Correlation between copy number variations of arm-level result and molecular subtypes
Esophageal Carcinoma (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): Esophageal Carcinoma (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/C1XG9P2V
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 38 arm-level results and molecular subtype 'METHLYATION_CNMF' across 20 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 38 arm-level results and 1 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, no significant finding detected.

Molecular
subtypes
METHLYATION
CNMF
nCNV (%) nWild-Type Fisher's exact test
1q gain 0 (0%) 16 0.569
(1.00)
2p gain 0 (0%) 17 0.711
(1.00)
3p gain 0 (0%) 16 1
(1.00)
3q gain 0 (0%) 13 0.223
(1.00)
5p gain 0 (0%) 14 1
(1.00)
7p gain 0 (0%) 13 0.164
(1.00)
7q gain 0 (0%) 14 1
(1.00)
8p gain 0 (0%) 13 0.553
(1.00)
8q gain 0 (0%) 9 0.835
(1.00)
9q gain 0 (0%) 16 1
(1.00)
10p gain 0 (0%) 16 0.0788
(1.00)
12p gain 0 (0%) 11 0.0677
(1.00)
14q gain 0 (0%) 16 0.569
(1.00)
17p gain 0 (0%) 15 0.198
(1.00)
17q gain 0 (0%) 15 0.147
(1.00)
18p gain 0 (0%) 16 1
(1.00)
20p gain 0 (0%) 10 1
(1.00)
20q gain 0 (0%) 10 1
(1.00)
21q gain 0 (0%) 17 1
(1.00)
22q gain 0 (0%) 15 1
(1.00)
Xq gain 0 (0%) 16 1
(1.00)
3p loss 0 (0%) 13 0.655
(1.00)
4p loss 0 (0%) 14 0.51
(1.00)
4q loss 0 (0%) 15 0.198
(1.00)
5p loss 0 (0%) 16 0.569
(1.00)
5q loss 0 (0%) 16 0.569
(1.00)
6p loss 0 (0%) 14 0.51
(1.00)
6q loss 0 (0%) 17 1
(1.00)
9p loss 0 (0%) 17 0.344
(1.00)
10p loss 0 (0%) 16 1
(1.00)
10q loss 0 (0%) 17 0.711
(1.00)
11p loss 0 (0%) 17 0.711
(1.00)
13q loss 0 (0%) 13 0.223
(1.00)
16q loss 0 (0%) 16 1
(1.00)
18p loss 0 (0%) 14 0.408
(1.00)
18q loss 0 (0%) 13 1
(1.00)
21q loss 0 (0%) 10 0.443
(1.00)
22q loss 0 (0%) 17 0.518
(1.00)
Methods & Data
Input
  • Mutation data file = broad_values_by_arm.mutsig.cluster.txt

  • Molecular subtypes file = ESCA-TP.transferedmergedcluster.txt

  • Number of patients = 20

  • Number of significantly arm-level cnvs = 38

  • Number of molecular subtypes = 1: 'METHLYATION_CNMF'

  • 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)