Correlation between copy number variation genes (focal events) and molecular subtypes
Overview
Introduction

This pipeline computes the correlation between significant copy number variation (cnv focal) genes and molecular subtypes.

Summary

Testing the association between copy number variation 40 focal events and 12 molecular subtypes across 162 patients, 12 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 4p cnv correlated to 'CN_CNMF'.

  • 4q cnv correlated to 'CN_CNMF'.

  • 7p cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 7q cnv correlated to 'CN_CNMF'.

  • 8p cnv correlated to 'CN_CNMF'.

  • 8q cnv correlated to 'CN_CNMF'.

  • 13q cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 18p cnv correlated to 'CN_CNMF'.

  • 18q cnv correlated to 'CN_CNMF'.

  • 19p 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 40 focal events and 12 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 12 significant findings detected.

Clinical
Features 		MRNA
CNMF 		MRNA
CHIERARCHICAL 		CN
CNMF 		METHLYATION
CNMF 		RPPA
CNMF 		RPPA
CHIERARCHICAL 		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 Chi-square test Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test Fisher's exact test Chi-square test Fisher's exact test Fisher's exact test Chi-square test
7p 102 (63%) 60 0.00506
(1.00) 		0.0115
(1.00) 		2.58e-05
(0.0123) 		0.00526
(1.00) 		0.638
(1.00) 		0.518
(1.00) 		0.00263
(1.00) 		7.32e-05
(0.0346) 		0.0612
(1.00) 		0.0211
(1.00) 		0.117
(1.00) 		0.238
(1.00)
13q 118 (73%) 44 0.608
(1.00) 		0.792
(1.00) 		1.81e-05
(0.00863) 		0.14
(1.00) 		0.838
(1.00) 		0.0948
(1.00) 		0.456
(1.00) 		0.000172
(0.0809) 		0.0274
(1.00) 		0.0216
(1.00) 		0.155
(1.00) 		0.317
(1.00)
4p 67 (41%) 95 0.606
(1.00) 		0.141
(1.00) 		9e-05
(0.0425) 		0.0275
(1.00) 		0.451
(1.00) 		0.0764
(1.00) 		0.983
(1.00) 		0.711
(1.00) 		0.817
(1.00) 		0.0477
(1.00) 		0.433
(1.00) 		0.519
(1.00)
4q 70 (43%) 92 0.538
(1.00) 		0.116
(1.00) 		1.49e-05
(0.00712) 		0.0132
(1.00) 		0.512
(1.00) 		0.349
(1.00) 		0.854
(1.00) 		0.9
(1.00) 		0.878
(1.00) 		0.0632
(1.00) 		0.767
(1.00) 		0.721
(1.00)
7q 86 (53%) 76 0.08
(1.00) 		0.076
(1.00) 		0.000171
(0.0802) 		0.273
(1.00) 		0.777
(1.00) 		0.967
(1.00) 		0.0783
(1.00) 		0.0229
(1.00) 		0.421
(1.00) 		0.416
(1.00) 		0.571
(1.00) 		0.763
(1.00)
8p 114 (70%) 48 0.0383
(1.00) 		0.142
(1.00) 		6.17e-08
(2.96e-05) 		0.328
(1.00) 		0.851
(1.00) 		0.712
(1.00) 		0.00456
(1.00) 		0.0657
(1.00) 		0.819
(1.00) 		0.406
(1.00) 		0.314
(1.00) 		0.0746
(1.00)
8q 99 (61%) 63 0.116
(1.00) 		0.229
(1.00) 		1.03e-06
(0.000496) 		0.0417
(1.00) 		0.574
(1.00) 		0.698
(1.00) 		0.0444
(1.00) 		0.0748
(1.00) 		0.362
(1.00) 		0.409
(1.00) 		0.812
(1.00) 		0.173
(1.00)
18p 133 (82%) 29 0.0761
(1.00) 		0.244
(1.00) 		0.000159
(0.0747) 		0.0354
(1.00) 		0.799
(1.00) 		0.442
(1.00) 		0.434
(1.00) 		0.162
(1.00) 		0.0685
(1.00) 		0.0324
(1.00) 		0.248
(1.00) 		0.905
(1.00)
18q 141 (87%) 21 0.0345
(1.00) 		0.0904
(1.00) 		3.82e-05
(0.0181) 		0.152
(1.00) 		1
(1.00) 		0.902
(1.00) 		0.627
(1.00) 		0.207
(1.00) 		0.0931
(1.00) 		0.0389
(1.00) 		0.012
(1.00) 		0.859
(1.00)
19p 53 (33%) 109 0.0415
(1.00) 		0.0562
(1.00) 		4.95e-05
(0.0235) 		0.109
(1.00) 		0.821
(1.00) 		0.629
(1.00) 		0.941
(1.00) 		0.831
(1.00) 		0.034
(1.00) 		0.162
(1.00) 		0.954
(1.00) 		0.743
(1.00)
1p 56 (35%) 106 0.602
(1.00) 		0.0373
(1.00) 		0.00124
(0.581) 		0.288
(1.00) 		0.576
(1.00) 		0.712
(1.00) 		0.83
(1.00) 		0.941
(1.00) 		0.501
(1.00) 		0.467
(1.00) 		0.729
(1.00) 		0.975
(1.00)
1q 57 (35%) 105 0.602
(1.00) 		0.291
(1.00) 		0.0116
(1.00) 		0.46
(1.00) 		0.286
(1.00) 		0.687
(1.00) 		0.877
(1.00) 		0.902
(1.00) 		0.205
(1.00) 		0.472
(1.00) 		0.365
(1.00) 		0.896
(1.00)
2p 50 (31%) 112 0.894
(1.00) 		0.18
(1.00) 		0.0105
(1.00) 		0.212
(1.00) 		0.603
(1.00) 		0.987
(1.00) 		0.271
(1.00) 		0.35
(1.00) 		0.566
(1.00) 		0.0823
(1.00) 		0.951
(1.00) 		0.0183
(1.00)
2q 47 (29%) 115 0.242
(1.00) 		0.18
(1.00) 		0.00706
(1.00) 		0.113
(1.00) 		0.266
(1.00) 		0.839
(1.00) 		0.0659
(1.00) 		0.0834
(1.00) 		0.181
(1.00) 		0.306
(1.00) 		0.455
(1.00) 		0.0107
(1.00)
3p 42 (26%) 120 1
(1.00) 		0.537
(1.00) 		0.37
(1.00) 		0.576
(1.00) 		0.106
(1.00) 		0.0796
(1.00) 		0.176
(1.00) 		0.228
(1.00) 		0.0917
(1.00) 		0.115
(1.00) 		0.513
(1.00) 		0.733
(1.00)
3q 44 (27%) 118 0.868
(1.00) 		0.927
(1.00) 		0.24
(1.00) 		0.555
(1.00) 		0.244
(1.00) 		0.176
(1.00) 		0.268
(1.00) 		0.568
(1.00) 		0.0742
(1.00) 		0.182
(1.00) 		0.822
(1.00) 		0.978
(1.00)
5p 60 (37%) 102 0.216
(1.00) 		0.329
(1.00) 		0.0125
(1.00) 		0.0331
(1.00) 		0.854
(1.00) 		0.373
(1.00) 		0.217
(1.00) 		0.201
(1.00) 		0.88
(1.00) 		0.435
(1.00) 		1
(1.00) 		0.939
(1.00)
5q 62 (38%) 100 0.0883
(1.00) 		0.0048
(1.00) 		0.00139
(0.646) 		0.0899
(1.00) 		0.434
(1.00) 		0.74
(1.00) 		0.266
(1.00) 		0.456
(1.00) 		0.906
(1.00) 		0.296
(1.00) 		0.931
(1.00) 		0.969
(1.00)
6p 53 (33%) 109 0.897
(1.00) 		0.607
(1.00) 		0.00273
(1.00) 		0.0235
(1.00) 		0.606
(1.00) 		0.85
(1.00) 		0.886
(1.00) 		0.828
(1.00) 		0.435
(1.00) 		0.818
(1.00) 		0.17
(1.00) 		0.941
(1.00)
6q 57 (35%) 105 0.286
(1.00) 		0.348
(1.00) 		0.00954
(1.00) 		0.143
(1.00) 		0.56
(1.00) 		0.743
(1.00) 		0.808
(1.00) 		0.584
(1.00) 		0.617
(1.00) 		0.816
(1.00) 		0.329
(1.00) 		0.472
(1.00)
9p 64 (40%) 98 0.179
(1.00) 		0.549
(1.00) 		0.149
(1.00) 		0.0492
(1.00) 		0.84
(1.00) 		0.395
(1.00) 		0.762
(1.00) 		0.853
(1.00) 		0.137
(1.00) 		0.129
(1.00) 		1
(1.00) 		0.159
(1.00)
9q 55 (34%) 107 0.264
(1.00) 		0.648
(1.00) 		0.337
(1.00) 		0.164
(1.00) 		0.868
(1.00) 		0.499
(1.00) 		0.954
(1.00) 		1
(1.00) 		0.208
(1.00) 		0.312
(1.00) 		1
(1.00) 		0.229
(1.00)
10p 44 (27%) 118 0.276
(1.00) 		0.0644
(1.00) 		0.185
(1.00) 		0.311
(1.00) 		0.208
(1.00) 		0.13
(1.00) 		0.164
(1.00) 		0.179
(1.00) 		0.841
(1.00) 		0.597
(1.00) 		0.8
(1.00) 		0.412
(1.00)
10q 43 (27%) 119 0.353
(1.00) 		0.58
(1.00) 		0.0549
(1.00) 		0.196
(1.00) 		0.173
(1.00) 		0.0513
(1.00) 		0.0724
(1.00) 		0.108
(1.00) 		0.612
(1.00) 		0.517
(1.00) 		0.802
(1.00) 		0.334
(1.00)
11p 54 (33%) 108 0.28
(1.00) 		0.167
(1.00) 		0.0931
(1.00) 		0.89
(1.00) 		0.459
(1.00) 		0.738
(1.00) 		0.491
(1.00) 		0.389
(1.00) 		0.22
(1.00) 		0.115
(1.00) 		0.0122
(1.00) 		0.0975
(1.00)
11q 55 (34%) 107 0.0655
(1.00) 		0.0816
(1.00) 		0.0487
(1.00) 		0.391
(1.00) 		0.252
(1.00) 		0.574
(1.00) 		0.611
(1.00) 		0.402
(1.00) 		0.161
(1.00) 		0.143
(1.00) 		0.111
(1.00) 		0.248
(1.00)
12p 55 (34%) 107 0.292
(1.00) 		0.777
(1.00) 		0.0331
(1.00) 		0.295
(1.00) 		0.222
(1.00) 		0.141
(1.00) 		0.647
(1.00) 		0.856
(1.00) 		0.83
(1.00) 		0.936
(1.00) 		0.894
(1.00) 		0.967
(1.00)
12q 43 (27%) 119 0.446
(1.00) 		0.241
(1.00) 		0.331
(1.00) 		0.57
(1.00) 		0.239
(1.00) 		0.206
(1.00) 		0.876
(1.00) 		0.581
(1.00) 		0.764
(1.00) 		0.583
(1.00) 		0.837
(1.00) 		0.678
(1.00)
14q 73 (45%) 89 0.28
(1.00) 		0.627
(1.00) 		0.00207
(0.961) 		0.574
(1.00) 		0.814
(1.00) 		0.211
(1.00) 		0.952
(1.00) 		0.694
(1.00) 		0.14
(1.00) 		0.292
(1.00) 		0.47
(1.00) 		0.798
(1.00)
15q 75 (46%) 87 0.422
(1.00) 		0.0221
(1.00) 		0.00459
(1.00) 		0.957
(1.00) 		0.158
(1.00) 		0.25
(1.00) 		0.635
(1.00) 		0.481
(1.00) 		0.612
(1.00) 		1
(1.00) 		0.9
(1.00) 		0.809
(1.00)
16p 48 (30%) 114 0.248
(1.00) 		0.54
(1.00) 		0.00798
(1.00) 		0.424
(1.00) 		0.668
(1.00) 		0.983
(1.00) 		0.486
(1.00) 		0.892
(1.00) 		0.0838
(1.00) 		0.313
(1.00) 		0.0954
(1.00) 		0.325
(1.00)
16q 53 (33%) 109 0.409
(1.00) 		0.436
(1.00) 		0.000656
(0.307) 		0.72
(1.00) 		0.74
(1.00) 		0.907
(1.00) 		0.42
(1.00) 		0.734
(1.00) 		0.147
(1.00) 		0.0934
(1.00) 		0.074
(1.00) 		0.125
(1.00)
17p 112 (69%) 50 0.0663
(1.00) 		0.128
(1.00) 		0.0141
(1.00) 		0.546
(1.00) 		0.901
(1.00) 		0.559
(1.00) 		0.362
(1.00) 		0.699
(1.00) 		0.994
(1.00) 		0.3
(1.00) 		0.802
(1.00) 		0.694
(1.00)
17q 55 (34%) 107 0.447
(1.00) 		1
(1.00) 		0.028
(1.00) 		0.182
(1.00) 		1
(1.00) 		0.88
(1.00) 		0.61
(1.00) 		0.427
(1.00) 		0.204
(1.00) 		0.698
(1.00) 		0.756
(1.00) 		0.995
(1.00)
19q 51 (31%) 111 0.14
(1.00) 		0.169
(1.00) 		0.00249
(1.00) 		0.0621
(1.00) 		0.799
(1.00) 		0.656
(1.00) 		0.964
(1.00) 		0.791
(1.00) 		0.0526
(1.00) 		0.183
(1.00) 		0.634
(1.00) 		0.241
(1.00)
20p 129 (80%) 33 0.0323
(1.00) 		0.171
(1.00) 		0.152
(1.00) 		0.282
(1.00) 		0.42
(1.00) 		0.966
(1.00) 		0.523
(1.00) 		0.0245
(1.00) 		0.0803
(1.00) 		0.362
(1.00) 		0.0579
(1.00) 		0.249
(1.00)
20q 143 (88%) 19 0.00777
(1.00) 		0.376
(1.00) 		0.00192
(0.889) 		0.138
(1.00) 		0.194
(1.00) 		0.0766
(1.00) 		0.652
(1.00) 		0.00136
(0.635) 		0.136
(1.00) 		0.143
(1.00) 		0.338
(1.00) 		0.369
(1.00)
21q 76 (47%) 86 0.422
(1.00) 		0.111
(1.00) 		0.00813
(1.00) 		0.937
(1.00) 		1
(1.00) 		0.247
(1.00) 		0.926
(1.00) 		0.771
(1.00) 		0.242
(1.00) 		0.213
(1.00) 		0.651
(1.00) 		0.274
(1.00)
22q 66 (41%) 96 0.538
(1.00) 		0.0784
(1.00) 		0.00979
(1.00) 		0.617
(1.00) 		0.519
(1.00) 		0.754
(1.00) 		0.228
(1.00) 		0.434
(1.00) 		0.014
(1.00) 		0.46
(1.00) 		0.431
(1.00) 		0.404
(1.00)
xq 57 (35%) 105 0.286
(1.00) 		0.397
(1.00) 		0.0474
(1.00) 		0.356
(1.00) 		0.782
(1.00) 		0.647
(1.00) 		0.387
(1.00) 		0.914
(1.00) 		0.997
(1.00) 		0.705
(1.00) 		0.487
(1.00) 		0.493
(1.00)
'4p' versus 'CN_CNMF'

P value = 9e-05 (Chi-square test), Q value = 0.042

Table S1.  Gene #7: '4p' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 10 34 42 30 24 22
4P MUTATED 4 15 8 17 18 5
4P WILD-TYPE 6 19 34 13 6 17

Figure S1.  Get High-res Image Gene #7: '4p' versus Molecular Subtype #3: 'CN_CNMF'

'4q' versus 'CN_CNMF'

P value = 1.49e-05 (Chi-square test), Q value = 0.0071

Table S2.  Gene #8: '4q' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 10 34 42 30 24 22
4Q MUTATED 5 17 7 18 18 5
4Q WILD-TYPE 5 17 35 12 6 17

Figure S2.  Get High-res Image Gene #8: '4q' versus Molecular Subtype #3: 'CN_CNMF'

'7p' versus 'CN_CNMF'

P value = 2.58e-05 (Chi-square test), Q value = 0.012

Table S3.  Gene #13: '7p' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 10 34 42 30 24 22
7P MUTATED 7 31 16 14 18 16
7P WILD-TYPE 3 3 26 16 6 6

Figure S3.  Get High-res Image Gene #13: '7p' versus Molecular Subtype #3: 'CN_CNMF'

'7p' versus 'MRNASEQ_CHIERARCHICAL'

P value = 7.32e-05 (Fisher's exact test), Q value = 0.035

Table S4.  Gene #13: '7p' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 7 50 31
7P MUTATED 38 1 43 17
7P WILD-TYPE 28 6 7 14

Figure S4.  Get High-res Image Gene #13: '7p' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

'7q' versus 'CN_CNMF'

P value = 0.000171 (Chi-square test), Q value = 0.08

Table S5.  Gene #14: '7q' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 10 34 42 30 24 22
7Q MUTATED 4 25 13 11 18 15
7Q WILD-TYPE 6 9 29 19 6 7

Figure S5.  Get High-res Image Gene #14: '7q' versus Molecular Subtype #3: 'CN_CNMF'

'8p' versus 'CN_CNMF'

P value = 6.17e-08 (Chi-square test), Q value = 3e-05

Table S6.  Gene #15: '8p' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 10 34 42 30 24 22
8P MUTATED 7 28 14 25 18 22
8P WILD-TYPE 3 6 28 5 6 0

Figure S6.  Get High-res Image Gene #15: '8p' versus Molecular Subtype #3: 'CN_CNMF'

'8q' versus 'CN_CNMF'

P value = 1.03e-06 (Chi-square test), Q value = 5e-04

Table S7.  Gene #16: '8q' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 10 34 42 30 24 22
8Q MUTATED 7 24 12 21 13 22
8Q WILD-TYPE 3 10 30 9 11 0

Figure S7.  Get High-res Image Gene #16: '8q' versus Molecular Subtype #3: 'CN_CNMF'

'13q' versus 'CN_CNMF'

P value = 1.81e-05 (Chi-square test), Q value = 0.0086

Table S8.  Gene #25: '13q' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 10 34 42 30 24 22
13Q MUTATED 8 28 19 20 24 19
13Q WILD-TYPE 2 6 23 10 0 3

Figure S8.  Get High-res Image Gene #25: '13q' versus Molecular Subtype #3: 'CN_CNMF'

'13q' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000172 (Fisher's exact test), Q value = 0.081

Table S9.  Gene #25: '13q' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 66 7 50 31
13Q MUTATED 46 0 41 25
13Q WILD-TYPE 20 7 9 6

Figure S9.  Get High-res Image Gene #25: '13q' versus Molecular Subtype #8: 'MRNASEQ_CHIERARCHICAL'

'18p' versus 'CN_CNMF'

P value = 0.000159 (Chi-square test), Q value = 0.075

Table S10.  Gene #32: '18p' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 10 34 42 30 24 22
18P MUTATED 10 33 25 24 20 21
18P WILD-TYPE 0 1 17 6 4 1

Figure S10.  Get High-res Image Gene #32: '18p' versus Molecular Subtype #3: 'CN_CNMF'

'18q' versus 'CN_CNMF'

P value = 3.82e-05 (Chi-square test), Q value = 0.018

Table S11.  Gene #33: '18q' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 10 34 42 30 24 22
18Q MUTATED 10 34 27 27 22 21
18Q WILD-TYPE 0 0 15 3 2 1

Figure S11.  Get High-res Image Gene #33: '18q' versus Molecular Subtype #3: 'CN_CNMF'

'19p' versus 'CN_CNMF'

P value = 4.95e-05 (Chi-square test), Q value = 0.023

Table S12.  Gene #34: '19p' versus Molecular Subtype #3: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 10 34 42 30 24 22
19P MUTATED 4 22 4 10 8 5
19P WILD-TYPE 6 12 38 20 16 17

Figure S12.  Get High-res Image Gene #34: '19p' versus Molecular Subtype #3: 'CN_CNMF'

Methods & Data
Input

  • Copy number data file = transformed.cor.cli.txt

  • Molecular subtype file = READ-TP.transferedmergedcluster.txt

  • Number of patients = 162

  • Number of significantly focal cnvs = 40

  • Number of molecular subtypes = 12

  • Exclude genes that fewer than K tumors have alterations, 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.

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)
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