Correlation between copy number variations of arm-level result and selected clinical features
Kidney Chromophobe (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1959GZB
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/C1959GZB
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, 6 significant findings detected with Q value < 0.25.

  • 5p gain cnv correlated to 'PATHOLOGIC_STAGE'.

  • 5q gain cnv correlated to 'PATHOLOGIC_STAGE'.

  • 16p loss cnv correlated to 'Time to Death' 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, 6 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 3 (5%) 63 5.46e-07
(0.000206) 		0.926
(1.00) 		0.00489
(0.37) 		0.0257
(0.616) 		0.000705
(0.133) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
16q loss 5 (8%) 61 2.01e-09
(1.52e-06) 		0.221
(0.874) 		0.00476
(0.37) 		0.0476
(0.628) 		0.000165
(0.0415) 		0.11
(0.704) 		0.641
(1.00) 		1
(1.00) 		1
(1.00)
5p gain 8 (12%) 58 0.00702
(0.408) 		0.0661
(0.639) 		0.00148
(0.186) 		0.364
(1.00) 		0.0874
(0.642) 		0.00952
(0.424) 		0.455
(1.00) 		1
(1.00) 		1
(1.00)
5q gain 8 (12%) 58 0.00702
(0.408) 		0.0661
(0.639) 		0.00135
(0.186) 		0.365
(1.00) 		0.0874
(0.642) 		0.00952
(0.424) 		0.455
(1.00) 		1
(1.00) 		1
(1.00)
3p gain 8 (12%) 58 0.00834
(0.42) 		0.0837
(0.639) 		0.0164
(0.539) 		0.465
(1.00) 		0.0327
(0.616) 		0.213
(0.86) 		0.128
(0.706) 		1
(1.00) 		0.294
(0.947) 		1
(1.00)
3q gain 8 (12%) 58 0.00834
(0.42) 		0.0837
(0.639) 		0.0162
(0.539) 		0.462
(1.00) 		0.0327
(0.616) 		0.213
(0.86) 		0.128
(0.706) 		1
(1.00) 		0.295
(0.947) 		1
(1.00)
4p gain 23 (35%) 43 0.876
(1.00) 		0.22
(0.874) 		0.0375
(0.616) 		0.585
(1.00) 		1
(1.00) 		0.124
(0.704) 		1
(1.00) 		0.528
(1.00) 		0.0317
(0.616) 		1
(1.00) 		0.277
(0.947)
4q gain 24 (36%) 42 0.885
(1.00) 		0.265
(0.945) 		0.14
(0.726) 		0.809
(1.00) 		1
(1.00) 		0.124
(0.704) 		1
(1.00) 		0.528
(1.00) 		0.0467
(0.628) 		0.0369
(0.616) 		1
(1.00) 		0.287
(0.947)
7p gain 24 (36%) 42 0.0281
(0.616) 		0.172
(0.759) 		0.362
(1.00) 		0.691
(1.00) 		0.636
(1.00) 		0.124
(0.704) 		0.195
(0.832) 		0.528
(1.00) 		0.784
(1.00) 		0.0606
(0.628) 		1
(1.00) 		0.303
(0.947)
7q gain 24 (36%) 42 0.0281
(0.616) 		0.172
(0.759) 		0.363
(1.00) 		0.692
(1.00) 		0.636
(1.00) 		0.124
(0.704) 		0.195
(0.832) 		0.528
(1.00) 		0.784
(1.00) 		0.0606
(0.628) 		1
(1.00) 		0.303
(0.947)
8p gain 16 (24%) 50 0.957
(1.00) 		0.134
(0.721) 		0.582
(1.00) 		0.621
(1.00) 		0.639
(1.00) 		0.4
(1.00) 		0.4
(1.00) 		0.528
(1.00) 		0.394
(1.00) 		1
(1.00) 		0.57
(1.00)
8q gain 17 (26%) 49 0.957
(1.00) 		0.142
(0.726) 		0.296
(0.947) 		0.64
(1.00) 		0.639
(1.00) 		0.0571
(0.628) 		0.391
(1.00) 		0.528
(1.00) 		0.394
(1.00) 		1
(1.00) 		0.57
(1.00)
9p gain 10 (15%) 56 0.624
(1.00) 		0.979
(1.00) 		0.122
(0.704) 		0.196
(0.832) 		0.306
(0.947) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.759
(1.00) 		0.377
(1.00) 		0.535
(1.00)
9q gain 10 (15%) 56 0.624
(1.00) 		0.979
(1.00) 		0.122
(0.704) 		0.195
(0.832) 		0.306
(0.947) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.759
(1.00) 		0.374
(1.00) 		0.535
(1.00)
10p gain 4 (6%) 62 0.558
(1.00) 		0.34
(0.994) 		0.269
(0.947) 		0.455
(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) 		0.741
(1.00) 		0.814
(1.00) 		0.617
(1.00) 		0.443
(1.00) 		1
(1.00) 		1
(1.00) 		0.0467
(0.628) 		0.0369
(0.616) 		0.558
(1.00) 		0.0756
(0.639)
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
(0.628) 		0.0369
(0.616) 		0.56
(1.00) 		0.0756
(0.639)
12p gain 19 (29%) 47 0.661
(1.00) 		0.0137
(0.493) 		0.0766
(0.639) 		0.318
(0.962) 		1
(1.00) 		0.0873
(0.642) 		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
(0.86) 		0.0696
(0.639) 		0.11
(0.704) 		0.709
(1.00) 		0.33
(0.986) 		0.0873
(0.642) 		0.593
(1.00) 		0.528
(1.00) 		0.234
(0.894) 		0.0369
(0.616) 		0.806
(1.00) 		1
(1.00)
14q gain 21 (32%) 45 0.819
(1.00) 		0.144
(0.726) 		0.0971
(0.683) 		0.384
(1.00) 		1
(1.00) 		0.105
(0.704) 		0.794
(1.00) 		0.528
(1.00) 		0.234
(0.894) 		0.0369
(0.616) 		1
(1.00) 		0.609
(1.00)
15q gain 21 (32%) 45 0.34
(0.994) 		0.283
(0.947) 		0.412
(1.00) 		0.477
(1.00) 		0.35
(1.00) 		0.105
(0.704) 		0.794
(1.00) 		0.528
(1.00) 		1
(1.00) 		0.233
(0.894) 		0.815
(1.00) 		0.124
(0.704)
16p gain 22 (33%) 44 0.572
(1.00) 		0.791
(1.00) 		0.347
(1.00) 		0.643
(1.00) 		1
(1.00) 		0.124
(0.704) 		1
(1.00) 		0.528
(1.00) 		0.0467
(0.628) 		0.0369
(0.616) 		1
(1.00) 		0.124
(0.704)
16q gain 21 (32%) 45 0.217
(0.873) 		0.995
(1.00) 		0.474
(1.00) 		0.403
(1.00) 		0.635
(1.00) 		1
(1.00) 		1
(1.00) 		0.528
(1.00) 		0.0467
(0.628) 		0.0369
(0.616) 		1
(1.00) 		0.124
(0.704)
18p gain 17 (26%) 49 0.872
(1.00) 		0.278
(0.947) 		0.287
(0.947) 		0.434
(1.00) 		0.303
(0.947) 		0.4
(1.00) 		0.776
(1.00) 		1
(1.00) 		0.298
(0.947) 		1
(1.00) 		0.57
(1.00)
18q gain 16 (24%) 50 0.355
(1.00) 		0.525
(1.00) 		0.311
(0.949) 		0.199
(0.841) 		0.303
(0.947) 		0.4
(1.00) 		1
(1.00) 		1
(1.00) 		0.298
(0.947) 		1
(1.00) 		0.305
(0.947)
19p gain 20 (30%) 46 0.0332
(0.616) 		0.0344
(0.616) 		0.0135
(0.493) 		0.418
(1.00) 		0.00358
(0.344) 		0.0714
(0.639) 		0.593
(1.00) 		1
(1.00) 		0.784
(1.00) 		0.0606
(0.628) 		0.365
(1.00) 		0.29
(0.947)
19q gain 18 (27%) 48 0.154
(0.741) 		0.0171
(0.539) 		0.227
(0.892) 		0.448
(1.00) 		0.166
(0.757) 		0.0571
(0.628) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.233
(0.894) 		0.468
(1.00) 		0.29
(0.947)
20p gain 22 (33%) 44 0.0945
(0.68) 		0.0642
(0.638) 		0.264
(0.945) 		0.896
(1.00) 		0.141
(0.726) 		0.524
(1.00) 		0.426
(1.00) 		0.528
(1.00) 		0.784
(1.00) 		0.0606
(0.628) 		0.371
(1.00) 		0.634
(1.00)
20q gain 22 (33%) 44 0.0945
(0.68) 		0.0642
(0.638) 		0.266
(0.945) 		0.897
(1.00) 		0.141
(0.726) 		0.524
(1.00) 		0.426
(1.00) 		0.528
(1.00) 		0.784
(1.00) 		0.0606
(0.628) 		0.37
(1.00) 		0.634
(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
(0.757) 		0.415
(1.00) 		0.494
(1.00) 		0.523
(1.00) 		0.166
(0.757) 		0.524
(1.00) 		0.412
(1.00) 		1
(1.00) 		0.784
(1.00) 		0.0606
(0.628) 		0.795
(1.00) 		0.588
(1.00)
xp gain 8 (12%) 58 0.34
(0.994) 		0.953
(1.00) 		0.906
(1.00) 		1
(1.00) 		1
(1.00) 		0.262
(0.943) 		1
(1.00) 		1
(1.00) 		0.57
(1.00) 		0.535
(1.00)
xq gain 8 (12%) 58 0.34
(0.994) 		0.953
(1.00) 		0.904
(1.00) 		1
(1.00) 		1
(1.00) 		0.262
(0.943) 		1
(1.00) 		1
(1.00) 		0.567
(1.00) 		0.535
(1.00)
1p loss 53 (80%) 13 0.431
(1.00) 		0.478
(1.00) 		0.0289
(0.616) 		0.0416
(0.628) 		1
(1.00) 		0.162
(0.756) 		0.534
(1.00) 		0.51
(1.00) 		0.609
(1.00) 		1
(1.00) 		1
(1.00)
1q loss 51 (77%) 15 0.823
(1.00) 		0.221
(0.874) 		0.0229
(0.616) 		0.0547
(0.628) 		0.529
(1.00) 		0.213
(0.86) 		0.563
(1.00) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
2p loss 46 (70%) 20 0.941
(1.00) 		0.241
(0.906) 		0.145
(0.726) 		0.115
(0.704) 		1
(1.00) 		0.4
(1.00) 		0.284
(0.947) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
2q loss 46 (70%) 20 0.941
(1.00) 		0.241
(0.906) 		0.144
(0.726) 		0.114
(0.704) 		1
(1.00) 		0.4
(1.00) 		0.284
(0.947) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
3p loss 9 (14%) 57 0.193
(0.832) 		0.0465
(0.628) 		0.0757
(0.639) 		0.0235
(0.616) 		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
(0.704) 		0.141
(0.726) 		0.0528
(0.628) 		1
(1.00) 		1
(1.00) 		0.256
(0.943) 		1
(1.00) 		0.535
(1.00)
5p loss 10 (15%) 56 0.771
(1.00) 		0.642
(1.00) 		0.134
(0.721) 		0.0831
(0.639) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.423
(1.00) 		0.155
(0.741) 		0.0736
(0.639) 		0.158
(0.741) 		0.121
(0.704)
5q loss 10 (15%) 56 0.771
(1.00) 		0.642
(1.00) 		0.132
(0.718) 		0.0833
(0.639) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.423
(1.00) 		0.155
(0.741) 		0.0736
(0.639) 		0.157
(0.741) 		0.121
(0.704)
6p loss 51 (77%) 15 0.579
(1.00) 		0.379
(1.00) 		0.082
(0.639) 		0.0566
(0.628) 		0.568
(1.00) 		0.356
(1.00) 		0.244
(0.909) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
6q loss 51 (77%) 15 0.579
(1.00) 		0.379
(1.00) 		0.0831
(0.639) 		0.0554
(0.628) 		0.568
(1.00) 		0.356
(1.00) 		0.244
(0.909) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
8p loss 10 (15%) 56 0.171
(0.759) 		0.788
(1.00) 		0.663
(1.00) 		0.324
(0.972) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.655
(1.00) 		0.555
(1.00)
8q loss 9 (14%) 57 0.204
(0.858) 		0.594
(1.00) 		0.741
(1.00) 		0.438
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.611
(1.00) 		0.566
(1.00)
9p loss 9 (14%) 57 0.0505
(0.628) 		0.00653
(0.408) 		0.873
(1.00) 		0.906
(1.00) 		1
(1.00) 		1
(1.00) 		0.727
(1.00) 		1
(1.00) 		0.466
(1.00)
9q loss 10 (15%) 56 0.00364
(0.344) 		0.0116
(0.463) 		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
(0.706) 		0.762
(1.00) 		0.544
(1.00) 		0.395
(1.00) 		1
(1.00) 		0.31
(0.949) 		1
(1.00) 		0.559
(1.00) 		0.26
(0.943) 		1
(1.00) 		1
(1.00)
10q loss 49 (74%) 17 0.146
(0.726) 		0.953
(1.00) 		0.346
(1.00) 		0.211
(0.86) 		1
(1.00) 		0.31
(0.949) 		1
(1.00) 		0.559
(1.00) 		0.26
(0.943) 		1
(1.00) 		1
(1.00)
11p loss 7 (11%) 59 0.305
(0.947) 		0.0527
(0.628) 		0.0962
(0.683) 		0.0783
(0.639) 		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
(0.947) 		0.0527
(0.628) 		0.0976
(0.683) 		0.0774
(0.639) 		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
(0.638) 		0.447
(1.00) 		0.361
(1.00) 		0.301
(0.947) 		1
(1.00) 		0.294
(0.947) 		1
(1.00) 		0.474
(1.00) 		0.371
(1.00) 		0.817
(1.00) 		1
(1.00)
17p loss 50 (76%) 16 0.788
(1.00) 		0.149
(0.729) 		0.0743
(0.639) 		0.0418
(0.628) 		0.568
(1.00) 		0.356
(1.00) 		0.158
(0.741) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
17q loss 50 (76%) 16 0.788
(1.00) 		0.149
(0.729) 		0.0734
(0.639) 		0.0426
(0.628) 		0.568
(1.00) 		0.356
(1.00) 		0.158
(0.741) 		0.51
(1.00) 		1
(1.00) 		1
(1.00)
18p loss 7 (11%) 59 0.859
(1.00) 		0.429
(1.00) 		0.313
(0.95) 		0.784
(1.00) 		0.166
(0.757) 		1
(1.00) 		0.432
(1.00) 		1
(1.00) 		0.255
(0.943) 		1
(1.00)
18q loss 9 (14%) 57 0.3
(0.947) 		0.322
(0.969) 		0.0824
(0.639) 		0.49
(1.00) 		0.211
(0.86) 		1
(1.00) 		0.469
(1.00) 		1
(1.00) 		0.334
(0.994) 		1
(1.00)
19q loss 3 (5%) 63 0.132
(0.718) 		0.423
(1.00) 		0.0114
(0.463) 		0.193
(0.832) 		0.0289
(0.616) 		1
(1.00) 		1
(1.00) 		0.101
(0.704) 		0.111
(0.704)
20p loss 4 (6%) 62 0.631
(1.00) 		0.237
(0.9) 		0.137
(0.726) 		0.142
(0.726) 		0.304
(0.947) 		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) 		0.0415
(0.628) 		0.0257
(0.616) 		0.304
(0.947) 		1
(1.00) 		1
(1.00) 		1
(1.00)
21q loss 35 (53%) 31 0.0353
(0.616) 		0.375
(1.00) 		0.905
(1.00) 		0.781
(1.00) 		0.0731
(0.639) 		1
(1.00) 		0.805
(1.00) 		0.231
(0.894) 		0.705
(1.00) 		0.112
(0.704) 		0.546
(1.00) 		0.613
(1.00)
22q loss 8 (12%) 58 0.29
(0.947) 		0.783
(1.00) 		0.179
(0.788) 		1
(1.00) 		0.211
(0.86) 		0.262
(0.943) 		0.0553
(0.628) 		1
(1.00) 		0.57
(1.00) 		0.39
(1.00)
xp loss 38 (58%) 28 0.865
(1.00) 		0.0808
(0.639) 		0.293
(0.947) 		0.544
(1.00) 		1
(1.00) 		1
(1.00) 		0.128
(0.706) 		1
(1.00) 		0.17
(0.759) 		0.112
(0.704) 		0.812
(1.00) 		1
(1.00)
xq loss 38 (58%) 28 0.34
(0.994) 		0.115
(0.704) 		0.549
(1.00) 		0.517
(1.00) 		1
(1.00) 		1
(1.00) 		0.311
(0.949) 		1
(1.00) 		0.17
(0.759) 		0.112
(0.704) 		0.815
(1.00) 		1
(1.00)
'5p gain' versus 'PATHOLOGIC_STAGE'

P value = 0.00148 (Fisher's exact test), Q value = 0.19

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 = 0.00135 (Fisher's exact test), Q value = 0.19

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'

'16p loss' versus 'Time to Death'

P value = 5.46e-07 (logrank test), Q value = 0.00021

Table S3.  Gene #51: '16p loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 65 9 1.0 - 153.7 (73.9)
16P LOSS MUTATED 3 2 1.0 - 30.2 (16.7)
16P LOSS WILD-TYPE 62 7 2.5 - 153.7 (85.7)

Figure S3.  Get High-res Image Gene #51: '16p loss' versus Clinical Feature #1: 'Time to Death'

'16p loss' versus 'PATHOLOGY_N_STAGE'

P value = 0.000705 (Fisher's exact test), Q value = 0.13

Table S4.  Gene #51: '16p loss' versus Clinical Feature #5: 'PATHOLOGY_N_STAGE'

nPatients N0 N1+N2
ALL 40 5
16P LOSS MUTATED 0 3
16P LOSS WILD-TYPE 40 2

Figure S4.  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 = 1.5e-06

Table S5.  Gene #52: '16q loss' versus Clinical Feature #1: 'Time to Death'

nPatients nDeath Duration Range (Median), Month
ALL 65 9 1.0 - 153.7 (73.9)
16Q LOSS MUTATED 5 4 1.0 - 52.3 (28.1)
16Q LOSS WILD-TYPE 60 5 2.5 - 153.7 (86.8)

Figure S5.  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 = 0.041

Table S6.  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 S6.  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/22507962/transformed.cor.cli.txt

  • Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/KICH-TP/22506450/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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