Correlation between copy number variations of arm-level result and selected clinical features
Kidney Chromophobe (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C1S46R56
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between copy number variations of arm-level result and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C1S46R56
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 63 arm-level events and 12 clinical features across 66 patients, 8 significant findings detected with Q value < 0.25.

  • 5p gain cnv correlated to 'PATHOLOGIC_STAGE'.

  • 5q gain cnv correlated to 'PATHOLOGIC_STAGE'.

  • 19p gain cnv correlated to 'PATHOLOGY_N_STAGE'.

  • 16p loss cnv correlated to 'Time to Death',  'PATHOLOGIC_STAGE', and 'PATHOLOGY_N_STAGE'.

  • 16q loss cnv correlated to 'Time to Death' and 'PATHOLOGY_N_STAGE'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 63 arm-level events and 12 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 8 significant findings detected.

Clinical
Features 		Time
to
Death 		YEARS
TO
BIRTH 		PATHOLOGIC
STAGE 		PATHOLOGY
T
STAGE 		PATHOLOGY
N
STAGE 		PATHOLOGY
M
STAGE 		GENDER KARNOFSKY
PERFORMANCE
SCORE 		NUMBER
PACK
YEARS
SMOKED 		YEAR
OF
TOBACCO
SMOKING
ONSET 		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 Wilcoxon-test Wilcoxon-test Fisher's exact test Fisher's exact test
16p loss 4 (6%) 62 3.48e-09
(1.32e-06) 		0.519
(1.00) 		0.00039
(0.059) 		0.00657
(0.354) 		3.36e-05
(0.00846) 		0.11
(0.723) 		0.639
(1.00) 		1
(1.00) 		1
(1.00)
16q loss 5 (8%) 61 2.01e-09
(1.32e-06) 		0.221
(0.888) 		0.00442
(0.304) 		0.0482
(0.587) 		0.000165
(0.0311) 		0.11
(0.723) 		0.641
(1.00) 		1
(1.00) 		1
(1.00)
5p gain 8 (12%) 58 0.00702
(0.354) 		0.0661
(0.649) 		0.00193
(0.208) 		0.363
(1.00) 		0.0874
(0.654) 		0.00952
(0.379) 		0.455
(1.00) 		1
(1.00) 		1
(1.00)
5q gain 8 (12%) 58 0.00702
(0.354) 		0.0661
(0.649) 		0.00141
(0.178) 		0.365
(1.00) 		0.0874
(0.654) 		0.00952
(0.379) 		0.455
(1.00) 		1
(1.00) 		1
(1.00)
19p gain 19 (29%) 47 0.0192
(0.502) 		0.0291
(0.569) 		0.0152
(0.441) 		0.519
(1.00) 		0.00246
(0.232) 		0.0571
(0.617) 		0.412
(1.00) 		1
(1.00) 		0.784
(1.00) 		0.0606
(0.619) 		0.256
(0.936) 		0.29
(0.94)
3p gain 8 (12%) 58 0.00834
(0.371) 		0.0837
(0.654) 		0.0163
(0.441) 		0.466
(1.00) 		0.0327
(0.569) 		0.213
(0.869) 		0.128
(0.723) 		1
(1.00) 		0.292
(0.94) 		1
(1.00)
3q gain 8 (12%) 58 0.00834
(0.371) 		0.0837
(0.654) 		0.0159
(0.441) 		0.467
(1.00) 		0.0327
(0.569) 		0.213
(0.869) 		0.128
(0.723) 		1
(1.00) 		0.295
(0.94) 		1
(1.00)
4p gain 24 (36%) 42 0.885
(1.00) 		0.265
(0.94) 		0.141
(0.731) 		0.81
(1.00) 		1
(1.00) 		0.124
(0.723) 		1
(1.00) 		0.528
(1.00) 		0.0467
(0.579) 		0.0369
(0.569) 		1
(1.00) 		0.287
(0.94)
4q gain 24 (36%) 42 0.885
(1.00) 		0.265
(0.94) 		0.142
(0.731) 		0.81
(1.00) 		1
(1.00) 		0.124
(0.723) 		1
(1.00) 		0.528
(1.00) 		0.0467
(0.579) 		0.0369
(0.569) 		1
(1.00) 		0.287
(0.94)
7p gain 24 (36%) 42 0.0281
(0.569) 		0.172
(0.777) 		0.361
(1.00) 		0.69
(1.00) 		0.636
(1.00) 		0.124
(0.723) 		0.195
(0.847) 		0.528
(1.00) 		0.784
(1.00) 		0.0606
(0.619) 		1
(1.00) 		0.303
(0.94)
7q gain 24 (36%) 42 0.0281
(0.569) 		0.172
(0.777) 		0.356
(1.00) 		0.69
(1.00) 		0.636
(1.00) 		0.124
(0.723) 		0.195
(0.847) 		0.528
(1.00) 		0.784
(1.00) 		0.0606
(0.619) 		1
(1.00) 		0.303
(0.94)
8p gain 17 (26%) 49 0.926
(1.00) 		0.142
(0.731) 		0.389
(1.00) 		0.407
(1.00) 		1
(1.00) 		0.443
(1.00) 		0.776
(1.00) 		0.528
(1.00) 		0.394
(1.00) 		1
(1.00) 		0.588
(1.00)
8q gain 18 (27%) 48 0.926
(1.00) 		0.15
(0.735) 		0.228
(0.894) 		0.45
(1.00) 		1
(1.00) 		0.0714
(0.654) 		0.577
(1.00) 		0.528
(1.00) 		0.394
(1.00) 		1
(1.00) 		0.588
(1.00)
9p gain 10 (15%) 56 0.624
(1.00) 		0.979
(1.00) 		0.12
(0.723) 		0.194
(0.847) 		0.306
(0.94) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.759
(1.00) 		0.375
(1.00) 		0.535
(1.00)
9q gain 10 (15%) 56 0.624
(1.00) 		0.979
(1.00) 		0.123
(0.723) 		0.193
(0.847) 		0.306
(0.94) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.759
(1.00) 		0.373
(1.00) 		0.535
(1.00)
10p gain 4 (6%) 62 0.558
(1.00) 		0.34
(1.00) 		0.267
(0.94) 		0.451
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
11p gain 15 (23%) 51 0.956
(1.00) 		0.812
(1.00) 		0.742
(1.00) 		0.812
(1.00) 		0.617
(1.00) 		0.443
(1.00) 		1
(1.00) 		1
(1.00) 		0.0467
(0.579) 		0.0369
(0.569) 		0.559
(1.00) 		0.0756
(0.654)
11q gain 15 (23%) 51 0.485
(1.00) 		0.945
(1.00) 		0.741
(1.00) 		0.81
(1.00) 		1
(1.00) 		0.443
(1.00) 		1
(1.00) 		1
(1.00) 		0.0467
(0.579) 		0.0369
(0.569) 		0.56
(1.00) 		0.0756
(0.654)
12p gain 19 (29%) 47 0.661
(1.00) 		0.0137
(0.415) 		0.0772
(0.654) 		0.317
(0.958) 		1
(1.00) 		0.0873
(0.654) 		0.412
(1.00) 		0.528
(1.00) 		0.357
(1.00) 		1
(1.00) 		1
(1.00)
12q gain 20 (30%) 46 0.209
(0.869) 		0.0696
(0.654) 		0.111
(0.723) 		0.71
(1.00) 		0.33
(0.993) 		0.0873
(0.654) 		0.593
(1.00) 		0.528
(1.00) 		0.234
(0.894) 		0.0369
(0.569) 		0.805
(1.00) 		1
(1.00)
14q gain 21 (32%) 45 0.819
(1.00) 		0.144
(0.731) 		0.0967
(0.697) 		0.381
(1.00) 		1
(1.00) 		0.105
(0.723) 		0.794
(1.00) 		0.528
(1.00) 		0.234
(0.894) 		0.0369
(0.569) 		1
(1.00) 		0.609
(1.00)
15q gain 21 (32%) 45 0.34
(1.00) 		0.283
(0.94) 		0.411
(1.00) 		0.48
(1.00) 		0.35
(1.00) 		0.105
(0.723) 		0.794
(1.00) 		0.528
(1.00) 		1
(1.00) 		0.233
(0.894) 		0.815
(1.00) 		0.124
(0.723)
16p gain 21 (32%) 45 0.217
(0.877) 		0.995
(1.00) 		0.472
(1.00) 		0.404
(1.00) 		0.635
(1.00) 		1
(1.00) 		1
(1.00) 		0.528
(1.00) 		0.0467
(0.579) 		0.0369
(0.569) 		1
(1.00) 		0.124
(0.723)
16q gain 21 (32%) 45 0.217
(0.877) 		0.995
(1.00) 		0.475
(1.00) 		0.404
(1.00) 		0.635
(1.00) 		1
(1.00) 		1
(1.00) 		0.528
(1.00) 		0.0467
(0.579) 		0.0369
(0.569) 		1
(1.00) 		0.124
(0.723)
18p gain 17 (26%) 49 0.872
(1.00) 		0.278
(0.94) 		0.293
(0.94) 		0.432
(1.00) 		0.303
(0.94) 		0.4
(1.00) 		0.776
(1.00) 		1
(1.00) 		0.298
(0.94) 		1
(1.00) 		0.57
(1.00)
18q gain 16 (24%) 50 0.355
(1.00) 		0.525
(1.00) 		0.31
(0.943) 		0.199
(0.858) 		0.303
(0.94) 		0.4
(1.00) 		1
(1.00) 		1
(1.00) 		0.298
(0.94) 		1
(1.00) 		0.305
(0.94)
19q gain 17 (26%) 49 0.106
(0.723) 		0.0137
(0.415) 		0.297
(0.94) 		0.644
(1.00) 		0.136
(0.731) 		0.0444
(0.579) 		0.776
(1.00) 		1
(1.00) 		1
(1.00) 		0.233
(0.894) 		0.594
(1.00) 		0.29
(0.94)
20p gain 20 (30%) 46 0.799
(1.00) 		0.128
(0.723) 		0.368
(1.00) 		0.793
(1.00) 		0.35
(1.00) 		0.524
(1.00) 		0.593
(1.00) 		0.528
(1.00) 		0.234
(0.894) 		0.0369
(0.569) 		0.364
(1.00) 		0.588
(1.00)
20q gain 21 (32%) 45 0.331
(0.993) 		0.053
(0.615) 		0.136
(0.731) 		0.845
(1.00) 		0.35
(1.00) 		0.524
(1.00) 		0.433
(1.00) 		0.528
(1.00) 		0.234
(0.894) 		0.0369
(0.569) 		0.367
(1.00) 		0.609
(1.00)
21q gain 4 (6%) 62 0.496
(1.00) 		0.591
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
22q gain 19 (29%) 47 0.164
(0.767) 		0.415
(1.00) 		0.49
(1.00) 		0.521
(1.00) 		0.166
(0.768) 		0.524
(1.00) 		0.412
(1.00) 		1
(1.00) 		0.784
(1.00) 		0.0606
(0.619) 		0.794
(1.00) 		0.588
(1.00)
xp gain 7 (11%) 59 0.406
(1.00) 		0.95
(1.00) 		0.698
(1.00) 		0.881
(1.00) 		1
(1.00) 		0.213
(0.869) 		0.691
(1.00) 		1
(1.00) 		0.519
(1.00) 		0.466
(1.00)
xq gain 6 (9%) 60 0.412
(1.00) 		0.815
(1.00) 		0.383
(1.00) 		0.662
(1.00) 		1
(1.00) 		0.213
(0.869) 		0.388
(1.00) 		1
(1.00) 		0.459
(1.00) 		0.39
(1.00)
1p loss 53 (80%) 13 0.431
(1.00) 		0.478
(1.00) 		0.0287
(0.569) 		0.0408
(0.579) 		1
(1.00) 		0.162
(0.76) 		0.534
(1.00) 		0.51
(1.00) 		0.609
(1.00) 		1
(1.00) 		1
(1.00)
1q loss 52 (79%) 14 0.823
(1.00) 		0.456
(1.00) 		0.00626
(0.354) 		0.0131
(0.415) 		0.529
(1.00) 		0.213
(0.869) 		0.367
(1.00) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
2p loss 46 (70%) 20 0.941
(1.00) 		0.241
(0.905) 		0.145
(0.731) 		0.114
(0.723) 		1
(1.00) 		0.4
(1.00) 		0.284
(0.94) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
2q loss 46 (70%) 20 0.941
(1.00) 		0.241
(0.905) 		0.145
(0.731) 		0.113
(0.723) 		1
(1.00) 		0.4
(1.00) 		0.284
(0.94) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
3p loss 9 (14%) 57 0.193
(0.847) 		0.0465
(0.579) 		0.0756
(0.654) 		0.0227
(0.569) 		1
(1.00) 		1
(1.00) 		0.469
(1.00) 		1
(1.00) 		0.535
(1.00)
3q loss 8 (12%) 58 0.231
(0.894) 		0.107
(0.723) 		0.142
(0.731) 		0.054
(0.615) 		1
(1.00) 		1
(1.00) 		0.256
(0.936) 		1
(1.00) 		0.535
(1.00)
5p loss 10 (15%) 56 0.771
(1.00) 		0.642
(1.00) 		0.134
(0.731) 		0.0842
(0.654) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.423
(1.00) 		0.155
(0.752) 		0.0736
(0.654) 		0.159
(0.752) 		0.121
(0.723)
5q loss 10 (15%) 56 0.771
(1.00) 		0.642
(1.00) 		0.133
(0.731) 		0.0835
(0.654) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.423
(1.00) 		0.155
(0.752) 		0.0736
(0.654) 		0.159
(0.752) 		0.121
(0.723)
6p loss 51 (77%) 15 0.579
(1.00) 		0.379
(1.00) 		0.0794
(0.654) 		0.0565
(0.617) 		0.568
(1.00) 		0.356
(1.00) 		0.244
(0.905) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
6q loss 51 (77%) 15 0.579
(1.00) 		0.379
(1.00) 		0.0841
(0.654) 		0.0549
(0.615) 		0.568
(1.00) 		0.356
(1.00) 		0.244
(0.905) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
8p loss 9 (14%) 57 0.204
(0.869) 		0.779
(1.00) 		0.741
(1.00) 		0.438
(1.00) 		1
(1.00) 		1
(1.00) 		0.727
(1.00) 		1
(1.00) 		0.615
(1.00) 		0.566
(1.00)
8q loss 8 (12%) 58 0.243
(0.905) 		0.575
(1.00) 		0.7
(1.00) 		0.411
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.567
(1.00) 		1
(1.00)
9p loss 10 (15%) 56 0.00364
(0.275) 		0.0116
(0.415) 		1
(1.00) 		1
(1.00) 		0.529
(1.00) 		1
(1.00) 		0.508
(1.00) 		1
(1.00) 		0.535
(1.00)
9q loss 10 (15%) 56 0.00364
(0.275) 		0.0116
(0.415) 		1
(1.00) 		1
(1.00) 		0.529
(1.00) 		1
(1.00) 		0.508
(1.00) 		1
(1.00) 		0.535
(1.00)
10p loss 48 (73%) 18 0.128
(0.723) 		0.762
(1.00) 		0.546
(1.00) 		0.395
(1.00) 		1
(1.00) 		0.31
(0.943) 		1
(1.00) 		0.559
(1.00) 		0.26
(0.938) 		1
(1.00) 		1
(1.00)
10q loss 49 (74%) 17 0.146
(0.731) 		0.953
(1.00) 		0.347
(1.00) 		0.21
(0.869) 		1
(1.00) 		0.31
(0.943) 		1
(1.00) 		0.559
(1.00) 		0.26
(0.938) 		1
(1.00) 		1
(1.00)
11p loss 7 (11%) 59 0.305
(0.94) 		0.0527
(0.615) 		0.0962
(0.697) 		0.0774
(0.654) 		0.461
(1.00) 		1
(1.00) 		0.691
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
11q loss 7 (11%) 59 0.305
(0.94) 		0.0527
(0.615) 		0.0961
(0.697) 		0.0784
(0.654) 		0.461
(1.00) 		1
(1.00) 		0.691
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
13q loss 43 (65%) 23 0.545
(1.00) 		0.0641
(0.646) 		0.443
(1.00) 		0.354
(1.00) 		0.301
(0.94) 		1
(1.00) 		0.294
(0.94) 		1
(1.00) 		0.474
(1.00) 		0.371
(1.00) 		0.818
(1.00) 		1
(1.00)
17p loss 50 (76%) 16 0.788
(1.00) 		0.149
(0.734) 		0.073
(0.654) 		0.0426
(0.579) 		0.568
(1.00) 		0.356
(1.00) 		0.158
(0.752) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
17q loss 50 (76%) 16 0.788
(1.00) 		0.149
(0.734) 		0.075
(0.654) 		0.0422
(0.579) 		0.568
(1.00) 		0.356
(1.00) 		0.158
(0.752) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
18p loss 8 (12%) 58 0.976
(1.00) 		0.455
(1.00) 		0.445
(1.00) 		0.899
(1.00) 		0.211
(0.869) 		1
(1.00) 		0.256
(0.936) 		1
(1.00) 		0.295
(0.94) 		1
(1.00)
18q loss 10 (15%) 56 0.433
(1.00) 		0.343
(1.00) 		0.139
(0.731) 		0.833
(1.00) 		0.258
(0.936) 		1
(1.00) 		0.295
(0.94) 		1
(1.00) 		0.376
(1.00) 		1
(1.00)
19q loss 3 (5%) 63 0.132
(0.731) 		0.423
(1.00) 		0.0122
(0.415) 		0.193
(0.847) 		0.0289
(0.569) 		1
(1.00) 		1
(1.00) 		0.101
(0.718) 		0.111
(0.723)
20p loss 4 (6%) 62 0.631
(1.00) 		0.237
(0.9) 		0.139
(0.731) 		0.142
(0.731) 		0.304
(0.94) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
20q loss 3 (5%) 63 0.436
(1.00) 		0.432
(1.00) 		0.0392
(0.579) 		0.0258
(0.569) 		0.304
(0.94) 		1
(1.00) 		1
(1.00) 		1
(1.00)
21q loss 35 (53%) 31 0.0353
(0.569) 		0.375
(1.00) 		0.906
(1.00) 		0.781
(1.00) 		0.0731
(0.654) 		1
(1.00) 		0.805
(1.00) 		0.231
(0.894) 		0.705
(1.00) 		0.112
(0.723) 		0.544
(1.00) 		0.613
(1.00)
22q loss 8 (12%) 58 0.29
(0.94) 		0.783
(1.00) 		0.177
(0.798) 		1
(1.00) 		0.211
(0.869) 		0.262
(0.938) 		0.0553
(0.615) 		1
(1.00) 		0.567
(1.00) 		0.39
(1.00)
xp loss 38 (58%) 28 0.865
(1.00) 		0.0808
(0.654) 		0.291
(0.94) 		0.546
(1.00) 		1
(1.00) 		1
(1.00) 		0.128
(0.723) 		1
(1.00) 		0.17
(0.777) 		0.112
(0.723) 		0.813
(1.00) 		1
(1.00)
xq loss 39 (59%) 27 0.346
(1.00) 		0.0923
(0.684) 		0.305
(0.94) 		0.361
(1.00) 		1
(1.00) 		1
(1.00) 		0.136
(0.731) 		1
(1.00) 		0.17
(0.777) 		0.233
(0.894) 		0.818
(1.00) 		1
(1.00)
'5p gain' versus 'PATHOLOGIC_STAGE'

P value = 0.00193 (Fisher's exact test), Q value = 0.21

Table S1.  Gene #5: '5p gain' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

nPatients STAGE I STAGE II STAGE III STAGE IV
ALL 21 25 14 6
5P GAIN MUTATED 1 3 0 4
5P GAIN WILD-TYPE 20 22 14 2

Figure S1.  Get High-res Image Gene #5: '5p gain' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

'5q gain' versus 'PATHOLOGIC_STAGE'

P value = 0.00141 (Fisher's exact test), Q value = 0.18

Table S2.  Gene #6: '5q gain' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

nPatients STAGE I STAGE II STAGE III STAGE IV
ALL 21 25 14 6
5Q GAIN MUTATED 1 3 0 4
5Q GAIN WILD-TYPE 20 22 14 2

Figure S2.  Get High-res Image Gene #6: '5q gain' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

'19p gain' versus 'PATHOLOGY_N_STAGE'

P value = 0.00246 (Fisher's exact test), Q value = 0.23

Table S3.  Gene #24: '19p gain' versus Clinical Feature #5: 'PATHOLOGY_N_STAGE'

nPatients N0 N1+N2
ALL 40 5
19P GAIN MUTATED 10 5
19P GAIN WILD-TYPE 30 0

Figure S3.  Get High-res Image Gene #24: '19p gain' versus Clinical Feature #5: 'PATHOLOGY_N_STAGE'

'16p loss' versus 'Time to Death'

P value = 3.48e-09 (logrank test), Q value = 1.3e-06

Table S4.  Gene #51: '16p loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 65 9 1.0 - 152.0 (73.9)
16P LOSS MUTATED 4 3 1.0 - 30.2 (22.4)
16P LOSS WILD-TYPE 61 6 2.5 - 152.0 (86.6)

Figure S4.  Get High-res Image Gene #51: '16p loss' versus Clinical Feature #1: 'Time to Death'

'16p loss' versus 'PATHOLOGIC_STAGE'

P value = 0.00039 (Fisher's exact test), Q value = 0.059

Table S5.  Gene #51: '16p loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

nPatients STAGE I STAGE II STAGE III STAGE IV
ALL 21 25 14 6
16P LOSS MUTATED 0 0 1 3
16P LOSS WILD-TYPE 21 25 13 3

Figure S5.  Get High-res Image Gene #51: '16p loss' versus Clinical Feature #3: 'PATHOLOGIC_STAGE'

'16p loss' versus 'PATHOLOGY_N_STAGE'

P value = 3.36e-05 (Fisher's exact test), Q value = 0.0085

Table S6.  Gene #51: '16p loss' versus Clinical Feature #5: 'PATHOLOGY_N_STAGE'

nPatients N0 N1+N2
ALL 40 5
16P LOSS MUTATED 0 4
16P LOSS WILD-TYPE 40 1

Figure S6.  Get High-res Image Gene #51: '16p loss' versus Clinical Feature #5: 'PATHOLOGY_N_STAGE'

'16q loss' versus 'Time to Death'

P value = 2.01e-09 (logrank test), Q value = 1.3e-06

Table S7.  Gene #52: '16q loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 65 9 1.0 - 152.0 (73.9)
16Q LOSS MUTATED 5 4 1.0 - 52.3 (28.1)
16Q LOSS WILD-TYPE 60 5 2.5 - 152.0 (86.8)

Figure S7.  Get High-res Image Gene #52: '16q loss' versus Clinical Feature #1: 'Time to Death'

'16q loss' versus 'PATHOLOGY_N_STAGE'

P value = 0.000165 (Fisher's exact test), Q value = 0.031

Table S8.  Gene #52: '16q loss' versus Clinical Feature #5: 'PATHOLOGY_N_STAGE'

nPatients N0 N1+N2
ALL 40 5
16Q LOSS MUTATED 1 4
16Q LOSS WILD-TYPE 39 1

Figure S8.  Get High-res Image Gene #52: '16q loss' versus Clinical Feature #5: 'PATHOLOGY_N_STAGE'

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/KICH-TP/19781646/transformed.cor.cli.txt

  • Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/KICH-TP/19775213/KICH-TP.merged_data.txt

  • Number of patients = 66

  • Number of significantly arm-level cnvs = 63

  • 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)
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