Correlation between copy number variations of arm-level result and molecular subtypes
Uterine Carcinosarcoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1FQ9V03
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/C1FQ9V03
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 72 arm-level results and 8 molecular subtypes across 56 patients, one significant finding detected with Q value < 0.25.

  • 13q loss cnv correlated to 'METHLYATION_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 72 arm-level results and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, one significant finding detected.

Molecular
subtypes 		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 Chi-square test Fisher's exact test Chi-square test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
13q loss 0 (0%) 41 0.372
(1.00) 		0.000426
(0.245) 		0.589
(1.00) 		0.733
(1.00) 		0.198
(1.00) 		0.539
(1.00) 		0.364
(1.00) 		0.536
(1.00)
1p gain 0 (0%) 42 0.637
(1.00) 		0.193
(1.00) 		1
(1.00) 		0.733
(1.00) 		0.324
(1.00) 		0.0236
(1.00) 		0.495
(1.00) 		0.131
(1.00)
1q gain 0 (0%) 33 0.755
(1.00) 		0.351
(1.00) 		0.248
(1.00) 		0.736
(1.00) 		0.287
(1.00) 		0.568
(1.00) 		0.682
(1.00) 		0.661
(1.00)
2p gain 0 (0%) 35 0.767
(1.00) 		0.0128
(1.00) 		0.0552
(1.00) 		0.0462
(1.00) 		0.254
(1.00) 		0.0371
(1.00) 		0.0704
(1.00) 		0.00726
(1.00)
2q gain 0 (0%) 39 0.233
(1.00) 		0.0158
(1.00) 		0.00118
(0.68) 		0.0399
(1.00) 		0.0428
(1.00) 		0.00289
(1.00) 		0.0111
(1.00) 		0.00062
(0.357)
3p gain 0 (0%) 51 0.47
(1.00) 		0.811
(1.00) 		1
(1.00) 		0.809
(1.00) 		0.802
(1.00) 		1
(1.00) 		0.815
(1.00) 		0.685
(1.00)
3q gain 0 (0%) 38 0.0557
(1.00) 		0.334
(1.00) 		0.424
(1.00) 		0.548
(1.00) 		0.292
(1.00) 		0.593
(1.00) 		0.253
(1.00) 		0.228
(1.00)
4p gain 0 (0%) 48 0.272
(1.00) 		0.3
(1.00) 		1
(1.00) 		0.71
(1.00) 		0.413
(1.00) 		0.362
(1.00) 		0.426
(1.00) 		0.529
(1.00)
4q gain 0 (0%) 53 0.048
(1.00) 		0.278
(1.00) 		0.769
(1.00) 		0.146
(1.00) 		0.673
(1.00) 		1
(1.00) 		0.687
(1.00) 		1
(1.00)
5p gain 0 (0%) 39 0.0622
(1.00) 		0.858
(1.00) 		0.667
(1.00) 		0.882
(1.00) 		0.718
(1.00) 		1
(1.00) 		0.969
(1.00) 		1
(1.00)
5q gain 0 (0%) 51 0.856
(1.00) 		0.611
(1.00) 		1
(1.00) 		0.44
(1.00) 		0.0722
(1.00) 		0.117
(1.00) 		0.155
(1.00) 		0.179
(1.00)
6p gain 0 (0%) 30 0.0971
(1.00) 		0.681
(1.00) 		0.944
(1.00) 		0.217
(1.00) 		0.929
(1.00) 		0.78
(1.00) 		0.955
(1.00) 		1
(1.00)
6q gain 0 (0%) 34 0.0931
(1.00) 		0.424
(1.00) 		0.942
(1.00) 		0.235
(1.00) 		1
(1.00) 		0.744
(1.00) 		0.802
(1.00) 		1
(1.00)
7p gain 0 (0%) 46 0.0201
(1.00) 		0.517
(1.00) 		0.454
(1.00) 		0.0958
(1.00) 		0.476
(1.00) 		0.115
(1.00) 		0.344
(1.00) 		0.0764
(1.00)
7q gain 0 (0%) 45 0.551
(1.00) 		0.631
(1.00) 		0.533
(1.00) 		0.716
(1.00) 		0.957
(1.00) 		0.793
(1.00) 		0.917
(1.00) 		1
(1.00)
8p gain 0 (0%) 41 0.441
(1.00) 		0.696
(1.00) 		0.248
(1.00) 		0.576
(1.00) 		0.677
(1.00) 		1
(1.00) 		0.725
(1.00) 		0.825
(1.00)
8q gain 0 (0%) 30 0.0392
(1.00) 		0.168
(1.00) 		0.0455
(1.00) 		0.792
(1.00) 		0.77
(1.00) 		0.68
(1.00) 		0.842
(1.00) 		0.501
(1.00)
9p gain 0 (0%) 53 0.382
(1.00) 		0.766
(1.00) 		1
(1.00) 		0.742
(1.00) 		0.833
(1.00) 		0.625
(1.00) 		0.836
(1.00) 		1
(1.00)
10p gain 0 (0%) 42 0.8
(1.00) 		0.106
(1.00) 		0.269
(1.00) 		0.245
(1.00) 		0.677
(1.00) 		0.821
(1.00) 		0.851
(1.00) 		0.531
(1.00)
10q gain 0 (0%) 41 0.161
(1.00) 		0.209
(1.00) 		0.28
(1.00) 		0.187
(1.00) 		0.486
(1.00) 		0.522
(1.00) 		0.707
(1.00) 		0.291
(1.00)
11q gain 0 (0%) 51 0.921
(1.00) 		0.00858
(1.00) 		0.00126
(0.719) 		0.0642
(1.00) 		0.0751
(1.00) 		1
(1.00) 		0.19
(1.00) 		0.685
(1.00)
12p gain 0 (0%) 41 0.928
(1.00) 		0.0321
(1.00) 		0.194
(1.00) 		0.145
(1.00) 		0.257
(1.00) 		0.673
(1.00) 		0.475
(1.00) 		0.446
(1.00)
12q gain 0 (0%) 50 0.64
(1.00) 		0.304
(1.00) 		0.417
(1.00) 		0.437
(1.00) 		0.528
(1.00) 		1
(1.00) 		0.123
(1.00) 		1
(1.00)
13q gain 0 (0%) 42 0.545
(1.00) 		0.0317
(1.00) 		0.0115
(1.00) 		0.0206
(1.00) 		0.217
(1.00) 		0.00367
(1.00) 		0.0862
(1.00) 		0.00682
(1.00)
14q gain 0 (0%) 53 0.589
(1.00) 		0.766
(1.00) 		0.769
(1.00) 		0.742
(1.00) 		0.442
(1.00) 		0.0545
(1.00) 		0.114
(1.00) 		0.0269
(1.00)
15q gain 0 (0%) 52 1
(1.00) 		0.36
(1.00) 		0.672
(1.00) 		0.766
(1.00) 		0.755
(1.00) 		0.39
(1.00) 		0.53
(1.00) 		0.643
(1.00)
16p gain 0 (0%) 52 0.0889
(1.00) 		0.479
(1.00) 		0.134
(1.00) 		0.669
(1.00) 		1
(1.00) 		0.0727
(1.00) 		0.24
(1.00) 		0.043
(1.00)
17q gain 0 (0%) 44 0.0802
(1.00) 		0.0293
(1.00) 		0.228
(1.00) 		0.202
(1.00) 		0.536
(1.00) 		0.15
(1.00) 		0.597
(1.00) 		0.104
(1.00)
18p gain 0 (0%) 45 0.0785
(1.00) 		0.0406
(1.00) 		0.302
(1.00) 		0.0113
(1.00) 		0.393
(1.00) 		1
(1.00) 		0.494
(1.00) 		1
(1.00)
18q gain 0 (0%) 49 0.945
(1.00) 		0.184
(1.00) 		0.402
(1.00) 		0.679
(1.00) 		0.617
(1.00) 		0.339
(1.00) 		0.226
(1.00) 		0.503
(1.00)
19p gain 0 (0%) 43 0.0576
(1.00) 		0.124
(1.00) 		0.27
(1.00) 		0.0444
(1.00) 		0.787
(1.00) 		0.264
(1.00) 		0.436
(1.00) 		0.204
(1.00)
19q gain 0 (0%) 41 0.366
(1.00) 		0.0143
(1.00) 		0.0548
(1.00) 		0.00592
(1.00) 		0.162
(1.00) 		0.0578
(1.00) 		0.074
(1.00) 		0.0132
(1.00)
20p gain 0 (0%) 32 0.152
(1.00) 		0.967
(1.00) 		0.337
(1.00) 		0.24
(1.00) 		0.811
(1.00) 		0.273
(1.00) 		1
(1.00) 		0.485
(1.00)
20q gain 0 (0%) 24 0.184
(1.00) 		0.987
(1.00) 		0.0187
(1.00) 		0.154
(1.00) 		0.454
(1.00) 		0.278
(1.00) 		0.178
(1.00) 		0.341
(1.00)
21q gain 0 (0%) 45 0.0122
(1.00) 		0.151
(1.00) 		0.454
(1.00) 		0.611
(1.00) 		0.552
(1.00) 		0.604
(1.00) 		0.795
(1.00) 		0.789
(1.00)
22q gain 0 (0%) 48 0.57
(1.00) 		0.927
(1.00) 		0.503
(1.00) 		0.758
(1.00) 		0.258
(1.00) 		0.539
(1.00) 		0.446
(1.00) 		0.753
(1.00)
Xq gain 0 (0%) 44 0.491
(1.00) 		0.65
(1.00) 		0.921
(1.00) 		0.75
(1.00) 		0.861
(1.00) 		0.477
(1.00) 		0.959
(1.00) 		0.619
(1.00)
1p loss 0 (0%) 50 0.454
(1.00) 		0.293
(1.00) 		0.561
(1.00) 		0.625
(1.00) 		0.0501
(1.00) 		0.0136
(1.00) 		0.0279
(1.00) 		0.0411
(1.00)
1q loss 0 (0%) 52 0.296
(1.00) 		0.405
(1.00) 		0.0959
(1.00) 		0.207
(1.00) 		0.0244
(1.00) 		0.117
(1.00) 		0.0705
(1.00) 		0.179
(1.00)
3p loss 0 (0%) 44 0.292
(1.00) 		0.743
(1.00) 		0.845
(1.00) 		0.661
(1.00) 		0.801
(1.00) 		0.299
(1.00) 		0.924
(1.00) 		0.307
(1.00)
3q loss 0 (0%) 49 0.285
(1.00) 		0.465
(1.00) 		0.88
(1.00) 		0.568
(1.00) 		0.547
(1.00) 		0.126
(1.00) 		0.189
(1.00) 		0.0861
(1.00)
4p loss 0 (0%) 35 0.472
(1.00) 		0.284
(1.00) 		0.133
(1.00) 		0.118
(1.00) 		0.17
(1.00) 		0.2
(1.00) 		0.268
(1.00) 		0.203
(1.00)
4q loss 0 (0%) 34 0.295
(1.00) 		0.0187
(1.00) 		0.00208
(1.00) 		0.00153
(0.875) 		0.0125
(1.00) 		1
(1.00) 		0.125
(1.00) 		1
(1.00)
5p loss 0 (0%) 50 0.219
(1.00) 		0.321
(1.00) 		0.355
(1.00) 		0.378
(1.00) 		0.909
(1.00) 		1
(1.00) 		0.436
(1.00) 		0.71
(1.00)
5q loss 0 (0%) 44 0.0658
(1.00) 		0.0202
(1.00) 		0.424
(1.00) 		0.417
(1.00) 		1
(1.00) 		0.802
(1.00) 		0.0675
(1.00) 		0.808
(1.00)
6p loss 0 (0%) 53 0.157
(1.00) 		0.32
(1.00) 		1
(1.00) 		0.784
(1.00) 		0.833
(1.00) 		0.625
(1.00) 		0.836
(1.00) 		1
(1.00)
6q loss 0 (0%) 50 0.751
(1.00) 		0.789
(1.00) 		0.258
(1.00) 		0.802
(1.00) 		0.771
(1.00) 		0.0933
(1.00) 		0.47
(1.00) 		0.132
(1.00)
7p loss 0 (0%) 49 0.77
(1.00) 		0.761
(1.00) 		0.466
(1.00) 		0.31
(1.00) 		0.516
(1.00) 		0.738
(1.00) 		0.377
(1.00) 		1
(1.00)
7q loss 0 (0%) 48 0.73
(1.00) 		0.71
(1.00) 		1
(1.00) 		0.71
(1.00) 		0.504
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
8p loss 0 (0%) 40 0.253
(1.00) 		0.794
(1.00) 		0.426
(1.00) 		0.716
(1.00) 		0.967
(1.00) 		0.0321
(1.00) 		0.781
(1.00) 		0.12
(1.00)
8q loss 0 (0%) 51 0.221
(1.00) 		0.56
(1.00) 		0.722
(1.00) 		0.47
(1.00) 		0.886
(1.00) 		0.411
(1.00) 		0.901
(1.00) 		0.246
(1.00)
9p loss 0 (0%) 31 0.0739
(1.00) 		0.0112
(1.00) 		0.703
(1.00) 		0.872
(1.00) 		0.726
(1.00) 		0.177
(1.00) 		0.794
(1.00) 		0.336
(1.00)
9q loss 0 (0%) 30 0.0544
(1.00) 		0.00595
(1.00) 		0.788
(1.00) 		0.428
(1.00) 		0.096
(1.00) 		0.0306
(1.00) 		0.339
(1.00) 		0.0763
(1.00)
10p loss 0 (0%) 40 0.278
(1.00) 		0.00439
(1.00) 		0.515
(1.00) 		0.0112
(1.00) 		0.401
(1.00) 		0.837
(1.00) 		0.429
(1.00) 		0.563
(1.00)
10q loss 0 (0%) 44 0.154
(1.00) 		0.116
(1.00) 		0.424
(1.00) 		0.575
(1.00) 		0.691
(1.00) 		0.625
(1.00) 		0.864
(1.00) 		0.489
(1.00)
11p loss 0 (0%) 36 0.941
(1.00) 		0.0524
(1.00) 		0.403
(1.00) 		0.412
(1.00) 		0.447
(1.00) 		0.862
(1.00) 		0.465
(1.00) 		0.619
(1.00)
11q loss 0 (0%) 39 0.645
(1.00) 		0.0115
(1.00) 		0.426
(1.00) 		0.479
(1.00) 		0.332
(1.00) 		0.481
(1.00) 		0.347
(1.00) 		0.482
(1.00)
12p loss 0 (0%) 46 0.617
(1.00) 		0.283
(1.00) 		0.685
(1.00) 		0.74
(1.00) 		0.728
(1.00) 		0.115
(1.00) 		0.716
(1.00) 		0.252
(1.00)
12q loss 0 (0%) 46 0.454
(1.00) 		0.608
(1.00) 		1
(1.00) 		0.868
(1.00) 		0.642
(1.00) 		0.246
(1.00) 		0.716
(1.00) 		0.114
(1.00)
14q loss 0 (0%) 34 0.514
(1.00) 		0.337
(1.00) 		0.133
(1.00) 		0.317
(1.00) 		0.724
(1.00) 		1
(1.00) 		0.583
(1.00) 		1
(1.00)
15q loss 0 (0%) 30 0.274
(1.00) 		0.572
(1.00) 		0.943
(1.00) 		0.962
(1.00) 		0.549
(1.00) 		0.591
(1.00) 		0.612
(1.00) 		0.887
(1.00)
16p loss 0 (0%) 28 0.605
(1.00) 		0.301
(1.00) 		0.413
(1.00) 		0.243
(1.00) 		0.378
(1.00) 		0.18
(1.00) 		0.304
(1.00) 		0.684
(1.00)
16q loss 0 (0%) 23 0.451
(1.00) 		0.655
(1.00) 		0.197
(1.00) 		0.199
(1.00) 		0.74
(1.00) 		0.216
(1.00) 		0.516
(1.00) 		0.87
(1.00)
17p loss 0 (0%) 33 0.492
(1.00) 		0.196
(1.00) 		1
(1.00) 		0.982
(1.00) 		0.624
(1.00) 		0.656
(1.00) 		0.749
(1.00) 		0.661
(1.00)
17q loss 0 (0%) 44 0.705
(1.00) 		0.355
(1.00) 		0.363
(1.00) 		0.284
(1.00) 		0.861
(1.00) 		0.477
(1.00) 		0.959
(1.00) 		0.619
(1.00)
18p loss 0 (0%) 45 0.196
(1.00) 		0.101
(1.00) 		0.0956
(1.00) 		0.196
(1.00) 		0.069
(1.00) 		0.343
(1.00) 		0.12
(1.00) 		0.132
(1.00)
18q loss 0 (0%) 40 0.171
(1.00) 		0.0642
(1.00) 		0.106
(1.00) 		0.0788
(1.00) 		0.0228
(1.00) 		0.0474
(1.00) 		0.0748
(1.00) 		0.0147
(1.00)
19p loss 0 (0%) 45 0.658
(1.00) 		0.0287
(1.00) 		0.146
(1.00) 		0.158
(1.00) 		0.302
(1.00) 		1
(1.00) 		0.383
(1.00) 		0.789
(1.00)
19q loss 0 (0%) 48 0.251
(1.00) 		0.0208
(1.00) 		0.88
(1.00) 		0.837
(1.00) 		0.258
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
21q loss 0 (0%) 45 0.165
(1.00) 		0.52
(1.00) 		0.7
(1.00) 		0.812
(1.00) 		0.957
(1.00) 		1
(1.00) 		0.743
(1.00) 		0.789
(1.00)
22q loss 0 (0%) 27 0.537
(1.00) 		0.624
(1.00) 		0.661
(1.00) 		0.809
(1.00) 		0.354
(1.00) 		0.226
(1.00) 		0.429
(1.00) 		0.106
(1.00)
Xq loss 0 (0%) 48 0.00864
(1.00) 		0.114
(1.00) 		0.4
(1.00) 		0.325
(1.00) 		0.789
(1.00) 		0.362
(1.00) 		0.32
(1.00) 		0.529
(1.00)
'13q loss' versus 'METHLYATION_CNMF'

P value = 0.000426 (Chi-square test), Q value = 0.25

Table S1.  Gene #59: '13q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 11 9 10 13 13
13Q LOSS CNV 0 5 0 8 2
13Q LOSS WILD-TYPE 11 4 10 5 11

Figure S1.  Get High-res Image Gene #59: '13q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

Methods & Data
Input

  • Mutation data file = broad_values_by_arm.mutsig.cluster.txt

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

  • Number of patients = 56

  • Number of significantly arm-level cnvs = 72

  • 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

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

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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[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)
Copyright © 2013 Broad Institute TCGA GDAC as part of the TCGA Research Network. All rights reserved.
Made with Nozzle