Correlation between copy number variations of arm-level result and molecular subtypes
Head and Neck Squamous Cell Carcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C14T6GJT
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C14T6GJT
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 322 patients, 59 significant findings detected with Q value < 0.25.

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

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

  • 3q gain cnv correlated to 'CN_CNMF' and 'METHLYATION_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'.

  • 8p gain cnv correlated to 'CN_CNMF'.

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

  • 9p gain cnv correlated to 'CN_CNMF'.

  • 9q 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'.

  • 18p gain cnv correlated to 'CN_CNMF'.

  • 18q gain cnv correlated to 'CN_CNMF' and '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 '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'.

  • 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', and 'MRNASEQ_CHIERARCHICAL'.

  • 17p loss cnv correlated to 'METHLYATION_CNMF'.

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

  • 21q loss cnv correlated to 'CN_CNMF'.

  • 22q 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, 59 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 78 (24%) 244 1.76e-11
(1.11e-08) 		4.56e-08
(2.81e-05) 		0.33
(1.00) 		0.17
(1.00) 		0.00457
(1.00) 		0.000275
(0.158) 		0.00017
(0.0985) 		0.0977
(1.00)
12p gain 61 (19%) 261 1.97e-07
(0.00012) 		1.89e-05
(0.0113) 		0.949
(1.00) 		0.688
(1.00) 		0.00399
(1.00) 		0.000612
(0.349) 		0.000125
(0.0726) 		0.0687
(1.00)
5q loss 62 (19%) 260 1.67e-10
(1.05e-07) 		2.31e-10
(1.44e-07) 		0.0485
(1.00) 		0.327
(1.00) 		0.0111
(1.00) 		5.52e-05
(0.0325) 		0.00506
(1.00) 		0.55
(1.00)
13q loss 65 (20%) 257 9e-10
(5.62e-07) 		9.48e-10
(5.91e-07) 		0.857
(1.00) 		0.692
(1.00) 		0.0286
(1.00) 		2.38e-05
(0.0141) 		0.0289
(1.00) 		0.0613
(1.00)
16q loss 26 (8%) 296 0.0371
(1.00) 		4.19e-05
(0.0247) 		0.0558
(1.00) 		0.00532
(1.00) 		4.72e-07
(0.000287) 		1.34e-08
(8.26e-06) 		0.0034
(1.00) 		0.0116
(1.00)
2p gain 30 (9%) 292 0.000188
(0.108) 		0.000213
(0.122) 		0.756
(1.00) 		0.946
(1.00) 		0.0219
(1.00) 		0.0361
(1.00) 		0.415
(1.00) 		0.654
(1.00)
3p gain 27 (8%) 295 3.7e-05
(0.0219) 		3.66e-05
(0.0217) 		0.672
(1.00) 		0.182
(1.00) 		0.00158
(0.89) 		0.00182
(1.00) 		0.00414
(1.00) 		0.0814
(1.00)
3q gain 104 (32%) 218 0.000352
(0.201) 		4.03e-05
(0.0238) 		0.201
(1.00) 		0.131
(1.00) 		0.012
(1.00) 		0.0018
(1.00) 		0.000681
(0.388) 		0.149
(1.00)
7p gain 72 (22%) 250 1.12e-06
(0.000679) 		0.000155
(0.0902) 		0.89
(1.00) 		0.875
(1.00) 		0.868
(1.00) 		0.895
(1.00) 		0.485
(1.00) 		0.472
(1.00)
7q gain 45 (14%) 277 6.97e-06
(0.00417) 		1.01e-06
(0.000612) 		0.81
(1.00) 		0.805
(1.00) 		0.275
(1.00) 		0.112
(1.00) 		0.143
(1.00) 		0.186
(1.00)
8q gain 129 (40%) 193 2.25e-07
(0.000137) 		0.00028
(0.16) 		0.798
(1.00) 		0.431
(1.00) 		0.568
(1.00) 		0.651
(1.00) 		0.57
(1.00) 		0.0905
(1.00)
18q gain 20 (6%) 302 0.000241
(0.138) 		0.000177
(0.103) 		0.157
(1.00) 		0.323
(1.00) 		0.0192
(1.00) 		0.0171
(1.00) 		0.00912
(1.00) 		1
(1.00)
20p gain 65 (20%) 257 3.18e-07
(0.000194) 		7.9e-05
(0.0463) 		0.296
(1.00) 		0.149
(1.00) 		0.617
(1.00) 		0.365
(1.00) 		0.535
(1.00) 		0.726
(1.00)
20q gain 70 (22%) 252 3.26e-09
(2.03e-06) 		6.1e-05
(0.0358) 		0.876
(1.00) 		0.753
(1.00) 		0.483
(1.00) 		0.789
(1.00) 		0.985
(1.00) 		0.447
(1.00)
1p loss 16 (5%) 306 5.13e-08
(3.15e-05) 		9.7e-07
(0.000589) 		0.173
(1.00) 		0.0662
(1.00) 		0.0129
(1.00) 		0.0156
(1.00) 		0.0635
(1.00) 		0.338
(1.00)
3p loss 125 (39%) 197 1.86e-12
(1.17e-09) 		1.53e-07
(9.34e-05) 		0.682
(1.00) 		0.861
(1.00) 		0.353
(1.00) 		0.149
(1.00) 		0.0518
(1.00) 		0.472
(1.00)
4q loss 51 (16%) 271 4.08e-09
(2.54e-06) 		5.94e-06
(0.00356) 		0.378
(1.00) 		0.243
(1.00) 		0.0281
(1.00) 		0.00522
(1.00) 		0.00213
(1.00) 		0.036
(1.00)
8p loss 70 (22%) 252 9.25e-05
(0.0539) 		1.39e-05
(0.0083) 		0.976
(1.00) 		1
(1.00) 		0.726
(1.00) 		0.59
(1.00) 		0.131
(1.00) 		0.275
(1.00)
9p loss 89 (28%) 233 9.95e-09
(6.17e-06) 		1.24e-08
(7.7e-06) 		0.384
(1.00) 		0.945
(1.00) 		0.252
(1.00) 		0.0529
(1.00) 		0.00243
(1.00) 		0.077
(1.00)
11q loss 62 (19%) 260 7.49e-09
(4.65e-06) 		7.55e-05
(0.0443) 		0.945
(1.00) 		0.589
(1.00) 		0.0112
(1.00) 		0.0622
(1.00) 		0.302
(1.00) 		0.897
(1.00)
18q loss 91 (28%) 231 2.14e-11
(1.34e-08) 		3.16e-08
(1.95e-05) 		0.29
(1.00) 		0.107
(1.00) 		0.0134
(1.00) 		0.442
(1.00) 		0.106
(1.00) 		0.75
(1.00)
5p gain 82 (25%) 240 2.54e-08
(1.56e-05) 		0.0437
(1.00) 		0.622
(1.00) 		0.562
(1.00) 		0.399
(1.00) 		0.409
(1.00) 		0.71
(1.00) 		0.513
(1.00)
8p gain 49 (15%) 273 7.85e-06
(0.00469) 		0.002
(1.00) 		0.67
(1.00) 		0.18
(1.00) 		0.381
(1.00) 		0.313
(1.00) 		0.287
(1.00) 		0.166
(1.00)
9p gain 38 (12%) 284 0.000203
(0.117) 		0.0595
(1.00) 		0.343
(1.00) 		0.438
(1.00) 		0.288
(1.00) 		0.643
(1.00) 		0.441
(1.00) 		0.946
(1.00)
9q gain 47 (15%) 275 4.33e-06
(0.00261) 		0.0103
(1.00) 		0.355
(1.00) 		0.301
(1.00) 		0.383
(1.00) 		0.191
(1.00) 		0.22
(1.00) 		0.524
(1.00)
14q gain 52 (16%) 270 9.96e-08
(6.11e-05) 		0.0159
(1.00) 		0.19
(1.00) 		0.116
(1.00) 		0.0271
(1.00) 		0.027
(1.00) 		0.0219
(1.00) 		0.113
(1.00)
16p gain 21 (7%) 301 0.00109
(0.614) 		8.45e-05
(0.0493) 		0.0286
(1.00) 		0.123
(1.00) 		0.241
(1.00) 		0.958
(1.00) 		0.706
(1.00) 		0.662
(1.00)
18p gain 52 (16%) 270 4.85e-06
(0.00291) 		0.0581
(1.00) 		0.907
(1.00) 		0.252
(1.00) 		0.114
(1.00) 		0.0049
(1.00) 		0.504
(1.00) 		0.414
(1.00)
22q gain 39 (12%) 283 0.00665
(1.00) 		8.21e-05
(0.0481) 		0.569
(1.00) 		0.417
(1.00) 		0.0775
(1.00) 		0.019
(1.00) 		0.257
(1.00) 		0.527
(1.00)
17p loss 45 (14%) 277 0.249
(1.00) 		1.27e-05
(0.00761) 		0.577
(1.00) 		0.677
(1.00) 		0.637
(1.00) 		0.0218
(1.00) 		0.492
(1.00) 		0.44
(1.00)
21q loss 57 (18%) 265 3.91e-06
(0.00236) 		0.0109
(1.00) 		0.92
(1.00) 		0.318
(1.00) 		0.892
(1.00) 		0.512
(1.00) 		0.181
(1.00) 		0.213
(1.00)
22q loss 25 (8%) 297 3.09e-06
(0.00187) 		0.0305
(1.00) 		0.396
(1.00) 		1
(1.00) 		0.391
(1.00) 		0.772
(1.00) 		0.00213
(1.00) 		0.857
(1.00)
1p gain 12 (4%) 310 0.714
(1.00) 		0.486
(1.00) 		0.229
(1.00) 		0.76
(1.00) 		0.1
(1.00) 		0.221
(1.00) 		0.812
(1.00) 		0.573
(1.00)
1q gain 41 (13%) 281 0.00686
(1.00) 		0.000755
(0.43) 		0.966
(1.00) 		0.234
(1.00) 		0.00748
(1.00) 		0.00279
(1.00) 		0.00692
(1.00) 		0.121
(1.00)
2q gain 20 (6%) 302 0.0152
(1.00) 		0.00347
(1.00) 		0.898
(1.00) 		1
(1.00) 		0.109
(1.00) 		0.157
(1.00) 		0.833
(1.00) 		0.582
(1.00)
4p gain 13 (4%) 309 0.00391
(1.00) 		0.064
(1.00) 		0.292
(1.00) 		1
(1.00) 		0.166
(1.00) 		0.228
(1.00) 		0.35
(1.00) 		0.268
(1.00)
4q gain 9 (3%) 313 0.233
(1.00) 		0.103
(1.00) 		0.295
(1.00) 		1
(1.00) 		0.576
(1.00) 		0.63
(1.00) 		0.917
(1.00) 		0.624
(1.00)
5q gain 28 (9%) 294 0.106
(1.00) 		0.693
(1.00) 		0.825
(1.00) 		0.828
(1.00) 		0.819
(1.00) 		0.461
(1.00) 		0.968
(1.00) 		0.261
(1.00)
6p gain 26 (8%) 296 0.0652
(1.00) 		0.0466
(1.00) 		0.762
(1.00) 		0.496
(1.00) 		0.902
(1.00) 		0.871
(1.00) 		0.9
(1.00) 		1
(1.00)
6q gain 19 (6%) 303 0.0198
(1.00) 		0.0821
(1.00) 		0.46
(1.00) 		0.828
(1.00) 		0.727
(1.00) 		0.378
(1.00) 		0.827
(1.00) 		0.79
(1.00)
10p gain 12 (4%) 310 0.51
(1.00) 		0.00278
(1.00) 		0.189
(1.00) 		0.521
(1.00) 		0.055
(1.00) 		0.0689
(1.00) 		0.256
(1.00) 		0.162
(1.00)
10q gain 6 (2%) 316 0.445
(1.00) 		0.338
(1.00) 		0.737
(1.00) 		0.768
(1.00) 		1
(1.00) 		1
(1.00) 		0.673
(1.00) 		0.75
(1.00)
11p gain 16 (5%) 306 0.00758
(1.00) 		0.67
(1.00) 		1
(1.00) 		0.323
(1.00) 		0.754
(1.00) 		0.845
(1.00) 		0.853
(1.00) 		0.765
(1.00)
11q gain 16 (5%) 306 0.103
(1.00) 		0.407
(1.00) 		0.624
(1.00) 		1
(1.00) 		0.159
(1.00) 		0.295
(1.00) 		0.653
(1.00) 		1
(1.00)
12q gain 25 (8%) 297 0.0107
(1.00) 		0.0021
(1.00) 		1
(1.00) 		0.396
(1.00) 		0.0398
(1.00) 		0.000869
(0.493) 		0.00387
(1.00) 		0.051
(1.00)
13q gain 17 (5%) 305 0.00117
(0.661) 		0.0352
(1.00) 		0.172
(1.00) 		0.805
(1.00) 		0.603
(1.00) 		0.904
(1.00) 		0.498
(1.00) 		0.289
(1.00)
15q gain 13 (4%) 309 0.37
(1.00) 		0.275
(1.00) 		1
(1.00) 		0.433
(1.00) 		0.727
(1.00) 		0.124
(1.00) 		0.489
(1.00) 		0.381
(1.00)
16q gain 28 (9%) 294 0.00831
(1.00) 		0.00423
(1.00) 		0.391
(1.00) 		1
(1.00) 		0.0266
(1.00) 		0.437
(1.00) 		0.607
(1.00) 		0.0884
(1.00)
17p gain 19 (6%) 303 0.00396
(1.00) 		0.0824
(1.00) 		0.888
(1.00) 		0.408
(1.00) 		0.18
(1.00) 		0.561
(1.00) 		0.295
(1.00) 		0.384
(1.00)
17q gain 23 (7%) 299 0.151
(1.00) 		0.0963
(1.00) 		0.275
(1.00) 		0.5
(1.00) 		0.19
(1.00) 		0.0519
(1.00) 		0.256
(1.00) 		0.581
(1.00)
19p gain 12 (4%) 310 0.00306
(1.00) 		0.00495
(1.00) 		0.184
(1.00) 		0.0962
(1.00) 		0.389
(1.00) 		0.0231
(1.00) 		0.194
(1.00) 		0.162
(1.00)
19q gain 21 (7%) 301 0.00591
(1.00) 		0.0581
(1.00) 		0.879
(1.00) 		0.381
(1.00) 		0.158
(1.00) 		0.319
(1.00) 		0.227
(1.00) 		0.389
(1.00)
21q gain 9 (3%) 313 0.089
(1.00) 		0.773
(1.00) 		0.682
(1.00) 		1
(1.00) 		0.0193
(1.00) 		0.0552
(1.00) 		0.269
(1.00) 		0.805
(1.00)
Xq gain 21 (7%) 301 0.00897
(1.00) 		0.109
(1.00) 		0.187
(1.00) 		0.162
(1.00) 		0.333
(1.00) 		0.77
(1.00) 		1
(1.00) 		0.823
(1.00)
2p loss 5 (2%) 317 0.692
(1.00) 		0.0118
(1.00) 		0.12
(1.00) 		1
(1.00) 		0.054
(1.00) 		0.0361
(1.00) 		0.0708
(1.00) 		0.213
(1.00)
2q loss 9 (3%) 313 0.573
(1.00) 		0.0662
(1.00) 		0.0644
(1.00) 		0.424
(1.00) 		0.0313
(1.00) 		0.0258
(1.00) 		0.107
(1.00) 		0.0105
(1.00)
3q loss 21 (7%) 301 0.0665
(1.00) 		0.115
(1.00) 		0.642
(1.00) 		0.453
(1.00) 		0.881
(1.00) 		0.959
(1.00) 		0.174
(1.00) 		0.549
(1.00)
5p loss 10 (3%) 312 0.00274
(1.00) 		0.00367
(1.00) 		0.727
(1.00) 		1
(1.00) 		0.287
(1.00) 		0.399
(1.00) 		0.0371
(1.00) 		1
(1.00)
6p loss 19 (6%) 303 0.135
(1.00) 		0.0127
(1.00) 		0.1
(1.00) 		0.116
(1.00) 		0.0317
(1.00) 		0.111
(1.00) 		0.0286
(1.00) 		0.106
(1.00)
6q loss 21 (7%) 301 0.237
(1.00) 		0.0701
(1.00) 		0.0474
(1.00) 		0.0529
(1.00) 		0.379
(1.00) 		0.392
(1.00) 		0.107
(1.00) 		0.0875
(1.00)
7p loss 5 (2%) 317 0.121
(1.00) 		0.388
(1.00) 		0.391
(1.00) 		0.452
(1.00) 		0.014
(1.00) 		1
(1.00)
7q loss 9 (3%) 313 0.0454
(1.00) 		0.161
(1.00) 		1
(1.00) 		0.74
(1.00) 		0.363
(1.00) 		0.694
(1.00) 		0.0878
(1.00) 		0.0692
(1.00)
8q loss 6 (2%) 316 0.153
(1.00) 		0.105
(1.00) 		0.638
(1.00) 		0.768
(1.00) 		1
(1.00) 		0.515
(1.00) 		0.881
(1.00) 		1
(1.00)
9q loss 31 (10%) 291 0.00846
(1.00) 		0.0679
(1.00) 		0.785
(1.00) 		0.496
(1.00) 		0.829
(1.00) 		0.855
(1.00) 		0.704
(1.00) 		0.00233
(1.00)
10p loss 47 (15%) 275 0.0107
(1.00) 		0.0719
(1.00) 		0.605
(1.00) 		0.446
(1.00) 		0.858
(1.00) 		0.751
(1.00) 		0.27
(1.00) 		0.393
(1.00)
10q loss 26 (8%) 296 0.0113
(1.00) 		0.00296
(1.00) 		0.893
(1.00) 		0.475
(1.00) 		0.0306
(1.00) 		0.00107
(0.607) 		0.00713
(1.00) 		0.258
(1.00)
11p loss 41 (13%) 281 0.000893
(0.506) 		0.0444
(1.00) 		0.688
(1.00) 		0.807
(1.00) 		0.00173
(0.974) 		0.00598
(1.00) 		0.0392
(1.00) 		0.406
(1.00)
12p loss 12 (4%) 310 0.0418
(1.00) 		0.139
(1.00) 		0.338
(1.00) 		0.199
(1.00) 		0.468
(1.00) 		0.459
(1.00) 		0.342
(1.00) 		0.41
(1.00)
12q loss 8 (2%) 314 0.197
(1.00) 		0.073
(1.00) 		0.614
(1.00) 		0.666
(1.00) 		0.201
(1.00) 		0.308
(1.00) 		0.605
(1.00) 		0.0107
(1.00)
14q loss 16 (5%) 306 0.121
(1.00) 		0.0415
(1.00) 		0.37
(1.00) 		0.726
(1.00) 		0.0108
(1.00) 		0.0154
(1.00) 		0.144
(1.00) 		0.338
(1.00)
15q loss 23 (7%) 299 0.1
(1.00) 		0.136
(1.00) 		0.42
(1.00) 		0.15
(1.00) 		0.708
(1.00) 		0.36
(1.00) 		0.325
(1.00) 		0.522
(1.00)
16p loss 12 (4%) 310 0.597
(1.00) 		0.0294
(1.00) 		0.078
(1.00) 		0.274
(1.00) 		0.0414
(1.00) 		0.014
(1.00) 		0.1
(1.00) 		0.106
(1.00)
17q loss 5 (2%) 317 0.21
(1.00) 		0.00402
(1.00) 		0.119
(1.00) 		0.666
(1.00) 		0.148
(1.00) 		0.386
(1.00) 		0.524
(1.00) 		0.108
(1.00)
18p loss 29 (9%) 293 0.007
(1.00) 		0.0243
(1.00) 		0.764
(1.00) 		0.492
(1.00) 		0.578
(1.00) 		0.747
(1.00) 		0.225
(1.00) 		0.654
(1.00)
19p loss 27 (8%) 295 0.0198
(1.00) 		0.113
(1.00) 		0.598
(1.00) 		0.875
(1.00) 		0.118
(1.00) 		0.416
(1.00) 		0.549
(1.00) 		0.488
(1.00)
19q loss 20 (6%) 302 0.0314
(1.00) 		0.18
(1.00) 		0.531
(1.00) 		0.519
(1.00) 		0.694
(1.00) 		0.833
(1.00) 		0.277
(1.00) 		0.814
(1.00)
20p loss 21 (7%) 301 0.0544
(1.00) 		0.319
(1.00) 		0.518
(1.00) 		0.815
(1.00) 		0.224
(1.00) 		0.0904
(1.00) 		0.333
(1.00) 		0.204
(1.00)
20q loss 10 (3%) 312 0.0389
(1.00) 		0.212
(1.00) 		0.638
(1.00) 		0.601
(1.00) 		0.0359
(1.00) 		0.0468
(1.00) 		0.512
(1.00) 		0.659
(1.00)
Xq loss 8 (2%) 314 0.328
(1.00) 		0.122
(1.00) 		0.194
(1.00) 		0.341
(1.00) 		0.499
(1.00) 		1
(1.00) 		0.497
(1.00) 		0.221
(1.00)
'2p gain mutation analysis' versus 'CN_CNMF'

P value = 0.000188 (Chi-square test), Q value = 0.11

Table S1.  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 CLUS_7
ALL 66 41 46 85 22 10 52
2P GAIN MUTATED 12 8 5 1 4 0 0
2P GAIN WILD-TYPE 54 33 41 84 18 10 52

Figure S1.  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 = 0.000213 (Chi-square test), Q value = 0.12

Table S2.  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 12 1 1 0
2P GAIN WILD-TYPE 34 41 39 44 46 50 3 19

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

'3p gain mutation analysis' versus 'CN_CNMF'

P value = 3.7e-05 (Chi-square test), Q value = 0.022

Table S3.  Gene #5: '3p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 66 41 46 85 22 10 52
3P GAIN MUTATED 3 2 7 5 3 5 2
3P GAIN WILD-TYPE 63 39 39 80 19 5 50

Figure S3.  Get High-res Image Gene #5: '3p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'3p gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 3.66e-05 (Chi-square test), Q value = 0.022

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 2 0 13 5 1 0 1
3P GAIN WILD-TYPE 39 45 39 32 53 50 4 18

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

'3q gain mutation analysis' versus 'CN_CNMF'

P value = 0.000352 (Chi-square test), Q value = 0.2

Table S5.  Gene #6: '3q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 66 41 46 85 22 10 52
3Q GAIN MUTATED 20 17 21 20 9 8 9
3Q GAIN WILD-TYPE 46 24 25 65 13 2 43

Figure S5.  Get High-res Image Gene #6: '3q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'3q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 4.03e-05 (Chi-square test), Q value = 0.024

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 15 6 23 25 6 2 3
3Q GAIN WILD-TYPE 23 32 33 22 33 45 2 16

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

'5p gain mutation analysis' versus 'CN_CNMF'

P value = 2.54e-08 (Chi-square test), Q value = 1.6e-05

Table S7.  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 CLUS_7
ALL 66 41 46 85 22 10 52
5P GAIN MUTATED 18 12 11 14 18 3 6
5P GAIN WILD-TYPE 48 29 35 71 4 7 46

Figure S7.  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 = 1.12e-06 (Chi-square test), Q value = 0.00068

Table S8.  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 CLUS_7
ALL 66 41 46 85 22 10 52
7P GAIN MUTATED 20 19 16 9 5 1 2
7P GAIN WILD-TYPE 46 22 30 76 17 9 50

Figure S8.  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 = 0.000155 (Chi-square test), Q value = 0.09

Table S9.  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 2 1 3
7P GAIN WILD-TYPE 28 35 27 42 37 49 3 16

Figure S9.  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 = 6.97e-06 (Chi-square test), Q value = 0.0042

Table S10.  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 CLUS_7
ALL 66 41 46 85 22 10 52
7Q GAIN MUTATED 13 10 15 5 2 0 0
7Q GAIN WILD-TYPE 53 31 31 80 20 10 52

Figure S10.  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 S11.  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 S11.  Get High-res Image Gene #14: '7q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'8p gain mutation analysis' versus 'CN_CNMF'

P value = 7.85e-06 (Chi-square test), Q value = 0.0047

Table S12.  Gene #15: '8p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 66 41 46 85 22 10 52
8P GAIN MUTATED 6 9 8 10 6 7 3
8P GAIN WILD-TYPE 60 32 38 75 16 3 49

Figure S12.  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 = 2.25e-07 (Chi-square test), Q value = 0.00014

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 CLUS_7
ALL 66 41 46 85 22 10 52
8Q GAIN MUTATED 31 25 15 16 14 9 19
8Q GAIN WILD-TYPE 35 16 31 69 8 1 33

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 = 0.00028 (Chi-square test), Q value = 0.16

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 24 19 14 22 8 4 9
8Q GAIN WILD-TYPE 20 23 20 31 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 = 0.000203 (Chi-square test), Q value = 0.12

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 CLUS_7
ALL 66 41 46 85 22 10 52
9P GAIN MUTATED 6 4 6 9 0 6 7
9P GAIN WILD-TYPE 60 37 40 76 22 4 45

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

'9q gain mutation analysis' versus 'CN_CNMF'

P value = 4.33e-06 (Chi-square test), Q value = 0.0026

Table S16.  Gene #18: '9q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 66 41 46 85 22 10 52
9Q GAIN MUTATED 10 3 7 8 0 7 12
9Q GAIN WILD-TYPE 56 38 39 77 22 3 40

Figure S16.  Get High-res Image Gene #18: '9q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'12p gain mutation analysis' versus 'CN_CNMF'

P value = 1.97e-07 (Chi-square test), Q value = 0.00012

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 CLUS_7
ALL 66 41 46 85 22 10 52
12P GAIN MUTATED 8 15 18 7 7 4 2
12P GAIN WILD-TYPE 58 26 28 78 15 6 50

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 = 0.000125 (Fisher's exact test), Q value = 0.073

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 101 127 93
12P GAIN MUTATED 12 39 10
12P GAIN WILD-TYPE 89 88 83

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 = 9.96e-08 (Chi-square test), Q value = 6.1e-05

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 CLUS_7
ALL 66 41 46 85 22 10 52
14Q GAIN MUTATED 16 17 7 1 2 4 5
14Q GAIN WILD-TYPE 50 24 39 84 20 6 47

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 = 0.049

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'

'18p gain mutation analysis' versus 'CN_CNMF'

P value = 4.85e-06 (Chi-square test), Q value = 0.0029

Table S22.  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 CLUS_7
ALL 66 41 46 85 22 10 52
18P GAIN MUTATED 11 10 11 5 7 6 2
18P GAIN WILD-TYPE 55 31 35 80 15 4 50

Figure S22.  Get High-res Image Gene #32: '18p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'18q gain mutation analysis' versus 'CN_CNMF'

P value = 0.000241 (Chi-square test), Q value = 0.14

Table S23.  Gene #33: '18q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 66 41 46 85 22 10 52
18Q GAIN MUTATED 3 1 8 5 0 3 0
18Q GAIN WILD-TYPE 63 40 38 80 22 7 52

Figure S23.  Get High-res Image Gene #33: '18q 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 = 3.18e-07 (Chi-square test), Q value = 0.00019

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 CLUS_7
ALL 66 41 46 85 22 10 52
20P GAIN MUTATED 12 21 11 6 8 1 6
20P GAIN WILD-TYPE 54 20 35 79 14 9 46

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 = 0.046

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 = 3.26e-09 (Chi-square test), Q value = 2e-06

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 CLUS_7
ALL 66 41 46 85 22 10 52
20Q GAIN MUTATED 14 23 11 5 9 3 5
20Q GAIN WILD-TYPE 52 18 35 80 13 7 47

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 = 6.1e-05 (Chi-square test), Q value = 0.036

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 18 5 6 16 2 3 4
20Q GAIN WILD-TYPE 29 29 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 'METHLYATION_CNMF'

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

Table S29.  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 S29.  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 = 5.13e-08 (Chi-square test), Q value = 3.1e-05

Table S30.  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 CLUS_7
ALL 66 41 46 85 22 10 52
1P LOSS MUTATED 2 3 11 0 0 0 0
1P LOSS WILD-TYPE 64 38 35 85 22 10 52

Figure S30.  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 S31.  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 S31.  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 = 1.86e-12 (Chi-square test), Q value = 1.2e-09

Table S32.  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 CLUS_7
ALL 66 41 46 85 22 10 52
3P LOSS MUTATED 36 20 25 3 15 3 23
3P LOSS WILD-TYPE 30 21 21 82 7 7 29

Figure S32.  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 = 1.53e-07 (Chi-square test), Q value = 9.3e-05

Table S33.  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 21 15 10 34 3 2 11
3P LOSS WILD-TYPE 21 26 24 35 24 48 2 8

Figure S33.  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 = 1.76e-11 (Chi-square test), Q value = 1.1e-08

Table S34.  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 CLUS_7
ALL 66 41 46 85 22 10 52
4P LOSS MUTATED 21 16 27 5 4 0 5
4P LOSS WILD-TYPE 45 25 19 80 18 10 47

Figure S34.  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 = 4.56e-08 (Chi-square test), Q value = 2.8e-05

Table S35.  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 8 12 31 1 1 3
4P LOSS WILD-TYPE 31 42 31 33 27 50 3 16

Figure S35.  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 = 0.000275 (Fisher's exact test), Q value = 0.16

Table S36.  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 10 43
4P LOSS WILD-TYPE 75 74 77

Figure S36.  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 = 0.00017 (Fisher's exact test), Q value = 0.098

Table S37.  Gene #46: '4p loss mutation analysis' versus Clinical Feature #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 101 127 93
4P LOSS MUTATED 20 46 12
4P LOSS WILD-TYPE 81 81 81

Figure S37.  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 = 4.08e-09 (Chi-square test), Q value = 2.5e-06

Table S38.  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 CLUS_7
ALL 66 41 46 85 22 10 52
4Q LOSS MUTATED 7 10 21 3 6 1 3
4Q LOSS WILD-TYPE 59 31 25 82 16 9 49

Figure S38.  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 = 5.94e-06 (Chi-square test), Q value = 0.0036

Table S39.  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 5 6 22 0 0 0
4Q LOSS WILD-TYPE 33 40 34 39 36 51 4 19

Figure S39.  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 = 1.67e-10 (Chi-square test), Q value = 1e-07

Table S40.  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 CLUS_7
ALL 66 41 46 85 22 10 52
5Q LOSS MUTATED 13 13 23 1 7 1 4
5Q LOSS WILD-TYPE 53 28 23 84 15 9 48

Figure S40.  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 = 2.31e-10 (Chi-square test), Q value = 1.4e-07

Table S41.  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 20 11 1 4 23 0 0 2
5Q LOSS WILD-TYPE 23 36 38 41 35 51 4 17

Figure S41.  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 = 5.52e-05 (Fisher's exact test), Q value = 0.033

Table S42.  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 17 6 38
5Q LOSS WILD-TYPE 78 78 82

Figure S42.  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 = 9.25e-05 (Chi-square test), Q value = 0.054

Table S43.  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 CLUS_7
ALL 66 41 46 85 22 10 52
8P LOSS MUTATED 24 10 9 3 7 2 15
8P LOSS WILD-TYPE 42 31 37 82 15 8 37

Figure S43.  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 = 1.39e-05 (Chi-square test), Q value = 0.0083

Table S44.  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 5 12 1 0 2
8P LOSS WILD-TYPE 34 29 23 40 46 50 4 17

Figure S44.  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 = 9.95e-09 (Chi-square test), Q value = 6.2e-06

Table S45.  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 CLUS_7
ALL 66 41 46 85 22 10 52
9P LOSS MUTATED 20 18 20 2 12 1 16
9P LOSS WILD-TYPE 46 23 26 83 10 9 36

Figure S45.  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 = 1.24e-08 (Chi-square test), Q value = 7.7e-06

Table S46.  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 26 1 2 5
9P LOSS WILD-TYPE 19 35 30 40 32 50 2 14

Figure S46.  Get High-res Image Gene #56: '9p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'11q loss mutation analysis' versus 'CN_CNMF'

P value = 7.49e-09 (Chi-square test), Q value = 4.7e-06

Table S47.  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 CLUS_7
ALL 66 41 46 85 22 10 52
11Q LOSS MUTATED 31 2 12 10 2 1 4
11Q LOSS WILD-TYPE 35 39 34 75 20 9 48

Figure S47.  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 = 7.55e-05 (Chi-square test), Q value = 0.044

Table S48.  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 13 1 1 3
11Q LOSS WILD-TYPE 38 41 28 26 45 50 3 16

Figure S48.  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 = 9e-10 (Chi-square test), Q value = 5.6e-07

Table S49.  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 CLUS_7
ALL 66 41 46 85 22 10 52
13Q LOSS MUTATED 13 9 26 7 6 0 4
13Q LOSS WILD-TYPE 53 32 20 78 16 10 48

Figure S49.  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 S50.  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 S50.  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 S51.  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 S51.  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 S52.  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 S52.  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 S53.  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 S53.  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 = 8.3e-06

Table S54.  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 S54.  Get High-res Image Gene #68: '16q loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

'17p loss mutation analysis' versus 'METHLYATION_CNMF'

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

Table S55.  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 S55.  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 = 2.14e-11 (Chi-square test), Q value = 1.3e-08

Table S56.  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 CLUS_7
ALL 66 41 46 85 22 10 52
18Q LOSS MUTATED 23 24 8 1 10 5 20
18Q LOSS WILD-TYPE 43 17 38 84 12 5 32

Figure S56.  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 = 3.16e-08 (Chi-square test), Q value = 1.9e-05

Table S57.  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 23 14 2 15 3 3 5
18Q LOSS WILD-TYPE 23 24 25 43 43 48 1 14

Figure S57.  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 = 3.91e-06 (Chi-square test), Q value = 0.0024

Table S58.  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 CLUS_7
ALL 66 41 46 85 22 10 52
21Q LOSS MUTATED 14 9 18 0 3 3 10
21Q LOSS WILD-TYPE 52 32 28 85 19 7 42

Figure S58.  Get High-res Image Gene #77: '21q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'22q loss mutation analysis' versus 'CN_CNMF'

P value = 3.09e-06 (Chi-square test), Q value = 0.0019

Table S59.  Gene #78: '22q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 66 41 46 85 22 10 52
22Q LOSS MUTATED 4 5 0 2 8 0 6
22Q LOSS WILD-TYPE 62 36 46 83 14 10 46

Figure S59.  Get High-res Image Gene #78: '22q 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 = 322

  • 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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle