Correlation between copy number variation genes (focal events) and molecular subtypes
Overview
Introduction

This pipeline computes the correlation between significant copy number variation (cnv focal) genes and molecular subtypes.

Summary

Testing the association between copy number variation 2 focal events and 10 molecular subtypes across 66 patients, 4 significant findings detected with P value < 0.05 and Q value < 0.25.

  • amp_8q11.23 cnv correlated to 'RPPA_CHIERARCHICAL',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • amp_15q22.31 cnv correlated to 'MRNASEQ_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 2 focal events and 10 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 4 significant findings detected.

Clinical
Features 		CN
CNMF 		METHLYATION
CNMF 		RPPA
CNMF 		RPPA
CHIERARCHICAL 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL 		MIRSEQ
MATURE
CNMF 		MIRSEQ
MATURE
CHIERARCHICAL
nCNV (%) 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 Fisher's exact test Fisher's exact test
amp 8q11 23 19 (29%) 47 0.322
(0.493) 		0.626
(0.659) 		0.186
(0.456) 		0.0444
(0.217) 		0.00295
(0.059) 		0.0248
(0.165) 		1
(1.00) 		0.23
(0.459) 		0.363
(0.493) 		0.117
(0.39)
amp 15q22 31 23 (35%) 43 0.0543
(0.217) 		0.582
(0.646) 		0.205
(0.456) 		0.37
(0.493) 		0.00635
(0.0635) 		0.182
(0.456) 		0.523
(0.646) 		0.299
(0.493) 		0.554
(0.646) 		0.364
(0.493)
'amp_8q11.23' versus 'RPPA_CHIERARCHICAL'

P value = 0.0444 (Fisher's exact test), Q value = 0.22

Table S1.  Gene #1: 'amp_8q11.23' versus Molecular Subtype #4: 'RPPA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 29 20 14
AMP PEAK 1(8Q11.23) MUTATED 12 2 5
AMP PEAK 1(8Q11.23) WILD-TYPE 17 18 9

Figure S1.  Get High-res Image Gene #1: 'amp_8q11.23' versus Molecular Subtype #4: 'RPPA_CHIERARCHICAL'

'amp_8q11.23' versus 'MRNASEQ_CNMF'

P value = 0.00295 (Fisher's exact test), Q value = 0.059

Table S2.  Gene #1: 'amp_8q11.23' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
AMP PEAK 1(8Q11.23) MUTATED 3 13 2 1
AMP PEAK 1(8Q11.23) WILD-TYPE 16 9 13 9

Figure S2.  Get High-res Image Gene #1: 'amp_8q11.23' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'amp_8q11.23' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.0248 (Fisher's exact test), Q value = 0.17

Table S3.  Gene #1: 'amp_8q11.23' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 19 16 7 6 10 4 4
AMP PEAK 1(8Q11.23) MUTATED 3 10 3 1 2 0 0
AMP PEAK 1(8Q11.23) WILD-TYPE 16 6 4 5 8 4 4

Figure S3.  Get High-res Image Gene #1: 'amp_8q11.23' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'amp_15q22.31' versus 'MRNASEQ_CNMF'

P value = 0.00635 (Fisher's exact test), Q value = 0.063

Table S4.  Gene #2: 'amp_15q22.31' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
AMP PEAK 2(15Q22.31) MUTATED 5 13 5 0
AMP PEAK 2(15Q22.31) WILD-TYPE 14 9 10 10

Figure S4.  Get High-res Image Gene #2: 'amp_15q22.31' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

Methods & Data
Input

  • Copy number data file = all_lesions.txt from GISTIC pipeline

  • Processed Copy number data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/KICH-TP/20146429/transformed.cor.cli.txt

  • Molecular subtype file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/KICH-TP/20147307/KICH-TP.transferedmergedcluster.txt

  • Number of patients = 66

  • Number of significantly focal cnvs = 2

  • Number of molecular subtypes = 10

  • Exclude genes that fewer than K tumors have alterations, 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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