Correlation between copy number variations of arm-level result and molecular subtypes
Mesothelioma (Primary solid tumor)
28 January 2016  |  analyses__2016_01_28
Maintainer Information
Citation Information
doi:10.7908/C14F1Q4N
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2016): Correlation between copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C14F1Q4N
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 72 arm-level events and 10 molecular subtypes across 87 patients, 43 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 7q gain cnv correlated to 'RPPA_CNMF'.

  • 12p gain cnv correlated to 'CN_CNMF'.

  • 12q gain cnv correlated to 'CN_CNMF'.

  • 15q gain cnv correlated to 'METHLYATION_CNMF',  'MIRSEQ_CNMF', and 'MIRSEQ_CHIERARCHICAL'.

  • 17p gain cnv correlated to 'RPPA_CHIERARCHICAL'.

  • 19p gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 21q gain cnv correlated to 'METHLYATION_CNMF' and 'MIRSEQ_CNMF'.

  • 1p loss cnv correlated to 'CN_CNMF'.

  • 2p loss cnv correlated to 'METHLYATION_CNMF'.

  • 4p loss cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 4q loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CNMF'.

  • 6q loss cnv correlated to 'CN_CNMF'.

  • 9p loss cnv correlated to 'CN_CNMF'.

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

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

  • 13q loss cnv correlated to 'MIRSEQ_MATURE_CNMF'.

  • 14q loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_CHIERARCHICAL', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 16p loss cnv correlated to 'CN_CNMF'.

  • 18p loss cnv correlated to 'CN_CNMF'.

  • 22q loss cnv correlated to 'METHLYATION_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • xp loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'RPPA_CNMF'.

  • xq loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'RPPA_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 72 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, 43 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
14q loss 35 (40%) 52 1e-05
(0.0024) 		0.00018
(0.0144) 		0.309
(0.738) 		0.428
(0.809) 		6e-05
(0.0072) 		2e-05
(0.0036) 		0.0299
(0.345) 		0.00058
(0.0321) 		0.136
(0.589) 		0.00083
(0.0427)
4q loss 34 (39%) 53 1e-05
(0.0024) 		0.0136
(0.234) 		0.419
(0.805) 		0.516
(0.865) 		0.00192
(0.0834) 		0.00023
(0.0166) 		0.01
(0.234) 		0.143
(0.589) 		0.488
(0.844) 		0.0276
(0.332)
15q gain 10 (11%) 77 0.269
(0.701) 		0.00536
(0.177) 		1
(1.00) 		0.0431
(0.392) 		0.0164
(0.257) 		0.11
(0.559) 		0.00722
(0.204) 		0.0131
(0.234) 		0.476
(0.838) 		0.201
(0.643)
xp loss 27 (31%) 60 0.00092
(0.0442) 		9e-05
(0.0081) 		0.0129
(0.234) 		0.133
(0.589) 		0.0346
(0.372) 		0.0559
(0.435) 		0.0605
(0.448) 		0.419
(0.805) 		0.0461
(0.394) 		0.0441
(0.392)
xq loss 28 (32%) 59 0.0003
(0.0196) 		7e-05
(0.0072) 		0.00766
(0.204) 		0.403
(0.795) 		0.0461
(0.394) 		0.0263
(0.321) 		0.0799
(0.484) 		0.41
(0.795) 		0.0391
(0.383) 		0.0393
(0.383)
19p gain 14 (16%) 73 0.0108
(0.234) 		0.0111
(0.234) 		0.81
(0.964) 		0.578
(0.897) 		0.141
(0.589) 		0.228
(0.664) 		0.221
(0.648) 		0.174
(0.627) 		1
(1.00) 		0.213
(0.648)
21q gain 6 (7%) 81 0.263
(0.7) 		0.00722
(0.204) 		1
(1.00) 		0.605
(0.915) 		0.205
(0.643) 		0.13
(0.589) 		0.00197
(0.0834) 		0.342
(0.747) 		0.0802
(0.484) 		0.166
(0.62)
4p loss 33 (38%) 54 1e-05
(0.0024) 		0.0632
(0.451) 		0.578
(0.897) 		0.618
(0.916) 		0.14
(0.589) 		0.0148
(0.247) 		0.0711
(0.478) 		0.39
(0.786) 		0.447
(0.817) 		0.399
(0.792)
10p loss 25 (29%) 62 0.00212
(0.0848) 		0.131
(0.589) 		0.511
(0.861) 		0.807
(0.964) 		0.0689
(0.477) 		0.0807
(0.484) 		0.0132
(0.234) 		0.236
(0.667) 		0.458
(0.83) 		0.198
(0.643)
11q loss 5 (6%) 82 1
(1.00) 		0.162
(0.611) 		0.0361
(0.376) 		0.346
(0.747) 		0.00742
(0.204) 		0.00623
(0.195) 		0.347
(0.747) 		0.359
(0.762) 		0.805
(0.964) 		0.832
(0.974)
22q loss 67 (77%) 20 0.113
(0.559) 		0.00854
(0.22) 		0.168
(0.623) 		0.972
(1.00) 		0.0171
(0.26) 		0.00542
(0.177) 		0.016
(0.256) 		0.646
(0.927) 		0.296
(0.732) 		0.422
(0.808)
7q gain 22 (25%) 65 0.709
(0.937) 		0.531
(0.87) 		0.00993
(0.234) 		0.114
(0.559) 		0.269
(0.701) 		0.0219
(0.286) 		0.325
(0.743) 		0.181
(0.633) 		0.324
(0.743) 		0.245
(0.677)
12p gain 18 (21%) 69 0.0128
(0.234) 		0.487
(0.844) 		0.552
(0.877) 		0.142
(0.589) 		0.855
(0.984) 		0.799
(0.964) 		0.723
(0.937) 		0.923
(1.00) 		0.943
(1.00) 		0.932
(1.00)
12q gain 18 (21%) 69 0.0124
(0.234) 		0.485
(0.844) 		0.552
(0.877) 		0.141
(0.589) 		0.857
(0.984) 		0.801
(0.964) 		0.722
(0.937) 		0.922
(1.00) 		0.942
(1.00) 		0.931
(1.00)
17p gain 8 (9%) 79 0.254
(0.691) 		0.669
(0.933) 		0.0358
(0.376) 		0.011
(0.234) 		0.314
(0.738) 		0.671
(0.933) 		0.71
(0.937) 		0.0756
(0.482) 		0.891
(0.988) 		0.309
(0.738)
1p loss 9 (10%) 78 0.0109
(0.234) 		0.465
(0.831) 		0.692
(0.937) 		0.545
(0.872) 		0.318
(0.741) 		0.643
(0.927) 		0.841
(0.976) 		0.389
(0.786) 		1
(1.00) 		0.774
(0.957)
2p loss 6 (7%) 81 0.0609
(0.448) 		0.00309
(0.111) 		0.693
(0.937) 		0.116
(0.559) 		0.207
(0.643) 		0.241
(0.669) 		0.0578
(0.442) 		0.585
(0.898) 		1
(1.00) 		0.181
(0.633)
6q loss 29 (33%) 58 4e-05
(0.00576) 		0.463
(0.831) 		0.971
(1.00) 		0.655
(0.931) 		0.373
(0.771) 		0.69
(0.937) 		0.172
(0.627) 		0.521
(0.869) 		0.113
(0.559) 		0.219
(0.648)
9p loss 28 (32%) 59 0.00253
(0.0959) 		0.0623
(0.451) 		0.0939
(0.52) 		0.111
(0.559) 		0.044
(0.392) 		0.0417
(0.392) 		0.104
(0.558) 		0.492
(0.848) 		0.957
(1.00) 		0.196
(0.643)
13q loss 33 (38%) 54 0.0182
(0.26) 		0.528
(0.87) 		0.535
(0.87) 		0.11
(0.559) 		0.33
(0.744) 		0.647
(0.927) 		0.56
(0.885) 		0.188
(0.643) 		0.0134
(0.234) 		0.34
(0.747)
16p loss 8 (9%) 79 0.0116
(0.234) 		0.708
(0.937) 		0.462
(0.831) 		0.634
(0.925) 		0.438
(0.814) 		0.195
(0.643) 		0.447
(0.817) 		0.322
(0.743) 		0.89
(0.988) 		0.959
(1.00)
18p loss 9 (10%) 78 0.00052
(0.0312) 		0.708
(0.937) 		0.367
(0.768) 		0.544
(0.872) 		0.702
(0.937) 		0.573
(0.897) 		0.789
(0.964) 		0.756
(0.949) 		0.66
(0.932) 		0.574
(0.897)
1p gain 8 (9%) 79 0.156
(0.606) 		0.766
(0.952) 		0.107
(0.559) 		0.0764
(0.482) 		1
(1.00) 		0.763
(0.952) 		0.92
(1.00) 		0.788
(0.964) 		0.54
(0.872) 		0.459
(0.83)
1q gain 20 (23%) 67 0.0784
(0.482) 		0.233
(0.667) 		0.945
(1.00) 		0.895
(0.989) 		0.0387
(0.383) 		0.142
(0.589) 		0.204
(0.643) 		0.106
(0.559) 		0.423
(0.808) 		0.307
(0.738)
2p gain 4 (5%) 83 0.0184
(0.26) 		0.648
(0.927) 		0.377
(0.771) 		0.749
(0.949) 		0.619
(0.916) 		0.758
(0.949) 		0.468
(0.831) 		0.144
(0.589) 		0.583
(0.898) 		0.157
(0.607)
2q gain 6 (7%) 81 0.291
(0.727) 		0.411
(0.795) 		0.869
(0.986) 		0.287
(0.726) 		0.483
(0.844) 		0.577
(0.897) 		0.257
(0.696) 		0.66
(0.932) 		0.161
(0.611) 		0.0562
(0.435)
3p gain 17 (20%) 70 0.153
(0.604) 		1
(1.00) 		0.367
(0.768) 		0.409
(0.795) 		0.775
(0.957) 		0.534
(0.87) 		0.598
(0.91) 		0.882
(0.986) 		0.779
(0.957) 		0.426
(0.808)
3q gain 19 (22%) 68 0.0681
(0.476) 		0.962
(1.00) 		0.625
(0.92) 		0.435
(0.814) 		0.771
(0.957) 		0.315
(0.738) 		0.65
(0.927) 		0.467
(0.831) 		0.62
(0.916) 		0.323
(0.743)
5p gain 24 (28%) 63 0.216
(0.648) 		0.214
(0.648) 		0.806
(0.964) 		0.936
(1.00) 		0.689
(0.937) 		0.804
(0.964) 		0.193
(0.643) 		0.434
(0.814) 		0.515
(0.864) 		0.679
(0.934)
5q gain 14 (16%) 73 0.067
(0.473) 		0.663
(0.933) 		0.704
(0.937) 		0.991
(1.00) 		0.699
(0.937) 		0.854
(0.984) 		0.218
(0.648) 		0.507
(0.857) 		0.201
(0.643) 		0.843
(0.977)
6p gain 7 (8%) 80 0.377
(0.771) 		0.183
(0.634) 		1
(1.00) 		0.125
(0.583) 		0.316
(0.74) 		0.343
(0.747) 		0.646
(0.927) 		0.965
(1.00) 		0.881
(0.986) 		0.813
(0.965)
6q gain 4 (5%) 83 0.238
(0.668) 		0.65
(0.927) 		1
(1.00) 		0.746
(0.949) 		0.837
(0.976) 		0.616
(0.916) 		0.906
(0.998) 		0.936
(1.00) 		0.376
(0.771) 		1
(1.00)
7p gain 25 (29%) 62 0.497
(0.849) 		0.37
(0.769) 		0.0316
(0.348) 		0.265
(0.7) 		0.173
(0.627) 		0.0516
(0.429) 		0.176
(0.63) 		0.0423
(0.392) 		0.173
(0.627) 		0.0522
(0.429)
8p gain 12 (14%) 75 0.718
(0.937) 		0.44
(0.814) 		0.019
(0.264) 		0.228
(0.664) 		0.758
(0.949) 		0.876
(0.986) 		0.281
(0.716) 		0.0384
(0.383) 		0.329
(0.744) 		0.311
(0.738)
8q gain 14 (16%) 73 0.957
(1.00) 		0.0777
(0.482) 		0.0842
(0.497) 		0.724
(0.938) 		0.793
(0.964) 		0.869
(0.986) 		0.606
(0.915) 		0.583
(0.898) 		0.477
(0.838) 		0.502
(0.853)
9q gain 3 (3%) 84 0.171
(0.627) 		0.0319
(0.348) 		0.199
(0.643) 		0.287
(0.726) 		0.364
(0.768) 		0.112
(0.559) 		1
(1.00) 		0.894
(0.988)
10p gain 3 (3%) 84 0.478
(0.838) 		0.676
(0.933) 		0.325
(0.743) 		0.928
(1.00) 		0.877
(0.986) 		0.265
(0.7) 		1
(1.00) 		0.597
(0.91)
10q gain 3 (3%) 84 0.479
(0.838) 		0.672
(0.933) 		0.327
(0.744) 		0.927
(1.00) 		0.877
(0.986) 		0.263
(0.7) 		1
(1.00) 		0.597
(0.91)
11p gain 12 (14%) 75 0.031
(0.348) 		0.345
(0.747) 		0.16
(0.611) 		0.821
(0.969) 		0.33
(0.744) 		0.0532
(0.429) 		0.288
(0.726) 		0.584
(0.898) 		0.672
(0.933) 		0.665
(0.933)
11q gain 12 (14%) 75 0.177
(0.63) 		0.0731
(0.478) 		0.41
(0.795) 		0.956
(1.00) 		0.182
(0.634) 		0.0238
(0.296) 		0.311
(0.738) 		0.547
(0.873) 		0.212
(0.648) 		0.534
(0.87)
13q gain 5 (6%) 82 0.391
(0.786) 		0.0926
(0.52) 		1
(1.00) 		0.883
(0.986) 		0.0234
(0.296) 		0.0222
(0.286) 		0.194
(0.643) 		0.432
(0.814) 		1
(1.00) 		0.18
(0.633)
16p gain 16 (18%) 71 0.251
(0.688) 		0.061
(0.448) 		0.22
(0.648) 		0.755
(0.949) 		0.0898
(0.515) 		0.105
(0.558) 		0.58
(0.898) 		0.333
(0.745) 		0.364
(0.768) 		0.332
(0.744)
16q gain 16 (18%) 71 0.152
(0.604) 		0.197
(0.643) 		0.0709
(0.478) 		0.876
(0.986) 		0.0465
(0.394) 		0.0724
(0.478) 		0.384
(0.779) 		0.66
(0.932) 		0.823
(0.97) 		0.63
(0.924)
17q gain 17 (20%) 70 0.23
(0.664) 		0.312
(0.738) 		0.0173
(0.26) 		0.114
(0.559) 		0.0178
(0.26) 		0.115
(0.559) 		0.424
(0.808) 		0.867
(0.986) 		0.83
(0.974) 		0.572
(0.897)
18p gain 8 (9%) 79 0.156
(0.606) 		0.193
(0.643) 		0.613
(0.916) 		0.828
(0.974) 		0.113
(0.559) 		0.144
(0.589) 		0.0214
(0.286) 		0.137
(0.589) 		0.881
(0.986) 		0.23
(0.664)
18q gain 4 (5%) 83 0.469
(0.831) 		0.312
(0.738) 		0.237
(0.667) 		0.28
(0.716) 		0.366
(0.768) 		0.639
(0.927) 		0.0536
(0.429) 		0.0837
(0.497) 		0.79
(0.964) 		0.0633
(0.451)
19q gain 11 (13%) 76 0.281
(0.716) 		0.269
(0.701) 		0.151
(0.604) 		0.521
(0.869) 		0.677
(0.933) 		0.399
(0.792) 		0.0708
(0.478) 		0.863
(0.986) 		0.688
(0.937) 		0.932
(1.00)
20p gain 8 (9%) 79 0.263
(0.7) 		0.352
(0.753) 		0.68
(0.934) 		0.495
(0.849) 		0.273
(0.708) 		0.806
(0.964) 		0.881
(0.986) 		0.441
(0.814) 		0.721
(0.937) 		0.6
(0.911)
20q gain 11 (13%) 76 0.0961
(0.528) 		0.932
(1.00) 		1
(1.00) 		0.722
(0.937) 		0.753
(0.949) 		1
(1.00) 		0.417
(0.805) 		0.933
(1.00) 		0.33
(0.744) 		0.721
(0.937)
xp gain 7 (8%) 80 0.544
(0.872) 		0.207
(0.643) 		0.298
(0.735) 		0.443
(0.814) 		0.729
(0.938) 		0.696
(0.937) 		0.644
(0.927) 		0.966
(1.00) 		0.687
(0.937) 		1
(1.00)
xq gain 6 (7%) 81 0.684
(0.937) 		0.236
(0.667) 		0.294
(0.731) 		0.688
(0.937) 		0.652
(0.927) 		0.533
(0.87) 		0.537
(0.87) 		0.84
(0.976) 		1
(1.00) 		0.934
(1.00)
2q loss 5 (6%) 82 0.0869
(0.509) 		0.0461
(0.394) 		1
(1.00) 		0.244
(0.677) 		0.355
(0.758) 		0.612
(0.916) 		0.197
(0.643) 		0.47
(0.831) 		0.806
(0.964) 		0.834
(0.974)
3p loss 8 (9%) 79 0.142
(0.589) 		0.697
(0.937) 		0.632
(0.925) 		0.538
(0.87) 		0.171
(0.627) 		0.114
(0.559) 		0.0296
(0.345) 		0.712
(0.937) 		0.134
(0.589) 		0.131
(0.589)
3q loss 7 (8%) 80 0.489
(0.845) 		0.38
(0.773) 		0.629
(0.924) 		0.214
(0.648) 		0.216
(0.648) 		0.27
(0.701) 		0.0527
(0.429) 		0.72
(0.937) 		0.342
(0.747) 		0.162
(0.611)
5p loss 4 (5%) 83 0.765
(0.952) 		0.938
(1.00) 		0.241
(0.669) 		0.537
(0.87) 		0.525
(0.87) 		0.726
(0.938) 		0.907
(0.998) 		0.936
(1.00) 		1
(1.00) 		0.202
(0.643)
5q loss 9 (10%) 78 0.15
(0.604) 		0.747
(0.949) 		0.19
(0.643) 		0.212
(0.648) 		0.5
(0.852) 		0.0934
(0.52) 		0.254
(0.691) 		0.668
(0.933) 		0.89
(0.988) 		0.808
(0.964)
6p loss 8 (9%) 79 0.404
(0.795) 		0.159
(0.611) 		0.237
(0.667) 		0.791
(0.964) 		0.437
(0.814) 		0.611
(0.916) 		0.118
(0.559) 		0.22
(0.648) 		0.89
(0.988) 		0.153
(0.604)
8p loss 13 (15%) 74 0.755
(0.949) 		0.0901
(0.515) 		0.859
(0.985) 		0.935
(1.00) 		0.553
(0.877) 		0.737
(0.944) 		0.143
(0.589) 		0.752
(0.949) 		0.736
(0.944) 		0.757
(0.949)
8q loss 4 (5%) 83 0.426
(0.808) 		0.816
(0.966) 		0.235
(0.667) 		0.277
(0.714) 		0.442
(0.814) 		0.513
(0.862) 		0.0435
(0.392) 		0.118
(0.559) 		0.375
(0.771) 		0.439
(0.814)
9q loss 22 (25%) 65 0.0898
(0.515) 		0.301
(0.738) 		0.0391
(0.383) 		0.251
(0.688) 		0.3
(0.738) 		0.343
(0.747) 		0.0593
(0.448) 		0.534
(0.87) 		0.291
(0.727) 		0.494
(0.848)
10q loss 19 (22%) 68 0.193
(0.643) 		0.324
(0.743) 		0.211
(0.648) 		0.922
(1.00) 		0.486
(0.844) 		0.305
(0.738) 		0.116
(0.559) 		0.722
(0.937) 		0.942
(1.00) 		0.857
(0.984)
11p loss 4 (5%) 83 0.394
(0.79) 		0.451
(0.819) 		0.237
(0.667) 		0.206
(0.643) 		0.368
(0.768) 		0.343
(0.747) 		1
(1.00) 		0.396
(0.79) 		0.806
(0.964) 		0.832
(0.974)
12p loss 4 (5%) 83 0.127
(0.589) 		0.812
(0.964) 		0.338
(0.747) 		0.179
(0.633) 		0.442
(0.814) 		0.395
(0.79) 		0.597
(0.91) 		0.818
(0.967) 		1
(1.00) 		0.892
(0.988)
15q loss 11 (13%) 76 0.664
(0.933) 		0.84
(0.976) 		0.574
(0.897) 		0.498
(0.849) 		0.341
(0.747) 		0.378
(0.771) 		0.204
(0.643) 		0.306
(0.738) 		0.73
(0.938) 		0.542
(0.872)
16q loss 11 (13%) 76 0.0424
(0.392) 		0.952
(1.00) 		0.41
(0.795) 		0.864
(0.986) 		0.207
(0.643) 		0.313
(0.738) 		0.468
(0.831) 		0.144
(0.589) 		1
(1.00) 		0.573
(0.897)
17p loss 23 (26%) 64 0.807
(0.964) 		0.0974
(0.528) 		0.758
(0.949) 		0.0302
(0.345) 		0.673
(0.933) 		0.507
(0.857) 		0.14
(0.589) 		0.139
(0.589) 		0.0558
(0.435) 		0.191
(0.643)
17q loss 7 (8%) 80 0.617
(0.916) 		0.148
(0.597) 		0.338
(0.747) 		0.0781
(0.482) 		0.647
(0.927) 		0.635
(0.925) 		0.699
(0.937) 		0.531
(0.87) 		0.411
(0.795) 		0.357
(0.759)
18q loss 14 (16%) 73 0.0158
(0.256) 		0.747
(0.949) 		0.809
(0.964) 		0.405
(0.795) 		0.727
(0.938) 		0.852
(0.984) 		0.465
(0.831) 		0.0925
(0.52) 		0.561
(0.886) 		0.165
(0.62)
19p loss 4 (5%) 83 0.765
(0.952) 		0.264
(0.7) 		1
(1.00) 		0.0974
(0.528) 		0.617
(0.916) 		0.448
(0.817) 		0.704
(0.937) 		0.348
(0.749) 		0.147
(0.597) 		0.624
(0.92)
19q loss 7 (8%) 80 1
(1.00) 		0.617
(0.916) 		0.695
(0.937) 		0.0217
(0.286) 		1
(1.00) 		0.881
(0.986) 		0.87
(0.986) 		0.79
(0.964) 		0.281
(0.716) 		0.702
(0.937)
20p loss 14 (16%) 73 0.0779
(0.482) 		0.0761
(0.482) 		0.676
(0.933) 		0.774
(0.957) 		0.134
(0.589) 		0.536
(0.87) 		0.846
(0.98) 		0.722
(0.937) 		0.369
(0.768) 		0.119
(0.562)
21q loss 11 (13%) 76 0.312
(0.738) 		0.602
(0.912) 		0.65
(0.927) 		0.779
(0.957) 		0.261
(0.7) 		0.0728
(0.478) 		0.193
(0.643) 		0.294
(0.731) 		0.776
(0.957) 		0.864
(0.986)
'7q gain' versus 'RPPA_CNMF'

P value = 0.00993 (Fisher's exact test), Q value = 0.23

Table S1.  Gene #12: '7q gain' versus Molecular Subtype #3: 'RPPA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 8 24 24 7
7Q GAIN MUTATED 6 7 5 0
7Q GAIN WILD-TYPE 2 17 19 7

Figure S1.  Get High-res Image Gene #12: '7q gain' versus Molecular Subtype #3: 'RPPA_CNMF'

'12p gain' versus 'CN_CNMF'

P value = 0.0128 (Fisher's exact test), Q value = 0.23

Table S2.  Gene #20: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
12P GAIN MUTATED 4 9 4 1
12P GAIN WILD-TYPE 23 12 12 22

Figure S2.  Get High-res Image Gene #20: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

'12q gain' versus 'CN_CNMF'

P value = 0.0124 (Fisher's exact test), Q value = 0.23

Table S3.  Gene #21: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
12Q GAIN MUTATED 4 9 4 1
12Q GAIN WILD-TYPE 23 12 12 22

Figure S3.  Get High-res Image Gene #21: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

'15q gain' versus 'METHLYATION_CNMF'

P value = 0.00536 (Fisher's exact test), Q value = 0.18

Table S4.  Gene #23: '15q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 16 19 18 25 9
15Q GAIN MUTATED 0 4 3 0 3
15Q GAIN WILD-TYPE 16 15 15 25 6

Figure S4.  Get High-res Image Gene #23: '15q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'15q gain' versus 'MIRSEQ_CNMF'

P value = 0.00722 (Fisher's exact test), Q value = 0.2

Table S5.  Gene #23: '15q gain' versus Molecular Subtype #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 21 25 16 25
15Q GAIN MUTATED 5 0 0 5
15Q GAIN WILD-TYPE 16 25 16 20

Figure S5.  Get High-res Image Gene #23: '15q gain' versus Molecular Subtype #7: 'MIRSEQ_CNMF'

'15q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.0131 (Fisher's exact test), Q value = 0.23

Table S6.  Gene #23: '15q gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 29 25 6 13 14
15Q GAIN MUTATED 0 7 0 2 1
15Q GAIN WILD-TYPE 29 18 6 11 13

Figure S6.  Get High-res Image Gene #23: '15q gain' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

'17p gain' versus 'RPPA_CHIERARCHICAL'

P value = 0.011 (Fisher's exact test), Q value = 0.23

Table S7.  Gene #26: '17p gain' versus Molecular Subtype #4: 'RPPA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 9 11 10 12 9 12
17P GAIN MUTATED 4 0 0 1 0 1
17P GAIN WILD-TYPE 5 11 10 11 9 11

Figure S7.  Get High-res Image Gene #26: '17p gain' versus Molecular Subtype #4: 'RPPA_CHIERARCHICAL'

'19p gain' versus 'CN_CNMF'

P value = 0.0108 (Fisher's exact test), Q value = 0.23

Table S8.  Gene #30: '19p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
19P GAIN MUTATED 0 4 5 5
19P GAIN WILD-TYPE 27 17 11 18

Figure S8.  Get High-res Image Gene #30: '19p gain' versus Molecular Subtype #1: 'CN_CNMF'

'19p gain' versus 'METHLYATION_CNMF'

P value = 0.0111 (Fisher's exact test), Q value = 0.23

Table S9.  Gene #30: '19p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 16 19 18 25 9
19P GAIN MUTATED 0 5 6 1 2
19P GAIN WILD-TYPE 16 14 12 24 7

Figure S9.  Get High-res Image Gene #30: '19p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'21q gain' versus 'METHLYATION_CNMF'

P value = 0.00722 (Fisher's exact test), Q value = 0.2

Table S10.  Gene #34: '21q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 16 19 18 25 9
21Q GAIN MUTATED 1 2 0 0 3
21Q GAIN WILD-TYPE 15 17 18 25 6

Figure S10.  Get High-res Image Gene #34: '21q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'21q gain' versus 'MIRSEQ_CNMF'

P value = 0.00197 (Fisher's exact test), Q value = 0.083

Table S11.  Gene #34: '21q gain' versus Molecular Subtype #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 21 25 16 25
21Q GAIN MUTATED 5 0 1 0
21Q GAIN WILD-TYPE 16 25 15 25

Figure S11.  Get High-res Image Gene #34: '21q gain' versus Molecular Subtype #7: 'MIRSEQ_CNMF'

'1p loss' versus 'CN_CNMF'

P value = 0.0109 (Fisher's exact test), Q value = 0.23

Table S12.  Gene #37: '1p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
1P LOSS MUTATED 0 5 3 1
1P LOSS WILD-TYPE 27 16 13 22

Figure S12.  Get High-res Image Gene #37: '1p loss' versus Molecular Subtype #1: 'CN_CNMF'

'2p loss' versus 'METHLYATION_CNMF'

P value = 0.00309 (Fisher's exact test), Q value = 0.11

Table S13.  Gene #38: '2p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 16 19 18 25 9
2P LOSS MUTATED 0 4 0 0 2
2P LOSS WILD-TYPE 16 15 18 25 7

Figure S13.  Get High-res Image Gene #38: '2p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'4p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0024

Table S14.  Gene #42: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
4P LOSS MUTATED 0 16 9 8
4P LOSS WILD-TYPE 27 5 7 15

Figure S14.  Get High-res Image Gene #42: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

'4p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.0148 (Fisher's exact test), Q value = 0.25

Table S15.  Gene #42: '4p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 23 12 21 15 16
4P LOSS MUTATED 3 7 11 4 8
4P LOSS WILD-TYPE 20 5 10 11 8

Figure S15.  Get High-res Image Gene #42: '4p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'4q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0024

Table S16.  Gene #43: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
4Q LOSS MUTATED 0 16 7 11
4Q LOSS WILD-TYPE 27 5 9 12

Figure S16.  Get High-res Image Gene #43: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

'4q loss' versus 'METHLYATION_CNMF'

P value = 0.0136 (Fisher's exact test), Q value = 0.23

Table S17.  Gene #43: '4q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 16 19 18 25 9
4Q LOSS MUTATED 2 13 7 8 4
4Q LOSS WILD-TYPE 14 6 11 17 5

Figure S17.  Get High-res Image Gene #43: '4q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'4q loss' versus 'MRNASEQ_CNMF'

P value = 0.00192 (Fisher's exact test), Q value = 0.083

Table S18.  Gene #43: '4q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 26 21 19 21
4Q LOSS MUTATED 3 12 7 12
4Q LOSS WILD-TYPE 23 9 12 9

Figure S18.  Get High-res Image Gene #43: '4q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'4q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00023 (Fisher's exact test), Q value = 0.017

Table S19.  Gene #43: '4q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 23 12 21 15 16
4Q LOSS MUTATED 1 6 12 5 10
4Q LOSS WILD-TYPE 22 6 9 10 6

Figure S19.  Get High-res Image Gene #43: '4q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'4q loss' versus 'MIRSEQ_CNMF'

P value = 0.01 (Fisher's exact test), Q value = 0.23

Table S20.  Gene #43: '4q loss' versus Molecular Subtype #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 21 25 16 25
4Q LOSS MUTATED 13 9 8 4
4Q LOSS WILD-TYPE 8 16 8 21

Figure S20.  Get High-res Image Gene #43: '4q loss' versus Molecular Subtype #7: 'MIRSEQ_CNMF'

'6q loss' versus 'CN_CNMF'

P value = 4e-05 (Fisher's exact test), Q value = 0.0058

Table S21.  Gene #47: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
6Q LOSS MUTATED 10 15 2 2
6Q LOSS WILD-TYPE 17 6 14 21

Figure S21.  Get High-res Image Gene #47: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'CN_CNMF'

P value = 0.00253 (Fisher's exact test), Q value = 0.096

Table S22.  Gene #50: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
9P LOSS MUTATED 4 12 8 4
9P LOSS WILD-TYPE 23 9 8 19

Figure S22.  Get High-res Image Gene #50: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'CN_CNMF'

P value = 0.00212 (Fisher's exact test), Q value = 0.085

Table S23.  Gene #52: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
10P LOSS MUTATED 2 10 8 5
10P LOSS WILD-TYPE 25 11 8 18

Figure S23.  Get High-res Image Gene #52: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'MIRSEQ_CNMF'

P value = 0.0132 (Fisher's exact test), Q value = 0.23

Table S24.  Gene #52: '10p loss' versus Molecular Subtype #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 21 25 16 25
10P LOSS MUTATED 10 10 2 3
10P LOSS WILD-TYPE 11 15 14 22

Figure S24.  Get High-res Image Gene #52: '10p loss' versus Molecular Subtype #7: 'MIRSEQ_CNMF'

'11q loss' versus 'MRNASEQ_CNMF'

P value = 0.00742 (Fisher's exact test), Q value = 0.2

Table S25.  Gene #55: '11q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 26 21 19 21
11Q LOSS MUTATED 0 1 4 0
11Q LOSS WILD-TYPE 26 20 15 21

Figure S25.  Get High-res Image Gene #55: '11q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'11q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00623 (Fisher's exact test), Q value = 0.2

Table S26.  Gene #55: '11q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 23 12 21 15 16
11Q LOSS MUTATED 0 0 1 4 0
11Q LOSS WILD-TYPE 23 12 20 11 16

Figure S26.  Get High-res Image Gene #55: '11q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'13q loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.0134 (Fisher's exact test), Q value = 0.23

Table S27.  Gene #57: '13q loss' versus Molecular Subtype #9: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 39 23 23
13Q LOSS MUTATED 16 12 3
13Q LOSS WILD-TYPE 23 11 20

Figure S27.  Get High-res Image Gene #57: '13q loss' versus Molecular Subtype #9: 'MIRSEQ_MATURE_CNMF'

'14q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0024

Table S28.  Gene #58: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
14Q LOSS MUTATED 1 13 8 13
14Q LOSS WILD-TYPE 26 8 8 10

Figure S28.  Get High-res Image Gene #58: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

'14q loss' versus 'METHLYATION_CNMF'

P value = 0.00018 (Fisher's exact test), Q value = 0.014

Table S29.  Gene #58: '14q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 16 19 18 25 9
14Q LOSS MUTATED 2 15 5 7 6
14Q LOSS WILD-TYPE 14 4 13 18 3

Figure S29.  Get High-res Image Gene #58: '14q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'14q loss' versus 'MRNASEQ_CNMF'

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

Table S30.  Gene #58: '14q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 26 21 19 21
14Q LOSS MUTATED 5 17 4 9
14Q LOSS WILD-TYPE 21 4 15 12

Figure S30.  Get High-res Image Gene #58: '14q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'14q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2e-05 (Fisher's exact test), Q value = 0.0036

Table S31.  Gene #58: '14q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 23 12 21 15 16
14Q LOSS MUTATED 4 7 17 1 6
14Q LOSS WILD-TYPE 19 5 4 14 10

Figure S31.  Get High-res Image Gene #58: '14q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'14q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00058 (Fisher's exact test), Q value = 0.032

Table S32.  Gene #58: '14q loss' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 29 25 6 13 14
14Q LOSS MUTATED 7 16 3 8 1
14Q LOSS WILD-TYPE 22 9 3 5 13

Figure S32.  Get High-res Image Gene #58: '14q loss' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

'14q loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.00083 (Fisher's exact test), Q value = 0.043

Table S33.  Gene #58: '14q loss' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 17 18 16 34
14Q LOSS MUTATED 2 14 6 12
14Q LOSS WILD-TYPE 15 4 10 22

Figure S33.  Get High-res Image Gene #58: '14q loss' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

'16p loss' versus 'CN_CNMF'

P value = 0.0116 (Fisher's exact test), Q value = 0.23

Table S34.  Gene #60: '16p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
16P LOSS MUTATED 0 5 0 3
16P LOSS WILD-TYPE 27 16 16 20

Figure S34.  Get High-res Image Gene #60: '16p loss' versus Molecular Subtype #1: 'CN_CNMF'

'18p loss' versus 'CN_CNMF'

P value = 0.00052 (Fisher's exact test), Q value = 0.031

Table S35.  Gene #64: '18p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
18P LOSS MUTATED 0 7 0 2
18P LOSS WILD-TYPE 27 14 16 21

Figure S35.  Get High-res Image Gene #64: '18p loss' versus Molecular Subtype #1: 'CN_CNMF'

'22q loss' versus 'METHLYATION_CNMF'

P value = 0.00854 (Fisher's exact test), Q value = 0.22

Table S36.  Gene #70: '22q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 16 19 18 25 9
22Q LOSS MUTATED 12 15 18 14 8
22Q LOSS WILD-TYPE 4 4 0 11 1

Figure S36.  Get High-res Image Gene #70: '22q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'22q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00542 (Fisher's exact test), Q value = 0.18

Table S37.  Gene #70: '22q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 23 12 21 15 16
22Q LOSS MUTATED 16 12 17 7 15
22Q LOSS WILD-TYPE 7 0 4 8 1

Figure S37.  Get High-res Image Gene #70: '22q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'xp loss' versus 'CN_CNMF'

P value = 0.00092 (Fisher's exact test), Q value = 0.044

Table S38.  Gene #71: 'xp loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
XP LOSS MUTATED 3 11 9 4
XP LOSS WILD-TYPE 24 10 7 19

Figure S38.  Get High-res Image Gene #71: 'xp loss' versus Molecular Subtype #1: 'CN_CNMF'

'xp loss' versus 'METHLYATION_CNMF'

P value = 9e-05 (Fisher's exact test), Q value = 0.0081

Table S39.  Gene #71: 'xp loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 16 19 18 25 9
XP LOSS MUTATED 5 11 8 0 3
XP LOSS WILD-TYPE 11 8 10 25 6

Figure S39.  Get High-res Image Gene #71: 'xp loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'xp loss' versus 'RPPA_CNMF'

P value = 0.0129 (Fisher's exact test), Q value = 0.23

Table S40.  Gene #71: 'xp loss' versus Molecular Subtype #3: 'RPPA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 8 24 24 7
XP LOSS MUTATED 0 11 10 0
XP LOSS WILD-TYPE 8 13 14 7

Figure S40.  Get High-res Image Gene #71: 'xp loss' versus Molecular Subtype #3: 'RPPA_CNMF'

'xq loss' versus 'CN_CNMF'

P value = 3e-04 (Fisher's exact test), Q value = 0.02

Table S41.  Gene #72: 'xq loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 21 16 23
XQ LOSS MUTATED 3 11 10 4
XQ LOSS WILD-TYPE 24 10 6 19

Figure S41.  Get High-res Image Gene #72: 'xq loss' versus Molecular Subtype #1: 'CN_CNMF'

'xq loss' versus 'METHLYATION_CNMF'

P value = 7e-05 (Fisher's exact test), Q value = 0.0072

Table S42.  Gene #72: 'xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 16 19 18 25 9
XQ LOSS MUTATED 6 11 8 0 3
XQ LOSS WILD-TYPE 10 8 10 25 6

Figure S42.  Get High-res Image Gene #72: 'xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'xq loss' versus 'RPPA_CNMF'

P value = 0.00766 (Fisher's exact test), Q value = 0.2

Table S43.  Gene #72: 'xq loss' versus Molecular Subtype #3: 'RPPA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 8 24 24 7
XQ LOSS MUTATED 0 12 10 0
XQ LOSS WILD-TYPE 8 12 14 7

Figure S43.  Get High-res Image Gene #72: 'xq loss' versus Molecular Subtype #3: 'RPPA_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/MESO-TP/22533659/transformed.cor.cli.txt

  • Molecular subtypes file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/MESO-TP/22541489/MESO-TP.transferedmergedcluster.txt

  • Number of patients = 87

  • Number of significantly arm-level cnvs = 72

  • 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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