Correlation between copy number variations of arm-level result and molecular subtypes
Pheochromocytoma and Paraganglioma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1TM7920
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/C1TM7920
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 67 arm-level events and 8 molecular subtypes across 162 patients, 26 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 1p loss cnv correlated to 'CN_CNMF' and 'MIRSEQ_CNMF'.

  • 3p loss cnv correlated to 'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_MATURE_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 3q loss cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 6q loss cnv correlated to 'METHLYATION_CNMF',  'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_CNMF', and 'MIRSEQ_CHIERARCHICAL'.

  • 11p loss cnv correlated to 'CN_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_CNMF',  'MIRSEQ_CHIERARCHICAL', and 'MIRSEQ_MATURE_CNMF'.

  • 11q loss cnv correlated to 'CN_CNMF',  'MRNASEQ_CNMF',  'MIRSEQ_CNMF',  'MIRSEQ_CHIERARCHICAL', and 'MIRSEQ_MATURE_CNMF'.

  • 17p loss cnv correlated to 'CN_CNMF'.

  • 17q loss cnv correlated to 'CN_CNMF'.

  • 22q loss cnv correlated to 'CN_CNMF'.

  • xq 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 67 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, 26 significant findings 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
11p loss 54 (33%) 108 1e-05
(0.00536) 		0.00053
(0.27) 		0.00024
(0.124) 		1e-05
(0.00536) 		7e-05
(0.0367) 		1e-05
(0.00536) 		4e-05
(0.0211) 		0.00251
(1.00)
11q loss 40 (25%) 122 2e-05
(0.0106) 		0.0686
(1.00) 		0.00023
(0.119) 		0.00087
(0.436) 		0.00024
(0.124) 		0.00035
(0.18) 		0.00027
(0.139) 		0.0273
(1.00)
6q loss 19 (12%) 143 0.00087
(0.436) 		0.00043
(0.22) 		0.00061
(0.309) 		0.00011
(0.0575) 		0.0003
(0.154) 		6e-05
(0.0315) 		0.012
(1.00) 		0.00215
(1.00)
3p loss 62 (38%) 100 0.00066
(0.333) 		0.0955
(1.00) 		0.00052
(0.265) 		4e-05
(0.0211) 		0.00082
(0.412) 		0.00122
(0.609) 		0.00015
(0.078) 		0.00021
(0.109)
1p loss 98 (60%) 64 1e-05
(0.00536) 		0.0159
(1.00) 		0.00248
(1.00) 		0.00189
(0.936) 		0.00012
(0.0625) 		0.0134
(1.00) 		0.00062
(0.314) 		0.135
(1.00)
3q loss 88 (54%) 74 0.00011
(0.0575) 		0.521
(1.00) 		0.0427
(1.00) 		1e-05
(0.00536) 		0.00307
(1.00) 		0.0307
(1.00) 		0.0124
(1.00) 		0.0159
(1.00)
17p loss 61 (38%) 101 0.00044
(0.225) 		0.0023
(1.00) 		0.0713
(1.00) 		0.0339
(1.00) 		0.0233
(1.00) 		0.0229
(1.00) 		0.213
(1.00) 		0.0138
(1.00)
17q loss 19 (12%) 143 3e-05
(0.0158) 		0.904
(1.00) 		0.297
(1.00) 		0.231
(1.00) 		0.369
(1.00) 		0.0895
(1.00) 		0.882
(1.00) 		0.262
(1.00)
22q loss 58 (36%) 104 2e-05
(0.0106) 		0.0127
(1.00) 		0.0325
(1.00) 		0.00237
(1.00) 		0.0483
(1.00) 		0.0515
(1.00) 		0.0274
(1.00) 		0.0242
(1.00)
xq loss 49 (30%) 113 2e-05
(0.0106) 		0.00123
(0.613) 		0.00799
(1.00) 		0.0006
(0.305) 		0.00371
(1.00) 		0.0107
(1.00) 		0.215
(1.00) 		0.0128
(1.00)
1p gain 7 (4%) 155 0.122
(1.00) 		0.783
(1.00) 		0.676
(1.00) 		0.822
(1.00) 		0.895
(1.00) 		0.524
(1.00) 		0.834
(1.00) 		0.652
(1.00)
1q gain 19 (12%) 143 0.00073
(0.368) 		0.353
(1.00) 		0.488
(1.00) 		0.592
(1.00) 		0.906
(1.00) 		0.665
(1.00) 		0.487
(1.00) 		0.846
(1.00)
2p gain 6 (4%) 156 0.506
(1.00) 		0.00663
(1.00) 		0.24
(1.00) 		0.342
(1.00) 		0.135
(1.00) 		0.336
(1.00) 		0.193
(1.00) 		0.459
(1.00)
4p gain 4 (2%) 158 0.68
(1.00) 		0.367
(1.00) 		0.822
(1.00) 		0.554
(1.00) 		0.453
(1.00) 		0.788
(1.00) 		0.772
(1.00) 		1
(1.00)
4q gain 3 (2%) 159 0.0619
(1.00) 		0.806
(1.00) 		0.473
(1.00) 		0.738
(1.00) 		0.614
(1.00) 		0.833
(1.00) 		0.814
(1.00) 		0.463
(1.00)
5p gain 11 (7%) 151 0.623
(1.00) 		0.435
(1.00) 		0.915
(1.00) 		0.657
(1.00) 		0.855
(1.00) 		0.612
(1.00) 		0.829
(1.00) 		0.217
(1.00)
5q gain 7 (4%) 155 0.896
(1.00) 		0.00567
(1.00) 		0.0725
(1.00) 		0.297
(1.00) 		0.482
(1.00) 		0.382
(1.00) 		0.944
(1.00) 		0.286
(1.00)
6p gain 15 (9%) 147 0.889
(1.00) 		0.254
(1.00) 		0.307
(1.00) 		0.373
(1.00) 		0.241
(1.00) 		0.303
(1.00) 		0.559
(1.00) 		0.508
(1.00)
6q gain 8 (5%) 154 0.149
(1.00) 		0.00165
(0.818) 		0.0363
(1.00) 		0.111
(1.00) 		0.129
(1.00) 		0.186
(1.00) 		0.0806
(1.00) 		0.266
(1.00)
7p gain 27 (17%) 135 0.0216
(1.00) 		0.073
(1.00) 		0.139
(1.00) 		0.379
(1.00) 		0.242
(1.00) 		0.0731
(1.00) 		0.316
(1.00) 		0.0875
(1.00)
7q gain 22 (14%) 140 0.00709
(1.00) 		0.00645
(1.00) 		0.171
(1.00) 		0.285
(1.00) 		0.142
(1.00) 		0.115
(1.00) 		0.52
(1.00) 		0.459
(1.00)
8p gain 10 (6%) 152 0.0185
(1.00) 		0.372
(1.00) 		0.0842
(1.00) 		0.0917
(1.00) 		0.0717
(1.00) 		0.155
(1.00) 		0.453
(1.00) 		0.102
(1.00)
8q gain 13 (8%) 149 0.243
(1.00) 		0.753
(1.00) 		0.0843
(1.00) 		0.0763
(1.00) 		0.113
(1.00) 		0.202
(1.00) 		0.804
(1.00) 		0.0877
(1.00)
9p gain 4 (2%) 158 0.231
(1.00) 		0.0714
(1.00) 		0.152
(1.00) 		0.225
(1.00) 		0.287
(1.00) 		0.256
(1.00) 		0.301
(1.00) 		0.511
(1.00)
9q gain 3 (2%) 159 0.457
(1.00) 		0.139
(1.00) 		0.237
(1.00) 		0.238
(1.00) 		0.461
(1.00) 		0.344
(1.00) 		0.295
(1.00) 		0.558
(1.00)
10p gain 12 (7%) 150 0.512
(1.00) 		0.0722
(1.00) 		0.513
(1.00) 		0.52
(1.00) 		1
(1.00) 		0.842
(1.00) 		0.488
(1.00) 		0.178
(1.00)
10q gain 10 (6%) 152 0.105
(1.00) 		0.695
(1.00) 		0.494
(1.00) 		0.594
(1.00) 		0.707
(1.00) 		0.511
(1.00) 		0.425
(1.00) 		0.153
(1.00)
11p gain 5 (3%) 157 0.0872
(1.00) 		0.518
(1.00) 		0.412
(1.00) 		0.303
(1.00) 		0.539
(1.00) 		0.492
(1.00) 		0.345
(1.00) 		0.688
(1.00)
12p gain 11 (7%) 151 0.0105
(1.00) 		0.00742
(1.00) 		0.337
(1.00) 		0.324
(1.00) 		0.0185
(1.00) 		0.214
(1.00) 		0.131
(1.00) 		0.429
(1.00)
12q gain 14 (9%) 148 0.0685
(1.00) 		0.225
(1.00) 		0.603
(1.00) 		0.653
(1.00) 		0.0611
(1.00) 		0.293
(1.00) 		0.224
(1.00) 		0.432
(1.00)
13q gain 9 (6%) 153 0.0181
(1.00) 		0.0216
(1.00) 		0.0102
(1.00) 		0.00874
(1.00) 		0.023
(1.00) 		0.0531
(1.00) 		0.00979
(1.00) 		0.359
(1.00)
14q gain 4 (2%) 158 0.0616
(1.00) 		0.37
(1.00) 		0.548
(1.00) 		0.554
(1.00) 		0.291
(1.00) 		0.787
(1.00) 		0.772
(1.00) 		0.875
(1.00)
15q gain 14 (9%) 148 0.252
(1.00) 		0.0327
(1.00) 		0.316
(1.00) 		0.767
(1.00) 		0.425
(1.00) 		0.794
(1.00) 		0.558
(1.00) 		0.926
(1.00)
16p gain 6 (4%) 156 0.24
(1.00) 		0.552
(1.00) 		0.742
(1.00) 		0.743
(1.00) 		0.381
(1.00) 		0.815
(1.00) 		0.292
(1.00) 		0.501
(1.00)
16q gain 6 (4%) 156 0.0149
(1.00) 		1
(1.00) 		0.272
(1.00) 		0.7
(1.00) 		1
(1.00) 		0.765
(1.00) 		0.399
(1.00) 		0.429
(1.00)
17q gain 5 (3%) 157 0.545
(1.00) 		0.312
(1.00) 		0.3
(1.00) 		0.304
(1.00) 		0.539
(1.00) 		0.771
(1.00) 		0.541
(1.00) 		0.211
(1.00)
18p gain 8 (5%) 154 0.147
(1.00) 		0.23
(1.00) 		0.383
(1.00) 		0.649
(1.00) 		0.465
(1.00) 		0.56
(1.00) 		0.129
(1.00) 		0.858
(1.00)
18q gain 10 (6%) 152 0.35
(1.00) 		0.581
(1.00) 		0.367
(1.00) 		0.538
(1.00) 		0.844
(1.00) 		0.44
(1.00) 		0.196
(1.00) 		0.53
(1.00)
19p gain 20 (12%) 142 0.0155
(1.00) 		0.0756
(1.00) 		0.747
(1.00) 		0.643
(1.00) 		0.276
(1.00) 		0.925
(1.00) 		0.206
(1.00) 		0.728
(1.00)
19q gain 14 (9%) 148 0.151
(1.00) 		0.00885
(1.00) 		0.373
(1.00) 		0.227
(1.00) 		0.461
(1.00) 		0.664
(1.00) 		0.527
(1.00) 		0.49
(1.00)
20p gain 12 (7%) 150 0.644
(1.00) 		0.366
(1.00) 		0.181
(1.00) 		0.341
(1.00) 		0.168
(1.00) 		0.381
(1.00) 		0.595
(1.00) 		0.591
(1.00)
20q gain 10 (6%) 152 0.542
(1.00) 		0.166
(1.00) 		0.0293
(1.00) 		0.0636
(1.00) 		0.0376
(1.00) 		0.0759
(1.00) 		0.0395
(1.00) 		0.513
(1.00)
21q gain 3 (2%) 159 0.249
(1.00) 		0.137
(1.00) 		0.237
(1.00) 		0.0682
(1.00) 		0.182
(1.00) 		0.409
(1.00) 		0.291
(1.00) 		0.807
(1.00)
22q gain 3 (2%) 159 0.249
(1.00) 		0.0828
(1.00) 		0.238
(1.00) 		0.149
(1.00) 		0.183
(1.00) 		0.407
(1.00) 		0.0556
(1.00) 		0.807
(1.00)
xq gain 5 (3%) 157 0.177
(1.00) 		0.0441
(1.00) 		0.0547
(1.00) 		0.0548
(1.00) 		0.14
(1.00) 		0.0676
(1.00) 		0.0306
(1.00) 		0.0976
(1.00)
1q loss 27 (17%) 135 0.895
(1.00) 		0.308
(1.00) 		0.123
(1.00) 		0.516
(1.00) 		0.665
(1.00) 		0.264
(1.00) 		0.031
(1.00) 		0.237
(1.00)
2p loss 10 (6%) 152 0.385
(1.00) 		0.0761
(1.00) 		0.00446
(1.00) 		0.178
(1.00) 		0.195
(1.00) 		0.00085
(0.427) 		0.148
(1.00) 		0.00779
(1.00)
2q loss 13 (8%) 149 0.822
(1.00) 		0.45
(1.00) 		0.416
(1.00) 		0.14
(1.00) 		0.535
(1.00) 		0.099
(1.00) 		0.326
(1.00) 		0.34
(1.00)
4p loss 11 (7%) 151 0.00334
(1.00) 		0.141
(1.00) 		0.00712
(1.00) 		0.184
(1.00) 		0.292
(1.00) 		0.391
(1.00) 		0.0577
(1.00) 		0.143
(1.00)
4q loss 10 (6%) 152 0.0717
(1.00) 		0.24
(1.00) 		0.0183
(1.00) 		0.339
(1.00) 		0.419
(1.00) 		0.528
(1.00) 		0.328
(1.00) 		0.323
(1.00)
5p loss 5 (3%) 157 0.0661
(1.00) 		0.377
(1.00) 		0.0366
(1.00) 		0.036
(1.00) 		0.141
(1.00) 		0.167
(1.00) 		0.169
(1.00) 		0.0555
(1.00)
5q loss 7 (4%) 155 0.382
(1.00) 		0.784
(1.00) 		0.646
(1.00) 		0.524
(1.00) 		0.895
(1.00) 		0.359
(1.00) 		0.229
(1.00) 		0.306
(1.00)
7q loss 6 (4%) 156 0.0327
(1.00) 		0.485
(1.00) 		0.04
(1.00) 		0.176
(1.00) 		0.0295
(1.00) 		0.0247
(1.00) 		0.248
(1.00) 		0.128
(1.00)
8p loss 20 (12%) 142 0.0219
(1.00) 		0.39
(1.00) 		0.125
(1.00) 		0.109
(1.00) 		0.717
(1.00) 		0.954
(1.00) 		0.28
(1.00) 		0.487
(1.00)
8q loss 12 (7%) 150 0.0448
(1.00) 		0.741
(1.00) 		0.33
(1.00) 		0.619
(1.00) 		0.114
(1.00) 		0.438
(1.00) 		0.928
(1.00) 		0.429
(1.00)
9p loss 11 (7%) 151 0.048
(1.00) 		0.719
(1.00) 		0.184
(1.00) 		0.18
(1.00) 		0.671
(1.00) 		0.0676
(1.00) 		0.55
(1.00) 		0.314
(1.00)
9q loss 11 (7%) 151 0.00729
(1.00) 		0.609
(1.00) 		0.51
(1.00) 		0.629
(1.00) 		0.723
(1.00) 		0.401
(1.00) 		0.828
(1.00) 		0.442
(1.00)
13q loss 8 (5%) 154 0.0353
(1.00) 		0.447
(1.00) 		0.31
(1.00) 		0.116
(1.00) 		0.528
(1.00) 		0.225
(1.00) 		0.546
(1.00) 		0.459
(1.00)
14q loss 20 (12%) 142 0.24
(1.00) 		0.0525
(1.00) 		0.309
(1.00) 		0.794
(1.00) 		0.155
(1.00) 		0.00193
(0.953) 		0.0294
(1.00) 		0.00144
(0.716)
15q loss 3 (2%) 159 0.352
(1.00) 		0.33
(1.00) 		1
(1.00) 		0.866
(1.00) 		0.618
(1.00) 		0.833
(1.00) 		0.898
(1.00) 		1
(1.00)
16p loss 9 (6%) 153 0.335
(1.00) 		0.0432
(1.00) 		0.554
(1.00) 		0.364
(1.00) 		0.248
(1.00) 		0.404
(1.00) 		0.675
(1.00) 		0.772
(1.00)
16q loss 5 (3%) 157 0.739
(1.00) 		0.442
(1.00) 		0.446
(1.00) 		0.0263
(1.00) 		0.21
(1.00) 		0.593
(1.00) 		0.0918
(1.00) 		0.829
(1.00)
18p loss 16 (10%) 146 0.502
(1.00) 		0.742
(1.00) 		0.856
(1.00) 		0.756
(1.00) 		0.892
(1.00) 		0.312
(1.00) 		0.607
(1.00) 		0.457
(1.00)
18q loss 6 (4%) 156 0.289
(1.00) 		0.875
(1.00) 		0.586
(1.00) 		0.66
(1.00) 		0.575
(1.00) 		0.581
(1.00) 		0.433
(1.00) 		0.866
(1.00)
19q loss 6 (4%) 156 0.241
(1.00) 		1
(1.00) 		0.942
(1.00) 		0.943
(1.00) 		0.332
(1.00) 		0.627
(1.00) 		0.926
(1.00) 		0.932
(1.00)
20q loss 3 (2%) 159 1
(1.00) 		1
(1.00) 		1
(1.00) 		0.643
(1.00) 		0.789
(1.00) 		1
(1.00) 		0.731
(1.00) 		0.808
(1.00)
21q loss 36 (22%) 126 0.205
(1.00) 		0.0501
(1.00) 		0.0419
(1.00) 		0.938
(1.00) 		0.564
(1.00) 		0.6
(1.00) 		0.908
(1.00) 		0.717
(1.00)
'1p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0054

Table S1.  Gene #36: '1p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 60 63 39
1P LOSS MUTATED 51 24 23
1P LOSS WILD-TYPE 9 39 16

Figure S1.  Get High-res Image Gene #36: '1p loss' versus Molecular Subtype #1: 'CN_CNMF'

'1p loss' versus 'MIRSEQ_CNMF'

P value = 0.00012 (Fisher's exact test), Q value = 0.063

Table S2.  Gene #36: '1p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 65 58 39
1P LOSS MUTATED 29 47 22
1P LOSS WILD-TYPE 36 11 17

Figure S2.  Get High-res Image Gene #36: '1p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'3p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 4e-05 (Fisher's exact test), Q value = 0.021

Table S3.  Gene #40: '3p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 34 64 43 21
3P LOSS MUTATED 9 21 30 2
3P LOSS WILD-TYPE 25 43 13 19

Figure S3.  Get High-res Image Gene #40: '3p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'3p loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.00015 (Fisher's exact test), Q value = 0.078

Table S4.  Gene #40: '3p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 34 58 11 35 23
3P LOSS MUTATED 13 16 2 25 6
3P LOSS WILD-TYPE 21 42 9 10 17

Figure S4.  Get High-res Image Gene #40: '3p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'3p loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.00021 (Fisher's exact test), Q value = 0.11

Table S5.  Gene #40: '3p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 71 53 18 19
3P LOSS MUTATED 20 33 6 3
3P LOSS WILD-TYPE 51 20 12 16

Figure S5.  Get High-res Image Gene #40: '3p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'3q loss' versus 'CN_CNMF'

P value = 0.00011 (Fisher's exact test), Q value = 0.058

Table S6.  Gene #41: '3q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 60 63 39
3Q LOSS MUTATED 36 22 30
3Q LOSS WILD-TYPE 24 41 9

Figure S6.  Get High-res Image Gene #41: '3q loss' versus Molecular Subtype #1: 'CN_CNMF'

'3q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0054

Table S7.  Gene #41: '3q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 34 64 43 21
3Q LOSS MUTATED 6 42 33 7
3Q LOSS WILD-TYPE 28 22 10 14

Figure S7.  Get High-res Image Gene #41: '3q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'6q loss' versus 'METHLYATION_CNMF'

P value = 0.00043 (Fisher's exact test), Q value = 0.22

Table S8.  Gene #46: '6q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 40 78 44
6Q LOSS MUTATED 1 17 1
6Q LOSS WILD-TYPE 39 61 43

Figure S8.  Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'6q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00011 (Fisher's exact test), Q value = 0.058

Table S9.  Gene #46: '6q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 34 64 43 21
6Q LOSS MUTATED 0 17 1 1
6Q LOSS WILD-TYPE 34 47 42 20

Figure S9.  Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'6q loss' versus 'MIRSEQ_CNMF'

P value = 3e-04 (Fisher's exact test), Q value = 0.15

Table S10.  Gene #46: '6q loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 65 58 39
6Q LOSS MUTATED 1 14 4
6Q LOSS WILD-TYPE 64 44 35

Figure S10.  Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'6q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 6e-05 (Fisher's exact test), Q value = 0.031

Table S11.  Gene #46: '6q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 54 18 24
6Q LOSS MUTATED 1 16 1 1
6Q LOSS WILD-TYPE 65 38 17 23

Figure S11.  Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'11p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0054

Table S12.  Gene #52: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 60 63 39
11P LOSS MUTATED 1 36 17
11P LOSS WILD-TYPE 59 27 22

Figure S12.  Get High-res Image Gene #52: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

'11p loss' versus 'MRNASEQ_CNMF'

P value = 0.00024 (Fisher's exact test), Q value = 0.12

Table S13.  Gene #52: '11p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 33 64 44 21
11P LOSS MUTATED 12 11 25 6
11P LOSS WILD-TYPE 21 53 19 15

Figure S13.  Get High-res Image Gene #52: '11p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'11p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0054

Table S14.  Gene #52: '11p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 34 64 43 21
11P LOSS MUTATED 11 9 28 6
11P LOSS WILD-TYPE 23 55 15 15

Figure S14.  Get High-res Image Gene #52: '11p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'11p loss' versus 'MIRSEQ_CNMF'

P value = 7e-05 (Fisher's exact test), Q value = 0.037

Table S15.  Gene #52: '11p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 65 58 39
11P LOSS MUTATED 34 9 11
11P LOSS WILD-TYPE 31 49 28

Figure S15.  Get High-res Image Gene #52: '11p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'11p loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0054

Table S16.  Gene #52: '11p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 54 18 24
11P LOSS MUTATED 37 6 5 6
11P LOSS WILD-TYPE 29 48 13 18

Figure S16.  Get High-res Image Gene #52: '11p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'11p loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 4e-05 (Fisher's exact test), Q value = 0.021

Table S17.  Gene #52: '11p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 34 58 11 35 23
11P LOSS MUTATED 12 7 3 20 11
11P LOSS WILD-TYPE 22 51 8 15 12

Figure S17.  Get High-res Image Gene #52: '11p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'11q loss' versus 'CN_CNMF'

P value = 2e-05 (Fisher's exact test), Q value = 0.011

Table S18.  Gene #53: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 60 63 39
11Q LOSS MUTATED 3 24 13
11Q LOSS WILD-TYPE 57 39 26

Figure S18.  Get High-res Image Gene #53: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

'11q loss' versus 'MRNASEQ_CNMF'

P value = 0.00023 (Fisher's exact test), Q value = 0.12

Table S19.  Gene #53: '11q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 33 64 44 21
11Q LOSS MUTATED 8 7 21 4
11Q LOSS WILD-TYPE 25 57 23 17

Figure S19.  Get High-res Image Gene #53: '11q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'11q loss' versus 'MIRSEQ_CNMF'

P value = 0.00024 (Fisher's exact test), Q value = 0.12

Table S20.  Gene #53: '11q loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 65 58 39
11Q LOSS MUTATED 26 5 9
11Q LOSS WILD-TYPE 39 53 30

Figure S20.  Get High-res Image Gene #53: '11q loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'11q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00035 (Fisher's exact test), Q value = 0.18

Table S21.  Gene #53: '11q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 54 18 24
11Q LOSS MUTATED 27 5 2 6
11Q LOSS WILD-TYPE 39 49 16 18

Figure S21.  Get High-res Image Gene #53: '11q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'11q loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.00027 (Fisher's exact test), Q value = 0.14

Table S22.  Gene #53: '11q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 34 58 11 35 23
11Q LOSS MUTATED 9 5 2 18 6
11Q LOSS WILD-TYPE 25 53 9 17 17

Figure S22.  Get High-res Image Gene #53: '11q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'17p loss' versus 'CN_CNMF'

P value = 0.00044 (Fisher's exact test), Q value = 0.22

Table S23.  Gene #59: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 60 63 39
17P LOSS MUTATED 20 16 25
17P LOSS WILD-TYPE 40 47 14

Figure S23.  Get High-res Image Gene #59: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

'17q loss' versus 'CN_CNMF'

P value = 3e-05 (Fisher's exact test), Q value = 0.016

Table S24.  Gene #60: '17q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 60 63 39
17Q LOSS MUTATED 4 2 13
17Q LOSS WILD-TYPE 56 61 26

Figure S24.  Get High-res Image Gene #60: '17q loss' versus Molecular Subtype #1: 'CN_CNMF'

'22q loss' versus 'CN_CNMF'

P value = 2e-05 (Fisher's exact test), Q value = 0.011

Table S25.  Gene #66: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 60 63 39
22Q LOSS MUTATED 35 8 15
22Q LOSS WILD-TYPE 25 55 24

Figure S25.  Get High-res Image Gene #66: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

'xq loss' versus 'CN_CNMF'

P value = 2e-05 (Fisher's exact test), Q value = 0.011

Table S26.  Gene #67: 'xq loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 60 63 39
XQ LOSS MUTATED 22 7 20
XQ LOSS WILD-TYPE 38 56 19

Figure S26.  Get High-res Image Gene #67: 'xq loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data
Input

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

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

  • Number of patients = 162

  • Number of significantly arm-level cnvs = 67

  • 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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