Head and Neck Squamous Cell Carcinoma: Correlation between copy number variations of arm-level result and molecular subtypes
(primary solid tumor cohort)
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
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 79 arm-level results and 8 molecular subtypes across 352 patients, 64 significant findings detected with Q value < 0.25.

  • 1q gain cnv correlated to 'CN_CNMF'.

  • 2p gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 3p gain cnv correlated to 'METHLYATION_CNMF' and 'MIRSEQ_CNMF'.

  • 3q gain cnv correlated to 'METHLYATION_CNMF' and 'MIRSEQ_CNMF'.

  • 5p gain cnv correlated to 'CN_CNMF'.

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

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

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

  • 9p gain cnv correlated to 'CN_CNMF'.

  • 11p gain cnv correlated to 'CN_CNMF'.

  • 12p gain cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MIRSEQ_CNMF'.

  • 14q gain cnv correlated to 'CN_CNMF'.

  • 16p gain cnv correlated to 'METHLYATION_CNMF'.

  • 17p gain cnv correlated to 'CN_CNMF'.

  • 18p gain cnv correlated to 'CN_CNMF'.

  • 18q gain cnv correlated to 'METHLYATION_CNMF'.

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

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

  • 22q gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 1p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 3p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 4p loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CNMF'.

  • 4q loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 5q loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 8p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

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

  • 10p loss cnv correlated to 'CN_CNMF'.

  • 10q loss cnv correlated to 'CN_CNMF' and 'MIRSEQ_CNMF'.

  • 11p loss cnv correlated to 'CN_CNMF'.

  • 11q loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 13q loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 16q loss cnv correlated to 'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CNMF'.

  • 17p loss cnv correlated to 'METHLYATION_CNMF'.

  • 18q loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 21q loss cnv correlated to 'CN_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 79 arm-level results and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 64 significant findings detected.

Molecular
subtypes 		CN
CNMF 		METHLYATION
CNMF 		RPPA
CNMF 		RPPA
CHIERARCHICAL 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL
nCNV (%) nWild-Type Chi-square test Chi-square 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
4p loss 82 (23%) 270 5.83e-12
(3.66e-09) 		2.98e-08
(1.83e-05) 		0.135
(1.00) 		0.0374
(1.00) 		0.00227
(1.00) 		0.000123
(0.0712) 		0.000172
(0.0995) 		0.0511
(1.00)
16q loss 29 (8%) 323 0.00704
(1.00) 		4.19e-05
(0.025) 		0.0347
(1.00) 		0.00546
(1.00) 		4.72e-07
(0.000287) 		1.34e-08
(8.24e-06) 		0.000419
(0.238) 		0.00955
(1.00)
12p gain 65 (18%) 287 1.64e-07
(1e-04) 		1.89e-05
(0.0113) 		0.663
(1.00) 		0.725
(1.00) 		0.00399
(1.00) 		0.000612
(0.346) 		7.64e-05
(0.0452) 		0.0106
(1.00)
5q loss 63 (18%) 289 2.15e-14
(1.36e-11) 		7.27e-10
(4.54e-07) 		0.434
(1.00) 		0.528
(1.00) 		0.00575
(1.00) 		4.53e-05
(0.0269) 		0.0594
(1.00) 		1
(1.00)
13q loss 72 (20%) 280 2.38e-07
(0.000145) 		9.48e-10
(5.9e-07) 		0.315
(1.00) 		0.439
(1.00) 		0.0286
(1.00) 		2.38e-05
(0.0142) 		0.00616
(1.00) 		0.339
(1.00)
2p gain 31 (9%) 321 9.19e-05
(0.0538) 		0.000103
(0.06) 		0.368
(1.00) 		0.802
(1.00) 		0.0146
(1.00) 		0.0236
(1.00) 		0.697
(1.00) 		0.204
(1.00)
3p gain 29 (8%) 323 0.489
(1.00) 		8.26e-05
(0.0486) 		0.0468
(1.00) 		0.583
(1.00) 		0.00323
(1.00) 		0.00326
(1.00) 		0.000433
(0.245) 		0.111
(1.00)
3q gain 112 (32%) 240 0.000825
(0.464) 		4.27e-05
(0.0254) 		0.228
(1.00) 		0.52
(1.00) 		0.0178
(1.00) 		0.00384
(1.00) 		0.000215
(0.123) 		0.27
(1.00)
7p gain 78 (22%) 274 2.95e-05
(0.0176) 		0.000406
(0.232) 		0.623
(1.00) 		0.64
(1.00) 		0.817
(1.00) 		0.939
(1.00) 		0.738
(1.00) 		0.465
(1.00)
7q gain 48 (14%) 304 7.08e-10
(4.43e-07) 		1.01e-06
(0.000612) 		0.488
(1.00) 		0.92
(1.00) 		0.275
(1.00) 		0.112
(1.00) 		0.141
(1.00) 		0.904
(1.00)
8q gain 145 (41%) 207 4.97e-09
(3.08e-06) 		0.000341
(0.195) 		0.52
(1.00) 		0.219
(1.00) 		0.52
(1.00) 		0.519
(1.00) 		0.484
(1.00) 		0.0494
(1.00)
20p gain 68 (19%) 284 7.5e-06
(0.00451) 		7.9e-05
(0.0467) 		0.062
(1.00) 		0.175
(1.00) 		0.617
(1.00) 		0.365
(1.00) 		0.216
(1.00) 		0.351
(1.00)
20q gain 72 (20%) 280 8.46e-07
(0.000515) 		0.000112
(0.0655) 		0.924
(1.00) 		0.884
(1.00) 		0.495
(1.00) 		0.726
(1.00) 		0.549
(1.00) 		0.228
(1.00)
22q gain 42 (12%) 310 0.00016
(0.0924) 		8.21e-05
(0.0485) 		0.641
(1.00) 		0.405
(1.00) 		0.0775
(1.00) 		0.019
(1.00) 		0.436
(1.00) 		0.947
(1.00)
1p loss 16 (5%) 336 4.35e-10
(2.72e-07) 		9.7e-07
(0.000589) 		0.114
(1.00) 		0.123
(1.00) 		0.0129
(1.00) 		0.0156
(1.00) 		0.0163
(1.00) 		0.543
(1.00)
3p loss 133 (38%) 219 8.24e-13
(5.18e-10) 		3.16e-07
(0.000193) 		0.304
(1.00) 		0.766
(1.00) 		0.365
(1.00) 		0.176
(1.00) 		0.126
(1.00) 		0.821
(1.00)
4q loss 55 (16%) 297 5.73e-09
(3.54e-06) 		3.38e-06
(0.00204) 		0.293
(1.00) 		0.147
(1.00) 		0.0148
(1.00) 		0.00277
(1.00) 		0.00107
(0.604) 		0.0913
(1.00)
8p loss 78 (22%) 274 1.8e-06
(0.00109) 		6.66e-06
(0.00401) 		0.891
(1.00) 		1
(1.00) 		0.619
(1.00) 		0.485
(1.00) 		0.106
(1.00) 		0.47
(1.00)
9p loss 93 (26%) 259 1.66e-09
(1.03e-06) 		2.25e-08
(1.38e-05) 		0.484
(1.00) 		0.847
(1.00) 		0.311
(1.00) 		0.0696
(1.00) 		0.0139
(1.00) 		0.267
(1.00)
10q loss 29 (8%) 323 8.12e-08
(4.98e-05) 		0.00667
(1.00) 		0.48
(1.00) 		0.742
(1.00) 		0.0334
(1.00) 		0.00123
(0.69) 		0.000419
(0.238) 		0.568
(1.00)
11q loss 69 (20%) 283 2.19e-13
(1.38e-10) 		7.28e-05
(0.0432) 		0.864
(1.00) 		0.594
(1.00) 		0.0115
(1.00) 		0.051
(1.00) 		0.0581
(1.00) 		0.834
(1.00)
18q loss 93 (26%) 259 1.92e-09
(1.19e-06) 		6.73e-08
(4.13e-05) 		0.386
(1.00) 		0.197
(1.00) 		0.0192
(1.00) 		0.512
(1.00) 		0.00726
(1.00) 		0.321
(1.00)
1q gain 42 (12%) 310 0.000122
(0.0711) 		0.00187
(1.00) 		0.49
(1.00) 		0.504
(1.00) 		0.0129
(1.00) 		0.00499
(1.00) 		0.0329
(1.00) 		0.248
(1.00)
5p gain 88 (25%) 264 5.64e-09
(3.49e-06) 		0.0326
(1.00) 		0.666
(1.00) 		0.43
(1.00) 		0.579
(1.00) 		0.409
(1.00) 		1
(1.00) 		0.67
(1.00)
9p gain 43 (12%) 309 0.00011
(0.0642) 		0.0595
(1.00) 		0.421
(1.00) 		0.303
(1.00) 		0.288
(1.00) 		0.643
(1.00) 		0.398
(1.00) 		0.491
(1.00)
11p gain 17 (5%) 335 0.000202
(0.116) 		0.67
(1.00) 		0.833
(1.00) 		0.399
(1.00) 		0.754
(1.00) 		0.845
(1.00) 		0.86
(1.00) 		0.273
(1.00)
14q gain 58 (16%) 294 0.000131
(0.076) 		0.0159
(1.00) 		0.445
(1.00) 		0.0667
(1.00) 		0.0271
(1.00) 		0.027
(1.00) 		0.0309
(1.00) 		0.0566
(1.00)
16p gain 22 (6%) 330 0.00785
(1.00) 		8.45e-05
(0.0497) 		0.0259
(1.00) 		0.362
(1.00) 		0.241
(1.00) 		0.958
(1.00) 		0.781
(1.00) 		0.45
(1.00)
17p gain 20 (6%) 332 0.000367
(0.21) 		0.0824
(1.00) 		0.544
(1.00) 		0.468
(1.00) 		0.18
(1.00) 		0.561
(1.00) 		0.18
(1.00) 		0.418
(1.00)
18p gain 55 (16%) 297 0.000122
(0.0711) 		0.0581
(1.00) 		0.318
(1.00) 		0.385
(1.00) 		0.114
(1.00) 		0.0049
(1.00) 		0.402
(1.00) 		0.766
(1.00)
18q gain 20 (6%) 332 0.0059
(1.00) 		0.000177
(0.102) 		0.531
(1.00) 		0.399
(1.00) 		0.0192
(1.00) 		0.0171
(1.00) 		0.00164
(0.915) 		1
(1.00)
10p loss 52 (15%) 300 8.93e-05
(0.0524) 		0.0656
(1.00) 		0.27
(1.00) 		0.594
(1.00) 		0.937
(1.00) 		0.805
(1.00) 		0.539
(1.00) 		0.43
(1.00)
11p loss 48 (14%) 304 0.000257
(0.147) 		0.0444
(1.00) 		0.11
(1.00) 		0.699
(1.00) 		0.00173
(0.967) 		0.00598
(1.00) 		0.0631
(1.00) 		0.817
(1.00)
17p loss 49 (14%) 303 0.0211
(1.00) 		1.27e-05
(0.00765) 		0.748
(1.00) 		0.567
(1.00) 		0.637
(1.00) 		0.0218
(1.00) 		0.178
(1.00) 		0.782
(1.00)
21q loss 63 (18%) 289 2.16e-06
(0.0013) 		0.0109
(1.00) 		0.942
(1.00) 		0.204
(1.00) 		0.892
(1.00) 		0.512
(1.00) 		0.649
(1.00) 		0.473
(1.00)
1p gain 11 (3%) 341 0.379
(1.00) 		0.694
(1.00) 		0.955
(1.00) 		0.64
(1.00) 		0.179
(1.00) 		0.34
(1.00) 		0.861
(1.00) 		1
(1.00)
2q gain 21 (6%) 331 0.00527
(1.00) 		0.00187
(1.00) 		0.509
(1.00) 		0.928
(1.00) 		0.0781
(1.00) 		0.127
(1.00) 		0.878
(1.00) 		0.136
(1.00)
4p gain 13 (4%) 339 0.0153
(1.00) 		0.064
(1.00) 		0.231
(1.00) 		1
(1.00) 		0.166
(1.00) 		0.228
(1.00) 		0.0417
(1.00) 		0.237
(1.00)
4q gain 9 (3%) 343 0.0661
(1.00) 		0.103
(1.00) 		0.679
(1.00) 		1
(1.00) 		0.576
(1.00) 		0.63
(1.00) 		0.917
(1.00) 		0.795
(1.00)
5q gain 28 (8%) 324 0.0432
(1.00) 		0.693
(1.00) 		1
(1.00) 		1
(1.00) 		0.819
(1.00) 		0.461
(1.00) 		1
(1.00) 		0.457
(1.00)
6p gain 26 (7%) 326 0.0172
(1.00) 		0.0466
(1.00) 		0.215
(1.00) 		0.547
(1.00) 		0.902
(1.00) 		0.871
(1.00) 		0.901
(1.00) 		0.221
(1.00)
6q gain 19 (5%) 333 0.412
(1.00) 		0.0821
(1.00) 		0.677
(1.00) 		0.764
(1.00) 		0.727
(1.00) 		0.378
(1.00) 		1
(1.00) 		0.453
(1.00)
8p gain 53 (15%) 299 0.00796
(1.00) 		0.002
(1.00) 		0.728
(1.00) 		0.114
(1.00) 		0.381
(1.00) 		0.313
(1.00) 		0.123
(1.00) 		0.349
(1.00)
9q gain 58 (16%) 294 0.000686
(0.387) 		0.0312
(1.00) 		0.239
(1.00) 		0.109
(1.00) 		0.215
(1.00) 		0.131
(1.00) 		0.345
(1.00) 		0.426
(1.00)
10p gain 12 (3%) 340 0.539
(1.00) 		0.00278
(1.00) 		0.798
(1.00) 		0.752
(1.00) 		0.055
(1.00) 		0.0689
(1.00) 		0.12
(1.00) 		0.262
(1.00)
10q gain 6 (2%) 346 0.194
(1.00) 		0.338
(1.00) 		0.57
(1.00) 		0.256
(1.00) 		1
(1.00) 		1
(1.00) 		0.677
(1.00) 		1
(1.00)
11q gain 17 (5%) 335 0.0297
(1.00) 		0.494
(1.00) 		0.362
(1.00) 		1
(1.00) 		0.195
(1.00) 		0.284
(1.00) 		0.952
(1.00) 		0.381
(1.00)
12q gain 26 (7%) 326 0.194
(1.00) 		0.0042
(1.00) 		0.173
(1.00) 		0.695
(1.00) 		0.0645
(1.00) 		0.00174
(0.971) 		0.016
(1.00) 		0.0828
(1.00)
13q gain 18 (5%) 334 0.101
(1.00) 		0.0352
(1.00) 		0.35
(1.00) 		0.645
(1.00) 		0.603
(1.00) 		0.904
(1.00) 		0.705
(1.00) 		0.752
(1.00)
15q gain 12 (3%) 340 0.489
(1.00) 		0.272
(1.00) 		0.542
(1.00) 		0.444
(1.00) 		0.872
(1.00) 		0.255
(1.00) 		0.813
(1.00) 		0.211
(1.00)
16q gain 30 (9%) 322 0.0018
(1.00) 		0.00423
(1.00) 		0.783
(1.00) 		0.659
(1.00) 		0.0266
(1.00) 		0.437
(1.00) 		0.885
(1.00) 		0.0734
(1.00)
17q gain 25 (7%) 327 0.000625
(0.353) 		0.0963
(1.00) 		0.0893
(1.00) 		0.514
(1.00) 		0.19
(1.00) 		0.0519
(1.00) 		0.223
(1.00) 		0.417
(1.00)
19p gain 12 (3%) 340 0.332
(1.00) 		0.00495
(1.00) 		0.0945
(1.00) 		0.0843
(1.00) 		0.389
(1.00) 		0.0231
(1.00) 		0.18
(1.00) 		0.262
(1.00)
19q gain 21 (6%) 331 0.187
(1.00) 		0.0581
(1.00) 		0.788
(1.00) 		0.402
(1.00) 		0.158
(1.00) 		0.319
(1.00) 		0.104
(1.00) 		0.801
(1.00)
21q gain 9 (3%) 343 0.182
(1.00) 		0.773
(1.00) 		1
(1.00) 		1
(1.00) 		0.0193
(1.00) 		0.0552
(1.00) 		0.0321
(1.00) 		1
(1.00)
Xq gain 23 (7%) 329 0.00145
(0.813) 		0.0888
(1.00) 		0.237
(1.00) 		0.177
(1.00) 		0.503
(1.00) 		0.913
(1.00) 		0.797
(1.00) 		0.906
(1.00)
2p loss 6 (2%) 346 0.969
(1.00) 		0.0441
(1.00) 		0.684
(1.00) 		1
(1.00) 		0.115
(1.00) 		0.0743
(1.00) 		0.0262
(1.00) 		0.171
(1.00)
2q loss 10 (3%) 342 0.394
(1.00) 		0.0939
(1.00) 		0.229
(1.00) 		0.449
(1.00) 		0.0147
(1.00) 		0.014
(1.00) 		0.0831
(1.00) 		0.0297
(1.00)
3q loss 22 (6%) 330 0.0168
(1.00) 		0.115
(1.00) 		0.331
(1.00) 		0.428
(1.00) 		0.881
(1.00) 		0.959
(1.00) 		0.275
(1.00) 		0.807
(1.00)
5p loss 8 (2%) 344 0.0314
(1.00) 		0.00598
(1.00) 		0.611
(1.00) 		0.821
(1.00) 		0.0763
(1.00) 		0.0888
(1.00) 		0.0575
(1.00) 		0.77
(1.00)
6p loss 19 (5%) 333 0.097
(1.00) 		0.0127
(1.00) 		0.00421
(1.00) 		0.169
(1.00) 		0.0317
(1.00) 		0.111
(1.00) 		0.00766
(1.00) 		0.235
(1.00)
6q loss 21 (6%) 331 0.199
(1.00) 		0.0701
(1.00) 		0.0106
(1.00) 		0.0725
(1.00) 		0.379
(1.00) 		0.392
(1.00) 		0.0547
(1.00) 		0.308
(1.00)
7p loss 5 (1%) 347 0.982
(1.00) 		0.388
(1.00) 		0.391
(1.00) 		0.452
(1.00) 		0.23
(1.00) 		1
(1.00)
7q loss 8 (2%) 344 0.155
(1.00) 		0.371
(1.00) 		0.752
(1.00) 		0.757
(1.00) 		0.315
(1.00) 		0.906
(1.00) 		0.164
(1.00) 		0.317
(1.00)
8q loss 7 (2%) 345 0.322
(1.00) 		0.0604
(1.00) 		0.845
(1.00) 		0.658
(1.00) 		1
(1.00) 		0.496
(1.00) 		0.273
(1.00) 		0.759
(1.00)
9q loss 31 (9%) 321 0.00345
(1.00) 		0.0679
(1.00) 		0.9
(1.00) 		0.477
(1.00) 		0.829
(1.00) 		0.855
(1.00) 		0.971
(1.00) 		0.0678
(1.00)
12p loss 13 (4%) 339 0.0414
(1.00) 		0.139
(1.00) 		0.169
(1.00) 		0.21
(1.00) 		0.468
(1.00) 		0.459
(1.00) 		0.597
(1.00) 		0.198
(1.00)
12q loss 8 (2%) 344 0.315
(1.00) 		0.073
(1.00) 		0.766
(1.00) 		0.671
(1.00) 		0.201
(1.00) 		0.308
(1.00) 		0.605
(1.00) 		0.0797
(1.00)
14q loss 18 (5%) 334 0.409
(1.00) 		0.0415
(1.00) 		0.141
(1.00) 		0.64
(1.00) 		0.0108
(1.00) 		0.0154
(1.00) 		0.00858
(1.00) 		0.299
(1.00)
15q loss 27 (8%) 325 0.00387
(1.00) 		0.173
(1.00) 		0.399
(1.00) 		0.318
(1.00) 		0.457
(1.00) 		0.246
(1.00) 		0.272
(1.00) 		0.189
(1.00)
16p loss 12 (3%) 340 0.0706
(1.00) 		0.0294
(1.00) 		0.109
(1.00) 		0.294
(1.00) 		0.0414
(1.00) 		0.014
(1.00) 		0.0921
(1.00) 		0.108
(1.00)
17q loss 6 (2%) 346 0.0446
(1.00) 		0.0232
(1.00) 		0.438
(1.00) 		0.402
(1.00) 		0.456
(1.00) 		0.861
(1.00) 		0.517
(1.00) 		1
(1.00)
18p loss 30 (9%) 322 0.0313
(1.00) 		0.0243
(1.00) 		0.846
(1.00) 		0.344
(1.00) 		0.578
(1.00) 		0.747
(1.00) 		0.457
(1.00) 		0.632
(1.00)
19p loss 27 (8%) 325 0.013
(1.00) 		0.113
(1.00) 		0.737
(1.00) 		0.941
(1.00) 		0.118
(1.00) 		0.416
(1.00) 		0.877
(1.00) 		0.113
(1.00)
19q loss 21 (6%) 331 0.0035
(1.00) 		0.18
(1.00) 		0.131
(1.00) 		0.293
(1.00) 		0.694
(1.00) 		0.833
(1.00) 		0.239
(1.00) 		1
(1.00)
20p loss 22 (6%) 330 0.0283
(1.00) 		0.319
(1.00) 		0.302
(1.00) 		0.814
(1.00) 		0.224
(1.00) 		0.0904
(1.00) 		0.55
(1.00) 		0.254
(1.00)
20q loss 10 (3%) 342 0.0222
(1.00) 		0.212
(1.00) 		0.651
(1.00) 		0.779
(1.00) 		0.0359
(1.00) 		0.0468
(1.00) 		0.788
(1.00) 		0.805
(1.00)
22q loss 26 (7%) 326 0.00331
(1.00) 		0.0305
(1.00) 		1
(1.00) 		0.779
(1.00) 		0.391
(1.00) 		0.772
(1.00) 		0.00758
(1.00) 		0.767
(1.00)
Xq loss 8 (2%) 344 0.0671
(1.00) 		0.0763
(1.00) 		0.903
(1.00) 		0.13
(1.00) 		0.804
(1.00) 		0.802
(1.00) 		1
(1.00) 		0.77
(1.00)
'1q gain mutation analysis' versus 'CN_CNMF'

P value = 0.000122 (Chi-square test), Q value = 0.071

Table S1.  Gene #2: '1q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
1Q GAIN MUTATED 15 3 14 8 1 1
1Q GAIN WILD-TYPE 67 38 36 84 73 12

Figure S1.  Get High-res Image Gene #2: '1q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'2p gain mutation analysis' versus 'CN_CNMF'

P value = 9.19e-05 (Chi-square test), Q value = 0.054

Table S2.  Gene #3: '2p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
2P GAIN MUTATED 12 9 7 1 1 1
2P GAIN WILD-TYPE 70 32 43 91 73 12

Figure S2.  Get High-res Image Gene #3: '2p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'2p gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000103 (Chi-square test), Q value = 0.06

Table S3.  Gene #3: '2p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
2P GAIN MUTATED 9 6 0 1 13 1 1 0
2P GAIN WILD-TYPE 34 41 39 44 45 50 3 19

Figure S3.  Get High-res Image Gene #3: '2p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'3p gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 8.26e-05 (Chi-square test), Q value = 0.049

Table S4.  Gene #5: '3p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
3P GAIN MUTATED 4 3 0 13 5 1 0 1
3P GAIN WILD-TYPE 39 44 39 32 53 50 4 18

Figure S4.  Get High-res Image Gene #5: '3p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'3p gain mutation analysis' versus 'MIRSEQ_CNMF'

P value = 0.000433 (Fisher's exact test), Q value = 0.25

Table S5.  Gene #5: '3p gain mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 113 137 101
3P GAIN MUTATED 4 21 3
3P GAIN WILD-TYPE 109 116 98

Figure S5.  Get High-res Image Gene #5: '3p gain mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

'3q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 4.27e-05 (Chi-square test), Q value = 0.025

Table S6.  Gene #6: '3q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
3Q GAIN MUTATED 20 17 6 23 25 6 2 3
3Q GAIN WILD-TYPE 23 30 33 22 33 45 2 16

Figure S6.  Get High-res Image Gene #6: '3q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'3q gain mutation analysis' versus 'MIRSEQ_CNMF'

P value = 0.000215 (Fisher's exact test), Q value = 0.12

Table S7.  Gene #6: '3q gain mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 113 137 101
3Q GAIN MUTATED 26 61 24
3Q GAIN WILD-TYPE 87 76 77

Figure S7.  Get High-res Image Gene #6: '3q gain mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

'5p gain mutation analysis' versus 'CN_CNMF'

P value = 5.64e-09 (Chi-square test), Q value = 3.5e-06

Table S8.  Gene #9: '5p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
5P GAIN MUTATED 21 27 11 17 8 4
5P GAIN WILD-TYPE 61 14 39 75 66 9

Figure S8.  Get High-res Image Gene #9: '5p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'7p gain mutation analysis' versus 'CN_CNMF'

P value = 2.95e-05 (Chi-square test), Q value = 0.018

Table S9.  Gene #13: '7p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
7P GAIN MUTATED 22 13 22 10 9 2
7P GAIN WILD-TYPE 60 28 28 82 65 11

Figure S9.  Get High-res Image Gene #13: '7p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'7p gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000406 (Chi-square test), Q value = 0.23

Table S10.  Gene #13: '7p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
7P GAIN MUTATED 15 12 12 3 21 3 1 3
7P GAIN WILD-TYPE 28 35 27 42 37 48 3 16

Figure S10.  Get High-res Image Gene #13: '7p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'7q gain mutation analysis' versus 'CN_CNMF'

P value = 7.08e-10 (Chi-square test), Q value = 4.4e-07

Table S11.  Gene #14: '7q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
7Q GAIN MUTATED 13 4 22 5 3 1
7Q GAIN WILD-TYPE 69 37 28 87 71 12

Figure S11.  Get High-res Image Gene #14: '7q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'7q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.01e-06 (Chi-square test), Q value = 0.00061

Table S12.  Gene #14: '7q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
7Q GAIN MUTATED 9 6 3 3 21 0 1 0
7Q GAIN WILD-TYPE 34 41 36 42 37 51 3 19

Figure S12.  Get High-res Image Gene #14: '7q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'8q gain mutation analysis' versus 'CN_CNMF'

P value = 4.97e-09 (Chi-square test), Q value = 3.1e-06

Table S13.  Gene #16: '8q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
8Q GAIN MUTATED 37 31 16 18 33 10
8Q GAIN WILD-TYPE 45 10 34 74 41 3

Figure S13.  Get High-res Image Gene #16: '8q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'8q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000341 (Chi-square test), Q value = 0.2

Table S14.  Gene #16: '8q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
8Q GAIN MUTATED 23 25 19 16 22 8 4 9
8Q GAIN WILD-TYPE 20 22 20 29 36 43 0 10

Figure S14.  Get High-res Image Gene #16: '8q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'9p gain mutation analysis' versus 'CN_CNMF'

P value = 0.00011 (Chi-square test), Q value = 0.064

Table S15.  Gene #17: '9p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
9P GAIN MUTATED 8 1 5 12 10 7
9P GAIN WILD-TYPE 74 40 45 80 64 6

Figure S15.  Get High-res Image Gene #17: '9p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'11p gain mutation analysis' versus 'CN_CNMF'

P value = 0.000202 (Chi-square test), Q value = 0.12

Table S16.  Gene #21: '11p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
11P GAIN MUTATED 1 1 2 3 6 4
11P GAIN WILD-TYPE 81 40 48 89 68 9

Figure S16.  Get High-res Image Gene #21: '11p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'12p gain mutation analysis' versus 'CN_CNMF'

P value = 1.64e-07 (Chi-square test), Q value = 1e-04

Table S17.  Gene #23: '12p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
12P GAIN MUTATED 11 14 22 9 6 3
12P GAIN WILD-TYPE 71 27 28 83 68 10

Figure S17.  Get High-res Image Gene #23: '12p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'12p gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.89e-05 (Chi-square test), Q value = 0.011

Table S18.  Gene #23: '12p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
12P GAIN MUTATED 13 7 0 10 23 4 1 2
12P GAIN WILD-TYPE 30 40 39 35 35 47 3 17

Figure S18.  Get High-res Image Gene #23: '12p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'12p gain mutation analysis' versus 'MIRSEQ_CNMF'

P value = 7.64e-05 (Fisher's exact test), Q value = 0.045

Table S19.  Gene #23: '12p gain mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 113 137 101
12P GAIN MUTATED 14 41 10
12P GAIN WILD-TYPE 99 96 91

Figure S19.  Get High-res Image Gene #23: '12p gain mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

'14q gain mutation analysis' versus 'CN_CNMF'

P value = 0.000131 (Chi-square test), Q value = 0.076

Table S20.  Gene #26: '14q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
14Q GAIN MUTATED 19 9 11 1 13 5
14Q GAIN WILD-TYPE 63 32 39 91 61 8

Figure S20.  Get High-res Image Gene #26: '14q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'16p gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 8.45e-05 (Chi-square test), Q value = 0.05

Table S21.  Gene #28: '16p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
16P GAIN MUTATED 8 5 1 1 2 1 2 0
16P GAIN WILD-TYPE 35 42 38 44 56 50 2 19

Figure S21.  Get High-res Image Gene #28: '16p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'17p gain mutation analysis' versus 'CN_CNMF'

P value = 0.000367 (Chi-square test), Q value = 0.21

Table S22.  Gene #30: '17p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
17P GAIN MUTATED 7 2 9 2 0 0
17P GAIN WILD-TYPE 75 39 41 90 74 13

Figure S22.  Get High-res Image Gene #30: '17p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'18p gain mutation analysis' versus 'CN_CNMF'

P value = 0.000122 (Chi-square test), Q value = 0.071

Table S23.  Gene #32: '18p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
18P GAIN MUTATED 12 11 16 7 5 4
18P GAIN WILD-TYPE 70 30 34 85 69 9

Figure S23.  Get High-res Image Gene #32: '18p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'18q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000177 (Chi-square test), Q value = 0.1

Table S24.  Gene #33: '18q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
18Q GAIN MUTATED 2 0 0 9 8 0 0 1
18Q GAIN WILD-TYPE 41 47 39 36 50 51 4 18

Figure S24.  Get High-res Image Gene #33: '18q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'20p gain mutation analysis' versus 'CN_CNMF'

P value = 7.5e-06 (Chi-square test), Q value = 0.0045

Table S25.  Gene #36: '20p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
20P GAIN MUTATED 15 20 11 7 13 2
20P GAIN WILD-TYPE 67 21 39 85 61 11

Figure S25.  Get High-res Image Gene #36: '20p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'20p gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 7.9e-05 (Chi-square test), Q value = 0.047

Table S26.  Gene #36: '20p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
20P GAIN MUTATED 11 17 3 9 16 2 3 2
20P GAIN WILD-TYPE 32 30 36 36 42 49 1 17

Figure S26.  Get High-res Image Gene #36: '20p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'20q gain mutation analysis' versus 'CN_CNMF'

P value = 8.46e-07 (Chi-square test), Q value = 0.00051

Table S27.  Gene #37: '20q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
20Q GAIN MUTATED 16 21 13 6 13 3
20Q GAIN WILD-TYPE 66 20 37 86 61 10

Figure S27.  Get High-res Image Gene #37: '20q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'20q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000112 (Chi-square test), Q value = 0.065

Table S28.  Gene #37: '20q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
20Q GAIN MUTATED 14 17 5 6 16 2 3 4
20Q GAIN WILD-TYPE 29 30 34 39 42 49 1 15

Figure S28.  Get High-res Image Gene #37: '20q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'22q gain mutation analysis' versus 'CN_CNMF'

P value = 0.00016 (Chi-square test), Q value = 0.092

Table S29.  Gene #39: '22q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
22Q GAIN MUTATED 10 5 15 3 6 3
22Q GAIN WILD-TYPE 72 36 35 89 68 10

Figure S29.  Get High-res Image Gene #39: '22q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'22q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 8.21e-05 (Chi-square test), Q value = 0.048

Table S30.  Gene #39: '22q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
22Q GAIN MUTATED 5 5 2 2 19 5 0 0
22Q GAIN WILD-TYPE 38 42 37 43 39 46 4 19

Figure S30.  Get High-res Image Gene #39: '22q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'1p loss mutation analysis' versus 'CN_CNMF'

P value = 4.35e-10 (Chi-square test), Q value = 2.7e-07

Table S31.  Gene #41: '1p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
1P LOSS MUTATED 3 0 12 0 1 0
1P LOSS WILD-TYPE 79 41 38 92 73 13

Figure S31.  Get High-res Image Gene #41: '1p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'1p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 9.7e-07 (Chi-square test), Q value = 0.00059

Table S32.  Gene #41: '1p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
1P LOSS MUTATED 2 0 0 1 12 0 1 0
1P LOSS WILD-TYPE 41 47 39 44 46 51 3 19

Figure S32.  Get High-res Image Gene #41: '1p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'3p loss mutation analysis' versus 'CN_CNMF'

P value = 8.24e-13 (Chi-square test), Q value = 5.2e-10

Table S33.  Gene #44: '3p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
3P LOSS MUTATED 44 19 32 5 28 5
3P LOSS WILD-TYPE 38 22 18 87 46 8

Figure S33.  Get High-res Image Gene #44: '3p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'3p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 3.16e-07 (Chi-square test), Q value = 0.00019

Table S34.  Gene #44: '3p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
3P LOSS MUTATED 22 20 15 9 33 3 2 10
3P LOSS WILD-TYPE 21 27 24 36 25 48 2 9

Figure S34.  Get High-res Image Gene #44: '3p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'4p loss mutation analysis' versus 'CN_CNMF'

P value = 5.83e-12 (Chi-square test), Q value = 3.7e-09

Table S35.  Gene #46: '4p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
4P LOSS MUTATED 27 6 30 8 11 0
4P LOSS WILD-TYPE 55 35 20 84 63 13

Figure S35.  Get High-res Image Gene #46: '4p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'4p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 2.98e-08 (Chi-square test), Q value = 1.8e-05

Table S36.  Gene #46: '4p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
4P LOSS MUTATED 12 5 7 12 31 1 1 3
4P LOSS WILD-TYPE 31 42 32 33 27 50 3 16

Figure S36.  Get High-res Image Gene #46: '4p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'4p loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000123 (Fisher's exact test), Q value = 0.071

Table S37.  Gene #46: '4p loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 95 84 120
4P LOSS MUTATED 20 9 43
4P LOSS WILD-TYPE 75 75 77

Figure S37.  Get High-res Image Gene #46: '4p loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

'4p loss mutation analysis' versus 'MIRSEQ_CNMF'

P value = 0.000172 (Fisher's exact test), Q value = 0.1

Table S38.  Gene #46: '4p loss mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 113 137 101
4P LOSS MUTATED 23 47 12
4P LOSS WILD-TYPE 90 90 89

Figure S38.  Get High-res Image Gene #46: '4p loss mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

'4q loss mutation analysis' versus 'CN_CNMF'

P value = 5.73e-09 (Chi-square test), Q value = 3.5e-06

Table S39.  Gene #47: '4q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
4Q LOSS MUTATED 13 6 23 4 9 0
4Q LOSS WILD-TYPE 69 35 27 88 65 13

Figure S39.  Get High-res Image Gene #47: '4q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'4q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 3.38e-06 (Chi-square test), Q value = 0.002

Table S40.  Gene #47: '4q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
4Q LOSS MUTATED 10 7 4 6 22 0 0 0
4Q LOSS WILD-TYPE 33 40 35 39 36 51 4 19

Figure S40.  Get High-res Image Gene #47: '4q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'5q loss mutation analysis' versus 'CN_CNMF'

P value = 2.15e-14 (Chi-square test), Q value = 1.4e-11

Table S41.  Gene #49: '5q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
5Q LOSS MUTATED 16 17 24 1 5 0
5Q LOSS WILD-TYPE 66 24 26 91 69 13

Figure S41.  Get High-res Image Gene #49: '5q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'5q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 7.27e-10 (Chi-square test), Q value = 4.5e-07

Table S42.  Gene #49: '5q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
5Q LOSS MUTATED 19 11 1 4 23 0 0 2
5Q LOSS WILD-TYPE 24 36 38 41 35 51 4 17

Figure S42.  Get High-res Image Gene #49: '5q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'5q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 4.53e-05 (Fisher's exact test), Q value = 0.027

Table S43.  Gene #49: '5q loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 95 84 120
5Q LOSS MUTATED 16 6 38
5Q LOSS WILD-TYPE 79 78 82

Figure S43.  Get High-res Image Gene #49: '5q loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

'8p loss mutation analysis' versus 'CN_CNMF'

P value = 1.8e-06 (Chi-square test), Q value = 0.0011

Table S44.  Gene #54: '8p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
8P LOSS MUTATED 31 9 12 2 20 4
8P LOSS WILD-TYPE 51 32 38 90 54 9

Figure S44.  Get High-res Image Gene #54: '8p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'8p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 6.66e-06 (Chi-square test), Q value = 0.004

Table S45.  Gene #54: '8p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
8P LOSS MUTATED 9 18 16 4 12 1 0 2
8P LOSS WILD-TYPE 34 29 23 41 46 50 4 17

Figure S45.  Get High-res Image Gene #54: '8p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'9p loss mutation analysis' versus 'CN_CNMF'

P value = 1.66e-09 (Chi-square test), Q value = 1e-06

Table S46.  Gene #56: '9p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
9P LOSS MUTATED 28 20 21 2 21 1
9P LOSS WILD-TYPE 54 21 29 90 53 12

Figure S46.  Get High-res Image Gene #56: '9p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'9p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 2.25e-08 (Chi-square test), Q value = 1.4e-05

Table S47.  Gene #56: '9p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
9P LOSS MUTATED 24 12 9 5 25 1 2 5
9P LOSS WILD-TYPE 19 35 30 40 33 50 2 14

Figure S47.  Get High-res Image Gene #56: '9p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'10p loss mutation analysis' versus 'CN_CNMF'

P value = 8.93e-05 (Chi-square test), Q value = 0.052

Table S48.  Gene #58: '10p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
10P LOSS MUTATED 12 10 12 1 12 5
10P LOSS WILD-TYPE 70 31 38 91 62 8

Figure S48.  Get High-res Image Gene #58: '10p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'10q loss mutation analysis' versus 'CN_CNMF'

P value = 8.12e-08 (Chi-square test), Q value = 5e-05

Table S49.  Gene #59: '10q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
10Q LOSS MUTATED 5 5 15 2 2 0
10Q LOSS WILD-TYPE 77 36 35 90 72 13

Figure S49.  Get High-res Image Gene #59: '10q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'10q loss mutation analysis' versus 'MIRSEQ_CNMF'

P value = 0.000419 (Fisher's exact test), Q value = 0.24

Table S50.  Gene #59: '10q loss mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 113 137 101
10Q LOSS MUTATED 6 21 2
10Q LOSS WILD-TYPE 107 116 99

Figure S50.  Get High-res Image Gene #59: '10q loss mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

'11p loss mutation analysis' versus 'CN_CNMF'

P value = 0.000257 (Chi-square test), Q value = 0.15

Table S51.  Gene #60: '11p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
11P LOSS MUTATED 22 7 9 5 5 0
11P LOSS WILD-TYPE 60 34 41 87 69 13

Figure S51.  Get High-res Image Gene #60: '11p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'11q loss mutation analysis' versus 'CN_CNMF'

P value = 2.19e-13 (Chi-square test), Q value = 1.4e-10

Table S52.  Gene #61: '11q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
11Q LOSS MUTATED 41 3 9 13 2 1
11Q LOSS WILD-TYPE 41 38 41 79 72 12

Figure S52.  Get High-res Image Gene #61: '11q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'11q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 7.28e-05 (Chi-square test), Q value = 0.043

Table S53.  Gene #61: '11q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
11Q LOSS MUTATED 5 6 11 19 12 1 1 3
11Q LOSS WILD-TYPE 38 41 28 26 46 50 3 16

Figure S53.  Get High-res Image Gene #61: '11q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'13q loss mutation analysis' versus 'CN_CNMF'

P value = 2.38e-07 (Chi-square test), Q value = 0.00015

Table S54.  Gene #64: '13q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
13Q LOSS MUTATED 19 12 24 8 8 1
13Q LOSS WILD-TYPE 63 29 26 84 66 12

Figure S54.  Get High-res Image Gene #64: '13q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'13q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 9.48e-10 (Chi-square test), Q value = 5.9e-07

Table S55.  Gene #64: '13q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
13Q LOSS MUTATED 25 7 5 9 14 0 0 2
13Q LOSS WILD-TYPE 18 40 34 36 44 51 4 17

Figure S55.  Get High-res Image Gene #64: '13q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'13q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.38e-05 (Fisher's exact test), Q value = 0.014

Table S56.  Gene #64: '13q loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 95 84 120
13Q LOSS MUTATED 16 6 39
13Q LOSS WILD-TYPE 79 78 81

Figure S56.  Get High-res Image Gene #64: '13q loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

'16q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 4.19e-05 (Chi-square test), Q value = 0.025

Table S57.  Gene #68: '16q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
16Q LOSS MUTATED 4 0 1 11 8 0 0 0
16Q LOSS WILD-TYPE 39 47 38 34 50 51 4 19

Figure S57.  Get High-res Image Gene #68: '16q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'16q loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 4.72e-07 (Fisher's exact test), Q value = 0.00029

Table S58.  Gene #68: '16q loss mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 118 91 90
16Q LOSS MUTATED 21 1 1
16Q LOSS WILD-TYPE 97 90 89

Figure S58.  Get High-res Image Gene #68: '16q loss mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'16q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1.34e-08 (Fisher's exact test), Q value = 8.2e-06

Table S59.  Gene #68: '16q loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 95 84 120
16Q LOSS MUTATED 0 1 22
16Q LOSS WILD-TYPE 95 83 98

Figure S59.  Get High-res Image Gene #68: '16q loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

'16q loss mutation analysis' versus 'MIRSEQ_CNMF'

P value = 0.000419 (Fisher's exact test), Q value = 0.24

Table S60.  Gene #68: '16q loss mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 113 137 101
16Q LOSS MUTATED 6 21 2
16Q LOSS WILD-TYPE 107 116 99

Figure S60.  Get High-res Image Gene #68: '16q loss mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

'17p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.27e-05 (Chi-square test), Q value = 0.0076

Table S61.  Gene #69: '17p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
17P LOSS MUTATED 17 8 1 6 7 1 1 2
17P LOSS WILD-TYPE 26 39 38 39 51 50 3 17

Figure S61.  Get High-res Image Gene #69: '17p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'18q loss mutation analysis' versus 'CN_CNMF'

P value = 1.92e-09 (Chi-square test), Q value = 1.2e-06

Table S62.  Gene #72: '18q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
18Q LOSS MUTATED 26 19 12 1 31 4
18Q LOSS WILD-TYPE 56 22 38 91 43 9

Figure S62.  Get High-res Image Gene #72: '18q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'18q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 6.73e-08 (Chi-square test), Q value = 4.1e-05

Table S63.  Gene #72: '18q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 43 47 39 45 58 51 4 19
18Q LOSS MUTATED 20 22 14 2 15 3 3 5
18Q LOSS WILD-TYPE 23 25 25 43 43 48 1 14

Figure S63.  Get High-res Image Gene #72: '18q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'21q loss mutation analysis' versus 'CN_CNMF'

P value = 2.16e-06 (Chi-square test), Q value = 0.0013

Table S64.  Gene #77: '21q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 82 41 50 92 74 13
21Q LOSS MUTATED 21 7 14 0 15 6
21Q LOSS WILD-TYPE 61 34 36 92 59 7

Figure S64.  Get High-res Image Gene #77: '21q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

Methods & Data
Input

  • Mutation data file = broad_values_by_arm.mutsig.cluster.txt

  • Molecular subtypes file = HNSC-TP.transferedmergedcluster.txt

  • Number of patients = 352

  • Number of significantly arm-level cnvs = 79

  • Number of molecular subtypes = 8

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

Chi-square test

For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.test' function in R

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.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

References
[1] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[2] 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)
[3] 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)
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