Correlation between copy number variations of arm-level result and molecular subtypes
Kidney Chromophobe (Primary solid tumor)
23 May 2013  |  analyses__2013_05_23
Maintainer Information
Citation Information
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/C1RN35W9
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 57 arm-level results and 8 molecular subtypes across 66 patients, 49 significant findings detected with Q value < 0.25.

  • 4p gain cnv correlated to 'MRNASEQ_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 4q gain cnv correlated to 'MRNASEQ_CNMF'.

  • 11p gain cnv correlated to 'MRNASEQ_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

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

  • 16p gain cnv correlated to 'MRNASEQ_CNMF'.

  • 16q gain cnv correlated to 'MRNASEQ_CNMF'.

  • Xq gain cnv correlated to 'MRNASEQ_CNMF'.

  • 1p loss cnv correlated to 'METHLYATION_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 1q loss cnv correlated to 'METHLYATION_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 2p loss cnv correlated to 'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

  • 2q loss cnv correlated to 'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

  • 6p loss cnv correlated to 'METHLYATION_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 6q loss cnv correlated to 'METHLYATION_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 8p loss cnv correlated to 'CN_CNMF'.

  • 8q loss cnv correlated to 'CN_CNMF'.

  • 10p loss cnv correlated to 'MRNASEQ_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 10q loss cnv correlated to 'MRNASEQ_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 13q loss cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

  • 16q loss cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

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

  • 17q loss cnv correlated to 'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

  • Xq loss cnv correlated to 'METHLYATION_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 57 arm-level results and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 49 significant findings detected.

Molecular
subtypes
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 Chi-square test Fisher's exact test Fisher's exact test Fisher's exact test Chi-square test
2p loss 0 (0%) 23 0.0828
(1.00)
2.89e-06
(0.00127)
8.31e-09
(3.77e-06)
2.26e-07
(0.000102)
0.0679
(1.00)
0.000592
(0.242)
0.0693
(1.00)
0.000864
(0.348)
2q loss 0 (0%) 23 0.0828
(1.00)
2.89e-06
(0.00127)
8.31e-09
(3.77e-06)
2.26e-07
(0.000102)
0.0679
(1.00)
0.000592
(0.242)
0.0693
(1.00)
0.000864
(0.348)
17p loss 0 (0%) 21 0.158
(1.00)
8.78e-07
(0.000392)
2.61e-09
(1.19e-06)
3e-07
(0.000135)
0.0256
(1.00)
0.000255
(0.105)
0.0183
(1.00)
0.00074
(0.301)
17q loss 0 (0%) 21 0.158
(1.00)
8.78e-07
(0.000392)
2.61e-09
(1.19e-06)
3e-07
(0.000135)
0.0256
(1.00)
0.000255
(0.105)
0.0183
(1.00)
0.00074
(0.301)
1p loss 0 (0%) 18 0.342
(1.00)
8.27e-05
(0.0353)
8.26e-06
(0.0036)
1.79e-05
(0.0078)
0.0572
(1.00)
0.00103
(0.41)
0.0195
(1.00)
0.00549
(1.00)
1q loss 0 (0%) 19 0.32
(1.00)
0.000139
(0.0584)
3.11e-05
(0.0134)
6.59e-05
(0.0283)
0.127
(1.00)
0.00157
(0.615)
0.0214
(1.00)
0.00502
(1.00)
6p loss 0 (0%) 19 0.32
(1.00)
0.000139
(0.0584)
1.26e-06
(0.000559)
2.67e-05
(0.0116)
0.127
(1.00)
0.00157
(0.615)
0.119
(1.00)
0.00502
(1.00)
6q loss 0 (0%) 19 0.32
(1.00)
0.000139
(0.0584)
1.26e-06
(0.000559)
2.67e-05
(0.0116)
0.127
(1.00)
0.00157
(0.615)
0.119
(1.00)
0.00502
(1.00)
Xq loss 0 (0%) 33 0.713
(1.00)
9.23e-05
(0.039)
7.96e-05
(0.0341)
0.000217
(0.0897)
0.019
(1.00)
0.00208
(0.806)
0.00422
(1.00)
0.00127
(0.5)
4p gain 0 (0%) 48 0.383
(1.00)
0.934
(1.00)
4.56e-05
(0.0196)
0.000161
(0.0672)
0.239
(1.00)
0.1
(1.00)
0.777
(1.00)
0.136
(1.00)
11p gain 0 (0%) 53 0.517
(1.00)
0.599
(1.00)
0.000287
(0.118)
0.000156
(0.0652)
0.5
(1.00)
0.186
(1.00)
0.628
(1.00)
0.1
(1.00)
11q gain 0 (0%) 52 0.606
(1.00)
0.613
(1.00)
8.33e-05
(0.0355)
2.78e-05
(0.012)
0.698
(1.00)
0.186
(1.00)
0.801
(1.00)
0.106
(1.00)
10p loss 0 (0%) 22 0.261
(1.00)
0.00329
(1.00)
2.51e-06
(0.00111)
3.03e-06
(0.00133)
0.391
(1.00)
0.0506
(1.00)
0.11
(1.00)
0.0517
(1.00)
10q loss 0 (0%) 22 0.261
(1.00)
0.00329
(1.00)
2.51e-06
(0.00111)
3.03e-06
(0.00133)
0.391
(1.00)
0.0506
(1.00)
0.11
(1.00)
0.0517
(1.00)
4q gain 0 (0%) 49 0.362
(1.00)
0.806
(1.00)
0.000173
(0.0717)
0.000784
(0.317)
0.144
(1.00)
0.0977
(1.00)
0.522
(1.00)
0.172
(1.00)
16p gain 0 (0%) 51 0.556
(1.00)
1
(1.00)
9.21e-05
(0.039)
0.000936
(0.375)
0.137
(1.00)
0.106
(1.00)
0.491
(1.00)
0.31
(1.00)
16q gain 0 (0%) 51 0.556
(1.00)
1
(1.00)
9.21e-05
(0.039)
0.000936
(0.375)
0.137
(1.00)
0.106
(1.00)
0.491
(1.00)
0.31
(1.00)
Xq gain 0 (0%) 57 1
(1.00)
1
(1.00)
8.84e-05
(0.0375)
0.00417
(1.00)
0.294
(1.00)
0.341
(1.00)
0.533
(1.00)
0.348
(1.00)
8p loss 0 (0%) 57 8.11e-08
(3.67e-05)
0.0857
(1.00)
0.0531
(1.00)
0.0036
(1.00)
0.148
(1.00)
0.341
(1.00)
0.0122
(1.00)
0.0254
(1.00)
8q loss 0 (0%) 58 5.86e-07
(0.000262)
0.0437
(1.00)
0.134
(1.00)
0.00434
(1.00)
0.291
(1.00)
0.586
(1.00)
0.0267
(1.00)
0.0851
(1.00)
13q loss 0 (0%) 29 0.116
(1.00)
0.00191
(0.743)
0.00123
(0.488)
0.000506
(0.207)
0.743
(1.00)
0.036
(1.00)
0.514
(1.00)
0.404
(1.00)
16q loss 0 (0%) 62 0.685
(1.00)
0.302
(1.00)
0.00219
(0.844)
8.58e-05
(0.0365)
0.678
(1.00)
0.452
(1.00)
0.674
(1.00)
0.577
(1.00)
3p gain 0 (0%) 61 0.721
(1.00)
1
(1.00)
1
(1.00)
0.942
(1.00)
0.15
(1.00)
0.134
(1.00)
0.0544
(1.00)
0.409
(1.00)
3q gain 0 (0%) 61 0.721
(1.00)
1
(1.00)
1
(1.00)
0.942
(1.00)
0.15
(1.00)
0.134
(1.00)
0.0544
(1.00)
0.409
(1.00)
5p gain 0 (0%) 61 0.549
(1.00)
1
(1.00)
1
(1.00)
0.839
(1.00)
0.857
(1.00)
0.134
(1.00)
0.718
(1.00)
0.343
(1.00)
5q gain 0 (0%) 61 0.549
(1.00)
1
(1.00)
1
(1.00)
0.839
(1.00)
0.857
(1.00)
0.134
(1.00)
0.718
(1.00)
0.343
(1.00)
7p gain 0 (0%) 48 0.383
(1.00)
0.934
(1.00)
0.00906
(1.00)
0.0191
(1.00)
0.197
(1.00)
1
(1.00)
0.438
(1.00)
0.35
(1.00)
7q gain 0 (0%) 48 0.383
(1.00)
0.934
(1.00)
0.00906
(1.00)
0.0191
(1.00)
0.197
(1.00)
1
(1.00)
0.438
(1.00)
0.35
(1.00)
8p gain 0 (0%) 53 0.274
(1.00)
0.599
(1.00)
0.0276
(1.00)
0.0848
(1.00)
0.177
(1.00)
1
(1.00)
0.131
(1.00)
0.665
(1.00)
8q gain 0 (0%) 52 0.157
(1.00)
0.613
(1.00)
0.00994
(1.00)
0.0317
(1.00)
0.387
(1.00)
1
(1.00)
0.241
(1.00)
0.761
(1.00)
9p gain 0 (0%) 58 1
(1.00)
0.779
(1.00)
0.911
(1.00)
0.841
(1.00)
0.804
(1.00)
0.298
(1.00)
0.572
(1.00)
0.603
(1.00)
9q gain 0 (0%) 58 1
(1.00)
0.779
(1.00)
0.911
(1.00)
0.841
(1.00)
0.804
(1.00)
0.298
(1.00)
0.572
(1.00)
0.603
(1.00)
12p gain 0 (0%) 52 0.688
(1.00)
1
(1.00)
0.0129
(1.00)
0.0542
(1.00)
0.698
(1.00)
1
(1.00)
0.931
(1.00)
0.726
(1.00)
12q gain 0 (0%) 53 0.764
(1.00)
0.772
(1.00)
0.0135
(1.00)
0.0191
(1.00)
0.86
(1.00)
0.675
(1.00)
0.58
(1.00)
0.592
(1.00)
14q gain 0 (0%) 50 0.34
(1.00)
0.928
(1.00)
0.000706
(0.287)
0.00332
(1.00)
0.261
(1.00)
0.436
(1.00)
0.578
(1.00)
0.587
(1.00)
15q gain 0 (0%) 52 0.224
(1.00)
0.664
(1.00)
0.00113
(0.449)
0.00646
(1.00)
0.287
(1.00)
0.671
(1.00)
0.137
(1.00)
0.363
(1.00)
18p gain 0 (0%) 52 0.475
(1.00)
0.562
(1.00)
0.0062
(1.00)
0.0191
(1.00)
0.806
(1.00)
0.386
(1.00)
0.555
(1.00)
0.26
(1.00)
18q gain 0 (0%) 53 0.671
(1.00)
0.772
(1.00)
0.00409
(1.00)
0.0183
(1.00)
0.926
(1.00)
1
(1.00)
0.79
(1.00)
0.311
(1.00)
19p gain 0 (0%) 55 0.867
(1.00)
0.904
(1.00)
0.00206
(0.8)
0.00219
(0.844)
0.29
(1.00)
0.337
(1.00)
0.641
(1.00)
0.27
(1.00)
19q gain 0 (0%) 57 0.713
(1.00)
0.712
(1.00)
0.00269
(1.00)
0.00372
(1.00)
0.397
(1.00)
0.341
(1.00)
0.665
(1.00)
0.406
(1.00)
20p gain 0 (0%) 52 0.224
(1.00)
0.562
(1.00)
0.00468
(1.00)
0.00377
(1.00)
0.124
(1.00)
0.671
(1.00)
0.343
(1.00)
0.639
(1.00)
20q gain 0 (0%) 51 0.282
(1.00)
0.283
(1.00)
0.00713
(1.00)
0.00743
(1.00)
0.17
(1.00)
1
(1.00)
0.276
(1.00)
0.757
(1.00)
21q gain 0 (0%) 63 0.646
(1.00)
0.158
(1.00)
0.327
(1.00)
0.333
(1.00)
0.194
(1.00)
0.361
(1.00)
0.106
(1.00)
0.528
(1.00)
22q gain 0 (0%) 51 0.882
(1.00)
0.53
(1.00)
0.0748
(1.00)
0.196
(1.00)
0.466
(1.00)
1
(1.00)
0.491
(1.00)
0.872
(1.00)
3p loss 0 (0%) 59 0.0826
(1.00)
1
(1.00)
0.252
(1.00)
0.00554
(1.00)
0.481
(1.00)
0.581
(1.00)
0.349
(1.00)
0.198
(1.00)
3q loss 0 (0%) 60 0.0326
(1.00)
0.621
(1.00)
0.135
(1.00)
0.00126
(0.497)
0.354
(1.00)
0.585
(1.00)
0.109
(1.00)
0.107
(1.00)
5p loss 0 (0%) 59 0.302
(1.00)
0.141
(1.00)
0.0329
(1.00)
0.00478
(1.00)
0.886
(1.00)
0.581
(1.00)
0.691
(1.00)
0.225
(1.00)
5q loss 0 (0%) 59 0.302
(1.00)
0.141
(1.00)
0.0329
(1.00)
0.00478
(1.00)
0.886
(1.00)
0.581
(1.00)
0.691
(1.00)
0.225
(1.00)
9p loss 0 (0%) 58 1
(1.00)
0.888
(1.00)
0.171
(1.00)
0.579
(1.00)
1
(1.00)
0.298
(1.00)
0.714
(1.00)
0.843
(1.00)
9q loss 0 (0%) 58 1
(1.00)
0.888
(1.00)
0.171
(1.00)
0.579
(1.00)
1
(1.00)
0.298
(1.00)
0.714
(1.00)
0.843
(1.00)
11p loss 0 (0%) 61 1
(1.00)
0.696
(1.00)
0.129
(1.00)
0.408
(1.00)
0.12
(1.00)
1
(1.00)
0.254
(1.00)
0.161
(1.00)
11q loss 0 (0%) 61 1
(1.00)
0.696
(1.00)
0.129
(1.00)
0.408
(1.00)
0.12
(1.00)
1
(1.00)
0.254
(1.00)
0.161
(1.00)
16p loss 0 (0%) 63 1
(1.00)
0.418
(1.00)
0.0126
(1.00)
0.00148
(0.581)
1
(1.00)
1
(1.00)
1
(1.00)
0.43
(1.00)
18p loss 0 (0%) 61 0.257
(1.00)
0.109
(1.00)
0.0134
(1.00)
0.0012
(0.476)
0.12
(1.00)
1
(1.00)
0.254
(1.00)
0.328
(1.00)
18q loss 0 (0%) 59 0.222
(1.00)
0.141
(1.00)
0.0481
(1.00)
0.0178
(1.00)
0.203
(1.00)
1
(1.00)
0.349
(1.00)
0.515
(1.00)
21q loss 0 (0%) 38 1
(1.00)
0.00704
(1.00)
0.23
(1.00)
0.0379
(1.00)
0.575
(1.00)
0.722
(1.00)
0.152
(1.00)
0.157
(1.00)
22q loss 0 (0%) 61 0.721
(1.00)
0.109
(1.00)
0.745
(1.00)
0.38
(1.00)
1
(1.00)
1
(1.00)
0.849
(1.00)
0.185
(1.00)
'4p gain' versus 'MRNASEQ_CNMF'

P value = 4.56e-05 (Fisher's exact test), Q value = 0.02

Table S1.  Gene #3: '4p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
4P GAIN CNV 3 14 1 0
4P GAIN WILD-TYPE 16 8 14 10

Figure S1.  Get High-res Image Gene #3: '4p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'4p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000161 (Chi-square test), Q value = 0.067

Table S2.  Gene #3: '4p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
4P GAIN CNV 1 1 12 0 4
4P GAIN WILD-TYPE 9 9 5 6 19

Figure S2.  Get High-res Image Gene #3: '4p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'4q gain' versus 'MRNASEQ_CNMF'

P value = 0.000173 (Fisher's exact test), Q value = 0.072

Table S3.  Gene #4: '4q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
4Q GAIN CNV 3 13 1 0
4Q GAIN WILD-TYPE 16 9 14 10

Figure S3.  Get High-res Image Gene #4: '4q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'11p gain' versus 'MRNASEQ_CNMF'

P value = 0.000287 (Fisher's exact test), Q value = 0.12

Table S4.  Gene #13: '11p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
11P GAIN CNV 1 11 1 0
11P GAIN WILD-TYPE 18 11 14 10

Figure S4.  Get High-res Image Gene #13: '11p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'11p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000156 (Chi-square test), Q value = 0.065

Table S5.  Gene #13: '11p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
11P GAIN CNV 1 1 10 0 1
11P GAIN WILD-TYPE 9 9 7 6 22

Figure S5.  Get High-res Image Gene #13: '11p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'11q gain' versus 'MRNASEQ_CNMF'

P value = 8.33e-05 (Fisher's exact test), Q value = 0.035

Table S6.  Gene #14: '11q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
11Q GAIN CNV 1 12 1 0
11Q GAIN WILD-TYPE 18 10 14 10

Figure S6.  Get High-res Image Gene #14: '11q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'11q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.78e-05 (Chi-square test), Q value = 0.012

Table S7.  Gene #14: '11q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
11Q GAIN CNV 1 1 11 0 1
11Q GAIN WILD-TYPE 9 9 6 6 22

Figure S7.  Get High-res Image Gene #14: '11q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'16p gain' versus 'MRNASEQ_CNMF'

P value = 9.21e-05 (Fisher's exact test), Q value = 0.039

Table S8.  Gene #19: '16p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
16P GAIN CNV 3 12 0 0
16P GAIN WILD-TYPE 16 10 15 10

Figure S8.  Get High-res Image Gene #19: '16p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'16q gain' versus 'MRNASEQ_CNMF'

P value = 9.21e-05 (Fisher's exact test), Q value = 0.039

Table S9.  Gene #20: '16q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
16Q GAIN CNV 3 12 0 0
16Q GAIN WILD-TYPE 16 10 15 10

Figure S9.  Get High-res Image Gene #20: '16q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'Xq gain' versus 'MRNASEQ_CNMF'

P value = 8.84e-05 (Fisher's exact test), Q value = 0.037

Table S10.  Gene #29: 'Xq gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
XQ GAIN CNV 0 9 0 0
XQ GAIN WILD-TYPE 19 13 15 10

Figure S10.  Get High-res Image Gene #29: 'Xq gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'1p loss' versus 'METHLYATION_CNMF'

P value = 8.27e-05 (Fisher's exact test), Q value = 0.035

Table S11.  Gene #30: '1p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 35 13
1P LOSS CNV 16 29 3
1P LOSS WILD-TYPE 2 6 10

Figure S11.  Get High-res Image Gene #30: '1p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'1p loss' versus 'MRNASEQ_CNMF'

P value = 8.26e-06 (Fisher's exact test), Q value = 0.0036

Table S12.  Gene #30: '1p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
1P LOSS CNV 19 12 14 3
1P LOSS WILD-TYPE 0 10 1 7

Figure S12.  Get High-res Image Gene #30: '1p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'1p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1.79e-05 (Chi-square test), Q value = 0.0078

Table S13.  Gene #30: '1p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
1P LOSS CNV 9 2 9 6 22
1P LOSS WILD-TYPE 1 8 8 0 1

Figure S13.  Get High-res Image Gene #30: '1p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'1q loss' versus 'METHLYATION_CNMF'

P value = 0.000139 (Fisher's exact test), Q value = 0.058

Table S14.  Gene #31: '1q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 35 13
1Q LOSS CNV 16 28 3
1Q LOSS WILD-TYPE 2 7 10

Figure S14.  Get High-res Image Gene #31: '1q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'1q loss' versus 'MRNASEQ_CNMF'

P value = 3.11e-05 (Fisher's exact test), Q value = 0.013

Table S15.  Gene #31: '1q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
1Q LOSS CNV 19 12 13 3
1Q LOSS WILD-TYPE 0 10 2 7

Figure S15.  Get High-res Image Gene #31: '1q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'1q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 6.59e-05 (Chi-square test), Q value = 0.028

Table S16.  Gene #31: '1q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
1Q LOSS CNV 9 2 9 5 22
1Q LOSS WILD-TYPE 1 8 8 1 1

Figure S16.  Get High-res Image Gene #31: '1q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'2p loss' versus 'METHLYATION_CNMF'

P value = 2.89e-06 (Fisher's exact test), Q value = 0.0013

Table S17.  Gene #32: '2p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 35 13
2P LOSS CNV 16 26 1
2P LOSS WILD-TYPE 2 9 12

Figure S17.  Get High-res Image Gene #32: '2p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'2p loss' versus 'MRNASEQ_CNMF'

P value = 8.31e-09 (Fisher's exact test), Q value = 3.8e-06

Table S18.  Gene #32: '2p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
2P LOSS CNV 19 11 13 0
2P LOSS WILD-TYPE 0 11 2 10

Figure S18.  Get High-res Image Gene #32: '2p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'2p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.26e-07 (Chi-square test), Q value = 1e-04

Table S19.  Gene #32: '2p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
2P LOSS CNV 10 0 8 3 22
2P LOSS WILD-TYPE 0 10 9 3 1

Figure S19.  Get High-res Image Gene #32: '2p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'2p loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000592 (Fisher's exact test), Q value = 0.24

Table S20.  Gene #32: '2p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2
ALL 9 57
2P LOSS CNV 1 42
2P LOSS WILD-TYPE 8 15

Figure S20.  Get High-res Image Gene #32: '2p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'2q loss' versus 'METHLYATION_CNMF'

P value = 2.89e-06 (Fisher's exact test), Q value = 0.0013

Table S21.  Gene #33: '2q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 35 13
2Q LOSS CNV 16 26 1
2Q LOSS WILD-TYPE 2 9 12

Figure S21.  Get High-res Image Gene #33: '2q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'2q loss' versus 'MRNASEQ_CNMF'

P value = 8.31e-09 (Fisher's exact test), Q value = 3.8e-06

Table S22.  Gene #33: '2q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
2Q LOSS CNV 19 11 13 0
2Q LOSS WILD-TYPE 0 11 2 10

Figure S22.  Get High-res Image Gene #33: '2q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'2q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.26e-07 (Chi-square test), Q value = 1e-04

Table S23.  Gene #33: '2q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
2Q LOSS CNV 10 0 8 3 22
2Q LOSS WILD-TYPE 0 10 9 3 1

Figure S23.  Get High-res Image Gene #33: '2q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'2q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000592 (Fisher's exact test), Q value = 0.24

Table S24.  Gene #33: '2q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2
ALL 9 57
2Q LOSS CNV 1 42
2Q LOSS WILD-TYPE 8 15

Figure S24.  Get High-res Image Gene #33: '2q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'6p loss' versus 'METHLYATION_CNMF'

P value = 0.000139 (Fisher's exact test), Q value = 0.058

Table S25.  Gene #38: '6p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 35 13
6P LOSS CNV 16 28 3
6P LOSS WILD-TYPE 2 7 10

Figure S25.  Get High-res Image Gene #38: '6p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'6p loss' versus 'MRNASEQ_CNMF'

P value = 1.26e-06 (Fisher's exact test), Q value = 0.00056

Table S26.  Gene #38: '6p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
6P LOSS CNV 19 12 14 2
6P LOSS WILD-TYPE 0 10 1 8

Figure S26.  Get High-res Image Gene #38: '6p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'6p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.67e-05 (Chi-square test), Q value = 0.012

Table S27.  Gene #38: '6p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
6P LOSS CNV 10 2 9 4 22
6P LOSS WILD-TYPE 0 8 8 2 1

Figure S27.  Get High-res Image Gene #38: '6p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'6q loss' versus 'METHLYATION_CNMF'

P value = 0.000139 (Fisher's exact test), Q value = 0.058

Table S28.  Gene #39: '6q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 35 13
6Q LOSS CNV 16 28 3
6Q LOSS WILD-TYPE 2 7 10

Figure S28.  Get High-res Image Gene #39: '6q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'6q loss' versus 'MRNASEQ_CNMF'

P value = 1.26e-06 (Fisher's exact test), Q value = 0.00056

Table S29.  Gene #39: '6q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
6Q LOSS CNV 19 12 14 2
6Q LOSS WILD-TYPE 0 10 1 8

Figure S29.  Get High-res Image Gene #39: '6q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'6q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.67e-05 (Chi-square test), Q value = 0.012

Table S30.  Gene #39: '6q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
6Q LOSS CNV 10 2 9 4 22
6Q LOSS WILD-TYPE 0 8 8 2 1

Figure S30.  Get High-res Image Gene #39: '6q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'8p loss' versus 'CN_CNMF'

P value = 8.11e-08 (Fisher's exact test), Q value = 3.7e-05

Table S31.  Gene #40: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 5 47 14
8P LOSS CNV 0 0 9
8P LOSS WILD-TYPE 5 47 5

Figure S31.  Get High-res Image Gene #40: '8p loss' versus Molecular Subtype #1: 'CN_CNMF'

'8q loss' versus 'CN_CNMF'

P value = 5.86e-07 (Fisher's exact test), Q value = 0.00026

Table S32.  Gene #41: '8q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 5 47 14
8Q LOSS CNV 0 0 8
8Q LOSS WILD-TYPE 5 47 6

Figure S32.  Get High-res Image Gene #41: '8q loss' versus Molecular Subtype #1: 'CN_CNMF'

'10p loss' versus 'MRNASEQ_CNMF'

P value = 2.51e-06 (Fisher's exact test), Q value = 0.0011

Table S33.  Gene #44: '10p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
10P LOSS CNV 19 9 13 3
10P LOSS WILD-TYPE 0 13 2 7

Figure S33.  Get High-res Image Gene #44: '10p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'10p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3.03e-06 (Chi-square test), Q value = 0.0013

Table S34.  Gene #44: '10p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
10P LOSS CNV 10 2 6 4 22
10P LOSS WILD-TYPE 0 8 11 2 1

Figure S34.  Get High-res Image Gene #44: '10p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'10q loss' versus 'MRNASEQ_CNMF'

P value = 2.51e-06 (Fisher's exact test), Q value = 0.0011

Table S35.  Gene #45: '10q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
10Q LOSS CNV 19 9 13 3
10Q LOSS WILD-TYPE 0 13 2 7

Figure S35.  Get High-res Image Gene #45: '10q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'10q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3.03e-06 (Chi-square test), Q value = 0.0013

Table S36.  Gene #45: '10q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
10Q LOSS CNV 10 2 6 4 22
10Q LOSS WILD-TYPE 0 8 11 2 1

Figure S36.  Get High-res Image Gene #45: '10q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'13q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000506 (Chi-square test), Q value = 0.21

Table S37.  Gene #48: '13q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
13Q LOSS CNV 10 1 8 2 16
13Q LOSS WILD-TYPE 0 9 9 4 7

Figure S37.  Get High-res Image Gene #48: '13q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'16q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 8.58e-05 (Chi-square test), Q value = 0.036

Table S38.  Gene #50: '16q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
16Q LOSS CNV 4 0 0 0 0
16Q LOSS WILD-TYPE 6 10 17 6 23

Figure S38.  Get High-res Image Gene #50: '16q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'17p loss' versus 'METHLYATION_CNMF'

P value = 8.78e-07 (Fisher's exact test), Q value = 0.00039

Table S39.  Gene #51: '17p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 35 13
17P LOSS CNV 16 28 1
17P LOSS WILD-TYPE 2 7 12

Figure S39.  Get High-res Image Gene #51: '17p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'17p loss' versus 'MRNASEQ_CNMF'

P value = 2.61e-09 (Fisher's exact test), Q value = 1.2e-06

Table S40.  Gene #51: '17p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
17P LOSS CNV 19 12 14 0
17P LOSS WILD-TYPE 0 10 1 10

Figure S40.  Get High-res Image Gene #51: '17p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'17p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3e-07 (Chi-square test), Q value = 0.00013

Table S41.  Gene #51: '17p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
17P LOSS CNV 10 0 9 4 22
17P LOSS WILD-TYPE 0 10 8 2 1

Figure S41.  Get High-res Image Gene #51: '17p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'17p loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000255 (Fisher's exact test), Q value = 0.11

Table S42.  Gene #51: '17p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2
ALL 9 57
17P LOSS CNV 1 44
17P LOSS WILD-TYPE 8 13

Figure S42.  Get High-res Image Gene #51: '17p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'17q loss' versus 'METHLYATION_CNMF'

P value = 8.78e-07 (Fisher's exact test), Q value = 0.00039

Table S43.  Gene #52: '17q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 35 13
17Q LOSS CNV 16 28 1
17Q LOSS WILD-TYPE 2 7 12

Figure S43.  Get High-res Image Gene #52: '17q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'17q loss' versus 'MRNASEQ_CNMF'

P value = 2.61e-09 (Fisher's exact test), Q value = 1.2e-06

Table S44.  Gene #52: '17q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
17Q LOSS CNV 19 12 14 0
17Q LOSS WILD-TYPE 0 10 1 10

Figure S44.  Get High-res Image Gene #52: '17q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'17q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3e-07 (Chi-square test), Q value = 0.00013

Table S45.  Gene #52: '17q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
17Q LOSS CNV 10 0 9 4 22
17Q LOSS WILD-TYPE 0 10 8 2 1

Figure S45.  Get High-res Image Gene #52: '17q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'17q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.000255 (Fisher's exact test), Q value = 0.11

Table S46.  Gene #52: '17q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2
ALL 9 57
17Q LOSS CNV 1 44
17Q LOSS WILD-TYPE 8 13

Figure S46.  Get High-res Image Gene #52: '17q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'Xq loss' versus 'METHLYATION_CNMF'

P value = 9.23e-05 (Fisher's exact test), Q value = 0.039

Table S47.  Gene #57: 'Xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 35 13
XQ LOSS CNV 12 21 0
XQ LOSS WILD-TYPE 6 14 13

Figure S47.  Get High-res Image Gene #57: 'Xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'Xq loss' versus 'MRNASEQ_CNMF'

P value = 7.96e-05 (Fisher's exact test), Q value = 0.034

Table S48.  Gene #57: 'Xq loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 19 22 15 10
XQ LOSS CNV 15 8 10 0
XQ LOSS WILD-TYPE 4 14 5 10

Figure S48.  Get High-res Image Gene #57: 'Xq loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'Xq loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000217 (Chi-square test), Q value = 0.09

Table S49.  Gene #57: 'Xq loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 10 10 17 6 23
XQ LOSS CNV 7 0 5 3 18
XQ LOSS WILD-TYPE 3 10 12 3 5

Figure S49.  Get High-res Image Gene #57: 'Xq loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

Methods & Data
Input
  • Mutation data file = broad_values_by_arm.mutsig.cluster.txt

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

  • Number of patients = 66

  • Number of significantly arm-level cnvs = 57

  • 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

Chi-square test

For multi-class clinical features (nominal or ordinal), Chi-square tests (Greenwood and Nikulin 1996) were used to estimate the P values using the 'chisq.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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[3] 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)