Correlation between copy number variations of arm-level result and molecular subtypes
Rectum Adenocarcinoma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C13F4NQ8
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2015): Correlation between copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C13F4NQ8
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 80 arm-level events and 12 molecular subtypes across 165 patients, 54 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 2q gain cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

  • 3p gain cnv correlated to 'CN_CNMF'.

  • 3q gain cnv correlated to 'CN_CNMF'.

  • 5p gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 5q gain cnv correlated to 'CN_CNMF'.

  • 6p gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 6q gain cnv correlated to 'METHLYATION_CNMF'.

  • 7p gain cnv correlated to 'MRNA_CNMF',  'MRNA_CHIERARCHICAL',  'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 7q gain cnv correlated to 'MRNA_CHIERARCHICAL',  'CN_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 8p gain cnv correlated to 'CN_CNMF'.

  • 8q gain cnv correlated to 'CN_CNMF'.

  • 11p gain cnv correlated to 'CN_CNMF'.

  • 11q gain cnv correlated to 'CN_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 13q gain cnv correlated to 'CN_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CNMF'.

  • 16p gain cnv correlated to 'CN_CNMF'.

  • 16q gain cnv correlated to 'CN_CNMF' and 'MRNASEQ_CNMF'.

  • 17q gain cnv correlated to 'CN_CNMF'.

  • 20q gain cnv correlated to 'MRNA_CNMF',  'CN_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • xp gain cnv correlated to 'MRNA_CNMF'.

  • 2p loss cnv correlated to 'CN_CNMF'.

  • 3q loss cnv correlated to 'MIRSEQ_CHIERARCHICAL'.

  • 4p loss cnv correlated to 'CN_CNMF'.

  • 4q loss cnv correlated to 'CN_CNMF'.

  • 5q loss cnv correlated to 'MRNA_CHIERARCHICAL'.

  • 6q loss cnv correlated to 'MIRSEQ_MATURE_CNMF'.

  • 9q loss cnv correlated to 'MIRSEQ_CHIERARCHICAL'.

  • 11p loss cnv correlated to 'CN_CNMF'.

  • 11q loss cnv correlated to 'CN_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 15q loss cnv correlated to 'CN_CNMF'.

  • 18p loss cnv correlated to 'CN_CNMF'.

  • 18q loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 19q loss cnv correlated to 'MIRSEQ_CHIERARCHICAL'.

  • 22q loss cnv correlated to 'MIRSEQ_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 80 arm-level events and 12 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 54 significant findings detected.

Clinical
Features 		MRNA
CNMF 		MRNA
CHIERARCHICAL 		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 Fisher's exact test Fisher's exact test
7p gain 102 (62%) 63 0.00229
(0.0828) 		0.00261
(0.0835) 		1e-05
(0.0048) 		0.00316
(0.0979) 		0.486
(0.899) 		0.376
(0.826) 		0.00024
(0.023) 		2e-05
(0.0048) 		0.0415
(0.419) 		0.0979
(0.556) 		0.594
(0.929) 		0.814
(1.00)
7q gain 85 (52%) 80 0.046
(0.439) 		0.00813
(0.174) 		2e-05
(0.0048) 		0.14
(0.619) 		0.619
(0.941) 		0.948
(1.00) 		0.0045
(0.123) 		0.00213
(0.0828) 		0.501
(0.899) 		0.827
(1.00) 		0.856
(1.00) 		0.856
(1.00)
13q gain 113 (68%) 52 0.285
(0.749) 		0.376
(0.826) 		1e-05
(0.0048) 		0.0713
(0.5) 		0.836
(1.00) 		0.317
(0.777) 		0.00051
(0.035) 		0.00047
(0.035) 		0.00351
(0.102) 		0.066
(0.494) 		0.711
(0.984) 		0.476
(0.897)
11q gain 26 (16%) 139 0.237
(0.71) 		0.428
(0.87) 		0.00202
(0.0828) 		0.0195
(0.267) 		0.574
(0.917) 		0.302
(0.766) 		0.00249
(0.0828) 		0.00043
(0.035) 		0.0253
(0.311) 		0.589
(0.929) 		0.119
(0.596) 		0.158
(0.652)
20q gain 145 (88%) 20 0.0074
(0.169) 		0.161
(0.661) 		0.00072
(0.0432) 		0.233
(0.71) 		0.162
(0.662) 		0.338
(0.802) 		0.443
(0.881) 		0.00247
(0.0828) 		0.0447
(0.438) 		0.361
(0.826) 		0.362
(0.826) 		1
(1.00)
11q loss 30 (18%) 135 0.0554
(0.47) 		0.205
(0.71) 		0.00698
(0.169) 		0.026
(0.315) 		0.606
(0.934) 		0.385
(0.829) 		0.00839
(0.174) 		0.00838
(0.174) 		0.203
(0.71) 		0.377
(0.826) 		0.415
(0.866) 		0.668
(0.957)
5p gain 36 (22%) 129 0.204
(0.71) 		0.098
(0.556) 		0.00174
(0.0795) 		0.0985
(0.556) 		0.215
(0.71) 		0.689
(0.967) 		0.113
(0.582) 		6e-05
(0.0072) 		0.19
(0.703) 		0.923
(1.00) 		0.492
(0.899) 		0.627
(0.947)
6p gain 41 (25%) 124 0.335
(0.801) 		0.565
(0.912) 		0.0089
(0.178) 		0.00328
(0.0984) 		0.773
(1.00) 		0.257
(0.721) 		0.797
(1.00) 		0.467
(0.892) 		0.241
(0.715) 		0.298
(0.763) 		0.278
(0.745) 		0.811
(1.00)
16q gain 41 (25%) 124 0.0514
(0.457) 		0.594
(0.929) 		3e-05
(0.00576) 		0.233
(0.71) 		1
(1.00) 		0.67
(0.957) 		0.01
(0.193) 		0.107
(0.572) 		0.0197
(0.267) 		0.245
(0.717) 		0.233
(0.71) 		0.916
(1.00)
18q loss 138 (84%) 27 0.0201
(0.267) 		0.174
(0.672) 		6e-05
(0.0072) 		0.012
(0.218) 		0.796
(1.00) 		0.484
(0.899) 		0.0712
(0.5) 		0.0198
(0.267) 		0.427
(0.867) 		0.0279
(0.315) 		0.516
(0.899) 		0.538
(0.908)
2q gain 43 (26%) 122 0.093
(0.553) 		0.0575
(0.481) 		0.121
(0.597) 		0.061
(0.488) 		0.721
(0.987) 		0.828
(1.00) 		0.0881
(0.551) 		0.0025
(0.0828) 		0.219
(0.71) 		0.307
(0.768) 		0.158
(0.652) 		0.188
(0.698)
3p gain 27 (16%) 138 1
(1.00) 		0.902
(1.00) 		0.00062
(0.0397) 		0.655
(0.951) 		0.0874
(0.551) 		0.459
(0.889) 		0.11
(0.581) 		0.928
(1.00) 		0.378
(0.826) 		0.361
(0.826) 		0.654
(0.951) 		0.825
(1.00)
3q gain 34 (21%) 131 0.605
(0.934) 		0.612
(0.938) 		0.00018
(0.0192) 		0.868
(1.00) 		0.251
(0.717) 		0.423
(0.866) 		0.103
(0.567) 		0.738
(0.989) 		0.22
(0.71) 		0.315
(0.776) 		0.659
(0.951) 		0.896
(1.00)
5q gain 24 (15%) 141 0.244
(0.717) 		0.0878
(0.551) 		0.00721
(0.169) 		0.0739
(0.51) 		0.186
(0.697) 		0.961
(1.00) 		0.449
(0.885) 		0.0911
(0.553) 		0.248
(0.717) 		0.522
(0.902) 		1
(1.00) 		0.652
(0.951)
6q gain 36 (22%) 129 0.671
(0.957) 		0.23
(0.71) 		0.0174
(0.267) 		0.00671
(0.169) 		0.842
(1.00) 		0.47
(0.894) 		0.673
(0.958) 		0.509
(0.899) 		0.341
(0.803) 		0.582
(0.923) 		0.202
(0.71) 		0.563
(0.912)
8p gain 42 (25%) 123 0.422
(0.866) 		0.236
(0.71) 		0.00224
(0.0828) 		0.517
(0.899) 		0.453
(0.885) 		0.0933
(0.553) 		0.514
(0.899) 		0.341
(0.803) 		0.814
(1.00) 		0.287
(0.749) 		0.918
(1.00) 		0.14
(0.619)
8q gain 89 (54%) 76 0.0364
(0.384) 		0.277
(0.745) 		5e-05
(0.0072) 		0.21
(0.71) 		0.548
(0.912) 		0.788
(1.00) 		0.604
(0.934) 		0.22
(0.71) 		0.244
(0.717) 		0.0675
(0.494) 		0.0208
(0.27) 		0.373
(0.826)
11p gain 32 (19%) 133 0.134
(0.618) 		0.389
(0.836) 		0.00852
(0.174) 		0.419
(0.866) 		0.72
(0.987) 		0.359
(0.826) 		0.133
(0.618) 		0.141
(0.62) 		0.0205
(0.27) 		0.209
(0.71) 		0.657
(0.951) 		0.532
(0.907)
16p gain 41 (25%) 124 0.144
(0.621) 		0.853
(1.00) 		0.00108
(0.0576) 		0.27
(0.743) 		0.924
(1.00) 		1
(1.00) 		0.116
(0.593) 		0.369
(0.826) 		0.151
(0.647) 		0.675
(0.958) 		0.335
(0.801) 		0.981
(1.00)
17q gain 32 (19%) 133 0.199
(0.71) 		0.943
(1.00) 		0.00703
(0.169) 		0.421
(0.866) 		0.879
(1.00) 		0.94
(1.00) 		0.366
(0.826) 		0.493
(0.899) 		0.0537
(0.464) 		0.46
(0.889) 		0.12
(0.597) 		0.637
(0.951)
xp gain 34 (21%) 131 0.0109
(0.206) 		0.143
(0.621) 		0.111
(0.581) 		0.4
(0.853) 		0.593
(0.929) 		0.621
(0.941) 		0.271
(0.743) 		0.669
(0.957) 		0.81
(1.00) 		0.846
(1.00) 		0.831
(1.00) 		0.643
(0.951)
2p loss 11 (7%) 154 0.638
(0.951) 		0.75
(0.989) 		0.00384
(0.108) 		0.483
(0.899) 		0.907
(1.00) 		0.542
(0.912) 		0.526
(0.905) 		0.0593
(0.487) 		0.435
(0.876) 		0.605
(0.934)
3q loss 10 (6%) 155 0.518
(0.899) 		0.793
(1.00) 		0.195
(0.71) 		0.409
(0.863) 		0.326
(0.791) 		0.657
(0.951) 		0.104
(0.567) 		0.22
(0.71) 		0.494
(0.899) 		0.00942
(0.185) 		0.422
(0.866) 		0.365
(0.826)
4p loss 59 (36%) 106 0.666
(0.957) 		0.375
(0.826) 		0.00196
(0.0828) 		0.0273
(0.315) 		0.971
(1.00) 		0.514
(0.899) 		0.713
(0.984) 		0.569
(0.912) 		0.974
(1.00) 		0.0998
(0.557) 		0.224
(0.71) 		0.211
(0.71)
4q loss 66 (40%) 99 0.779
(1.00) 		0.27
(0.743) 		0.00106
(0.0576) 		0.0401
(0.409) 		0.82
(1.00) 		0.516
(0.899) 		0.768
(1.00) 		0.435
(0.876) 		0.812
(1.00) 		0.217
(0.71) 		0.567
(0.912) 		0.916
(1.00)
5q loss 40 (24%) 125 0.0919
(0.553) 		0.0117
(0.215) 		0.216
(0.71) 		0.168
(0.67) 		1
(1.00) 		0.548
(0.912) 		0.926
(1.00) 		0.221
(0.71) 		0.912
(1.00) 		0.207
(0.71) 		0.113
(0.582) 		0.227
(0.71)
6q loss 22 (13%) 143 0.17
(0.67) 		0.644
(0.951) 		0.155
(0.647) 		0.422
(0.866) 		0.452
(0.885) 		0.604
(0.934) 		0.153
(0.647) 		0.152
(0.647) 		0.264
(0.733) 		0.409
(0.863) 		0.0132
(0.235) 		0.553
(0.912)
9q loss 23 (14%) 142 0.21
(0.71) 		0.447
(0.885) 		0.281
(0.745) 		0.138
(0.618) 		0.941
(1.00) 		0.905
(1.00) 		0.516
(0.899) 		0.195
(0.71) 		0.0713
(0.5) 		0.00166
(0.0795) 		0.46
(0.889) 		0.0151
(0.253)
11p loss 23 (14%) 142 0.244
(0.717) 		0.371
(0.826) 		0.00603
(0.159) 		0.205
(0.71) 		0.224
(0.71) 		0.174
(0.672) 		0.0193
(0.267) 		0.234
(0.71) 		0.977
(1.00) 		0.741
(0.989) 		0.602
(0.934) 		0.291
(0.75)
15q loss 73 (44%) 92 0.451
(0.885) 		0.111
(0.581) 		0.00048
(0.035) 		1
(1.00) 		0.0865
(0.551) 		0.249
(0.717) 		0.439
(0.88) 		0.477
(0.899) 		0.817
(1.00) 		0.631
(0.949) 		0.906
(1.00) 		0.746
(0.989)
18p loss 128 (78%) 37 0.0601
(0.488) 		0.707
(0.984) 		0.00133
(0.0672) 		0.0263
(0.315) 		0.601
(0.934) 		0.152
(0.647) 		0.118
(0.593) 		0.0146
(0.251) 		0.168
(0.67) 		0.163
(0.662) 		0.619
(0.941) 		0.594
(0.929)
19q loss 20 (12%) 145 0.829
(1.00) 		0.503
(0.899) 		0.0701
(0.5) 		0.0821
(0.533) 		0.82
(1.00) 		0.775
(1.00) 		0.553
(0.912) 		0.716
(0.985) 		0.0675
(0.494) 		0.00845
(0.174) 		1
(1.00) 		0.749
(0.989)
22q loss 58 (35%) 107 0.853
(1.00) 		0.312
(0.771) 		0.0642
(0.494) 		0.776
(1.00) 		0.75
(0.989) 		0.297
(0.763) 		0.34
(0.803) 		0.169
(0.67) 		0.00614
(0.159) 		0.181
(0.688) 		0.126
(0.607) 		0.0186
(0.267)
1p gain 12 (7%) 153 0.51
(0.899) 		0.941
(1.00) 		0.829
(1.00) 		0.527
(0.906) 		0.0309
(0.337) 		0.0173
(0.267) 		0.332
(0.8) 		0.595
(0.929) 		0.941
(1.00) 		0.459
(0.889) 		0.87
(1.00) 		0.653
(0.951)
1q gain 34 (21%) 131 0.583
(0.924) 		0.65
(0.951) 		0.136
(0.618) 		0.311
(0.771) 		0.0687
(0.496) 		0.212
(0.71) 		0.452
(0.885) 		0.996
(1.00) 		0.536
(0.907) 		0.879
(1.00) 		0.87
(1.00) 		0.366
(0.826)
2p gain 41 (25%) 124 0.508
(0.899) 		0.0197
(0.267) 		0.259
(0.721) 		0.025
(0.311) 		0.669
(0.957) 		0.641
(0.951) 		0.0465
(0.439) 		0.0191
(0.267) 		0.188
(0.698) 		0.0761
(0.514) 		0.726
(0.987) 		0.501
(0.899)
4p gain 9 (5%) 156 1
(1.00) 		0.791
(1.00) 		0.965
(1.00) 		0.765
(1.00) 		0.0897
(0.552) 		0.172
(0.672) 		0.488
(0.899) 		0.628
(0.947) 		0.223
(0.71) 		0.374
(0.826) 		0.744
(0.989) 		0.949
(1.00)
4q gain 5 (3%) 160 0.298
(0.763) 		0.648
(0.951) 		0.675
(0.958) 		0.219
(0.71) 		0.488
(0.899) 		0.712
(0.984) 		1
(1.00) 		0.889
(1.00) 		1
(1.00)
9p gain 42 (25%) 123 0.0176
(0.267) 		0.196
(0.71) 		0.442
(0.881) 		0.163
(0.662) 		0.652
(0.951) 		0.229
(0.71) 		0.0512
(0.457) 		0.278
(0.745) 		0.273
(0.745) 		0.328
(0.792) 		0.864
(1.00) 		0.867
(1.00)
9q gain 33 (20%) 132 0.0153
(0.253) 		0.211
(0.71) 		0.28
(0.745) 		0.468
(0.892) 		0.561
(0.912) 		0.0979
(0.556) 		0.371
(0.826) 		0.0909
(0.553) 		0.786
(1.00) 		0.622
(0.942) 		0.83
(1.00) 		0.932
(1.00)
10p gain 13 (8%) 152 1
(1.00) 		0.918
(1.00) 		0.336
(0.801) 		0.716
(0.985) 		0.666
(0.957) 		0.75
(0.989) 		0.522
(0.902) 		0.126
(0.607) 		0.653
(0.951) 		0.919
(1.00) 		0.616
(0.941) 		0.791
(1.00)
10q gain 7 (4%) 158 0.518
(0.899) 		0.0817
(0.533) 		0.254
(0.72) 		1
(1.00) 		1
(1.00) 		0.872
(1.00) 		1
(1.00) 		0.503
(0.899) 		0.774
(1.00) 		0.864
(1.00)
12p gain 33 (20%) 132 0.692
(0.968) 		0.481
(0.899) 		0.235
(0.71) 		0.728
(0.987) 		0.181
(0.688) 		0.122
(0.598) 		0.084
(0.541) 		0.202
(0.71) 		0.374
(0.826) 		0.55
(0.912) 		0.281
(0.745) 		0.869
(1.00)
12q gain 24 (15%) 141 0.776
(1.00) 		0.519
(0.899) 		0.74
(0.989) 		0.307
(0.768) 		0.265
(0.733) 		0.213
(0.71) 		0.042
(0.42) 		0.51
(0.899) 		0.224
(0.71) 		0.742
(0.989) 		0.0532
(0.464) 		0.949
(1.00)
14q gain 8 (5%) 157 0.832
(1.00) 		0.916
(1.00) 		0.112
(0.582) 		0.223
(0.71) 		0.519
(0.899) 		0.544
(0.912) 		0.494
(0.899) 		0.913
(1.00) 		0.129
(0.614) 		0.862
(1.00)
15q gain 3 (2%) 162 0.417
(0.866) 		0.481
(0.899) 		0.356
(0.826) 		0.644
(0.951)
17p gain 8 (5%) 157 0.108
(0.577) 		0.38
(0.826) 		0.233
(0.71) 		0.466
(0.892) 		1
(1.00) 		0.872
(1.00) 		0.423
(0.866) 		0.685
(0.966) 		0.49
(0.899) 		0.443
(0.881)
18p gain 8 (5%) 157 0.516
(0.899) 		0.391
(0.837) 		0.216
(0.71) 		0.728
(0.987) 		0.807
(1.00) 		0.738
(0.989) 		0.678
(0.959) 		0.383
(0.827) 		0.5
(0.899) 		0.558
(0.912) 		1
(1.00) 		0.893
(1.00)
18q gain 6 (4%) 159 0.792
(1.00) 		0.379
(0.826) 		0.492
(0.899) 		0.893
(1.00) 		0.534
(0.907) 		0.227
(0.71) 		0.654
(0.951) 		0.632
(0.949) 		1
(1.00) 		0.892
(1.00)
19p gain 33 (20%) 132 0.0652
(0.494) 		0.417
(0.866) 		0.106
(0.572) 		0.766
(1.00) 		0.544
(0.912) 		0.463
(0.89) 		0.566
(0.912) 		0.0277
(0.315) 		0.138
(0.618) 		0.957
(1.00) 		1
(1.00) 		0.973
(1.00)
19q gain 32 (19%) 133 0.082
(0.533) 		0.533
(0.907) 		0.0748
(0.513) 		0.53
(0.907) 		0.958
(1.00) 		0.594
(0.929) 		0.226
(0.71) 		0.128
(0.613) 		0.353
(0.826) 		0.581
(0.923) 		1
(1.00) 		0.973
(1.00)
20p gain 109 (66%) 56 0.0954
(0.556) 		0.726
(0.987) 		0.138
(0.618) 		0.251
(0.717) 		0.134
(0.618) 		0.831
(1.00) 		0.604
(0.934) 		0.566
(0.912) 		0.0973
(0.556) 		0.0468
(0.439) 		0.304
(0.766) 		0.0777
(0.514)
21q gain 10 (6%) 155 0.535
(0.907) 		0.659
(0.951) 		0.637
(0.951) 		1
(1.00) 		0.62
(0.941) 		0.792
(1.00) 		0.947
(1.00) 		0.921
(1.00) 		0.289
(0.75) 		0.724
(0.987)
22q gain 9 (5%) 156 0.729
(0.987) 		0.0608
(0.488) 		0.0754
(0.513) 		1
(1.00) 		0.422
(0.866) 		0.234
(0.71) 		0.351
(0.823) 		0.201
(0.71) 		1
(1.00) 		1
(1.00)
xq gain 34 (21%) 131 0.156
(0.647) 		0.382
(0.826) 		0.0454
(0.439) 		0.288
(0.749) 		0.818
(1.00) 		0.302
(0.766) 		0.104
(0.567) 		0.647
(0.951) 		0.981
(1.00) 		1
(1.00) 		0.453
(0.885) 		0.212
(0.71)
1p loss 46 (28%) 119 0.69
(0.967) 		0.0273
(0.315) 		0.0508
(0.457) 		0.185
(0.693) 		0.935
(1.00) 		0.207
(0.71) 		0.366
(0.826) 		0.169
(0.67) 		0.442
(0.881) 		0.61
(0.937) 		0.559
(0.912) 		0.567
(0.912)
1q loss 26 (16%) 139 0.912
(1.00) 		0.0576
(0.481) 		0.257
(0.721) 		0.0288
(0.321) 		0.843
(1.00) 		0.532
(0.907) 		0.0654
(0.494) 		0.463
(0.89) 		0.561
(0.912) 		0.226
(0.71) 		0.5
(0.899) 		0.275
(0.745)
2q loss 6 (4%) 159 1
(1.00) 		0.569
(0.912) 		0.0523
(0.461) 		0.103
(0.567) 		0.304
(0.766) 		0.81
(1.00) 		0.0656
(0.494) 		0.203
(0.71) 		0.466
(0.892)
3p loss 15 (9%) 150 1
(1.00) 		0.365
(0.826) 		0.203
(0.71) 		0.774
(1.00) 		0.258
(0.721) 		0.895
(1.00) 		0.154
(0.647) 		0.557
(0.912) 		0.453
(0.885) 		0.134
(0.618) 		0.0983
(0.556) 		0.0445
(0.438)
5p loss 26 (16%) 139 0.239
(0.713) 		0.816
(1.00) 		0.137
(0.618) 		0.178
(0.68) 		0.525
(0.904) 		0.0652
(0.494) 		0.878
(1.00) 		0.125
(0.607) 		0.724
(0.987) 		0.577
(0.921) 		0.174
(0.672) 		0.246
(0.717)
6p loss 13 (8%) 152 0.546
(0.912) 		0.931
(1.00) 		0.7
(0.975) 		0.121
(0.597) 		0.311
(0.771) 		0.359
(0.826) 		0.749
(0.989) 		0.278
(0.745) 		0.566
(0.912) 		0.256
(0.721)
7q loss 3 (2%) 162 0.357
(0.826) 		0.785
(1.00) 		0.773
(1.00) 		0.0375
(0.391) 		0.759
(0.996) 		0.858
(1.00) 		1
(1.00)
8p loss 73 (44%) 92 0.123
(0.6) 		0.246
(0.717) 		0.134
(0.618) 		0.964
(1.00) 		0.785
(1.00) 		0.252
(0.719) 		0.024
(0.303) 		0.117
(0.593) 		0.894
(1.00) 		0.973
(1.00) 		0.733
(0.989) 		0.229
(0.71)
8q loss 11 (7%) 154 0.687
(0.966) 		0.714
(0.984) 		0.41
(0.863) 		0.468
(0.892) 		0.794
(1.00) 		0.279
(0.745) 		0.545
(0.912) 		0.326
(0.791) 		0.866
(1.00) 		0.302
(0.766) 		0.169
(0.67) 		0.405
(0.858)
9p loss 23 (14%) 142 0.634
(0.95) 		0.616
(0.941) 		0.321
(0.782) 		0.141
(0.62) 		0.749
(0.989) 		0.564
(0.912) 		0.811
(1.00) 		0.515
(0.899) 		0.308
(0.769) 		0.0481
(0.444) 		0.713
(0.984) 		0.0391
(0.404)
10p loss 33 (20%) 132 0.144
(0.621) 		0.172
(0.672) 		0.137
(0.618) 		0.0672
(0.494) 		0.144
(0.621) 		0.24
(0.715) 		0.201
(0.71) 		0.455
(0.886) 		0.837
(1.00) 		0.117
(0.593) 		0.816
(1.00) 		0.749
(0.989)
10q loss 38 (23%) 127 0.177
(0.68) 		0.155
(0.647) 		0.0593
(0.487) 		0.0934
(0.553) 		0.13
(0.615) 		0.0324
(0.348) 		0.374
(0.826) 		0.0734
(0.51) 		0.682
(0.963) 		0.0884
(0.551) 		0.899
(1.00) 		0.537
(0.908)
12p loss 22 (13%) 143 0.424
(0.866) 		0.278
(0.745) 		0.654
(0.951) 		0.401
(0.853) 		0.693
(0.969) 		0.0775
(0.514) 		0.752
(0.99) 		0.433
(0.875) 		0.45
(0.885) 		0.775
(1.00) 		0.0662
(0.494) 		0.512
(0.899)
12q loss 19 (12%) 146 0.502
(0.899) 		0.771
(1.00) 		0.237
(0.71) 		0.93
(1.00) 		0.555
(0.912) 		0.258
(0.721) 		0.834
(1.00) 		0.254
(0.72) 		0.379
(0.826) 		0.317
(0.777) 		0.274
(0.745) 		0.868
(1.00)
13q loss 8 (5%) 157 0.518
(0.899) 		1
(1.00) 		0.657
(0.951) 		0.107
(0.572) 		0.0544
(0.466) 		0.431
(0.873) 		1
(1.00) 		0.492
(0.899) 		0.174
(0.672) 		1
(1.00)
14q loss 67 (41%) 98 0.501
(0.899) 		0.25
(0.717) 		0.02
(0.267) 		0.567
(0.912) 		0.802
(1.00) 		0.493
(0.899) 		0.382
(0.826) 		0.0777
(0.514) 		0.335
(0.801) 		0.202
(0.71) 		0.748
(0.989) 		0.781
(1.00)
16p loss 9 (5%) 156 0.378
(0.826) 		0.756
(0.995) 		0.0996
(0.557) 		0.0624
(0.494) 		0.654
(0.951) 		0.632
(0.949) 		0.184
(0.693) 		0.913
(1.00) 		0.563
(0.912) 		1
(1.00) 		0.25
(0.717) 		0.486
(0.899)
16q loss 15 (9%) 150 0.282
(0.745) 		0.678
(0.959) 		0.0471
(0.439) 		0.334
(0.801) 		0.723
(0.987) 		0.898
(1.00) 		0.402
(0.855) 		0.996
(1.00) 		0.869
(1.00) 		1
(1.00) 		0.939
(1.00) 		0.964
(1.00)
17p loss 107 (65%) 58 0.206
(0.71) 		0.376
(0.826) 		0.0946
(0.556) 		0.199
(0.71) 		0.971
(1.00) 		0.319
(0.78) 		0.617
(0.941) 		0.593
(0.929) 		0.981
(1.00) 		0.398
(0.851) 		0.288
(0.749) 		0.664
(0.957)
17q loss 26 (16%) 139 0.904
(1.00) 		0.737
(0.989) 		0.0278
(0.315) 		0.0894
(0.552) 		0.746
(0.989) 		0.974
(1.00) 		0.113
(0.582) 		0.34
(0.803) 		0.87
(1.00) 		0.947
(1.00) 		0.423
(0.866) 		0.476
(0.897)
19p loss 21 (13%) 144 0.729
(0.987) 		0.834
(1.00) 		0.135
(0.618) 		0.0304
(0.335) 		0.65
(0.951) 		0.808
(1.00) 		0.591
(0.929) 		0.566
(0.912) 		0.377
(0.826) 		0.0183
(0.267) 		0.964
(1.00) 		0.74
(0.989)
20p loss 23 (14%) 142 1
(1.00) 		0.952
(1.00) 		0.0507
(0.457) 		0.284
(0.749) 		0.378
(0.826) 		0.985
(1.00) 		0.439
(0.88) 		0.674
(0.958) 		0.0326
(0.348) 		0.0227
(0.291) 		0.304
(0.766) 		0.0145
(0.251)
21q loss 68 (41%) 97 0.285
(0.749) 		0.247
(0.717) 		0.413
(0.866) 		1
(1.00) 		0.973
(1.00) 		0.531
(0.907) 		0.82
(1.00) 		0.687
(0.966) 		0.0157
(0.256) 		0.183
(0.69) 		0.224
(0.71) 		0.068
(0.494)
xp loss 25 (15%) 140 0.29
(0.75) 		0.899
(1.00) 		0.305
(0.766) 		0.475
(0.897) 		0.504
(0.899) 		0.84
(1.00) 		0.426
(0.867) 		0.858
(1.00) 		0.977
(1.00) 		0.579
(0.921) 		0.571
(0.913) 		0.78
(1.00)
xq loss 24 (15%) 141 0.609
(0.937) 		0.478
(0.899) 		0.709
(0.984) 		0.315
(0.776) 		0.695
(0.969) 		0.901
(1.00) 		0.563
(0.912) 		0.954
(1.00) 		0.841
(1.00) 		0.366
(0.826) 		0.474
(0.897) 		0.806
(1.00)
'2q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.0025 (Fisher's exact test), Q value = 0.083

Table S1.  Gene #4: '2q gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 27 36 12 19 32 18 20
2Q GAIN MUTATED 14 6 2 6 10 0 4
2Q GAIN WILD-TYPE 13 30 10 13 22 18 16

Figure S1.  Get High-res Image Gene #4: '2q gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

'3p gain' versus 'CN_CNMF'

P value = 0.00062 (Fisher's exact test), Q value = 0.04

Table S2.  Gene #5: '3p gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
3P GAIN MUTATED 3 10 9 5
3P GAIN WILD-TYPE 63 22 22 31

Figure S2.  Get High-res Image Gene #5: '3p gain' versus Molecular Subtype #3: 'CN_CNMF'

'3q gain' versus 'CN_CNMF'

P value = 0.00018 (Fisher's exact test), Q value = 0.019

Table S3.  Gene #6: '3q gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
3Q GAIN MUTATED 4 12 11 7
3Q GAIN WILD-TYPE 62 20 20 29

Figure S3.  Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #3: 'CN_CNMF'

'5p gain' versus 'CN_CNMF'

P value = 0.00174 (Fisher's exact test), Q value = 0.08

Table S4.  Gene #9: '5p gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
5P GAIN MUTATED 5 10 9 12
5P GAIN WILD-TYPE 61 22 22 24

Figure S4.  Get High-res Image Gene #9: '5p gain' versus Molecular Subtype #3: 'CN_CNMF'

'5p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 6e-05 (Fisher's exact test), Q value = 0.0072

Table S5.  Gene #9: '5p gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 27 36 12 19 32 18 20
5P GAIN MUTATED 8 2 9 2 10 2 3
5P GAIN WILD-TYPE 19 34 3 17 22 16 17

Figure S5.  Get High-res Image Gene #9: '5p gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

'5q gain' versus 'CN_CNMF'

P value = 0.00721 (Fisher's exact test), Q value = 0.17

Table S6.  Gene #10: '5q gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
5Q GAIN MUTATED 3 6 5 10
5Q GAIN WILD-TYPE 63 26 26 26

Figure S6.  Get High-res Image Gene #10: '5q gain' versus Molecular Subtype #3: 'CN_CNMF'

'6p gain' versus 'CN_CNMF'

P value = 0.0089 (Fisher's exact test), Q value = 0.18

Table S7.  Gene #11: '6p gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
6P GAIN MUTATED 11 15 9 6
6P GAIN WILD-TYPE 55 17 22 30

Figure S7.  Get High-res Image Gene #11: '6p gain' versus Molecular Subtype #3: 'CN_CNMF'

'6p gain' versus 'METHLYATION_CNMF'

P value = 0.00328 (Fisher's exact test), Q value = 0.098

Table S8.  Gene #11: '6p gain' versus Molecular Subtype #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 28 39 29
6P GAIN MUTATED 14 5 7
6P GAIN WILD-TYPE 14 34 22

Figure S8.  Get High-res Image Gene #11: '6p gain' versus Molecular Subtype #4: 'METHLYATION_CNMF'

'6q gain' versus 'METHLYATION_CNMF'

P value = 0.00671 (Fisher's exact test), Q value = 0.17

Table S9.  Gene #12: '6q gain' versus Molecular Subtype #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 28 39 29
6Q GAIN MUTATED 13 5 6
6Q GAIN WILD-TYPE 15 34 23

Figure S9.  Get High-res Image Gene #12: '6q gain' versus Molecular Subtype #4: 'METHLYATION_CNMF'

'7p gain' versus 'MRNA_CNMF'

P value = 0.00229 (Fisher's exact test), Q value = 0.083

Table S10.  Gene #13: '7p gain' versus Molecular Subtype #1: 'MRNA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 25 22 22
7P GAIN MUTATED 8 11 18
7P GAIN WILD-TYPE 17 11 4

Figure S10.  Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #1: 'MRNA_CNMF'

'7p gain' versus 'MRNA_CHIERARCHICAL'

P value = 0.00261 (Fisher's exact test), Q value = 0.084

Table S11.  Gene #13: '7p gain' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 6 13 13 9 8 9 8 3
7P GAIN MUTATED 1 3 7 7 7 5 7 0
7P GAIN WILD-TYPE 5 10 6 2 1 4 1 3

Figure S11.  Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

'7p gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0048

Table S12.  Gene #13: '7p gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
7P GAIN MUTATED 24 26 28 24
7P GAIN WILD-TYPE 42 6 3 12

Figure S12.  Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #3: 'CN_CNMF'

'7p gain' versus 'METHLYATION_CNMF'

P value = 0.00316 (Fisher's exact test), Q value = 0.098

Table S13.  Gene #13: '7p gain' versus Molecular Subtype #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 28 39 29
7P GAIN MUTATED 24 19 22
7P GAIN WILD-TYPE 4 20 7

Figure S13.  Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #4: 'METHLYATION_CNMF'

'7p gain' versus 'MRNASEQ_CNMF'

P value = 0.00024 (Fisher's exact test), Q value = 0.023

Table S14.  Gene #13: '7p gain' versus Molecular Subtype #7: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 29 14 33 28 60
7P GAIN MUTATED 24 7 13 24 33
7P GAIN WILD-TYPE 5 7 20 4 27

Figure S14.  Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #7: 'MRNASEQ_CNMF'

'7p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2e-05 (Fisher's exact test), Q value = 0.0048

Table S15.  Gene #13: '7p gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 27 36 12 19 32 18 20
7P GAIN MUTATED 25 17 9 13 20 3 14
7P GAIN WILD-TYPE 2 19 3 6 12 15 6

Figure S15.  Get High-res Image Gene #13: '7p gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

'7q gain' versus 'MRNA_CHIERARCHICAL'

P value = 0.00813 (Fisher's exact test), Q value = 0.17

Table S16.  Gene #14: '7q gain' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 6 13 13 9 8 9 8 3
7Q GAIN MUTATED 1 3 7 4 7 4 7 0
7Q GAIN WILD-TYPE 5 10 6 5 1 5 1 3

Figure S16.  Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

'7q gain' versus 'CN_CNMF'

P value = 2e-05 (Fisher's exact test), Q value = 0.0048

Table S17.  Gene #14: '7q gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
7Q GAIN MUTATED 18 23 22 22
7Q GAIN WILD-TYPE 48 9 9 14

Figure S17.  Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #3: 'CN_CNMF'

'7q gain' versus 'MRNASEQ_CNMF'

P value = 0.0045 (Fisher's exact test), Q value = 0.12

Table S18.  Gene #14: '7q gain' versus Molecular Subtype #7: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 29 14 33 28 60
7Q GAIN MUTATED 17 5 11 22 29
7Q GAIN WILD-TYPE 12 9 22 6 31

Figure S18.  Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #7: 'MRNASEQ_CNMF'

'7q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00213 (Fisher's exact test), Q value = 0.083

Table S19.  Gene #14: '7q gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 27 36 12 19 32 18 20
7Q GAIN MUTATED 19 12 8 12 18 3 12
7Q GAIN WILD-TYPE 8 24 4 7 14 15 8

Figure S19.  Get High-res Image Gene #14: '7q gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

'8p gain' versus 'CN_CNMF'

P value = 0.00224 (Fisher's exact test), Q value = 0.083

Table S20.  Gene #15: '8p gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
8P GAIN MUTATED 10 8 6 18
8P GAIN WILD-TYPE 56 24 25 18

Figure S20.  Get High-res Image Gene #15: '8p gain' versus Molecular Subtype #3: 'CN_CNMF'

'8q gain' versus 'CN_CNMF'

P value = 5e-05 (Fisher's exact test), Q value = 0.0072

Table S21.  Gene #16: '8q gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
8Q GAIN MUTATED 29 13 15 32
8Q GAIN WILD-TYPE 37 19 16 4

Figure S21.  Get High-res Image Gene #16: '8q gain' versus Molecular Subtype #3: 'CN_CNMF'

'11p gain' versus 'CN_CNMF'

P value = 0.00852 (Fisher's exact test), Q value = 0.17

Table S22.  Gene #21: '11p gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
11P GAIN MUTATED 8 6 13 5
11P GAIN WILD-TYPE 58 26 18 31

Figure S22.  Get High-res Image Gene #21: '11p gain' versus Molecular Subtype #3: 'CN_CNMF'

'11q gain' versus 'CN_CNMF'

P value = 0.00202 (Fisher's exact test), Q value = 0.083

Table S23.  Gene #22: '11q gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
11Q GAIN MUTATED 7 5 12 2
11Q GAIN WILD-TYPE 59 27 19 34

Figure S23.  Get High-res Image Gene #22: '11q gain' versus Molecular Subtype #3: 'CN_CNMF'

'11q gain' versus 'MRNASEQ_CNMF'

P value = 0.00249 (Fisher's exact test), Q value = 0.083

Table S24.  Gene #22: '11q gain' versus Molecular Subtype #7: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 29 14 33 28 60
11Q GAIN MUTATED 7 1 0 9 9
11Q GAIN WILD-TYPE 22 13 33 19 51

Figure S24.  Get High-res Image Gene #22: '11q gain' versus Molecular Subtype #7: 'MRNASEQ_CNMF'

'11q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00043 (Fisher's exact test), Q value = 0.035

Table S25.  Gene #22: '11q gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 27 36 12 19 32 18 20
11Q GAIN MUTATED 9 1 0 7 7 1 1
11Q GAIN WILD-TYPE 18 35 12 12 25 17 19

Figure S25.  Get High-res Image Gene #22: '11q gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

'13q gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0048

Table S26.  Gene #25: '13q gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
13Q GAIN MUTATED 32 30 26 25
13Q GAIN WILD-TYPE 34 2 5 11

Figure S26.  Get High-res Image Gene #25: '13q gain' versus Molecular Subtype #3: 'CN_CNMF'

'13q gain' versus 'MRNASEQ_CNMF'

P value = 0.00051 (Fisher's exact test), Q value = 0.035

Table S27.  Gene #25: '13q gain' versus Molecular Subtype #7: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 29 14 33 28 60
13Q GAIN MUTATED 19 11 16 27 39
13Q GAIN WILD-TYPE 10 3 17 1 21

Figure S27.  Get High-res Image Gene #25: '13q gain' versus Molecular Subtype #7: 'MRNASEQ_CNMF'

'13q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00047 (Fisher's exact test), Q value = 0.035

Table S28.  Gene #25: '13q gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 27 36 12 19 32 18 20
13Q GAIN MUTATED 21 25 7 17 25 4 13
13Q GAIN WILD-TYPE 6 11 5 2 7 14 7

Figure S28.  Get High-res Image Gene #25: '13q gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

'13q gain' versus 'MIRSEQ_CNMF'

P value = 0.00351 (Fisher's exact test), Q value = 0.1

Table S29.  Gene #25: '13q gain' versus Molecular Subtype #9: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 18 42 17 8 56
13Q GAIN MUTATED 15 37 9 6 32
13Q GAIN WILD-TYPE 3 5 8 2 24

Figure S29.  Get High-res Image Gene #25: '13q gain' versus Molecular Subtype #9: 'MIRSEQ_CNMF'

'16p gain' versus 'CN_CNMF'

P value = 0.00108 (Fisher's exact test), Q value = 0.058

Table S30.  Gene #28: '16p gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
16P GAIN MUTATED 7 14 11 9
16P GAIN WILD-TYPE 59 18 20 27

Figure S30.  Get High-res Image Gene #28: '16p gain' versus Molecular Subtype #3: 'CN_CNMF'

'16q gain' versus 'CN_CNMF'

P value = 3e-05 (Fisher's exact test), Q value = 0.0058

Table S31.  Gene #29: '16q gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
16Q GAIN MUTATED 5 15 13 8
16Q GAIN WILD-TYPE 61 17 18 28

Figure S31.  Get High-res Image Gene #29: '16q gain' versus Molecular Subtype #3: 'CN_CNMF'

'16q gain' versus 'MRNASEQ_CNMF'

P value = 0.01 (Fisher's exact test), Q value = 0.19

Table S32.  Gene #29: '16q gain' versus Molecular Subtype #7: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 29 14 33 28 60
16Q GAIN MUTATED 11 1 4 12 12
16Q GAIN WILD-TYPE 18 13 29 16 48

Figure S32.  Get High-res Image Gene #29: '16q gain' versus Molecular Subtype #7: 'MRNASEQ_CNMF'

'17q gain' versus 'CN_CNMF'

P value = 0.00703 (Fisher's exact test), Q value = 0.17

Table S33.  Gene #31: '17q gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
17Q GAIN MUTATED 9 3 13 7
17Q GAIN WILD-TYPE 57 29 18 29

Figure S33.  Get High-res Image Gene #31: '17q gain' versus Molecular Subtype #3: 'CN_CNMF'

'20q gain' versus 'MRNA_CNMF'

P value = 0.0074 (Fisher's exact test), Q value = 0.17

Table S34.  Gene #37: '20q gain' versus Molecular Subtype #1: 'MRNA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 25 22 22
20Q GAIN MUTATED 22 15 22
20Q GAIN WILD-TYPE 3 7 0

Figure S34.  Get High-res Image Gene #37: '20q gain' versus Molecular Subtype #1: 'MRNA_CNMF'

'20q gain' versus 'CN_CNMF'

P value = 0.00072 (Fisher's exact test), Q value = 0.043

Table S35.  Gene #37: '20q gain' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
20Q GAIN MUTATED 53 32 31 29
20Q GAIN WILD-TYPE 13 0 0 7

Figure S35.  Get High-res Image Gene #37: '20q gain' versus Molecular Subtype #3: 'CN_CNMF'

'20q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00247 (Fisher's exact test), Q value = 0.083

Table S36.  Gene #37: '20q gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 27 36 12 19 32 18 20
20Q GAIN MUTATED 26 33 9 18 30 10 18
20Q GAIN WILD-TYPE 1 3 3 1 2 8 2

Figure S36.  Get High-res Image Gene #37: '20q gain' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

'xp gain' versus 'MRNA_CNMF'

P value = 0.0109 (Fisher's exact test), Q value = 0.21

Table S37.  Gene #40: 'xp gain' versus Molecular Subtype #1: 'MRNA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 25 22 22
XP GAIN MUTATED 4 1 9
XP GAIN WILD-TYPE 21 21 13

Figure S37.  Get High-res Image Gene #40: 'xp gain' versus Molecular Subtype #1: 'MRNA_CNMF'

'2p loss' versus 'CN_CNMF'

P value = 0.00384 (Fisher's exact test), Q value = 0.11

Table S38.  Gene #44: '2p loss' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
2P LOSS MUTATED 0 5 2 4
2P LOSS WILD-TYPE 66 27 29 32

Figure S38.  Get High-res Image Gene #44: '2p loss' versus Molecular Subtype #3: 'CN_CNMF'

'3q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00942 (Fisher's exact test), Q value = 0.18

Table S39.  Gene #47: '3q loss' versus Molecular Subtype #10: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 22 63 56
3Q LOSS MUTATED 5 4 1
3Q LOSS WILD-TYPE 17 59 55

Figure S39.  Get High-res Image Gene #47: '3q loss' versus Molecular Subtype #10: 'MIRSEQ_CHIERARCHICAL'

'4p loss' versus 'CN_CNMF'

P value = 0.00196 (Fisher's exact test), Q value = 0.083

Table S40.  Gene #48: '4p loss' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
4P LOSS MUTATED 15 20 12 12
4P LOSS WILD-TYPE 51 12 19 24

Figure S40.  Get High-res Image Gene #48: '4p loss' versus Molecular Subtype #3: 'CN_CNMF'

'4q loss' versus 'CN_CNMF'

P value = 0.00106 (Fisher's exact test), Q value = 0.058

Table S41.  Gene #49: '4q loss' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
4Q LOSS MUTATED 16 21 14 15
4Q LOSS WILD-TYPE 50 11 17 21

Figure S41.  Get High-res Image Gene #49: '4q loss' versus Molecular Subtype #3: 'CN_CNMF'

'5q loss' versus 'MRNA_CHIERARCHICAL'

P value = 0.0117 (Fisher's exact test), Q value = 0.22

Table S42.  Gene #51: '5q loss' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7 CLUS_8
ALL 6 13 13 9 8 9 8 3
5Q LOSS MUTATED 0 3 1 6 3 0 2 0
5Q LOSS WILD-TYPE 6 10 12 3 5 9 6 3

Figure S42.  Get High-res Image Gene #51: '5q loss' versus Molecular Subtype #2: 'MRNA_CHIERARCHICAL'

'6q loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.0132 (Fisher's exact test), Q value = 0.24

Table S43.  Gene #53: '6q loss' versus Molecular Subtype #11: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 9 14 14 13
6Q LOSS MUTATED 0 0 4 0
6Q LOSS WILD-TYPE 9 14 10 13

Figure S43.  Get High-res Image Gene #53: '6q loss' versus Molecular Subtype #11: 'MIRSEQ_MATURE_CNMF'

'9q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00166 (Fisher's exact test), Q value = 0.08

Table S44.  Gene #58: '9q loss' versus Molecular Subtype #10: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 22 63 56
9Q LOSS MUTATED 9 5 7
9Q LOSS WILD-TYPE 13 58 49

Figure S44.  Get High-res Image Gene #58: '9q loss' versus Molecular Subtype #10: 'MIRSEQ_CHIERARCHICAL'

'11p loss' versus 'CN_CNMF'

P value = 0.00603 (Fisher's exact test), Q value = 0.16

Table S45.  Gene #61: '11p loss' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
11P LOSS MUTATED 5 8 1 9
11P LOSS WILD-TYPE 61 24 30 27

Figure S45.  Get High-res Image Gene #61: '11p loss' versus Molecular Subtype #3: 'CN_CNMF'

'11q loss' versus 'CN_CNMF'

P value = 0.00698 (Fisher's exact test), Q value = 0.17

Table S46.  Gene #62: '11q loss' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
11Q LOSS MUTATED 9 9 1 11
11Q LOSS WILD-TYPE 57 23 30 25

Figure S46.  Get High-res Image Gene #62: '11q loss' versus Molecular Subtype #3: 'CN_CNMF'

'11q loss' versus 'MRNASEQ_CNMF'

P value = 0.00839 (Fisher's exact test), Q value = 0.17

Table S47.  Gene #62: '11q loss' versus Molecular Subtype #7: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 29 14 33 28 60
11Q LOSS MUTATED 3 5 11 1 10
11Q LOSS WILD-TYPE 26 9 22 27 50

Figure S47.  Get High-res Image Gene #62: '11q loss' versus Molecular Subtype #7: 'MRNASEQ_CNMF'

'11q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00838 (Fisher's exact test), Q value = 0.17

Table S48.  Gene #62: '11q loss' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 27 36 12 19 32 18 20
11Q LOSS MUTATED 1 11 4 2 2 6 4
11Q LOSS WILD-TYPE 26 25 8 17 30 12 16

Figure S48.  Get High-res Image Gene #62: '11q loss' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

'15q loss' versus 'CN_CNMF'

P value = 0.00048 (Fisher's exact test), Q value = 0.035

Table S49.  Gene #67: '15q loss' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
15Q LOSS MUTATED 17 21 15 20
15Q LOSS WILD-TYPE 49 11 16 16

Figure S49.  Get High-res Image Gene #67: '15q loss' versus Molecular Subtype #3: 'CN_CNMF'

'18p loss' versus 'CN_CNMF'

P value = 0.00133 (Fisher's exact test), Q value = 0.067

Table S50.  Gene #72: '18p loss' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
18P LOSS MUTATED 42 26 30 30
18P LOSS WILD-TYPE 24 6 1 6

Figure S50.  Get High-res Image Gene #72: '18p loss' versus Molecular Subtype #3: 'CN_CNMF'

'18q loss' versus 'CN_CNMF'

P value = 6e-05 (Fisher's exact test), Q value = 0.0072

Table S51.  Gene #73: '18q loss' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 32 31 36
18Q LOSS MUTATED 45 28 31 34
18Q LOSS WILD-TYPE 21 4 0 2

Figure S51.  Get High-res Image Gene #73: '18q loss' versus Molecular Subtype #3: 'CN_CNMF'

'18q loss' versus 'METHLYATION_CNMF'

P value = 0.012 (Fisher's exact test), Q value = 0.22

Table S52.  Gene #73: '18q loss' versus Molecular Subtype #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 28 39 29
18Q LOSS MUTATED 28 30 25
18Q LOSS WILD-TYPE 0 9 4

Figure S52.  Get High-res Image Gene #73: '18q loss' versus Molecular Subtype #4: 'METHLYATION_CNMF'

'19q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00845 (Fisher's exact test), Q value = 0.17

Table S53.  Gene #75: '19q loss' versus Molecular Subtype #10: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 22 63 56
19Q LOSS MUTATED 7 8 3
19Q LOSS WILD-TYPE 15 55 53

Figure S53.  Get High-res Image Gene #75: '19q loss' versus Molecular Subtype #10: 'MIRSEQ_CHIERARCHICAL'

'22q loss' versus 'MIRSEQ_CNMF'

P value = 0.00614 (Fisher's exact test), Q value = 0.16

Table S54.  Gene #78: '22q loss' versus Molecular Subtype #9: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 18 42 17 8 56
22Q LOSS MUTATED 4 24 2 4 20
22Q LOSS WILD-TYPE 14 18 15 4 36

Figure S54.  Get High-res Image Gene #78: '22q loss' versus Molecular Subtype #9: 'MIRSEQ_CNMF'

Methods & Data
Input

  • Copy number data file = broad_values_by_arm.txt from GISTIC pipeline

  • Processed Copy number data file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_Correlate_Genomic_Events_Preprocess/READ-TP/15096456/transformed.cor.cli.txt

  • Molecular subtypes file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/READ-TP/15107799/READ-TP.transferedmergedcluster.txt

  • Number of patients = 165

  • Number of significantly arm-level cnvs = 80

  • Number of molecular subtypes = 12

  • 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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