Correlation between copy number variations of arm-level result and molecular subtypes
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and subtypes.

Summary

Testing the association between copy number variation 78 arm-level results and 10 molecular subtypes across 267 patients, 43 significant findings detected with Q value < 0.25.

  • 1q gain cnv correlated to 'CN_CNMF'.

  • 2q gain cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

  • 5p gain cnv correlated to 'CN_CNMF'.

  • 6p gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 7p gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.

  • 7q gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.

  • 8p gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.

  • 8q gain cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.

  • 11p gain cnv correlated to 'CN_CNMF'.

  • 11q gain cnv correlated to 'CN_CNMF'.

  • 12p gain cnv correlated to 'CN_CNMF'.

  • 13q gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 16p gain cnv correlated to 'CN_CNMF'.

  • 20p gain cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.

  • 20q gain cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.

  • 21q gain cnv correlated to 'METHLYATION_CNMF'.

  • 22q gain cnv correlated to 'CN_CNMF'.

  • 6q loss cnv correlated to 'CN_CNMF'.

  • 9p loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.

  • 10p loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.

  • 10q loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.

  • 11p loss cnv correlated to 'CN_CNMF'.

  • 11q loss cnv correlated to 'CN_CNMF'.

  • 12q loss cnv correlated to 'METHLYATION_CNMF'.

  • 14q loss cnv correlated to 'CN_CNMF'.

  • 18p loss cnv correlated to 'MRNASEQ_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 78 arm-level results and 10 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 43 significant findings detected.

Molecular
subtypes
CN
CNMF
METHLYATION
CNMF
RPPA
CNMF
RPPA
CHIERARCHICAL
MRNASEQ
CNMF
MRNASEQ
CHIERARCHICAL
MIRSEQ
CNMF
MIRSEQ
CHIERARCHICAL
MIRSEQ
MATURE
CNMF
MIRSEQ
MATURE
CHIERARCHICAL
nCNV (%) nWild-Type Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
8q gain 0 (0%) 176 1.74e-09
(1.34e-06)
5.27e-06
(0.00399)
0.798
(1.00)
0.0963
(1.00)
3.49e-05
(0.0262)
0.032
(1.00)
0.734
(1.00)
0.858
(1.00)
0.349
(1.00)
0.912
(1.00)
20p gain 0 (0%) 188 3.68e-08
(2.82e-05)
0.000277
(0.204)
0.481
(1.00)
0.767
(1.00)
1.72e-06
(0.00131)
0.00063
(0.462)
0.0795
(1.00)
0.0742
(1.00)
0.043
(1.00)
0.0466
(1.00)
20q gain 0 (0%) 168 4.52e-10
(3.5e-07)
0.000284
(0.209)
0.371
(1.00)
0.566
(1.00)
0.000151
(0.113)
0.0224
(1.00)
0.224
(1.00)
0.211
(1.00)
0.19
(1.00)
0.0354
(1.00)
9p loss 0 (0%) 122 3.43e-07
(0.000261)
5.67e-05
(0.0425)
0.272
(1.00)
0.906
(1.00)
0.000225
(0.167)
0.0025
(1.00)
0.461
(1.00)
0.351
(1.00)
0.417
(1.00)
0.231
(1.00)
10p loss 0 (0%) 157 1.36e-11
(1.05e-08)
3.27e-06
(0.00248)
0.664
(1.00)
0.226
(1.00)
3.21e-06
(0.00243)
0.00368
(1.00)
0.491
(1.00)
0.439
(1.00)
0.152
(1.00)
0.735
(1.00)
10q loss 0 (0%) 142 8.25e-10
(6.38e-07)
1.15e-05
(0.00867)
0.797
(1.00)
0.0893
(1.00)
3.3e-07
(0.000252)
0.00107
(0.777)
0.756
(1.00)
0.604
(1.00)
0.223
(1.00)
0.658
(1.00)
6p gain 0 (0%) 182 0.00019
(0.141)
1.17e-05
(0.00886)
0.738
(1.00)
0.0688
(1.00)
0.0385
(1.00)
0.0863
(1.00)
0.0314
(1.00)
0.00175
(1.00)
0.373
(1.00)
0.00105
(0.76)
7p gain 0 (0%) 156 1.85e-08
(1.43e-05)
0.11
(1.00)
0.894
(1.00)
0.692
(1.00)
8.78e-05
(0.0655)
0.144
(1.00)
0.153
(1.00)
0.363
(1.00)
0.578
(1.00)
0.216
(1.00)
7q gain 0 (0%) 155 2.61e-06
(0.00199)
0.183
(1.00)
0.981
(1.00)
0.503
(1.00)
7.12e-05
(0.0532)
0.0548
(1.00)
0.0876
(1.00)
0.0718
(1.00)
0.398
(1.00)
0.109
(1.00)
8p gain 0 (0%) 209 2.99e-08
(2.3e-05)
0.00288
(1.00)
0.71
(1.00)
0.0468
(1.00)
0.000246
(0.182)
0.0304
(1.00)
0.857
(1.00)
0.591
(1.00)
0.673
(1.00)
0.844
(1.00)
13q gain 0 (0%) 222 2.05e-07
(0.000157)
1.36e-05
(0.0103)
0.0281
(1.00)
0.86
(1.00)
0.0252
(1.00)
0.179
(1.00)
0.402
(1.00)
0.314
(1.00)
0.87
(1.00)
0.392
(1.00)
1q gain 0 (0%) 178 3.71e-12
(2.89e-09)
0.00267
(1.00)
0.154
(1.00)
0.602
(1.00)
0.0452
(1.00)
0.29
(1.00)
0.221
(1.00)
0.00533
(1.00)
0.299
(1.00)
0.0321
(1.00)
2q gain 0 (0%) 238 0.0244
(1.00)
0.188
(1.00)
0.986
(1.00)
0.127
(1.00)
0.000513
(0.377)
6.37e-05
(0.0477)
0.0201
(1.00)
0.00571
(1.00)
0.0322
(1.00)
0.000708
(0.518)
5p gain 0 (0%) 234 2.1e-05
(0.0158)
0.0698
(1.00)
0.879
(1.00)
0.645
(1.00)
0.411
(1.00)
0.385
(1.00)
0.0616
(1.00)
0.466
(1.00)
0.064
(1.00)
0.365
(1.00)
11p gain 0 (0%) 250 3.42e-05
(0.0257)
0.902
(1.00)
0.218
(1.00)
0.106
(1.00)
0.00505
(1.00)
0.76
(1.00)
0.642
(1.00)
0.0959
(1.00)
0.328
(1.00)
0.142
(1.00)
11q gain 0 (0%) 252 6.95e-08
(5.31e-05)
0.415
(1.00)
0.0728
(1.00)
0.153
(1.00)
0.00689
(1.00)
0.447
(1.00)
0.884
(1.00)
0.122
(1.00)
0.54
(1.00)
0.451
(1.00)
12p gain 0 (0%) 240 2.46e-05
(0.0185)
0.071
(1.00)
0.513
(1.00)
0.506
(1.00)
0.0027
(1.00)
0.149
(1.00)
0.155
(1.00)
0.181
(1.00)
0.0556
(1.00)
0.0466
(1.00)
16p gain 0 (0%) 247 0.000123
(0.0917)
0.00261
(1.00)
0.753
(1.00)
0.774
(1.00)
0.00639
(1.00)
0.0622
(1.00)
0.576
(1.00)
0.427
(1.00)
0.334
(1.00)
0.843
(1.00)
21q gain 0 (0%) 237 0.0149
(1.00)
0.000271
(0.2)
0.668
(1.00)
1
(1.00)
0.0918
(1.00)
0.00494
(1.00)
0.695
(1.00)
0.741
(1.00)
0.341
(1.00)
0.846
(1.00)
22q gain 0 (0%) 202 4.57e-08
(3.5e-05)
0.0665
(1.00)
0.635
(1.00)
0.974
(1.00)
0.24
(1.00)
0.342
(1.00)
0.65
(1.00)
0.569
(1.00)
0.52
(1.00)
0.189
(1.00)
6q loss 0 (0%) 174 2.9e-08
(2.23e-05)
0.00328
(1.00)
0.741
(1.00)
0.258
(1.00)
0.00102
(0.744)
0.0155
(1.00)
0.611
(1.00)
0.613
(1.00)
0.775
(1.00)
0.538
(1.00)
11p loss 0 (0%) 204 1.67e-09
(1.29e-06)
0.00109
(0.791)
0.306
(1.00)
0.159
(1.00)
0.00811
(1.00)
0.0529
(1.00)
0.0256
(1.00)
0.318
(1.00)
0.0935
(1.00)
0.172
(1.00)
11q loss 0 (0%) 193 7.43e-11
(5.77e-08)
0.00713
(1.00)
0.818
(1.00)
0.56
(1.00)
0.00405
(1.00)
0.207
(1.00)
0.158
(1.00)
0.287
(1.00)
0.433
(1.00)
0.203
(1.00)
12q loss 0 (0%) 242 0.011
(1.00)
0.000192
(0.143)
0.919
(1.00)
0.756
(1.00)
0.169
(1.00)
0.168
(1.00)
1
(1.00)
0.654
(1.00)
0.889
(1.00)
0.631
(1.00)
14q loss 0 (0%) 207 8.29e-11
(6.43e-08)
0.119
(1.00)
0.473
(1.00)
0.773
(1.00)
0.00268
(1.00)
0.421
(1.00)
0.981
(1.00)
0.682
(1.00)
0.682
(1.00)
0.929
(1.00)
18p loss 0 (0%) 216 0.00274
(1.00)
0.02
(1.00)
0.413
(1.00)
0.968
(1.00)
0.000266
(0.197)
0.0947
(1.00)
0.728
(1.00)
0.737
(1.00)
0.492
(1.00)
0.67
(1.00)
1p gain 0 (0%) 237 0.00995
(1.00)
0.191
(1.00)
0.827
(1.00)
0.918
(1.00)
0.065
(1.00)
0.0796
(1.00)
0.436
(1.00)
0.108
(1.00)
0.194
(1.00)
0.197
(1.00)
2p gain 0 (0%) 236 0.0252
(1.00)
0.138
(1.00)
0.735
(1.00)
0.353
(1.00)
0.00243
(1.00)
0.0007
(0.512)
0.0625
(1.00)
0.0218
(1.00)
0.103
(1.00)
0.0027
(1.00)
3p gain 0 (0%) 244 0.0178
(1.00)
0.0766
(1.00)
0.295
(1.00)
0.044
(1.00)
0.0891
(1.00)
0.267
(1.00)
0.533
(1.00)
0.61
(1.00)
0.664
(1.00)
0.726
(1.00)
3q gain 0 (0%) 237 0.057
(1.00)
0.179
(1.00)
0.321
(1.00)
0.0714
(1.00)
0.0918
(1.00)
0.434
(1.00)
0.672
(1.00)
0.591
(1.00)
0.595
(1.00)
0.411
(1.00)
4p gain 0 (0%) 240 0.0235
(1.00)
0.0662
(1.00)
0.123
(1.00)
1
(1.00)
0.622
(1.00)
0.93
(1.00)
0.333
(1.00)
0.491
(1.00)
0.868
(1.00)
0.501
(1.00)
4q gain 0 (0%) 245 0.000759
(0.554)
0.013
(1.00)
0.583
(1.00)
0.333
(1.00)
0.521
(1.00)
0.474
(1.00)
0.203
(1.00)
0.289
(1.00)
0.749
(1.00)
0.175
(1.00)
5q gain 0 (0%) 248 0.00225
(1.00)
0.0983
(1.00)
0.596
(1.00)
0.228
(1.00)
0.223
(1.00)
0.0533
(1.00)
0.0474
(1.00)
0.0702
(1.00)
0.188
(1.00)
0.171
(1.00)
6q gain 0 (0%) 246 0.919
(1.00)
0.0719
(1.00)
0.723
(1.00)
0.845
(1.00)
0.714
(1.00)
0.419
(1.00)
0.76
(1.00)
0.838
(1.00)
0.489
(1.00)
0.943
(1.00)
9p gain 0 (0%) 257 0.724
(1.00)
0.394
(1.00)
0.172
(1.00)
0.175
(1.00)
0.472
(1.00)
0.7
(1.00)
0.712
(1.00)
0.564
(1.00)
0.714
(1.00)
0.655
(1.00)
9q gain 0 (0%) 255 0.872
(1.00)
0.565
(1.00)
0.0902
(1.00)
0.19
(1.00)
0.707
(1.00)
1
(1.00)
0.925
(1.00)
0.432
(1.00)
0.927
(1.00)
0.556
(1.00)
12q gain 0 (0%) 253 0.0176
(1.00)
0.415
(1.00)
0.921
(1.00)
0.379
(1.00)
0.0315
(1.00)
0.369
(1.00)
0.783
(1.00)
0.472
(1.00)
0.302
(1.00)
0.451
(1.00)
14q gain 0 (0%) 250 0.0478
(1.00)
0.043
(1.00)
0.171
(1.00)
0.138
(1.00)
0.701
(1.00)
0.76
(1.00)
0.45
(1.00)
0.936
(1.00)
0.951
(1.00)
0.767
(1.00)
15q gain 0 (0%) 232 0.0162
(1.00)
0.414
(1.00)
0.669
(1.00)
0.953
(1.00)
0.238
(1.00)
0.381
(1.00)
0.97
(1.00)
0.152
(1.00)
0.862
(1.00)
0.311
(1.00)
16q gain 0 (0%) 250 0.00148
(1.00)
0.0281
(1.00)
0.0997
(1.00)
0.318
(1.00)
0.00505
(1.00)
0.0548
(1.00)
0.81
(1.00)
0.303
(1.00)
0.251
(1.00)
0.473
(1.00)
17p gain 0 (0%) 249 0.019
(1.00)
0.232
(1.00)
0.412
(1.00)
0.122
(1.00)
0.587
(1.00)
0.731
(1.00)
0.247
(1.00)
0.627
(1.00)
0.151
(1.00)
0.38
(1.00)
17q gain 0 (0%) 237 0.0874
(1.00)
0.0767
(1.00)
0.0415
(1.00)
0.032
(1.00)
0.69
(1.00)
0.652
(1.00)
0.0738
(1.00)
0.254
(1.00)
0.0551
(1.00)
0.218
(1.00)
18p gain 0 (0%) 238 0.0753
(1.00)
0.239
(1.00)
0.465
(1.00)
0.282
(1.00)
0.0332
(1.00)
0.257
(1.00)
0.198
(1.00)
0.254
(1.00)
0.317
(1.00)
0.17
(1.00)
18q gain 0 (0%) 248 0.0116
(1.00)
0.0938
(1.00)
0.385
(1.00)
1
(1.00)
0.134
(1.00)
0.45
(1.00)
0.819
(1.00)
0.82
(1.00)
0.611
(1.00)
0.732
(1.00)
19p gain 0 (0%) 250 0.0253
(1.00)
0.0264
(1.00)
0.0549
(1.00)
0.625
(1.00)
0.003
(1.00)
0.00218
(1.00)
0.147
(1.00)
0.655
(1.00)
0.664
(1.00)
0.581
(1.00)
19q gain 0 (0%) 246 0.118
(1.00)
0.0663
(1.00)
0.293
(1.00)
0.946
(1.00)
0.000466
(0.343)
0.0098
(1.00)
0.516
(1.00)
0.633
(1.00)
0.959
(1.00)
0.547
(1.00)
Xq gain 0 (0%) 263 0.191
(1.00)
0.837
(1.00)
0.757
(1.00)
1
(1.00)
0.0398
(1.00)
0.0874
(1.00)
0.552
(1.00)
0.42
(1.00)
0.376
(1.00)
1
(1.00)
1p loss 0 (0%) 251 0.191
(1.00)
0.0116
(1.00)
0.458
(1.00)
0.211
(1.00)
0.0168
(1.00)
0.527
(1.00)
0.424
(1.00)
0.866
(1.00)
0.946
(1.00)
1
(1.00)
1q loss 0 (0%) 261 0.385
(1.00)
0.294
(1.00)
0.341
(1.00)
1
(1.00)
0.336
(1.00)
1
(1.00)
0.765
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
2p loss 0 (0%) 247 0.0967
(1.00)
0.0643
(1.00)
0.233
(1.00)
0.0364
(1.00)
0.512
(1.00)
0.467
(1.00)
0.00145
(1.00)
0.00774
(1.00)
0.00332
(1.00)
0.0108
(1.00)
2q loss 0 (0%) 247 0.298
(1.00)
0.0144
(1.00)
0.138
(1.00)
0.04
(1.00)
0.328
(1.00)
0.487
(1.00)
0.00147
(1.00)
0.0347
(1.00)
0.00663
(1.00)
0.0369
(1.00)
3p loss 0 (0%) 242 0.23
(1.00)
0.0328
(1.00)
0.0302
(1.00)
0.643
(1.00)
0.0162
(1.00)
0.0695
(1.00)
0.893
(1.00)
0.453
(1.00)
0.495
(1.00)
0.719
(1.00)
3q loss 0 (0%) 245 0.425
(1.00)
0.0208
(1.00)
0.0374
(1.00)
0.643
(1.00)
0.198
(1.00)
0.279
(1.00)
0.604
(1.00)
0.271
(1.00)
0.415
(1.00)
0.147
(1.00)
4p loss 0 (0%) 236 0.836
(1.00)
0.138
(1.00)
0.298
(1.00)
0.183
(1.00)
0.00993
(1.00)
0.0334
(1.00)
0.647
(1.00)
0.541
(1.00)
0.0477
(1.00)
0.452
(1.00)
4q loss 0 (0%) 234 0.236
(1.00)
0.023
(1.00)
0.338
(1.00)
0.157
(1.00)
0.0149
(1.00)
0.0106
(1.00)
0.178
(1.00)
0.114
(1.00)
0.00215
(1.00)
0.0259
(1.00)
5p loss 0 (0%) 233 0.233
(1.00)
0.427
(1.00)
0.938
(1.00)
0.561
(1.00)
0.365
(1.00)
0.242
(1.00)
0.0353
(1.00)
0.131
(1.00)
0.0677
(1.00)
0.113
(1.00)
5q loss 0 (0%) 217 0.209
(1.00)
0.13
(1.00)
0.506
(1.00)
0.826
(1.00)
0.263
(1.00)
0.318
(1.00)
0.184
(1.00)
0.737
(1.00)
0.298
(1.00)
0.83
(1.00)
6p loss 0 (0%) 241 0.00626
(1.00)
0.341
(1.00)
0.733
(1.00)
0.798
(1.00)
0.267
(1.00)
0.361
(1.00)
0.481
(1.00)
0.515
(1.00)
0.544
(1.00)
0.601
(1.00)
7p loss 0 (0%) 260 0.498
(1.00)
0.0355
(1.00)
0.0769
(1.00)
0.387
(1.00)
0.798
(1.00)
1
(1.00)
0.548
(1.00)
0.74
(1.00)
0.801
(1.00)
0.642
(1.00)
7q loss 0 (0%) 261 0.586
(1.00)
0.0926
(1.00)
0.228
(1.00)
1
(1.00)
1
(1.00)
0.872
(1.00)
1
(1.00)
0.707
(1.00)
0.768
(1.00)
0.719
(1.00)
8p loss 0 (0%) 237 0.432
(1.00)
0.191
(1.00)
0.0948
(1.00)
0.0618
(1.00)
0.065
(1.00)
0.479
(1.00)
0.321
(1.00)
0.5
(1.00)
0.506
(1.00)
0.31
(1.00)
8q loss 0 (0%) 262 1
(1.00)
0.072
(1.00)
0.761
(1.00)
0.121
(1.00)
0.379
(1.00)
0.0381
(1.00)
0.848
(1.00)
1
(1.00)
0.383
(1.00)
1
(1.00)
9q loss 0 (0%) 157 0.0118
(1.00)
0.00484
(1.00)
0.326
(1.00)
0.04
(1.00)
0.379
(1.00)
0.507
(1.00)
0.147
(1.00)
0.285
(1.00)
0.315
(1.00)
0.199
(1.00)
12p loss 0 (0%) 249 0.0601
(1.00)
0.00401
(1.00)
0.952
(1.00)
0.24
(1.00)
0.0877
(1.00)
0.482
(1.00)
1
(1.00)
0.866
(1.00)
0.898
(1.00)
1
(1.00)
13q loss 0 (0%) 231 0.0342
(1.00)
0.252
(1.00)
0.405
(1.00)
0.923
(1.00)
0.473
(1.00)
0.275
(1.00)
0.277
(1.00)
0.252
(1.00)
0.303
(1.00)
0.44
(1.00)
15q loss 0 (0%) 249 0.093
(1.00)
0.132
(1.00)
0.456
(1.00)
0.0842
(1.00)
0.587
(1.00)
0.772
(1.00)
0.53
(1.00)
0.655
(1.00)
0.456
(1.00)
0.581
(1.00)
16p loss 0 (0%) 244 0.00811
(1.00)
0.0191
(1.00)
0.00129
(0.937)
0.0134
(1.00)
0.134
(1.00)
0.19
(1.00)
0.0694
(1.00)
0.176
(1.00)
0.0842
(1.00)
0.207
(1.00)
16q loss 0 (0%) 219 0.00186
(1.00)
0.0413
(1.00)
0.0583
(1.00)
0.878
(1.00)
0.00103
(0.751)
0.0751
(1.00)
0.0585
(1.00)
0.115
(1.00)
0.0969
(1.00)
0.02
(1.00)
17p loss 0 (0%) 214 0.602
(1.00)
0.124
(1.00)
0.369
(1.00)
0.451
(1.00)
0.0648
(1.00)
0.731
(1.00)
0.728
(1.00)
0.624
(1.00)
0.0216
(1.00)
0.484
(1.00)
17q loss 0 (0%) 245 0.408
(1.00)
0.539
(1.00)
0.0237
(1.00)
0.333
(1.00)
0.0919
(1.00)
0.704
(1.00)
0.663
(1.00)
0.701
(1.00)
0.609
(1.00)
0.843
(1.00)
18q loss 0 (0%) 220 0.0118
(1.00)
0.0599
(1.00)
0.267
(1.00)
0.201
(1.00)
0.0921
(1.00)
0.852
(1.00)
0.934
(1.00)
0.587
(1.00)
0.819
(1.00)
0.918
(1.00)
19p loss 0 (0%) 248 0.173
(1.00)
0.687
(1.00)
0.702
(1.00)
0.405
(1.00)
0.128
(1.00)
0.11
(1.00)
0.38
(1.00)
0.939
(1.00)
0.424
(1.00)
0.617
(1.00)
19q loss 0 (0%) 248 0.0259
(1.00)
0.544
(1.00)
0.982
(1.00)
0.18
(1.00)
0.338
(1.00)
0.254
(1.00)
0.56
(1.00)
0.939
(1.00)
0.873
(1.00)
0.617
(1.00)
20p loss 0 (0%) 253 0.0176
(1.00)
0.577
(1.00)
0.549
(1.00)
0.6
(1.00)
0.652
(1.00)
0.591
(1.00)
0.0882
(1.00)
0.541
(1.00)
0.364
(1.00)
0.392
(1.00)
20q loss 0 (0%) 264 0.0537
(1.00)
0.188
(1.00)
0.492
(1.00)
0.207
(1.00)
0.796
(1.00)
1
(1.00)
0.62
(1.00)
1
(1.00)
21q loss 0 (0%) 235 0.0291
(1.00)
0.245
(1.00)
0.582
(1.00)
0.0473
(1.00)
0.315
(1.00)
0.623
(1.00)
0.913
(1.00)
0.505
(1.00)
0.1
(1.00)
0.543
(1.00)
22q loss 0 (0%) 246 0.161
(1.00)
0.109
(1.00)
0.925
(1.00)
1
(1.00)
0.684
(1.00)
0.606
(1.00)
0.0767
(1.00)
0.431
(1.00)
0.953
(1.00)
0.45
(1.00)
Xq loss 0 (0%) 257 0.434
(1.00)
0.00338
(1.00)
0.625
(1.00)
0.115
(1.00)
0.435
(1.00)
0.115
(1.00)
0.166
(1.00)
0.503
(1.00)
0.112
(1.00)
0.587
(1.00)
'1q gain' versus 'CN_CNMF'

P value = 3.71e-12 (Fisher's exact test), Q value = 2.9e-09

Table S1.  Gene #2: '1q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
1Q GAIN CNV 54 23 12
1Q GAIN WILD-TYPE 30 83 65

Figure S1.  Get High-res Image Gene #2: '1q gain' versus Molecular Subtype #1: 'CN_CNMF'

'2q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 6.37e-05 (Fisher's exact test), Q value = 0.048

Table S2.  Gene #4: '2q gain' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 62 132 72
2Q GAIN CNV 5 6 18
2Q GAIN WILD-TYPE 57 126 54

Figure S2.  Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'5p gain' versus 'CN_CNMF'

P value = 2.1e-05 (Fisher's exact test), Q value = 0.016

Table S3.  Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
5P GAIN CNV 16 2 15
5P GAIN WILD-TYPE 68 104 62

Figure S3.  Get High-res Image Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

'6p gain' versus 'CN_CNMF'

P value = 0.00019 (Fisher's exact test), Q value = 0.14

Table S4.  Gene #11: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
6P GAIN CNV 37 19 29
6P GAIN WILD-TYPE 47 87 48

Figure S4.  Get High-res Image Gene #11: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

'6p gain' versus 'METHLYATION_CNMF'

P value = 1.17e-05 (Fisher's exact test), Q value = 0.0089

Table S5.  Gene #11: '6p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 98 102
6P GAIN CNV 34 34 17
6P GAIN WILD-TYPE 33 64 85

Figure S5.  Get High-res Image Gene #11: '6p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'7p gain' versus 'CN_CNMF'

P value = 1.85e-08 (Fisher's exact test), Q value = 1.4e-05

Table S6.  Gene #13: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
7P GAIN CNV 47 21 43
7P GAIN WILD-TYPE 37 85 34

Figure S6.  Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

'7p gain' versus 'MRNASEQ_CNMF'

P value = 8.78e-05 (Fisher's exact test), Q value = 0.065

Table S7.  Gene #13: '7p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 91 72 103
7P GAIN CNV 54 20 37
7P GAIN WILD-TYPE 37 52 66

Figure S7.  Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'7q gain' versus 'CN_CNMF'

P value = 2.61e-06 (Fisher's exact test), Q value = 0.002

Table S8.  Gene #14: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
7Q GAIN CNV 43 25 44
7Q GAIN WILD-TYPE 41 81 33

Figure S8.  Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

'7q gain' versus 'MRNASEQ_CNMF'

P value = 7.12e-05 (Fisher's exact test), Q value = 0.053

Table S9.  Gene #14: '7q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 91 72 103
7Q GAIN CNV 55 22 35
7Q GAIN WILD-TYPE 36 50 68

Figure S9.  Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'8p gain' versus 'CN_CNMF'

P value = 2.99e-08 (Fisher's exact test), Q value = 2.3e-05

Table S10.  Gene #15: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
8P GAIN CNV 28 5 25
8P GAIN WILD-TYPE 56 101 52

Figure S10.  Get High-res Image Gene #15: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

'8p gain' versus 'MRNASEQ_CNMF'

P value = 0.000246 (Fisher's exact test), Q value = 0.18

Table S11.  Gene #15: '8p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 91 72 103
8P GAIN CNV 29 5 24
8P GAIN WILD-TYPE 62 67 79

Figure S11.  Get High-res Image Gene #15: '8p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'8q gain' versus 'CN_CNMF'

P value = 1.74e-09 (Fisher's exact test), Q value = 1.3e-06

Table S12.  Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
8Q GAIN CNV 40 13 38
8Q GAIN WILD-TYPE 44 93 39

Figure S12.  Get High-res Image Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

'8q gain' versus 'METHLYATION_CNMF'

P value = 5.27e-06 (Fisher's exact test), Q value = 0.004

Table S13.  Gene #16: '8q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 98 102
8Q GAIN CNV 39 30 22
8Q GAIN WILD-TYPE 28 68 80

Figure S13.  Get High-res Image Gene #16: '8q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'8q gain' versus 'MRNASEQ_CNMF'

P value = 3.49e-05 (Fisher's exact test), Q value = 0.026

Table S14.  Gene #16: '8q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 91 72 103
8Q GAIN CNV 41 10 40
8Q GAIN WILD-TYPE 50 62 63

Figure S14.  Get High-res Image Gene #16: '8q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'11p gain' versus 'CN_CNMF'

P value = 3.42e-05 (Fisher's exact test), Q value = 0.026

Table S15.  Gene #19: '11p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
11P GAIN CNV 3 1 13
11P GAIN WILD-TYPE 81 105 64

Figure S15.  Get High-res Image Gene #19: '11p gain' versus Molecular Subtype #1: 'CN_CNMF'

'11q gain' versus 'CN_CNMF'

P value = 6.95e-08 (Fisher's exact test), Q value = 5.3e-05

Table S16.  Gene #20: '11q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
11Q GAIN CNV 1 0 14
11Q GAIN WILD-TYPE 83 106 63

Figure S16.  Get High-res Image Gene #20: '11q gain' versus Molecular Subtype #1: 'CN_CNMF'

'12p gain' versus 'CN_CNMF'

P value = 2.46e-05 (Fisher's exact test), Q value = 0.019

Table S17.  Gene #21: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
12P GAIN CNV 15 1 11
12P GAIN WILD-TYPE 69 105 66

Figure S17.  Get High-res Image Gene #21: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

'13q gain' versus 'CN_CNMF'

P value = 2.05e-07 (Fisher's exact test), Q value = 0.00016

Table S18.  Gene #23: '13q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
13Q GAIN CNV 19 3 23
13Q GAIN WILD-TYPE 65 103 54

Figure S18.  Get High-res Image Gene #23: '13q gain' versus Molecular Subtype #1: 'CN_CNMF'

'13q gain' versus 'METHLYATION_CNMF'

P value = 1.36e-05 (Fisher's exact test), Q value = 0.01

Table S19.  Gene #23: '13q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 98 102
13Q GAIN CNV 21 19 5
13Q GAIN WILD-TYPE 46 79 97

Figure S19.  Get High-res Image Gene #23: '13q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'16p gain' versus 'CN_CNMF'

P value = 0.000123 (Fisher's exact test), Q value = 0.092

Table S20.  Gene #26: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
16P GAIN CNV 14 1 5
16P GAIN WILD-TYPE 70 105 72

Figure S20.  Get High-res Image Gene #26: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

'20p gain' versus 'CN_CNMF'

P value = 3.68e-08 (Fisher's exact test), Q value = 2.8e-05

Table S21.  Gene #34: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
20P GAIN CNV 34 11 34
20P GAIN WILD-TYPE 50 95 43

Figure S21.  Get High-res Image Gene #34: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

'20p gain' versus 'METHLYATION_CNMF'

P value = 0.000277 (Fisher's exact test), Q value = 0.2

Table S22.  Gene #34: '20p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 98 102
20P GAIN CNV 30 32 17
20P GAIN WILD-TYPE 37 66 85

Figure S22.  Get High-res Image Gene #34: '20p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'20p gain' versus 'MRNASEQ_CNMF'

P value = 1.72e-06 (Fisher's exact test), Q value = 0.0013

Table S23.  Gene #34: '20p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 91 72 103
20P GAIN CNV 44 9 26
20P GAIN WILD-TYPE 47 63 77

Figure S23.  Get High-res Image Gene #34: '20p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'20q gain' versus 'CN_CNMF'

P value = 4.52e-10 (Fisher's exact test), Q value = 3.5e-07

Table S24.  Gene #35: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
20Q GAIN CNV 46 15 38
20Q GAIN WILD-TYPE 38 91 39

Figure S24.  Get High-res Image Gene #35: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

'20q gain' versus 'METHLYATION_CNMF'

P value = 0.000284 (Fisher's exact test), Q value = 0.21

Table S25.  Gene #35: '20q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 98 102
20Q GAIN CNV 34 42 23
20Q GAIN WILD-TYPE 33 56 79

Figure S25.  Get High-res Image Gene #35: '20q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'20q gain' versus 'MRNASEQ_CNMF'

P value = 0.000151 (Fisher's exact test), Q value = 0.11

Table S26.  Gene #35: '20q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 91 72 103
20Q GAIN CNV 49 17 33
20Q GAIN WILD-TYPE 42 55 70

Figure S26.  Get High-res Image Gene #35: '20q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'21q gain' versus 'METHLYATION_CNMF'

P value = 0.000271 (Fisher's exact test), Q value = 0.2

Table S27.  Gene #36: '21q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 98 102
21Q GAIN CNV 15 12 3
21Q GAIN WILD-TYPE 52 86 99

Figure S27.  Get High-res Image Gene #36: '21q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'22q gain' versus 'CN_CNMF'

P value = 4.57e-08 (Fisher's exact test), Q value = 3.5e-05

Table S28.  Gene #37: '22q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
22Q GAIN CNV 40 14 11
22Q GAIN WILD-TYPE 44 92 66

Figure S28.  Get High-res Image Gene #37: '22q gain' versus Molecular Subtype #1: 'CN_CNMF'

'6q loss' versus 'CN_CNMF'

P value = 2.9e-08 (Fisher's exact test), Q value = 2.2e-05

Table S29.  Gene #50: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
6Q LOSS CNV 32 17 44
6Q LOSS WILD-TYPE 52 89 33

Figure S29.  Get High-res Image Gene #50: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'CN_CNMF'

P value = 3.43e-07 (Fisher's exact test), Q value = 0.00026

Table S30.  Gene #55: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
9P LOSS CNV 55 36 54
9P LOSS WILD-TYPE 29 70 23

Figure S30.  Get High-res Image Gene #55: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'METHLYATION_CNMF'

P value = 5.67e-05 (Fisher's exact test), Q value = 0.042

Table S31.  Gene #55: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 98 102
9P LOSS CNV 42 65 38
9P LOSS WILD-TYPE 25 33 64

Figure S31.  Get High-res Image Gene #55: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'9p loss' versus 'MRNASEQ_CNMF'

P value = 0.000225 (Fisher's exact test), Q value = 0.17

Table S32.  Gene #55: '9p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 91 72 103
9P LOSS CNV 60 25 60
9P LOSS WILD-TYPE 31 47 43

Figure S32.  Get High-res Image Gene #55: '9p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'10p loss' versus 'CN_CNMF'

P value = 1.36e-11 (Fisher's exact test), Q value = 1.1e-08

Table S33.  Gene #57: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
10P LOSS CNV 52 17 41
10P LOSS WILD-TYPE 32 89 36

Figure S33.  Get High-res Image Gene #57: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'METHLYATION_CNMF'

P value = 3.27e-06 (Fisher's exact test), Q value = 0.0025

Table S34.  Gene #57: '10p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 98 102
10P LOSS CNV 38 49 23
10P LOSS WILD-TYPE 29 49 79

Figure S34.  Get High-res Image Gene #57: '10p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'10p loss' versus 'MRNASEQ_CNMF'

P value = 3.21e-06 (Fisher's exact test), Q value = 0.0024

Table S35.  Gene #57: '10p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 91 72 103
10P LOSS CNV 54 15 41
10P LOSS WILD-TYPE 37 57 62

Figure S35.  Get High-res Image Gene #57: '10p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'10q loss' versus 'CN_CNMF'

P value = 8.25e-10 (Fisher's exact test), Q value = 6.4e-07

Table S36.  Gene #58: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
10Q LOSS CNV 57 25 43
10Q LOSS WILD-TYPE 27 81 34

Figure S36.  Get High-res Image Gene #58: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

'10q loss' versus 'METHLYATION_CNMF'

P value = 1.15e-05 (Fisher's exact test), Q value = 0.0087

Table S37.  Gene #58: '10q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 98 102
10Q LOSS CNV 39 57 29
10Q LOSS WILD-TYPE 28 41 73

Figure S37.  Get High-res Image Gene #58: '10q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'10q loss' versus 'MRNASEQ_CNMF'

P value = 3.3e-07 (Fisher's exact test), Q value = 0.00025

Table S38.  Gene #58: '10q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 91 72 103
10Q LOSS CNV 62 19 44
10Q LOSS WILD-TYPE 29 53 59

Figure S38.  Get High-res Image Gene #58: '10q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'11p loss' versus 'CN_CNMF'

P value = 1.67e-09 (Fisher's exact test), Q value = 1.3e-06

Table S39.  Gene #59: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
11P LOSS CNV 41 13 9
11P LOSS WILD-TYPE 43 93 68

Figure S39.  Get High-res Image Gene #59: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

'11q loss' versus 'CN_CNMF'

P value = 7.43e-11 (Fisher's exact test), Q value = 5.8e-08

Table S40.  Gene #60: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
11Q LOSS CNV 47 16 11
11Q LOSS WILD-TYPE 37 90 66

Figure S40.  Get High-res Image Gene #60: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

'12q loss' versus 'METHLYATION_CNMF'

P value = 0.000192 (Fisher's exact test), Q value = 0.14

Table S41.  Gene #62: '12q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 98 102
12Q LOSS CNV 10 14 1
12Q LOSS WILD-TYPE 57 84 101

Figure S41.  Get High-res Image Gene #62: '12q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'14q loss' versus 'CN_CNMF'

P value = 8.29e-11 (Fisher's exact test), Q value = 6.4e-08

Table S42.  Gene #64: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 84 106 77
14Q LOSS CNV 23 4 33
14Q LOSS WILD-TYPE 61 102 44

Figure S42.  Get High-res Image Gene #64: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

'18p loss' versus 'MRNASEQ_CNMF'

P value = 0.000266 (Fisher's exact test), Q value = 0.2

Table S43.  Gene #70: '18p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 91 72 103
18P LOSS CNV 30 7 14
18P LOSS WILD-TYPE 61 65 89

Figure S43.  Get High-res Image Gene #70: '18p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

Methods & Data
Input
  • Mutation data file = broad_values_by_arm.mutsig.cluster.txt

  • Molecular subtypes file = SKCM-TM.transferedmergedcluster.txt

  • Number of patients = 267

  • Number of significantly arm-level cnvs = 78

  • Number of molecular subtypes = 10

  • Exclude genes that fewer than K tumors have mutations, K = 3

Fisher's exact test

For binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R

Q value calculation

For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.

References
[1] Fisher, R.A., On the interpretation of chi-square from contingency tables, and the calculation of P, Journal of the Royal Statistical Society 85(1):87-94 (1922)
[2] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)