Correlation between copy number variations of arm-level result and molecular subtypes
Bladder Urothelial Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1MK6BG6
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/C1MK6BG6
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 10 molecular subtypes across 250 patients, 35 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 1p gain cnv correlated to 'CN_CNMF'.

  • 2p gain cnv correlated to 'CN_CNMF'.

  • 3p gain cnv correlated to 'CN_CNMF'.

  • 3q gain cnv correlated to 'CN_CNMF'.

  • 5p gain cnv correlated to 'CN_CNMF'.

  • 7p gain cnv correlated to 'CN_CNMF'.

  • 8p gain cnv correlated to 'CN_CNMF'.

  • 9p gain cnv correlated to 'CN_CNMF'.

  • 10p gain cnv correlated to 'CN_CNMF'.

  • 17p gain cnv correlated to 'MIRSEQ_CHIERARCHICAL'.

  • 18p gain cnv correlated to 'CN_CNMF'.

  • 18q gain cnv correlated to 'CN_CNMF'.

  • 21q gain cnv correlated to 'CN_CNMF' and 'MIRSEQ_CHIERARCHICAL'.

  • 22q gain cnv correlated to 'CN_CNMF'.

  • 2q loss cnv correlated to 'CN_CNMF'.

  • 3p loss cnv correlated to 'MRNASEQ_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 4p loss cnv correlated to 'CN_CNMF'.

  • 4q loss cnv correlated to 'CN_CNMF'.

  • 6q loss cnv correlated to 'CN_CNMF'.

  • 8p loss cnv correlated to 'CN_CNMF'.

  • 9p loss cnv correlated to 'CN_CNMF'.

  • 9q loss cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

  • 10q loss cnv correlated to 'CN_CNMF'.

  • 11p 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'.

  • 14q loss cnv correlated to 'CN_CNMF'.

  • 15q loss cnv correlated to 'CN_CNMF'.

  • 16p loss cnv correlated to 'CN_CNMF'.

  • 16q 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 80 arm-level events and 10 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 35 significant findings detected.

Clinical
Features 		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 Chi-square 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
21q gain 75 (30%) 175 5.05e-05
(0.0392) 		0.024
(1.00) 		0.614
(1.00) 		0.568
(1.00) 		0.0964
(1.00) 		0.0652
(1.00) 		0.00041
(0.314) 		0.000199
(0.153) 		0.0176
(1.00) 		0.00259
(1.00)
3p loss 29 (12%) 221 0.00237
(1.00) 		0.0615
(1.00) 		0.0523
(1.00) 		0.0175
(1.00) 		2.13e-06
(0.00169) 		1.33e-05
(0.0105) 		0.671
(1.00) 		0.454
(1.00) 		0.268
(1.00) 		0.0117
(1.00)
11p loss 104 (42%) 146 2.39e-06
(0.00189) 		3.55e-07
(0.000282) 		0.25
(1.00) 		0.516
(1.00) 		0.014
(1.00) 		0.00118
(0.887) 		0.0383
(1.00) 		0.0904
(1.00) 		0.00469
(1.00) 		0.0311
(1.00)
11q loss 77 (31%) 173 8.57e-06
(0.00674) 		2.93e-05
(0.0229) 		0.0686
(1.00) 		0.0698
(1.00) 		0.0414
(1.00) 		0.0373
(1.00) 		0.33
(1.00) 		0.21
(1.00) 		0.0849
(1.00) 		0.0705
(1.00)
1p gain 53 (21%) 197 0.000196
(0.151) 		0.0539
(1.00) 		0.51
(1.00) 		0.511
(1.00) 		0.611
(1.00) 		1
(1.00) 		0.869
(1.00) 		0.941
(1.00) 		0.751
(1.00) 		0.931
(1.00)
2p gain 73 (29%) 177 4.13e-05
(0.0321) 		0.000882
(0.667) 		0.394
(1.00) 		0.783
(1.00) 		0.319
(1.00) 		0.262
(1.00) 		0.129
(1.00) 		0.127
(1.00) 		0.32
(1.00) 		0.00439
(1.00)
3p gain 89 (36%) 161 5.51e-06
(0.00435) 		0.112
(1.00) 		0.105
(1.00) 		0.311
(1.00) 		0.00849
(1.00) 		0.0452
(1.00) 		0.00137
(1.00) 		0.0278
(1.00) 		0.00326
(1.00) 		0.00874
(1.00)
3q gain 112 (45%) 138 0.000274
(0.21) 		0.712
(1.00) 		0.431
(1.00) 		0.926
(1.00) 		0.147
(1.00) 		0.0824
(1.00) 		0.0019
(1.00) 		0.00327
(1.00) 		0.00135
(1.00) 		0.00102
(0.773)
5p gain 103 (41%) 147 2.73e-05
(0.0213) 		0.599
(1.00) 		0.0422
(1.00) 		0.237
(1.00) 		0.29
(1.00) 		0.0183
(1.00) 		0.138
(1.00) 		0.0312
(1.00) 		0.263
(1.00) 		0.0313
(1.00)
7p gain 108 (43%) 142 0.000213
(0.164) 		0.0234
(1.00) 		0.0232
(1.00) 		0.858
(1.00) 		0.84
(1.00) 		0.411
(1.00) 		0.0699
(1.00) 		0.0811
(1.00) 		0.377
(1.00) 		0.385
(1.00)
8p gain 51 (20%) 199 1.43e-06
(0.00113) 		0.0347
(1.00) 		0.0529
(1.00) 		0.0601
(1.00) 		0.493
(1.00) 		0.324
(1.00) 		0.733
(1.00) 		0.333
(1.00) 		0.527
(1.00) 		0.216
(1.00)
9p gain 37 (15%) 213 1.86e-05
(0.0146) 		0.791
(1.00) 		0.631
(1.00) 		0.614
(1.00) 		0.129
(1.00) 		0.0199
(1.00) 		0.346
(1.00) 		1
(1.00) 		0.939
(1.00) 		0.528
(1.00)
10p gain 74 (30%) 176 1.2e-09
(9.62e-07) 		0.591
(1.00) 		0.804
(1.00) 		0.586
(1.00) 		0.905
(1.00) 		0.216
(1.00) 		0.524
(1.00) 		0.527
(1.00) 		0.966
(1.00) 		0.902
(1.00)
17p gain 34 (14%) 216 0.0212
(1.00) 		0.0659
(1.00) 		0.475
(1.00) 		0.714
(1.00) 		0.853
(1.00) 		0.425
(1.00) 		0.00125
(0.939) 		0.000187
(0.144) 		0.00321
(1.00) 		0.000505
(0.385)
18p gain 76 (30%) 174 5.83e-09
(4.66e-06) 		0.00386
(1.00) 		0.935
(1.00) 		0.824
(1.00) 		0.102
(1.00) 		0.0591
(1.00) 		0.688
(1.00) 		0.0349
(1.00) 		0.611
(1.00) 		0.979
(1.00)
18q gain 39 (16%) 211 0.000306
(0.234) 		0.00648
(1.00) 		0.44
(1.00) 		0.236
(1.00) 		0.606
(1.00) 		0.214
(1.00) 		0.679
(1.00) 		0.251
(1.00) 		0.507
(1.00) 		0.886
(1.00)
22q gain 35 (14%) 215 7.92e-05
(0.0613) 		0.00312
(1.00) 		0.475
(1.00) 		0.62
(1.00) 		0.0416
(1.00) 		0.15
(1.00) 		0.2
(1.00) 		0.232
(1.00) 		0.581
(1.00) 		0.358
(1.00)
2q loss 57 (23%) 193 2.4e-05
(0.0188) 		0.0381
(1.00) 		0.602
(1.00) 		0.308
(1.00) 		0.185
(1.00) 		0.069
(1.00) 		0.653
(1.00) 		0.328
(1.00) 		0.168
(1.00) 		0.0341
(1.00)
4p loss 84 (34%) 166 0.000114
(0.0883) 		0.45
(1.00) 		0.571
(1.00) 		0.447
(1.00) 		0.072
(1.00) 		0.039
(1.00) 		0.119
(1.00) 		0.706
(1.00) 		0.16
(1.00) 		0.0433
(1.00)
4q loss 86 (34%) 164 6.13e-06
(0.00483) 		0.175
(1.00) 		0.194
(1.00) 		0.25
(1.00) 		0.0692
(1.00) 		0.0533
(1.00) 		0.222
(1.00) 		0.434
(1.00) 		0.0926
(1.00) 		0.0326
(1.00)
6q loss 93 (37%) 157 1.86e-06
(0.00147) 		0.000421
(0.322) 		0.837
(1.00) 		0.559
(1.00) 		0.545
(1.00) 		0.0121
(1.00) 		0.799
(1.00) 		0.711
(1.00) 		0.896
(1.00) 		0.399
(1.00)
8p loss 113 (45%) 137 1.49e-07
(0.000118) 		0.104
(1.00) 		0.136
(1.00) 		0.0727
(1.00) 		0.0387
(1.00) 		0.0187
(1.00) 		0.00831
(1.00) 		0.0355
(1.00) 		0.0504
(1.00) 		0.00595
(1.00)
9p loss 109 (44%) 141 3.3e-05
(0.0257) 		0.201
(1.00) 		0.283
(1.00) 		0.0752
(1.00) 		0.69
(1.00) 		0.0218
(1.00) 		0.835
(1.00) 		0.202
(1.00) 		0.782
(1.00) 		0.947
(1.00)
9q loss 99 (40%) 151 0.161
(1.00) 		0.00635
(1.00) 		0.0319
(1.00) 		0.00701
(1.00) 		0.0298
(1.00) 		2.39e-05
(0.0187) 		1
(1.00) 		0.756
(1.00) 		0.471
(1.00) 		0.509
(1.00)
10q loss 83 (33%) 167 6.47e-06
(0.00509) 		0.00222
(1.00) 		0.479
(1.00) 		0.792
(1.00) 		0.112
(1.00) 		0.222
(1.00) 		0.29
(1.00) 		0.322
(1.00) 		0.291
(1.00) 		0.432
(1.00)
13q loss 53 (21%) 197 0.000271
(0.208) 		0.412
(1.00) 		0.00573
(1.00) 		0.0292
(1.00) 		0.0878
(1.00) 		0.565
(1.00) 		0.901
(1.00) 		0.36
(1.00) 		0.971
(1.00) 		0.259
(1.00)
14q loss 74 (30%) 176 3.93e-07
(0.000312) 		0.112
(1.00) 		0.118
(1.00) 		0.048
(1.00) 		0.0683
(1.00) 		0.000468
(0.357) 		0.00888
(1.00) 		0.0739
(1.00) 		0.0109
(1.00) 		0.406
(1.00)
15q loss 85 (34%) 165 7.1e-05
(0.055) 		0.0033
(1.00) 		0.0999
(1.00) 		0.289
(1.00) 		0.139
(1.00) 		0.0152
(1.00) 		0.0853
(1.00) 		0.0524
(1.00) 		0.0468
(1.00) 		0.44
(1.00)
16p loss 64 (26%) 186 5.46e-08
(4.35e-05) 		0.0927
(1.00) 		0.575
(1.00) 		0.393
(1.00) 		0.251
(1.00) 		0.831
(1.00) 		0.935
(1.00) 		0.537
(1.00) 		0.469
(1.00) 		0.916
(1.00)
16q loss 58 (23%) 192 9.06e-09
(7.23e-06) 		0.0342
(1.00) 		0.237
(1.00) 		0.912
(1.00) 		0.867
(1.00) 		0.915
(1.00) 		0.731
(1.00) 		0.447
(1.00) 		0.739
(1.00) 		0.372
(1.00)
22q loss 97 (39%) 153 1.6e-05
(0.0125) 		0.0067
(1.00) 		0.548
(1.00) 		0.0155
(1.00) 		0.00676
(1.00) 		0.0131
(1.00) 		0.716
(1.00) 		0.556
(1.00) 		0.0608
(1.00) 		0.0586
(1.00)
1q gain 78 (31%) 172 0.00237
(1.00) 		0.319
(1.00) 		0.57
(1.00) 		0.714
(1.00) 		0.753
(1.00) 		0.938
(1.00) 		0.826
(1.00) 		0.627
(1.00) 		0.466
(1.00) 		0.971
(1.00)
2q gain 34 (14%) 216 0.0372
(1.00) 		0.0739
(1.00) 		0.529
(1.00) 		0.702
(1.00) 		0.862
(1.00) 		0.752
(1.00) 		0.631
(1.00) 		0.463
(1.00) 		0.945
(1.00) 		0.349
(1.00)
4p gain 31 (12%) 219 0.0615
(1.00) 		0.0109
(1.00) 		0.478
(1.00) 		0.655
(1.00) 		0.0374
(1.00) 		0.0266
(1.00) 		0.178
(1.00) 		0.238
(1.00) 		0.181
(1.00) 		0.00603
(1.00)
4q gain 18 (7%) 232 0.0566
(1.00) 		0.0514
(1.00) 		0.569
(1.00) 		0.161
(1.00) 		0.048
(1.00) 		0.0602
(1.00) 		0.253
(1.00) 		0.336
(1.00) 		0.468
(1.00) 		0.42
(1.00)
5q gain 36 (14%) 214 0.00433
(1.00) 		0.207
(1.00) 		0.0172
(1.00) 		0.659
(1.00) 		0.64
(1.00) 		0.673
(1.00) 		0.115
(1.00) 		0.0549
(1.00) 		0.0319
(1.00) 		0.29
(1.00)
6p gain 40 (16%) 210 0.0695
(1.00) 		0.76
(1.00) 		0.786
(1.00) 		0.177
(1.00) 		0.349
(1.00) 		0.503
(1.00) 		0.53
(1.00) 		0.0536
(1.00) 		0.696
(1.00) 		0.659
(1.00)
6q gain 22 (9%) 228 0.346
(1.00) 		0.674
(1.00) 		0.934
(1.00) 		0.101
(1.00) 		0.138
(1.00) 		0.288
(1.00) 		0.3
(1.00) 		0.0952
(1.00) 		0.513
(1.00) 		0.707
(1.00)
7q gain 96 (38%) 154 0.00125
(0.942) 		0.0388
(1.00) 		0.183
(1.00) 		0.917
(1.00) 		0.678
(1.00) 		0.374
(1.00) 		0.144
(1.00) 		0.0447
(1.00) 		0.308
(1.00) 		0.303
(1.00)
8q gain 111 (44%) 139 0.00742
(1.00) 		0.108
(1.00) 		0.0504
(1.00) 		0.159
(1.00) 		0.752
(1.00) 		0.759
(1.00) 		0.695
(1.00) 		0.862
(1.00) 		0.436
(1.00) 		0.144
(1.00)
9q gain 32 (13%) 218 0.0575
(1.00) 		0.0353
(1.00) 		0.776
(1.00) 		0.0315
(1.00) 		0.00473
(1.00) 		0.00369
(1.00) 		0.909
(1.00) 		0.532
(1.00) 		0.52
(1.00) 		0.0845
(1.00)
10q gain 23 (9%) 227 0.0238
(1.00) 		0.442
(1.00) 		0.436
(1.00) 		0.322
(1.00) 		0.802
(1.00) 		0.146
(1.00) 		0.266
(1.00) 		1
(1.00) 		0.564
(1.00) 		0.871
(1.00)
11p gain 23 (9%) 227 0.0275
(1.00) 		0.167
(1.00) 		0.181
(1.00) 		0.0947
(1.00) 		0.057
(1.00) 		0.0362
(1.00) 		0.661
(1.00) 		0.304
(1.00) 		0.495
(1.00) 		0.0529
(1.00)
11q gain 33 (13%) 217 0.0243
(1.00) 		0.136
(1.00) 		0.152
(1.00) 		0.0161
(1.00) 		0.148
(1.00) 		0.0331
(1.00) 		0.927
(1.00) 		0.463
(1.00) 		0.43
(1.00) 		0.0392
(1.00)
12p gain 73 (29%) 177 0.00269
(1.00) 		0.169
(1.00) 		0.677
(1.00) 		0.413
(1.00) 		0.934
(1.00) 		1
(1.00) 		1
(1.00) 		0.0144
(1.00) 		0.975
(1.00) 		0.216
(1.00)
12q gain 52 (21%) 198 0.00745
(1.00) 		0.0459
(1.00) 		0.0991
(1.00) 		0.0241
(1.00) 		0.19
(1.00) 		0.264
(1.00) 		0.406
(1.00) 		0.118
(1.00) 		0.482
(1.00) 		0.0819
(1.00)
13q gain 64 (26%) 186 0.101
(1.00) 		0.739
(1.00) 		0.966
(1.00) 		0.85
(1.00) 		0.14
(1.00) 		0.901
(1.00) 		0.669
(1.00) 		0.523
(1.00) 		1
(1.00) 		0.538
(1.00)
14q gain 41 (16%) 209 0.00434
(1.00) 		0.08
(1.00) 		0.364
(1.00) 		0.525
(1.00) 		0.0433
(1.00) 		0.0266
(1.00) 		0.901
(1.00) 		0.43
(1.00) 		0.518
(1.00) 		0.962
(1.00)
15q gain 23 (9%) 227 0.501
(1.00) 		0.0119
(1.00) 		0.576
(1.00) 		0.396
(1.00) 		0.93
(1.00) 		0.231
(1.00) 		0.373
(1.00) 		0.821
(1.00) 		1
(1.00) 		1
(1.00)
16p gain 42 (17%) 208 0.00603
(1.00) 		0.901
(1.00) 		0.281
(1.00) 		0.636
(1.00) 		0.894
(1.00) 		0.404
(1.00) 		0.446
(1.00) 		0.73
(1.00) 		0.528
(1.00) 		1
(1.00)
16q gain 51 (20%) 199 0.00988
(1.00) 		0.441
(1.00) 		0.0986
(1.00) 		0.438
(1.00) 		0.447
(1.00) 		0.0809
(1.00) 		0.324
(1.00) 		1
(1.00) 		0.169
(1.00) 		0.534
(1.00)
17q gain 84 (34%) 166 0.0181
(1.00) 		0.00854
(1.00) 		0.451
(1.00) 		0.528
(1.00) 		0.243
(1.00) 		0.195
(1.00) 		0.0748
(1.00) 		0.0105
(1.00) 		0.00486
(1.00) 		0.014
(1.00)
19p gain 49 (20%) 201 0.269
(1.00) 		0.121
(1.00) 		0.286
(1.00) 		0.565
(1.00) 		0.0575
(1.00) 		0.15
(1.00) 		0.197
(1.00) 		0.0405
(1.00) 		0.577
(1.00) 		0.194
(1.00)
19q gain 84 (34%) 166 0.000852
(0.646) 		0.0486
(1.00) 		0.294
(1.00) 		0.666
(1.00) 		0.39
(1.00) 		0.211
(1.00) 		0.334
(1.00) 		0.0439
(1.00) 		0.796
(1.00) 		0.375
(1.00)
20p gain 126 (50%) 124 0.00483
(1.00) 		0.0309
(1.00) 		0.516
(1.00) 		0.0433
(1.00) 		0.834
(1.00) 		0.0908
(1.00) 		0.0883
(1.00) 		0.14
(1.00) 		0.00878
(1.00) 		0.11
(1.00)
20q gain 140 (56%) 110 0.000799
(0.607) 		0.0579
(1.00) 		0.374
(1.00) 		0.153
(1.00) 		1
(1.00) 		0.208
(1.00) 		0.0607
(1.00) 		0.0288
(1.00) 		0.043
(1.00) 		0.302
(1.00)
xq gain 30 (12%) 220 0.103
(1.00) 		0.0848
(1.00) 		0.401
(1.00) 		0.848
(1.00) 		0.738
(1.00) 		0.434
(1.00) 		0.445
(1.00) 		1
(1.00) 		0.623
(1.00) 		0.6
(1.00)
1p loss 20 (8%) 230 0.0203
(1.00) 		1
(1.00) 		0.139
(1.00) 		0.118
(1.00) 		0.802
(1.00) 		0.146
(1.00) 		0.437
(1.00) 		0.157
(1.00) 		0.921
(1.00) 		0.694
(1.00)
1q loss 22 (9%) 228 0.00332
(1.00) 		0.915
(1.00) 		0.569
(1.00) 		1
(1.00) 		0.64
(1.00) 		0.145
(1.00) 		0.601
(1.00) 		0.541
(1.00) 		0.827
(1.00) 		0.919
(1.00)
2p loss 25 (10%) 225 0.00518
(1.00) 		0.123
(1.00) 		0.841
(1.00) 		0.759
(1.00) 		0.77
(1.00) 		0.202
(1.00) 		0.203
(1.00) 		0.572
(1.00) 		0.463
(1.00) 		0.284
(1.00)
3q loss 13 (5%) 237 0.126
(1.00) 		0.308
(1.00) 		0.00159
(1.00) 		0.0123
(1.00) 		0.0262
(1.00) 		0.0205
(1.00) 		1
(1.00) 		1
(1.00) 		0.901
(1.00) 		0.185
(1.00)
5p loss 39 (16%) 211 0.642
(1.00) 		0.716
(1.00) 		0.391
(1.00) 		0.602
(1.00) 		0.874
(1.00) 		0.191
(1.00) 		0.849
(1.00) 		0.86
(1.00) 		0.541
(1.00) 		0.752
(1.00)
5q loss 100 (40%) 150 0.00104
(0.786) 		0.192
(1.00) 		0.824
(1.00) 		0.292
(1.00) 		0.0986
(1.00) 		0.00386
(1.00) 		0.935
(1.00) 		0.54
(1.00) 		0.493
(1.00) 		0.321
(1.00)
6p loss 61 (24%) 189 0.0964
(1.00) 		0.000629
(0.478) 		0.766
(1.00) 		0.835
(1.00) 		0.239
(1.00) 		0.00738
(1.00) 		0.625
(1.00) 		0.757
(1.00) 		0.703
(1.00) 		0.115
(1.00)
7p loss 10 (4%) 240 0.688
(1.00) 		0.772
(1.00) 		0.385
(1.00) 		0.924
(1.00) 		1
(1.00) 		0.645
(1.00) 		0.417
(1.00) 		0.0138
(1.00) 		0.279
(1.00) 		0.83
(1.00)
7q loss 15 (6%) 235 0.245
(1.00) 		0.8
(1.00) 		0.312
(1.00) 		0.833
(1.00) 		0.943
(1.00) 		0.901
(1.00) 		0.388
(1.00) 		0.00127
(0.957) 		1
(1.00) 		0.938
(1.00)
8q loss 27 (11%) 223 0.424
(1.00) 		0.27
(1.00) 		0.333
(1.00) 		0.0167
(1.00) 		0.0542
(1.00) 		0.0429
(1.00) 		0.00881
(1.00) 		0.426
(1.00) 		0.00971
(1.00) 		0.00322
(1.00)
10p loss 46 (18%) 204 0.000492
(0.375) 		0.016
(1.00) 		0.788
(1.00) 		0.51
(1.00) 		0.04
(1.00) 		0.0925
(1.00) 		0.0838
(1.00) 		0.0416
(1.00) 		0.286
(1.00) 		0.12
(1.00)
12p loss 25 (10%) 225 0.0573
(1.00) 		0.157
(1.00) 		0.87
(1.00) 		0.41
(1.00) 		0.577
(1.00) 		0.654
(1.00) 		0.407
(1.00) 		0.614
(1.00) 		0.752
(1.00) 		0.942
(1.00)
12q loss 32 (13%) 218 0.0477
(1.00) 		0.838
(1.00) 		0.333
(1.00) 		0.542
(1.00) 		0.721
(1.00) 		0.296
(1.00) 		0.723
(1.00) 		0.691
(1.00) 		0.856
(1.00) 		0.818
(1.00)
17p loss 109 (44%) 141 0.0622
(1.00) 		0.259
(1.00) 		0.947
(1.00) 		0.362
(1.00) 		0.263
(1.00) 		0.697
(1.00) 		0.381
(1.00) 		0.436
(1.00) 		0.291
(1.00) 		0.0779
(1.00)
17q loss 27 (11%) 223 0.683
(1.00) 		0.165
(1.00) 		0.896
(1.00) 		0.783
(1.00) 		0.681
(1.00) 		0.748
(1.00) 		0.791
(1.00) 		0.339
(1.00) 		0.814
(1.00) 		0.606
(1.00)
18p loss 57 (23%) 193 0.0193
(1.00) 		0.569
(1.00) 		0.46
(1.00) 		0.274
(1.00) 		0.836
(1.00) 		0.255
(1.00) 		0.517
(1.00) 		0.162
(1.00) 		0.619
(1.00) 		0.318
(1.00)
18q loss 86 (34%) 164 0.00365
(1.00) 		0.737
(1.00) 		0.548
(1.00) 		0.84
(1.00) 		0.75
(1.00) 		0.932
(1.00) 		0.0429
(1.00) 		0.0172
(1.00) 		0.0405
(1.00) 		0.348
(1.00)
19p loss 64 (26%) 186 0.0433
(1.00) 		0.424
(1.00) 		0.68
(1.00) 		0.404
(1.00) 		0.019
(1.00) 		0.0688
(1.00) 		1
(1.00) 		0.498
(1.00) 		0.672
(1.00) 		0.299
(1.00)
19q loss 39 (16%) 211 0.208
(1.00) 		0.884
(1.00) 		0.208
(1.00) 		0.101
(1.00) 		0.251
(1.00) 		0.448
(1.00) 		0.228
(1.00) 		0.678
(1.00) 		0.291
(1.00) 		0.169
(1.00)
20p loss 20 (8%) 230 0.144
(1.00) 		0.154
(1.00) 		0.259
(1.00) 		0.0352
(1.00) 		0.918
(1.00) 		0.437
(1.00) 		0.839
(1.00) 		1
(1.00) 		0.286
(1.00) 		0.483
(1.00)
20q loss 8 (3%) 242 0.41
(1.00) 		0.716
(1.00) 		0.331
(1.00) 		0.287
(1.00) 		0.557
(1.00) 		0.791
(1.00) 		0.593
(1.00) 		0.809
(1.00) 		1
(1.00) 		0.44
(1.00)
21q loss 41 (16%) 209 0.479
(1.00) 		0.527
(1.00) 		0.114
(1.00) 		0.189
(1.00) 		0.00936
(1.00) 		0.116
(1.00) 		0.567
(1.00) 		0.244
(1.00) 		0.653
(1.00) 		0.181
(1.00)
xq loss 48 (19%) 202 0.00175
(1.00) 		0.0255
(1.00) 		0.981
(1.00) 		1
(1.00) 		0.155
(1.00) 		0.471
(1.00) 		0.0822
(1.00) 		0.729
(1.00) 		0.0361
(1.00) 		0.167
(1.00)
'1p gain' versus 'CN_CNMF'

P value = 0.000196 (Chi-square test), Q value = 0.15

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

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
1P GAIN MUTATED 1 7 7 5 9 11 11 2
1P GAIN WILD-TYPE 14 81 10 15 29 21 13 14

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

'2p gain' versus 'CN_CNMF'

P value = 4.13e-05 (Chi-square test), Q value = 0.032

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

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
2P GAIN MUTATED 6 7 6 9 16 12 12 5
2P GAIN WILD-TYPE 9 81 11 11 22 20 12 11

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

'3p gain' versus 'CN_CNMF'

P value = 5.51e-06 (Chi-square test), Q value = 0.0043

Table S3.  Gene #5: '3p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
3P GAIN MUTATED 9 20 11 8 10 10 18 3
3P GAIN WILD-TYPE 6 68 6 12 28 22 6 13

Figure S3.  Get High-res Image Gene #5: '3p gain' versus Molecular Subtype #1: 'CN_CNMF'

'3q gain' versus 'CN_CNMF'

P value = 0.000274 (Chi-square test), Q value = 0.21

Table S4.  Gene #6: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
3Q GAIN MUTATED 11 24 11 10 17 17 17 5
3Q GAIN WILD-TYPE 4 64 6 10 21 15 7 11

Figure S4.  Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

'5p gain' versus 'CN_CNMF'

P value = 2.73e-05 (Chi-square test), Q value = 0.021

Table S5.  Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
5P GAIN MUTATED 7 19 8 6 21 18 18 6
5P GAIN WILD-TYPE 8 69 9 14 17 14 6 10

Figure S5.  Get High-res Image Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

'7p gain' versus 'CN_CNMF'

P value = 0.000213 (Chi-square test), Q value = 0.16

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

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
7P GAIN MUTATED 7 21 10 9 21 22 13 5
7P GAIN WILD-TYPE 8 67 7 11 17 10 11 11

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

'8p gain' versus 'CN_CNMF'

P value = 1.43e-06 (Chi-square test), Q value = 0.0011

Table S7.  Gene #15: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
8P GAIN MUTATED 5 14 12 7 8 2 2 1
8P GAIN WILD-TYPE 10 74 5 13 30 30 22 15

Figure S7.  Get High-res Image Gene #15: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

'9p gain' versus 'CN_CNMF'

P value = 1.86e-05 (Chi-square test), Q value = 0.015

Table S8.  Gene #17: '9p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
9P GAIN MUTATED 3 3 4 2 2 12 5 6
9P GAIN WILD-TYPE 12 85 13 18 36 20 19 10

Figure S8.  Get High-res Image Gene #17: '9p gain' versus Molecular Subtype #1: 'CN_CNMF'

'10p gain' versus 'CN_CNMF'

P value = 1.2e-09 (Chi-square test), Q value = 9.6e-07

Table S9.  Gene #19: '10p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
10P GAIN MUTATED 8 5 5 14 10 13 14 5
10P GAIN WILD-TYPE 7 83 12 6 28 19 10 11

Figure S9.  Get High-res Image Gene #19: '10p gain' versus Molecular Subtype #1: 'CN_CNMF'

'17p gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000187 (Fisher's exact test), Q value = 0.14

Table S10.  Gene #30: '17p gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 176 15 58
17P GAIN MUTATED 15 1 18
17P GAIN WILD-TYPE 161 14 40

Figure S10.  Get High-res Image Gene #30: '17p gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

'18p gain' versus 'CN_CNMF'

P value = 5.83e-09 (Chi-square test), Q value = 4.7e-06

Table S11.  Gene #32: '18p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
18P GAIN MUTATED 2 5 7 7 18 13 14 10
18P GAIN WILD-TYPE 13 83 10 13 20 19 10 6

Figure S11.  Get High-res Image Gene #32: '18p gain' versus Molecular Subtype #1: 'CN_CNMF'

'18q gain' versus 'CN_CNMF'

P value = 0.000306 (Chi-square test), Q value = 0.23

Table S12.  Gene #33: '18q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
18Q GAIN MUTATED 2 4 5 4 6 4 6 8
18Q GAIN WILD-TYPE 13 84 12 16 32 28 18 8

Figure S12.  Get High-res Image Gene #33: '18q gain' versus Molecular Subtype #1: 'CN_CNMF'

'21q gain' versus 'CN_CNMF'

P value = 5.05e-05 (Chi-square test), Q value = 0.039

Table S13.  Gene #38: '21q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
21Q GAIN MUTATED 5 8 6 9 13 16 11 7
21Q GAIN WILD-TYPE 10 80 11 11 25 16 13 9

Figure S13.  Get High-res Image Gene #38: '21q gain' versus Molecular Subtype #1: 'CN_CNMF'

'21q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000199 (Fisher's exact test), Q value = 0.15

Table S14.  Gene #38: '21q gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 176 15 58
21Q GAIN MUTATED 40 4 30
21Q GAIN WILD-TYPE 136 11 28

Figure S14.  Get High-res Image Gene #38: '21q gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

'22q gain' versus 'CN_CNMF'

P value = 7.92e-05 (Chi-square test), Q value = 0.061

Table S15.  Gene #39: '22q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
22Q GAIN MUTATED 6 6 7 0 3 7 5 1
22Q GAIN WILD-TYPE 9 82 10 20 35 25 19 15

Figure S15.  Get High-res Image Gene #39: '22q gain' versus Molecular Subtype #1: 'CN_CNMF'

'2q loss' versus 'CN_CNMF'

P value = 2.4e-05 (Chi-square test), Q value = 0.019

Table S16.  Gene #44: '2q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
2Q LOSS MUTATED 2 6 6 7 11 6 13 6
2Q LOSS WILD-TYPE 13 82 11 13 27 26 11 10

Figure S16.  Get High-res Image Gene #44: '2q loss' versus Molecular Subtype #1: 'CN_CNMF'

'3p loss' versus 'MRNASEQ_CNMF'

P value = 2.13e-06 (Fisher's exact test), Q value = 0.0017

Table S17.  Gene #45: '3p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 104 70 64
3P LOSS MUTATED 6 3 20
3P LOSS WILD-TYPE 98 67 44

Figure S17.  Get High-res Image Gene #45: '3p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'3p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1.33e-05 (Fisher's exact test), Q value = 0.01

Table S18.  Gene #45: '3p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 98 48 92
3P LOSS MUTATED 23 0 6
3P LOSS WILD-TYPE 75 48 86

Figure S18.  Get High-res Image Gene #45: '3p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'4p loss' versus 'CN_CNMF'

P value = 0.000114 (Chi-square test), Q value = 0.088

Table S19.  Gene #47: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
4P LOSS MUTATED 3 13 8 8 21 16 10 5
4P LOSS WILD-TYPE 12 75 9 12 17 16 14 11

Figure S19.  Get High-res Image Gene #47: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

'4q loss' versus 'CN_CNMF'

P value = 6.13e-06 (Chi-square test), Q value = 0.0048

Table S20.  Gene #48: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
4Q LOSS MUTATED 3 12 8 6 23 15 11 8
4Q LOSS WILD-TYPE 12 76 9 14 15 17 13 8

Figure S20.  Get High-res Image Gene #48: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

'6q loss' versus 'CN_CNMF'

P value = 1.86e-06 (Chi-square test), Q value = 0.0015

Table S21.  Gene #52: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
6Q LOSS MUTATED 10 12 9 9 21 11 14 7
6Q LOSS WILD-TYPE 5 76 8 11 17 21 10 9

Figure S21.  Get High-res Image Gene #52: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'8p loss' versus 'CN_CNMF'

P value = 1.49e-07 (Chi-square test), Q value = 0.00012

Table S22.  Gene #55: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
8P LOSS MUTATED 7 24 1 9 20 22 17 13
8P LOSS WILD-TYPE 8 64 16 11 18 10 7 3

Figure S22.  Get High-res Image Gene #55: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'CN_CNMF'

P value = 3.3e-05 (Chi-square test), Q value = 0.026

Table S23.  Gene #57: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
9P LOSS MUTATED 5 36 7 10 29 8 13 1
9P LOSS WILD-TYPE 10 52 10 10 9 24 11 15

Figure S23.  Get High-res Image Gene #57: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.39e-05 (Fisher's exact test), Q value = 0.019

Table S24.  Gene #58: '9q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 98 48 92
9Q LOSS MUTATED 23 28 45
9Q LOSS WILD-TYPE 75 20 47

Figure S24.  Get High-res Image Gene #58: '9q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'10q loss' versus 'CN_CNMF'

P value = 6.47e-06 (Chi-square test), Q value = 0.0051

Table S25.  Gene #60: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
10Q LOSS MUTATED 5 9 7 7 21 15 11 8
10Q LOSS WILD-TYPE 10 79 10 13 17 17 13 8

Figure S25.  Get High-res Image Gene #60: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

'11p loss' versus 'CN_CNMF'

P value = 2.39e-06 (Chi-square test), Q value = 0.0019

Table S26.  Gene #61: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
11P LOSS MUTATED 9 18 9 13 26 12 13 4
11P LOSS WILD-TYPE 6 70 8 7 12 20 11 12

Figure S26.  Get High-res Image Gene #61: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

'11p loss' versus 'METHLYATION_CNMF'

P value = 3.55e-07 (Fisher's exact test), Q value = 0.00028

Table S27.  Gene #61: '11p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 98 103 49
11P LOSS MUTATED 58 23 23
11P LOSS WILD-TYPE 40 80 26

Figure S27.  Get High-res Image Gene #61: '11p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'11q loss' versus 'CN_CNMF'

P value = 8.57e-06 (Chi-square test), Q value = 0.0067

Table S28.  Gene #62: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
11Q LOSS MUTATED 7 10 8 9 20 8 12 3
11Q LOSS WILD-TYPE 8 78 9 11 18 24 12 13

Figure S28.  Get High-res Image Gene #62: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

'11q loss' versus 'METHLYATION_CNMF'

P value = 2.93e-05 (Fisher's exact test), Q value = 0.023

Table S29.  Gene #62: '11q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 98 103 49
11Q LOSS MUTATED 46 18 13
11Q LOSS WILD-TYPE 52 85 36

Figure S29.  Get High-res Image Gene #62: '11q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'13q loss' versus 'CN_CNMF'

P value = 0.000271 (Chi-square test), Q value = 0.21

Table S30.  Gene #65: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
13Q LOSS MUTATED 4 5 7 4 15 10 6 2
13Q LOSS WILD-TYPE 11 83 10 16 23 22 18 14

Figure S30.  Get High-res Image Gene #65: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

'14q loss' versus 'CN_CNMF'

P value = 3.93e-07 (Chi-square test), Q value = 0.00031

Table S31.  Gene #66: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
14Q LOSS MUTATED 7 16 2 12 6 16 14 1
14Q LOSS WILD-TYPE 8 72 15 8 32 16 10 15

Figure S31.  Get High-res Image Gene #66: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

'15q loss' versus 'CN_CNMF'

P value = 7.1e-05 (Chi-square test), Q value = 0.055

Table S32.  Gene #67: '15q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
15Q LOSS MUTATED 6 13 3 9 21 13 12 8
15Q LOSS WILD-TYPE 9 75 14 11 17 19 12 8

Figure S32.  Get High-res Image Gene #67: '15q loss' versus Molecular Subtype #1: 'CN_CNMF'

'16p loss' versus 'CN_CNMF'

P value = 5.46e-08 (Chi-square test), Q value = 4.3e-05

Table S33.  Gene #68: '16p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
16P LOSS MUTATED 4 5 5 2 17 11 9 11
16P LOSS WILD-TYPE 11 83 12 18 21 21 15 5

Figure S33.  Get High-res Image Gene #68: '16p loss' versus Molecular Subtype #1: 'CN_CNMF'

'16q loss' versus 'CN_CNMF'

P value = 9.06e-09 (Chi-square test), Q value = 7.2e-06

Table S34.  Gene #69: '16q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
16Q LOSS MUTATED 4 3 7 0 16 9 10 9
16Q LOSS WILD-TYPE 11 85 10 20 22 23 14 7

Figure S34.  Get High-res Image Gene #69: '16q loss' versus Molecular Subtype #1: 'CN_CNMF'

'22q loss' versus 'CN_CNMF'

P value = 1.6e-05 (Chi-square test), Q value = 0.013

Table S35.  Gene #79: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 15 88 17 20 38 32 24 16
22Q LOSS MUTATED 5 15 6 12 21 16 11 11
22Q LOSS WILD-TYPE 10 73 11 8 17 16 13 5

Figure S35.  Get High-res Image Gene #79: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data
Input

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

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

  • Number of patients = 250

  • Number of significantly arm-level cnvs = 80

  • Number of molecular subtypes = 10

  • 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

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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[2] Fisher, R.A., On the interpretation of chi-square from contingency tables, and the calculation of P, Journal of the Royal Statistical Society 85(1):87-94 (1922)
[3] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
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