Correlation between copy number variations of arm-level result and molecular subtypes
Liver Hepatocellular Carcinoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C15Q4TT2
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/C15Q4TT2
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 208 patients, 37 significant findings detected with P value < 0.05 and Q value < 0.25.

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

  • 10p gain cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

  • 10q gain cnv correlated to 'MRNASEQ_CNMF'.

  • 12p gain cnv correlated to 'MRNASEQ_CHIERARCHICAL' and 'MIRSEQ_MATURE_CNMF'.

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

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

  • 20p gain cnv correlated to 'CN_CNMF'.

  • 20q 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' and 'MRNASEQ_CNMF'.

  • 8q 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',  'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_CHIERARCHICAL', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

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

  • 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, 37 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
16q loss 78 (38%) 130 2e-05
(0.0127) 		6e-05
(0.0376) 		2e-05
(0.0127) 		0.0003
(0.183) 		0.205
(1.00) 		0.00792
(1.00) 		0.00949
(1.00) 		0.00011
(0.0685)
16p loss 63 (30%) 145 0.0049
(1.00) 		0.074
(1.00) 		2e-05
(0.0127) 		0.00027
(0.166) 		0.438
(1.00) 		0.00027
(0.166) 		0.00064
(0.385) 		0.00017
(0.106)
1q gain 118 (57%) 90 1e-05
(0.0064) 		0.00018
(0.111) 		5e-05
(0.0314) 		0.00641
(1.00) 		0.632
(1.00) 		0.0391
(1.00) 		0.572
(1.00) 		0.00311
(1.00)
12p gain 26 (12%) 182 0.479
(1.00) 		0.0728
(1.00) 		0.00417
(1.00) 		0.0003
(0.183) 		0.442
(1.00) 		0.162
(1.00) 		0.0004
(0.242) 		0.121
(1.00)
19p gain 39 (19%) 169 0.0811
(1.00) 		0.00012
(0.0746) 		3e-05
(0.019) 		0.00047
(0.283) 		0.0127
(1.00) 		0.00275
(1.00) 		0.00227
(1.00) 		0.00195
(1.00)
19q gain 46 (22%) 162 0.0324
(1.00) 		0.00033
(0.2) 		0.00022
(0.136) 		0.00105
(0.622) 		0.0377
(1.00) 		0.00947
(1.00) 		0.00313
(1.00) 		0.00073
(0.438)
1p loss 46 (22%) 162 0.00102
(0.606) 		3e-05
(0.019) 		3e-05
(0.019) 		0.0955
(1.00) 		0.0163
(1.00) 		0.0352
(1.00) 		0.0493
(1.00) 		0.0275
(1.00)
4q loss 77 (37%) 131 1e-05
(0.0064) 		0.00328
(1.00) 		0.00039
(0.236) 		0.434
(1.00) 		0.931
(1.00) 		0.0475
(1.00) 		0.116
(1.00) 		0.0853
(1.00)
5p gain 78 (38%) 130 0.00036
(0.218) 		0.0152
(1.00) 		0.884
(1.00) 		0.615
(1.00) 		0.558
(1.00) 		0.92
(1.00) 		0.779
(1.00) 		0.33
(1.00)
5q gain 56 (27%) 152 4e-05
(0.0252) 		0.108
(1.00) 		0.912
(1.00) 		0.855
(1.00) 		0.861
(1.00) 		0.995
(1.00) 		0.985
(1.00) 		0.999
(1.00)
6p gain 66 (32%) 142 2e-05
(0.0127) 		0.00064
(0.385) 		0.00233
(1.00) 		0.105
(1.00) 		0.348
(1.00) 		0.00077
(0.461) 		0.0853
(1.00) 		0.0161
(1.00)
8q gain 101 (49%) 107 1e-05
(0.0064) 		0.271
(1.00) 		0.0247
(1.00) 		0.0464
(1.00) 		0.174
(1.00) 		0.154
(1.00) 		0.484
(1.00) 		0.0761
(1.00)
10p gain 33 (16%) 175 0.109
(1.00) 		0.00334
(1.00) 		0.0236
(1.00) 		0.00023
(0.141) 		0.145
(1.00) 		0.389
(1.00) 		0.00103
(0.611) 		0.044
(1.00)
10q gain 20 (10%) 188 0.00926
(1.00) 		0.00263
(1.00) 		0.00017
(0.106) 		0.0221
(1.00) 		0.0558
(1.00) 		0.0972
(1.00) 		0.012
(1.00) 		0.158
(1.00)
20p gain 63 (30%) 145 8e-05
(0.05) 		0.0364
(1.00) 		0.00435
(1.00) 		0.0172
(1.00) 		0.438
(1.00) 		0.0495
(1.00) 		0.00183
(1.00) 		0.0924
(1.00)
20q gain 65 (31%) 143 5e-05
(0.0314) 		0.0216
(1.00) 		0.00662
(1.00) 		0.0135
(1.00) 		0.384
(1.00) 		0.0647
(1.00) 		0.00742
(1.00) 		0.083
(1.00)
4p loss 55 (26%) 153 0.00027
(0.166) 		0.0681
(1.00) 		0.00419
(1.00) 		0.154
(1.00) 		0.729
(1.00) 		0.0134
(1.00) 		0.111
(1.00) 		0.0993
(1.00)
8q loss 24 (12%) 184 0.00017
(0.106) 		0.838
(1.00) 		0.0946
(1.00) 		0.127
(1.00) 		0.961
(1.00) 		0.902
(1.00) 		0.416
(1.00) 		0.197
(1.00)
10q loss 49 (24%) 159 0.62
(1.00) 		0.79
(1.00) 		4e-05
(0.0252) 		0.242
(1.00) 		0.222
(1.00) 		0.00116
(0.686) 		0.402
(1.00) 		0.0132
(1.00)
13q loss 73 (35%) 135 0.0002
(0.123) 		0.283
(1.00) 		0.248
(1.00) 		0.0217
(1.00) 		0.591
(1.00) 		0.138
(1.00) 		0.231
(1.00) 		0.143
(1.00)
17p loss 110 (53%) 98 0.00031
(0.188) 		0.0866
(1.00) 		0.24
(1.00) 		0.231
(1.00) 		0.0415
(1.00) 		0.003
(1.00) 		0.0168
(1.00) 		0.00531
(1.00)
19p loss 29 (14%) 179 0.00027
(0.166) 		0.0282
(1.00) 		0.173
(1.00) 		0.525
(1.00) 		0.308
(1.00) 		0.00769
(1.00) 		0.989
(1.00) 		0.0972
(1.00)
19q loss 23 (11%) 185 0.0001
(0.0624) 		0.397
(1.00) 		0.304
(1.00) 		0.122
(1.00) 		0.811
(1.00) 		0.00089
(0.53) 		0.37
(1.00) 		0.162
(1.00)
1p gain 37 (18%) 171 0.163
(1.00) 		0.631
(1.00) 		0.318
(1.00) 		0.202
(1.00) 		0.39
(1.00) 		0.0238
(1.00) 		0.642
(1.00) 		0.0969
(1.00)
2p gain 29 (14%) 179 0.275
(1.00) 		0.531
(1.00) 		0.368
(1.00) 		0.167
(1.00) 		0.967
(1.00) 		0.727
(1.00) 		0.434
(1.00) 		0.743
(1.00)
2q gain 26 (12%) 182 0.264
(1.00) 		0.669
(1.00) 		0.144
(1.00) 		0.0831
(1.00) 		0.711
(1.00) 		0.859
(1.00) 		0.303
(1.00) 		0.504
(1.00)
3p gain 22 (11%) 186 0.0258
(1.00) 		0.718
(1.00) 		0.476
(1.00) 		0.64
(1.00) 		0.917
(1.00) 		0.457
(1.00) 		0.361
(1.00) 		0.919
(1.00)
3q gain 24 (12%) 184 0.0202
(1.00) 		0.681
(1.00) 		0.691
(1.00) 		0.455
(1.00) 		0.752
(1.00) 		0.345
(1.00) 		0.242
(1.00) 		0.537
(1.00)
4p gain 18 (9%) 190 0.0282
(1.00) 		0.185
(1.00) 		0.325
(1.00) 		0.234
(1.00) 		0.188
(1.00) 		0.693
(1.00) 		0.523
(1.00) 		0.935
(1.00)
4q gain 6 (3%) 202 0.443
(1.00) 		0.385
(1.00) 		0.525
(1.00) 		0.434
(1.00) 		0.579
(1.00) 		0.689
(1.00) 		0.0123
(1.00) 		0.891
(1.00)
6q gain 40 (19%) 168 0.00402
(1.00) 		0.0549
(1.00) 		0.0523
(1.00) 		0.245
(1.00) 		0.518
(1.00) 		0.0355
(1.00) 		0.078
(1.00) 		0.325
(1.00)
7p gain 63 (30%) 145 0.811
(1.00) 		0.351
(1.00) 		0.663
(1.00) 		0.348
(1.00) 		0.06
(1.00) 		0.441
(1.00) 		0.103
(1.00) 		0.328
(1.00)
7q gain 65 (31%) 143 0.812
(1.00) 		0.0159
(1.00) 		0.898
(1.00) 		0.817
(1.00) 		0.053
(1.00) 		0.225
(1.00) 		0.0331
(1.00) 		0.75
(1.00)
8p gain 41 (20%) 167 0.00542
(1.00) 		0.0735
(1.00) 		0.254
(1.00) 		0.122
(1.00) 		0.149
(1.00) 		0.603
(1.00) 		0.0871
(1.00) 		0.255
(1.00)
9p gain 12 (6%) 196 0.284
(1.00) 		0.491
(1.00) 		0.0443
(1.00) 		0.432
(1.00) 		0.805
(1.00) 		0.733
(1.00) 		0.554
(1.00) 		0.698
(1.00)
9q gain 13 (6%) 195 0.126
(1.00) 		0.863
(1.00) 		0.0436
(1.00) 		0.265
(1.00) 		0.308
(1.00) 		0.746
(1.00) 		0.532
(1.00) 		0.936
(1.00)
11p gain 15 (7%) 193 0.944
(1.00) 		0.353
(1.00) 		0.287
(1.00) 		0.317
(1.00) 		0.264
(1.00) 		0.144
(1.00) 		0.00326
(1.00) 		0.69
(1.00)
11q gain 14 (7%) 194 1
(1.00) 		1
(1.00) 		0.742
(1.00) 		0.751
(1.00) 		0.384
(1.00) 		0.856
(1.00) 		0.195
(1.00) 		1
(1.00)
12q gain 30 (14%) 178 0.428
(1.00) 		0.402
(1.00) 		0.00859
(1.00) 		0.00171
(1.00) 		0.537
(1.00) 		0.205
(1.00) 		0.00368
(1.00) 		0.319
(1.00)
13q gain 14 (7%) 194 0.1
(1.00) 		0.206
(1.00) 		0.033
(1.00) 		0.628
(1.00) 		0.493
(1.00) 		0.0147
(1.00) 		0.0409
(1.00) 		0.533
(1.00)
14q gain 12 (6%) 196 0.261
(1.00) 		0.649
(1.00) 		0.297
(1.00) 		0.178
(1.00) 		0.931
(1.00) 		0.621
(1.00) 		0.742
(1.00) 		0.618
(1.00)
15q gain 18 (9%) 190 1
(1.00) 		0.415
(1.00) 		0.907
(1.00) 		0.621
(1.00) 		0.209
(1.00) 		0.424
(1.00) 		0.817
(1.00) 		0.597
(1.00)
16p gain 19 (9%) 189 0.316
(1.00) 		0.754
(1.00) 		0.692
(1.00) 		0.543
(1.00) 		1
(1.00) 		0.488
(1.00) 		0.331
(1.00) 		0.0764
(1.00)
16q gain 10 (5%) 198 0.846
(1.00) 		0.731
(1.00) 		0.0659
(1.00) 		0.335
(1.00) 		0.259
(1.00) 		0.862
(1.00) 		0.0554
(1.00) 		0.121
(1.00)
17p gain 17 (8%) 191 0.9
(1.00) 		0.0341
(1.00) 		0.435
(1.00) 		0.106
(1.00) 		1
(1.00) 		0.416
(1.00) 		0.82
(1.00) 		0.654
(1.00)
17q gain 52 (25%) 156 0.0125
(1.00) 		0.0606
(1.00) 		0.297
(1.00) 		0.0338
(1.00) 		1
(1.00) 		0.401
(1.00) 		0.457
(1.00) 		0.67
(1.00)
18p gain 17 (8%) 191 0.192
(1.00) 		0.0724
(1.00) 		0.00254
(1.00) 		0.0012
(0.708) 		0.174
(1.00) 		0.0343
(1.00) 		0.018
(1.00) 		0.0578
(1.00)
18q gain 15 (7%) 193 0.489
(1.00) 		0.062
(1.00) 		0.00088
(0.525) 		0.00088
(0.525) 		0.402
(1.00) 		0.0671
(1.00) 		0.0313
(1.00) 		0.114
(1.00)
21q gain 17 (8%) 191 0.143
(1.00) 		0.724
(1.00) 		0.592
(1.00) 		0.322
(1.00) 		0.948
(1.00) 		0.33
(1.00) 		0.247
(1.00) 		0.524
(1.00)
22q gain 28 (13%) 180 0.0555
(1.00) 		0.0255
(1.00) 		0.00436
(1.00) 		0.00658
(1.00) 		0.103
(1.00) 		0.356
(1.00) 		0.0979
(1.00) 		0.406
(1.00)
xq gain 36 (17%) 172 0.0036
(1.00) 		0.0267
(1.00) 		0.703
(1.00) 		0.373
(1.00) 		0.103
(1.00) 		0.284
(1.00) 		0.207
(1.00) 		0.13
(1.00)
1q loss 14 (7%) 194 0.534
(1.00) 		0.299
(1.00) 		0.211
(1.00) 		0.384
(1.00) 		0.359
(1.00) 		0.325
(1.00) 		0.335
(1.00) 		0.841
(1.00)
2p loss 20 (10%) 188 0.062
(1.00) 		0.912
(1.00) 		0.294
(1.00) 		0.559
(1.00) 		0.101
(1.00) 		0.38
(1.00) 		0.201
(1.00) 		0.746
(1.00)
2q loss 22 (11%) 186 0.0182
(1.00) 		0.773
(1.00) 		0.304
(1.00) 		0.508
(1.00) 		0.0266
(1.00) 		0.7
(1.00) 		0.706
(1.00) 		0.723
(1.00)
3p loss 30 (14%) 178 0.214
(1.00) 		0.161
(1.00) 		0.0192
(1.00) 		0.00641
(1.00) 		0.264
(1.00) 		0.193
(1.00) 		0.0261
(1.00) 		0.00323
(1.00)
3q loss 19 (9%) 189 1
(1.00) 		0.901
(1.00) 		0.286
(1.00) 		0.196
(1.00) 		0.139
(1.00) 		0.419
(1.00) 		0.0706
(1.00) 		0.143
(1.00)
5p loss 15 (7%) 193 0.554
(1.00) 		0.94
(1.00) 		0.473
(1.00) 		0.885
(1.00) 		0.661
(1.00) 		0.471
(1.00) 		0.0195
(1.00) 		0.663
(1.00)
5q loss 23 (11%) 185 0.215
(1.00) 		0.541
(1.00) 		0.254
(1.00) 		0.118
(1.00) 		0.423
(1.00) 		0.126
(1.00) 		0.203
(1.00) 		0.445
(1.00)
6p loss 21 (10%) 187 0.917
(1.00) 		0.838
(1.00) 		0.215
(1.00) 		1
(1.00) 		0.0301
(1.00) 		0.898
(1.00) 		0.416
(1.00) 		0.282
(1.00)
6q loss 56 (27%) 152 0.797
(1.00) 		0.616
(1.00) 		0.565
(1.00) 		0.785
(1.00) 		0.17
(1.00) 		0.228
(1.00) 		0.91
(1.00) 		0.326
(1.00)
7p loss 12 (6%) 196 0.519
(1.00) 		0.326
(1.00) 		0.00395
(1.00) 		0.631
(1.00) 		0.866
(1.00) 		0.799
(1.00) 		0.755
(1.00) 		0.355
(1.00)
7q loss 16 (8%) 192 0.717
(1.00) 		0.206
(1.00) 		0.01
(1.00) 		0.516
(1.00) 		0.636
(1.00) 		0.326
(1.00) 		0.799
(1.00) 		0.211
(1.00)
8p loss 101 (49%) 107 0.00852
(1.00) 		0.0463
(1.00) 		0.193
(1.00) 		0.883
(1.00) 		0.229
(1.00) 		0.431
(1.00) 		0.0554
(1.00) 		0.132
(1.00)
9p loss 66 (32%) 142 0.00266
(1.00) 		0.154
(1.00) 		0.624
(1.00) 		0.804
(1.00) 		0.579
(1.00) 		0.541
(1.00) 		0.888
(1.00) 		0.632
(1.00)
9q loss 64 (31%) 144 0.0343
(1.00) 		0.0428
(1.00) 		0.385
(1.00) 		0.317
(1.00) 		0.774
(1.00) 		0.314
(1.00) 		0.815
(1.00) 		0.513
(1.00)
10p loss 29 (14%) 179 0.792
(1.00) 		0.457
(1.00) 		0.0926
(1.00) 		0.342
(1.00) 		0.165
(1.00) 		0.0288
(1.00) 		0.386
(1.00) 		0.0818
(1.00)
11p loss 40 (19%) 168 0.217
(1.00) 		0.461
(1.00) 		0.232
(1.00) 		0.169
(1.00) 		0.542
(1.00) 		0.194
(1.00) 		0.243
(1.00) 		0.166
(1.00)
11q loss 43 (21%) 165 0.209
(1.00) 		0.151
(1.00) 		0.463
(1.00) 		0.309
(1.00) 		0.335
(1.00) 		0.387
(1.00) 		0.37
(1.00) 		0.444
(1.00)
12p loss 40 (19%) 168 0.0432
(1.00) 		0.0729
(1.00) 		0.0955
(1.00) 		0.625
(1.00) 		0.226
(1.00) 		0.219
(1.00) 		0.242
(1.00) 		0.176
(1.00)
12q loss 22 (11%) 186 0.187
(1.00) 		0.532
(1.00) 		0.601
(1.00) 		0.765
(1.00) 		0.486
(1.00) 		0.88
(1.00) 		0.424
(1.00) 		0.87
(1.00)
14q loss 64 (31%) 144 0.0012
(0.708) 		0.367
(1.00) 		0.0262
(1.00) 		0.00354
(1.00) 		0.276
(1.00) 		0.232
(1.00) 		0.1
(1.00) 		0.142
(1.00)
15q loss 45 (22%) 163 0.0175
(1.00) 		0.14
(1.00) 		0.0537
(1.00) 		0.0334
(1.00) 		0.824
(1.00) 		0.0199
(1.00) 		0.00363
(1.00) 		0.0825
(1.00)
17q loss 32 (15%) 176 0.104
(1.00) 		0.602
(1.00) 		0.409
(1.00) 		0.847
(1.00) 		0.68
(1.00) 		0.835
(1.00) 		0.549
(1.00) 		0.541
(1.00)
18p loss 43 (21%) 165 0.0294
(1.00) 		0.00295
(1.00) 		0.7
(1.00) 		0.33
(1.00) 		0.724
(1.00) 		0.351
(1.00) 		0.493
(1.00) 		0.194
(1.00)
18q loss 46 (22%) 162 0.00078
(0.466) 		0.00378
(1.00) 		0.733
(1.00) 		0.272
(1.00) 		0.423
(1.00) 		0.177
(1.00) 		0.0735
(1.00) 		0.0373
(1.00)
20p loss 13 (6%) 195 0.412
(1.00) 		0.57
(1.00) 		0.65
(1.00) 		0.0519
(1.00) 		0.579
(1.00) 		0.732
(1.00) 		0.181
(1.00) 		0.167
(1.00)
20q loss 9 (4%) 199 0.692
(1.00) 		0.621
(1.00) 		0.565
(1.00) 		0.0659
(1.00) 		0.576
(1.00) 		0.949
(1.00) 		0.284
(1.00) 		0.382
(1.00)
21q loss 59 (28%) 149 0.0207
(1.00) 		0.881
(1.00) 		0.018
(1.00) 		0.334
(1.00) 		0.33
(1.00) 		0.00142
(0.835) 		0.0217
(1.00) 		0.0815
(1.00)
22q loss 51 (25%) 157 0.69
(1.00) 		0.64
(1.00) 		0.533
(1.00) 		0.342
(1.00) 		0.399
(1.00) 		0.218
(1.00) 		0.514
(1.00) 		0.107
(1.00)
xq loss 36 (17%) 172 0.00169
(0.992) 		0.0509
(1.00) 		0.84
(1.00) 		0.81
(1.00) 		0.673
(1.00) 		0.934
(1.00) 		0.424
(1.00) 		0.929
(1.00)
'1q gain' versus 'CN_CNMF'

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

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
1Q GAIN MUTATED 37 29 52
1Q GAIN WILD-TYPE 14 53 23

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

'1q gain' versus 'METHLYATION_CNMF'

P value = 0.00018 (Fisher's exact test), Q value = 0.11

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 59 50
1Q GAIN MUTATED 57 41 16
1Q GAIN WILD-TYPE 33 18 34

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

'1q gain' versus 'MRNASEQ_CNMF'

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

Table S3.  Gene #2: '1q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 39 31 57 38 40
1Q GAIN MUTATED 18 19 20 30 28
1Q GAIN WILD-TYPE 21 12 37 8 12

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

'5p gain' versus 'CN_CNMF'

P value = 0.00036 (Fisher's exact test), Q value = 0.22

Table S4.  Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
5P GAIN MUTATED 28 18 32
5P GAIN WILD-TYPE 23 64 43

Figure S4.  Get High-res Image Gene #9: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

'5q gain' versus 'CN_CNMF'

P value = 4e-05 (Fisher's exact test), Q value = 0.025

Table S5.  Gene #10: '5q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
5Q GAIN MUTATED 25 11 20
5Q GAIN WILD-TYPE 26 71 55

Figure S5.  Get High-res Image Gene #10: '5q gain' versus Molecular Subtype #1: 'CN_CNMF'

'6p gain' versus 'CN_CNMF'

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

Table S6.  Gene #11: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
6P GAIN MUTATED 16 12 38
6P GAIN WILD-TYPE 35 70 37

Figure S6.  Get High-res Image Gene #11: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

'8q gain' versus 'CN_CNMF'

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

Table S7.  Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
8Q GAIN MUTATED 46 24 31
8Q GAIN WILD-TYPE 5 58 44

Figure S7.  Get High-res Image Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

'10p gain' versus 'MRNASEQ_CHIERARCHICAL'

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

Table S8.  Gene #19: '10p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 82 84 39
10P GAIN MUTATED 22 4 7
10P GAIN WILD-TYPE 60 80 32

Figure S8.  Get High-res Image Gene #19: '10p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'10q gain' versus 'MRNASEQ_CNMF'

P value = 0.00017 (Fisher's exact test), Q value = 0.11

Table S9.  Gene #20: '10q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 39 31 57 38 40
10Q GAIN MUTATED 1 0 3 11 5
10Q GAIN WILD-TYPE 38 31 54 27 35

Figure S9.  Get High-res Image Gene #20: '10q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'12p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3e-04 (Fisher's exact test), Q value = 0.18

Table S10.  Gene #23: '12p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 82 84 39
12P GAIN MUTATED 20 4 2
12P GAIN WILD-TYPE 62 80 37

Figure S10.  Get High-res Image Gene #23: '12p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'12p gain' versus 'MIRSEQ_MATURE_CNMF'

P value = 4e-04 (Fisher's exact test), Q value = 0.24

Table S11.  Gene #23: '12p gain' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 28 35 43 60 37
12P GAIN MUTATED 6 1 3 4 12
12P GAIN WILD-TYPE 22 34 40 56 25

Figure S11.  Get High-res Image Gene #23: '12p gain' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'19p gain' versus 'METHLYATION_CNMF'

P value = 0.00012 (Fisher's exact test), Q value = 0.075

Table S12.  Gene #34: '19p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 59 50
19P GAIN MUTATED 9 22 7
19P GAIN WILD-TYPE 81 37 43

Figure S12.  Get High-res Image Gene #34: '19p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'19p gain' versus 'MRNASEQ_CNMF'

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

Table S13.  Gene #34: '19p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 39 31 57 38 40
19P GAIN MUTATED 8 3 7 18 2
19P GAIN WILD-TYPE 31 28 50 20 38

Figure S13.  Get High-res Image Gene #34: '19p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'19q gain' versus 'METHLYATION_CNMF'

P value = 0.00033 (Fisher's exact test), Q value = 0.2

Table S14.  Gene #35: '19q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 59 50
19Q GAIN MUTATED 12 24 8
19Q GAIN WILD-TYPE 78 35 42

Figure S14.  Get High-res Image Gene #35: '19q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'19q gain' versus 'MRNASEQ_CNMF'

P value = 0.00022 (Fisher's exact test), Q value = 0.14

Table S15.  Gene #35: '19q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 39 31 57 38 40
19Q GAIN MUTATED 9 5 8 19 4
19Q GAIN WILD-TYPE 30 26 49 19 36

Figure S15.  Get High-res Image Gene #35: '19q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'20p gain' versus 'CN_CNMF'

P value = 8e-05 (Fisher's exact test), Q value = 0.05

Table S16.  Gene #36: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
20P GAIN MUTATED 16 12 35
20P GAIN WILD-TYPE 35 70 40

Figure S16.  Get High-res Image Gene #36: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

'20q gain' versus 'CN_CNMF'

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

Table S17.  Gene #37: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
20Q GAIN MUTATED 17 12 36
20Q GAIN WILD-TYPE 34 70 39

Figure S17.  Get High-res Image Gene #37: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

'1p loss' versus 'METHLYATION_CNMF'

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

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 59 50
1P LOSS MUTATED 16 25 3
1P LOSS WILD-TYPE 74 34 47

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

'1p loss' versus 'MRNASEQ_CNMF'

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

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

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 39 31 57 38 40
1P LOSS MUTATED 6 2 12 20 5
1P LOSS WILD-TYPE 33 29 45 18 35

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

'4p loss' versus 'CN_CNMF'

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

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
4P LOSS MUTATED 13 11 31
4P LOSS WILD-TYPE 38 71 44

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

'4q loss' versus 'CN_CNMF'

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

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
4Q LOSS MUTATED 17 12 48
4Q LOSS WILD-TYPE 34 70 27

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

'4q loss' versus 'MRNASEQ_CNMF'

P value = 0.00039 (Fisher's exact test), Q value = 0.24

Table S22.  Gene #48: '4q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 39 31 57 38 40
4Q LOSS MUTATED 7 12 21 25 12
4Q LOSS WILD-TYPE 32 19 36 13 28

Figure S22.  Get High-res Image Gene #48: '4q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'8q loss' versus 'CN_CNMF'

P value = 0.00017 (Fisher's exact test), Q value = 0.11

Table S23.  Gene #56: '8q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
8Q LOSS MUTATED 2 4 18
8Q LOSS WILD-TYPE 49 78 57

Figure S23.  Get High-res Image Gene #56: '8q loss' versus Molecular Subtype #1: 'CN_CNMF'

'10q loss' versus 'MRNASEQ_CNMF'

P value = 4e-05 (Fisher's exact test), Q value = 0.025

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

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 39 31 57 38 40
10Q LOSS MUTATED 11 17 13 2 6
10Q LOSS WILD-TYPE 28 14 44 36 34

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

'13q loss' versus 'CN_CNMF'

P value = 2e-04 (Fisher's exact test), Q value = 0.12

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
13Q LOSS MUTATED 12 21 40
13Q LOSS WILD-TYPE 39 61 35

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

'16p loss' versus 'MRNASEQ_CNMF'

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

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

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 39 31 57 38 40
16P LOSS MUTATED 10 10 14 24 5
16P LOSS WILD-TYPE 29 21 43 14 35

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

'16p loss' versus 'MRNASEQ_CHIERARCHICAL'

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

Table S27.  Gene #68: '16p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 82 84 39
16P LOSS MUTATED 38 20 5
16P LOSS WILD-TYPE 44 64 34

Figure S27.  Get High-res Image Gene #68: '16p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'16p loss' versus 'MIRSEQ_CHIERARCHICAL'

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

Table S28.  Gene #68: '16p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 26 53 74 26 24
16P LOSS MUTATED 8 10 30 13 1
16P LOSS WILD-TYPE 18 43 44 13 23

Figure S28.  Get High-res Image Gene #68: '16p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'16p loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.00017 (Fisher's exact test), Q value = 0.11

Table S29.  Gene #68: '16p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 25 44 36 74 24
16P LOSS MUTATED 8 6 19 27 2
16P LOSS WILD-TYPE 17 38 17 47 22

Figure S29.  Get High-res Image Gene #68: '16p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'16q loss' versus 'CN_CNMF'

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

Table S30.  Gene #69: '16q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
16Q LOSS MUTATED 17 18 43
16Q LOSS WILD-TYPE 34 64 32

Figure S30.  Get High-res Image Gene #69: '16q loss' versus Molecular Subtype #1: 'CN_CNMF'

'16q loss' versus 'METHLYATION_CNMF'

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

Table S31.  Gene #69: '16q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 59 50
16Q LOSS MUTATED 28 35 10
16Q LOSS WILD-TYPE 62 24 40

Figure S31.  Get High-res Image Gene #69: '16q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'16q loss' versus 'MRNASEQ_CNMF'

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

Table S32.  Gene #69: '16q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 39 31 57 38 40
16Q LOSS MUTATED 9 15 20 27 7
16Q LOSS WILD-TYPE 30 16 37 11 33

Figure S32.  Get High-res Image Gene #69: '16q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'16q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3e-04 (Fisher's exact test), Q value = 0.18

Table S33.  Gene #69: '16q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 82 84 39
16Q LOSS MUTATED 44 27 7
16Q LOSS WILD-TYPE 38 57 32

Figure S33.  Get High-res Image Gene #69: '16q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'16q loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.00011 (Fisher's exact test), Q value = 0.069

Table S34.  Gene #69: '16q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 25 44 36 74 24
16Q LOSS MUTATED 8 12 23 32 2
16Q LOSS WILD-TYPE 17 32 13 42 22

Figure S34.  Get High-res Image Gene #69: '16q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'17p loss' versus 'CN_CNMF'

P value = 0.00031 (Fisher's exact test), Q value = 0.19

Table S35.  Gene #70: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
17P LOSS MUTATED 19 38 53
17P LOSS WILD-TYPE 32 44 22

Figure S35.  Get High-res Image Gene #70: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

'19p loss' versus 'CN_CNMF'

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

Table S36.  Gene #74: '19p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
19P LOSS MUTATED 7 3 19
19P LOSS WILD-TYPE 44 79 56

Figure S36.  Get High-res Image Gene #74: '19p loss' versus Molecular Subtype #1: 'CN_CNMF'

'19q loss' versus 'CN_CNMF'

P value = 1e-04 (Fisher's exact test), Q value = 0.062

Table S37.  Gene #75: '19q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 51 82 75
19Q LOSS MUTATED 6 1 16
19Q LOSS WILD-TYPE 45 81 59

Figure S37.  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 = 208

  • 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)
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