Correlation between copy number variation genes (focal events) and selected clinical features
Uterine Carcinosarcoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C19Z93VC
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 variation genes (focal events) and selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C19Z93VC
Overview
Introduction

This pipeline computes the correlation between significant copy number variation (cnv focal) genes and selected clinical features.

Summary

Testing the association between copy number variation 61 focal events and 3 clinical features across 56 patients, no significant finding detected with Q value < 0.25.

  • No focal 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 61 focal 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
amp 1q22 42 (75%) 14 0.671
(1.00) 		0.576
(1.00) 		0.236
(1.00)
amp 2p14 28 (50%) 28 0.299
(1.00) 		0.768
(1.00) 		0.146
(1.00)
amp 2q13 29 (52%) 27 0.79
(1.00) 		0.345
(1.00) 		0.592
(1.00)
amp 3p25 1 20 (36%) 36 0.12
(1.00) 		0.392
(1.00) 		0.451
(1.00)
amp 3q26 2 37 (66%) 19 0.66
(1.00) 		0.382
(1.00) 		0.757
(1.00)
amp 4p16 3 25 (45%) 31 0.151
(1.00) 		0.343
(1.00) 		0.358
(1.00)
amp 5p13 2 26 (46%) 30 0.987
(1.00) 		0.902
(1.00) 		0.314
(1.00)
amp 6p24 2 37 (66%) 19 0.0468
(1.00) 		0.0963
(1.00) 		0.758
(1.00)
amp 8p11 21 33 (59%) 23 0.782
(1.00) 		0.14
(1.00) 		0.405
(1.00)
amp 8q11 23 38 (68%) 18 0.87
(1.00) 		0.226
(1.00) 		0.257
(1.00)
amp 8q24 21 42 (75%) 14 0.307
(1.00) 		0.902
(1.00) 		0.28
(1.00)
amp 8q24 21 40 (71%) 16 0.0811
(1.00) 		0.574
(1.00) 		0.148
(1.00)
amp 10q22 2 26 (46%) 30 0.371
(1.00) 		0.111
(1.00) 		0.889
(1.00)
amp 11q13 1 19 (34%) 37 0.257
(1.00) 		0.446
(1.00) 		0.496
(1.00)
amp 12q12 22 (39%) 34 0.465
(1.00) 		0.512
(1.00) 		0.105
(1.00)
amp 12q15 17 (30%) 39 0.903
(1.00) 		0.108
(1.00) 		0.146
(1.00)
amp 13q31 3 25 (45%) 31 0.52
(1.00) 		0.276
(1.00) 		0.781
(1.00)
amp 16p11 2 20 (36%) 36 0.435
(1.00) 		0.134
(1.00) 		0.759
(1.00)
amp 17q12 27 (48%) 29 0.695
(1.00) 		0.889
(1.00) 		1
(1.00)
amp 17q25 1 32 (57%) 24 0.77
(1.00) 		0.0588
(1.00) 		0.597
(1.00)
amp 19p13 2 19 (34%) 37 0.933
(1.00) 		0.762
(1.00) 		0.496
(1.00)
amp 19q12 45 (80%) 11 0.527
(1.00) 		0.82
(1.00) 		0.685
(1.00)
amp 20q11 21 48 (86%) 8 0.345
(1.00) 		0.535
(1.00) 		0.0491
(1.00)
amp 20q11 21 48 (86%) 8 0.829
(1.00) 		0.87
(1.00) 		0.05
(1.00)
amp xp11 21 28 (50%) 28 0.508
(1.00) 		0.0136
(1.00) 		1
(1.00)
del 1p36 21 19 (34%) 37 0.957
(1.00) 		0.148
(1.00) 		1
(1.00)
del 2q22 1 11 (20%) 45 0.0828
(1.00) 		0.877
(1.00) 		0.556
(1.00)
del 3p14 2 37 (66%) 19 0.724
(1.00) 		0.979
(1.00) 		0.0494
(1.00)
del 3q13 31 22 (39%) 34 0.294
(1.00) 		0.425
(1.00) 		0.458
(1.00)
del 4q22 1 37 (66%) 19 0.974
(1.00) 		0.562
(1.00) 		0.761
(1.00)
del 4q34 3 37 (66%) 19 0.416
(1.00) 		0.646
(1.00) 		0.229
(1.00)
del 5q12 1 26 (46%) 30 0.572
(1.00) 		0.324
(1.00) 		1
(1.00)
del 6q26 10 (18%) 46 0.502
(1.00) 		0.872
(1.00) 		0.515
(1.00)
del 7q11 22 12 (21%) 44 0.255
(1.00) 		0.889
(1.00) 		1
(1.00)
del 7q36 2 20 (36%) 36 0.157
(1.00) 		0.669
(1.00) 		0.518
(1.00)
del 8p23 2 33 (59%) 23 0.329
(1.00) 		0.745
(1.00) 		0.156
(1.00)
del 9p23 34 (61%) 22 0.629
(1.00) 		0.0167
(1.00) 		0.879
(1.00)
del 9q21 13 39 (70%) 17 0.37
(1.00) 		0.568
(1.00) 		0.409
(1.00)
del 9q33 3 39 (70%) 17 0.166
(1.00) 		0.284
(1.00) 		0.865
(1.00)
del 10q23 31 20 (36%) 36 0.689
(1.00) 		0.532
(1.00) 		0.236
(1.00)
del 11p15 5 25 (45%) 31 0.102
(1.00) 		0.895
(1.00) 		0.599
(1.00)
del 11q14 1 26 (46%) 30 0.875
(1.00) 		0.22
(1.00) 		0.883
(1.00)
del 11q23 2 26 (46%) 30 0.498
(1.00) 		0.246
(1.00) 		0.45
(1.00)
del 12q23 1 20 (36%) 36 0.118
(1.00) 		0.031
(1.00) 		1
(1.00)
del 12q24 31 20 (36%) 36 0.196
(1.00) 		0.244
(1.00) 		1
(1.00)
del 13q12 11 30 (54%) 26 0.388
(1.00) 		0.344
(1.00) 		0.601
(1.00)
del 13q14 2 32 (57%) 24 0.928
(1.00) 		0.567
(1.00) 		0.594
(1.00)
del 14q21 1 28 (50%) 28 0.303
(1.00) 		0.38
(1.00) 		0.249
(1.00)
del 15q11 2 41 (73%) 15 0.889
(1.00) 		0.251
(1.00) 		0.204
(1.00)
del 15q15 1 43 (77%) 13 0.362
(1.00) 		0.217
(1.00) 		1
(1.00)
del 16p13 3 33 (59%) 23 0.942
(1.00) 		0.967
(1.00) 		0.0147
(1.00)
del 16q23 1 39 (70%) 17 0.0163
(1.00) 		0.239
(1.00) 		0.295
(1.00)
del 17p13 1 42 (75%) 14 0.577
(1.00) 		0.94
(1.00) 		0.176
(1.00)
del 17q21 32 19 (34%) 37 0.0243
(1.00) 		0.35
(1.00) 		0.188
(1.00)
del 18q22 2 26 (46%) 30 0.449
(1.00) 		0.278
(1.00) 		0.0131
(1.00)
del 19p13 3 47 (84%) 9 0.229
(1.00) 		0.269
(1.00) 		0.0341
(1.00)
del 19q13 33 17 (30%) 39 0.283
(1.00) 		0.837
(1.00) 		0.479
(1.00)
del 20p12 1 9 (16%) 47 0.87
(1.00) 		0.688
(1.00) 		0.372
(1.00)
del 22q13 31 40 (71%) 16 0.643
(1.00) 		0.388
(1.00) 		1
(1.00)
del xp21 1 18 (32%) 38 0.258
(1.00) 		0.304
(1.00) 		1
(1.00)
del xq25 23 (41%) 33 0.943
(1.00) 		0.297
(1.00) 		0.771
(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 focal cnvs = 61

  • Number of selected clinical features = 3

  • Exclude genes 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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