Correlation between copy number variations of arm-level result and molecular subtypes
Prostate Adenocarcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
doi:10.7908/C1416VH0
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/C1416VH0
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 67 arm-level events and 10 molecular subtypes across 278 patients, 35 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 3q gain cnv correlated to 'CN_CNMF'.

  • 7p gain cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.

  • 7q gain cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.

  • 8p gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 8q gain cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 9q gain cnv correlated to 'CN_CNMF'.

  • 18p gain cnv correlated to 'CN_CNMF'.

  • 5q loss cnv correlated to 'CN_CNMF'.

  • 6p loss cnv correlated to 'CN_CNMF'.

  • 6q loss cnv correlated to 'CN_CNMF'.

  • 8p loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 8q loss cnv correlated to 'CN_CNMF'.

  • 9p loss cnv correlated to 'CN_CNMF'.

  • 10p loss cnv correlated to 'CN_CNMF'.

  • 10q loss cnv correlated to 'CN_CNMF'.

  • 12q loss cnv correlated to 'CN_CNMF'.

  • 13q loss cnv correlated to 'CN_CNMF'.

  • 15q loss cnv correlated to 'CN_CNMF'.

  • 16q loss cnv correlated to 'CN_CNMF'.

  • 17p loss cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 18p loss cnv correlated to 'CN_CNMF'.

  • 18q loss cnv correlated to 'CN_CNMF'.

  • 22q loss cnv correlated to 'CN_CNMF'.

  • xq 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 67 arm-level events and 10 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 35 significant findings detected.

Clinical
Features 		CN
CNMF 		METHLYATION
CNMF 		RPPA
CNMF 		RPPA
CHIERARCHICAL 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL 		MIRSEQ
MATURE
CNMF 		MIRSEQ
MATURE
CHIERARCHICAL
nCNV (%) nWild-Type Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test Fisher's exact test Fisher's exact test
8p loss 85 (31%) 193 2.91e-06
(0.00181) 		1.19e-08
(7.55e-06) 		0.543
(1.00) 		0.904
(1.00) 		9.34e-07
(0.000585) 		6.93e-05
(0.0423) 		0.000554
(0.333) 		0.776
(1.00) 		0.428
(1.00) 		0.572
(1.00)
7p gain 46 (17%) 232 5.53e-07
(0.000348) 		1.05e-06
(0.000657) 		0.413
(1.00) 		0.561
(1.00) 		6.61e-05
(0.0405) 		0.0219
(1.00) 		0.418
(1.00) 		0.962
(1.00) 		0.73
(1.00) 		0.902
(1.00)
7q gain 43 (15%) 235 4.36e-06
(0.0027) 		1.73e-06
(0.00108) 		0.586
(1.00) 		0.551
(1.00) 		8.81e-05
(0.0537) 		0.0572
(1.00) 		0.415
(1.00) 		0.829
(1.00) 		0.728
(1.00) 		0.87
(1.00)
8q gain 59 (21%) 219 1.91e-15
(1.22e-12) 		2.05e-05
(0.0127) 		0.0013
(0.77) 		0.00492
(1.00) 		0.0101
(1.00) 		2.38e-05
(0.0146) 		0.0225
(1.00) 		0.0258
(1.00) 		0.0998
(1.00) 		0.244
(1.00)
8p gain 34 (12%) 244 8.95e-14
(5.69e-11) 		2.41e-07
(0.000152) 		0.00511
(1.00) 		0.0193
(1.00) 		0.00868
(1.00) 		0.000657
(0.393) 		0.316
(1.00) 		0.379
(1.00) 		0.331
(1.00) 		0.69
(1.00)
17p loss 38 (14%) 240 7.39e-14
(4.71e-11) 		0.00208
(1.00) 		0.00344
(1.00) 		0.0141
(1.00) 		0.00195
(1.00) 		3e-05
(0.0184) 		0.691
(1.00) 		0.832
(1.00) 		0.689
(1.00) 		0.616
(1.00)
3q gain 25 (9%) 253 7.25e-06
(0.00449) 		0.106
(1.00) 		0.0396
(1.00) 		0.248
(1.00) 		0.251
(1.00) 		0.0163
(1.00) 		0.587
(1.00) 		0.804
(1.00) 		0.774
(1.00) 		0.433
(1.00)
9q gain 20 (7%) 258 9.22e-07
(0.000579) 		0.378
(1.00) 		0.0281
(1.00) 		0.0112
(1.00) 		0.869
(1.00) 		0.158
(1.00) 		0.387
(1.00) 		0.0712
(1.00) 		0.387
(1.00) 		0.482
(1.00)
18p gain 9 (3%) 269 0.000249
(0.15) 		0.693
(1.00) 		1
(1.00) 		0.564
(1.00) 		0.389
(1.00) 		0.403
(1.00) 		0.617
(1.00) 		0.627
(1.00) 		1
(1.00) 		1
(1.00)
5q loss 8 (3%) 270 0.000137
(0.083) 		0.319
(1.00) 		0.255
(1.00) 		0.155
(1.00) 		0.299
(1.00) 		0.103
(1.00) 		0.726
(1.00) 		0.365
(1.00) 		1
(1.00) 		0.715
(1.00)
6p loss 9 (3%) 269 3.18e-05
(0.0195) 		0.00342
(1.00) 		0.255
(1.00) 		0.155
(1.00) 		0.00455
(1.00) 		0.00206
(1.00) 		0.565
(1.00) 		0.832
(1.00) 		0.914
(1.00) 		0.916
(1.00)
6q loss 16 (6%) 262 2.01e-06
(0.00125) 		0.0019
(1.00) 		0.0761
(1.00) 		0.502
(1.00) 		0.00903
(1.00) 		0.00435
(1.00) 		0.499
(1.00) 		0.687
(1.00) 		0.729
(1.00) 		0.875
(1.00)
8q loss 11 (4%) 267 4.27e-06
(0.00265) 		0.245
(1.00) 		0.73
(1.00) 		1
(1.00) 		0.0515
(1.00) 		0.00262
(1.00) 		0.202
(1.00) 		0.254
(1.00) 		0.228
(1.00) 		0.0865
(1.00)
9p loss 12 (4%) 266 0.000373
(0.225) 		0.812
(1.00) 		0.0855
(1.00) 		0.348
(1.00) 		0.163
(1.00) 		0.296
(1.00) 		0.246
(1.00) 		0.125
(1.00) 		0.246
(1.00) 		0.251
(1.00)
10p loss 18 (6%) 260 8.67e-06
(0.00536) 		0.000966
(0.577) 		0.00682
(1.00) 		0.031
(1.00) 		0.00677
(1.00) 		0.0156
(1.00) 		0.342
(1.00) 		0.554
(1.00) 		0.18
(1.00) 		0.47
(1.00)
10q loss 22 (8%) 256 3.98e-07
(0.000251) 		0.0255
(1.00) 		0.0392
(1.00) 		0.0498
(1.00) 		0.137
(1.00) 		0.0657
(1.00) 		0.445
(1.00) 		0.517
(1.00) 		0.159
(1.00) 		0.205
(1.00)
12q loss 11 (4%) 267 0.000126
(0.0765) 		0.466
(1.00) 		0.297
(1.00) 		0.495
(1.00) 		0.292
(1.00) 		0.312
(1.00) 		0.518
(1.00) 		0.347
(1.00) 		0.637
(1.00) 		0.695
(1.00)
13q loss 39 (14%) 239 1.13e-07
(7.17e-05) 		0.318
(1.00) 		0.543
(1.00) 		0.545
(1.00) 		0.916
(1.00) 		0.37
(1.00) 		0.815
(1.00) 		0.911
(1.00) 		0.776
(1.00) 		0.791
(1.00)
15q loss 16 (6%) 262 7.16e-05
(0.0437) 		0.0352
(1.00) 		0.0413
(1.00) 		0.0879
(1.00) 		0.221
(1.00) 		0.0614
(1.00) 		0.181
(1.00) 		0.746
(1.00) 		0.192
(1.00) 		0.47
(1.00)
16q loss 53 (19%) 225 1.27e-10
(8.09e-08) 		0.00449
(1.00) 		0.492
(1.00) 		0.299
(1.00) 		0.0546
(1.00) 		0.0157
(1.00) 		0.615
(1.00) 		1
(1.00) 		0.172
(1.00) 		0.397
(1.00)
18p loss 34 (12%) 244 1.58e-06
(0.000987) 		0.0286
(1.00) 		0.0633
(1.00) 		0.0794
(1.00) 		0.0554
(1.00) 		0.0215
(1.00) 		0.365
(1.00) 		0.491
(1.00) 		0.199
(1.00) 		0.265
(1.00)
18q loss 50 (18%) 228 6.03e-09
(3.82e-06) 		0.031
(1.00) 		0.016
(1.00) 		0.0188
(1.00) 		0.0122
(1.00) 		0.014
(1.00) 		0.646
(1.00) 		0.742
(1.00) 		0.68
(1.00) 		0.769
(1.00)
22q loss 19 (7%) 259 0.000193
(0.117) 		0.203
(1.00) 		0.442
(1.00) 		0.805
(1.00) 		0.293
(1.00) 		0.0959
(1.00) 		0.788
(1.00) 		0.639
(1.00) 		0.534
(1.00) 		0.643
(1.00)
xq loss 18 (6%) 260 6.29e-05
(0.0385) 		0.00143
(0.842) 		0.193
(1.00) 		0.235
(1.00) 		0.004
(1.00) 		0.0263
(1.00) 		0.278
(1.00) 		0.281
(1.00) 		0.14
(1.00) 		0.181
(1.00)
1p gain 7 (3%) 271 0.0351
(1.00) 		0.0921
(1.00) 		0.0411
(1.00) 		0.495
(1.00) 		0.595
(1.00) 		0.14
(1.00) 		0.754
(1.00) 		1
(1.00) 		0.797
(1.00) 		0.89
(1.00)
1q gain 11 (4%) 267 0.0128
(1.00) 		0.0255
(1.00) 		0.0223
(1.00) 		0.224
(1.00) 		0.25
(1.00) 		0.0628
(1.00) 		0.72
(1.00) 		0.922
(1.00) 		1
(1.00) 		0.853
(1.00)
2p gain 4 (1%) 274 0.498
(1.00) 		0.105
(1.00) 		0.233
(1.00) 		0.176
(1.00) 		0.265
(1.00) 		0.696
(1.00) 		0.112
(1.00) 		0.691
(1.00)
2q gain 3 (1%) 275 0.154
(1.00) 		0.289
(1.00) 		0.559
(1.00) 		0.346
(1.00) 		0.0836
(1.00) 		0.103
(1.00) 		0.0265
(1.00) 		0.198
(1.00)
3p gain 19 (7%) 259 0.00131
(0.778) 		0.0692
(1.00) 		0.0561
(1.00) 		0.46
(1.00) 		0.654
(1.00) 		0.0591
(1.00) 		0.393
(1.00) 		1
(1.00) 		0.732
(1.00) 		0.389
(1.00)
4p gain 4 (1%) 274 0.498
(1.00) 		0.391
(1.00) 		0.843
(1.00) 		0.751
(1.00) 		0.628
(1.00) 		0.484
(1.00) 		0.554
(1.00) 		0.39
(1.00)
4q gain 3 (1%) 275 0.749
(1.00) 		0.509
(1.00) 		1
(1.00) 		1
(1.00) 		0.632
(1.00) 		0.461
(1.00) 		0.644
(1.00) 		0.779
(1.00)
5p gain 6 (2%) 272 0.00139
(0.822) 		0.164
(1.00) 		0.298
(1.00) 		0.387
(1.00) 		0.637
(1.00) 		0.803
(1.00) 		0.295
(1.00) 		0.0761
(1.00) 		0.165
(1.00) 		0.129
(1.00)
5q gain 3 (1%) 275 0.0598
(1.00) 		0.113
(1.00) 		0.494
(1.00) 		0.776
(1.00)
9p gain 10 (4%) 268 0.000481
(0.289) 		0.662
(1.00) 		0.484
(1.00) 		0.2
(1.00) 		0.97
(1.00) 		0.656
(1.00) 		0.774
(1.00) 		0.244
(1.00) 		0.562
(1.00) 		0.173
(1.00)
10p gain 7 (3%) 271 0.00305
(1.00) 		0.302
(1.00) 		0.784
(1.00) 		0.635
(1.00) 		1
(1.00) 		0.0945
(1.00) 		0.0339
(1.00) 		0.0343
(1.00) 		0.0526
(1.00) 		0.0804
(1.00)
10q gain 8 (3%) 270 0.000994
(0.593) 		0.319
(1.00) 		0.0403
(1.00) 		0.0376
(1.00) 		0.963
(1.00) 		0.0733
(1.00) 		0.273
(1.00) 		0.266
(1.00) 		0.125
(1.00) 		0.639
(1.00)
11p gain 9 (3%) 269 0.0017
(1.00) 		0.295
(1.00) 		0.768
(1.00) 		0.585
(1.00) 		0.236
(1.00) 		0.267
(1.00) 		0.943
(1.00) 		1
(1.00) 		1
(1.00) 		0.819
(1.00)
11q gain 9 (3%) 269 0.0017
(1.00) 		0.295
(1.00) 		0.768
(1.00) 		0.585
(1.00) 		0.236
(1.00) 		0.267
(1.00) 		0.943
(1.00) 		1
(1.00) 		1
(1.00) 		0.819
(1.00)
12q gain 5 (2%) 273 0.252
(1.00) 		0.103
(1.00) 		0.848
(1.00) 		0.863
(1.00) 		0.443
(1.00) 		0.178
(1.00) 		0.909
(1.00) 		0.177
(1.00) 		1
(1.00) 		0.279
(1.00)
14q gain 5 (2%) 273 0.0178
(1.00) 		0.0364
(1.00) 		0.784
(1.00) 		0.635
(1.00) 		0.07
(1.00) 		0.0562
(1.00) 		0.0329
(1.00) 		0.226
(1.00) 		0.0253
(1.00) 		0.1
(1.00)
15q gain 3 (1%) 275 0.582
(1.00) 		1
(1.00) 		0.79
(1.00) 		1
(1.00) 		0.136
(1.00) 		0.256
(1.00) 		0.777
(1.00) 		0.779
(1.00)
16p gain 14 (5%) 264 0.000464
(0.279) 		0.254
(1.00) 		0.521
(1.00) 		0.39
(1.00) 		0.694
(1.00) 		0.148
(1.00) 		0.247
(1.00) 		0.606
(1.00) 		0.278
(1.00) 		0.343
(1.00)
16q gain 5 (2%) 273 0.0777
(1.00) 		0.86
(1.00) 		0.677
(1.00) 		0.466
(1.00) 		0.47
(1.00) 		0.573
(1.00) 		0.83
(1.00) 		0.863
(1.00) 		1
(1.00) 		1
(1.00)
17q gain 4 (1%) 274 0.0152
(1.00) 		0.833
(1.00) 		0.471
(1.00) 		0.635
(1.00) 		0.672
(1.00) 		0.751
(1.00) 		0.894
(1.00) 		0.814
(1.00) 		0.838
(1.00) 		0.83
(1.00)
18q gain 4 (1%) 274 0.0152
(1.00) 		0.833
(1.00) 		1
(1.00) 		0.385
(1.00) 		0.843
(1.00) 		0.35
(1.00) 		0.57
(1.00) 		0.696
(1.00) 		0.688
(1.00) 		0.691
(1.00)
19p gain 3 (1%) 275 0.0598
(1.00) 		0.509
(1.00) 		0.628
(1.00) 		0.152
(1.00)
19q gain 4 (1%) 274 0.0152
(1.00) 		0.391
(1.00) 		0.784
(1.00) 		0.635
(1.00) 		0.45
(1.00) 		0.0376
(1.00)
20p gain 6 (2%) 272 0.0981
(1.00) 		0.0662
(1.00) 		0.371
(1.00) 		0.145
(1.00) 		0.0979
(1.00) 		0.0798
(1.00) 		0.364
(1.00) 		0.131
(1.00) 		0.234
(1.00) 		0.233
(1.00)
20q gain 8 (3%) 270 0.0151
(1.00) 		0.143
(1.00) 		0.621
(1.00) 		0.798
(1.00) 		0.38
(1.00) 		0.409
(1.00) 		0.827
(1.00) 		0.598
(1.00) 		0.905
(1.00) 		0.907
(1.00)
21q gain 6 (2%) 272 0.00139
(0.822) 		0.164
(1.00) 		0.445
(1.00) 		0.326
(1.00) 		0.2
(1.00) 		0.356
(1.00) 		0.433
(1.00) 		0.453
(1.00) 		0.278
(1.00) 		0.329
(1.00)
1p loss 8 (3%) 270 0.0151
(1.00) 		0.087
(1.00) 		0.255
(1.00) 		0.155
(1.00) 		0.0564
(1.00) 		0.0287
(1.00) 		0.275
(1.00) 		0.294
(1.00) 		0.142
(1.00) 		0.165
(1.00)
2p loss 3 (1%) 275 0.0598
(1.00) 		0.113
(1.00) 		0.494
(1.00) 		0.152
(1.00) 		0.639
(1.00) 		0.622
(1.00) 		0.521
(1.00) 		0.64
(1.00)
2q loss 4 (1%) 274 0.0152
(1.00) 		0.463
(1.00) 		0.619
(1.00) 		0.384
(1.00) 		0.638
(1.00) 		0.387
(1.00) 		0.268
(1.00) 		0.319
(1.00)
3p loss 4 (1%) 274 0.226
(1.00) 		0.321
(1.00) 		0.283
(1.00) 		0.254
(1.00) 		0.258
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
4p loss 9 (3%) 269 0.0189
(1.00) 		0.326
(1.00) 		0.298
(1.00) 		1
(1.00) 		0.0393
(1.00) 		0.133
(1.00) 		0.0382
(1.00) 		0.00281
(1.00) 		0.0756
(1.00) 		0.0493
(1.00)
4q loss 6 (2%) 272 0.0981
(1.00) 		0.518
(1.00) 		0.784
(1.00) 		0.385
(1.00) 		0.0979
(1.00) 		0.295
(1.00) 		0.267
(1.00) 		0.0968
(1.00) 		0.0818
(1.00) 		0.115
(1.00)
5p loss 4 (1%) 274 0.0152
(1.00) 		0.391
(1.00) 		0.784
(1.00) 		1
(1.00) 		0.45
(1.00) 		0.0376
(1.00) 		0.96
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
9q loss 5 (2%) 273 0.0178
(1.00) 		0.447
(1.00) 		0.445
(1.00) 		0.863
(1.00) 		0.648
(1.00) 		0.759
(1.00) 		0.403
(1.00) 		0.453
(1.00) 		0.863
(1.00) 		0.865
(1.00)
12p loss 26 (9%) 252 0.000453
(0.273) 		0.0901
(1.00) 		0.186
(1.00) 		0.647
(1.00) 		0.0954
(1.00) 		0.102
(1.00) 		0.864
(1.00) 		0.189
(1.00) 		0.317
(1.00) 		0.784
(1.00)
14q loss 10 (4%) 268 0.0958
(1.00) 		0.212
(1.00) 		0.464
(1.00) 		0.348
(1.00) 		0.474
(1.00) 		0.457
(1.00) 		0.00123
(0.731) 		0.0105
(1.00) 		0.000695
(0.416) 		0.0017
(1.00)
16p loss 16 (6%) 262 0.00887
(1.00) 		0.188
(1.00) 		0.599
(1.00) 		0.599
(1.00) 		0.344
(1.00) 		0.365
(1.00) 		0.388
(1.00) 		0.629
(1.00) 		0.364
(1.00) 		0.561
(1.00)
17q loss 7 (3%) 271 0.00305
(1.00) 		0.0198
(1.00) 		0.452
(1.00) 		0.314
(1.00) 		0.0109
(1.00) 		0.0987
(1.00) 		0.74
(1.00) 		0.882
(1.00) 		0.142
(1.00) 		0.165
(1.00)
19p loss 9 (3%) 269 0.0189
(1.00) 		0.763
(1.00) 		0.677
(1.00) 		1
(1.00) 		0.67
(1.00) 		0.964
(1.00) 		0.459
(1.00) 		0.339
(1.00) 		0.397
(1.00) 		0.357
(1.00)
19q loss 9 (3%) 269 0.0189
(1.00) 		0.763
(1.00) 		0.677
(1.00) 		1
(1.00) 		0.67
(1.00) 		0.964
(1.00) 		0.459
(1.00) 		0.339
(1.00) 		0.397
(1.00) 		0.357
(1.00)
20p loss 10 (4%) 268 0.463
(1.00) 		0.0353
(1.00) 		0.896
(1.00) 		1
(1.00) 		0.832
(1.00) 		0.477
(1.00) 		0.725
(1.00) 		0.204
(1.00) 		0.914
(1.00) 		0.479
(1.00)
20q loss 6 (2%) 272 0.0981
(1.00) 		0.0662
(1.00) 		1
(1.00) 		0.863
(1.00) 		0.669
(1.00) 		0.163
(1.00) 		0.638
(1.00) 		0.662
(1.00) 		0.597
(1.00) 		0.29
(1.00)
21q loss 9 (3%) 269 0.0723
(1.00) 		0.295
(1.00) 		0.505
(1.00) 		0.445
(1.00) 		0.528
(1.00) 		0.185
(1.00) 		0.581
(1.00) 		0.423
(1.00) 		0.545
(1.00) 		0.819
(1.00)
'3q gain' versus 'CN_CNMF'

P value = 7.25e-06 (Fisher's exact test), Q value = 0.0045

Table S1.  Gene #6: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
3Q GAIN MUTATED 4 3 18
3Q GAIN WILD-TYPE 44 142 67

Figure S1.  Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

'7p gain' versus 'CN_CNMF'

P value = 5.53e-07 (Fisher's exact test), Q value = 0.00035

Table S2.  Gene #11: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
7P GAIN MUTATED 14 8 24
7P GAIN WILD-TYPE 34 137 61

Figure S2.  Get High-res Image Gene #11: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

'7p gain' versus 'METHLYATION_CNMF'

P value = 1.05e-06 (Fisher's exact test), Q value = 0.00066

Table S3.  Gene #11: '7p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 80 93 105
7P GAIN MUTATED 27 4 15
7P GAIN WILD-TYPE 53 89 90

Figure S3.  Get High-res Image Gene #11: '7p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'7p gain' versus 'MRNASEQ_CNMF'

P value = 6.61e-05 (Fisher's exact test), Q value = 0.04

Table S4.  Gene #11: '7p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 76 65 80 56
7P GAIN MUTATED 25 9 10 2
7P GAIN WILD-TYPE 51 56 70 54

Figure S4.  Get High-res Image Gene #11: '7p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'7q gain' versus 'CN_CNMF'

P value = 4.36e-06 (Fisher's exact test), Q value = 0.0027

Table S5.  Gene #12: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
7Q GAIN MUTATED 13 8 22
7Q GAIN WILD-TYPE 35 137 63

Figure S5.  Get High-res Image Gene #12: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

'7q gain' versus 'METHLYATION_CNMF'

P value = 1.73e-06 (Fisher's exact test), Q value = 0.0011

Table S6.  Gene #12: '7q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 80 93 105
7Q GAIN MUTATED 26 4 13
7Q GAIN WILD-TYPE 54 89 92

Figure S6.  Get High-res Image Gene #12: '7q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'7q gain' versus 'MRNASEQ_CNMF'

P value = 8.81e-05 (Fisher's exact test), Q value = 0.054

Table S7.  Gene #12: '7q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 76 65 80 56
7Q GAIN MUTATED 24 8 9 2
7Q GAIN WILD-TYPE 52 57 71 54

Figure S7.  Get High-res Image Gene #12: '7q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'8p gain' versus 'CN_CNMF'

P value = 8.95e-14 (Fisher's exact test), Q value = 5.7e-11

Table S8.  Gene #13: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
8P GAIN MUTATED 6 0 28
8P GAIN WILD-TYPE 42 145 57

Figure S8.  Get High-res Image Gene #13: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

'8p gain' versus 'METHLYATION_CNMF'

P value = 2.41e-07 (Fisher's exact test), Q value = 0.00015

Table S9.  Gene #13: '8p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 80 93 105
8P GAIN MUTATED 24 3 7
8P GAIN WILD-TYPE 56 90 98

Figure S9.  Get High-res Image Gene #13: '8p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'8q gain' versus 'CN_CNMF'

P value = 1.91e-15 (Fisher's exact test), Q value = 1.2e-12

Table S10.  Gene #14: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
8Q GAIN MUTATED 7 8 44
8Q GAIN WILD-TYPE 41 137 41

Figure S10.  Get High-res Image Gene #14: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

'8q gain' versus 'METHLYATION_CNMF'

P value = 2.05e-05 (Fisher's exact test), Q value = 0.013

Table S11.  Gene #14: '8q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 80 93 105
8Q GAIN MUTATED 30 8 21
8Q GAIN WILD-TYPE 50 85 84

Figure S11.  Get High-res Image Gene #14: '8q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'8q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.38e-05 (Fisher's exact test), Q value = 0.015

Table S12.  Gene #14: '8q gain' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 81 86 70 40
8Q GAIN MUTATED 4 22 24 9
8Q GAIN WILD-TYPE 77 64 46 31

Figure S12.  Get High-res Image Gene #14: '8q gain' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'9q gain' versus 'CN_CNMF'

P value = 9.22e-07 (Fisher's exact test), Q value = 0.00058

Table S13.  Gene #16: '9q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
9Q GAIN MUTATED 0 3 17
9Q GAIN WILD-TYPE 48 142 68

Figure S13.  Get High-res Image Gene #16: '9q gain' versus Molecular Subtype #1: 'CN_CNMF'

'18p gain' versus 'CN_CNMF'

P value = 0.000249 (Fisher's exact test), Q value = 0.15

Table S14.  Gene #27: '18p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
18P GAIN MUTATED 1 0 8
18P GAIN WILD-TYPE 47 145 77

Figure S14.  Get High-res Image Gene #27: '18p gain' versus Molecular Subtype #1: 'CN_CNMF'

'5q loss' versus 'CN_CNMF'

P value = 0.000137 (Fisher's exact test), Q value = 0.083

Table S15.  Gene #41: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
5Q LOSS MUTATED 0 0 8
5Q LOSS WILD-TYPE 48 145 77

Figure S15.  Get High-res Image Gene #41: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

'6p loss' versus 'CN_CNMF'

P value = 3.18e-05 (Fisher's exact test), Q value = 0.02

Table S16.  Gene #42: '6p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
6P LOSS MUTATED 0 0 9
6P LOSS WILD-TYPE 48 145 76

Figure S16.  Get High-res Image Gene #42: '6p loss' versus Molecular Subtype #1: 'CN_CNMF'

'6q loss' versus 'CN_CNMF'

P value = 2.01e-06 (Fisher's exact test), Q value = 0.0013

Table S17.  Gene #43: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
6Q LOSS MUTATED 3 0 13
6Q LOSS WILD-TYPE 45 145 72

Figure S17.  Get High-res Image Gene #43: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'8p loss' versus 'CN_CNMF'

P value = 2.91e-06 (Fisher's exact test), Q value = 0.0018

Table S18.  Gene #44: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
8P LOSS MUTATED 4 40 41
8P LOSS WILD-TYPE 44 105 44

Figure S18.  Get High-res Image Gene #44: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

'8p loss' versus 'METHLYATION_CNMF'

P value = 1.19e-08 (Fisher's exact test), Q value = 7.6e-06

Table S19.  Gene #44: '8p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 80 93 105
8P LOSS MUTATED 21 11 53
8P LOSS WILD-TYPE 59 82 52

Figure S19.  Get High-res Image Gene #44: '8p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'8p loss' versus 'MRNASEQ_CNMF'

P value = 9.34e-07 (Fisher's exact test), Q value = 0.00059

Table S20.  Gene #44: '8p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 76 65 80 56
8P LOSS MUTATED 17 18 43 7
8P LOSS WILD-TYPE 59 47 37 49

Figure S20.  Get High-res Image Gene #44: '8p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'8p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 6.93e-05 (Fisher's exact test), Q value = 0.042

Table S21.  Gene #44: '8p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 81 86 70 40
8P LOSS MUTATED 14 42 16 13
8P LOSS WILD-TYPE 67 44 54 27

Figure S21.  Get High-res Image Gene #44: '8p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'8q loss' versus 'CN_CNMF'

P value = 4.27e-06 (Fisher's exact test), Q value = 0.0026

Table S22.  Gene #45: '8q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
8Q LOSS MUTATED 0 0 11
8Q LOSS WILD-TYPE 48 145 74

Figure S22.  Get High-res Image Gene #45: '8q loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'CN_CNMF'

P value = 0.000373 (Fisher's exact test), Q value = 0.23

Table S23.  Gene #46: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
9P LOSS MUTATED 1 1 10
9P LOSS WILD-TYPE 47 144 75

Figure S23.  Get High-res Image Gene #46: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'CN_CNMF'

P value = 8.67e-06 (Fisher's exact test), Q value = 0.0054

Table S24.  Gene #48: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
10P LOSS MUTATED 1 2 15
10P LOSS WILD-TYPE 47 143 70

Figure S24.  Get High-res Image Gene #48: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10q loss' versus 'CN_CNMF'

P value = 3.98e-07 (Fisher's exact test), Q value = 0.00025

Table S25.  Gene #49: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
10Q LOSS MUTATED 4 1 17
10Q LOSS WILD-TYPE 44 144 68

Figure S25.  Get High-res Image Gene #49: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

'12q loss' versus 'CN_CNMF'

P value = 0.000126 (Fisher's exact test), Q value = 0.077

Table S26.  Gene #51: '12q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
12Q LOSS MUTATED 0 1 10
12Q LOSS WILD-TYPE 48 144 75

Figure S26.  Get High-res Image Gene #51: '12q loss' versus Molecular Subtype #1: 'CN_CNMF'

'13q loss' versus 'CN_CNMF'

P value = 1.13e-07 (Fisher's exact test), Q value = 7.2e-05

Table S27.  Gene #52: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
13Q LOSS MUTATED 10 5 24
13Q LOSS WILD-TYPE 38 140 61

Figure S27.  Get High-res Image Gene #52: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

'15q loss' versus 'CN_CNMF'

P value = 7.16e-05 (Fisher's exact test), Q value = 0.044

Table S28.  Gene #54: '15q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
15Q LOSS MUTATED 1 2 13
15Q LOSS WILD-TYPE 47 143 72

Figure S28.  Get High-res Image Gene #54: '15q loss' versus Molecular Subtype #1: 'CN_CNMF'

'16q loss' versus 'CN_CNMF'

P value = 1.27e-10 (Fisher's exact test), Q value = 8.1e-08

Table S29.  Gene #56: '16q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
16Q LOSS MUTATED 6 10 37
16Q LOSS WILD-TYPE 42 135 48

Figure S29.  Get High-res Image Gene #56: '16q loss' versus Molecular Subtype #1: 'CN_CNMF'

'17p loss' versus 'CN_CNMF'

P value = 7.39e-14 (Fisher's exact test), Q value = 4.7e-11

Table S30.  Gene #57: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
17P LOSS MUTATED 1 4 33
17P LOSS WILD-TYPE 47 141 52

Figure S30.  Get High-res Image Gene #57: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

'17p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3e-05 (Fisher's exact test), Q value = 0.018

Table S31.  Gene #57: '17p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 81 86 70 40
17P LOSS MUTATED 4 25 7 2
17P LOSS WILD-TYPE 77 61 63 38

Figure S31.  Get High-res Image Gene #57: '17p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'18p loss' versus 'CN_CNMF'

P value = 1.58e-06 (Fisher's exact test), Q value = 0.00099

Table S32.  Gene #59: '18p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
18P LOSS MUTATED 3 7 24
18P LOSS WILD-TYPE 45 138 61

Figure S32.  Get High-res Image Gene #59: '18p loss' versus Molecular Subtype #1: 'CN_CNMF'

'18q loss' versus 'CN_CNMF'

P value = 6.03e-09 (Fisher's exact test), Q value = 3.8e-06

Table S33.  Gene #60: '18q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
18Q LOSS MUTATED 8 9 33
18Q LOSS WILD-TYPE 40 136 52

Figure S33.  Get High-res Image Gene #60: '18q loss' versus Molecular Subtype #1: 'CN_CNMF'

'22q loss' versus 'CN_CNMF'

P value = 0.000193 (Fisher's exact test), Q value = 0.12

Table S34.  Gene #66: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
22Q LOSS MUTATED 2 3 14
22Q LOSS WILD-TYPE 46 142 71

Figure S34.  Get High-res Image Gene #66: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

'xq loss' versus 'CN_CNMF'

P value = 6.29e-05 (Fisher's exact test), Q value = 0.039

Table S35.  Gene #67: 'xq loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 48 145 85
XQ LOSS MUTATED 2 2 14
XQ LOSS WILD-TYPE 46 143 71

Figure S35.  Get High-res Image Gene #67: 'xq loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data
Input

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

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

  • Number of patients = 278

  • Number of significantly arm-level cnvs = 67

  • 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)
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