Correlation between copy number variations of arm-level result and molecular subtypes

Sarcoma (Primary solid tumor)

22 February 2013 | analyses__2013_02_22

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 (2013): Correlation between copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1G73BX6

Overview

Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and subtypes.

Summary

Testing the association between copy number variation 46 arm-level results and 4 molecular subtypes across 29 patients, no significant finding detected with Q value < 0.25.

No arm-level cnvs related to molecular subtypes.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 46 arm-level results and 4 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, no significant finding detected.


		Molecular subtypes	CN CNMF	METHLYATION CNMF	MIRSEQ CNMF	MIRSEQ CHIERARCHICAL
	nCNV (%)	nWild-Type	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
5p gain	4 (14%)	25	0.268 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
5q gain	4 (14%)	25	0.268 (1.00)	0.518 (1.00)	1 (1.00)	1 (1.00)
6p gain	4 (14%)	25	0.622 (1.00)	0.518 (1.00)	0.107 (1.00)	0.235 (1.00)
6q gain	5 (17%)	24	0.0539 (1.00)	0.387 (1.00)	0.0476 (1.00)	0.0926 (1.00)
7p gain	5 (17%)	24	0.622 (1.00)	0.387 (1.00)	0.632 (1.00)	0.283 (1.00)
7q gain	5 (17%)	24	0.622 (1.00)	0.387 (1.00)	0.632 (1.00)	0.283 (1.00)
8p gain	5 (17%)	24	0.126 (1.00)	0.704 (1.00)	0.632 (1.00)	0.689 (1.00)
8q gain	4 (14%)	25	1 (1.00)	0.169 (1.00)	1 (1.00)	1 (1.00)
9p gain	3 (10%)	26	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
9q gain	5 (17%)	24	0.339 (1.00)	0.476 (1.00)	0.343 (1.00)	0.466 (1.00)
16p gain	3 (10%)	26	1 (1.00)	0.353 (1.00)	0.573 (1.00)	0.606 (1.00)
17q gain	3 (10%)	26	0.268 (1.00)	0.353 (1.00)	0.573 (1.00)	0.103 (1.00)
18q gain	3 (10%)	26	1 (1.00)	0.0482 (1.00)	1 (1.00)	1 (1.00)
20p gain	4 (14%)	25	0.268 (1.00)	0.116 (1.00)	1 (1.00)	1 (1.00)
20q gain	5 (17%)	24	0.622 (1.00)	0.033 (1.00)	1 (1.00)	1 (1.00)
1p loss	5 (17%)	24	0.126 (1.00)	0.269 (1.00)	0.144 (1.00)	0.0558 (1.00)
1q loss	3 (10%)	26	0.268 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
2p loss	3 (10%)	26	0.268 (1.00)	0.17 (1.00)	0.573 (1.00)	0.606 (1.00)
2q loss	3 (10%)	26	1 (1.00)	0.353 (1.00)	1 (1.00)	1 (1.00)
3p loss	4 (14%)	25	0.0139 (1.00)	0.518 (1.00)	0.107 (1.00)	0.235 (1.00)
3q loss	5 (17%)	24	0.0539 (1.00)	1 (1.00)	0.343 (1.00)	0.466 (1.00)
5p loss	3 (10%)	26	1 (1.00)	0.473 (1.00)	1 (1.00)	1 (1.00)
6p loss	6 (21%)	23	1 (1.00)	0.443 (1.00)	0.364 (1.00)	0.488 (1.00)
7p loss	3 (10%)	26	0.268 (1.00)	0.17 (1.00)	0.573 (1.00)	0.606 (1.00)
7q loss	4 (14%)	25	1 (1.00)	0.116 (1.00)	0.606 (1.00)	0.667 (1.00)
8p loss	5 (17%)	24	1 (1.00)	1 (1.00)	1 (1.00)	0.149 (1.00)
9p loss	5 (17%)	24	1 (1.00)	0.0525 (1.00)	0.343 (1.00)	0.0262 (1.00)
9q loss	3 (10%)	26	0.268 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
10p loss	8 (28%)	21	0.11 (1.00)	0.591 (1.00)	1 (1.00)	0.34 (1.00)
10q loss	10 (34%)	19	0.0436 (1.00)	0.381 (1.00)	0.0641 (1.00)	0.0718 (1.00)
11p loss	7 (24%)	22	1 (1.00)	0.0975 (1.00)	0.41 (1.00)	0.0647 (1.00)
11q loss	6 (21%)	23	0.646 (1.00)	0.222 (1.00)	0.183 (1.00)	0.363 (1.00)
13q loss	12 (41%)	17	0.273 (1.00)	0.13 (1.00)	0.716 (1.00)	0.56 (1.00)
14q loss	8 (28%)	21	1 (1.00)	0.334 (1.00)	0.406 (1.00)	0.443 (1.00)
15q loss	6 (21%)	23	0.164 (1.00)	0.183 (1.00)	0.0205 (1.00)	0.0463 (1.00)
16p loss	5 (17%)	24	1 (1.00)	1 (1.00)	0.343 (1.00)	0.466 (1.00)
16q loss	9 (31%)	20	1 (1.00)	0.599 (1.00)	0.688 (1.00)	0.368 (1.00)
17p loss	5 (17%)	24	0.622 (1.00)	0.122 (1.00)	0.632 (1.00)	0.689 (1.00)
17q loss	3 (10%)	26	1 (1.00)	0.254 (1.00)	0.573 (1.00)	0.606 (1.00)
18p loss	4 (14%)	25	1 (1.00)	1 (1.00)	0.606 (1.00)	0.667 (1.00)
18q loss	4 (14%)	25	1 (1.00)	1 (1.00)	0.606 (1.00)	0.667 (1.00)
19q loss	3 (10%)	26	0.268 (1.00)	0.353 (1.00)	0.573 (1.00)	0.103 (1.00)
20p loss	6 (21%)	23	0.0185 (1.00)	0.854 (1.00)	0.183 (1.00)	0.363 (1.00)
21q loss	6 (21%)	23	0.646 (1.00)	0.729 (1.00)	0.663 (1.00)	0.741 (1.00)
22q loss	11 (38%)	18	1 (1.00)	0.639 (1.00)	0.702 (1.00)	0.817 (1.00)
Xq loss	6 (21%)	23	1 (1.00)	0.0728 (1.00)	1 (1.00)	1 (1.00)

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Molecular subtypes file = SARC-TP.transferedmergedcluster.txt
Number of patients = 29
Number of significantly arm-level cnvs = 46
Number of molecular subtypes = 4
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

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

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)

Made with Nozzle