Correlation between gene mutation status and molecular subtypes
Kidney Chromophobe (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
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 gene mutation status and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1RX99F5
Overview
Introduction

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

Summary

Testing the association between mutation status of 2 genes and 8 molecular subtypes across 66 patients, one significant finding detected with P value < 0.05 and Q value < 0.25.

  • PTEN mutation correlated to 'MIRSEQ_MATURE_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between mutation status of 2 genes and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, one significant finding detected.

Clinical
Features
CN
CNMF
METHLYATION
CNMF
MRNASEQ
CNMF
MRNASEQ
CHIERARCHICAL
MIRSEQ
CNMF
MIRSEQ
CHIERARCHICAL
MIRSEQ
MATURE
CNMF
MIRSEQ
MATURE
CHIERARCHICAL
nMutated (%) nWild-Type Fisher's exact test Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test
PTEN 6 (9%) 60 0.0988
(1.00)
0.321
(1.00)
0.351
(1.00)
0.13
(1.00)
0.354
(1.00)
0.585
(1.00)
0.00617
(0.0988)
0.0812
(1.00)
TP53 22 (33%) 44 0.615
(1.00)
0.0882
(1.00)
0.0646
(0.904)
0.0593
(0.89)
0.645
(1.00)
0.706
(1.00)
0.76
(1.00)
0.898
(1.00)
'PTEN MUTATION STATUS' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.00617 (Chi-square test), Q value = 0.099

Table S1.  Gene #2: 'PTEN MUTATION STATUS' versus Clinical Feature #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 16 16 10 14
PTEN MUTATED 4 0 1 0 1
PTEN WILD-TYPE 6 16 15 10 13

Figure S1.  Get High-res Image Gene #2: 'PTEN MUTATION STATUS' versus Clinical Feature #7: 'MIRSEQ_MATURE_CNMF'

Methods & Data
Input
  • Mutation data file = KICH-TP.mutsig.cluster.txt

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

  • Number of patients = 66

  • Number of significantly mutated genes = 2

  • Number of Molecular subtypes = 8

  • 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

Chi-square test

For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[3] 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)