Skin Cutaneous Melanoma: Correlation between copy number variations of arm-level result and molecular subtypes
(All_Samples 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 78 arm-level results and 8 molecular subtypes across 288 patients, 44 significant findings detected with Q value < 0.25.

  • 5p gain cnv correlated to 'CN_CNMF'.

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

  • 7p gain cnv correlated to 'CN_CNMF'.

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

  • 8p gain cnv correlated to 'CN_CNMF'.

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

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

  • 19q gain cnv correlated to 'MRNASEQ_CNMF'.

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

  • 20q gain cnv correlated to 'CN_CNMF'.

  • 21q gain cnv correlated to 'METHLYATION_CNMF'.

  • 22q gain cnv correlated to 'CN_CNMF'.

  • 1p loss cnv correlated to 'METHLYATION_CNMF'.

  • 2p loss cnv correlated to 'CN_CNMF' and 'MIRSEQ_CNMF'.

  • 2q loss cnv correlated to 'MIRSEQ_CNMF'.

  • 5q loss cnv correlated to 'CN_CNMF'.

  • 6q loss cnv correlated to 'CN_CNMF'.

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

  • 9q loss cnv correlated to 'CN_CNMF'.

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

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

  • 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' and 'MRNASEQ_CHIERARCHICAL'.

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 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 44 significant findings detected.

Molecular
subtypes 		CN
CNMF 		METHLYATION
CNMF 		RPPA
CNMF 		RPPA
CHIERARCHICAL 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
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
9p loss 159 (55%) 129 1.61e-12
(9.96e-10) 		4.49e-07
(0.000274) 		0.0227
(1.00) 		0.959
(1.00) 		0.000231
(0.135) 		7.09e-05
(0.0419) 		0.499
(1.00) 		0.217
(1.00)
10p loss 120 (42%) 168 4.96e-13
(3.08e-10) 		2.82e-05
(0.0168) 		0.978
(1.00) 		0.0853
(1.00) 		2.32e-07
(0.000142) 		2.13e-06
(0.00129) 		0.39
(1.00) 		0.264
(1.00)
10q loss 135 (47%) 153 2.18e-13
(1.35e-10) 		5.77e-06
(0.00349) 		0.626
(1.00) 		0.151
(1.00) 		6.83e-08
(4.18e-05) 		1.47e-05
(0.00883) 		0.739
(1.00) 		0.623
(1.00)
6p gain 89 (31%) 199 2.68e-06
(0.00162) 		1.14e-06
(0.000694) 		0.222
(1.00) 		0.526
(1.00) 		0.0158
(1.00) 		0.134
(1.00) 		0.0011
(0.629) 		9.96e-05
(0.0585)
8q gain 92 (32%) 196 5.12e-09
(3.15e-06) 		1.23e-05
(0.00741) 		0.472
(1.00) 		0.483
(1.00) 		8.38e-05
(0.0494) 		0.00263
(1.00) 		0.514
(1.00) 		0.793
(1.00)
7q gain 120 (42%) 168 5.82e-11
(3.59e-08) 		0.207
(1.00) 		0.0207
(1.00) 		0.0255
(1.00) 		6.75e-05
(0.04) 		0.00169
(0.944) 		0.208
(1.00) 		0.0472
(1.00)
13q gain 45 (16%) 243 5.6e-10
(3.45e-07) 		1.6e-05
(0.00958) 		0.429
(1.00) 		0.876
(1.00) 		0.00198
(1.00) 		0.17
(1.00) 		0.374
(1.00) 		0.735
(1.00)
20p gain 79 (27%) 209 2.69e-05
(0.016) 		0.00543
(1.00) 		0.398
(1.00) 		0.79
(1.00) 		6.15e-05
(0.0365) 		0.00422
(1.00) 		0.0496
(1.00) 		0.0282
(1.00)
2p loss 24 (8%) 264 0.000322
(0.187) 		0.119
(1.00) 		0.0828
(1.00) 		0.00804
(1.00) 		0.0999
(1.00) 		0.319
(1.00) 		1.56e-05
(0.00937) 		0.00155
(0.87)
18p loss 54 (19%) 234 0.00886
(1.00) 		0.00609
(1.00) 		0.475
(1.00) 		0.808
(1.00) 		0.000398
(0.23) 		3.59e-05
(0.0214) 		0.316
(1.00) 		1
(1.00)
5p gain 35 (12%) 253 0.000304
(0.177) 		0.0998
(1.00) 		1
(1.00) 		0.814
(1.00) 		0.606
(1.00) 		0.581
(1.00) 		0.381
(1.00) 		0.707
(1.00)
7p gain 119 (41%) 169 3.74e-12
(2.31e-09) 		0.0814
(1.00) 		0.0383
(1.00) 		0.0206
(1.00) 		0.00116
(0.661) 		0.00395
(1.00) 		0.523
(1.00) 		0.212
(1.00)
8p gain 55 (19%) 233 0.000343
(0.199) 		0.016
(1.00) 		0.0759
(1.00) 		0.184
(1.00) 		0.00616
(1.00) 		0.00139
(0.781) 		0.417
(1.00) 		0.275
(1.00)
19q gain 22 (8%) 266 0.00639
(1.00) 		0.0231
(1.00) 		0.373
(1.00) 		0.677
(1.00) 		0.000253
(0.148) 		0.00135
(0.768) 		0.921
(1.00) 		0.651
(1.00)
20q gain 100 (35%) 188 3.23e-07
(0.000197) 		0.00936
(1.00) 		0.245
(1.00) 		0.398
(1.00) 		0.000855
(0.489) 		0.0146
(1.00) 		0.321
(1.00) 		0.0945
(1.00)
21q gain 31 (11%) 257 0.00274
(1.00) 		0.000341
(0.198) 		0.855
(1.00) 		0.72
(1.00) 		0.00615
(1.00) 		0.0427
(1.00) 		0.152
(1.00) 		0.551
(1.00)
22q gain 64 (22%) 224 7.71e-06
(0.00465) 		0.525
(1.00) 		0.828
(1.00) 		0.776
(1.00) 		0.154
(1.00) 		0.538
(1.00) 		0.541
(1.00) 		0.459
(1.00)
1p loss 20 (7%) 268 0.0296
(1.00) 		0.000142
(0.0835) 		0.574
(1.00) 		0.493
(1.00) 		0.00534
(1.00) 		0.117
(1.00) 		0.558
(1.00) 		0.633
(1.00)
2q loss 24 (8%) 264 0.00152
(0.855) 		0.0177
(1.00) 		0.0828
(1.00) 		0.0115
(1.00) 		0.0109
(1.00) 		0.319
(1.00) 		8.67e-05
(0.051) 		0.00759
(1.00)
5q loss 52 (18%) 236 1.01e-05
(0.00609) 		0.00519
(1.00) 		0.08
(1.00) 		0.372
(1.00) 		0.598
(1.00) 		0.599
(1.00) 		0.699
(1.00) 		1
(1.00)
6q loss 100 (35%) 188 1.2e-12
(7.44e-10) 		0.04
(1.00) 		0.848
(1.00) 		0.227
(1.00) 		0.00922
(1.00) 		0.02
(1.00) 		0.417
(1.00) 		0.157
(1.00)
9q loss 115 (40%) 173 0.000154
(0.09) 		0.00135
(0.768) 		0.35
(1.00) 		0.626
(1.00) 		0.175
(1.00) 		0.0911
(1.00) 		0.499
(1.00) 		0.318
(1.00)
11p loss 63 (22%) 225 5.1e-08
(3.12e-05) 		0.00517
(1.00) 		0.632
(1.00) 		0.561
(1.00) 		0.0865
(1.00) 		0.541
(1.00) 		0.143
(1.00) 		0.554
(1.00)
11q loss 72 (25%) 216 6.12e-06
(0.0037) 		0.005
(1.00) 		0.653
(1.00) 		1
(1.00) 		0.191
(1.00) 		0.687
(1.00) 		0.787
(1.00) 		0.888
(1.00)
12q loss 31 (11%) 257 0.132
(1.00) 		5.4e-05
(0.0321) 		1
(1.00) 		0.533
(1.00) 		0.0643
(1.00) 		0.0278
(1.00) 		0.779
(1.00) 		0.429
(1.00)
14q loss 61 (21%) 227 1.79e-08
(1.1e-05) 		0.016
(1.00) 		0.913
(1.00) 		0.731
(1.00) 		0.00178
(0.991) 		0.00521
(1.00) 		0.612
(1.00) 		0.764
(1.00)
1p gain 32 (11%) 256 0.338
(1.00) 		0.477
(1.00) 		0.587
(1.00) 		0.669
(1.00) 		0.754
(1.00) 		0.582
(1.00) 		0.584
(1.00) 		0.332
(1.00)
1q gain 89 (31%) 199 0.000666
(0.384) 		0.159
(1.00) 		0.825
(1.00) 		0.823
(1.00) 		0.00786
(1.00) 		0.894
(1.00) 		0.177
(1.00) 		0.0172
(1.00)
2p gain 31 (11%) 257 0.00356
(1.00) 		0.158
(1.00) 		0.345
(1.00) 		0.469
(1.00) 		0.0135
(1.00) 		0.0804
(1.00) 		0.11
(1.00) 		0.0055
(1.00)
2q gain 28 (10%) 260 0.00167
(0.936) 		0.436
(1.00) 		0.181
(1.00) 		0.0503
(1.00) 		0.0125
(1.00) 		0.0344
(1.00) 		0.0263
(1.00) 		0.000789
(0.453)
3p gain 25 (9%) 263 0.0579
(1.00) 		0.255
(1.00) 		0.94
(1.00) 		1
(1.00) 		0.0526
(1.00) 		0.186
(1.00) 		0.892
(1.00) 		1
(1.00)
3q gain 32 (11%) 256 0.122
(1.00) 		0.366
(1.00) 		0.562
(1.00) 		1
(1.00) 		0.0567
(1.00) 		0.298
(1.00) 		0.808
(1.00) 		0.695
(1.00)
4p gain 27 (9%) 261 0.0104
(1.00) 		0.0186
(1.00) 		0.691
(1.00) 		0.211
(1.00) 		0.458
(1.00) 		0.496
(1.00) 		1
(1.00) 		0.834
(1.00)
4q gain 21 (7%) 267 0.0447
(1.00) 		0.0214
(1.00) 		0.922
(1.00) 		0.786
(1.00) 		0.535
(1.00) 		0.881
(1.00) 		0.774
(1.00) 		0.485
(1.00)
5q gain 15 (5%) 273 0.00201
(1.00) 		0.306
(1.00) 		1
(1.00) 		0.891
(1.00) 		0.389
(1.00) 		0.472
(1.00) 		0.612
(1.00) 		0.264
(1.00)
6q gain 22 (8%) 266 0.161
(1.00) 		0.198
(1.00) 		0.723
(1.00) 		0.772
(1.00) 		0.585
(1.00) 		0.586
(1.00) 		0.464
(1.00) 		0.338
(1.00)
9p gain 9 (3%) 279 0.719
(1.00) 		0.144
(1.00) 		0.142
(1.00) 		0.488
(1.00) 		0.229
(1.00) 		0.497
(1.00) 		0.762
(1.00) 		0.733
(1.00)
9q gain 11 (4%) 277 0.181
(1.00) 		0.332
(1.00) 		0.142
(1.00) 		0.488
(1.00) 		0.721
(1.00) 		1
(1.00) 		0.922
(1.00) 		0.51
(1.00)
11p gain 19 (7%) 269 0.00543
(1.00) 		1
(1.00) 		0.14
(1.00) 		0.0199
(1.00) 		0.0213
(1.00) 		0.0107
(1.00) 		0.644
(1.00) 		0.0436
(1.00)
11q gain 16 (6%) 272 0.00191
(1.00) 		0.493
(1.00) 		0.286
(1.00) 		0.105
(1.00) 		0.0161
(1.00) 		0.0302
(1.00) 		0.666
(1.00) 		0.0975
(1.00)
12p gain 23 (8%) 265 0.000474
(0.274) 		0.328
(1.00) 		0.536
(1.00) 		0.324
(1.00) 		0.000938
(0.535) 		0.0272
(1.00) 		0.383
(1.00) 		0.0233
(1.00)
12q gain 11 (4%) 277 0.0614
(1.00) 		1
(1.00) 		1
(1.00) 		0.667
(1.00) 		0.0252
(1.00) 		0.31
(1.00) 		0.536
(1.00) 		0.0226
(1.00)
14q gain 16 (6%) 272 0.0154
(1.00) 		0.0586
(1.00) 		0.166
(1.00) 		0.722
(1.00) 		0.185
(1.00) 		1
(1.00) 		0.899
(1.00) 		1
(1.00)
15q gain 37 (13%) 251 0.00989
(1.00) 		0.448
(1.00) 		0.944
(1.00) 		0.592
(1.00) 		0.00731
(1.00) 		0.436
(1.00) 		0.869
(1.00) 		0.132
(1.00)
16p gain 17 (6%) 271 0.0252
(1.00) 		0.0267
(1.00) 		0.562
(1.00) 		0.692
(1.00) 		0.0171
(1.00) 		0.106
(1.00) 		0.103
(1.00) 		0.444
(1.00)
16q gain 16 (6%) 272 0.0191
(1.00) 		0.0789
(1.00) 		0.217
(1.00) 		0.247
(1.00) 		0.035
(1.00) 		0.158
(1.00) 		0.291
(1.00) 		0.12
(1.00)
17p gain 17 (6%) 271 0.15
(1.00) 		0.215
(1.00) 		0.464
(1.00) 		0.43
(1.00) 		0.164
(1.00) 		0.699
(1.00) 		0.145
(1.00) 		0.444
(1.00)
17q gain 30 (10%) 258 0.0195
(1.00) 		0.0698
(1.00) 		0.0374
(1.00) 		0.0113
(1.00) 		0.103
(1.00) 		0.507
(1.00) 		0.2
(1.00) 		0.312
(1.00)
18p gain 33 (11%) 255 0.104
(1.00) 		0.18
(1.00) 		0.587
(1.00) 		0.64
(1.00) 		0.354
(1.00) 		0.489
(1.00) 		0.89
(1.00) 		0.703
(1.00)
18q gain 23 (8%) 265 0.176
(1.00) 		0.064
(1.00) 		1
(1.00) 		0.932
(1.00) 		0.268
(1.00) 		0.0452
(1.00) 		0.401
(1.00) 		0.364
(1.00)
19p gain 18 (6%) 270 0.0977
(1.00) 		0.0643
(1.00) 		0.119
(1.00) 		0.203
(1.00) 		0.00867
(1.00) 		0.00119
(0.677) 		0.551
(1.00) 		0.805
(1.00)
Xq gain 6 (2%) 282 1
(1.00) 		0.293
(1.00) 		0.692
(1.00) 		0.355
(1.00) 		0.137
(1.00) 		0.00815
(1.00) 		0.179
(1.00) 		0.0867
(1.00)
1q loss 9 (3%) 279 0.0151
(1.00) 		0.144
(1.00) 		0.119
(1.00) 		0.819
(1.00) 		0.102
(1.00) 		0.481
(1.00) 		1
(1.00) 		1
(1.00)
3p loss 24 (8%) 264 0.271
(1.00) 		0.139
(1.00) 		0.0486
(1.00) 		0.239
(1.00) 		0.00671
(1.00) 		0.000841
(0.482) 		0.963
(1.00) 		0.387
(1.00)
3q loss 21 (7%) 267 0.149
(1.00) 		0.0867
(1.00) 		0.0486
(1.00) 		0.269
(1.00) 		0.113
(1.00) 		0.0901
(1.00) 		0.711
(1.00) 		1
(1.00)
4p loss 35 (12%) 253 0.0708
(1.00) 		0.115
(1.00) 		0.809
(1.00) 		0.281
(1.00) 		0.0477
(1.00) 		0.115
(1.00) 		0.609
(1.00) 		0.576
(1.00)
4q loss 38 (13%) 250 0.00159
(0.891) 		0.0126
(1.00) 		0.957
(1.00) 		0.187
(1.00) 		0.0558
(1.00) 		0.0932
(1.00) 		0.313
(1.00) 		0.278
(1.00)
5p loss 34 (12%) 254 0.0144
(1.00) 		0.0973
(1.00) 		0.0489
(1.00) 		0.1
(1.00) 		0.352
(1.00) 		0.219
(1.00) 		0.578
(1.00) 		0.446
(1.00)
6p loss 25 (9%) 263 0.0239
(1.00) 		0.623
(1.00) 		0.289
(1.00) 		0.746
(1.00) 		0.144
(1.00) 		0.076
(1.00) 		0.179
(1.00) 		0.133
(1.00)
7p loss 7 (2%) 281 0.466
(1.00) 		0.0344
(1.00) 		0.27
(1.00) 		0.305
(1.00) 		0.166
(1.00) 		0.804
(1.00) 		0.628
(1.00) 		0.715
(1.00)
7q loss 6 (2%) 282 0.671
(1.00) 		0.09
(1.00) 		0.253
(1.00) 		0.329
(1.00) 		0.696
(1.00) 		0.883
(1.00) 		1
(1.00) 		1
(1.00)
8p loss 36 (12%) 252 0.427
(1.00) 		0.159
(1.00) 		0.62
(1.00) 		0.909
(1.00) 		0.347
(1.00) 		0.42
(1.00) 		0.12
(1.00) 		0.0248
(1.00)
8q loss 9 (3%) 279 0.201
(1.00) 		0.181
(1.00) 		0.659
(1.00) 		1
(1.00) 		0.249
(1.00) 		0.0136
(1.00) 		0.43
(1.00) 		0.491
(1.00)
12p loss 21 (7%) 267 0.157
(1.00) 		0.000787
(0.453) 		0.873
(1.00) 		0.203
(1.00) 		0.448
(1.00) 		0.0901
(1.00) 		0.764
(1.00) 		0.815
(1.00)
13q loss 40 (14%) 248 0.000522
(0.301) 		0.316
(1.00) 		0.85
(1.00) 		0.339
(1.00) 		0.931
(1.00) 		0.226
(1.00) 		0.466
(1.00) 		0.86
(1.00)
15q loss 17 (6%) 271 0.0105
(1.00) 		0.0427
(1.00) 		0.116
(1.00) 		0.221
(1.00) 		0.827
(1.00) 		0.119
(1.00) 		0.434
(1.00) 		0.609
(1.00)
16p loss 24 (8%) 264 0.0083
(1.00) 		0.00136
(0.771) 		0.119
(1.00) 		0.761
(1.00) 		0.106
(1.00) 		0.86
(1.00) 		0.107
(1.00) 		0.0431
(1.00)
16q loss 57 (20%) 231 0.00171
(0.954) 		0.00247
(1.00) 		1
(1.00) 		0.573
(1.00) 		0.006
(1.00) 		0.77
(1.00) 		0.0335
(1.00) 		0.0282
(1.00)
17p loss 56 (19%) 232 0.0361
(1.00) 		0.245
(1.00) 		0.692
(1.00) 		0.488
(1.00) 		0.173
(1.00) 		0.878
(1.00) 		0.251
(1.00) 		0.35
(1.00)
17q loss 27 (9%) 261 0.0775
(1.00) 		0.332
(1.00) 		0.614
(1.00) 		0.761
(1.00) 		0.169
(1.00) 		0.37
(1.00) 		1
(1.00) 		1
(1.00)
18q loss 49 (17%) 239 0.0247
(1.00) 		0.0259
(1.00) 		0.138
(1.00) 		0.205
(1.00) 		0.0223
(1.00) 		0.00444
(1.00) 		0.762
(1.00) 		1
(1.00)
19p loss 22 (8%) 266 0.0161
(1.00) 		0.458
(1.00) 		0.277
(1.00) 		0.761
(1.00) 		0.0499
(1.00) 		0.0297
(1.00) 		0.2
(1.00) 		0.651
(1.00)
19q loss 22 (8%) 266 0.00188
(1.00) 		0.458
(1.00) 		0.824
(1.00) 		0.677
(1.00) 		0.343
(1.00) 		0.0953
(1.00) 		0.493
(1.00) 		0.364
(1.00)
20p loss 14 (5%) 274 0.828
(1.00) 		0.539
(1.00) 		0.369
(1.00) 		1
(1.00) 		0.436
(1.00) 		0.251
(1.00) 		0.247
(1.00) 		1
(1.00)
20q loss 3 (1%) 285 0.219
(1.00) 		0.186
(1.00) 		0.489
(1.00) 		0.191
(1.00) 		0.791
(1.00) 		1
(1.00)
21q loss 33 (11%) 255 0.367
(1.00) 		0.475
(1.00) 		0.483
(1.00) 		0.842
(1.00) 		0.824
(1.00) 		0.539
(1.00) 		0.194
(1.00) 		0.569
(1.00)
22q loss 24 (8%) 264 0.0147
(1.00) 		0.042
(1.00) 		0.214
(1.00) 		0.878
(1.00) 		0.758
(1.00) 		0.214
(1.00) 		0.467
(1.00) 		0.269
(1.00)
Xq loss 9 (3%) 279 0.353
(1.00) 		0.00884
(1.00) 		0.418
(1.00) 		0.328
(1.00) 		0.322
(1.00) 		0.481
(1.00) 		0.0622
(1.00) 		1
(1.00)
'5p gain mutation analysis' versus 'CN_CNMF'

P value = 0.000304 (Fisher's exact test), Q value = 0.18

Table S1.  Gene #9: '5p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
5P GAIN MUTATED 3 12 2 18
5P GAIN WILD-TYPE 51 83 66 53

Figure S1.  Get High-res Image Gene #9: '5p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'6p gain mutation analysis' versus 'CN_CNMF'

P value = 2.68e-06 (Fisher's exact test), Q value = 0.0016

Table S2.  Gene #11: '6p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
6P GAIN MUTATED 12 49 11 17
6P GAIN WILD-TYPE 42 46 57 54

Figure S2.  Get High-res Image Gene #11: '6p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'6p gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.14e-06 (Fisher's exact test), Q value = 0.00069

Table S3.  Gene #11: '6p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 71 105 112
6P GAIN MUTATED 34 39 16
6P GAIN WILD-TYPE 37 66 96

Figure S3.  Get High-res Image Gene #11: '6p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'6p gain mutation analysis' versus 'MIRSEQ_CHIERARCHICAL'

P value = 9.96e-05 (Fisher's exact test), Q value = 0.059

Table S4.  Gene #11: '6p gain mutation analysis' versus Clinical Feature #8: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2
ALL 176 106
6P GAIN MUTATED 69 18
6P GAIN WILD-TYPE 107 88

Figure S4.  Get High-res Image Gene #11: '6p gain mutation analysis' versus Clinical Feature #8: 'MIRSEQ_CHIERARCHICAL'

'7p gain mutation analysis' versus 'CN_CNMF'

P value = 3.74e-12 (Fisher's exact test), Q value = 2.3e-09

Table S5.  Gene #13: '7p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
7P GAIN MUTATED 18 40 9 52
7P GAIN WILD-TYPE 36 55 59 19

Figure S5.  Get High-res Image Gene #13: '7p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'7q gain mutation analysis' versus 'CN_CNMF'

P value = 5.82e-11 (Fisher's exact test), Q value = 3.6e-08

Table S6.  Gene #14: '7q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
7Q GAIN MUTATED 18 39 11 52
7Q GAIN WILD-TYPE 36 56 57 19

Figure S6.  Get High-res Image Gene #14: '7q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'7q gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 6.75e-05 (Fisher's exact test), Q value = 0.04

Table S7.  Gene #14: '7q gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 44 81 85 72
7Q GAIN MUTATED 11 30 53 25
7Q GAIN WILD-TYPE 33 51 32 47

Figure S7.  Get High-res Image Gene #14: '7q gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'8p gain mutation analysis' versus 'CN_CNMF'

P value = 0.000343 (Fisher's exact test), Q value = 0.2

Table S8.  Gene #15: '8p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
8P GAIN MUTATED 8 24 3 20
8P GAIN WILD-TYPE 46 71 65 51

Figure S8.  Get High-res Image Gene #15: '8p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'8q gain mutation analysis' versus 'CN_CNMF'

P value = 5.12e-09 (Fisher's exact test), Q value = 3.1e-06

Table S9.  Gene #16: '8q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
8Q GAIN MUTATED 13 44 4 31
8Q GAIN WILD-TYPE 41 51 64 40

Figure S9.  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 = 1.23e-05 (Fisher's exact test), Q value = 0.0074

Table S10.  Gene #16: '8q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 71 105 112
8Q GAIN MUTATED 38 32 22
8Q GAIN WILD-TYPE 33 73 90

Figure S10.  Get High-res Image Gene #16: '8q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'8q gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 8.38e-05 (Fisher's exact test), Q value = 0.049

Table S11.  Gene #16: '8q gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 44 81 85 72
8Q GAIN MUTATED 14 30 38 9
8Q GAIN WILD-TYPE 30 51 47 63

Figure S11.  Get High-res Image Gene #16: '8q gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'13q gain mutation analysis' versus 'CN_CNMF'

P value = 5.6e-10 (Fisher's exact test), Q value = 3.4e-07

Table S12.  Gene #23: '13q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
13Q GAIN MUTATED 6 33 0 6
13Q GAIN WILD-TYPE 48 62 68 65

Figure S12.  Get High-res Image Gene #23: '13q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'13q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.6e-05 (Fisher's exact test), Q value = 0.0096

Table S13.  Gene #23: '13q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 71 105 112
13Q GAIN MUTATED 22 17 6
13Q GAIN WILD-TYPE 49 88 106

Figure S13.  Get High-res Image Gene #23: '13q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'19q gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 0.000253 (Fisher's exact test), Q value = 0.15

Table S14.  Gene #33: '19q gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 44 81 85 72
19Q GAIN MUTATED 1 6 14 0
19Q GAIN WILD-TYPE 43 75 71 72

Figure S14.  Get High-res Image Gene #33: '19q gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'20p gain mutation analysis' versus 'CN_CNMF'

P value = 2.69e-05 (Fisher's exact test), Q value = 0.016

Table S15.  Gene #34: '20p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
20P GAIN MUTATED 9 35 7 28
20P GAIN WILD-TYPE 45 60 61 43

Figure S15.  Get High-res Image Gene #34: '20p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'20p gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 6.15e-05 (Fisher's exact test), Q value = 0.036

Table S16.  Gene #34: '20p gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 44 81 85 72
20P GAIN MUTATED 6 22 39 12
20P GAIN WILD-TYPE 38 59 46 60

Figure S16.  Get High-res Image Gene #34: '20p gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'20q gain mutation analysis' versus 'CN_CNMF'

P value = 3.23e-07 (Fisher's exact test), Q value = 2e-04

Table S17.  Gene #35: '20q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
20Q GAIN MUTATED 14 40 8 38
20Q GAIN WILD-TYPE 40 55 60 33

Figure S17.  Get High-res Image Gene #35: '20q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'21q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000341 (Fisher's exact test), Q value = 0.2

Table S18.  Gene #36: '21q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 71 105 112
21Q GAIN MUTATED 16 11 4
21Q GAIN WILD-TYPE 55 94 108

Figure S18.  Get High-res Image Gene #36: '21q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'22q gain mutation analysis' versus 'CN_CNMF'

P value = 7.71e-06 (Fisher's exact test), Q value = 0.0047

Table S19.  Gene #37: '22q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
22Q GAIN MUTATED 6 16 10 32
22Q GAIN WILD-TYPE 48 79 58 39

Figure S19.  Get High-res Image Gene #37: '22q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'1p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000142 (Fisher's exact test), Q value = 0.083

Table S20.  Gene #39: '1p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 71 105 112
1P LOSS MUTATED 13 5 2
1P LOSS WILD-TYPE 58 100 110

Figure S20.  Get High-res Image Gene #39: '1p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'2p loss mutation analysis' versus 'CN_CNMF'

P value = 0.000322 (Fisher's exact test), Q value = 0.19

Table S21.  Gene #41: '2p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
2P LOSS MUTATED 11 9 0 4
2P LOSS WILD-TYPE 43 86 68 67

Figure S21.  Get High-res Image Gene #41: '2p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'2p loss mutation analysis' versus 'MIRSEQ_CNMF'

P value = 1.56e-05 (Fisher's exact test), Q value = 0.0094

Table S22.  Gene #41: '2p loss mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 122 88 72
2P LOSS MUTATED 21 1 2
2P LOSS WILD-TYPE 101 87 70

Figure S22.  Get High-res Image Gene #41: '2p loss mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

'2q loss mutation analysis' versus 'MIRSEQ_CNMF'

P value = 8.67e-05 (Fisher's exact test), Q value = 0.051

Table S23.  Gene #42: '2q loss mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 122 88 72
2Q LOSS MUTATED 20 1 3
2Q LOSS WILD-TYPE 102 87 69

Figure S23.  Get High-res Image Gene #42: '2q loss mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

'5q loss mutation analysis' versus 'CN_CNMF'

P value = 1.01e-05 (Fisher's exact test), Q value = 0.0061

Table S24.  Gene #48: '5q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
5Q LOSS MUTATED 18 11 3 20
5Q LOSS WILD-TYPE 36 84 65 51

Figure S24.  Get High-res Image Gene #48: '5q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'6q loss mutation analysis' versus 'CN_CNMF'

P value = 1.2e-12 (Fisher's exact test), Q value = 7.4e-10

Table S25.  Gene #50: '6q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
6Q LOSS MUTATED 3 46 11 40
6Q LOSS WILD-TYPE 51 49 57 31

Figure S25.  Get High-res Image Gene #50: '6q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'9p loss mutation analysis' versus 'CN_CNMF'

P value = 1.61e-12 (Fisher's exact test), Q value = 1e-09

Table S26.  Gene #55: '9p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
9P LOSS MUTATED 38 71 13 37
9P LOSS WILD-TYPE 16 24 55 34

Figure S26.  Get High-res Image Gene #55: '9p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'9p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 4.49e-07 (Fisher's exact test), Q value = 0.00027

Table S27.  Gene #55: '9p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 71 105 112
9P LOSS MUTATED 51 68 40
9P LOSS WILD-TYPE 20 37 72

Figure S27.  Get High-res Image Gene #55: '9p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'9p loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 0.000231 (Fisher's exact test), Q value = 0.13

Table S28.  Gene #55: '9p loss mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 44 81 85 72
9P LOSS MUTATED 25 48 60 26
9P LOSS WILD-TYPE 19 33 25 46

Figure S28.  Get High-res Image Gene #55: '9p loss mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'9p loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 7.09e-05 (Fisher's exact test), Q value = 0.042

Table S29.  Gene #55: '9p loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 79 115 88
9P LOSS MUTATED 54 47 58
9P LOSS WILD-TYPE 25 68 30

Figure S29.  Get High-res Image Gene #55: '9p loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

'9q loss mutation analysis' versus 'CN_CNMF'

P value = 0.000154 (Fisher's exact test), Q value = 0.09

Table S30.  Gene #56: '9q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
9Q LOSS MUTATED 26 46 12 31
9Q LOSS WILD-TYPE 28 49 56 40

Figure S30.  Get High-res Image Gene #56: '9q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'10p loss mutation analysis' versus 'CN_CNMF'

P value = 4.96e-13 (Fisher's exact test), Q value = 3.1e-10

Table S31.  Gene #57: '10p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
10P LOSS MUTATED 32 42 4 42
10P LOSS WILD-TYPE 22 53 64 29

Figure S31.  Get High-res Image Gene #57: '10p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'10p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 2.82e-05 (Fisher's exact test), Q value = 0.017

Table S32.  Gene #57: '10p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 71 105 112
10P LOSS MUTATED 41 50 29
10P LOSS WILD-TYPE 30 55 83

Figure S32.  Get High-res Image Gene #57: '10p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'10p loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 2.32e-07 (Fisher's exact test), Q value = 0.00014

Table S33.  Gene #57: '10p loss mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 44 81 85 72
10P LOSS MUTATED 13 38 54 15
10P LOSS WILD-TYPE 31 43 31 57

Figure S33.  Get High-res Image Gene #57: '10p loss mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'10p loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.13e-06 (Fisher's exact test), Q value = 0.0013

Table S34.  Gene #57: '10p loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 79 115 88
10P LOSS MUTATED 36 30 54
10P LOSS WILD-TYPE 43 85 34

Figure S34.  Get High-res Image Gene #57: '10p loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

'10q loss mutation analysis' versus 'CN_CNMF'

P value = 2.18e-13 (Fisher's exact test), Q value = 1.4e-10

Table S35.  Gene #58: '10q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
10Q LOSS MUTATED 36 49 6 44
10Q LOSS WILD-TYPE 18 46 62 27

Figure S35.  Get High-res Image Gene #58: '10q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'10q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 5.77e-06 (Fisher's exact test), Q value = 0.0035

Table S36.  Gene #58: '10q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 71 105 112
10Q LOSS MUTATED 45 57 33
10Q LOSS WILD-TYPE 26 48 79

Figure S36.  Get High-res Image Gene #58: '10q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'10q loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 6.83e-08 (Fisher's exact test), Q value = 4.2e-05

Table S37.  Gene #58: '10q loss mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 44 81 85 72
10Q LOSS MUTATED 16 41 60 18
10Q LOSS WILD-TYPE 28 40 25 54

Figure S37.  Get High-res Image Gene #58: '10q loss mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'10q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1.47e-05 (Fisher's exact test), Q value = 0.0088

Table S38.  Gene #58: '10q loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 79 115 88
10Q LOSS MUTATED 37 39 59
10Q LOSS WILD-TYPE 42 76 29

Figure S38.  Get High-res Image Gene #58: '10q loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

'11p loss mutation analysis' versus 'CN_CNMF'

P value = 5.1e-08 (Fisher's exact test), Q value = 3.1e-05

Table S39.  Gene #59: '11p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
11P LOSS MUTATED 8 16 5 34
11P LOSS WILD-TYPE 46 79 63 37

Figure S39.  Get High-res Image Gene #59: '11p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'11q loss mutation analysis' versus 'CN_CNMF'

P value = 6.12e-06 (Fisher's exact test), Q value = 0.0037

Table S40.  Gene #60: '11q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
11Q LOSS MUTATED 6 21 11 34
11Q LOSS WILD-TYPE 48 74 57 37

Figure S40.  Get High-res Image Gene #60: '11q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'12q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 5.4e-05 (Fisher's exact test), Q value = 0.032

Table S41.  Gene #62: '12q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 71 105 112
12Q LOSS MUTATED 14 15 2
12Q LOSS WILD-TYPE 57 90 110

Figure S41.  Get High-res Image Gene #62: '12q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'14q loss mutation analysis' versus 'CN_CNMF'

P value = 1.79e-08 (Fisher's exact test), Q value = 1.1e-05

Table S42.  Gene #64: '14q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 54 95 68 71
14Q LOSS MUTATED 6 33 1 21
14Q LOSS WILD-TYPE 48 62 67 50

Figure S42.  Get High-res Image Gene #64: '14q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'18p loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 0.000398 (Fisher's exact test), Q value = 0.23

Table S43.  Gene #70: '18p loss mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 44 81 85 72
18P LOSS MUTATED 6 13 29 6
18P LOSS WILD-TYPE 38 68 56 66

Figure S43.  Get High-res Image Gene #70: '18p loss mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'18p loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3.59e-05 (Fisher's exact test), Q value = 0.021

Table S44.  Gene #70: '18p loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 79 115 88
18P LOSS MUTATED 14 10 30
18P LOSS WILD-TYPE 65 105 58

Figure S44.  Get High-res Image Gene #70: '18p loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

Methods & Data
Input

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

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

  • Number of patients = 288

  • Number of significantly arm-level cnvs = 78

  • Number of molecular subtypes = 8

  • 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.

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] 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)
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