Correlation between copy number variation genes (focal events) and selected clinical features
Uterine Carcinosarcoma (Primary solid tumor)
16 April 2014 | analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1D50KN2
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/C1D50KN2
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 62 focal events and 2 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 62 focal events and 2 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
| nCNV (%) | nWild-Type | logrank test | t-test
amp 1q22 | 42 (75%) | 14 | 0.85 (1.00) | 0.366 (1.00)
amp 2p14 | 28 (50%) | 28 | 0.253 (1.00) | 0.47 (1.00)
amp 2q13 | 29 (52%) | 27 | 0.716 (1.00) | 0.221 (1.00)
amp 3p25 1 | 20 (36%) | 36 | 0.0949 (1.00) | 0.468 (1.00)
amp 3q26 2 | 37 (66%) | 19 | 0.534 (1.00) | 0.404 (1.00)
amp 4p16 3 | 25 (45%) | 31 | 0.116 (1.00) | 0.187 (1.00)
amp 5p13 2 | 26 (46%) | 30 | 0.884 (1.00) | 0.958 (1.00)
amp 6p24 2 | 37 (66%) | 19 | 0.0753 (1.00) | 0.0983 (1.00)
amp 8p11 21 | 33 (59%) | 23 | 0.681 (1.00) | 0.0671 (1.00)
amp 8q11 23 | 38 (68%) | 18 | 0.916 (1.00) | 0.204 (1.00)
amp 8q24 21 | 42 (75%) | 14 | 0.416 (1.00) | 0.847 (1.00)
amp 8q24 21 | 40 (71%) | 16 | 0.115 (1.00) | 0.445 (1.00)
amp 10q22 2 | 26 (46%) | 30 | 0.375 (1.00) | 0.15 (1.00)
amp 11q13 1 | 19 (34%) | 37 | 0.151 (1.00) | 0.546 (1.00)
amp 12q12 | 22 (39%) | 34 | 0.415 (1.00) | 0.438 (1.00)
amp 12q15 | 17 (30%) | 39 | 0.999 (1.00) | 0.122 (1.00)
amp 13q31 3 | 25 (45%) | 31 | 0.703 (1.00) | 0.381 (1.00)
amp 16p11 2 | 20 (36%) | 36 | 0.403 (1.00) | 0.108 (1.00)
amp 17q12 | 27 (48%) | 29 | 0.499 (1.00) | 0.773 (1.00)
amp 17q25 1 | 32 (57%) | 24 | 0.789 (1.00) | 0.0577 (1.00)
amp 19p13 2 | 19 (34%) | 37 | 0.987 (1.00) | 0.487 (1.00)
amp 19q12 | 45 (80%) | 11 | 0.484 (1.00) | 0.543 (1.00)
amp 20q11 21 | 48 (86%) | 8 | 0.353 (1.00) | 0.495 (1.00)
amp 20q11 21 | 48 (86%) | 8 | 0.802 (1.00) | 0.985 (1.00)
amp xp11 21 | 28 (50%) | 28 | 0.598 (1.00) | 0.00929 (1.00)
del 1p36 21 | 19 (34%) | 37 | 0.843 (1.00) | 0.173 (1.00)
del 2q22 1 | 11 (20%) | 45 | 0.089 (1.00) | 0.92 (1.00)
del 3p21 1 | 37 (66%) | 19 | 0.867 (1.00) | 0.744 (1.00)
del 3p14 1 | 30 (54%) | 26 | 0.99 (1.00) | 0.694 (1.00)
del 3q13 31 | 19 (34%) | 37 | 0.448 (1.00) | 0.523 (1.00)
del 4q22 1 | 37 (66%) | 19 | 0.932 (1.00) | 0.766 (1.00)
del 4q34 3 | 37 (66%) | 19 | 0.454 (1.00) | 0.817 (1.00)
del 5q11 2 | 26 (46%) | 30 | 0.464 (1.00) | 0.361 (1.00)
del 6q26 | 10 (18%) | 46 | 0.526 (1.00) | 0.866 (1.00)
del 7q11 22 | 12 (21%) | 44 | 0.265 (1.00) | 0.817 (1.00)
del 7q36 2 | 20 (36%) | 36 | 0.0828 (1.00) | 0.671 (1.00)
del 8p21 3 | 32 (57%) | 24 | 0.323 (1.00) | 0.443 (1.00)
del 9p23 | 34 (61%) | 22 | 0.661 (1.00) | 0.0357 (1.00)
del 9q21 13 | 39 (70%) | 17 | 0.511 (1.00) | 0.676 (1.00)
del 9q33 3 | 38 (68%) | 18 | 0.121 (1.00) | 0.28 (1.00)
del 10q21 1 | 18 (32%) | 38 | 0.817 (1.00) | 0.965 (1.00)
del 10q23 31 | 20 (36%) | 36 | 0.602 (1.00) | 0.296 (1.00)
del 11p15 5 | 25 (45%) | 31 | 0.114 (1.00) | 0.784 (1.00)
del 11q14 1 | 26 (46%) | 30 | 0.965 (1.00) | 0.0655 (1.00)
del 11q24 2 | 27 (48%) | 29 | 0.532 (1.00) | 0.332 (1.00)
del 12q23 1 | 20 (36%) | 36 | 0.134 (1.00) | 0.0621 (1.00)
del 12q24 31 | 20 (36%) | 36 | 0.225 (1.00) | 0.251 (1.00)
del 13q12 11 | 30 (54%) | 26 | 0.434 (1.00) | 0.263 (1.00)
del 13q14 2 | 32 (57%) | 24 | 0.729 (1.00) | 0.834 (1.00)
del 14q21 1 | 28 (50%) | 28 | 0.432 (1.00) | 0.3 (1.00)
del 15q15 1 | 43 (77%) | 13 | 0.393 (1.00) | 0.201 (1.00)
del 16p13 3 | 33 (59%) | 23 | 0.872 (1.00) | 0.787 (1.00)
del 16q23 1 | 39 (70%) | 17 | 0.0164 (1.00) | 0.24 (1.00)
del 17p13 1 | 42 (75%) | 14 | 0.59 (1.00) | 0.817 (1.00)
del 17q21 32 | 19 (34%) | 37 | 0.0271 (1.00) | 0.506 (1.00)
del 18q22 2 | 26 (46%) | 30 | 0.458 (1.00) | 0.481 (1.00)
del 19p13 3 | 47 (84%) | 9 | 0.236 (1.00) | 0.331 (1.00)
del 19q13 33 | 17 (30%) | 39 | 0.306 (1.00) | 0.855 (1.00)
del 20p12 1 | 9 (16%) | 47 | 0.844 (1.00) | 0.967 (1.00)
del 22q13 31 | 40 (71%) | 16 | 0.651 (1.00) | 0.421 (1.00)
del xp21 1 | 18 (32%) | 38 | 0.225 (1.00) | 0.34 (1.00)
del xq25 | 23 (41%) | 33 | 0.821 (1.00) | 0.323 (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 = 62

- Number of selected clinical features = 2

- 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

Student's t-test analysis

For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between tumors with and without gene mutations using 't.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.

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

References
[1] Bland and Altman, Statistics notes: The logrank test, BMJ 328(7447):1073 (2004)
[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[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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