Correlation between gene mutation status and molecular subtypes
Prostate Adenocarcinoma (Primary solid tumor)
21 April 2013 | analyses__2013_04_21
Maintainer Information
Citation Information
doi:10.7908/C1445JF1
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Prostate Adenocarcinoma (Primary solid tumor cohort) - 21 April 2013: Correlation between gene mutation status and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1445JF1
Overview
Introduction

This pipeline computes the correlation between significantly recurrent gene mutations and molecular subtypes.

Summary

Testing the association between mutation status of 13 genes and 6 molecular subtypes across 83 patients, no significant finding detected with P value < 0.05 and Q value < 0.25.

- No gene mutations related to molecuar subtypes.

Results
Overview of the results

Table 1. Get Full Table Overview of the association between mutation status of 13 genes 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 | MRNASEQ CNMF | MRNASEQ CHIERARCHICAL | MIRSEQ CNMF | MIRSEQ CHIERARCHICAL
| nMutated (%) | 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
NKX3-1 | 5 (6%) | 78 | 0.177 (1.00) | 0.366 (1.00) | 0.845 (1.00) | 0.583 (1.00) | 0.0691 (1.00) | 0.18 (1.00)
TP53 | 5 (6%) | 78 | 0.00583 (0.455) | 0.366 (1.00) | 0.21 (1.00) | 0.117 (1.00) | 0.547 (1.00) | 0.18 (1.00)
FRG1 | 4 (5%) | 79 | 0.255 (1.00) | 0.57 (1.00) | 0.363 (1.00) | 0.668 (1.00) | 0.357 (1.00) | 1 (1.00)
SPOP | 4 (5%) | 79 | 0.0148 (1.00) | 0.0695 (1.00) | 0.0596 (1.00) | 0.00937 (0.712) | 0.788 (1.00) | 0.79 (1.00)
YBX1 | 3 (4%) | 80 | 0.701 (1.00) | 0.225 (1.00) | 1 (1.00) | 0.295 (1.00) | 0.511 (1.00) | 0.687 (1.00)
CCNF | 3 (4%) | 80 | 1 (1.00) | 0.796 (1.00) | 0.471 (1.00) | 0.436 (1.00) | 1 (1.00) | 0.687 (1.00)
CLSTN1 | 3 (4%) | 80 | 1 (1.00) | 0.441 (1.00) | 0.618 (1.00) | 1 (1.00) | 0.738 (1.00) | 1 (1.00)
PRR21 | 4 (5%) | 79 | 0.701 (1.00) | 0.459 (1.00) | 1 (1.00) | 1 (1.00) | 0.185 (1.00) | 0.229 (1.00)
AGT | 3 (4%) | 80 | 0.701 (1.00) | 1 (1.00) | 1 (1.00) | 0.771 (1.00) | 0.511 (1.00) | 0.235 (1.00)
CTNNB1 | 3 (4%) | 80 | 1 (1.00) | 0.603 (1.00) | 0.471 (1.00) | 0.436 (1.00) | 0.356 (1.00) | 0.00646 (0.497)
DUSP27 | 3 (4%) | 80 | 0.513 (1.00) | 0.441 (1.00) | 0.618 (1.00) | 0.583 (1.00) | 0.738 (1.00) | 0.687 (1.00)
OR4D5 | 3 (4%) | 80 | 0.224 (1.00) | 1 (1.00) | 1 (1.00) | 0.771 (1.00) | 1 (1.00) | 0.687 (1.00)
OR6N1 | 3 (4%) | 80 | 0.364 (1.00) | 1 (1.00) | 1 (1.00) | 0.771 (1.00) | 0.173 (1.00) | 0.687 (1.00)

Methods & Data
Input

- Mutation data file = PRAD-TP.mutsig.cluster.txt

- Molecular subtypes file = PRAD-TP.transferedmergedcluster.txt

- Number of patients = 83

- Number of significantly mutated genes = 13

- 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

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

- Analysis Results (MD5 checksum)

- Auxiliary Data (MD5 checksum)

- MAGE-TAB File (MD5 checksum)

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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle