Correlation between copy number variations of arm-level result and molecular subtypes
Cholangiocarcinoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1VX0FB0
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/C1VX0FB0
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 65 arm-level events and 7 molecular subtypes across 36 patients, one significant finding detected with P value < 0.05 and Q value < 0.25.

  • 6q loss cnv correlated to 'CN_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 65 arm-level events and 7 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, one significant finding detected.

Clinical
Features 		CN
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
6q loss 20 (56%) 16 0.000242
(0.11) 		0.189
(1.00) 		0.143
(1.00) 		0.21
(1.00) 		0.254
(1.00) 		0.32
(1.00) 		0.411
(1.00)
1p gain 10 (28%) 26 0.139
(1.00) 		0.637
(1.00) 		0.555
(1.00) 		0.11
(1.00) 		0.263
(1.00) 		0.26
(1.00) 		0.685
(1.00)
1q gain 21 (58%) 15 0.516
(1.00) 		0.692
(1.00) 		0.236
(1.00) 		0.112
(1.00) 		0.179
(1.00) 		0.736
(1.00) 		0.591
(1.00)
2p gain 6 (17%) 30 0.662
(1.00) 		1
(1.00) 		0.923
(1.00) 		0.366
(1.00) 		0.546
(1.00) 		1
(1.00) 		0.6
(1.00)
2q gain 6 (17%) 30 0.182
(1.00) 		0.523
(1.00) 		0.503
(1.00) 		0.37
(1.00) 		0.399
(1.00) 		1
(1.00) 		0.599
(1.00)
3p gain 3 (8%) 33 0.231
(1.00) 		0.324
(1.00) 		0.157
(1.00) 		0.336
(1.00) 		0.237
(1.00) 		0.0637
(1.00) 		0.578
(1.00)
3q gain 8 (22%) 28 0.236
(1.00) 		0.0997
(1.00) 		0.0979
(1.00) 		0.538
(1.00) 		0.667
(1.00) 		1
(1.00) 		0.397
(1.00)
4p gain 3 (8%) 33 1
(1.00) 		1
(1.00) 		0.792
(1.00) 		0.767
(1.00) 		0.422
(1.00) 		0.559
(1.00) 		1
(1.00)
5p gain 12 (33%) 24 1
(1.00) 		0.612
(1.00) 		0.977
(1.00) 		0.767
(1.00) 		1
(1.00) 		1
(1.00) 		0.762
(1.00)
5q gain 12 (33%) 24 1
(1.00) 		0.614
(1.00) 		0.977
(1.00) 		0.763
(1.00) 		1
(1.00) 		1
(1.00) 		0.763
(1.00)
6p gain 7 (19%) 29 0.684
(1.00) 		0.367
(1.00) 		0.894
(1.00) 		0.187
(1.00) 		0.317
(1.00) 		0.674
(1.00) 		0.239
(1.00)
7p gain 7 (19%) 29 0.684
(1.00) 		0.208
(1.00) 		0.387
(1.00) 		0.372
(1.00) 		0.567
(1.00) 		0.674
(1.00) 		0.0189
(1.00)
7q gain 6 (17%) 30 1
(1.00) 		0.449
(1.00) 		0.535
(1.00) 		0.686
(1.00) 		0.821
(1.00) 		1
(1.00) 		0.00763
(1.00)
8p gain 6 (17%) 30 1
(1.00) 		0.332
(1.00) 		0.167
(1.00) 		0.204
(1.00) 		0.366
(1.00) 		0.367
(1.00) 		0.116
(1.00)
8q gain 12 (33%) 24 1
(1.00) 		0.172
(1.00) 		0.541
(1.00) 		0.182
(1.00) 		0.167
(1.00) 		0.721
(1.00) 		0.131
(1.00)
10p gain 5 (14%) 31 1
(1.00) 		0.834
(1.00) 		0.0755
(1.00) 		0.788
(1.00) 		0.933
(1.00) 		0.63
(1.00) 		0.862
(1.00)
11p gain 4 (11%) 32 0.605
(1.00) 		0.202
(1.00) 		0.0052
(1.00) 		0.741
(1.00) 		0.745
(1.00) 		0.287
(1.00) 		0.187
(1.00)
11q gain 4 (11%) 32 0.605
(1.00) 		0.202
(1.00) 		0.00541
(1.00) 		0.74
(1.00) 		0.748
(1.00) 		0.287
(1.00) 		0.188
(1.00)
12p gain 9 (25%) 27 1
(1.00) 		1
(1.00) 		0.907
(1.00) 		0.462
(1.00) 		0.84
(1.00) 		0.443
(1.00) 		0.335
(1.00)
12q gain 8 (22%) 28 1
(1.00) 		0.88
(1.00) 		0.983
(1.00) 		0.437
(1.00) 		0.825
(1.00) 		0.236
(1.00) 		0.629
(1.00)
13q gain 3 (8%) 33 0.231
(1.00) 		0.0428
(1.00) 		0.0397
(1.00) 		0.395
(1.00) 		0.889
(1.00) 		1
(1.00) 		0.0243
(1.00)
15q gain 6 (17%) 30 0.662
(1.00) 		0.863
(1.00) 		0.659
(1.00) 		0.193
(1.00) 		0.437
(1.00) 		0.677
(1.00) 		0.00928
(1.00)
16p gain 7 (19%) 29 0.0918
(1.00) 		0.661
(1.00) 		0.64
(1.00) 		0.374
(1.00) 		0.915
(1.00) 		0.674
(1.00) 		0.297
(1.00)
16q gain 5 (14%) 31 0.342
(1.00) 		1
(1.00) 		0.623
(1.00) 		0.921
(1.00) 		0.933
(1.00) 		1
(1.00) 		0.927
(1.00)
17p gain 3 (8%) 33 1
(1.00) 		0.774
(1.00) 		0.214
(1.00) 		0.683
(1.00) 		0.611
(1.00) 		0.559
(1.00) 		0.578
(1.00)
17q gain 7 (19%) 29 1
(1.00) 		0.496
(1.00) 		0.255
(1.00) 		0.936
(1.00) 		1
(1.00) 		0.418
(1.00) 		0.521
(1.00)
18p gain 7 (19%) 29 1
(1.00) 		0.663
(1.00) 		0.762
(1.00) 		0.482
(1.00) 		0.88
(1.00) 		0.418
(1.00) 		0.846
(1.00)
18q gain 6 (17%) 30 0.391
(1.00) 		0.0708
(1.00) 		0.569
(1.00) 		0.194
(1.00) 		0.437
(1.00) 		0.677
(1.00) 		0.391
(1.00)
19p gain 6 (17%) 30 0.662
(1.00) 		0.627
(1.00) 		0.659
(1.00) 		0.58
(1.00) 		0.437
(1.00) 		0.0628
(1.00) 		1
(1.00)
19q gain 6 (17%) 30 0.662
(1.00) 		0.625
(1.00) 		0.659
(1.00) 		0.583
(1.00) 		0.435
(1.00) 		0.0628
(1.00) 		1
(1.00)
20p gain 11 (31%) 25 1
(1.00) 		0.724
(1.00) 		0.423
(1.00) 		0.237
(1.00) 		0.281
(1.00) 		0.465
(1.00) 		0.343
(1.00)
20q gain 12 (33%) 24 0.732
(1.00) 		0.754
(1.00) 		0.284
(1.00) 		0.142
(1.00) 		0.149
(1.00) 		0.499
(1.00) 		0.225
(1.00)
21q gain 3 (8%) 33 1
(1.00) 		0.458
(1.00) 		0.886
(1.00) 		0.184
(1.00) 		0.708
(1.00) 		0.25
(1.00) 		0.133
(1.00)
22q gain 5 (14%) 31 0.342
(1.00) 		0.0864
(1.00) 		0.284
(1.00) 		0.851
(1.00) 		0.935
(1.00) 		1
(1.00) 		0.926
(1.00)
1p loss 4 (11%) 32 1
(1.00) 		0.656
(1.00) 		0.613
(1.00) 		0.816
(1.00) 		0.796
(1.00) 		0.626
(1.00) 		0.81
(1.00)
3p loss 22 (61%) 14 0.00222
(1.00) 		0.616
(1.00) 		0.0119
(1.00) 		0.774
(1.00) 		0.585
(1.00) 		0.499
(1.00) 		0.991
(1.00)
3q loss 3 (8%) 33 0.593
(1.00) 		0.167
(1.00) 		0.0219
(1.00) 		0.683
(1.00) 		0.611
(1.00) 		0.559
(1.00) 		0.396
(1.00)
4p loss 10 (28%) 26 0.274
(1.00) 		0.223
(1.00) 		0.323
(1.00) 		0.783
(1.00) 		0.647
(1.00) 		0.709
(1.00) 		0.288
(1.00)
4q loss 13 (36%) 23 1
(1.00) 		0.37
(1.00) 		0.388
(1.00) 		0.459
(1.00) 		0.837
(1.00) 		0.736
(1.00) 		0.363
(1.00)
6p loss 5 (14%) 31 0.65
(1.00) 		0.703
(1.00) 		0.982
(1.00) 		0.371
(1.00) 		0.241
(1.00) 		0.63
(1.00) 		0.982
(1.00)
7p loss 4 (11%) 32 0.605
(1.00) 		0.43
(1.00) 		0.283
(1.00) 		0.516
(1.00) 		0.905
(1.00) 		1
(1.00) 		0.859
(1.00)
7q loss 4 (11%) 32 1
(1.00) 		0.429
(1.00) 		0.283
(1.00) 		0.321
(1.00) 		0.276
(1.00) 		0.287
(1.00) 		0.391
(1.00)
8p loss 10 (28%) 26 0.717
(1.00) 		0.0176
(1.00) 		0.0777
(1.00) 		0.0944
(1.00) 		0.0365
(1.00) 		0.26
(1.00) 		0.173
(1.00)
8q loss 3 (8%) 33 0.593
(1.00) 		0.244
(1.00) 		0.792
(1.00) 		0.769
(1.00) 		0.0761
(1.00) 		1
(1.00) 		0.135
(1.00)
9p loss 18 (50%) 18 1
(1.00) 		0.694
(1.00) 		0.296
(1.00) 		0.188
(1.00) 		0.126
(1.00) 		0.5
(1.00) 		0.591
(1.00)
9q loss 19 (53%) 17 1
(1.00) 		0.579
(1.00) 		0.133
(1.00) 		0.708
(1.00) 		0.367
(1.00) 		0.192
(1.00) 		0.604
(1.00)
10p loss 6 (17%) 30 1
(1.00) 		0.732
(1.00) 		0.36
(1.00) 		0.579
(1.00) 		0.774
(1.00) 		0.677
(1.00) 		0.0147
(1.00)
10q loss 5 (14%) 31 0.167
(1.00) 		0.41
(1.00) 		0.982
(1.00) 		0.849
(1.00) 		0.695
(1.00) 		1
(1.00) 		0.555
(1.00)
11p loss 8 (22%) 28 0.434
(1.00) 		0.207
(1.00) 		0.532
(1.00) 		1
(1.00) 		0.84
(1.00) 		0.694
(1.00) 		0.393
(1.00)
11q loss 9 (25%) 27 0.255
(1.00) 		0.0738
(1.00) 		0.473
(1.00) 		0.765
(1.00) 		0.583
(1.00) 		0.705
(1.00) 		0.759
(1.00)
12q loss 3 (8%) 33 0.231
(1.00) 		0.325
(1.00) 		0.157
(1.00) 		0.607
(1.00) 		1
(1.00) 		1
(1.00) 		0.396
(1.00)
13q loss 15 (42%) 21 1
(1.00) 		0.629
(1.00) 		0.745
(1.00) 		0.753
(1.00) 		0.313
(1.00) 		0.736
(1.00) 		0.331
(1.00)
14q loss 13 (36%) 23 0.014
(1.00) 		1
(1.00) 		0.044
(1.00) 		1
(1.00) 		0.909
(1.00) 		0.484
(1.00) 		0.279
(1.00)
15q loss 5 (14%) 31 0.342
(1.00) 		0.0857
(1.00) 		0.287
(1.00) 		0.51
(1.00) 		0.756
(1.00) 		0.63
(1.00) 		0.982
(1.00)
16p loss 4 (11%) 32 1
(1.00) 		0.806
(1.00) 		1
(1.00) 		0.74
(1.00) 		0.966
(1.00) 		0.626
(1.00) 		0.186
(1.00)
16q loss 7 (19%) 29 0.684
(1.00) 		0.662
(1.00) 		0.412
(1.00) 		0.66
(1.00) 		0.0191
(1.00) 		1
(1.00) 		0.664
(1.00)
17p loss 10 (28%) 26 0.717
(1.00) 		0.114
(1.00) 		0.352
(1.00) 		0.254
(1.00) 		0.29
(1.00) 		1
(1.00) 		0.14
(1.00)
18p loss 6 (17%) 30 1
(1.00) 		0.448
(1.00) 		0.604
(1.00) 		0.239
(1.00) 		0.571
(1.00) 		0.367
(1.00) 		0.31
(1.00)
18q loss 8 (22%) 28 0.236
(1.00) 		0.101
(1.00) 		0.612
(1.00) 		0.134
(1.00) 		0.251
(1.00) 		0.424
(1.00) 		0.0645
(1.00)
19p loss 4 (11%) 32 0.605
(1.00) 		0.145
(1.00) 		0.683
(1.00) 		0.0504
(1.00) 		0.241
(1.00) 		0.125
(1.00) 		0.00844
(1.00)
19q loss 3 (8%) 33 1
(1.00) 		0.326
(1.00) 		0.73
(1.00) 		0.862
(1.00) 		1
(1.00) 		1
(1.00) 		0.579
(1.00)
20p loss 5 (14%) 31 1
(1.00) 		0.0315
(1.00) 		0.522
(1.00) 		0.0963
(1.00) 		0.415
(1.00) 		0.376
(1.00) 		0.0114
(1.00)
21q loss 15 (42%) 21 0.311
(1.00) 		0.133
(1.00) 		0.288
(1.00) 		0.336
(1.00) 		0.63
(1.00) 		0.31
(1.00) 		0.688
(1.00)
22q loss 5 (14%) 31 0.65
(1.00) 		0.329
(1.00) 		0.154
(1.00) 		0.674
(1.00) 		0.805
(1.00) 		0.376
(1.00) 		0.401
(1.00)
xq loss 15 (42%) 21 0.00185
(0.84) 		1
(1.00) 		0.266
(1.00) 		0.574
(1.00) 		0.962
(1.00) 		0.501
(1.00) 		0.996
(1.00)
'6q loss' versus 'CN_CNMF'

P value = 0.000242 (Fisher's exact test), Q value = 0.11

Table S1.  Gene #40: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2
ALL 19 17
6Q LOSS MUTATED 5 15
6Q LOSS WILD-TYPE 14 2

Figure S1.  Get High-res Image Gene #40: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data
Input

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

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

  • Number of patients = 36

  • Number of significantly arm-level cnvs = 65

  • Number of molecular subtypes = 7

  • 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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