Correlation between copy number variations of arm-level result and molecular subtypes
Kidney Renal Papillary Cell Carcinoma (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/C1RB72NB
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 59 arm-level results and 8 molecular subtypes across 127 patients, 43 significant findings detected with Q value < 0.25.

  • 1q gain cnv correlated to 'METHLYATION_CNMF'.

  • 3p gain cnv correlated to 'CN_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

  • 3q gain cnv correlated to 'CN_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_CHIERARCHICAL', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 5p gain cnv correlated to 'CN_CNMF'.

  • 5q gain cnv correlated to 'CN_CNMF'.

  • 7p gain cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

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

  • 12p gain cnv correlated to 'CN_CNMF'.

  • 12q gain cnv correlated to 'CN_CNMF'.

  • 16p gain cnv correlated to 'CN_CNMF',  'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

  • 16q gain cnv correlated to 'CN_CNMF',  'MRNASEQ_CHIERARCHICAL', and 'MIRSEQ_CHIERARCHICAL'.

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

  • 17q gain cnv correlated to 'CN_CNMF'.

  • 4p loss cnv correlated to 'CN_CNMF'.

  • 5q loss cnv correlated to 'CN_CNMF'.

  • 6p 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'.

  • 14q loss cnv correlated to 'CN_CNMF'.

  • 22q loss cnv correlated to 'CN_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 59 arm-level results and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 43 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 Chi-square 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
3q gain 0 (0%) 94 1.95e-12
(8.49e-10)
0.00739
(1.00)
3.65e-05
(0.015)
6.94e-06
(0.00291)
0.000679
(0.267)
6.07e-08
(2.61e-05)
0.197
(1.00)
0.000241
(0.0969)
17p gain 0 (0%) 61 9.52e-08
(4.09e-05)
1.3e-06
(0.000555)
3.49e-05
(0.0144)
2.21e-06
(0.000937)
0.0228
(1.00)
7.75e-05
(0.0316)
0.0197
(1.00)
0.012
(1.00)
3p gain 0 (0%) 98 7.99e-15
(3.49e-12)
0.0132
(1.00)
0.000268
(0.108)
3.64e-07
(0.000156)
0.00686
(1.00)
4.64e-09
(2.01e-06)
0.232
(1.00)
0.00425
(1.00)
7p gain 0 (0%) 60 2.69e-07
(0.000115)
2.62e-06
(0.00111)
5.65e-05
(0.0231)
2.01e-05
(0.00834)
0.0834
(1.00)
0.00341
(1.00)
0.156
(1.00)
0.00708
(1.00)
7q gain 0 (0%) 59 5.79e-08
(2.5e-05)
9.37e-06
(0.00392)
0.000181
(0.0735)
3.74e-05
(0.0153)
0.0474
(1.00)
0.0042
(1.00)
0.0832
(1.00)
0.00741
(1.00)
16p gain 0 (0%) 67 4.19e-06
(0.00177)
0.221
(1.00)
0.00874
(1.00)
0.000182
(0.0738)
0.0074
(1.00)
1.89e-05
(0.00787)
0.0997
(1.00)
0.00401
(1.00)
16q gain 0 (0%) 69 9.17e-06
(0.00384)
0.0521
(1.00)
0.00419
(1.00)
1.46e-05
(0.00609)
0.00489
(1.00)
1.8e-06
(0.000764)
0.134
(1.00)
0.00254
(0.968)
9p loss 0 (0%) 112 0.000169
(0.069)
0.000318
(0.127)
0.00782
(1.00)
0.0678
(1.00)
0.114
(1.00)
0.314
(1.00)
1
(1.00)
0.0241
(1.00)
9q loss 0 (0%) 110 0.000445
(0.177)
3.17e-05
(0.0131)
0.0256
(1.00)
0.131
(1.00)
0.0751
(1.00)
0.0814
(1.00)
1
(1.00)
0.00493
(1.00)
1q gain 0 (0%) 118 0.00553
(1.00)
0.000353
(0.141)
0.00232
(0.89)
0.00827
(1.00)
0.446
(1.00)
0.112
(1.00)
0.812
(1.00)
0.128
(1.00)
5p gain 0 (0%) 113 1.96e-08
(8.45e-06)
0.0521
(1.00)
0.156
(1.00)
0.8
(1.00)
0.835
(1.00)
0.411
(1.00)
0.437
(1.00)
0.536
(1.00)
5q gain 0 (0%) 113 2.18e-10
(9.48e-08)
0.0521
(1.00)
0.579
(1.00)
0.8
(1.00)
0.851
(1.00)
0.411
(1.00)
0.437
(1.00)
0.536
(1.00)
12p gain 0 (0%) 87 0.00055
(0.218)
0.833
(1.00)
0.161
(1.00)
0.0648
(1.00)
0.0938
(1.00)
0.103
(1.00)
0.465
(1.00)
0.11
(1.00)
12q gain 0 (0%) 87 0.00055
(0.218)
0.833
(1.00)
0.161
(1.00)
0.0648
(1.00)
0.0938
(1.00)
0.103
(1.00)
0.465
(1.00)
0.11
(1.00)
17q gain 0 (0%) 50 5.4e-06
(0.00227)
0.00104
(0.404)
0.0144
(1.00)
0.000926
(0.362)
0.0536
(1.00)
0.0135
(1.00)
0.0442
(1.00)
0.05
(1.00)
4p loss 0 (0%) 116 0.000247
(0.0993)
0.00449
(1.00)
0.0129
(1.00)
0.18
(1.00)
0.181
(1.00)
0.657
(1.00)
0.346
(1.00)
0.0408
(1.00)
5q loss 0 (0%) 121 1.96e-05
(0.00815)
0.23
(1.00)
0.41
(1.00)
0.211
(1.00)
0.547
(1.00)
0.665
(1.00)
0.239
(1.00)
0.615
(1.00)
6p loss 0 (0%) 118 0.00043
(0.171)
0.443
(1.00)
0.468
(1.00)
1
(1.00)
0.214
(1.00)
0.546
(1.00)
0.812
(1.00)
1
(1.00)
14q loss 0 (0%) 104 1.54e-11
(6.7e-09)
0.267
(1.00)
0.135
(1.00)
0.0977
(1.00)
0.757
(1.00)
0.934
(1.00)
1
(1.00)
0.458
(1.00)
22q loss 0 (0%) 103 0.000233
(0.0942)
0.00271
(1.00)
0.673
(1.00)
0.0477
(1.00)
0.0178
(1.00)
0.0721
(1.00)
0.0885
(1.00)
0.0331
(1.00)
2p gain 0 (0%) 114 0.0607
(1.00)
0.132
(1.00)
0.585
(1.00)
0.338
(1.00)
0.788
(1.00)
0.227
(1.00)
0.0415
(1.00)
0.155
(1.00)
2q gain 0 (0%) 112 0.0309
(1.00)
0.354
(1.00)
0.329
(1.00)
0.205
(1.00)
0.877
(1.00)
0.441
(1.00)
0.27
(1.00)
0.291
(1.00)
4p gain 0 (0%) 123 0.382
(1.00)
0.457
(1.00)
1
(1.00)
0.754
(1.00)
0.874
(1.00)
4q gain 0 (0%) 124 0.572
(1.00)
0.645
(1.00)
0.602
(1.00)
0.759
(1.00)
0.604
(1.00)
6p gain 0 (0%) 123 0.503
(1.00)
0.44
(1.00)
0.114
(1.00)
0.677
(1.00)
0.282
(1.00)
0.514
(1.00)
0.279
(1.00)
1
(1.00)
6q gain 0 (0%) 124 0.213
(1.00)
0.41
(1.00)
1
(1.00)
0.429
(1.00)
0.518
(1.00)
8p gain 0 (0%) 118 0.318
(1.00)
0.087
(1.00)
0.732
(1.00)
0.232
(1.00)
0.502
(1.00)
0.389
(1.00)
0.424
(1.00)
0.128
(1.00)
8q gain 0 (0%) 116 0.00446
(1.00)
0.0131
(1.00)
0.243
(1.00)
0.0683
(1.00)
0.0899
(1.00)
0.396
(1.00)
0.246
(1.00)
0.0765
(1.00)
10p gain 0 (0%) 123 0.184
(1.00)
0.645
(1.00)
0.602
(1.00)
0.138
(1.00)
0.874
(1.00)
10q gain 0 (0%) 124 0.393
(1.00)
0.317
(1.00)
0.442
(1.00)
13q gain 0 (0%) 113 0.00662
(1.00)
0.179
(1.00)
0.324
(1.00)
0.0445
(1.00)
0.638
(1.00)
0.307
(1.00)
0.928
(1.00)
0.414
(1.00)
18p gain 0 (0%) 121 0.16
(1.00)
0.329
(1.00)
0.863
(1.00)
1
(1.00)
0.885
(1.00)
0.804
(1.00)
0.188
(1.00)
0.761
(1.00)
18q gain 0 (0%) 123 0.0227
(1.00)
0.329
(1.00)
0.77
(1.00)
0.432
(1.00)
0.827
(1.00)
0.32
(1.00)
0.188
(1.00)
0.761
(1.00)
20p gain 0 (0%) 88 0.0185
(1.00)
0.0743
(1.00)
0.000722
(0.284)
0.0152
(1.00)
0.256
(1.00)
0.267
(1.00)
0.0791
(1.00)
0.189
(1.00)
20q gain 0 (0%) 87 0.0107
(1.00)
0.142
(1.00)
0.000813
(0.319)
0.0381
(1.00)
0.166
(1.00)
0.524
(1.00)
0.0213
(1.00)
0.259
(1.00)
21q gain 0 (0%) 122 0.637
(1.00)
0.468
(1.00)
0.0267
(1.00)
0.193
(1.00)
0.00525
(1.00)
1
(1.00)
Xq gain 0 (0%) 122 0.121
(1.00)
0.137
(1.00)
0.457
(1.00)
1
(1.00)
0.278
(1.00)
0.752
(1.00)
0.827
(1.00)
0.204
(1.00)
1p loss 0 (0%) 113 0.0256
(1.00)
0.328
(1.00)
0.611
(1.00)
0.589
(1.00)
0.417
(1.00)
0.283
(1.00)
0.162
(1.00)
0.472
(1.00)
1q loss 0 (0%) 120 0.0171
(1.00)
0.193
(1.00)
0.103
(1.00)
0.432
(1.00)
0.111
(1.00)
0.00803
(1.00)
0.377
(1.00)
0.123
(1.00)
3p loss 0 (0%) 119 0.00138
(0.536)
0.00142
(0.549)
0.058
(1.00)
0.0149
(1.00)
0.0923
(1.00)
0.073
(1.00)
0.426
(1.00)
0.00239
(0.914)
3q loss 0 (0%) 124 0.248
(1.00)
0.0335
(1.00)
0.0288
(1.00)
0.0762
(1.00)
0.106
(1.00)
0.518
(1.00)
0.778
(1.00)
0.0539
(1.00)
4q loss 0 (0%) 115 0.00104
(0.404)
0.00153
(0.59)
0.0999
(1.00)
0.0683
(1.00)
0.394
(1.00)
0.802
(1.00)
0.671
(1.00)
0.163
(1.00)
5p loss 0 (0%) 122 0.00932
(1.00)
0.246
(1.00)
0.114
(1.00)
0.0626
(1.00)
0.805
(1.00)
0.831
(1.00)
0.438
(1.00)
0.848
(1.00)
6q loss 0 (0%) 115 0.00107
(0.415)
0.066
(1.00)
0.374
(1.00)
0.558
(1.00)
0.151
(1.00)
0.802
(1.00)
0.618
(1.00)
0.163
(1.00)
8p loss 0 (0%) 124 0.846
(1.00)
1
(1.00)
0.604
(1.00)
10p loss 0 (0%) 120 0.0171
(1.00)
0.056
(1.00)
0.269
(1.00)
0.18
(1.00)
0.273
(1.00)
0.51
(1.00)
0.438
(1.00)
0.222
(1.00)
10q loss 0 (0%) 119 0.00696
(1.00)
0.0362
(1.00)
0.269
(1.00)
0.0871
(1.00)
0.0171
(1.00)
0.134
(1.00)
0.171
(1.00)
0.0667
(1.00)
11p loss 0 (0%) 118 0.167
(1.00)
0.113
(1.00)
0.269
(1.00)
0.145
(1.00)
0.446
(1.00)
0.585
(1.00)
0.899
(1.00)
0.366
(1.00)
11q loss 0 (0%) 116 0.00512
(1.00)
0.00354
(1.00)
0.296
(1.00)
0.0563
(1.00)
0.355
(1.00)
0.936
(1.00)
0.671
(1.00)
0.911
(1.00)
13q loss 0 (0%) 115 0.019
(1.00)
0.00153
(0.59)
0.091
(1.00)
0.403
(1.00)
0.016
(1.00)
0.0706
(1.00)
0.186
(1.00)
0.00342
(1.00)
15q loss 0 (0%) 116 0.00407
(1.00)
0.119
(1.00)
0.579
(1.00)
0.487
(1.00)
0.727
(1.00)
0.714
(1.00)
0.772
(1.00)
0.667
(1.00)
16q loss 0 (0%) 124 0.632
(1.00)
0.139
(1.00)
0.871
(1.00)
0.22
(1.00)
0.498
(1.00)
0.283
(1.00)
17p loss 0 (0%) 122 0.756
(1.00)
0.0436
(1.00)
0.0288
(1.00)
0.0762
(1.00)
0.301
(1.00)
0.267
(1.00)
0.309
(1.00)
0.116
(1.00)
18p loss 0 (0%) 108 0.0863
(1.00)
0.0306
(1.00)
0.0772
(1.00)
0.0114
(1.00)
0.543
(1.00)
0.426
(1.00)
0.373
(1.00)
0.94
(1.00)
18q loss 0 (0%) 107 0.209
(1.00)
0.0155
(1.00)
0.0392
(1.00)
0.00363
(1.00)
0.755
(1.00)
0.349
(1.00)
0.63
(1.00)
0.836
(1.00)
19p loss 0 (0%) 123 0.0513
(1.00)
1
(1.00)
1
(1.00)
0.32
(1.00)
0.555
(1.00)
0.38
(1.00)
19q loss 0 (0%) 123 0.0513
(1.00)
1
(1.00)
1
(1.00)
0.697
(1.00)
0.555
(1.00)
1
(1.00)
21q loss 0 (0%) 112 0.504
(1.00)
0.231
(1.00)
0.246
(1.00)
0.728
(1.00)
0.472
(1.00)
0.376
(1.00)
0.863
(1.00)
0.173
(1.00)
Xq loss 0 (0%) 124 0.632
(1.00)
0.665
(1.00)
0.442
(1.00)
'1q gain' versus 'METHLYATION_CNMF'

P value = 0.000353 (Fisher's exact test), Q value = 0.14

Table S1.  Gene #1: '1q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 53 31
1Q GAIN CNV 1 0 7
1Q GAIN WILD-TYPE 26 53 24

Figure S1.  Get High-res Image Gene #1: '1q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'3p gain' versus 'CN_CNMF'

P value = 7.99e-15 (Chi-square test), Q value = 3.5e-12

Table S2.  Gene #4: '3p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
3P GAIN CNV 1 3 1 5 19
3P GAIN WILD-TYPE 23 41 12 21 1

Figure S2.  Get High-res Image Gene #4: '3p gain' versus Molecular Subtype #1: 'CN_CNMF'

'3p gain' versus 'MRNASEQ_CNMF'

P value = 0.000268 (Fisher's exact test), Q value = 0.11

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

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 24 25
3P GAIN CNV 12 0 7
3P GAIN WILD-TYPE 15 24 18

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

'3p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3.64e-07 (Fisher's exact test), Q value = 0.00016

Table S4.  Gene #4: '3p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 37 21
3P GAIN CNV 0 19 0
3P GAIN WILD-TYPE 18 18 21

Figure S4.  Get High-res Image Gene #4: '3p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'3p gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 4.64e-09 (Fisher's exact test), Q value = 2e-06

Table S5.  Gene #4: '3p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 48 33 11 35
3P GAIN CNV 4 2 10 13
3P GAIN WILD-TYPE 44 31 1 22

Figure S5.  Get High-res Image Gene #4: '3p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'3q gain' versus 'CN_CNMF'

P value = 1.95e-12 (Chi-square test), Q value = 8.5e-10

Table S6.  Gene #5: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
3Q GAIN CNV 2 4 2 6 19
3Q GAIN WILD-TYPE 22 40 11 20 1

Figure S6.  Get High-res Image Gene #5: '3q gain' versus Molecular Subtype #1: 'CN_CNMF'

'3q gain' versus 'MRNASEQ_CNMF'

P value = 3.65e-05 (Fisher's exact test), Q value = 0.015

Table S7.  Gene #5: '3q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 24 25
3Q GAIN CNV 14 0 8
3Q GAIN WILD-TYPE 13 24 17

Figure S7.  Get High-res Image Gene #5: '3q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'3q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 6.94e-06 (Fisher's exact test), Q value = 0.0029

Table S8.  Gene #5: '3q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 37 21
3Q GAIN CNV 1 20 1
3Q GAIN WILD-TYPE 17 17 20

Figure S8.  Get High-res Image Gene #5: '3q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'3q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 6.07e-08 (Fisher's exact test), Q value = 2.6e-05

Table S9.  Gene #5: '3q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 48 33 11 35
3Q GAIN CNV 4 5 10 14
3Q GAIN WILD-TYPE 44 28 1 21

Figure S9.  Get High-res Image Gene #5: '3q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'3q gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 0.000241 (Fisher's exact test), Q value = 0.097

Table S10.  Gene #5: '3q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 47 16 48
3Q GAIN CNV 20 0 7
3Q GAIN WILD-TYPE 27 16 41

Figure S10.  Get High-res Image Gene #5: '3q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'5p gain' versus 'CN_CNMF'

P value = 1.96e-08 (Chi-square test), Q value = 8.4e-06

Table S11.  Gene #8: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
5P GAIN CNV 1 0 0 12 1
5P GAIN WILD-TYPE 23 44 13 14 19

Figure S11.  Get High-res Image Gene #8: '5p gain' versus Molecular Subtype #1: 'CN_CNMF'

'5q gain' versus 'CN_CNMF'

P value = 2.18e-10 (Chi-square test), Q value = 9.5e-08

Table S12.  Gene #9: '5q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
5Q GAIN CNV 0 0 0 13 1
5Q GAIN WILD-TYPE 24 44 13 13 19

Figure S12.  Get High-res Image Gene #9: '5q gain' versus Molecular Subtype #1: 'CN_CNMF'

'7p gain' versus 'CN_CNMF'

P value = 2.69e-07 (Chi-square test), Q value = 0.00012

Table S13.  Gene #12: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
7P GAIN CNV 5 22 13 9 18
7P GAIN WILD-TYPE 19 22 0 17 2

Figure S13.  Get High-res Image Gene #12: '7p gain' versus Molecular Subtype #1: 'CN_CNMF'

'7p gain' versus 'METHLYATION_CNMF'

P value = 2.62e-06 (Fisher's exact test), Q value = 0.0011

Table S14.  Gene #12: '7p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 53 31
7P GAIN CNV 10 40 7
7P GAIN WILD-TYPE 17 13 24

Figure S14.  Get High-res Image Gene #12: '7p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'7p gain' versus 'MRNASEQ_CNMF'

P value = 5.65e-05 (Fisher's exact test), Q value = 0.023

Table S15.  Gene #12: '7p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 24 25
7P GAIN CNV 22 5 12
7P GAIN WILD-TYPE 5 19 13

Figure S15.  Get High-res Image Gene #12: '7p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'7p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.01e-05 (Fisher's exact test), Q value = 0.0083

Table S16.  Gene #12: '7p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 37 21
7P GAIN CNV 5 29 5
7P GAIN WILD-TYPE 13 8 16

Figure S16.  Get High-res Image Gene #12: '7p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'7q gain' versus 'CN_CNMF'

P value = 5.79e-08 (Chi-square test), Q value = 2.5e-05

Table S17.  Gene #13: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
7Q GAIN CNV 5 22 13 9 19
7Q GAIN WILD-TYPE 19 22 0 17 1

Figure S17.  Get High-res Image Gene #13: '7q gain' versus Molecular Subtype #1: 'CN_CNMF'

'7q gain' versus 'METHLYATION_CNMF'

P value = 9.37e-06 (Fisher's exact test), Q value = 0.0039

Table S18.  Gene #13: '7q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 53 31
7Q GAIN CNV 10 40 8
7Q GAIN WILD-TYPE 17 13 23

Figure S18.  Get High-res Image Gene #13: '7q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'7q gain' versus 'MRNASEQ_CNMF'

P value = 0.000181 (Fisher's exact test), Q value = 0.073

Table S19.  Gene #13: '7q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 24 25
7Q GAIN CNV 22 6 12
7Q GAIN WILD-TYPE 5 18 13

Figure S19.  Get High-res Image Gene #13: '7q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'7q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3.74e-05 (Fisher's exact test), Q value = 0.015

Table S20.  Gene #13: '7q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 37 21
7Q GAIN CNV 6 29 5
7Q GAIN WILD-TYPE 12 8 16

Figure S20.  Get High-res Image Gene #13: '7q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'12p gain' versus 'CN_CNMF'

P value = 0.00055 (Chi-square test), Q value = 0.22

Table S21.  Gene #18: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
12P GAIN CNV 7 6 10 9 8
12P GAIN WILD-TYPE 17 38 3 17 12

Figure S21.  Get High-res Image Gene #18: '12p gain' versus Molecular Subtype #1: 'CN_CNMF'

'12q gain' versus 'CN_CNMF'

P value = 0.00055 (Chi-square test), Q value = 0.22

Table S22.  Gene #19: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
12Q GAIN CNV 7 6 10 9 8
12Q GAIN WILD-TYPE 17 38 3 17 12

Figure S22.  Get High-res Image Gene #19: '12q gain' versus Molecular Subtype #1: 'CN_CNMF'

'16p gain' versus 'CN_CNMF'

P value = 4.19e-06 (Chi-square test), Q value = 0.0018

Table S23.  Gene #21: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
16P GAIN CNV 6 16 3 16 19
16P GAIN WILD-TYPE 18 28 10 10 1

Figure S23.  Get High-res Image Gene #21: '16p gain' versus Molecular Subtype #1: 'CN_CNMF'

'16p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000182 (Fisher's exact test), Q value = 0.074

Table S24.  Gene #21: '16p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 37 21
16P GAIN CNV 2 24 6
16P GAIN WILD-TYPE 16 13 15

Figure S24.  Get High-res Image Gene #21: '16p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'16p gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1.89e-05 (Fisher's exact test), Q value = 0.0079

Table S25.  Gene #21: '16p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 48 33 11 35
16P GAIN CNV 13 13 10 24
16P GAIN WILD-TYPE 35 20 1 11

Figure S25.  Get High-res Image Gene #21: '16p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'16q gain' versus 'CN_CNMF'

P value = 9.17e-06 (Chi-square test), Q value = 0.0038

Table S26.  Gene #22: '16q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
16Q GAIN CNV 6 16 3 14 19
16Q GAIN WILD-TYPE 18 28 10 12 1

Figure S26.  Get High-res Image Gene #22: '16q gain' versus Molecular Subtype #1: 'CN_CNMF'

'16q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1.46e-05 (Fisher's exact test), Q value = 0.0061

Table S27.  Gene #22: '16q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 37 21
16Q GAIN CNV 2 24 3
16Q GAIN WILD-TYPE 16 13 18

Figure S27.  Get High-res Image Gene #22: '16q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'16q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1.8e-06 (Fisher's exact test), Q value = 0.00076

Table S28.  Gene #22: '16q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 48 33 11 35
16Q GAIN CNV 13 10 10 25
16Q GAIN WILD-TYPE 35 23 1 10

Figure S28.  Get High-res Image Gene #22: '16q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'17p gain' versus 'CN_CNMF'

P value = 9.52e-08 (Chi-square test), Q value = 4.1e-05

Table S29.  Gene #23: '17p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
17P GAIN CNV 6 19 13 9 19
17P GAIN WILD-TYPE 18 25 0 17 1

Figure S29.  Get High-res Image Gene #23: '17p gain' versus Molecular Subtype #1: 'CN_CNMF'

'17p gain' versus 'METHLYATION_CNMF'

P value = 1.3e-06 (Fisher's exact test), Q value = 0.00056

Table S30.  Gene #23: '17p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 53 31
17P GAIN CNV 9 40 7
17P GAIN WILD-TYPE 18 13 24

Figure S30.  Get High-res Image Gene #23: '17p gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'17p gain' versus 'MRNASEQ_CNMF'

P value = 3.49e-05 (Fisher's exact test), Q value = 0.014

Table S31.  Gene #23: '17p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 24 25
17P GAIN CNV 20 3 10
17P GAIN WILD-TYPE 7 21 15

Figure S31.  Get High-res Image Gene #23: '17p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'17p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 2.21e-06 (Fisher's exact test), Q value = 0.00094

Table S32.  Gene #23: '17p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 37 21
17P GAIN CNV 3 27 3
17P GAIN WILD-TYPE 15 10 18

Figure S32.  Get High-res Image Gene #23: '17p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'17p gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 7.75e-05 (Fisher's exact test), Q value = 0.032

Table S33.  Gene #23: '17p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 48 33 11 35
17P GAIN CNV 22 9 10 25
17P GAIN WILD-TYPE 26 24 1 10

Figure S33.  Get High-res Image Gene #23: '17p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'17q gain' versus 'CN_CNMF'

P value = 5.4e-06 (Chi-square test), Q value = 0.0023

Table S34.  Gene #24: '17q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
17Q GAIN CNV 7 25 13 13 19
17Q GAIN WILD-TYPE 17 19 0 13 1

Figure S34.  Get High-res Image Gene #24: '17q gain' versus Molecular Subtype #1: 'CN_CNMF'

'4p loss' versus 'CN_CNMF'

P value = 0.000247 (Chi-square test), Q value = 0.099

Table S35.  Gene #35: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
4P LOSS CNV 7 0 0 4 0
4P LOSS WILD-TYPE 17 44 13 22 20

Figure S35.  Get High-res Image Gene #35: '4p loss' versus Molecular Subtype #1: 'CN_CNMF'

'5q loss' versus 'CN_CNMF'

P value = 1.96e-05 (Chi-square test), Q value = 0.0081

Table S36.  Gene #38: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
5Q LOSS CNV 6 0 0 0 0
5Q LOSS WILD-TYPE 18 44 13 26 20

Figure S36.  Get High-res Image Gene #38: '5q loss' versus Molecular Subtype #1: 'CN_CNMF'

'6p loss' versus 'CN_CNMF'

P value = 0.00043 (Chi-square test), Q value = 0.17

Table S37.  Gene #39: '6p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
6P LOSS CNV 1 0 0 7 1
6P LOSS WILD-TYPE 23 44 13 19 19

Figure S37.  Get High-res Image Gene #39: '6p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'CN_CNMF'

P value = 0.000169 (Chi-square test), Q value = 0.069

Table S38.  Gene #42: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
9P LOSS CNV 8 0 0 6 1
9P LOSS WILD-TYPE 16 44 13 20 19

Figure S38.  Get High-res Image Gene #42: '9p loss' versus Molecular Subtype #1: 'CN_CNMF'

'9p loss' versus 'METHLYATION_CNMF'

P value = 0.000318 (Fisher's exact test), Q value = 0.13

Table S39.  Gene #42: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 53 31
9P LOSS CNV 5 0 7
9P LOSS WILD-TYPE 22 53 24

Figure S39.  Get High-res Image Gene #42: '9p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'9q loss' versus 'CN_CNMF'

P value = 0.000445 (Chi-square test), Q value = 0.18

Table S40.  Gene #43: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
9Q LOSS CNV 8 1 0 7 1
9Q LOSS WILD-TYPE 16 43 13 19 19

Figure S40.  Get High-res Image Gene #43: '9q loss' versus Molecular Subtype #1: 'CN_CNMF'

'9q loss' versus 'METHLYATION_CNMF'

P value = 3.17e-05 (Fisher's exact test), Q value = 0.013

Table S41.  Gene #43: '9q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 27 53 31
9Q LOSS CNV 6 0 9
9Q LOSS WILD-TYPE 21 53 22

Figure S41.  Get High-res Image Gene #43: '9q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'14q loss' versus 'CN_CNMF'

P value = 1.54e-11 (Chi-square test), Q value = 6.7e-09

Table S42.  Gene #49: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
14Q LOSS CNV 16 0 0 7 0
14Q LOSS WILD-TYPE 8 44 13 19 20

Figure S42.  Get High-res Image Gene #49: '14q loss' versus Molecular Subtype #1: 'CN_CNMF'

'22q loss' versus 'CN_CNMF'

P value = 0.000233 (Chi-square test), Q value = 0.094

Table S43.  Gene #58: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 24 44 13 26 20
22Q LOSS CNV 6 6 0 12 0
22Q LOSS WILD-TYPE 18 38 13 14 20

Figure S43.  Get High-res Image Gene #58: '22q loss' versus Molecular Subtype #1: 'CN_CNMF'

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

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

  • Number of patients = 127

  • Number of significantly arm-level cnvs = 59

  • Number of molecular subtypes = 8

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

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

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] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[2] 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)
[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)