Correlation between gene mutation status and molecular subtypes

Kidney Renal Papillary Cell Carcinoma (Primary solid tumor)

15 January 2014 | analyses__2014_01_15

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 gene mutation status and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1668BKS

Overview

Introduction

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

Summary

Testing the association between 'NF2 MUTATION ANALYSIS' and 8 molecular subtypes across 112 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 1 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, no 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	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test	Fisher's exact test
NF2	7 (6%)	105	0.0599 (0.479)	0.0672 (0.479)	0.237 (1.00)	0.471 (1.00)	0.891 (1.00)	0.423 (1.00)	1 (1.00)	1 (1.00)

'NF2 MUTATION STATUS' versus 'CN_CNMF'

P value = 0.0599 (Fisher's exact test), Q value = 0.48

Table S1. Gene #1: 'NF2 MUTATION STATUS' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	20	51	20	21
NF2 MUTATED	0	3	0	4
NF2 WILD-TYPE	20	48	20	17

'NF2 MUTATION STATUS' versus 'METHLYATION_CNMF'

P value = 0.0672 (Fisher's exact test), Q value = 0.48

Table S2. Gene #1: 'NF2 MUTATION STATUS' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	28	31	38
NF2 MUTATED	0	5	2
NF2 WILD-TYPE	28	26	36

'NF2 MUTATION STATUS' versus 'MRNASEQ_CNMF'

P value = 0.237 (Fisher's exact test), Q value = 1

Table S3. Gene #1: 'NF2 MUTATION STATUS' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4
ALL	41	25	17	20
NF2 MUTATED	5	2	0	0
NF2 WILD-TYPE	36	23	17	20

'NF2 MUTATION STATUS' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.471 (Fisher's exact test), Q value = 1

Table S4. Gene #1: 'NF2 MUTATION STATUS' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	23	44	36
NF2 MUTATED	3	2	2
NF2 WILD-TYPE	20	42	34

'NF2 MUTATION STATUS' versus 'MIRSEQ_CNMF'

P value = 0.891 (Fisher's exact test), Q value = 1

Table S5. Gene #1: 'NF2 MUTATION STATUS' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	41	45	26
NF2 MUTATED	2	3	2
NF2 WILD-TYPE	39	42	24

'NF2 MUTATION STATUS' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.423 (Fisher's exact test), Q value = 1

Table S6. Gene #1: 'NF2 MUTATION STATUS' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	16	49	47
NF2 MUTATED	2	2	3
NF2 WILD-TYPE	14	47	44

'NF2 MUTATION STATUS' versus 'MIRSEQ_MATURE_CNMF'

P value = 1 (Fisher's exact test), Q value = 1

Table S7. Gene #1: 'NF2 MUTATION STATUS' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	42	50	20
NF2 MUTATED	3	3	1
NF2 WILD-TYPE	39	47	19

'NF2 MUTATION STATUS' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 1 (Fisher's exact test), Q value = 1

Table S8. Gene #1: 'NF2 MUTATION STATUS' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	12	53	47
NF2 MUTATED	0	4	3
NF2 WILD-TYPE	12	49	44

Methods & Data

Input

Mutation data file = transformed.cor.cli.txt
Molecular subtypes file = KIRP-TP.transferedmergedcluster.txt
Number of patients = 112
Number of significantly mutated genes = 1: 'NF2 MUTATION ANALYSIS'
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

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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