Correlation between copy number variations of arm-level result and selected clinical features
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 11 clinical features across 357 patients, 20 significant findings detected with Q value < 0.25.

  • 2p gain cnv correlated to 'GENDER'.

  • 2q gain cnv correlated to 'GENDER'.

  • 8q gain cnv correlated to 'GENDER'.

  • 10p gain cnv correlated to 'YEARS_TO_BIRTH'.

  • 12p gain cnv correlated to 'HISTOLOGICAL_TYPE'.

  • 22q gain cnv correlated to 'PATHOLOGY_T_STAGE'.

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

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

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

  • 10q loss cnv correlated to 'RACE'.

  • 12q loss cnv correlated to 'NEOPLASM_DISEASESTAGE'.

  • 13q loss cnv correlated to 'PATHOLOGY_T_STAGE'.

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

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

  • 17p loss cnv correlated to 'NEOPLASM_DISEASESTAGE'.

  • 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 11 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 20 significant findings detected.

Clinical
Features 		Time
to
Death 		YEARS
TO
BIRTH 		NEOPLASM
DISEASESTAGE 		PATHOLOGY
T
STAGE 		PATHOLOGY
N
STAGE 		PATHOLOGY
M
STAGE 		GENDER HISTOLOGICAL
TYPE 		COMPLETENESS
OF
RESECTION 		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
3p loss 50 (14%) 307 0.473
(0.873) 		0.159
(0.664) 		0.0139
(0.331) 		0.00277
(0.214) 		0.363
(0.787) 		0.446
(0.857) 		0.326
(0.768) 		0.00353
(0.214) 		0.395
(0.814) 		0.971
(1.00) 		1
(1.00)
4q loss 142 (40%) 215 0.612
(0.941) 		0.00336
(0.214) 		0.268
(0.731) 		0.417
(0.826) 		0.569
(0.927) 		0.323
(0.768) 		0.296
(0.75) 		0.732
(1.00) 		0.327
(0.768) 		0.00091
(0.125) 		0.763
(1.00)
16p loss 108 (30%) 249 0.298
(0.75) 		0.00212
(0.191) 		0.263
(0.731) 		0.345
(0.781) 		0.253
(0.721) 		0.607
(0.938) 		0.265
(0.731) 		1
(1.00) 		0.0642
(0.553) 		0.00389
(0.214) 		0.325
(0.768)
16q loss 143 (40%) 214 0.523
(0.892) 		0.000119
(0.0359) 		0.0872
(0.554) 		0.0708
(0.554) 		0.58
(0.927) 		1
(1.00) 		0.297
(0.75) 		0.733
(1.00) 		0.361
(0.787) 		1e-05
(0.00902) 		0.367
(0.788)
2p gain 44 (12%) 313 0.176
(0.69) 		0.111
(0.586) 		0.0949
(0.559) 		0.0922
(0.557) 		0.0433
(0.465) 		0.0732
(0.554) 		8.98e-05
(0.0359) 		0.395
(0.814) 		0.0934
(0.557) 		0.268
(0.731) 		0.64
(0.95)
2q gain 40 (11%) 317 0.131
(0.619) 		0.448
(0.859) 		0.159
(0.664) 		0.144
(0.635) 		0.336
(0.777) 		0.0732
(0.554) 		0.000449
(0.081) 		0.355
(0.785) 		0.226
(0.703) 		0.715
(1.00) 		0.625
(0.944)
8q gain 182 (51%) 175 0.724
(1.00) 		0.133
(0.623) 		0.212
(0.698) 		0.359
(0.785) 		0.596
(0.93) 		1
(1.00) 		0.000969
(0.125) 		0.638
(0.95) 		0.98
(1.00) 		0.0363
(0.42) 		1
(1.00)
10p gain 60 (17%) 297 0.845
(1.00) 		0.00497
(0.235) 		0.072
(0.554) 		0.0644
(0.553) 		1
(1.00) 		0.141
(0.634) 		1
(1.00) 		0.375
(0.795) 		0.758
(1.00) 		0.335
(0.776) 		0.413
(0.826)
12p gain 39 (11%) 318 0.21
(0.698) 		0.588
(0.927) 		0.197
(0.695) 		0.0629
(0.553) 		1
(1.00) 		1
(1.00) 		0.203
(0.698) 		0.00521
(0.235) 		0.692
(0.992) 		0.894
(1.00) 		0.617
(0.941)
22q gain 48 (13%) 309 0.661
(0.962) 		0.916
(1.00) 		0.0242
(0.394) 		0.00333
(0.214) 		0.327
(0.768) 		1
(1.00) 		0.243
(0.721) 		0.432
(0.846) 		0.267
(0.731) 		0.939
(1.00) 		1
(1.00)
7q loss 20 (6%) 337 0.00427
(0.214) 		0.369
(0.791) 		0.916
(1.00) 		0.792
(1.00) 		1
(1.00) 		1
(1.00) 		0.0266
(0.394) 		1
(1.00) 		0.21
(0.698) 		0.12
(0.596) 		1
(1.00)
10q loss 74 (21%) 283 0.273
(0.731) 		0.957
(1.00) 		0.364
(0.788) 		0.211
(0.698) 		0.486
(0.873) 		0.583
(0.927) 		0.575
(0.927) 		0.03
(0.394) 		0.35
(0.785) 		0.00026
(0.0586) 		1
(1.00)
12q loss 33 (9%) 324 0.57
(0.927) 		0.0857
(0.554) 		0.00425
(0.214) 		0.508
(0.89) 		1
(1.00) 		0.057
(0.527) 		0.696
(0.993) 		0.587
(0.927) 		0.0928
(0.557) 		0.238
(0.717) 		0.277
(0.731)
13q loss 115 (32%) 242 0.454
(0.865) 		0.626
(0.944) 		0.0697
(0.554) 		0.00129
(0.145) 		1
(1.00) 		0.598
(0.93) 		0.0688
(0.554) 		0.244
(0.721) 		0.0809
(0.554) 		0.914
(1.00) 		1
(1.00)
17p loss 177 (50%) 180 0.0377
(0.43) 		0.576
(0.927) 		0.00145
(0.145) 		0.015
(0.346) 		0.247
(0.721) 		0.622
(0.943) 		0.909
(1.00) 		0.639
(0.95) 		0.274
(0.731) 		0.366
(0.788) 		0.138
(0.627)
xp loss 92 (26%) 265 0.0865
(0.554) 		0.0731
(0.554) 		0.798
(1.00) 		0.462
(0.868) 		1
(1.00) 		1
(1.00) 		0.00407
(0.214) 		0.419
(0.827) 		0.227
(0.703) 		0.559
(0.921) 		1
(1.00)
1p gain 54 (15%) 303 0.879
(1.00) 		0.155
(0.664) 		0.406
(0.822) 		0.109
(0.585) 		1
(1.00) 		1
(1.00) 		0.208
(0.698) 		1
(1.00) 		0.25
(0.721) 		0.0844
(0.554) 		0.227
(0.703)
1q gain 215 (60%) 142 0.676
(0.976) 		0.53
(0.896) 		0.487
(0.873) 		0.586
(0.927) 		0.561
(0.921) 		0.3
(0.75) 		0.488
(0.873) 		0.133
(0.623) 		0.457
(0.865) 		0.105
(0.585) 		0.758
(1.00)
3p gain 35 (10%) 322 0.515
(0.89) 		0.53
(0.896) 		0.334
(0.776) 		0.789
(1.00) 		0.25
(0.721) 		0.352
(0.785) 		0.13
(0.619) 		1
(1.00) 		0.195
(0.695) 		0.807
(1.00) 		0.303
(0.75)
3q gain 38 (11%) 319 0.115
(0.586) 		0.739
(1.00) 		0.343
(0.781) 		0.775
(1.00) 		0.27
(0.731) 		0.363
(0.787) 		0.196
(0.695) 		0.641
(0.95) 		0.262
(0.731) 		0.652
(0.957) 		0.106
(0.585)
4p gain 26 (7%) 331 0.0263
(0.394) 		0.697
(0.993) 		0.638
(0.95) 		0.592
(0.93) 		1
(1.00) 		1
(1.00) 		0.124
(0.61) 		1
(1.00) 		0.774
(1.00) 		1
(1.00) 		1
(1.00)
4q gain 7 (2%) 350 0.698
(0.993) 		0.237
(0.717) 		0.762
(1.00) 		0.684
(0.986) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.161
(0.664) 		0.582
(0.927) 		0.207
(0.698)
5p gain 132 (37%) 225 0.137
(0.626) 		0.101
(0.578) 		0.414
(0.826) 		0.0973
(0.566) 		0.554
(0.917) 		1
(1.00) 		0.724
(1.00) 		0.62
(0.941) 		0.924
(1.00) 		0.923
(1.00) 		1
(1.00)
5q gain 104 (29%) 253 0.337
(0.777) 		0.0551
(0.527) 		0.934
(1.00) 		0.428
(0.841) 		0.564
(0.925) 		1
(1.00) 		0.103
(0.585) 		1
(1.00) 		0.856
(1.00) 		0.795
(1.00) 		0.737
(1.00)
6p gain 111 (31%) 246 0.393
(0.814) 		0.203
(0.698) 		0.501
(0.887) 		0.201
(0.698) 		0.555
(0.917) 		0.594
(0.93) 		0.328
(0.768) 		0.713
(1.00) 		0.581
(0.927) 		0.278
(0.731) 		0.748
(1.00)
6q gain 62 (17%) 295 0.187
(0.695) 		0.747
(1.00) 		0.178
(0.691) 		0.216
(0.698) 		1
(1.00) 		0.136
(0.626) 		0.179
(0.691) 		1
(1.00) 		0.3
(0.75) 		0.354
(0.785) 		0.11
(0.585)
7p gain 107 (30%) 250 0.617
(0.941) 		0.0209
(0.385) 		0.377
(0.795) 		0.76
(1.00) 		0.192
(0.695) 		1
(1.00) 		0.216
(0.698) 		0.708
(0.997) 		0.747
(1.00) 		0.221
(0.701) 		0.742
(1.00)
7q gain 107 (30%) 250 0.48
(0.873) 		0.00962
(0.31) 		0.376
(0.795) 		0.489
(0.873) 		0.197
(0.695) 		1
(1.00) 		0.804
(1.00) 		0.709
(0.997) 		0.939
(1.00) 		0.0879
(0.554) 		0.325
(0.768)
8p gain 75 (21%) 282 0.719
(1.00) 		0.0935
(0.557) 		0.971
(1.00) 		0.817
(1.00) 		1
(1.00) 		1
(1.00) 		0.0359
(0.42) 		0.359
(0.785) 		0.248
(0.721) 		0.15
(0.656) 		0.705
(0.996)
9p gain 18 (5%) 339 0.733
(1.00) 		0.238
(0.717) 		0.0669
(0.554) 		0.11
(0.585) 		1
(1.00) 		0.21
(0.698) 		0.297
(0.75) 		0.0696
(0.554) 		0.171
(0.679) 		0.435
(0.847) 		0.416
(0.826)
9q gain 20 (6%) 337 0.657
(0.959) 		0.168
(0.677) 		0.13
(0.619) 		0.113
(0.586) 		1
(1.00) 		0.222
(0.701) 		0.0266
(0.394) 		0.408
(0.822) 		0.18
(0.692) 		0.871
(1.00) 		0.474
(0.873)
10q gain 36 (10%) 321 0.38
(0.799) 		0.0783
(0.554) 		0.0707
(0.554) 		0.0569
(0.527) 		1
(1.00) 		0.0609
(0.544) 		0.347
(0.783) 		0.619
(0.941) 		0.828
(1.00) 		0.96
(1.00) 		0.315
(0.76)
11p gain 17 (5%) 340 0.523
(0.892) 		0.813
(1.00) 		0.392
(0.814) 		0.251
(0.721) 		1
(1.00) 		0.197
(0.695) 		0.426
(0.84) 		1
(1.00) 		0.0135
(0.331) 		0.922
(1.00) 		1
(1.00)
11q gain 18 (5%) 339 0.402
(0.819) 		0.64
(0.95) 		0.237
(0.717) 		0.086
(0.554) 		1
(1.00) 		0.222
(0.701) 		0.297
(0.75) 		1
(1.00) 		0.0162
(0.358) 		0.789
(1.00) 		1
(1.00)
12q gain 44 (12%) 313 0.765
(1.00) 		0.479
(0.873) 		0.0361
(0.42) 		0.0349
(0.42) 		0.345
(0.781) 		1
(1.00) 		0.169
(0.677) 		0.0566
(0.527) 		0.402
(0.819) 		1
(1.00) 		1
(1.00)
13q gain 22 (6%) 335 0.173
(0.682) 		0.994
(1.00) 		0.12
(0.596) 		0.616
(0.941) 		0.21
(0.698) 		0.247
(0.721) 		0.161
(0.664) 		1
(1.00) 		0.514
(0.89) 		0.494
(0.879) 		0.492
(0.877)
14q gain 23 (6%) 334 0.483
(0.873) 		0.468
(0.872) 		0.506
(0.89) 		0.543
(0.909) 		1
(1.00) 		0.197
(0.695) 		0.247
(0.721) 		0.106
(0.585) 		0.109
(0.585) 		0.193
(0.695) 		0.509
(0.89)
15q gain 33 (9%) 324 0.28
(0.731) 		0.993
(1.00) 		0.457
(0.865) 		0.357
(0.785) 		1
(1.00) 		1
(1.00) 		0.696
(0.993) 		0.192
(0.695) 		1
(1.00) 		0.605
(0.938) 		0.277
(0.731)
16p gain 28 (8%) 329 0.648
(0.954) 		0.162
(0.664) 		0.377
(0.795) 		0.314
(0.76) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.0782
(0.554) 		0.489
(0.873) 		0.339
(0.777) 		1
(1.00)
16q gain 14 (4%) 343 0.926
(1.00) 		0.0575
(0.527) 		0.201
(0.698) 		0.115
(0.586) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.0203
(0.385) 		0.305
(0.753) 		0.28
(0.731) 		0.331
(0.772)
17p gain 30 (8%) 327 0.484
(0.873) 		0.56
(0.921) 		0.213
(0.698) 		0.163
(0.665) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.552
(0.917) 		0.0845
(0.554) 		0.293
(0.75) 		0.609
(0.938)
17q gain 92 (26%) 265 0.845
(1.00) 		0.519
(0.892) 		0.433
(0.846) 		0.189
(0.695) 		1
(1.00) 		0.261
(0.731) 		0.12
(0.596) 		0.825
(1.00) 		0.0427
(0.464) 		0.129
(0.619) 		1
(1.00)
18p gain 35 (10%) 322 0.859
(1.00) 		0.415
(0.826) 		0.118
(0.593) 		0.162
(0.664) 		1
(1.00) 		0.341
(0.779) 		0.848
(1.00) 		1
(1.00) 		0.0878
(0.554) 		0.0783
(0.554) 		1
(1.00)
18q gain 27 (8%) 330 0.822
(1.00) 		0.151
(0.656) 		0.0602
(0.543) 		0.162
(0.664) 		1
(1.00) 		0.272
(0.731) 		0.668
(0.966) 		1
(1.00) 		0.031
(0.394) 		0.199
(0.697) 		0.603
(0.937)
19p gain 53 (15%) 304 0.784
(1.00) 		0.509
(0.89) 		0.0756
(0.554) 		0.877
(1.00) 		0.397
(0.815) 		0.0125
(0.331) 		0.0251
(0.394) 		0.478
(0.873) 		0.139
(0.628) 		0.293
(0.75) 		0.219
(0.7)
19q gain 68 (19%) 289 0.843
(1.00) 		0.301
(0.75) 		0.179
(0.691) 		0.84
(1.00) 		0.463
(0.868) 		0.0237
(0.394) 		0.196
(0.695) 		0.752
(1.00) 		0.187
(0.695) 		0.658
(0.959) 		0.237
(0.717)
20p gain 105 (29%) 252 0.00689
(0.286) 		0.0354
(0.42) 		0.0784
(0.554) 		0.109
(0.585) 		1
(1.00) 		0.0903
(0.557) 		0.17
(0.678) 		1
(1.00) 		0.346
(0.781) 		0.793
(1.00) 		1
(1.00)
20q gain 109 (31%) 248 0.0555
(0.527) 		0.0497
(0.515) 		0.16
(0.664) 		0.0916
(0.557) 		1
(1.00) 		0.596
(0.93) 		0.39
(0.813) 		1
(1.00) 		0.376
(0.795) 		0.886
(1.00) 		0.516
(0.89)
21q gain 26 (7%) 331 0.916
(1.00) 		0.651
(0.957) 		0.0181
(0.378) 		0.0112
(0.331) 		1
(1.00) 		1
(1.00) 		0.827
(1.00) 		0.5
(0.887) 		0.0114
(0.331) 		0.308
(0.753) 		0.574
(0.927)
xp gain 39 (11%) 318 0.704
(0.996) 		0.228
(0.704) 		0.983
(1.00) 		0.927
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.464
(0.868) 		0.185
(0.695) 		1
(1.00)
xq gain 61 (17%) 296 0.259
(0.731) 		0.473
(0.873) 		0.994
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.131
(0.619) 		0.733
(1.00) 		0.761
(1.00) 		0.227
(0.703) 		0.698
(0.993)
1p loss 81 (23%) 276 0.932
(1.00) 		0.325
(0.768) 		0.522
(0.892) 		0.355
(0.785) 		0.545
(0.909) 		0.056
(0.527) 		0.277
(0.731) 		0.295
(0.75) 		0.282
(0.734) 		0.807
(1.00) 		0.719
(1.00)
1q loss 22 (6%) 335 0.122
(0.604) 		0.518
(0.891) 		0.484
(0.873) 		0.338
(0.777) 		0.169
(0.677) 		1
(1.00) 		0.64
(0.95) 		0.438
(0.851) 		0.253
(0.721) 		0.655
(0.959) 		1
(1.00)
2p loss 31 (9%) 326 0.546
(0.909) 		0.782
(1.00) 		0.726
(1.00) 		0.638
(0.95) 		1
(1.00) 		1
(1.00) 		0.315
(0.76) 		0.565
(0.925) 		0.22
(0.7) 		0.752
(1.00) 		0.609
(0.938)
2q loss 36 (10%) 321 0.808
(1.00) 		0.245
(0.721) 		0.954
(1.00) 		0.959
(1.00) 		1
(1.00) 		1
(1.00) 		0.707
(0.997) 		0.62
(0.941) 		0.0774
(0.554) 		0.749
(1.00) 		1
(1.00)
3q loss 38 (11%) 319 0.26
(0.731) 		0.143
(0.635) 		0.115
(0.586) 		0.0527
(0.527) 		0.289
(0.748) 		1
(1.00) 		0.466
(0.869) 		0.0653
(0.554) 		0.586
(0.927) 		0.928
(1.00) 		1
(1.00)
4p loss 102 (29%) 255 0.545
(0.909) 		0.0578
(0.527) 		0.0228
(0.394) 		0.0886
(0.554) 		0.188
(0.695) 		0.0844
(0.554) 		0.131
(0.619) 		1
(1.00) 		0.453
(0.865) 		0.0309
(0.394) 		0.309
(0.753)
5p loss 27 (8%) 330 0.873
(1.00) 		0.0403
(0.449) 		0.359
(0.785) 		0.191
(0.695) 		0.25
(0.721) 		1
(1.00) 		0.389
(0.813) 		0.0275
(0.394) 		1
(1.00) 		0.205
(0.698) 		1
(1.00)
5q loss 38 (11%) 319 0.353
(0.785) 		0.0495
(0.515) 		0.188
(0.695) 		0.0127
(0.331) 		0.299
(0.75) 		1
(1.00) 		1
(1.00) 		0.0139
(0.331) 		0.764
(1.00) 		0.527
(0.895) 		0.619
(0.941)
6p loss 27 (8%) 330 0.885
(1.00) 		0.614
(0.941) 		0.183
(0.695) 		0.322
(0.768) 		0.231
(0.71) 		0.295
(0.75) 		0.0294
(0.394) 		1
(1.00) 		1
(1.00) 		0.184
(0.695) 		0.574
(0.927)
6q loss 90 (25%) 267 0.598
(0.93) 		0.0186
(0.378) 		0.286
(0.74) 		0.658
(0.959) 		0.169
(0.677) 		0.307
(0.753) 		0.018
(0.378) 		0.412
(0.826) 		1
(1.00) 		0.648
(0.954) 		0.737
(1.00)
7p loss 15 (4%) 342 0.511
(0.89) 		0.444
(0.857) 		0.944
(1.00) 		0.815
(1.00) 		1
(1.00) 		1
(1.00) 		0.256
(0.726) 		1
(1.00) 		0.8
(1.00) 		0.598
(0.93) 		1
(1.00)
8p loss 185 (52%) 172 0.667
(0.966) 		0.138
(0.627) 		0.215
(0.698) 		0.504
(0.89) 		0.118
(0.593) 		1
(1.00) 		1
(1.00) 		0.0258
(0.394) 		0.744
(1.00) 		0.0955
(0.56) 		0.546
(0.909)
8q loss 42 (12%) 315 0.833
(1.00) 		0.929
(1.00) 		0.44
(0.853) 		0.637
(0.95) 		0.28
(0.731) 		0.405
(0.822) 		0.0523
(0.527) 		0.68
(0.981) 		0.433
(0.846) 		0.642
(0.95) 		1
(1.00)
9p loss 115 (32%) 242 0.372
(0.795) 		0.0268
(0.394) 		0.279
(0.731) 		0.813
(1.00) 		0.248
(0.721) 		0.106
(0.585) 		0.088
(0.554) 		1
(1.00) 		0.446
(0.857) 		0.234
(0.715) 		0.351
(0.785)
9q loss 105 (29%) 252 0.202
(0.698) 		0.782
(1.00) 		0.08
(0.554) 		0.582
(0.927) 		0.0208
(0.385) 		0.0681
(0.554) 		0.213
(0.698) 		1
(1.00) 		0.218
(0.698) 		0.768
(1.00) 		0.514
(0.89)
10p loss 44 (12%) 313 0.232
(0.712) 		0.172
(0.679) 		0.16
(0.664) 		0.316
(0.76) 		0.28
(0.731) 		1
(1.00) 		0.863
(1.00) 		0.057
(0.527) 		0.514
(0.89) 		0.205
(0.698) 		1
(1.00)
11p loss 61 (17%) 296 0.821
(1.00) 		0.688
(0.989) 		0.00883
(0.295) 		0.0132
(0.331) 		0.0763
(0.554) 		0.546
(0.909) 		0.764
(1.00) 		0.0692
(0.554) 		0.688
(0.989) 		0.825
(1.00) 		0.0938
(0.557)
11q loss 70 (20%) 287 0.876
(1.00) 		0.445
(0.857) 		0.0358
(0.42) 		0.0891
(0.554) 		0.113
(0.586) 		1
(1.00) 		1
(1.00) 		0.101
(0.578) 		0.482
(0.873) 		0.938
(1.00) 		0.0422
(0.464)
12p loss 60 (17%) 297 0.664
(0.964) 		0.478
(0.873) 		0.0202
(0.385) 		0.514
(0.89) 		0.073
(0.554) 		0.152
(0.657) 		0.648
(0.954) 		1
(1.00) 		0.21
(0.698) 		0.515
(0.89) 		0.403
(0.819)
14q loss 104 (29%) 253 0.41
(0.826) 		0.113
(0.586) 		0.0454
(0.482) 		0.00697
(0.286) 		1
(1.00) 		0.596
(0.93) 		0.26
(0.731) 		0.357
(0.785) 		0.754
(1.00) 		0.0853
(0.554) 		0.521
(0.892)
15q loss 63 (18%) 294 0.0189
(0.378) 		0.874
(1.00) 		0.0271
(0.394) 		0.00843
(0.295) 		0.0831
(0.554) 		0.585
(0.927) 		1
(1.00) 		0.567
(0.927) 		0.853
(1.00) 		0.217
(0.698) 		0.418
(0.826)
17q loss 37 (10%) 320 0.0224
(0.394) 		0.136
(0.626) 		0.00766
(0.295) 		0.142
(0.635) 		0.0246
(0.394) 		0.374
(0.795) 		0.262
(0.731) 		0.0124
(0.331) 		1
(1.00) 		0.128
(0.619) 		0.303
(0.75)
18p loss 70 (20%) 287 0.967
(1.00) 		0.584
(0.927) 		0.772
(1.00) 		0.769
(1.00) 		0.502
(0.887) 		1
(1.00) 		0.316
(0.76) 		0.00879
(0.295) 		0.721
(1.00) 		0.798
(1.00) 		0.459
(0.865)
18q loss 73 (20%) 284 0.732
(1.00) 		0.855
(1.00) 		0.713
(1.00) 		1
(1.00) 		0.524
(0.892) 		0.223
(0.701) 		0.481
(0.873) 		0.0403
(0.449) 		0.477
(0.873) 		0.98
(1.00) 		0.243
(0.721)
19p loss 53 (15%) 304 0.331
(0.772) 		0.0242
(0.394) 		0.546
(0.909) 		0.4
(0.819) 		0.397
(0.815) 		1
(1.00) 		0.15
(0.656) 		0.48
(0.873) 		0.355
(0.785) 		0.089
(0.554) 		0.384
(0.804)
19q loss 38 (11%) 319 0.924
(1.00) 		0.0299
(0.394) 		0.253
(0.721) 		0.395
(0.814) 		0.308
(0.753) 		1
(1.00) 		0.196
(0.695) 		0.638
(0.95) 		0.276
(0.731) 		0.0738
(0.554) 		0.341
(0.779)
20p loss 24 (7%) 333 0.766
(1.00) 		0.144
(0.635) 		0.191
(0.695) 		0.455
(0.865) 		1
(1.00) 		0.272
(0.731) 		0.824
(1.00) 		0.0578
(0.527) 		0.572
(0.927) 		0.7
(0.993) 		0.543
(0.909)
20q loss 12 (3%) 345 0.486
(0.873) 		0.414
(0.826) 		0.272
(0.731) 		0.7
(0.993) 		1
(1.00) 		1
(1.00) 		0.53
(0.896) 		0.0839
(0.554) 		0.243
(0.721) 		0.451
(0.864) 		0.307
(0.753)
21q loss 106 (30%) 251 0.0163
(0.358) 		0.323
(0.768) 		0.367
(0.788) 		0.877
(1.00) 		0.217
(0.698) 		0.0996
(0.576) 		0.107
(0.585) 		0.113
(0.586) 		0.555
(0.917) 		0.717
(1.00) 		0.736
(1.00)
22q loss 66 (18%) 291 0.646
(0.954) 		0.267
(0.731) 		0.135
(0.626) 		0.0349
(0.42) 		1
(1.00) 		0.579
(0.927) 		0.381
(0.799) 		0.0303
(0.394) 		0.0124
(0.331) 		0.00841
(0.295) 		0.0306
(0.394)
xq loss 68 (19%) 289 0.458
(0.865) 		0.0635
(0.553) 		0.846
(1.00) 		0.47
(0.873) 		0.463
(0.868) 		0.583
(0.927) 		0.0302
(0.394) 		0.161
(0.664) 		0.624
(0.944) 		0.178
(0.691) 		1
(1.00)
'2p gain' versus 'GENDER'

P value = 8.98e-05 (Fisher's exact test), Q value = 0.036

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

nPatients FEMALE MALE
ALL 113 244
2P GAIN MUTATED 26 18
2P GAIN WILD-TYPE 87 226

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

'2q gain' versus 'GENDER'

P value = 0.000449 (Fisher's exact test), Q value = 0.081

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

nPatients FEMALE MALE
ALL 113 244
2Q GAIN MUTATED 23 17
2Q GAIN WILD-TYPE 90 227

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

'8q gain' versus 'GENDER'

P value = 0.000969 (Fisher's exact test), Q value = 0.12

Table S3.  Gene #16: '8q gain' versus Clinical Feature #7: 'GENDER'

nPatients FEMALE MALE
ALL 113 244
8Q GAIN MUTATED 43 139
8Q GAIN WILD-TYPE 70 105

Figure S3.  Get High-res Image Gene #16: '8q gain' versus Clinical Feature #7: 'GENDER'

'10p gain' versus 'YEARS_TO_BIRTH'

P value = 0.00497 (Wilcoxon-test), Q value = 0.23

Table S4.  Gene #19: '10p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 354 59.8 (12.7)
10P GAIN MUTATED 60 55.9 (12.1)
10P GAIN WILD-TYPE 294 60.5 (12.7)

Figure S4.  Get High-res Image Gene #19: '10p gain' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'12p gain' versus 'HISTOLOGICAL_TYPE'

P value = 0.00521 (Fisher's exact test), Q value = 0.23

Table S5.  Gene #23: '12p gain' versus Clinical Feature #8: 'HISTOLOGICAL_TYPE'

nPatients FIBROLAMELLAR CARCINOMA HEPATOCELLULAR CARCINOMA HEPATOCHOLANGIOCARCINOMA (MIXED)
ALL 2 348 7
12P GAIN MUTATED 0 35 4
12P GAIN WILD-TYPE 2 313 3

Figure S5.  Get High-res Image Gene #23: '12p gain' versus Clinical Feature #8: 'HISTOLOGICAL_TYPE'

'22q gain' versus 'PATHOLOGY_T_STAGE'

P value = 0.00333 (Fisher's exact test), Q value = 0.21

Table S6.  Gene #39: '22q gain' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

nPatients T0+T1 T2 T3 T4
ALL 179 91 73 12
22Q GAIN MUTATED 13 17 16 2
22Q GAIN WILD-TYPE 166 74 57 10

Figure S6.  Get High-res Image Gene #39: '22q gain' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

'3p loss' versus 'PATHOLOGY_T_STAGE'

P value = 0.00277 (Fisher's exact test), Q value = 0.21

Table S7.  Gene #46: '3p loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

nPatients T0+T1 T2 T3 T4
ALL 179 91 73 12
3P LOSS MUTATED 14 16 17 3
3P LOSS WILD-TYPE 165 75 56 9

Figure S7.  Get High-res Image Gene #46: '3p loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

'3p loss' versus 'HISTOLOGICAL_TYPE'

P value = 0.00353 (Fisher's exact test), Q value = 0.21

Table S8.  Gene #46: '3p loss' versus Clinical Feature #8: 'HISTOLOGICAL_TYPE'

nPatients FIBROLAMELLAR CARCINOMA HEPATOCELLULAR CARCINOMA HEPATOCHOLANGIOCARCINOMA (MIXED)
ALL 2 348 7
3P LOSS MUTATED 1 45 4
3P LOSS WILD-TYPE 1 303 3

Figure S8.  Get High-res Image Gene #46: '3p loss' versus Clinical Feature #8: 'HISTOLOGICAL_TYPE'

'4q loss' versus 'YEARS_TO_BIRTH'

P value = 0.00336 (Wilcoxon-test), Q value = 0.21

Table S9.  Gene #49: '4q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 354 59.8 (12.7)
4Q LOSS MUTATED 140 57.4 (13.4)
4Q LOSS WILD-TYPE 214 61.3 (12.0)

Figure S9.  Get High-res Image Gene #49: '4q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'4q loss' versus 'RACE'

P value = 0.00091 (Fisher's exact test), Q value = 0.12

Table S10.  Gene #49: '4q loss' versus Clinical Feature #10: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 1 156 17 173
4Q LOSS MUTATED 0 79 9 54
4Q LOSS WILD-TYPE 1 77 8 119

Figure S10.  Get High-res Image Gene #49: '4q loss' versus Clinical Feature #10: 'RACE'

'7q loss' versus 'Time to Death'

P value = 0.00427 (logrank test), Q value = 0.21

Table S11.  Gene #55: '7q loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 334 109 0.0 - 120.8 (19.3)
7Q LOSS MUTATED 17 10 0.2 - 76.4 (13.7)
7Q LOSS WILD-TYPE 317 99 0.0 - 120.8 (19.5)

Figure S11.  Get High-res Image Gene #55: '7q loss' versus Clinical Feature #1: 'Time to Death'

'10q loss' versus 'RACE'

P value = 0.00026 (Fisher's exact test), Q value = 0.059

Table S12.  Gene #61: '10q loss' versus Clinical Feature #10: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 1 156 17 173
10Q LOSS MUTATED 0 38 10 26
10Q LOSS WILD-TYPE 1 118 7 147

Figure S12.  Get High-res Image Gene #61: '10q loss' versus Clinical Feature #10: 'RACE'

'12q loss' versus 'NEOPLASM_DISEASESTAGE'

P value = 0.00425 (Fisher's exact test), Q value = 0.21

Table S13.  Gene #65: '12q loss' versus Clinical Feature #3: 'NEOPLASM_DISEASESTAGE'

nPatients STAGE I STAGE II STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA STAGE IVB
ALL 168 84 3 59 8 7 3 1 2
12Q LOSS MUTATED 12 9 1 5 2 0 3 0 0
12Q LOSS WILD-TYPE 156 75 2 54 6 7 0 1 2

Figure S13.  Get High-res Image Gene #65: '12q loss' versus Clinical Feature #3: 'NEOPLASM_DISEASESTAGE'

'13q loss' versus 'PATHOLOGY_T_STAGE'

P value = 0.00129 (Fisher's exact test), Q value = 0.15

Table S14.  Gene #66: '13q loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

nPatients T0+T1 T2 T3 T4
ALL 179 91 73 12
13Q LOSS MUTATED 47 37 22 9
13Q LOSS WILD-TYPE 132 54 51 3

Figure S14.  Get High-res Image Gene #66: '13q loss' versus Clinical Feature #4: 'PATHOLOGY_T_STAGE'

'16p loss' versus 'YEARS_TO_BIRTH'

P value = 0.00212 (Wilcoxon-test), Q value = 0.19

Table S15.  Gene #69: '16p loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 354 59.8 (12.7)
16P LOSS MUTATED 107 56.9 (12.8)
16P LOSS WILD-TYPE 247 61.0 (12.5)

Figure S15.  Get High-res Image Gene #69: '16p loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'16p loss' versus 'RACE'

P value = 0.00389 (Fisher's exact test), Q value = 0.21

Table S16.  Gene #69: '16p loss' versus Clinical Feature #10: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 1 156 17 173
16P LOSS MUTATED 0 62 6 39
16P LOSS WILD-TYPE 1 94 11 134

Figure S16.  Get High-res Image Gene #69: '16p loss' versus Clinical Feature #10: 'RACE'

'16q loss' versus 'YEARS_TO_BIRTH'

P value = 0.000119 (Wilcoxon-test), Q value = 0.036

Table S17.  Gene #70: '16q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

nPatients Mean (Std.Dev)
ALL 354 59.8 (12.7)
16Q LOSS MUTATED 142 56.8 (12.9)
16Q LOSS WILD-TYPE 212 61.7 (12.2)

Figure S17.  Get High-res Image Gene #70: '16q loss' versus Clinical Feature #2: 'YEARS_TO_BIRTH'

'16q loss' versus 'RACE'

P value = 1e-05 (Fisher's exact test), Q value = 0.009

Table S18.  Gene #70: '16q loss' versus Clinical Feature #10: 'RACE'

nPatients AMERICAN INDIAN OR ALASKA NATIVE ASIAN BLACK OR AFRICAN AMERICAN WHITE
ALL 1 156 17 173
16Q LOSS MUTATED 0 84 7 49
16Q LOSS WILD-TYPE 1 72 10 124

Figure S18.  Get High-res Image Gene #70: '16q loss' versus Clinical Feature #10: 'RACE'

'17p loss' versus 'NEOPLASM_DISEASESTAGE'

P value = 0.00145 (Fisher's exact test), Q value = 0.15

Table S19.  Gene #71: '17p loss' versus Clinical Feature #3: 'NEOPLASM_DISEASESTAGE'

nPatients STAGE I STAGE II STAGE III STAGE IIIA STAGE IIIB STAGE IIIC STAGE IV STAGE IVA STAGE IVB
ALL 168 84 3 59 8 7 3 1 2
17P LOSS MUTATED 67 48 2 33 3 7 3 1 1
17P LOSS WILD-TYPE 101 36 1 26 5 0 0 0 1

Figure S19.  Get High-res Image Gene #71: '17p loss' versus Clinical Feature #3: 'NEOPLASM_DISEASESTAGE'

'xp loss' versus 'GENDER'

P value = 0.00407 (Fisher's exact test), Q value = 0.21

Table S20.  Gene #81: 'xp loss' versus Clinical Feature #7: 'GENDER'

nPatients FEMALE MALE
ALL 113 244
XP LOSS MUTATED 18 74
XP LOSS WILD-TYPE 95 170

Figure S20.  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/15089886/transformed.cor.cli.txt

  • Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/LIHC-TP/15082975/LIHC-TP.merged_data.txt

  • Number of patients = 357

  • Number of significantly arm-level cnvs = 82

  • Number of selected clinical features = 11

  • 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.

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)
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