 0.008 0.992
#> GSM1233132 2 0.0424 0.973 0.008 0.992 0.000
#> GSM1233139 3 0.0592 0.984 0.000 0.012 0.988
#> GSM1233143 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233145 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233067 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233069 3 0.0424 0.987 0.000 0.008 0.992
#> GSM1233072 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233086 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233102 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233103 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233107 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233108 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233109 2 0.0424 0.973 0.008 0.992 0.000
#> GSM1233110 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233113 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233116 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233120 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233121 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233123 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233124 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233125 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233126 2 0.1031 0.958 0.000 0.976 0.024
#> GSM1233127 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233128 1 0.0000 0.983 1.000 0.000 0.000
#> GSM1233130 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233131 2 0.0237 0.976 0.004 0.996 0.000
#> GSM1233133 2 0.0237 0.976 0.004 0.996 0.000
#> GSM1233134 3 0.0424 0.987 0.000 0.008 0.992
#> GSM1233135 3 0.1411 0.961 0.000 0.036 0.964
#> GSM1233136 2 0.2711 0.894 0.000 0.912 0.088
#> GSM1233137 2 0.0000 0.978 0.000 1.000 0.000
#> GSM1233138 3 0.2537 0.911 0.000 0.080 0.920
#> GSM1233140 1 0.0747 0.969 0.984 0.016 0.000
#> GSM1233141 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233142 3 0.0000 0.991 0.000 0.000 1.000
#> GSM1233144 2 0.0237 0.976 0.004 0.996 0.000
#> GSM1233147 3 0.0892 0.977 0.000 0.020 0.980
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233002 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233003 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233014 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233015 4 0.1867 0.8726 0.000 0.000 0.072 0.928
#> GSM1233016 3 0.3400 0.7491 0.000 0.000 0.820 0.180
#> GSM1233024 2 0.4866 0.4885 0.000 0.596 0.404 0.000
#> GSM1233049 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233064 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233068 3 0.0921 0.8811 0.000 0.000 0.972 0.028
#> GSM1233073 3 0.4697 0.4574 0.000 0.000 0.644 0.356
#> GSM1233093 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233115 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1232992 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1232993 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233005 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233007 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233010 4 0.3311 0.7817 0.000 0.000 0.172 0.828
#> GSM1233013 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233018 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233019 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233021 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233025 4 0.1557 0.8827 0.000 0.000 0.056 0.944
#> GSM1233029 3 0.0336 0.8856 0.000 0.008 0.992 0.000
#> GSM1233030 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233031 3 0.4697 0.4574 0.000 0.000 0.644 0.356
#> GSM1233032 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233035 3 0.0707 0.8840 0.000 0.000 0.980 0.020
#> GSM1233038 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233039 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233042 3 0.0188 0.8888 0.000 0.000 0.996 0.004
#> GSM1233043 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233044 4 0.0817 0.8989 0.000 0.000 0.024 0.976
#> GSM1233046 4 0.4999 -0.0238 0.000 0.000 0.492 0.508
#> GSM1233051 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233054 4 0.2408 0.8486 0.000 0.000 0.104 0.896
#> GSM1233057 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233060 3 0.0921 0.8811 0.000 0.000 0.972 0.028
#> GSM1233062 3 0.0188 0.8877 0.000 0.004 0.996 0.000
#> GSM1233075 2 0.0707 0.8438 0.000 0.980 0.020 0.000
#> GSM1233078 3 0.4713 0.4480 0.000 0.000 0.640 0.360
#> GSM1233079 4 0.3801 0.6813 0.220 0.000 0.000 0.780
#> GSM1233082 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233083 1 0.1940 0.9239 0.924 0.000 0.000 0.076
#> GSM1233091 3 0.4643 0.4832 0.000 0.000 0.656 0.344
#> GSM1233095 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233096 4 0.1118 0.8861 0.036 0.000 0.000 0.964
#> GSM1233101 1 0.0921 0.9689 0.972 0.000 0.000 0.028
#> GSM1233105 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233117 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233118 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233001 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233006 3 0.2281 0.8151 0.000 0.096 0.904 0.000
#> GSM1233008 2 0.4661 0.5807 0.000 0.652 0.348 0.000
#> GSM1233009 2 0.4008 0.6936 0.000 0.756 0.244 0.000
#> GSM1233017 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233020 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233022 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233026 3 0.4040 0.6564 0.000 0.000 0.752 0.248
#> GSM1233028 3 0.4661 0.4744 0.000 0.000 0.652 0.348
#> GSM1233034 2 0.4981 0.3442 0.000 0.536 0.464 0.000
#> GSM1233040 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233048 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233056 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233058 3 0.2868 0.8006 0.000 0.000 0.864 0.136
#> GSM1233059 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233066 3 0.0921 0.8811 0.000 0.000 0.972 0.028
#> GSM1233071 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233074 2 0.4898 0.4652 0.000 0.584 0.416 0.000
#> GSM1233076 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233080 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233088 3 0.0921 0.8811 0.000 0.000 0.972 0.028
#> GSM1233090 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233092 3 0.4989 -0.1636 0.000 0.472 0.528 0.000
#> GSM1233094 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233097 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233100 4 0.2281 0.8553 0.000 0.000 0.096 0.904
#> GSM1233104 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233106 4 0.2281 0.8553 0.000 0.000 0.096 0.904
#> GSM1233111 4 0.4103 0.6232 0.256 0.000 0.000 0.744
#> GSM1233122 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233146 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1232994 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1232996 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1232997 3 0.2011 0.8302 0.000 0.080 0.920 0.000
#> GSM1232998 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1232999 3 0.2281 0.8151 0.000 0.096 0.904 0.000
#> GSM1233000 2 0.4907 0.4568 0.000 0.580 0.420 0.000
#> GSM1233004 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233011 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233012 2 0.4925 0.4393 0.000 0.572 0.428 0.000
#> GSM1233023 2 0.4948 0.4100 0.000 0.560 0.440 0.000
#> GSM1233027 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233033 4 0.0592 0.8989 0.016 0.000 0.000 0.984
#> GSM1233036 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233037 3 0.4477 0.5474 0.000 0.000 0.688 0.312
#> GSM1233041 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233045 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233047 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233050 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233052 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233053 4 0.4866 0.3217 0.404 0.000 0.000 0.596
#> GSM1233055 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233061 3 0.4661 0.4744 0.000 0.000 0.652 0.348
#> GSM1233063 4 0.0188 0.9051 0.004 0.000 0.000 0.996
#> GSM1233065 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233070 3 0.2281 0.8151 0.000 0.096 0.904 0.000
#> GSM1233077 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233081 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233084 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233087 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233089 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233099 4 0.3219 0.7907 0.000 0.000 0.164 0.836
#> GSM1233112 4 0.2469 0.8354 0.108 0.000 0.000 0.892
#> GSM1233085 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233098 2 0.3172 0.7663 0.000 0.840 0.160 0.000
#> GSM1233114 4 0.0592 0.8989 0.016 0.000 0.000 0.984
#> GSM1233119 4 0.3528 0.7564 0.000 0.000 0.192 0.808
#> GSM1233129 3 0.2281 0.8151 0.000 0.096 0.904 0.000
#> GSM1233132 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233139 3 0.2281 0.8151 0.000 0.096 0.904 0.000
#> GSM1233143 2 0.4697 0.5690 0.000 0.644 0.356 0.000
#> GSM1233145 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233067 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233069 2 0.4925 0.4393 0.000 0.572 0.428 0.000
#> GSM1233072 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233086 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233102 4 0.2081 0.8480 0.084 0.000 0.000 0.916
#> GSM1233103 3 0.0336 0.8877 0.000 0.000 0.992 0.008
#> GSM1233107 3 0.0921 0.8811 0.000 0.000 0.972 0.028
#> GSM1233108 4 0.4661 0.4519 0.348 0.000 0.000 0.652
#> GSM1233109 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233110 3 0.2530 0.8227 0.000 0.000 0.888 0.112
#> GSM1233113 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233116 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233120 4 0.1557 0.8827 0.000 0.000 0.056 0.944
#> GSM1233121 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233123 3 0.1389 0.8696 0.000 0.000 0.952 0.048
#> GSM1233124 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233125 1 0.1867 0.9250 0.928 0.000 0.000 0.072
#> GSM1233126 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233127 2 0.4661 0.5807 0.000 0.652 0.348 0.000
#> GSM1233128 1 0.0000 0.9912 1.000 0.000 0.000 0.000
#> GSM1233130 3 0.0921 0.8811 0.000 0.000 0.972 0.028
#> GSM1233131 4 0.0336 0.9051 0.000 0.000 0.008 0.992
#> GSM1233133 4 0.0000 0.9067 0.000 0.000 0.000 1.000
#> GSM1233134 3 0.3975 0.5887 0.000 0.240 0.760 0.000
#> GSM1233135 3 0.2281 0.8151 0.000 0.096 0.904 0.000
#> GSM1233136 3 0.0000 0.8896 0.000 0.000 1.000 0.000
#> GSM1233137 4 0.0336 0.9051 0.000 0.000 0.008 0.992
#> GSM1233138 3 0.2281 0.8151 0.000 0.096 0.904 0.000
#> GSM1233140 4 0.0188 0.9051 0.004 0.000 0.000 0.996
#> GSM1233141 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233142 2 0.0000 0.8536 0.000 1.000 0.000 0.000
#> GSM1233144 4 0.0188 0.9060 0.000 0.000 0.004 0.996
#> GSM1233147 3 0.2281 0.8151 0.000 0.096 0.904 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233002 1 0.0703 0.8648 0.976 0.000 0.000 0.024 0.000
#> GSM1233003 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233014 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233015 4 0.4278 0.0450 0.452 0.000 0.000 0.548 0.000
#> GSM1233016 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233024 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233049 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233064 3 0.4278 0.2767 0.000 0.000 0.548 0.452 0.000
#> GSM1233068 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233073 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233093 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233115 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1232992 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1232993 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233005 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233007 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233010 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233013 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233018 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233019 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233021 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233025 1 0.4283 0.2200 0.544 0.000 0.000 0.456 0.000
#> GSM1233029 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233030 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233031 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233032 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233035 4 0.3586 0.5932 0.000 0.000 0.264 0.736 0.000
#> GSM1233038 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233039 3 0.4300 0.2071 0.000 0.000 0.524 0.476 0.000
#> GSM1233042 4 0.0510 0.8819 0.000 0.000 0.016 0.984 0.000
#> GSM1233043 3 0.3932 0.5511 0.000 0.000 0.672 0.328 0.000
#> GSM1233044 4 0.4305 -0.0879 0.488 0.000 0.000 0.512 0.000
#> GSM1233046 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233051 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233054 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233057 4 0.4307 -0.1637 0.000 0.000 0.496 0.504 0.000
#> GSM1233060 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233062 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233075 2 0.0963 0.9389 0.000 0.964 0.036 0.000 0.000
#> GSM1233078 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233079 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233082 1 0.1197 0.8517 0.952 0.000 0.000 0.048 0.000
#> GSM1233083 5 0.4268 0.2974 0.444 0.000 0.000 0.000 0.556
#> GSM1233091 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233095 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233096 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233101 5 0.2605 0.8146 0.148 0.000 0.000 0.000 0.852
#> GSM1233105 1 0.3143 0.6994 0.796 0.000 0.000 0.204 0.000
#> GSM1233117 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233118 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233001 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233006 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233008 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233009 3 0.2966 0.7385 0.000 0.184 0.816 0.000 0.000
#> GSM1233017 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233020 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233022 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233026 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233028 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233034 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233040 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233048 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233056 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233058 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233059 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233066 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233071 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233074 3 0.0404 0.9297 0.000 0.012 0.988 0.000 0.000
#> GSM1233076 3 0.0162 0.9359 0.000 0.000 0.996 0.004 0.000
#> GSM1233080 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233088 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233090 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233092 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233094 3 0.3837 0.5865 0.000 0.000 0.692 0.308 0.000
#> GSM1233097 3 0.4300 0.2104 0.000 0.000 0.524 0.476 0.000
#> GSM1233100 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233104 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233106 4 0.4088 0.3072 0.368 0.000 0.000 0.632 0.000
#> GSM1233111 1 0.0162 0.8724 0.996 0.000 0.000 0.000 0.004
#> GSM1233122 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233146 3 0.2230 0.8433 0.000 0.000 0.884 0.116 0.000
#> GSM1232994 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1232996 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1232997 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1232998 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1232999 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233000 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233004 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233011 3 0.0162 0.9359 0.000 0.000 0.996 0.004 0.000
#> GSM1233012 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233023 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233027 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233033 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233036 3 0.0162 0.9359 0.000 0.000 0.996 0.004 0.000
#> GSM1233037 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233041 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233045 3 0.2852 0.7807 0.000 0.000 0.828 0.172 0.000
#> GSM1233047 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233050 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233052 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233053 1 0.3949 0.3600 0.668 0.000 0.000 0.000 0.332
#> GSM1233055 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233061 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233063 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233065 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233070 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233077 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233081 1 0.1121 0.8544 0.956 0.000 0.000 0.044 0.000
#> GSM1233084 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233087 1 0.4291 0.1968 0.536 0.000 0.000 0.464 0.000
#> GSM1233089 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233099 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233112 1 0.1121 0.8410 0.956 0.000 0.000 0.000 0.044
#> GSM1233085 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233098 2 0.4201 0.2921 0.000 0.592 0.408 0.000 0.000
#> GSM1233114 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233119 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233129 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233132 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233139 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233143 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233145 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233067 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233069 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233072 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233086 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233102 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233103 4 0.0162 0.8939 0.000 0.000 0.004 0.996 0.000
#> GSM1233107 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233108 1 0.1732 0.8043 0.920 0.000 0.000 0.000 0.080
#> GSM1233109 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233110 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233113 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233116 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233120 4 0.4287 0.0145 0.460 0.000 0.000 0.540 0.000
#> GSM1233121 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233123 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233124 3 0.1478 0.8915 0.000 0.000 0.936 0.064 0.000
#> GSM1233125 5 0.3707 0.6188 0.284 0.000 0.000 0.000 0.716
#> GSM1233126 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233127 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233128 5 0.0000 0.9552 0.000 0.000 0.000 0.000 1.000
#> GSM1233130 4 0.0000 0.8977 0.000 0.000 0.000 1.000 0.000
#> GSM1233131 1 0.4150 0.3942 0.612 0.000 0.000 0.388 0.000
#> GSM1233133 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233134 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233135 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233136 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233137 1 0.4242 0.3007 0.572 0.000 0.000 0.428 0.000
#> GSM1233138 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
#> GSM1233140 1 0.0000 0.8748 1.000 0.000 0.000 0.000 0.000
#> GSM1233141 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233142 2 0.0000 0.9797 0.000 1.000 0.000 0.000 0.000
#> GSM1233144 1 0.4235 0.3119 0.576 0.000 0.000 0.424 0.000
#> GSM1233147 3 0.0000 0.9383 0.000 0.000 1.000 0.000 0.000
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.0146 0.97073 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1233002 3 0.2378 0.71352 0.000 0.000 0.848 0.000 0.152 0.000
#> GSM1233003 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233014 6 0.1957 0.90034 0.000 0.000 0.000 0.112 0.000 0.888
#> GSM1233015 3 0.1196 0.77865 0.000 0.000 0.952 0.040 0.008 0.000
#> GSM1233016 4 0.2527 0.80617 0.000 0.000 0.168 0.832 0.000 0.000
#> GSM1233024 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233049 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233064 4 0.3288 0.51014 0.000 0.000 0.000 0.724 0.000 0.276
#> GSM1233068 4 0.2219 0.81773 0.000 0.000 0.136 0.864 0.000 0.000
#> GSM1233073 4 0.2300 0.81585 0.000 0.000 0.144 0.856 0.000 0.000
#> GSM1233093 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233115 5 0.0260 0.87688 0.000 0.000 0.008 0.000 0.992 0.000
#> GSM1232992 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232993 6 0.1765 0.90581 0.000 0.000 0.000 0.096 0.000 0.904
#> GSM1233005 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233007 6 0.2260 0.88197 0.000 0.000 0.000 0.140 0.000 0.860
#> GSM1233010 4 0.3126 0.74670 0.000 0.000 0.248 0.752 0.000 0.000
#> GSM1233013 2 0.0146 0.97073 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1233018 2 0.0146 0.97073 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1233019 2 0.0146 0.97073 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1233021 2 0.0146 0.97073 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1233025 3 0.0909 0.79067 0.000 0.000 0.968 0.020 0.012 0.000
#> GSM1233029 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233030 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233031 4 0.2219 0.81674 0.000 0.000 0.136 0.864 0.000 0.000
#> GSM1233032 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233035 4 0.5076 0.60687 0.000 0.000 0.132 0.620 0.000 0.248
#> GSM1233038 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233039 4 0.3023 0.59012 0.000 0.000 0.000 0.768 0.000 0.232
#> GSM1233042 4 0.1327 0.80909 0.000 0.000 0.064 0.936 0.000 0.000
#> GSM1233043 4 0.3838 0.00732 0.000 0.000 0.000 0.552 0.000 0.448
#> GSM1233044 3 0.0777 0.78308 0.000 0.000 0.972 0.024 0.004 0.000
#> GSM1233046 4 0.2454 0.81094 0.000 0.000 0.160 0.840 0.000 0.000
#> GSM1233051 5 0.0632 0.87641 0.000 0.000 0.024 0.000 0.976 0.000
#> GSM1233054 4 0.3647 0.61354 0.000 0.000 0.360 0.640 0.000 0.000
#> GSM1233057 4 0.2793 0.62525 0.000 0.000 0.000 0.800 0.000 0.200
#> GSM1233060 4 0.0000 0.78325 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1233062 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233075 2 0.2300 0.80946 0.000 0.856 0.000 0.000 0.000 0.144
#> GSM1233078 4 0.2260 0.81641 0.000 0.000 0.140 0.860 0.000 0.000
#> GSM1233079 5 0.0000 0.87453 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1233082 3 0.1411 0.78373 0.000 0.000 0.936 0.004 0.060 0.000
#> GSM1233083 5 0.0632 0.85813 0.024 0.000 0.000 0.000 0.976 0.000
#> GSM1233091 4 0.2092 0.81788 0.000 0.000 0.124 0.876 0.000 0.000
#> GSM1233095 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233096 5 0.0146 0.87601 0.000 0.000 0.004 0.000 0.996 0.000
#> GSM1233101 1 0.2454 0.79227 0.840 0.000 0.000 0.000 0.160 0.000
#> GSM1233105 3 0.1204 0.78332 0.000 0.000 0.944 0.000 0.056 0.000
#> GSM1233117 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233118 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233001 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233006 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233008 6 0.0146 0.93494 0.000 0.004 0.000 0.000 0.000 0.996
#> GSM1233009 6 0.1501 0.87594 0.000 0.076 0.000 0.000 0.000 0.924
#> GSM1233017 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233020 2 0.0146 0.97073 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1233022 6 0.0260 0.93519 0.000 0.000 0.000 0.008 0.000 0.992
#> GSM1233026 4 0.2378 0.81341 0.000 0.000 0.152 0.848 0.000 0.000
#> GSM1233028 4 0.2260 0.81613 0.000 0.000 0.140 0.860 0.000 0.000
#> GSM1233034 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233040 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233048 1 0.0146 0.98688 0.996 0.000 0.000 0.000 0.004 0.000
#> GSM1233056 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233058 4 0.2219 0.81674 0.000 0.000 0.136 0.864 0.000 0.000
#> GSM1233059 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233066 4 0.1663 0.81580 0.000 0.000 0.088 0.912 0.000 0.000
#> GSM1233071 6 0.1863 0.90229 0.000 0.000 0.000 0.104 0.000 0.896
#> GSM1233074 6 0.0458 0.92831 0.000 0.016 0.000 0.000 0.000 0.984
#> GSM1233076 6 0.2562 0.85601 0.000 0.000 0.000 0.172 0.000 0.828
#> GSM1233080 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233088 4 0.0000 0.78325 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1233090 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233092 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233094 4 0.3867 -0.13854 0.000 0.000 0.000 0.512 0.000 0.488
#> GSM1233097 4 0.3330 0.50041 0.000 0.000 0.000 0.716 0.000 0.284
#> GSM1233100 4 0.3198 0.73751 0.000 0.000 0.260 0.740 0.000 0.000
#> GSM1233104 6 0.2219 0.88625 0.000 0.000 0.000 0.136 0.000 0.864
#> GSM1233106 3 0.2562 0.64447 0.000 0.000 0.828 0.172 0.000 0.000
#> GSM1233111 5 0.0000 0.87453 0.000 0.000 0.000 0.000 1.000 0.000
#> GSM1233122 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233146 6 0.3464 0.66497 0.000 0.000 0.000 0.312 0.000 0.688
#> GSM1232994 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232996 2 0.0146 0.97073 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1232997 6 0.0547 0.93209 0.000 0.000 0.000 0.020 0.000 0.980
#> GSM1232998 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1232999 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233000 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233004 3 0.3828 0.32002 0.000 0.000 0.560 0.000 0.440 0.000
#> GSM1233011 6 0.2260 0.88234 0.000 0.000 0.000 0.140 0.000 0.860
#> GSM1233012 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233023 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233027 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233033 5 0.3789 0.03661 0.000 0.000 0.416 0.000 0.584 0.000
#> GSM1233036 6 0.2135 0.88971 0.000 0.000 0.000 0.128 0.000 0.872
#> GSM1233037 4 0.2219 0.81674 0.000 0.000 0.136 0.864 0.000 0.000
#> GSM1233041 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233045 6 0.3607 0.58528 0.000 0.000 0.000 0.348 0.000 0.652
#> GSM1233047 5 0.1327 0.85482 0.000 0.000 0.064 0.000 0.936 0.000
#> GSM1233050 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233052 5 0.0547 0.87723 0.000 0.000 0.020 0.000 0.980 0.000
#> GSM1233053 5 0.0547 0.87723 0.000 0.000 0.020 0.000 0.980 0.000
#> GSM1233055 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233061 4 0.2378 0.81328 0.000 0.000 0.152 0.848 0.000 0.000
#> GSM1233063 5 0.0458 0.87779 0.000 0.000 0.016 0.000 0.984 0.000
#> GSM1233065 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233070 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233077 6 0.1957 0.89926 0.000 0.000 0.000 0.112 0.000 0.888
#> GSM1233081 3 0.1714 0.76622 0.000 0.000 0.908 0.000 0.092 0.000
#> GSM1233084 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233087 3 0.0891 0.78511 0.000 0.000 0.968 0.024 0.008 0.000
#> GSM1233089 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233099 4 0.3101 0.75029 0.000 0.000 0.244 0.756 0.000 0.000
#> GSM1233112 5 0.0458 0.87786 0.000 0.000 0.016 0.000 0.984 0.000
#> GSM1233085 5 0.2092 0.80042 0.000 0.000 0.124 0.000 0.876 0.000
#> GSM1233098 2 0.3847 0.19884 0.000 0.544 0.000 0.000 0.000 0.456
#> GSM1233114 5 0.3244 0.50269 0.000 0.000 0.268 0.000 0.732 0.000
#> GSM1233119 4 0.3101 0.74864 0.000 0.000 0.244 0.756 0.000 0.000
#> GSM1233129 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233132 5 0.3151 0.59862 0.000 0.000 0.252 0.000 0.748 0.000
#> GSM1233139 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233143 6 0.0146 0.93494 0.000 0.004 0.000 0.000 0.000 0.996
#> GSM1233145 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233067 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233069 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233072 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233086 6 0.2135 0.89099 0.000 0.000 0.000 0.128 0.000 0.872
#> GSM1233102 3 0.3854 0.30148 0.000 0.000 0.536 0.000 0.464 0.000
#> GSM1233103 4 0.0000 0.78325 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1233107 4 0.1765 0.81727 0.000 0.000 0.096 0.904 0.000 0.000
#> GSM1233108 5 0.0458 0.87777 0.000 0.000 0.016 0.000 0.984 0.000
#> GSM1233109 3 0.3756 0.40065 0.000 0.000 0.600 0.000 0.400 0.000
#> GSM1233110 4 0.0000 0.78325 0.000 0.000 0.000 1.000 0.000 0.000
#> GSM1233113 2 0.0146 0.97073 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1233116 2 0.0146 0.97073 0.000 0.996 0.004 0.000 0.000 0.000
#> GSM1233120 3 0.1285 0.76568 0.000 0.000 0.944 0.052 0.004 0.000
#> GSM1233121 6 0.2378 0.87479 0.000 0.000 0.000 0.152 0.000 0.848
#> GSM1233123 4 0.1957 0.81815 0.000 0.000 0.112 0.888 0.000 0.000
#> GSM1233124 6 0.3076 0.77826 0.000 0.000 0.000 0.240 0.000 0.760
#> GSM1233125 5 0.3547 0.53113 0.300 0.000 0.004 0.000 0.696 0.000
#> GSM1233126 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233127 6 0.0146 0.93494 0.000 0.004 0.000 0.000 0.000 0.996
#> GSM1233128 1 0.0000 0.99007 1.000 0.000 0.000 0.000 0.000 0.000
#> GSM1233130 4 0.0363 0.78890 0.000 0.000 0.012 0.988 0.000 0.000
#> GSM1233131 3 0.1151 0.79316 0.000 0.000 0.956 0.012 0.032 0.000
#> GSM1233133 3 0.3823 0.23483 0.000 0.000 0.564 0.000 0.436 0.000
#> GSM1233134 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233135 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233136 6 0.2219 0.88625 0.000 0.000 0.000 0.136 0.000 0.864
#> GSM1233137 3 0.0717 0.79195 0.000 0.000 0.976 0.008 0.016 0.000
#> GSM1233138 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
#> GSM1233140 3 0.3833 0.31816 0.000 0.000 0.556 0.000 0.444 0.000
#> GSM1233141 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233142 2 0.0000 0.97182 0.000 1.000 0.000 0.000 0.000 0.000
#> GSM1233144 3 0.0458 0.79189 0.000 0.000 0.984 0.000 0.016 0.000
#> GSM1233147 6 0.0000 0.93659 0.000 0.000 0.000 0.000 0.000 1.000
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> ATC:pam 156 0.966 1.000 0.943 2
#> ATC:pam 155 0.436 0.517 0.909 3
#> ATC:pam 139 0.427 0.755 0.400 4
#> ATC:pam 140 0.479 0.463 0.166 5
#> ATC:pam 147 0.400 0.326 0.204 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 51941 rows and 156 columns.
#> Top rows (1000, 2000, 3000, 4000, 5000) are extracted by 'ATC' method.
#> Subgroups are detected by 'mclust' method.
#> Performed in total 1250 partitions by row resampling.
#> Best k for subgroups seems to be 2.
#>
#> Following methods can be applied to this 'ConsensusPartition' object:
#> [1] "cola_report" "collect_classes" "collect_plots"
#> [4] "collect_stats" "colnames" "compare_signatures"
#> [7] "consensus_heatmap" "dimension_reduction" "functional_enrichment"
#> [10] "get_anno_col" "get_anno" "get_classes"
#> [13] "get_consensus" "get_matrix" "get_membership"
#> [16] "get_param" "get_signatures" "get_stats"
#> [19] "is_best_k" "is_stable_k" "membership_heatmap"
#> [22] "ncol" "nrow" "plot_ecdf"
#> [25] "rownames" "select_partition_number" "show"
#> [28] "suggest_best_k" "test_to_known_factors"
collect_plots() function collects all the plots made from res for all k (number of partitions)
into one single page to provide an easy and fast comparison between different k.
collect_plots(res)
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 0.594 0.863 0.932 0.4281 0.557 0.557
#> 3 3 0.392 0.815 0.774 0.1858 0.497 0.348
#> 4 4 0.388 0.384 0.639 0.2768 0.549 0.300
#> 5 5 0.447 0.466 0.653 0.0759 0.631 0.287
#> 6 6 0.551 0.621 0.739 0.0823 0.870 0.626
suggest_best_k() suggests the best \(k\) based on these statistics. The rules are as follows:
suggest_best_k(res)
#> [1] 2
Following shows the table of the partitions (You need to click the show/hide
code output link to see it). The membership matrix (columns with name p*)
is inferred by
clue::cl_consensus()
function with the SE method. Basically the value in the membership matrix
represents the probability to belong to a certain group. The finall class
label for an item is determined with the group with highest probability it
belongs to.
In get_classes() function, the entropy is calculated from the membership
matrix and the silhouette score is calculated from the consensus matrix.
cbind(get_classes(res, k = 2), get_membership(res, k = 2))
#> class entropy silhouette p1 p2
#> GSM1232995 2 0.7299 0.817 0.204 0.796
#> GSM1233002 1 0.0000 0.942 1.000 0.000
#> GSM1233003 1 0.0000 0.942 1.000 0.000
#> GSM1233014 2 0.0000 0.879 0.000 1.000
#> GSM1233015 1 0.0000 0.942 1.000 0.000
#> GSM1233016 1 0.0000 0.942 1.000 0.000
#> GSM1233024 1 0.9522 0.375 0.628 0.372
#> GSM1233049 1 0.0000 0.942 1.000 0.000
#> GSM1233064 1 0.8144 0.656 0.748 0.252
#> GSM1233068 1 0.0000 0.942 1.000 0.000
#> GSM1233073 1 0.1633 0.927 0.976 0.024
#> GSM1233093 1 0.0000 0.942 1.000 0.000
#> GSM1233115 1 0.0000 0.942 1.000 0.000
#> GSM1232992 2 0.1414 0.874 0.020 0.980
#> GSM1232993 1 0.2603 0.912 0.956 0.044
#> GSM1233005 2 0.7299 0.817 0.204 0.796
#> GSM1233007 1 0.0376 0.940 0.996 0.004
#> GSM1233010 1 0.0000 0.942 1.000 0.000
#> GSM1233013 2 0.5842 0.849 0.140 0.860
#> GSM1233018 2 0.7299 0.817 0.204 0.796
#> GSM1233019 2 0.7299 0.817 0.204 0.796
#> GSM1233021 2 0.7299 0.817 0.204 0.796
#> GSM1233025 1 0.0000 0.942 1.000 0.000
#> GSM1233029 2 0.0000 0.879 0.000 1.000
#> GSM1233030 2 0.5946 0.847 0.144 0.856
#> GSM1233031 1 0.2778 0.908 0.952 0.048
#> GSM1233032 1 0.0000 0.942 1.000 0.000
#> GSM1233035 1 0.0000 0.942 1.000 0.000
#> GSM1233038 1 0.0000 0.942 1.000 0.000
#> GSM1233039 1 0.8763 0.567 0.704 0.296
#> GSM1233042 1 0.0376 0.940 0.996 0.004
#> GSM1233043 1 0.6343 0.795 0.840 0.160
#> GSM1233044 1 0.0000 0.942 1.000 0.000
#> GSM1233046 1 0.0376 0.940 0.996 0.004
#> GSM1233051 1 0.0000 0.942 1.000 0.000
#> GSM1233054 1 0.0000 0.942 1.000 0.000
#> GSM1233057 1 0.5294 0.841 0.880 0.120
#> GSM1233060 1 0.8144 0.655 0.748 0.252
#> GSM1233062 2 0.9850 0.362 0.428 0.572
#> GSM1233075 2 0.0000 0.879 0.000 1.000
#> GSM1233078 1 0.0000 0.942 1.000 0.000
#> GSM1233079 1 0.0000 0.942 1.000 0.000
#> GSM1233082 1 0.0000 0.942 1.000 0.000
#> GSM1233083 1 0.0000 0.942 1.000 0.000
#> GSM1233091 1 0.0000 0.942 1.000 0.000
#> GSM1233095 1 0.0000 0.942 1.000 0.000
#> GSM1233096 1 0.0000 0.942 1.000 0.000
#> GSM1233101 1 0.0000 0.942 1.000 0.000
#> GSM1233105 1 0.0000 0.942 1.000 0.000
#> GSM1233117 2 0.0000 0.879 0.000 1.000
#> GSM1233118 2 0.0000 0.879 0.000 1.000
#> GSM1233001 2 0.0000 0.879 0.000 1.000
#> GSM1233006 2 0.1633 0.873 0.024 0.976
#> GSM1233008 1 0.4815 0.859 0.896 0.104
#> GSM1233009 2 0.0000 0.879 0.000 1.000
#> GSM1233017 2 0.0000 0.879 0.000 1.000
#> GSM1233020 2 0.7299 0.817 0.204 0.796
#> GSM1233022 1 0.5629 0.829 0.868 0.132
#> GSM1233026 1 0.0000 0.942 1.000 0.000
#> GSM1233028 1 0.0938 0.935 0.988 0.012
#> GSM1233034 1 0.1633 0.927 0.976 0.024
#> GSM1233040 1 0.0000 0.942 1.000 0.000
#> GSM1233048 1 0.0000 0.942 1.000 0.000
#> GSM1233056 1 0.0000 0.942 1.000 0.000
#> GSM1233058 1 0.0000 0.942 1.000 0.000
#> GSM1233059 1 0.0000 0.942 1.000 0.000
#> GSM1233066 1 0.3431 0.895 0.936 0.064
#> GSM1233071 2 0.6438 0.821 0.164 0.836
#> GSM1233074 1 0.9087 0.502 0.676 0.324
#> GSM1233076 2 0.8386 0.740 0.268 0.732
#> GSM1233080 1 0.0000 0.942 1.000 0.000
#> GSM1233088 1 0.8499 0.608 0.724 0.276
#> GSM1233090 1 0.0000 0.942 1.000 0.000
#> GSM1233092 2 0.0000 0.879 0.000 1.000
#> GSM1233094 1 0.0672 0.937 0.992 0.008
#> GSM1233097 1 0.0000 0.942 1.000 0.000
#> GSM1233100 1 0.0000 0.942 1.000 0.000
#> GSM1233104 2 0.9427 0.552 0.360 0.640
#> GSM1233106 1 0.0000 0.942 1.000 0.000
#> GSM1233111 1 0.0000 0.942 1.000 0.000
#> GSM1233122 2 0.0000 0.879 0.000 1.000
#> GSM1233146 1 0.0000 0.942 1.000 0.000
#> GSM1232994 2 0.8081 0.763 0.248 0.752
#> GSM1232996 2 0.8327 0.739 0.264 0.736
#> GSM1232997 1 0.4431 0.869 0.908 0.092
#> GSM1232998 2 0.7528 0.804 0.216 0.784
#> GSM1232999 2 0.0000 0.879 0.000 1.000
#> GSM1233000 2 0.0000 0.879 0.000 1.000
#> GSM1233004 1 0.0000 0.942 1.000 0.000
#> GSM1233011 1 0.5519 0.834 0.872 0.128
#> GSM1233012 2 0.5842 0.849 0.140 0.860
#> GSM1233023 1 0.8909 0.542 0.692 0.308
#> GSM1233027 1 0.9710 0.286 0.600 0.400
#> GSM1233033 1 0.0000 0.942 1.000 0.000
#> GSM1233036 1 0.0938 0.935 0.988 0.012
#> GSM1233037 1 0.1633 0.927 0.976 0.024
#> GSM1233041 1 0.0000 0.942 1.000 0.000
#> GSM1233045 1 0.7602 0.709 0.780 0.220
#> GSM1233047 1 0.0000 0.942 1.000 0.000
#> GSM1233050 1 0.0000 0.942 1.000 0.000
#> GSM1233052 1 0.0000 0.942 1.000 0.000
#> GSM1233053 1 0.0000 0.942 1.000 0.000
#> GSM1233055 1 0.0000 0.942 1.000 0.000
#> GSM1233061 1 0.0000 0.942 1.000 0.000
#> GSM1233063 1 0.0000 0.942 1.000 0.000
#> GSM1233065 2 0.7376 0.813 0.208 0.792
#> GSM1233070 2 0.0000 0.879 0.000 1.000
#> GSM1233077 2 0.0000 0.879 0.000 1.000
#> GSM1233081 1 0.0000 0.942 1.000 0.000
#> GSM1233084 1 0.0000 0.942 1.000 0.000
#> GSM1233087 1 0.0000 0.942 1.000 0.000
#> GSM1233089 2 0.7299 0.817 0.204 0.796
#> GSM1233099 1 0.0000 0.942 1.000 0.000
#> GSM1233112 1 0.0000 0.942 1.000 0.000
#> GSM1233085 1 0.0000 0.942 1.000 0.000
#> GSM1233098 2 0.0000 0.879 0.000 1.000
#> GSM1233114 1 0.0000 0.942 1.000 0.000
#> GSM1233119 1 0.0000 0.942 1.000 0.000
#> GSM1233129 1 0.7376 0.728 0.792 0.208
#> GSM1233132 1 0.0000 0.942 1.000 0.000
#> GSM1233139 2 0.0000 0.879 0.000 1.000
#> GSM1233143 1 0.4939 0.856 0.892 0.108
#> GSM1233145 1 0.0000 0.942 1.000 0.000
#> GSM1233067 2 0.7299 0.817 0.204 0.796
#> GSM1233069 2 0.0000 0.879 0.000 1.000
#> GSM1233072 2 0.0000 0.879 0.000 1.000
#> GSM1233086 2 0.6247 0.842 0.156 0.844
#> GSM1233102 1 0.0000 0.942 1.000 0.000
#> GSM1233103 1 0.1633 0.927 0.976 0.024
#> GSM1233107 1 0.0000 0.942 1.000 0.000
#> GSM1233108 1 0.0000 0.942 1.000 0.000
#> GSM1233109 1 0.0000 0.942 1.000 0.000
#> GSM1233110 1 0.4690 0.862 0.900 0.100
#> GSM1233113 2 0.7299 0.817 0.204 0.796
#> GSM1233116 2 0.0000 0.879 0.000 1.000
#> GSM1233120 1 0.0000 0.942 1.000 0.000
#> GSM1233121 2 0.0000 0.879 0.000 1.000
#> GSM1233123 1 0.0000 0.942 1.000 0.000
#> GSM1233124 2 0.7376 0.813 0.208 0.792
#> GSM1233125 1 0.0000 0.942 1.000 0.000
#> GSM1233126 2 0.7299 0.817 0.204 0.796
#> GSM1233127 2 0.0000 0.879 0.000 1.000
#> GSM1233128 1 0.0000 0.942 1.000 0.000
#> GSM1233130 1 0.9129 0.484 0.672 0.328
#> GSM1233131 1 0.0000 0.942 1.000 0.000
#> GSM1233133 1 0.0000 0.942 1.000 0.000
#> GSM1233134 2 0.0000 0.879 0.000 1.000
#> GSM1233135 1 1.0000 -0.134 0.504 0.496
#> GSM1233136 2 0.9087 0.646 0.324 0.676
#> GSM1233137 1 0.0000 0.942 1.000 0.000
#> GSM1233138 1 0.8443 0.613 0.728 0.272
#> GSM1233140 1 0.0000 0.942 1.000 0.000
#> GSM1233141 2 0.0000 0.879 0.000 1.000
#> GSM1233142 2 0.0000 0.879 0.000 1.000
#> GSM1233144 1 0.0000 0.942 1.000 0.000
#> GSM1233147 2 0.0000 0.879 0.000 1.000
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 2 0.6981 0.735 0.228 0.704 0.068
#> GSM1233002 1 0.6143 0.955 0.684 0.304 0.012
#> GSM1233003 3 0.6897 0.905 0.040 0.292 0.668
#> GSM1233014 2 0.4974 0.768 0.000 0.764 0.236
#> GSM1233015 1 0.5797 0.965 0.712 0.280 0.008
#> GSM1233016 1 0.5497 0.962 0.708 0.292 0.000
#> GSM1233024 2 0.3644 0.784 0.124 0.872 0.004
#> GSM1233049 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233064 2 0.0475 0.782 0.004 0.992 0.004
#> GSM1233068 2 0.2200 0.758 0.056 0.940 0.004
#> GSM1233073 2 0.0237 0.780 0.000 0.996 0.004
#> GSM1233093 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233115 1 0.8847 0.733 0.552 0.300 0.148
#> GSM1232992 2 0.6808 0.763 0.084 0.732 0.184
#> GSM1232993 2 0.0592 0.777 0.000 0.988 0.012
#> GSM1233005 2 0.6019 0.720 0.288 0.700 0.012
#> GSM1233007 2 0.1529 0.760 0.000 0.960 0.040
#> GSM1233010 2 0.1860 0.760 0.052 0.948 0.000
#> GSM1233013 2 0.7144 0.734 0.220 0.700 0.080
#> GSM1233018 2 0.6019 0.720 0.288 0.700 0.012
#> GSM1233019 2 0.6019 0.720 0.288 0.700 0.012
#> GSM1233021 2 0.6019 0.720 0.288 0.700 0.012
#> GSM1233025 1 0.6051 0.970 0.696 0.292 0.012
#> GSM1233029 2 0.5517 0.757 0.004 0.728 0.268
#> GSM1233030 2 0.5722 0.745 0.004 0.704 0.292
#> GSM1233031 2 0.0237 0.780 0.000 0.996 0.004
#> GSM1233032 1 0.6051 0.970 0.696 0.292 0.012
#> GSM1233035 2 0.4575 0.554 0.184 0.812 0.004
#> GSM1233038 1 0.6051 0.970 0.696 0.292 0.012
#> GSM1233039 2 0.0747 0.784 0.016 0.984 0.000
#> GSM1233042 2 0.1643 0.756 0.000 0.956 0.044
#> GSM1233043 2 0.0848 0.782 0.008 0.984 0.008
#> GSM1233044 2 0.1950 0.754 0.040 0.952 0.008
#> GSM1233046 2 0.0592 0.777 0.000 0.988 0.012
#> GSM1233051 3 0.8371 0.797 0.116 0.292 0.592
#> GSM1233054 3 0.6008 0.821 0.000 0.372 0.628
#> GSM1233057 2 0.0747 0.783 0.016 0.984 0.000
#> GSM1233060 2 0.0237 0.780 0.000 0.996 0.004
#> GSM1233062 2 0.1031 0.786 0.024 0.976 0.000
#> GSM1233075 2 0.5497 0.746 0.000 0.708 0.292
#> GSM1233078 2 0.4465 0.551 0.176 0.820 0.004
#> GSM1233079 1 0.5797 0.965 0.712 0.280 0.008
#> GSM1233082 1 0.5831 0.968 0.708 0.284 0.008
#> GSM1233083 3 0.6326 0.930 0.020 0.292 0.688
#> GSM1233091 2 0.1643 0.756 0.000 0.956 0.044
#> GSM1233095 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233096 1 0.5831 0.968 0.708 0.284 0.008
#> GSM1233101 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233105 1 0.5797 0.965 0.712 0.280 0.008
#> GSM1233117 2 0.5722 0.745 0.004 0.704 0.292
#> GSM1233118 2 0.6820 0.746 0.052 0.700 0.248
#> GSM1233001 2 0.5722 0.745 0.004 0.704 0.292
#> GSM1233006 2 0.5497 0.746 0.000 0.708 0.292
#> GSM1233008 2 0.2448 0.780 0.076 0.924 0.000
#> GSM1233009 2 0.7024 0.748 0.072 0.704 0.224
#> GSM1233017 2 0.6562 0.746 0.036 0.700 0.264
#> GSM1233020 2 0.6019 0.720 0.288 0.700 0.012
#> GSM1233022 2 0.1399 0.766 0.028 0.968 0.004
#> GSM1233026 2 0.2096 0.748 0.052 0.944 0.004
#> GSM1233028 2 0.0237 0.780 0.000 0.996 0.004
#> GSM1233034 2 0.2261 0.768 0.068 0.932 0.000
#> GSM1233040 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233048 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233056 3 0.5722 0.946 0.004 0.292 0.704
#> GSM1233058 2 0.1643 0.756 0.000 0.956 0.044
#> GSM1233059 3 0.6193 0.934 0.016 0.292 0.692
#> GSM1233066 2 0.0592 0.781 0.012 0.988 0.000
#> GSM1233071 2 0.5465 0.748 0.000 0.712 0.288
#> GSM1233074 2 0.2550 0.791 0.056 0.932 0.012
#> GSM1233076 2 0.1031 0.789 0.000 0.976 0.024
#> GSM1233080 3 0.9693 0.453 0.252 0.292 0.456
#> GSM1233088 2 0.0237 0.780 0.000 0.996 0.004
#> GSM1233090 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233092 2 0.5497 0.746 0.000 0.708 0.292
#> GSM1233094 2 0.1529 0.760 0.000 0.960 0.040
#> GSM1233097 2 0.1411 0.763 0.000 0.964 0.036
#> GSM1233100 2 0.1860 0.750 0.000 0.948 0.052
#> GSM1233104 2 0.1453 0.788 0.024 0.968 0.008
#> GSM1233106 1 0.5656 0.963 0.712 0.284 0.004
#> GSM1233111 1 0.5797 0.965 0.712 0.280 0.008
#> GSM1233122 2 0.5722 0.745 0.004 0.704 0.292
#> GSM1233146 1 0.5621 0.939 0.692 0.308 0.000
#> GSM1232994 2 0.6019 0.720 0.288 0.700 0.012
#> GSM1232996 2 0.6019 0.720 0.288 0.700 0.012
#> GSM1232997 2 0.2261 0.768 0.068 0.932 0.000
#> GSM1232998 2 0.6019 0.720 0.288 0.700 0.012
#> GSM1232999 2 0.5397 0.752 0.000 0.720 0.280
#> GSM1233000 2 0.5497 0.746 0.000 0.708 0.292
#> GSM1233004 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233011 2 0.0747 0.783 0.016 0.984 0.000
#> GSM1233012 2 0.6625 0.768 0.080 0.744 0.176
#> GSM1233023 2 0.2682 0.790 0.076 0.920 0.004
#> GSM1233027 2 0.5848 0.732 0.268 0.720 0.012
#> GSM1233033 1 0.5797 0.965 0.712 0.280 0.008
#> GSM1233036 2 0.1964 0.761 0.056 0.944 0.000
#> GSM1233037 2 0.0592 0.779 0.012 0.988 0.000
#> GSM1233041 1 0.6051 0.970 0.696 0.292 0.012
#> GSM1233045 2 0.0848 0.782 0.008 0.984 0.008
#> GSM1233047 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233050 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233052 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233053 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233055 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233061 2 0.1643 0.756 0.000 0.956 0.044
#> GSM1233063 1 0.5864 0.969 0.704 0.288 0.008
#> GSM1233065 2 0.4235 0.772 0.176 0.824 0.000
#> GSM1233070 2 0.5497 0.746 0.000 0.708 0.292
#> GSM1233077 2 0.5497 0.746 0.000 0.708 0.292
#> GSM1233081 2 0.2116 0.751 0.040 0.948 0.012
#> GSM1233084 1 0.6051 0.970 0.696 0.292 0.012
#> GSM1233087 2 0.2173 0.750 0.048 0.944 0.008
#> GSM1233089 2 0.6019 0.720 0.288 0.700 0.012
#> GSM1233099 3 0.5529 0.944 0.000 0.296 0.704
#> GSM1233112 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233085 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233098 2 0.5497 0.746 0.000 0.708 0.292
#> GSM1233114 1 0.5797 0.965 0.712 0.280 0.008
#> GSM1233119 1 0.5754 0.965 0.700 0.296 0.004
#> GSM1233129 2 0.3267 0.789 0.000 0.884 0.116
#> GSM1233132 3 0.5497 0.949 0.000 0.292 0.708
#> GSM1233139 2 0.5497 0.746 0.000 0.708 0.292
#> GSM1233143 2 0.2550 0.772 0.040 0.936 0.024
#> GSM1233145 1 0.6051 0.970 0.696 0.292 0.012
#> GSM1233067 2 0.7064 0.737 0.220 0.704 0.076
#> GSM1233069 2 0.5497 0.746 0.000 0.708 0.292
#> GSM1233072 2 0.6699 0.747 0.044 0.700 0.256
#> GSM1233086 2 0.2703 0.792 0.016 0.928 0.056
#> GSM1233102 1 0.6051 0.970 0.696 0.292 0.012
#> GSM1233103 2 0.0424 0.779 0.000 0.992 0.008
#> GSM1233107 2 0.2261 0.745 0.068 0.932 0.000
#> GSM1233108 1 0.6051 0.970 0.696 0.292 0.012
#> GSM1233109 1 0.6448 0.851 0.636 0.352 0.012
#> GSM1233110 2 0.1170 0.777 0.016 0.976 0.008
#> GSM1233113 2 0.6625 0.754 0.196 0.736 0.068
#> GSM1233116 2 0.7424 0.744 0.128 0.700 0.172
#> GSM1233120 3 0.5785 0.893 0.000 0.332 0.668
#> GSM1233121 2 0.5497 0.746 0.000 0.708 0.292
#> GSM1233123 2 0.1643 0.756 0.000 0.956 0.044
#> GSM1233124 2 0.4002 0.783 0.000 0.840 0.160
#> GSM1233125 1 0.6051 0.970 0.696 0.292 0.012
#> GSM1233126 2 0.4692 0.782 0.012 0.820 0.168
#> GSM1233127 2 0.5953 0.747 0.012 0.708 0.280
#> GSM1233128 1 0.6051 0.970 0.696 0.292 0.012
#> GSM1233130 2 0.0661 0.781 0.004 0.988 0.008
#> GSM1233131 2 0.2313 0.749 0.024 0.944 0.032
#> GSM1233133 3 0.6169 0.840 0.004 0.360 0.636
#> GSM1233134 2 0.6731 0.766 0.088 0.740 0.172
#> GSM1233135 2 0.1620 0.786 0.012 0.964 0.024
#> GSM1233136 2 0.1170 0.782 0.016 0.976 0.008
#> GSM1233137 3 0.6079 0.784 0.000 0.388 0.612
#> GSM1233138 2 0.1765 0.757 0.040 0.956 0.004
#> GSM1233140 1 0.6051 0.970 0.696 0.292 0.012
#> GSM1233141 2 0.5722 0.745 0.004 0.704 0.292
#> GSM1233142 2 0.7424 0.744 0.128 0.700 0.172
#> GSM1233144 2 0.2116 0.751 0.040 0.948 0.012
#> GSM1233147 2 0.5497 0.746 0.000 0.708 0.292
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 4 0.7780 -0.63726 0.000 0.272 0.300 0.428
#> GSM1233002 4 0.4941 0.44640 0.000 0.436 0.000 0.564
#> GSM1233003 4 0.7249 0.34364 0.200 0.260 0.000 0.540
#> GSM1233014 2 0.5421 0.92883 0.004 0.548 0.008 0.440
#> GSM1233015 4 0.6924 0.41975 0.008 0.104 0.320 0.568
#> GSM1233016 4 0.6316 0.45339 0.000 0.184 0.156 0.660
#> GSM1233024 4 0.5383 -0.79978 0.000 0.012 0.452 0.536
#> GSM1233049 1 0.2778 0.68282 0.900 0.004 0.080 0.016
#> GSM1233064 1 0.6301 0.33364 0.544 0.004 0.052 0.400
#> GSM1233068 4 0.6016 0.41470 0.064 0.016 0.228 0.692
#> GSM1233073 4 0.5074 0.12497 0.236 0.000 0.040 0.724
#> GSM1233093 1 0.2778 0.68282 0.900 0.004 0.080 0.016
#> GSM1233115 4 0.6561 0.43823 0.140 0.212 0.004 0.644
#> GSM1232992 4 0.7442 -0.72435 0.000 0.340 0.184 0.476
#> GSM1232993 1 0.5279 0.42567 0.588 0.000 0.012 0.400
#> GSM1233005 3 0.5452 0.95618 0.000 0.016 0.556 0.428
#> GSM1233007 1 0.5290 0.42887 0.584 0.000 0.012 0.404
#> GSM1233010 4 0.2342 0.35259 0.000 0.080 0.008 0.912
#> GSM1233013 4 0.7782 -0.64245 0.000 0.276 0.296 0.428
#> GSM1233018 3 0.5229 0.96262 0.000 0.008 0.564 0.428
#> GSM1233019 3 0.5229 0.96262 0.000 0.008 0.564 0.428
#> GSM1233021 3 0.5229 0.96262 0.000 0.008 0.564 0.428
#> GSM1233025 4 0.4933 0.44799 0.000 0.432 0.000 0.568
#> GSM1233029 2 0.6152 0.90204 0.004 0.520 0.040 0.436
#> GSM1233030 2 0.5105 0.93380 0.000 0.564 0.004 0.432
#> GSM1233031 4 0.3687 0.25070 0.080 0.064 0.000 0.856
#> GSM1233032 4 0.4941 0.44640 0.000 0.436 0.000 0.564
#> GSM1233035 4 0.6077 0.43749 0.004 0.076 0.260 0.660
#> GSM1233038 4 0.4941 0.44640 0.000 0.436 0.000 0.564
#> GSM1233039 4 0.6508 -0.42308 0.084 0.000 0.360 0.556
#> GSM1233042 1 0.5112 0.44045 0.608 0.000 0.008 0.384
#> GSM1233043 1 0.6871 0.24400 0.508 0.004 0.092 0.396
#> GSM1233044 4 0.2412 0.32239 0.084 0.000 0.008 0.908
#> GSM1233046 1 0.5334 0.42098 0.588 0.004 0.008 0.400
#> GSM1233051 4 0.7568 0.28380 0.280 0.208 0.004 0.508
#> GSM1233054 1 0.3088 0.66566 0.864 0.000 0.008 0.128
#> GSM1233057 4 0.6136 -0.22092 0.080 0.000 0.288 0.632
#> GSM1233060 4 0.7149 -0.25341 0.424 0.064 0.028 0.484
#> GSM1233062 4 0.5415 -0.74602 0.004 0.008 0.436 0.552
#> GSM1233075 2 0.4941 0.93556 0.000 0.564 0.000 0.436
#> GSM1233078 4 0.2198 0.35321 0.000 0.072 0.008 0.920
#> GSM1233079 4 0.6915 0.44555 0.000 0.296 0.140 0.564
#> GSM1233082 4 0.6893 0.44592 0.000 0.300 0.136 0.564
#> GSM1233083 1 0.5032 0.61842 0.796 0.044 0.036 0.124
#> GSM1233091 1 0.5138 0.42836 0.600 0.000 0.008 0.392
#> GSM1233095 1 0.3989 0.66350 0.852 0.012 0.080 0.056
#> GSM1233096 4 0.6634 0.44779 0.000 0.336 0.100 0.564
#> GSM1233101 1 0.2593 0.68357 0.904 0.000 0.080 0.016
#> GSM1233105 4 0.7050 0.44282 0.000 0.264 0.172 0.564
#> GSM1233117 2 0.5105 0.93429 0.000 0.564 0.004 0.432
#> GSM1233118 2 0.6924 0.79931 0.000 0.464 0.108 0.428
#> GSM1233001 2 0.5229 0.93025 0.000 0.564 0.008 0.428
#> GSM1233006 2 0.5105 0.93380 0.000 0.564 0.004 0.432
#> GSM1233008 4 0.4857 -0.29720 0.000 0.008 0.324 0.668
#> GSM1233009 2 0.7154 0.73573 0.000 0.436 0.132 0.432
#> GSM1233017 2 0.6430 0.87257 0.000 0.504 0.068 0.428
#> GSM1233020 3 0.5971 0.91445 0.000 0.040 0.532 0.428
#> GSM1233022 4 0.1489 0.24210 0.000 0.044 0.004 0.952
#> GSM1233026 4 0.1489 0.32042 0.000 0.044 0.004 0.952
#> GSM1233028 4 0.5180 0.13374 0.196 0.000 0.064 0.740
#> GSM1233034 4 0.4585 -0.13557 0.000 0.000 0.332 0.668
#> GSM1233040 1 0.2778 0.68282 0.900 0.004 0.080 0.016
#> GSM1233048 1 0.2778 0.68282 0.900 0.004 0.080 0.016
#> GSM1233056 1 0.7403 0.41116 0.608 0.064 0.080 0.248
#> GSM1233058 1 0.5085 0.45035 0.616 0.000 0.008 0.376
#> GSM1233059 1 0.6985 0.54735 0.680 0.096 0.080 0.144
#> GSM1233066 4 0.1557 0.21590 0.000 0.000 0.056 0.944
#> GSM1233071 2 0.5407 0.84788 0.000 0.504 0.012 0.484
#> GSM1233074 4 0.5778 -0.61336 0.000 0.040 0.356 0.604
#> GSM1233076 4 0.4661 -0.30871 0.004 0.284 0.004 0.708
#> GSM1233080 4 0.7192 0.40627 0.028 0.340 0.080 0.552
#> GSM1233088 4 0.7272 -0.60870 0.104 0.412 0.012 0.472
#> GSM1233090 1 0.2998 0.68001 0.892 0.004 0.080 0.024
#> GSM1233092 2 0.4941 0.93556 0.000 0.564 0.000 0.436
#> GSM1233094 1 0.5138 0.42836 0.600 0.000 0.008 0.392
#> GSM1233097 1 0.5138 0.42836 0.600 0.000 0.008 0.392
#> GSM1233100 1 0.5050 0.43135 0.588 0.000 0.004 0.408
#> GSM1233104 4 0.6576 -0.42064 0.000 0.200 0.168 0.632
#> GSM1233106 4 0.6883 0.45376 0.000 0.260 0.156 0.584
#> GSM1233111 4 0.7234 0.42992 0.004 0.176 0.260 0.560
#> GSM1233122 2 0.5229 0.93025 0.000 0.564 0.008 0.428
#> GSM1233146 4 0.5850 0.44209 0.000 0.116 0.184 0.700
#> GSM1232994 3 0.5220 0.95563 0.000 0.008 0.568 0.424
#> GSM1232996 3 0.5229 0.96262 0.000 0.008 0.564 0.428
#> GSM1232997 4 0.5682 -0.19358 0.036 0.000 0.352 0.612
#> GSM1232998 3 0.5229 0.96262 0.000 0.008 0.564 0.428
#> GSM1232999 2 0.6449 0.84713 0.000 0.480 0.068 0.452
#> GSM1233000 2 0.5112 0.93501 0.000 0.560 0.004 0.436
#> GSM1233004 1 0.1994 0.67541 0.936 0.004 0.008 0.052
#> GSM1233011 4 0.0927 0.24995 0.000 0.008 0.016 0.976
#> GSM1233012 4 0.7669 -0.69128 0.000 0.312 0.236 0.452
#> GSM1233023 4 0.5212 -0.68306 0.000 0.008 0.420 0.572
#> GSM1233027 3 0.5277 0.90527 0.000 0.008 0.532 0.460
#> GSM1233033 4 0.7209 0.42856 0.004 0.168 0.268 0.560
#> GSM1233036 4 0.5807 -0.00502 0.044 0.000 0.344 0.612
#> GSM1233037 4 0.5850 0.05541 0.184 0.000 0.116 0.700
#> GSM1233041 4 0.4941 0.44640 0.000 0.436 0.000 0.564
#> GSM1233045 1 0.6569 0.28566 0.520 0.004 0.068 0.408
#> GSM1233047 1 0.2593 0.68357 0.904 0.000 0.080 0.016
#> GSM1233050 1 0.2778 0.68282 0.900 0.004 0.080 0.016
#> GSM1233052 1 0.2778 0.68282 0.900 0.004 0.080 0.016
#> GSM1233053 1 0.2593 0.68357 0.904 0.000 0.080 0.016
#> GSM1233055 1 0.2593 0.68357 0.904 0.000 0.080 0.016
#> GSM1233061 1 0.5138 0.42836 0.600 0.000 0.008 0.392
#> GSM1233063 4 0.6791 0.44683 0.000 0.316 0.120 0.564
#> GSM1233065 3 0.5588 0.83862 0.008 0.008 0.508 0.476
#> GSM1233070 2 0.4941 0.93556 0.000 0.564 0.000 0.436
#> GSM1233077 2 0.5105 0.93380 0.000 0.564 0.004 0.432
#> GSM1233081 4 0.4720 0.08144 0.324 0.000 0.004 0.672
#> GSM1233084 4 0.4941 0.44640 0.000 0.436 0.000 0.564
#> GSM1233087 4 0.2197 0.32087 0.080 0.000 0.004 0.916
#> GSM1233089 3 0.5452 0.95631 0.000 0.016 0.556 0.428
#> GSM1233099 1 0.1890 0.67546 0.936 0.000 0.008 0.056
#> GSM1233112 1 0.2593 0.68357 0.904 0.000 0.080 0.016
#> GSM1233085 1 0.1022 0.68003 0.968 0.000 0.000 0.032
#> GSM1233098 2 0.5105 0.93380 0.000 0.564 0.004 0.432
#> GSM1233114 4 0.7244 0.43060 0.004 0.180 0.256 0.560
#> GSM1233119 4 0.4974 0.44642 0.000 0.224 0.040 0.736
#> GSM1233129 4 0.7551 -0.33041 0.352 0.172 0.004 0.472
#> GSM1233132 1 0.2593 0.68357 0.904 0.000 0.080 0.016
#> GSM1233139 2 0.5105 0.93380 0.000 0.564 0.004 0.432
#> GSM1233143 4 0.1722 0.23252 0.000 0.048 0.008 0.944
#> GSM1233145 4 0.6130 0.44022 0.044 0.388 0.004 0.564
#> GSM1233067 4 0.7782 -0.64219 0.000 0.276 0.296 0.428
#> GSM1233069 2 0.4941 0.93556 0.000 0.564 0.000 0.436
#> GSM1233072 2 0.6837 0.81621 0.000 0.472 0.100 0.428
#> GSM1233086 4 0.7479 -0.61085 0.008 0.276 0.180 0.536
#> GSM1233102 4 0.4941 0.44640 0.000 0.436 0.000 0.564
#> GSM1233103 1 0.6046 0.38201 0.544 0.024 0.012 0.420
#> GSM1233107 4 0.1820 0.32928 0.000 0.020 0.036 0.944
#> GSM1233108 4 0.4941 0.44640 0.000 0.436 0.000 0.564
#> GSM1233109 4 0.4933 0.44835 0.000 0.432 0.000 0.568
#> GSM1233110 4 0.0967 0.26786 0.004 0.016 0.004 0.976
#> GSM1233113 4 0.7784 -0.64743 0.000 0.280 0.292 0.428
#> GSM1233116 4 0.7613 -0.76387 0.000 0.368 0.204 0.428
#> GSM1233120 1 0.3088 0.66748 0.864 0.000 0.008 0.128
#> GSM1233121 2 0.5269 0.92796 0.004 0.564 0.004 0.428
#> GSM1233123 1 0.5383 0.35897 0.536 0.000 0.012 0.452
#> GSM1233124 2 0.5399 0.84552 0.012 0.520 0.000 0.468
#> GSM1233125 4 0.4941 0.44640 0.000 0.436 0.000 0.564
#> GSM1233126 4 0.6949 -0.82987 0.008 0.440 0.084 0.468
#> GSM1233127 2 0.6438 0.86729 0.000 0.496 0.068 0.436
#> GSM1233128 4 0.4941 0.44640 0.000 0.436 0.000 0.564
#> GSM1233130 4 0.3808 -0.00370 0.004 0.184 0.004 0.808
#> GSM1233131 4 0.5137 -0.26026 0.452 0.004 0.000 0.544
#> GSM1233133 1 0.4946 0.55424 0.680 0.004 0.008 0.308
#> GSM1233134 4 0.7669 -0.71480 0.000 0.328 0.228 0.444
#> GSM1233135 4 0.3208 0.08346 0.004 0.148 0.000 0.848
#> GSM1233136 4 0.2311 0.20341 0.004 0.076 0.004 0.916
#> GSM1233137 1 0.3810 0.63892 0.804 0.000 0.008 0.188
#> GSM1233138 4 0.1675 0.24366 0.004 0.044 0.004 0.948
#> GSM1233140 4 0.4941 0.44640 0.000 0.436 0.000 0.564
#> GSM1233141 2 0.5229 0.93025 0.000 0.564 0.008 0.428
#> GSM1233142 4 0.7538 -0.78618 0.000 0.384 0.188 0.428
#> GSM1233144 4 0.2715 0.31448 0.100 0.004 0.004 0.892
#> GSM1233147 2 0.4941 0.93556 0.000 0.564 0.000 0.436
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.4016 0.6280 0.000 0.796 0.092 0.112 0.000
#> GSM1233002 5 0.2605 0.5954 0.004 0.044 0.056 0.000 0.896
#> GSM1233003 5 0.3231 0.4445 0.196 0.000 0.000 0.004 0.800
#> GSM1233014 2 0.1186 0.6601 0.000 0.964 0.008 0.020 0.008
#> GSM1233015 3 0.5124 0.3256 0.004 0.004 0.700 0.080 0.212
#> GSM1233016 5 0.5083 0.3143 0.000 0.036 0.432 0.000 0.532
#> GSM1233024 2 0.5811 0.5350 0.000 0.680 0.068 0.188 0.064
#> GSM1233049 1 0.0727 0.8092 0.980 0.000 0.004 0.004 0.012
#> GSM1233064 4 0.6100 0.5957 0.108 0.416 0.000 0.472 0.004
#> GSM1233068 3 0.6802 0.4660 0.000 0.044 0.552 0.260 0.144
#> GSM1233073 2 0.7362 -0.4753 0.084 0.464 0.000 0.332 0.120
#> GSM1233093 1 0.0727 0.8092 0.980 0.000 0.004 0.004 0.012
#> GSM1233115 5 0.7246 0.1813 0.264 0.012 0.024 0.204 0.496
#> GSM1232992 2 0.3470 0.6531 0.000 0.852 0.052 0.080 0.016
#> GSM1232993 4 0.5925 0.6940 0.128 0.316 0.000 0.556 0.000
#> GSM1233005 2 0.4872 0.5893 0.000 0.720 0.120 0.160 0.000
#> GSM1233007 2 0.6683 -0.4245 0.124 0.492 0.000 0.356 0.028
#> GSM1233010 2 0.7382 -0.0307 0.000 0.424 0.120 0.080 0.376
#> GSM1233013 2 0.4203 0.6218 0.000 0.780 0.092 0.128 0.000
#> GSM1233018 2 0.5854 0.4533 0.000 0.596 0.152 0.252 0.000
#> GSM1233019 2 0.5810 0.4646 0.000 0.604 0.152 0.244 0.000
#> GSM1233021 2 0.5815 0.4455 0.000 0.592 0.136 0.272 0.000
#> GSM1233025 5 0.2678 0.5884 0.004 0.036 0.060 0.004 0.896
#> GSM1233029 2 0.0566 0.6587 0.000 0.984 0.004 0.012 0.000
#> GSM1233030 2 0.1968 0.6455 0.004 0.932 0.020 0.040 0.004
#> GSM1233031 2 0.6542 -0.2522 0.004 0.496 0.000 0.300 0.200
#> GSM1233032 5 0.0671 0.5983 0.016 0.000 0.000 0.004 0.980
#> GSM1233035 3 0.6316 0.4324 0.000 0.028 0.612 0.196 0.164
#> GSM1233038 5 0.3596 0.5824 0.016 0.000 0.200 0.000 0.784
#> GSM1233039 2 0.6907 -0.2071 0.004 0.432 0.024 0.404 0.136
#> GSM1233042 4 0.6386 0.4591 0.320 0.188 0.000 0.492 0.000
#> GSM1233043 4 0.5928 0.6903 0.124 0.328 0.000 0.548 0.000
#> GSM1233044 2 0.6552 -0.1829 0.000 0.444 0.000 0.208 0.348
#> GSM1233046 2 0.6343 -0.5832 0.124 0.456 0.000 0.412 0.008
#> GSM1233051 5 0.7208 0.1247 0.268 0.032 0.000 0.236 0.464
#> GSM1233054 1 0.5101 0.3998 0.552 0.024 0.000 0.416 0.008
#> GSM1233057 4 0.7382 0.2533 0.012 0.396 0.036 0.408 0.148
#> GSM1233060 2 0.6286 -0.5035 0.092 0.500 0.000 0.388 0.020
#> GSM1233062 2 0.6571 0.1908 0.004 0.528 0.020 0.328 0.120
#> GSM1233075 2 0.1721 0.6541 0.004 0.944 0.020 0.028 0.004
#> GSM1233078 5 0.6430 0.1668 0.000 0.252 0.156 0.020 0.572
#> GSM1233079 5 0.4522 0.4081 0.008 0.000 0.440 0.000 0.552
#> GSM1233082 5 0.4310 0.4244 0.004 0.000 0.392 0.000 0.604
#> GSM1233083 1 0.4429 0.6456 0.744 0.000 0.000 0.064 0.192
#> GSM1233091 4 0.6828 0.6418 0.212 0.356 0.000 0.424 0.008
#> GSM1233095 1 0.1591 0.7870 0.940 0.000 0.004 0.004 0.052
#> GSM1233096 5 0.4341 0.4557 0.004 0.000 0.404 0.000 0.592
#> GSM1233101 1 0.0854 0.8101 0.976 0.000 0.004 0.012 0.008
#> GSM1233105 5 0.4410 0.3658 0.004 0.000 0.440 0.000 0.556
#> GSM1233117 2 0.1439 0.6551 0.004 0.956 0.020 0.016 0.004
#> GSM1233118 2 0.2235 0.6606 0.004 0.920 0.032 0.040 0.004
#> GSM1233001 2 0.1538 0.6560 0.004 0.952 0.020 0.020 0.004
#> GSM1233006 2 0.1918 0.6424 0.004 0.932 0.012 0.048 0.004
#> GSM1233008 3 0.8247 0.2821 0.000 0.324 0.332 0.212 0.132
#> GSM1233009 2 0.2809 0.6571 0.004 0.888 0.036 0.068 0.004
#> GSM1233017 2 0.1889 0.6617 0.004 0.936 0.020 0.036 0.004
#> GSM1233020 2 0.4734 0.5921 0.000 0.728 0.096 0.176 0.000
#> GSM1233022 2 0.4407 0.5614 0.000 0.764 0.040 0.016 0.180
#> GSM1233026 5 0.4873 0.2030 0.000 0.280 0.012 0.032 0.676
#> GSM1233028 4 0.7252 0.6270 0.096 0.372 0.000 0.444 0.088
#> GSM1233034 3 0.8196 0.4192 0.000 0.240 0.400 0.216 0.144
#> GSM1233040 1 0.0566 0.8096 0.984 0.000 0.004 0.000 0.012
#> GSM1233048 1 0.0451 0.8100 0.988 0.000 0.004 0.000 0.008
#> GSM1233056 1 0.2497 0.7424 0.880 0.000 0.004 0.004 0.112
#> GSM1233058 1 0.5927 0.0366 0.468 0.104 0.000 0.428 0.000
#> GSM1233059 1 0.3006 0.6972 0.836 0.000 0.004 0.004 0.156
#> GSM1233066 2 0.6296 0.2351 0.000 0.584 0.012 0.204 0.200
#> GSM1233071 2 0.1082 0.6593 0.000 0.964 0.000 0.008 0.028
#> GSM1233074 2 0.5225 0.5849 0.000 0.740 0.056 0.132 0.072
#> GSM1233076 2 0.3340 0.6226 0.000 0.852 0.008 0.044 0.096
#> GSM1233080 5 0.3819 0.4949 0.208 0.000 0.016 0.004 0.772
#> GSM1233088 2 0.6121 -0.1321 0.032 0.596 0.000 0.288 0.084
#> GSM1233090 1 0.0727 0.8092 0.980 0.000 0.004 0.004 0.012
#> GSM1233092 2 0.1806 0.6480 0.004 0.940 0.020 0.032 0.004
#> GSM1233094 4 0.6118 0.6155 0.128 0.404 0.000 0.468 0.000
#> GSM1233097 4 0.6200 0.6996 0.180 0.280 0.000 0.540 0.000
#> GSM1233100 4 0.7526 0.4308 0.304 0.144 0.000 0.464 0.088
#> GSM1233104 2 0.3861 0.6228 0.000 0.816 0.004 0.092 0.088
#> GSM1233106 5 0.4826 0.2576 0.000 0.020 0.472 0.000 0.508
#> GSM1233111 3 0.6763 0.1066 0.008 0.000 0.480 0.252 0.260
#> GSM1233122 2 0.1538 0.6560 0.004 0.952 0.020 0.020 0.004
#> GSM1233146 3 0.5228 0.0600 0.000 0.056 0.588 0.000 0.356
#> GSM1232994 2 0.6005 0.4144 0.000 0.568 0.156 0.276 0.000
#> GSM1232996 2 0.5797 0.4447 0.000 0.592 0.132 0.276 0.000
#> GSM1232997 3 0.8101 0.4497 0.000 0.168 0.400 0.288 0.144
#> GSM1232998 2 0.5797 0.4447 0.000 0.592 0.132 0.276 0.000
#> GSM1232999 2 0.1364 0.6626 0.000 0.952 0.000 0.036 0.012
#> GSM1233000 2 0.1334 0.6542 0.004 0.960 0.020 0.012 0.004
#> GSM1233004 1 0.5431 0.4432 0.584 0.008 0.000 0.356 0.052
#> GSM1233011 2 0.5059 0.5278 0.000 0.720 0.024 0.060 0.196
#> GSM1233012 2 0.2844 0.6500 0.000 0.876 0.028 0.092 0.004
#> GSM1233023 2 0.7903 0.0207 0.000 0.412 0.260 0.240 0.088
#> GSM1233027 2 0.6831 0.3219 0.000 0.512 0.216 0.252 0.020
#> GSM1233033 3 0.6763 0.1066 0.008 0.000 0.480 0.252 0.260
#> GSM1233036 3 0.7650 0.4715 0.000 0.108 0.468 0.280 0.144
#> GSM1233037 4 0.7206 0.5961 0.072 0.340 0.004 0.484 0.100
#> GSM1233041 5 0.3684 0.5840 0.016 0.000 0.192 0.004 0.788
#> GSM1233045 4 0.6118 0.6237 0.128 0.404 0.000 0.468 0.000
#> GSM1233047 1 0.0960 0.8098 0.972 0.000 0.004 0.016 0.008
#> GSM1233050 1 0.0404 0.8099 0.988 0.000 0.000 0.000 0.012
#> GSM1233052 1 0.0771 0.8083 0.976 0.000 0.004 0.000 0.020
#> GSM1233053 1 0.0771 0.8083 0.976 0.000 0.004 0.000 0.020
#> GSM1233055 1 0.0451 0.8100 0.988 0.000 0.004 0.000 0.008
#> GSM1233061 4 0.6613 0.4728 0.332 0.228 0.000 0.440 0.000
#> GSM1233063 5 0.4367 0.4431 0.004 0.000 0.416 0.000 0.580
#> GSM1233065 2 0.6819 0.2392 0.004 0.512 0.072 0.348 0.064
#> GSM1233070 2 0.2045 0.6425 0.004 0.928 0.020 0.044 0.004
#> GSM1233077 2 0.1331 0.6475 0.000 0.952 0.008 0.040 0.000
#> GSM1233081 4 0.8366 0.6688 0.144 0.304 0.028 0.416 0.108
#> GSM1233084 5 0.2873 0.5880 0.016 0.000 0.128 0.000 0.856
#> GSM1233087 4 0.8456 0.4525 0.036 0.280 0.072 0.400 0.212
#> GSM1233089 2 0.4981 0.5792 0.000 0.708 0.120 0.172 0.000
#> GSM1233099 1 0.4936 0.4140 0.560 0.016 0.000 0.416 0.008
#> GSM1233112 1 0.0798 0.8100 0.976 0.000 0.000 0.008 0.016
#> GSM1233085 1 0.4025 0.5950 0.700 0.000 0.000 0.292 0.008
#> GSM1233098 2 0.1790 0.6475 0.004 0.940 0.016 0.036 0.004
#> GSM1233114 3 0.6763 0.1066 0.008 0.000 0.480 0.252 0.260
#> GSM1233119 5 0.4996 0.4487 0.000 0.128 0.164 0.000 0.708
#> GSM1233129 2 0.4993 0.4543 0.076 0.756 0.000 0.124 0.044
#> GSM1233132 1 0.1082 0.8080 0.964 0.000 0.000 0.028 0.008
#> GSM1233139 2 0.1889 0.6460 0.004 0.936 0.020 0.036 0.004
#> GSM1233143 2 0.5592 0.5250 0.000 0.704 0.088 0.048 0.160
#> GSM1233145 5 0.3951 0.5828 0.028 0.000 0.192 0.004 0.776
#> GSM1233067 2 0.4158 0.6229 0.000 0.784 0.092 0.124 0.000
#> GSM1233069 2 0.1968 0.6438 0.004 0.932 0.020 0.040 0.004
#> GSM1233072 2 0.2689 0.6611 0.004 0.896 0.056 0.040 0.004
#> GSM1233086 2 0.3635 0.6315 0.000 0.828 0.004 0.112 0.056
#> GSM1233102 5 0.0955 0.6046 0.004 0.000 0.028 0.000 0.968
#> GSM1233103 2 0.6275 -0.5487 0.104 0.452 0.000 0.432 0.012
#> GSM1233107 5 0.7323 -0.1431 0.000 0.204 0.364 0.036 0.396
#> GSM1233108 5 0.2970 0.6032 0.004 0.000 0.168 0.000 0.828
#> GSM1233109 5 0.2972 0.5591 0.004 0.064 0.004 0.048 0.880
#> GSM1233110 2 0.4210 0.5243 0.000 0.740 0.000 0.036 0.224
#> GSM1233113 2 0.3967 0.6301 0.000 0.800 0.092 0.108 0.000
#> GSM1233116 2 0.3471 0.6449 0.000 0.836 0.072 0.092 0.000
#> GSM1233120 1 0.5370 0.3770 0.544 0.040 0.000 0.408 0.008
#> GSM1233121 2 0.1557 0.6432 0.000 0.940 0.008 0.052 0.000
#> GSM1233123 2 0.7318 -0.3277 0.124 0.500 0.000 0.288 0.088
#> GSM1233124 2 0.1484 0.6462 0.000 0.944 0.008 0.048 0.000
#> GSM1233125 5 0.0566 0.5990 0.012 0.000 0.000 0.004 0.984
#> GSM1233126 2 0.3738 0.5784 0.012 0.832 0.000 0.092 0.064
#> GSM1233127 2 0.1725 0.6624 0.004 0.944 0.024 0.024 0.004
#> GSM1233128 5 0.3596 0.5836 0.016 0.000 0.200 0.000 0.784
#> GSM1233130 2 0.3804 0.5851 0.000 0.796 0.000 0.044 0.160
#> GSM1233131 2 0.7407 -0.5446 0.100 0.424 0.000 0.376 0.100
#> GSM1233133 4 0.8409 0.5398 0.260 0.264 0.000 0.324 0.152
#> GSM1233134 2 0.2812 0.6499 0.000 0.876 0.024 0.096 0.004
#> GSM1233135 2 0.3730 0.5889 0.000 0.800 0.004 0.028 0.168
#> GSM1233136 2 0.3847 0.5741 0.000 0.784 0.000 0.036 0.180
#> GSM1233137 1 0.5630 0.3304 0.528 0.044 0.000 0.412 0.016
#> GSM1233138 2 0.4037 0.5676 0.000 0.776 0.008 0.028 0.188
#> GSM1233140 5 0.1569 0.6046 0.004 0.008 0.044 0.000 0.944
#> GSM1233141 2 0.1631 0.6532 0.004 0.948 0.020 0.024 0.004
#> GSM1233142 2 0.3327 0.6510 0.004 0.852 0.060 0.084 0.000
#> GSM1233144 2 0.6958 -0.2433 0.012 0.436 0.000 0.236 0.316
#> GSM1233147 2 0.1631 0.6515 0.004 0.948 0.020 0.024 0.004
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.4777 0.67035 0.008 0.696 0.000 0.000 0.140 0.156
#> GSM1233002 3 0.2321 0.63644 0.000 0.000 0.900 0.008 0.052 0.040
#> GSM1233003 3 0.4479 0.48130 0.180 0.000 0.732 0.024 0.064 0.000
#> GSM1233014 2 0.4010 0.71117 0.000 0.808 0.048 0.052 0.084 0.008
#> GSM1233015 6 0.5630 -0.10154 0.000 0.000 0.256 0.004 0.184 0.556
#> GSM1233016 3 0.5818 0.39895 0.000 0.016 0.572 0.012 0.112 0.288
#> GSM1233024 2 0.5300 0.60125 0.004 0.624 0.028 0.036 0.012 0.296
#> GSM1233049 1 0.1924 0.85380 0.928 0.000 0.012 0.028 0.028 0.004
#> GSM1233064 4 0.2765 0.75314 0.004 0.064 0.016 0.884 0.004 0.028
#> GSM1233068 6 0.3996 0.38616 0.000 0.000 0.112 0.032 0.064 0.792
#> GSM1233073 4 0.4526 0.71700 0.000 0.076 0.116 0.756 0.000 0.052
#> GSM1233093 1 0.1924 0.85380 0.928 0.000 0.012 0.028 0.028 0.004
#> GSM1233115 3 0.5077 0.25168 0.040 0.000 0.568 0.372 0.012 0.008
#> GSM1232992 2 0.4230 0.71949 0.000 0.792 0.056 0.008 0.052 0.092
#> GSM1232993 4 0.2282 0.74064 0.004 0.052 0.000 0.904 0.004 0.036
#> GSM1233005 2 0.5268 0.64860 0.020 0.656 0.000 0.000 0.152 0.172
#> GSM1233007 4 0.4055 0.67789 0.016 0.184 0.044 0.756 0.000 0.000
#> GSM1233010 3 0.6846 0.28000 0.000 0.056 0.544 0.092 0.060 0.248
#> GSM1233013 2 0.4843 0.66651 0.008 0.688 0.000 0.000 0.140 0.164
#> GSM1233018 2 0.5298 0.64499 0.020 0.652 0.000 0.000 0.152 0.176
#> GSM1233019 2 0.5268 0.64860 0.020 0.656 0.000 0.000 0.152 0.172
#> GSM1233021 2 0.5389 0.62921 0.020 0.636 0.000 0.000 0.140 0.204
#> GSM1233025 3 0.2639 0.63062 0.000 0.008 0.880 0.000 0.064 0.048
#> GSM1233029 2 0.2803 0.73415 0.000 0.872 0.000 0.052 0.064 0.012
#> GSM1233030 2 0.2152 0.72214 0.000 0.904 0.000 0.024 0.068 0.004
#> GSM1233031 4 0.6030 0.46311 0.004 0.244 0.156 0.572 0.016 0.008
#> GSM1233032 3 0.1141 0.62840 0.000 0.000 0.948 0.000 0.052 0.000
#> GSM1233035 6 0.4123 0.37793 0.000 0.000 0.124 0.032 0.064 0.780
#> GSM1233038 3 0.3385 0.57363 0.032 0.000 0.788 0.000 0.180 0.000
#> GSM1233039 4 0.7153 -0.09878 0.000 0.176 0.108 0.360 0.000 0.356
#> GSM1233042 4 0.1349 0.73473 0.056 0.000 0.000 0.940 0.004 0.000
#> GSM1233043 4 0.2145 0.75220 0.008 0.056 0.000 0.912 0.004 0.020
#> GSM1233044 4 0.5337 0.41370 0.004 0.072 0.376 0.540 0.004 0.004
#> GSM1233046 4 0.2966 0.76402 0.016 0.068 0.044 0.868 0.000 0.004
#> GSM1233051 4 0.5337 0.19641 0.072 0.000 0.432 0.484 0.012 0.000
#> GSM1233054 4 0.2364 0.75158 0.072 0.004 0.032 0.892 0.000 0.000
#> GSM1233057 6 0.7125 0.12375 0.000 0.172 0.108 0.332 0.000 0.388
#> GSM1233060 4 0.3598 0.73861 0.000 0.112 0.080 0.804 0.000 0.004
#> GSM1233062 2 0.6522 0.24099 0.004 0.468 0.076 0.056 0.016 0.380
#> GSM1233075 2 0.1442 0.73264 0.000 0.944 0.000 0.012 0.040 0.004
#> GSM1233078 3 0.6394 0.34398 0.000 0.044 0.552 0.036 0.080 0.288
#> GSM1233079 3 0.5277 0.42990 0.004 0.000 0.620 0.000 0.204 0.172
#> GSM1233082 3 0.4634 0.52718 0.004 0.000 0.708 0.004 0.100 0.184
#> GSM1233083 1 0.6408 -0.00899 0.408 0.000 0.228 0.344 0.020 0.000
#> GSM1233091 4 0.2133 0.75665 0.052 0.020 0.016 0.912 0.000 0.000
#> GSM1233095 1 0.3295 0.77739 0.844 0.000 0.096 0.028 0.028 0.004
#> GSM1233096 3 0.5056 0.48260 0.004 0.000 0.644 0.000 0.220 0.132
#> GSM1233101 1 0.1843 0.86104 0.912 0.000 0.004 0.080 0.004 0.000
#> GSM1233105 3 0.5437 0.44131 0.004 0.000 0.596 0.004 0.136 0.260
#> GSM1233117 2 0.1313 0.73530 0.000 0.952 0.000 0.016 0.028 0.004
#> GSM1233118 2 0.2294 0.73071 0.000 0.892 0.000 0.000 0.072 0.036
#> GSM1233001 2 0.1074 0.73875 0.000 0.960 0.000 0.000 0.028 0.012
#> GSM1233006 2 0.3113 0.70851 0.000 0.844 0.000 0.048 0.100 0.008
#> GSM1233008 6 0.5665 0.33944 0.000 0.328 0.100 0.024 0.000 0.548
#> GSM1233009 2 0.1863 0.73984 0.000 0.920 0.000 0.004 0.016 0.060
#> GSM1233017 2 0.1700 0.73686 0.000 0.928 0.000 0.000 0.024 0.048
#> GSM1233020 2 0.5268 0.64860 0.020 0.656 0.000 0.000 0.152 0.172
#> GSM1233022 2 0.5602 0.60959 0.004 0.680 0.144 0.044 0.012 0.116
#> GSM1233026 3 0.6293 0.38715 0.008 0.128 0.656 0.052 0.092 0.064
#> GSM1233028 4 0.4311 0.72246 0.000 0.056 0.116 0.772 0.000 0.056
#> GSM1233034 6 0.4666 0.52920 0.000 0.160 0.092 0.024 0.000 0.724
#> GSM1233040 1 0.1829 0.85848 0.928 0.000 0.008 0.036 0.028 0.000
#> GSM1233048 1 0.1843 0.86104 0.912 0.000 0.004 0.080 0.004 0.000
#> GSM1233056 1 0.3617 0.74499 0.812 0.000 0.132 0.024 0.028 0.004
#> GSM1233058 4 0.1226 0.73534 0.040 0.004 0.000 0.952 0.004 0.000
#> GSM1233059 1 0.3986 0.68144 0.772 0.000 0.172 0.024 0.028 0.004
#> GSM1233066 2 0.8037 -0.09279 0.004 0.360 0.204 0.180 0.020 0.232
#> GSM1233071 2 0.4601 0.69471 0.004 0.772 0.080 0.052 0.084 0.008
#> GSM1233074 2 0.5506 0.61523 0.000 0.668 0.116 0.040 0.008 0.168
#> GSM1233076 2 0.5534 0.64253 0.008 0.696 0.112 0.088 0.092 0.004
#> GSM1233080 3 0.3877 0.51998 0.160 0.000 0.764 0.000 0.076 0.000
#> GSM1233088 4 0.5658 0.26142 0.000 0.384 0.088 0.508 0.016 0.004
#> GSM1233090 1 0.2018 0.85271 0.924 0.000 0.016 0.028 0.028 0.004
#> GSM1233092 2 0.2344 0.71925 0.000 0.892 0.000 0.028 0.076 0.004
#> GSM1233094 4 0.1793 0.74596 0.008 0.040 0.000 0.932 0.004 0.016
#> GSM1233097 4 0.1579 0.74275 0.020 0.024 0.000 0.944 0.004 0.008
#> GSM1233100 4 0.4216 0.73117 0.056 0.008 0.120 0.784 0.000 0.032
#> GSM1233104 2 0.5590 0.66642 0.004 0.704 0.096 0.040 0.040 0.116
#> GSM1233106 3 0.5640 0.37956 0.004 0.000 0.548 0.020 0.088 0.340
#> GSM1233111 5 0.4890 1.00000 0.000 0.000 0.180 0.000 0.660 0.160
#> GSM1233122 2 0.1168 0.73863 0.000 0.956 0.000 0.000 0.028 0.016
#> GSM1233146 6 0.6354 0.08428 0.000 0.040 0.392 0.020 0.084 0.464
#> GSM1232994 2 0.5143 0.59091 0.004 0.608 0.000 0.000 0.108 0.280
#> GSM1232996 2 0.5394 0.60889 0.016 0.620 0.000 0.000 0.128 0.236
#> GSM1232997 6 0.4620 0.53081 0.000 0.124 0.092 0.032 0.004 0.748
#> GSM1232998 2 0.5304 0.59758 0.012 0.612 0.000 0.000 0.112 0.264
#> GSM1232999 2 0.3655 0.72844 0.000 0.836 0.060 0.048 0.044 0.012
#> GSM1233000 2 0.1957 0.73273 0.000 0.920 0.000 0.024 0.048 0.008
#> GSM1233004 4 0.4575 0.69061 0.180 0.004 0.088 0.720 0.008 0.000
#> GSM1233011 2 0.6275 0.52971 0.004 0.612 0.152 0.044 0.020 0.168
#> GSM1233012 2 0.4338 0.71801 0.004 0.776 0.036 0.040 0.008 0.136
#> GSM1233023 6 0.5236 0.40081 0.004 0.288 0.052 0.024 0.004 0.628
#> GSM1233027 2 0.5303 0.52352 0.004 0.568 0.008 0.028 0.028 0.364
#> GSM1233033 5 0.4890 1.00000 0.000 0.000 0.180 0.000 0.660 0.160
#> GSM1233036 6 0.4002 0.47806 0.000 0.040 0.092 0.032 0.024 0.812
#> GSM1233037 4 0.4853 0.68656 0.000 0.052 0.120 0.728 0.000 0.100
#> GSM1233041 3 0.3385 0.57363 0.032 0.000 0.788 0.000 0.180 0.000
#> GSM1233045 4 0.2512 0.75286 0.004 0.060 0.008 0.896 0.004 0.028
#> GSM1233047 1 0.2946 0.77534 0.808 0.000 0.004 0.184 0.004 0.000
#> GSM1233050 1 0.1908 0.86171 0.924 0.000 0.012 0.044 0.020 0.000
#> GSM1233052 1 0.2196 0.84867 0.884 0.000 0.004 0.108 0.004 0.000
#> GSM1233053 1 0.1843 0.86104 0.912 0.000 0.004 0.080 0.004 0.000
#> GSM1233055 1 0.1843 0.86104 0.912 0.000 0.004 0.080 0.004 0.000
#> GSM1233061 4 0.1364 0.74145 0.048 0.004 0.004 0.944 0.000 0.000
#> GSM1233063 3 0.5067 0.48811 0.004 0.000 0.640 0.000 0.228 0.128
#> GSM1233065 2 0.6625 0.55043 0.000 0.564 0.024 0.072 0.116 0.224
#> GSM1233070 2 0.2981 0.70862 0.000 0.852 0.000 0.040 0.100 0.008
#> GSM1233077 2 0.3237 0.70836 0.000 0.836 0.000 0.056 0.100 0.008
#> GSM1233081 4 0.5192 0.67636 0.012 0.028 0.180 0.704 0.008 0.068
#> GSM1233084 3 0.3122 0.57884 0.020 0.000 0.804 0.000 0.176 0.000
#> GSM1233087 4 0.5941 0.54556 0.000 0.024 0.212 0.612 0.020 0.132
#> GSM1233089 2 0.5268 0.64860 0.020 0.656 0.000 0.000 0.152 0.172
#> GSM1233099 4 0.2100 0.71646 0.112 0.000 0.004 0.884 0.000 0.000
#> GSM1233112 1 0.1866 0.86203 0.908 0.000 0.008 0.084 0.000 0.000
#> GSM1233085 4 0.3490 0.51887 0.268 0.000 0.008 0.724 0.000 0.000
#> GSM1233098 2 0.2320 0.71783 0.000 0.892 0.000 0.024 0.080 0.004
#> GSM1233114 5 0.4890 1.00000 0.000 0.000 0.180 0.000 0.660 0.160
#> GSM1233119 3 0.5321 0.52264 0.000 0.008 0.664 0.020 0.112 0.196
#> GSM1233129 2 0.4330 0.56537 0.000 0.680 0.004 0.272 0.044 0.000
#> GSM1233132 1 0.2346 0.84487 0.868 0.000 0.008 0.124 0.000 0.000
#> GSM1233139 2 0.2764 0.70641 0.000 0.864 0.000 0.028 0.100 0.008
#> GSM1233143 2 0.5620 0.58893 0.004 0.648 0.140 0.040 0.000 0.168
#> GSM1233145 3 0.3352 0.57620 0.032 0.000 0.792 0.000 0.176 0.000
#> GSM1233067 2 0.4869 0.66913 0.012 0.692 0.000 0.000 0.136 0.160
#> GSM1233069 2 0.2425 0.71496 0.000 0.884 0.000 0.024 0.088 0.004
#> GSM1233072 2 0.2702 0.73034 0.000 0.868 0.000 0.004 0.092 0.036
#> GSM1233086 2 0.4959 0.69746 0.000 0.756 0.080 0.060 0.044 0.060
#> GSM1233102 3 0.0405 0.63676 0.000 0.000 0.988 0.000 0.004 0.008
#> GSM1233103 4 0.4195 0.72970 0.008 0.116 0.068 0.784 0.024 0.000
#> GSM1233107 6 0.6651 0.09317 0.000 0.044 0.384 0.036 0.084 0.452
#> GSM1233108 3 0.3103 0.61952 0.000 0.000 0.836 0.000 0.100 0.064
#> GSM1233109 3 0.3078 0.59503 0.000 0.020 0.848 0.112 0.016 0.004
#> GSM1233110 2 0.6415 0.57072 0.008 0.620 0.172 0.088 0.092 0.020
#> GSM1233113 2 0.4915 0.67011 0.008 0.692 0.004 0.000 0.140 0.156
#> GSM1233116 2 0.4036 0.69198 0.000 0.756 0.000 0.000 0.108 0.136
#> GSM1233120 4 0.2719 0.75820 0.072 0.012 0.040 0.876 0.000 0.000
#> GSM1233121 2 0.3552 0.70397 0.004 0.820 0.000 0.068 0.100 0.008
#> GSM1233123 4 0.4754 0.62457 0.028 0.200 0.068 0.704 0.000 0.000
#> GSM1233124 2 0.3618 0.70103 0.000 0.816 0.008 0.092 0.080 0.004
#> GSM1233125 3 0.1141 0.62840 0.000 0.000 0.948 0.000 0.052 0.000
#> GSM1233126 2 0.4309 0.66635 0.004 0.752 0.000 0.160 0.072 0.012
#> GSM1233127 2 0.1124 0.74325 0.000 0.956 0.000 0.008 0.000 0.036
#> GSM1233128 3 0.2697 0.57979 0.000 0.000 0.812 0.000 0.188 0.000
#> GSM1233130 2 0.5787 0.61509 0.008 0.668 0.144 0.084 0.092 0.004
#> GSM1233131 4 0.4196 0.72947 0.024 0.056 0.144 0.772 0.004 0.000
#> GSM1233133 4 0.4506 0.72099 0.060 0.040 0.156 0.744 0.000 0.000
#> GSM1233134 2 0.3813 0.73532 0.000 0.816 0.028 0.040 0.012 0.104
#> GSM1233135 2 0.5264 0.65257 0.008 0.712 0.140 0.064 0.072 0.004
#> GSM1233136 2 0.5759 0.61855 0.008 0.668 0.152 0.076 0.092 0.004
#> GSM1233137 4 0.3013 0.76434 0.064 0.028 0.044 0.864 0.000 0.000
#> GSM1233138 2 0.5489 0.63687 0.008 0.692 0.148 0.072 0.076 0.004
#> GSM1233140 3 0.2505 0.63156 0.000 0.008 0.888 0.000 0.064 0.040
#> GSM1233141 2 0.1503 0.73803 0.000 0.944 0.000 0.008 0.032 0.016
#> GSM1233142 2 0.4053 0.69573 0.004 0.764 0.000 0.000 0.104 0.128
#> GSM1233144 4 0.5188 0.43467 0.004 0.072 0.368 0.552 0.004 0.000
#> GSM1233147 2 0.2715 0.72073 0.000 0.872 0.012 0.028 0.088 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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> ATC:mclust 151 0.2021 0.9916 0.323 2
#> ATC:mclust 155 0.5085 0.1854 0.724 3
#> ATC:mclust 60 0.0732 0.4778 0.197 4
#> ATC:mclust 94 0.0111 0.0499 0.263 5
#> ATC:mclust 127 0.0750 0.0363 0.437 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 51941 rows and 156 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 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 0.337 0.567 0.778 0.4135 0.650 0.650
#> 3 3 0.387 0.617 0.797 0.5262 0.619 0.458
#> 4 4 0.403 0.435 0.644 0.1613 0.769 0.474
#> 5 5 0.440 0.410 0.617 0.0750 0.825 0.471
#> 6 6 0.514 0.376 0.593 0.0454 0.882 0.549
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
#> GSM1232995 2 0.9866 0.5686 0.432 0.568
#> GSM1233002 1 0.9286 0.6062 0.656 0.344
#> GSM1233003 1 0.2043 0.6804 0.968 0.032
#> GSM1233014 1 0.4690 0.6900 0.900 0.100
#> GSM1233015 1 0.9933 0.5247 0.548 0.452
#> GSM1233016 1 0.9922 0.5267 0.552 0.448
#> GSM1233024 2 0.8861 0.0824 0.304 0.696
#> GSM1233049 1 0.2423 0.6837 0.960 0.040
#> GSM1233064 1 0.4161 0.6268 0.916 0.084
#> GSM1233068 1 0.9933 0.5203 0.548 0.452
#> GSM1233073 1 0.5946 0.6841 0.856 0.144
#> GSM1233093 1 0.3879 0.6893 0.924 0.076
#> GSM1233115 1 0.9460 0.5952 0.636 0.364
#> GSM1232992 2 0.3114 0.6008 0.056 0.944
#> GSM1232993 1 0.3733 0.6304 0.928 0.072
#> GSM1233005 2 0.2043 0.5994 0.032 0.968
#> GSM1233007 1 0.2603 0.6458 0.956 0.044
#> GSM1233010 1 0.9754 0.5649 0.592 0.408
#> GSM1233013 2 0.9552 0.5762 0.376 0.624
#> GSM1233018 2 0.2423 0.6022 0.040 0.960
#> GSM1233019 2 0.2236 0.6009 0.036 0.964
#> GSM1233021 2 0.2043 0.5994 0.032 0.968
#> GSM1233025 1 0.9754 0.5650 0.592 0.408
#> GSM1233029 1 0.4815 0.6732 0.896 0.104
#> GSM1233030 2 0.9983 0.5256 0.476 0.524
#> GSM1233031 1 0.1843 0.6804 0.972 0.028
#> GSM1233032 1 0.4939 0.6881 0.892 0.108
#> GSM1233035 1 0.9944 0.5198 0.544 0.456
#> GSM1233038 1 0.9850 0.5478 0.572 0.428
#> GSM1233039 1 0.9933 0.5212 0.548 0.452
#> GSM1233042 1 0.4815 0.6130 0.896 0.104
#> GSM1233043 1 0.9661 0.5056 0.608 0.392
#> GSM1233044 1 0.3733 0.6880 0.928 0.072
#> GSM1233046 1 0.1414 0.6702 0.980 0.020
#> GSM1233051 1 0.7376 0.6692 0.792 0.208
#> GSM1233054 1 0.1633 0.6638 0.976 0.024
#> GSM1233057 1 0.9988 0.4796 0.520 0.480
#> GSM1233060 1 0.1843 0.6748 0.972 0.028
#> GSM1233062 1 0.9775 0.5601 0.588 0.412
#> GSM1233075 2 0.9933 0.5561 0.452 0.548
#> GSM1233078 1 0.9896 0.5354 0.560 0.440
#> GSM1233079 1 0.9881 0.5399 0.564 0.436
#> GSM1233082 1 0.9881 0.5399 0.564 0.436
#> GSM1233083 1 0.6887 0.6775 0.816 0.184
#> GSM1233091 1 0.1843 0.6607 0.972 0.028
#> GSM1233095 1 0.7528 0.6682 0.784 0.216
#> GSM1233096 1 0.9881 0.5399 0.564 0.436
#> GSM1233101 1 0.1184 0.6691 0.984 0.016
#> GSM1233105 1 0.9896 0.5354 0.560 0.440
#> GSM1233117 2 0.9933 0.5586 0.452 0.548
#> GSM1233118 2 0.9922 0.5610 0.448 0.552
#> GSM1233001 2 0.9850 0.5724 0.428 0.572
#> GSM1233006 1 0.2236 0.6523 0.964 0.036
#> GSM1233008 2 0.3114 0.5455 0.056 0.944
#> GSM1233009 2 0.9795 0.5707 0.416 0.584
#> GSM1233017 2 0.9988 0.5309 0.480 0.520
#> GSM1233020 2 0.2423 0.6022 0.040 0.960
#> GSM1233022 1 0.9922 0.5267 0.552 0.448
#> GSM1233026 1 0.8016 0.6564 0.756 0.244
#> GSM1233028 1 0.9661 0.5769 0.608 0.392
#> GSM1233034 2 1.0000 -0.4619 0.496 0.504
#> GSM1233040 1 0.1633 0.6790 0.976 0.024
#> GSM1233048 1 0.1414 0.6665 0.980 0.020
#> GSM1233056 1 0.5294 0.6880 0.880 0.120
#> GSM1233058 1 0.2423 0.6689 0.960 0.040
#> GSM1233059 1 0.3274 0.6877 0.940 0.060
#> GSM1233066 1 0.9795 0.5558 0.584 0.416
#> GSM1233071 1 0.9129 0.6155 0.672 0.328
#> GSM1233074 2 0.8955 0.0566 0.312 0.688
#> GSM1233076 1 0.1184 0.6705 0.984 0.016
#> GSM1233080 1 0.7674 0.6642 0.776 0.224
#> GSM1233088 1 0.1414 0.6706 0.980 0.020
#> GSM1233090 1 0.1414 0.6792 0.980 0.020
#> GSM1233092 1 0.2603 0.6596 0.956 0.044
#> GSM1233094 1 0.2603 0.6458 0.956 0.044
#> GSM1233097 1 0.4939 0.5846 0.892 0.108
#> GSM1233100 1 0.7299 0.6679 0.796 0.204
#> GSM1233104 1 0.8861 0.6270 0.696 0.304
#> GSM1233106 1 0.9881 0.5399 0.564 0.436
#> GSM1233111 1 0.9896 0.5354 0.560 0.440
#> GSM1233122 2 0.9896 0.5662 0.440 0.560
#> GSM1233146 1 0.9922 0.5267 0.552 0.448
#> GSM1232994 2 0.1184 0.5903 0.016 0.984
#> GSM1232996 2 0.0938 0.5888 0.012 0.988
#> GSM1232997 2 0.9732 -0.2455 0.404 0.596
#> GSM1232998 2 0.1184 0.5903 0.016 0.984
#> GSM1232999 1 0.7602 0.6656 0.780 0.220
#> GSM1233000 1 0.9944 -0.4276 0.544 0.456
#> GSM1233004 1 0.0938 0.6751 0.988 0.012
#> GSM1233011 1 0.9909 0.5309 0.556 0.444
#> GSM1233012 1 0.9996 0.4691 0.512 0.488
#> GSM1233023 2 0.8327 0.1900 0.264 0.736
#> GSM1233027 2 0.2043 0.5610 0.032 0.968
#> GSM1233033 1 0.9922 0.5267 0.552 0.448
#> GSM1233036 1 0.9977 0.4931 0.528 0.472
#> GSM1233037 1 0.9866 0.5428 0.568 0.432
#> GSM1233041 1 0.9491 0.5918 0.632 0.368
#> GSM1233045 1 0.7139 0.6254 0.804 0.196
#> GSM1233047 1 0.1414 0.6665 0.980 0.020
#> GSM1233050 1 0.0938 0.6755 0.988 0.012
#> GSM1233052 1 0.1843 0.6607 0.972 0.028
#> GSM1233053 1 0.1633 0.6691 0.976 0.024
#> GSM1233055 1 0.0938 0.6714 0.988 0.012
#> GSM1233061 1 0.1633 0.6638 0.976 0.024
#> GSM1233063 1 0.9881 0.5399 0.564 0.436
#> GSM1233065 2 0.3431 0.6047 0.064 0.936
#> GSM1233070 1 0.2778 0.6362 0.952 0.048
#> GSM1233077 1 0.1843 0.6734 0.972 0.028
#> GSM1233081 1 0.9754 0.5645 0.592 0.408
#> GSM1233084 1 0.9754 0.5652 0.592 0.408
#> GSM1233087 1 0.9754 0.5624 0.592 0.408
#> GSM1233089 2 0.3274 0.6044 0.060 0.940
#> GSM1233099 1 0.2423 0.6494 0.960 0.040
#> GSM1233112 1 0.2948 0.6871 0.948 0.052
#> GSM1233085 1 0.0672 0.6733 0.992 0.008
#> GSM1233098 1 0.9983 -0.4597 0.524 0.476
#> GSM1233114 1 0.9909 0.5309 0.556 0.444
#> GSM1233119 1 0.9881 0.5399 0.564 0.436
#> GSM1233129 1 0.5946 0.4962 0.856 0.144
#> GSM1233132 1 0.1843 0.6607 0.972 0.028
#> GSM1233139 1 0.4161 0.6043 0.916 0.084
#> GSM1233143 2 0.9427 -0.0998 0.360 0.640
#> GSM1233145 1 0.9815 0.5549 0.580 0.420
#> GSM1233067 2 0.9850 0.5703 0.428 0.572
#> GSM1233069 1 0.4298 0.5985 0.912 0.088
#> GSM1233072 2 0.9896 0.5631 0.440 0.560
#> GSM1233086 1 0.3114 0.6877 0.944 0.056
#> GSM1233102 1 0.9323 0.6038 0.652 0.348
#> GSM1233103 1 0.2043 0.6572 0.968 0.032
#> GSM1233107 1 0.9909 0.5309 0.556 0.444
#> GSM1233108 1 0.9881 0.5399 0.564 0.436
#> GSM1233109 1 0.6712 0.6784 0.824 0.176
#> GSM1233110 1 0.2778 0.6843 0.952 0.048
#> GSM1233113 2 0.9850 0.5709 0.428 0.572
#> GSM1233116 2 0.9815 0.5749 0.420 0.580
#> GSM1233120 1 0.1414 0.6665 0.980 0.020
#> GSM1233121 1 0.1843 0.6633 0.972 0.028
#> GSM1233123 1 0.2043 0.6560 0.968 0.032
#> GSM1233124 1 0.1184 0.6705 0.984 0.016
#> GSM1233125 1 0.8661 0.6360 0.712 0.288
#> GSM1233126 1 0.2236 0.6657 0.964 0.036
#> GSM1233127 1 0.9209 0.0357 0.664 0.336
#> GSM1233128 1 0.9881 0.5399 0.564 0.436
#> GSM1233130 1 0.5178 0.6879 0.884 0.116
#> GSM1233131 1 0.3879 0.6895 0.924 0.076
#> GSM1233133 1 0.0938 0.6768 0.988 0.012
#> GSM1233134 1 0.8608 0.6326 0.716 0.284
#> GSM1233135 1 0.8144 0.6528 0.748 0.252
#> GSM1233136 1 0.1633 0.6711 0.976 0.024
#> GSM1233137 1 0.0938 0.6714 0.988 0.012
#> GSM1233138 1 0.5842 0.6846 0.860 0.140
#> GSM1233140 1 0.9686 0.5728 0.604 0.396
#> GSM1233141 2 0.9896 0.5662 0.440 0.560
#> GSM1233142 2 0.9909 0.5655 0.444 0.556
#> GSM1233144 1 0.4161 0.6888 0.916 0.084
#> GSM1233147 1 0.2043 0.6756 0.968 0.032
cbind(get_classes(res, k = 3), get_membership(res, k = 3))
#> class entropy silhouette p1 p2 p3
#> GSM1232995 3 0.5291 0.5815 0.000 0.268 0.732
#> GSM1233002 1 0.5803 0.5899 0.736 0.248 0.016
#> GSM1233003 2 0.3846 0.7359 0.108 0.876 0.016
#> GSM1233014 2 0.4602 0.7119 0.152 0.832 0.016
#> GSM1233015 1 0.4465 0.6920 0.820 0.004 0.176
#> GSM1233016 1 0.1753 0.7462 0.952 0.000 0.048
#> GSM1233024 1 0.4062 0.7039 0.836 0.000 0.164
#> GSM1233049 2 0.1170 0.7771 0.016 0.976 0.008
#> GSM1233064 2 0.4978 0.6671 0.004 0.780 0.216
#> GSM1233068 1 0.5480 0.6325 0.732 0.004 0.264
#> GSM1233073 2 0.4663 0.7224 0.156 0.828 0.016
#> GSM1233093 2 0.3148 0.7766 0.048 0.916 0.036
#> GSM1233115 1 0.9112 0.4914 0.524 0.168 0.308
#> GSM1232992 3 0.7348 0.4027 0.348 0.044 0.608
#> GSM1232993 2 0.5420 0.6353 0.008 0.752 0.240
#> GSM1233005 3 0.2261 0.6223 0.068 0.000 0.932
#> GSM1233007 2 0.2261 0.7663 0.000 0.932 0.068
#> GSM1233010 1 0.4099 0.6964 0.852 0.140 0.008
#> GSM1233013 3 0.7944 0.5923 0.088 0.296 0.616
#> GSM1233018 3 0.1411 0.6359 0.036 0.000 0.964
#> GSM1233019 3 0.1525 0.6376 0.032 0.004 0.964
#> GSM1233021 3 0.1860 0.6313 0.052 0.000 0.948
#> GSM1233025 1 0.2998 0.7279 0.916 0.068 0.016
#> GSM1233029 2 0.5582 0.7232 0.088 0.812 0.100
#> GSM1233030 2 0.8414 -0.0300 0.092 0.528 0.380
#> GSM1233031 2 0.3846 0.7419 0.108 0.876 0.016
#> GSM1233032 2 0.6161 0.5736 0.288 0.696 0.016
#> GSM1233035 1 0.5024 0.6651 0.776 0.004 0.220
#> GSM1233038 1 0.2651 0.7478 0.928 0.060 0.012
#> GSM1233039 1 0.6297 0.5517 0.640 0.008 0.352
#> GSM1233042 2 0.5958 0.5693 0.008 0.692 0.300
#> GSM1233043 3 0.9767 0.0362 0.248 0.320 0.432
#> GSM1233044 2 0.4782 0.7001 0.164 0.820 0.016
#> GSM1233046 2 0.0661 0.7746 0.008 0.988 0.004
#> GSM1233051 2 0.6777 0.4151 0.364 0.616 0.020
#> GSM1233054 2 0.1860 0.7700 0.000 0.948 0.052
#> GSM1233057 1 0.5873 0.5897 0.684 0.004 0.312
#> GSM1233060 2 0.1399 0.7744 0.004 0.968 0.028
#> GSM1233062 1 0.6738 0.5416 0.624 0.020 0.356
#> GSM1233075 3 0.8025 0.3933 0.064 0.420 0.516
#> GSM1233078 1 0.1905 0.7484 0.956 0.028 0.016
#> GSM1233079 1 0.2651 0.7468 0.928 0.012 0.060
#> GSM1233082 1 0.1129 0.7504 0.976 0.004 0.020
#> GSM1233083 2 0.7319 0.6192 0.164 0.708 0.128
#> GSM1233091 2 0.2959 0.7546 0.000 0.900 0.100
#> GSM1233095 2 0.8569 0.4668 0.196 0.608 0.196
#> GSM1233096 1 0.2229 0.7522 0.944 0.012 0.044
#> GSM1233101 2 0.2066 0.7684 0.000 0.940 0.060
#> GSM1233105 1 0.1267 0.7501 0.972 0.004 0.024
#> GSM1233117 2 0.6553 -0.0586 0.008 0.580 0.412
#> GSM1233118 3 0.6483 0.4223 0.004 0.452 0.544
#> GSM1233001 3 0.8511 0.5811 0.152 0.244 0.604
#> GSM1233006 2 0.1015 0.7724 0.012 0.980 0.008
#> GSM1233008 1 0.4399 0.6894 0.812 0.000 0.188
#> GSM1233009 3 0.8350 0.5770 0.120 0.280 0.600
#> GSM1233017 2 0.7203 -0.1340 0.028 0.556 0.416
#> GSM1233020 3 0.1015 0.6435 0.008 0.012 0.980
#> GSM1233022 1 0.1482 0.7503 0.968 0.012 0.020
#> GSM1233026 1 0.5639 0.6082 0.752 0.232 0.016
#> GSM1233028 1 0.9054 0.4262 0.496 0.144 0.360
#> GSM1233034 1 0.5404 0.6380 0.740 0.004 0.256
#> GSM1233040 2 0.2116 0.7747 0.012 0.948 0.040
#> GSM1233048 2 0.3267 0.7458 0.000 0.884 0.116
#> GSM1233056 2 0.4390 0.7285 0.148 0.840 0.012
#> GSM1233058 2 0.5335 0.6443 0.008 0.760 0.232
#> GSM1233059 2 0.3690 0.7462 0.100 0.884 0.016
#> GSM1233066 1 0.3009 0.7556 0.920 0.028 0.052
#> GSM1233071 1 0.5803 0.5946 0.736 0.248 0.016
#> GSM1233074 1 0.3551 0.7229 0.868 0.000 0.132
#> GSM1233076 2 0.3445 0.7473 0.088 0.896 0.016
#> GSM1233080 2 0.6925 0.1745 0.452 0.532 0.016
#> GSM1233088 2 0.2031 0.7715 0.032 0.952 0.016
#> GSM1233090 2 0.0848 0.7740 0.008 0.984 0.008
#> GSM1233092 2 0.5237 0.7096 0.120 0.824 0.056
#> GSM1233094 2 0.3551 0.7372 0.000 0.868 0.132
#> GSM1233097 2 0.5864 0.5825 0.008 0.704 0.288
#> GSM1233100 2 0.9021 0.3543 0.156 0.528 0.316
#> GSM1233104 1 0.5939 0.6114 0.748 0.224 0.028
#> GSM1233106 1 0.1765 0.7495 0.956 0.004 0.040
#> GSM1233111 1 0.1860 0.7452 0.948 0.000 0.052
#> GSM1233122 3 0.8258 0.5783 0.112 0.284 0.604
#> GSM1233146 1 0.1031 0.7492 0.976 0.000 0.024
#> GSM1232994 3 0.2711 0.6088 0.088 0.000 0.912
#> GSM1232996 3 0.3619 0.5693 0.136 0.000 0.864
#> GSM1232997 1 0.5722 0.6115 0.704 0.004 0.292
#> GSM1232998 3 0.2625 0.6122 0.084 0.000 0.916
#> GSM1232999 1 0.7533 0.2701 0.564 0.392 0.044
#> GSM1233000 2 0.5882 0.2222 0.000 0.652 0.348
#> GSM1233004 2 0.1289 0.7737 0.000 0.968 0.032
#> GSM1233011 1 0.1170 0.7486 0.976 0.016 0.008
#> GSM1233012 1 0.5610 0.5990 0.776 0.028 0.196
#> GSM1233023 1 0.5690 0.6162 0.708 0.004 0.288
#> GSM1233027 1 0.6062 0.4951 0.616 0.000 0.384
#> GSM1233033 1 0.3573 0.7184 0.876 0.004 0.120
#> GSM1233036 1 0.5623 0.6179 0.716 0.004 0.280
#> GSM1233037 1 0.7997 0.5013 0.568 0.072 0.360
#> GSM1233041 1 0.4390 0.6874 0.840 0.148 0.012
#> GSM1233045 2 0.7640 0.4412 0.056 0.592 0.352
#> GSM1233047 2 0.3619 0.7337 0.000 0.864 0.136
#> GSM1233050 2 0.2496 0.7697 0.004 0.928 0.068
#> GSM1233052 2 0.2066 0.7682 0.000 0.940 0.060
#> GSM1233053 2 0.5536 0.6399 0.012 0.752 0.236
#> GSM1233055 2 0.4634 0.7100 0.012 0.824 0.164
#> GSM1233061 2 0.1964 0.7696 0.000 0.944 0.056
#> GSM1233063 1 0.2339 0.7502 0.940 0.012 0.048
#> GSM1233065 3 0.1411 0.6443 0.000 0.036 0.964
#> GSM1233070 2 0.0661 0.7738 0.004 0.988 0.008
#> GSM1233077 2 0.3587 0.7473 0.088 0.892 0.020
#> GSM1233081 3 0.9982 -0.2284 0.348 0.304 0.348
#> GSM1233084 1 0.3983 0.6961 0.852 0.144 0.004
#> GSM1233087 1 0.5650 0.7308 0.808 0.108 0.084
#> GSM1233089 3 0.1950 0.6415 0.040 0.008 0.952
#> GSM1233099 2 0.3038 0.7541 0.000 0.896 0.104
#> GSM1233112 2 0.5435 0.6845 0.024 0.784 0.192
#> GSM1233085 2 0.2955 0.7638 0.008 0.912 0.080
#> GSM1233098 2 0.7777 0.1099 0.060 0.576 0.364
#> GSM1233114 1 0.1753 0.7463 0.952 0.000 0.048
#> GSM1233119 1 0.1620 0.7466 0.964 0.024 0.012
#> GSM1233129 2 0.2356 0.7652 0.000 0.928 0.072
#> GSM1233132 2 0.4110 0.7202 0.004 0.844 0.152
#> GSM1233139 2 0.3276 0.7536 0.068 0.908 0.024
#> GSM1233143 1 0.6526 0.4708 0.704 0.036 0.260
#> GSM1233145 1 0.5235 0.7043 0.812 0.152 0.036
#> GSM1233067 3 0.4654 0.6092 0.000 0.208 0.792
#> GSM1233069 2 0.2681 0.7617 0.040 0.932 0.028
#> GSM1233072 3 0.5733 0.5579 0.000 0.324 0.676
#> GSM1233086 2 0.2384 0.7696 0.056 0.936 0.008
#> GSM1233102 1 0.5681 0.6039 0.748 0.236 0.016
#> GSM1233103 2 0.0747 0.7737 0.000 0.984 0.016
#> GSM1233107 1 0.1877 0.7402 0.956 0.032 0.012
#> GSM1233108 1 0.1999 0.7385 0.952 0.036 0.012
#> GSM1233109 1 0.6919 0.1523 0.536 0.448 0.016
#> GSM1233110 2 0.5803 0.6185 0.248 0.736 0.016
#> GSM1233113 3 0.6062 0.5447 0.000 0.384 0.616
#> GSM1233116 3 0.8334 0.5912 0.136 0.248 0.616
#> GSM1233120 2 0.2796 0.7600 0.000 0.908 0.092
#> GSM1233121 2 0.3832 0.7402 0.100 0.880 0.020
#> GSM1233123 2 0.0661 0.7733 0.008 0.988 0.004
#> GSM1233124 2 0.3610 0.7431 0.096 0.888 0.016
#> GSM1233125 1 0.6445 0.5066 0.672 0.308 0.020
#> GSM1233126 2 0.4136 0.7476 0.020 0.864 0.116
#> GSM1233127 2 0.9342 -0.1436 0.168 0.452 0.380
#> GSM1233128 1 0.1315 0.7477 0.972 0.020 0.008
#> GSM1233130 2 0.6090 0.6001 0.264 0.716 0.020
#> GSM1233131 2 0.3678 0.7704 0.080 0.892 0.028
#> GSM1233133 2 0.2116 0.7653 0.040 0.948 0.012
#> GSM1233134 1 0.9613 0.0714 0.472 0.244 0.284
#> GSM1233135 1 0.7922 0.1922 0.532 0.408 0.060
#> GSM1233136 2 0.4418 0.7195 0.132 0.848 0.020
#> GSM1233137 2 0.1399 0.7751 0.004 0.968 0.028
#> GSM1233138 1 0.6704 0.3534 0.608 0.376 0.016
#> GSM1233140 1 0.3445 0.7197 0.896 0.088 0.016
#> GSM1233141 3 0.8262 0.5800 0.116 0.276 0.608
#> GSM1233142 3 0.7470 0.5681 0.052 0.336 0.612
#> GSM1233144 2 0.5414 0.6589 0.212 0.772 0.016
#> GSM1233147 2 0.5253 0.6749 0.188 0.792 0.020
cbind(get_classes(res, k = 4), get_membership(res, k = 4))
#> class entropy silhouette p1 p2 p3 p4
#> GSM1232995 2 0.622 0.50005 0.316 0.608 0.000 0.076
#> GSM1233002 3 0.509 0.56647 0.040 0.128 0.792 0.040
#> GSM1233003 1 0.586 0.06677 0.492 0.024 0.480 0.004
#> GSM1233014 3 0.646 0.09635 0.412 0.072 0.516 0.000
#> GSM1233015 4 0.480 0.45240 0.000 0.004 0.340 0.656
#> GSM1233016 3 0.456 0.36192 0.000 0.004 0.700 0.296
#> GSM1233024 4 0.700 0.34709 0.000 0.140 0.316 0.544
#> GSM1233049 1 0.360 0.66414 0.876 0.024 0.032 0.068
#> GSM1233064 1 0.588 0.54057 0.632 0.056 0.000 0.312
#> GSM1233068 4 0.385 0.58027 0.000 0.012 0.180 0.808
#> GSM1233073 1 0.681 0.57841 0.672 0.048 0.192 0.088
#> GSM1233093 1 0.472 0.64870 0.804 0.016 0.048 0.132
#> GSM1233115 4 0.709 0.43127 0.176 0.004 0.236 0.584
#> GSM1232992 2 0.519 0.40378 0.000 0.616 0.372 0.012
#> GSM1232993 1 0.484 0.52754 0.688 0.012 0.000 0.300
#> GSM1233005 2 0.423 0.49730 0.004 0.776 0.008 0.212
#> GSM1233007 1 0.293 0.65513 0.900 0.068 0.008 0.024
#> GSM1233010 3 0.349 0.54564 0.028 0.004 0.864 0.104
#> GSM1233013 2 0.643 0.59437 0.164 0.672 0.156 0.008
#> GSM1233018 2 0.592 0.41837 0.040 0.608 0.004 0.348
#> GSM1233019 2 0.623 0.41344 0.068 0.584 0.000 0.348
#> GSM1233021 2 0.535 0.36772 0.004 0.616 0.012 0.368
#> GSM1233025 3 0.247 0.56468 0.004 0.024 0.920 0.052
#> GSM1233029 1 0.805 0.35078 0.564 0.192 0.188 0.056
#> GSM1233030 2 0.722 0.33579 0.188 0.540 0.272 0.000
#> GSM1233031 1 0.671 0.05971 0.464 0.088 0.448 0.000
#> GSM1233032 3 0.594 0.44746 0.212 0.104 0.684 0.000
#> GSM1233035 4 0.559 0.40763 0.012 0.012 0.364 0.612
#> GSM1233038 3 0.493 0.40318 0.024 0.000 0.712 0.264
#> GSM1233039 4 0.222 0.55738 0.020 0.020 0.024 0.936
#> GSM1233042 1 0.693 0.29695 0.456 0.108 0.000 0.436
#> GSM1233043 4 0.737 0.02965 0.268 0.212 0.000 0.520
#> GSM1233044 3 0.680 0.29905 0.308 0.124 0.568 0.000
#> GSM1233046 1 0.413 0.62330 0.840 0.044 0.104 0.012
#> GSM1233051 1 0.737 0.02219 0.464 0.036 0.432 0.068
#> GSM1233054 1 0.393 0.65802 0.856 0.084 0.016 0.044
#> GSM1233057 4 0.314 0.57893 0.020 0.024 0.060 0.896
#> GSM1233060 1 0.501 0.60438 0.780 0.152 0.056 0.012
#> GSM1233062 4 0.658 0.44979 0.240 0.008 0.112 0.640
#> GSM1233075 2 0.459 0.56578 0.068 0.812 0.112 0.008
#> GSM1233078 3 0.658 0.44772 0.000 0.168 0.632 0.200
#> GSM1233079 3 0.479 0.19971 0.000 0.000 0.620 0.380
#> GSM1233082 3 0.425 0.39597 0.000 0.000 0.724 0.276
#> GSM1233083 1 0.610 0.60889 0.672 0.028 0.040 0.260
#> GSM1233091 1 0.391 0.65853 0.836 0.044 0.000 0.120
#> GSM1233095 1 0.586 0.53298 0.632 0.020 0.020 0.328
#> GSM1233096 3 0.443 0.39304 0.004 0.000 0.720 0.276
#> GSM1233101 1 0.246 0.66118 0.912 0.008 0.004 0.076
#> GSM1233105 3 0.477 0.37866 0.008 0.004 0.708 0.280
#> GSM1233117 2 0.542 0.54509 0.240 0.704 0.056 0.000
#> GSM1233118 2 0.394 0.61401 0.188 0.800 0.012 0.000
#> GSM1233001 2 0.415 0.61757 0.056 0.824 0.120 0.000
#> GSM1233006 1 0.745 0.29370 0.484 0.324 0.192 0.000
#> GSM1233008 4 0.584 0.46286 0.000 0.060 0.292 0.648
#> GSM1233009 2 0.612 0.60298 0.160 0.680 0.160 0.000
#> GSM1233017 2 0.733 0.44755 0.368 0.504 0.116 0.012
#> GSM1233020 2 0.552 0.43557 0.028 0.652 0.004 0.316
#> GSM1233022 3 0.385 0.49593 0.000 0.012 0.808 0.180
#> GSM1233026 3 0.344 0.57060 0.048 0.084 0.868 0.000
#> GSM1233028 4 0.502 0.42175 0.220 0.012 0.024 0.744
#> GSM1233034 4 0.438 0.49929 0.000 0.000 0.296 0.704
#> GSM1233040 1 0.241 0.66369 0.920 0.004 0.016 0.060
#> GSM1233048 1 0.409 0.64087 0.804 0.024 0.000 0.172
#> GSM1233056 1 0.645 0.58973 0.704 0.060 0.172 0.064
#> GSM1233058 1 0.493 0.54299 0.688 0.016 0.000 0.296
#> GSM1233059 1 0.487 0.53096 0.736 0.032 0.232 0.000
#> GSM1233066 3 0.645 0.32739 0.092 0.008 0.640 0.260
#> GSM1233071 3 0.654 0.48766 0.044 0.252 0.656 0.048
#> GSM1233074 4 0.773 0.18007 0.000 0.232 0.356 0.412
#> GSM1233076 3 0.788 0.03044 0.328 0.292 0.380 0.000
#> GSM1233080 3 0.788 0.13873 0.380 0.064 0.480 0.076
#> GSM1233088 1 0.766 0.29028 0.488 0.296 0.212 0.004
#> GSM1233090 1 0.333 0.61614 0.864 0.024 0.112 0.000
#> GSM1233092 3 0.786 0.19671 0.200 0.356 0.436 0.008
#> GSM1233094 1 0.343 0.64749 0.844 0.012 0.000 0.144
#> GSM1233097 1 0.604 0.43027 0.560 0.048 0.000 0.392
#> GSM1233100 1 0.579 0.38967 0.580 0.016 0.012 0.392
#> GSM1233104 3 0.643 0.54811 0.076 0.180 0.700 0.044
#> GSM1233106 3 0.465 0.33262 0.004 0.000 0.684 0.312
#> GSM1233111 3 0.476 0.29643 0.004 0.000 0.664 0.332
#> GSM1233122 2 0.430 0.63005 0.084 0.820 0.096 0.000
#> GSM1233146 3 0.428 0.38778 0.000 0.000 0.720 0.280
#> GSM1232994 4 0.594 0.00298 0.008 0.388 0.028 0.576
#> GSM1232996 2 0.560 0.37652 0.000 0.632 0.036 0.332
#> GSM1232997 4 0.420 0.58493 0.000 0.036 0.156 0.808
#> GSM1232998 4 0.551 0.10216 0.004 0.384 0.016 0.596
#> GSM1232999 3 0.453 0.53507 0.132 0.068 0.800 0.000
#> GSM1233000 2 0.482 0.51829 0.236 0.740 0.016 0.008
#> GSM1233004 1 0.577 0.56600 0.716 0.212 0.052 0.020
#> GSM1233011 3 0.361 0.47786 0.000 0.000 0.800 0.200
#> GSM1233012 3 0.526 0.49953 0.024 0.128 0.780 0.068
#> GSM1233023 4 0.512 0.52820 0.000 0.044 0.232 0.724
#> GSM1233027 4 0.585 0.53652 0.000 0.100 0.208 0.692
#> GSM1233033 4 0.500 0.14334 0.000 0.000 0.492 0.508
#> GSM1233036 4 0.399 0.57842 0.008 0.004 0.188 0.800
#> GSM1233037 4 0.426 0.42819 0.188 0.012 0.008 0.792
#> GSM1233041 3 0.427 0.51964 0.040 0.004 0.816 0.140
#> GSM1233045 4 0.759 -0.19408 0.352 0.204 0.000 0.444
#> GSM1233047 1 0.441 0.63688 0.780 0.028 0.000 0.192
#> GSM1233050 1 0.501 0.65268 0.772 0.112 0.000 0.116
#> GSM1233052 1 0.106 0.66144 0.972 0.012 0.000 0.016
#> GSM1233053 1 0.430 0.54985 0.716 0.000 0.000 0.284
#> GSM1233055 1 0.432 0.59860 0.760 0.012 0.000 0.228
#> GSM1233061 1 0.239 0.65291 0.928 0.024 0.036 0.012
#> GSM1233063 3 0.516 0.21187 0.012 0.000 0.624 0.364
#> GSM1233065 4 0.662 0.08040 0.120 0.280 0.000 0.600
#> GSM1233070 1 0.721 0.35652 0.540 0.276 0.184 0.000
#> GSM1233077 2 0.806 -0.12067 0.296 0.352 0.348 0.004
#> GSM1233081 4 0.618 -0.09969 0.424 0.000 0.052 0.524
#> GSM1233084 3 0.416 0.54267 0.012 0.024 0.824 0.140
#> GSM1233087 4 0.663 0.36440 0.048 0.024 0.348 0.580
#> GSM1233089 2 0.538 0.43081 0.008 0.656 0.016 0.320
#> GSM1233099 1 0.545 0.63561 0.736 0.108 0.000 0.156
#> GSM1233112 1 0.425 0.59171 0.744 0.004 0.000 0.252
#> GSM1233085 1 0.360 0.65164 0.848 0.008 0.012 0.132
#> GSM1233098 2 0.582 0.46429 0.112 0.724 0.156 0.008
#> GSM1233114 3 0.499 0.27275 0.004 0.004 0.648 0.344
#> GSM1233119 3 0.345 0.50707 0.000 0.004 0.828 0.168
#> GSM1233129 1 0.339 0.64843 0.880 0.080 0.024 0.016
#> GSM1233132 1 0.450 0.62670 0.764 0.024 0.000 0.212
#> GSM1233139 1 0.789 0.08536 0.372 0.340 0.288 0.000
#> GSM1233143 3 0.253 0.55756 0.008 0.048 0.920 0.024
#> GSM1233145 3 0.669 0.17341 0.072 0.008 0.544 0.376
#> GSM1233067 2 0.665 0.47519 0.316 0.576 0.000 0.108
#> GSM1233069 2 0.801 -0.08852 0.336 0.388 0.272 0.004
#> GSM1233072 2 0.468 0.60181 0.176 0.776 0.000 0.048
#> GSM1233086 1 0.582 0.45626 0.652 0.016 0.304 0.028
#> GSM1233102 3 0.450 0.57085 0.040 0.088 0.832 0.040
#> GSM1233103 1 0.532 0.50804 0.672 0.296 0.032 0.000
#> GSM1233107 3 0.392 0.52707 0.028 0.008 0.840 0.124
#> GSM1233108 3 0.463 0.51135 0.000 0.048 0.780 0.172
#> GSM1233109 3 0.493 0.54435 0.168 0.028 0.780 0.024
#> GSM1233110 3 0.633 0.42499 0.216 0.132 0.652 0.000
#> GSM1233113 2 0.397 0.63173 0.164 0.816 0.004 0.016
#> GSM1233116 2 0.641 0.58019 0.148 0.648 0.204 0.000
#> GSM1233120 1 0.644 0.61298 0.648 0.184 0.000 0.168
#> GSM1233121 3 0.807 0.01229 0.312 0.340 0.344 0.004
#> GSM1233123 1 0.452 0.54321 0.768 0.028 0.204 0.000
#> GSM1233124 1 0.639 0.10011 0.492 0.064 0.444 0.000
#> GSM1233125 3 0.593 0.54772 0.040 0.188 0.724 0.048
#> GSM1233126 1 0.668 0.57353 0.612 0.116 0.004 0.268
#> GSM1233127 3 0.722 -0.01641 0.160 0.328 0.512 0.000
#> GSM1233128 3 0.395 0.46116 0.000 0.004 0.780 0.216
#> GSM1233130 3 0.749 0.27603 0.172 0.328 0.496 0.004
#> GSM1233131 1 0.676 0.61048 0.684 0.176 0.064 0.076
#> GSM1233133 1 0.615 0.42548 0.636 0.084 0.280 0.000
#> GSM1233134 3 0.689 0.34262 0.152 0.192 0.640 0.016
#> GSM1233135 3 0.605 0.45502 0.060 0.276 0.656 0.008
#> GSM1233136 3 0.789 0.17118 0.232 0.348 0.416 0.004
#> GSM1233137 1 0.464 0.61218 0.804 0.132 0.056 0.008
#> GSM1233138 3 0.485 0.53925 0.072 0.152 0.776 0.000
#> GSM1233140 3 0.236 0.56382 0.004 0.020 0.924 0.052
#> GSM1233141 2 0.369 0.61850 0.064 0.856 0.080 0.000
#> GSM1233142 2 0.630 0.57986 0.260 0.636 0.104 0.000
#> GSM1233144 3 0.758 0.13472 0.336 0.208 0.456 0.000
#> GSM1233147 3 0.647 0.34636 0.288 0.104 0.608 0.000
cbind(get_classes(res, k = 5), get_membership(res, k = 5))
#> class entropy silhouette p1 p2 p3 p4 p5
#> GSM1232995 2 0.378 0.56555 0.000 0.752 0.000 0.236 0.012
#> GSM1233002 3 0.614 0.21586 0.380 0.036 0.536 0.008 0.040
#> GSM1233003 3 0.910 0.13354 0.256 0.068 0.312 0.276 0.088
#> GSM1233014 3 0.793 0.49764 0.180 0.100 0.536 0.148 0.036
#> GSM1233015 1 0.452 0.15510 0.600 0.012 0.000 0.000 0.388
#> GSM1233016 1 0.308 0.63545 0.868 0.004 0.072 0.000 0.056
#> GSM1233024 5 0.649 0.37928 0.276 0.016 0.160 0.000 0.548
#> GSM1233049 4 0.533 0.59722 0.008 0.084 0.140 0.736 0.032
#> GSM1233064 4 0.633 0.55436 0.000 0.112 0.056 0.632 0.200
#> GSM1233068 5 0.445 0.33064 0.400 0.000 0.000 0.008 0.592
#> GSM1233073 4 0.895 0.37645 0.064 0.228 0.192 0.404 0.112
#> GSM1233093 4 0.637 0.60641 0.040 0.156 0.060 0.680 0.064
#> GSM1233115 5 0.844 0.31914 0.272 0.088 0.084 0.096 0.460
#> GSM1232992 2 0.544 0.43858 0.228 0.676 0.076 0.000 0.020
#> GSM1232993 4 0.555 0.56490 0.040 0.080 0.024 0.740 0.116
#> GSM1233005 5 0.710 -0.16103 0.008 0.388 0.192 0.012 0.400
#> GSM1233007 4 0.439 0.56433 0.004 0.020 0.160 0.780 0.036
#> GSM1233010 1 0.487 0.62421 0.776 0.056 0.104 0.004 0.060
#> GSM1233013 2 0.219 0.61439 0.016 0.924 0.004 0.044 0.012
#> GSM1233018 2 0.536 0.35087 0.032 0.600 0.000 0.020 0.348
#> GSM1233019 2 0.644 0.36314 0.028 0.572 0.004 0.104 0.292
#> GSM1233021 5 0.578 -0.16400 0.020 0.456 0.020 0.016 0.488
#> GSM1233025 1 0.458 0.54124 0.716 0.012 0.244 0.000 0.028
#> GSM1233029 4 0.935 0.05211 0.124 0.164 0.288 0.328 0.096
#> GSM1233030 2 0.589 0.24359 0.012 0.600 0.320 0.048 0.020
#> GSM1233031 3 0.885 0.35636 0.132 0.216 0.440 0.140 0.072
#> GSM1233032 3 0.635 0.36771 0.300 0.056 0.592 0.020 0.032
#> GSM1233035 1 0.624 0.32674 0.648 0.028 0.020 0.088 0.216
#> GSM1233038 1 0.265 0.63296 0.904 0.008 0.024 0.012 0.052
#> GSM1233039 5 0.560 0.51425 0.188 0.020 0.004 0.100 0.688
#> GSM1233042 4 0.662 0.20743 0.000 0.020 0.132 0.480 0.368
#> GSM1233043 5 0.679 0.20064 0.000 0.024 0.216 0.228 0.532
#> GSM1233044 3 0.814 0.48983 0.164 0.208 0.504 0.076 0.048
#> GSM1233046 4 0.839 0.44535 0.056 0.292 0.120 0.444 0.088
#> GSM1233051 1 0.958 -0.20700 0.296 0.196 0.184 0.240 0.084
#> GSM1233054 4 0.642 0.57209 0.000 0.200 0.148 0.612 0.040
#> GSM1233057 5 0.566 0.52137 0.184 0.040 0.004 0.076 0.696
#> GSM1233060 4 0.746 0.42268 0.004 0.224 0.260 0.468 0.044
#> GSM1233062 4 0.824 -0.00160 0.348 0.048 0.044 0.380 0.180
#> GSM1233075 3 0.537 0.23663 0.012 0.264 0.668 0.012 0.044
#> GSM1233078 3 0.754 0.06379 0.348 0.036 0.384 0.004 0.228
#> GSM1233079 1 0.477 0.52215 0.728 0.008 0.064 0.000 0.200
#> GSM1233082 1 0.491 0.60194 0.764 0.040 0.096 0.000 0.100
#> GSM1233083 4 0.768 0.55316 0.028 0.096 0.120 0.548 0.208
#> GSM1233091 4 0.635 0.59273 0.000 0.136 0.128 0.652 0.084
#> GSM1233095 4 0.815 0.46195 0.012 0.172 0.108 0.436 0.272
#> GSM1233096 1 0.296 0.62756 0.884 0.020 0.020 0.004 0.072
#> GSM1233101 4 0.561 0.60166 0.000 0.228 0.056 0.672 0.044
#> GSM1233105 1 0.177 0.62818 0.932 0.016 0.000 0.000 0.052
#> GSM1233117 2 0.502 0.59917 0.000 0.728 0.172 0.084 0.016
#> GSM1233118 2 0.357 0.63609 0.000 0.836 0.092 0.068 0.004
#> GSM1233001 2 0.388 0.61665 0.036 0.812 0.140 0.008 0.004
#> GSM1233006 3 0.459 0.43532 0.000 0.032 0.752 0.188 0.028
#> GSM1233008 5 0.538 0.25673 0.416 0.008 0.040 0.000 0.536
#> GSM1233009 2 0.283 0.61493 0.020 0.896 0.020 0.056 0.008
#> GSM1233017 4 0.919 -0.10313 0.188 0.292 0.088 0.336 0.096
#> GSM1233020 2 0.550 0.36431 0.000 0.576 0.024 0.032 0.368
#> GSM1233022 1 0.443 0.61926 0.772 0.020 0.172 0.004 0.032
#> GSM1233026 1 0.634 0.22697 0.540 0.052 0.364 0.016 0.028
#> GSM1233028 4 0.753 0.03867 0.192 0.040 0.012 0.468 0.288
#> GSM1233034 1 0.482 -0.04893 0.540 0.004 0.004 0.008 0.444
#> GSM1233040 4 0.435 0.58945 0.028 0.040 0.040 0.824 0.068
#> GSM1233048 4 0.315 0.61842 0.000 0.044 0.052 0.876 0.028
#> GSM1233056 4 0.859 0.35287 0.032 0.228 0.232 0.408 0.100
#> GSM1233058 4 0.439 0.53635 0.012 0.040 0.028 0.804 0.116
#> GSM1233059 4 0.837 0.39930 0.088 0.132 0.188 0.508 0.084
#> GSM1233066 1 0.643 0.47153 0.676 0.040 0.040 0.120 0.124
#> GSM1233071 3 0.512 0.42663 0.252 0.012 0.680 0.000 0.056
#> GSM1233074 5 0.733 0.17373 0.308 0.028 0.260 0.000 0.404
#> GSM1233076 3 0.384 0.57621 0.060 0.012 0.840 0.076 0.012
#> GSM1233080 3 0.944 0.32610 0.212 0.180 0.360 0.144 0.104
#> GSM1233088 3 0.628 0.37545 0.008 0.064 0.652 0.200 0.076
#> GSM1233090 4 0.565 0.52608 0.024 0.032 0.192 0.704 0.048
#> GSM1233092 3 0.395 0.55476 0.068 0.028 0.844 0.028 0.032
#> GSM1233094 4 0.549 0.60663 0.004 0.244 0.024 0.672 0.056
#> GSM1233097 4 0.574 0.44377 0.000 0.052 0.032 0.616 0.300
#> GSM1233100 4 0.678 0.45032 0.020 0.168 0.004 0.532 0.276
#> GSM1233104 3 0.916 0.26444 0.188 0.284 0.304 0.040 0.184
#> GSM1233106 1 0.172 0.62785 0.936 0.004 0.008 0.000 0.052
#> GSM1233111 1 0.306 0.59766 0.856 0.008 0.016 0.000 0.120
#> GSM1233122 2 0.372 0.63116 0.016 0.824 0.128 0.032 0.000
#> GSM1233146 1 0.478 0.59336 0.764 0.024 0.096 0.000 0.116
#> GSM1232994 5 0.678 0.11735 0.120 0.372 0.008 0.020 0.480
#> GSM1232996 2 0.556 0.28484 0.060 0.572 0.008 0.000 0.360
#> GSM1232997 5 0.442 0.45447 0.296 0.024 0.000 0.000 0.680
#> GSM1232998 5 0.489 0.36731 0.056 0.212 0.008 0.004 0.720
#> GSM1232999 1 0.755 0.20946 0.520 0.096 0.284 0.032 0.068
#> GSM1233000 2 0.593 0.51767 0.000 0.640 0.244 0.076 0.040
#> GSM1233004 3 0.641 -0.03525 0.000 0.028 0.484 0.400 0.088
#> GSM1233011 1 0.305 0.65212 0.868 0.024 0.096 0.000 0.012
#> GSM1233012 1 0.513 0.57815 0.736 0.172 0.044 0.004 0.044
#> GSM1233023 5 0.466 0.42844 0.324 0.012 0.012 0.000 0.652
#> GSM1233027 5 0.559 0.24565 0.436 0.060 0.004 0.000 0.500
#> GSM1233033 1 0.410 0.42687 0.724 0.004 0.012 0.000 0.260
#> GSM1233036 1 0.676 -0.13576 0.468 0.028 0.012 0.088 0.404
#> GSM1233037 5 0.683 0.17359 0.104 0.036 0.004 0.388 0.468
#> GSM1233041 1 0.420 0.63616 0.832 0.036 0.068 0.028 0.036
#> GSM1233045 5 0.714 0.04676 0.000 0.028 0.232 0.272 0.468
#> GSM1233047 4 0.478 0.63001 0.000 0.104 0.052 0.776 0.068
#> GSM1233050 4 0.456 0.58734 0.000 0.036 0.176 0.760 0.028
#> GSM1233052 4 0.351 0.60626 0.000 0.040 0.068 0.856 0.036
#> GSM1233053 4 0.484 0.60658 0.004 0.128 0.008 0.752 0.108
#> GSM1233055 4 0.531 0.61871 0.004 0.204 0.020 0.704 0.068
#> GSM1233061 4 0.771 0.51984 0.028 0.308 0.088 0.488 0.088
#> GSM1233063 1 0.340 0.58194 0.844 0.024 0.008 0.004 0.120
#> GSM1233065 5 0.651 0.25780 0.000 0.200 0.016 0.224 0.560
#> GSM1233070 3 0.497 0.36279 0.000 0.020 0.684 0.264 0.032
#> GSM1233077 3 0.482 0.53001 0.032 0.012 0.780 0.060 0.116
#> GSM1233081 4 0.757 0.15813 0.136 0.052 0.016 0.448 0.348
#> GSM1233084 1 0.531 0.55003 0.680 0.036 0.244 0.000 0.040
#> GSM1233087 5 0.912 0.24079 0.220 0.160 0.132 0.084 0.404
#> GSM1233089 2 0.479 0.38749 0.020 0.644 0.004 0.004 0.328
#> GSM1233099 4 0.684 0.57622 0.000 0.160 0.128 0.604 0.108
#> GSM1233112 4 0.614 0.60803 0.000 0.160 0.044 0.652 0.144
#> GSM1233085 4 0.516 0.62362 0.004 0.184 0.036 0.728 0.048
#> GSM1233098 3 0.458 0.51093 0.004 0.084 0.796 0.040 0.076
#> GSM1233114 1 0.502 0.55063 0.736 0.028 0.068 0.000 0.168
#> GSM1233119 1 0.397 0.61814 0.772 0.008 0.200 0.000 0.020
#> GSM1233129 4 0.554 0.55241 0.008 0.052 0.160 0.720 0.060
#> GSM1233132 4 0.407 0.62249 0.000 0.072 0.028 0.820 0.080
#> GSM1233139 3 0.678 0.47972 0.040 0.156 0.640 0.124 0.040
#> GSM1233143 1 0.574 0.56161 0.708 0.096 0.136 0.004 0.056
#> GSM1233145 1 0.663 0.46209 0.632 0.064 0.068 0.024 0.212
#> GSM1233067 2 0.577 0.46541 0.024 0.600 0.004 0.324 0.048
#> GSM1233069 3 0.437 0.53523 0.008 0.040 0.812 0.088 0.052
#> GSM1233072 2 0.711 0.46225 0.004 0.540 0.256 0.144 0.056
#> GSM1233086 4 0.945 0.22046 0.208 0.184 0.140 0.360 0.108
#> GSM1233102 3 0.633 0.12104 0.412 0.044 0.492 0.004 0.048
#> GSM1233103 3 0.691 -0.01911 0.000 0.080 0.500 0.344 0.076
#> GSM1233107 1 0.417 0.64257 0.824 0.072 0.052 0.004 0.048
#> GSM1233108 1 0.557 0.54451 0.668 0.032 0.236 0.000 0.064
#> GSM1233109 1 0.729 0.27052 0.544 0.060 0.288 0.056 0.052
#> GSM1233110 3 0.787 0.41386 0.228 0.224 0.472 0.020 0.056
#> GSM1233113 2 0.329 0.62635 0.000 0.868 0.044 0.060 0.028
#> GSM1233116 2 0.659 0.54898 0.140 0.660 0.096 0.084 0.020
#> GSM1233120 4 0.640 0.45234 0.000 0.032 0.264 0.584 0.120
#> GSM1233121 3 0.626 0.52183 0.024 0.140 0.688 0.068 0.080
#> GSM1233123 4 0.820 0.29817 0.096 0.068 0.228 0.508 0.100
#> GSM1233124 2 0.949 -0.24092 0.148 0.320 0.264 0.172 0.096
#> GSM1233125 3 0.452 0.30100 0.340 0.008 0.644 0.000 0.008
#> GSM1233126 4 0.762 0.41447 0.084 0.040 0.172 0.572 0.132
#> GSM1233127 1 0.865 -0.00534 0.364 0.316 0.200 0.060 0.060
#> GSM1233128 1 0.267 0.63917 0.892 0.016 0.076 0.000 0.016
#> GSM1233130 3 0.322 0.57140 0.104 0.012 0.860 0.004 0.020
#> GSM1233131 4 0.760 0.35975 0.084 0.032 0.260 0.532 0.092
#> GSM1233133 3 0.860 -0.00272 0.056 0.180 0.380 0.316 0.068
#> GSM1233134 1 0.837 0.31802 0.520 0.100 0.100 0.164 0.116
#> GSM1233135 3 0.381 0.52909 0.164 0.008 0.800 0.000 0.028
#> GSM1233136 3 0.356 0.56967 0.048 0.008 0.860 0.024 0.060
#> GSM1233137 4 0.748 0.41457 0.000 0.200 0.280 0.460 0.060
#> GSM1233138 3 0.594 0.18797 0.388 0.012 0.540 0.016 0.044
#> GSM1233140 1 0.469 0.47507 0.676 0.012 0.292 0.000 0.020
#> GSM1233141 2 0.551 0.46853 0.028 0.584 0.364 0.016 0.008
#> GSM1233142 2 0.313 0.61645 0.016 0.872 0.016 0.088 0.008
#> GSM1233144 3 0.615 0.58109 0.108 0.096 0.700 0.076 0.020
#> GSM1233147 3 0.775 0.40410 0.264 0.108 0.520 0.060 0.048
cbind(get_classes(res, k = 6), get_membership(res, k = 6))
#> class entropy silhouette p1 p2 p3 p4 p5 p6
#> GSM1232995 2 0.412 0.612710 0.124 0.780 0.000 0.064 0.000 0.032
#> GSM1233002 5 0.716 0.128116 0.040 0.060 0.352 0.028 0.464 0.056
#> GSM1233003 4 0.731 0.317260 0.072 0.020 0.132 0.540 0.200 0.036
#> GSM1233014 3 0.834 0.349408 0.080 0.060 0.428 0.192 0.204 0.036
#> GSM1233015 5 0.451 0.098627 0.008 0.012 0.000 0.004 0.544 0.432
#> GSM1233016 5 0.513 0.522543 0.000 0.000 0.072 0.100 0.708 0.120
#> GSM1233024 6 0.696 0.397281 0.008 0.060 0.204 0.016 0.184 0.528
#> GSM1233049 1 0.461 0.459991 0.756 0.008 0.060 0.140 0.004 0.032
#> GSM1233064 1 0.563 0.421075 0.680 0.068 0.020 0.076 0.000 0.156
#> GSM1233068 6 0.538 0.273998 0.008 0.016 0.004 0.048 0.360 0.564
#> GSM1233073 1 0.718 0.487652 0.608 0.064 0.056 0.068 0.116 0.088
#> GSM1233093 1 0.421 0.516710 0.800 0.056 0.000 0.088 0.032 0.024
#> GSM1233115 1 0.755 -0.000669 0.332 0.076 0.004 0.012 0.276 0.300
#> GSM1232992 2 0.444 0.498432 0.004 0.708 0.016 0.012 0.244 0.016
#> GSM1232993 1 0.614 0.049731 0.464 0.040 0.000 0.412 0.016 0.068
#> GSM1233005 2 0.644 0.243534 0.008 0.424 0.272 0.008 0.000 0.288
#> GSM1233007 4 0.670 0.222444 0.320 0.028 0.116 0.492 0.000 0.044
#> GSM1233010 5 0.475 0.532389 0.044 0.024 0.024 0.060 0.784 0.064
#> GSM1233013 2 0.331 0.638553 0.088 0.848 0.004 0.004 0.040 0.016
#> GSM1233018 2 0.495 0.483104 0.028 0.644 0.000 0.020 0.016 0.292
#> GSM1233019 2 0.573 0.487997 0.012 0.600 0.004 0.108 0.012 0.264
#> GSM1233021 2 0.523 0.217173 0.004 0.484 0.028 0.012 0.012 0.460
#> GSM1233025 5 0.635 0.412142 0.000 0.024 0.208 0.192 0.556 0.020
#> GSM1233029 4 0.676 0.402813 0.028 0.012 0.204 0.584 0.100 0.072
#> GSM1233030 2 0.845 0.312762 0.172 0.468 0.128 0.088 0.076 0.068
#> GSM1233031 1 0.937 0.044528 0.304 0.072 0.208 0.132 0.196 0.088
#> GSM1233032 3 0.787 0.221792 0.068 0.048 0.424 0.072 0.332 0.056
#> GSM1233035 5 0.601 0.260224 0.000 0.008 0.004 0.356 0.472 0.160
#> GSM1233038 5 0.452 0.558767 0.020 0.004 0.008 0.092 0.764 0.112
#> GSM1233039 6 0.530 0.491930 0.060 0.012 0.008 0.056 0.152 0.712
#> GSM1233042 1 0.844 -0.058901 0.284 0.060 0.220 0.168 0.000 0.268
#> GSM1233043 6 0.759 0.064872 0.212 0.056 0.324 0.044 0.000 0.364
#> GSM1233044 1 0.937 0.041006 0.296 0.100 0.216 0.088 0.212 0.088
#> GSM1233046 1 0.678 0.446664 0.612 0.112 0.004 0.116 0.068 0.088
#> GSM1233051 1 0.826 0.311231 0.420 0.092 0.024 0.108 0.268 0.088
#> GSM1233054 1 0.401 0.514759 0.812 0.084 0.056 0.024 0.000 0.024
#> GSM1233057 6 0.623 0.412429 0.136 0.056 0.000 0.012 0.200 0.596
#> GSM1233060 1 0.607 0.491238 0.668 0.100 0.132 0.052 0.008 0.040
#> GSM1233062 4 0.470 0.480615 0.028 0.000 0.004 0.732 0.156 0.080
#> GSM1233075 3 0.457 0.527979 0.016 0.212 0.724 0.004 0.020 0.024
#> GSM1233078 5 0.839 -0.024550 0.072 0.084 0.316 0.016 0.332 0.180
#> GSM1233079 5 0.476 0.427082 0.020 0.020 0.012 0.008 0.688 0.252
#> GSM1233082 5 0.460 0.502198 0.020 0.028 0.016 0.016 0.752 0.168
#> GSM1233083 1 0.640 0.456290 0.644 0.064 0.048 0.032 0.040 0.172
#> GSM1233091 1 0.395 0.511222 0.824 0.044 0.044 0.052 0.000 0.036
#> GSM1233095 1 0.622 0.483122 0.644 0.056 0.040 0.012 0.064 0.184
#> GSM1233096 5 0.372 0.543206 0.012 0.016 0.004 0.020 0.808 0.140
#> GSM1233101 1 0.307 0.517151 0.860 0.060 0.000 0.064 0.004 0.012
#> GSM1233105 5 0.413 0.538814 0.008 0.012 0.000 0.076 0.780 0.124
#> GSM1233117 2 0.516 0.634157 0.100 0.728 0.092 0.068 0.004 0.008
#> GSM1233118 2 0.374 0.628609 0.128 0.808 0.044 0.012 0.004 0.004
#> GSM1233001 2 0.487 0.637566 0.068 0.760 0.100 0.028 0.040 0.004
#> GSM1233006 3 0.470 0.579484 0.088 0.056 0.764 0.076 0.000 0.016
#> GSM1233008 6 0.582 0.341898 0.000 0.028 0.096 0.008 0.296 0.572
#> GSM1233009 2 0.581 0.565375 0.168 0.680 0.012 0.060 0.036 0.044
#> GSM1233017 4 0.569 0.397870 0.016 0.168 0.020 0.660 0.128 0.008
#> GSM1233020 2 0.505 0.479616 0.016 0.636 0.024 0.020 0.004 0.300
#> GSM1233022 5 0.637 0.385312 0.000 0.016 0.128 0.268 0.548 0.040
#> GSM1233026 5 0.740 0.207708 0.016 0.060 0.288 0.132 0.472 0.032
#> GSM1233028 4 0.639 0.354865 0.104 0.012 0.000 0.588 0.092 0.204
#> GSM1233034 5 0.609 -0.099883 0.008 0.020 0.008 0.088 0.460 0.416
#> GSM1233040 4 0.529 0.007171 0.444 0.004 0.020 0.496 0.008 0.028
#> GSM1233048 1 0.546 0.236679 0.612 0.008 0.036 0.288 0.000 0.056
#> GSM1233056 1 0.610 0.509159 0.696 0.044 0.052 0.056 0.092 0.060
#> GSM1233058 4 0.641 0.200372 0.340 0.028 0.028 0.500 0.000 0.104
#> GSM1233059 1 0.709 0.411018 0.576 0.032 0.024 0.176 0.112 0.080
#> GSM1233066 5 0.592 0.218472 0.040 0.012 0.008 0.392 0.508 0.040
#> GSM1233071 3 0.549 0.507672 0.000 0.012 0.684 0.100 0.152 0.052
#> GSM1233074 6 0.687 0.242777 0.000 0.060 0.304 0.000 0.224 0.412
#> GSM1233076 3 0.385 0.623877 0.028 0.024 0.828 0.080 0.036 0.004
#> GSM1233080 1 0.832 0.263349 0.412 0.044 0.100 0.064 0.284 0.096
#> GSM1233088 3 0.510 0.516543 0.208 0.036 0.696 0.008 0.008 0.044
#> GSM1233090 1 0.628 0.241143 0.552 0.008 0.096 0.296 0.012 0.036
#> GSM1233092 3 0.344 0.598984 0.000 0.008 0.844 0.076 0.032 0.040
#> GSM1233094 1 0.403 0.515367 0.796 0.104 0.000 0.068 0.004 0.028
#> GSM1233097 1 0.670 0.282808 0.548 0.060 0.028 0.124 0.000 0.240
#> GSM1233100 1 0.597 0.462097 0.660 0.064 0.000 0.052 0.060 0.164
#> GSM1233104 1 0.888 0.193091 0.312 0.172 0.048 0.040 0.260 0.168
#> GSM1233106 5 0.374 0.547079 0.004 0.004 0.004 0.080 0.808 0.100
#> GSM1233111 5 0.343 0.484770 0.008 0.008 0.000 0.004 0.780 0.200
#> GSM1233122 2 0.453 0.642515 0.080 0.788 0.056 0.032 0.040 0.004
#> GSM1233146 5 0.368 0.503866 0.004 0.016 0.016 0.000 0.780 0.184
#> GSM1232994 6 0.598 -0.138937 0.004 0.408 0.000 0.064 0.052 0.472
#> GSM1232996 2 0.489 0.347703 0.008 0.572 0.004 0.000 0.040 0.376
#> GSM1232997 6 0.477 0.421234 0.024 0.044 0.000 0.000 0.272 0.660
#> GSM1232998 6 0.530 0.332484 0.020 0.244 0.012 0.008 0.056 0.660
#> GSM1232999 5 0.786 0.280295 0.012 0.228 0.084 0.144 0.468 0.064
#> GSM1233000 2 0.555 0.541994 0.192 0.656 0.112 0.020 0.000 0.020
#> GSM1233004 3 0.711 0.251513 0.288 0.064 0.496 0.084 0.000 0.068
#> GSM1233011 5 0.492 0.552483 0.004 0.020 0.048 0.112 0.752 0.064
#> GSM1233012 5 0.570 0.360680 0.004 0.308 0.012 0.080 0.580 0.016
#> GSM1233023 6 0.509 0.443970 0.008 0.048 0.020 0.008 0.244 0.672
#> GSM1233027 6 0.634 0.334381 0.000 0.092 0.020 0.044 0.316 0.528
#> GSM1233033 5 0.444 0.321610 0.000 0.000 0.008 0.028 0.632 0.332
#> GSM1233036 4 0.684 -0.147708 0.020 0.012 0.000 0.324 0.320 0.324
#> GSM1233037 6 0.748 0.048635 0.188 0.044 0.004 0.284 0.048 0.432
#> GSM1233041 5 0.371 0.571519 0.036 0.008 0.012 0.100 0.828 0.016
#> GSM1233045 6 0.769 0.058272 0.272 0.060 0.288 0.040 0.000 0.340
#> GSM1233047 1 0.429 0.461150 0.792 0.028 0.024 0.096 0.000 0.060
#> GSM1233050 1 0.660 0.292537 0.564 0.020 0.148 0.216 0.004 0.048
#> GSM1233052 1 0.553 0.041163 0.496 0.004 0.044 0.420 0.000 0.036
#> GSM1233053 1 0.524 0.385398 0.668 0.032 0.000 0.212 0.004 0.084
#> GSM1233055 1 0.366 0.510583 0.832 0.060 0.000 0.064 0.008 0.036
#> GSM1233061 1 0.683 0.461109 0.616 0.132 0.012 0.076 0.076 0.088
#> GSM1233063 5 0.449 0.498287 0.012 0.012 0.000 0.056 0.736 0.184
#> GSM1233065 6 0.719 0.214859 0.200 0.212 0.020 0.084 0.000 0.484
#> GSM1233070 3 0.503 0.559396 0.108 0.028 0.728 0.120 0.004 0.012
#> GSM1233077 3 0.348 0.624172 0.040 0.024 0.856 0.016 0.012 0.052
#> GSM1233081 1 0.711 0.303293 0.508 0.068 0.000 0.032 0.176 0.216
#> GSM1233084 5 0.635 0.498756 0.020 0.020 0.188 0.044 0.624 0.104
#> GSM1233087 1 0.774 0.022919 0.312 0.088 0.008 0.012 0.300 0.280
#> GSM1233089 2 0.513 0.512971 0.032 0.672 0.028 0.000 0.028 0.240
#> GSM1233099 1 0.488 0.492254 0.760 0.064 0.060 0.036 0.000 0.080
#> GSM1233112 1 0.354 0.523302 0.848 0.024 0.008 0.032 0.016 0.072
#> GSM1233085 1 0.369 0.501082 0.820 0.060 0.000 0.096 0.008 0.016
#> GSM1233098 3 0.289 0.638052 0.036 0.052 0.880 0.000 0.012 0.020
#> GSM1233114 5 0.486 0.421275 0.024 0.032 0.008 0.004 0.680 0.252
#> GSM1233119 5 0.494 0.544290 0.000 0.008 0.148 0.104 0.716 0.024
#> GSM1233129 4 0.658 0.341026 0.236 0.056 0.092 0.572 0.000 0.044
#> GSM1233132 1 0.629 0.148775 0.524 0.036 0.028 0.332 0.000 0.080
#> GSM1233139 3 0.846 0.194278 0.096 0.308 0.380 0.092 0.076 0.048
#> GSM1233143 5 0.570 0.500415 0.000 0.136 0.040 0.076 0.688 0.060
#> GSM1233145 5 0.689 0.270258 0.188 0.040 0.008 0.020 0.520 0.224
#> GSM1233067 2 0.560 0.462532 0.092 0.596 0.000 0.276 0.000 0.036
#> GSM1233069 3 0.353 0.629804 0.072 0.060 0.840 0.004 0.012 0.012
#> GSM1233072 2 0.753 0.146836 0.040 0.380 0.212 0.324 0.008 0.036
#> GSM1233086 1 0.838 0.184400 0.372 0.104 0.008 0.256 0.180 0.080
#> GSM1233102 5 0.731 0.084078 0.040 0.060 0.364 0.028 0.440 0.068
#> GSM1233103 3 0.631 0.091728 0.388 0.036 0.480 0.044 0.000 0.052
#> GSM1233107 5 0.421 0.546129 0.016 0.060 0.012 0.060 0.812 0.040
#> GSM1233108 5 0.510 0.516958 0.000 0.020 0.156 0.008 0.696 0.120
#> GSM1233109 5 0.728 0.345350 0.036 0.012 0.176 0.212 0.512 0.052
#> GSM1233110 1 0.934 0.088021 0.280 0.156 0.148 0.060 0.260 0.096
#> GSM1233113 2 0.351 0.637610 0.144 0.812 0.024 0.000 0.012 0.008
#> GSM1233116 2 0.577 0.569639 0.024 0.680 0.056 0.160 0.072 0.008
#> GSM1233120 1 0.765 0.229821 0.464 0.064 0.244 0.112 0.000 0.116
#> GSM1233121 3 0.711 0.443420 0.216 0.100 0.560 0.024 0.044 0.056
#> GSM1233123 4 0.696 0.323413 0.224 0.040 0.056 0.576 0.064 0.040
#> GSM1233124 1 0.888 0.302687 0.404 0.168 0.056 0.104 0.172 0.096
#> GSM1233125 3 0.540 0.511490 0.000 0.012 0.676 0.100 0.180 0.032
#> GSM1233126 4 0.544 0.514988 0.040 0.008 0.112 0.724 0.068 0.048
#> GSM1233127 2 0.786 0.108343 0.012 0.376 0.084 0.216 0.288 0.024
#> GSM1233128 5 0.553 0.453523 0.004 0.000 0.080 0.260 0.620 0.036
#> GSM1233130 3 0.286 0.626691 0.000 0.008 0.880 0.040 0.052 0.020
#> GSM1233131 4 0.654 0.433930 0.080 0.012 0.212 0.604 0.052 0.040
#> GSM1233133 1 0.857 0.248837 0.404 0.040 0.200 0.200 0.088 0.068
#> GSM1233134 4 0.692 0.174120 0.028 0.092 0.032 0.504 0.316 0.028
#> GSM1233135 3 0.347 0.603861 0.000 0.008 0.832 0.028 0.108 0.024
#> GSM1233136 3 0.187 0.638805 0.016 0.012 0.936 0.004 0.020 0.012
#> GSM1233137 1 0.564 0.496465 0.692 0.056 0.156 0.048 0.004 0.044
#> GSM1233138 3 0.677 0.189028 0.000 0.024 0.460 0.220 0.276 0.020
#> GSM1233140 5 0.600 0.408646 0.000 0.020 0.236 0.152 0.580 0.012
#> GSM1233141 2 0.541 0.504785 0.008 0.624 0.280 0.060 0.024 0.004
#> GSM1233142 2 0.406 0.632515 0.128 0.792 0.004 0.048 0.024 0.004
#> GSM1233144 3 0.681 0.539587 0.140 0.036 0.612 0.064 0.124 0.024
#> GSM1233147 3 0.932 0.202829 0.100 0.140 0.300 0.136 0.256 0.068
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: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
Signature heatmaps where rows are not scaled:
get_signatures(res, k = 2, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 3, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 4, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 5, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
get_signatures(res, k = 6, scale_rows = FALSE)
#> Error: The width or height of the raster image is zero, maybe you forget to turn off the
#> previous graphic device or it was corrupted. Run `dev.off()` to close it.
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 genotype/variation(p) protocol(p) other(p) k
#> ATC:NMF 143 0.5701 0.951 0.368 2
#> ATC:NMF 131 0.2773 0.644 0.449 3
#> ATC:NMF 76 0.0429 0.491 0.670 4
#> ATC:NMF 71 0.0110 0.513 0.742 5
#> ATC:NMF 52 0.2464 0.779 0.896 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