Correlation between copy number variations of arm-level result and molecular subtypes
Sarcoma (Primary solid tumor)
23 September 2013  |  analyses__2013_09_23
Maintainer Information
Citation Information
doi:10.7908/C1N58JR6
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/C1N58JR6
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 77 arm-level results and 8 molecular subtypes across 83 patients, 7 significant findings detected with Q value < 0.25.

  • 9p loss cnv correlated to 'CN_CNMF'.

  • 10p loss cnv correlated to 'METHLYATION_CNMF'.

  • 10q loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MIRSEQ_MATURE_CNMF'.

  • 13q loss cnv correlated to 'CN_CNMF'.

  • 16q 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 77 arm-level results and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 7 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 Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
10q loss 0 (0%) 51 3.78e-06
(0.0023) 		4.58e-05
(0.0277) 		0.0117
(1.00) 		0.00249
(1.00) 		0.0182
(1.00) 		0.00815
(1.00) 		0.000295
(0.178) 		0.00203
(1.00)
9p loss 0 (0%) 66 1.09e-06
(0.000665) 		0.0877
(1.00) 		0.0114
(1.00) 		0.0186
(1.00) 		0.0437
(1.00) 		0.34
(1.00) 		0.249
(1.00) 		0.242
(1.00)
10p loss 0 (0%) 55 0.00172
(1.00) 		0.000361
(0.217) 		0.0109
(1.00) 		0.0195
(1.00) 		0.0101
(1.00) 		0.0222
(1.00) 		0.00298
(1.00) 		0.0253
(1.00)
13q loss 0 (0%) 49 0.000148
(0.0895) 		0.0784
(1.00) 		0.707
(1.00) 		0.692
(1.00) 		0.323
(1.00) 		0.912
(1.00) 		0.723
(1.00) 		0.559
(1.00)
16q loss 0 (0%) 49 0.114
(1.00) 		3.72e-05
(0.0226) 		0.16
(1.00) 		0.0179
(1.00) 		0.000895
(0.537) 		0.00903
(1.00) 		0.017
(1.00) 		0.00953
(1.00)
1p gain 0 (0%) 69 0.00991
(1.00) 		0.0942
(1.00) 		0.394
(1.00) 		0.38
(1.00) 		0.342
(1.00) 		0.69
(1.00) 		0.51
(1.00) 		0.478
(1.00)
1q gain 0 (0%) 71 0.103
(1.00) 		0.261
(1.00) 		0.561
(1.00) 		0.172
(1.00) 		0.0712
(1.00) 		0.133
(1.00) 		0.152
(1.00) 		0.0639
(1.00)
2p gain 0 (0%) 78 0.754
(1.00) 		0.0732
(1.00) 		0.0221
(1.00) 		0.655
(1.00) 		0.422
(1.00) 		0.442
(1.00) 		0.372
(1.00) 		0.398
(1.00)
2q gain 0 (0%) 80 0.55
(1.00) 		0.0601
(1.00) 		0.222
(1.00) 		0.299
(1.00) 		0.284
(1.00) 		0.269
(1.00)
3p gain 0 (0%) 79 0.44
(1.00) 		0.26
(1.00) 		0.674
(1.00) 		0.34
(1.00) 		0.117
(1.00) 		0.0953
(1.00) 		0.161
(1.00) 		0.101
(1.00)
3q gain 0 (0%) 79 0.44
(1.00) 		0.26
(1.00) 		0.674
(1.00) 		0.34
(1.00) 		0.117
(1.00) 		0.0953
(1.00) 		0.161
(1.00) 		0.101
(1.00)
4p gain 0 (0%) 75 0.665
(1.00) 		0.524
(1.00) 		0.433
(1.00) 		0.495
(1.00) 		0.837
(1.00) 		0.184
(1.00) 		0.425
(1.00) 		0.533
(1.00)
4q gain 0 (0%) 79 0.365
(1.00) 		0.542
(1.00) 		0.88
(1.00) 		0.585
(1.00) 		0.743
(1.00) 		0.134
(1.00) 		1
(1.00) 		1
(1.00)
5p gain 0 (0%) 64 0.0632
(1.00) 		0.521
(1.00) 		0.373
(1.00) 		0.128
(1.00) 		0.27
(1.00) 		0.879
(1.00) 		0.0949
(1.00) 		0.32
(1.00)
5q gain 0 (0%) 69 0.139
(1.00) 		0.0826
(1.00) 		0.296
(1.00) 		0.0873
(1.00) 		0.117
(1.00) 		0.696
(1.00) 		0.184
(1.00) 		0.124
(1.00)
6p gain 0 (0%) 72 0.334
(1.00) 		0.0129
(1.00) 		0.185
(1.00) 		0.0197
(1.00) 		0.00299
(1.00) 		0.099
(1.00) 		0.00527
(1.00) 		0.0834
(1.00)
6q gain 0 (0%) 71 0.276
(1.00) 		0.067
(1.00) 		0.384
(1.00) 		0.221
(1.00) 		0.0249
(1.00) 		0.0678
(1.00) 		0.0223
(1.00) 		0.0387
(1.00)
7p gain 0 (0%) 68 0.00185
(1.00) 		0.285
(1.00) 		0.585
(1.00) 		1
(1.00) 		0.207
(1.00) 		0.477
(1.00) 		0.853
(1.00) 		0.643
(1.00)
7q gain 0 (0%) 70 0.0159
(1.00) 		0.153
(1.00) 		0.641
(1.00) 		0.437
(1.00) 		0.511
(1.00) 		0.212
(1.00) 		0.783
(1.00) 		1
(1.00)
8p gain 0 (0%) 68 0.525
(1.00) 		0.204
(1.00) 		0.571
(1.00) 		0.248
(1.00) 		0.242
(1.00) 		0.719
(1.00) 		0.801
(1.00) 		0.173
(1.00)
8q gain 0 (0%) 66 0.419
(1.00) 		0.00987
(1.00) 		0.0951
(1.00) 		0.232
(1.00) 		0.59
(1.00) 		0.861
(1.00) 		0.87
(1.00) 		0.192
(1.00)
9p gain 0 (0%) 76 0.0158
(1.00) 		0.888
(1.00) 		0.579
(1.00) 		1
(1.00) 		0.323
(1.00) 		0.533
(1.00) 		0.588
(1.00) 		0.481
(1.00)
9q gain 0 (0%) 73 0.124
(1.00) 		0.486
(1.00) 		0.838
(1.00) 		0.759
(1.00) 		0.696
(1.00) 		0.482
(1.00) 		0.733
(1.00) 		0.396
(1.00)
11p gain 0 (0%) 80 0.433
(1.00) 		0.299
(1.00) 		0.76
(1.00) 		1
(1.00) 		0.00226
(1.00) 		0.16
(1.00) 		0.0323
(1.00) 		0.148
(1.00)
11q gain 0 (0%) 80 0.286
(1.00) 		0.771
(1.00) 		0.775
(1.00) 		0.585
(1.00) 		0.0859
(1.00) 		0.16
(1.00) 		0.203
(1.00) 		0.148
(1.00)
12p gain 0 (0%) 73 0.0521
(1.00) 		0.914
(1.00) 		0.125
(1.00) 		0.759
(1.00) 		0.00352
(1.00) 		0.616
(1.00) 		0.104
(1.00) 		0.577
(1.00)
12q gain 0 (0%) 78 1
(1.00) 		0.0732
(1.00) 		0.362
(1.00) 		1
(1.00) 		0.0489
(1.00) 		1
(1.00) 		0.81
(1.00) 		1
(1.00)
14q gain 0 (0%) 79 0.779
(1.00) 		0.834
(1.00) 		0.743
(1.00) 		0.656
(1.00) 		0.514
(1.00) 		0.634
(1.00)
15q gain 0 (0%) 70 0.686
(1.00) 		0.699
(1.00) 		0.271
(1.00) 		0.0818
(1.00) 		0.376
(1.00) 		0.36
(1.00) 		0.367
(1.00) 		0.339
(1.00)
16p gain 0 (0%) 75 1
(1.00) 		0.423
(1.00) 		0.662
(1.00) 		0.495
(1.00) 		0.388
(1.00) 		0.561
(1.00) 		0.883
(1.00) 		0.533
(1.00)
16q gain 0 (0%) 80 0.331
(1.00) 		1
(1.00) 		0.65
(1.00) 		0.623
(1.00) 		0.551
(1.00) 		0.63
(1.00)
17p gain 0 (0%) 73 0.396
(1.00) 		0.00294
(1.00) 		0.0567
(1.00) 		0.221
(1.00) 		0.281
(1.00) 		0.0791
(1.00) 		0.228
(1.00) 		0.396
(1.00)
17q gain 0 (0%) 75 0.958
(1.00) 		0.202
(1.00) 		0.453
(1.00) 		0.721
(1.00) 		0.837
(1.00) 		0.138
(1.00) 		1
(1.00) 		0.74
(1.00)
18p gain 0 (0%) 71 0.00616
(1.00) 		0.0735
(1.00) 		0.653
(1.00) 		0.145
(1.00) 		0.928
(1.00) 		0.196
(1.00) 		0.841
(1.00) 		0.203
(1.00)
18q gain 0 (0%) 73 0.00369
(1.00) 		0.765
(1.00) 		0.593
(1.00) 		0.769
(1.00) 		1
(1.00) 		0.364
(1.00) 		0.441
(1.00) 		1
(1.00)
19p gain 0 (0%) 67 0.0326
(1.00) 		0.121
(1.00) 		0.166
(1.00) 		1
(1.00) 		0.119
(1.00) 		0.179
(1.00) 		0.393
(1.00) 		0.417
(1.00)
19q gain 0 (0%) 72 0.286
(1.00) 		0.0776
(1.00) 		0.438
(1.00) 		0.374
(1.00) 		0.0738
(1.00) 		1
(1.00) 		0.0809
(1.00) 		1
(1.00)
20p gain 0 (0%) 64 0.069
(1.00) 		0.0162
(1.00) 		0.711
(1.00) 		0.167
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.309
(1.00)
20q gain 0 (0%) 61 0.192
(1.00) 		0.0116
(1.00) 		0.687
(1.00) 		0.151
(1.00) 		0.432
(1.00) 		0.798
(1.00) 		0.155
(1.00) 		0.223
(1.00)
21q gain 0 (0%) 68 0.154
(1.00) 		0.00129
(0.773) 		0.843
(1.00) 		0.18
(1.00) 		0.141
(1.00) 		1
(1.00) 		0.184
(1.00) 		0.241
(1.00)
22q gain 0 (0%) 74 0.0646
(1.00) 		0.906
(1.00) 		0.463
(1.00) 		0.541
(1.00) 		0.0568
(1.00) 		0.297
(1.00) 		0.0607
(1.00) 		0.0684
(1.00)
Xq gain 0 (0%) 80 0.16
(1.00) 		1
(1.00) 		0.65
(1.00) 		0.623
(1.00) 		0.765
(1.00) 		0.63
(1.00)
1p loss 0 (0%) 74 0.0378
(1.00) 		0.341
(1.00) 		0.189
(1.00) 		0.744
(1.00) 		0.294
(1.00) 		0.16
(1.00) 		0.189
(1.00) 		0.387
(1.00)
1q loss 0 (0%) 76 0.728
(1.00) 		0.55
(1.00) 		0.856
(1.00) 		0.715
(1.00) 		0.518
(1.00) 		0.748
(1.00) 		0.51
(1.00) 		0.737
(1.00)
2p loss 0 (0%) 67 0.00674
(1.00) 		0.00626
(1.00) 		0.0844
(1.00) 		0.0335
(1.00) 		0.0836
(1.00) 		0.0804
(1.00) 		0.0176
(1.00) 		0.233
(1.00)
2q loss 0 (0%) 67 0.000501
(0.301) 		0.0354
(1.00) 		0.918
(1.00) 		0.232
(1.00) 		0.292
(1.00) 		0.524
(1.00) 		0.609
(1.00) 		0.192
(1.00)
3p loss 0 (0%) 70 0.117
(1.00) 		0.153
(1.00) 		0.393
(1.00) 		0.287
(1.00) 		0.0532
(1.00) 		0.55
(1.00) 		0.1
(1.00) 		0.349
(1.00)
3q loss 0 (0%) 68 0.07
(1.00) 		0.0112
(1.00) 		0.468
(1.00) 		0.444
(1.00) 		0.0691
(1.00) 		0.082
(1.00) 		0.00665
(1.00) 		0.0232
(1.00)
4p loss 0 (0%) 73 0.0497
(1.00) 		0.0523
(1.00) 		0.313
(1.00) 		0.397
(1.00) 		0.569
(1.00) 		0.616
(1.00) 		0.285
(1.00) 		0.577
(1.00)
4q loss 0 (0%) 73 0.656
(1.00) 		0.057
(1.00) 		0.113
(1.00) 		0.769
(1.00) 		0.875
(1.00) 		1
(1.00) 		0.441
(1.00) 		1
(1.00)
5p loss 0 (0%) 77 0.619
(1.00) 		0.869
(1.00) 		0.484
(1.00) 		0.668
(1.00) 		0.774
(1.00) 		1
(1.00) 		0.732
(1.00) 		1
(1.00)
5q loss 0 (0%) 77 1
(1.00) 		0.24
(1.00) 		0.229
(1.00) 		0.668
(1.00) 		0.774
(1.00) 		1
(1.00) 		0.732
(1.00) 		1
(1.00)
6p loss 0 (0%) 71 0.804
(1.00) 		0.261
(1.00) 		0.535
(1.00) 		0.582
(1.00) 		0.189
(1.00) 		0.36
(1.00) 		0.177
(1.00) 		0.339
(1.00)
6q loss 0 (0%) 76 0.102
(1.00) 		0.0876
(1.00) 		0.599
(1.00) 		0.291
(1.00) 		0.247
(1.00) 		0.365
(1.00) 		0.228
(1.00) 		0.327
(1.00)
7p loss 0 (0%) 73 0.0016
(0.956) 		0.21
(1.00) 		0.28
(1.00) 		0.0324
(1.00) 		0.507
(1.00) 		0.616
(1.00) 		0.532
(1.00) 		0.0507
(1.00)
7q loss 0 (0%) 75 0.326
(1.00) 		0.524
(1.00) 		0.556
(1.00) 		0.744
(1.00) 		0.837
(1.00) 		1
(1.00) 		0.883
(1.00) 		1
(1.00)
8p loss 0 (0%) 69 0.0825
(1.00) 		0.814
(1.00) 		0.684
(1.00) 		1
(1.00) 		0.845
(1.00) 		0.0108
(1.00) 		1
(1.00) 		0.619
(1.00)
8q loss 0 (0%) 75 0.421
(1.00) 		0.376
(1.00) 		0.783
(1.00) 		1
(1.00) 		0.745
(1.00) 		0.138
(1.00) 		0.776
(1.00) 		0.74
(1.00)
9q loss 0 (0%) 75 0.00101
(0.605) 		0.334
(1.00) 		0.0316
(1.00) 		0.221
(1.00) 		0.0167
(1.00) 		0.771
(1.00) 		0.18
(1.00) 		0.74
(1.00)
11p loss 0 (0%) 57 0.269
(1.00) 		0.00189
(1.00) 		0.589
(1.00) 		0.298
(1.00) 		0.754
(1.00) 		0.395
(1.00) 		0.654
(1.00) 		0.246
(1.00)
11q loss 0 (0%) 62 0.0036
(1.00) 		0.00585
(1.00) 		0.788
(1.00) 		0.193
(1.00) 		0.607
(1.00) 		0.198
(1.00) 		0.212
(1.00) 		0.0426
(1.00)
12p loss 0 (0%) 74 0.0252
(1.00) 		0.247
(1.00) 		0.859
(1.00) 		1
(1.00) 		0.704
(1.00) 		0.0916
(1.00) 		0.893
(1.00) 		0.539
(1.00)
12q loss 0 (0%) 70 0.31
(1.00) 		0.807
(1.00) 		0.937
(1.00) 		1
(1.00) 		0.902
(1.00) 		0.319
(1.00) 		1
(1.00) 		1
(1.00)
14q loss 0 (0%) 59 0.455
(1.00) 		0.754
(1.00) 		0.0103
(1.00) 		0.374
(1.00) 		0.222
(1.00) 		0.574
(1.00) 		0.723
(1.00) 		0.199
(1.00)
15q loss 0 (0%) 72 0.221
(1.00) 		0.277
(1.00) 		0.198
(1.00) 		0.221
(1.00) 		0.0216
(1.00) 		0.0104
(1.00) 		0.0331
(1.00) 		0.0834
(1.00)
16p loss 0 (0%) 67 0.00326
(1.00) 		0.171
(1.00) 		0.841
(1.00) 		0.263
(1.00) 		0.292
(1.00) 		0.524
(1.00) 		0.609
(1.00) 		0.192
(1.00)
17p loss 0 (0%) 71 0.307
(1.00) 		0.116
(1.00) 		0.0922
(1.00) 		0.347
(1.00) 		0.562
(1.00) 		0.36
(1.00) 		0.443
(1.00) 		0.339
(1.00)
17q loss 0 (0%) 75 0.793
(1.00) 		0.109
(1.00) 		0.0505
(1.00) 		0.345
(1.00) 		0.175
(1.00) 		0.297
(1.00) 		0.369
(1.00) 		0.237
(1.00)
18p loss 0 (0%) 70 0.447
(1.00) 		0.081
(1.00) 		0.423
(1.00) 		1
(1.00) 		0.431
(1.00) 		1
(1.00) 		0.724
(1.00) 		1
(1.00)
18q loss 0 (0%) 69 0.11
(1.00) 		0.199
(1.00) 		0.363
(1.00) 		0.618
(1.00) 		0.264
(1.00) 		0.847
(1.00) 		0.923
(1.00) 		1
(1.00)
19p loss 0 (0%) 79 0.44
(1.00) 		0.319
(1.00) 		0.339
(1.00) 		0.585
(1.00) 		0.534
(1.00) 		0.395
(1.00) 		0.379
(1.00) 		0.391
(1.00)
19q loss 0 (0%) 74 0.523
(1.00) 		0.0793
(1.00) 		0.611
(1.00) 		0.744
(1.00) 		0.453
(1.00) 		0.783
(1.00) 		0.458
(1.00) 		0.766
(1.00)
20p loss 0 (0%) 73 0.77
(1.00) 		0.765
(1.00) 		0.827
(1.00) 		1
(1.00) 		0.836
(1.00) 		0.15
(1.00) 		1
(1.00) 		0.769
(1.00)
20q loss 0 (0%) 79 0.722
(1.00) 		0.685
(1.00) 		0.835
(1.00) 		1
(1.00) 		0.41
(1.00) 		0.0248
(1.00) 		0.81
(1.00) 		0.634
(1.00)
21q loss 0 (0%) 71 0.111
(1.00) 		1
(1.00) 		0.505
(1.00) 		0.79
(1.00) 		0.324
(1.00) 		0.196
(1.00) 		0.916
(1.00) 		0.792
(1.00)
22q loss 0 (0%) 62 0.801
(1.00) 		0.137
(1.00) 		0.144
(1.00) 		1
(1.00) 		0.883
(1.00) 		1
(1.00) 		0.706
(1.00) 		1
(1.00)
Xq loss 0 (0%) 69 0.143
(1.00) 		0.109
(1.00) 		0.543
(1.00) 		0.18
(1.00) 		0.247
(1.00) 		0.696
(1.00) 		0.578
(1.00) 		0.124
(1.00)
'9p loss' versus 'CN_CNMF'

P value = 1.09e-06 (Fisher's exact test), Q value = 0.00067

Table S1.  Gene #54: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 24 22 18 19
9P LOSS CNV 14 2 1 0
9P LOSS WILD-TYPE 10 20 17 19

Figure S1.  Get High-res Image Gene #54: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'METHLYATION_CNMF'

P value = 0.000361 (Fisher's exact test), Q value = 0.22

Table S2.  Gene #56: '10p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 26 27 30
10P LOSS CNV 2 9 17
10P LOSS WILD-TYPE 24 18 13

Figure S2.  Get High-res Image Gene #56: '10p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'10q loss' versus 'CN_CNMF'

P value = 3.78e-06 (Fisher's exact test), Q value = 0.0023

Table S3.  Gene #57: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 24 22 18 19
10Q LOSS CNV 10 0 13 9
10Q LOSS WILD-TYPE 14 22 5 10

Figure S3.  Get High-res Image Gene #57: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

'10q loss' versus 'METHLYATION_CNMF'

P value = 4.58e-05 (Fisher's exact test), Q value = 0.028

Table S4.  Gene #57: '10q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 26 27 30
10Q LOSS CNV 2 11 19
10Q LOSS WILD-TYPE 24 16 11

Figure S4.  Get High-res Image Gene #57: '10q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'10q loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.000295 (Fisher's exact test), Q value = 0.18

Table S5.  Gene #57: '10q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 13 36 33
10Q LOSS CNV 1 10 21
10Q LOSS WILD-TYPE 12 26 12

Figure S5.  Get High-res Image Gene #57: '10q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'13q loss' versus 'CN_CNMF'

P value = 0.000148 (Fisher's exact test), Q value = 0.09

Table S6.  Gene #62: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 24 22 18 19
13Q LOSS CNV 14 4 13 3
13Q LOSS WILD-TYPE 10 18 5 16

Figure S6.  Get High-res Image Gene #62: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

'16q loss' versus 'METHLYATION_CNMF'

P value = 3.72e-05 (Fisher's exact test), Q value = 0.023

Table S7.  Gene #66: '16q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 26 27 30
16Q LOSS CNV 2 13 19
16Q LOSS WILD-TYPE 24 14 11

Figure S7.  Get High-res Image Gene #66: '16q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

Methods & Data
Input

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

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

  • Number of patients = 83

  • Number of significantly arm-level cnvs = 77

  • 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