Correlation between copy number variations of arm-level result and molecular subtypes
Bladder Urothelial Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1Q52NBD
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/C1Q52NBD
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 264 patients, 26 significant findings detected with P value < 0.05 and Q value < 0.25.

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

  • 3q gain cnv correlated to 'CN_CNMF'.

  • 7p gain cnv correlated to 'CN_CNMF'.

  • 8p 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 'CN_CNMF'.

  • 19q gain cnv correlated to 'CN_CNMF'.

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

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

  • 6p loss cnv correlated to 'MIRSEQ_CHIERARCHICAL'.

  • 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 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 11p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 11q loss cnv correlated to 'CN_CNMF'.

  • 14q loss cnv correlated to 'CN_CNMF'.

  • 15q loss cnv correlated to 'METHLYATION_CNMF' and 'MIRSEQ_CHIERARCHICAL'.

  • 17p 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, 26 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 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 75 (28%) 189 0.00018
(0.14) 		1e-05
(0.008) 		0.326
(1.00) 		0.735
(1.00) 		0.107
(1.00) 		0.063
(1.00) 		0.137
(1.00) 		0.0356
(1.00) 		0.199
(1.00) 		0.0367
(1.00)
21q gain 79 (30%) 185 1e-05
(0.008) 		7e-05
(0.0549) 		0.653
(1.00) 		0.403
(1.00) 		0.0473
(1.00) 		0.00478
(1.00) 		0.00214
(1.00) 		0.00701
(1.00) 		0.00665
(1.00) 		0.00247
(1.00)
3p loss 31 (12%) 233 0.832
(1.00) 		0.0413
(1.00) 		0.0223
(1.00) 		0.0248
(1.00) 		1e-05
(0.008) 		1e-05
(0.008) 		0.403
(1.00) 		0.13
(1.00) 		0.165
(1.00) 		0.103
(1.00)
9q loss 104 (39%) 160 1e-05
(0.008) 		0.0119
(1.00) 		0.0279
(1.00) 		0.0099
(1.00) 		0.0284
(1.00) 		7e-05
(0.0549) 		0.973
(1.00) 		0.137
(1.00) 		0.569
(1.00) 		0.285
(1.00)
11p loss 108 (41%) 156 1e-05
(0.008) 		1e-05
(0.008) 		0.18
(1.00) 		0.748
(1.00) 		0.00202
(1.00) 		0.0005
(0.385) 		0.116
(1.00) 		0.0939
(1.00) 		0.00574
(1.00) 		0.0749
(1.00)
15q loss 88 (33%) 176 0.00588
(1.00) 		0.00026
(0.201) 		0.107
(1.00) 		0.317
(1.00) 		0.452
(1.00) 		0.0706
(1.00) 		0.152
(1.00) 		4e-05
(0.0315) 		0.0927
(1.00) 		0.311
(1.00)
3q gain 118 (45%) 146 5e-05
(0.0393) 		0.363
(1.00) 		0.568
(1.00) 		1
(1.00) 		0.399
(1.00) 		0.197
(1.00) 		0.00918
(1.00) 		0.00057
(0.438) 		0.00128
(0.975) 		0.00044
(0.34)
7p gain 111 (42%) 153 0.00024
(0.186) 		0.102
(1.00) 		0.0211
(1.00) 		0.445
(1.00) 		0.923
(1.00) 		0.795
(1.00) 		0.263
(1.00) 		0.333
(1.00) 		0.555
(1.00) 		0.279
(1.00)
8p gain 55 (21%) 209 9e-05
(0.0704) 		0.0584
(1.00) 		0.0833
(1.00) 		0.0184
(1.00) 		0.523
(1.00) 		0.996
(1.00) 		0.26
(1.00) 		0.0178
(1.00) 		0.14
(1.00) 		0.161
(1.00)
8q gain 122 (46%) 142 0.00017
(0.133) 		0.015
(1.00) 		0.0397
(1.00) 		0.186
(1.00) 		0.355
(1.00) 		0.84
(1.00) 		0.353
(1.00) 		0.0117
(1.00) 		0.109
(1.00) 		0.145
(1.00)
10p gain 75 (28%) 189 6e-05
(0.0471) 		0.00414
(1.00) 		0.837
(1.00) 		0.431
(1.00) 		0.67
(1.00) 		0.083
(1.00) 		0.638
(1.00) 		0.786
(1.00) 		0.775
(1.00) 		0.982
(1.00)
17q gain 90 (34%) 174 0.0002
(0.156) 		0.249
(1.00) 		0.497
(1.00) 		0.388
(1.00) 		0.149
(1.00) 		0.22
(1.00) 		0.111
(1.00) 		0.0028
(1.00) 		0.00346
(1.00) 		0.00458
(1.00)
19q gain 90 (34%) 174 0.0001
(0.0781) 		0.0023
(1.00) 		0.32
(1.00) 		0.549
(1.00) 		0.267
(1.00) 		0.254
(1.00) 		0.806
(1.00) 		0.0272
(1.00) 		0.669
(1.00) 		0.0647
(1.00)
6p loss 64 (24%) 200 0.00229
(1.00) 		0.0189
(1.00) 		0.755
(1.00) 		0.825
(1.00) 		0.0606
(1.00) 		0.0112
(1.00) 		0.655
(1.00) 		0.00024
(0.186) 		0.616
(1.00) 		0.0172
(1.00)
6q loss 97 (37%) 167 1e-05
(0.008) 		0.00465
(1.00) 		0.833
(1.00) 		0.491
(1.00) 		0.229
(1.00) 		0.013
(1.00) 		0.8
(1.00) 		0.0125
(1.00) 		0.942
(1.00) 		0.218
(1.00)
8p loss 121 (46%) 143 5e-05
(0.0393) 		0.00073
(0.56) 		0.216
(1.00) 		0.17
(1.00) 		0.0513
(1.00) 		0.61
(1.00) 		0.018
(1.00) 		0.0306
(1.00) 		0.0449
(1.00) 		0.0421
(1.00)
9p loss 114 (43%) 150 1e-05
(0.008) 		0.175
(1.00) 		0.193
(1.00) 		0.0608
(1.00) 		0.419
(1.00) 		0.00276
(1.00) 		0.671
(1.00) 		0.348
(1.00) 		0.958
(1.00) 		1
(1.00)
11q loss 81 (31%) 183 1e-05
(0.008) 		0.00132
(1.00) 		0.0573
(1.00) 		0.199
(1.00) 		0.0259
(1.00) 		0.0679
(1.00) 		0.516
(1.00) 		0.61
(1.00) 		0.0817
(1.00) 		0.317
(1.00)
14q loss 75 (28%) 189 1e-05
(0.008) 		0.00039
(0.301) 		0.07
(1.00) 		0.0375
(1.00) 		0.0551
(1.00) 		0.00037
(0.286) 		0.0118
(1.00) 		0.0141
(1.00) 		0.0291
(1.00) 		0.396
(1.00)
17p loss 116 (44%) 148 1e-05
(0.008) 		0.412
(1.00) 		0.957
(1.00) 		0.729
(1.00) 		0.408
(1.00) 		0.097
(1.00) 		0.264
(1.00) 		0.0963
(1.00) 		0.164
(1.00) 		0.453
(1.00)
1p gain 57 (22%) 207 0.0306
(1.00) 		0.0143
(1.00) 		0.691
(1.00) 		0.613
(1.00) 		0.795
(1.00) 		0.996
(1.00) 		0.696
(1.00) 		0.857
(1.00) 		0.96
(1.00) 		0.843
(1.00)
1q gain 83 (31%) 181 0.00085
(0.649) 		0.251
(1.00) 		0.6
(1.00) 		0.885
(1.00) 		0.775
(1.00) 		0.951
(1.00) 		0.763
(1.00) 		0.977
(1.00) 		0.702
(1.00) 		0.818
(1.00)
2q gain 37 (14%) 227 0.0965
(1.00) 		0.167
(1.00) 		0.308
(1.00) 		0.352
(1.00) 		0.428
(1.00) 		0.554
(1.00) 		0.502
(1.00) 		0.416
(1.00) 		0.728
(1.00) 		0.312
(1.00)
3p gain 92 (35%) 172 0.00214
(1.00) 		0.229
(1.00) 		0.0981
(1.00) 		0.405
(1.00) 		0.00753
(1.00) 		0.0184
(1.00) 		0.0031
(1.00) 		0.00943
(1.00) 		0.00168
(1.00) 		0.00105
(0.801)
4p gain 33 (12%) 231 0.00073
(0.56) 		0.0133
(1.00) 		0.608
(1.00) 		0.414
(1.00) 		0.034
(1.00) 		0.00577
(1.00) 		0.135
(1.00) 		0.00183
(1.00) 		0.0548
(1.00) 		0.00471
(1.00)
4q gain 19 (7%) 245 0.00507
(1.00) 		0.0265
(1.00) 		0.544
(1.00) 		0.203
(1.00) 		0.0376
(1.00) 		0.09
(1.00) 		0.268
(1.00) 		0.132
(1.00) 		0.325
(1.00) 		0.409
(1.00)
5p gain 103 (39%) 161 0.00283
(1.00) 		0.177
(1.00) 		0.0429
(1.00) 		0.24
(1.00) 		0.326
(1.00) 		0.123
(1.00) 		0.0702
(1.00) 		0.036
(1.00) 		0.346
(1.00) 		0.106
(1.00)
5q gain 37 (14%) 227 0.368
(1.00) 		0.0401
(1.00) 		0.024
(1.00) 		0.283
(1.00) 		0.786
(1.00) 		0.738
(1.00) 		0.261
(1.00) 		0.144
(1.00) 		0.12
(1.00) 		0.503
(1.00)
6p gain 43 (16%) 221 0.465
(1.00) 		0.743
(1.00) 		0.847
(1.00) 		0.133
(1.00) 		0.436
(1.00) 		0.305
(1.00) 		0.545
(1.00) 		0.75
(1.00) 		0.56
(1.00) 		0.833
(1.00)
6q gain 24 (9%) 240 0.369
(1.00) 		0.816
(1.00) 		0.975
(1.00) 		0.0416
(1.00) 		0.306
(1.00) 		0.0545
(1.00) 		0.287
(1.00) 		0.409
(1.00) 		0.208
(1.00) 		0.741
(1.00)
7q gain 101 (38%) 163 0.00237
(1.00) 		0.331
(1.00) 		0.194
(1.00) 		0.921
(1.00) 		0.825
(1.00) 		0.31
(1.00) 		0.331
(1.00) 		0.461
(1.00) 		0.396
(1.00) 		0.118
(1.00)
9p gain 40 (15%) 224 0.00044
(0.34) 		0.66
(1.00) 		0.86
(1.00) 		0.381
(1.00) 		0.188
(1.00) 		0.1
(1.00) 		0.337
(1.00) 		0.129
(1.00) 		0.745
(1.00) 		0.297
(1.00)
9q gain 36 (14%) 228 0.0165
(1.00) 		0.172
(1.00) 		0.881
(1.00) 		0.0293
(1.00) 		0.0065
(1.00) 		0.00076
(0.581) 		0.974
(1.00) 		0.371
(1.00) 		0.865
(1.00) 		0.0496
(1.00)
10q gain 23 (9%) 241 0.044
(1.00) 		0.0924
(1.00) 		0.56
(1.00) 		0.549
(1.00) 		0.526
(1.00) 		0.0117
(1.00) 		0.787
(1.00) 		0.69
(1.00) 		0.773
(1.00) 		0.464
(1.00)
11p gain 25 (9%) 239 0.428
(1.00) 		0.0829
(1.00) 		0.114
(1.00) 		0.122
(1.00) 		0.084
(1.00) 		0.0594
(1.00) 		0.489
(1.00) 		0.0138
(1.00) 		0.575
(1.00) 		0.0815
(1.00)
11q gain 37 (14%) 227 0.577
(1.00) 		0.429
(1.00) 		0.2
(1.00) 		0.0472
(1.00) 		0.178
(1.00) 		0.0214
(1.00) 		0.633
(1.00) 		0.104
(1.00) 		0.753
(1.00) 		0.158
(1.00)
12p gain 75 (28%) 189 0.0697
(1.00) 		0.198
(1.00) 		0.758
(1.00) 		0.531
(1.00) 		0.739
(1.00) 		0.953
(1.00) 		0.854
(1.00) 		0.138
(1.00) 		0.725
(1.00) 		0.396
(1.00)
12q gain 56 (21%) 208 0.00407
(1.00) 		0.00883
(1.00) 		0.0681
(1.00) 		0.0129
(1.00) 		0.114
(1.00) 		0.065
(1.00) 		0.517
(1.00) 		0.384
(1.00) 		0.366
(1.00) 		0.153
(1.00)
13q gain 70 (27%) 194 0.24
(1.00) 		0.895
(1.00) 		0.976
(1.00) 		0.839
(1.00) 		0.24
(1.00) 		0.424
(1.00) 		0.755
(1.00) 		0.396
(1.00) 		0.808
(1.00) 		0.833
(1.00)
14q gain 44 (17%) 220 0.153
(1.00) 		0.337
(1.00) 		0.378
(1.00) 		0.15
(1.00) 		0.0385
(1.00) 		0.234
(1.00) 		1
(1.00) 		0.0422
(1.00) 		0.531
(1.00) 		0.923
(1.00)
15q gain 24 (9%) 240 0.00726
(1.00) 		0.0765
(1.00) 		0.715
(1.00) 		0.804
(1.00) 		0.655
(1.00) 		0.23
(1.00) 		0.308
(1.00) 		0.754
(1.00) 		1
(1.00) 		0.844
(1.00)
16p gain 42 (16%) 222 0.166
(1.00) 		0.804
(1.00) 		0.374
(1.00) 		0.341
(1.00) 		0.635
(1.00) 		0.467
(1.00) 		0.222
(1.00) 		0.418
(1.00) 		0.474
(1.00) 		0.85
(1.00)
16q gain 52 (20%) 212 0.271
(1.00) 		0.627
(1.00) 		0.135
(1.00) 		0.14
(1.00) 		0.381
(1.00) 		0.135
(1.00) 		0.102
(1.00) 		0.0875
(1.00) 		0.19
(1.00) 		0.544
(1.00)
17p gain 35 (13%) 229 0.0869
(1.00) 		0.398
(1.00) 		0.55
(1.00) 		0.875
(1.00) 		0.735
(1.00) 		0.0414
(1.00) 		0.00269
(1.00) 		0.0138
(1.00) 		0.00134
(1.00) 		0.00341
(1.00)
18p gain 79 (30%) 185 0.0261
(1.00) 		0.00303
(1.00) 		0.951
(1.00) 		0.912
(1.00) 		0.19
(1.00) 		0.039
(1.00) 		0.667
(1.00) 		0.102
(1.00) 		0.746
(1.00) 		0.983
(1.00)
18q gain 41 (16%) 223 0.409
(1.00) 		0.0723
(1.00) 		0.321
(1.00) 		0.302
(1.00) 		0.677
(1.00) 		0.418
(1.00) 		0.525
(1.00) 		0.218
(1.00) 		0.534
(1.00) 		0.414
(1.00)
19p gain 55 (21%) 209 0.00958
(1.00) 		0.0421
(1.00) 		0.267
(1.00) 		0.421
(1.00) 		0.0177
(1.00) 		0.0991
(1.00) 		0.746
(1.00) 		0.0337
(1.00) 		0.502
(1.00) 		0.061
(1.00)
20p gain 131 (50%) 133 0.331
(1.00) 		0.437
(1.00) 		0.539
(1.00) 		0.0498
(1.00) 		0.694
(1.00) 		0.0269
(1.00) 		0.168
(1.00) 		0.0462
(1.00) 		0.0391
(1.00) 		0.177
(1.00)
20q gain 147 (56%) 117 0.00892
(1.00) 		0.213
(1.00) 		0.4
(1.00) 		0.117
(1.00) 		0.962
(1.00) 		0.615
(1.00) 		0.144
(1.00) 		0.0129
(1.00) 		0.169
(1.00) 		0.134
(1.00)
22q gain 36 (14%) 228 0.00298
(1.00) 		0.0066
(1.00) 		0.418
(1.00) 		0.337
(1.00) 		0.0183
(1.00) 		0.208
(1.00) 		0.195
(1.00) 		0.202
(1.00) 		0.405
(1.00) 		0.438
(1.00)
xq gain 33 (12%) 231 0.0132
(1.00) 		0.366
(1.00) 		0.707
(1.00) 		0.574
(1.00) 		0.916
(1.00) 		0.922
(1.00) 		0.523
(1.00) 		0.669
(1.00) 		0.427
(1.00) 		0.338
(1.00)
1p loss 23 (9%) 241 0.34
(1.00) 		0.305
(1.00) 		0.108
(1.00) 		0.081
(1.00) 		0.526
(1.00) 		0.111
(1.00) 		0.641
(1.00) 		0.196
(1.00) 		0.88
(1.00) 		0.959
(1.00)
1q loss 25 (9%) 239 0.721
(1.00) 		0.598
(1.00) 		0.404
(1.00) 		0.956
(1.00) 		0.435
(1.00) 		0.132
(1.00) 		0.527
(1.00) 		0.00247
(1.00) 		1
(1.00) 		0.78
(1.00)
2p loss 27 (10%) 237 0.424
(1.00) 		0.105
(1.00) 		0.961
(1.00) 		0.752
(1.00) 		0.732
(1.00) 		0.259
(1.00) 		0.179
(1.00) 		0.94
(1.00) 		0.665
(1.00) 		0.296
(1.00)
2q loss 58 (22%) 206 0.0954
(1.00) 		0.354
(1.00) 		0.748
(1.00) 		0.542
(1.00) 		0.292
(1.00) 		0.148
(1.00) 		0.699
(1.00) 		0.0497
(1.00) 		0.332
(1.00) 		0.0971
(1.00)
3q loss 13 (5%) 251 0.935
(1.00) 		0.173
(1.00) 		0.0189
(1.00) 		0.0522
(1.00) 		0.1
(1.00) 		0.0106
(1.00) 		1
(1.00) 		0.621
(1.00) 		1
(1.00) 		0.746
(1.00)
4p loss 86 (33%) 178 0.763
(1.00) 		0.809
(1.00) 		0.743
(1.00) 		0.78
(1.00) 		0.161
(1.00) 		0.027
(1.00) 		0.054
(1.00) 		0.481
(1.00) 		0.146
(1.00) 		0.0712
(1.00)
4q loss 91 (34%) 173 0.545
(1.00) 		0.38
(1.00) 		0.304
(1.00) 		0.348
(1.00) 		0.238
(1.00) 		0.127
(1.00) 		0.17
(1.00) 		0.476
(1.00) 		0.158
(1.00) 		0.0763
(1.00)
5p loss 40 (15%) 224 0.0174
(1.00) 		0.019
(1.00) 		0.316
(1.00) 		0.665
(1.00) 		0.634
(1.00) 		0.0479
(1.00) 		0.576
(1.00) 		0.905
(1.00) 		0.404
(1.00) 		1
(1.00)
5q loss 104 (39%) 160 0.00229
(1.00) 		0.00555
(1.00) 		0.86
(1.00) 		0.346
(1.00) 		0.517
(1.00) 		0.0787
(1.00) 		0.75
(1.00) 		0.148
(1.00) 		0.738
(1.00) 		0.173
(1.00)
7p loss 11 (4%) 253 0.257
(1.00) 		0.973
(1.00) 		0.322
(1.00) 		0.861
(1.00) 		0.74
(1.00) 		0.719
(1.00) 		0.25
(1.00) 		0.112
(1.00) 		0.0832
(1.00) 		0.192
(1.00)
7q loss 16 (6%) 248 0.0862
(1.00) 		0.763
(1.00) 		0.231
(1.00) 		0.677
(1.00) 		0.61
(1.00) 		1
(1.00) 		0.252
(1.00) 		0.0825
(1.00) 		0.698
(1.00) 		0.942
(1.00)
8q loss 29 (11%) 235 0.237
(1.00) 		0.0963
(1.00) 		0.498
(1.00) 		0.0107
(1.00) 		0.00307
(1.00) 		0.169
(1.00) 		0.0347
(1.00) 		0.0436
(1.00) 		0.00299
(1.00) 		0.137
(1.00)
10p loss 47 (18%) 217 0.503
(1.00) 		0.013
(1.00) 		0.911
(1.00) 		0.264
(1.00) 		0.0242
(1.00) 		0.0627
(1.00) 		0.315
(1.00) 		0.293
(1.00) 		0.568
(1.00) 		0.305
(1.00)
10q loss 87 (33%) 177 0.00066
(0.507) 		0.00914
(1.00) 		0.563
(1.00) 		0.73
(1.00) 		0.0425
(1.00) 		0.293
(1.00) 		0.299
(1.00) 		0.133
(1.00) 		0.262
(1.00) 		0.42
(1.00)
12p loss 28 (11%) 236 0.227
(1.00) 		0.462
(1.00) 		0.943
(1.00) 		0.472
(1.00) 		0.399
(1.00) 		0.646
(1.00) 		0.374
(1.00) 		0.903
(1.00) 		0.699
(1.00) 		0.892
(1.00)
12q loss 34 (13%) 230 0.587
(1.00) 		0.728
(1.00) 		0.369
(1.00) 		0.409
(1.00) 		0.973
(1.00) 		0.891
(1.00) 		0.486
(1.00) 		0.741
(1.00) 		0.914
(1.00) 		0.938
(1.00)
13q loss 53 (20%) 211 0.00351
(1.00) 		0.872
(1.00) 		0.0106
(1.00) 		0.103
(1.00) 		0.0943
(1.00) 		0.609
(1.00) 		1
(1.00) 		0.0108
(1.00) 		0.861
(1.00) 		0.251
(1.00)
16p loss 68 (26%) 196 0.0694
(1.00) 		0.0441
(1.00) 		0.657
(1.00) 		0.477
(1.00) 		0.634
(1.00) 		0.778
(1.00) 		0.774
(1.00) 		0.0507
(1.00) 		0.71
(1.00) 		0.499
(1.00)
16q loss 62 (23%) 202 0.0277
(1.00) 		0.0365
(1.00) 		0.226
(1.00) 		0.792
(1.00) 		0.563
(1.00) 		0.799
(1.00) 		0.342
(1.00) 		0.0543
(1.00) 		0.575
(1.00) 		0.0795
(1.00)
17q loss 27 (10%) 237 0.258
(1.00) 		0.27
(1.00) 		0.97
(1.00) 		0.942
(1.00) 		0.869
(1.00) 		0.864
(1.00) 		0.811
(1.00) 		0.571
(1.00) 		0.893
(1.00) 		0.826
(1.00)
18p loss 60 (23%) 204 0.0184
(1.00) 		0.265
(1.00) 		0.464
(1.00) 		0.372
(1.00) 		0.652
(1.00) 		0.0409
(1.00) 		0.595
(1.00) 		0.24
(1.00) 		0.59
(1.00) 		0.708
(1.00)
18q loss 91 (34%) 173 0.0477
(1.00) 		0.995
(1.00) 		0.683
(1.00) 		0.743
(1.00) 		0.891
(1.00) 		0.338
(1.00) 		0.0358
(1.00) 		0.0093
(1.00) 		0.116
(1.00) 		0.12
(1.00)
19p loss 67 (25%) 197 0.0116
(1.00) 		0.196
(1.00) 		0.596
(1.00) 		0.398
(1.00) 		0.0142
(1.00) 		0.178
(1.00) 		0.828
(1.00) 		0.0341
(1.00) 		0.643
(1.00) 		0.29
(1.00)
19q loss 41 (16%) 223 0.221
(1.00) 		0.618
(1.00) 		0.205
(1.00) 		0.0968
(1.00) 		0.335
(1.00) 		0.675
(1.00) 		0.422
(1.00) 		0.526
(1.00) 		0.357
(1.00) 		0.238
(1.00)
20p loss 23 (9%) 241 0.101
(1.00) 		0.0325
(1.00) 		0.165
(1.00) 		0.0328
(1.00) 		0.757
(1.00) 		0.461
(1.00) 		0.394
(1.00) 		0.844
(1.00) 		0.167
(1.00) 		0.797
(1.00)
20q loss 9 (3%) 255 0.0278
(1.00) 		0.444
(1.00) 		0.479
(1.00) 		0.346
(1.00) 		1
(1.00) 		0.873
(1.00) 		0.631
(1.00) 		0.817
(1.00) 		1
(1.00) 		0.527
(1.00)
21q loss 44 (17%) 220 0.204
(1.00) 		0.0197
(1.00) 		0.106
(1.00) 		0.296
(1.00) 		0.0196
(1.00) 		0.0246
(1.00) 		0.77
(1.00) 		0.398
(1.00) 		0.194
(1.00) 		0.485
(1.00)
22q loss 102 (39%) 162 0.0146
(1.00) 		0.0171
(1.00) 		0.581
(1.00) 		0.0116
(1.00) 		0.0294
(1.00) 		0.177
(1.00) 		0.222
(1.00) 		0.0303
(1.00) 		0.0976
(1.00) 		0.0881
(1.00)
xq loss 50 (19%) 214 0.0314
(1.00) 		0.00403
(1.00) 		0.995
(1.00) 		0.714
(1.00) 		0.125
(1.00) 		0.763
(1.00) 		0.0285
(1.00) 		0.855
(1.00) 		0.0896
(1.00) 		0.398
(1.00)
'2p gain' versus 'CN_CNMF'

P value = 0.00018 (Fisher's exact test), Q value = 0.14

Table S1.  Gene #3: '2p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
2P GAIN MUTATED 29 14 32
2P GAIN WILD-TYPE 38 82 69

Figure S1.  Get High-res Image Gene #3: '2p gain' versus Molecular Subtype #1: 'CN_CNMF'

'2p gain' versus 'METHLYATION_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.008

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

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 89 60 54 47
2P GAIN MUTATED 20 33 12 7
2P GAIN WILD-TYPE 69 27 42 40

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

'3q gain' versus 'CN_CNMF'

P value = 5e-05 (Fisher's exact test), Q value = 0.039

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
3Q GAIN MUTATED 44 29 45
3Q GAIN WILD-TYPE 23 67 56

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

'7p gain' versus 'CN_CNMF'

P value = 0.00024 (Fisher's exact test), Q value = 0.19

Table S4.  Gene #13: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
7P GAIN MUTATED 36 25 50
7P GAIN WILD-TYPE 31 71 51

Figure S4.  Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

'8p gain' versus 'CN_CNMF'

P value = 9e-05 (Fisher's exact test), Q value = 0.07

Table S5.  Gene #15: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
8P GAIN MUTATED 14 8 33
8P GAIN WILD-TYPE 53 88 68

Figure S5.  Get High-res Image Gene #15: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

'8q gain' versus 'CN_CNMF'

P value = 0.00017 (Fisher's exact test), Q value = 0.13

Table S6.  Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
8Q GAIN MUTATED 37 28 57
8Q GAIN WILD-TYPE 30 68 44

Figure S6.  Get High-res Image Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

'10p gain' versus 'CN_CNMF'

P value = 6e-05 (Fisher's exact test), Q value = 0.047

Table S7.  Gene #19: '10p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
10P GAIN MUTATED 33 17 25
10P GAIN WILD-TYPE 34 79 76

Figure S7.  Get High-res Image Gene #19: '10p gain' versus Molecular Subtype #1: 'CN_CNMF'

'17q gain' versus 'CN_CNMF'

P value = 2e-04 (Fisher's exact test), Q value = 0.16

Table S8.  Gene #31: '17q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
17Q GAIN MUTATED 30 18 42
17Q GAIN WILD-TYPE 37 78 59

Figure S8.  Get High-res Image Gene #31: '17q gain' versus Molecular Subtype #1: 'CN_CNMF'

'19q gain' versus 'CN_CNMF'

P value = 1e-04 (Fisher's exact test), Q value = 0.078

Table S9.  Gene #35: '19q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
19Q GAIN MUTATED 31 17 42
19Q GAIN WILD-TYPE 36 79 59

Figure S9.  Get High-res Image Gene #35: '19q gain' versus Molecular Subtype #1: 'CN_CNMF'

'21q gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.008

Table S10.  Gene #38: '21q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
21Q GAIN MUTATED 41 17 21
21Q GAIN WILD-TYPE 26 79 80

Figure S10.  Get High-res Image Gene #38: '21q gain' versus Molecular Subtype #1: 'CN_CNMF'

'21q gain' versus 'METHLYATION_CNMF'

P value = 7e-05 (Fisher's exact test), Q value = 0.055

Table S11.  Gene #38: '21q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 89 60 54 47
21Q GAIN MUTATED 19 33 14 9
21Q GAIN WILD-TYPE 70 27 40 38

Figure S11.  Get High-res Image Gene #38: '21q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'3p loss' versus 'MRNASEQ_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.008

Table S12.  Gene #45: '3p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 118 72 73
3P LOSS MUTATED 7 3 21
3P LOSS WILD-TYPE 111 69 52

Figure S12.  Get High-res Image Gene #45: '3p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'3p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.008

Table S13.  Gene #45: '3p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 96 44 64 59
3P LOSS MUTATED 6 5 1 19
3P LOSS WILD-TYPE 90 39 63 40

Figure S13.  Get High-res Image Gene #45: '3p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'6p loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00024 (Fisher's exact test), Q value = 0.19

Table S14.  Gene #51: '6p loss' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 44 24 31 34 47 36 47
6P LOSS MUTATED 16 4 12 12 13 5 2
6P LOSS WILD-TYPE 28 20 19 22 34 31 45

Figure S14.  Get High-res Image Gene #51: '6p loss' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

'6q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.008

Table S15.  Gene #52: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
6Q LOSS MUTATED 35 19 43
6Q LOSS WILD-TYPE 32 77 58

Figure S15.  Get High-res Image Gene #52: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'8p loss' versus 'CN_CNMF'

P value = 5e-05 (Fisher's exact test), Q value = 0.039

Table S16.  Gene #55: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
8P LOSS MUTATED 45 45 31
8P LOSS WILD-TYPE 22 51 70

Figure S16.  Get High-res Image Gene #55: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.008

Table S17.  Gene #57: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
9P LOSS MUTATED 23 20 71
9P LOSS WILD-TYPE 44 76 30

Figure S17.  Get High-res Image Gene #57: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.008

Table S18.  Gene #58: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
9Q LOSS MUTATED 22 20 62
9Q LOSS WILD-TYPE 45 76 39

Figure S18.  Get High-res Image Gene #58: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

'9q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 7e-05 (Fisher's exact test), Q value = 0.055

Table S19.  Gene #58: '9q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 96 44 64 59
9Q LOSS MUTATED 43 10 37 14
9Q LOSS WILD-TYPE 53 34 27 45

Figure S19.  Get High-res Image Gene #58: '9q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'11p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.008

Table S20.  Gene #61: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
11P LOSS MUTATED 38 11 59
11P LOSS WILD-TYPE 29 85 42

Figure S20.  Get High-res Image Gene #61: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

'11p loss' versus 'METHLYATION_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.008

Table S21.  Gene #61: '11p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 89 60 54 47
11P LOSS MUTATED 18 34 28 24
11P LOSS WILD-TYPE 71 26 26 23

Figure S21.  Get High-res Image Gene #61: '11p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'11q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.008

Table S22.  Gene #62: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
11Q LOSS MUTATED 32 8 41
11Q LOSS WILD-TYPE 35 88 60

Figure S22.  Get High-res Image Gene #62: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

'14q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.008

Table S23.  Gene #66: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
14Q LOSS MUTATED 34 11 30
14Q LOSS WILD-TYPE 33 85 71

Figure S23.  Get High-res Image Gene #66: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

'15q loss' versus 'METHLYATION_CNMF'

P value = 0.00026 (Fisher's exact test), Q value = 0.2

Table S24.  Gene #67: '15q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 89 60 54 47
15Q LOSS MUTATED 38 27 15 5
15Q LOSS WILD-TYPE 51 33 39 42

Figure S24.  Get High-res Image Gene #67: '15q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'15q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 4e-05 (Fisher's exact test), Q value = 0.032

Table S25.  Gene #67: '15q loss' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 44 24 31 34 47 36 47
15Q LOSS MUTATED 18 13 16 15 11 11 4
15Q LOSS WILD-TYPE 26 11 15 19 36 25 43

Figure S25.  Get High-res Image Gene #67: '15q loss' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

'17p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.008

Table S26.  Gene #70: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 67 96 101
17P LOSS MUTATED 34 22 60
17P LOSS WILD-TYPE 33 74 41

Figure S26.  Get High-res Image Gene #70: '17p 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 = 264

  • Number of significantly arm-level cnvs = 80

  • 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

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] 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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