Correlation between copy number variations of arm-level result and selected clinical features
Uterine Carcinosarcoma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1930S1V
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/C1930S1V
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 77 arm-level events and 3 clinical features across 56 patients, no significant finding detected with Q value < 0.25.

  • No arm-level cnvs related to clinical features.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 77 arm-level events and 3 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, no significant finding detected.

Clinical
Features 		Time
to
Death 		AGE RACE
nCNV (%) nWild-Type logrank test Wilcoxon-test Fisher's exact test
1p gain 24 (43%) 32 0.627
(1.00) 		0.169
(1.00) 		0.272
(1.00)
1q gain 31 (55%) 25 0.296
(1.00) 		0.509
(1.00) 		0.148
(1.00)
2p gain 23 (41%) 33 0.0947
(1.00) 		0.526
(1.00) 		1
(1.00)
2q gain 21 (38%) 35 0.712
(1.00) 		0.635
(1.00) 		0.875
(1.00)
3p gain 12 (21%) 44 0.536
(1.00) 		0.322
(1.00) 		0.0963
(1.00)
3q gain 23 (41%) 33 0.662
(1.00) 		0.309
(1.00) 		0.678
(1.00)
4p gain 9 (16%) 47 0.564
(1.00) 		0.738
(1.00) 		0.165
(1.00)
4q gain 3 (5%) 53 0.875
(1.00) 		0.985
(1.00) 		1
(1.00)
5p gain 23 (41%) 33 0.922
(1.00) 		0.683
(1.00) 		0.876
(1.00)
5q gain 8 (14%) 48 0.954
(1.00) 		0.833
(1.00) 		0.242
(1.00)
6p gain 30 (54%) 26 0.846
(1.00) 		0.114
(1.00) 		0.452
(1.00)
6q gain 27 (48%) 29 0.99
(1.00) 		0.178
(1.00) 		0.599
(1.00)
7p gain 21 (38%) 35 0.923
(1.00) 		0.192
(1.00) 		0.234
(1.00)
7q gain 17 (30%) 39 0.697
(1.00) 		0.532
(1.00) 		0.869
(1.00)
8p gain 19 (34%) 37 0.0938
(1.00) 		0.401
(1.00) 		0.305
(1.00)
8q gain 30 (54%) 26 0.189
(1.00) 		0.336
(1.00) 		0.451
(1.00)
9p gain 6 (11%) 50 0.943
(1.00) 		0.353
(1.00) 		0.702
(1.00)
10p gain 21 (38%) 35 0.464
(1.00) 		0.78
(1.00) 		0.665
(1.00)
10q gain 17 (30%) 39 0.275
(1.00) 		0.865
(1.00) 		0.351
(1.00)
11p gain 5 (9%) 51 0.979
(1.00) 		0.752
(1.00) 		1
(1.00)
11q gain 7 (12%) 49 0.94
(1.00) 		0.457
(1.00) 		1
(1.00)
12p gain 22 (39%) 34 0.188
(1.00) 		0.45
(1.00) 		0.283
(1.00)
12q gain 11 (20%) 45 0.969
(1.00) 		0.584
(1.00) 		0.395
(1.00)
13q gain 15 (27%) 41 0.338
(1.00) 		0.505
(1.00) 		0.73
(1.00)
14q gain 7 (12%) 49 0.037
(1.00) 		0.766
(1.00) 		0.557
(1.00)
15q gain 4 (7%) 52 0.505
(1.00) 		0.166
(1.00) 		0.204
(1.00)
16p gain 10 (18%) 46 0.649
(1.00) 		0.416
(1.00) 		0.395
(1.00)
16q gain 6 (11%) 50 0.502
(1.00) 		0.853
(1.00) 		0.492
(1.00)
17p gain 9 (16%) 47 0.25
(1.00) 		0.396
(1.00) 		0.283
(1.00)
17q gain 18 (32%) 38 0.834
(1.00) 		0.765
(1.00) 		0.75
(1.00)
18p gain 18 (32%) 38 0.391
(1.00) 		0.854
(1.00) 		0.652
(1.00)
18q gain 14 (25%) 42 0.579
(1.00) 		0.985
(1.00) 		0.855
(1.00)
19p gain 24 (43%) 32 0.631
(1.00) 		0.637
(1.00) 		0.597
(1.00)
19q gain 28 (50%) 28 0.975
(1.00) 		0.522
(1.00) 		0.595
(1.00)
20p gain 37 (66%) 19 0.778
(1.00) 		0.209
(1.00) 		0.438
(1.00)
20q gain 44 (79%) 12 0.726
(1.00) 		0.697
(1.00) 		0.196
(1.00)
21q gain 18 (32%) 38 0.609
(1.00) 		0.752
(1.00) 		0.259
(1.00)
22q gain 8 (14%) 48 0.0868
(1.00) 		0.038
(1.00) 		0.272
(1.00)
xq gain 14 (25%) 42 0.649
(1.00) 		0.32
(1.00) 		0.151
(1.00)
1p loss 9 (16%) 47 0.734
(1.00) 		0.584
(1.00) 		0.613
(1.00)
1q loss 9 (16%) 47 0.494
(1.00) 		0.454
(1.00) 		0.613
(1.00)
3p loss 20 (36%) 36 0.209
(1.00) 		0.784
(1.00) 		0.523
(1.00)
3q loss 14 (25%) 42 0.378
(1.00) 		0.302
(1.00) 		0.73
(1.00)
4p loss 31 (55%) 25 0.313
(1.00) 		0.98
(1.00) 		1
(1.00)
4q loss 33 (59%) 23 0.2
(1.00) 		0.537
(1.00) 		0.517
(1.00)
5p loss 9 (16%) 47 0.116
(1.00) 		0.118
(1.00) 		0.614
(1.00)
5q loss 18 (32%) 38 0.592
(1.00) 		0.533
(1.00) 		0.749
(1.00)
6p loss 5 (9%) 51 0.185
(1.00) 		0.508
(1.00) 		0.405
(1.00)
6q loss 7 (12%) 49 0.442
(1.00) 		0.682
(1.00) 		0.182
(1.00)
7p loss 13 (23%) 43 0.963
(1.00) 		0.734
(1.00) 		1
(1.00)
7q loss 13 (23%) 43 0.121
(1.00) 		0.923
(1.00) 		0.716
(1.00)
8p loss 23 (41%) 33 0.64
(1.00) 		0.653
(1.00) 		0.221
(1.00)
8q loss 9 (16%) 47 0.856
(1.00) 		0.577
(1.00) 		0.284
(1.00)
9p loss 34 (61%) 22 0.584
(1.00) 		0.118
(1.00) 		0.523
(1.00)
9q loss 39 (70%) 17 0.282
(1.00) 		0.178
(1.00) 		0.413
(1.00)
10p loss 23 (41%) 33 0.553
(1.00) 		0.214
(1.00) 		0.264
(1.00)
10q loss 21 (38%) 35 0.289
(1.00) 		0.748
(1.00) 		0.285
(1.00)
11p loss 26 (46%) 30 0.0388
(1.00) 		0.23
(1.00) 		0.885
(1.00)
11q loss 24 (43%) 32 0.534
(1.00) 		0.573
(1.00) 		0.767
(1.00)
12p loss 13 (23%) 43 0.482
(1.00) 		0.907
(1.00) 		0.3
(1.00)
12q loss 14 (25%) 42 0.366
(1.00) 		0.191
(1.00) 		0.729
(1.00)
13q loss 26 (46%) 30 0.989
(1.00) 		0.831
(1.00) 		1
(1.00)
14q loss 27 (48%) 29 0.464
(1.00) 		0.533
(1.00) 		0.084
(1.00)
15q loss 32 (57%) 24 0.72
(1.00) 		0.797
(1.00) 		0.358
(1.00)
16p loss 32 (57%) 24 0.605
(1.00) 		0.868
(1.00) 		0.517
(1.00)
16q loss 37 (66%) 19 0.182
(1.00) 		0.965
(1.00) 		0.322
(1.00)
17p loss 34 (61%) 22 0.19
(1.00) 		0.574
(1.00) 		0.244
(1.00)
17q loss 17 (30%) 39 0.0378
(1.00) 		0.562
(1.00) 		0.74
(1.00)
18p loss 18 (32%) 38 0.64
(1.00) 		0.699
(1.00) 		0.259
(1.00)
18q loss 20 (36%) 36 0.265
(1.00) 		0.515
(1.00) 		0.0357
(1.00)
19p loss 15 (27%) 41 0.958
(1.00) 		0.505
(1.00) 		0.739
(1.00)
19q loss 13 (23%) 43 0.59
(1.00) 		0.437
(1.00) 		0.398
(1.00)
20p loss 7 (12%) 49 0.915
(1.00) 		0.823
(1.00) 		0.558
(1.00)
20q loss 4 (7%) 52 0.888
(1.00) 		0.886
(1.00) 		1
(1.00)
21q loss 17 (30%) 39 0.164
(1.00) 		0.175
(1.00) 		1
(1.00)
22q loss 33 (59%) 23 0.322
(1.00) 		0.683
(1.00) 		0.101
(1.00)
xq loss 19 (34%) 37 0.48
(1.00) 		0.965
(1.00) 		0.657
(1.00)
Methods & Data
Input

  • Copy number data file = transformed.cor.cli.txt

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

  • Number of patients = 56

  • Number of significantly arm-level cnvs = 77

  • Number of selected clinical features = 3

  • 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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