Correlation between copy number variations of arm-level result and selected clinical features
Uterine Carcinosarcoma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C1RB744F
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/C1RB744F
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 79 arm-level events and 5 clinical features across 56 patients, one significant finding detected with Q value < 0.25.

  • 21q loss cnv correlated to 'RADIATION_THERAPY'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 79 arm-level events and 5 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, one significant finding detected.

Clinical
Features 		Time
to
Death 		YEARS
TO
BIRTH 		RADIATION
THERAPY 		HISTOLOGICAL
TYPE 		RACE
nCNV (%) nWild-Type logrank test Wilcoxon-test Fisher's exact test Fisher's exact test Fisher's exact test
21q loss 17 (30%) 39 0.195
(1.00) 		0.175
(1.00) 		0.000482
(0.19) 		0.708
(1.00) 		1
(1.00)
1p gain 24 (43%) 32 0.757
(1.00) 		0.285
(1.00) 		0.579
(1.00) 		0.45
(1.00) 		0.452
(1.00)
1q gain 31 (55%) 25 0.0585
(1.00) 		0.723
(1.00) 		0.786
(1.00) 		0.699
(1.00) 		0.167
(1.00)
2p gain 23 (41%) 33 0.119
(1.00) 		0.526
(1.00) 		0.0558
(1.00) 		0.69
(1.00) 		1
(1.00)
2q gain 21 (38%) 35 0.77
(1.00) 		0.635
(1.00) 		0.0481
(1.00) 		0.884
(1.00) 		0.873
(1.00)
3p gain 10 (18%) 46 0.522
(1.00) 		0.578
(1.00) 		0.482
(1.00) 		0.454
(1.00) 		0.129
(1.00)
3q gain 22 (39%) 34 0.415
(1.00) 		0.271
(1.00) 		1
(1.00) 		0.609
(1.00) 		0.755
(1.00)
4p gain 10 (18%) 46 0.482
(1.00) 		0.822
(1.00) 		0.715
(1.00) 		0.322
(1.00) 		0.0687
(1.00)
4q gain 3 (5%) 53 0.952
(1.00) 		0.985
(1.00) 		0.0864
(1.00) 		0.45
(1.00) 		1
(1.00)
5p gain 23 (41%) 33 0.625
(1.00) 		0.683
(1.00) 		1
(1.00) 		1
(1.00) 		0.878
(1.00)
5q gain 8 (14%) 48 0.782
(1.00) 		0.833
(1.00) 		0.444
(1.00) 		0.103
(1.00) 		0.24
(1.00)
6p gain 31 (55%) 25 0.971
(1.00) 		0.108
(1.00) 		1
(1.00) 		0.655
(1.00) 		0.449
(1.00)
6q gain 27 (48%) 29 0.707
(1.00) 		0.178
(1.00) 		1
(1.00) 		0.277
(1.00) 		0.602
(1.00)
7p gain 21 (38%) 35 0.709
(1.00) 		0.192
(1.00) 		0.78
(1.00) 		0.178
(1.00) 		0.237
(1.00)
7q gain 18 (32%) 38 0.788
(1.00) 		0.409
(1.00) 		0.766
(1.00) 		0.0567
(1.00) 		1
(1.00)
8p gain 18 (32%) 38 0.273
(1.00) 		0.673
(1.00) 		0.235
(1.00) 		0.0745
(1.00) 		0.417
(1.00)
8q gain 30 (54%) 26 0.154
(1.00) 		0.336
(1.00) 		0.00582
(1.00) 		0.0905
(1.00) 		0.449
(1.00)
9p gain 6 (11%) 50 0.874
(1.00) 		0.353
(1.00) 		1
(1.00) 		0.0217
(1.00) 		0.703
(1.00)
10p gain 20 (36%) 36 0.386
(1.00) 		0.837
(1.00) 		0.401
(1.00) 		0.822
(1.00) 		0.439
(1.00)
10q gain 17 (30%) 39 0.287
(1.00) 		0.865
(1.00) 		0.766
(1.00) 		0.813
(1.00) 		0.353
(1.00)
11p gain 5 (9%) 51 0.967
(1.00) 		0.752
(1.00) 		1
(1.00) 		0.84
(1.00) 		1
(1.00)
11q gain 7 (12%) 49 0.942
(1.00) 		0.457
(1.00) 		0.688
(1.00) 		0.582
(1.00) 		1
(1.00)
12p gain 22 (39%) 34 0.116
(1.00) 		0.45
(1.00) 		0.582
(1.00) 		0.344
(1.00) 		0.282
(1.00)
12q gain 11 (20%) 45 0.93
(1.00) 		0.584
(1.00) 		1
(1.00) 		0.688
(1.00) 		0.394
(1.00)
13q gain 15 (27%) 41 0.248
(1.00) 		0.505
(1.00) 		0.535
(1.00) 		0.469
(1.00) 		0.731
(1.00)
14q gain 7 (12%) 49 0.0241
(1.00) 		0.766
(1.00) 		1
(1.00) 		0.771
(1.00) 		0.56
(1.00)
15q gain 4 (7%) 52 0.574
(1.00) 		0.166
(1.00) 		1
(1.00) 		0.672
(1.00) 		0.204
(1.00)
16p gain 10 (18%) 46 0.584
(1.00) 		0.416
(1.00) 		1
(1.00) 		0.406
(1.00) 		0.397
(1.00)
16q gain 6 (11%) 50 0.39
(1.00) 		0.853
(1.00) 		0.678
(1.00) 		0.465
(1.00) 		0.493
(1.00)
17p gain 9 (16%) 47 0.24
(1.00) 		0.396
(1.00) 		0.444
(1.00) 		0.268
(1.00) 		0.284
(1.00)
17q gain 18 (32%) 38 0.903
(1.00) 		0.765
(1.00) 		1
(1.00) 		0.819
(1.00) 		0.753
(1.00)
18p gain 18 (32%) 38 0.334
(1.00) 		0.854
(1.00) 		0.557
(1.00) 		0.154
(1.00) 		0.655
(1.00)
18q gain 13 (23%) 43 0.408
(1.00) 		0.93
(1.00) 		0.751
(1.00) 		0.395
(1.00) 		0.404
(1.00)
19p gain 24 (43%) 32 0.612
(1.00) 		1
(1.00) 		0.161
(1.00) 		0.942
(1.00) 		0.877
(1.00)
19q gain 29 (52%) 27 0.611
(1.00) 		0.538
(1.00) 		0.0136
(1.00) 		0.221
(1.00) 		0.523
(1.00)
20p gain 36 (64%) 20 0.491
(1.00) 		0.202
(1.00) 		0.16
(1.00) 		0.938
(1.00) 		0.335
(1.00)
20q gain 43 (77%) 13 0.959
(1.00) 		0.676
(1.00) 		1
(1.00) 		0.287
(1.00) 		0.252
(1.00)
21q gain 18 (32%) 38 0.645
(1.00) 		0.752
(1.00) 		0.384
(1.00) 		0.934
(1.00) 		0.257
(1.00)
22q gain 8 (14%) 48 0.0711
(1.00) 		0.038
(1.00) 		1
(1.00) 		0.627
(1.00) 		0.278
(1.00)
xp gain 18 (32%) 38 0.572
(1.00) 		0.0382
(1.00) 		0.372
(1.00) 		0.874
(1.00) 		0.751
(1.00)
xq gain 15 (27%) 41 0.407
(1.00) 		0.63
(1.00) 		1
(1.00) 		0.929
(1.00) 		0.0878
(1.00)
1p loss 10 (18%) 46 0.268
(1.00) 		0.275
(1.00) 		0.715
(1.00) 		0.144
(1.00) 		0.651
(1.00)
1q loss 10 (18%) 46 0.142
(1.00) 		0.199
(1.00) 		0.269
(1.00) 		0.113
(1.00) 		0.645
(1.00)
3p loss 22 (39%) 34 0.324
(1.00) 		0.731
(1.00) 		0.16
(1.00) 		0.829
(1.00) 		0.46
(1.00)
3q loss 15 (27%) 41 0.563
(1.00) 		0.331
(1.00) 		0.338
(1.00) 		0.636
(1.00) 		0.435
(1.00)
4p loss 30 (54%) 26 0.307
(1.00) 		0.974
(1.00) 		0.786
(1.00) 		0.0474
(1.00) 		0.881
(1.00)
4q loss 34 (61%) 22 0.419
(1.00) 		0.626
(1.00) 		0.573
(1.00) 		0.162
(1.00) 		0.156
(1.00)
5p loss 9 (16%) 47 0.0784
(1.00) 		0.118
(1.00) 		0.269
(1.00) 		0.894
(1.00) 		0.608
(1.00)
5q loss 18 (32%) 38 0.495
(1.00) 		0.533
(1.00) 		0.235
(1.00) 		0.933
(1.00) 		0.751
(1.00)
6p loss 5 (9%) 51 0.1
(1.00) 		0.508
(1.00) 		0.649
(1.00) 		0.84
(1.00) 		0.404
(1.00)
6q loss 7 (12%) 49 0.218
(1.00) 		0.738
(1.00) 		1
(1.00) 		1
(1.00) 		0.181
(1.00)
7p loss 13 (23%) 43 0.864
(1.00) 		0.734
(1.00) 		0.75
(1.00) 		0.719
(1.00) 		1
(1.00)
7q loss 12 (21%) 44 0.132
(1.00) 		0.905
(1.00) 		0.187
(1.00) 		0.709
(1.00) 		0.469
(1.00)
8p loss 24 (43%) 32 0.783
(1.00) 		0.967
(1.00) 		0.786
(1.00) 		0.482
(1.00) 		0.357
(1.00)
8q loss 9 (16%) 47 0.951
(1.00) 		0.577
(1.00) 		0.0623
(1.00) 		0.268
(1.00) 		0.283
(1.00)
9p loss 35 (62%) 21 0.734
(1.00) 		0.0673
(1.00) 		0.566
(1.00) 		0.0337
(1.00) 		0.677
(1.00)
9q loss 40 (71%) 16 0.34
(1.00) 		0.1
(1.00) 		0.547
(1.00) 		0.287
(1.00) 		0.466
(1.00)
10p loss 24 (43%) 32 0.6
(1.00) 		0.246
(1.00) 		0.278
(1.00) 		0.736
(1.00) 		0.148
(1.00)
10q loss 20 (36%) 36 0.182
(1.00) 		0.804
(1.00) 		0.772
(1.00) 		0.207
(1.00) 		0.235
(1.00)
11p loss 28 (50%) 28 0.0193
(1.00) 		0.21
(1.00) 		0.17
(1.00) 		0.123
(1.00) 		1
(1.00)
11q loss 26 (46%) 30 0.337
(1.00) 		0.537
(1.00) 		0.783
(1.00) 		0.207
(1.00) 		0.882
(1.00)
12p loss 13 (23%) 43 0.435
(1.00) 		0.907
(1.00) 		0.534
(1.00) 		1
(1.00) 		0.303
(1.00)
12q loss 14 (25%) 42 0.33
(1.00) 		0.191
(1.00) 		1
(1.00) 		0.673
(1.00) 		0.731
(1.00)
13q loss 26 (46%) 30 0.767
(1.00) 		0.831
(1.00) 		0.783
(1.00) 		0.888
(1.00) 		1
(1.00)
14q loss 27 (48%) 29 0.252
(1.00) 		0.533
(1.00) 		0.098
(1.00) 		0.0866
(1.00) 		0.0858
(1.00)
15q loss 33 (59%) 23 0.353
(1.00) 		0.647
(1.00) 		0.154
(1.00) 		0.573
(1.00) 		0.222
(1.00)
16p loss 32 (57%) 24 0.517
(1.00) 		0.868
(1.00) 		0.416
(1.00) 		0.544
(1.00) 		0.516
(1.00)
16q loss 37 (66%) 19 0.134
(1.00) 		0.965
(1.00) 		0.146
(1.00) 		0.302
(1.00) 		0.326
(1.00)
17p loss 34 (61%) 22 0.18
(1.00) 		0.574
(1.00) 		0.573
(1.00) 		0.371
(1.00) 		0.243
(1.00)
17q loss 17 (30%) 39 0.0663
(1.00) 		0.562
(1.00) 		1
(1.00) 		0.464
(1.00) 		0.741
(1.00)
18p loss 18 (32%) 38 0.821
(1.00) 		0.699
(1.00) 		0.145
(1.00) 		0.0971
(1.00) 		0.259
(1.00)
18q loss 20 (36%) 36 0.309
(1.00) 		0.515
(1.00) 		0.78
(1.00) 		0.171
(1.00) 		0.0372
(1.00)
19p loss 15 (27%) 41 0.97
(1.00) 		0.897
(1.00) 		0.76
(1.00) 		0.862
(1.00) 		1
(1.00)
19q loss 12 (21%) 44 0.99
(1.00) 		0.442
(1.00) 		0.482
(1.00) 		0.353
(1.00) 		0.706
(1.00)
20p loss 8 (14%) 48 0.638
(1.00) 		0.797
(1.00) 		0.436
(1.00) 		1
(1.00) 		0.444
(1.00)
20q loss 5 (9%) 51 0.53
(1.00) 		0.943
(1.00) 		0.617
(1.00) 		0.706
(1.00) 		0.682
(1.00)
22q loss 33 (59%) 23 0.31
(1.00) 		0.683
(1.00) 		0.278
(1.00) 		0.614
(1.00) 		0.102
(1.00)
xp loss 15 (27%) 41 0.795
(1.00) 		0.604
(1.00) 		1
(1.00) 		0.737
(1.00) 		1
(1.00)
xq loss 18 (32%) 38 0.453
(1.00) 		0.611
(1.00) 		0.384
(1.00) 		0.874
(1.00) 		0.497
(1.00)
'21q loss' versus 'RADIATION_THERAPY'

P value = 0.000482 (Fisher's exact test), Q value = 0.19

Table S1.  Gene #76: '21q loss' versus Clinical Feature #3: 'RADIATION_THERAPY'

nPatients NO YES
ALL 29 24
21Q LOSS MUTATED 14 1
21Q LOSS WILD-TYPE 15 23

Figure S1.  Get High-res Image Gene #76: '21q loss' versus Clinical Feature #3: 'RADIATION_THERAPY'

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/UCS-TP/22533738/transformed.cor.cli.txt

  • Clinical data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/Append_Data/UCS-TP/22507158/UCS-TP.merged_data.txt

  • Number of patients = 56

  • Number of significantly arm-level cnvs = 79

  • Number of selected clinical features = 5

  • 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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