Correlation between copy number variations of arm-level result and molecular subtypes
Stomach Adenocarcinoma (Primary solid tumor)
22 February 2013  |  analyses__2013_02_22
Maintainer Information
Citation Information
doi:10.7908/C1SF2TF6
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/C1SF2TF6
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 74 arm-level results and 6 molecular subtypes across 237 patients, 46 significant findings detected with Q value < 0.25.

  • 1q gain cnv correlated to 'CN_CNMF'.

  • 2q gain cnv correlated to 'CN_CNMF'.

  • 5p gain cnv correlated to 'CN_CNMF'.

  • 7p gain cnv correlated to 'CN_CNMF'.

  • 7q gain cnv correlated to 'CN_CNMF'.

  • 8p gain cnv correlated to 'CN_CNMF'.

  • 8q gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 10p gain cnv correlated to 'CN_CNMF'.

  • 12p gain cnv correlated to 'CN_CNMF'.

  • 13q gain cnv correlated to 'CN_CNMF'.

  • 17q gain cnv correlated to 'CN_CNMF'.

  • 20p gain cnv correlated to 'CN_CNMF'.

  • 20q gain cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 3p loss cnv correlated to 'CN_CNMF'.

  • 3q loss cnv correlated to 'MIRSEQ_CNMF'.

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

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

  • 5p loss cnv correlated to 'CN_CNMF'.

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

  • 8p loss cnv correlated to 'CN_CNMF'.

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

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

  • 10p loss cnv correlated to 'CN_CNMF'.

  • 10q loss cnv correlated to 'CN_CNMF'.

  • 12p loss cnv correlated to 'CN_CNMF'.

  • 14q loss cnv correlated to 'CN_CNMF'.

  • 15q loss cnv correlated to 'CN_CNMF'.

  • 16p loss cnv correlated to 'CN_CNMF'.

  • 16q loss cnv correlated to 'CN_CNMF'.

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

  • 18q loss cnv correlated to 'CN_CNMF'.

  • 19p loss cnv correlated to 'CN_CNMF'.

  • 19q loss cnv correlated to 'CN_CNMF'.

  • 21q loss cnv correlated to 'CN_CNMF'.

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

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 74 arm-level results and 6 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 46 significant findings detected.

Molecular
subtypes 		CN
CNMF 		METHLYATION
CNMF 		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
17p loss 46 (19%) 191 5.09e-14
(2.11e-11) 		0.000115
(0.0443) 		0.281
(1.00) 		0.0973
(1.00) 		0.00186
(0.673) 		0.000328
(0.123)
22q loss 30 (13%) 207 1.26e-12
(5.2e-10) 		0.000259
(0.0978) 		0.664
(1.00) 		1
(1.00) 		0.000238
(0.0904) 		0.000908
(0.332)
8q gain 84 (35%) 153 1.37e-15
(5.7e-13) 		0.000134
(0.0516) 		0.364
(1.00) 		0.779
(1.00) 		0.00581
(1.00) 		0.106
(1.00)
20q gain 115 (49%) 122 2.62e-17
(1.09e-14) 		5.6e-06
(0.00222) 		0.227
(1.00) 		0.0227
(1.00) 		0.00174
(0.629) 		0.00236
(0.846)
4p loss 38 (16%) 199 2.07e-10
(8.47e-08) 		0.00621
(1.00) 		0.457
(1.00) 		0.674
(1.00) 		0.00803
(1.00) 		6.41e-07
(0.000258)
4q loss 34 (14%) 203 4.26e-11
(1.75e-08) 		0.00519
(1.00) 		0.412
(1.00) 		0.84
(1.00) 		0.00668
(1.00) 		1.4e-06
(0.000561)
5q loss 25 (11%) 212 2.11e-10
(8.6e-08) 		0.0044
(1.00) 		1
(1.00) 		1
(1.00) 		0.0158
(1.00) 		7.05e-05
(0.0272)
9p loss 38 (16%) 199 2.42e-13
(9.99e-11) 		0.000277
(0.105) 		1
(1.00) 		1
(1.00) 		0.00803
(1.00) 		0.00502
(1.00)
9q loss 20 (8%) 217 1.42e-05
(0.00558) 		0.000633
(0.235) 		0.488
(1.00) 		0.131
(1.00) 		0.0313
(1.00)
1q gain 30 (13%) 207 4.09e-05
(0.0159) 		0.063
(1.00) 		1
(1.00) 		0.84
(1.00) 		0.00675
(1.00) 		0.0376
(1.00)
2q gain 14 (6%) 223 0.000399
(0.15) 		0.0074
(1.00) 		0.233
(1.00) 		0.268
(1.00) 		0.436
(1.00) 		0.067
(1.00)
5p gain 30 (13%) 207 2.69e-05
(0.0105) 		0.0923
(1.00) 		0.281
(1.00) 		0.464
(1.00) 		0.106
(1.00) 		0.117
(1.00)
7p gain 64 (27%) 173 1.55e-08
(6.26e-06) 		0.00742
(1.00) 		1
(1.00) 		0.523
(1.00) 		0.0137
(1.00) 		0.0136
(1.00)
7q gain 56 (24%) 181 6.74e-07
(0.000271) 		0.0312
(1.00) 		1
(1.00) 		1
(1.00) 		0.0156
(1.00) 		0.301
(1.00)
8p gain 61 (26%) 176 4.52e-16
(1.88e-13) 		0.037
(1.00) 		0.543
(1.00) 		0.84
(1.00) 		0.0083
(1.00) 		0.59
(1.00)
10p gain 29 (12%) 208 1.28e-06
(0.000512) 		0.0106
(1.00) 		0.412
(1.00) 		0.557
(1.00) 		0.568
(1.00) 		0.0642
(1.00)
12p gain 20 (8%) 217 0.000215
(0.0817) 		0.0774
(1.00) 		0.233
(1.00) 		0.268
(1.00) 		0.108
(1.00) 		0.759
(1.00)
13q gain 42 (18%) 195 4.43e-05
(0.0172) 		0.00345
(1.00) 		0.721
(1.00) 		0.885
(1.00) 		0.502
(1.00) 		0.219
(1.00)
17q gain 11 (5%) 226 0.000151
(0.0577) 		1
(1.00) 		1
(1.00) 		0.0906
(1.00) 		0.792
(1.00)
20p gain 91 (38%) 146 6.59e-11
(2.7e-08) 		0.00367
(1.00) 		0.129
(1.00) 		0.0165
(1.00) 		0.114
(1.00) 		0.0208
(1.00)
3p loss 16 (7%) 221 2.11e-06
(0.000844) 		0.0401
(1.00) 		0.233
(1.00) 		0.00362
(1.00) 		0.0155
(1.00)
3q loss 9 (4%) 228 0.000707
(0.262) 		0.0516
(1.00) 		0.233
(1.00) 		0.000629
(0.235) 		0.0137
(1.00)
5p loss 13 (5%) 224 3.64e-05
(0.0142) 		0.121
(1.00) 		0.488
(1.00) 		0.414
(1.00) 		0.161
(1.00)
8p loss 17 (7%) 220 2.36e-05
(0.00925) 		0.529
(1.00) 		0.664
(1.00) 		0.73
(1.00) 		0.0228
(1.00) 		0.0155
(1.00)
10p loss 14 (6%) 223 9.62e-06
(0.0038) 		0.011
(1.00) 		1
(1.00) 		0.203
(1.00) 		0.343
(1.00) 		0.337
(1.00)
10q loss 14 (6%) 223 9.62e-06
(0.0038) 		0.011
(1.00) 		0.345
(1.00) 		0.481
(1.00) 		0.24
(1.00) 		0.209
(1.00)
12p loss 15 (6%) 222 0.000174
(0.0662) 		0.143
(1.00) 		0.108
(1.00) 		0.0284
(1.00) 		0.146
(1.00) 		0.106
(1.00)
14q loss 19 (8%) 218 0.000421
(0.157) 		0.0782
(1.00) 		0.345
(1.00) 		0.481
(1.00) 		0.0535
(1.00) 		0.0677
(1.00)
15q loss 15 (6%) 222 4.29e-06
(0.0017) 		0.024
(1.00) 		0.607
(1.00) 		0.745
(1.00) 		0.491
(1.00) 		0.219
(1.00)
16p loss 11 (5%) 226 0.000151
(0.0577) 		0.546
(1.00) 		1
(1.00) 		1
(1.00) 		0.2
(1.00) 		0.164
(1.00)
16q loss 17 (7%) 220 2.36e-05
(0.00925) 		0.108
(1.00) 		1
(1.00) 		0.349
(1.00) 		0.0386
(1.00) 		0.215
(1.00)
18q loss 37 (16%) 200 4.23e-07
(0.000171) 		0.167
(1.00) 		0.736
(1.00) 		1
(1.00) 		0.136
(1.00) 		0.208
(1.00)
19p loss 23 (10%) 214 1.3e-09
(5.29e-07) 		0.0704
(1.00) 		0.0089
(1.00) 		0.0106
(1.00) 		0.219
(1.00) 		0.00203
(0.728)
19q loss 16 (7%) 221 2.11e-06
(0.000844) 		0.0175
(1.00) 		0.0211
(1.00) 		0.0358
(1.00) 		0.101
(1.00) 		0.00326
(1.00)
21q loss 42 (18%) 195 3.54e-09
(1.44e-06) 		0.0238
(1.00) 		0.281
(1.00) 		0.0973
(1.00) 		0.0043
(1.00) 		0.453
(1.00)
1p gain 9 (4%) 228 0.00479
(1.00) 		0.323
(1.00) 		1
(1.00) 		0.387
(1.00) 		0.577
(1.00) 		0.626
(1.00)
2p gain 13 (5%) 224 0.000937
(0.342) 		0.0203
(1.00) 		0.488
(1.00) 		0.23
(1.00) 		0.00766
(1.00)
3p gain 5 (2%) 232 0.834
(1.00) 		0.858
(1.00) 		0.488
(1.00) 		0.248
(1.00) 		0.382
(1.00)
3q gain 17 (7%) 220 0.111
(1.00) 		0.193
(1.00) 		0.0211
(1.00) 		0.117
(1.00) 		0.453
(1.00) 		0.149
(1.00)
4p gain 4 (2%) 233 0.145
(1.00) 		1
(1.00) 		0.837
(1.00) 		0.689
(1.00)
5q gain 6 (3%) 231 0.0477
(1.00) 		0.108
(1.00) 		0.101
(1.00) 		0.334
(1.00) 		0.768
(1.00)
6p gain 15 (6%) 222 0.00197
(0.707) 		0.0636
(1.00) 		1
(1.00) 		1
(1.00) 		0.0269
(1.00) 		0.263
(1.00)
6q gain 13 (5%) 224 0.00374
(1.00) 		0.0296
(1.00) 		0.607
(1.00) 		0.745
(1.00) 		0.101
(1.00) 		0.251
(1.00)
9p gain 13 (5%) 224 0.0239
(1.00) 		0.581
(1.00) 		0.108
(1.00) 		0.161
(1.00) 		0.823
(1.00) 		0.445
(1.00)
9q gain 17 (7%) 220 0.00564
(1.00) 		0.978
(1.00) 		0.0485
(1.00) 		0.0394
(1.00) 		0.769
(1.00) 		0.526
(1.00)
10q gain 17 (7%) 220 0.0115
(1.00) 		0.0673
(1.00) 		0.233
(1.00) 		0.268
(1.00) 		0.0357
(1.00) 		0.556
(1.00)
11p gain 7 (3%) 230 0.198
(1.00) 		0.475
(1.00) 		1
(1.00) 		0.7
(1.00) 		0.548
(1.00)
11q gain 12 (5%) 225 0.048
(1.00) 		0.167
(1.00) 		0.488
(1.00) 		0.414
(1.00) 		0.805
(1.00)
12q gain 15 (6%) 222 0.00992
(1.00) 		0.26
(1.00) 		0.108
(1.00) 		0.279
(1.00) 		0.491
(1.00) 		0.554
(1.00)
15q gain 9 (4%) 228 0.000707
(0.262) 		0.374
(1.00) 		0.827
(1.00) 		0.0276
(1.00)
16p gain 13 (5%) 224 0.00631
(1.00) 		0.056
(1.00) 		0.607
(1.00) 		0.643
(1.00) 		0.618
(1.00) 		0.251
(1.00)
16q gain 10 (4%) 227 0.0108
(1.00) 		0.658
(1.00) 		0.607
(1.00) 		0.643
(1.00) 		0.848
(1.00) 		0.123
(1.00)
17p gain 8 (3%) 229 0.00293
(1.00) 		0.546
(1.00) 		1
(1.00) 		0.374
(1.00) 		1
(1.00)
18p gain 16 (7%) 221 0.025
(1.00) 		0.0483
(1.00) 		0.664
(1.00) 		0.84
(1.00) 		0.027
(1.00) 		0.604
(1.00)
18q gain 8 (3%) 229 0.403
(1.00) 		0.256
(1.00) 		0.607
(1.00) 		1
(1.00) 		0.0701
(1.00) 		0.132
(1.00)
19p gain 10 (4%) 227 0.901
(1.00) 		0.279
(1.00) 		0.345
(1.00) 		0.356
(1.00) 		0.066
(1.00) 		0.264
(1.00)
19q gain 21 (9%) 216 0.362
(1.00) 		0.291
(1.00) 		0.412
(1.00) 		0.23
(1.00) 		0.592
(1.00) 		0.453
(1.00)
22q gain 4 (2%) 233 0.145
(1.00) 		0.0573
(1.00) 		0.453
(1.00) 		0.369
(1.00)
1p loss 9 (4%) 228 0.000707
(0.262) 		0.877
(1.00) 		0.488
(1.00) 		0.282
(1.00) 		1
(1.00)
2p loss 4 (2%) 233 0.0722
(1.00) 		0.858
(1.00) 		1
(1.00) 		1
(1.00) 		0.087
(1.00)
2q loss 5 (2%) 232 0.0389
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.447
(1.00)
6p loss 10 (4%) 227 0.0627
(1.00) 		0.413
(1.00) 		0.488
(1.00) 		0.106
(1.00) 		0.46
(1.00)
6q loss 16 (7%) 221 0.00525
(1.00) 		0.0742
(1.00) 		0.607
(1.00) 		0.0105
(1.00) 		0.303
(1.00) 		0.486
(1.00)
7p loss 4 (2%) 233 0.0722
(1.00) 		0.233
(1.00) 		0.453
(1.00) 		0.283
(1.00)
7q loss 9 (4%) 228 0.000707
(0.262) 		0.0516
(1.00) 		0.233
(1.00) 		0.00667
(1.00) 		0.0276
(1.00)
8q loss 5 (2%) 232 0.0389
(1.00) 		0.637
(1.00) 		1
(1.00) 		0.372
(1.00) 		0.0172
(1.00)
11p loss 15 (6%) 222 0.00155
(0.564) 		0.0581
(1.00) 		1
(1.00) 		0.0974
(1.00) 		0.059
(1.00) 		0.106
(1.00)
11q loss 11 (5%) 226 0.00491
(1.00) 		0.253
(1.00) 		1
(1.00) 		0.387
(1.00) 		0.0689
(1.00) 		0.32
(1.00)
12q loss 8 (3%) 229 0.00293
(1.00) 		0.037
(1.00) 		0.233
(1.00) 		0.374
(1.00) 		0.0561
(1.00)
13q loss 8 (3%) 229 0.00293
(1.00) 		0.299
(1.00) 		0.233
(1.00) 		0.268
(1.00) 		0.374
(1.00) 		0.731
(1.00)
17q loss 15 (6%) 222 0.00082
(0.301) 		0.898
(1.00) 		0.664
(1.00) 		1
(1.00) 		0.0782
(1.00) 		0.0185
(1.00)
18p loss 24 (10%) 213 0.00162
(0.589) 		0.0513
(1.00) 		0.698
(1.00) 		0.863
(1.00) 		0.219
(1.00) 		0.126
(1.00)
20p loss 7 (3%) 230 0.0246
(1.00) 		0.0538
(1.00) 		0.488
(1.00) 		0.346
(1.00) 		0.703
(1.00)
Xq loss 12 (5%) 225 0.0622
(1.00) 		0.541
(1.00) 		0.607
(1.00) 		0.745
(1.00) 		0.355
(1.00) 		0.308
(1.00)
'1q gain mutation analysis' versus 'CN_CNMF'

P value = 4.09e-05 (Fisher's exact test), Q value = 0.016

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
1Q GAIN MUTATED 6 21 3
1Q GAIN WILD-TYPE 24 78 105

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

'2q gain mutation analysis' versus 'CN_CNMF'

P value = 0.000399 (Fisher's exact test), Q value = 0.15

Table S2.  Gene #4: '2q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
2Q GAIN MUTATED 0 13 1
2Q GAIN WILD-TYPE 30 86 107

Figure S2.  Get High-res Image Gene #4: '2q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'5p gain mutation analysis' versus 'CN_CNMF'

P value = 2.69e-05 (Fisher's exact test), Q value = 0.01

Table S3.  Gene #8: '5p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
5P GAIN MUTATED 2 24 4
5P GAIN WILD-TYPE 28 75 104

Figure S3.  Get High-res Image Gene #8: '5p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'7p gain mutation analysis' versus 'CN_CNMF'

P value = 1.55e-08 (Fisher's exact test), Q value = 6.3e-06

Table S4.  Gene #12: '7p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
7P GAIN MUTATED 10 44 10
7P GAIN WILD-TYPE 20 55 98

Figure S4.  Get High-res Image Gene #12: '7p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'7q gain mutation analysis' versus 'CN_CNMF'

P value = 6.74e-07 (Fisher's exact test), Q value = 0.00027

Table S5.  Gene #13: '7q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
7Q GAIN MUTATED 10 37 9
7Q GAIN WILD-TYPE 20 62 99

Figure S5.  Get High-res Image Gene #13: '7q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'8p gain mutation analysis' versus 'CN_CNMF'

P value = 4.52e-16 (Fisher's exact test), Q value = 1.9e-13

Table S6.  Gene #14: '8p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
8P GAIN MUTATED 26 26 9
8P GAIN WILD-TYPE 4 73 99

Figure S6.  Get High-res Image Gene #14: '8p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'8q gain mutation analysis' versus 'CN_CNMF'

P value = 1.37e-15 (Fisher's exact test), Q value = 5.7e-13

Table S7.  Gene #15: '8q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
8Q GAIN MUTATED 26 45 13
8Q GAIN WILD-TYPE 4 54 95

Figure S7.  Get High-res Image Gene #15: '8q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'8q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000134 (Fisher's exact test), Q value = 0.052

Table S8.  Gene #15: '8q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 52 55 55
8Q GAIN MUTATED 6 18 7 28
8Q GAIN WILD-TYPE 21 34 48 27

Figure S8.  Get High-res Image Gene #15: '8q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'10p gain mutation analysis' versus 'CN_CNMF'

P value = 1.28e-06 (Fisher's exact test), Q value = 0.00051

Table S9.  Gene #18: '10p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
10P GAIN MUTATED 1 25 3
10P GAIN WILD-TYPE 29 74 105

Figure S9.  Get High-res Image Gene #18: '10p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'12p gain mutation analysis' versus 'CN_CNMF'

P value = 0.000215 (Fisher's exact test), Q value = 0.082

Table S10.  Gene #22: '12p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
12P GAIN MUTATED 0 17 3
12P GAIN WILD-TYPE 30 82 105

Figure S10.  Get High-res Image Gene #22: '12p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'13q gain mutation analysis' versus 'CN_CNMF'

P value = 4.43e-05 (Fisher's exact test), Q value = 0.017

Table S11.  Gene #24: '13q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
13Q GAIN MUTATED 6 29 7
13Q GAIN WILD-TYPE 24 70 101

Figure S11.  Get High-res Image Gene #24: '13q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'17q gain mutation analysis' versus 'CN_CNMF'

P value = 0.000151 (Fisher's exact test), Q value = 0.058

Table S12.  Gene #29: '17q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
17Q GAIN MUTATED 0 11 0
17Q GAIN WILD-TYPE 30 88 108

Figure S12.  Get High-res Image Gene #29: '17q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'20p gain mutation analysis' versus 'CN_CNMF'

P value = 6.59e-11 (Fisher's exact test), Q value = 2.7e-08

Table S13.  Gene #34: '20p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
20P GAIN MUTATED 15 59 17
20P GAIN WILD-TYPE 15 40 91

Figure S13.  Get High-res Image Gene #34: '20p gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'20q gain mutation analysis' versus 'CN_CNMF'

P value = 2.62e-17 (Fisher's exact test), Q value = 1.1e-14

Table S14.  Gene #35: '20q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
20Q GAIN MUTATED 17 77 21
20Q GAIN WILD-TYPE 13 22 87

Figure S14.  Get High-res Image Gene #35: '20q gain mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'20q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 5.6e-06 (Fisher's exact test), Q value = 0.0022

Table S15.  Gene #35: '20q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 52 55 55
20Q GAIN MUTATED 14 21 15 41
20Q GAIN WILD-TYPE 13 31 40 14

Figure S15.  Get High-res Image Gene #35: '20q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'3p loss mutation analysis' versus 'CN_CNMF'

P value = 2.11e-06 (Fisher's exact test), Q value = 0.00084

Table S16.  Gene #40: '3p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
3P LOSS MUTATED 0 16 0
3P LOSS WILD-TYPE 30 83 108

Figure S16.  Get High-res Image Gene #40: '3p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'3q loss mutation analysis' versus 'MIRSEQ_CNMF'

P value = 0.000629 (Fisher's exact test), Q value = 0.23

Table S17.  Gene #41: '3q loss mutation analysis' versus Clinical Feature #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 89 55 92
3Q LOSS MUTATED 0 0 9
3Q LOSS WILD-TYPE 89 55 83

Figure S17.  Get High-res Image Gene #41: '3q loss mutation analysis' versus Clinical Feature #5: 'MIRSEQ_CNMF'

'4p loss mutation analysis' versus 'CN_CNMF'

P value = 2.07e-10 (Fisher's exact test), Q value = 8.5e-08

Table S18.  Gene #42: '4p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
4P LOSS MUTATED 0 34 4
4P LOSS WILD-TYPE 30 65 104

Figure S18.  Get High-res Image Gene #42: '4p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'4p loss mutation analysis' versus 'MIRSEQ_CHIERARCHICAL'

P value = 6.41e-07 (Fisher's exact test), Q value = 0.00026

Table S19.  Gene #42: '4p loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 59 104 73
4P LOSS MUTATED 23 9 5
4P LOSS WILD-TYPE 36 95 68

Figure S19.  Get High-res Image Gene #42: '4p loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'4q loss mutation analysis' versus 'CN_CNMF'

P value = 4.26e-11 (Fisher's exact test), Q value = 1.8e-08

Table S20.  Gene #43: '4q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
4Q LOSS MUTATED 0 32 2
4Q LOSS WILD-TYPE 30 67 106

Figure S20.  Get High-res Image Gene #43: '4q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'4q loss mutation analysis' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1.4e-06 (Fisher's exact test), Q value = 0.00056

Table S21.  Gene #43: '4q loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 59 104 73
4Q LOSS MUTATED 21 8 4
4Q LOSS WILD-TYPE 38 96 69

Figure S21.  Get High-res Image Gene #43: '4q loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'5p loss mutation analysis' versus 'CN_CNMF'

P value = 3.64e-05 (Fisher's exact test), Q value = 0.014

Table S22.  Gene #44: '5p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
5P LOSS MUTATED 0 13 0
5P LOSS WILD-TYPE 30 86 108

Figure S22.  Get High-res Image Gene #44: '5p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'5q loss mutation analysis' versus 'CN_CNMF'

P value = 2.11e-10 (Fisher's exact test), Q value = 8.6e-08

Table S23.  Gene #45: '5q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
5Q LOSS MUTATED 0 25 0
5Q LOSS WILD-TYPE 30 74 108

Figure S23.  Get High-res Image Gene #45: '5q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'5q loss mutation analysis' versus 'MIRSEQ_CHIERARCHICAL'

P value = 7.05e-05 (Fisher's exact test), Q value = 0.027

Table S24.  Gene #45: '5q loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 59 104 73
5Q LOSS MUTATED 15 7 2
5Q LOSS WILD-TYPE 44 97 71

Figure S24.  Get High-res Image Gene #45: '5q loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'8p loss mutation analysis' versus 'CN_CNMF'

P value = 2.36e-05 (Fisher's exact test), Q value = 0.0092

Table S25.  Gene #50: '8p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
8P LOSS MUTATED 0 16 1
8P LOSS WILD-TYPE 30 83 107

Figure S25.  Get High-res Image Gene #50: '8p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'9p loss mutation analysis' versus 'CN_CNMF'

P value = 2.42e-13 (Fisher's exact test), Q value = 1e-10

Table S26.  Gene #52: '9p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
9P LOSS MUTATED 1 36 1
9P LOSS WILD-TYPE 29 63 107

Figure S26.  Get High-res Image Gene #52: '9p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'9p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000277 (Fisher's exact test), Q value = 0.1

Table S27.  Gene #52: '9p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 52 55 55
9P LOSS MUTATED 1 5 5 19
9P LOSS WILD-TYPE 26 47 50 36

Figure S27.  Get High-res Image Gene #52: '9p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'9q loss mutation analysis' versus 'CN_CNMF'

P value = 1.42e-05 (Fisher's exact test), Q value = 0.0056

Table S28.  Gene #53: '9q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
9Q LOSS MUTATED 1 18 1
9Q LOSS WILD-TYPE 29 81 107

Figure S28.  Get High-res Image Gene #53: '9q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'9q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000633 (Fisher's exact test), Q value = 0.24

Table S29.  Gene #53: '9q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 52 55 55
9Q LOSS MUTATED 1 3 1 13
9Q LOSS WILD-TYPE 26 49 54 42

Figure S29.  Get High-res Image Gene #53: '9q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'10p loss mutation analysis' versus 'CN_CNMF'

P value = 9.62e-06 (Fisher's exact test), Q value = 0.0038

Table S30.  Gene #54: '10p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
10P LOSS MUTATED 0 14 0
10P LOSS WILD-TYPE 30 85 108

Figure S30.  Get High-res Image Gene #54: '10p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'10q loss mutation analysis' versus 'CN_CNMF'

P value = 9.62e-06 (Fisher's exact test), Q value = 0.0038

Table S31.  Gene #55: '10q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
10Q LOSS MUTATED 0 14 0
10Q LOSS WILD-TYPE 30 85 108

Figure S31.  Get High-res Image Gene #55: '10q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'12p loss mutation analysis' versus 'CN_CNMF'

P value = 0.000174 (Fisher's exact test), Q value = 0.066

Table S32.  Gene #58: '12p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
12P LOSS MUTATED 0 14 1
12P LOSS WILD-TYPE 30 85 107

Figure S32.  Get High-res Image Gene #58: '12p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'14q loss mutation analysis' versus 'CN_CNMF'

P value = 0.000421 (Fisher's exact test), Q value = 0.16

Table S33.  Gene #61: '14q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
14Q LOSS MUTATED 1 16 2
14Q LOSS WILD-TYPE 29 83 106

Figure S33.  Get High-res Image Gene #61: '14q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'15q loss mutation analysis' versus 'CN_CNMF'

P value = 4.29e-06 (Fisher's exact test), Q value = 0.0017

Table S34.  Gene #62: '15q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
15Q LOSS MUTATED 0 15 0
15Q LOSS WILD-TYPE 30 84 108

Figure S34.  Get High-res Image Gene #62: '15q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'16p loss mutation analysis' versus 'CN_CNMF'

P value = 0.000151 (Fisher's exact test), Q value = 0.058

Table S35.  Gene #63: '16p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
16P LOSS MUTATED 0 11 0
16P LOSS WILD-TYPE 30 88 108

Figure S35.  Get High-res Image Gene #63: '16p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'16q loss mutation analysis' versus 'CN_CNMF'

P value = 2.36e-05 (Fisher's exact test), Q value = 0.0092

Table S36.  Gene #64: '16q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
16Q LOSS MUTATED 0 16 1
16Q LOSS WILD-TYPE 30 83 107

Figure S36.  Get High-res Image Gene #64: '16q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'17p loss mutation analysis' versus 'CN_CNMF'

P value = 5.09e-14 (Fisher's exact test), Q value = 2.1e-11

Table S37.  Gene #65: '17p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
17P LOSS MUTATED 1 42 3
17P LOSS WILD-TYPE 29 57 105

Figure S37.  Get High-res Image Gene #65: '17p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'17p loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000115 (Fisher's exact test), Q value = 0.044

Table S38.  Gene #65: '17p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 52 55 55
17P LOSS MUTATED 2 7 5 22
17P LOSS WILD-TYPE 25 45 50 33

Figure S38.  Get High-res Image Gene #65: '17p loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'17p loss mutation analysis' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000328 (Fisher's exact test), Q value = 0.12

Table S39.  Gene #65: '17p loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 59 104 73
17P LOSS MUTATED 22 17 7
17P LOSS WILD-TYPE 37 87 66

Figure S39.  Get High-res Image Gene #65: '17p loss mutation analysis' versus Clinical Feature #6: 'MIRSEQ_CHIERARCHICAL'

'18q loss mutation analysis' versus 'CN_CNMF'

P value = 4.23e-07 (Fisher's exact test), Q value = 0.00017

Table S40.  Gene #68: '18q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
18Q LOSS MUTATED 0 30 7
18Q LOSS WILD-TYPE 30 69 101

Figure S40.  Get High-res Image Gene #68: '18q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'19p loss mutation analysis' versus 'CN_CNMF'

P value = 1.3e-09 (Fisher's exact test), Q value = 5.3e-07

Table S41.  Gene #69: '19p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
19P LOSS MUTATED 0 23 0
19P LOSS WILD-TYPE 30 76 108

Figure S41.  Get High-res Image Gene #69: '19p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'19q loss mutation analysis' versus 'CN_CNMF'

P value = 2.11e-06 (Fisher's exact test), Q value = 0.00084

Table S42.  Gene #70: '19q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
19Q LOSS MUTATED 0 16 0
19Q LOSS WILD-TYPE 30 83 108

Figure S42.  Get High-res Image Gene #70: '19q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'21q loss mutation analysis' versus 'CN_CNMF'

P value = 3.54e-09 (Fisher's exact test), Q value = 1.4e-06

Table S43.  Gene #72: '21q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
21Q LOSS MUTATED 3 35 4
21Q LOSS WILD-TYPE 27 64 104

Figure S43.  Get High-res Image Gene #72: '21q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'22q loss mutation analysis' versus 'CN_CNMF'

P value = 1.26e-12 (Fisher's exact test), Q value = 5.2e-10

Table S44.  Gene #73: '22q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 99 108
22Q LOSS MUTATED 0 30 0
22Q LOSS WILD-TYPE 30 69 108

Figure S44.  Get High-res Image Gene #73: '22q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'22q loss mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000259 (Fisher's exact test), Q value = 0.098

Table S45.  Gene #73: '22q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 27 52 55 55
22Q LOSS MUTATED 0 6 2 15
22Q LOSS WILD-TYPE 27 46 53 40

Figure S45.  Get High-res Image Gene #73: '22q loss mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'22q loss mutation analysis' versus 'MIRSEQ_CNMF'

P value = 0.000238 (Fisher's exact test), Q value = 0.09

Table S46.  Gene #73: '22q loss mutation analysis' versus Clinical Feature #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 89 55 92
22Q LOSS MUTATED 11 0 19
22Q LOSS WILD-TYPE 78 55 73

Figure S46.  Get High-res Image Gene #73: '22q loss mutation analysis' versus Clinical Feature #5: 'MIRSEQ_CNMF'

Methods & Data
Input

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

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

  • Number of patients = 237

  • Number of significantly arm-level cnvs = 74

  • Number of molecular subtypes = 6

  • 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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