Correlation between copy number variations of arm-level result and molecular subtypes
Lung Squamous Cell Carcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C1PK0DC1
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2013): Correlation between copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1PK0DC1
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and subtypes.

Summary

Testing the association between copy number variation 80 arm-level results and 10 molecular subtypes across 358 patients, 51 significant findings detected with Q value < 0.25.

  • 1q gain cnv correlated to 'CN_CNMF'.

  • 2p gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 5p gain cnv correlated to 'CN_CNMF'.

  • 7p gain cnv correlated to 'CN_CNMF'.

  • 7q gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 9p gain cnv correlated to 'RPPA_CHIERARCHICAL'.

  • 12p gain cnv correlated to 'CN_CNMF'.

  • 12q gain cnv correlated to 'CN_CNMF'.

  • 16q gain cnv correlated to 'CN_CNMF'.

  • 17q gain cnv correlated to 'CN_CNMF'.

  • 18p gain cnv correlated to 'MRNA_CHIERARCHICAL' and 'CN_CNMF'.

  • 18q gain cnv correlated to 'MRNA_CHIERARCHICAL'.

  • 19p gain cnv correlated to 'CN_CNMF'.

  • 20p gain cnv correlated to 'CN_CNMF'.

  • 20q gain cnv correlated to 'CN_CNMF'.

  • 22q gain cnv correlated to 'CN_CNMF'.

  • 1p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 3p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

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

  • 4q loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 5q loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 8p loss cnv correlated to 'CN_CNMF'.

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

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

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

  • 10q loss cnv correlated to 'MRNA_CHIERARCHICAL',  'CN_CNMF', and 'METHLYATION_CNMF'.

  • 11q loss cnv correlated to 'CN_CNMF'.

  • 13q loss cnv correlated to 'CN_CNMF'.

  • 14q loss cnv correlated to 'MRNASEQ_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 16p loss cnv correlated to 'CN_CNMF'.

  • 17p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 19p loss cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

  • 21q loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 80 arm-level results and 10 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 51 significant findings detected.

Molecular
subtypes 		MRNA
CNMF 		MRNA
CHIERARCHICAL 		CN
CNMF 		METHLYATION
CNMF 		RPPA
CNMF 		RPPA
CHIERARCHICAL 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
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
9q loss 94 (26%) 264 0.0026
(1.00) 		0.00385
(1.00) 		5.68e-11
(4.4e-08) 		1.02e-05
(0.00771) 		0.937
(1.00) 		0.274
(1.00) 		0.00125
(0.876) 		9.56e-05
(0.0704) 		0.314
(1.00) 		0.0119
(1.00)
10p loss 81 (23%) 277 0.0543
(1.00) 		0.134
(1.00) 		7.57e-08
(5.78e-05) 		8.4e-07
(0.000639) 		1
(1.00) 		0.0638
(1.00) 		0.0034
(1.00) 		0.0108
(1.00) 		0.0769
(1.00) 		0.000201
(0.147)
10q loss 82 (23%) 276 0.00913
(1.00) 		0.000153
(0.112) 		4.14e-11
(3.21e-08) 		2.75e-05
(0.0205) 		0.169
(1.00) 		0.00263
(1.00) 		0.000503
(0.361) 		0.000886
(0.626) 		0.0551
(1.00) 		0.000437
(0.316)
2p gain 85 (24%) 273 0.0103
(1.00) 		0.0162
(1.00) 		4.69e-09
(3.61e-06) 		1.96e-05
(0.0147) 		0.105
(1.00) 		0.37
(1.00) 		0.0165
(1.00) 		0.000531
(0.38) 		0.983
(1.00) 		0.249
(1.00)
7q gain 88 (25%) 270 0.066
(1.00) 		0.0979
(1.00) 		4.5e-11
(3.49e-08) 		3.6e-06
(0.00273) 		0.622
(1.00) 		0.7
(1.00) 		0.0227
(1.00) 		0.026
(1.00) 		0.384
(1.00) 		0.00164
(1.00)
18p gain 56 (16%) 302 0.0026
(1.00) 		9.52e-06
(0.00718) 		0.000245
(0.178) 		0.185
(1.00) 		0.14
(1.00) 		0.15
(1.00) 		0.0391
(1.00) 		0.00977
(1.00) 		0.649
(1.00) 		0.102
(1.00)
1p loss 52 (15%) 306 0.00248
(1.00) 		0.000419
(0.304) 		1.77e-09
(1.37e-06) 		1.19e-06
(0.000908) 		0.211
(1.00) 		0.124
(1.00) 		0.000766
(0.544) 		0.00707
(1.00) 		0.243
(1.00) 		0.0215
(1.00)
3p loss 148 (41%) 210 0.0501
(1.00) 		0.448
(1.00) 		6.64e-05
(0.0491) 		3.09e-05
(0.023) 		0.668
(1.00) 		0.235
(1.00) 		0.649
(1.00) 		0.0233
(1.00) 		0.768
(1.00) 		0.0843
(1.00)
4p loss 149 (42%) 209 0.171
(1.00) 		0.0319
(1.00) 		2.26e-08
(1.74e-05) 		3.56e-08
(2.72e-05) 		0.0619
(1.00) 		0.456
(1.00) 		0.441
(1.00) 		0.0331
(1.00) 		0.3
(1.00) 		0.232
(1.00)
4q loss 128 (36%) 230 0.00796
(1.00) 		0.000975
(0.687) 		1.3e-09
(1e-06) 		3.74e-06
(0.00283) 		0.0177
(1.00) 		0.194
(1.00) 		0.0137
(1.00) 		0.00387
(1.00) 		0.0702
(1.00) 		0.00684
(1.00)
5q loss 137 (38%) 221 0.185
(1.00) 		0.363
(1.00) 		7.55e-08
(5.77e-05) 		1.65e-09
(1.27e-06) 		0.103
(1.00) 		0.108
(1.00) 		0.246
(1.00) 		0.382
(1.00) 		0.445
(1.00) 		0.286
(1.00)
9p loss 149 (42%) 209 0.0591
(1.00) 		0.498
(1.00) 		1.17e-11
(9.09e-09) 		2.81e-08
(2.15e-05) 		0.916
(1.00) 		0.325
(1.00) 		0.936
(1.00) 		0.594
(1.00) 		0.936
(1.00) 		0.71
(1.00)
14q loss 67 (19%) 291 0.00058
(0.414) 		0.0217
(1.00) 		0.000493
(0.354) 		0.00111
(0.781) 		0.0461
(1.00) 		0.0164
(1.00) 		0.000101
(0.0742) 		6.4e-09
(4.92e-06) 		0.434
(1.00) 		0.0614
(1.00)
17p loss 129 (36%) 229 0.102
(1.00) 		1
(1.00) 		0.000127
(0.0931) 		7.31e-05
(0.0539) 		0.0133
(1.00) 		0.112
(1.00) 		0.499
(1.00) 		0.437
(1.00) 		0.197
(1.00) 		0.00218
(1.00)
21q loss 111 (31%) 247 0.0247
(1.00) 		0.0161
(1.00) 		9.73e-10
(7.53e-07) 		1.31e-05
(0.00988) 		0.338
(1.00) 		0.229
(1.00) 		0.0115
(1.00) 		0.0159
(1.00) 		0.00969
(1.00) 		0.61
(1.00)
1q gain 74 (21%) 284 0.133
(1.00) 		0.1
(1.00) 		1.5e-05
(0.0112) 		0.0111
(1.00) 		0.627
(1.00) 		0.522
(1.00) 		0.00329
(1.00) 		0.00179
(1.00) 		0.0462
(1.00) 		0.0852
(1.00)
5p gain 163 (46%) 195 0.886
(1.00) 		0.846
(1.00) 		0.000185
(0.135) 		0.0238
(1.00) 		0.282
(1.00) 		0.302
(1.00) 		0.15
(1.00) 		0.602
(1.00) 		0.441
(1.00) 		0.125
(1.00)
7p gain 94 (26%) 264 0.129
(1.00) 		0.171
(1.00) 		4.08e-05
(0.0302) 		0.00106
(0.746) 		0.808
(1.00) 		0.867
(1.00) 		0.255
(1.00) 		0.0994
(1.00) 		0.922
(1.00) 		0.00994
(1.00)
9p gain 19 (5%) 339 0.29
(1.00) 		0.139
(1.00) 		0.102
(1.00) 		0.93
(1.00) 		0.173
(1.00) 		0.000255
(0.186) 		0.00967
(1.00) 		0.0172
(1.00) 		0.436
(1.00) 		0.0532
(1.00)
12p gain 97 (27%) 261 0.0146
(1.00) 		0.119
(1.00) 		1.77e-05
(0.0133) 		0.208
(1.00) 		0.182
(1.00) 		0.817
(1.00) 		0.153
(1.00) 		0.0565
(1.00) 		0.775
(1.00) 		0.489
(1.00)
12q gain 43 (12%) 315 0.0296
(1.00) 		0.143
(1.00) 		2.34e-05
(0.0175) 		0.196
(1.00) 		0.144
(1.00) 		0.759
(1.00) 		0.534
(1.00) 		0.00869
(1.00) 		0.348
(1.00) 		0.283
(1.00)
16q gain 21 (6%) 337 0.237
(1.00) 		0.844
(1.00) 		8.24e-05
(0.0608) 		0.63
(1.00) 		0.397
(1.00) 		0.127
(1.00) 		0.345
(1.00) 		0.735
(1.00) 		0.218
(1.00) 		0.592
(1.00)
17q gain 37 (10%) 321 0.013
(1.00) 		0.0282
(1.00) 		1.09e-07
(8.32e-05) 		0.00336
(1.00) 		0.419
(1.00) 		0.75
(1.00) 		0.00328
(1.00) 		0.00619
(1.00) 		0.528
(1.00) 		0.186
(1.00)
18q gain 39 (11%) 319 0.00248
(1.00) 		4.95e-05
(0.0367) 		0.00872
(1.00) 		0.652
(1.00) 		0.175
(1.00) 		0.0606
(1.00) 		0.00873
(1.00) 		0.00404
(1.00) 		0.193
(1.00) 		0.0555
(1.00)
19p gain 35 (10%) 323 0.0516
(1.00) 		0.163
(1.00) 		6.25e-05
(0.0463) 		0.00467
(1.00) 		0.000492
(0.354) 		0.00194
(1.00) 		0.0695
(1.00) 		0.00866
(1.00) 		0.0723
(1.00) 		0.314
(1.00)
20p gain 97 (27%) 261 0.132
(1.00) 		0.0379
(1.00) 		4.29e-06
(0.00324) 		0.0594
(1.00) 		0.558
(1.00) 		0.282
(1.00) 		0.322
(1.00) 		0.322
(1.00) 		0.343
(1.00) 		0.0148
(1.00)
20q gain 88 (25%) 270 0.593
(1.00) 		0.464
(1.00) 		4.87e-06
(0.00368) 		0.216
(1.00) 		0.765
(1.00) 		0.328
(1.00) 		0.103
(1.00) 		0.00314
(1.00) 		0.523
(1.00) 		0.0182
(1.00)
22q gain 84 (23%) 274 0.00362
(1.00) 		0.00858
(1.00) 		4.05e-05
(0.0301) 		0.0131
(1.00) 		0.258
(1.00) 		0.00753
(1.00) 		0.0705
(1.00) 		0.0563
(1.00) 		0.983
(1.00) 		0.0122
(1.00)
8p loss 105 (29%) 253 0.276
(1.00) 		0.396
(1.00) 		3.49e-06
(0.00265) 		0.0154
(1.00) 		0.217
(1.00) 		0.966
(1.00) 		0.398
(1.00) 		0.525
(1.00) 		0.787
(1.00) 		0.524
(1.00)
11q loss 37 (10%) 321 0.322
(1.00) 		0.568
(1.00) 		3.1e-05
(0.023) 		0.000572
(0.408) 		0.0695
(1.00) 		0.246
(1.00) 		0.0484
(1.00) 		0.054
(1.00) 		0.384
(1.00) 		0.273
(1.00)
13q loss 137 (38%) 221 0.2
(1.00) 		0.626
(1.00) 		1.22e-08
(9.33e-06) 		0.000478
(0.344) 		0.162
(1.00) 		0.355
(1.00) 		0.452
(1.00) 		0.582
(1.00) 		0.808
(1.00) 		0.0412
(1.00)
16p loss 55 (15%) 303 0.422
(1.00) 		0.423
(1.00) 		0.000165
(0.121) 		0.0176
(1.00) 		0.411
(1.00) 		0.301
(1.00) 		0.334
(1.00) 		0.0367
(1.00) 		0.302
(1.00) 		0.0133
(1.00)
19p loss 60 (17%) 298 0.0394
(1.00) 		0.045
(1.00) 		0.000476
(0.343) 		0.185
(1.00) 		0.708
(1.00) 		0.827
(1.00) 		0.00105
(0.735) 		2.38e-05
(0.0178) 		0.00212
(1.00) 		0.000442
(0.319)
1p gain 21 (6%) 337 0.971
(1.00) 		0.652
(1.00) 		0.213
(1.00) 		0.217
(1.00) 		0.867
(1.00) 		0.232
(1.00) 		0.719
(1.00) 		0.14
(1.00) 		0.244
(1.00) 		0.614
(1.00)
2q gain 39 (11%) 319 0.216
(1.00) 		0.0679
(1.00) 		0.00038
(0.276) 		0.00905
(1.00) 		0.449
(1.00) 		0.497
(1.00) 		0.00456
(1.00) 		0.00461
(1.00) 		0.855
(1.00) 		0.361
(1.00)
3p gain 42 (12%) 316 0.539
(1.00) 		0.215
(1.00) 		0.00797
(1.00) 		0.000802
(0.569) 		0.741
(1.00) 		0.616
(1.00) 		0.135
(1.00) 		0.0651
(1.00) 		0.884
(1.00) 		0.251
(1.00)
3q gain 162 (45%) 196 0.072
(1.00) 		0.653
(1.00) 		0.0238
(1.00) 		0.0343
(1.00) 		0.495
(1.00) 		0.537
(1.00) 		0.441
(1.00) 		0.305
(1.00) 		0.726
(1.00) 		0.465
(1.00)
4p gain 14 (4%) 344 0.148
(1.00) 		0.15
(1.00) 		0.0232
(1.00) 		0.149
(1.00) 		0.194
(1.00) 		0.493
(1.00) 		0.0124
(1.00) 		0.163
(1.00) 		1
(1.00) 		0.924
(1.00)
4q gain 7 (2%) 351 0.363
(1.00) 		1
(1.00) 		0.456
(1.00) 		0.767
(1.00) 		0.356
(1.00) 		0.61
(1.00) 		0.74
(1.00)
5q gain 34 (9%) 324 0.0912
(1.00) 		0.371
(1.00) 		0.0367
(1.00) 		0.0414
(1.00) 		0.661
(1.00) 		0.578
(1.00) 		0.154
(1.00) 		0.392
(1.00) 		0.681
(1.00) 		0.0791
(1.00)
6p gain 31 (9%) 327 0.00102
(0.716) 		0.00853
(1.00) 		0.00522
(1.00) 		0.351
(1.00) 		0.58
(1.00) 		0.237
(1.00) 		0.0445
(1.00) 		0.00141
(0.982) 		0.923
(1.00) 		1
(1.00)
6q gain 19 (5%) 339 0.00321
(1.00) 		0.0174
(1.00) 		0.00526
(1.00) 		0.0283
(1.00) 		0.721
(1.00) 		0.555
(1.00) 		0.186
(1.00) 		0.00112
(0.782) 		0.696
(1.00) 		0.423
(1.00)
8p gain 47 (13%) 311 0.129
(1.00) 		0.143
(1.00) 		0.194
(1.00) 		0.706
(1.00) 		0.783
(1.00) 		0.427
(1.00) 		0.0705
(1.00) 		0.00455
(1.00) 		0.251
(1.00) 		0.178
(1.00)
8q gain 101 (28%) 257 0.0365
(1.00) 		0.0246
(1.00) 		0.0141
(1.00) 		0.0824
(1.00) 		0.756
(1.00) 		0.877
(1.00) 		0.0115
(1.00) 		0.00128
(0.892) 		0.0823
(1.00) 		0.16
(1.00)
9q gain 28 (8%) 330 0.0699
(1.00) 		0.0294
(1.00) 		0.0342
(1.00) 		0.084
(1.00) 		0.0753
(1.00) 		0.00248
(1.00) 		0.00177
(1.00) 		0.0015
(1.00) 		0.254
(1.00) 		0.0413
(1.00)
10p gain 16 (4%) 342 0.208
(1.00) 		1
(1.00) 		0.592
(1.00) 		0.224
(1.00) 		0.463
(1.00) 		0.107
(1.00) 		0.525
(1.00) 		1
(1.00) 		0.869
(1.00) 		0.82
(1.00)
10q gain 6 (2%) 352 0.526
(1.00) 		0.223
(1.00) 		0.104
(1.00) 		0.651
(1.00) 		0.578
(1.00) 		1
(1.00) 		0.493
(1.00) 		1
(1.00)
11p gain 19 (5%) 339 0.908
(1.00) 		0.734
(1.00) 		0.876
(1.00) 		0.306
(1.00) 		0.794
(1.00) 		0.445
(1.00) 		0.835
(1.00) 		0.789
(1.00) 		0.436
(1.00) 		0.852
(1.00)
11q gain 22 (6%) 336 0.0411
(1.00) 		0.193
(1.00) 		0.209
(1.00) 		0.207
(1.00) 		0.946
(1.00) 		0.381
(1.00) 		0.432
(1.00) 		0.0423
(1.00) 		0.86
(1.00) 		0.755
(1.00)
13q gain 8 (2%) 350 0.769
(1.00) 		1
(1.00) 		0.605
(1.00) 		0.118
(1.00) 		0.287
(1.00) 		0.351
(1.00) 		0.132
(1.00) 		0.0835
(1.00) 		0.757
(1.00) 		0.765
(1.00)
14q gain 35 (10%) 323 0.0869
(1.00) 		0.568
(1.00) 		0.95
(1.00) 		0.78
(1.00) 		0.862
(1.00) 		0.664
(1.00) 		0.342
(1.00) 		0.522
(1.00) 		0.0807
(1.00) 		0.139
(1.00)
15q gain 33 (9%) 325 0.208
(1.00) 		0.0325
(1.00) 		0.01
(1.00) 		0.0296
(1.00) 		0.215
(1.00) 		0.0214
(1.00) 		0.00672
(1.00) 		0.0575
(1.00) 		0.0502
(1.00) 		0.00193
(1.00)
16p gain 16 (4%) 342 0.589
(1.00) 		1
(1.00) 		0.000971
(0.686) 		0.355
(1.00) 		0.721
(1.00) 		0.291
(1.00) 		0.521
(1.00) 		0.266
(1.00) 		0.869
(1.00) 		0.934
(1.00)
17p gain 9 (3%) 349 0.298
(1.00) 		0.0881
(1.00) 		0.00379
(1.00) 		0.118
(1.00) 		0.0685
(1.00) 		0.406
(1.00) 		0.354
(1.00) 		0.026
(1.00) 		0.284
(1.00) 		0.0395
(1.00)
19q gain 50 (14%) 308 0.0577
(1.00) 		0.773
(1.00) 		0.0285
(1.00) 		0.692
(1.00) 		0.068
(1.00) 		0.0214
(1.00) 		0.27
(1.00) 		0.0775
(1.00) 		0.642
(1.00) 		0.952
(1.00)
21q gain 18 (5%) 340 0.968
(1.00) 		0.425
(1.00) 		0.655
(1.00) 		0.0324
(1.00) 		0.578
(1.00) 		0.965
(1.00) 		0.697
(1.00) 		0.354
(1.00) 		0.761
(1.00) 		0.176
(1.00)
Xq gain 9 (3%) 349 0.769
(1.00) 		1
(1.00) 		0.116
(1.00) 		0.624
(1.00) 		0.45
(1.00) 		0.584
(1.00) 		0.773
(1.00) 		0.154
(1.00) 		0.678
(1.00) 		0.21
(1.00)
1q loss 9 (3%) 349 0.25
(1.00) 		0.355
(1.00) 		0.737
(1.00) 		0.755
(1.00) 		0.385
(1.00) 		0.286
(1.00) 		1
(1.00) 		0.811
(1.00)
2p loss 3 (1%) 355 0.307
(1.00)
2q loss 11 (3%) 347 0.395
(1.00) 		1
(1.00) 		0.00394
(1.00) 		0.0126
(1.00) 		0.738
(1.00) 		0.584
(1.00) 		0.769
(1.00) 		0.788
(1.00) 		0.54
(1.00) 		0.742
(1.00)
3q loss 26 (7%) 332 0.261
(1.00) 		0.701
(1.00) 		0.0329
(1.00) 		0.0591
(1.00) 		0.774
(1.00) 		0.941
(1.00) 		0.384
(1.00) 		0.0769
(1.00) 		0.745
(1.00) 		0.913
(1.00)
5p loss 24 (7%) 334 0.198
(1.00) 		0.514
(1.00) 		0.0269
(1.00) 		0.248
(1.00) 		0.309
(1.00) 		0.438
(1.00) 		0.727
(1.00) 		0.393
(1.00) 		1
(1.00) 		0.83
(1.00)
6p loss 34 (9%) 324 0.0798
(1.00) 		0.0164
(1.00) 		0.000373
(0.271) 		0.00188
(1.00) 		0.0755
(1.00) 		0.0311
(1.00) 		0.00371
(1.00) 		0.00924
(1.00) 		0.52
(1.00) 		0.212
(1.00)
6q loss 40 (11%) 318 0.0827
(1.00) 		0.0116
(1.00) 		0.0023
(1.00) 		0.0169
(1.00) 		0.0748
(1.00) 		0.142
(1.00) 		0.0644
(1.00) 		0.117
(1.00) 		1
(1.00) 		0.826
(1.00)
7p loss 22 (6%) 336 0.408
(1.00) 		0.834
(1.00) 		0.00253
(1.00) 		0.0196
(1.00) 		0.502
(1.00) 		0.109
(1.00) 		0.462
(1.00) 		0.187
(1.00) 		0.0968
(1.00) 		0.104
(1.00)
7q loss 11 (3%) 347 0.472
(1.00) 		0.848
(1.00) 		0.0746
(1.00) 		0.509
(1.00) 		1
(1.00) 		0.695
(1.00) 		0.0825
(1.00) 		0.045
(1.00) 		0.383
(1.00) 		0.377
(1.00)
8q loss 12 (3%) 346 0.208
(1.00) 		0.262
(1.00) 		0.00941
(1.00) 		0.303
(1.00) 		0.296
(1.00) 		0.629
(1.00) 		0.303
(1.00) 		0.0674
(1.00) 		0.25
(1.00) 		0.85
(1.00)
11p loss 57 (16%) 301 0.0118
(1.00) 		0.311
(1.00) 		0.000693
(0.493) 		0.000583
(0.415) 		0.0453
(1.00) 		0.0134
(1.00) 		0.14
(1.00) 		0.0941
(1.00) 		0.872
(1.00) 		0.372
(1.00)
12p loss 6 (2%) 352 0.69
(1.00) 		0.179
(1.00) 		0.225
(1.00) 		0.431
(1.00) 		0.432
(1.00) 		0.571
(1.00)
12q loss 5 (1%) 353 0.532
(1.00) 		0.179
(1.00) 		0.296
(1.00) 		0.437
(1.00) 		0.775
(1.00) 		0.0917
(1.00) 		1
(1.00) 		0.571
(1.00)
15q loss 40 (11%) 318 0.764
(1.00) 		0.115
(1.00) 		0.336
(1.00) 		0.00115
(0.803) 		0.00762
(1.00) 		0.00174
(1.00) 		0.169
(1.00) 		0.0119
(1.00) 		0.188
(1.00) 		0.359
(1.00)
16q loss 70 (20%) 288 0.0651
(1.00) 		0.237
(1.00) 		0.0021
(1.00) 		0.0116
(1.00) 		0.111
(1.00) 		0.171
(1.00) 		0.154
(1.00) 		0.00052
(0.372) 		0.903
(1.00) 		0.00129
(0.901)
17q loss 22 (6%) 336 0.147
(1.00) 		0.193
(1.00) 		0.104
(1.00) 		0.0123
(1.00) 		0.303
(1.00) 		0.943
(1.00) 		0.000845
(0.598) 		0.0352
(1.00) 		0.817
(1.00) 		0.35
(1.00)
18p loss 40 (11%) 318 0.835
(1.00) 		0.907
(1.00) 		0.0134
(1.00) 		0.0612
(1.00) 		0.278
(1.00) 		0.718
(1.00) 		0.0217
(1.00) 		0.179
(1.00) 		0.667
(1.00) 		0.686
(1.00)
18q loss 73 (20%) 285 0.58
(1.00) 		0.844
(1.00) 		0.00548
(1.00) 		0.111
(1.00) 		0.193
(1.00) 		0.561
(1.00) 		0.244
(1.00) 		0.919
(1.00) 		0.0718
(1.00) 		0.982
(1.00)
19q loss 40 (11%) 318 0.541
(1.00) 		0.243
(1.00) 		0.249
(1.00) 		0.0222
(1.00) 		0.0366
(1.00) 		0.111
(1.00) 		0.811
(1.00) 		0.138
(1.00) 		0.235
(1.00) 		0.342
(1.00)
20p loss 17 (5%) 341 0.268
(1.00) 		0.0237
(1.00) 		0.101
(1.00) 		0.206
(1.00) 		0.0408
(1.00) 		0.575
(1.00) 		0.802
(1.00) 		0.597
(1.00) 		0.401
(1.00) 		0.4
(1.00)
20q loss 20 (6%) 338 0.0376
(1.00) 		0.0203
(1.00) 		0.0213
(1.00) 		0.14
(1.00) 		0.0774
(1.00) 		0.466
(1.00) 		0.0126
(1.00) 		0.0108
(1.00) 		0.541
(1.00) 		0.163
(1.00)
22q loss 35 (10%) 323 0.057
(1.00) 		0.157
(1.00) 		0.509
(1.00) 		0.754
(1.00) 		0.607
(1.00) 		0.188
(1.00) 		0.46
(1.00) 		0.0524
(1.00) 		0.103
(1.00) 		0.459
(1.00)
Xq loss 14 (4%) 344 0.634
(1.00) 		1
(1.00) 		0.428
(1.00) 		0.664
(1.00) 		0.281
(1.00) 		0.000424
(0.307) 		0.674
(1.00) 		0.853
(1.00) 		0.335
(1.00) 		0.313
(1.00)
'1q gain mutation analysis' versus 'CN_CNMF'

P value = 1.5e-05 (Fisher's exact test), Q value = 0.011

Table S1.  Gene #2: '1q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
1Q GAIN MUTATED 15 40 19
1Q GAIN WILD-TYPE 114 72 98

Figure S1.  Get High-res Image Gene #2: '1q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'2p gain mutation analysis' versus 'CN_CNMF'

P value = 4.69e-09 (Fisher's exact test), Q value = 3.6e-06

Table S2.  Gene #3: '2p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
2P GAIN MUTATED 13 49 23
2P GAIN WILD-TYPE 116 63 94

Figure S2.  Get High-res Image Gene #3: '2p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'2p gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.96e-05 (Fisher's exact test), Q value = 0.015

Table S3.  Gene #3: '2p gain mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
2P GAIN MUTATED 16 33 7
2P GAIN WILD-TYPE 74 42 52

Figure S3.  Get High-res Image Gene #3: '2p gain mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

'5p gain mutation analysis' versus 'CN_CNMF'

P value = 0.000185 (Fisher's exact test), Q value = 0.14

Table S4.  Gene #9: '5p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
5P GAIN MUTATED 45 47 71
5P GAIN WILD-TYPE 84 65 46

Figure S4.  Get High-res Image Gene #9: '5p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'7p gain mutation analysis' versus 'CN_CNMF'

P value = 4.08e-05 (Fisher's exact test), Q value = 0.03

Table S5.  Gene #13: '7p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
7P GAIN MUTATED 19 45 30
7P GAIN WILD-TYPE 110 67 87

Figure S5.  Get High-res Image Gene #13: '7p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'7q gain mutation analysis' versus 'CN_CNMF'

P value = 4.5e-11 (Fisher's exact test), Q value = 3.5e-08

Table S6.  Gene #14: '7q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
7Q GAIN MUTATED 11 52 25
7Q GAIN WILD-TYPE 118 60 92

Figure S6.  Get High-res Image Gene #14: '7q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'7q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 3.6e-06 (Fisher's exact test), Q value = 0.0027

Table S7.  Gene #14: '7q gain mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
7Q GAIN MUTATED 8 31 11
7Q GAIN WILD-TYPE 82 44 48

Figure S7.  Get High-res Image Gene #14: '7q gain mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

'9p gain mutation analysis' versus 'RPPA_CHIERARCHICAL'

P value = 0.000255 (Fisher's exact test), Q value = 0.19

Table S8.  Gene #17: '9p gain mutation analysis' versus Clinical Feature #6: 'RPPA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 47 48 58 41
9P GAIN MUTATED 0 0 9 1
9P GAIN WILD-TYPE 47 48 49 40

Figure S8.  Get High-res Image Gene #17: '9p gain mutation analysis' versus Clinical Feature #6: 'RPPA_CHIERARCHICAL'

'12p gain mutation analysis' versus 'CN_CNMF'

P value = 1.77e-05 (Fisher's exact test), Q value = 0.013

Table S9.  Gene #23: '12p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
12P GAIN MUTATED 18 45 34
12P GAIN WILD-TYPE 111 67 83

Figure S9.  Get High-res Image Gene #23: '12p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'12q gain mutation analysis' versus 'CN_CNMF'

P value = 2.34e-05 (Fisher's exact test), Q value = 0.017

Table S10.  Gene #24: '12q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
12Q GAIN MUTATED 5 26 12
12Q GAIN WILD-TYPE 124 86 105

Figure S10.  Get High-res Image Gene #24: '12q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'16q gain mutation analysis' versus 'CN_CNMF'

P value = 8.24e-05 (Fisher's exact test), Q value = 0.061

Table S11.  Gene #29: '16q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
16Q GAIN MUTATED 0 8 13
16Q GAIN WILD-TYPE 129 104 104

Figure S11.  Get High-res Image Gene #29: '16q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'17q gain mutation analysis' versus 'CN_CNMF'

P value = 1.09e-07 (Fisher's exact test), Q value = 8.3e-05

Table S12.  Gene #31: '17q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
17Q GAIN MUTATED 2 26 9
17Q GAIN WILD-TYPE 127 86 108

Figure S12.  Get High-res Image Gene #31: '17q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'18p gain mutation analysis' versus 'MRNA_CHIERARCHICAL'

P value = 9.52e-06 (Fisher's exact test), Q value = 0.0072

Table S13.  Gene #32: '18p gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 28 54 72
18P GAIN MUTATED 2 20 4
18P GAIN WILD-TYPE 26 34 68

Figure S13.  Get High-res Image Gene #32: '18p gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

'18p gain mutation analysis' versus 'CN_CNMF'

P value = 0.000245 (Fisher's exact test), Q value = 0.18

Table S14.  Gene #32: '18p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
18P GAIN MUTATED 14 31 11
18P GAIN WILD-TYPE 115 81 106

Figure S14.  Get High-res Image Gene #32: '18p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'18q gain mutation analysis' versus 'MRNA_CHIERARCHICAL'

P value = 4.95e-05 (Fisher's exact test), Q value = 0.037

Table S15.  Gene #33: '18q gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 28 54 72
18Q GAIN MUTATED 2 17 3
18Q GAIN WILD-TYPE 26 37 69

Figure S15.  Get High-res Image Gene #33: '18q gain mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

'19p gain mutation analysis' versus 'CN_CNMF'

P value = 6.25e-05 (Fisher's exact test), Q value = 0.046

Table S16.  Gene #34: '19p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
19P GAIN MUTATED 7 23 5
19P GAIN WILD-TYPE 122 89 112

Figure S16.  Get High-res Image Gene #34: '19p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'20p gain mutation analysis' versus 'CN_CNMF'

P value = 4.29e-06 (Fisher's exact test), Q value = 0.0032

Table S17.  Gene #36: '20p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
20P GAIN MUTATED 16 43 38
20P GAIN WILD-TYPE 113 69 79

Figure S17.  Get High-res Image Gene #36: '20p gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'20q gain mutation analysis' versus 'CN_CNMF'

P value = 4.87e-06 (Fisher's exact test), Q value = 0.0037

Table S18.  Gene #37: '20q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
20Q GAIN MUTATED 14 31 43
20Q GAIN WILD-TYPE 115 81 74

Figure S18.  Get High-res Image Gene #37: '20q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'22q gain mutation analysis' versus 'CN_CNMF'

P value = 4.05e-05 (Fisher's exact test), Q value = 0.03

Table S19.  Gene #39: '22q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
22Q GAIN MUTATED 15 40 29
22Q GAIN WILD-TYPE 114 72 88

Figure S19.  Get High-res Image Gene #39: '22q gain mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'1p loss mutation analysis' versus 'CN_CNMF'

P value = 1.77e-09 (Fisher's exact test), Q value = 1.4e-06

Table S20.  Gene #41: '1p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
1P LOSS MUTATED 5 36 11
1P LOSS WILD-TYPE 124 76 106

Figure S20.  Get High-res Image Gene #41: '1p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'1p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.19e-06 (Fisher's exact test), Q value = 0.00091

Table S21.  Gene #41: '1p loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
1P LOSS MUTATED 3 24 7
1P LOSS WILD-TYPE 87 51 52

Figure S21.  Get High-res Image Gene #41: '1p loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

'3p loss mutation analysis' versus 'CN_CNMF'

P value = 6.64e-05 (Fisher's exact test), Q value = 0.049

Table S22.  Gene #45: '3p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
3P LOSS MUTATED 34 55 59
3P LOSS WILD-TYPE 95 57 58

Figure S22.  Get High-res Image Gene #45: '3p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'3p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 3.09e-05 (Fisher's exact test), Q value = 0.023

Table S23.  Gene #45: '3p loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
3P LOSS MUTATED 20 36 33
3P LOSS WILD-TYPE 70 39 26

Figure S23.  Get High-res Image Gene #45: '3p loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

'4p loss mutation analysis' versus 'CN_CNMF'

P value = 2.26e-08 (Fisher's exact test), Q value = 1.7e-05

Table S24.  Gene #47: '4p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
4P LOSS MUTATED 34 71 44
4P LOSS WILD-TYPE 95 41 73

Figure S24.  Get High-res Image Gene #47: '4p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'4p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 3.56e-08 (Fisher's exact test), Q value = 2.7e-05

Table S25.  Gene #47: '4p loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
4P LOSS MUTATED 15 42 31
4P LOSS WILD-TYPE 75 33 28

Figure S25.  Get High-res Image Gene #47: '4p loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

'4q loss mutation analysis' versus 'CN_CNMF'

P value = 1.3e-09 (Fisher's exact test), Q value = 1e-06

Table S26.  Gene #48: '4q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
4Q LOSS MUTATED 26 66 36
4Q LOSS WILD-TYPE 103 46 81

Figure S26.  Get High-res Image Gene #48: '4q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'4q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 3.74e-06 (Fisher's exact test), Q value = 0.0028

Table S27.  Gene #48: '4q loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
4Q LOSS MUTATED 13 35 26
4Q LOSS WILD-TYPE 77 40 33

Figure S27.  Get High-res Image Gene #48: '4q loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

'5q loss mutation analysis' versus 'CN_CNMF'

P value = 7.55e-08 (Fisher's exact test), Q value = 5.8e-05

Table S28.  Gene #50: '5q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
5Q LOSS MUTATED 25 58 54
5Q LOSS WILD-TYPE 104 54 63

Figure S28.  Get High-res Image Gene #50: '5q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'5q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.65e-09 (Fisher's exact test), Q value = 1.3e-06

Table S29.  Gene #50: '5q loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
5Q LOSS MUTATED 13 34 37
5Q LOSS WILD-TYPE 77 41 22

Figure S29.  Get High-res Image Gene #50: '5q loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

'8p loss mutation analysis' versus 'CN_CNMF'

P value = 3.49e-06 (Fisher's exact test), Q value = 0.0027

Table S30.  Gene #55: '8p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
8P LOSS MUTATED 21 31 53
8P LOSS WILD-TYPE 108 81 64

Figure S30.  Get High-res Image Gene #55: '8p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'9p loss mutation analysis' versus 'CN_CNMF'

P value = 1.17e-11 (Fisher's exact test), Q value = 9.1e-09

Table S31.  Gene #57: '9p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
9P LOSS MUTATED 27 46 76
9P LOSS WILD-TYPE 102 66 41

Figure S31.  Get High-res Image Gene #57: '9p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'9p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 2.81e-08 (Fisher's exact test), Q value = 2.2e-05

Table S32.  Gene #57: '9p loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
9P LOSS MUTATED 17 32 39
9P LOSS WILD-TYPE 73 43 20

Figure S32.  Get High-res Image Gene #57: '9p loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

'9q loss mutation analysis' versus 'CN_CNMF'

P value = 5.68e-11 (Fisher's exact test), Q value = 4.4e-08

Table S33.  Gene #58: '9q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
9Q LOSS MUTATED 17 19 58
9Q LOSS WILD-TYPE 112 93 59

Figure S33.  Get High-res Image Gene #58: '9q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'9q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.02e-05 (Fisher's exact test), Q value = 0.0077

Table S34.  Gene #58: '9q loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
9Q LOSS MUTATED 14 11 28
9Q LOSS WILD-TYPE 76 64 31

Figure S34.  Get High-res Image Gene #58: '9q loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

'9q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 9.56e-05 (Fisher's exact test), Q value = 0.07

Table S35.  Gene #58: '9q loss mutation analysis' versus Clinical Feature #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 116 86 55
9Q LOSS MUTATED 32 11 25
9Q LOSS WILD-TYPE 84 75 30

Figure S35.  Get High-res Image Gene #58: '9q loss mutation analysis' versus Clinical Feature #8: 'MRNASEQ_CHIERARCHICAL'

'10p loss mutation analysis' versus 'CN_CNMF'

P value = 7.57e-08 (Fisher's exact test), Q value = 5.8e-05

Table S36.  Gene #59: '10p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
10P LOSS MUTATED 9 38 34
10P LOSS WILD-TYPE 120 74 83

Figure S36.  Get High-res Image Gene #59: '10p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'10p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 8.4e-07 (Fisher's exact test), Q value = 0.00064

Table S37.  Gene #59: '10p loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
10P LOSS MUTATED 6 30 14
10P LOSS WILD-TYPE 84 45 45

Figure S37.  Get High-res Image Gene #59: '10p loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

'10p loss mutation analysis' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000201 (Fisher's exact test), Q value = 0.15

Table S38.  Gene #59: '10p loss mutation analysis' versus Clinical Feature #10: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 50 173 108
10P LOSS MUTATED 21 25 27
10P LOSS WILD-TYPE 29 148 81

Figure S38.  Get High-res Image Gene #59: '10p loss mutation analysis' versus Clinical Feature #10: 'MIRSEQ_CHIERARCHICAL'

'10q loss mutation analysis' versus 'MRNA_CHIERARCHICAL'

P value = 0.000153 (Fisher's exact test), Q value = 0.11

Table S39.  Gene #60: '10q loss mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 28 54 72
10Q LOSS MUTATED 5 21 6
10Q LOSS WILD-TYPE 23 33 66

Figure S39.  Get High-res Image Gene #60: '10q loss mutation analysis' versus Clinical Feature #2: 'MRNA_CHIERARCHICAL'

'10q loss mutation analysis' versus 'CN_CNMF'

P value = 4.14e-11 (Fisher's exact test), Q value = 3.2e-08

Table S40.  Gene #60: '10q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
10Q LOSS MUTATED 6 43 33
10Q LOSS WILD-TYPE 123 69 84

Figure S40.  Get High-res Image Gene #60: '10q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'10q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 2.75e-05 (Fisher's exact test), Q value = 0.02

Table S41.  Gene #60: '10q loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
10Q LOSS MUTATED 8 28 17
10Q LOSS WILD-TYPE 82 47 42

Figure S41.  Get High-res Image Gene #60: '10q loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

'11q loss mutation analysis' versus 'CN_CNMF'

P value = 3.1e-05 (Fisher's exact test), Q value = 0.023

Table S42.  Gene #62: '11q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
11Q LOSS MUTATED 2 17 18
11Q LOSS WILD-TYPE 127 95 99

Figure S42.  Get High-res Image Gene #62: '11q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'13q loss mutation analysis' versus 'CN_CNMF'

P value = 1.22e-08 (Fisher's exact test), Q value = 9.3e-06

Table S43.  Gene #65: '13q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
13Q LOSS MUTATED 27 42 68
13Q LOSS WILD-TYPE 102 70 49

Figure S43.  Get High-res Image Gene #65: '13q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'14q loss mutation analysis' versus 'MRNASEQ_CNMF'

P value = 0.000101 (Fisher's exact test), Q value = 0.074

Table S44.  Gene #66: '14q loss mutation analysis' versus Clinical Feature #7: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 60 80 79 38
14Q LOSS MUTATED 2 20 23 4
14Q LOSS WILD-TYPE 58 60 56 34

Figure S44.  Get High-res Image Gene #66: '14q loss mutation analysis' versus Clinical Feature #7: 'MRNASEQ_CNMF'

'14q loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 6.4e-09 (Fisher's exact test), Q value = 4.9e-06

Table S45.  Gene #66: '14q loss mutation analysis' versus Clinical Feature #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 116 86 55
14Q LOSS MUTATED 5 22 22
14Q LOSS WILD-TYPE 111 64 33

Figure S45.  Get High-res Image Gene #66: '14q loss mutation analysis' versus Clinical Feature #8: 'MRNASEQ_CHIERARCHICAL'

'16p loss mutation analysis' versus 'CN_CNMF'

P value = 0.000165 (Fisher's exact test), Q value = 0.12

Table S46.  Gene #68: '16p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
16P LOSS MUTATED 7 22 26
16P LOSS WILD-TYPE 122 90 91

Figure S46.  Get High-res Image Gene #68: '16p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'17p loss mutation analysis' versus 'CN_CNMF'

P value = 0.000127 (Fisher's exact test), Q value = 0.093

Table S47.  Gene #70: '17p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
17P LOSS MUTATED 34 35 60
17P LOSS WILD-TYPE 95 77 57

Figure S47.  Get High-res Image Gene #70: '17p loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'17p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 7.31e-05 (Fisher's exact test), Q value = 0.054

Table S48.  Gene #70: '17p loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
17P LOSS MUTATED 19 26 33
17P LOSS WILD-TYPE 71 49 26

Figure S48.  Get High-res Image Gene #70: '17p loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

'19p loss mutation analysis' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.38e-05 (Fisher's exact test), Q value = 0.018

Table S49.  Gene #74: '19p loss mutation analysis' versus Clinical Feature #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 116 86 55
19P LOSS MUTATED 15 7 21
19P LOSS WILD-TYPE 101 79 34

Figure S49.  Get High-res Image Gene #74: '19p loss mutation analysis' versus Clinical Feature #8: 'MRNASEQ_CHIERARCHICAL'

'21q loss mutation analysis' versus 'CN_CNMF'

P value = 9.73e-10 (Fisher's exact test), Q value = 7.5e-07

Table S50.  Gene #78: '21q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 129 112 117
21Q LOSS MUTATED 15 53 43
21Q LOSS WILD-TYPE 114 59 74

Figure S50.  Get High-res Image Gene #78: '21q loss mutation analysis' versus Clinical Feature #3: 'CN_CNMF'

'21q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 1.31e-05 (Fisher's exact test), Q value = 0.0099

Table S51.  Gene #78: '21q loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 90 75 59
21Q LOSS MUTATED 10 30 22
21Q LOSS WILD-TYPE 80 45 37

Figure S51.  Get High-res Image Gene #78: '21q loss mutation analysis' versus Clinical Feature #4: 'METHLYATION_CNMF'

Methods & Data
Input

  • Mutation data file = broad_values_by_arm.mutsig.cluster.txt

  • Molecular subtypes file = LUSC-TP.transferedmergedcluster.txt

  • Number of patients = 358

  • Number of significantly arm-level cnvs = 80

  • 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

This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.

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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