Correlation between copy number variation genes (focal events) and selected clinical features
Lymphoid Neoplasm Diffuse Large B-cell Lymphoma (Primary solid tumor)
17 October 2014 | analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1K0733K
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/C1K0733K
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 37 focal events and 4 clinical features across 35 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 37 focal events and 4 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 | GENDER | RACE
| nCNV (%) | nWild-Type | logrank test | Wilcoxon-test | Fisher's exact test | Fisher's exact test
amp 1q24 2 | 11 (31%) | 24 | 0.175 (1.00) | 0.213 (1.00) | 1 (1.00) | 0.414 (1.00)
amp 2p16 1 | 9 (26%) | 26 | 0.138 (1.00) | 0.521 (1.00) | 0.443 (1.00) | 0.586 (1.00)
amp 3q27 3 | 10 (29%) | 25 | 0.247 (1.00) | 0.956 (1.00) | 0.711 (1.00) | 0.797 (1.00)
amp 3q29 | 9 (26%) | 26 | 0.26 (1.00) | 0.558 (1.00) | 0.443 (1.00) | 1 (1.00)
amp 5p13 1 | 4 (11%) | 31 | 0.461 (1.00) | 0.5 (1.00) | 0.603 (1.00) | 0.646 (1.00)
amp 7p22 3 | 11 (31%) | 24 | 0.114 (1.00) | 0.569 (1.00) | 0.471 (1.00) | 1 (1.00)
amp 7q21 3 | 10 (29%) | 25 | 0.357 (1.00) | 0.855 (1.00) | 0.711 (1.00) | 0.478 (1.00)
amp 8q24 23 | 8 (23%) | 27 | 0.469 (1.00) | 0.906 (1.00) | 0.228 (1.00) | 0.407 (1.00)
amp 12q21 1 | 9 (26%) | 26 | 0.508 (1.00) | 0.242 (1.00) | 0.443 (1.00) | 0.204 (1.00)
amp 16p12 2 | 8 (23%) | 27 | 0.725 (1.00) | 0.504 (1.00) | 0.691 (1.00) | 1 (1.00)
amp 18q21 2 | 11 (31%) | 24 | 0.991 (1.00) | 0.499 (1.00) | 1 (1.00) | 0.00269 (0.395)
amp 19q13 43 | 7 (20%) | 28 | 0.0451 (1.00) | 0.62 (1.00) | 0.402 (1.00) | 0.524 (1.00)
amp xq27 3 | 6 (17%) | 29 | 0.486 (1.00) | 1 (1.00) | 1 (1.00) | 0.32 (1.00)
del 1p36 32 | 8 (23%) | 27 | 0.877 (1.00) | 0.529 (1.00) | 1 (1.00) | 0.559 (1.00)
del 1p13 1 | 10 (29%) | 25 | 0.332 (1.00) | 0.235 (1.00) | 0.146 (1.00) | 0.799 (1.00)
del 1q43 | 9 (26%) | 26 | 0.417 (1.00) | 0.108 (1.00) | 0.443 (1.00) | 0.59 (1.00)
del 2q23 1 | 6 (17%) | 29 | 0.783 (1.00) | 0.584 (1.00) | 0.177 (1.00) | 0.236 (1.00)
del 3p21 31 | 3 (9%) | 32 |  | 0.125 (1.00) | 0.603 (1.00) | 0.626 (1.00)
del 4q35 1 | 8 (23%) | 27 | 0.298 (1.00) | 0.443 (1.00) | 1 (1.00) | 0.41 (1.00)
del 6p21 32 | 4 (11%) | 31 | 0.559 (1.00) | 0.938 (1.00) | 1 (1.00) | 0.399 (1.00)
del 6q14 1 | 12 (34%) | 23 | 0.14 (1.00) | 0.59 (1.00) | 0.489 (1.00) | 0.822 (1.00)
del 6q22 32 | 10 (29%) | 25 | 0.647 (1.00) | 0.826 (1.00) | 0.471 (1.00) | 0.615 (1.00)
del 6q23 3 | 8 (23%) | 27 | 0.584 (1.00) | 0.937 (1.00) | 0.443 (1.00) | 0.182 (1.00)
del 8p23 2 | 7 (20%) | 28 | 0.589 (1.00) | 0.563 (1.00) | 0.0877 (1.00) | 0.522 (1.00)
del 8q12 1 | 7 (20%) | 28 | 0.235 (1.00) | 0.386 (1.00) | 1 (1.00) | 1 (1.00)
del 9p21 3 | 13 (37%) | 22 | 0.712 (1.00) | 0.539 (1.00) | 0.733 (1.00) | 0.219 (1.00)
del 10q23 31 | 5 (14%) | 30 | 0.479 (1.00) | 0.31 (1.00) | 0.338 (1.00) | 0.698 (1.00)
del 12p13 2 | 7 (20%) | 28 | 0.445 (1.00) | 0.397 (1.00) | 0.402 (1.00) | 0.523 (1.00)
del 13q14 2 | 3 (9%) | 32 | 0.123 (1.00) | 0.637 (1.00) | 0.229 (1.00) | 0.629 (1.00)
del 15q21 1 | 9 (26%) | 26 | 0.956 (1.00) | 0.821 (1.00) | 0.121 (1.00) | 0.442 (1.00)
del 16p13 13 | 4 (11%) | 31 | 0.661 (1.00) | 0.678 (1.00) | 0.104 (1.00) | 0.649 (1.00)
del 16q23 1 | 5 (14%) | 30 | 0.661 (1.00) | 0.62 (1.00) | 0.338 (1.00) | 0.436 (1.00)
del 17p13 1 | 6 (17%) | 29 | 0.582 (1.00) | 0.742 (1.00) | 0.177 (1.00) | 0.718 (1.00)
del 17q24 1 | 3 (9%) | 32 | 0.0114 (1.00) | 0.86 (1.00) | 1 (1.00) | 0.625 (1.00)
del 19p13 2 | 3 (9%) | 32 | 0.623 (1.00) | 0.68 (1.00) | 0.603 (1.00) | 0.627 (1.00)
del 19q13 2 | 3 (9%) | 32 | 0.559 (1.00) | 0.768 (1.00) | 1 (1.00) | 1 (1.00)
del 22q13 31 | 5 (14%) | 30 | 0.589 (1.00) | 0.396 (1.00) | 0.338 (1.00) | 0.436 (1.00)

Methods & Data
Input

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

- Clinical data file = DLBC-TP.merged_data.txt

- Number of patients = 35

- Number of significantly focal cnvs = 37

- Number of selected clinical features = 4

- 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.

- 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] 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)
Copyright © 2015 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle