Correlation between copy number variations of arm-level result and molecular subtypes
Cervical Squamous Cell Carcinoma and Endocervical Adenocarcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
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/C1ZW1JS1
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 8 molecular subtypes across 295 patients, 26 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 1p gain cnv correlated to 'MIRSEQ_CHIERARCHICAL'.

  • 1q gain cnv correlated to 'CN_CNMF'.

  • 2p gain cnv correlated to 'CN_CNMF'.

  • 2q gain cnv correlated to 'CN_CNMF'.

  • 3q gain cnv correlated to 'CN_CNMF',  'MIRSEQ_CHIERARCHICAL', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 5p gain cnv correlated to 'CN_CNMF'.

  • 8q gain cnv correlated to 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 19q gain cnv correlated to 'CN_CNMF'.

  • 3p loss cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

  • 4p loss cnv correlated to 'CN_CNMF' and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 4q loss cnv correlated to 'CN_CNMF'.

  • 8p loss cnv correlated to 'CN_CNMF'.

  • 8q loss cnv correlated to 'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

  • 9q loss cnv correlated to 'CN_CNMF'.

  • 11q loss cnv correlated to 'CN_CNMF'.

  • 18q loss cnv correlated to 'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

  • 19p loss cnv correlated to 'CN_CNMF' and 'MIRSEQ_CHIERARCHICAL'.

  • 21q 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 8 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
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
3q gain 175 (59%) 120 1e-05
(0.0064)
0.00168
(0.983)
0.0005
(0.305)
0.00209
(1.00)
0.357
(1.00)
0.00028
(0.173)
0.00345
(1.00)
0.00023
(0.143)
8q loss 24 (8%) 271 0.126
(1.00)
0.0155
(1.00)
5e-05
(0.0314)
0.00034
(0.209)
0.0169
(1.00)
0.00027
(0.167)
0.463
(1.00)
0.0013
(0.764)
18q loss 73 (25%) 222 0.616
(1.00)
0.00083
(0.496)
1e-05
(0.0064)
0.0004
(0.246)
0.0823
(1.00)
0.00019
(0.118)
0.078
(1.00)
0.0195
(1.00)
4p loss 131 (44%) 164 1e-05
(0.0064)
0.068
(1.00)
0.00119
(0.703)
0.00047
(0.288)
0.394
(1.00)
0.00082
(0.492)
1
(1.00)
0.00029
(0.179)
19p loss 60 (20%) 235 1e-05
(0.0064)
0.0025
(1.00)
0.00052
(0.317)
0.00309
(1.00)
0.0299
(1.00)
0.00016
(0.0998)
0.0503
(1.00)
0.0145
(1.00)
1p gain 90 (31%) 205 0.0094
(1.00)
0.0148
(1.00)
0.00125
(0.737)
0.0429
(1.00)
0.418
(1.00)
6e-05
(0.0377)
0.333
(1.00)
0.0124
(1.00)
1q gain 140 (47%) 155 0.00016
(0.0998)
0.0164
(1.00)
0.00762
(1.00)
0.0797
(1.00)
0.488
(1.00)
0.00372
(1.00)
0.155
(1.00)
0.0101
(1.00)
2p gain 64 (22%) 231 1e-05
(0.0064)
0.153
(1.00)
0.025
(1.00)
0.0473
(1.00)
0.169
(1.00)
0.00085
(0.507)
0.182
(1.00)
0.389
(1.00)
2q gain 37 (13%) 258 0.00016
(0.0998)
0.397
(1.00)
0.0181
(1.00)
0.00592
(1.00)
0.161
(1.00)
0.00251
(1.00)
0.157
(1.00)
0.661
(1.00)
5p gain 113 (38%) 182 1e-05
(0.0064)
0.0975
(1.00)
0.0271
(1.00)
0.00489
(1.00)
0.0345
(1.00)
0.00788
(1.00)
0.496
(1.00)
0.0294
(1.00)
8q gain 91 (31%) 204 0.271
(1.00)
0.26
(1.00)
0.0781
(1.00)
0.00947
(1.00)
0.166
(1.00)
0.0067
(1.00)
0.616
(1.00)
0.00013
(0.0814)
19q gain 72 (24%) 223 1e-05
(0.0064)
0.102
(1.00)
0.357
(1.00)
0.0566
(1.00)
0.68
(1.00)
0.0952
(1.00)
0.816
(1.00)
0.802
(1.00)
3p loss 82 (28%) 213 0.604
(1.00)
0.00255
(1.00)
0.00928
(1.00)
3e-05
(0.0189)
0.0269
(1.00)
0.00385
(1.00)
0.00213
(1.00)
0.00082
(0.492)
4q loss 93 (32%) 202 1e-05
(0.0064)
0.399
(1.00)
0.121
(1.00)
0.00089
(0.53)
0.961
(1.00)
0.0506
(1.00)
0.0545
(1.00)
0.67
(1.00)
8p loss 82 (28%) 213 7e-05
(0.0439)
0.274
(1.00)
0.014
(1.00)
0.614
(1.00)
0.0189
(1.00)
0.0445
(1.00)
0.0104
(1.00)
0.0692
(1.00)
9q loss 51 (17%) 244 0.00015
(0.0937)
0.162
(1.00)
0.0252
(1.00)
0.0436
(1.00)
0.471
(1.00)
0.437
(1.00)
0.00203
(1.00)
0.175
(1.00)
11q loss 115 (39%) 180 2e-05
(0.0126)
0.321
(1.00)
0.357
(1.00)
0.305
(1.00)
0.726
(1.00)
0.00759
(1.00)
0.805
(1.00)
0.47
(1.00)
21q loss 49 (17%) 246 2e-05
(0.0126)
0.0387
(1.00)
0.023
(1.00)
0.00096
(0.571)
0.303
(1.00)
0.0275
(1.00)
0.527
(1.00)
0.774
(1.00)
3p gain 71 (24%) 224 0.515
(1.00)
0.111
(1.00)
0.168
(1.00)
0.328
(1.00)
0.429
(1.00)
0.579
(1.00)
0.428
(1.00)
0.557
(1.00)
4p gain 11 (4%) 284 0.538
(1.00)
0.893
(1.00)
0.653
(1.00)
0.454
(1.00)
0.54
(1.00)
0.598
(1.00)
0.924
(1.00)
0.875
(1.00)
4q gain 16 (5%) 279 0.322
(1.00)
0.0973
(1.00)
0.94
(1.00)
0.362
(1.00)
0.897
(1.00)
0.336
(1.00)
0.898
(1.00)
0.868
(1.00)
5q gain 44 (15%) 251 0.00189
(1.00)
0.88
(1.00)
0.181
(1.00)
0.771
(1.00)
0.893
(1.00)
0.956
(1.00)
0.634
(1.00)
0.874
(1.00)
6p gain 52 (18%) 243 0.122
(1.00)
0.00737
(1.00)
0.00376
(1.00)
0.035
(1.00)
0.544
(1.00)
0.0364
(1.00)
0.308
(1.00)
0.0995
(1.00)
6q gain 36 (12%) 259 0.128
(1.00)
0.114
(1.00)
0.0854
(1.00)
0.107
(1.00)
0.337
(1.00)
0.192
(1.00)
0.337
(1.00)
0.209
(1.00)
7p gain 38 (13%) 257 0.211
(1.00)
0.0377
(1.00)
0.0161
(1.00)
0.259
(1.00)
0.00052
(0.317)
0.0955
(1.00)
0.0597
(1.00)
0.137
(1.00)
7q gain 37 (13%) 258 0.0491
(1.00)
0.148
(1.00)
0.13
(1.00)
0.375
(1.00)
0.00098
(0.582)
0.19
(1.00)
0.0104
(1.00)
0.0615
(1.00)
8p gain 53 (18%) 242 0.777
(1.00)
0.787
(1.00)
0.0955
(1.00)
0.366
(1.00)
0.722
(1.00)
0.0266
(1.00)
0.941
(1.00)
0.0287
(1.00)
9p gain 49 (17%) 246 0.645
(1.00)
0.231
(1.00)
0.528
(1.00)
0.0352
(1.00)
0.327
(1.00)
0.0174
(1.00)
0.787
(1.00)
0.0268
(1.00)
9q gain 47 (16%) 248 0.665
(1.00)
0.00387
(1.00)
0.0546
(1.00)
0.00044
(0.27)
0.0246
(1.00)
0.00336
(1.00)
0.291
(1.00)
0.00053
(0.322)
10p gain 25 (8%) 270 0.0749
(1.00)
0.693
(1.00)
0.155
(1.00)
0.435
(1.00)
0.105
(1.00)
0.697
(1.00)
0.862
(1.00)
0.319
(1.00)
10q gain 17 (6%) 278 0.623
(1.00)
0.72
(1.00)
0.624
(1.00)
0.266
(1.00)
0.356
(1.00)
0.915
(1.00)
0.624
(1.00)
0.707
(1.00)
11p gain 9 (3%) 286 0.761
(1.00)
0.919
(1.00)
0.523
(1.00)
0.168
(1.00)
0.632
(1.00)
0.0201
(1.00)
0.834
(1.00)
0.805
(1.00)
11q gain 8 (3%) 287 0.0182
(1.00)
0.744
(1.00)
0.0091
(1.00)
0.00308
(1.00)
0.202
(1.00)
0.0224
(1.00)
0.266
(1.00)
0.579
(1.00)
12p gain 53 (18%) 242 0.238
(1.00)
0.266
(1.00)
0.563
(1.00)
0.413
(1.00)
0.708
(1.00)
0.347
(1.00)
0.903
(1.00)
0.902
(1.00)
12q gain 50 (17%) 245 0.176
(1.00)
0.158
(1.00)
0.594
(1.00)
0.397
(1.00)
0.924
(1.00)
0.27
(1.00)
1
(1.00)
0.88
(1.00)
13q gain 24 (8%) 271 0.963
(1.00)
0.233
(1.00)
0.036
(1.00)
0.107
(1.00)
0.00596
(1.00)
0.0681
(1.00)
0.0995
(1.00)
0.108
(1.00)
14q gain 47 (16%) 248 0.047
(1.00)
0.296
(1.00)
0.26
(1.00)
0.448
(1.00)
0.284
(1.00)
0.149
(1.00)
0.496
(1.00)
0.988
(1.00)
15q gain 52 (18%) 243 0.109
(1.00)
0.644
(1.00)
0.931
(1.00)
0.514
(1.00)
0.733
(1.00)
0.764
(1.00)
0.604
(1.00)
0.218
(1.00)
16p gain 44 (15%) 251 0.00774
(1.00)
0.312
(1.00)
0.718
(1.00)
0.136
(1.00)
0.0973
(1.00)
0.099
(1.00)
0.881
(1.00)
0.58
(1.00)
16q gain 40 (14%) 255 0.456
(1.00)
0.0775
(1.00)
0.373
(1.00)
0.0468
(1.00)
0.0919
(1.00)
0.0871
(1.00)
0.477
(1.00)
0.467
(1.00)
17p gain 22 (7%) 273 0.00075
(0.451)
0.00049
(0.3)
0.593
(1.00)
0.398
(1.00)
0.247
(1.00)
0.65
(1.00)
0.078
(1.00)
0.504
(1.00)
17q gain 42 (14%) 253 0.0155
(1.00)
0.0961
(1.00)
0.426
(1.00)
0.193
(1.00)
0.158
(1.00)
0.809
(1.00)
0.266
(1.00)
0.787
(1.00)
18p gain 49 (17%) 246 0.0342
(1.00)
0.165
(1.00)
0.45
(1.00)
0.238
(1.00)
0.92
(1.00)
0.286
(1.00)
0.786
(1.00)
0.689
(1.00)
18q gain 32 (11%) 263 0.133
(1.00)
0.277
(1.00)
0.683
(1.00)
0.288
(1.00)
0.339
(1.00)
0.339
(1.00)
0.425
(1.00)
0.393
(1.00)
19p gain 44 (15%) 251 0.0166
(1.00)
0.169
(1.00)
0.541
(1.00)
0.839
(1.00)
0.936
(1.00)
0.193
(1.00)
0.635
(1.00)
0.593
(1.00)
20p gain 100 (34%) 195 0.00065
(0.393)
0.0312
(1.00)
0.273
(1.00)
0.0444
(1.00)
0.0501
(1.00)
0.102
(1.00)
0.661
(1.00)
0.593
(1.00)
20q gain 115 (39%) 180 0.00466
(1.00)
0.0996
(1.00)
0.265
(1.00)
0.0294
(1.00)
0.462
(1.00)
0.0331
(1.00)
0.807
(1.00)
0.345
(1.00)
21q gain 37 (13%) 258 0.355
(1.00)
0.704
(1.00)
0.164
(1.00)
0.518
(1.00)
0.754
(1.00)
0.756
(1.00)
0.922
(1.00)
0.602
(1.00)
22q gain 29 (10%) 266 0.148
(1.00)
0.489
(1.00)
0.751
(1.00)
0.209
(1.00)
0.778
(1.00)
0.332
(1.00)
0.147
(1.00)
0.961
(1.00)
xq gain 40 (14%) 255 0.0145
(1.00)
0.0439
(1.00)
0.136
(1.00)
0.189
(1.00)
0.228
(1.00)
0.17
(1.00)
0.313
(1.00)
0.149
(1.00)
1p loss 13 (4%) 282 0.0539
(1.00)
0.139
(1.00)
0.0111
(1.00)
0.0545
(1.00)
0.134
(1.00)
0.201
(1.00)
0.445
(1.00)
0.675
(1.00)
1q loss 9 (3%) 286 0.0205
(1.00)
0.33
(1.00)
0.0233
(1.00)
0.169
(1.00)
0.0916
(1.00)
0.441
(1.00)
0.475
(1.00)
0.742
(1.00)
2p loss 19 (6%) 276 0.653
(1.00)
0.829
(1.00)
0.193
(1.00)
0.257
(1.00)
0.524
(1.00)
0.214
(1.00)
0.511
(1.00)
0.347
(1.00)
2q loss 35 (12%) 260 0.801
(1.00)
0.36
(1.00)
0.052
(1.00)
0.0628
(1.00)
0.146
(1.00)
0.0216
(1.00)
0.862
(1.00)
0.205
(1.00)
3q loss 14 (5%) 281 0.3
(1.00)
0.247
(1.00)
0.227
(1.00)
0.562
(1.00)
0.0731
(1.00)
0.371
(1.00)
0.257
(1.00)
0.151
(1.00)
5p loss 19 (6%) 276 0.719
(1.00)
0.539
(1.00)
0.901
(1.00)
0.573
(1.00)
0.599
(1.00)
0.592
(1.00)
0.685
(1.00)
0.108
(1.00)
5q loss 51 (17%) 244 0.00182
(1.00)
0.513
(1.00)
0.485
(1.00)
0.77
(1.00)
0.0286
(1.00)
0.267
(1.00)
0.426
(1.00)
0.0456
(1.00)
6p loss 47 (16%) 248 0.15
(1.00)
0.0904
(1.00)
0.0456
(1.00)
0.117
(1.00)
0.445
(1.00)
0.123
(1.00)
0.897
(1.00)
0.123
(1.00)
6q loss 74 (25%) 221 0.00479
(1.00)
0.0472
(1.00)
0.105
(1.00)
0.201
(1.00)
0.207
(1.00)
0.0342
(1.00)
0.244
(1.00)
0.163
(1.00)
7p loss 26 (9%) 269 0.0465
(1.00)
0.34
(1.00)
0.027
(1.00)
0.0191
(1.00)
0.214
(1.00)
0.826
(1.00)
0.556
(1.00)
0.0542
(1.00)
7q loss 37 (13%) 258 0.0972
(1.00)
0.177
(1.00)
0.0402
(1.00)
0.196
(1.00)
0.145
(1.00)
0.254
(1.00)
0.57
(1.00)
0.572
(1.00)
9p loss 54 (18%) 241 0.00132
(0.775)
0.967
(1.00)
0.411
(1.00)
0.672
(1.00)
0.928
(1.00)
0.953
(1.00)
0.0512
(1.00)
0.796
(1.00)
10p loss 66 (22%) 229 0.00053
(0.322)
0.579
(1.00)
0.732
(1.00)
0.232
(1.00)
0.711
(1.00)
0.602
(1.00)
0.113
(1.00)
0.739
(1.00)
10q loss 74 (25%) 221 0.00068
(0.411)
0.8
(1.00)
0.781
(1.00)
0.162
(1.00)
0.76
(1.00)
0.137
(1.00)
0.243
(1.00)
0.554
(1.00)
11p loss 100 (34%) 195 0.00127
(0.748)
0.152
(1.00)
0.332
(1.00)
0.188
(1.00)
0.635
(1.00)
0.0613
(1.00)
0.947
(1.00)
0.221
(1.00)
12p loss 40 (14%) 255 0.0222
(1.00)
0.32
(1.00)
0.463
(1.00)
0.67
(1.00)
0.27
(1.00)
0.803
(1.00)
0.308
(1.00)
0.207
(1.00)
12q loss 15 (5%) 280 0.361
(1.00)
0.498
(1.00)
1
(1.00)
0.455
(1.00)
0.196
(1.00)
0.536
(1.00)
0.238
(1.00)
0.91
(1.00)
13q loss 80 (27%) 215 0.00074
(0.446)
0.202
(1.00)
0.0154
(1.00)
0.00978
(1.00)
0.102
(1.00)
0.00318
(1.00)
0.636
(1.00)
0.107
(1.00)
14q loss 35 (12%) 260 0.00103
(0.611)
0.358
(1.00)
0.0335
(1.00)
0.0861
(1.00)
0.851
(1.00)
0.0991
(1.00)
0.0154
(1.00)
0.625
(1.00)
15q loss 47 (16%) 248 0.0584
(1.00)
0.414
(1.00)
0.48
(1.00)
0.336
(1.00)
0.294
(1.00)
0.511
(1.00)
0.263
(1.00)
0.693
(1.00)
16p loss 34 (12%) 261 0.103
(1.00)
0.0818
(1.00)
0.162
(1.00)
0.224
(1.00)
0.412
(1.00)
0.0104
(1.00)
0.0539
(1.00)
0.202
(1.00)
16q loss 44 (15%) 251 0.142
(1.00)
0.0151
(1.00)
0.00607
(1.00)
0.0473
(1.00)
0.00949
(1.00)
0.00117
(0.693)
0.0899
(1.00)
0.0137
(1.00)
17p loss 95 (32%) 200 0.00133
(0.779)
0.191
(1.00)
0.104
(1.00)
0.0426
(1.00)
0.137
(1.00)
0.056
(1.00)
0.541
(1.00)
0.292
(1.00)
17q loss 37 (13%) 258 0.173
(1.00)
0.456
(1.00)
0.152
(1.00)
0.0786
(1.00)
0.0484
(1.00)
0.332
(1.00)
0.568
(1.00)
0.19
(1.00)
18p loss 55 (19%) 240 0.392
(1.00)
0.0376
(1.00)
0.00063
(0.382)
0.0109
(1.00)
0.42
(1.00)
0.0346
(1.00)
0.303
(1.00)
0.151
(1.00)
19q loss 29 (10%) 266 0.22
(1.00)
0.0533
(1.00)
0.559
(1.00)
0.42
(1.00)
0.271
(1.00)
0.107
(1.00)
0.2
(1.00)
0.0253
(1.00)
20p loss 23 (8%) 272 0.791
(1.00)
0.0549
(1.00)
0.0555
(1.00)
0.224
(1.00)
0.116
(1.00)
0.148
(1.00)
0.135
(1.00)
0.366
(1.00)
20q loss 10 (3%) 285 0.509
(1.00)
0.0183
(1.00)
0.235
(1.00)
0.0461
(1.00)
1
(1.00)
0.65
(1.00)
1
(1.00)
0.516
(1.00)
22q loss 71 (24%) 224 0.00242
(1.00)
0.196
(1.00)
0.023
(1.00)
0.00078
(0.469)
0.912
(1.00)
0.211
(1.00)
0.627
(1.00)
0.794
(1.00)
xq loss 58 (20%) 237 0.0303
(1.00)
0.0638
(1.00)
0.15
(1.00)
0.179
(1.00)
0.204
(1.00)
0.941
(1.00)
0.0461
(1.00)
0.471
(1.00)
'1p gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 6e-05 (Fisher's exact test), Q value = 0.038

Table S1.  Gene #1: '1p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 60 95 72 25 43
1P GAIN MUTATED 9 31 35 9 6
1P GAIN WILD-TYPE 51 64 37 16 37

Figure S1.  Get High-res Image Gene #1: '1p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'1q gain' versus 'CN_CNMF'

P value = 0.00016 (Fisher's exact test), Q value = 0.1

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
1Q GAIN MUTATED 46 34 60
1Q GAIN WILD-TYPE 83 39 33

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

'2p gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0064

Table S3.  Gene #3: '2p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
2P GAIN MUTATED 14 32 18
2P GAIN WILD-TYPE 115 41 75

Figure S3.  Get High-res Image Gene #3: '2p gain' versus Molecular Subtype #1: 'CN_CNMF'

'2q gain' versus 'CN_CNMF'

P value = 0.00016 (Fisher's exact test), Q value = 0.1

Table S4.  Gene #4: '2q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
2Q GAIN MUTATED 8 20 9
2Q GAIN WILD-TYPE 121 53 84

Figure S4.  Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #1: 'CN_CNMF'

'3q gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0064

Table S5.  Gene #6: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
3Q GAIN MUTATED 61 40 74
3Q GAIN WILD-TYPE 68 33 19

Figure S5.  Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

'3q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00028 (Fisher's exact test), Q value = 0.17

Table S6.  Gene #6: '3q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 60 95 72 25 43
3Q GAIN MUTATED 23 59 55 16 22
3Q GAIN WILD-TYPE 37 36 17 9 21

Figure S6.  Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'3q gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.00023 (Fisher's exact test), Q value = 0.14

Table S7.  Gene #6: '3q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 64 50 26 142
3Q GAIN MUTATED 26 36 22 83
3Q GAIN WILD-TYPE 38 14 4 59

Figure S7.  Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'5p gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0064

Table S8.  Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
5P GAIN MUTATED 31 48 34
5P GAIN WILD-TYPE 98 25 59

Figure S8.  Get High-res Image Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

'8q gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.00013 (Fisher's exact test), Q value = 0.081

Table S9.  Gene #16: '8q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 64 50 26 142
8Q GAIN MUTATED 7 15 7 57
8Q GAIN WILD-TYPE 57 35 19 85

Figure S9.  Get High-res Image Gene #16: '8q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'19q gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0064

Table S10.  Gene #35: '19q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
19Q GAIN MUTATED 16 38 18
19Q GAIN WILD-TYPE 113 35 75

Figure S10.  Get High-res Image Gene #35: '19q gain' versus Molecular Subtype #1: 'CN_CNMF'

'3p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3e-05 (Fisher's exact test), Q value = 0.019

Table S11.  Gene #45: '3p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 56 154 33
3P LOSS MUTATED 5 59 6
3P LOSS WILD-TYPE 51 95 27

Figure S11.  Get High-res Image Gene #45: '3p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'4p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0064

Table S12.  Gene #47: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
4P LOSS MUTATED 32 48 51
4P LOSS WILD-TYPE 97 25 42

Figure S12.  Get High-res Image Gene #47: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

'4p loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.00029 (Fisher's exact test), Q value = 0.18

Table S13.  Gene #47: '4p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 64 50 26 142
4P LOSS MUTATED 15 26 17 66
4P LOSS WILD-TYPE 49 24 9 76

Figure S13.  Get High-res Image Gene #47: '4p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'4q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0064

Table S14.  Gene #48: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
4Q LOSS MUTATED 16 45 32
4Q LOSS WILD-TYPE 113 28 61

Figure S14.  Get High-res Image Gene #48: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

'8p loss' versus 'CN_CNMF'

P value = 7e-05 (Fisher's exact test), Q value = 0.044

Table S15.  Gene #55: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
8P LOSS MUTATED 23 34 25
8P LOSS WILD-TYPE 106 39 68

Figure S15.  Get High-res Image Gene #55: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

'8q loss' versus 'MRNASEQ_CNMF'

P value = 5e-05 (Fisher's exact test), Q value = 0.031

Table S16.  Gene #56: '8q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 77 101 65
8Q LOSS MUTATED 12 0 8
8Q LOSS WILD-TYPE 65 101 57

Figure S16.  Get High-res Image Gene #56: '8q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'8q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00034 (Fisher's exact test), Q value = 0.21

Table S17.  Gene #56: '8q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 56 154 33
8Q LOSS MUTATED 11 5 4
8Q LOSS WILD-TYPE 45 149 29

Figure S17.  Get High-res Image Gene #56: '8q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'8q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00027 (Fisher's exact test), Q value = 0.17

Table S18.  Gene #56: '8q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 60 95 72 25 43
8Q LOSS MUTATED 12 3 1 2 6
8Q LOSS WILD-TYPE 48 92 71 23 37

Figure S18.  Get High-res Image Gene #56: '8q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'9q loss' versus 'CN_CNMF'

P value = 0.00015 (Fisher's exact test), Q value = 0.094

Table S19.  Gene #58: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
9Q LOSS MUTATED 11 23 17
9Q LOSS WILD-TYPE 118 50 76

Figure S19.  Get High-res Image Gene #58: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

'11q loss' versus 'CN_CNMF'

P value = 2e-05 (Fisher's exact test), Q value = 0.013

Table S20.  Gene #62: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
11Q LOSS MUTATED 33 28 54
11Q LOSS WILD-TYPE 96 45 39

Figure S20.  Get High-res Image Gene #62: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

'18q loss' versus 'MRNASEQ_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0064

Table S21.  Gene #73: '18q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 77 101 65
18Q LOSS MUTATED 26 9 25
18Q LOSS WILD-TYPE 51 92 40

Figure S21.  Get High-res Image Gene #73: '18q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'18q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 4e-04 (Fisher's exact test), Q value = 0.25

Table S22.  Gene #73: '18q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 56 154 33
18Q LOSS MUTATED 23 25 12
18Q LOSS WILD-TYPE 33 129 21

Figure S22.  Get High-res Image Gene #73: '18q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'18q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00019 (Fisher's exact test), Q value = 0.12

Table S23.  Gene #73: '18q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 60 95 72 25 43
18Q LOSS MUTATED 25 15 11 5 17
18Q LOSS WILD-TYPE 35 80 61 20 26

Figure S23.  Get High-res Image Gene #73: '18q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'19p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0064

Table S24.  Gene #74: '19p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
19P LOSS MUTATED 14 31 15
19P LOSS WILD-TYPE 115 42 78

Figure S24.  Get High-res Image Gene #74: '19p loss' versus Molecular Subtype #1: 'CN_CNMF'

'19p loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00016 (Fisher's exact test), Q value = 0.1

Table S25.  Gene #74: '19p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 60 95 72 25 43
19P LOSS MUTATED 13 15 6 12 14
19P LOSS WILD-TYPE 47 80 66 13 29

Figure S25.  Get High-res Image Gene #74: '19p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'21q loss' versus 'CN_CNMF'

P value = 2e-05 (Fisher's exact test), Q value = 0.013

Table S26.  Gene #78: '21q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 73 93
21Q LOSS MUTATED 9 24 16
21Q LOSS WILD-TYPE 120 49 77

Figure S26.  Get High-res Image Gene #78: '21q loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data
Input
  • Copy number data file = transformed.cor.cli.txt

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

  • Number of patients = 295

  • Number of significantly arm-level cnvs = 80

  • Number of molecular subtypes = 8

  • 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)