Correlation between copy number variations of arm-level result and molecular subtypes
Rectum Adenocarcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C1K64G9R
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/C1K64G9R
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 75 arm-level results and 10 molecular subtypes across 162 patients, 11 significant findings detected with Q value < 0.25.

  • 6p gain cnv correlated to 'CN_CNMF'.

  • 6q gain cnv correlated to 'CN_CNMF'.

  • 7p gain cnv correlated to 'CN_CNMF'.

  • 7q gain cnv correlated to 'CN_CNMF'.

  • 8q gain cnv correlated to 'CN_CNMF'.

  • 13q gain cnv correlated to 'CN_CNMF'.

  • 16q gain cnv correlated to 'CN_CNMF'.

  • 20q gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 18p loss cnv correlated to 'CN_CNMF'.

  • 18q 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 75 arm-level results and 10 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 11 significant findings detected.

Molecular
subtypes 		MRNA
CNMF 		MRNA
CHIERARCHICAL 		CN
CNMF 		METHLYATION
CNMF 		RPPA
CNMF 		RPPA
CHIERARCHICAL 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL
nCNV (%) nWild-Type Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test
20q gain 132 (81%) 30 0.0858
(1.00) 		0.0909
(1.00) 		0.000265
(0.181) 		0.226
(1.00) 		0.252
(1.00) 		0.978
(1.00) 		0.0379
(1.00) 		6.95e-06
(0.00477) 		0.791
(1.00) 		0.465
(1.00)
6p gain 27 (17%) 135 0.432
(1.00) 		0.263
(1.00) 		3.03e-05
(0.0207) 		0.00823
(1.00) 		0.55
(1.00) 		0.264
(1.00) 		0.246
(1.00) 		0.0339
(1.00) 		0.748
(1.00) 		0.694
(1.00)
6q gain 27 (17%) 135 0.432
(1.00) 		0.263
(1.00) 		7.74e-05
(0.0529) 		0.0597
(1.00) 		0.55
(1.00) 		0.268
(1.00) 		0.246
(1.00) 		0.0339
(1.00) 		0.861
(1.00) 		0.694
(1.00)
7p gain 90 (56%) 72 0.00256
(1.00) 		0.00222
(1.00) 		1.28e-06
(0.000879) 		0.0155
(1.00) 		0.579
(1.00) 		0.83
(1.00) 		0.0277
(1.00) 		0.0072
(1.00) 		0.151
(1.00) 		0.0302
(1.00)
7q gain 79 (49%) 83 0.00631
(1.00) 		0.00494
(1.00) 		6.47e-07
(0.000446) 		0.0926
(1.00) 		0.923
(1.00) 		0.408
(1.00) 		0.0656
(1.00) 		0.0128
(1.00) 		0.651
(1.00) 		0.354
(1.00)
8q gain 72 (44%) 90 0.00878
(1.00) 		0.019
(1.00) 		3.13e-08
(2.16e-05) 		0.523
(1.00) 		0.101
(1.00) 		0.0977
(1.00) 		0.0728
(1.00) 		0.0513
(1.00) 		0.488
(1.00) 		0.288
(1.00)
13q gain 102 (63%) 60 0.225
(1.00) 		0.175
(1.00) 		1.28e-07
(8.83e-05) 		0.362
(1.00) 		0.622
(1.00) 		0.721
(1.00) 		0.11
(1.00) 		0.0129
(1.00) 		0.0316
(1.00) 		0.108
(1.00)
16q gain 30 (19%) 132 0.356
(1.00) 		0.474
(1.00) 		0.000114
(0.078) 		0.532
(1.00) 		0.803
(1.00) 		0.742
(1.00) 		0.658
(1.00) 		0.745
(1.00) 		0.0397
(1.00) 		0.0964
(1.00)
18p loss 114 (70%) 48 0.0181
(1.00) 		0.0163
(1.00) 		1.17e-05
(0.00801) 		0.425
(1.00) 		0.309
(1.00) 		0.716
(1.00) 		0.0738
(1.00) 		0.332
(1.00) 		0.582
(1.00) 		0.406
(1.00)
18q loss 126 (78%) 36 0.0195
(1.00) 		0.0148
(1.00) 		9.16e-07
(0.000631) 		0.37
(1.00) 		0.737
(1.00) 		0.935
(1.00) 		0.0319
(1.00) 		0.548
(1.00) 		0.613
(1.00) 		0.668
(1.00)
1p gain 4 (2%) 158 0.708
(1.00) 		0.481
(1.00) 		1
(1.00) 		0.0105
(1.00) 		0.15
(1.00) 		0.748
(1.00)
1q gain 27 (17%) 135 0.724
(1.00) 		0.923
(1.00) 		0.0332
(1.00) 		0.16
(1.00) 		0.0777
(1.00) 		0.28
(1.00) 		0.316
(1.00) 		0.793
(1.00) 		0.43
(1.00) 		0.761
(1.00)
2p gain 20 (12%) 142 0.197
(1.00) 		0.427
(1.00) 		0.157
(1.00) 		0.697
(1.00) 		0.538
(1.00) 		0.787
(1.00) 		0.0461
(1.00) 		0.0818
(1.00) 		0.553
(1.00) 		0.346
(1.00)
2q gain 21 (13%) 141 0.0305
(1.00) 		0.0789
(1.00) 		0.701
(1.00) 		0.797
(1.00) 		0.679
(1.00) 		0.718
(1.00) 		0.0471
(1.00) 		0.0175
(1.00) 		0.108
(1.00) 		0.726
(1.00)
3p gain 17 (10%) 145 0.833
(1.00) 		0.671
(1.00) 		0.0252
(1.00) 		0.605
(1.00) 		0.0641
(1.00) 		0.837
(1.00) 		1
(1.00) 		0.817
(1.00) 		0.344
(1.00) 		0.0138
(1.00)
3q gain 23 (14%) 139 1
(1.00) 		0.808
(1.00) 		0.00832
(1.00) 		1
(1.00) 		0.0239
(1.00) 		0.226
(1.00) 		0.638
(1.00) 		0.569
(1.00) 		0.518
(1.00) 		0.041
(1.00)
4p gain 4 (2%) 158 0.391
(1.00) 		1
(1.00) 		0.57
(1.00) 		0.58
(1.00) 		0.366
(1.00) 		0.501
(1.00)
4q gain 3 (2%) 159 0.286
(1.00) 		0.476
(1.00) 		0.552
(1.00) 		0.78
(1.00) 		0.512
(1.00)
5p gain 20 (12%) 142 0.832
(1.00) 		1
(1.00) 		0.072
(1.00) 		0.108
(1.00) 		0.799
(1.00) 		0.719
(1.00) 		0.638
(1.00) 		0.231
(1.00) 		0.331
(1.00) 		0.68
(1.00)
5q gain 12 (7%) 150 0.543
(1.00) 		0.418
(1.00) 		0.056
(1.00) 		0.0444
(1.00) 		0.907
(1.00) 		0.282
(1.00) 		0.866
(1.00) 		0.356
(1.00) 		0.397
(1.00) 		0.447
(1.00)
8p gain 27 (17%) 135 0.631
(1.00) 		0.238
(1.00) 		0.00775
(1.00) 		0.662
(1.00) 		0.063
(1.00) 		0.0618
(1.00) 		0.943
(1.00) 		0.499
(1.00) 		0.94
(1.00) 		0.499
(1.00)
9p gain 35 (22%) 127 0.0354
(1.00) 		0.201
(1.00) 		0.482
(1.00) 		0.0493
(1.00) 		0.593
(1.00) 		0.181
(1.00) 		0.98
(1.00) 		0.67
(1.00) 		0.153
(1.00) 		0.712
(1.00)
9q gain 26 (16%) 136 0.0426
(1.00) 		0.271
(1.00) 		0.135
(1.00) 		0.44
(1.00) 		0.471
(1.00) 		0.272
(1.00) 		0.144
(1.00) 		0.0237
(1.00) 		0.306
(1.00) 		0.465
(1.00)
10p gain 8 (5%) 154 0.309
(1.00) 		0.515
(1.00) 		0.245
(1.00) 		0.481
(1.00) 		0.189
(1.00) 		0.549
(1.00) 		0.00187
(1.00) 		0.0794
(1.00) 		0.391
(1.00) 		0.87
(1.00)
10q gain 4 (2%) 158 0.444
(1.00) 		0.785
(1.00) 		0.925
(1.00) 		0.631
(1.00) 		0.788
(1.00)
11p gain 21 (13%) 141 0.0363
(1.00) 		0.0609
(1.00) 		0.0813
(1.00) 		0.333
(1.00) 		0.794
(1.00) 		0.871
(1.00) 		0.0612
(1.00) 		0.0968
(1.00) 		0.464
(1.00) 		0.15
(1.00)
11q gain 17 (10%) 145 0.0848
(1.00) 		0.14
(1.00) 		0.00131
(0.889) 		0.024
(1.00) 		0.617
(1.00) 		0.721
(1.00) 		0.00291
(1.00) 		0.125
(1.00) 		0.936
(1.00) 		0.796
(1.00)
12p gain 28 (17%) 134 0.582
(1.00) 		0.381
(1.00) 		0.0201
(1.00) 		0.797
(1.00) 		0.274
(1.00) 		0.084
(1.00) 		0.102
(1.00) 		0.0218
(1.00) 		0.297
(1.00) 		0.164
(1.00)
12q gain 19 (12%) 143 1
(1.00) 		1
(1.00) 		0.32
(1.00) 		0.458
(1.00) 		0.451
(1.00) 		0.038
(1.00) 		0.671
(1.00) 		0.112
(1.00) 		0.342
(1.00) 		0.485
(1.00)
14q gain 4 (2%) 158 0.708
(1.00) 		0.176
(1.00) 		0.463
(1.00) 		0.41
(1.00) 		0.111
(1.00) 		0.19
(1.00)
16p gain 29 (18%) 133 0.245
(1.00) 		0.356
(1.00) 		0.0101
(1.00) 		0.455
(1.00) 		1
(1.00) 		0.801
(1.00) 		0.428
(1.00) 		0.52
(1.00) 		0.449
(1.00) 		0.332
(1.00)
17p gain 3 (2%) 159 0.111
(1.00)
17q gain 18 (11%) 144 0.189
(1.00) 		0.606
(1.00) 		0.0397
(1.00) 		0.909
(1.00) 		0.933
(1.00) 		0.884
(1.00) 		0.108
(1.00) 		0.39
(1.00) 		0.409
(1.00) 		0.31
(1.00)
18p gain 7 (4%) 155 0.282
(1.00) 		0.774
(1.00) 		0.118
(1.00) 		0.299
(1.00) 		0.795
(1.00) 		0.808
(1.00) 		0.73
(1.00) 		0.672
(1.00) 		0.757
(1.00) 		1
(1.00)
18q gain 4 (2%) 158 0.708
(1.00) 		0.113
(1.00) 		1
(1.00) 		0.789
(1.00) 		0.735
(1.00) 		0.501
(1.00)
19p gain 20 (12%) 142 0.00723
(1.00) 		0.115
(1.00) 		0.00524
(1.00) 		0.703
(1.00) 		0.895
(1.00) 		0.751
(1.00) 		0.0675
(1.00) 		0.121
(1.00) 		0.357
(1.00) 		0.232
(1.00)
19q gain 23 (14%) 139 0.0202
(1.00) 		0.0827
(1.00) 		0.00568
(1.00) 		0.614
(1.00) 		0.471
(1.00) 		0.524
(1.00) 		0.00418
(1.00) 		0.0223
(1.00) 		0.407
(1.00) 		0.788
(1.00)
20p gain 95 (59%) 67 0.717
(1.00) 		0.466
(1.00) 		0.147
(1.00) 		0.619
(1.00) 		0.0295
(1.00) 		0.838
(1.00) 		0.67
(1.00) 		0.0386
(1.00) 		0.577
(1.00) 		0.19
(1.00)
21q gain 7 (4%) 155 0.502
(1.00) 		0.107
(1.00) 		0.467
(1.00) 		0.818
(1.00) 		1
(1.00) 		0.634
(1.00) 		0.495
(1.00) 		1
(1.00) 		0.307
(1.00) 		1
(1.00)
22q gain 5 (3%) 157 0.191
(1.00) 		0.107
(1.00) 		0.563
(1.00) 		0.728
(1.00) 		0.0639
(1.00) 		0.167
(1.00) 		0.175
(1.00) 		0.631
(1.00) 		0.788
(1.00)
Xq gain 7 (4%) 155 1
(1.00) 		0.829
(1.00) 		0.591
(1.00) 		1
(1.00) 		0.762
(1.00) 		0.63
(1.00) 		0.73
(1.00) 		0.672
(1.00) 		0.744
(1.00) 		0.87
(1.00)
1p loss 21 (13%) 141 0.604
(1.00) 		1
(1.00) 		0.0239
(1.00) 		0.395
(1.00) 		0.344
(1.00) 		0.418
(1.00) 		0.123
(1.00) 		0.283
(1.00) 		0.387
(1.00) 		0.463
(1.00)
1q loss 7 (4%) 155 0.833
(1.00) 		0.671
(1.00) 		0.536
(1.00) 		0.622
(1.00) 		0.57
(1.00) 		0.616
(1.00) 		0.11
(1.00) 		0.0512
(1.00) 		0.52
(1.00) 		0.87
(1.00)
2p loss 5 (3%) 157 0.426
(1.00) 		0.62
(1.00) 		0.413
(1.00) 		0.682
(1.00) 		0.123
(1.00) 		0.112
(1.00) 		0.355
(1.00) 		0.0965
(1.00) 		0.0741
(1.00)
3p loss 8 (5%) 154 1
(1.00) 		1
(1.00) 		0.486
(1.00) 		0.461
(1.00) 		0.903
(1.00) 		0.775
(1.00) 		0.783
(1.00) 		0.817
(1.00) 		0.754
(1.00) 		0.775
(1.00)
3q loss 4 (2%) 158 0.463
(1.00) 		1
(1.00) 		0.314
(1.00) 		0.413
(1.00) 		1
(1.00)
4p loss 39 (24%) 123 0.365
(1.00) 		0.94
(1.00) 		0.002
(1.00) 		0.867
(1.00) 		0.54
(1.00) 		0.358
(1.00) 		0.393
(1.00) 		0.445
(1.00) 		0.783
(1.00) 		1
(1.00)
4q loss 46 (28%) 116 0.591
(1.00) 		1
(1.00) 		0.000856
(0.581) 		0.841
(1.00) 		0.523
(1.00) 		0.369
(1.00) 		0.141
(1.00) 		0.27
(1.00) 		0.885
(1.00) 		0.818
(1.00)
5p loss 11 (7%) 151 0.151
(1.00) 		0.25
(1.00) 		0.745
(1.00) 		0.368
(1.00) 		0.592
(1.00) 		0.701
(1.00) 		0.267
(1.00) 		0.363
(1.00) 		0.438
(1.00) 		0.127
(1.00)
5q loss 23 (14%) 139 0.0173
(1.00) 		0.0609
(1.00) 		0.204
(1.00) 		0.108
(1.00) 		0.895
(1.00) 		0.838
(1.00) 		0.377
(1.00) 		0.0871
(1.00) 		0.774
(1.00) 		0.16
(1.00)
6p loss 8 (5%) 154 0.38
(1.00) 		0.829
(1.00) 		0.572
(1.00) 		0.0133
(1.00) 		1
(1.00) 		0.702
(1.00) 		0.143
(1.00) 		0.153
(1.00) 		0.757
(1.00) 		0.87
(1.00)
6q loss 14 (9%) 148 1
(1.00) 		0.606
(1.00) 		0.269
(1.00) 		0.268
(1.00) 		0.31
(1.00) 		0.828
(1.00) 		0.269
(1.00) 		0.00482
(1.00) 		0.186
(1.00) 		0.135
(1.00)
8p loss 56 (35%) 106 0.642
(1.00) 		0.373
(1.00) 		0.0258
(1.00) 		0.697
(1.00) 		0.692
(1.00) 		0.679
(1.00) 		0.56
(1.00) 		0.269
(1.00) 		0.716
(1.00) 		0.102
(1.00)
8q loss 3 (2%) 159 0.486
(1.00) 		0.785
(1.00) 		0.925
(1.00) 		0.527
(1.00) 		1
(1.00)
9p loss 12 (7%) 150 0.662
(1.00) 		0.758
(1.00) 		0.101
(1.00) 		0.883
(1.00) 		0.439
(1.00) 		0.514
(1.00) 		0.0213
(1.00) 		0.363
(1.00) 		0.965
(1.00) 		1
(1.00)
9q loss 11 (7%) 151 0.607
(1.00) 		0.315
(1.00) 		0.265
(1.00) 		1
(1.00) 		0.558
(1.00) 		0.644
(1.00) 		0.227
(1.00) 		0.175
(1.00) 		0.645
(1.00) 		0.317
(1.00)
10p loss 17 (10%) 145 0.0447
(1.00) 		0.0149
(1.00) 		0.353
(1.00) 		0.614
(1.00) 		0.109
(1.00) 		0.344
(1.00) 		0.263
(1.00) 		0.271
(1.00) 		0.91
(1.00) 		1
(1.00)
10q loss 21 (13%) 141 0.136
(1.00) 		0.317
(1.00) 		0.0692
(1.00) 		0.582
(1.00) 		0.428
(1.00) 		0.838
(1.00) 		0.0433
(1.00) 		0.0548
(1.00) 		0.97
(1.00) 		0.894
(1.00)
11p loss 19 (12%) 143 0.0628
(1.00) 		0.131
(1.00) 		0.0303
(1.00) 		0.0434
(1.00) 		0.607
(1.00) 		0.101
(1.00) 		0.111
(1.00) 		0.0526
(1.00) 		0.856
(1.00) 		0.661
(1.00)
11q loss 23 (14%) 139 0.0628
(1.00) 		0.131
(1.00) 		0.0221
(1.00) 		0.117
(1.00) 		0.95
(1.00) 		0.146
(1.00) 		0.136
(1.00) 		0.0526
(1.00) 		0.101
(1.00) 		0.221
(1.00)
12p loss 12 (7%) 150 0.731
(1.00) 		0.848
(1.00) 		0.331
(1.00) 		0.0753
(1.00) 		0.617
(1.00) 		0.0822
(1.00) 		0.164
(1.00) 		0.125
(1.00) 		0.871
(1.00) 		0.535
(1.00)
12q loss 8 (5%) 154 1
(1.00) 		0.625
(1.00) 		0.541
(1.00) 		1
(1.00) 		0.795
(1.00) 		0.592
(1.00) 		0.129
(1.00) 		0.175
(1.00) 		0.483
(1.00) 		0.57
(1.00)
13q loss 5 (3%) 157 0.092
(1.00) 		0.186
(1.00) 		0.318
(1.00) 		0.597
(1.00) 		0.345
(1.00) 		0.843
(1.00)
14q loss 51 (31%) 111 0.805
(1.00) 		0.252
(1.00) 		0.000406
(0.276) 		1
(1.00) 		0.429
(1.00) 		0.255
(1.00) 		0.142
(1.00) 		0.804
(1.00) 		0.965
(1.00) 		0.371
(1.00)
15q loss 58 (36%) 104 0.785
(1.00) 		0.227
(1.00) 		0.00229
(1.00) 		0.45
(1.00) 		0.0216
(1.00) 		0.0757
(1.00) 		0.717
(1.00) 		0.82
(1.00) 		0.566
(1.00) 		0.714
(1.00)
16p loss 6 (4%) 156 0.191
(1.00) 		0.488
(1.00) 		0.225
(1.00) 		0.481
(1.00) 		0.762
(1.00) 		0.563
(1.00) 		0.388
(1.00) 		0.329
(1.00) 		0.568
(1.00) 		1
(1.00)
16q loss 10 (6%) 152 0.0202
(1.00) 		0.12
(1.00) 		0.00539
(1.00) 		0.441
(1.00) 		0.373
(1.00) 		0.641
(1.00) 		0.112
(1.00) 		0.434
(1.00) 		0.612
(1.00) 		0.603
(1.00)
17p loss 89 (55%) 73 0.866
(1.00) 		1
(1.00) 		0.252
(1.00) 		0.606
(1.00) 		0.249
(1.00) 		0.285
(1.00) 		0.408
(1.00) 		0.653
(1.00) 		0.615
(1.00) 		0.893
(1.00)
17q loss 15 (9%) 147 0.614
(1.00) 		0.362
(1.00) 		0.303
(1.00) 		0.134
(1.00) 		0.707
(1.00) 		0.477
(1.00) 		0.899
(1.00) 		0.817
(1.00) 		0.336
(1.00) 		0.736
(1.00)
19p loss 7 (4%) 155 0.265
(1.00) 		0.368
(1.00) 		0.795
(1.00) 		0.571
(1.00) 		0.143
(1.00) 		0.141
(1.00)
19q loss 7 (4%) 155 0.494
(1.00) 		0.105
(1.00) 		0.662
(1.00) 		0.563
(1.00) 		0.701
(1.00) 		0.351
(1.00)
20p loss 18 (11%) 144 1
(1.00) 		1
(1.00) 		0.162
(1.00) 		0.65
(1.00) 		0.197
(1.00) 		0.867
(1.00) 		0.301
(1.00) 		0.92
(1.00) 		0.0305
(1.00) 		0.0916
(1.00)
21q loss 43 (27%) 119 0.879
(1.00) 		0.676
(1.00) 		0.25
(1.00) 		0.596
(1.00) 		0.149
(1.00) 		0.915
(1.00) 		0.948
(1.00) 		0.885
(1.00) 		0.099
(1.00) 		0.663
(1.00)
22q loss 42 (26%) 120 0.887
(1.00) 		0.739
(1.00) 		0.5
(1.00) 		0.311
(1.00) 		0.639
(1.00) 		0.475
(1.00) 		0.616
(1.00) 		0.944
(1.00) 		0.119
(1.00) 		0.788
(1.00)
Xq loss 6 (4%) 156 0.771
(1.00) 		0.37
(1.00) 		0.283
(1.00) 		0.481
(1.00) 		0.855
(1.00) 		0.706
(1.00) 		0.893
(1.00) 		1
(1.00) 		0.843
(1.00) 		0.843
(1.00)
'6p gain mutation analysis' versus 'CN_CNMF'

P value = 3.03e-05 (Chi-square test), Q value = 0.021

Table S1.  Gene #11: '6p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 7 32 46 55 22
6P GAIN MUTATED 4 11 4 2 6
6P GAIN WILD-TYPE 3 21 42 53 16

Figure S1.  Get High-res Image Gene #11: '6p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'6q gain mutation analysis' versus 'CN_CNMF'

P value = 7.74e-05 (Chi-square test), Q value = 0.053

Table S2.  Gene #12: '6q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 7 32 46 55 22
6Q GAIN MUTATED 3 12 4 2 6
6Q GAIN WILD-TYPE 4 20 42 53 16

Figure S2.  Get High-res Image Gene #12: '6q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'7p gain mutation analysis' versus 'CN_CNMF'

P value = 1.28e-06 (Chi-square test), Q value = 0.00088

Table S3.  Gene #13: '7p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 7 32 46 55 22
7P GAIN MUTATED 5 29 26 16 14
7P GAIN WILD-TYPE 2 3 20 39 8

Figure S3.  Get High-res Image Gene #13: '7p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'7q gain mutation analysis' versus 'CN_CNMF'

P value = 6.47e-07 (Chi-square test), Q value = 0.00045

Table S4.  Gene #14: '7q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 7 32 46 55 22
7Q GAIN MUTATED 3 27 23 12 14
7Q GAIN WILD-TYPE 4 5 23 43 8

Figure S4.  Get High-res Image Gene #14: '7q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'8q gain mutation analysis' versus 'CN_CNMF'

P value = 3.13e-08 (Chi-square test), Q value = 2.2e-05

Table S5.  Gene #16: '8q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 7 32 46 55 22
8Q GAIN MUTATED 1 15 37 11 8
8Q GAIN WILD-TYPE 6 17 9 44 14

Figure S5.  Get High-res Image Gene #16: '8q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'13q gain mutation analysis' versus 'CN_CNMF'

P value = 1.28e-07 (Chi-square test), Q value = 8.8e-05

Table S6.  Gene #25: '13q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 7 32 46 55 22
13Q GAIN MUTATED 5 29 27 20 21
13Q GAIN WILD-TYPE 2 3 19 35 1

Figure S6.  Get High-res Image Gene #25: '13q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'16q gain mutation analysis' versus 'CN_CNMF'

P value = 0.000114 (Chi-square test), Q value = 0.078

Table S7.  Gene #28: '16q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 7 32 46 55 22
16Q GAIN MUTATED 3 11 7 1 8
16Q GAIN WILD-TYPE 4 21 39 54 14

Figure S7.  Get High-res Image Gene #28: '16q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'20q gain mutation analysis' versus 'CN_CNMF'

P value = 0.000265 (Chi-square test), Q value = 0.18

Table S8.  Gene #36: '20q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 7 32 46 55 22
20Q GAIN MUTATED 7 32 36 36 21
20Q GAIN WILD-TYPE 0 0 10 19 1

Figure S8.  Get High-res Image Gene #36: '20q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'20q gain mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 6.95e-06 (Fisher's exact test), Q value = 0.0048

Table S9.  Gene #36: '20q gain mutation analysis' versus Clinical Feature #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 17 24 30
20Q GAIN MUTATED 16 11 29
20Q GAIN WILD-TYPE 1 13 1

Figure S9.  Get High-res Image Gene #36: '20q gain mutation analysis' versus Clinical Feature #8: 'MRNASEQ_CHIERARCHICAL'

'18p loss mutation analysis' versus 'CN_CNMF'

P value = 1.17e-05 (Chi-square test), Q value = 0.008

Table S10.  Gene #68: '18p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 7 32 46 55 22
18P LOSS MUTATED 7 31 34 26 16
18P LOSS WILD-TYPE 0 1 12 29 6

Figure S10.  Get High-res Image Gene #68: '18p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'18q loss mutation analysis' versus 'CN_CNMF'

P value = 9.16e-07 (Chi-square test), Q value = 0.00063

Table S11.  Gene #69: '18q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 7 32 46 55 22
18Q LOSS MUTATED 7 32 40 29 18
18Q LOSS WILD-TYPE 0 0 6 26 4

Figure S11.  Get High-res Image Gene #69: '18q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

Methods & Data
Input

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

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

  • Number of patients = 162

  • Number of significantly arm-level cnvs = 75

  • 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

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] 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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