Cervical Squamous Cell Carcinoma: Correlation between copy number variations of arm-level result and selected clinical features
Maintained by TCGA GDAC Team (Broad Institute/Dana-Farber Cancer Institute/Harvard Medical School)
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 20 arm-level results and 2 clinical features across 14 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 20 arm-level results 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
1q gain | 6 (43%) | 8 | 0.0455 (1.00) | 0.0583 (1.00)
3p gain | 3 (21%) | 11 | 1 (1.00) | 0.566 (1.00)
3q gain | 8 (57%) | 6 | 0.414 (1.00) | 0.939 (1.00)
5p gain | 4 (29%) | 10 | 0.617 (1.00) | 0.151 (1.00)
6p gain | 3 (21%) | 11 | 1 (1.00) | 0.905 (1.00)
8q gain | 5 (36%) | 9 | 0.617 (1.00) | 0.973 (1.00)
20q gain | 3 (21%) | 11 | 1 (1.00) | 0.42 (1.00)
3p loss | 6 (43%) | 8 | 0.617 (1.00) | 0.0724 (1.00)
4p loss | 6 (43%) | 8 | 0.414 (1.00) | 0.671 (1.00)
5p loss | 3 (21%) | 11 | 0.414 (1.00) | 0.378 (1.00)
5q loss | 7 (50%) | 7 | 0.414 (1.00) | 0.526 (1.00)
8p loss | 4 (29%) | 10 | 0.221 (1.00) | 0.236 (1.00)
10p loss | 4 (29%) | 10 | 0.617 (1.00) | 0.296 (1.00)
10q loss | 5 (36%) | 9 | 0.221 (1.00) | 0.231 (1.00)
11p loss | 6 (43%) | 8 | 0.414 (1.00) | 0.157 (1.00)
11q loss | 5 (36%) | 9 | 0.414 (1.00) | 0.393 (1.00)
12p loss | 4 (29%) | 10 | 0.0455 (1.00) | 0.0823 (1.00)
13q loss | 7 (50%) | 7 | 0.221 (1.00) | 0.152 (1.00)
17p loss | 5 (36%) | 9 | 0.414 (1.00) | 0.938 (1.00)
19p loss | 3 (21%) | 11 | 0.414 (1.00) | 0.307 (1.00)

Methods & Data
Input

- Mutation data file = broad_values_by_arm.mutsig.cluster.txt

- Clinical data file = CESC.clin.merged.picked.txt

- Number of patients = 14

- Number of significantly arm-level cnvs = 20

- 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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

- 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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