Correlation between copy number variations of arm-level result and molecular subtypes
Pheochromocytoma and Paraganglioma (Primary solid tumor)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1X63KQ3
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/C1X63KQ3
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 160 patients, 33 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 1q gain cnv correlated to 'CN_CNMF'.

  • 7q gain cnv correlated to 'CN_CNMF'.

  • 12p gain cnv correlated to 'MIRSEQ_MATURE_CNMF'.

  • 13q gain cnv correlated to 'CN_CNMF' and 'MIRSEQ_MATURE_CNMF'.

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

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

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

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

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

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

  • 17p loss cnv correlated to 'CN_CNMF'.

  • 22q 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, 33 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
6q loss 19 (12%) 141 0.00362
(1.00) 		0.00041
(0.209) 		0.00047
(0.237) 		0.0001
(0.0518) 		0.00012
(0.062) 		2e-05
(0.0105) 		3e-05
(0.0157) 		3e-05
(0.0157)
11p loss 53 (33%) 107 1e-05
(0.00536) 		0.00083
(0.413) 		0.00012
(0.062) 		1e-05
(0.00536) 		3e-05
(0.0157) 		1e-05
(0.00536) 		5e-05
(0.026) 		1e-05
(0.00536)
11q loss 39 (24%) 121 1e-05
(0.00536) 		0.0495
(1.00) 		0.00042
(0.213) 		0.00109
(0.54) 		0.00036
(0.184) 		0.0007
(0.351) 		0.00044
(0.223) 		0.00033
(0.169)
1p loss 94 (59%) 66 1e-05
(0.00536) 		0.02
(1.00) 		0.00473
(1.00) 		0.00275
(1.00) 		0.00014
(0.0721) 		0.015
(1.00) 		0.00046
(0.232) 		0.00364
(1.00)
13q gain 9 (6%) 151 6e-05
(0.0311) 		0.0216
(1.00) 		0.0112
(1.00) 		0.0112
(1.00) 		0.0239
(1.00) 		0.0486
(1.00) 		0.00026
(0.133) 		0.0296
(1.00)
3p loss 61 (38%) 99 1e-05
(0.00536) 		0.0797
(1.00) 		0.00074
(0.369) 		1e-05
(0.00536) 		0.00112
(0.553) 		0.00172
(0.839) 		0.0112
(1.00) 		0.0173
(1.00)
3q loss 88 (55%) 72 1e-05
(0.00536) 		0.6
(1.00) 		0.0384
(1.00) 		1e-05
(0.00536) 		0.00216
(1.00) 		0.0242
(1.00) 		0.379
(1.00) 		0.0143
(1.00)
1q gain 19 (12%) 141 1e-05
(0.00536) 		0.352
(1.00) 		0.502
(1.00) 		0.612
(1.00) 		0.907
(1.00) 		0.642
(1.00) 		0.743
(1.00) 		0.711
(1.00)
7q gain 21 (13%) 139 0.00014
(0.0721) 		0.0109
(1.00) 		0.0851
(1.00) 		0.168
(1.00) 		0.0645
(1.00) 		0.0401
(1.00) 		0.00209
(1.00) 		0.0319
(1.00)
12p gain 11 (7%) 149 0.00306
(1.00) 		0.00712
(1.00) 		0.332
(1.00) 		0.33
(1.00) 		0.0188
(1.00) 		0.21
(1.00) 		0.00043
(0.218) 		0.0333
(1.00)
17p loss 61 (38%) 99 0.0003
(0.154) 		0.00222
(1.00) 		0.0629
(1.00) 		0.03
(1.00) 		0.0196
(1.00) 		0.0193
(1.00) 		0.00484
(1.00) 		0.00955
(1.00)
22q loss 57 (36%) 103 1e-05
(0.00536) 		0.0213
(1.00) 		0.0175
(1.00) 		0.00143
(0.702) 		0.0313
(1.00) 		0.0311
(1.00) 		0.0444
(1.00) 		0.00611
(1.00)
1p gain 8 (5%) 152 0.00056
(0.281) 		1
(1.00) 		0.43
(1.00) 		0.726
(1.00) 		0.816
(1.00) 		0.541
(1.00) 		0.336
(1.00) 		0.245
(1.00)
2p gain 6 (4%) 154 0.348
(1.00) 		0.00559
(1.00) 		0.259
(1.00) 		0.347
(1.00) 		0.135
(1.00) 		0.3
(1.00) 		0.00293
(1.00) 		0.139
(1.00)
4p gain 4 (2%) 156 0.0184
(1.00) 		0.374
(1.00) 		0.897
(1.00) 		0.553
(1.00) 		0.454
(1.00) 		0.79
(1.00) 		0.216
(1.00) 		0.458
(1.00)
4q gain 3 (2%) 157 0.169
(1.00) 		0.801
(1.00) 		0.473
(1.00) 		0.74
(1.00) 		0.616
(1.00) 		0.836
(1.00) 		0.247
(1.00) 		0.611
(1.00)
5p gain 11 (7%) 149 0.025
(1.00) 		0.402
(1.00) 		0.942
(1.00) 		0.659
(1.00) 		0.854
(1.00) 		0.613
(1.00) 		0.787
(1.00) 		0.669
(1.00)
5q gain 7 (4%) 153 0.0257
(1.00) 		0.00511
(1.00) 		0.0775
(1.00) 		0.296
(1.00) 		0.484
(1.00) 		0.383
(1.00) 		0.7
(1.00) 		0.613
(1.00)
6p gain 14 (9%) 146 0.77
(1.00) 		0.386
(1.00) 		0.323
(1.00) 		0.408
(1.00) 		0.327
(1.00) 		0.349
(1.00) 		0.369
(1.00) 		0.343
(1.00)
6q gain 8 (5%) 152 0.0141
(1.00) 		0.00166
(0.812) 		0.0318
(1.00) 		0.115
(1.00) 		0.13
(1.00) 		0.188
(1.00) 		0.0329
(1.00) 		0.214
(1.00)
7p gain 26 (16%) 134 0.0131
(1.00) 		0.122
(1.00) 		0.0812
(1.00) 		0.239
(1.00) 		0.119
(1.00) 		0.0467
(1.00) 		0.0333
(1.00) 		0.126
(1.00)
8p gain 10 (6%) 150 0.028
(1.00) 		0.37
(1.00) 		0.0861
(1.00) 		0.0939
(1.00) 		0.0813
(1.00) 		0.161
(1.00) 		0.0778
(1.00) 		0.104
(1.00)
8q gain 13 (8%) 147 0.291
(1.00) 		0.752
(1.00) 		0.0827
(1.00) 		0.0808
(1.00) 		0.113
(1.00) 		0.211
(1.00) 		0.0828
(1.00) 		0.14
(1.00)
9p gain 4 (2%) 156 0.174
(1.00) 		0.0693
(1.00) 		0.154
(1.00) 		0.223
(1.00) 		0.293
(1.00) 		0.259
(1.00) 		0.122
(1.00) 		0.359
(1.00)
9q gain 3 (2%) 157 0.354
(1.00) 		0.137
(1.00) 		0.239
(1.00) 		0.241
(1.00) 		0.464
(1.00) 		0.348
(1.00) 		0.112
(1.00) 		0.469
(1.00)
10p gain 12 (8%) 148 0.751
(1.00) 		0.0589
(1.00) 		0.54
(1.00) 		0.504
(1.00) 		1
(1.00) 		0.845
(1.00) 		0.8
(1.00) 		0.637
(1.00)
10q gain 10 (6%) 150 0.383
(1.00) 		0.693
(1.00) 		0.524
(1.00) 		0.579
(1.00) 		0.704
(1.00) 		0.509
(1.00) 		0.545
(1.00) 		0.548
(1.00)
11p gain 4 (2%) 156 0.887
(1.00) 		0.807
(1.00) 		0.2
(1.00) 		0.203
(1.00) 		0.129
(1.00) 		0.159
(1.00) 		0.0808
(1.00) 		0.123
(1.00)
12q gain 13 (8%) 147 0.0207
(1.00) 		0.132
(1.00) 		0.784
(1.00) 		0.784
(1.00) 		0.0968
(1.00) 		0.416
(1.00) 		0.00731
(1.00) 		0.128
(1.00)
14q gain 4 (2%) 156 0.496
(1.00) 		0.37
(1.00) 		0.552
(1.00) 		0.553
(1.00) 		0.291
(1.00) 		0.791
(1.00) 		0.0535
(1.00) 		0.462
(1.00)
15q gain 14 (9%) 146 0.0958
(1.00) 		0.0317
(1.00) 		0.319
(1.00) 		0.77
(1.00) 		0.425
(1.00) 		0.778
(1.00) 		0.216
(1.00) 		0.882
(1.00)
16p gain 6 (4%) 154 0.246
(1.00) 		0.553
(1.00) 		0.742
(1.00) 		0.742
(1.00) 		0.332
(1.00) 		0.815
(1.00) 		0.437
(1.00) 		0.573
(1.00)
16q gain 6 (4%) 154 0.27
(1.00) 		1
(1.00) 		0.272
(1.00) 		0.7
(1.00) 		1
(1.00) 		0.769
(1.00) 		0.761
(1.00) 		0.381
(1.00)
17q gain 5 (3%) 155 0.234
(1.00) 		0.312
(1.00) 		0.303
(1.00) 		0.303
(1.00) 		0.539
(1.00) 		0.776
(1.00) 		0.168
(1.00) 		0.446
(1.00)
18p gain 8 (5%) 152 0.0663
(1.00) 		0.229
(1.00) 		0.384
(1.00) 		0.65
(1.00) 		0.466
(1.00) 		0.565
(1.00) 		0.043
(1.00) 		0.589
(1.00)
18q gain 10 (6%) 150 0.152
(1.00) 		0.584
(1.00) 		0.352
(1.00) 		0.538
(1.00) 		0.844
(1.00) 		0.426
(1.00) 		0.147
(1.00) 		1
(1.00)
19p gain 20 (12%) 140 0.019
(1.00) 		0.0754
(1.00) 		0.748
(1.00) 		0.672
(1.00) 		0.314
(1.00) 		0.952
(1.00) 		0.487
(1.00) 		0.647
(1.00)
19q gain 14 (9%) 146 0.0198
(1.00) 		0.00889
(1.00) 		0.389
(1.00) 		0.252
(1.00) 		0.497
(1.00) 		0.691
(1.00) 		0.247
(1.00) 		0.458
(1.00)
20p gain 11 (7%) 149 0.324
(1.00) 		0.189
(1.00) 		0.31
(1.00) 		0.587
(1.00) 		0.294
(1.00) 		0.53
(1.00) 		0.22
(1.00) 		0.785
(1.00)
20q gain 9 (6%) 151 0.0596
(1.00) 		0.0434
(1.00) 		0.0605
(1.00) 		0.137
(1.00) 		0.072
(1.00) 		0.117
(1.00) 		0.044
(1.00) 		0.249
(1.00)
21q gain 3 (2%) 157 0.143
(1.00) 		0.138
(1.00) 		0.241
(1.00) 		0.0693
(1.00) 		0.12
(1.00) 		0.412
(1.00) 		0.112
(1.00) 		0.18
(1.00)
22q gain 3 (2%) 157 0.126
(1.00) 		0.0843
(1.00) 		0.241
(1.00) 		0.152
(1.00) 		0.12
(1.00) 		0.411
(1.00) 		0.0114
(1.00) 		0.182
(1.00)
xq gain 5 (3%) 155 0.109
(1.00) 		0.0551
(1.00) 		0.0536
(1.00) 		0.0549
(1.00) 		0.142
(1.00) 		0.0683
(1.00) 		0.103
(1.00) 		0.254
(1.00)
1q loss 26 (16%) 134 0.0509
(1.00) 		0.233
(1.00) 		0.0868
(1.00) 		0.421
(1.00) 		0.503
(1.00) 		0.14
(1.00) 		0.102
(1.00) 		0.108
(1.00)
2p loss 10 (6%) 150 0.0831
(1.00) 		0.0748
(1.00) 		0.00465
(1.00) 		0.17
(1.00) 		0.198
(1.00) 		0.0008
(0.398) 		0.254
(1.00) 		0.0014
(0.689)
2q loss 13 (8%) 147 0.0591
(1.00) 		0.447
(1.00) 		0.418
(1.00) 		0.144
(1.00) 		0.535
(1.00) 		0.0938
(1.00) 		0.616
(1.00) 		0.308
(1.00)
4p loss 11 (7%) 149 0.00247
(1.00) 		0.144
(1.00) 		0.00653
(1.00) 		0.205
(1.00) 		0.297
(1.00) 		0.385
(1.00) 		0.218
(1.00) 		0.342
(1.00)
4q loss 10 (6%) 150 0.00949
(1.00) 		0.241
(1.00) 		0.0162
(1.00) 		0.346
(1.00) 		0.42
(1.00) 		0.526
(1.00) 		0.409
(1.00) 		0.501
(1.00)
5p loss 5 (3%) 155 0.014
(1.00) 		0.376
(1.00) 		0.037
(1.00) 		0.0383
(1.00) 		0.142
(1.00) 		0.167
(1.00) 		0.102
(1.00) 		0.168
(1.00)
5q loss 7 (4%) 153 0.277
(1.00) 		0.784
(1.00) 		0.647
(1.00) 		0.501
(1.00) 		0.895
(1.00) 		0.365
(1.00) 		1
(1.00) 		1
(1.00)
7q loss 6 (4%) 154 0.0441
(1.00) 		0.425
(1.00) 		0.0385
(1.00) 		0.164
(1.00) 		0.0226
(1.00) 		0.0252
(1.00) 		0.153
(1.00) 		0.015
(1.00)
8p loss 19 (12%) 141 0.111
(1.00) 		0.541
(1.00) 		0.0609
(1.00) 		0.121
(1.00) 		0.55
(1.00) 		0.867
(1.00) 		0.18
(1.00) 		0.745
(1.00)
8q loss 12 (8%) 148 0.368
(1.00) 		0.744
(1.00) 		0.345
(1.00) 		0.597
(1.00) 		0.104
(1.00) 		0.413
(1.00) 		0.547
(1.00) 		0.478
(1.00)
9p loss 11 (7%) 149 0.394
(1.00) 		0.72
(1.00) 		0.173
(1.00) 		0.172
(1.00) 		0.673
(1.00) 		0.0656
(1.00) 		0.074
(1.00) 		0.316
(1.00)
9q loss 11 (7%) 149 0.406
(1.00) 		0.608
(1.00) 		0.502
(1.00) 		0.627
(1.00) 		0.725
(1.00) 		0.402
(1.00) 		0.853
(1.00) 		0.787
(1.00)
13q loss 7 (4%) 153 0.574
(1.00) 		0.611
(1.00) 		0.324
(1.00) 		0.161
(1.00) 		0.298
(1.00) 		0.106
(1.00) 		0.337
(1.00) 		0.288
(1.00)
14q loss 20 (12%) 140 0.175
(1.00) 		0.0499
(1.00) 		0.283
(1.00) 		0.765
(1.00) 		0.164
(1.00) 		0.0019
(0.925) 		0.397
(1.00) 		0.0228
(1.00)
15q loss 3 (2%) 157 0.386
(1.00) 		0.33
(1.00) 		1
(1.00) 		0.866
(1.00) 		0.617
(1.00) 		0.835
(1.00) 		0.45
(1.00) 		0.613
(1.00)
16p loss 8 (5%) 152 0.17
(1.00) 		0.0249
(1.00) 		0.631
(1.00) 		0.628
(1.00) 		0.34
(1.00) 		0.563
(1.00) 		0.652
(1.00) 		0.592
(1.00)
16q loss 4 (2%) 156 0.0532
(1.00) 		0.275
(1.00) 		0.895
(1.00) 		0.0728
(1.00) 		0.233
(1.00) 		0.623
(1.00) 		0.45
(1.00) 		1
(1.00)
17q loss 19 (12%) 141 0.00071
(0.355) 		0.903
(1.00) 		0.268
(1.00) 		0.221
(1.00) 		0.334
(1.00) 		0.0831
(1.00) 		0.579
(1.00) 		0.0852
(1.00)
18p loss 16 (10%) 144 0.853
(1.00) 		0.744
(1.00) 		0.856
(1.00) 		0.757
(1.00) 		0.893
(1.00) 		0.302
(1.00) 		0.947
(1.00) 		0.531
(1.00)
18q loss 6 (4%) 154 0.344
(1.00) 		0.877
(1.00) 		0.586
(1.00) 		0.659
(1.00) 		0.576
(1.00) 		0.589
(1.00) 		0.276
(1.00) 		0.57
(1.00)
19q loss 6 (4%) 154 0.835
(1.00) 		1
(1.00) 		0.942
(1.00) 		0.941
(1.00) 		0.382
(1.00) 		0.626
(1.00) 		1
(1.00) 		0.763
(1.00)
20q loss 3 (2%) 157 0.906
(1.00) 		1
(1.00) 		1
(1.00) 		0.646
(1.00) 		0.789
(1.00) 		1
(1.00) 		1
(1.00) 		0.791
(1.00)
21q loss 34 (21%) 126 0.0175
(1.00) 		0.0763
(1.00) 		0.0577
(1.00) 		0.955
(1.00) 		0.472
(1.00) 		0.504
(1.00) 		0.729
(1.00) 		0.254
(1.00)
xq loss 49 (31%) 111 0.00121
(0.597) 		0.00098
(0.486) 		0.00724
(1.00) 		0.00052
(0.262) 		0.00334
(1.00) 		0.00975
(1.00) 		0.011
(1.00) 		0.00157
(0.769)
'1q gain' versus 'CN_CNMF'

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

Table S1.  Gene #2: '1q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 15 24 55 43 23
1Q GAIN MUTATED 11 0 5 1 2
1Q GAIN WILD-TYPE 4 24 50 42 21

Figure S1.  Get High-res Image Gene #2: '1q gain' versus Molecular Subtype #1: 'CN_CNMF'

'7q gain' versus 'CN_CNMF'

P value = 0.00014 (Fisher's exact test), Q value = 0.072

Table S2.  Gene #11: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 15 24 55 43 23
7Q GAIN MUTATED 3 4 0 12 2
7Q GAIN WILD-TYPE 12 20 55 31 21

Figure S2.  Get High-res Image Gene #11: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

'12p gain' versus 'MIRSEQ_MATURE_CNMF'

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

Table S3.  Gene #19: '12p gain' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 37 66 57
12P GAIN MUTATED 8 1 2
12P GAIN WILD-TYPE 29 65 55

Figure S3.  Get High-res Image Gene #19: '12p gain' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'13q gain' versus 'CN_CNMF'

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

Table S4.  Gene #21: '13q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 15 24 55 43 23
13Q GAIN MUTATED 0 0 0 9 0
13Q GAIN WILD-TYPE 15 24 55 34 23

Figure S4.  Get High-res Image Gene #21: '13q gain' versus Molecular Subtype #1: 'CN_CNMF'

'13q gain' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.00026 (Fisher's exact test), Q value = 0.13

Table S5.  Gene #21: '13q gain' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 37 66 57
13Q GAIN MUTATED 7 0 2
13Q GAIN WILD-TYPE 30 66 55

Figure S5.  Get High-res Image Gene #21: '13q gain' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'1p loss' versus 'CN_CNMF'

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

Table S6.  Gene #36: '1p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 15 24 55 43 23
1P LOSS MUTATED 9 4 42 20 19
1P LOSS WILD-TYPE 6 20 13 23 4

Figure S6.  Get High-res Image Gene #36: '1p loss' versus Molecular Subtype #1: 'CN_CNMF'

'1p loss' versus 'MIRSEQ_CNMF'

P value = 0.00014 (Fisher's exact test), Q value = 0.072

Table S7.  Gene #36: '1p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 64 57 39
1P LOSS MUTATED 27 45 22
1P LOSS WILD-TYPE 37 12 17

Figure S7.  Get High-res Image Gene #36: '1p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'1p loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.00046 (Fisher's exact test), Q value = 0.23

Table S8.  Gene #36: '1p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 37 66 57
1P LOSS MUTATED 13 49 32
1P LOSS WILD-TYPE 24 17 25

Figure S8.  Get High-res Image Gene #36: '1p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'3p loss' versus 'CN_CNMF'

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

Table S9.  Gene #40: '3p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 15 24 55 43 23
3P LOSS MUTATED 9 1 13 33 5
3P LOSS WILD-TYPE 6 23 42 10 18

Figure S9.  Get High-res Image Gene #40: '3p loss' versus Molecular Subtype #1: 'CN_CNMF'

'3p loss' versus 'MRNASEQ_CHIERARCHICAL'

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

Table S10.  Gene #40: '3p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 33 63 43 21
3P LOSS MUTATED 8 21 30 2
3P LOSS WILD-TYPE 25 42 13 19

Figure S10.  Get High-res Image Gene #40: '3p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'3q loss' versus 'CN_CNMF'

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

Table S11.  Gene #41: '3q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 15 24 55 43 23
3Q LOSS MUTATED 8 0 35 31 14
3Q LOSS WILD-TYPE 7 24 20 12 9

Figure S11.  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 S12.  Gene #41: '3q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 33 63 43 21
3Q LOSS MUTATED 6 42 33 7
3Q LOSS WILD-TYPE 27 21 10 14

Figure S12.  Get High-res Image Gene #41: '3q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'6q loss' versus 'METHLYATION_CNMF'

P value = 0.00041 (Fisher's exact test), Q value = 0.21

Table S13.  Gene #46: '6q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 40 77 43
6Q LOSS MUTATED 1 17 1
6Q LOSS WILD-TYPE 39 60 42

Figure S13.  Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'6q loss' versus 'MRNASEQ_CNMF'

P value = 0.00047 (Fisher's exact test), Q value = 0.24

Table S14.  Gene #46: '6q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 33 63 43 21
6Q LOSS MUTATED 1 16 1 1
6Q LOSS WILD-TYPE 32 47 42 20

Figure S14.  Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'6q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1e-04 (Fisher's exact test), Q value = 0.052

Table S15.  Gene #46: '6q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 33 63 43 21
6Q LOSS MUTATED 0 17 1 1
6Q LOSS WILD-TYPE 33 46 42 20

Figure S15.  Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'6q loss' versus 'MIRSEQ_CNMF'

P value = 0.00012 (Fisher's exact test), Q value = 0.062

Table S16.  Gene #46: '6q loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 64 57 39
6Q LOSS MUTATED 1 14 4
6Q LOSS WILD-TYPE 63 43 35

Figure S16.  Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'6q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 2e-05 (Fisher's exact test), Q value = 0.01

Table S17.  Gene #46: '6q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 65 53 18 24
6Q LOSS MUTATED 1 16 1 1
6Q LOSS WILD-TYPE 64 37 17 23

Figure S17.  Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'6q loss' versus 'MIRSEQ_MATURE_CNMF'

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

Table S18.  Gene #46: '6q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 37 66 57
6Q LOSS MUTATED 1 17 1
6Q LOSS WILD-TYPE 36 49 56

Figure S18.  Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'6q loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

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

Table S19.  Gene #46: '6q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 68 53 39
6Q LOSS MUTATED 1 16 2
6Q LOSS WILD-TYPE 67 37 37

Figure S19.  Get High-res Image Gene #46: '6q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'11p loss' versus 'CN_CNMF'

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

Table S20.  Gene #52: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 15 24 55 43 23
11P LOSS MUTATED 5 5 1 31 11
11P LOSS WILD-TYPE 10 19 54 12 12

Figure S20.  Get High-res Image Gene #52: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

'11p loss' versus 'MRNASEQ_CNMF'

P value = 0.00012 (Fisher's exact test), Q value = 0.062

Table S21.  Gene #52: '11p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 33 63 43 21
11P LOSS MUTATED 12 10 25 6
11P LOSS WILD-TYPE 21 53 18 15

Figure S21.  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 S22.  Gene #52: '11p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 33 63 43 21
11P LOSS MUTATED 11 8 28 6
11P LOSS WILD-TYPE 22 55 15 15

Figure S22.  Get High-res Image Gene #52: '11p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'11p loss' versus 'MIRSEQ_CNMF'

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

Table S23.  Gene #52: '11p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 64 57 39
11P LOSS MUTATED 34 8 11
11P LOSS WILD-TYPE 30 49 28

Figure S23.  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 S24.  Gene #52: '11p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 65 53 18 24
11P LOSS MUTATED 37 5 5 6
11P LOSS WILD-TYPE 28 48 13 18

Figure S24.  Get High-res Image Gene #52: '11p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'11p loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 5e-05 (Fisher's exact test), Q value = 0.026

Table S25.  Gene #52: '11p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 37 66 57
11P LOSS MUTATED 22 11 20
11P LOSS WILD-TYPE 15 55 37

Figure S25.  Get High-res Image Gene #52: '11p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'11p loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

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

Table S26.  Gene #52: '11p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 68 53 39
11P LOSS MUTATED 36 7 10
11P LOSS WILD-TYPE 32 46 29

Figure S26.  Get High-res Image Gene #52: '11p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'11q loss' versus 'CN_CNMF'

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

Table S27.  Gene #53: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 15 24 55 43 23
11Q LOSS MUTATED 2 3 1 31 2
11Q LOSS WILD-TYPE 13 21 54 12 21

Figure S27.  Get High-res Image Gene #53: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

'11q loss' versus 'MRNASEQ_CNMF'

P value = 0.00042 (Fisher's exact test), Q value = 0.21

Table S28.  Gene #53: '11q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 33 63 43 21
11Q LOSS MUTATED 8 7 20 4
11Q LOSS WILD-TYPE 25 56 23 17

Figure S28.  Get High-res Image Gene #53: '11q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'11q loss' versus 'MIRSEQ_CNMF'

P value = 0.00036 (Fisher's exact test), Q value = 0.18

Table S29.  Gene #53: '11q loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 64 57 39
11Q LOSS MUTATED 25 5 9
11Q LOSS WILD-TYPE 39 52 30

Figure S29.  Get High-res Image Gene #53: '11q loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'11q loss' versus 'MIRSEQ_MATURE_CNMF'

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

Table S30.  Gene #53: '11q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 37 66 57
11Q LOSS MUTATED 18 9 12
11Q LOSS WILD-TYPE 19 57 45

Figure S30.  Get High-res Image Gene #53: '11q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'11q loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.00033 (Fisher's exact test), Q value = 0.17

Table S31.  Gene #53: '11q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 68 53 39
11Q LOSS MUTATED 27 5 7
11Q LOSS WILD-TYPE 41 48 32

Figure S31.  Get High-res Image Gene #53: '11q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'17p loss' versus 'CN_CNMF'

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

Table S32.  Gene #59: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 15 24 55 43 23
17P LOSS MUTATED 5 4 28 22 2
17P LOSS WILD-TYPE 10 20 27 21 21

Figure S32.  Get High-res Image Gene #59: '17p loss' versus Molecular Subtype #1: 'CN_CNMF'

'22q loss' versus 'CN_CNMF'

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

Table S33.  Gene #66: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 15 24 55 43 23
22Q LOSS MUTATED 6 4 35 10 2
22Q LOSS WILD-TYPE 9 20 20 33 21

Figure S33.  Get High-res Image Gene #66: '22q 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 = 160

  • 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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