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 8 molecular subtypes across 90 patients, 15 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 5p cnv correlated to 'CN_CNMF'.

  • 5q cnv correlated to 'CN_CNMF' and 'MRNASEQ_CHIERARCHICAL'.

  • 6q cnv correlated to 'CN_CNMF'.

  • 7p cnv correlated to 'MRNASEQ_CNMF'.

  • 7q cnv correlated to 'MRNASEQ_CNMF'.

  • 9p cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

  • 9q cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

  • 10p cnv correlated to 'MRNASEQ_CHIERARCHICAL'.

  • 12q cnv correlated to 'CN_CNMF'.

  • 16p cnv correlated to 'CN_CNMF'.

  • 16q cnv correlated to 'CN_CNMF'.

  • 20p cnv correlated to 'CN_CNMF'.

  • 20q cnv correlated to 'CN_CNMF' and 'MRNASEQ_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 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by P value < 0.05 and Q value < 0.25, 15 significant findings detected.

Clinical
Features
CN
CNMF
METHLYATION
CNMF
MRNASEQ
CNMF
MRNASEQ
CHIERARCHICAL
MIRSEQ
CNMF
MIRSEQ
CHIERARCHICAL
MIRSEQ
MATURE
CNMF
MIRSEQ
MATURE
CHIERARCHICAL
nCNV (%) nWild-Type Chi-square test 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
5q 60 (67%) 30 6.48e-05
(0.0205)
0.0513
(1.00)
0.0192
(1.00)
0.000624
(0.192)
0.573
(1.00)
0.371
(1.00)
0.47
(1.00)
0.396
(1.00)
20q 52 (58%) 38 6.6e-05
(0.0209)
0.0687
(1.00)
0.000328
(0.102)
0.00734
(1.00)
0.0467
(1.00)
0.0505
(1.00)
0.00225
(0.661)
0.07
(1.00)
5p 65 (72%) 25 6.95e-05
(0.0219)
0.416
(1.00)
0.00705
(1.00)
0.0375
(1.00)
0.262
(1.00)
0.403
(1.00)
0.198
(1.00)
0.466
(1.00)
6q 38 (42%) 52 0.000608
(0.187)
0.748
(1.00)
0.134
(1.00)
0.551
(1.00)
0.136
(1.00)
0.175
(1.00)
0.21
(1.00)
0.241
(1.00)
7p 53 (59%) 37 0.00674
(1.00)
0.248
(1.00)
0.000629
(0.192)
0.00367
(1.00)
0.898
(1.00)
1
(1.00)
0.685
(1.00)
0.953
(1.00)
7q 54 (60%) 36 0.00265
(0.77)
0.411
(1.00)
7.36e-05
(0.0231)
0.000876
(0.266)
0.945
(1.00)
1
(1.00)
0.917
(1.00)
0.907
(1.00)
9p 40 (44%) 50 0.0152
(1.00)
0.0141
(1.00)
0.0124
(1.00)
0.000551
(0.17)
0.00123
(0.37)
0.103
(1.00)
0.0035
(1.00)
0.0788
(1.00)
9q 40 (44%) 50 0.0102
(1.00)
0.0164
(1.00)
0.0309
(1.00)
0.000332
(0.103)
0.00842
(1.00)
0.213
(1.00)
0.00948
(1.00)
0.108
(1.00)
10p 37 (41%) 53 0.00144
(0.429)
0.0319
(1.00)
0.0011
(0.332)
0.000362
(0.112)
0.0467
(1.00)
0.554
(1.00)
0.157
(1.00)
0.349
(1.00)
12q 68 (76%) 22 3.25e-05
(0.0103)
0.414
(1.00)
0.00998
(1.00)
0.0359
(1.00)
0.434
(1.00)
0.852
(1.00)
0.284
(1.00)
0.727
(1.00)
16p 55 (61%) 35 1.35e-05
(0.0043)
0.218
(1.00)
0.0295
(1.00)
0.0014
(0.419)
0.286
(1.00)
0.0688
(1.00)
0.139
(1.00)
0.21
(1.00)
16q 52 (58%) 38 1.91e-06
(0.000612)
0.0861
(1.00)
0.0114
(1.00)
0.00166
(0.49)
0.173
(1.00)
0.308
(1.00)
0.0764
(1.00)
0.625
(1.00)
20p 55 (61%) 35 0.000159
(0.0499)
0.232
(1.00)
0.00882
(1.00)
0.164
(1.00)
0.06
(1.00)
0.0155
(1.00)
0.00442
(1.00)
0.0702
(1.00)
1p 33 (37%) 57 0.0563
(1.00)
0.238
(1.00)
0.155
(1.00)
0.0612
(1.00)
0.7
(1.00)
0.657
(1.00)
0.891
(1.00)
0.771
(1.00)
1q 28 (31%) 62 0.38
(1.00)
0.061
(1.00)
0.459
(1.00)
0.225
(1.00)
1
(1.00)
0.614
(1.00)
1
(1.00)
0.868
(1.00)
2p 30 (33%) 60 0.0152
(1.00)
0.269
(1.00)
0.687
(1.00)
0.177
(1.00)
0.155
(1.00)
0.209
(1.00)
0.212
(1.00)
0.154
(1.00)
2q 27 (30%) 63 0.0275
(1.00)
0.0925
(1.00)
1
(1.00)
0.916
(1.00)
0.108
(1.00)
0.208
(1.00)
0.0478
(1.00)
0.18
(1.00)
3p 33 (37%) 57 0.171
(1.00)
0.806
(1.00)
0.401
(1.00)
0.504
(1.00)
1
(1.00)
0.662
(1.00)
0.843
(1.00)
0.519
(1.00)
3q 35 (39%) 55 0.0832
(1.00)
0.911
(1.00)
0.494
(1.00)
0.329
(1.00)
0.67
(1.00)
0.4
(1.00)
0.406
(1.00)
0.241
(1.00)
4p 47 (52%) 43 0.00501
(1.00)
0.349
(1.00)
0.101
(1.00)
0.0807
(1.00)
0.81
(1.00)
0.767
(1.00)
1
(1.00)
1
(1.00)
4q 44 (49%) 46 0.00727
(1.00)
0.551
(1.00)
0.287
(1.00)
0.0689
(1.00)
0.81
(1.00)
1
(1.00)
0.921
(1.00)
1
(1.00)
6p 37 (41%) 53 0.00301
(0.87)
0.461
(1.00)
0.116
(1.00)
0.563
(1.00)
0.0558
(1.00)
0.0524
(1.00)
0.0871
(1.00)
0.0957
(1.00)
8p 48 (53%) 42 0.158
(1.00)
0.92
(1.00)
0.48
(1.00)
0.377
(1.00)
0.178
(1.00)
0.917
(1.00)
0.455
(1.00)
0.643
(1.00)
8q 50 (56%) 40 0.0737
(1.00)
0.685
(1.00)
0.468
(1.00)
0.0985
(1.00)
0.283
(1.00)
0.789
(1.00)
0.127
(1.00)
0.541
(1.00)
10q 36 (40%) 54 0.00274
(0.796)
0.0614
(1.00)
0.00117
(0.351)
0.0025
(0.729)
0.0711
(1.00)
0.871
(1.00)
0.254
(1.00)
0.716
(1.00)
11p 29 (32%) 61 0.00999
(1.00)
0.0429
(1.00)
0.336
(1.00)
0.737
(1.00)
0.557
(1.00)
0.701
(1.00)
0.735
(1.00)
0.751
(1.00)
11q 29 (32%) 61 0.0016
(0.474)
0.0326
(1.00)
0.342
(1.00)
0.92
(1.00)
0.47
(1.00)
0.473
(1.00)
0.291
(1.00)
0.375
(1.00)
12p 69 (77%) 21 0.000921
(0.279)
0.124
(1.00)
0.00226
(0.661)
0.00578
(1.00)
0.491
(1.00)
0.46
(1.00)
0.329
(1.00)
0.412
(1.00)
13q 45 (50%) 45 0.0153
(1.00)
0.111
(1.00)
0.414
(1.00)
0.475
(1.00)
0.816
(1.00)
0.756
(1.00)
0.637
(1.00)
0.531
(1.00)
14q 39 (43%) 51 0.0354
(1.00)
0.72
(1.00)
0.746
(1.00)
0.382
(1.00)
0.0167
(1.00)
0.0315
(1.00)
0.0315
(1.00)
0.0447
(1.00)
15q 32 (36%) 58 0.298
(1.00)
0.247
(1.00)
1
(1.00)
0.914
(1.00)
0.209
(1.00)
0.477
(1.00)
0.31
(1.00)
0.385
(1.00)
17p 37 (41%) 53 0.000844
(0.257)
0.00616
(1.00)
0.0355
(1.00)
0.169
(1.00)
0.244
(1.00)
0.228
(1.00)
0.233
(1.00)
0.205
(1.00)
17q 31 (34%) 59 0.00581
(1.00)
0.0461
(1.00)
0.329
(1.00)
0.264
(1.00)
0.245
(1.00)
0.279
(1.00)
0.336
(1.00)
0.273
(1.00)
18p 43 (48%) 47 0.0147
(1.00)
0.297
(1.00)
0.601
(1.00)
0.933
(1.00)
0.865
(1.00)
0.474
(1.00)
1
(1.00)
0.689
(1.00)
18q 40 (44%) 50 0.0429
(1.00)
0.468
(1.00)
0.774
(1.00)
0.948
(1.00)
0.5
(1.00)
0.505
(1.00)
0.815
(1.00)
0.623
(1.00)
19p 61 (68%) 29 0.0573
(1.00)
0.123
(1.00)
0.00502
(1.00)
0.00546
(1.00)
0.238
(1.00)
0.803
(1.00)
0.23
(1.00)
0.43
(1.00)
19q 56 (62%) 34 0.0173
(1.00)
0.0627
(1.00)
0.00195
(0.575)
0.00587
(1.00)
0.178
(1.00)
0.311
(1.00)
0.125
(1.00)
0.114
(1.00)
21q 46 (51%) 44 0.458
(1.00)
0.0101
(1.00)
0.243
(1.00)
0.0835
(1.00)
0.179
(1.00)
0.414
(1.00)
0.384
(1.00)
0.601
(1.00)
22q 51 (57%) 39 0.0261
(1.00)
0.0962
(1.00)
0.734
(1.00)
0.678
(1.00)
0.842
(1.00)
0.782
(1.00)
0.674
(1.00)
0.828
(1.00)
xq 57 (63%) 33 0.0383
(1.00)
0.149
(1.00)
0.414
(1.00)
0.715
(1.00)
0.63
(1.00)
0.266
(1.00)
0.194
(1.00)
0.145
(1.00)
'5p' versus 'CN_CNMF'

P value = 6.95e-05 (Chi-square test), Q value = 0.022

Table S1.  Gene #9: '5p' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 32 24 15 10 9
5P MUTATED 16 23 14 4 8
5P WILD-TYPE 16 1 1 6 1

Figure S1.  Get High-res Image Gene #9: '5p' versus Molecular Subtype #1: 'CN_CNMF'

'5q' versus 'CN_CNMF'

P value = 6.48e-05 (Chi-square test), Q value = 0.021

Table S2.  Gene #10: '5q' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 32 24 15 10 9
5Q MUTATED 13 21 14 4 8
5Q WILD-TYPE 19 3 1 6 1

Figure S2.  Get High-res Image Gene #10: '5q' versus Molecular Subtype #1: 'CN_CNMF'

'5q' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000624 (Fisher's exact test), Q value = 0.19

Table S3.  Gene #10: '5q' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 23 32 22
5Q MUTATED 9 24 20
5Q WILD-TYPE 14 8 2

Figure S3.  Get High-res Image Gene #10: '5q' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'6q' versus 'CN_CNMF'

P value = 0.000608 (Chi-square test), Q value = 0.19

Table S4.  Gene #12: '6q' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 32 24 15 10 9
6Q MUTATED 17 3 4 7 7
6Q WILD-TYPE 15 21 11 3 2

Figure S4.  Get High-res Image Gene #12: '6q' versus Molecular Subtype #1: 'CN_CNMF'

'7p' versus 'MRNASEQ_CNMF'

P value = 0.000629 (Fisher's exact test), Q value = 0.19

Table S5.  Gene #13: '7p' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 24 13 17 23
7P MUTATED 8 12 14 12
7P WILD-TYPE 16 1 3 11

Figure S5.  Get High-res Image Gene #13: '7p' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'7q' versus 'MRNASEQ_CNMF'

P value = 7.36e-05 (Fisher's exact test), Q value = 0.023

Table S6.  Gene #14: '7q' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 24 13 17 23
7Q MUTATED 8 13 14 12
7Q WILD-TYPE 16 0 3 11

Figure S6.  Get High-res Image Gene #14: '7q' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'9p' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000551 (Fisher's exact test), Q value = 0.17

Table S7.  Gene #17: '9p' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 23 32 22
9P MUTATED 15 6 13
9P WILD-TYPE 8 26 9

Figure S7.  Get High-res Image Gene #17: '9p' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'9q' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000332 (Fisher's exact test), Q value = 0.1

Table S8.  Gene #18: '9q' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 23 32 22
9Q MUTATED 13 5 14
9Q WILD-TYPE 10 27 8

Figure S8.  Get High-res Image Gene #18: '9q' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'10p' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.000362 (Fisher's exact test), Q value = 0.11

Table S9.  Gene #19: '10p' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 23 32 22
10P MUTATED 10 6 16
10P WILD-TYPE 13 26 6

Figure S9.  Get High-res Image Gene #19: '10p' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'12q' versus 'CN_CNMF'

P value = 3.25e-05 (Chi-square test), Q value = 0.01

Table S10.  Gene #24: '12q' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 32 24 15 10 9
12Q MUTATED 18 24 15 4 7
12Q WILD-TYPE 14 0 0 6 2

Figure S10.  Get High-res Image Gene #24: '12q' versus Molecular Subtype #1: 'CN_CNMF'

'16p' versus 'CN_CNMF'

P value = 1.35e-05 (Chi-square test), Q value = 0.0043

Table S11.  Gene #28: '16p' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 32 24 15 10 9
16P MUTATED 11 24 11 4 5
16P WILD-TYPE 21 0 4 6 4

Figure S11.  Get High-res Image Gene #28: '16p' versus Molecular Subtype #1: 'CN_CNMF'

'16q' versus 'CN_CNMF'

P value = 1.91e-06 (Chi-square test), Q value = 0.00061

Table S12.  Gene #29: '16q' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 32 24 15 10 9
16Q MUTATED 9 23 12 3 5
16Q WILD-TYPE 23 1 3 7 4

Figure S12.  Get High-res Image Gene #29: '16q' versus Molecular Subtype #1: 'CN_CNMF'

'20p' versus 'CN_CNMF'

P value = 0.000159 (Chi-square test), Q value = 0.05

Table S13.  Gene #36: '20p' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 32 24 15 10 9
20P MUTATED 10 22 11 6 6
20P WILD-TYPE 22 2 4 4 3

Figure S13.  Get High-res Image Gene #36: '20p' versus Molecular Subtype #1: 'CN_CNMF'

'20q' versus 'CN_CNMF'

P value = 6.6e-05 (Chi-square test), Q value = 0.021

Table S14.  Gene #37: '20q' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5
ALL 32 24 15 10 9
20Q MUTATED 10 21 12 3 6
20Q WILD-TYPE 22 3 3 7 3

Figure S14.  Get High-res Image Gene #37: '20q' versus Molecular Subtype #1: 'CN_CNMF'

'20q' versus 'MRNASEQ_CNMF'

P value = 0.000328 (Fisher's exact test), Q value = 0.1

Table S15.  Gene #37: '20q' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 24 13 17 23
20Q MUTATED 6 11 9 18
20Q WILD-TYPE 18 2 8 5

Figure S15.  Get High-res Image Gene #37: '20q' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

Methods & Data
Input
  • Copy number data file = transformed.cor.cli.txt

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

  • Number of patients = 90

  • Number of significantly focal cnvs = 40

  • Number of molecular subtypes = 8

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

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)