Correlation between copy number variations of arm-level result and selected clinical features
Glioblastoma Multiforme (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
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 (2014): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1GX49FS
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 80 arm-level events and 8 clinical features across 565 patients, 11 significant findings detected with Q value < 0.25.

  • 7p gain cnv correlated to 'Time to Death' and 'AGE'.

  • 7q gain cnv correlated to 'Time to Death' and 'AGE'.

  • 10p gain cnv correlated to 'AGE'.

  • 20p gain cnv correlated to 'AGE'.

  • 20q gain cnv correlated to 'AGE'.

  • 10p loss cnv correlated to 'Time to Death' and 'AGE'.

  • 10q loss cnv correlated to 'Time to Death' and 'AGE'.

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

Clinical
Features
Time
to
Death
AGE GENDER KARNOFSKY
PERFORMANCE
SCORE
HISTOLOGICAL
TYPE
RADIATIONS
RADIATION
REGIMENINDICATION
RACE ETHNICITY
nCNV (%) nWild-Type logrank test Wilcoxon-test Fisher's exact test Wilcoxon-test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
7p gain 458 (81%) 107 0.000108
(0.0682)
4.34e-06
(0.00276)
0.827
(1.00)
0.853
(1.00)
0.0205
(1.00)
0.136
(1.00)
0.0536
(1.00)
0.27
(1.00)
7q gain 463 (82%) 102 0.000282
(0.177)
1.48e-05
(0.00942)
0.314
(1.00)
0.96
(1.00)
0.0301
(1.00)
0.103
(1.00)
0.0335
(1.00)
0.249
(1.00)
10p loss 472 (84%) 93 2.98e-05
(0.0189)
6.98e-09
(4.46e-06)
0.245
(1.00)
0.165
(1.00)
0.00488
(1.00)
0.629
(1.00)
0.105
(1.00)
0.132
(1.00)
10q loss 483 (85%) 82 7.54e-05
(0.0477)
5.06e-08
(3.23e-05)
0.541
(1.00)
0.0142
(1.00)
0.0411
(1.00)
0.799
(1.00)
0.0661
(1.00)
0.0902
(1.00)
10p gain 12 (2%) 553 0.00415
(1.00)
0.000204
(0.129)
0.0707
(1.00)
0.633
(1.00)
0.379
(1.00)
1
(1.00)
0.0292
(1.00)
0.265
(1.00)
20p gain 217 (38%) 348 0.486
(1.00)
4.6e-05
(0.0292)
0.33
(1.00)
0.54
(1.00)
0.353
(1.00)
0.407
(1.00)
0.025
(1.00)
1
(1.00)
20q gain 215 (38%) 350 0.669
(1.00)
0.00023
(0.145)
0.25
(1.00)
0.722
(1.00)
0.35
(1.00)
0.518
(1.00)
0.0376
(1.00)
1
(1.00)
1p gain 81 (14%) 484 0.219
(1.00)
0.469
(1.00)
0.624
(1.00)
0.24
(1.00)
0.0627
(1.00)
0.306
(1.00)
0.947
(1.00)
0.667
(1.00)
1q gain 88 (16%) 477 0.57
(1.00)
0.618
(1.00)
0.342
(1.00)
0.335
(1.00)
0.387
(1.00)
0.389
(1.00)
0.584
(1.00)
0.691
(1.00)
2p gain 37 (7%) 528 0.595
(1.00)
0.788
(1.00)
0.163
(1.00)
0.544
(1.00)
1
(1.00)
0.72
(1.00)
0.24
(1.00)
1
(1.00)
2q gain 36 (6%) 529 0.486
(1.00)
0.313
(1.00)
0.378
(1.00)
0.383
(1.00)
1
(1.00)
1
(1.00)
0.23
(1.00)
1
(1.00)
3p gain 56 (10%) 509 0.981
(1.00)
0.0251
(1.00)
0.391
(1.00)
0.888
(1.00)
0.264
(1.00)
1
(1.00)
0.922
(1.00)
1
(1.00)
3q gain 62 (11%) 503 0.734
(1.00)
0.0702
(1.00)
0.492
(1.00)
0.811
(1.00)
0.211
(1.00)
0.569
(1.00)
0.928
(1.00)
1
(1.00)
4p gain 36 (6%) 529 0.899
(1.00)
0.49
(1.00)
0.86
(1.00)
0.0747
(1.00)
1
(1.00)
0.586
(1.00)
0.549
(1.00)
0.58
(1.00)
4q gain 33 (6%) 532 0.968
(1.00)
0.561
(1.00)
0.467
(1.00)
0.0712
(1.00)
1
(1.00)
0.343
(1.00)
0.385
(1.00)
1
(1.00)
5p gain 49 (9%) 516 0.822
(1.00)
0.681
(1.00)
0.169
(1.00)
0.207
(1.00)
0.0568
(1.00)
0.751
(1.00)
1
(1.00)
0.303
(1.00)
5q gain 41 (7%) 524 0.657
(1.00)
0.529
(1.00)
0.134
(1.00)
0.736
(1.00)
0.0813
(1.00)
0.605
(1.00)
0.741
(1.00)
0.612
(1.00)
6p gain 24 (4%) 541 0.413
(1.00)
0.494
(1.00)
0.671
(1.00)
0.766
(1.00)
1
(1.00)
0.268
(1.00)
0.572
(1.00)
1
(1.00)
6q gain 23 (4%) 542 0.359
(1.00)
0.248
(1.00)
1
(1.00)
0.73
(1.00)
1
(1.00)
0.651
(1.00)
0.461
(1.00)
1
(1.00)
8p gain 52 (9%) 513 0.826
(1.00)
0.808
(1.00)
0.657
(1.00)
0.595
(1.00)
0.74
(1.00)
0.757
(1.00)
0.229
(1.00)
1
(1.00)
8q gain 59 (10%) 506 0.478
(1.00)
0.368
(1.00)
0.482
(1.00)
0.699
(1.00)
0.642
(1.00)
1
(1.00)
0.484
(1.00)
1
(1.00)
9p gain 47 (8%) 518 0.626
(1.00)
0.646
(1.00)
0.164
(1.00)
0.875
(1.00)
0.221
(1.00)
0.871
(1.00)
0.386
(1.00)
0.245
(1.00)
9q gain 70 (12%) 495 0.867
(1.00)
0.931
(1.00)
0.153
(1.00)
0.814
(1.00)
0.503
(1.00)
0.892
(1.00)
0.479
(1.00)
0.646
(1.00)
10q gain 3 (1%) 562 0.472
(1.00)
0.66
(1.00)
0.565
(1.00)
1
(1.00)
0.249
(1.00)
1
(1.00)
0.0734
(1.00)
11p gain 17 (3%) 548 0.6
(1.00)
0.955
(1.00)
0.806
(1.00)
0.374
(1.00)
1
(1.00)
0.6
(1.00)
0.595
(1.00)
0.338
(1.00)
11q gain 14 (2%) 551 0.147
(1.00)
0.116
(1.00)
0.267
(1.00)
0.164
(1.00)
0.435
(1.00)
0.162
(1.00)
1
(1.00)
0.302
(1.00)
12p gain 58 (10%) 507 0.635
(1.00)
0.416
(1.00)
0.571
(1.00)
0.789
(1.00)
0.767
(1.00)
0.461
(1.00)
0.853
(1.00)
1
(1.00)
12q gain 47 (8%) 518 0.981
(1.00)
0.786
(1.00)
0.279
(1.00)
0.936
(1.00)
0.522
(1.00)
0.518
(1.00)
0.0955
(1.00)
1
(1.00)
13q gain 10 (2%) 555 0.537
(1.00)
0.011
(1.00)
0.202
(1.00)
0.072
(1.00)
0.52
(1.00)
0.0859
(1.00)
0.675
(1.00)
1
(1.00)
14q gain 22 (4%) 543 0.256
(1.00)
0.0587
(1.00)
0.513
(1.00)
0.471
(1.00)
0.0737
(1.00)
0.817
(1.00)
1
(1.00)
1
(1.00)
15q gain 24 (4%) 541 0.495
(1.00)
0.883
(1.00)
0.527
(1.00)
0.0921
(1.00)
0.66
(1.00)
0.182
(1.00)
0.84
(1.00)
1
(1.00)
16p gain 38 (7%) 527 0.0323
(1.00)
0.851
(1.00)
0.306
(1.00)
0.957
(1.00)
1
(1.00)
0.0716
(1.00)
0.315
(1.00)
1
(1.00)
16q gain 37 (7%) 528 0.121
(1.00)
0.872
(1.00)
0.606
(1.00)
0.848
(1.00)
1
(1.00)
0.0714
(1.00)
0.266
(1.00)
1
(1.00)
17p gain 47 (8%) 518 0.227
(1.00)
0.0379
(1.00)
0.212
(1.00)
0.387
(1.00)
0.639
(1.00)
0.417
(1.00)
0.521
(1.00)
1
(1.00)
17q gain 58 (10%) 507 0.0362
(1.00)
0.0202
(1.00)
0.48
(1.00)
0.473
(1.00)
0.638
(1.00)
0.376
(1.00)
0.593
(1.00)
0.371
(1.00)
18p gain 57 (10%) 508 0.757
(1.00)
0.394
(1.00)
0.669
(1.00)
0.237
(1.00)
0.086
(1.00)
0.766
(1.00)
0.292
(1.00)
0.352
(1.00)
18q gain 57 (10%) 508 0.909
(1.00)
0.229
(1.00)
0.2
(1.00)
0.24
(1.00)
0.0864
(1.00)
0.551
(1.00)
0.498
(1.00)
1
(1.00)
19p gain 219 (39%) 346 0.383
(1.00)
0.806
(1.00)
0.791
(1.00)
0.979
(1.00)
0.619
(1.00)
0.854
(1.00)
0.578
(1.00)
0.55
(1.00)
19q gain 193 (34%) 372 0.446
(1.00)
0.588
(1.00)
0.586
(1.00)
0.884
(1.00)
0.929
(1.00)
0.571
(1.00)
0.33
(1.00)
0.355
(1.00)
21q gain 62 (11%) 503 0.598
(1.00)
0.106
(1.00)
1
(1.00)
0.125
(1.00)
0.141
(1.00)
1
(1.00)
0.106
(1.00)
0.376
(1.00)
22q gain 34 (6%) 531 0.419
(1.00)
0.576
(1.00)
1
(1.00)
0.322
(1.00)
0.399
(1.00)
1
(1.00)
0.686
(1.00)
0.151
(1.00)
xq gain 16 (3%) 549 0.846
(1.00)
0.557
(1.00)
1
(1.00)
0.619
(1.00)
0.313
(1.00)
0.174
(1.00)
0.733
(1.00)
0.246
(1.00)
1p loss 15 (3%) 550 0.281
(1.00)
0.0518
(1.00)
0.425
(1.00)
0.819
(1.00)
0.464
(1.00)
0.58
(1.00)
0.732
(1.00)
1
(1.00)
1q loss 14 (2%) 551 0.519
(1.00)
0.0265
(1.00)
1
(1.00)
0.17
(1.00)
1
(1.00)
0.4
(1.00)
0.712
(1.00)
1
(1.00)
2p loss 31 (5%) 534 0.819
(1.00)
0.0829
(1.00)
0.0877
(1.00)
0.844
(1.00)
1
(1.00)
0.324
(1.00)
0.671
(1.00)
1
(1.00)
2q loss 31 (5%) 534 0.996
(1.00)
0.111
(1.00)
0.185
(1.00)
0.572
(1.00)
0.52
(1.00)
0.166
(1.00)
0.673
(1.00)
1
(1.00)
3p loss 40 (7%) 525 0.291
(1.00)
0.0681
(1.00)
1
(1.00)
0.998
(1.00)
0.464
(1.00)
0.0827
(1.00)
0.583
(1.00)
0.207
(1.00)
3q loss 34 (6%) 531 0.766
(1.00)
0.652
(1.00)
0.589
(1.00)
0.636
(1.00)
0.745
(1.00)
0.572
(1.00)
0.697
(1.00)
0.519
(1.00)
4p loss 53 (9%) 512 0.752
(1.00)
0.733
(1.00)
0.184
(1.00)
0.258
(1.00)
0.416
(1.00)
0.541
(1.00)
0.577
(1.00)
0.303
(1.00)
4q loss 54 (10%) 511 0.214
(1.00)
0.122
(1.00)
0.771
(1.00)
0.305
(1.00)
1
(1.00)
0.76
(1.00)
0.587
(1.00)
0.284
(1.00)
5p loss 42 (7%) 523 0.056
(1.00)
0.518
(1.00)
1
(1.00)
0.567
(1.00)
0.48
(1.00)
0.0252
(1.00)
0.109
(1.00)
0.207
(1.00)
5q loss 43 (8%) 522 0.108
(1.00)
0.568
(1.00)
1
(1.00)
0.757
(1.00)
0.254
(1.00)
0.126
(1.00)
0.404
(1.00)
0.0499
(1.00)
6p loss 86 (15%) 479 0.00482
(1.00)
0.388
(1.00)
0.811
(1.00)
0.496
(1.00)
0.677
(1.00)
0.619
(1.00)
0.239
(1.00)
0.701
(1.00)
6q loss 124 (22%) 441 0.369
(1.00)
0.761
(1.00)
0.298
(1.00)
0.691
(1.00)
0.789
(1.00)
1
(1.00)
0.18
(1.00)
0.478
(1.00)
7p loss 8 (1%) 557 0.355
(1.00)
0.0522
(1.00)
1
(1.00)
0.741
(1.00)
1
(1.00)
0.448
(1.00)
0.592
(1.00)
1
(1.00)
7q loss 6 (1%) 559 0.528
(1.00)
0.0236
(1.00)
1
(1.00)
0.303
(1.00)
1
(1.00)
0.669
(1.00)
0.488
(1.00)
1
(1.00)
8p loss 58 (10%) 507 0.602
(1.00)
0.175
(1.00)
0.156
(1.00)
0.39
(1.00)
0.768
(1.00)
0.461
(1.00)
0.00535
(1.00)
0.62
(1.00)
8q loss 42 (7%) 523 0.201
(1.00)
0.211
(1.00)
0.416
(1.00)
0.245
(1.00)
1
(1.00)
0.866
(1.00)
0.304
(1.00)
1
(1.00)
9p loss 197 (35%) 368 0.71
(1.00)
0.547
(1.00)
0.652
(1.00)
0.525
(1.00)
0.81
(1.00)
0.707
(1.00)
0.437
(1.00)
0.064
(1.00)
9q loss 92 (16%) 473 0.578
(1.00)
0.741
(1.00)
0.414
(1.00)
0.77
(1.00)
0.211
(1.00)
0.716
(1.00)
0.226
(1.00)
0.234
(1.00)
11p loss 98 (17%) 467 0.184
(1.00)
0.948
(1.00)
0.111
(1.00)
0.759
(1.00)
0.449
(1.00)
0.636
(1.00)
0.652
(1.00)
0.7
(1.00)
11q loss 93 (16%) 472 0.904
(1.00)
0.361
(1.00)
0.419
(1.00)
0.773
(1.00)
1
(1.00)
0.276
(1.00)
1
(1.00)
0.229
(1.00)
12p loss 58 (10%) 507 0.999
(1.00)
0.62
(1.00)
0.48
(1.00)
0.778
(1.00)
0.835
(1.00)
0.461
(1.00)
0.298
(1.00)
1
(1.00)
12q loss 57 (10%) 508 0.96
(1.00)
0.667
(1.00)
0.568
(1.00)
0.611
(1.00)
0.518
(1.00)
1
(1.00)
0.291
(1.00)
0.333
(1.00)
13q loss 183 (32%) 382 0.75
(1.00)
0.715
(1.00)
1
(1.00)
0.76
(1.00)
0.594
(1.00)
0.701
(1.00)
0.5
(1.00)
0.759
(1.00)
14q loss 144 (25%) 421 0.976
(1.00)
0.689
(1.00)
0.429
(1.00)
0.881
(1.00)
0.546
(1.00)
0.758
(1.00)
0.199
(1.00)
0.311
(1.00)
15q loss 102 (18%) 463 0.712
(1.00)
0.0527
(1.00)
0.576
(1.00)
0.982
(1.00)
0.719
(1.00)
0.0799
(1.00)
0.516
(1.00)
0.249
(1.00)
16p loss 63 (11%) 502 0.042
(1.00)
0.312
(1.00)
0.683
(1.00)
0.862
(1.00)
0.279
(1.00)
0.045
(1.00)
1
(1.00)
1
(1.00)
16q loss 82 (15%) 483 0.015
(1.00)
0.83
(1.00)
1
(1.00)
0.599
(1.00)
0.59
(1.00)
0.0216
(1.00)
0.481
(1.00)
0.699
(1.00)
17p loss 62 (11%) 503 0.658
(1.00)
0.579
(1.00)
0.336
(1.00)
0.947
(1.00)
0.919
(1.00)
0.196
(1.00)
0.933
(1.00)
1
(1.00)
17q loss 40 (7%) 525 0.978
(1.00)
0.472
(1.00)
0.503
(1.00)
0.69
(1.00)
1
(1.00)
0.0527
(1.00)
0.591
(1.00)
0.591
(1.00)
18p loss 69 (12%) 496 0.129
(1.00)
0.73
(1.00)
0.602
(1.00)
0.601
(1.00)
0.682
(1.00)
1
(1.00)
0.325
(1.00)
0.646
(1.00)
18q loss 61 (11%) 504 0.3
(1.00)
0.682
(1.00)
0.89
(1.00)
0.278
(1.00)
0.777
(1.00)
0.248
(1.00)
0.199
(1.00)
0.143
(1.00)
19p loss 27 (5%) 538 0.548
(1.00)
0.948
(1.00)
1
(1.00)
0.749
(1.00)
0.843
(1.00)
0.835
(1.00)
1
(1.00)
1
(1.00)
19q loss 35 (6%) 530 0.661
(1.00)
0.877
(1.00)
1
(1.00)
0.766
(1.00)
0.335
(1.00)
1
(1.00)
0.794
(1.00)
1
(1.00)
20p loss 18 (3%) 547 0.857
(1.00)
0.382
(1.00)
0.219
(1.00)
0.92
(1.00)
1
(1.00)
1
(1.00)
0.287
(1.00)
0.338
(1.00)
20q loss 16 (3%) 549 0.765
(1.00)
0.715
(1.00)
0.196
(1.00)
0.988
(1.00)
1
(1.00)
0.787
(1.00)
0.754
(1.00)
1
(1.00)
21q loss 41 (7%) 524 0.968
(1.00)
0.852
(1.00)
0.619
(1.00)
0.321
(1.00)
1
(1.00)
0.388
(1.00)
0.821
(1.00)
0.235
(1.00)
22q loss 180 (32%) 385 0.482
(1.00)
0.11
(1.00)
0.926
(1.00)
0.437
(1.00)
0.569
(1.00)
0.847
(1.00)
0.78
(1.00)
1
(1.00)
xq loss 104 (18%) 461 0.364
(1.00)
0.729
(1.00)
0.375
(1.00)
0.394
(1.00)
0.852
(1.00)
0.729
(1.00)
0.193
(1.00)
0.468
(1.00)
'7p gain' versus 'Time to Death'

P value = 0.000108 (logrank test), Q value = 0.068

Table S1.  Gene #13: '7p gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 565 462 0.1 - 127.6 (10.0)
7P GAIN MUTATED 458 382 0.1 - 127.6 (9.7)
7P GAIN WILD-TYPE 107 80 0.2 - 108.8 (12.4)

Figure S1.  Get High-res Image Gene #13: '7p gain' versus Clinical Feature #1: 'Time to Death'

'7p gain' versus 'AGE'

P value = 4.34e-06 (Wilcoxon-test), Q value = 0.0028

Table S2.  Gene #13: '7p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 565 57.8 (14.5)
7P GAIN MUTATED 458 59.6 (12.4)
7P GAIN WILD-TYPE 107 49.8 (19.4)

Figure S2.  Get High-res Image Gene #13: '7p gain' versus Clinical Feature #2: 'AGE'

'7q gain' versus 'Time to Death'

P value = 0.000282 (logrank test), Q value = 0.18

Table S3.  Gene #14: '7q gain' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 565 462 0.1 - 127.6 (10.0)
7Q GAIN MUTATED 463 383 0.1 - 127.6 (9.6)
7Q GAIN WILD-TYPE 102 79 0.2 - 108.8 (13.8)

Figure S3.  Get High-res Image Gene #14: '7q gain' versus Clinical Feature #1: 'Time to Death'

'7q gain' versus 'AGE'

P value = 1.48e-05 (Wilcoxon-test), Q value = 0.0094

Table S4.  Gene #14: '7q gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 565 57.8 (14.5)
7Q GAIN MUTATED 463 59.6 (12.3)
7Q GAIN WILD-TYPE 102 49.6 (20.1)

Figure S4.  Get High-res Image Gene #14: '7q gain' versus Clinical Feature #2: 'AGE'

'10p gain' versus 'AGE'

P value = 0.000204 (Wilcoxon-test), Q value = 0.13

Table S5.  Gene #19: '10p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 565 57.8 (14.5)
10P GAIN MUTATED 12 38.1 (18.1)
10P GAIN WILD-TYPE 553 58.2 (14.1)

Figure S5.  Get High-res Image Gene #19: '10p gain' versus Clinical Feature #2: 'AGE'

'20p gain' versus 'AGE'

P value = 4.6e-05 (Wilcoxon-test), Q value = 0.029

Table S6.  Gene #36: '20p gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 565 57.8 (14.5)
20P GAIN MUTATED 217 60.9 (13.0)
20P GAIN WILD-TYPE 348 55.8 (15.0)

Figure S6.  Get High-res Image Gene #36: '20p gain' versus Clinical Feature #2: 'AGE'

'20q gain' versus 'AGE'

P value = 0.00023 (Wilcoxon-test), Q value = 0.14

Table S7.  Gene #37: '20q gain' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 565 57.8 (14.5)
20Q GAIN MUTATED 215 60.7 (13.3)
20Q GAIN WILD-TYPE 350 56.0 (14.9)

Figure S7.  Get High-res Image Gene #37: '20q gain' versus Clinical Feature #2: 'AGE'

'10p loss' versus 'Time to Death'

P value = 2.98e-05 (logrank test), Q value = 0.019

Table S8.  Gene #59: '10p loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 565 462 0.1 - 127.6 (10.0)
10P LOSS MUTATED 472 391 0.1 - 127.6 (9.8)
10P LOSS WILD-TYPE 93 71 0.2 - 108.8 (12.7)

Figure S8.  Get High-res Image Gene #59: '10p loss' versus Clinical Feature #1: 'Time to Death'

'10p loss' versus 'AGE'

P value = 6.98e-09 (Wilcoxon-test), Q value = 4.5e-06

Table S9.  Gene #59: '10p loss' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 565 57.8 (14.5)
10P LOSS MUTATED 472 59.6 (12.7)
10P LOSS WILD-TYPE 93 48.1 (18.8)

Figure S9.  Get High-res Image Gene #59: '10p loss' versus Clinical Feature #2: 'AGE'

'10q loss' versus 'Time to Death'

P value = 7.54e-05 (logrank test), Q value = 0.048

Table S10.  Gene #60: '10q loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 565 462 0.1 - 127.6 (10.0)
10Q LOSS MUTATED 483 400 0.1 - 127.6 (9.9)
10Q LOSS WILD-TYPE 82 62 0.2 - 108.8 (12.2)

Figure S10.  Get High-res Image Gene #60: '10q loss' versus Clinical Feature #1: 'Time to Death'

'10q loss' versus 'AGE'

P value = 5.06e-08 (Wilcoxon-test), Q value = 3.2e-05

Table S11.  Gene #60: '10q loss' versus Clinical Feature #2: 'AGE'

nPatients Mean (Std.Dev)
ALL 565 57.8 (14.5)
10Q LOSS MUTATED 483 59.4 (13.0)
10Q LOSS WILD-TYPE 82 48.1 (18.5)

Figure S11.  Get High-res Image Gene #60: '10q loss' versus Clinical Feature #2: 'AGE'

Methods & Data
Input
  • Copy number data file = transformed.cor.cli.txt

  • Clinical data file = GBM-TP.merged_data.txt

  • Number of patients = 565

  • Number of significantly arm-level cnvs = 80

  • Number of selected clinical features = 8

  • 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)