Skin Cutaneous Melanoma: Correlation between copy number variations of arm-level result and molecular subtypes<BR>(WT cohort)

Skin Cutaneous Melanoma: Correlation between copy number variations of arm-level result and molecular subtypes
(WT cohort)

Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)

Overview

Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and subtypes.

Summary

Testing the association between copy number variation 55 arm-level results and 8 molecular subtypes across 35 patients, 2 significant findings detected with Q value < 0.25.

6p gain cnv correlated to 'METHLYATION_CNMF'.
20q gain cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 55 arm-level results and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 2 significant findings detected.


		Molecular subtypes	CN CNMF	METHLYATION CNMF	RPPA CNMF	RPPA CHIERARCHICAL	MRNASEQ CNMF	MRNASEQ CHIERARCHICAL	MIRSEQ CNMF	MIRSEQ 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
6p gain	14 (40%)	21	0.0153 (1.00)	0.000556 (0.229)	0.197 (1.00)	0.257 (1.00)	0.0328 (1.00)	0.13 (1.00)	0.079 (1.00)	0.0167 (1.00)
20q gain	12 (34%)	23	0.289 (1.00)	0.163 (1.00)	0.653 (1.00)	0.0839 (1.00)	0.022 (1.00)	0.000346 (0.142)	0.271 (1.00)	1 (1.00)
1p gain	4 (11%)	31	0.603 (1.00)	0.619 (1.00)	1 (1.00)		0.284 (1.00)	0.215 (1.00)	1 (1.00)	0.828 (1.00)
1q gain	12 (34%)	23	0.0116 (1.00)	0.034 (1.00)	0.642 (1.00)	0.57 (1.00)	0.249 (1.00)	0.5 (1.00)	0.152 (1.00)	0.0489 (1.00)
2p gain	3 (9%)	32	1 (1.00)	1 (1.00)	0.479 (1.00)		0.284 (1.00)	0.51 (1.00)	0.238 (1.00)	0.515 (1.00)
3p gain	3 (9%)	32	0.229 (1.00)	0.244 (1.00)	0.479 (1.00)		0.523 (1.00)		1 (1.00)	0.757 (1.00)
3q gain	4 (11%)	31	0.603 (1.00)	0.619 (1.00)	1 (1.00)	0.754 (1.00)	0.284 (1.00)	0.215 (1.00)	1 (1.00)	1 (1.00)
4p gain	8 (23%)	27	0.0408 (1.00)	0.101 (1.00)	0.157 (1.00)	0.0291 (1.00)	1 (1.00)	0.226 (1.00)	0.0529 (1.00)	0.0845 (1.00)
4q gain	4 (11%)	31	0.104 (1.00)	0.119 (1.00)	0.218 (1.00)	0.00877 (1.00)	1 (1.00)	0.575 (1.00)	0.113 (1.00)	0.293 (1.00)
5p gain	4 (11%)	31	0.104 (1.00)	0.119 (1.00)	0.479 (1.00)		1 (1.00)	1 (1.00)	0.238 (1.00)	0.0919 (1.00)
5q gain	4 (11%)	31	0.104 (1.00)	0.119 (1.00)	0.479 (1.00)		1 (1.00)	1 (1.00)	0.238 (1.00)	0.0919 (1.00)
6q gain	3 (9%)	32	0.603 (1.00)	0.244 (1.00)	1 (1.00)	0.0886 (1.00)	1 (1.00)	1 (1.00)	0.238 (1.00)	0.0919 (1.00)
7p gain	10 (29%)	25	0.711 (1.00)	0.458 (1.00)	1 (1.00)	0.848 (1.00)	0.71 (1.00)	0.00816 (1.00)	0.24 (1.00)	0.886 (1.00)
7q gain	9 (26%)	26	1 (1.00)	0.7 (1.00)	1 (1.00)	0.848 (1.00)	1 (1.00)	0.00475 (1.00)	0.257 (1.00)	0.681 (1.00)
8p gain	8 (23%)	27	0.228 (1.00)	0.101 (1.00)	1 (1.00)	0.503 (1.00)	0.0319 (1.00)	0.0618 (1.00)	0.1 (1.00)	0.681 (1.00)
8q gain	11 (31%)	24	0.0275 (1.00)	0.00947 (1.00)	0.642 (1.00)	0.334 (1.00)	0.00498 (1.00)	0.0153 (1.00)	0.718 (1.00)	0.207 (1.00)
12p gain	4 (11%)	31	1 (1.00)	0.619 (1.00)	1 (1.00)	0.503 (1.00)	0.271 (1.00)	0.314 (1.00)	1 (1.00)	0.515 (1.00)
12q gain	3 (9%)	32	0.603 (1.00)	1 (1.00)	0.566 (1.00)	1 (1.00)	0.284 (1.00)	0.215 (1.00)	0.571 (1.00)	0.515 (1.00)
13q gain	3 (9%)	32	0.603 (1.00)	0.244 (1.00)	0.189 (1.00)		1 (1.00)	1 (1.00)	1 (1.00)	0.757 (1.00)
15q gain	4 (11%)	31	0.603 (1.00)	0.119 (1.00)	0.479 (1.00)		1 (1.00)	1 (1.00)	0.238 (1.00)	0.515 (1.00)
17q gain	5 (14%)	30	0.0455 (1.00)	0.057 (1.00)	0.218 (1.00)	0.22 (1.00)	0.63 (1.00)	0.811 (1.00)	0.113 (1.00)	0.0249 (1.00)
18p gain	8 (23%)	27	0.228 (1.00)	0.419 (1.00)	0.157 (1.00)	0.334 (1.00)	0.0299 (1.00)	0.0363 (1.00)	1 (1.00)	0.467 (1.00)
18q gain	4 (11%)	31	0.603 (1.00)	0.619 (1.00)	1 (1.00)	0.15 (1.00)	0.271 (1.00)	0.0576 (1.00)	1 (1.00)	0.293 (1.00)
19q gain	3 (9%)	32	1 (1.00)	1 (1.00)	0.479 (1.00)		0.523 (1.00)		1 (1.00)	0.515 (1.00)
20p gain	10 (29%)	25	0.264 (1.00)	0.134 (1.00)	0.406 (1.00)	0.0219 (1.00)	0.0545 (1.00)	0.00489 (1.00)	0.24 (1.00)	0.715 (1.00)
21q gain	5 (14%)	30	0.338 (1.00)	0.057 (1.00)	1 (1.00)	0.00877 (1.00)	0.63 (1.00)	0.811 (1.00)	1 (1.00)	0.583 (1.00)
22q gain	7 (20%)	28	0.0877 (1.00)	0.199 (1.00)	0.319 (1.00)	0.22 (1.00)	0.0648 (1.00)	0.0576 (1.00)	1 (1.00)	0.444 (1.00)
1p loss	4 (11%)	31	0.603 (1.00)	0.119 (1.00)	1 (1.00)		0.271 (1.00)	0.314 (1.00)	0.299 (1.00)	1 (1.00)
2p loss	4 (11%)	31	0.603 (1.00)	1 (1.00)	0.479 (1.00)		0.61 (1.00)	0.41 (1.00)	0.113 (1.00)	0.515 (1.00)
2q loss	5 (14%)	30	0.338 (1.00)	1 (1.00)	0.479 (1.00)		1 (1.00)	0.66 (1.00)	0.0526 (1.00)	0.243 (1.00)
4p loss	4 (11%)	31	0.603 (1.00)	0.119 (1.00)	1 (1.00)		0.271 (1.00)	0.234 (1.00)	0.613 (1.00)	0.293 (1.00)
4q loss	3 (9%)	32	0.229 (1.00)	0.244 (1.00)			0.284 (1.00)	0.51 (1.00)	0.187 (1.00)
6p loss	4 (11%)	31	0.603 (1.00)	1 (1.00)	1 (1.00)		1 (1.00)	0.575 (1.00)	0.613 (1.00)	0.828 (1.00)
6q loss	9 (26%)	26	0.121 (1.00)	0.7 (1.00)	0.642 (1.00)	1 (1.00)	0.107 (1.00)	0.139 (1.00)	0.257 (1.00)	0.599 (1.00)
8p loss	3 (9%)	32	0.229 (1.00)	0.244 (1.00)	0.479 (1.00)		0.284 (1.00)	0.51 (1.00)	0.492 (1.00)
9p loss	14 (40%)	21	0.733 (1.00)	0.728 (1.00)	0.67 (1.00)	0.844 (1.00)	0.486 (1.00)	0.323 (1.00)	0.079 (1.00)	0.228 (1.00)
9q loss	10 (29%)	25	0.711 (1.00)	1 (1.00)	0.642 (1.00)	1 (1.00)	0.71 (1.00)	0.104 (1.00)	0.24 (1.00)	0.167 (1.00)
10p loss	15 (43%)	20	0.176 (1.00)	0.492 (1.00)	1 (1.00)	0.169 (1.00)	0.16 (1.00)	0.0947 (1.00)	0.495 (1.00)	0.0489 (1.00)
10q loss	13 (37%)	22	0.489 (1.00)	0.737 (1.00)	1 (1.00)	0.0542 (1.00)	0.278 (1.00)	0.12 (1.00)	0.476 (1.00)	0.365 (1.00)
11p loss	9 (26%)	26	0.443 (1.00)	0.7 (1.00)	0.642 (1.00)	0.334 (1.00)	0.107 (1.00)	0.175 (1.00)	0.697 (1.00)	0.0558 (1.00)
11q loss	11 (31%)	24	0.146 (1.00)	0.0693 (1.00)	0.197 (1.00)	0.00799 (1.00)	0.00207 (0.848)	0.00946 (1.00)	0.451 (1.00)	0.413 (1.00)
12p loss	3 (9%)	32	0.229 (1.00)	0.244 (1.00)	0.479 (1.00)		0.284 (1.00)	0.215 (1.00)	0.492 (1.00)
12q loss	4 (11%)	31	0.603 (1.00)	0.619 (1.00)	0.218 (1.00)	0.435 (1.00)	0.271 (1.00)	0.314 (1.00)	0.613 (1.00)	0.293 (1.00)
13q loss	6 (17%)	29	0.658 (1.00)	0.68 (1.00)	0.591 (1.00)	0.503 (1.00)	1 (1.00)	0.218 (1.00)	0.196 (1.00)	0.654 (1.00)
14q loss	5 (14%)	30	1 (1.00)	0.365 (1.00)	0.591 (1.00)	1 (1.00)	0.63 (1.00)	0.811 (1.00)	1 (1.00)	0.583 (1.00)
15q loss	3 (9%)	32	1 (1.00)	1 (1.00)	0.479 (1.00)		0.284 (1.00)	0.51 (1.00)	1 (1.00)	0.515 (1.00)
16p loss	5 (14%)	30	0.338 (1.00)	1 (1.00)	1 (1.00)		0.63 (1.00)	0.811 (1.00)	0.613 (1.00)	0.828 (1.00)
16q loss	8 (23%)	27	0.691 (1.00)	0.419 (1.00)	1 (1.00)	1 (1.00)	0.678 (1.00)	0.855 (1.00)	0.104 (1.00)	0.654 (1.00)
17p loss	3 (9%)	32	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	1 (1.00)	0.215 (1.00)	0.238 (1.00)	0.515 (1.00)
17q loss	3 (9%)	32	0.603 (1.00)	1 (1.00)	0.566 (1.00)	1 (1.00)	1 (1.00)	0.215 (1.00)	1 (1.00)	1 (1.00)
18p loss	3 (9%)	32	0.603 (1.00)	0.565 (1.00)	0.189 (1.00)		1 (1.00)	0.0326 (1.00)	1 (1.00)	0.294 (1.00)
18q loss	4 (11%)	31	1 (1.00)	1 (1.00)	0.566 (1.00)	0.582 (1.00)	1 (1.00)	0.0576 (1.00)	0.613 (1.00)	0.828 (1.00)
19q loss	3 (9%)	32	1 (1.00)	1 (1.00)	1 (1.00)		0.284 (1.00)	0.0326 (1.00)	0.571 (1.00)	1 (1.00)
21q loss	5 (14%)	30	1 (1.00)	0.631 (1.00)	1 (1.00)	0.798 (1.00)	1 (1.00)	0.168 (1.00)	0.355 (1.00)	0.487 (1.00)
22q loss	3 (9%)	32	1 (1.00)	0.244 (1.00)	0.479 (1.00)		1 (1.00)	1 (1.00)	0.492 (1.00)

'6p gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000556 (Fisher's exact test), Q value = 0.23

Table S1. Gene #10: '6p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2
ALL	20	15
6P GAIN MUTATED	13	1
6P GAIN WILD-TYPE	7	14

Figure S1. Get High-res Image Gene #10: '6p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'20q gain mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000346 (Fisher's exact test), Q value = 0.14

Table S2. Gene #25: '20q gain mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	4	11	18
20Q GAIN MUTATED	4	0	8
20Q GAIN WILD-TYPE	0	11	10

Figure S2. Get High-res Image Gene #25: '20q gain mutation analysis' versus Clinical Feature #6: 'MRNASEQ_CHIERARCHICAL'

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Molecular subtypes file = SKCM-WT.transferedmergedcluster.txt
Number of patients = 35
Number of significantly arm-level cnvs = 55
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

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

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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