Correlation between copy number variations of arm-level result and molecular subtypes
Bladder Urothelial Carcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C1RN361H
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/C1RN361H
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 76 arm-level results and 8 molecular subtypes across 150 patients, 15 significant findings detected with Q value < 0.25.

  • 2p gain cnv correlated to 'CN_CNMF'.

  • 3p gain cnv correlated to 'CN_CNMF'.

  • 17q gain cnv correlated to 'CN_CNMF'.

  • 18p gain cnv correlated to 'CN_CNMF'.

  • 6q loss cnv correlated to 'CN_CNMF'.

  • 8p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_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'.

  • 11q loss cnv correlated to 'CN_CNMF'.

  • 14q loss cnv correlated to 'CN_CNMF'.

  • 18q 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 76 arm-level results and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 15 significant findings detected.

Molecular
subtypes 		CN
CNMF 		METHLYATION
CNMF 		RPPA
CNMF 		RPPA
CHIERARCHICAL 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL
nCNV (%) nWild-Type Chi-square test 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
8p loss 49 (33%) 101 6.4e-07
(0.000361) 		3.08e-05
(0.0172) 		0.143
(1.00) 		0.123
(1.00) 		0.643
(1.00) 		0.441
(1.00) 		0.048
(1.00) 		0.0745
(1.00)
9q loss 41 (27%) 109 7.82e-05
(0.0435) 		0.00545
(1.00) 		0.00121
(0.65) 		0.00113
(0.612) 		0.00274
(1.00) 		0.000115
(0.0637) 		0.798
(1.00) 		0.348
(1.00)
2p gain 28 (19%) 122 0.000111
(0.0615) 		0.00102
(0.555) 		0.214
(1.00) 		0.528
(1.00) 		0.282
(1.00) 		0.738
(1.00) 		0.0171
(1.00) 		0.0605
(1.00)
3p gain 30 (20%) 120 3.51e-06
(0.00197) 		0.0447
(1.00) 		0.0287
(1.00) 		0.159
(1.00) 		0.0909
(1.00) 		0.005
(1.00) 		0.0454
(1.00) 		0.261
(1.00)
17q gain 25 (17%) 125 0.000383
(0.211) 		0.0103
(1.00) 		0.497
(1.00) 		0.333
(1.00) 		0.0233
(1.00) 		0.108
(1.00) 		0.147
(1.00) 		0.0627
(1.00)
18p gain 26 (17%) 124 4.9e-06
(0.00275) 		0.221
(1.00) 		0.933
(1.00) 		0.303
(1.00) 		0.0652
(1.00) 		0.579
(1.00) 		0.214
(1.00) 		0.665
(1.00)
6q loss 29 (19%) 121 6.05e-06
(0.00339) 		0.00883
(1.00) 		0.247
(1.00) 		0.521
(1.00) 		0.26
(1.00) 		0.0477
(1.00) 		0.825
(1.00) 		0.752
(1.00)
9p loss 43 (29%) 107 0.0002
(0.11) 		0.00652
(1.00) 		0.0374
(1.00) 		0.125
(1.00) 		0.0341
(1.00) 		0.000813
(0.442) 		0.883
(1.00) 		0.115
(1.00)
11p loss 48 (32%) 102 1.36e-06
(0.000767) 		0.0019
(1.00) 		0.232
(1.00) 		0.365
(1.00) 		0.0739
(1.00) 		0.00248
(1.00) 		0.206
(1.00) 		0.647
(1.00)
11q loss 35 (23%) 115 0.000188
(0.104) 		0.0298
(1.00) 		0.3
(1.00) 		0.697
(1.00) 		0.211
(1.00) 		0.424
(1.00) 		0.201
(1.00) 		0.246
(1.00)
14q loss 25 (17%) 125 0.000374
(0.206) 		0.0272
(1.00) 		0.818
(1.00) 		0.364
(1.00) 		0.746
(1.00) 		0.47
(1.00) 		0.0573
(1.00) 		0.117
(1.00)
18q loss 39 (26%) 111 1.54e-05
(0.0086) 		0.709
(1.00) 		0.813
(1.00) 		0.489
(1.00) 		0.182
(1.00) 		0.559
(1.00) 		0.553
(1.00) 		0.218
(1.00)
22q loss 29 (19%) 121 6.3e-05
(0.0351) 		0.669
(1.00) 		0.0706
(1.00) 		0.00444
(1.00) 		0.0686
(1.00) 		0.12
(1.00) 		0.885
(1.00) 		0.415
(1.00)
1p gain 16 (11%) 134 0.00303
(1.00) 		0.172
(1.00) 		0.466
(1.00) 		0.869
(1.00) 		0.518
(1.00) 		0.386
(1.00) 		0.279
(1.00) 		0.816
(1.00)
1q gain 32 (21%) 118 0.127
(1.00) 		0.478
(1.00) 		0.941
(1.00) 		0.59
(1.00) 		0.822
(1.00) 		0.655
(1.00) 		0.34
(1.00) 		0.467
(1.00)
2q gain 11 (7%) 139 0.059
(1.00) 		0.241
(1.00) 		0.69
(1.00) 		0.777
(1.00) 		0.342
(1.00) 		0.359
(1.00) 		0.201
(1.00) 		0.274
(1.00)
3q gain 42 (28%) 108 0.000559
(0.307) 		0.264
(1.00) 		1
(1.00) 		0.576
(1.00) 		0.586
(1.00) 		0.0857
(1.00) 		0.228
(1.00) 		0.0628
(1.00)
4p gain 8 (5%) 142 0.443
(1.00) 		0.625
(1.00) 		1
(1.00) 		0.643
(1.00) 		1
(1.00) 		0.613
(1.00) 		0.15
(1.00) 		1
(1.00)
4q gain 3 (2%) 147 0.296
(1.00) 		0.405
(1.00) 		0.782
(1.00) 		0.727
(1.00) 		0.435
(1.00) 		1
(1.00)
5p gain 40 (27%) 110 0.0862
(1.00) 		0.402
(1.00) 		0.0287
(1.00) 		0.264
(1.00) 		0.354
(1.00) 		0.601
(1.00) 		0.459
(1.00) 		0.158
(1.00)
5q gain 18 (12%) 132 0.0903
(1.00) 		0.0769
(1.00) 		0.228
(1.00) 		0.666
(1.00) 		0.703
(1.00) 		1
(1.00) 		0.191
(1.00) 		0.252
(1.00)
6p gain 8 (5%) 142 0.545
(1.00) 		0.182
(1.00) 		1
(1.00) 		0.227
(1.00) 		0.753
(1.00) 		0.83
(1.00)
6q gain 5 (3%) 145 0.402
(1.00) 		0.382
(1.00) 		0.206
(1.00) 		0.194
(1.00)
7p gain 46 (31%) 104 0.00188
(1.00) 		0.00172
(0.926) 		0.835
(1.00) 		0.38
(1.00) 		0.968
(1.00) 		0.963
(1.00) 		0.0753
(1.00) 		0.554
(1.00)
7q gain 43 (29%) 107 0.00249
(1.00) 		0.0504
(1.00) 		1
(1.00) 		0.523
(1.00) 		0.968
(1.00) 		0.891
(1.00) 		0.51
(1.00) 		1
(1.00)
8p gain 15 (10%) 135 0.104
(1.00) 		0.0034
(1.00) 		0.192
(1.00) 		0.625
(1.00) 		0.0776
(1.00) 		1
(1.00) 		0.0911
(1.00) 		0.279
(1.00)
8q gain 39 (26%) 111 0.0523
(1.00) 		0.0887
(1.00) 		0.623
(1.00) 		0.928
(1.00) 		0.278
(1.00) 		0.889
(1.00) 		0.199
(1.00) 		0.297
(1.00)
9p gain 15 (10%) 135 0.00336
(1.00) 		0.437
(1.00) 		0.189
(1.00) 		0.643
(1.00) 		0.518
(1.00) 		0.0987
(1.00) 		0.134
(1.00) 		0.321
(1.00)
9q gain 11 (7%) 139 0.494
(1.00) 		0.323
(1.00) 		0.0979
(1.00) 		0.394
(1.00) 		0.0556
(1.00) 		0.038
(1.00) 		0.777
(1.00) 		0.886
(1.00)
10p gain 28 (19%) 122 0.00114
(0.614) 		0.00192
(1.00) 		0.382
(1.00) 		0.0203
(1.00) 		0.523
(1.00) 		0.651
(1.00) 		0.664
(1.00) 		0.261
(1.00)
10q gain 7 (5%) 143 0.341
(1.00) 		0.188
(1.00) 		0.512
(1.00) 		0.347
(1.00) 		0.553
(1.00) 		0.164
(1.00) 		0.887
(1.00) 		0.149
(1.00)
11p gain 8 (5%) 142 0.0507
(1.00) 		0.956
(1.00) 		0.724
(1.00) 		1
(1.00) 		0.445
(1.00) 		0.725
(1.00)
11q gain 8 (5%) 142 0.247
(1.00) 		0.518
(1.00) 		0.483
(1.00) 		0.36
(1.00) 		0.642
(1.00) 		0.522
(1.00)
12p gain 24 (16%) 126 0.00378
(1.00) 		0.624
(1.00) 		0.13
(1.00) 		0.264
(1.00) 		0.914
(1.00) 		0.493
(1.00) 		0.045
(1.00) 		0.369
(1.00)
12q gain 17 (11%) 133 0.0139
(1.00) 		0.308
(1.00) 		0.419
(1.00) 		0.435
(1.00) 		0.409
(1.00) 		0.759
(1.00) 		0.0363
(1.00) 		0.498
(1.00)
13q gain 25 (17%) 125 0.218
(1.00) 		0.885
(1.00) 		0.0318
(1.00) 		0.0351
(1.00) 		0.0442
(1.00) 		0.0452
(1.00) 		0.399
(1.00) 		0.819
(1.00)
14q gain 11 (7%) 139 0.0903
(1.00) 		0.898
(1.00) 		0.206
(1.00) 		0.287
(1.00) 		0.278
(1.00) 		0.176
(1.00) 		0.357
(1.00) 		0.379
(1.00)
15q gain 5 (3%) 145 0.0382
(1.00) 		0.0314
(1.00) 		0.296
(1.00) 		0.777
(1.00) 		0.683
(1.00) 		1
(1.00) 		0.455
(1.00) 		0.519
(1.00)
16p gain 10 (7%) 140 0.0499
(1.00) 		0.609
(1.00) 		0.638
(1.00) 		0.814
(1.00) 		0.751
(1.00) 		0.717
(1.00) 		1
(1.00) 		0.115
(1.00)
16q gain 13 (9%) 137 0.0043
(1.00) 		0.266
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.256
(1.00) 		0.925
(1.00) 		0.197
(1.00)
17p gain 9 (6%) 141 0.193
(1.00) 		0.551
(1.00) 		0.724
(1.00) 		0.545
(1.00) 		0.15
(1.00) 		0.432
(1.00)
18q gain 9 (6%) 141 0.0331
(1.00) 		0.599
(1.00) 		0.465
(1.00) 		0.337
(1.00) 		0.431
(1.00) 		0.289
(1.00) 		1
(1.00) 		1
(1.00)
19p gain 15 (10%) 135 0.0331
(1.00) 		0.0585
(1.00) 		0.109
(1.00) 		0.489
(1.00) 		0.513
(1.00) 		0.64
(1.00)
19q gain 29 (19%) 121 0.0007
(0.383) 		0.117
(1.00) 		0.633
(1.00) 		0.822
(1.00) 		0.0467
(1.00) 		0.105
(1.00) 		0.588
(1.00) 		1
(1.00)
20p gain 54 (36%) 96 0.0335
(1.00) 		0.0771
(1.00) 		0.415
(1.00) 		0.37
(1.00) 		0.475
(1.00) 		0.151
(1.00) 		0.265
(1.00) 		0.309
(1.00)
20q gain 59 (39%) 91 0.0206
(1.00) 		0.0511
(1.00) 		0.439
(1.00) 		0.662
(1.00) 		0.0775
(1.00) 		0.088
(1.00) 		0.0564
(1.00) 		0.229
(1.00)
21q gain 27 (18%) 123 0.00187
(1) 		0.0011
(0.599) 		0.598
(1.00) 		1
(1.00) 		0.191
(1.00) 		0.102
(1.00) 		0.273
(1.00) 		0.103
(1.00)
22q gain 12 (8%) 138 0.000744
(0.405) 		0.165
(1.00) 		0.536
(1.00) 		0.44
(1.00) 		0.451
(1.00) 		0.903
(1.00) 		0.0424
(1.00) 		0.232
(1.00)
Xq gain 6 (4%) 144 0.113
(1.00) 		0.801
(1.00) 		0.763
(1.00) 		1
(1.00) 		1
(1.00) 		0.293
(1.00)
1p loss 4 (3%) 146 0.456
(1.00) 		0.0509
(1.00) 		0.605
(1.00) 		1
(1.00)
2p loss 8 (5%) 142 0.828
(1.00) 		0.0229
(1.00) 		0.368
(1.00) 		0.164
(1.00) 		1
(1.00) 		0.432
(1.00)
2q loss 17 (11%) 133 0.0112
(1.00) 		0.472
(1.00) 		1
(1.00) 		0.424
(1.00) 		0.463
(1.00) 		0.0323
(1.00) 		0.779
(1.00) 		0.911
(1.00)
3p loss 9 (6%) 141 0.0633
(1.00) 		0.773
(1.00) 		0.345
(1.00) 		0.666
(1.00) 		0.0858
(1.00) 		0.0719
(1.00) 		0.148
(1.00) 		0.273
(1.00)
4p loss 29 (19%) 121 0.000739
(0.403) 		0.292
(1.00) 		0.853
(1.00) 		0.68
(1.00) 		0.425
(1.00) 		0.342
(1.00) 		0.425
(1.00) 		0.517
(1.00)
4q loss 26 (17%) 124 0.0777
(1.00) 		0.78
(1.00) 		0.68
(1.00) 		0.333
(1.00) 		0.593
(1.00) 		0.601
(1.00) 		0.326
(1.00) 		0.675
(1.00)
5p loss 14 (9%) 136 0.000607
(0.333) 		0.609
(1.00) 		0.517
(1.00) 		1
(1.00) 		0.532
(1.00) 		0.721
(1.00) 		0.279
(1.00) 		0.262
(1.00)
5q loss 36 (24%) 114 0.00112
(0.608) 		0.0923
(1.00) 		0.767
(1.00) 		0.822
(1.00) 		0.895
(1.00) 		0.772
(1.00) 		0.151
(1.00) 		0.415
(1.00)
6p loss 18 (12%) 132 0.0517
(1.00) 		0.238
(1.00) 		0.233
(1.00) 		0.353
(1.00) 		0.384
(1.00) 		0.812
(1.00) 		0.759
(1.00) 		0.519
(1.00)
7q loss 3 (2%) 147 0.375
(1.00) 		0.292
(1.00)
8q loss 5 (3%) 145 0.285
(1.00) 		0.192
(1.00) 		0.782
(1.00) 		1
(1.00) 		0.349
(1.00) 		0.0688
(1.00)
10p loss 19 (13%) 131 0.763
(1.00) 		0.878
(1.00) 		0.189
(1.00) 		0.409
(1.00) 		0.252
(1.00) 		0.275
(1.00) 		0.183
(1.00) 		0.42
(1.00)
10q loss 30 (20%) 120 0.118
(1.00) 		0.0538
(1.00) 		0.921
(1.00) 		0.717
(1.00) 		0.209
(1.00) 		0.0406
(1.00) 		0.0308
(1.00) 		0.359
(1.00)
12p loss 6 (4%) 144 0.159
(1.00) 		0.161
(1.00) 		0.325
(1.00) 		0.284
(1.00) 		1
(1.00) 		0.439
(1.00)
12q loss 9 (6%) 141 0.159
(1.00) 		1
(1.00) 		0.15
(1.00) 		0.36
(1.00) 		0.15
(1.00) 		1
(1.00)
13q loss 20 (13%) 130 0.0157
(1.00) 		0.311
(1.00) 		0.104
(1.00) 		0.173
(1.00) 		0.111
(1.00) 		0.418
(1.00) 		0.049
(1.00) 		0.662
(1.00)
15q loss 19 (13%) 131 0.168
(1.00) 		0.095
(1.00) 		0.121
(1.00) 		0.561
(1.00) 		0.0776
(1.00) 		0.0576
(1.00) 		0.0515
(1.00) 		0.246
(1.00)
16p loss 17 (11%) 133 0.0179
(1.00) 		0.276
(1.00) 		0.603
(1.00) 		0.471
(1.00) 		0.343
(1.00) 		0.864
(1.00) 		0.326
(1.00) 		0.686
(1.00)
16q loss 17 (11%) 133 0.00477
(1.00) 		0.399
(1.00) 		0.75
(1.00) 		0.503
(1.00) 		0.735
(1.00) 		0.806
(1.00) 		0.823
(1.00) 		0.828
(1.00)
17p loss 42 (28%) 108 0.00208
(1.00) 		0.108
(1.00) 		0.541
(1.00) 		0.869
(1.00) 		0.00626
(1.00) 		0.161
(1.00) 		0.217
(1.00) 		0.323
(1.00)
17q loss 6 (4%) 144 0.72
(1.00) 		0.0394
(1.00) 		0.857
(1.00) 		0.845
(1.00) 		0.266
(1.00) 		0.51
(1.00)
18p loss 22 (15%) 128 0.005
(1.00) 		0.0335
(1.00) 		0.507
(1.00) 		0.195
(1.00) 		1
(1.00) 		0.172
(1.00) 		0.581
(1.00) 		0.0113
(1.00)
19p loss 9 (6%) 141 0.3
(1.00) 		0.933
(1.00) 		0.252
(1.00) 		0.11
(1.00) 		0.415
(1.00) 		0.356
(1.00) 		0.15
(1.00) 		1
(1.00)
19q loss 4 (3%) 146 0.545
(1.00) 		0.702
(1.00) 		0.48
(1.00) 		0.727
(1.00) 		0.183
(1.00) 		1
(1.00)
20p loss 7 (5%) 143 0.313
(1.00) 		0.251
(1.00) 		1
(1.00) 		1
(1.00) 		0.868
(1.00) 		0.663
(1.00)
21q loss 17 (11%) 133 0.556
(1.00) 		0.533
(1.00) 		0.466
(1.00) 		0.471
(1.00) 		0.674
(1.00) 		0.584
(1.00) 		0.467
(1.00) 		0.904
(1.00)
Xq loss 4 (3%) 146 0.252
(1.00) 		0.285
(1.00) 		0.48
(1.00) 		0.562
(1.00) 		0.808
(1.00) 		1
(1.00)
'2p gain mutation analysis' versus 'CN_CNMF'

P value = 0.000111 (Chi-square test), Q value = 0.062

Table S1.  Gene #3: '2p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
2P GAIN MUTATED 4 1 6 4 7 6
2P GAIN WILD-TYPE 10 52 18 25 6 11

Figure S1.  Get High-res Image Gene #3: '2p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'3p gain mutation analysis' versus 'CN_CNMF'

P value = 3.51e-06 (Chi-square test), Q value = 0.002

Table S2.  Gene #5: '3p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
3P GAIN MUTATED 2 3 7 7 0 11
3P GAIN WILD-TYPE 12 50 17 22 13 6

Figure S2.  Get High-res Image Gene #5: '3p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'17q gain mutation analysis' versus 'CN_CNMF'

P value = 0.000383 (Chi-square test), Q value = 0.21

Table S3.  Gene #31: '17q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
17Q GAIN MUTATED 6 0 7 7 1 4
17Q GAIN WILD-TYPE 8 53 17 22 12 13

Figure S3.  Get High-res Image Gene #31: '17q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'18p gain mutation analysis' versus 'CN_CNMF'

P value = 4.9e-06 (Chi-square test), Q value = 0.0027

Table S4.  Gene #32: '18p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
18P GAIN MUTATED 1 1 11 3 6 4
18P GAIN WILD-TYPE 13 52 13 26 7 13

Figure S4.  Get High-res Image Gene #32: '18p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'6q loss mutation analysis' versus 'CN_CNMF'

P value = 6.05e-06 (Chi-square test), Q value = 0.0034

Table S5.  Gene #50: '6q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
6Q LOSS MUTATED 4 0 4 8 3 10
6Q LOSS WILD-TYPE 10 53 20 21 10 7

Figure S5.  Get High-res Image Gene #50: '6q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'8p loss mutation analysis' versus 'CN_CNMF'

P value = 6.4e-07 (Chi-square test), Q value = 0.00036

Table S6.  Gene #52: '8p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
8P LOSS MUTATED 10 11 12 0 8 8
8P LOSS WILD-TYPE 4 42 12 29 5 9

Figure S6.  Get High-res Image Gene #52: '8p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'8p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 3.08e-05 (Fisher's exact test), Q value = 0.017

Table S7.  Gene #52: '8p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 36 50 39 25
8P LOSS MUTATED 23 15 5 6
8P LOSS WILD-TYPE 13 35 34 19

Figure S7.  Get High-res Image Gene #52: '8p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'9p loss mutation analysis' versus 'CN_CNMF'

P value = 2e-04 (Chi-square test), Q value = 0.11

Table S8.  Gene #54: '9p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
9P LOSS MUTATED 2 9 9 17 0 6
9P LOSS WILD-TYPE 12 44 15 12 13 11

Figure S8.  Get High-res Image Gene #54: '9p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'9q loss mutation analysis' versus 'CN_CNMF'

P value = 7.82e-05 (Chi-square test), Q value = 0.044

Table S9.  Gene #55: '9q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
9Q LOSS MUTATED 1 8 10 17 1 4
9Q LOSS WILD-TYPE 13 45 14 12 12 13

Figure S9.  Get High-res Image Gene #55: '9q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'9q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000115 (Fisher's exact test), Q value = 0.064

Table S10.  Gene #55: '9q loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 39 18 64
9Q LOSS MUTATED 4 2 29
9Q LOSS WILD-TYPE 35 16 35

Figure S10.  Get High-res Image Gene #55: '9q loss mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

'11p loss mutation analysis' versus 'CN_CNMF'

P value = 1.36e-06 (Chi-square test), Q value = 0.00077

Table S11.  Gene #58: '11p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
11P LOSS MUTATED 4 4 11 15 2 12
11P LOSS WILD-TYPE 10 49 13 14 11 5

Figure S11.  Get High-res Image Gene #58: '11p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'11q loss mutation analysis' versus 'CN_CNMF'

P value = 0.000188 (Chi-square test), Q value = 0.1

Table S12.  Gene #59: '11q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
11Q LOSS MUTATED 2 2 10 13 3 5
11Q LOSS WILD-TYPE 12 51 14 16 10 12

Figure S12.  Get High-res Image Gene #59: '11q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'14q loss mutation analysis' versus 'CN_CNMF'

P value = 0.000374 (Chi-square test), Q value = 0.21

Table S13.  Gene #63: '14q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
14Q LOSS MUTATED 4 1 8 3 2 7
14Q LOSS WILD-TYPE 10 52 16 26 11 10

Figure S13.  Get High-res Image Gene #63: '14q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'18q loss mutation analysis' versus 'CN_CNMF'

P value = 1.54e-05 (Chi-square test), Q value = 0.0086

Table S14.  Gene #70: '18q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
18Q LOSS MUTATED 5 4 15 6 2 7
18Q LOSS WILD-TYPE 9 49 9 23 11 10

Figure S14.  Get High-res Image Gene #70: '18q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'22q loss mutation analysis' versus 'CN_CNMF'

P value = 6.3e-05 (Chi-square test), Q value = 0.035

Table S15.  Gene #75: '22q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 53 24 29 13 17
22Q LOSS MUTATED 2 6 7 3 9 2
22Q LOSS WILD-TYPE 12 47 17 26 4 15

Figure S15.  Get High-res Image Gene #75: '22q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

Methods & Data
Input

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

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

  • Number of patients = 150

  • Number of significantly arm-level cnvs = 76

  • Number of molecular subtypes = 8

  • Exclude genes that fewer than K tumors have mutations, K = 3

Chi-square test

For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.test' function in R

Fisher's exact test

For binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R

Q value calculation

For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.

Download Results

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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