Correlation between copy number variations of arm-level result and molecular subtypes
Liver Hepatocellular Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1NZ8695
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/C1NZ8695
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 199 patients, 33 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 1q gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 5p gain cnv correlated to 'CN_CNMF'.

  • 5q gain cnv correlated to 'CN_CNMF'.

  • 6p gain cnv correlated to 'CN_CNMF'.

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

  • 19p gain cnv correlated to 'METHLYATION_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 19q gain cnv correlated to 'METHLYATION_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 20p gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.

  • 20q gain cnv correlated to 'MRNASEQ_CNMF'.

  • xq gain cnv correlated to 'CN_CNMF'.

  • 1p loss cnv correlated to 'METHLYATION_CNMF' and 'MRNASEQ_CNMF'.

  • 4p loss cnv correlated to 'CN_CNMF'.

  • 4q loss cnv correlated to 'CN_CNMF'.

  • 8p loss cnv correlated to 'CN_CNMF'.

  • 9p loss cnv correlated to 'CN_CNMF'.

  • 10q loss cnv correlated to 'MRNASEQ_CNMF'.

  • 13q loss cnv correlated to 'CN_CNMF'.

  • 16p loss cnv correlated to 'MRNASEQ_CNMF' and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 16q loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.

  • 17p loss cnv correlated to 'CN_CNMF'.

  • 19p loss cnv correlated to 'CN_CNMF'.

  • 19q 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, 33 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 Chi-square test Fisher's exact test Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test
19p gain 38 (19%) 161 0.292
(1.00) 		3.57e-05
(0.0224) 		1.82e-05
(0.0115) 		6.04e-05
(0.0377) 		0.0304
(1.00) 		0.00197
(1.00) 		0.00205
(1.00) 		0.00126
(0.752)
19q gain 44 (22%) 155 0.114
(1.00) 		6.06e-05
(0.0377) 		1.79e-05
(0.0114) 		5.03e-05
(0.0315) 		0.105
(1.00) 		0.00227
(1.00) 		0.000713
(0.431) 		0.000924
(0.554)
16q loss 73 (37%) 126 3.33e-05
(0.021) 		5.44e-05
(0.034) 		7.16e-05
(0.0445) 		0.00916
(1.00) 		0.78
(1.00) 		0.0472
(1.00) 		0.0436
(1.00) 		0.014
(1.00)
1q gain 113 (57%) 86 2.28e-06
(0.00145) 		0.000386
(0.235) 		0.00698
(1.00) 		0.0106
(1.00) 		0.478
(1.00) 		0.0893
(1.00) 		0.311
(1.00) 		0.329
(1.00)
8q gain 97 (49%) 102 1.42e-11
(9.06e-09) 		0.361
(1.00) 		0.0554
(1.00) 		0.000294
(0.18) 		0.133
(1.00) 		0.267
(1.00) 		0.929
(1.00) 		0.783
(1.00)
20p gain 58 (29%) 141 0.000399
(0.243) 		0.0284
(1.00) 		0.000297
(0.182) 		0.0413
(1.00) 		0.441
(1.00) 		0.272
(1.00) 		0.00518
(1.00) 		0.03
(1.00)
1p loss 45 (23%) 154 0.0117
(1.00) 		0.000278
(0.17) 		5.32e-06
(0.00338) 		0.0551
(1.00) 		0.0755
(1.00) 		0.274
(1.00) 		0.0349
(1.00) 		0.218
(1.00)
16p loss 59 (30%) 140 0.00318
(1.00) 		0.0828
(1.00) 		0.000101
(0.0629) 		0.00314
(1.00) 		0.436
(1.00) 		0.0119
(1.00) 		0.0354
(1.00) 		0.000388
(0.236)
5p gain 75 (38%) 124 0.000274
(0.168) 		0.0226
(1.00) 		0.233
(1.00) 		0.462
(1.00) 		0.736
(1.00) 		0.702
(1.00) 		0.195
(1.00) 		0.884
(1.00)
5q gain 54 (27%) 145 1.99e-05
(0.0126) 		0.0536
(1.00) 		0.903
(1.00) 		1
(1.00) 		0.879
(1.00) 		0.95
(1.00) 		0.326
(1.00) 		0.969
(1.00)
6p gain 60 (30%) 139 2.06e-06
(0.00131) 		0.00159
(0.942) 		0.00222
(1.00) 		0.0941
(1.00) 		0.368
(1.00) 		0.0138
(1.00) 		0.546
(1.00) 		0.707
(1.00)
20q gain 61 (31%) 138 0.000832
(0.501) 		0.0193
(1.00) 		0.000234
(0.144) 		0.0388
(1.00) 		0.45
(1.00) 		0.328
(1.00) 		0.0261
(1.00) 		0.051
(1.00)
xq gain 33 (17%) 166 2e-05
(0.0126) 		0.0248
(1.00) 		0.431
(1.00) 		0.516
(1.00) 		0.0682
(1.00) 		0.072
(1.00) 		0.541
(1.00) 		0.31
(1.00)
4p loss 53 (27%) 146 2.59e-05
(0.0163) 		0.0274
(1.00) 		0.0119
(1.00) 		0.0455
(1.00) 		0.613
(1.00) 		0.721
(1.00) 		0.436
(1.00) 		0.611
(1.00)
4q loss 73 (37%) 126 1.23e-08
(7.86e-06) 		0.00708
(1.00) 		0.00809
(1.00) 		0.345
(1.00) 		0.757
(1.00) 		0.759
(1.00) 		0.41
(1.00) 		0.819
(1.00)
8p loss 97 (49%) 102 4.63e-05
(0.029) 		0.0324
(1.00) 		0.593
(1.00) 		0.988
(1.00) 		0.0539
(1.00) 		0.333
(1.00) 		0.409
(1.00) 		0.182
(1.00)
9p loss 64 (32%) 135 0.000333
(0.203) 		0.482
(1.00) 		0.1
(1.00) 		0.679
(1.00) 		0.196
(1.00) 		0.683
(1.00) 		0.572
(1.00) 		0.719
(1.00)
10q loss 47 (24%) 152 0.156
(1.00) 		0.824
(1.00) 		4.63e-06
(0.00294) 		0.065
(1.00) 		0.0911
(1.00) 		0.163
(1.00) 		0.0262
(1.00) 		0.105
(1.00)
13q loss 69 (35%) 130 7.83e-05
(0.0486) 		0.385
(1.00) 		0.0674
(1.00) 		0.0114
(1.00) 		0.71
(1.00) 		0.0743
(1.00) 		0.00149
(0.889) 		0.0716
(1.00)
17p loss 106 (53%) 93 0.000163
(0.101) 		0.0908
(1.00) 		0.15
(1.00) 		0.259
(1.00) 		0.000873
(0.525) 		0.00351
(1.00) 		0.0198
(1.00) 		0.00692
(1.00)
19p loss 30 (15%) 169 0.000269
(0.166) 		0.253
(1.00) 		0.0232
(1.00) 		0.215
(1.00) 		0.0956
(1.00) 		0.0337
(1.00) 		0.153
(1.00) 		0.0637
(1.00)
19q loss 23 (12%) 176 0.000108
(0.0671) 		0.428
(1.00) 		0.311
(1.00) 		0.0713
(1.00) 		0.429
(1.00) 		0.122
(1.00) 		0.275
(1.00) 		0.469
(1.00)
1p gain 34 (17%) 165 0.258
(1.00) 		0.575
(1.00) 		0.0143
(1.00) 		0.406
(1.00) 		0.473
(1.00) 		0.0532
(1.00) 		0.103
(1.00) 		0.0769
(1.00)
2p gain 28 (14%) 171 0.201
(1.00) 		0.393
(1.00) 		0.135
(1.00) 		0.332
(1.00) 		0.478
(1.00) 		0.801
(1.00) 		0.715
(1.00) 		0.572
(1.00)
2q gain 23 (12%) 176 0.0489
(1.00) 		0.35
(1.00) 		0.0379
(1.00) 		0.134
(1.00) 		0.131
(1.00) 		0.594
(1.00) 		0.722
(1.00) 		0.553
(1.00)
3p gain 20 (10%) 179 0.01
(1.00) 		0.706
(1.00) 		0.68
(1.00) 		0.528
(1.00) 		0.203
(1.00) 		0.635
(1.00) 		0.552
(1.00) 		0.379
(1.00)
3q gain 22 (11%) 177 0.015
(1.00) 		0.812
(1.00) 		0.68
(1.00) 		0.528
(1.00) 		0.0154
(1.00) 		0.354
(1.00) 		0.185
(1.00) 		0.284
(1.00)
4p gain 16 (8%) 183 0.0576
(1.00) 		0.569
(1.00) 		0.408
(1.00) 		0.383
(1.00) 		0.25
(1.00) 		0.417
(1.00) 		0.424
(1.00) 		0.815
(1.00)
4q gain 5 (3%) 194 1
(1.00) 		0.603
(1.00) 		0.564
(1.00) 		0.351
(1.00) 		0.848
(1.00) 		0.53
(1.00) 		0.19
(1.00) 		0.246
(1.00)
6q gain 39 (20%) 160 0.00209
(1.00) 		0.0382
(1.00) 		0.0119
(1.00) 		0.0562
(1.00) 		0.598
(1.00) 		0.7
(1.00) 		0.552
(1.00) 		0.9
(1.00)
7p gain 58 (29%) 141 0.116
(1.00) 		0.356
(1.00) 		0.544
(1.00) 		0.524
(1.00) 		0.0365
(1.00) 		0.398
(1.00) 		0.687
(1.00) 		0.341
(1.00)
7q gain 60 (30%) 139 0.368
(1.00) 		0.0327
(1.00) 		0.574
(1.00) 		0.657
(1.00) 		0.0609
(1.00) 		0.462
(1.00) 		0.487
(1.00) 		0.326
(1.00)
8p gain 39 (20%) 160 0.0614
(1.00) 		0.375
(1.00) 		0.162
(1.00) 		0.0461
(1.00) 		0.0577
(1.00) 		0.381
(1.00) 		0.691
(1.00) 		0.229
(1.00)
9p gain 11 (6%) 188 0.424
(1.00) 		0.299
(1.00) 		0.229
(1.00) 		0.219
(1.00) 		0.578
(1.00) 		0.84
(1.00) 		0.672
(1.00) 		0.56
(1.00)
9q gain 12 (6%) 187 0.169
(1.00) 		0.648
(1.00) 		0.0475
(1.00) 		0.132
(1.00) 		0.692
(1.00) 		0.815
(1.00) 		0.813
(1.00) 		0.5
(1.00)
10p gain 29 (15%) 170 0.459
(1.00) 		0.0131
(1.00) 		0.0637
(1.00) 		0.0478
(1.00) 		0.179
(1.00) 		0.674
(1.00) 		0.205
(1.00) 		0.17
(1.00)
10q gain 17 (9%) 182 0.141
(1.00) 		0.0259
(1.00) 		0.0017
(1.00) 		0.0918
(1.00) 		0.0787
(1.00) 		0.204
(1.00) 		0.0674
(1.00) 		0.0528
(1.00)
11p gain 14 (7%) 185 0.749
(1.00) 		0.406
(1.00) 		0.0728
(1.00) 		0.619
(1.00) 		0.113
(1.00) 		0.153
(1.00) 		0.0787
(1.00) 		0.124
(1.00)
11q gain 12 (6%) 187 1
(1.00) 		0.802
(1.00) 		0.24
(1.00) 		0.94
(1.00) 		0.196
(1.00) 		0.815
(1.00) 		0.379
(1.00) 		0.5
(1.00)
12p gain 23 (12%) 176 0.811
(1.00) 		0.121
(1.00) 		0.0441
(1.00) 		0.00108
(0.647) 		0.569
(1.00) 		0.474
(1.00) 		0.0114
(1.00) 		0.269
(1.00)
12q gain 27 (14%) 172 1
(1.00) 		0.386
(1.00) 		0.0849
(1.00) 		0.0206
(1.00) 		0.65
(1.00) 		0.474
(1.00) 		0.0705
(1.00) 		0.311
(1.00)
13q gain 13 (7%) 186 0.101
(1.00) 		0.113
(1.00) 		0.0203
(1.00) 		0.304
(1.00) 		0.205
(1.00) 		0.508
(1.00) 		0.00209
(1.00) 		0.114
(1.00)
14q gain 12 (6%) 187 0.1
(1.00) 		0.485
(1.00) 		0.389
(1.00) 		0.0334
(1.00) 		1
(1.00) 		0.243
(1.00) 		0.541
(1.00) 		0.212
(1.00)
15q gain 17 (9%) 182 0.225
(1.00) 		0.663
(1.00) 		0.8
(1.00) 		0.573
(1.00) 		0.179
(1.00) 		0.218
(1.00) 		0.667
(1.00) 		0.196
(1.00)
16p gain 16 (8%) 183 0.194
(1.00) 		0.893
(1.00) 		0.96
(1.00) 		0.963
(1.00) 		0.488
(1.00) 		0.0444
(1.00) 		0.136
(1.00) 		0.556
(1.00)
16q gain 8 (4%) 191 0.9
(1.00) 		0.419
(1.00) 		0.514
(1.00) 		0.241
(1.00) 		0.378
(1.00) 		0.343
(1.00) 		0.0248
(1.00) 		0.366
(1.00)
17p gain 16 (8%) 183 0.576
(1.00) 		0.0132
(1.00) 		0.214
(1.00) 		0.0788
(1.00) 		0.893
(1.00) 		0.652
(1.00) 		0.343
(1.00) 		0.292
(1.00)
17q gain 48 (24%) 151 0.0186
(1.00) 		0.0419
(1.00) 		0.114
(1.00) 		0.0194
(1.00) 		0.761
(1.00) 		0.54
(1.00) 		0.607
(1.00) 		0.567
(1.00)
18p gain 17 (9%) 182 0.146
(1.00) 		0.0845
(1.00) 		0.000664
(0.402) 		0.00163
(0.966) 		0.195
(1.00) 		0.259
(1.00) 		0.0146
(1.00) 		0.0988
(1.00)
18q gain 15 (8%) 184 0.272
(1.00) 		0.0393
(1.00) 		0.00104
(0.626) 		0.000744
(0.449) 		0.446
(1.00) 		0.413
(1.00) 		0.0122
(1.00) 		0.176
(1.00)
21q gain 17 (9%) 182 0.12
(1.00) 		0.893
(1.00) 		0.365
(1.00) 		0.524
(1.00) 		0.706
(1.00) 		0.775
(1.00) 		0.272
(1.00) 		0.455
(1.00)
22q gain 28 (14%) 171 0.0055
(1.00) 		0.21
(1.00) 		0.0136
(1.00) 		0.0361
(1.00) 		0.281
(1.00) 		0.434
(1.00) 		0.178
(1.00) 		0.107
(1.00)
1q loss 12 (6%) 187 0.868
(1.00) 		0.922
(1.00) 		0.435
(1.00) 		0.574
(1.00) 		0.34
(1.00) 		0.288
(1.00) 		0.421
(1.00) 		0.677
(1.00)
2p loss 19 (10%) 180 0.077
(1.00) 		0.775
(1.00) 		0.209
(1.00) 		0.626
(1.00) 		0.0147
(1.00) 		0.406
(1.00) 		0.674
(1.00) 		0.596
(1.00)
2q loss 22 (11%) 177 0.0303
(1.00) 		0.659
(1.00) 		0.12
(1.00) 		0.59
(1.00) 		0.0281
(1.00) 		0.613
(1.00) 		0.979
(1.00) 		0.765
(1.00)
3p loss 29 (15%) 170 0.0525
(1.00) 		0.329
(1.00) 		0.0924
(1.00) 		0.03
(1.00) 		0.359
(1.00) 		0.412
(1.00) 		0.0146
(1.00) 		0.0546
(1.00)
3q loss 18 (9%) 181 0.52
(1.00) 		1
(1.00) 		0.447
(1.00) 		0.412
(1.00) 		0.446
(1.00) 		0.781
(1.00) 		0.209
(1.00) 		0.246
(1.00)
5p loss 14 (7%) 185 0.413
(1.00) 		0.759
(1.00) 		0.834
(1.00) 		0.897
(1.00) 		0.753
(1.00) 		0.608
(1.00) 		0.437
(1.00) 		0.627
(1.00)
5q loss 22 (11%) 177 0.148
(1.00) 		0.22
(1.00) 		0.467
(1.00) 		0.54
(1.00) 		0.276
(1.00) 		0.772
(1.00) 		0.404
(1.00) 		0.775
(1.00)
6p loss 21 (11%) 178 0.827
(1.00) 		0.531
(1.00) 		0.398
(1.00) 		0.51
(1.00) 		0.041
(1.00) 		0.805
(1.00) 		0.674
(1.00) 		0.766
(1.00)
6q loss 54 (27%) 145 0.12
(1.00) 		0.691
(1.00) 		0.504
(1.00) 		0.372
(1.00) 		0.314
(1.00) 		0.2
(1.00) 		0.562
(1.00) 		0.775
(1.00)
7p loss 12 (6%) 187 0.56
(1.00) 		0.172
(1.00) 		0.0102
(1.00) 		0.657
(1.00) 		0.865
(1.00) 		0.897
(1.00) 		0.815
(1.00) 		0.868
(1.00)
7q loss 16 (8%) 183 1
(1.00) 		0.21
(1.00) 		0.0606
(1.00) 		0.699
(1.00) 		0.605
(1.00) 		0.323
(1.00) 		0.754
(1.00) 		0.292
(1.00)
8q loss 22 (11%) 177 0.00362
(1.00) 		1
(1.00) 		0.103
(1.00) 		0.0377
(1.00) 		0.656
(1.00) 		0.0721
(1.00) 		0.187
(1.00) 		0.434
(1.00)
9q loss 63 (32%) 136 0.00156
(0.928) 		0.391
(1.00) 		0.0165
(1.00) 		0.121
(1.00) 		0.392
(1.00) 		0.457
(1.00) 		0.372
(1.00) 		0.447
(1.00)
10p loss 28 (14%) 171 0.192
(1.00) 		0.371
(1.00) 		0.0132
(1.00) 		0.0983
(1.00) 		0.113
(1.00) 		0.0836
(1.00) 		0.149
(1.00) 		0.7
(1.00)
11p loss 40 (20%) 159 0.029
(1.00) 		0.191
(1.00) 		0.573
(1.00) 		0.429
(1.00) 		1
(1.00) 		0.969
(1.00) 		0.224
(1.00) 		0.545
(1.00)
11q loss 44 (22%) 155 0.036
(1.00) 		0.0318
(1.00) 		0.693
(1.00) 		0.538
(1.00) 		0.377
(1.00) 		0.912
(1.00) 		0.687
(1.00) 		1
(1.00)
12p loss 39 (20%) 160 0.254
(1.00) 		0.0792
(1.00) 		0.0262
(1.00) 		0.671
(1.00) 		0.0509
(1.00) 		0.141
(1.00) 		0.221
(1.00) 		0.0173
(1.00)
12q loss 21 (11%) 178 0.362
(1.00) 		0.273
(1.00) 		0.475
(1.00) 		0.759
(1.00) 		0.912
(1.00) 		0.806
(1.00) 		0.754
(1.00) 		0.765
(1.00)
14q loss 60 (30%) 139 0.00082
(0.494) 		0.482
(1.00) 		0.0202
(1.00) 		0.0975
(1.00) 		0.193
(1.00) 		0.115
(1.00) 		0.0481
(1.00) 		0.265
(1.00)
15q loss 44 (22%) 155 0.119
(1.00) 		0.218
(1.00) 		0.567
(1.00) 		0.0954
(1.00) 		0.903
(1.00) 		0.725
(1.00) 		0.192
(1.00) 		0.421
(1.00)
17q loss 33 (17%) 166 0.0451
(1.00) 		0.686
(1.00) 		0.441
(1.00) 		0.673
(1.00) 		0.445
(1.00) 		0.778
(1.00) 		0.0758
(1.00) 		0.754
(1.00)
18p loss 40 (20%) 159 0.0173
(1.00) 		0.0693
(1.00) 		0.735
(1.00) 		0.512
(1.00) 		0.736
(1.00) 		0.862
(1.00) 		0.992
(1.00) 		0.475
(1.00)
18q loss 44 (22%) 155 0.00315
(1.00) 		0.156
(1.00) 		0.727
(1.00) 		0.326
(1.00) 		1
(1.00) 		0.474
(1.00) 		0.946
(1.00) 		0.327
(1.00)
20p loss 11 (6%) 188 0.36
(1.00) 		0.355
(1.00) 		0.482
(1.00) 		0.202
(1.00) 		0.398
(1.00) 		0.753
(1.00) 		0.484
(1.00) 		0.643
(1.00)
20q loss 7 (4%) 192 0.625
(1.00) 		0.485
(1.00) 		0.75
(1.00) 		0.288
(1.00) 		0.228
(1.00) 		0.436
(1.00) 		0.374
(1.00) 		0.447
(1.00)
21q loss 56 (28%) 143 0.142
(1.00) 		0.897
(1.00) 		0.0386
(1.00) 		0.921
(1.00) 		0.341
(1.00) 		0.382
(1.00) 		0.0924
(1.00) 		0.319
(1.00)
22q loss 48 (24%) 151 0.467
(1.00) 		0.64
(1.00) 		0.15
(1.00) 		0.284
(1.00) 		0.904
(1.00) 		0.899
(1.00) 		0.612
(1.00) 		0.863
(1.00)
xq loss 35 (18%) 164 0.00046
(0.279) 		0.139
(1.00) 		0.67
(1.00) 		0.169
(1.00) 		0.67
(1.00) 		0.36
(1.00) 		0.487
(1.00) 		0.561
(1.00)
'1q gain' versus 'CN_CNMF'

P value = 2.28e-06 (Fisher's exact test), Q value = 0.0015

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
1Q GAIN MUTATED 41 28 44
1Q GAIN WILD-TYPE 11 50 25

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

'1q gain' versus 'METHLYATION_CNMF'

P value = 0.000386 (Fisher's exact test), Q value = 0.24

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 57 52 89
1Q GAIN MUTATED 20 35 58
1Q GAIN WILD-TYPE 37 17 31

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

'5p gain' versus 'CN_CNMF'

P value = 0.000274 (Fisher's exact test), Q value = 0.17

Table S3.  Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
5P GAIN MUTATED 29 17 29
5P GAIN WILD-TYPE 23 61 40

Figure S3.  Get High-res Image Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

'5q gain' versus 'CN_CNMF'

P value = 1.99e-05 (Fisher's exact test), Q value = 0.013

Table S4.  Gene #10: '5q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
5Q GAIN MUTATED 25 9 20
5Q GAIN WILD-TYPE 27 69 49

Figure S4.  Get High-res Image Gene #10: '5q gain' versus Molecular Subtype #1: 'CN_CNMF'

'6p gain' versus 'CN_CNMF'

P value = 2.06e-06 (Fisher's exact test), Q value = 0.0013

Table S5.  Gene #11: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
6P GAIN MUTATED 17 9 34
6P GAIN WILD-TYPE 35 69 35

Figure S5.  Get High-res Image Gene #11: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

'8q gain' versus 'CN_CNMF'

P value = 1.42e-11 (Fisher's exact test), Q value = 9.1e-09

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
8Q GAIN MUTATED 46 23 28
8Q GAIN WILD-TYPE 6 55 41

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

'8q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000294 (Fisher's exact test), Q value = 0.18

Table S7.  Gene #16: '8q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 31 35 69 52
8Q GAIN MUTATED 17 20 41 12
8Q GAIN WILD-TYPE 14 15 28 40

Figure S7.  Get High-res Image Gene #16: '8q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'19p gain' versus 'METHLYATION_CNMF'

P value = 3.57e-05 (Fisher's exact test), Q value = 0.022

Table S8.  Gene #34: '19p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 57 52 89
19P GAIN MUTATED 8 21 8
19P GAIN WILD-TYPE 49 31 81

Figure S8.  Get High-res Image Gene #34: '19p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'19p gain' versus 'MRNASEQ_CNMF'

P value = 1.82e-05 (Chi-square test), Q value = 0.012

Table S9.  Gene #34: '19p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 44 32 51 27 33
19P GAIN MUTATED 20 4 5 3 3
19P GAIN WILD-TYPE 24 28 46 24 30

Figure S9.  Get High-res Image Gene #34: '19p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'19p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 6.04e-05 (Fisher's exact test), Q value = 0.038

Table S10.  Gene #34: '19p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 31 35 69 52
19P GAIN MUTATED 6 3 24 2
19P GAIN WILD-TYPE 25 32 45 50

Figure S10.  Get High-res Image Gene #34: '19p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'19q gain' versus 'METHLYATION_CNMF'

P value = 6.06e-05 (Fisher's exact test), Q value = 0.038

Table S11.  Gene #35: '19q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 57 52 89
19Q GAIN MUTATED 9 23 11
19Q GAIN WILD-TYPE 48 29 78

Figure S11.  Get High-res Image Gene #35: '19q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'19q gain' versus 'MRNASEQ_CNMF'

P value = 1.79e-05 (Chi-square test), Q value = 0.011

Table S12.  Gene #35: '19q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 44 32 51 27 33
19Q GAIN MUTATED 22 6 6 3 4
19Q GAIN WILD-TYPE 22 26 45 24 29

Figure S12.  Get High-res Image Gene #35: '19q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'19q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 5.03e-05 (Fisher's exact test), Q value = 0.031

Table S13.  Gene #35: '19q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 31 35 69 52
19Q GAIN MUTATED 7 4 27 3
19Q GAIN WILD-TYPE 24 31 42 49

Figure S13.  Get High-res Image Gene #35: '19q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'20p gain' versus 'CN_CNMF'

P value = 0.000399 (Fisher's exact test), Q value = 0.24

Table S14.  Gene #36: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
20P GAIN MUTATED 15 12 31
20P GAIN WILD-TYPE 37 66 38

Figure S14.  Get High-res Image Gene #36: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

'20p gain' versus 'MRNASEQ_CNMF'

P value = 0.000297 (Chi-square test), Q value = 0.18

Table S15.  Gene #36: '20p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 44 32 51 27 33
20P GAIN MUTATED 23 13 12 4 4
20P GAIN WILD-TYPE 21 19 39 23 29

Figure S15.  Get High-res Image Gene #36: '20p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'20q gain' versus 'MRNASEQ_CNMF'

P value = 0.000234 (Chi-square test), Q value = 0.14

Table S16.  Gene #37: '20q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 44 32 51 27 33
20Q GAIN MUTATED 24 13 14 4 4
20Q GAIN WILD-TYPE 20 19 37 23 29

Figure S16.  Get High-res Image Gene #37: '20q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'xq gain' versus 'CN_CNMF'

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

Table S17.  Gene #40: 'xq gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
XQ GAIN MUTATED 19 4 10
XQ GAIN WILD-TYPE 33 74 59

Figure S17.  Get High-res Image Gene #40: 'xq gain' versus Molecular Subtype #1: 'CN_CNMF'

'1p loss' versus 'METHLYATION_CNMF'

P value = 0.000278 (Fisher's exact test), Q value = 0.17

Table S18.  Gene #41: '1p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 57 52 89
1P LOSS MUTATED 6 22 16
1P LOSS WILD-TYPE 51 30 73

Figure S18.  Get High-res Image Gene #41: '1p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'1p loss' versus 'MRNASEQ_CNMF'

P value = 5.32e-06 (Chi-square test), Q value = 0.0034

Table S19.  Gene #41: '1p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 44 32 51 27 33
1P LOSS MUTATED 22 3 12 1 4
1P LOSS WILD-TYPE 22 29 39 26 29

Figure S19.  Get High-res Image Gene #41: '1p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'4p loss' versus 'CN_CNMF'

P value = 2.59e-05 (Fisher's exact test), Q value = 0.016

Table S20.  Gene #47: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
4P LOSS MUTATED 13 9 31
4P LOSS WILD-TYPE 39 69 38

Figure S20.  Get High-res Image Gene #47: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

'4q loss' versus 'CN_CNMF'

P value = 1.23e-08 (Fisher's exact test), Q value = 7.9e-06

Table S21.  Gene #48: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
4Q LOSS MUTATED 16 13 44
4Q LOSS WILD-TYPE 36 65 25

Figure S21.  Get High-res Image Gene #48: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

'8p loss' versus 'CN_CNMF'

P value = 4.63e-05 (Fisher's exact test), Q value = 0.029

Table S22.  Gene #55: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
8P LOSS MUTATED 34 23 40
8P LOSS WILD-TYPE 18 55 29

Figure S22.  Get High-res Image Gene #55: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'CN_CNMF'

P value = 0.000333 (Fisher's exact test), Q value = 0.2

Table S23.  Gene #57: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
9P LOSS MUTATED 19 13 32
9P LOSS WILD-TYPE 33 65 37

Figure S23.  Get High-res Image Gene #57: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10q loss' versus 'MRNASEQ_CNMF'

P value = 4.63e-06 (Chi-square test), Q value = 0.0029

Table S24.  Gene #60: '10q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 44 32 51 27 33
10Q LOSS MUTATED 7 19 10 4 3
10Q LOSS WILD-TYPE 37 13 41 23 30

Figure S24.  Get High-res Image Gene #60: '10q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'13q loss' versus 'CN_CNMF'

P value = 7.83e-05 (Fisher's exact test), Q value = 0.049

Table S25.  Gene #65: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
13Q LOSS MUTATED 12 19 38
13Q LOSS WILD-TYPE 40 59 31

Figure S25.  Get High-res Image Gene #65: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

'16p loss' versus 'MRNASEQ_CNMF'

P value = 0.000101 (Chi-square test), Q value = 0.063

Table S26.  Gene #68: '16p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 44 32 51 27 33
16P LOSS MUTATED 24 12 12 7 2
16P LOSS WILD-TYPE 20 20 39 20 31

Figure S26.  Get High-res Image Gene #68: '16p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'16p loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.000388 (Fisher's exact test), Q value = 0.24

Table S27.  Gene #68: '16p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 21 89 84
16P LOSS MUTATED 6 15 37
16P LOSS WILD-TYPE 15 74 47

Figure S27.  Get High-res Image Gene #68: '16p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'16q loss' versus 'CN_CNMF'

P value = 3.33e-05 (Fisher's exact test), Q value = 0.021

Table S28.  Gene #69: '16q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
16Q LOSS MUTATED 15 18 40
16Q LOSS WILD-TYPE 37 60 29

Figure S28.  Get High-res Image Gene #69: '16q loss' versus Molecular Subtype #1: 'CN_CNMF'

'16q loss' versus 'METHLYATION_CNMF'

P value = 5.44e-05 (Fisher's exact test), Q value = 0.034

Table S29.  Gene #69: '16q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 57 52 89
16Q LOSS MUTATED 13 32 27
16Q LOSS WILD-TYPE 44 20 62

Figure S29.  Get High-res Image Gene #69: '16q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'16q loss' versus 'MRNASEQ_CNMF'

P value = 7.16e-05 (Chi-square test), Q value = 0.045

Table S30.  Gene #69: '16q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 44 32 51 27 33
16Q LOSS MUTATED 26 17 17 6 4
16Q LOSS WILD-TYPE 18 15 34 21 29

Figure S30.  Get High-res Image Gene #69: '16q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'17p loss' versus 'CN_CNMF'

P value = 0.000163 (Fisher's exact test), Q value = 0.1

Table S31.  Gene #70: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
17P LOSS MUTATED 19 37 50
17P LOSS WILD-TYPE 33 41 19

Figure S31.  Get High-res Image Gene #70: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

'19p loss' versus 'CN_CNMF'

P value = 0.000269 (Fisher's exact test), Q value = 0.17

Table S32.  Gene #74: '19p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
19P LOSS MUTATED 6 4 20
19P LOSS WILD-TYPE 46 74 49

Figure S32.  Get High-res Image Gene #74: '19p loss' versus Molecular Subtype #1: 'CN_CNMF'

'19q loss' versus 'CN_CNMF'

P value = 0.000108 (Fisher's exact test), Q value = 0.067

Table S33.  Gene #75: '19q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 52 78 69
19Q LOSS MUTATED 4 2 17
19Q LOSS WILD-TYPE 48 76 52

Figure S33.  Get High-res Image Gene #75: '19q loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data
Input

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

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

  • Number of patients = 199

  • 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

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)
Copyright © 2014 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle