Correlation between copy number variation genes (focal events) and selected clinical features

Testicular Germ Cell Tumors (Primary solid tumor)

17 October 2014 | analyses__2014_10_17

Maintainer Information

Citation Information

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/C1BK1B84

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 42 focal events and 5 clinical features across 31 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 42 focal events and 5 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, no significant finding detected.


		Clinical Features	AGE	NEOPLASM DISEASESTAGE	PATHOLOGY T STAGE	PATHOLOGY N STAGE	ETHNICITY
	nCNV (%)	nWild-Type	Wilcoxon-test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
amp 1q21 2	13 (42%)	18	0.763 (1.00)	0.785 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
amp 2p24 1	16 (52%)	15	0.452 (1.00)	0.199 (1.00)	0.156 (1.00)	0.584 (1.00)	0.101 (1.00)
amp 3q27 3	12 (39%)	19	0.951 (1.00)	0.0132 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
amp 4q12	4 (13%)	27	0.345 (1.00)	0.891 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
amp 7q11 22	28 (90%)	3	0.947 (1.00)	1 (1.00)	0.6 (1.00)	1 (1.00)	0.271 (1.00)
amp 8q11 23	28 (90%)	3	0.525 (1.00)	0.0634 (1.00)	0.6 (1.00)	1 (1.00)	1 (1.00)
amp 8q23 3	25 (81%)	6	0.531 (1.00)	0.532 (1.00)	0.0829 (1.00)	0.519 (1.00)	0.488 (1.00)
amp 12q15	22 (71%)	9	0.0773 (1.00)	1 (1.00)	1 (1.00)	0.519 (1.00)	0.195 (1.00)
amp 16q21	6 (19%)	25	0.599 (1.00)	0.422 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
amp 20q11 21	11 (35%)	20	0.432 (1.00)	0.637 (1.00)	0.135 (1.00)	1 (1.00)	0.535 (1.00)
amp 22q11 21	10 (32%)	21	0.227 (1.00)	0.842 (1.00)	0.458 (1.00)	0.519 (1.00)	0.533 (1.00)
del 1p36 31	7 (23%)	24	0.477 (1.00)	0.85 (1.00)	0.22 (1.00)	1 (1.00)	0.12 (1.00)
del 1p31 1	8 (26%)	23	1 (1.00)	0.479 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
del 2q37 3	5 (16%)	26	0.0595 (1.00)	0.349 (1.00)	0.654 (1.00)	1 (1.00)	1 (1.00)
del 3p26 2	14 (45%)	17	0.619 (1.00)	0.442 (1.00)	0.285 (1.00)	0.576 (1.00)	1 (1.00)
del 4q22 2	25 (81%)	6	0.0674 (1.00)	0.703 (1.00)	1 (1.00)	0.541 (1.00)	1 (1.00)
del 5p15 2	21 (68%)	10	0.271 (1.00)	0.965 (1.00)	0.252 (1.00)	1 (1.00)	1 (1.00)
del 5p14 3	22 (71%)	9	0.383 (1.00)	0.771 (1.00)	0.113 (1.00)	1 (1.00)	1 (1.00)
del 5q12 1	21 (68%)	10	0.799 (1.00)	0.349 (1.00)	0.0538 (1.00)	1 (1.00)	1 (1.00)
del 6p22 3	7 (23%)	24	0.758 (1.00)	0.736 (1.00)	1 (1.00)	0.519 (1.00)	0.55 (1.00)
del 6q26	8 (26%)	23	1 (1.00)	0.627 (1.00)	0.433 (1.00)	1 (1.00)	1 (1.00)
del 7q11 22	3 (10%)	28	0.815 (1.00)	0.912 (1.00)	0.6 (1.00)	1 (1.00)	0.271 (1.00)
del 7q36 1	4 (13%)	27	0.249 (1.00)	0.79 (1.00)	0.333 (1.00)	0.541 (1.00)	0.349 (1.00)
del 9p24 3	19 (61%)	12	0.807 (1.00)	0.506 (1.00)	0.473 (1.00)	0.261 (1.00)	1 (1.00)
del 9p23	19 (61%)	12	0.807 (1.00)	0.507 (1.00)	0.473 (1.00)	0.261 (1.00)	1 (1.00)
del 9q33 3	16 (52%)	15	0.276 (1.00)	0.712 (1.00)	0.724 (1.00)	0.237 (1.00)	0.6 (1.00)
del 9q34 2	14 (45%)	17	0.426 (1.00)	0.352 (1.00)	0.722 (1.00)	0.103 (1.00)	0.232 (1.00)
del 10p15 3	22 (71%)	9	0.138 (1.00)	0.256 (1.00)	0.704 (1.00)	0.519 (1.00)	0.195 (1.00)
del 10q23 1	20 (65%)	11	0.148 (1.00)	0.741 (1.00)	0.458 (1.00)	0.519 (1.00)	0.0367 (1.00)
del 10q26 3	18 (58%)	13	0.0959 (1.00)	0.538 (1.00)	1 (1.00)	0.261 (1.00)	0.0636 (1.00)
del 11p15 5	18 (58%)	13	0.422 (1.00)	0.867 (1.00)	0.722 (1.00)	0.603 (1.00)	1 (1.00)
del 11p12	19 (61%)	12	0.155 (1.00)	0.588 (1.00)	0.473 (1.00)	0.603 (1.00)	1 (1.00)
del 11q12 3	23 (74%)	8	0.161 (1.00)	0.427 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
del 11q24 2	26 (84%)	5	0.206 (1.00)	0.567 (1.00)	0.654 (1.00)	0.541 (1.00)	0.422 (1.00)
del 13q34	22 (71%)	9	0.081 (1.00)	0.862 (1.00)	0.704 (1.00)	0.261 (1.00)	0.537 (1.00)
del 16q23 1	15 (48%)	16	0.0433 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.101 (1.00)
del 18p11 32	26 (84%)	5	0.132 (1.00)	0.131 (1.00)	1 (1.00)	0.426 (1.00)	1 (1.00)
del 18q22 2	27 (87%)	4	0.148 (1.00)	0.0307 (1.00)	0.6 (1.00)	0.235 (1.00)	1 (1.00)
del 19q13 41	18 (58%)	13	0.185 (1.00)	0.00355 (0.745)	0.722 (1.00)	1 (1.00)	1 (1.00)
del 20p12 1	7 (23%)	24	0.813 (1.00)	0.296 (1.00)	1 (1.00)	0.219 (1.00)	0.55 (1.00)
del xp21 1	7 (23%)	24	0.636 (1.00)	0.36 (1.00)	0.0373 (1.00)	0.519 (1.00)	0.55 (1.00)
del xq27 3	7 (23%)	24	0.136 (1.00)	0.851 (1.00)	0.0373 (1.00)	0.541 (1.00)	0.55 (1.00)

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Clinical data file = TGCT-TP.merged_data.txt
Number of patients = 31
Number of significantly focal cnvs = 42
Number of selected clinical features = 5
Exclude genes that fewer than K tumors have mutations, K = 3

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] 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)

[2] 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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