Correlation between copy number variations of arm-level result and molecular subtypes

Pancreatic Adenocarcinoma (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 copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1QJ7FNN

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 25 arm-level results and 8 molecular subtypes across 65 patients, 14 significant findings detected with Q value < 0.25.

20q gain cnv correlated to 'CN_CNMF'.
6q loss cnv correlated to 'METHLYATION_CNMF' and 'MRNASEQ_CHIERARCHICAL'.
9p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.
17p loss cnv correlated to 'CN_CNMF', 'METHLYATION_CNMF', and 'MIRSEQ_MATURE_CNMF'.
17q loss cnv correlated to 'CN_CNMF'.
18q loss cnv correlated to 'METHLYATION_CNMF' and 'MIRSEQ_MATURE_CNMF'.
21q loss cnv correlated to 'CN_CNMF', 'METHLYATION_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

Results

Overview of the results

Table 1. Get Full Table Overview of the association between significant copy number variation of 25 arm-level results and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 14 significant findings detected.


		Molecular subtypes	CN CNMF	METHLYATION CNMF	MRNASEQ CNMF	MRNASEQ CHIERARCHICAL	MIRSEQ CNMF	MIRSEQ CHIERARCHICAL	MIRSEQ MATURE CNMF	MIRSEQ MATURE CHIERARCHICAL
	nCNV (%)	nWild-Type	Chi-square 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
17p loss	0 (0%)	51	4.38e-05 (0.00809)	0.000128 (0.0234)	0.145 (1.00)	0.00942 (1.00)	0.0194 (1.00)	0.00541 (0.888)	0.000454 (0.0817)	0.00402 (0.663)
21q loss	0 (0%)	56	0.000375 (0.0679)	0.00118 (0.207)	0.019 (1.00)	0.000786 (0.14)	0.0089 (1.00)	0.0614 (1.00)	0.0138 (1.00)	0.0413 (1.00)
6q loss	0 (0%)	55	0.0193 (1.00)	3.91e-05 (0.00726)	0.019 (1.00)	0.000786 (0.14)	0.0089 (1.00)	0.00596 (0.965)	0.00148 (0.258)	0.00236 (0.403)
9p loss	0 (0%)	53	0.000601 (0.108)	0.000223 (0.0406)	0.00328 (0.554)	0.00272 (0.463)	0.0113 (1.00)	0.00895 (1.00)	0.00227 (0.39)	0.0089 (1.00)
18q loss	0 (0%)	52	0.00378 (0.635)	7.67e-05 (0.0141)	0.0703 (1.00)	0.0147 (1.00)	0.0421 (1.00)	0.0149 (1.00)	0.00118 (0.207)	0.0107 (1.00)
20q gain	0 (0%)	58	1.67e-05 (0.00315)	0.404 (1.00)	0.314 (1.00)	0.195 (1.00)	0.111 (1.00)	0.138 (1.00)	0.0383 (1.00)	0.092 (1.00)
17q loss	0 (0%)	60	2.4e-05 (0.0045)	0.0147 (1.00)	0.577 (1.00)	0.533 (1.00)	0.318 (1.00)	0.407 (1.00)	0.138 (1.00)	0.271 (1.00)
1q gain	0 (0%)	61	0.14 (1.00)	0.0189 (1.00)	0.26 (1.00)	0.122 (1.00)	0.289 (1.00)	0.289 (1.00)	0.206 (1.00)	0.301 (1.00)
3q gain	0 (0%)	62	0.106 (1.00)	0.338 (1.00)	0.26 (1.00)	0.122 (1.00)	0.289 (1.00)	0.289 (1.00)	0.206 (1.00)	0.301 (1.00)
7p gain	0 (0%)	61	0.24 (1.00)	0.167 (1.00)	0.885 (1.00)	0.683 (1.00)	0.394 (1.00)	0.661 (1.00)	0.509 (1.00)	0.531 (1.00)
8p gain	0 (0%)	62	0.0607 (1.00)	0.0595 (1.00)	0.26 (1.00)	0.122 (1.00)	0.289 (1.00)	0.289 (1.00)	0.206 (1.00)	0.301 (1.00)
8q gain	0 (0%)	56	0.00203 (0.351)	0.00883 (1.00)	0.0244 (1.00)	0.0185 (1.00)	0.0436 (1.00)	0.00989 (1.00)	0.0181 (1.00)	0.00739 (1.00)
18p gain	0 (0%)	60	0.11 (1.00)	0.167 (1.00)	0.26 (1.00)	0.122 (1.00)	0.232 (1.00)	0.126 (1.00)	0.0916 (1.00)	0.133 (1.00)
19q gain	0 (0%)	62	0.106 (1.00)	0.0595 (1.00)	0.26 (1.00)	0.122 (1.00)	0.289 (1.00)	0.289 (1.00)	0.206 (1.00)	0.301 (1.00)
5q loss	0 (0%)	62	0.106 (1.00)	0.338 (1.00)			0.289 (1.00)	0.289 (1.00)	0.206 (1.00)	0.301 (1.00)
6p loss	0 (0%)	59	0.0267 (1.00)	0.00382 (0.639)	0.0191 (1.00)	0.0092 (1.00)	0.0375 (1.00)	0.0331 (1.00)	0.013 (1.00)	0.0185 (1.00)
8p loss	0 (0%)	62	0.41 (1.00)	0.338 (1.00)			0.289 (1.00)	0.289 (1.00)	0.206 (1.00)	0.301 (1.00)
9q loss	0 (0%)	61	0.248 (1.00)	0.167 (1.00)
10p loss	0 (0%)	61	0.0452 (1.00)	0.0189 (1.00)	0.26 (1.00)	0.122 (1.00)	0.232 (1.00)	0.126 (1.00)	0.0916 (1.00)	0.133 (1.00)
10q loss	0 (0%)	61	0.00554 (0.903)	0.0189 (1.00)	0.26 (1.00)	0.122 (1.00)	0.232 (1.00)	0.126 (1.00)	0.0916 (1.00)	0.133 (1.00)
12q loss	0 (0%)	61	0.0452 (1.00)	0.0189 (1.00)	0.885 (1.00)	0.683 (1.00)	0.577 (1.00)	1 (1.00)	0.385 (1.00)	1 (1.00)
13q loss	0 (0%)	62	0.00387 (0.643)	0.338 (1.00)			0.289 (1.00)	0.289 (1.00)	0.206 (1.00)	0.301 (1.00)
15q loss	0 (0%)	61	0.208 (1.00)	0.0189 (1.00)	0.321 (1.00)	0.0588 (1.00)	0.232 (1.00)	0.126 (1.00)	0.0916 (1.00)	0.133 (1.00)
18p loss	0 (0%)	59	0.319 (1.00)	0.0252 (1.00)	0.667 (1.00)	0.257 (1.00)	0.571 (1.00)	0.407 (1.00)	0.138 (1.00)	0.271 (1.00)
22q loss	0 (0%)	61	0.0187 (1.00)	0.167 (1.00)	0.26 (1.00)	0.122 (1.00)	0.289 (1.00)	0.289 (1.00)	0.206 (1.00)	0.301 (1.00)

'20q gain' versus 'CN_CNMF'

P value = 1.67e-05 (Chi-square test), Q value = 0.0031

Table S1. Gene #8: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	11	35	9	9	1
20Q GAIN CNV	6	0	1	0	0
20Q GAIN WILD-TYPE	5	35	8	9	1

Figure S1. Get High-res Image Gene #8: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

'6q loss' versus 'METHLYATION_CNMF'

P value = 3.91e-05 (Fisher's exact test), Q value = 0.0073

Table S2. Gene #11: '6q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	25	15
6Q LOSS CNV	10	0	0
6Q LOSS WILD-TYPE	14	25	15

Figure S2. Get High-res Image Gene #11: '6q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'6q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000786 (Fisher's exact test), Q value = 0.14

Table S3. Gene #11: '6q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	5	22	28
6Q LOSS CNV	0	8	0
6Q LOSS WILD-TYPE	5	14	28

Figure S3. Get High-res Image Gene #11: '6q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'9p loss' versus 'CN_CNMF'

P value = 0.000601 (Chi-square test), Q value = 0.11

Table S4. Gene #13: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	11	35	9	9	1
9P LOSS CNV	5	2	5	0	0
9P LOSS WILD-TYPE	6	33	4	9	1

Figure S4. Get High-res Image Gene #13: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'METHLYATION_CNMF'

P value = 0.000223 (Fisher's exact test), Q value = 0.041

Table S5. Gene #13: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	25	15
9P LOSS CNV	10	0	2
9P LOSS WILD-TYPE	14	25	13

Figure S5. Get High-res Image Gene #13: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'17p loss' versus 'CN_CNMF'

P value = 4.38e-05 (Chi-square test), Q value = 0.0081

Table S6. Gene #20: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	11	35	9	9	1
17P LOSS CNV	8	1	2	3	0
17P LOSS WILD-TYPE	3	34	7	6	1

Figure S6. Get High-res Image Gene #20: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

'17p loss' versus 'METHLYATION_CNMF'

P value = 0.000128 (Fisher's exact test), Q value = 0.023

Table S7. Gene #20: '17p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	25	15
17P LOSS CNV	11	0	3
17P LOSS WILD-TYPE	13	25	12

Figure S7. Get High-res Image Gene #20: '17p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'17p loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.000454 (Fisher's exact test), Q value = 0.082

Table S8. Gene #20: '17p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	25	10	23
17P LOSS CNV	11	2	0
17P LOSS WILD-TYPE	14	8	23

Figure S8. Get High-res Image Gene #20: '17p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'17q loss' versus 'CN_CNMF'

P value = 2.4e-05 (Chi-square test), Q value = 0.0045

Table S9. Gene #21: '17q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	11	35	9	9	1
17Q LOSS CNV	5	0	0	0	0
17Q LOSS WILD-TYPE	6	35	9	9	1

Figure S9. Get High-res Image Gene #21: '17q loss' versus Molecular Subtype #1: 'CN_CNMF'

'18q loss' versus 'METHLYATION_CNMF'

P value = 7.67e-05 (Fisher's exact test), Q value = 0.014

Table S10. Gene #23: '18q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	25	15
18Q LOSS CNV	11	0	2
18Q LOSS WILD-TYPE	13	25	13

Figure S10. Get High-res Image Gene #23: '18q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'18q loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.00118 (Fisher's exact test), Q value = 0.21

Table S11. Gene #23: '18q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	25	10	23
18Q LOSS CNV	10	2	0
18Q LOSS WILD-TYPE	15	8	23

Figure S11. Get High-res Image Gene #23: '18q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'21q loss' versus 'CN_CNMF'

P value = 0.000375 (Chi-square test), Q value = 0.068

Table S12. Gene #24: '21q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3	CLUS_4	CLUS_5
ALL	11	35	9	9	1
21Q LOSS CNV	3	0	5	1	0
21Q LOSS WILD-TYPE	8	35	4	8	1

Figure S12. Get High-res Image Gene #24: '21q loss' versus Molecular Subtype #1: 'CN_CNMF'

'21q loss' versus 'METHLYATION_CNMF'

P value = 0.00118 (Fisher's exact test), Q value = 0.21

Table S13. Gene #24: '21q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	24	25	15
21Q LOSS CNV	8	0	1
21Q LOSS WILD-TYPE	16	25	14

Figure S13. Get High-res Image Gene #24: '21q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'21q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000786 (Fisher's exact test), Q value = 0.14

Table S14. Gene #24: '21q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients	CLUS_1	CLUS_2	CLUS_3
ALL	5	22	28
21Q LOSS CNV	0	8	0
21Q LOSS WILD-TYPE	5	14	28

Figure S14. Get High-res Image Gene #24: '21q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

Methods & Data

Input

Mutation data file = broad_values_by_arm.mutsig.cluster.txt
Molecular subtypes file = PAAD-TP.transferedmergedcluster.txt
Number of patients = 65
Number of significantly arm-level cnvs = 25
Number of molecular subtypes = 8
Exclude genes that fewer than K tumors have mutations, K = 3

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

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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)

[2] 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)

[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)

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