Correlation between copy number variations of arm-level result and selected clinical features
Liver Hepatocellular Carcinoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C10G3JK8
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.

Summary

Testing the association between copy number variation 82 arm-level events and 12 clinical features across 370 patients, 31 significant findings detected with Q value < 0.25.

  • 2p gain cnv correlated to 'GENDER'.

  • 2q gain cnv correlated to 'GENDER'.

  • 6q gain cnv correlated to 'ETHNICITY'.

  • 8q gain cnv correlated to 'GENDER'.

  • 12p gain cnv correlated to 'HISTOLOGICAL_TYPE'.

  • 16q gain cnv correlated to 'HISTOLOGICAL_TYPE'.

  • 20p gain cnv correlated to 'Time to Death'.

  • 22q gain cnv correlated to 'PATHOLOGY_T_STAGE'.

  • 3p loss cnv correlated to 'PATHOLOGIC_STAGE',  'PATHOLOGY_T_STAGE', and 'HISTOLOGICAL_TYPE'.

  • 4q loss cnv correlated to 'YEARS_TO_BIRTH' and 'RACE'.

  • 6q loss cnv correlated to 'YEARS_TO_BIRTH'.

  • 7q loss cnv correlated to 'Time to Death'.

  • 10q loss cnv correlated to 'RACE'.

  • 12p loss cnv correlated to 'PATHOLOGIC_STAGE' and 'PATHOLOGY_N_STAGE'.

  • 12q loss cnv correlated to 'PATHOLOGIC_STAGE'.

  • 15q loss cnv correlated to 'Time to Death' and 'PATHOLOGY_T_STAGE'.

  • 16p loss cnv correlated to 'RACE'.

  • 16q loss cnv correlated to 'YEARS_TO_BIRTH' and 'RACE'.

  • 17p loss cnv correlated to 'PATHOLOGIC_STAGE'.

  • 17q loss cnv correlated to 'PATHOLOGIC_STAGE' and 'HISTOLOGICAL_TYPE'.

  • 18p loss cnv correlated to 'HISTOLOGICAL_TYPE'.

  • 22q loss cnv correlated to 'HISTOLOGICAL_TYPE' and 'RACE'.

  • xp loss cnv correlated to 'GENDER'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 82 arm-level events and 12 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 31 significant findings detected.

Clinical
Features
Time
to
Death
YEARS
TO
BIRTH
PATHOLOGIC
STAGE
PATHOLOGY
T
STAGE
PATHOLOGY
N
STAGE
PATHOLOGY
M
STAGE
GENDER RADIATION
THERAPY
HISTOLOGICAL
TYPE
RESIDUAL
TUMOR
RACE ETHNICITY
nCNV (%) nWild-Type logrank test Wilcoxon-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 Fisher's exact test Fisher's exact test Fisher's exact test
3p loss 52 (14%) 318 0.759
(1.00)
0.187
(0.685)
0.00239
(0.181)
0.00383
(0.192)
0.0523
(0.468)
0.447
(0.873)
0.199
(0.7)
0.618
(0.968)
0.00082
(0.115)
0.742
(1.00)
0.951
(1.00)
0.708
(1.00)
4q loss 146 (39%) 224 0.172
(0.669)
0.00228
(0.181)
0.754
(1.00)
0.66
(0.995)
1
(1.00)
0.319
(0.77)
0.0883
(0.554)
1
(1.00)
0.514
(0.926)
0.281
(0.75)
0.00065
(0.107)
0.442
(0.868)
12p loss 66 (18%) 304 0.422
(0.858)
0.587
(0.963)
0.00731
(0.244)
0.324
(0.77)
0.00507
(0.192)
0.168
(0.665)
0.884
(1.00)
0.367
(0.814)
0.786
(1.00)
0.122
(0.595)
0.683
(1.00)
1
(1.00)
15q loss 67 (18%) 303 0.00477
(0.192)
0.849
(1.00)
0.0257
(0.395)
0.00647
(0.236)
0.087
(0.554)
0.583
(0.96)
1
(1.00)
1
(1.00)
0.789
(1.00)
0.663
(0.995)
0.109
(0.573)
1
(1.00)
16q loss 145 (39%) 225 0.0889
(0.554)
0.000393
(0.0964)
0.255
(0.741)
0.127
(0.604)
1
(1.00)
1
(1.00)
0.304
(0.762)
0.491
(0.907)
0.517
(0.929)
0.56
(0.955)
2e-05
(0.0197)
0.442
(0.868)
17q loss 40 (11%) 330 0.0725
(0.528)
0.508
(0.92)
0.00768
(0.244)
0.178
(0.674)
0.0278
(0.402)
0.388
(0.828)
0.281
(0.75)
0.606
(0.963)
0.00295
(0.189)
0.925
(1.00)
0.0288
(0.402)
0.667
(0.996)
22q loss 70 (19%) 300 0.424
(0.858)
0.173
(0.669)
0.0576
(0.495)
0.0232
(0.387)
0.448
(0.873)
1
(1.00)
0.32
(0.77)
0.669
(0.996)
0.00747
(0.244)
0.0229
(0.387)
0.00406
(0.192)
0.048
(0.468)
2p gain 43 (12%) 327 0.186
(0.683)
0.051
(0.468)
0.0717
(0.528)
0.133
(0.613)
0.0392
(0.438)
0.0662
(0.509)
4.32e-05
(0.0213)
0.606
(0.963)
0.328
(0.773)
0.119
(0.594)
0.154
(0.652)
1
(1.00)
2q gain 40 (11%) 330 0.255
(0.741)
0.409
(0.843)
0.0951
(0.565)
0.141
(0.633)
0.33
(0.773)
0.0662
(0.509)
0.00049
(0.0964)
0.605
(0.963)
0.295
(0.762)
0.277
(0.75)
0.425
(0.858)
0.408
(0.843)
6q gain 67 (18%) 303 0.605
(0.963)
0.302
(0.762)
0.0408
(0.444)
0.0816
(0.55)
1
(1.00)
0.0186
(0.359)
0.386
(0.826)
1
(1.00)
1
(1.00)
0.135
(0.617)
0.232
(0.73)
0.00308
(0.189)
8q gain 184 (50%) 186 0.983
(1.00)
0.22
(0.72)
0.0728
(0.528)
0.226
(0.726)
0.108
(0.573)
1
(1.00)
0.0012
(0.132)
0.101
(0.565)
0.52
(0.932)
0.885
(1.00)
0.0373
(0.422)
0.62
(0.969)
12p gain 40 (11%) 330 0.0895
(0.554)
0.536
(0.938)
0.54
(0.942)
0.158
(0.652)
1
(1.00)
1
(1.00)
0.473
(0.893)
0.605
(0.963)
0.00506
(0.192)
0.79
(1.00)
0.308
(0.762)
1
(1.00)
16q gain 17 (5%) 353 0.574
(0.96)
0.00815
(0.251)
0.0307
(0.403)
0.129
(0.604)
0.155
(0.652)
1
(1.00)
1
(1.00)
0.349
(0.796)
0.00187
(0.18)
0.432
(0.859)
0.359
(0.806)
0.129
(0.604)
20p gain 107 (29%) 263 0.0071
(0.244)
0.0344
(0.419)
0.235
(0.732)
0.178
(0.674)
1
(1.00)
0.0878
(0.554)
0.268
(0.747)
1
(1.00)
0.859
(1.00)
0.287
(0.753)
0.925
(1.00)
0.781
(1.00)
22q gain 48 (13%) 322 0.593
(0.963)
0.841
(1.00)
0.03
(0.402)
0.00466
(0.192)
0.321
(0.77)
1
(1.00)
0.246
(0.741)
0.613
(0.963)
0.493
(0.907)
0.313
(0.762)
0.922
(1.00)
0.708
(1.00)
6q loss 94 (25%) 276 0.391
(0.83)
0.00271
(0.189)
0.391
(0.83)
0.886
(1.00)
0.167
(0.664)
1
(1.00)
0.0541
(0.476)
0.461
(0.881)
0.401
(0.836)
0.823
(1.00)
0.644
(0.984)
0.77
(1.00)
7q loss 21 (6%) 349 0.00113
(0.132)
0.271
(0.747)
0.955
(1.00)
0.788
(1.00)
1
(1.00)
1
(1.00)
0.0521
(0.468)
0.418
(0.854)
1
(1.00)
0.19
(0.687)
0.0924
(0.561)
1
(1.00)
10q loss 78 (21%) 292 0.11
(0.573)
0.959
(1.00)
0.737
(1.00)
0.144
(0.638)
1
(1.00)
0.579
(0.96)
0.682
(1.00)
0.69
(1.00)
0.0423
(0.448)
0.486
(0.905)
0.00022
(0.0722)
1
(1.00)
12q loss 36 (10%) 334 0.209
(0.708)
0.1
(0.565)
0.00424
(0.192)
0.477
(0.897)
0.265
(0.746)
0.0584
(0.495)
1
(1.00)
1
(1.00)
0.253
(0.741)
0.156
(0.652)
0.313
(0.762)
0.66
(0.995)
16p loss 108 (29%) 262 0.034
(0.419)
0.0108
(0.279)
0.524
(0.933)
0.412
(0.847)
1
(1.00)
0.601
(0.963)
0.272
(0.747)
0.0642
(0.509)
0.858
(1.00)
0.0766
(0.535)
0.00422
(0.192)
0.577
(0.96)
17p loss 185 (50%) 185 0.0108
(0.279)
0.552
(0.951)
0.00358
(0.192)
0.015
(0.315)
0.247
(0.741)
0.623
(0.969)
0.911
(1.00)
1
(1.00)
0.46
(0.881)
0.307
(0.762)
0.663
(0.995)
0.32
(0.77)
18p loss 74 (20%) 296 0.739
(1.00)
0.467
(0.885)
0.341
(0.786)
0.808
(1.00)
0.113
(0.578)
1
(1.00)
0.163
(0.657)
0.381
(0.821)
0.00201
(0.18)
0.92
(1.00)
0.832
(1.00)
1
(1.00)
xp loss 95 (26%) 275 0.304
(0.762)
0.126
(0.601)
0.961
(1.00)
0.571
(0.96)
1
(1.00)
1
(1.00)
0.00477
(0.192)
0.701
(1.00)
0.405
(0.842)
0.521
(0.932)
0.429
(0.859)
0.77
(1.00)
1p gain 62 (17%) 308 0.814
(1.00)
0.0302
(0.402)
0.688
(1.00)
0.265
(0.746)
1
(1.00)
1
(1.00)
0.0517
(0.468)
1
(1.00)
1
(1.00)
0.397
(0.835)
0.14
(0.63)
0.0846
(0.554)
1q gain 226 (61%) 144 0.841
(1.00)
0.64
(0.983)
0.258
(0.741)
0.36
(0.806)
0.0578
(0.495)
0.301
(0.762)
0.494
(0.907)
0.737
(1.00)
0.0544
(0.476)
0.813
(1.00)
0.136
(0.618)
0.431
(0.859)
3p gain 35 (9%) 335 0.221
(0.72)
0.592
(0.963)
0.654
(0.992)
0.809
(1.00)
0.246
(0.741)
0.346
(0.791)
0.13
(0.605)
1
(1.00)
1
(1.00)
0.236
(0.732)
0.764
(1.00)
0.66
(0.995)
3q gain 38 (10%) 332 0.0402
(0.444)
0.677
(1.00)
0.668
(0.996)
0.775
(1.00)
0.265
(0.746)
0.356
(0.803)
0.145
(0.638)
0.607
(0.963)
0.665
(0.996)
0.27
(0.747)
0.645
(0.984)
0.231
(0.73)
4p gain 27 (7%) 343 0.108
(0.573)
0.698
(1.00)
0.663
(0.995)
0.641
(0.983)
1
(1.00)
1
(1.00)
0.197
(0.698)
0.494
(0.907)
1
(1.00)
0.886
(1.00)
1
(1.00)
1
(1.00)
4q gain 7 (2%) 363 0.916
(1.00)
0.253
(0.741)
0.757
(1.00)
0.685
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.176
(0.674)
0.582
(0.96)
0.281
(0.75)
5p gain 134 (36%) 236 0.0458
(0.459)
0.118
(0.594)
0.389
(0.829)
0.1
(0.565)
0.553
(0.951)
1
(1.00)
0.729
(1.00)
0.299
(0.762)
0.523
(0.933)
0.853
(1.00)
0.738
(1.00)
0.795
(1.00)
5q gain 110 (30%) 260 0.125
(0.601)
0.0419
(0.448)
0.941
(1.00)
0.516
(0.928)
0.562
(0.955)
1
(1.00)
0.0516
(0.468)
0.0248
(0.394)
0.858
(1.00)
0.71
(1.00)
0.875
(1.00)
1
(1.00)
6p gain 116 (31%) 254 0.366
(0.814)
0.434
(0.86)
0.195
(0.696)
0.0964
(0.565)
0.554
(0.951)
0.0968
(0.565)
0.4
(0.836)
0.282
(0.75)
0.547
(0.946)
0.635
(0.981)
0.334
(0.774)
0.0509
(0.468)
7p gain 109 (29%) 261 0.766
(1.00)
0.0471
(0.468)
0.645
(0.984)
0.701
(1.00)
0.19
(0.687)
1
(1.00)
0.328
(0.773)
1
(1.00)
0.533
(0.938)
0.893
(1.00)
0.152
(0.651)
0.577
(0.96)
7q gain 110 (30%) 260 0.563
(0.955)
0.0217
(0.382)
0.465
(0.885)
0.375
(0.82)
0.2
(0.7)
1
(1.00)
1
(1.00)
0.461
(0.881)
0.536
(0.938)
1
(1.00)
0.0611
(0.499)
0.269
(0.747)
8p gain 73 (20%) 297 0.324
(0.77)
0.15
(0.651)
0.941
(1.00)
0.929
(1.00)
1
(1.00)
1
(1.00)
0.162
(0.657)
0.0672
(0.509)
0.807
(1.00)
0.163
(0.657)
0.203
(0.705)
1
(1.00)
9p gain 19 (5%) 351 0.849
(1.00)
0.227
(0.726)
0.0673
(0.509)
0.144
(0.638)
1
(1.00)
0.218
(0.719)
0.323
(0.77)
1
(1.00)
0.0867
(0.554)
0.184
(0.68)
0.282
(0.75)
0.556
(0.952)
9q gain 19 (5%) 351 0.96
(1.00)
0.328
(0.773)
0.151
(0.651)
0.209
(0.708)
1
(1.00)
0.205
(0.707)
0.0733
(0.528)
1
(1.00)
0.414
(0.848)
0.183
(0.68)
0.87
(1.00)
0.577
(0.96)
10p gain 58 (16%) 312 0.185
(0.682)
0.021
(0.375)
0.243
(0.741)
0.161
(0.657)
1
(1.00)
0.12
(0.594)
1
(1.00)
0.635
(0.981)
0.584
(0.96)
0.853
(1.00)
0.562
(0.955)
0.307
(0.762)
10q gain 36 (10%) 334 0.61
(0.963)
0.207
(0.707)
0.108
(0.573)
0.151
(0.651)
1
(1.00)
0.0547
(0.476)
0.576
(0.96)
0.574
(0.96)
0.642
(0.983)
0.916
(1.00)
1
(1.00)
0.206
(0.707)
11p gain 18 (5%) 352 0.508
(0.92)
0.872
(1.00)
0.349
(0.796)
0.324
(0.77)
1
(1.00)
0.205
(0.707)
0.605
(0.963)
1
(1.00)
1
(1.00)
0.0238
(0.39)
0.731
(1.00)
1
(1.00)
11q gain 20 (5%) 350 0.426
(0.858)
0.855
(1.00)
0.293
(0.76)
0.209
(0.708)
1
(1.00)
0.242
(0.741)
0.462
(0.882)
1
(1.00)
1
(1.00)
0.0345
(0.419)
0.759
(1.00)
1
(1.00)
12q gain 47 (13%) 323 0.841
(1.00)
0.526
(0.933)
0.102
(0.566)
0.101
(0.565)
0.357
(0.803)
1
(1.00)
0.319
(0.77)
0.608
(0.963)
0.0888
(0.554)
0.4
(0.836)
0.448
(0.873)
1
(1.00)
13q gain 23 (6%) 347 0.212
(0.713)
0.908
(1.00)
0.0989
(0.565)
0.623
(0.969)
0.207
(0.707)
0.242
(0.741)
0.107
(0.573)
0.449
(0.873)
1
(1.00)
0.211
(0.71)
0.534
(0.938)
0.247
(0.741)
14q gain 22 (6%) 348 0.481
(0.902)
0.393
(0.831)
0.31
(0.762)
0.555
(0.951)
1
(1.00)
0.18
(0.679)
0.353
(0.799)
1
(1.00)
0.114
(0.579)
0.0884
(0.554)
0.183
(0.68)
1
(1.00)
15q gain 33 (9%) 337 0.545
(0.944)
0.941
(1.00)
0.738
(1.00)
0.362
(0.808)
1
(1.00)
1
(1.00)
0.696
(1.00)
1
(1.00)
0.34
(0.786)
0.91
(1.00)
0.639
(0.983)
0.648
(0.987)
16p gain 32 (9%) 338 0.253
(0.741)
0.0256
(0.395)
0.114
(0.58)
0.398
(0.835)
0.236
(0.732)
1
(1.00)
1
(1.00)
0.178
(0.674)
0.014
(0.315)
0.744
(1.00)
0.46
(0.881)
1
(1.00)
17p gain 30 (8%) 340 0.843
(1.00)
0.613
(0.963)
0.257
(0.741)
0.191
(0.687)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.576
(0.96)
0.128
(0.604)
0.304
(0.762)
0.38
(0.821)
17q gain 93 (25%) 277 0.804
(1.00)
0.595
(0.963)
0.233
(0.732)
0.163
(0.657)
1
(1.00)
0.27
(0.747)
0.0955
(0.565)
1
(1.00)
0.603
(0.963)
0.0902
(0.555)
0.0688
(0.517)
0.571
(0.96)
18p gain 36 (10%) 334 0.795
(1.00)
0.308
(0.762)
0.333
(0.774)
0.191
(0.687)
1
(1.00)
0.346
(0.791)
0.707
(1.00)
0.608
(0.963)
1
(1.00)
0.106
(0.573)
0.0161
(0.325)
1
(1.00)
18q gain 28 (8%) 342 0.73
(1.00)
0.0974
(0.565)
0.226
(0.726)
0.181
(0.679)
1
(1.00)
0.278
(0.75)
0.529
(0.936)
1
(1.00)
1
(1.00)
0.0451
(0.459)
0.036
(0.42)
1
(1.00)
19p gain 56 (15%) 314 0.425
(0.858)
0.65
(0.988)
0.11
(0.573)
0.668
(0.996)
1
(1.00)
0.0135
(0.315)
0.0299
(0.402)
1
(1.00)
0.131
(0.608)
0.117
(0.591)
0.064
(0.509)
0.718
(1.00)
19q gain 71 (19%) 299 0.507
(0.92)
0.491
(0.907)
0.143
(0.638)
0.504
(0.92)
1
(1.00)
0.0248
(0.394)
0.257
(0.741)
1
(1.00)
0.217
(0.718)
0.313
(0.762)
0.283
(0.75)
0.53
(0.936)
20q gain 112 (30%) 258 0.0197
(0.359)
0.0639
(0.509)
0.172
(0.669)
0.121
(0.594)
1
(1.00)
0.596
(0.963)
0.467
(0.885)
0.73
(1.00)
0.859
(1.00)
0.451
(0.873)
0.889
(1.00)
1
(1.00)
21q gain 26 (7%) 344 0.438
(0.866)
0.715
(1.00)
0.0292
(0.402)
0.0149
(0.315)
1
(1.00)
1
(1.00)
0.828
(1.00)
1
(1.00)
0.522
(0.933)
0.0195
(0.359)
0.378
(0.821)
1
(1.00)
xp gain 41 (11%) 329 0.741
(1.00)
0.474
(0.894)
0.975
(1.00)
0.859
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.258
(0.741)
1
(1.00)
0.575
(0.96)
0.37
(0.816)
0.687
(1.00)
xq gain 60 (16%) 310 0.336
(0.778)
0.571
(0.96)
0.992
(1.00)
0.845
(1.00)
1
(1.00)
1
(1.00)
0.132
(0.611)
0.157
(0.652)
0.77
(1.00)
0.854
(1.00)
0.35
(0.796)
1
(1.00)
1p loss 78 (21%) 292 0.84
(1.00)
0.256
(0.741)
0.265
(0.746)
0.381
(0.821)
0.537
(0.939)
0.0505
(0.468)
0.173
(0.669)
0.214
(0.715)
0.26
(0.746)
0.373
(0.82)
0.29
(0.758)
1
(1.00)
1q loss 20 (5%) 350 0.0606
(0.499)
0.584
(0.96)
0.724
(1.00)
0.895
(1.00)
0.155
(0.652)
1
(1.00)
0.22
(0.72)
1
(1.00)
0.432
(0.859)
0.439
(0.866)
0.745
(1.00)
1
(1.00)
2p loss 33 (9%) 337 0.766
(1.00)
0.421
(0.858)
0.251
(0.741)
0.486
(0.905)
0.217
(0.718)
1
(1.00)
0.434
(0.86)
0.535
(0.938)
0.222
(0.72)
0.299
(0.762)
0.242
(0.741)
0.38
(0.821)
2q loss 38 (10%) 332 0.746
(1.00)
0.104
(0.57)
0.487
(0.905)
0.962
(1.00)
0.265
(0.746)
1
(1.00)
0.854
(1.00)
0.598
(0.963)
0.273
(0.749)
0.112
(0.578)
0.258
(0.741)
1
(1.00)
3q loss 41 (11%) 329 0.426
(0.858)
0.104
(0.57)
0.0142
(0.315)
0.0411
(0.444)
0.0344
(0.419)
1
(1.00)
0.293
(0.76)
0.605
(0.963)
0.00998
(0.273)
0.798
(1.00)
0.88
(1.00)
1
(1.00)
4p loss 105 (28%) 265 0.452
(0.873)
0.0665
(0.509)
0.217
(0.718)
0.199
(0.7)
1
(1.00)
0.0794
(0.539)
0.0363
(0.42)
1
(1.00)
0.858
(1.00)
0.305
(0.762)
0.0163
(0.325)
0.255
(0.741)
5p loss 29 (8%) 341 0.331
(0.773)
0.0302
(0.402)
0.455
(0.877)
0.313
(0.762)
0.246
(0.741)
1
(1.00)
0.412
(0.847)
0.494
(0.907)
0.0451
(0.459)
0.891
(1.00)
0.372
(0.819)
1
(1.00)
5q loss 37 (10%) 333 0.0842
(0.554)
0.0353
(0.419)
0.155
(0.652)
0.01
(0.273)
0.275
(0.749)
1
(1.00)
0.711
(1.00)
0.586
(0.962)
0.0123
(0.302)
1
(1.00)
0.62
(0.969)
1
(1.00)
6p loss 31 (8%) 339 0.814
(1.00)
0.989
(1.00)
0.549
(0.948)
0.278
(0.75)
0.236
(0.732)
1
(1.00)
0.0454
(0.459)
0.508
(0.92)
1
(1.00)
0.811
(1.00)
0.172
(0.669)
0.632
(0.979)
7p loss 16 (4%) 354 0.0848
(0.554)
0.543
(0.944)
0.966
(1.00)
0.828
(1.00)
1
(1.00)
1
(1.00)
0.167
(0.664)
0.331
(0.773)
1
(1.00)
0.396
(0.835)
0.639
(0.983)
0.511
(0.922)
8p loss 196 (53%) 174 0.174
(0.669)
0.165
(0.66)
0.157
(0.652)
0.507
(0.92)
1
(1.00)
1
(1.00)
0.739
(1.00)
1
(1.00)
0.071
(0.528)
0.504
(0.92)
0.451
(0.873)
0.61
(0.963)
8q loss 45 (12%) 325 0.876
(1.00)
0.908
(1.00)
0.731
(1.00)
0.78
(1.00)
0.294
(0.76)
0.428
(0.858)
0.0613
(0.499)
0.606
(0.963)
0.732
(1.00)
0.472
(0.893)
0.891
(1.00)
0.704
(1.00)
9p loss 119 (32%) 251 0.101
(0.565)
0.0784
(0.536)
0.386
(0.826)
0.888
(1.00)
0.25
(0.741)
0.106
(0.573)
0.12
(0.594)
0.726
(1.00)
1
(1.00)
0.243
(0.741)
0.331
(0.773)
0.102
(0.566)
9q loss 110 (30%) 260 0.075
(0.531)
0.796
(1.00)
0.135
(0.617)
0.576
(0.96)
0.0232
(0.387)
0.074
(0.528)
0.225
(0.726)
1
(1.00)
1
(1.00)
0.305
(0.762)
0.682
(1.00)
0.163
(0.657)
10p loss 47 (13%) 323 0.287
(0.753)
0.367
(0.814)
0.487
(0.905)
0.183
(0.68)
1
(1.00)
1
(1.00)
1
(1.00)
0.613
(0.963)
0.0883
(0.554)
0.591
(0.963)
0.197
(0.698)
1
(1.00)
11p loss 63 (17%) 307 0.323
(0.77)
0.631
(0.979)
0.015
(0.315)
0.00989
(0.273)
0.0735
(0.528)
0.545
(0.944)
0.882
(1.00)
1
(1.00)
0.019
(0.359)
0.282
(0.75)
0.286
(0.753)
0.307
(0.762)
11q loss 72 (19%) 298 0.428
(0.858)
0.325
(0.771)
0.0596
(0.497)
0.0778
(0.536)
0.113
(0.578)
1
(1.00)
1
(1.00)
1
(1.00)
0.0319
(0.413)
0.406
(0.842)
0.504
(0.92)
0.195
(0.696)
13q loss 122 (33%) 248 0.27
(0.747)
0.911
(1.00)
0.0277
(0.402)
0.00928
(0.273)
0.271
(0.747)
0.605
(0.963)
0.0979
(0.565)
0.724
(1.00)
0.353
(0.799)
0.159
(0.655)
0.868
(1.00)
1
(1.00)
14q loss 109 (29%) 261 0.0497
(0.468)
0.0762
(0.535)
0.0945
(0.565)
0.0353
(0.419)
0.229
(0.728)
0.601
(0.963)
0.393
(0.831)
1
(1.00)
0.262
(0.746)
0.777
(1.00)
0.0345
(0.419)
0.785
(1.00)
18q loss 79 (21%) 291 0.781
(1.00)
0.996
(1.00)
0.287
(0.753)
1
(1.00)
0.125
(0.601)
0.227
(0.726)
0.221
(0.72)
0.0852
(0.554)
0.0115
(0.29)
0.443
(0.869)
0.986
(1.00)
0.345
(0.791)
19p loss 52 (14%) 318 0.0452
(0.459)
0.0261
(0.395)
0.675
(1.00)
0.375
(0.82)
0.382
(0.822)
1
(1.00)
0.152
(0.651)
0.61
(0.963)
1
(1.00)
0.653
(0.992)
0.0497
(0.468)
0.713
(1.00)
19q loss 39 (11%) 331 0.201
(0.703)
0.0129
(0.31)
0.426
(0.858)
0.376
(0.821)
0.312
(0.762)
1
(1.00)
0.145
(0.638)
1
(1.00)
1
(1.00)
0.453
(0.874)
0.0165
(0.325)
0.687
(1.00)
20p loss 26 (7%) 344 0.961
(1.00)
0.059
(0.496)
0.0924
(0.561)
0.312
(0.762)
1
(1.00)
0.29
(0.758)
0.828
(1.00)
0.479
(0.9)
0.151
(0.651)
0.622
(0.969)
0.19
(0.687)
0.3
(0.762)
20q loss 13 (4%) 357 0.36
(0.806)
0.229
(0.728)
0.262
(0.746)
0.723
(1.00)
1
(1.00)
1
(1.00)
0.562
(0.955)
0.274
(0.749)
0.121
(0.595)
0.299
(0.762)
0.0649
(0.509)
0.406
(0.842)
21q loss 110 (30%) 260 0.0278
(0.402)
0.169
(0.667)
0.377
(0.821)
0.953
(1.00)
1
(1.00)
0.0999
(0.565)
0.0516
(0.468)
1
(1.00)
0.369
(0.815)
0.544
(0.944)
0.526
(0.933)
1
(1.00)
xq loss 74 (20%) 296 0.854
(1.00)
0.078
(0.536)
0.934
(1.00)
0.659
(0.995)
0.487
(0.905)
0.582
(0.96)
0.0367
(0.42)
1
(1.00)
0.235
(0.732)
0.779
(1.00)
0.123
(0.595)
0.748
(1.00)
'2p gain' versus 'GENDER'

P value = 4.32e-05 (Fisher's exact test), Q value = 0.021

Table S1.  Gene #3: '2p gain' versus Clinical Feature #7: 'GENDER'

nPatients FEMALE MALE
ALL 118 252
2P GAIN MUTATED 26 17
2P GAIN WILD-TYPE 92 235

Figure S1.  Get High-res Image Gene #3: '2p gain' versus Clinical Feature #7: 'GENDER'

'2q gain' versus 'GENDER'

P value = 0.00049 (Fisher's exact test), Q value = 0.096

Table S2.  Gene #4: '2q gain' versus Clinical Feature #7: 'GENDER'

nPatients FEMALE MALE
ALL 118 252
2Q GAIN MUTATED 23 17
2Q GAIN WILD-TYPE 95 235

Figure S2.  Get High-res Image Gene #4: '2q gain' versus Clinical Feature #7: 'GENDER'

'6q gain' versus 'ETHNICITY'

P value = 0.00308 (Fisher's exact test), Q value = 0.19

Table S3.  Gene #12: '6q gain' versus Clinical Feature #12: 'ETHNICITY'

nPatients HISPANIC OR LATINO NOT HISPANIC OR LATINO
ALL 16 335
6Q GAIN MUTATED 8 56
6Q GAIN WILD-TYPE 8 279

Figure S3.  Get High-res Image Gene #12: '6q gain' versus Clinical Feature #12: 'ETHNICITY'

'8q gain' versus 'GENDER'

P value = 0.0012 (Fisher's exact test), Q value = 0.13

Table S4.  Gene #16: '8q gain' versus Clinical Feature #7: 'GENDER'

nPatients FEMALE MALE
ALL 118 252
8Q GAIN MUTATED 44 140
8Q GAIN WILD-TYPE 74 112

Figure S4.  Get High-res Image Gene #16: '8q gain' versus Clinical Feature #7: 'GENDER'

'12p gain' versus 'HISTOLOGICAL_TYPE'

P value = 0.00506 (Fisher's exact test), Q value = 0.19

Table S5.  Gene #23: '12p gain' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

nPatients FIBROLAMELLAR CARCINOMA HEPATOCELLULAR CARCINOMA HEPATOCHOLANGIOCARCINOMA (MIXED)
ALL 3 360 7
12P GAIN MUTATED 0 36 4
12P GAIN WILD-TYPE 3 324 3

Figure S5.  Get High-res Image Gene #23: '12p gain' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

'16q gain' versus 'HISTOLOGICAL_TYPE'

P value = 0.00187 (Fisher's exact test), Q value = 0.18

Table S6.  Gene #29: '16q gain' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

nPatients FIBROLAMELLAR CARCINOMA HEPATOCELLULAR CARCINOMA HEPATOCHOLANGIOCARCINOMA (MIXED)
ALL 3 360 7
16Q GAIN MUTATED 2 14 1
16Q GAIN WILD-TYPE 1 346 6

Figure S6.  Get High-res Image Gene #29: '16q gain' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

'20p gain' versus 'Time to Death'

P value = 0.0071 (logrank test), Q value = 0.24

Table S7.  Gene #36: '20p gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 364 129 0.0 - 120.8 (19.8)
20P GAIN MUTATED 105 48 0.3 - 114.3 (18.2)
20P GAIN WILD-TYPE 259 81 0.0 - 120.8 (20.2)

Figure S7.  Get High-res Image Gene #36: '20p gain' versus Clinical Feature #1: 'Time to Death'

'22q gain' versus 'PATHOLOGY_T_STAGE'

P value = 0.00466 (Fisher's exact test), Q value = 0.19

Table S8.  Gene #39: '22q gain' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

nPatients T1 T2 T3 T4
ALL 183 95 77 12
22Q GAIN MUTATED 13 17 16 2
22Q GAIN WILD-TYPE 170 78 61 10

Figure S8.  Get High-res Image Gene #39: '22q gain' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

'3p loss' versus 'PATHOLOGIC_STAGE'

P value = 0.00239 (Fisher's exact test), Q value = 0.18

Table S9.  Gene #46: '3p loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

nPatients STAGE I STAGE II STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA STAGE IVB
ALL 173 87 3 62 9 7 2 1 2
3P LOSS MUTATED 13 15 0 15 2 2 0 1 1
3P LOSS WILD-TYPE 160 72 3 47 7 5 2 0 1

Figure S9.  Get High-res Image Gene #46: '3p loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

'3p loss' versus 'PATHOLOGY_T_STAGE'

P value = 0.00383 (Fisher's exact test), Q value = 0.19

Table S10.  Gene #46: '3p loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

nPatients T1 T2 T3 T4
ALL 183 95 77 12
3P LOSS MUTATED 15 16 18 3
3P LOSS WILD-TYPE 168 79 59 9

Figure S10.  Get High-res Image Gene #46: '3p loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

'3p loss' versus 'HISTOLOGICAL_TYPE'

P value = 0.00082 (Fisher's exact test), Q value = 0.12

Table S11.  Gene #46: '3p loss' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

nPatients FIBROLAMELLAR CARCINOMA HEPATOCELLULAR CARCINOMA HEPATOCHOLANGIOCARCINOMA (MIXED)
ALL 3 360 7
3P LOSS MUTATED 2 46 4
3P LOSS WILD-TYPE 1 314 3

Figure S11.  Get High-res Image Gene #46: '3p loss' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

'4q loss' versus 'YEARS_TO_BIRTH'

P value = 0.00228 (Wilcoxon-test), Q value = 0.18

Table S12.  Gene #49: '4q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 366 59.4 (13.2)
4Q LOSS MUTATED 144 57.1 (13.4)
4Q LOSS WILD-TYPE 222 61.0 (12.8)

Figure S12.  Get High-res Image Gene #49: '4q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'4q loss' versus 'RACE'

P value = 0.00065 (Fisher's exact test), Q value = 0.11

Table S13.  Gene #49: '4q loss' versus Clinical Feature #11: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 2 158 17 183
4Q LOSS MUTATED 1 80 9 56
4Q LOSS WILD-TYPE 1 78 8 127

Figure S13.  Get High-res Image Gene #49: '4q loss' versus Clinical Feature #11: 'RACE'

'6q loss' versus 'YEARS_TO_BIRTH'

P value = 0.00271 (Wilcoxon-test), Q value = 0.19

Table S14.  Gene #53: '6q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 366 59.4 (13.2)
6Q LOSS MUTATED 93 63.1 (12.3)
6Q LOSS WILD-TYPE 273 58.2 (13.3)

Figure S14.  Get High-res Image Gene #53: '6q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'7q loss' versus 'Time to Death'

P value = 0.00113 (logrank test), Q value = 0.13

Table S15.  Gene #55: '7q loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 364 129 0.0 - 120.8 (19.8)
7Q LOSS MUTATED 21 13 0.2 - 76.4 (13.6)
7Q LOSS WILD-TYPE 343 116 0.0 - 120.8 (20.1)

Figure S15.  Get High-res Image Gene #55: '7q loss' versus Clinical Feature #1: 'Time to Death'

'10q loss' versus 'RACE'

P value = 0.00022 (Fisher's exact test), Q value = 0.072

Table S16.  Gene #61: '10q loss' versus Clinical Feature #11: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 2 158 17 183
10Q LOSS MUTATED 0 40 10 28
10Q LOSS WILD-TYPE 2 118 7 155

Figure S16.  Get High-res Image Gene #61: '10q loss' versus Clinical Feature #11: 'RACE'

'12p loss' versus 'PATHOLOGIC_STAGE'

P value = 0.00731 (Fisher's exact test), Q value = 0.24

Table S17.  Gene #64: '12p loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

nPatients STAGE I STAGE II STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA STAGE IVB
ALL 173 87 3 62 9 7 2 1 2
12P LOSS MUTATED 24 18 1 9 4 2 2 1 0
12P LOSS WILD-TYPE 149 69 2 53 5 5 0 0 2

Figure S17.  Get High-res Image Gene #64: '12p loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

'12p loss' versus 'PATHOLOGY_N_STAGE'

P value = 0.00507 (Fisher's exact test), Q value = 0.19

Table S18.  Gene #64: '12p loss' versus Clinical Feature #5: 'PATHOLOGY_N_STAGE'

nPatients 0 1
ALL 254 3
12P LOSS MUTATED 42 3
12P LOSS WILD-TYPE 212 0

Figure S18.  Get High-res Image Gene #64: '12p loss' versus Clinical Feature #5: 'PATHOLOGY_N_STAGE'

'12q loss' versus 'PATHOLOGIC_STAGE'

P value = 0.00424 (Fisher's exact test), Q value = 0.19

Table S19.  Gene #65: '12q loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

nPatients STAGE I STAGE II STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA STAGE IVB
ALL 173 87 3 62 9 7 2 1 2
12Q LOSS MUTATED 12 10 1 6 2 0 2 1 0
12Q LOSS WILD-TYPE 161 77 2 56 7 7 0 0 2

Figure S19.  Get High-res Image Gene #65: '12q loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

'15q loss' versus 'Time to Death'

P value = 0.00477 (logrank test), Q value = 0.19

Table S20.  Gene #68: '15q loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 364 129 0.0 - 120.8 (19.8)
15Q LOSS MUTATED 64 31 0.2 - 102.7 (13.3)
15Q LOSS WILD-TYPE 300 98 0.0 - 120.8 (20.9)

Figure S20.  Get High-res Image Gene #68: '15q loss' versus Clinical Feature #1: 'Time to Death'

'15q loss' versus 'PATHOLOGY_T_STAGE'

P value = 0.00647 (Fisher's exact test), Q value = 0.24

Table S21.  Gene #68: '15q loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

nPatients T1 T2 T3 T4
ALL 183 95 77 12
15Q LOSS MUTATED 22 23 21 1
15Q LOSS WILD-TYPE 161 72 56 11

Figure S21.  Get High-res Image Gene #68: '15q loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

'16p loss' versus 'RACE'

P value = 0.00422 (Fisher's exact test), Q value = 0.19

Table S22.  Gene #69: '16p loss' versus Clinical Feature #11: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 2 158 17 183
16P LOSS MUTATED 0 61 6 40
16P LOSS WILD-TYPE 2 97 11 143

Figure S22.  Get High-res Image Gene #69: '16p loss' versus Clinical Feature #11: 'RACE'

'16q loss' versus 'YEARS_TO_BIRTH'

P value = 0.000393 (Wilcoxon-test), Q value = 0.096

Table S23.  Gene #70: '16q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 366 59.4 (13.2)
16Q LOSS MUTATED 144 56.9 (12.9)
16Q LOSS WILD-TYPE 222 61.1 (13.1)

Figure S23.  Get High-res Image Gene #70: '16q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'16q loss' versus 'RACE'

P value = 2e-05 (Fisher's exact test), Q value = 0.02

Table S24.  Gene #70: '16q loss' versus Clinical Feature #11: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 2 158 17 183
16Q LOSS MUTATED 0 84 7 51
16Q LOSS WILD-TYPE 2 74 10 132

Figure S24.  Get High-res Image Gene #70: '16q loss' versus Clinical Feature #11: 'RACE'

'17p loss' versus 'PATHOLOGIC_STAGE'

P value = 0.00358 (Fisher's exact test), Q value = 0.19

Table S25.  Gene #71: '17p loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

nPatients STAGE I STAGE II STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA STAGE IVB
ALL 173 87 3 62 9 7 2 1 2
17P LOSS MUTATED 70 50 2 34 4 7 2 1 1
17P LOSS WILD-TYPE 103 37 1 28 5 0 0 0 1

Figure S25.  Get High-res Image Gene #71: '17p loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

'17q loss' versus 'PATHOLOGIC_STAGE'

P value = 0.00768 (Fisher's exact test), Q value = 0.24

Table S26.  Gene #72: '17q loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

nPatients STAGE I STAGE II STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA STAGE IVB
ALL 173 87 3 62 9 7 2 1 2
17Q LOSS MUTATED 10 12 0 9 2 2 1 1 0
17Q LOSS WILD-TYPE 163 75 3 53 7 5 1 0 2

Figure S26.  Get High-res Image Gene #72: '17q loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

'17q loss' versus 'HISTOLOGICAL_TYPE'

P value = 0.00295 (Fisher's exact test), Q value = 0.19

Table S27.  Gene #72: '17q loss' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

nPatients FIBROLAMELLAR CARCINOMA HEPATOCELLULAR CARCINOMA HEPATOCHOLANGIOCARCINOMA (MIXED)
ALL 3 360 7
17Q LOSS MUTATED 2 35 3
17Q LOSS WILD-TYPE 1 325 4

Figure S27.  Get High-res Image Gene #72: '17q loss' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

'18p loss' versus 'HISTOLOGICAL_TYPE'

P value = 0.00201 (Fisher's exact test), Q value = 0.18

Table S28.  Gene #73: '18p loss' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

nPatients FIBROLAMELLAR CARCINOMA HEPATOCELLULAR CARCINOMA HEPATOCHOLANGIOCARCINOMA (MIXED)
ALL 3 360 7
18P LOSS MUTATED 3 68 3
18P LOSS WILD-TYPE 0 292 4

Figure S28.  Get High-res Image Gene #73: '18p loss' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

'22q loss' versus 'HISTOLOGICAL_TYPE'

P value = 0.00747 (Fisher's exact test), Q value = 0.24

Table S29.  Gene #80: '22q loss' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

nPatients FIBROLAMELLAR CARCINOMA HEPATOCELLULAR CARCINOMA HEPATOCHOLANGIOCARCINOMA (MIXED)
ALL 3 360 7
22Q LOSS MUTATED 3 65 2
22Q LOSS WILD-TYPE 0 295 5

Figure S29.  Get High-res Image Gene #80: '22q loss' versus Clinical Feature #9: 'HISTOLOGICAL_TYPE'

'22q loss' versus 'RACE'

P value = 0.00406 (Fisher's exact test), Q value = 0.19

Table S30.  Gene #80: '22q loss' versus Clinical Feature #11: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 2 158 17 183
22Q LOSS MUTATED 1 22 8 39
22Q LOSS WILD-TYPE 1 136 9 144

Figure S30.  Get High-res Image Gene #80: '22q loss' versus Clinical Feature #11: 'RACE'

'xp loss' versus 'GENDER'

P value = 0.00477 (Fisher's exact test), Q value = 0.19

Table S31.  Gene #81: 'xp loss' versus Clinical Feature #7: 'GENDER'

nPatients FEMALE MALE
ALL 118 252
XP LOSS MUTATED 19 76
XP LOSS WILD-TYPE 99 176

Figure S31.  Get High-res Image Gene #81: 'xp loss' versus Clinical Feature #7: 'GENDER'

Methods & Data
Input
  • Copy number data file = broad_values_by_arm.txt from GISTIC pipeline

  • Processed Copy number data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/LIHC-TP/22531240/transformed.cor.cli.txt

  • Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/LIHC-TP/22506983/LIHC-TP.merged_data.txt

  • Number of patients = 370

  • Number of significantly arm-level cnvs = 82

  • Number of selected clinical features = 12

  • Exclude regions that fewer than K tumors have mutations, K = 3

Survival analysis

For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene mutations were plotted and the statistical significance P values were estimated by logrank test (Bland and Altman 2004) using the 'survdiff' function in R

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] Bland and Altman, Statistics notes: The logrank test, BMJ 328(7447):1073 (2004)
[2] 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)
[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)