Correlation between copy number variations of arm-level result and molecular subtypes
Mesothelioma (Primary solid tumor)
02 April 2015  |  analyses__2015_04_02
Maintainer Information
Citation Information
doi:10.7908/C12J69X9
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/C12J69X9
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 8 molecular subtypes across 87 patients, 50 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',  'MRNASEQ_CNMF', and 'MIRSEQ_CNMF'.

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

  • 16q gain cnv correlated to 'CN_CNMF'.

  • 17q gain cnv correlated to 'MRNASEQ_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'.

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

  • 10q loss cnv correlated to 'METHLYATION_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',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_CHIERARCHICAL',  'MIRSEQ_MATURE_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 16p loss cnv correlated to 'CN_CNMF'.

  • 20q loss cnv correlated to 'MIRSEQ_CHIERARCHICAL'.

  • 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 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 50 significant findings detected.

Clinical
Features 		CN
CNMF 		METHLYATION
CNMF 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
CHIERARCHICAL 		MIRSEQ
MATURE
CNMF 		MIRSEQ
MATURE
CHIERARCHICAL
nCNV (%) nWild-Type Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
14q loss 35 (40%) 52 0.0004
(0.0191) 		0.355
(0.747) 		0.00023
(0.0136) 		1e-05
(0.00395) 		0.0495
(0.391) 		0.0006
(0.0253) 		0.014
(0.195) 		0.00174
(0.0572)
15q gain 11 (13%) 76 0.0242
(0.257) 		0.00434
(0.0894) 		0.0198
(0.244) 		0.128
(0.514) 		0.00323
(0.0824) 		0.0775
(0.456) 		0.774
(0.937) 		0.227
(0.634)
4q loss 33 (38%) 54 2e-05
(0.00395) 		0.1
(0.484) 		0.00384
(0.0894) 		0.00042
(0.0191) 		0.0579
(0.423) 		0.144
(0.524) 		0.775
(0.937) 		0.0921
(0.482)
9p loss 28 (32%) 59 5e-05
(0.00592) 		0.0152
(0.2) 		0.0432
(0.366) 		0.0111
(0.169) 		0.957
(1.00) 		0.493
(0.843) 		0.915
(0.978) 		0.153
(0.538)
22q loss 67 (77%) 20 0.00534
(0.102) 		4e-05
(0.00592) 		0.0561
(0.421) 		0.00446
(0.0894) 		1
(1.00) 		0.645
(0.906) 		0.134
(0.52) 		0.83
(0.958)
xp loss 27 (31%) 60 0.00599
(0.111) 		0.0001
(0.00987) 		0.0684
(0.445) 		0.00709
(0.123) 		0.0914
(0.482) 		0.417
(0.784) 		0.074
(0.454) 		0.305
(0.726)
xq loss 28 (32%) 59 0.00199
(0.062) 		0.00016
(0.0118) 		0.0866
(0.478) 		0.00329
(0.0824) 		0.152
(0.538) 		0.408
(0.78) 		0.068
(0.445) 		0.311
(0.735)
16p gain 17 (20%) 70 0.00692
(0.123) 		0.566
(0.872) 		0.012
(0.178) 		0.0671
(0.445) 		0.177
(0.576) 		0.186
(0.586) 		0.631
(0.906) 		0.08
(0.456)
4p loss 32 (37%) 55 2e-05
(0.00395) 		0.323
(0.74) 		0.272
(0.687) 		0.0041
(0.0894) 		0.129
(0.514) 		0.334
(0.742) 		0.387
(0.763) 		0.514
(0.846)
10p loss 24 (28%) 63 0.00453
(0.0894) 		0.00073
(0.027) 		0.132
(0.52) 		0.136
(0.522) 		0.87
(0.971) 		0.305
(0.726) 		0.707
(0.915) 		0.731
(0.929)
11q loss 5 (6%) 82 0.578
(0.879) 		0.618
(0.905) 		0.00424
(0.0894) 		0.00283
(0.0798) 		0.846
(0.963) 		0.356
(0.747) 		0.562
(0.871) 		0.914
(0.978)
1p gain 10 (11%) 77 0.0143
(0.195) 		0.782
(0.937) 		0.768
(0.937) 		0.683
(0.906) 		0.44
(0.804) 		0.819
(0.955) 		0.233
(0.643) 		0.342
(0.742)
1q gain 21 (24%) 66 0.00941
(0.154) 		0.0317
(0.303) 		0.104
(0.484) 		0.157
(0.544) 		0.231
(0.64) 		0.206
(0.606) 		0.574
(0.879) 		0.51
(0.846)
3p gain 17 (20%) 70 0.00064
(0.0253) 		0.93
(0.984) 		0.619
(0.905) 		0.624
(0.906) 		0.889
(0.973) 		0.884
(0.973) 		0.441
(0.804) 		0.606
(0.896)
3q gain 19 (22%) 68 0.00012
(0.0101) 		0.767
(0.937) 		0.67
(0.906) 		0.389
(0.763) 		0.455
(0.813) 		0.466
(0.814) 		0.33
(0.742) 		0.538
(0.855)
7p gain 25 (29%) 62 0.0145
(0.195) 		0.394
(0.764) 		0.0954
(0.483) 		0.0712
(0.445) 		0.0974
(0.484) 		0.0427
(0.366) 		0.321
(0.74) 		0.0236
(0.257)
11p gain 11 (13%) 76 0.00778
(0.132) 		0.661
(0.906) 		0.293
(0.72) 		0.0917
(0.482) 		0.388
(0.763) 		0.668
(0.906) 		1
(1.00) 		0.824
(0.955)
11q gain 12 (14%) 75 0.00986
(0.154) 		0.38
(0.763) 		0.0664
(0.445) 		0.0347
(0.321) 		0.528
(0.854) 		0.55
(0.869) 		0.569
(0.873) 		0.482
(0.83)
12p gain 18 (21%) 69 0.0003
(0.0161) 		0.814
(0.955) 		0.892
(0.973) 		0.854
(0.963) 		0.751
(0.932) 		0.921
(0.978) 		1
(1.00) 		0.862
(0.969)
12q gain 18 (21%) 69 0.00019
(0.0125) 		0.816
(0.955) 		0.892
(0.973) 		0.854
(0.963) 		0.751
(0.932) 		0.921
(0.978) 		1
(1.00) 		0.862
(0.969)
16q gain 16 (18%) 71 0.00279
(0.0798) 		0.804
(0.952) 		0.0226
(0.257) 		0.108
(0.494) 		0.562
(0.871) 		0.659
(0.906) 		0.876
(0.973) 		0.378
(0.763)
17q gain 17 (20%) 70 0.0939
(0.482) 		0.318
(0.74) 		0.0206
(0.244) 		0.0456
(0.37) 		0.145
(0.524) 		0.869
(0.971) 		0.742
(0.932) 		0.845
(0.963)
6q loss 29 (33%) 58 0.00334
(0.0824) 		0.215
(0.624) 		0.394
(0.764) 		0.651
(0.906) 		0.652
(0.906) 		0.522
(0.853) 		0.112
(0.498) 		0.0814
(0.459)
9q loss 21 (24%) 66 0.00164
(0.0571) 		0.205
(0.606) 		0.143
(0.524) 		0.161
(0.548) 		0.95
(0.996) 		0.536
(0.855) 		0.577
(0.879) 		0.263
(0.673)
10q loss 19 (22%) 68 0.0231
(0.257) 		0.0165
(0.212) 		0.502
(0.844) 		0.322
(0.74) 		0.257
(0.673) 		0.72
(0.924) 		1
(1.00) 		0.837
(0.96)
13q loss 33 (38%) 54 0.105
(0.484) 		0.738
(0.932) 		0.169
(0.562) 		0.662
(0.906) 		0.753
(0.932) 		0.188
(0.588) 		0.0204
(0.244) 		0.469
(0.814)
16p loss 7 (8%) 80 0.0096
(0.154) 		0.193
(0.603) 		0.531
(0.854) 		0.344
(0.742) 		0.417
(0.784) 		0.362
(0.752) 		1
(1.00) 		1
(1.00)
20q loss 3 (3%) 84 0.24
(0.658) 		0.341
(0.742) 		0.789
(0.938) 		0.203
(0.606) 		0.258
(0.673) 		0.0185
(0.233) 		1
(1.00) 		0.443
(0.804)
21q loss 11 (13%) 76 0.109
(0.494) 		0.013
(0.187) 		0.22
(0.627) 		0.0798
(0.456) 		0.658
(0.906) 		0.293
(0.72) 		0.848
(0.963) 		0.826
(0.955)
2p gain 4 (5%) 83 0.103
(0.484) 		0.374
(0.76) 		0.607
(0.896) 		0.785
(0.937) 		0.122
(0.506) 		0.143
(0.524) 		0.357
(0.747) 		0.182
(0.576)
2q gain 7 (8%) 80 0.516
(0.847) 		0.46
(0.814) 		0.355
(0.747) 		0.425
(0.789) 		0.247
(0.665) 		0.913
(0.978) 		0.133
(0.52) 		0.0638
(0.445)
5p gain 24 (28%) 63 0.197
(0.606) 		0.332
(0.742) 		0.514
(0.846) 		0.58
(0.88) 		0.0369
(0.331) 		0.434
(0.8) 		0.499
(0.844) 		0.448
(0.806)
5q gain 15 (17%) 72 0.0622
(0.444) 		0.357
(0.747) 		0.302
(0.726) 		0.69
(0.906) 		0.151
(0.538) 		0.37
(0.758) 		0.34
(0.742) 		0.345
(0.742)
6p gain 7 (8%) 80 0.0761
(0.455) 		0.0944
(0.482) 		0.0682
(0.445) 		0.384
(0.763) 		0.0711
(0.445) 		0.965
(1.00) 		0.884
(0.973) 		0.715
(0.92)
6q gain 4 (5%) 83 0.103
(0.484) 		0.634
(0.906) 		0.4
(0.769) 		0.694
(0.906) 		0.671
(0.906) 		0.936
(0.984) 		0.676
(0.906) 		0.756
(0.932)
7q gain 22 (25%) 65 0.0242
(0.257) 		0.447
(0.806) 		0.143
(0.524) 		0.03
(0.291) 		0.224
(0.631) 		0.181
(0.576) 		0.526
(0.854) 		0.116
(0.498)
8p gain 12 (14%) 75 0.0448
(0.37) 		0.525
(0.854) 		0.666
(0.906) 		0.759
(0.933) 		0.139
(0.524) 		0.0389
(0.339) 		0.599
(0.893) 		0.249
(0.666)
8q gain 14 (16%) 73 0.0486
(0.389) 		0.935
(0.984) 		0.699
(0.91) 		0.748
(0.932) 		0.263
(0.673) 		0.586
(0.883) 		0.744
(0.932) 		0.543
(0.859)
9p gain 3 (3%) 84 0.702
(0.911) 		0.536
(0.855) 		0.318
(0.74) 		1
(1.00) 		0.114
(0.498) 		0.809
(0.954) 		0.101
(0.484) 		0.0249
(0.257)
9q gain 4 (5%) 83 0.501
(0.844) 		0.0715
(0.445) 		0.476
(0.821) 		0.635
(0.906) 		0.0576
(0.423) 		0.469
(0.814) 		0.813
(0.955) 		0.691
(0.906)
10p gain 3 (3%) 84 0.0802
(0.456) 		0.775
(0.937) 		0.881
(0.973) 		0.918
(0.978) 		1
(1.00) 		0.264
(0.673) 		1
(1.00) 		0.888
(0.973)
10q gain 3 (3%) 84 0.0799
(0.456) 		0.774
(0.937) 		0.883
(0.973) 		0.92
(0.978) 		1
(1.00) 		0.265
(0.673) 		1
(1.00) 		0.887
(0.973)
13q gain 5 (6%) 82 0.424
(0.789) 		0.0975
(0.484) 		0.0265
(0.262) 		0.0454
(0.37) 		0.61
(0.896) 		0.428
(0.793) 		0.851
(0.963) 		0.389
(0.763)
17p gain 7 (8%) 80 0.218
(0.624) 		1
(1.00) 		0.441
(0.804) 		0.684
(0.906) 		0.695
(0.907) 		0.113
(0.498) 		0.469
(0.814) 		0.244
(0.665)
18p gain 8 (9%) 79 0.0679
(0.445) 		0.313
(0.735) 		0.116
(0.498) 		0.18
(0.576) 		0.122
(0.506) 		0.137
(0.523) 		0.604
(0.896) 		0.134
(0.52)
18q gain 4 (5%) 83 0.0871
(0.478) 		1
(1.00) 		0.297
(0.723) 		0.634
(0.906) 		0.0325
(0.305) 		0.0838
(0.468) 		0.607
(0.896) 		0.194
(0.603)
19p gain 14 (16%) 73 0.275
(0.691) 		0.0352
(0.321) 		0.163
(0.551) 		0.174
(0.572) 		0.465
(0.814) 		0.175
(0.572) 		0.693
(0.906) 		0.205
(0.606)
19q gain 10 (11%) 77 0.807
(0.953) 		0.12
(0.506) 		0.327
(0.741) 		0.682
(0.906) 		0.535
(0.855) 		0.708
(0.915) 		0.539
(0.855) 		0.895
(0.974)
20p gain 8 (9%) 79 0.692
(0.906) 		0.729
(0.928) 		0.381
(0.763) 		0.783
(0.937) 		0.583
(0.88) 		0.441
(0.804) 		0.641
(0.906) 		0.669
(0.906)
20q gain 10 (11%) 77 0.205
(0.606) 		0.907
(0.978) 		0.639
(0.906) 		0.937
(0.984) 		0.324
(0.74) 		0.749
(0.932) 		0.525
(0.854) 		0.594
(0.89)
21q gain 6 (7%) 81 0.252
(0.668) 		0.61
(0.896) 		0.222
(0.629) 		0.218
(0.624) 		0.0744
(0.454) 		0.344
(0.742) 		0.0386
(0.339) 		0.16
(0.546)
xp gain 7 (8%) 80 0.134
(0.52) 		0.358
(0.747) 		0.247
(0.665) 		0.778
(0.937) 		0.786
(0.937) 		0.967
(1.00) 		0.784
(0.937) 		0.905
(0.978)
xq gain 6 (7%) 81 0.23
(0.639) 		0.501
(0.844) 		0.153
(0.538) 		0.646
(0.906) 		0.485
(0.832) 		0.837
(0.96) 		1
(1.00) 		0.88
(0.973)
1p loss 8 (9%) 79 0.0243
(0.257) 		0.226
(0.633) 		0.42
(0.786) 		0.913
(0.978) 		0.284
(0.707) 		0.206
(0.606) 		0.0538
(0.409) 		0.647
(0.906)
2p loss 6 (7%) 81 0.687
(0.906) 		0.384
(0.763) 		0.256
(0.673) 		0.0694
(0.445) 		0.0753
(0.455) 		0.582
(0.88) 		0.85
(0.963) 		0.159
(0.546)
2q loss 4 (5%) 83 0.635
(0.906) 		0.343
(0.742) 		0.297
(0.723) 		0.506
(0.845) 		0.559
(0.871) 		0.392
(0.764) 		1
(1.00) 		1
(1.00)
3p loss 8 (9%) 79 0.366
(0.756) 		0.091
(0.482) 		0.168
(0.561) 		0.119
(0.505) 		0.462
(0.814) 		0.712
(0.919) 		0.199
(0.606) 		0.0622
(0.444)
3q loss 6 (7%) 81 0.721
(0.924) 		0.0904
(0.482) 		0.18
(0.576) 		0.416
(0.784) 		1
(1.00) 		0.506
(0.845) 		0.656
(0.906) 		0.622
(0.906)
5p loss 4 (5%) 83 0.5
(0.844) 		0.693
(0.906) 		0.368
(0.757) 		0.636
(0.906) 		0.357
(0.747) 		0.936
(0.984) 		1
(1.00) 		0.445
(0.805)
5q loss 9 (10%) 78 0.0256
(0.257) 		0.838
(0.96) 		0.495
(0.844) 		0.105
(0.484) 		0.366
(0.756) 		0.668
(0.906) 		0.41
(0.78) 		0.916
(0.978)
6p loss 9 (10%) 78 0.836
(0.96) 		0.321
(0.74) 		0.25
(0.666) 		0.503
(0.844) 		0.903
(0.978) 		0.171
(0.566) 		0.207
(0.606) 		0.11
(0.495)
8p loss 13 (15%) 74 0.871
(0.971) 		0.69
(0.906) 		0.665
(0.906) 		0.75
(0.932) 		0.328
(0.741) 		0.75
(0.932) 		0.746
(0.932) 		0.282
(0.705)
8q loss 4 (5%) 83 0.103
(0.484) 		0.375
(0.76) 		0.511
(0.846) 		0.558
(0.871) 		0.164
(0.553) 		0.122
(0.506) 		1
(1.00) 		0.104
(0.484)
11p loss 4 (5%) 83 0.682
(0.906) 		0.826
(0.955) 		0.299
(0.725) 		0.265
(0.673) 		0.82
(0.955) 		0.395
(0.764) 		0.564
(0.872) 		0.911
(0.978)
12p loss 4 (5%) 83 0.258
(0.673) 		0.0711
(0.445) 		0.475
(0.821) 		0.464
(0.814) 		0.291
(0.72) 		0.817
(0.955) 		0.465
(0.814) 		0.599
(0.893)
15q loss 11 (13%) 76 0.115
(0.498) 		0.759
(0.933) 		0.276
(0.691) 		0.3
(0.725) 		0.328
(0.741) 		0.304
(0.726) 		0.746
(0.932) 		0.405
(0.776)
16q loss 10 (11%) 77 0.0512
(0.396) 		0.907
(0.978) 		0.218
(0.624) 		0.453
(0.813) 		0.692
(0.906) 		0.126
(0.514) 		1
(1.00) 		0.878
(0.973)
17p loss 23 (26%) 64 0.349
(0.745) 		0.381
(0.763) 		0.764
(0.937) 		0.628
(0.906) 		0.15
(0.538) 		0.14
(0.524) 		0.511
(0.846) 		0.261
(0.673)
17q loss 7 (8%) 80 0.56
(0.871) 		0.155
(0.541) 		0.669
(0.906) 		0.729
(0.928) 		0.246
(0.665) 		0.53
(0.854) 		0.422
(0.787) 		0.214
(0.623)
18p loss 9 (10%) 78 0.14
(0.524) 		0.781
(0.937) 		0.675
(0.906) 		0.691
(0.906) 		0.333
(0.742) 		0.755
(0.932) 		0.4
(0.769) 		0.686
(0.906)
18q loss 14 (16%) 73 0.411
(0.78) 		0.687
(0.906) 		0.847
(0.963) 		0.865
(0.969) 		0.123
(0.508) 		0.0936
(0.482) 		0.338
(0.742) 		0.181
(0.576)
19p loss 4 (5%) 83 0.683
(0.906) 		0.201
(0.606) 		0.558
(0.871) 		0.463
(0.814) 		1
(1.00) 		0.348
(0.745) 		0.203
(0.606) 		0.371
(0.758)
19q loss 7 (8%) 80 0.559
(0.871) 		0.0515
(0.396) 		1
(1.00) 		0.934
(0.984) 		0.787
(0.937) 		0.792
(0.94) 		0.313
(0.735) 		0.823
(0.955)
20p loss 14 (16%) 73 0.0257
(0.257) 		0.109
(0.494) 		0.144
(0.524) 		0.588
(0.883) 		0.34
(0.742) 		0.723
(0.924) 		0.568
(0.873) 		0.127
(0.514)
'1p gain' versus 'CN_CNMF'

P value = 0.0143 (Fisher's exact test), Q value = 0.2

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 = 0.00941 (Fisher's exact test), Q value = 0.15

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 = 0.00064 (Fisher's exact test), Q value = 0.025

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 = 0.01

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 = 0.0145 (Fisher's exact test), Q value = 0.2

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 = 0.00778 (Fisher's exact test), Q value = 0.13

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 = 0.00986 (Fisher's exact test), Q value = 0.15

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 = 3e-04 (Fisher's exact test), Q value = 0.016

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 = 0.00019 (Fisher's exact test), Q value = 0.012

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 = 0.00434 (Fisher's exact test), Q value = 0.089

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 'MRNASEQ_CNMF'

P value = 0.0198 (Fisher's exact test), Q value = 0.24

Table S11.  Gene #24: '15q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 26 22 17 21
15Q GAIN MUTATED 1 6 0 4
15Q GAIN WILD-TYPE 25 16 17 17

Figure S11.  Get High-res Image Gene #24: '15q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'15q gain' versus 'MIRSEQ_CNMF'

P value = 0.00323 (Fisher's exact test), Q value = 0.082

Table S12.  Gene #24: '15q gain' versus Molecular Subtype #5: '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 #5: 'MIRSEQ_CNMF'

'16p gain' versus 'CN_CNMF'

P value = 0.00692 (Fisher's exact test), Q value = 0.12

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 = 0.18

Table S14.  Gene #25: '16p gain' versus Molecular Subtype #3: '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 #3: 'MRNASEQ_CNMF'

'16q gain' versus 'CN_CNMF'

P value = 0.00279 (Fisher's exact test), Q value = 0.08

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'

'17q gain' versus 'MRNASEQ_CNMF'

P value = 0.0206 (Fisher's exact test), Q value = 0.24

Table S16.  Gene #28: '17q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 26 22 17 21
17Q GAIN MUTATED 8 6 3 0
17Q GAIN WILD-TYPE 18 16 14 21

Figure S16.  Get High-res Image Gene #28: '17q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'4p loss' versus 'CN_CNMF'

P value = 2e-05 (Fisher's exact test), Q value = 0.0039

Table S17.  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 S17.  Get High-res Image Gene #43: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

'4p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.0041 (Fisher's exact test), Q value = 0.089

Table S18.  Gene #43: '4p loss' versus Molecular Subtype #4: '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 S18.  Get High-res Image Gene #43: '4p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'4q loss' versus 'CN_CNMF'

P value = 2e-05 (Fisher's exact test), Q value = 0.0039

Table S19.  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 S19.  Get High-res Image Gene #44: '4q loss' versus Molecular Subtype #1: 'CN_CNMF'

'4q loss' versus 'MRNASEQ_CNMF'

P value = 0.00384 (Fisher's exact test), Q value = 0.089

Table S20.  Gene #44: '4q loss' versus Molecular Subtype #3: '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 S20.  Get High-res Image Gene #44: '4q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'4q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00042 (Fisher's exact test), Q value = 0.019

Table S21.  Gene #44: '4q loss' versus Molecular Subtype #4: '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 S21.  Get High-res Image Gene #44: '4q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'6q loss' versus 'CN_CNMF'

P value = 0.00334 (Fisher's exact test), Q value = 0.082

Table S22.  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 S22.  Get High-res Image Gene #48: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'CN_CNMF'

P value = 5e-05 (Fisher's exact test), Q value = 0.0059

Table S23.  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 S23.  Get High-res Image Gene #51: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'METHLYATION_CNMF'

P value = 0.0152 (Fisher's exact test), Q value = 0.2

Table S24.  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 S24.  Get High-res Image Gene #51: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'9p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.0111 (Fisher's exact test), Q value = 0.17

Table S25.  Gene #51: '9p loss' versus Molecular Subtype #4: '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 S25.  Get High-res Image Gene #51: '9p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'9q loss' versus 'CN_CNMF'

P value = 0.00164 (Fisher's exact test), Q value = 0.057

Table S26.  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 S26.  Get High-res Image Gene #52: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'CN_CNMF'

P value = 0.00453 (Fisher's exact test), Q value = 0.089

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 = 0.00073 (Fisher's exact test), Q value = 0.027

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'

'10q loss' versus 'METHLYATION_CNMF'

P value = 0.0165 (Fisher's exact test), Q value = 0.21

Table S29.  Gene #54: '10q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 14 20 26 27
10Q LOSS MUTATED 1 8 8 2
10Q LOSS WILD-TYPE 13 12 18 25

Figure S29.  Get High-res Image Gene #54: '10q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'11q loss' versus 'MRNASEQ_CNMF'

P value = 0.00424 (Fisher's exact test), Q value = 0.089

Table S30.  Gene #56: '11q loss' versus Molecular Subtype #3: '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 S30.  Get High-res Image Gene #56: '11q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'11q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00283 (Fisher's exact test), Q value = 0.08

Table S31.  Gene #56: '11q loss' versus Molecular Subtype #4: '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 S31.  Get High-res Image Gene #56: '11q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'13q loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.0204 (Fisher's exact test), Q value = 0.24

Table S32.  Gene #58: '13q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 37 27 21
13Q LOSS MUTATED 14 5 12
13Q LOSS WILD-TYPE 23 22 9

Figure S32.  Get High-res Image Gene #58: '13q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'14q loss' versus 'CN_CNMF'

P value = 4e-04 (Fisher's exact test), Q value = 0.019

Table S33.  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 S33.  Get High-res Image Gene #59: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

'14q loss' versus 'MRNASEQ_CNMF'

P value = 0.00023 (Fisher's exact test), Q value = 0.014

Table S34.  Gene #59: '14q loss' versus Molecular Subtype #3: '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 S34.  Get High-res Image Gene #59: '14q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'14q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S35.  Gene #59: '14q loss' versus Molecular Subtype #4: '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 S35.  Get High-res Image Gene #59: '14q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'14q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 6e-04 (Fisher's exact test), Q value = 0.025

Table S36.  Gene #59: '14q loss' versus Molecular Subtype #6: '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 S36.  Get High-res Image Gene #59: '14q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'14q loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 0.014 (Fisher's exact test), Q value = 0.2

Table S37.  Gene #59: '14q loss' versus Molecular Subtype #7: '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 S37.  Get High-res Image Gene #59: '14q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'14q loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.00174 (Fisher's exact test), Q value = 0.057

Table S38.  Gene #59: '14q loss' versus Molecular Subtype #8: '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 S38.  Get High-res Image Gene #59: '14q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'16p loss' versus 'CN_CNMF'

P value = 0.0096 (Fisher's exact test), Q value = 0.15

Table S39.  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 S39.  Get High-res Image Gene #61: '16p loss' versus Molecular Subtype #1: 'CN_CNMF'

'20q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.0185 (Fisher's exact test), Q value = 0.23

Table S40.  Gene #70: '20q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 29 25 6 13 14
20Q LOSS MUTATED 1 0 2 0 0
20Q LOSS WILD-TYPE 28 25 4 13 14

Figure S40.  Get High-res Image Gene #70: '20q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'21q loss' versus 'METHLYATION_CNMF'

P value = 0.013 (Fisher's exact test), Q value = 0.19

Table S41.  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 S41.  Get High-res Image Gene #71: '21q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'22q loss' versus 'CN_CNMF'

P value = 0.00534 (Fisher's exact test), Q value = 0.1

Table S42.  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 S42.  Get High-res Image Gene #72: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

'22q loss' versus 'METHLYATION_CNMF'

P value = 4e-05 (Fisher's exact test), Q value = 0.0059

Table S43.  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 S43.  Get High-res Image Gene #72: '22q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'22q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00446 (Fisher's exact test), Q value = 0.089

Table S44.  Gene #72: '22q loss' versus Molecular Subtype #4: '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 S44.  Get High-res Image Gene #72: '22q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'xp loss' versus 'CN_CNMF'

P value = 0.00599 (Fisher's exact test), Q value = 0.11

Table S45.  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 S45.  Get High-res Image Gene #73: 'xp loss' versus Molecular Subtype #1: 'CN_CNMF'

'xp loss' versus 'METHLYATION_CNMF'

P value = 1e-04 (Fisher's exact test), Q value = 0.0099

Table S46.  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 S46.  Get High-res Image Gene #73: 'xp loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'xp loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00709 (Fisher's exact test), Q value = 0.12

Table S47.  Gene #73: 'xp loss' versus Molecular Subtype #4: '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 S47.  Get High-res Image Gene #73: 'xp loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'xq loss' versus 'CN_CNMF'

P value = 0.00199 (Fisher's exact test), Q value = 0.062

Table S48.  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 S48.  Get High-res Image Gene #74: 'xq loss' versus Molecular Subtype #1: 'CN_CNMF'

'xq loss' versus 'METHLYATION_CNMF'

P value = 0.00016 (Fisher's exact test), Q value = 0.012

Table S49.  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 S49.  Get High-res Image Gene #74: 'xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'xq loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00329 (Fisher's exact test), Q value = 0.082

Table S50.  Gene #74: 'xq loss' versus Molecular Subtype #4: '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 S50.  Get High-res Image Gene #74: 'xq loss' versus Molecular Subtype #4: '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/15089879/transformed.cor.cli.txt

  • Molecular subtypes file = /xchip/cga/gdac-prod/tcga-gdac/jobResults/GDAC_mergedClustering/MESO-TP/15104504/MESO-TP.transferedmergedcluster.txt

  • Number of patients = 87

  • Number of significantly arm-level cnvs = 74

  • Number of molecular subtypes = 8

  • Exclude genes that fewer than K tumors have mutations, K = 3

Fisher's exact test

For binary or multi-class clinical features (nominal or ordinal), two-tailed Fisher's exact tests (Fisher 1922) were used to estimate the P values using the 'fisher.test' function in R

Q value calculation

For multiple hypothesis correction, Q value is the False Discovery Rate (FDR) analogue of the P value (Benjamini and Hochberg 1995), defined as the minimum FDR at which the test may be called significant. We used the 'Benjamini and Hochberg' method of 'p.adjust' function in R to convert P values into Q values.

Download Results

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

References
[1] Fisher, R.A., On the interpretation of chi-square from contingency tables, and the calculation of P, Journal of the Royal Statistical Society 85(1):87-94 (1922)
[2] Benjamini and Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing, Journal of the Royal Statistical Society Series B 59:289-300 (1995)
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