Correlation between copy number variations of arm-level result and molecular subtypes
Mesothelioma (Primary solid tumor)
21 August 2015  |  analyses__2015_08_21
Maintainer Information
Citation Information
doi:10.7908/C14F1Q0V
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/C14F1Q0V
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 74 arm-level events and 10 molecular subtypes across 87 patients, 47 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 1p gain cnv correlated to 'CN_CNMF'.

  • 1q gain cnv correlated to 'CN_CNMF'.

  • 3p gain cnv correlated to 'CN_CNMF'.

  • 3q gain cnv correlated to 'CN_CNMF'.

  • 7p gain cnv correlated to 'CN_CNMF'.

  • 11p gain cnv correlated to 'CN_CNMF'.

  • 11q gain cnv correlated to 'CN_CNMF'.

  • 12p gain cnv correlated to 'CN_CNMF'.

  • 12q gain cnv correlated to 'CN_CNMF'.

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

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

  • 16q gain cnv correlated to 'CN_CNMF'.

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

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

  • 6q loss cnv correlated to 'CN_CNMF'.

  • 9p loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 9q loss cnv correlated to 'CN_CNMF' and 'RPPA_CNMF'.

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

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

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

  • 16p loss cnv correlated to 'CN_CNMF'.

  • 21q loss cnv correlated to 'METHLYATION_CNMF'.

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

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

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

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 74 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, 47 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 0.00056
(0.0296) 		0.36
(0.779) 		0.777
(0.953) 		0.426
(0.811) 		0.00026
(0.0197) 		1e-05
(0.00247) 		0.0488
(0.441) 		0.0006
(0.0296) 		0.0141
(0.229) 		0.00167
(0.0727)
15q gain 11 (13%) 76 0.025
(0.309) 		0.0043
(0.111) 		0.178
(0.603) 		0.0117
(0.211) 		0.0197
(0.291) 		0.13
(0.547) 		0.00352
(0.109) 		0.0782
(0.51) 		0.774
(0.953) 		0.226
(0.667)
4q loss 33 (38%) 54 1e-05
(0.00247) 		0.101
(0.535) 		0.036
(0.381) 		0.154
(0.565) 		0.004
(0.111) 		0.00029
(0.0197) 		0.0579
(0.487) 		0.145
(0.552) 		0.776
(0.953) 		0.09
(0.529)
9p loss 28 (32%) 59 1e-05
(0.00247) 		0.015
(0.236) 		0.0925
(0.529) 		0.113
(0.535) 		0.0417
(0.414) 		0.0105
(0.195) 		0.958
(1.00) 		0.487
(0.847) 		0.914
(0.992) 		0.154
(0.565)
22q loss 67 (77%) 20 0.00539
(0.125) 		3e-05
(0.00555) 		0.821
(0.972) 		0.973
(1.00) 		0.0555
(0.478) 		0.0045
(0.111) 		1
(1.00) 		0.641
(0.921) 		0.131
(0.547) 		0.832
(0.976)
xp loss 27 (31%) 60 0.00527
(0.125) 		0.00013
(0.012) 		0.0683
(0.501) 		0.13
(0.547) 		0.0682
(0.501) 		0.00724
(0.153) 		0.0917
(0.529) 		0.418
(0.807) 		0.0741
(0.505) 		0.305
(0.752)
xq loss 28 (32%) 59 0.00196
(0.0763) 		0.00012
(0.012) 		0.134
(0.547) 		0.405
(0.799) 		0.0859
(0.521) 		0.003
(0.101) 		0.155
(0.565) 		0.41
(0.801) 		0.0679
(0.501) 		0.313
(0.764)
16p gain 17 (20%) 70 0.00666
(0.145) 		0.567
(0.885) 		0.527
(0.865) 		0.756
(0.948) 		0.012
(0.212) 		0.0663
(0.501) 		0.178
(0.603) 		0.187
(0.618) 		0.634
(0.921) 		0.081
(0.512)
4p loss 32 (37%) 55 5e-05
(0.0074) 		0.323
(0.766) 		0.0579
(0.487) 		0.388
(0.793) 		0.272
(0.712) 		0.00422
(0.111) 		0.131
(0.547) 		0.333
(0.769) 		0.39
(0.793) 		0.512
(0.86)
9q loss 21 (24%) 66 0.00181
(0.0744) 		0.206
(0.641) 		0.00618
(0.139) 		0.0675
(0.501) 		0.142
(0.549) 		0.161
(0.573) 		0.95
(1.00) 		0.538
(0.865) 		0.578
(0.893) 		0.259
(0.704)
10p loss 24 (28%) 63 0.00434
(0.111) 		0.00074
(0.0342) 		0.127
(0.547) 		0.593
(0.9) 		0.133
(0.547) 		0.136
(0.547) 		0.871
(0.985) 		0.304
(0.752) 		0.707
(0.934) 		0.729
(0.947)
11q loss 5 (6%) 82 0.577
(0.893) 		0.618
(0.916) 		0.256
(0.704) 		0.346
(0.772) 		0.00447
(0.111) 		0.00276
(0.0973) 		0.848
(0.977) 		0.358
(0.779) 		0.561
(0.882) 		0.913
(0.992)
1p gain 10 (11%) 77 0.0142
(0.229) 		0.78
(0.953) 		0.382
(0.793) 		0.442
(0.822) 		0.768
(0.953) 		0.683
(0.925) 		0.44
(0.822) 		0.821
(0.972) 		0.232
(0.668) 		0.343
(0.772)
1q gain 21 (24%) 66 0.00919
(0.184) 		0.0317
(0.356) 		0.841
(0.977) 		0.771
(0.953) 		0.102
(0.535) 		0.155
(0.565) 		0.228
(0.667) 		0.205
(0.641) 		0.575
(0.893) 		0.507
(0.855)
3p gain 17 (20%) 70 0.00056
(0.0296) 		0.931
(0.997) 		0.107
(0.535) 		0.407
(0.799) 		0.619
(0.916) 		0.626
(0.921) 		0.886
(0.985) 		0.883
(0.985) 		0.44
(0.822) 		0.608
(0.908)
3q gain 19 (22%) 68 0.00012
(0.012) 		0.768
(0.953) 		0.23
(0.668) 		0.431
(0.815) 		0.668
(0.925) 		0.388
(0.793) 		0.456
(0.829) 		0.467
(0.831) 		0.328
(0.767) 		0.54
(0.865)
7p gain 25 (29%) 62 0.0141
(0.229) 		0.391
(0.793) 		0.371
(0.787) 		0.263
(0.704) 		0.0954
(0.529) 		0.0719
(0.502) 		0.0966
(0.529) 		0.0421
(0.414) 		0.319
(0.764) 		0.0244
(0.309)
11p gain 11 (13%) 76 0.00745
(0.153) 		0.664
(0.925) 		0.636
(0.921) 		0.823
(0.972) 		0.294
(0.749) 		0.0921
(0.529) 		0.39
(0.793) 		0.666
(0.925) 		1
(1.00) 		0.826
(0.972)
11q gain 12 (14%) 75 0.00968
(0.189) 		0.381
(0.793) 		0.751
(0.948) 		0.955
(1.00) 		0.0655
(0.501) 		0.0353
(0.378) 		0.529
(0.865) 		0.545
(0.87) 		0.566
(0.885) 		0.482
(0.847)
12p gain 18 (21%) 69 0.00031
(0.0197) 		0.813
(0.972) 		0.487
(0.847) 		0.141
(0.549) 		0.893
(0.988) 		0.852
(0.977) 		0.751
(0.948) 		0.922
(0.992) 		1
(1.00) 		0.862
(0.983)
12q gain 18 (21%) 69 0.00032
(0.0197) 		0.815
(0.972) 		0.481
(0.847) 		0.141
(0.549) 		0.891
(0.987) 		0.853
(0.977) 		0.749
(0.948) 		0.922
(0.992) 		1
(1.00) 		0.861
(0.983)
16q gain 16 (18%) 71 0.00238
(0.0881) 		0.806
(0.968) 		0.529
(0.865) 		0.878
(0.985) 		0.0229
(0.309) 		0.107
(0.535) 		0.561
(0.882) 		0.66
(0.925) 		0.875
(0.985) 		0.376
(0.791)
6q loss 29 (33%) 58 0.00331
(0.106) 		0.214
(0.652) 		0.578
(0.893) 		0.66
(0.925) 		0.395
(0.794) 		0.65
(0.925) 		0.653
(0.925) 		0.521
(0.865) 		0.113
(0.535) 		0.0817
(0.512)
16p loss 7 (8%) 80 0.00994
(0.189) 		0.192
(0.628) 		0.965
(1.00) 		0.33
(0.767) 		0.532
(0.865) 		0.347
(0.772) 		0.415
(0.807) 		0.364
(0.782) 		1
(1.00) 		1
(1.00)
21q loss 11 (13%) 76 0.108
(0.535) 		0.0129
(0.222) 		0.395
(0.794) 		0.78
(0.953) 		0.222
(0.665) 		0.0803
(0.512) 		0.655
(0.925) 		0.295
(0.749) 		0.846
(0.977) 		0.824
(0.972)
2p gain 4 (5%) 83 0.104
(0.535) 		0.375
(0.791) 		0.966
(1.00) 		0.744
(0.948) 		0.604
(0.906) 		0.786
(0.953) 		0.122
(0.543) 		0.142
(0.549) 		0.356
(0.779) 		0.185
(0.615)
2q gain 7 (8%) 80 0.516
(0.86) 		0.462
(0.831) 		0.904
(0.991) 		0.604
(0.906) 		0.36
(0.779) 		0.425
(0.811) 		0.247
(0.697) 		0.912
(0.992) 		0.135
(0.547) 		0.0644
(0.501)
5p gain 24 (28%) 63 0.196
(0.638) 		0.329
(0.767) 		0.0961
(0.529) 		0.937
(0.997) 		0.514
(0.86) 		0.58
(0.893) 		0.0388
(0.399) 		0.433
(0.818) 		0.494
(0.852) 		0.446
(0.823)
5q gain 15 (17%) 72 0.0604
(0.496) 		0.354
(0.779) 		0.501
(0.852) 		0.992
(1.00) 		0.3
(0.75) 		0.69
(0.925) 		0.151
(0.565) 		0.367
(0.785) 		0.34
(0.772) 		0.345
(0.772)
6p gain 7 (8%) 80 0.0757
(0.509) 		0.0953
(0.529) 		0.866
(0.984) 		0.125
(0.547) 		0.0681
(0.501) 		0.386
(0.793) 		0.0719
(0.502) 		0.966
(1.00) 		0.884
(0.985) 		0.715
(0.94)
6q gain 4 (5%) 83 0.102
(0.535) 		0.633
(0.921) 		0.907
(0.991) 		0.746
(0.948) 		0.401
(0.799) 		0.694
(0.925) 		0.674
(0.925) 		0.936
(0.997) 		0.68
(0.925) 		0.752
(0.948)
7q gain 22 (25%) 65 0.0241
(0.309) 		0.447
(0.823) 		0.659
(0.925) 		0.114
(0.535) 		0.143
(0.549) 		0.03
(0.342) 		0.228
(0.667) 		0.183
(0.611) 		0.528
(0.865) 		0.116
(0.535)
8p gain 12 (14%) 75 0.0463
(0.429) 		0.523
(0.865) 		0.341
(0.772) 		0.231
(0.668) 		0.664
(0.925) 		0.76
(0.951) 		0.141
(0.549) 		0.0382
(0.399) 		0.6
(0.906) 		0.249
(0.697)
8q gain 14 (16%) 73 0.0488
(0.441) 		0.934
(0.997) 		0.228
(0.667) 		0.723
(0.944) 		0.7
(0.929) 		0.75
(0.948) 		0.262
(0.704) 		0.586
(0.896) 		0.746
(0.948) 		0.541
(0.865)
9p gain 3 (3%) 84 0.702
(0.929) 		0.533
(0.865) 		0.317
(0.764) 		1
(1.00) 		0.112
(0.535) 		0.807
(0.968) 		0.1
(0.535) 		0.0263
(0.314)
9q gain 4 (5%) 83 0.5
(0.852) 		0.0711
(0.502) 		0.45
(0.824) 		1
(1.00) 		0.473
(0.838) 		0.636
(0.921) 		0.0586
(0.487) 		0.468
(0.831) 		0.814
(0.972) 		0.693
(0.925)
10p gain 3 (3%) 84 0.0785
(0.51) 		0.775
(0.953) 		0.883
(0.985) 		0.918
(0.992) 		1
(1.00) 		0.265
(0.704) 		1
(1.00) 		0.886
(0.985)
10q gain 3 (3%) 84 0.0808
(0.512) 		0.775
(0.953) 		0.885
(0.985) 		0.921
(0.992) 		1
(1.00) 		0.265
(0.704) 		1
(1.00) 		0.89
(0.987)
13q gain 5 (6%) 82 0.421
(0.807) 		0.098
(0.533) 		0.348
(0.772) 		0.883
(0.985) 		0.0267
(0.314) 		0.0454
(0.425) 		0.611
(0.91) 		0.431
(0.815) 		0.851
(0.977) 		0.386
(0.793)
17p gain 7 (8%) 80 0.221
(0.665) 		1
(1.00) 		0.151
(0.565) 		0.0705
(0.502) 		0.442
(0.822) 		0.684
(0.925) 		0.696
(0.927) 		0.113
(0.535) 		0.468
(0.831) 		0.245
(0.697)
17q gain 17 (20%) 70 0.0929
(0.529) 		0.318
(0.764) 		0.3
(0.75) 		0.114
(0.535) 		0.0217
(0.303) 		0.0443
(0.421) 		0.146
(0.552) 		0.868
(0.985) 		0.74
(0.948) 		0.846
(0.977)
18p gain 8 (9%) 79 0.0673
(0.501) 		0.318
(0.764) 		0.402
(0.799) 		0.825
(0.972) 		0.118
(0.54) 		0.183
(0.611) 		0.12
(0.54) 		0.135
(0.547) 		0.605
(0.906) 		0.134
(0.547)
18q gain 4 (5%) 83 0.0851
(0.521) 		1
(1.00) 		0.263
(0.704) 		0.279
(0.721) 		0.301
(0.75) 		0.637
(0.921) 		0.0335
(0.369) 		0.0832
(0.518) 		0.606
(0.907) 		0.193
(0.628)
19p gain 14 (16%) 73 0.271
(0.712) 		0.0339
(0.369) 		0.857
(0.98) 		0.581
(0.893) 		0.161
(0.573) 		0.172
(0.596) 		0.463
(0.831) 		0.174
(0.599) 		0.69
(0.925) 		0.206
(0.641)
19q gain 10 (11%) 77 0.802
(0.965) 		0.118
(0.54) 		0.484
(0.847) 		0.591
(0.898) 		0.325
(0.767) 		0.686
(0.925) 		0.532
(0.865) 		0.712
(0.939) 		0.541
(0.865) 		0.895
(0.988)
20p gain 8 (9%) 79 0.693
(0.925) 		0.729
(0.947) 		0.665
(0.925) 		0.491
(0.851) 		0.384
(0.793) 		0.783
(0.953) 		0.581
(0.893) 		0.445
(0.823) 		0.641
(0.921) 		0.67
(0.925)
20q gain 10 (11%) 77 0.206
(0.641) 		0.907
(0.991) 		0.847
(0.977) 		0.752
(0.948) 		0.641
(0.921) 		0.937
(0.997) 		0.321
(0.765) 		0.747
(0.948) 		0.525
(0.865) 		0.591
(0.898)
21q gain 6 (7%) 81 0.252
(0.704) 		0.614
(0.912) 		0.639
(0.921) 		0.605
(0.906) 		0.224
(0.667) 		0.217
(0.658) 		0.0744
(0.505) 		0.344
(0.772) 		0.0395
(0.401) 		0.159
(0.571)
xp gain 7 (8%) 80 0.133
(0.547) 		0.36
(0.779) 		0.986
(1.00) 		0.442
(0.822) 		0.246
(0.697) 		0.777
(0.953) 		0.787
(0.953) 		0.966
(1.00) 		0.783
(0.953) 		0.906
(0.991)
xq gain 6 (7%) 81 0.229
(0.667) 		0.499
(0.852) 		1
(1.00) 		0.685
(0.925) 		0.156
(0.565) 		0.643
(0.923) 		0.488
(0.847) 		0.838
(0.977) 		1
(1.00) 		0.881
(0.985)
1p loss 8 (9%) 79 0.025
(0.309) 		0.227
(0.667) 		0.536
(0.865) 		0.315
(0.764) 		0.421
(0.807) 		0.912
(0.992) 		0.285
(0.732) 		0.208
(0.643) 		0.0552
(0.478) 		0.648
(0.925)
2p loss 6 (7%) 81 0.688
(0.925) 		0.384
(0.793) 		0.639
(0.921) 		0.115
(0.535) 		0.256
(0.704) 		0.0684
(0.501) 		0.0743
(0.505) 		0.586
(0.896) 		0.85
(0.977) 		0.159
(0.571)
2q loss 4 (5%) 83 0.635
(0.921) 		0.345
(0.772) 		0.756
(0.948) 		0.425
(0.811) 		0.3
(0.75) 		0.506
(0.855) 		0.557
(0.881) 		0.391
(0.793) 		1
(1.00) 		1
(1.00)
3p loss 8 (9%) 79 0.368
(0.785) 		0.0897
(0.529) 		0.484
(0.847) 		0.541
(0.865) 		0.164
(0.58) 		0.12
(0.54) 		0.459
(0.831) 		0.713
(0.939) 		0.199
(0.64) 		0.0623
(0.501)
3q loss 6 (7%) 81 0.723
(0.944) 		0.091
(0.529) 		0.397
(0.797) 		0.27
(0.712) 		0.182
(0.611) 		0.419
(0.807) 		1
(1.00) 		0.502
(0.853) 		0.655
(0.925) 		0.621
(0.917)
5p loss 4 (5%) 83 0.499
(0.852) 		0.693
(0.925) 		0.345
(0.772) 		0.536
(0.865) 		0.364
(0.782) 		0.636
(0.921) 		0.36
(0.779) 		0.935
(0.997) 		1
(1.00) 		0.443
(0.822)
5q loss 9 (10%) 78 0.0256
(0.311) 		0.838
(0.977) 		0.272
(0.712) 		0.21
(0.644) 		0.495
(0.852) 		0.105
(0.535) 		0.364
(0.782) 		0.67
(0.925) 		0.408
(0.799) 		0.918
(0.992)
6p loss 9 (10%) 78 0.837
(0.977) 		0.321
(0.765) 		0.0775
(0.51) 		0.795
(0.958) 		0.248
(0.697) 		0.506
(0.855) 		0.902
(0.991) 		0.171
(0.593) 		0.203
(0.641) 		0.112
(0.535)
8p loss 13 (15%) 74 0.87
(0.985) 		0.69
(0.925) 		0.896
(0.988) 		0.935
(0.997) 		0.664
(0.925) 		0.752
(0.948) 		0.329
(0.767) 		0.751
(0.948) 		0.747
(0.948) 		0.282
(0.726)
8q loss 4 (5%) 83 0.105
(0.535) 		0.375
(0.791) 		0.261
(0.704) 		0.277
(0.72) 		0.515
(0.86) 		0.555
(0.881) 		0.164
(0.58) 		0.121
(0.541) 		1
(1.00) 		0.106
(0.535)
10q loss 19 (22%) 68 0.0233
(0.309) 		0.0171
(0.263) 		0.129
(0.547) 		0.921
(0.992) 		0.501
(0.852) 		0.318
(0.764) 		0.258
(0.704) 		0.721
(0.944) 		1
(1.00) 		0.837
(0.977)
11p loss 4 (5%) 83 0.682
(0.925) 		0.829
(0.974) 		0.167
(0.584) 		0.204
(0.641) 		0.296
(0.749) 		0.266
(0.704) 		0.819
(0.972) 		0.393
(0.794) 		0.567
(0.885) 		0.912
(0.992)
12p loss 4 (5%) 83 0.26
(0.704) 		0.0694
(0.502) 		0.135
(0.547) 		0.178
(0.603) 		0.475
(0.839) 		0.465
(0.831) 		0.287
(0.736) 		0.816
(0.972) 		0.463
(0.831) 		0.598
(0.905)
13q loss 33 (38%) 54 0.105
(0.535) 		0.736
(0.948) 		0.702
(0.929) 		0.112
(0.535) 		0.167
(0.584) 		0.665
(0.925) 		0.752
(0.948) 		0.189
(0.621) 		0.0208
(0.302) 		0.467
(0.831)
15q loss 11 (13%) 76 0.115
(0.535) 		0.761
(0.951) 		0.313
(0.764) 		0.501
(0.852) 		0.275
(0.715) 		0.3
(0.75) 		0.329
(0.767) 		0.304
(0.752) 		0.746
(0.948) 		0.406
(0.799)
16q loss 10 (11%) 77 0.0495
(0.441) 		0.905
(0.991) 		0.955
(1.00) 		0.883
(0.985) 		0.219
(0.662) 		0.452
(0.826) 		0.693
(0.925) 		0.126
(0.547) 		1
(1.00) 		0.879
(0.985)
17p loss 23 (26%) 64 0.35
(0.773) 		0.381
(0.793) 		0.198
(0.64) 		0.0299
(0.342) 		0.766
(0.953) 		0.627
(0.921) 		0.153
(0.565) 		0.14
(0.549) 		0.513
(0.86) 		0.262
(0.704)
17q loss 7 (8%) 80 0.557
(0.881) 		0.155
(0.565) 		0.448
(0.823) 		0.0782
(0.51) 		0.67
(0.925) 		0.728
(0.947) 		0.246
(0.697) 		0.532
(0.865) 		0.421
(0.807) 		0.214
(0.652)
18p loss 9 (10%) 78 0.139
(0.549) 		0.781
(0.953) 		0.0858
(0.521) 		0.54
(0.865) 		0.677
(0.925) 		0.693
(0.925) 		0.331
(0.768) 		0.756
(0.948) 		0.4
(0.799) 		0.686
(0.925)
18q loss 14 (16%) 73 0.403
(0.799) 		0.685
(0.925) 		0.453
(0.826) 		0.406
(0.799) 		0.848
(0.977) 		0.864
(0.984) 		0.123
(0.543) 		0.0935
(0.529) 		0.34
(0.772) 		0.179
(0.603)
19p loss 4 (5%) 83 0.685
(0.925) 		0.201
(0.641) 		1
(1.00) 		0.0962
(0.529) 		0.556
(0.881) 		0.465
(0.831) 		1
(1.00) 		0.349
(0.773) 		0.209
(0.644) 		0.371
(0.787)
19q loss 7 (8%) 80 0.558
(0.881) 		0.051
(0.45) 		0.85
(0.977) 		0.0216
(0.303) 		1
(1.00) 		0.933
(0.997) 		0.788
(0.953) 		0.79
(0.954) 		0.312
(0.764) 		0.822
(0.972)
20p loss 14 (16%) 73 0.0246
(0.309) 		0.109
(0.535) 		0.0443
(0.421) 		0.771
(0.953) 		0.142
(0.549) 		0.589
(0.898) 		0.344
(0.772) 		0.723
(0.944) 		0.57
(0.888) 		0.127
(0.547)
20q loss 3 (3%) 84 0.24
(0.689) 		0.34
(0.772) 		0.0425
(0.414) 		0.421
(0.807) 		0.788
(0.953) 		0.205
(0.641) 		0.257
(0.704) 		0.0182
(0.275) 		1
(1.00) 		0.443
(0.822)
'1p gain' versus 'CN_CNMF'

P value = 0.0142 (Fisher's exact test), Q value = 0.23

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

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
1P GAIN MUTATED 1 6 0 3
1P GAIN WILD-TYPE 22 20 24 11

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

'1q gain' versus 'CN_CNMF'

P value = 0.00919 (Fisher's exact test), Q value = 0.18

Table S2.  Gene #2: '1q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
1Q GAIN MUTATED 3 9 2 7
1Q GAIN WILD-TYPE 20 17 22 7

Figure S2.  Get High-res Image Gene #2: '1q gain' versus Molecular Subtype #1: 'CN_CNMF'

'3p gain' versus 'CN_CNMF'

P value = 0.00056 (Fisher's exact test), Q value = 0.03

Table S3.  Gene #5: '3p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
3P GAIN MUTATED 1 11 1 4
3P GAIN WILD-TYPE 22 15 23 10

Figure S3.  Get High-res Image Gene #5: '3p gain' versus Molecular Subtype #1: 'CN_CNMF'

'3q gain' versus 'CN_CNMF'

P value = 0.00012 (Fisher's exact test), Q value = 0.012

Table S4.  Gene #6: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
3Q GAIN MUTATED 1 12 1 5
3Q GAIN WILD-TYPE 22 14 23 9

Figure S4.  Get High-res Image Gene #6: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

'7p gain' versus 'CN_CNMF'

P value = 0.0141 (Fisher's exact test), Q value = 0.23

Table S5.  Gene #11: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
7P GAIN MUTATED 2 13 6 4
7P GAIN WILD-TYPE 21 13 18 10

Figure S5.  Get High-res Image Gene #11: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

'11p gain' versus 'CN_CNMF'

P value = 0.00745 (Fisher's exact test), Q value = 0.15

Table S6.  Gene #19: '11p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
11P GAIN MUTATED 0 8 2 1
11P GAIN WILD-TYPE 23 18 22 13

Figure S6.  Get High-res Image Gene #19: '11p gain' versus Molecular Subtype #1: 'CN_CNMF'

'11q gain' versus 'CN_CNMF'

P value = 0.00968 (Fisher's exact test), Q value = 0.19

Table S7.  Gene #20: '11q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
11Q GAIN MUTATED 0 8 2 2
11Q GAIN WILD-TYPE 23 18 22 12

Figure S7.  Get High-res Image Gene #20: '11q gain' versus Molecular Subtype #1: 'CN_CNMF'

'12p gain' versus 'CN_CNMF'

P value = 0.00031 (Fisher's exact test), Q value = 0.02

Table S8.  Gene #21: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
12P GAIN MUTATED 1 13 3 1
12P GAIN WILD-TYPE 22 13 21 13

Figure S8.  Get High-res Image Gene #21: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

'12q gain' versus 'CN_CNMF'

P value = 0.00032 (Fisher's exact test), Q value = 0.02

Table S9.  Gene #22: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
12Q GAIN MUTATED 1 13 3 1
12Q GAIN WILD-TYPE 22 13 21 13

Figure S9.  Get High-res Image Gene #22: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

'15q gain' versus 'METHLYATION_CNMF'

P value = 0.0043 (Fisher's exact test), Q value = 0.11

Table S10.  Gene #24: '15q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 14 20 26 27
15Q GAIN MUTATED 1 2 8 0
15Q GAIN WILD-TYPE 13 18 18 27

Figure S10.  Get High-res Image Gene #24: '15q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'15q gain' versus 'RPPA_CHIERARCHICAL'

P value = 0.0117 (Fisher's exact test), Q value = 0.21

Table S11.  Gene #24: '15q 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
15Q GAIN MUTATED 0 1 4 0 2 0
15Q GAIN WILD-TYPE 9 10 6 12 7 12

Figure S11.  Get High-res Image Gene #24: '15q gain' versus Molecular Subtype #4: 'RPPA_CHIERARCHICAL'

'15q gain' versus 'MIRSEQ_CNMF'

P value = 0.00352 (Fisher's exact test), Q value = 0.11

Table S12.  Gene #24: '15q gain' versus Molecular Subtype #7: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 36 29 22
15Q GAIN MUTATED 0 7 4
15Q GAIN WILD-TYPE 36 22 18

Figure S12.  Get High-res Image Gene #24: '15q gain' versus Molecular Subtype #7: 'MIRSEQ_CNMF'

'16p gain' versus 'CN_CNMF'

P value = 0.00666 (Fisher's exact test), Q value = 0.14

Table S13.  Gene #25: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
16P GAIN MUTATED 0 9 4 4
16P GAIN WILD-TYPE 23 17 20 10

Figure S13.  Get High-res Image Gene #25: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

'16p gain' versus 'MRNASEQ_CNMF'

P value = 0.012 (Fisher's exact test), Q value = 0.21

Table S14.  Gene #25: '16p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 26 22 17 21
16P GAIN MUTATED 3 10 2 2
16P GAIN WILD-TYPE 23 12 15 19

Figure S14.  Get High-res Image Gene #25: '16p gain' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'16q gain' versus 'CN_CNMF'

P value = 0.00238 (Fisher's exact test), Q value = 0.088

Table S15.  Gene #26: '16q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
16Q GAIN MUTATED 0 10 3 3
16Q GAIN WILD-TYPE 23 16 21 11

Figure S15.  Get High-res Image Gene #26: '16q gain' versus Molecular Subtype #1: 'CN_CNMF'

'4p loss' versus 'CN_CNMF'

P value = 5e-05 (Fisher's exact test), Q value = 0.0074

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

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
4P LOSS MUTATED 3 18 4 7
4P LOSS WILD-TYPE 20 8 20 7

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

'4p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00422 (Fisher's exact test), Q value = 0.11

Table S17.  Gene #43: '4p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 22 12 22 13 17
4P LOSS MUTATED 2 7 11 3 9
4P LOSS WILD-TYPE 20 5 11 10 8

Figure S17.  Get High-res Image Gene #43: '4p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'4q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0025

Table S18.  Gene #44: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
4Q LOSS MUTATED 3 17 4 9
4Q LOSS WILD-TYPE 20 9 20 5

Figure S18.  Get High-res Image Gene #44: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

'4q loss' versus 'MRNASEQ_CNMF'

P value = 0.004 (Fisher's exact test), Q value = 0.11

Table S19.  Gene #44: '4q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 26 22 17 21
4Q LOSS MUTATED 3 11 7 12
4Q LOSS WILD-TYPE 23 11 10 9

Figure S19.  Get High-res Image Gene #44: '4q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'4q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00029 (Fisher's exact test), Q value = 0.02

Table S20.  Gene #44: '4q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 22 12 22 13 17
4Q LOSS MUTATED 1 5 12 4 11
4Q LOSS WILD-TYPE 21 7 10 9 6

Figure S20.  Get High-res Image Gene #44: '4q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'6q loss' versus 'CN_CNMF'

P value = 0.00331 (Fisher's exact test), Q value = 0.11

Table S21.  Gene #48: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
6Q LOSS MUTATED 10 14 4 1
6Q LOSS WILD-TYPE 13 12 20 13

Figure S21.  Get High-res Image Gene #48: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0025

Table S22.  Gene #51: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
9P LOSS MUTATED 0 16 9 3
9P LOSS WILD-TYPE 23 10 15 11

Figure S22.  Get High-res Image Gene #51: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'METHLYATION_CNMF'

P value = 0.015 (Fisher's exact test), Q value = 0.24

Table S23.  Gene #51: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 14 20 26 27
9P LOSS MUTATED 1 11 10 6
9P LOSS WILD-TYPE 13 9 16 21

Figure S23.  Get High-res Image Gene #51: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'9p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.0105 (Fisher's exact test), Q value = 0.2

Table S24.  Gene #51: '9p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 22 12 22 13 17
9P LOSS MUTATED 1 6 9 5 7
9P LOSS WILD-TYPE 21 6 13 8 10

Figure S24.  Get High-res Image Gene #51: '9p loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'9q loss' versus 'CN_CNMF'

P value = 0.00181 (Fisher's exact test), Q value = 0.074

Table S25.  Gene #52: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
9Q LOSS MUTATED 0 11 7 3
9Q LOSS WILD-TYPE 23 15 17 11

Figure S25.  Get High-res Image Gene #52: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

'9q loss' versus 'RPPA_CNMF'

P value = 0.00618 (Fisher's exact test), Q value = 0.14

Table S26.  Gene #52: '9q loss' versus Molecular Subtype #3: 'RPPA_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 14 7 13 8 7 14
9Q LOSS MUTATED 1 4 0 4 1 4
9Q LOSS WILD-TYPE 13 3 13 4 6 10

Figure S26.  Get High-res Image Gene #52: '9q loss' versus Molecular Subtype #3: 'RPPA_CNMF'

'10p loss' versus 'CN_CNMF'

P value = 0.00434 (Fisher's exact test), Q value = 0.11

Table S27.  Gene #53: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
10P LOSS MUTATED 2 12 9 1
10P LOSS WILD-TYPE 21 14 15 13

Figure S27.  Get High-res Image Gene #53: '10p loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'METHLYATION_CNMF'

P value = 0.00074 (Fisher's exact test), Q value = 0.034

Table S28.  Gene #53: '10p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 14 20 26 27
10P LOSS MUTATED 1 12 8 3
10P LOSS WILD-TYPE 13 8 18 24

Figure S28.  Get High-res Image Gene #53: '10p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'11q loss' versus 'MRNASEQ_CNMF'

P value = 0.00447 (Fisher's exact test), Q value = 0.11

Table S29.  Gene #56: '11q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 26 22 17 21
11Q LOSS MUTATED 0 1 4 0
11Q LOSS WILD-TYPE 26 21 13 21

Figure S29.  Get High-res Image Gene #56: '11q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'11q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00276 (Fisher's exact test), Q value = 0.097

Table S30.  Gene #56: '11q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 22 12 22 13 17
11Q LOSS MUTATED 0 0 1 4 0
11Q LOSS WILD-TYPE 22 12 21 9 17

Figure S30.  Get High-res Image Gene #56: '11q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'14q loss' versus 'CN_CNMF'

P value = 0.00056 (Fisher's exact test), Q value = 0.03

Table S31.  Gene #59: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
14Q LOSS MUTATED 3 15 7 10
14Q LOSS WILD-TYPE 20 11 17 4

Figure S31.  Get High-res Image Gene #59: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

'14q loss' versus 'MRNASEQ_CNMF'

P value = 0.00026 (Fisher's exact test), Q value = 0.02

Table S32.  Gene #59: '14q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 26 22 17 21
14Q LOSS MUTATED 5 17 4 9
14Q LOSS WILD-TYPE 21 5 13 12

Figure S32.  Get High-res Image Gene #59: '14q loss' versus Molecular Subtype #5: 'MRNASEQ_CNMF'

'14q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0025

Table S33.  Gene #59: '14q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 22 12 22 13 17
14Q LOSS MUTATED 4 7 18 0 6
14Q LOSS WILD-TYPE 18 5 4 13 11

Figure S33.  Get High-res Image Gene #59: '14q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'14q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 6e-04 (Fisher's exact test), Q value = 0.03

Table S34.  Gene #59: '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 S34.  Get High-res Image Gene #59: '14q loss' versus Molecular Subtype #8: 'MIRSEQ_CHIERARCHICAL'

'14q loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.0141 (Fisher's exact test), Q value = 0.23

Table S35.  Gene #59: '14q loss' versus Molecular Subtype #9: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 37 27 21
14Q LOSS MUTATED 20 5 9
14Q LOSS WILD-TYPE 17 22 12

Figure S35.  Get High-res Image Gene #59: '14q loss' versus Molecular Subtype #9: 'MIRSEQ_MATURE_CNMF'

'14q loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.00167 (Fisher's exact test), Q value = 0.073

Table S36.  Gene #59: '14q loss' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 16 17 21 31
14Q LOSS MUTATED 2 13 8 11
14Q LOSS WILD-TYPE 14 4 13 20

Figure S36.  Get High-res Image Gene #59: '14q loss' versus Molecular Subtype #10: 'MIRSEQ_MATURE_CHIERARCHICAL'

'16p loss' versus 'CN_CNMF'

P value = 0.00994 (Fisher's exact test), Q value = 0.19

Table S37.  Gene #61: '16p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
16P LOSS MUTATED 0 4 0 3
16P LOSS WILD-TYPE 23 22 24 11

Figure S37.  Get High-res Image Gene #61: '16p loss' versus Molecular Subtype #1: 'CN_CNMF'

'21q loss' versus 'METHLYATION_CNMF'

P value = 0.0129 (Fisher's exact test), Q value = 0.22

Table S38.  Gene #71: '21q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 14 20 26 27
21Q LOSS MUTATED 1 7 1 2
21Q LOSS WILD-TYPE 13 13 25 25

Figure S38.  Get High-res Image Gene #71: '21q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'22q loss' versus 'CN_CNMF'

P value = 0.00539 (Fisher's exact test), Q value = 0.12

Table S39.  Gene #72: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
22Q LOSS MUTATED 12 23 22 10
22Q LOSS WILD-TYPE 11 3 2 4

Figure S39.  Get High-res Image Gene #72: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

'22q loss' versus 'METHLYATION_CNMF'

P value = 3e-05 (Fisher's exact test), Q value = 0.0055

Table S40.  Gene #72: '22q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 14 20 26 27
22Q LOSS MUTATED 10 19 25 13
22Q LOSS WILD-TYPE 4 1 1 14

Figure S40.  Get High-res Image Gene #72: '22q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'22q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.0045 (Fisher's exact test), Q value = 0.11

Table S41.  Gene #72: '22q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 22 12 22 13 17
22Q LOSS MUTATED 15 12 18 6 16
22Q LOSS WILD-TYPE 7 0 4 7 1

Figure S41.  Get High-res Image Gene #72: '22q loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'xp loss' versus 'CN_CNMF'

P value = 0.00527 (Fisher's exact test), Q value = 0.12

Table S42.  Gene #73: 'xp loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
XP LOSS MUTATED 2 14 8 3
XP LOSS WILD-TYPE 21 12 16 11

Figure S42.  Get High-res Image Gene #73: 'xp loss' versus Molecular Subtype #1: 'CN_CNMF'

'xp loss' versus 'METHLYATION_CNMF'

P value = 0.00013 (Fisher's exact test), Q value = 0.012

Table S43.  Gene #73: 'xp loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 14 20 26 27
XP LOSS MUTATED 3 9 14 1
XP LOSS WILD-TYPE 11 11 12 26

Figure S43.  Get High-res Image Gene #73: 'xp loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'xp loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00724 (Fisher's exact test), Q value = 0.15

Table S44.  Gene #73: 'xp loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 22 12 22 13 17
XP LOSS MUTATED 4 6 10 0 7
XP LOSS WILD-TYPE 18 6 12 13 10

Figure S44.  Get High-res Image Gene #73: 'xp loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

'xq loss' versus 'CN_CNMF'

P value = 0.00196 (Fisher's exact test), Q value = 0.076

Table S45.  Gene #74: 'xq loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 23 26 24 14
XQ LOSS MUTATED 2 15 8 3
XQ LOSS WILD-TYPE 21 11 16 11

Figure S45.  Get High-res Image Gene #74: 'xq loss' versus Molecular Subtype #1: 'CN_CNMF'

'xq loss' versus 'METHLYATION_CNMF'

P value = 0.00012 (Fisher's exact test), Q value = 0.012

Table S46.  Gene #74: 'xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 14 20 26 27
XQ LOSS MUTATED 4 9 14 1
XQ LOSS WILD-TYPE 10 11 12 26

Figure S46.  Get High-res Image Gene #74: 'xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'xq loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.003 (Fisher's exact test), Q value = 0.1

Table S47.  Gene #74: 'xq loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 22 12 22 13 17
XQ LOSS MUTATED 4 7 10 0 7
XQ LOSS WILD-TYPE 18 5 12 13 10

Figure S47.  Get High-res Image Gene #74: 'xq loss' versus Molecular Subtype #6: 'MRNASEQ_CHIERARCHICAL'

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/19781626/transformed.cor.cli.txt

  • Molecular subtypes file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/MESO-TP/20139528/MESO-TP.transferedmergedcluster.txt

  • Number of patients = 87

  • Number of significantly arm-level cnvs = 74

  • 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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