Correlation between copy number variations of arm-level result and molecular subtypes
Bladder Urothelial Carcinoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C198859R
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/C198859R
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 77 arm-level results and 10 molecular subtypes across 182 patients, 22 significant findings detected with Q value < 0.25.

  • 1p gain cnv correlated to 'CN_CNMF'.

  • 2p gain cnv correlated to 'CN_CNMF'.

  • 3q gain cnv correlated to 'CN_CNMF'.

  • 5p gain cnv correlated to 'CN_CNMF'.

  • 8q gain cnv correlated to 'CN_CNMF'.

  • 10p gain cnv correlated to 'CN_CNMF'.

  • 17q gain cnv correlated to 'MIRSEQ_MATURE_CNMF'.

  • 18p gain cnv correlated to 'CN_CNMF'.

  • 5q 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',  'METHLYATION_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 9q loss cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 10q loss cnv correlated to 'CN_CNMF'.

  • 11p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_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 77 arm-level results and 10 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 22 significant findings detected.

Molecular
subtypes 		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 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
9p loss 0 (0%) 128 2.97e-06
(0.00226) 		0.000178
(0.133) 		0.15
(1.00) 		0.00152
(1.00) 		0.000486
(0.36) 		1.38e-05
(0.0105) 		0.344
(1.00) 		0.548
(1.00) 		0.0741
(1.00) 		0.015
(1.00)
9q loss 0 (0%) 130 7.61e-05
(0.057) 		0.000459
(0.341) 		0.0166
(1.00) 		0.00117
(0.861) 		0.000535
(0.396) 		3.05e-06
(0.00231) 		0.581
(1.00) 		0.702
(1.00) 		0.085
(1.00) 		0.0414
(1.00)
11p loss 0 (0%) 130 9.99e-05
(0.0746) 		9.48e-05
(0.0709) 		0.0259
(1.00) 		0.464
(1.00) 		0.00875
(1.00) 		0.00828
(1.00) 		0.172
(1.00) 		0.816
(1.00) 		0.193
(1.00) 		0.14
(1.00)
1p gain 0 (0%) 160 3.04e-05
(0.023) 		0.28
(1.00) 		0.387
(1.00) 		0.0238
(1.00) 		0.0723
(1.00) 		0.8
(1.00) 		0.957
(1.00) 		0.356
(1.00) 		0.833
(1.00) 		1
(1.00)
2p gain 0 (0%) 152 5.37e-05
(0.0404) 		0.013
(1.00) 		0.223
(1.00) 		0.627
(1.00) 		0.0186
(1.00) 		0.478
(1.00) 		0.0912
(1.00) 		0.0841
(1.00) 		0.163
(1.00) 		0.0129
(1.00)
3q gain 0 (0%) 133 1.18e-06
(0.000897) 		0.0967
(1.00) 		0.102
(1.00) 		0.2
(1.00) 		0.0357
(1.00) 		0.0561
(1.00) 		0.216
(1.00) 		0.187
(1.00) 		0.0941
(1.00) 		0.0533
(1.00)
5p gain 0 (0%) 130 7.4e-05
(0.0555) 		0.832
(1.00) 		0.0227
(1.00) 		0.445
(1.00) 		0.0864
(1.00) 		0.019
(1.00) 		0.609
(1.00) 		0.255
(1.00) 		0.519
(1.00) 		0.26
(1.00)
8q gain 0 (0%) 126 2.53e-05
(0.0192) 		0.0966
(1.00) 		0.367
(1.00) 		0.14
(1.00) 		0.15
(1.00) 		0.296
(1.00) 		0.934
(1.00) 		0.865
(1.00) 		0.791
(1.00) 		0.273
(1.00)
10p gain 0 (0%) 146 4.56e-05
(0.0344) 		0.398
(1.00) 		0.157
(1.00) 		0.342
(1.00) 		0.576
(1.00) 		0.102
(1.00) 		0.344
(1.00) 		0.189
(1.00) 		0.108
(1.00) 		0.578
(1.00)
17q gain 0 (0%) 153 0.0094
(1.00) 		0.00335
(1.00) 		0.00685
(1.00) 		0.00487
(1.00) 		0.00552
(1.00) 		0.0491
(1.00) 		0.0268
(1.00) 		0.0318
(1.00) 		0.000256
(0.191) 		0.00269
(1.00)
18p gain 0 (0%) 150 4.52e-05
(0.0341) 		0.00364
(1.00) 		0.812
(1.00) 		0.943
(1.00) 		0.0583
(1.00) 		0.14
(1.00) 		0.569
(1.00) 		0.0899
(1.00) 		0.523
(1.00) 		0.505
(1.00)
5q loss 0 (0%) 140 3.26e-05
(0.0246) 		0.118
(1.00) 		0.484
(1.00) 		0.194
(1.00) 		0.355
(1.00) 		0.552
(1.00) 		0.16
(1.00) 		0.49
(1.00) 		0.604
(1.00) 		1
(1.00)
6q loss 0 (0%) 147 0.000115
(0.0857) 		0.0101
(1.00) 		0.105
(1.00) 		0.835
(1.00) 		0.474
(1.00) 		0.214
(1.00) 		1
(1.00) 		0.935
(1.00) 		0.776
(1.00) 		0.495
(1.00)
8p loss 0 (0%) 124 2.17e-09
(1.66e-06) 		0.535
(1.00) 		0.432
(1.00) 		0.0542
(1.00) 		0.139
(1.00) 		0.0825
(1.00) 		0.035
(1.00) 		0.0664
(1.00) 		0.104
(1.00) 		0.0376
(1.00)
10q loss 0 (0%) 148 0.000263
(0.196) 		0.0026
(1.00) 		0.601
(1.00) 		0.382
(1.00) 		0.235
(1.00) 		0.207
(1.00) 		0.064
(1.00) 		0.0584
(1.00) 		0.0636
(1.00) 		0.0135
(1.00)
16p loss 0 (0%) 159 1.92e-07
(0.000146) 		0.305
(1.00) 		0.336
(1.00) 		0.362
(1.00) 		0.207
(1.00) 		0.771
(1.00) 		0.0238
(1.00) 		0.0221
(1.00) 		0.128
(1.00) 		0.606
(1.00)
16q loss 0 (0%) 159 4.1e-07
(0.000312) 		0.0832
(1.00) 		0.103
(1.00) 		0.976
(1.00) 		0.118
(1.00) 		0.74
(1.00) 		0.112
(1.00) 		0.0574
(1.00) 		0.0184
(1.00) 		0.288
(1.00)
22q loss 0 (0%) 146 6.22e-05
(0.0467) 		0.219
(1.00) 		0.511
(1.00) 		0.0753
(1.00) 		0.0788
(1.00) 		0.583
(1.00) 		0.578
(1.00) 		0.0129
(1.00) 		0.446
(1.00) 		0.966
(1.00)
1q gain 0 (0%) 142 0.0372
(1.00) 		0.396
(1.00) 		0.676
(1.00) 		0.885
(1.00) 		0.00478
(1.00) 		1
(1.00) 		0.714
(1.00) 		0.688
(1.00) 		0.363
(1.00) 		0.335
(1.00)
2q gain 0 (0%) 169 0.00448
(1.00) 		0.00793
(1.00) 		0.369
(1.00) 		0.563
(1.00) 		0.0042
(1.00) 		0.2
(1.00) 		0.127
(1.00) 		0.0576
(1.00) 		0.166
(1.00) 		0.00978
(1.00)
3p gain 0 (0%) 149 0.0011
(0.806) 		0.00337
(1.00) 		0.0354
(1.00) 		0.185
(1.00) 		0.0791
(1.00) 		0.00396
(1.00) 		0.0335
(1.00) 		0.0224
(1.00) 		0.0177
(1.00) 		0.193
(1.00)
4p gain 0 (0%) 171 0.224
(1.00) 		0.671
(1.00) 		0.86
(1.00) 		0.521
(1.00) 		0.756
(1.00) 		0.919
(1.00) 		0.198
(1.00) 		0.544
(1.00) 		0.918
(1.00) 		0.682
(1.00)
4q gain 0 (0%) 175 0.0377
(1.00) 		1
(1.00) 		0.542
(1.00) 		0.287
(1.00) 		0.763
(1.00) 		0.69
(1.00) 		0.201
(1.00) 		0.387
(1.00) 		0.609
(1.00) 		0.761
(1.00)
5q gain 0 (0%) 162 0.262
(1.00) 		0.131
(1.00) 		0.0845
(1.00) 		0.956
(1.00) 		0.528
(1.00) 		0.583
(1.00) 		0.556
(1.00) 		0.654
(1.00) 		0.402
(1.00) 		0.679
(1.00)
6p gain 0 (0%) 165 0.0433
(1.00) 		0.235
(1.00) 		0.684
(1.00) 		0.533
(1.00) 		0.415
(1.00) 		1
(1.00) 		0.284
(1.00) 		0.134
(1.00) 		0.311
(1.00) 		0.879
(1.00)
6q gain 0 (0%) 176 0.0125
(1.00) 		1
(1.00) 		0.549
(1.00) 		0.0079
(1.00) 		0.112
(1.00) 		1
(1.00) 		0.0449
(1.00) 		0.0495
(1.00) 		0.155
(1.00) 		0.347
(1.00)
7p gain 0 (0%) 130 0.00214
(1.00) 		0.00218
(1.00) 		0.0502
(1.00) 		0.38
(1.00) 		0.0493
(1.00) 		0.77
(1.00) 		0.0947
(1.00) 		0.269
(1.00) 		0.785
(1.00) 		0.484
(1.00)
7q gain 0 (0%) 137 0.000987
(0.727) 		0.00731
(1.00) 		0.392
(1.00) 		0.763
(1.00) 		0.145
(1.00) 		0.66
(1.00) 		0.974
(1.00) 		0.271
(1.00) 		0.765
(1.00) 		0.943
(1.00)
8p gain 0 (0%) 163 0.0138
(1.00) 		0.0272
(1.00) 		0.165
(1.00) 		0.0283
(1.00) 		0.0272
(1.00) 		0.0389
(1.00) 		0.395
(1.00) 		0.722
(1.00) 		0.409
(1.00) 		0.256
(1.00)
9p gain 0 (0%) 168 0.123
(1.00) 		0.43
(1.00) 		0.0721
(1.00) 		0.571
(1.00) 		0.00176
(1.00) 		0.163
(1.00) 		0.367
(1.00) 		1
(1.00) 		0.936
(1.00) 		0.74
(1.00)
9q gain 0 (0%) 169 0.819
(1.00) 		0.221
(1.00) 		0.755
(1.00) 		0.41
(1.00) 		0.0212
(1.00) 		0.135
(1.00) 		1
(1.00) 		0.713
(1.00) 		0.806
(1.00) 		0.405
(1.00)
10q gain 0 (0%) 173 0.0574
(1.00) 		0.825
(1.00) 		0.684
(1.00) 		0.356
(1.00) 		0.481
(1.00) 		0.551
(1.00) 		0.616
(1.00) 		1
(1.00) 		0.596
(1.00) 		1
(1.00)
11p gain 0 (0%) 173 0.0416
(1.00) 		0.751
(1.00) 		0.75
(1.00) 		0.596
(1.00) 		0.168
(1.00) 		0.67
(1.00) 		0.22
(1.00) 		0.476
(1.00) 		0.66
(1.00) 		0.801
(1.00)
11q gain 0 (0%) 168 0.151
(1.00) 		0.878
(1.00) 		0.649
(1.00) 		0.637
(1.00) 		0.292
(1.00) 		0.103
(1.00) 		0.72
(1.00) 		0.639
(1.00) 		0.936
(1.00) 		1
(1.00)
12p gain 0 (0%) 153 0.00191
(1.00) 		0.785
(1.00) 		0.138
(1.00) 		0.162
(1.00) 		0.0362
(1.00) 		0.0527
(1.00) 		0.0524
(1.00) 		1
(1.00) 		0.143
(1.00) 		0.073
(1.00)
12q gain 0 (0%) 162 0.0992
(1.00) 		0.354
(1.00) 		0.0221
(1.00) 		0.0226
(1.00) 		0.0119
(1.00) 		0.038
(1.00) 		0.0641
(1.00) 		0.186
(1.00) 		0.0306
(1.00) 		0.0644
(1.00)
13q gain 0 (0%) 156 0.00995
(1.00) 		0.766
(1.00) 		0.76
(1.00) 		0.66
(1.00) 		0.0804
(1.00) 		0.291
(1.00) 		0.732
(1.00) 		0.561
(1.00) 		0.923
(1.00) 		0.876
(1.00)
14q gain 0 (0%) 171 0.724
(1.00) 		0.927
(1.00) 		0.395
(1.00) 		0.733
(1.00) 		0.102
(1.00) 		0.0595
(1.00) 		1
(1.00) 		0.677
(1.00) 		0.1
(1.00) 		0.354
(1.00)
15q gain 0 (0%) 176 1
(1.00) 		0.188
(1.00) 		0.522
(1.00) 		1
(1.00) 		0.3
(1.00) 		0.206
(1.00) 		0.571
(1.00) 		1
(1.00) 		0.489
(1.00) 		0.429
(1.00)
16p gain 0 (0%) 169 0.0711
(1.00) 		1
(1.00) 		0.203
(1.00) 		0.889
(1.00) 		0.155
(1.00) 		0.751
(1.00) 		1
(1.00) 		0.854
(1.00) 		0.75
(1.00) 		1
(1.00)
16q gain 0 (0%) 166 0.0137
(1.00) 		0.562
(1.00) 		0.0782
(1.00) 		0.395
(1.00) 		0.0472
(1.00) 		0.17
(1.00) 		0.839
(1.00) 		0.778
(1.00) 		0.194
(1.00) 		0.441
(1.00)
17p gain 0 (0%) 174 0.419
(1.00) 		0.814
(1.00) 		0.841
(1.00) 		1
(1.00) 		0.0705
(1.00) 		0.329
(1.00) 		0.576
(1.00) 		0.251
(1.00) 		0.565
(1.00) 		0.616
(1.00)
18q gain 0 (0%) 170 0.0549
(1.00) 		0.0145
(1.00) 		0.583
(1.00) 		0.221
(1.00) 		0.464
(1.00) 		0.545
(1.00) 		0.548
(1.00) 		0.321
(1.00) 		0.629
(1.00) 		0.772
(1.00)
19p gain 0 (0%) 168 0.56
(1.00) 		0.0993
(1.00) 		0.751
(1.00) 		0.89
(1.00) 		0.0496
(1.00) 		0.0347
(1.00) 		0.392
(1.00) 		0.378
(1.00) 		0.197
(1.00) 		0.112
(1.00)
19q gain 0 (0%) 149 0.00131
(0.961) 		0.301
(1.00) 		0.447
(1.00) 		0.61
(1.00) 		0.137
(1.00) 		0.175
(1.00) 		0.473
(1.00) 		0.866
(1.00) 		0.609
(1.00) 		0.411
(1.00)
20p gain 0 (0%) 122 0.0812
(1.00) 		0.0829
(1.00) 		0.326
(1.00) 		0.474
(1.00) 		0.188
(1.00) 		0.133
(1.00) 		0.786
(1.00) 		0.43
(1.00) 		0.698
(1.00) 		0.465
(1.00)
20q gain 0 (0%) 114 0.0138
(1.00) 		0.00237
(1.00) 		0.0598
(1.00) 		0.68
(1.00) 		0.0133
(1.00) 		0.0451
(1.00) 		0.0391
(1.00) 		0.235
(1.00) 		0.11
(1.00) 		0.0275
(1.00)
21q gain 0 (0%) 152 0.00131
(0.961) 		0.689
(1.00) 		0.228
(1.00) 		0.671
(1.00) 		0.113
(1.00) 		0.0328
(1.00) 		0.0845
(1.00) 		0.392
(1.00) 		0.196
(1.00) 		0.3
(1.00)
22q gain 0 (0%) 169 0.195
(1.00) 		0.205
(1.00) 		0.147
(1.00) 		0.52
(1.00) 		0.226
(1.00) 		0.61
(1.00) 		0.0133
(1.00) 		0.854
(1.00) 		0.296
(1.00) 		0.476
(1.00)
Xq gain 0 (0%) 175 0.00882
(1.00) 		0.615
(1.00) 		0.964
(1.00) 		0.86
(1.00) 		0.214
(1.00) 		0.69
(1.00) 		0.421
(1.00) 		0.292
(1.00) 		0.261
(1.00) 		0.0827
(1.00)
1p loss 0 (0%) 178 0.203
(1.00) 		0.124
(1.00) 		0.265
(1.00) 		0.0446
(1.00) 		0.438
(1.00) 		1
(1.00) 		0.18
(1.00) 		0.0515
(1.00)
2p loss 0 (0%) 173 0.827
(1.00) 		0.0335
(1.00) 		0.23
(1.00) 		0.269
(1.00) 		0.0783
(1.00) 		0.0434
(1.00) 		0.441
(1.00) 		1
(1.00) 		0.0808
(1.00) 		0.00774
(1.00)
2q loss 0 (0%) 161 0.00147
(1.00) 		0.17
(1.00) 		0.757
(1.00) 		0.612
(1.00) 		0.00476
(1.00) 		0.0582
(1.00) 		0.828
(1.00) 		0.526
(1.00) 		0.326
(1.00) 		0.0432
(1.00)
3p loss 0 (0%) 170 1
(1.00) 		1
(1.00) 		0.0337
(1.00) 		0.367
(1.00) 		0.019
(1.00) 		0.0113
(1.00) 		0.148
(1.00) 		0.117
(1.00) 		0.139
(1.00) 		0.261
(1.00)
3q loss 0 (0%) 179 0.795
(1.00) 		1
(1.00) 		0.669
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.782
(1.00) 		1
(1.00)
4p loss 0 (0%) 148 0.0143
(1.00) 		0.298
(1.00) 		0.43
(1.00) 		0.933
(1.00) 		0.264
(1.00) 		0.748
(1.00) 		0.372
(1.00) 		0.658
(1.00) 		0.199
(1.00) 		0.561
(1.00)
4q loss 0 (0%) 154 0.524
(1.00) 		0.19
(1.00) 		0.106
(1.00) 		0.861
(1.00) 		0.106
(1.00) 		0.565
(1.00) 		0.774
(1.00) 		0.178
(1.00) 		0.254
(1.00) 		0.746
(1.00)
5p loss 0 (0%) 167 0.0527
(1.00) 		1
(1.00) 		0.326
(1.00) 		0.17
(1.00) 		0.868
(1.00) 		0.527
(1.00) 		0.122
(1.00) 		0.562
(1.00) 		0.217
(1.00) 		0.236
(1.00)
6p loss 0 (0%) 161 0.148
(1.00) 		0.17
(1.00) 		0.196
(1.00) 		0.541
(1.00) 		0.344
(1.00) 		0.484
(1.00) 		0.227
(1.00) 		1
(1.00) 		0.254
(1.00) 		1
(1.00)
7q loss 0 (0%) 176 0.0259
(1.00) 		0.0938
(1.00) 		0.844
(1.00) 		0.363
(1.00) 		0.352
(1.00) 		0.7
(1.00) 		0.13
(1.00) 		1
(1.00)
8q loss 0 (0%) 174 0.293
(1.00) 		0.369
(1.00) 		0.643
(1.00) 		0.0826
(1.00) 		0.255
(1.00) 		0.511
(1.00) 		0.33
(1.00) 		0.0901
(1.00) 		0.357
(1.00) 		0.0458
(1.00)
10p loss 0 (0%) 162 0.128
(1.00) 		0.487
(1.00) 		0.759
(1.00) 		0.343
(1.00) 		0.111
(1.00) 		0.273
(1.00) 		0.864
(1.00) 		0.241
(1.00) 		0.707
(1.00) 		0.345
(1.00)
11q loss 0 (0%) 142 0.0027
(1.00) 		0.0431
(1.00) 		0.0638
(1.00) 		0.0328
(1.00) 		0.0124
(1.00) 		0.0604
(1.00) 		0.674
(1.00) 		0.785
(1.00) 		0.409
(1.00) 		0.437
(1.00)
12p loss 0 (0%) 175 0.0487
(1.00) 		0.433
(1.00) 		0.964
(1.00) 		0.86
(1.00) 		0.243
(1.00) 		0.243
(1.00) 		0.888
(1.00) 		1
(1.00) 		0.689
(1.00) 		0.868
(1.00)
12q loss 0 (0%) 174 0.419
(1.00) 		0.814
(1.00) 		0.356
(1.00) 		0.442
(1.00) 		0.224
(1.00) 		0.417
(1.00) 		0.576
(1.00) 		0.251
(1.00) 		0.405
(1.00) 		0.616
(1.00)
13q loss 0 (0%) 159 0.000902
(0.666) 		0.0547
(1.00) 		0.101
(1.00) 		0.0628
(1.00) 		0.206
(1.00) 		0.383
(1.00) 		0.771
(1.00) 		0.413
(1.00) 		0.877
(1.00) 		1
(1.00)
14q loss 0 (0%) 154 0.000588
(0.434) 		0.112
(1.00) 		0.126
(1.00) 		0.0601
(1.00) 		0.117
(1.00) 		0.1
(1.00) 		0.0228
(1.00) 		0.195
(1.00) 		0.0455
(1.00) 		0.452
(1.00)
15q loss 0 (0%) 156 0.0374
(1.00) 		0.565
(1.00) 		0.027
(1.00) 		0.0979
(1.00) 		0.459
(1.00) 		0.23
(1.00) 		0.376
(1.00) 		0.0263
(1.00) 		0.57
(1.00) 		0.8
(1.00)
17p loss 0 (0%) 131 0.252
(1.00) 		0.377
(1.00) 		0.974
(1.00) 		0.446
(1.00) 		0.176
(1.00) 		0.301
(1.00) 		0.019
(1.00) 		0.0135
(1.00) 		0.0586
(1.00) 		0.0705
(1.00)
17q loss 0 (0%) 176 1
(1.00) 		0.0405
(1.00) 		0.735
(1.00) 		0.426
(1.00) 		0.452
(1.00) 		0.308
(1.00) 		0.484
(1.00) 		0.503
(1.00) 		0.351
(1.00) 		0.23
(1.00)
18p loss 0 (0%) 158 0.146
(1.00) 		0.28
(1.00) 		0.731
(1.00) 		0.785
(1.00) 		0.895
(1.00) 		0.555
(1.00) 		0.281
(1.00) 		0.0114
(1.00) 		0.00852
(1.00) 		0.0108
(1.00)
18q loss 0 (0%) 140 0.00508
(1.00) 		0.238
(1.00) 		0.758
(1.00) 		0.669
(1.00) 		0.152
(1.00) 		0.0929
(1.00) 		0.24
(1.00) 		0.224
(1.00) 		0.658
(1.00) 		0.691
(1.00)
19p loss 0 (0%) 168 0.0375
(1.00) 		0.599
(1.00) 		0.739
(1.00) 		0.151
(1.00) 		0.241
(1.00) 		0.514
(1.00) 		0.367
(1.00) 		0.378
(1.00) 		0.437
(1.00) 		0.59
(1.00)
19q loss 0 (0%) 175 0.089
(1.00) 		1
(1.00) 		0.714
(1.00) 		0.109
(1.00) 		0.214
(1.00) 		0.42
(1.00) 		0.0223
(1.00) 		0.387
(1.00) 		0.062
(1.00) 		0.14
(1.00)
20p loss 0 (0%) 174 0.371
(1.00) 		0.126
(1.00) 		0.301
(1.00) 		0.0272
(1.00) 		0.737
(1.00) 		0.151
(1.00) 		0.458
(1.00) 		0.251
(1.00) 		0.1
(1.00) 		0.691
(1.00)
21q loss 0 (0%) 160 0.202
(1.00) 		0.916
(1.00) 		0.361
(1.00) 		0.419
(1.00) 		0.811
(1.00) 		0.531
(1.00) 		0.638
(1.00) 		0.169
(1.00) 		0.158
(1.00) 		0.86
(1.00)
Xq loss 0 (0%) 176 0.0259
(1.00) 		0.758
(1.00) 		0.78
(1.00) 		0.636
(1.00) 		0.162
(1.00) 		0.308
(1.00) 		0.309
(1.00) 		0.503
(1.00) 		0.351
(1.00) 		0.23
(1.00)
'1p gain' versus 'CN_CNMF'

P value = 3.04e-05 (Fisher's exact test), Q value = 0.023

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
1P GAIN CNV 12 1 9
1P GAIN WILD-TYPE 43 81 36

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

'2p gain' versus 'CN_CNMF'

P value = 5.37e-05 (Fisher's exact test), Q value = 0.04

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
2P GAIN CNV 18 4 8
2P GAIN WILD-TYPE 37 78 37

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

'3q gain' versus 'CN_CNMF'

P value = 1.18e-06 (Fisher's exact test), Q value = 9e-04

Table S3.  Gene #6: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
3Q GAIN CNV 29 10 10
3Q GAIN WILD-TYPE 26 72 35

Figure S3.  Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

'5p gain' versus 'CN_CNMF'

P value = 7.4e-05 (Fisher's exact test), Q value = 0.055

Table S4.  Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
5P GAIN CNV 20 11 21
5P GAIN WILD-TYPE 35 71 24

Figure S4.  Get High-res Image Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

'8q gain' versus 'CN_CNMF'

P value = 2.53e-05 (Fisher's exact test), Q value = 0.019

Table S5.  Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
8Q GAIN CNV 30 19 7
8Q GAIN WILD-TYPE 25 63 38

Figure S5.  Get High-res Image Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

'10p gain' versus 'CN_CNMF'

P value = 4.56e-05 (Fisher's exact test), Q value = 0.034

Table S6.  Gene #19: '10p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
10P GAIN CNV 19 5 12
10P GAIN WILD-TYPE 36 77 33

Figure S6.  Get High-res Image Gene #19: '10p gain' versus Molecular Subtype #1: 'CN_CNMF'

'17q gain' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.000256 (Fisher's exact test), Q value = 0.19

Table S7.  Gene #31: '17q gain' versus Molecular Subtype #9: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 33 79 70
17Q GAIN CNV 11 4 14
17Q GAIN WILD-TYPE 22 75 56

Figure S7.  Get High-res Image Gene #31: '17q gain' versus Molecular Subtype #9: 'MIRSEQ_MATURE_CNMF'

'18p gain' versus 'CN_CNMF'

P value = 4.52e-05 (Fisher's exact test), Q value = 0.034

Table S8.  Gene #32: '18p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
18P GAIN CNV 13 4 15
18P GAIN WILD-TYPE 42 78 30

Figure S8.  Get High-res Image Gene #32: '18p gain' versus Molecular Subtype #1: 'CN_CNMF'

'5q loss' versus 'CN_CNMF'

P value = 3.26e-05 (Fisher's exact test), Q value = 0.025

Table S9.  Gene #49: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
5Q LOSS CNV 22 7 13
5Q LOSS WILD-TYPE 33 75 32

Figure S9.  Get High-res Image Gene #49: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

'6q loss' versus 'CN_CNMF'

P value = 0.000115 (Fisher's exact test), Q value = 0.086

Table S10.  Gene #51: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
6Q LOSS CNV 21 7 7
6Q LOSS WILD-TYPE 34 75 38

Figure S10.  Get High-res Image Gene #51: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'8p loss' versus 'CN_CNMF'

P value = 2.17e-09 (Fisher's exact test), Q value = 1.7e-06

Table S11.  Gene #53: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
8P LOSS CNV 18 10 30
8P LOSS WILD-TYPE 37 72 15

Figure S11.  Get High-res Image Gene #53: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'CN_CNMF'

P value = 2.97e-06 (Fisher's exact test), Q value = 0.0023

Table S12.  Gene #55: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
9P LOSS CNV 26 26 2
9P LOSS WILD-TYPE 29 56 43

Figure S12.  Get High-res Image Gene #55: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'METHLYATION_CNMF'

P value = 0.000178 (Fisher's exact test), Q value = 0.13

Table S13.  Gene #55: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 70 71 41
9P LOSS CNV 28 9 17
9P LOSS WILD-TYPE 42 62 24

Figure S13.  Get High-res Image Gene #55: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'9p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1.38e-05 (Fisher's exact test), Q value = 0.01

Table S14.  Gene #55: '9p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 36 67 76
9P LOSS CNV 13 31 9
9P LOSS WILD-TYPE 23 36 67

Figure S14.  Get High-res Image Gene #55: '9p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'9q loss' versus 'CN_CNMF'

P value = 7.61e-05 (Fisher's exact test), Q value = 0.057

Table S15.  Gene #56: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
9Q LOSS CNV 24 25 3
9Q LOSS WILD-TYPE 31 57 42

Figure S15.  Get High-res Image Gene #56: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

'9q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3.05e-06 (Fisher's exact test), Q value = 0.0023

Table S16.  Gene #56: '9q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 36 67 76
9Q LOSS CNV 14 29 7
9Q LOSS WILD-TYPE 22 38 69

Figure S16.  Get High-res Image Gene #56: '9q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'10q loss' versus 'CN_CNMF'

P value = 0.000263 (Fisher's exact test), Q value = 0.2

Table S17.  Gene #58: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
10Q LOSS CNV 19 6 9
10Q LOSS WILD-TYPE 36 76 36

Figure S17.  Get High-res Image Gene #58: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

'11p loss' versus 'CN_CNMF'

P value = 9.99e-05 (Fisher's exact test), Q value = 0.075

Table S18.  Gene #59: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
11P LOSS CNV 28 16 8
11P LOSS WILD-TYPE 27 66 37

Figure S18.  Get High-res Image Gene #59: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

'11p loss' versus 'METHLYATION_CNMF'

P value = 9.48e-05 (Fisher's exact test), Q value = 0.071

Table S19.  Gene #59: '11p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 70 71 41
11P LOSS CNV 28 8 16
11P LOSS WILD-TYPE 42 63 25

Figure S19.  Get High-res Image Gene #59: '11p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'16p loss' versus 'CN_CNMF'

P value = 1.92e-07 (Fisher's exact test), Q value = 0.00015

Table S20.  Gene #66: '16p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
16P LOSS CNV 10 0 13
16P LOSS WILD-TYPE 45 82 32

Figure S20.  Get High-res Image Gene #66: '16p loss' versus Molecular Subtype #1: 'CN_CNMF'

'16q loss' versus 'CN_CNMF'

P value = 4.1e-07 (Fisher's exact test), Q value = 0.00031

Table S21.  Gene #67: '16q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
16Q LOSS CNV 11 0 12
16Q LOSS WILD-TYPE 44 82 33

Figure S21.  Get High-res Image Gene #67: '16q loss' versus Molecular Subtype #1: 'CN_CNMF'

'22q loss' versus 'CN_CNMF'

P value = 6.22e-05 (Fisher's exact test), Q value = 0.047

Table S22.  Gene #76: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 55 82 45
22Q LOSS CNV 16 5 15
22Q LOSS WILD-TYPE 39 77 30

Figure S22.  Get High-res Image Gene #76: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data
Input

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

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

  • Number of patients = 182

  • Number of significantly arm-level cnvs = 77

  • Number of molecular subtypes = 10

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