Correlation between gene mutation status and molecular subtypes
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.

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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