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

Sarcoma (Primary solid tumor)

21 April 2013 | analyses__2013_04_21

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): Sarcoma (Primary solid tumor cohort) - 21 April 2013: Correlation between copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1J38QHH

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 65 arm-level results and 4 molecular subtypes across 51 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 65 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
1p gain	0 (0%)	43	0.119 (1.00)	0.248 (1.00)	0.573 (1.00)	0.606 (1.00)
1q gain	0 (0%)	44	0.224 (1.00)	0.0127 (1.00)	0.0783 (1.00)	0.164 (1.00)
4p gain	0 (0%)	46	0.588 (1.00)	0.417 (1.00)
5p gain	0 (0%)	39	0.0662 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
5q gain	0 (0%)	42	0.0624 (1.00)	0.221 (1.00)	1 (1.00)	1 (1.00)
6p gain	0 (0%)	44	0.0233 (1.00)	0.111 (1.00)	0.107 (1.00)	0.235 (1.00)
6q gain	0 (0%)	42	0.0346 (1.00)	0.0354 (1.00)	0.0476 (1.00)	0.0926 (1.00)
7p gain	0 (0%)	38	0.00452 (1.00)	0.222 (1.00)	0.632 (1.00)	0.283 (1.00)
7q gain	0 (0%)	40	0.0536 (1.00)	0.114 (1.00)	0.632 (1.00)	0.283 (1.00)
8p gain	0 (0%)	42	0.0205 (1.00)	0.588 (1.00)	0.632 (1.00)	0.689 (1.00)
8q gain	0 (0%)	43	0.498 (1.00)	0.0569 (1.00)	1 (1.00)	1 (1.00)
9p gain	0 (0%)	48	0.101 (1.00)	0.502 (1.00)	0.488 (1.00)
9q gain	0 (0%)	45	0.0153 (1.00)	0.484 (1.00)	0.107 (1.00)	0.235 (1.00)
11p gain	0 (0%)	48	0.459 (1.00)	1 (1.00)	0.448 (1.00)
12p gain	0 (0%)	44	1 (1.00)	0.774 (1.00)	1 (1.00)
14q gain	0 (0%)	48	1 (1.00)	0.282 (1.00)	1 (1.00)
15q gain	0 (0%)	43	0.202 (1.00)	0.712 (1.00)	1 (1.00)
16p gain	0 (0%)	45	0.546 (1.00)	0.14 (1.00)	0.573 (1.00)	0.606 (1.00)
17p gain	0 (0%)	44	0.00158 (0.383)	0.00216 (0.523)	1 (1.00)
17q gain	0 (0%)	46	0.0669 (1.00)	0.417 (1.00)	0.573 (1.00)	0.103 (1.00)
18p gain	0 (0%)	45	0.301 (1.00)	0.484 (1.00)	1 (1.00)
18q gain	0 (0%)	43	0.498 (1.00)	0.44 (1.00)	1 (1.00)	1 (1.00)
19p gain	0 (0%)	42	0.0046 (1.00)	0.588 (1.00)	0.573 (1.00)	0.103 (1.00)
19q gain	0 (0%)	46	0.00241 (0.58)	0.851 (1.00)
20p gain	0 (0%)	40	0.316 (1.00)	0.334 (1.00)	1 (1.00)	1 (1.00)
20q gain	0 (0%)	37	0.251 (1.00)	0.0463 (1.00)	1 (1.00)	1 (1.00)
21q gain	0 (0%)	45	0.64 (1.00)	0.164 (1.00)	1 (1.00)
22q gain	0 (0%)	46	1 (1.00)	1 (1.00)	0.448 (1.00)
1p loss	0 (0%)	42	0.0624 (1.00)	0.198 (1.00)	0.144 (1.00)	0.0558 (1.00)
1q loss	0 (0%)	45	0.403 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)
2p loss	0 (0%)	41	0.908 (1.00)	0.163 (1.00)	0.632 (1.00)	0.689 (1.00)
2q loss	0 (0%)	43	0.892 (1.00)	0.311 (1.00)	1 (1.00)	1 (1.00)
3p loss	0 (0%)	41	0.134 (1.00)	0.559 (1.00)	0.107 (1.00)	0.235 (1.00)
3q loss	0 (0%)	39	0.407 (1.00)	0.6 (1.00)	0.183 (1.00)	0.363 (1.00)
4p loss	0 (0%)	44	0.17 (1.00)	0.111 (1.00)	1 (1.00)	1 (1.00)
4q loss	0 (0%)	44	0.29 (1.00)	0.111 (1.00)	1 (1.00)	1 (1.00)
5p loss	0 (0%)	47	0.67 (1.00)	0.533 (1.00)	1 (1.00)	1 (1.00)
5q loss	0 (0%)	47	1 (1.00)	1 (1.00)	0.488 (1.00)
6p loss	0 (0%)	43	0.62 (1.00)	0.248 (1.00)	0.364 (1.00)	0.488 (1.00)
6q loss	0 (0%)	47	0.67 (1.00)	0.193 (1.00)	1 (1.00)
7p loss	0 (0%)	47	0.67 (1.00)	0.193 (1.00)	0.573 (1.00)	0.606 (1.00)
7q loss	0 (0%)	45	0.64 (1.00)	0.14 (1.00)	0.606 (1.00)	0.667 (1.00)
8p loss	0 (0%)	42	0.376 (1.00)	0.43 (1.00)	0.663 (1.00)	0.119 (1.00)
8q loss	0 (0%)	46	0.71 (1.00)	0.115 (1.00)	0.232 (1.00)	0.317 (1.00)
9p loss	0 (0%)	40	0.104 (1.00)	0.162 (1.00)	0.183 (1.00)	0.0128 (1.00)
9q loss	0 (0%)	45	0.64 (1.00)	0.656 (1.00)	0.606 (1.00)	0.667 (1.00)
10p loss	0 (0%)	34	0.155 (1.00)	0.196 (1.00)	1 (1.00)	0.34 (1.00)
10q loss	0 (0%)	31	0.0714 (1.00)	0.0227 (1.00)	0.0641 (1.00)	0.0718 (1.00)
11p loss	0 (0%)	36	0.363 (1.00)	0.221 (1.00)	0.41 (1.00)	0.0647 (1.00)
11q loss	0 (0%)	40	0.0668 (1.00)	0.334 (1.00)	0.183 (1.00)	0.363 (1.00)
12q loss	0 (0%)	47	0.45 (1.00)	1 (1.00)	0.488 (1.00)
13q loss	0 (0%)	28	0.18 (1.00)	0.334 (1.00)	0.716 (1.00)	0.56 (1.00)
14q loss	0 (0%)	36	0.0792 (1.00)	0.299 (1.00)	0.226 (1.00)	0.15 (1.00)
15q loss	0 (0%)	42	0.376 (1.00)	0.27 (1.00)	0.00843 (1.00)	0.0136 (1.00)
16p loss	0 (0%)	42	0.65 (1.00)	1 (1.00)	0.343 (1.00)	0.466 (1.00)
16q loss	0 (0%)	31	0.934 (1.00)	0.0457 (1.00)	0.688 (1.00)	0.368 (1.00)
17p loss	0 (0%)	43	0.226 (1.00)	0.248 (1.00)	1 (1.00)	1 (1.00)
17q loss	0 (0%)	46	0.0353 (1.00)	0.115 (1.00)	0.573 (1.00)	0.606 (1.00)
18p loss	0 (0%)	43	1 (1.00)	0.89 (1.00)	0.606 (1.00)	0.667 (1.00)
18q loss	0 (0%)	41	0.818 (1.00)	1 (1.00)	0.606 (1.00)	0.667 (1.00)
19q loss	0 (0%)	46	0.71 (1.00)	0.248 (1.00)	1 (1.00)
20p loss	0 (0%)	46	0.114 (1.00)	0.851 (1.00)	0.343 (1.00)	0.466 (1.00)
21q loss	0 (0%)	43	0.137 (1.00)	0.89 (1.00)	1 (1.00)	1 (1.00)
22q loss	0 (0%)	36	0.423 (1.00)	0.639 (1.00)	0.702 (1.00)	0.817 (1.00)
Xq loss	0 (0%)	41	0.035 (1.00)	0.0715 (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 = 51
Number of significantly arm-level cnvs = 65
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)

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