Correlation between copy number variations of arm-level result and molecular subtypes
Skin Cutaneous Melanoma (Metastatic)
15 July 2014  |  analyses__2014_07_15
Maintainer Information
Citation Information
doi:10.7908/C1QV3K9D
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/C1QV3K9D
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 79 arm-level events and 10 molecular subtypes across 299 patients, 30 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 1q gain cnv correlated to 'CN_CNMF'.

  • 2p gain cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

  • 2q gain cnv correlated to 'CN_CNMF',  'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_CHIERARCHICAL', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 6p gain cnv correlated to 'CN_CNMF'.

  • 7p gain cnv correlated to 'CN_CNMF'.

  • 7q gain cnv correlated to 'CN_CNMF'.

  • 8p gain cnv correlated to 'CN_CNMF'.

  • 8q gain cnv correlated to 'CN_CNMF'.

  • 11q gain cnv correlated to 'MIRSEQ_CHIERARCHICAL'.

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

  • 15q gain cnv correlated to 'CN_CNMF'.

  • 16p gain cnv correlated to 'MRNASEQ_CNMF'.

  • 16q gain cnv correlated to 'MRNASEQ_CNMF'.

  • 20p gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.

  • 20q gain cnv correlated to 'CN_CNMF'.

  • 6q loss cnv correlated to 'CN_CNMF'.

  • 10p loss cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.

  • 10q loss cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.

  • 11p loss cnv correlated to 'CN_CNMF'.

  • 11q loss cnv correlated to 'CN_CNMF'.

  • 13q loss cnv correlated to 'CN_CNMF'.

  • 14q loss cnv correlated to 'CN_CNMF'.

  • xq 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 79 arm-level events and 10 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 30 significant findings detected.

Clinical
Features 		CN
CNMF 		METHLYATION
CNMF 		RPPA
CNMF 		RPPA
CHIERARCHICAL 		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 Fisher's exact test Fisher's exact test
2q gain 56 (19%) 243 2e-05
(0.0154) 		0.862
(1.00) 		0.761
(1.00) 		0.533
(1.00) 		0.00083
(0.626) 		7e-05
(0.0535) 		0.0576
(1.00) 		0.00024
(0.182) 		0.00915
(1.00) 		5e-05
(0.0384)
13q gain 75 (25%) 224 1e-05
(0.00788) 		1e-05
(0.00788) 		0.503
(1.00) 		0.179
(1.00) 		0.00131
(0.98) 		0.0104
(1.00) 		0.925
(1.00) 		0.853
(1.00) 		0.642
(1.00) 		0.882
(1.00)
20p gain 124 (41%) 175 1e-05
(0.00788) 		0.0188
(1.00) 		0.842
(1.00) 		0.985
(1.00) 		0.00014
(0.107) 		0.00086
(0.647) 		0.32
(1.00) 		0.144
(1.00) 		0.0946
(1.00) 		0.188
(1.00)
10p loss 167 (56%) 132 1e-05
(0.00788) 		0.0318
(1.00) 		0.896
(1.00) 		0.454
(1.00) 		5e-05
(0.0384) 		0.001
(0.75) 		0.36
(1.00) 		0.105
(1.00) 		0.57
(1.00) 		0.781
(1.00)
10q loss 185 (62%) 114 1e-05
(0.00788) 		0.0318
(1.00) 		0.918
(1.00) 		0.201
(1.00) 		4e-05
(0.0308) 		0.00046
(0.348) 		0.178
(1.00) 		0.0152
(1.00) 		0.746
(1.00) 		0.935
(1.00)
1q gain 136 (45%) 163 1e-05
(0.00788) 		0.0855
(1.00) 		0.285
(1.00) 		0.561
(1.00) 		0.0357
(1.00) 		0.0691
(1.00) 		0.224
(1.00) 		0.0447
(1.00) 		0.142
(1.00) 		0.17
(1.00)
2p gain 58 (19%) 241 0.00036
(0.273) 		0.535
(1.00) 		0.639
(1.00) 		0.89
(1.00) 		0.0111
(1.00) 		0.00031
(0.235) 		0.0836
(1.00) 		0.00118
(0.884) 		0.032
(1.00) 		0.00056
(0.423)
6p gain 117 (39%) 182 1e-05
(0.00788) 		0.00415
(1.00) 		0.845
(1.00) 		0.168
(1.00) 		0.634
(1.00) 		0.116
(1.00) 		0.0245
(1.00) 		0.00261
(1.00) 		0.0137
(1.00) 		0.00466
(1.00)
7p gain 161 (54%) 138 1e-05
(0.00788) 		0.587
(1.00) 		0.457
(1.00) 		0.374
(1.00) 		0.0299
(1.00) 		0.175
(1.00) 		0.488
(1.00) 		0.777
(1.00) 		0.581
(1.00) 		0.414
(1.00)
7q gain 159 (53%) 140 1e-05
(0.00788) 		0.385
(1.00) 		0.691
(1.00) 		0.517
(1.00) 		0.00577
(1.00) 		0.0225
(1.00) 		0.672
(1.00) 		0.515
(1.00) 		0.777
(1.00) 		0.407
(1.00)
8p gain 99 (33%) 200 5e-05
(0.0384) 		0.0943
(1.00) 		0.609
(1.00) 		0.843
(1.00) 		0.0164
(1.00) 		0.743
(1.00) 		0.452
(1.00) 		0.962
(1.00) 		0.058
(1.00) 		0.481
(1.00)
8q gain 141 (47%) 158 2e-05
(0.0154) 		0.00332
(1.00) 		0.651
(1.00) 		0.851
(1.00) 		0.00229
(1.00) 		0.589
(1.00) 		0.48
(1.00) 		0.738
(1.00) 		0.0944
(1.00) 		0.182
(1.00)
11q gain 26 (9%) 273 0.00054
(0.408) 		0.281
(1.00) 		0.0766
(1.00) 		0.0873
(1.00) 		0.00433
(1.00) 		0.257
(1.00) 		0.0596
(1.00) 		6e-05
(0.0459) 		0.196
(1.00) 		0.0222
(1.00)
15q gain 69 (23%) 230 1e-05
(0.00788) 		0.324
(1.00) 		0.845
(1.00) 		0.797
(1.00) 		0.0124
(1.00) 		0.0692
(1.00) 		0.211
(1.00) 		0.0364
(1.00) 		0.499
(1.00) 		0.023
(1.00)
16p gain 41 (14%) 258 0.0908
(1.00) 		0.0195
(1.00) 		1
(1.00) 		0.79
(1.00) 		0.00012
(0.0914) 		0.0103
(1.00) 		0.191
(1.00) 		0.263
(1.00) 		0.0959
(1.00) 		0.079
(1.00)
16q gain 35 (12%) 264 0.275
(1.00) 		0.0563
(1.00) 		0.266
(1.00) 		0.805
(1.00) 		0.0001
(0.0763) 		0.00598
(1.00) 		0.412
(1.00) 		0.0988
(1.00) 		0.162
(1.00) 		0.0632
(1.00)
20q gain 147 (49%) 152 1e-05
(0.00788) 		0.0381
(1.00) 		0.94
(1.00) 		0.974
(1.00) 		0.00229
(1.00) 		0.0154
(1.00) 		0.646
(1.00) 		0.176
(1.00) 		0.252
(1.00) 		0.369
(1.00)
6q loss 146 (49%) 153 1e-05
(0.00788) 		0.062
(1.00) 		0.992
(1.00) 		0.361
(1.00) 		0.0107
(1.00) 		0.039
(1.00) 		0.521
(1.00) 		0.555
(1.00) 		0.788
(1.00) 		0.102
(1.00)
11p loss 102 (34%) 197 1e-05
(0.00788) 		0.0566
(1.00) 		0.585
(1.00) 		0.509
(1.00) 		0.306
(1.00) 		0.085
(1.00) 		0.654
(1.00) 		0.138
(1.00) 		0.524
(1.00) 		0.425
(1.00)
11q loss 117 (39%) 182 1e-05
(0.00788) 		0.286
(1.00) 		0.962
(1.00) 		0.762
(1.00) 		0.115
(1.00) 		0.164
(1.00) 		0.639
(1.00) 		0.455
(1.00) 		1
(1.00) 		0.266
(1.00)
13q loss 65 (22%) 234 1e-05
(0.00788) 		0.00226
(1.00) 		0.0402
(1.00) 		0.378
(1.00) 		0.922
(1.00) 		0.163
(1.00) 		0.831
(1.00) 		0.64
(1.00) 		0.818
(1.00) 		0.274
(1.00)
14q loss 93 (31%) 206 1e-05
(0.00788) 		0.65
(1.00) 		0.411
(1.00) 		0.271
(1.00) 		0.00098
(0.736) 		0.351
(1.00) 		0.0229
(1.00) 		0.937
(1.00) 		0.0167
(1.00) 		0.273
(1.00)
xq loss 74 (25%) 225 0.0241
(1.00) 		4e-05
(0.0308) 		0.304
(1.00) 		0.0859
(1.00) 		0.0018
(1.00) 		0.0318
(1.00) 		0.0419
(1.00) 		0.199
(1.00) 		0.228
(1.00) 		0.709
(1.00)
1p gain 70 (23%) 229 0.0961
(1.00) 		0.955
(1.00) 		0.898
(1.00) 		0.92
(1.00) 		0.204
(1.00) 		0.344
(1.00) 		0.649
(1.00) 		0.955
(1.00) 		0.851
(1.00) 		0.663
(1.00)
3p gain 48 (16%) 251 0.661
(1.00) 		0.117
(1.00) 		0.0378
(1.00) 		0.0207
(1.00) 		0.138
(1.00) 		0.736
(1.00) 		0.622
(1.00) 		0.109
(1.00) 		0.57
(1.00) 		0.636
(1.00)
3q gain 58 (19%) 241 0.272
(1.00) 		0.347
(1.00) 		0.0191
(1.00) 		0.0448
(1.00) 		0.00803
(1.00) 		0.445
(1.00) 		0.34
(1.00) 		0.229
(1.00) 		0.562
(1.00) 		1
(1.00)
4p gain 44 (15%) 255 0.00957
(1.00) 		0.158
(1.00) 		0.309
(1.00) 		0.857
(1.00) 		0.686
(1.00) 		0.362
(1.00) 		0.421
(1.00) 		0.0233
(1.00) 		0.203
(1.00) 		0.217
(1.00)
4q gain 37 (12%) 262 0.0193
(1.00) 		0.0523
(1.00) 		0.264
(1.00) 		0.934
(1.00) 		0.74
(1.00) 		0.471
(1.00) 		0.579
(1.00) 		0.0211
(1.00) 		0.476
(1.00) 		0.363
(1.00)
5p gain 58 (19%) 241 0.0135
(1.00) 		0.369
(1.00) 		0.893
(1.00) 		0.542
(1.00) 		0.221
(1.00) 		0.879
(1.00) 		0.141
(1.00) 		0.285
(1.00) 		0.148
(1.00) 		0.564
(1.00)
5q gain 36 (12%) 263 0.0475
(1.00) 		0.623
(1.00) 		0.412
(1.00) 		0.239
(1.00) 		0.753
(1.00) 		0.678
(1.00) 		0.519
(1.00) 		0.504
(1.00) 		0.0234
(1.00) 		0.148
(1.00)
6q gain 39 (13%) 260 0.0215
(1.00) 		0.167
(1.00) 		0.919
(1.00) 		0.247
(1.00) 		0.953
(1.00) 		0.811
(1.00) 		0.846
(1.00) 		0.189
(1.00) 		0.536
(1.00) 		0.25
(1.00)
9p gain 15 (5%) 284 0.345
(1.00) 		0.273
(1.00) 		0.376
(1.00) 		0.838
(1.00) 		0.399
(1.00) 		0.87
(1.00) 		0.973
(1.00) 		0.552
(1.00) 		0.946
(1.00) 		0.427
(1.00)
9q gain 20 (7%) 279 0.17
(1.00) 		0.877
(1.00) 		0.135
(1.00) 		0.928
(1.00) 		0.477
(1.00) 		0.897
(1.00) 		0.875
(1.00) 		0.896
(1.00) 		0.865
(1.00) 		0.636
(1.00)
10p gain 10 (3%) 289 0.889
(1.00) 		0.851
(1.00) 		0.869
(1.00) 		0.548
(1.00) 		0.85
(1.00) 		0.312
(1.00) 		0.22
(1.00) 		0.253
(1.00) 		0.84
(1.00) 		0.518
(1.00)
11p gain 30 (10%) 269 0.0135
(1.00) 		0.371
(1.00) 		0.0851
(1.00) 		0.188
(1.00) 		0.00181
(1.00) 		0.309
(1.00) 		0.117
(1.00) 		0.00281
(1.00) 		0.148
(1.00) 		0.0447
(1.00)
12p gain 50 (17%) 249 0.00416
(1.00) 		0.327
(1.00) 		0.374
(1.00) 		0.366
(1.00) 		0.0215
(1.00) 		0.129
(1.00) 		0.942
(1.00) 		0.446
(1.00) 		0.923
(1.00) 		0.974
(1.00)
12q gain 33 (11%) 266 0.0635
(1.00) 		0.69
(1.00) 		0.617
(1.00) 		0.0584
(1.00) 		0.536
(1.00) 		0.185
(1.00) 		0.887
(1.00) 		0.269
(1.00) 		0.613
(1.00) 		0.823
(1.00)
14q gain 32 (11%) 267 0.31
(1.00) 		0.115
(1.00) 		0.495
(1.00) 		0.197
(1.00) 		0.813
(1.00) 		0.368
(1.00) 		0.897
(1.00) 		0.61
(1.00) 		0.643
(1.00) 		0.976
(1.00)
17p gain 34 (11%) 265 0.00697
(1.00) 		0.00925
(1.00) 		0.601
(1.00) 		0.483
(1.00) 		0.196
(1.00) 		0.261
(1.00) 		0.627
(1.00) 		0.385
(1.00) 		0.657
(1.00) 		0.409
(1.00)
17q gain 59 (20%) 240 0.0627
(1.00) 		0.0781
(1.00) 		0.0815
(1.00) 		0.182
(1.00) 		0.672
(1.00) 		0.978
(1.00) 		0.225
(1.00) 		0.422
(1.00) 		0.0599
(1.00) 		0.00556
(1.00)
18p gain 48 (16%) 251 0.0429
(1.00) 		0.812
(1.00) 		0.202
(1.00) 		0.405
(1.00) 		0.296
(1.00) 		0.33
(1.00) 		0.803
(1.00) 		0.723
(1.00) 		0.344
(1.00) 		0.478
(1.00)
18q gain 39 (13%) 260 0.0216
(1.00) 		0.928
(1.00) 		0.402
(1.00) 		0.6
(1.00) 		0.676
(1.00) 		1
(1.00) 		0.65
(1.00) 		0.815
(1.00) 		0.444
(1.00) 		0.816
(1.00)
19p gain 43 (14%) 256 0.253
(1.00) 		0.0807
(1.00) 		0.251
(1.00) 		0.798
(1.00) 		0.00576
(1.00) 		0.0739
(1.00) 		0.782
(1.00) 		0.71
(1.00) 		0.954
(1.00) 		0.63
(1.00)
19q gain 44 (15%) 255 0.129
(1.00) 		0.0106
(1.00) 		0.296
(1.00) 		1
(1.00) 		0.00084
(0.633) 		0.0668
(1.00) 		0.723
(1.00) 		0.607
(1.00) 		0.653
(1.00) 		0.684
(1.00)
21q gain 54 (18%) 245 0.432
(1.00) 		0.0854
(1.00) 		0.889
(1.00) 		0.53
(1.00) 		0.417
(1.00) 		0.119
(1.00) 		0.449
(1.00) 		0.931
(1.00) 		0.731
(1.00) 		0.889
(1.00)
22q gain 107 (36%) 192 0.00511
(1.00) 		0.342
(1.00) 		0.895
(1.00) 		0.944
(1.00) 		0.154
(1.00) 		0.0409
(1.00) 		0.806
(1.00) 		0.372
(1.00) 		0.467
(1.00) 		0.744
(1.00)
xq gain 32 (11%) 267 0.00786
(1.00) 		0.036
(1.00) 		0.689
(1.00) 		0.881
(1.00) 		0.16
(1.00) 		0.129
(1.00) 		0.825
(1.00) 		0.439
(1.00) 		0.809
(1.00) 		0.621
(1.00)
1p loss 36 (12%) 263 0.244
(1.00) 		0.003
(1.00) 		0.386
(1.00) 		0.0993
(1.00) 		0.0288
(1.00) 		0.0674
(1.00) 		0.171
(1.00) 		0.596
(1.00) 		0.487
(1.00) 		0.561
(1.00)
1q loss 20 (7%) 279 0.102
(1.00) 		0.412
(1.00) 		0.969
(1.00) 		0.461
(1.00) 		0.1
(1.00) 		0.647
(1.00) 		0.733
(1.00) 		0.195
(1.00) 		0.382
(1.00) 		0.402
(1.00)
2p loss 38 (13%) 261 0.191
(1.00) 		0.279
(1.00) 		0.0472
(1.00) 		0.0151
(1.00) 		0.38
(1.00) 		0.102
(1.00) 		0.00209
(1.00) 		0.0133
(1.00) 		0.00943
(1.00) 		0.0382
(1.00)
2q loss 39 (13%) 260 0.0347
(1.00) 		0.0602
(1.00) 		0.0117
(1.00) 		0.00178
(1.00) 		0.161
(1.00) 		0.272
(1.00) 		0.00715
(1.00) 		0.0289
(1.00) 		0.00679
(1.00) 		0.0629
(1.00)
3p loss 48 (16%) 251 0.269
(1.00) 		0.661
(1.00) 		0.483
(1.00) 		0.32
(1.00) 		0.0287
(1.00) 		0.245
(1.00) 		0.0192
(1.00) 		0.495
(1.00) 		0.031
(1.00) 		0.0865
(1.00)
3q loss 37 (12%) 262 0.313
(1.00) 		0.274
(1.00) 		0.382
(1.00) 		0.35
(1.00) 		0.173
(1.00) 		0.361
(1.00) 		0.145
(1.00) 		0.482
(1.00) 		0.166
(1.00) 		0.686
(1.00)
4p loss 64 (21%) 235 0.776
(1.00) 		0.105
(1.00) 		0.353
(1.00) 		0.969
(1.00) 		0.289
(1.00) 		0.182
(1.00) 		0.671
(1.00) 		0.0132
(1.00) 		0.318
(1.00) 		0.142
(1.00)
4q loss 66 (22%) 233 0.404
(1.00) 		0.0303
(1.00) 		0.482
(1.00) 		0.751
(1.00) 		0.125
(1.00) 		0.197
(1.00) 		0.576
(1.00) 		0.00379
(1.00) 		0.1
(1.00) 		0.0158
(1.00)
5p loss 66 (22%) 233 0.217
(1.00) 		0.467
(1.00) 		0.8
(1.00) 		0.833
(1.00) 		0.937
(1.00) 		0.87
(1.00) 		0.753
(1.00) 		0.714
(1.00) 		0.693
(1.00) 		0.655
(1.00)
5q loss 84 (28%) 215 0.0171
(1.00) 		0.108
(1.00) 		0.439
(1.00) 		0.287
(1.00) 		0.781
(1.00) 		0.124
(1.00) 		0.979
(1.00) 		0.876
(1.00) 		0.774
(1.00) 		0.698
(1.00)
6p loss 56 (19%) 243 0.00212
(1.00) 		0.706
(1.00) 		0.903
(1.00) 		0.295
(1.00) 		0.0121
(1.00) 		0.105
(1.00) 		0.0538
(1.00) 		0.0292
(1.00) 		0.0908
(1.00) 		0.0499
(1.00)
7p loss 16 (5%) 283 0.8
(1.00) 		0.00384
(1.00) 		0.0942
(1.00) 		0.559
(1.00) 		0.713
(1.00) 		0.871
(1.00) 		0.64
(1.00) 		0.881
(1.00) 		0.558
(1.00) 		0.857
(1.00)
7q loss 15 (5%) 284 0.775
(1.00) 		0.00248
(1.00) 		0.34
(1.00) 		0.436
(1.00) 		0.354
(1.00) 		0.5
(1.00) 		0.777
(1.00) 		0.78
(1.00) 		0.248
(1.00) 		0.772
(1.00)
8p loss 53 (18%) 246 0.712
(1.00) 		0.621
(1.00) 		0.0873
(1.00) 		0.394
(1.00) 		0.316
(1.00) 		0.954
(1.00) 		0.266
(1.00) 		0.057
(1.00) 		0.388
(1.00) 		0.507
(1.00)
8q loss 21 (7%) 278 0.373
(1.00) 		0.11
(1.00) 		0.315
(1.00) 		0.536
(1.00) 		0.467
(1.00) 		0.811
(1.00) 		0.225
(1.00) 		0.627
(1.00) 		0.213
(1.00) 		0.235
(1.00)
9p loss 197 (66%) 102 0.0301
(1.00) 		0.0503
(1.00) 		0.646
(1.00) 		0.45
(1.00) 		0.00285
(1.00) 		0.0116
(1.00) 		0.0284
(1.00) 		0.157
(1.00) 		0.882
(1.00) 		0.311
(1.00)
9q loss 154 (52%) 145 0.855
(1.00) 		0.0447
(1.00) 		0.973
(1.00) 		0.109
(1.00) 		0.0352
(1.00) 		0.584
(1.00) 		0.0626
(1.00) 		0.0159
(1.00) 		0.64
(1.00) 		0.622
(1.00)
12p loss 46 (15%) 253 0.0145
(1.00) 		0.0314
(1.00) 		0.767
(1.00) 		0.682
(1.00) 		0.0489
(1.00) 		0.899
(1.00) 		0.407
(1.00) 		0.173
(1.00) 		0.483
(1.00) 		0.76
(1.00)
12q loss 52 (17%) 247 0.00405
(1.00) 		0.043
(1.00) 		0.992
(1.00) 		0.923
(1.00) 		0.0575
(1.00) 		0.392
(1.00) 		0.329
(1.00) 		0.438
(1.00) 		0.834
(1.00) 		0.94
(1.00)
15q loss 42 (14%) 257 0.00183
(1.00) 		0.143
(1.00) 		0.127
(1.00) 		0.0592
(1.00) 		0.297
(1.00) 		0.504
(1.00) 		0.82
(1.00) 		0.705
(1.00) 		0.739
(1.00) 		0.221
(1.00)
16p loss 58 (19%) 241 0.113
(1.00) 		0.0677
(1.00) 		0.0461
(1.00) 		0.52
(1.00) 		0.0196
(1.00) 		0.506
(1.00) 		0.217
(1.00) 		0.306
(1.00) 		0.162
(1.00) 		0.307
(1.00)
16q loss 87 (29%) 212 0.0531
(1.00) 		0.169
(1.00) 		0.0112
(1.00) 		0.849
(1.00) 		0.0194
(1.00) 		0.309
(1.00) 		0.137
(1.00) 		0.0937
(1.00) 		0.156
(1.00) 		0.114
(1.00)
17p loss 101 (34%) 198 0.718
(1.00) 		0.177
(1.00) 		0.756
(1.00) 		0.486
(1.00) 		0.29
(1.00) 		0.454
(1.00) 		0.759
(1.00) 		0.46
(1.00) 		0.744
(1.00) 		0.709
(1.00)
17q loss 50 (17%) 249 0.617
(1.00) 		0.592
(1.00) 		0.174
(1.00) 		0.405
(1.00) 		0.855
(1.00) 		1
(1.00) 		0.526
(1.00) 		0.661
(1.00) 		0.847
(1.00) 		0.687
(1.00)
18p loss 86 (29%) 213 0.302
(1.00) 		0.358
(1.00) 		0.379
(1.00) 		0.513
(1.00) 		0.0183
(1.00) 		0.288
(1.00) 		0.055
(1.00) 		0.424
(1.00) 		0.8
(1.00) 		0.311
(1.00)
18q loss 82 (27%) 217 0.0861
(1.00) 		0.356
(1.00) 		0.397
(1.00) 		0.525
(1.00) 		0.438
(1.00) 		0.529
(1.00) 		0.347
(1.00) 		0.181
(1.00) 		0.985
(1.00) 		0.507
(1.00)
19p loss 62 (21%) 237 0.00411
(1.00) 		0.104
(1.00) 		0.785
(1.00) 		0.088
(1.00) 		0.0871
(1.00) 		0.192
(1.00) 		0.444
(1.00) 		0.575
(1.00) 		0.206
(1.00) 		0.489
(1.00)
19q loss 60 (20%) 239 0.00626
(1.00) 		0.0411
(1.00) 		0.978
(1.00) 		0.0836
(1.00) 		0.261
(1.00) 		0.201
(1.00) 		0.832
(1.00) 		0.726
(1.00) 		0.488
(1.00) 		0.396
(1.00)
20p loss 18 (6%) 281 0.447
(1.00) 		0.953
(1.00) 		0.235
(1.00) 		0.772
(1.00) 		0.752
(1.00) 		0.0816
(1.00) 		0.146
(1.00) 		0.134
(1.00) 		0.465
(1.00) 		0.278
(1.00)
20q loss 7 (2%) 292 0.5
(1.00) 		0.492
(1.00) 		0.235
(1.00) 		0.0138
(1.00) 		0.288
(1.00) 		0.95
(1.00) 		0.798
(1.00) 		0.711
(1.00)
21q loss 58 (19%) 241 0.143
(1.00) 		0.413
(1.00) 		0.47
(1.00) 		0.932
(1.00) 		0.509
(1.00) 		0.895
(1.00) 		0.0635
(1.00) 		0.516
(1.00) 		0.0429
(1.00) 		0.22
(1.00)
22q loss 32 (11%) 267 0.181
(1.00) 		0.443
(1.00) 		0.955
(1.00) 		0.939
(1.00) 		0.686
(1.00) 		0.291
(1.00) 		0.767
(1.00) 		0.725
(1.00) 		0.942
(1.00) 		0.982
(1.00)
'1q gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

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

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
1Q GAIN MUTATED 68 10 30 28
1Q GAIN WILD-TYPE 17 47 21 78

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

'2p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00031 (Fisher's exact test), Q value = 0.24

Table S2.  Gene #3: '2p gain' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 70 178 50
2P GAIN MUTATED 14 24 20
2P GAIN WILD-TYPE 56 154 30

Figure S2.  Get High-res Image Gene #3: '2p gain' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'2q gain' versus 'CN_CNMF'

P value = 2e-05 (Fisher's exact test), Q value = 0.015

Table S3.  Gene #4: '2q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
2Q GAIN MUTATED 13 9 23 11
2Q GAIN WILD-TYPE 72 48 28 95

Figure S3.  Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #1: 'CN_CNMF'

'2q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 7e-05 (Fisher's exact test), Q value = 0.053

Table S4.  Gene #4: '2q gain' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 70 178 50
2Q GAIN MUTATED 12 23 21
2Q GAIN WILD-TYPE 58 155 29

Figure S4.  Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'2q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00024 (Fisher's exact test), Q value = 0.18

Table S5.  Gene #4: '2q gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 76 80 36 95
2Q GAIN MUTATED 7 27 10 12
2Q GAIN WILD-TYPE 69 53 26 83

Figure S5.  Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

'2q gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 5e-05 (Fisher's exact test), Q value = 0.038

Table S6.  Gene #4: '2q gain' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 118 89 55 25
2Q GAIN MUTATED 16 29 3 8
2Q GAIN WILD-TYPE 102 60 52 17

Figure S6.  Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

'6p gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S7.  Gene #11: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
6P GAIN MUTATED 49 29 6 33
6P GAIN WILD-TYPE 36 28 45 73

Figure S7.  Get High-res Image Gene #11: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

'7p gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S8.  Gene #13: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
7P GAIN MUTATED 44 35 41 41
7P GAIN WILD-TYPE 41 22 10 65

Figure S8.  Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

'7q gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S9.  Gene #14: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
7Q GAIN MUTATED 39 33 43 44
7Q GAIN WILD-TYPE 46 24 8 62

Figure S9.  Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

'8p gain' versus 'CN_CNMF'

P value = 5e-05 (Fisher's exact test), Q value = 0.038

Table S10.  Gene #15: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
8P GAIN MUTATED 27 29 24 19
8P GAIN WILD-TYPE 58 28 27 87

Figure S10.  Get High-res Image Gene #15: '8p gain' versus Molecular Subtype #1: 'CN_CNMF'

'8q gain' versus 'CN_CNMF'

P value = 2e-05 (Fisher's exact test), Q value = 0.015

Table S11.  Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
8Q GAIN MUTATED 49 36 28 28
8Q GAIN WILD-TYPE 36 21 23 78

Figure S11.  Get High-res Image Gene #16: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

'11q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 6e-05 (Fisher's exact test), Q value = 0.046

Table S12.  Gene #21: '11q gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 76 80 36 95
11Q GAIN MUTATED 0 13 0 11
11Q GAIN WILD-TYPE 76 67 36 84

Figure S12.  Get High-res Image Gene #21: '11q gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

'13q gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S13.  Gene #24: '13q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
13Q GAIN MUTATED 26 31 7 11
13Q GAIN WILD-TYPE 59 26 44 95

Figure S13.  Get High-res Image Gene #24: '13q gain' versus Molecular Subtype #1: 'CN_CNMF'

'13q gain' versus 'METHLYATION_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S14.  Gene #24: '13q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 112 111 76
13Q GAIN MUTATED 26 15 34
13Q GAIN WILD-TYPE 86 96 42

Figure S14.  Get High-res Image Gene #24: '13q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'15q gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S15.  Gene #26: '15q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
15Q GAIN MUTATED 11 11 27 20
15Q GAIN WILD-TYPE 74 46 24 86

Figure S15.  Get High-res Image Gene #26: '15q gain' versus Molecular Subtype #1: 'CN_CNMF'

'16p gain' versus 'MRNASEQ_CNMF'

P value = 0.00012 (Fisher's exact test), Q value = 0.091

Table S16.  Gene #27: '16p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 99 87 112
16P GAIN MUTATED 25 11 5
16P GAIN WILD-TYPE 74 76 107

Figure S16.  Get High-res Image Gene #27: '16p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'16q gain' versus 'MRNASEQ_CNMF'

P value = 1e-04 (Fisher's exact test), Q value = 0.076

Table S17.  Gene #28: '16q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 99 87 112
16Q GAIN MUTATED 23 7 5
16Q GAIN WILD-TYPE 76 80 107

Figure S17.  Get High-res Image Gene #28: '16q gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'20p gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S18.  Gene #35: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
20P GAIN MUTATED 38 31 32 23
20P GAIN WILD-TYPE 47 26 19 83

Figure S18.  Get High-res Image Gene #35: '20p gain' versus Molecular Subtype #1: 'CN_CNMF'

'20p gain' versus 'MRNASEQ_CNMF'

P value = 0.00014 (Fisher's exact test), Q value = 0.11

Table S19.  Gene #35: '20p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 99 87 112
20P GAIN MUTATED 58 29 37
20P GAIN WILD-TYPE 41 58 75

Figure S19.  Get High-res Image Gene #35: '20p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'20q gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S20.  Gene #36: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
20Q GAIN MUTATED 49 33 35 30
20Q GAIN WILD-TYPE 36 24 16 76

Figure S20.  Get High-res Image Gene #36: '20q gain' versus Molecular Subtype #1: 'CN_CNMF'

'6q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S21.  Gene #51: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
6Q LOSS MUTATED 42 36 37 31
6Q LOSS WILD-TYPE 43 21 14 75

Figure S21.  Get High-res Image Gene #51: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S22.  Gene #58: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
10P LOSS MUTATED 49 38 44 36
10P LOSS WILD-TYPE 36 19 7 70

Figure S22.  Get High-res Image Gene #58: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'MRNASEQ_CNMF'

P value = 5e-05 (Fisher's exact test), Q value = 0.038

Table S23.  Gene #58: '10p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 99 87 112
10P LOSS MUTATED 73 37 57
10P LOSS WILD-TYPE 26 50 55

Figure S23.  Get High-res Image Gene #58: '10p loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'10q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S24.  Gene #59: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
10Q LOSS MUTATED 51 42 47 45
10Q LOSS WILD-TYPE 34 15 4 61

Figure S24.  Get High-res Image Gene #59: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

'10q loss' versus 'MRNASEQ_CNMF'

P value = 4e-05 (Fisher's exact test), Q value = 0.031

Table S25.  Gene #59: '10q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 99 87 112
10Q LOSS MUTATED 80 44 61
10Q LOSS WILD-TYPE 19 43 51

Figure S25.  Get High-res Image Gene #59: '10q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'11p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S26.  Gene #60: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
11P LOSS MUTATED 43 12 25 22
11P LOSS WILD-TYPE 42 45 26 84

Figure S26.  Get High-res Image Gene #60: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

'11q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S27.  Gene #61: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
11Q LOSS MUTATED 51 15 27 24
11Q LOSS WILD-TYPE 34 42 24 82

Figure S27.  Get High-res Image Gene #61: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

'13q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S28.  Gene #64: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
13Q LOSS MUTATED 17 5 25 18
13Q LOSS WILD-TYPE 68 52 26 88

Figure S28.  Get High-res Image Gene #64: '13q loss' versus Molecular Subtype #1: 'CN_CNMF'

'14q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0079

Table S29.  Gene #65: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 85 57 51 106
14Q LOSS MUTATED 20 31 25 17
14Q LOSS WILD-TYPE 65 26 26 89

Figure S29.  Get High-res Image Gene #65: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

'xq loss' versus 'METHLYATION_CNMF'

P value = 4e-05 (Fisher's exact test), Q value = 0.031

Table S30.  Gene #79: 'xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 112 111 76
XQ LOSS MUTATED 42 12 20
XQ LOSS WILD-TYPE 70 99 56

Figure S30.  Get High-res Image Gene #79: 'xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

Methods & Data
Input

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

  • Molecular subtypes file = SKCM-TM.transferedmergedcluster.txt

  • Number of patients = 299

  • Number of significantly arm-level cnvs = 79

  • Number of molecular subtypes = 10

  • 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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