Correlation between copy number variations of arm-level result and molecular subtypes
Ovarian Serous Cystadenocarcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C12J6997
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C12J6997
Overview
Introduction

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

Summary

Testing the association between copy number variation 80 arm-level events and 14 molecular subtypes across 569 patients, 49 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 1q gain cnv correlated to 'CN_CNMF'.

  • 2p gain cnv correlated to 'MRNA_CNMF',  'MRNA_CHIERARCHICAL',  'MIR_CHIERARCHICAL',  'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.

  • 2q gain cnv correlated to 'MRNA_CHIERARCHICAL',  'CN_CNMF', and 'METHLYATION_CNMF'.

  • 3q gain cnv correlated to 'CN_CNMF'.

  • 5p gain cnv correlated to 'CN_CNMF'.

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

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

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

  • 7q gain cnv correlated to 'CN_CNMF'.

  • 10p gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

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

  • 12q gain cnv correlated to 'MRNA_CHIERARCHICAL',  'CN_CNMF', and 'METHLYATION_CNMF'.

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

  • 19p gain cnv correlated to 'CN_CNMF'.

  • 19q gain cnv correlated to 'CN_CNMF'.

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

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

  • 3p loss cnv correlated to 'CN_CNMF'.

  • 5p loss cnv correlated to 'MRNASEQ_CNMF'.

  • 5q loss cnv correlated to 'METHLYATION_CNMF'.

  • 9q loss cnv correlated to 'CN_CNMF'.

  • 13q loss cnv correlated to 'METHLYATION_CNMF'.

  • 14q loss cnv correlated to 'CN_CNMF'.

  • 15q loss cnv correlated to 'MIR_CNMF',  'CN_CNMF', and 'METHLYATION_CNMF'.

  • 17q loss cnv correlated to 'MIRSEQ_MATURE_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 80 arm-level events and 14 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 49 significant findings detected.

Clinical
Features 		MRNA
CNMF 		MRNA
CHIERARCHICAL 		MIR
CNMF 		MIR
CHIERARCHICAL 		CN
CNMF 		METHLYATION
CNMF 		RPPA
CNMF 		RPPA
CHIERARCHICAL 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL 		MIRSEQ
MATURE
CNMF 		MIRSEQ
MATURE
CHIERARCHICAL
nCNV (%) nWild-Type Fisher's exact test Fisher's exact test Fisher's exact test 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 Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
2p gain 178 (31%) 391 1.48e-06
(0.00163) 		1.96e-06
(0.00216) 		0.811
(1.00) 		0.000101
(0.109) 		2.36e-11
(2.62e-08) 		1.32e-07
(0.000147) 		0.0376
(1.00) 		0.285
(1.00) 		0.000127
(0.137) 		0.0072
(1.00) 		0.812
(1.00) 		0.264
(1.00) 		0.797
(1.00) 		0.299
(1.00)
12p gain 250 (44%) 319 4.4e-05
(0.0478) 		8.88e-05
(0.0961) 		0.744
(1.00) 		0.000726
(0.771) 		1.05e-13
(1.18e-10) 		1.84e-07
(0.000203) 		0.299
(1.00) 		0.565
(1.00) 		0.000383
(0.41) 		0.00426
(1.00) 		0.183
(1.00) 		0.307
(1.00) 		0.297
(1.00) 		0.137
(1.00)
20q gain 320 (56%) 249 8.76e-06
(0.0096) 		0.00146
(1.00) 		0.67
(1.00) 		0.000204
(0.219) 		4.5e-15
(5.04e-12) 		2.58e-10
(2.87e-07) 		0.659
(1.00) 		0.0232
(1.00) 		0.00896
(1.00) 		0.843
(1.00) 		0.259
(1.00) 		0.924
(1.00) 		0.668
(1.00) 		0.483
(1.00)
2q gain 150 (26%) 419 0.000417
(0.446) 		1.82e-05
(0.0199) 		0.979
(1.00) 		0.00325
(1.00) 		4.42e-09
(4.91e-06) 		0.000143
(0.154) 		0.0979
(1.00) 		0.716
(1.00) 		0.0037
(1.00) 		0.0188
(1.00) 		0.606
(1.00) 		0.869
(1.00) 		0.108
(1.00) 		0.131
(1.00)
12q gain 174 (31%) 395 0.00627
(1.00) 		5.09e-05
(0.0552) 		0.644
(1.00) 		0.339
(1.00) 		2.04e-12
(2.28e-09) 		5.49e-06
(0.00602) 		0.0258
(1.00) 		0.263
(1.00) 		0.00189
(1.00) 		0.00415
(1.00) 		0.102
(1.00) 		0.11
(1.00) 		0.571
(1.00) 		0.122
(1.00)
13q gain 60 (11%) 509 0.00641
(1.00) 		0.0352
(1.00) 		0.568
(1.00) 		3.21e-05
(0.035) 		0.000125
(0.135) 		4.9e-06
(0.00538) 		0.577
(1.00) 		0.453
(1.00) 		0.246
(1.00) 		0.826
(1.00) 		0.188
(1.00) 		1
(1.00) 		0.954
(1.00) 		0.911
(1.00)
15q loss 276 (49%) 293 0.00043
(0.459) 		0.00118
(1.00) 		0.000104
(0.113) 		0.000634
(0.674) 		4.31e-12
(4.81e-09) 		3.98e-07
(0.000439) 		0.371
(1.00) 		0.413
(1.00) 		0.0656
(1.00) 		0.839
(1.00) 		0.0069
(1.00) 		0.288
(1.00) 		0.03
(1.00) 		0.00102
(1.00)
6p gain 166 (29%) 403 0.51
(1.00) 		0.137
(1.00) 		0.897
(1.00) 		0.0871
(1.00) 		1.38e-06
(0.00152) 		8.61e-05
(0.0933) 		0.86
(1.00) 		0.144
(1.00) 		0.158
(1.00) 		0.842
(1.00) 		0.35
(1.00) 		0.59
(1.00) 		0.441
(1.00) 		0.22
(1.00)
6q gain 96 (17%) 473 0.648
(1.00) 		0.0973
(1.00) 		0.819
(1.00) 		0.174
(1.00) 		3.06e-07
(0.000339) 		1.35e-05
(0.0148) 		0.802
(1.00) 		0.677
(1.00) 		0.00499
(1.00) 		0.261
(1.00) 		0.195
(1.00) 		0.253
(1.00) 		0.467
(1.00) 		0.0705
(1.00)
7p gain 181 (32%) 388 0.623
(1.00) 		0.861
(1.00) 		0.0716
(1.00) 		0.156
(1.00) 		7.57e-07
(0.000835) 		0.00011
(0.118) 		0.505
(1.00) 		0.38
(1.00) 		0.561
(1.00) 		0.47
(1.00) 		0.921
(1.00) 		0.303
(1.00) 		0.366
(1.00) 		0.62
(1.00)
10p gain 184 (32%) 385 0.00442
(1.00) 		0.0622
(1.00) 		0.671
(1.00) 		0.0299
(1.00) 		1.45e-10
(1.61e-07) 		0.000174
(0.186) 		0.974
(1.00) 		0.241
(1.00) 		0.0112
(1.00) 		0.467
(1.00) 		0.543
(1.00) 		0.625
(1.00) 		0.507
(1.00) 		0.221
(1.00)
20p gain 282 (50%) 287 0.00138
(1.00) 		0.00614
(1.00) 		0.718
(1.00) 		0.000615
(0.654) 		1e-11
(1.12e-08) 		2.73e-08
(3.03e-05) 		0.337
(1.00) 		0.22
(1.00) 		0.00273
(1.00) 		0.338
(1.00) 		0.224
(1.00) 		0.918
(1.00) 		0.602
(1.00) 		0.706
(1.00)
1q gain 218 (38%) 351 0.776
(1.00) 		0.348
(1.00) 		0.705
(1.00) 		0.147
(1.00) 		9.78e-08
(0.000108) 		0.00574
(1.00) 		0.456
(1.00) 		0.992
(1.00) 		0.436
(1.00) 		0.567
(1.00) 		0.205
(1.00) 		0.35
(1.00) 		0.113
(1.00) 		0.179
(1.00)
3q gain 268 (47%) 301 0.971
(1.00) 		0.78
(1.00) 		0.251
(1.00) 		0.6
(1.00) 		3.53e-06
(0.00388) 		0.0188
(1.00) 		0.585
(1.00) 		0.339
(1.00) 		0.698
(1.00) 		0.643
(1.00) 		0.183
(1.00) 		0.149
(1.00) 		0.119
(1.00) 		0.4
(1.00)
5p gain 196 (34%) 373 0.586
(1.00) 		0.986
(1.00) 		0.854
(1.00) 		0.663
(1.00) 		6.79e-05
(0.0737) 		0.194
(1.00) 		0.483
(1.00) 		0.246
(1.00) 		0.123
(1.00) 		0.443
(1.00) 		0.23
(1.00) 		0.55
(1.00) 		0.621
(1.00) 		0.0525
(1.00)
7q gain 198 (35%) 371 0.646
(1.00) 		0.267
(1.00) 		0.297
(1.00) 		0.556
(1.00) 		1.69e-05
(0.0185) 		0.00145
(1.00) 		0.448
(1.00) 		0.199
(1.00) 		0.919
(1.00) 		0.691
(1.00) 		0.148
(1.00) 		0.748
(1.00) 		0.0543
(1.00) 		0.739
(1.00)
19p gain 167 (29%) 402 0.0676
(1.00) 		0.181
(1.00) 		0.566
(1.00) 		0.739
(1.00) 		4.18e-05
(0.0455) 		0.0295
(1.00) 		0.0556
(1.00) 		0.632
(1.00) 		0.232
(1.00) 		0.484
(1.00) 		0.376
(1.00) 		0.2
(1.00) 		0.545
(1.00) 		0.809
(1.00)
19q gain 160 (28%) 409 0.208
(1.00) 		0.456
(1.00) 		0.861
(1.00) 		0.474
(1.00) 		4.54e-06
(0.00499) 		0.0989
(1.00) 		0.485
(1.00) 		0.896
(1.00) 		0.208
(1.00) 		0.257
(1.00) 		0.269
(1.00) 		0.152
(1.00) 		0.443
(1.00) 		0.903
(1.00)
3p loss 95 (17%) 474 0.0406
(1.00) 		0.0268
(1.00) 		0.886
(1.00) 		0.0202
(1.00) 		0.000106
(0.114) 		0.0027
(1.00) 		0.63
(1.00) 		0.293
(1.00) 		0.0595
(1.00) 		0.857
(1.00) 		0.127
(1.00) 		0.943
(1.00) 		0.909
(1.00) 		0.00194
(1.00)
5p loss 129 (23%) 440 0.0942
(1.00) 		0.0877
(1.00) 		0.489
(1.00) 		0.00453
(1.00) 		0.0209
(1.00) 		0.00675
(1.00) 		0.108
(1.00) 		0.677
(1.00) 		0.000137
(0.147) 		0.51
(1.00) 		0.654
(1.00) 		0.524
(1.00) 		0.384
(1.00) 		0.0512
(1.00)
5q loss 218 (38%) 351 0.00053
(0.564) 		0.03
(1.00) 		0.766
(1.00) 		0.00222
(1.00) 		0.000885
(0.937) 		1.41e-07
(0.000156) 		0.0452
(1.00) 		0.204
(1.00) 		0.00101
(1.00) 		0.647
(1.00) 		0.54
(1.00) 		0.6
(1.00) 		0.297
(1.00) 		0.439
(1.00)
9q loss 280 (49%) 289 0.00515
(1.00) 		0.0375
(1.00) 		0.222
(1.00) 		0.0113
(1.00) 		2.19e-12
(2.45e-09) 		0.00367
(1.00) 		0.585
(1.00) 		1
(1.00) 		0.00444
(1.00) 		0.407
(1.00) 		0.183
(1.00) 		0.178
(1.00) 		0.251
(1.00) 		0.0929
(1.00)
13q loss 303 (53%) 266 0.0343
(1.00) 		0.0425
(1.00) 		0.787
(1.00) 		0.182
(1.00) 		0.00605
(1.00) 		1.36e-05
(0.0149) 		0.01
(1.00) 		0.0182
(1.00) 		0.472
(1.00) 		0.978
(1.00) 		0.253
(1.00) 		0.825
(1.00) 		0.0938
(1.00) 		0.948
(1.00)
14q loss 208 (37%) 361 0.21
(1.00) 		0.101
(1.00) 		0.974
(1.00) 		0.908
(1.00) 		1.35e-05
(0.0147) 		0.00323
(1.00) 		0.971
(1.00) 		0.812
(1.00) 		0.00383
(1.00) 		0.148
(1.00) 		0.798
(1.00) 		0.797
(1.00) 		0.97
(1.00) 		0.45
(1.00)
17q loss 376 (66%) 193 0.0591
(1.00) 		0.039
(1.00) 		0.0263
(1.00) 		0.577
(1.00) 		0.968
(1.00) 		0.505
(1.00) 		0.432
(1.00) 		0.209
(1.00) 		0.47
(1.00) 		0.423
(1.00) 		0.0562
(1.00) 		0.418
(1.00) 		7.66e-05
(0.083) 		0.779
(1.00)
1p gain 166 (29%) 403 0.105
(1.00) 		0.176
(1.00) 		0.12
(1.00) 		0.249
(1.00) 		0.00241
(1.00) 		0.155
(1.00) 		0.0875
(1.00) 		0.619
(1.00) 		0.601
(1.00) 		0.797
(1.00) 		0.215
(1.00) 		0.885
(1.00) 		0.155
(1.00) 		0.231
(1.00)
3p gain 154 (27%) 415 0.337
(1.00) 		0.658
(1.00) 		0.0431
(1.00) 		0.554
(1.00) 		0.013
(1.00) 		0.839
(1.00) 		1
(1.00) 		0.896
(1.00) 		0.772
(1.00) 		0.436
(1.00) 		0.916
(1.00) 		0.406
(1.00) 		0.9
(1.00) 		0.135
(1.00)
4p gain 57 (10%) 512 0.243
(1.00) 		0.246
(1.00) 		0.00516
(1.00) 		0.319
(1.00) 		0.128
(1.00) 		0.117
(1.00) 		0.472
(1.00) 		0.182
(1.00) 		0.595
(1.00) 		0.439
(1.00) 		0.323
(1.00) 		0.0619
(1.00) 		0.574
(1.00) 		0.0897
(1.00)
4q gain 32 (6%) 537 0.657
(1.00) 		0.767
(1.00) 		0.155
(1.00) 		0.577
(1.00) 		0.0351
(1.00) 		0.0176
(1.00) 		0.274
(1.00) 		0.607
(1.00) 		0.774
(1.00) 		0.514
(1.00) 		0.376
(1.00) 		0.00672
(1.00) 		0.482
(1.00) 		0.404
(1.00)
5q gain 60 (11%) 509 0.0829
(1.00) 		0.222
(1.00) 		0.799
(1.00) 		0.502
(1.00) 		0.499
(1.00) 		0.507
(1.00) 		0.424
(1.00) 		0.242
(1.00) 		0.735
(1.00) 		0.49
(1.00) 		0.498
(1.00) 		0.603
(1.00) 		0.646
(1.00) 		0.495
(1.00)
8p gain 117 (21%) 452 0.0685
(1.00) 		0.0128
(1.00) 		0.298
(1.00) 		0.0193
(1.00) 		0.714
(1.00) 		0.796
(1.00) 		0.131
(1.00) 		0.175
(1.00) 		0.61
(1.00) 		0.656
(1.00) 		0.106
(1.00) 		0.126
(1.00) 		0.175
(1.00) 		0.0639
(1.00)
8q gain 238 (42%) 331 0.0206
(1.00) 		0.00665
(1.00) 		0.061
(1.00) 		0.119
(1.00) 		0.18
(1.00) 		0.446
(1.00) 		0.317
(1.00) 		0.526
(1.00) 		0.03
(1.00) 		0.204
(1.00) 		0.461
(1.00) 		0.596
(1.00) 		0.289
(1.00) 		0.641
(1.00)
9p gain 91 (16%) 478 0.107
(1.00) 		0.832
(1.00) 		0.239
(1.00) 		0.773
(1.00) 		0.0188
(1.00) 		0.00832
(1.00) 		0.396
(1.00) 		0.922
(1.00) 		0.679
(1.00) 		0.164
(1.00) 		0.186
(1.00) 		0.323
(1.00) 		0.488
(1.00) 		0.158
(1.00)
9q gain 45 (8%) 524 0.248
(1.00) 		0.216
(1.00) 		0.0943
(1.00) 		0.641
(1.00) 		0.181
(1.00) 		0.222
(1.00) 		0.565
(1.00) 		0.226
(1.00) 		0.471
(1.00) 		0.0203
(1.00) 		0.487
(1.00) 		0.703
(1.00) 		0.439
(1.00) 		0.752
(1.00)
10q gain 108 (19%) 461 0.00379
(1.00) 		0.0339
(1.00) 		0.238
(1.00) 		0.00922
(1.00) 		0.00126
(1.00) 		0.0909
(1.00) 		0.759
(1.00) 		0.631
(1.00) 		0.108
(1.00) 		0.447
(1.00) 		0.736
(1.00) 		0.69
(1.00) 		0.949
(1.00) 		0.361
(1.00)
11p gain 76 (13%) 493 0.684
(1.00) 		0.303
(1.00) 		0.624
(1.00) 		0.849
(1.00) 		0.344
(1.00) 		0.014
(1.00) 		0.0276
(1.00) 		0.0338
(1.00) 		0.0602
(1.00) 		0.241
(1.00) 		0.553
(1.00) 		0.652
(1.00) 		0.866
(1.00) 		1
(1.00)
11q gain 114 (20%) 455 0.446
(1.00) 		0.387
(1.00) 		0.863
(1.00) 		0.0862
(1.00) 		0.0406
(1.00) 		0.00161
(1.00) 		0.164
(1.00) 		0.0166
(1.00) 		0.289
(1.00) 		0.08
(1.00) 		0.521
(1.00) 		0.799
(1.00) 		0.843
(1.00) 		0.669
(1.00)
14q gain 58 (10%) 511 0.147
(1.00) 		0.525
(1.00) 		0.401
(1.00) 		0.287
(1.00) 		0.801
(1.00) 		0.733
(1.00) 		0.329
(1.00) 		0.125
(1.00) 		0.496
(1.00) 		0.324
(1.00) 		0.638
(1.00) 		0.681
(1.00) 		0.565
(1.00) 		0.426
(1.00)
15q gain 39 (7%) 530 0.843
(1.00) 		0.572
(1.00) 		0.0942
(1.00) 		0.284
(1.00) 		0.401
(1.00) 		0.57
(1.00) 		0.11
(1.00) 		0.232
(1.00) 		0.753
(1.00) 		0.531
(1.00) 		0.298
(1.00) 		0.362
(1.00) 		0.518
(1.00) 		0.158
(1.00)
16p gain 58 (10%) 511 0.00265
(1.00) 		0.00279
(1.00) 		0.401
(1.00) 		0.599
(1.00) 		0.085
(1.00) 		0.0182
(1.00) 		0.348
(1.00) 		0.0142
(1.00) 		0.637
(1.00) 		0.665
(1.00) 		0.128
(1.00) 		0.142
(1.00) 		0.195
(1.00) 		0.0444
(1.00)
16q gain 30 (5%) 539 0.000828
(0.878) 		0.0133
(1.00) 		0.169
(1.00) 		0.478
(1.00) 		0.687
(1.00) 		0.00369
(1.00) 		0.433
(1.00) 		0.232
(1.00) 		1
(1.00) 		0.151
(1.00) 		0.000925
(0.977) 		0.0345
(1.00) 		0.00272
(1.00) 		0.0065
(1.00)
17p gain 22 (4%) 547 0.423
(1.00) 		0.556
(1.00) 		0.065
(1.00) 		0.455
(1.00) 		0.224
(1.00) 		0.241
(1.00) 		0.483
(1.00) 		0.511
(1.00) 		0.203
(1.00) 		0.705
(1.00) 		0.174
(1.00) 		0.474
(1.00) 		0.412
(1.00) 		0.238
(1.00)
17q gain 49 (9%) 520 0.335
(1.00) 		0.165
(1.00) 		0.854
(1.00) 		0.692
(1.00) 		0.774
(1.00) 		0.297
(1.00) 		0.462
(1.00) 		0.437
(1.00) 		0.9
(1.00) 		0.905
(1.00) 		0.771
(1.00) 		0.836
(1.00) 		0.443
(1.00) 		0.827
(1.00)
18p gain 117 (21%) 452 0.231
(1.00) 		0.122
(1.00) 		0.921
(1.00) 		0.441
(1.00) 		0.00473
(1.00) 		0.000472
(0.503) 		0.0231
(1.00) 		0.107
(1.00) 		0.779
(1.00) 		0.777
(1.00) 		0.355
(1.00) 		0.938
(1.00) 		0.342
(1.00) 		0.783
(1.00)
18q gain 71 (12%) 498 0.645
(1.00) 		0.471
(1.00) 		0.286
(1.00) 		0.375
(1.00) 		0.0538
(1.00) 		0.038
(1.00) 		0.532
(1.00) 		0.359
(1.00) 		0.482
(1.00) 		0.133
(1.00) 		0.112
(1.00) 		0.379
(1.00) 		0.054
(1.00) 		0.459
(1.00)
21q gain 109 (19%) 460 0.293
(1.00) 		0.221
(1.00) 		0.966
(1.00) 		0.964
(1.00) 		0.00117
(1.00) 		0.0168
(1.00) 		0.443
(1.00) 		0.523
(1.00) 		0.327
(1.00) 		0.0902
(1.00) 		0.0239
(1.00) 		0.502
(1.00) 		0.102
(1.00) 		0.258
(1.00)
22q gain 25 (4%) 544 0.526
(1.00) 		0.825
(1.00) 		0.884
(1.00) 		0.763
(1.00) 		0.13
(1.00) 		0.216
(1.00) 		0.37
(1.00) 		0.8
(1.00) 		0.465
(1.00) 		0.691
(1.00) 		0.0613
(1.00) 		0.0948
(1.00) 		0.0873
(1.00) 		0.119
(1.00)
xq gain 104 (18%) 465 0.553
(1.00) 		0.504
(1.00) 		0.824
(1.00) 		0.715
(1.00) 		0.00241
(1.00) 		0.878
(1.00) 		0.265
(1.00) 		0.374
(1.00) 		0.777
(1.00) 		0.881
(1.00) 		0.541
(1.00) 		0.876
(1.00) 		0.464
(1.00) 		0.292
(1.00)
1p loss 61 (11%) 508 0.0288
(1.00) 		0.0154
(1.00) 		0.594
(1.00) 		0.14
(1.00) 		0.457
(1.00) 		0.259
(1.00) 		0.0357
(1.00) 		0.341
(1.00) 		0.585
(1.00) 		0.49
(1.00) 		0.444
(1.00) 		0.636
(1.00) 		0.0423
(1.00) 		0.361
(1.00)
1q loss 39 (7%) 530 0.0979
(1.00) 		0.0105
(1.00) 		0.119
(1.00) 		0.689
(1.00) 		0.959
(1.00) 		0.319
(1.00) 		0.326
(1.00) 		0.793
(1.00) 		0.468
(1.00) 		0.202
(1.00) 		0.95
(1.00) 		1
(1.00) 		0.254
(1.00) 		0.876
(1.00)
2p loss 53 (9%) 516 0.899
(1.00) 		0.833
(1.00) 		0.814
(1.00) 		0.724
(1.00) 		0.518
(1.00) 		0.719
(1.00) 		0.47
(1.00) 		0.525
(1.00) 		0.612
(1.00) 		0.484
(1.00) 		0.718
(1.00) 		0.117
(1.00) 		0.596
(1.00) 		0.906
(1.00)
2q loss 59 (10%) 510 0.965
(1.00) 		0.629
(1.00) 		0.76
(1.00) 		0.101
(1.00) 		0.751
(1.00) 		0.63
(1.00) 		0.796
(1.00) 		0.886
(1.00) 		0.632
(1.00) 		0.33
(1.00) 		0.67
(1.00) 		0.232
(1.00) 		0.648
(1.00) 		0.417
(1.00)
3q loss 41 (7%) 528 0.0211
(1.00) 		0.0123
(1.00) 		0.297
(1.00) 		0.135
(1.00) 		0.006
(1.00) 		0.00139
(1.00) 		1
(1.00) 		0.614
(1.00) 		0.234
(1.00) 		0.717
(1.00) 		0.235
(1.00) 		0.102
(1.00) 		0.279
(1.00) 		0.00706
(1.00)
4p loss 312 (55%) 257 0.466
(1.00) 		0.304
(1.00) 		0.277
(1.00) 		0.0273
(1.00) 		0.00407
(1.00) 		0.602
(1.00) 		0.145
(1.00) 		0.298
(1.00) 		0.608
(1.00) 		0.861
(1.00) 		0.0687
(1.00) 		0.00763
(1.00) 		0.0525
(1.00) 		0.0262
(1.00)
4q loss 355 (62%) 214 0.282
(1.00) 		0.264
(1.00) 		0.446
(1.00) 		0.0359
(1.00) 		0.00137
(1.00) 		0.668
(1.00) 		0.103
(1.00) 		0.0837
(1.00) 		0.359
(1.00) 		0.173
(1.00) 		0.135
(1.00) 		0.000408
(0.436) 		0.0272
(1.00) 		0.0402
(1.00)
6p loss 164 (29%) 405 0.968
(1.00) 		0.468
(1.00) 		0.371
(1.00) 		0.725
(1.00) 		0.0604
(1.00) 		0.113
(1.00) 		0.702
(1.00) 		0.597
(1.00) 		0.409
(1.00) 		0.529
(1.00) 		0.476
(1.00) 		0.673
(1.00) 		0.322
(1.00) 		0.635
(1.00)
6q loss 239 (42%) 330 0.959
(1.00) 		0.412
(1.00) 		0.439
(1.00) 		0.536
(1.00) 		0.0171
(1.00) 		0.071
(1.00) 		0.623
(1.00) 		0.394
(1.00) 		0.0202
(1.00) 		0.0314
(1.00) 		0.792
(1.00) 		0.943
(1.00) 		0.911
(1.00) 		0.445
(1.00)
7p loss 118 (21%) 451 0.981
(1.00) 		0.602
(1.00) 		0.43
(1.00) 		0.386
(1.00) 		0.3
(1.00) 		0.142
(1.00) 		0.592
(1.00) 		0.796
(1.00) 		0.632
(1.00) 		0.0262
(1.00) 		0.527
(1.00) 		0.41
(1.00) 		0.766
(1.00) 		0.416
(1.00)
7q loss 81 (14%) 488 0.343
(1.00) 		0.408
(1.00) 		0.342
(1.00) 		0.392
(1.00) 		0.917
(1.00) 		0.109
(1.00) 		0.815
(1.00) 		0.223
(1.00) 		0.477
(1.00) 		0.163
(1.00) 		0.125
(1.00) 		1
(1.00) 		0.502
(1.00) 		0.908
(1.00)
8p loss 271 (48%) 298 0.743
(1.00) 		0.877
(1.00) 		0.24
(1.00) 		0.736
(1.00) 		0.00359
(1.00) 		0.109
(1.00) 		0.12
(1.00) 		0.166
(1.00) 		0.476
(1.00) 		0.842
(1.00) 		0.686
(1.00) 		0.0268
(1.00) 		0.802
(1.00) 		0.269
(1.00)
8q loss 88 (15%) 481 0.0075
(1.00) 		0.0581
(1.00) 		0.533
(1.00) 		0.0858
(1.00) 		0.00191
(1.00) 		0.0347
(1.00) 		0.0221
(1.00) 		0.213
(1.00) 		0.000873
(0.924) 		0.0371
(1.00) 		0.646
(1.00) 		0.37
(1.00) 		0.765
(1.00) 		0.501
(1.00)
9p loss 255 (45%) 314 0.00319
(1.00) 		0.0346
(1.00) 		0.512
(1.00) 		0.104
(1.00) 		0.00834
(1.00) 		0.0701
(1.00) 		0.787
(1.00) 		0.505
(1.00) 		0.883
(1.00) 		0.353
(1.00) 		0.0531
(1.00) 		0.371
(1.00) 		0.0625
(1.00) 		0.286
(1.00)
10p loss 94 (17%) 475 0.297
(1.00) 		0.75
(1.00) 		0.258
(1.00) 		0.162
(1.00) 		0.566
(1.00) 		0.276
(1.00) 		0.589
(1.00) 		0.122
(1.00) 		0.799
(1.00) 		0.266
(1.00) 		0.434
(1.00) 		0.563
(1.00) 		0.405
(1.00) 		0.495
(1.00)
10q loss 122 (21%) 447 0.964
(1.00) 		0.458
(1.00) 		0.00409
(1.00) 		0.187
(1.00) 		0.081
(1.00) 		0.00115
(1.00) 		0.355
(1.00) 		0.0263
(1.00) 		0.68
(1.00) 		0.191
(1.00) 		0.762
(1.00) 		0.771
(1.00) 		0.85
(1.00) 		0.765
(1.00)
11p loss 193 (34%) 376 0.237
(1.00) 		0.0292
(1.00) 		0.542
(1.00) 		0.576
(1.00) 		0.124
(1.00) 		0.0352
(1.00) 		0.1
(1.00) 		0.563
(1.00) 		0.0389
(1.00) 		0.103
(1.00) 		0.476
(1.00) 		0.0925
(1.00) 		0.0777
(1.00) 		0.121
(1.00)
11q loss 144 (25%) 425 0.361
(1.00) 		0.32
(1.00) 		0.177
(1.00) 		0.624
(1.00) 		0.0157
(1.00) 		0.0936
(1.00) 		0.464
(1.00) 		0.643
(1.00) 		0.263
(1.00) 		0.253
(1.00) 		0.511
(1.00) 		0.146
(1.00) 		0.102
(1.00) 		0.0438
(1.00)
12p loss 78 (14%) 491 0.00282
(1.00) 		0.0239
(1.00) 		0.536
(1.00) 		0.148
(1.00) 		0.0029
(1.00) 		0.255
(1.00) 		0.771
(1.00) 		0.234
(1.00) 		0.327
(1.00) 		0.337
(1.00) 		0.00971
(1.00) 		0.00435
(1.00) 		0.0023
(1.00) 		0.00818
(1.00)
12q loss 104 (18%) 465 0.0677
(1.00) 		0.00566
(1.00) 		0.76
(1.00) 		0.623
(1.00) 		0.0589
(1.00) 		0.203
(1.00) 		0.264
(1.00) 		0.656
(1.00) 		0.238
(1.00) 		0.0173
(1.00) 		0.0459
(1.00) 		0.0204
(1.00) 		0.108
(1.00) 		0.031
(1.00)
16p loss 325 (57%) 244 0.319
(1.00) 		0.565
(1.00) 		0.0376
(1.00) 		0.503
(1.00) 		0.123
(1.00) 		0.0957
(1.00) 		0.8
(1.00) 		0.523
(1.00) 		0.0528
(1.00) 		0.433
(1.00) 		0.0802
(1.00) 		0.116
(1.00) 		0.113
(1.00) 		0.0983
(1.00)
16q loss 404 (71%) 165 0.565
(1.00) 		0.406
(1.00) 		0.00345
(1.00) 		0.302
(1.00) 		0.00205
(1.00) 		0.0627
(1.00) 		0.948
(1.00) 		0.844
(1.00) 		0.209
(1.00) 		0.427
(1.00) 		0.07
(1.00) 		0.0556
(1.00) 		0.0487
(1.00) 		0.0983
(1.00)
17p loss 471 (83%) 98 0.278
(1.00) 		0.221
(1.00) 		0.179
(1.00) 		0.524
(1.00) 		0.47
(1.00) 		0.208
(1.00) 		0.535
(1.00) 		0.196
(1.00) 		0.102
(1.00) 		0.268
(1.00) 		0.475
(1.00) 		0.362
(1.00) 		0.134
(1.00) 		0.639
(1.00)
18p loss 234 (41%) 335 0.418
(1.00) 		0.219
(1.00) 		0.51
(1.00) 		0.0864
(1.00) 		0.236
(1.00) 		0.00323
(1.00) 		0.311
(1.00) 		0.00279
(1.00) 		0.0236
(1.00) 		0.504
(1.00) 		0.84
(1.00) 		0.508
(1.00) 		0.611
(1.00) 		0.798
(1.00)
18q loss 290 (51%) 279 0.317
(1.00) 		0.0821
(1.00) 		0.401
(1.00) 		0.729
(1.00) 		0.973
(1.00) 		0.106
(1.00) 		0.806
(1.00) 		0.0116
(1.00) 		0.0108
(1.00) 		0.214
(1.00) 		0.969
(1.00) 		0.927
(1.00) 		0.82
(1.00) 		0.721
(1.00)
19p loss 181 (32%) 388 0.987
(1.00) 		0.906
(1.00) 		0.231
(1.00) 		0.515
(1.00) 		0.0167
(1.00) 		0.0324
(1.00) 		0.0215
(1.00) 		0.63
(1.00) 		0.745
(1.00) 		0.726
(1.00) 		0.795
(1.00) 		0.892
(1.00) 		0.86
(1.00) 		1
(1.00)
19q loss 172 (30%) 397 0.829
(1.00) 		0.394
(1.00) 		0.285
(1.00) 		0.812
(1.00) 		0.038
(1.00) 		0.132
(1.00) 		0.0941
(1.00) 		0.346
(1.00) 		1
(1.00) 		0.792
(1.00) 		0.368
(1.00) 		0.635
(1.00) 		0.41
(1.00) 		0.755
(1.00)
20p loss 49 (9%) 520 0.495
(1.00) 		0.973
(1.00) 		0.223
(1.00) 		0.446
(1.00) 		0.121
(1.00) 		0.272
(1.00) 		0.0994
(1.00) 		0.114
(1.00) 		0.0131
(1.00) 		0.116
(1.00) 		0.000767
(0.814) 		0.434
(1.00) 		0.00653
(1.00) 		0.703
(1.00)
20q loss 31 (5%) 538 0.126
(1.00) 		0.485
(1.00) 		0.036
(1.00) 		0.469
(1.00) 		0.524
(1.00) 		0.619
(1.00) 		0.0533
(1.00) 		0.0336
(1.00) 		0.126
(1.00) 		0.247
(1.00) 		0.131
(1.00) 		0.246
(1.00) 		0.0599
(1.00) 		0.715
(1.00)
21q loss 195 (34%) 374 0.816
(1.00) 		0.38
(1.00) 		0.383
(1.00) 		0.327
(1.00) 		0.397
(1.00) 		0.141
(1.00) 		0.641
(1.00) 		0.292
(1.00) 		0.584
(1.00) 		0.588
(1.00) 		0.681
(1.00) 		0.917
(1.00) 		0.145
(1.00) 		0.867
(1.00)
22q loss 421 (74%) 148 0.00473
(1.00) 		0.038
(1.00) 		0.0362
(1.00) 		0.0352
(1.00) 		0.00035
(0.375) 		0.00406
(1.00) 		0.0697
(1.00) 		0.187
(1.00) 		0.184
(1.00) 		0.757
(1.00) 		0.0402
(1.00) 		0.631
(1.00) 		0.0501
(1.00) 		0.264
(1.00)
xq loss 273 (48%) 296 0.0583
(1.00) 		0.235
(1.00) 		0.289
(1.00) 		0.322
(1.00) 		0.006
(1.00) 		0.0973
(1.00) 		0.373
(1.00) 		0.0102
(1.00) 		0.49
(1.00) 		0.521
(1.00) 		0.788
(1.00) 		0.731
(1.00) 		0.888
(1.00) 		0.912
(1.00)
'1q gain' versus 'CN_CNMF'

P value = 9.78e-08 (Fisher's exact test), Q value = 0.00011

Table S1.  Gene #2: '1q gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
1Q GAIN MUTATED 58 57 103
1Q GAIN WILD-TYPE 116 149 86

Figure S1.  Get High-res Image Gene #2: '1q gain' versus Molecular Subtype #5: 'CN_CNMF'

'2p gain' versus 'MRNA_CNMF'

P value = 1.48e-06 (Fisher's exact test), Q value = 0.0016

Table S2.  Gene #3: '2p gain' versus Molecular Subtype #1: 'MRNA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 215 216 126
2P GAIN MUTATED 93 44 36
2P GAIN WILD-TYPE 122 172 90

Figure S2.  Get High-res Image Gene #3: '2p gain' versus Molecular Subtype #1: 'MRNA_CNMF'

'2p gain' versus 'MRNA_CHIERARCHICAL'

P value = 1.96e-06 (Fisher's exact test), Q value = 0.0022

Table S3.  Gene #3: '2p gain' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 128 210 219
2P GAIN MUTATED 37 91 45
2P GAIN WILD-TYPE 91 119 174

Figure S3.  Get High-res Image Gene #3: '2p gain' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

'2p gain' versus 'MIR_CHIERARCHICAL'

P value = 0.000101 (Chi-square test), Q value = 0.11

Table S4.  Gene #3: '2p gain' versus Molecular Subtype #4: 'MIR_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 65 115 125 99 57 94
2P GAIN MUTATED 17 23 37 28 20 48
2P GAIN WILD-TYPE 48 92 88 71 37 46

Figure S4.  Get High-res Image Gene #3: '2p gain' versus Molecular Subtype #4: 'MIR_CHIERARCHICAL'

'2p gain' versus 'CN_CNMF'

P value = 2.36e-11 (Fisher's exact test), Q value = 2.6e-08

Table S5.  Gene #3: '2p gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
2P GAIN MUTATED 35 47 96
2P GAIN WILD-TYPE 139 159 93

Figure S5.  Get High-res Image Gene #3: '2p gain' versus Molecular Subtype #5: 'CN_CNMF'

'2p gain' versus 'METHLYATION_CNMF'

P value = 1.32e-07 (Fisher's exact test), Q value = 0.00015

Table S6.  Gene #3: '2p gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
2P GAIN MUTATED 83 43 52
2P GAIN WILD-TYPE 89 132 169

Figure S6.  Get High-res Image Gene #3: '2p gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'2p gain' versus 'MRNASEQ_CNMF'

P value = 0.000127 (Fisher's exact test), Q value = 0.14

Table S7.  Gene #3: '2p gain' versus Molecular Subtype #9: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 100 67 91
2P GAIN MUTATED 31 12 45
2P GAIN WILD-TYPE 69 55 46

Figure S7.  Get High-res Image Gene #3: '2p gain' versus Molecular Subtype #9: 'MRNASEQ_CNMF'

'2q gain' versus 'MRNA_CHIERARCHICAL'

P value = 1.82e-05 (Fisher's exact test), Q value = 0.02

Table S8.  Gene #4: '2q gain' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 128 210 219
2Q GAIN MUTATED 32 77 37
2Q GAIN WILD-TYPE 96 133 182

Figure S8.  Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

'2q gain' versus 'CN_CNMF'

P value = 4.42e-09 (Fisher's exact test), Q value = 4.9e-06

Table S9.  Gene #4: '2q gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
2Q GAIN MUTATED 29 40 81
2Q GAIN WILD-TYPE 145 166 108

Figure S9.  Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #5: 'CN_CNMF'

'2q gain' versus 'METHLYATION_CNMF'

P value = 0.000143 (Fisher's exact test), Q value = 0.15

Table S10.  Gene #4: '2q gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
2Q GAIN MUTATED 66 35 49
2Q GAIN WILD-TYPE 106 140 172

Figure S10.  Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'3q gain' versus 'CN_CNMF'

P value = 3.53e-06 (Fisher's exact test), Q value = 0.0039

Table S11.  Gene #6: '3q gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
3Q GAIN MUTATED 63 89 116
3Q GAIN WILD-TYPE 111 117 73

Figure S11.  Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #5: 'CN_CNMF'

'5p gain' versus 'CN_CNMF'

P value = 6.79e-05 (Fisher's exact test), Q value = 0.074

Table S12.  Gene #9: '5p gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
5P GAIN MUTATED 38 78 80
5P GAIN WILD-TYPE 136 128 109

Figure S12.  Get High-res Image Gene #9: '5p gain' versus Molecular Subtype #5: 'CN_CNMF'

'6p gain' versus 'CN_CNMF'

P value = 1.38e-06 (Fisher's exact test), Q value = 0.0015

Table S13.  Gene #11: '6p gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
6P GAIN MUTATED 30 57 79
6P GAIN WILD-TYPE 144 149 110

Figure S13.  Get High-res Image Gene #11: '6p gain' versus Molecular Subtype #5: 'CN_CNMF'

'6p gain' versus 'METHLYATION_CNMF'

P value = 8.61e-05 (Fisher's exact test), Q value = 0.093

Table S14.  Gene #11: '6p gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
6P GAIN MUTATED 72 39 55
6P GAIN WILD-TYPE 100 136 166

Figure S14.  Get High-res Image Gene #11: '6p gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'6q gain' versus 'CN_CNMF'

P value = 3.06e-07 (Fisher's exact test), Q value = 0.00034

Table S15.  Gene #12: '6q gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
6Q GAIN MUTATED 12 31 53
6Q GAIN WILD-TYPE 162 175 136

Figure S15.  Get High-res Image Gene #12: '6q gain' versus Molecular Subtype #5: 'CN_CNMF'

'6q gain' versus 'METHLYATION_CNMF'

P value = 1.35e-05 (Fisher's exact test), Q value = 0.015

Table S16.  Gene #12: '6q gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
6Q GAIN MUTATED 48 16 32
6Q GAIN WILD-TYPE 124 159 189

Figure S16.  Get High-res Image Gene #12: '6q gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'7p gain' versus 'CN_CNMF'

P value = 7.57e-07 (Fisher's exact test), Q value = 0.00083

Table S17.  Gene #13: '7p gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
7P GAIN MUTATED 46 47 88
7P GAIN WILD-TYPE 128 159 101

Figure S17.  Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #5: 'CN_CNMF'

'7p gain' versus 'METHLYATION_CNMF'

P value = 0.00011 (Fisher's exact test), Q value = 0.12

Table S18.  Gene #13: '7p gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
7P GAIN MUTATED 76 41 64
7P GAIN WILD-TYPE 96 134 157

Figure S18.  Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'7q gain' versus 'CN_CNMF'

P value = 1.69e-05 (Fisher's exact test), Q value = 0.018

Table S19.  Gene #14: '7q gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
7Q GAIN MUTATED 47 60 91
7Q GAIN WILD-TYPE 127 146 98

Figure S19.  Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #5: 'CN_CNMF'

'10p gain' versus 'CN_CNMF'

P value = 1.45e-10 (Fisher's exact test), Q value = 1.6e-07

Table S20.  Gene #19: '10p gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
10P GAIN MUTATED 39 48 97
10P GAIN WILD-TYPE 135 158 92

Figure S20.  Get High-res Image Gene #19: '10p gain' versus Molecular Subtype #5: 'CN_CNMF'

'10p gain' versus 'METHLYATION_CNMF'

P value = 0.000174 (Fisher's exact test), Q value = 0.19

Table S21.  Gene #19: '10p gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
10P GAIN MUTATED 77 44 63
10P GAIN WILD-TYPE 95 131 158

Figure S21.  Get High-res Image Gene #19: '10p gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'12p gain' versus 'MRNA_CNMF'

P value = 4.4e-05 (Fisher's exact test), Q value = 0.048

Table S22.  Gene #23: '12p gain' versus Molecular Subtype #1: 'MRNA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 215 216 126
12P GAIN MUTATED 119 75 49
12P GAIN WILD-TYPE 96 141 77

Figure S22.  Get High-res Image Gene #23: '12p gain' versus Molecular Subtype #1: 'MRNA_CNMF'

'12p gain' versus 'MRNA_CHIERARCHICAL'

P value = 8.88e-05 (Fisher's exact test), Q value = 0.096

Table S23.  Gene #23: '12p gain' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 128 210 219
12P GAIN MUTATED 49 116 78
12P GAIN WILD-TYPE 79 94 141

Figure S23.  Get High-res Image Gene #23: '12p gain' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

'12p gain' versus 'CN_CNMF'

P value = 1.05e-13 (Fisher's exact test), Q value = 1.2e-10

Table S24.  Gene #23: '12p gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
12P GAIN MUTATED 55 69 126
12P GAIN WILD-TYPE 119 137 63

Figure S24.  Get High-res Image Gene #23: '12p gain' versus Molecular Subtype #5: 'CN_CNMF'

'12p gain' versus 'METHLYATION_CNMF'

P value = 1.84e-07 (Fisher's exact test), Q value = 2e-04

Table S25.  Gene #23: '12p gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
12P GAIN MUTATED 105 71 74
12P GAIN WILD-TYPE 67 104 147

Figure S25.  Get High-res Image Gene #23: '12p gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'12q gain' versus 'MRNA_CHIERARCHICAL'

P value = 5.09e-05 (Fisher's exact test), Q value = 0.055

Table S26.  Gene #24: '12q gain' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 128 210 219
12Q GAIN MUTATED 35 86 47
12Q GAIN WILD-TYPE 93 124 172

Figure S26.  Get High-res Image Gene #24: '12q gain' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

'12q gain' versus 'CN_CNMF'

P value = 2.04e-12 (Fisher's exact test), Q value = 2.3e-09

Table S27.  Gene #24: '12q gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
12Q GAIN MUTATED 40 38 96
12Q GAIN WILD-TYPE 134 168 93

Figure S27.  Get High-res Image Gene #24: '12q gain' versus Molecular Subtype #5: 'CN_CNMF'

'12q gain' versus 'METHLYATION_CNMF'

P value = 5.49e-06 (Fisher's exact test), Q value = 0.006

Table S28.  Gene #24: '12q gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
12Q GAIN MUTATED 78 42 54
12Q GAIN WILD-TYPE 94 133 167

Figure S28.  Get High-res Image Gene #24: '12q gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'13q gain' versus 'MIR_CHIERARCHICAL'

P value = 3.21e-05 (Chi-square test), Q value = 0.035

Table S29.  Gene #25: '13q gain' versus Molecular Subtype #4: 'MIR_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 65 115 125 99 57 94
13Q GAIN MUTATED 7 7 11 2 8 22
13Q GAIN WILD-TYPE 58 108 114 97 49 72

Figure S29.  Get High-res Image Gene #25: '13q gain' versus Molecular Subtype #4: 'MIR_CHIERARCHICAL'

'13q gain' versus 'CN_CNMF'

P value = 0.000125 (Fisher's exact test), Q value = 0.14

Table S30.  Gene #25: '13q gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
13Q GAIN MUTATED 22 8 30
13Q GAIN WILD-TYPE 152 198 159

Figure S30.  Get High-res Image Gene #25: '13q gain' versus Molecular Subtype #5: 'CN_CNMF'

'13q gain' versus 'METHLYATION_CNMF'

P value = 4.9e-06 (Fisher's exact test), Q value = 0.0054

Table S31.  Gene #25: '13q gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
13Q GAIN MUTATED 32 20 8
13Q GAIN WILD-TYPE 140 155 213

Figure S31.  Get High-res Image Gene #25: '13q gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'19p gain' versus 'CN_CNMF'

P value = 4.18e-05 (Fisher's exact test), Q value = 0.046

Table S32.  Gene #34: '19p gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
19P GAIN MUTATED 34 56 77
19P GAIN WILD-TYPE 140 150 112

Figure S32.  Get High-res Image Gene #34: '19p gain' versus Molecular Subtype #5: 'CN_CNMF'

'19q gain' versus 'CN_CNMF'

P value = 4.54e-06 (Fisher's exact test), Q value = 0.005

Table S33.  Gene #35: '19q gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
19Q GAIN MUTATED 33 49 78
19Q GAIN WILD-TYPE 141 157 111

Figure S33.  Get High-res Image Gene #35: '19q gain' versus Molecular Subtype #5: 'CN_CNMF'

'20p gain' versus 'CN_CNMF'

P value = 1e-11 (Fisher's exact test), Q value = 1.1e-08

Table S34.  Gene #36: '20p gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
20P GAIN MUTATED 64 85 133
20P GAIN WILD-TYPE 110 121 56

Figure S34.  Get High-res Image Gene #36: '20p gain' versus Molecular Subtype #5: 'CN_CNMF'

'20p gain' versus 'METHLYATION_CNMF'

P value = 2.73e-08 (Fisher's exact test), Q value = 3e-05

Table S35.  Gene #36: '20p gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
20P GAIN MUTATED 117 78 87
20P GAIN WILD-TYPE 55 97 134

Figure S35.  Get High-res Image Gene #36: '20p gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'20q gain' versus 'MRNA_CNMF'

P value = 8.76e-06 (Fisher's exact test), Q value = 0.0096

Table S36.  Gene #37: '20q gain' versus Molecular Subtype #1: 'MRNA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 215 216 126
20Q GAIN MUTATED 143 95 76
20Q GAIN WILD-TYPE 72 121 50

Figure S36.  Get High-res Image Gene #37: '20q gain' versus Molecular Subtype #1: 'MRNA_CNMF'

'20q gain' versus 'MIR_CHIERARCHICAL'

P value = 0.000204 (Chi-square test), Q value = 0.22

Table S37.  Gene #37: '20q gain' versus Molecular Subtype #4: 'MIR_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 65 115 125 99 57 94
20Q GAIN MUTATED 32 59 63 50 36 73
20Q GAIN WILD-TYPE 33 56 62 49 21 21

Figure S37.  Get High-res Image Gene #37: '20q gain' versus Molecular Subtype #4: 'MIR_CHIERARCHICAL'

'20q gain' versus 'CN_CNMF'

P value = 4.5e-15 (Fisher's exact test), Q value = 5e-12

Table S38.  Gene #37: '20q gain' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
20Q GAIN MUTATED 68 103 149
20Q GAIN WILD-TYPE 106 103 40

Figure S38.  Get High-res Image Gene #37: '20q gain' versus Molecular Subtype #5: 'CN_CNMF'

'20q gain' versus 'METHLYATION_CNMF'

P value = 2.58e-10 (Fisher's exact test), Q value = 2.9e-07

Table S39.  Gene #37: '20q gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
20Q GAIN MUTATED 132 87 101
20Q GAIN WILD-TYPE 40 88 120

Figure S39.  Get High-res Image Gene #37: '20q gain' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'3p loss' versus 'CN_CNMF'

P value = 0.000106 (Fisher's exact test), Q value = 0.11

Table S40.  Gene #45: '3p loss' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
3P LOSS MUTATED 21 24 50
3P LOSS WILD-TYPE 153 182 139

Figure S40.  Get High-res Image Gene #45: '3p loss' versus Molecular Subtype #5: 'CN_CNMF'

'5p loss' versus 'MRNASEQ_CNMF'

P value = 0.000137 (Fisher's exact test), Q value = 0.15

Table S41.  Gene #49: '5p loss' versus Molecular Subtype #9: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 100 67 91
5P LOSS MUTATED 21 10 39
5P LOSS WILD-TYPE 79 57 52

Figure S41.  Get High-res Image Gene #49: '5p loss' versus Molecular Subtype #9: 'MRNASEQ_CNMF'

'5q loss' versus 'METHLYATION_CNMF'

P value = 1.41e-07 (Fisher's exact test), Q value = 0.00016

Table S42.  Gene #50: '5q loss' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
5Q LOSS MUTATED 96 51 71
5Q LOSS WILD-TYPE 76 124 150

Figure S42.  Get High-res Image Gene #50: '5q loss' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'9q loss' versus 'CN_CNMF'

P value = 2.19e-12 (Fisher's exact test), Q value = 2.5e-09

Table S43.  Gene #58: '9q loss' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
9Q LOSS MUTATED 81 68 131
9Q LOSS WILD-TYPE 93 138 58

Figure S43.  Get High-res Image Gene #58: '9q loss' versus Molecular Subtype #5: 'CN_CNMF'

'13q loss' versus 'METHLYATION_CNMF'

P value = 1.36e-05 (Fisher's exact test), Q value = 0.015

Table S44.  Gene #65: '13q loss' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
13Q LOSS MUTATED 88 72 143
13Q LOSS WILD-TYPE 84 103 78

Figure S44.  Get High-res Image Gene #65: '13q loss' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'14q loss' versus 'CN_CNMF'

P value = 1.35e-05 (Fisher's exact test), Q value = 0.015

Table S45.  Gene #66: '14q loss' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
14Q LOSS MUTATED 52 61 95
14Q LOSS WILD-TYPE 122 145 94

Figure S45.  Get High-res Image Gene #66: '14q loss' versus Molecular Subtype #5: 'CN_CNMF'

'15q loss' versus 'MIR_CNMF'

P value = 0.000104 (Fisher's exact test), Q value = 0.11

Table S46.  Gene #67: '15q loss' versus Molecular Subtype #3: 'MIR_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 159 164 232
15Q LOSS MUTATED 62 70 137
15Q LOSS WILD-TYPE 97 94 95

Figure S46.  Get High-res Image Gene #67: '15q loss' versus Molecular Subtype #3: 'MIR_CNMF'

'15q loss' versus 'CN_CNMF'

P value = 4.31e-12 (Fisher's exact test), Q value = 4.8e-09

Table S47.  Gene #67: '15q loss' versus Molecular Subtype #5: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 174 206 189
15Q LOSS MUTATED 66 78 132
15Q LOSS WILD-TYPE 108 128 57

Figure S47.  Get High-res Image Gene #67: '15q loss' versus Molecular Subtype #5: 'CN_CNMF'

'15q loss' versus 'METHLYATION_CNMF'

P value = 3.98e-07 (Fisher's exact test), Q value = 0.00044

Table S48.  Gene #67: '15q loss' versus Molecular Subtype #6: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 172 175 221
15Q LOSS MUTATED 113 69 94
15Q LOSS WILD-TYPE 59 106 127

Figure S48.  Get High-res Image Gene #67: '15q loss' versus Molecular Subtype #6: 'METHLYATION_CNMF'

'17q loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 7.66e-05 (Fisher's exact test), Q value = 0.083

Table S49.  Gene #71: '17q loss' versus Molecular Subtype #13: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 95 195 157
17Q LOSS MUTATED 46 145 107
17Q LOSS WILD-TYPE 49 50 50

Figure S49.  Get High-res Image Gene #71: '17q loss' versus Molecular Subtype #13: 'MIRSEQ_MATURE_CNMF'

Methods & Data
Input

  • Copy number data file = transformed.cor.cli.txt

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

  • Number of patients = 569

  • Number of significantly arm-level cnvs = 80

  • Number of molecular subtypes = 14

  • 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

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

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

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

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