Correlation between copy number variations of arm-level result and molecular subtypes
Mesothelioma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1Q52ND9
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 copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1Q52ND9
Overview
Introduction

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

Summary

Testing the association between copy number variation 52 arm-level events and 8 molecular subtypes across 37 patients, no significant finding detected with P value < 0.05 and Q value < 0.25.

  • No arm-level cnvs related to molecular subtypes.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 52 arm-level events 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
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
1p gain 3 (8%) 34 0.568
(1.00) 		0.0875
(1.00) 		0.229
(1.00) 		0.483
(1.00) 		1
(1.00) 		1
(1.00)
1q gain 10 (27%) 27 0.274
(1.00) 		0.725
(1.00) 		0.711
(1.00) 		0.425
(1.00) 		1
(1.00) 		0.394
(1.00) 		0.683
(1.00) 		0.0953
(1.00)
3p gain 8 (22%) 29 0.254
(1.00) 		0.428
(1.00) 		1
(1.00) 		0.878
(1.00) 		0.644
(1.00) 		0.754
(1.00) 		0.365
(1.00) 		1
(1.00)
3q gain 9 (24%) 28 0.136
(1.00) 		0.251
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.577
(1.00) 		0.665
(1.00) 		0.913
(1.00)
5p gain 11 (30%) 26 0.151
(1.00) 		1
(1.00) 		1
(1.00) 		0.753
(1.00) 		0.0873
(1.00) 		0.192
(1.00) 		0.11
(1.00) 		0.164
(1.00)
5q gain 7 (19%) 30 1
(1.00) 		0.68
(1.00) 		1
(1.00) 		0.442
(1.00) 		0.121
(1.00) 		0.187
(1.00) 		0.33
(1.00) 		0.272
(1.00)
7p gain 10 (27%) 27 0.0667
(1.00) 		1
(1.00) 		1
(1.00) 		0.424
(1.00) 		0.0989
(1.00) 		0.19
(1.00) 		0.216
(1.00) 		0.535
(1.00)
7q gain 7 (19%) 30 0.437
(1.00) 		0.68
(1.00) 		1
(1.00) 		0.336
(1.00) 		0.352
(1.00) 		0.32
(1.00) 		0.652
(1.00) 		0.621
(1.00)
8p gain 5 (14%) 32 1
(1.00) 		1
(1.00) 		1
(1.00) 		0.837
(1.00) 		0.617
(1.00) 		0.474
(1.00) 		0.33
(1.00) 		0.23
(1.00)
8q gain 6 (16%) 31 0.68
(1.00) 		1
(1.00) 		0.658
(1.00) 		0.63
(1.00) 		1
(1.00) 		0.442
(1.00) 		0.652
(1.00) 		0.312
(1.00)
11p gain 6 (16%) 31 0.371
(1.00) 		1
(1.00) 		0.658
(1.00) 		0.459
(1.00) 		0.262
(1.00) 		0.25
(1.00) 		1
(1.00) 		0.491
(1.00)
11q gain 5 (14%) 32 0.634
(1.00) 		1
(1.00) 		1
(1.00) 		0.0222
(1.00) 		0.136
(1.00) 		0.21
(1.00) 		0.598
(1.00) 		0.325
(1.00)
12p gain 7 (19%) 30 0.0287
(1.00) 		0.68
(1.00) 		1
(1.00) 		0.335
(1.00) 		0.625
(1.00) 		0.48
(1.00) 		0.306
(1.00) 		0.739
(1.00)
12q gain 7 (19%) 30 0.0287
(1.00) 		0.68
(1.00) 		1
(1.00) 		0.334
(1.00) 		0.625
(1.00) 		0.477
(1.00) 		0.306
(1.00) 		0.742
(1.00)
15q gain 5 (14%) 32 0.144
(1.00) 		0.348
(1.00) 		1
(1.00) 		0.0221
(1.00) 		1
(1.00) 		1
(1.00) 		0.598
(1.00) 		0.652
(1.00)
16p gain 8 (22%) 29 0.254
(1.00) 		1
(1.00) 		0.691
(1.00) 		0.00134
(0.531) 		0.668
(1.00) 		0.361
(1.00) 		0.391
(1.00) 		0.42
(1.00)
16q gain 9 (24%) 28 0.136
(1.00) 		0.703
(1.00) 		0.443
(1.00) 		0.0193
(1.00) 		0.42
(1.00) 		0.613
(1.00) 		0.216
(1.00) 		0.703
(1.00)
17p gain 3 (8%) 34 0.0721
(1.00) 		0.0875
(1.00) 		0.229
(1.00) 		0.262
(1.00) 		0.385
(1.00) 		0.462
(1.00)
17q gain 7 (19%) 30 0.0287
(1.00) 		1
(1.00) 		1
(1.00) 		0.0198
(1.00) 		1
(1.00) 		0.525
(1.00) 		0.598
(1.00) 		0.256
(1.00)
18p gain 3 (8%) 34 0.568
(1.00) 		0.584
(1.00) 		0.229
(1.00) 		0.479
(1.00) 		0.508
(1.00) 		0.483
(1.00)
19p gain 5 (14%) 32 0.634
(1.00) 		1
(1.00) 		1
(1.00) 		0.226
(1.00) 		1
(1.00) 		0.716
(1.00) 		0.598
(1.00) 		0.415
(1.00)
19q gain 3 (8%) 34 0.568
(1.00) 		0.584
(1.00) 		1
(1.00) 		0.479
(1.00) 		0.508
(1.00) 		0.483
(1.00)
20p gain 3 (8%) 34 1
(1.00) 		0.584
(1.00) 		1
(1.00) 		0.477
(1.00) 		1
(1.00) 		1
(1.00)
20q gain 3 (8%) 34 1
(1.00) 		0.584
(1.00) 		0.229
(1.00) 		0.481
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
1p loss 7 (19%) 30 0.202
(1.00) 		1
(1.00) 		1
(1.00) 		0.44
(1.00) 		0.352
(1.00) 		1
(1.00) 		0.652
(1.00) 		0.645
(1.00)
2q loss 3 (8%) 34 0.568
(1.00) 		0.584
(1.00) 		1
(1.00) 		1
(1.00) 		0.262
(1.00) 		0.601
(1.00) 		0.225
(1.00) 		0.409
(1.00)
4p loss 16 (43%) 21 0.0516
(1.00) 		0.746
(1.00) 		0.315
(1.00) 		0.0348
(1.00) 		0.422
(1.00) 		0.159
(1.00) 		0.431
(1.00) 		0.0259
(1.00)
4q loss 14 (38%) 23 0.305
(1.00) 		0.328
(1.00) 		0.0858
(1.00) 		0.0113
(1.00) 		0.701
(1.00) 		0.205
(1.00) 		0.267
(1.00) 		0.112
(1.00)
5q loss 3 (8%) 34 0.568
(1.00) 		0.584
(1.00) 		1
(1.00) 		0.762
(1.00) 		1
(1.00) 		1
(1.00)
6p loss 6 (16%) 31 0.0662
(1.00) 		1
(1.00) 		0.658
(1.00) 		0.0353
(1.00) 		1
(1.00) 		0.141
(1.00) 		0.598
(1.00) 		0.284
(1.00)
6q loss 14 (38%) 23 0.733
(1.00) 		0.328
(1.00) 		0.733
(1.00) 		0.633
(1.00) 		1
(1.00) 		0.131
(1.00) 		0.683
(1.00) 		0.374
(1.00)
8p loss 5 (14%) 32 1
(1.00) 		1
(1.00) 		0.338
(1.00) 		0.595
(1.00) 		1
(1.00) 		1
(1.00)
9p loss 15 (41%) 22 0.00588
(1.00) 		1
(1.00) 		0.0409
(1.00) 		0.00746
(1.00) 		0.422
(1.00) 		0.244
(1.00) 		0.431
(1.00) 		0.229
(1.00)
9q loss 11 (30%) 26 0.151
(1.00) 		0.719
(1.00) 		0.146
(1.00) 		0.0858
(1.00) 		0.425
(1.00) 		0.35
(1.00) 		0.422
(1.00) 		0.552
(1.00)
10p loss 11 (30%) 26 0.151
(1.00) 		1
(1.00) 		0.471
(1.00) 		0.21
(1.00) 		1
(1.00) 		0.278
(1.00) 		0.422
(1.00) 		0.0896
(1.00)
10q loss 8 (22%) 29 0.705
(1.00) 		1
(1.00) 		0.691
(1.00) 		0.701
(1.00) 		1
(1.00) 		0.763
(1.00) 		0.19
(1.00) 		0.223
(1.00)
11q loss 4 (11%) 33 1
(1.00) 		0.036
(1.00) 		0.104
(1.00) 		0.0282
(1.00) 		0.0462
(1.00) 		0.0313
(1.00) 		0.0846
(1.00) 		0.142
(1.00)
13q loss 18 (49%) 19 0.0489
(1.00) 		0.103
(1.00) 		0.318
(1.00) 		0.7
(1.00) 		1
(1.00) 		0.538
(1.00) 		1
(1.00) 		0.398
(1.00)
14q loss 16 (43%) 21 0.00896
(1.00) 		0.746
(1.00) 		1
(1.00) 		0.212
(1.00) 		0.105
(1.00) 		0.159
(1.00) 		0.431
(1.00) 		0.0255
(1.00)
15q loss 6 (16%) 31 0.371
(1.00) 		0.0752
(1.00) 		0.177
(1.00) 		0.334
(1.00) 		0.625
(1.00) 		0.876
(1.00) 		0.306
(1.00) 		0.955
(1.00)
16p loss 3 (8%) 34 0.568
(1.00) 		0.584
(1.00) 		1
(1.00) 		0.763
(1.00) 		1
(1.00) 		0.203
(1.00)
16q loss 4 (11%) 33 0.296
(1.00) 		1
(1.00) 		0.603
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.58
(1.00) 		1
(1.00)
17p loss 9 (24%) 28 1
(1.00) 		1
(1.00) 		0.691
(1.00) 		0.537
(1.00) 		0.19
(1.00) 		0.941
(1.00) 		0.391
(1.00) 		0.803
(1.00)
17q loss 3 (8%) 34 1
(1.00) 		0.584
(1.00) 		1
(1.00) 		0.761
(1.00) 		1
(1.00) 		1
(1.00) 		0.58
(1.00) 		1
(1.00)
18p loss 5 (14%) 32 1
(1.00) 		0.644
(1.00) 		1
(1.00) 		0.596
(1.00) 		0.617
(1.00) 		1
(1.00) 		0.635
(1.00) 		0.772
(1.00)
18q loss 9 (24%) 28 1
(1.00) 		1
(1.00) 		1
(1.00) 		0.699
(1.00) 		0.668
(1.00) 		0.942
(1.00) 		0.665
(1.00) 		0.304
(1.00)
19q loss 3 (8%) 34 1
(1.00) 		1
(1.00) 		1
(1.00) 		0.762
(1.00) 		1
(1.00) 		0.203
(1.00)
20p loss 7 (19%) 30 0.0287
(1.00) 		0.0975
(1.00) 		1
(1.00) 		0.572
(1.00) 		0.617
(1.00) 		0.715
(1.00) 		1
(1.00) 		0.539
(1.00)
20q loss 3 (8%) 34 0.0721
(1.00) 		1
(1.00) 		1
(1.00) 		0.764
(1.00) 		1
(1.00) 		0.203
(1.00)
21q loss 6 (16%) 31 0.0662
(1.00) 		1
(1.00) 		0.658
(1.00) 		1
(1.00) 		0.617
(1.00) 		0.975
(1.00) 		1
(1.00) 		0.939
(1.00)
22q loss 29 (78%) 8 0.104
(1.00) 		0.109
(1.00) 		0.691
(1.00) 		1
(1.00) 		0.0532
(1.00) 		0.134
(1.00) 		0.0171
(1.00) 		0.00841
(1.00)
xq loss 7 (19%) 30 0.0287
(1.00) 		0.00942
(1.00) 		0.402
(1.00) 		0.661
(1.00) 		1
(1.00) 		0.393
(1.00) 		1
(1.00) 		0.302
(1.00)
Methods & Data
Input

  • Copy number data file = transformed.cor.cli.txt

  • Molecular subtypes file = MESO-TP.transferedmergedcluster.txt

  • Number of patients = 37

  • Number of significantly arm-level cnvs = 52

  • 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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