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

Mesothelioma (Primary solid tumor)

16 April 2014 | analyses__2014_04_16

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 variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1C24V3C

Overview

Introduction

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

Summary

Testing the association between copy number variation 52 arm-level events and 6 molecular subtypes across 37 patients, no significant finding detected with P value < 0.05 and 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 52 arm-level events and 6 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, no significant finding detected.


		Clinical Features	CN CNMF	METHLYATION CNMF	MIRSEQ CNMF	MIRSEQ CHIERARCHICAL	MIRSEQ MATURE CNMF	MIRSEQ MATURE CHIERARCHICAL
	nCNV (%)	nWild-Type	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
1p gain	3 (8%)	34	0.568 (1.00)	0.0875 (1.00)	1 (1.00)		1 (1.00)	1 (1.00)
1q gain	10 (27%)	27	0.274 (1.00)	0.725 (1.00)	1 (1.00)	0.749 (1.00)	0.683 (1.00)	1 (1.00)
3p gain	8 (22%)	29	0.254 (1.00)	0.428 (1.00)	0.644 (1.00)	0.422 (1.00)	0.365 (1.00)	1 (1.00)
3q gain	9 (24%)	28	0.136 (1.00)	0.251 (1.00)	1 (1.00)	0.228 (1.00)	0.665 (1.00)	1 (1.00)
5p gain	11 (30%)	26	0.151 (1.00)	1 (1.00)	0.0873 (1.00)	0.0749 (1.00)	0.11 (1.00)	0.217 (1.00)
5q gain	7 (19%)	30	1 (1.00)	0.68 (1.00)	0.121 (1.00)	0.0407 (1.00)	0.33 (1.00)	0.356 (1.00)
7p gain	10 (27%)	27	0.0667 (1.00)	1 (1.00)	0.0989 (1.00)	0.105 (1.00)	0.216 (1.00)	0.395 (1.00)
7q gain	7 (19%)	30	0.437 (1.00)	0.68 (1.00)	0.352 (1.00)	0.341 (1.00)	0.652 (1.00)	1 (1.00)
8p gain	5 (14%)	32	1 (1.00)	1 (1.00)	0.617 (1.00)	0.297 (1.00)	0.33 (1.00)	0.356 (1.00)
8q gain	6 (16%)	31	0.68 (1.00)	1 (1.00)	1 (1.00)	0.341 (1.00)	0.652 (1.00)	1 (1.00)
11p gain	6 (16%)	31	0.371 (1.00)	1 (1.00)	0.262 (1.00)	0.271 (1.00)	1 (1.00)	1 (1.00)
11q gain	5 (14%)	32	0.634 (1.00)	1 (1.00)	0.136 (1.00)	0.108 (1.00)	0.598 (1.00)	0.614 (1.00)
12p gain	7 (19%)	30	0.0287 (1.00)	0.68 (1.00)	0.625 (1.00)	0.801 (1.00)	0.306 (1.00)	1 (1.00)
12q gain	7 (19%)	30	0.0287 (1.00)	0.68 (1.00)	0.625 (1.00)	0.801 (1.00)	0.306 (1.00)	1 (1.00)
15q gain	5 (14%)	32	0.144 (1.00)	0.348 (1.00)	1 (1.00)	1 (1.00)	0.598 (1.00)	0.614 (1.00)
16p gain	8 (22%)	29	0.254 (1.00)	1 (1.00)	0.668 (1.00)	0.271 (1.00)	0.391 (1.00)	0.658 (1.00)
16q gain	9 (24%)	28	0.136 (1.00)	0.703 (1.00)	0.42 (1.00)	0.305 (1.00)	0.216 (1.00)	0.395 (1.00)
17p gain	3 (8%)	34	0.0721 (1.00)	0.0875 (1.00)	0.385 (1.00)		0.462 (1.00)	0.423 (1.00)
17q gain	7 (19%)	30	0.0287 (1.00)	1 (1.00)	1 (1.00)	0.498 (1.00)	0.598 (1.00)	0.614 (1.00)
18p gain	3 (8%)	34	0.568 (1.00)	0.584 (1.00)	0.508 (1.00)		0.483 (1.00)	0.492 (1.00)
19p gain	5 (14%)	32	0.634 (1.00)	1 (1.00)	1 (1.00)	0.365 (1.00)	0.598 (1.00)	0.614 (1.00)
19q gain	3 (8%)	34	0.568 (1.00)	0.584 (1.00)	0.508 (1.00)		0.483 (1.00)	0.492 (1.00)
20p gain	3 (8%)	34	1 (1.00)	0.584 (1.00)	1 (1.00)		1 (1.00)	1 (1.00)
20q gain	3 (8%)	34	1 (1.00)	0.584 (1.00)	1 (1.00)	0.564 (1.00)	1 (1.00)	1 (1.00)
1p loss	7 (19%)	30	0.202 (1.00)	1 (1.00)	0.352 (1.00)	1 (1.00)	0.652 (1.00)	1 (1.00)
2q loss	3 (8%)	34	0.568 (1.00)	0.584 (1.00)	0.262 (1.00)	1 (1.00)	0.225 (1.00)	0.238 (1.00)
4p loss	16 (43%)	21	0.0516 (1.00)	0.746 (1.00)	0.422 (1.00)	0.879 (1.00)	0.431 (1.00)	0.233 (1.00)
4q loss	14 (38%)	23	0.305 (1.00)	0.328 (1.00)	0.701 (1.00)	0.879 (1.00)	0.267 (1.00)	0.13 (1.00)
5q loss	3 (8%)	34	0.568 (1.00)	0.584 (1.00)	1 (1.00)		1 (1.00)	1 (1.00)
6p loss	6 (16%)	31	0.0662 (1.00)	1 (1.00)	1 (1.00)	0.498 (1.00)	0.598 (1.00)	0.614 (1.00)
6q loss	14 (38%)	23	0.733 (1.00)	0.328 (1.00)	1 (1.00)	0.084 (1.00)	0.683 (1.00)	1 (1.00)
8p loss	5 (14%)	32	1 (1.00)	1 (1.00)	1 (1.00)		1 (1.00)	1 (1.00)
9p loss	15 (41%)	22	0.00588 (1.00)	1 (1.00)	0.422 (1.00)	0.524 (1.00)	0.431 (1.00)	0.233 (1.00)
9q loss	11 (30%)	26	0.151 (1.00)	0.719 (1.00)	0.425 (1.00)	0.449 (1.00)	0.422 (1.00)	0.228 (1.00)
10p loss	11 (30%)	26	0.151 (1.00)	1 (1.00)	1 (1.00)	0.512 (1.00)	0.422 (1.00)	0.228 (1.00)
10q loss	8 (22%)	29	0.705 (1.00)	1 (1.00)	1 (1.00)	0.519 (1.00)	0.19 (1.00)	0.0946 (1.00)
11q loss	4 (11%)	33	1 (1.00)	0.036 (1.00)	0.0462 (1.00)	0.0362 (1.00)	0.0846 (1.00)	0.0635 (1.00)
13q loss	18 (49%)	19	0.0489 (1.00)	0.103 (1.00)	1 (1.00)	0.203 (1.00)	1 (1.00)	0.692 (1.00)
14q loss	16 (43%)	21	0.00896 (1.00)	0.746 (1.00)	0.105 (1.00)	0.235 (1.00)	0.431 (1.00)	0.233 (1.00)
15q loss	6 (16%)	31	0.371 (1.00)	0.0752 (1.00)	0.625 (1.00)	0.801 (1.00)	0.306 (1.00)	0.279 (1.00)
16p loss	3 (8%)	34	0.568 (1.00)	0.584 (1.00)	1 (1.00)		0.203 (1.00)	0.169 (1.00)
16q loss	4 (11%)	33	0.296 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.58 (1.00)	0.556 (1.00)
17p loss	9 (24%)	28	1 (1.00)	1 (1.00)	0.19 (1.00)	0.86 (1.00)	0.391 (1.00)	0.658 (1.00)
17q loss	3 (8%)	34	1 (1.00)	0.584 (1.00)	1 (1.00)	1 (1.00)	0.58 (1.00)	0.556 (1.00)
18p loss	5 (14%)	32	1 (1.00)	0.644 (1.00)	0.617 (1.00)	0.669 (1.00)	0.635 (1.00)	0.62 (1.00)
18q loss	9 (24%)	28	1 (1.00)	1 (1.00)	0.668 (1.00)	0.86 (1.00)	0.665 (1.00)	0.407 (1.00)
19q loss	3 (8%)	34	1 (1.00)	1 (1.00)	1 (1.00)		0.203 (1.00)	0.169 (1.00)
20p loss	7 (19%)	30	0.0287 (1.00)	0.0975 (1.00)	0.617 (1.00)	0.819 (1.00)	1 (1.00)	0.356 (1.00)
20q loss	3 (8%)	34	0.0721 (1.00)	1 (1.00)	1 (1.00)		0.203 (1.00)	1 (1.00)
21q loss	6 (16%)	31	0.0662 (1.00)	1 (1.00)	0.617 (1.00)	0.669 (1.00)	1 (1.00)	1 (1.00)
22q loss	29 (78%)	8	0.104 (1.00)	0.109 (1.00)	0.0532 (1.00)	0.151 (1.00)	0.0171 (1.00)	0.0237 (1.00)
xq loss	7 (19%)	30	0.0287 (1.00)	0.00942 (1.00)	1 (1.00)	0.037 (1.00)	1 (1.00)	1 (1.00)

Methods & Data

Input

Copy number data file = transformed.cor.cli.txt
Molecular subtypes file = MESO-TP.transferedmergedcluster.txt
Number of patients = 37
Number of significantly arm-level cnvs = 52
Number of molecular subtypes = 6
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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