Skin Cutaneous Melanoma: Correlation between copy number variations of arm-level result and molecular subtypes
(NRAS_Hotspot_Mutants cohort)
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
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 67 arm-level results and 8 molecular subtypes across 62 patients, 8 significant findings detected with Q value < 0.25.

  • 6p gain cnv correlated to 'METHLYATION_CNMF'.

  • 8p gain cnv correlated to 'MRNASEQ_CNMF'.

  • 8q gain cnv correlated to 'MRNASEQ_CNMF'.

  • 13q gain cnv correlated to 'METHLYATION_CNMF' and 'MRNASEQ_CNMF'.

  • 16p gain cnv correlated to 'MRNASEQ_CNMF'.

  • 10p loss cnv correlated to 'CN_CNMF'.

  • 10q 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 67 arm-level results and 8 molecular subtypes. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 8 significant findings detected.

Molecular
subtypes 		CN
CNMF 		METHLYATION
CNMF 		RPPA
CNMF 		RPPA
CHIERARCHICAL 		MRNASEQ
CNMF 		MRNASEQ
CHIERARCHICAL 		MIRSEQ
CNMF 		MIRSEQ
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 Fisher's exact test
13q gain 18 (29%) 44 0.0282
(1.00) 		0.000223
(0.115) 		0.716
(1.00) 		0.398
(1.00) 		0.000484
(0.246) 		0.018
(1.00) 		0.0797
(1.00) 		0.102
(1.00)
6p gain 28 (45%) 34 0.00131
(0.664) 		0.000279
(0.143) 		1
(1.00) 		0.395
(1.00) 		0.0887
(1.00) 		0.201
(1.00) 		0.0566
(1.00) 		0.0478
(1.00)
8p gain 13 (21%) 49 0.313
(1.00) 		0.0253
(1.00) 		1
(1.00) 		0.267
(1.00) 		9.88e-05
(0.0508) 		0.0606
(1.00) 		0.252
(1.00) 		1
(1.00)
8q gain 21 (34%) 41 0.0343
(1.00) 		0.00327
(1.00) 		0.301
(1.00) 		0.244
(1.00) 		5.82e-05
(0.03) 		0.0286
(1.00) 		0.626
(1.00) 		0.92
(1.00)
16p gain 7 (11%) 55 0.033
(1.00) 		0.0231
(1.00) 		1
(1.00) 		0.000386
(0.197) 		0.014
(1.00) 		0.677
(1.00) 		0.851
(1.00)
10p loss 25 (40%) 37 6.88e-06
(0.00355) 		0.00949
(1.00) 		1
(1.00) 		0.045
(1.00) 		0.0133
(1.00) 		0.129
(1.00) 		0.334
(1.00) 		0.581
(1.00)
10q loss 27 (44%) 35 0.000302
(0.154) 		0.0533
(1.00) 		1
(1.00) 		0.045
(1.00) 		0.0168
(1.00) 		0.225
(1.00) 		0.669
(1.00) 		0.425
(1.00)
1p gain 8 (13%) 54 0.429
(1.00) 		0.804
(1.00) 		0.661
(1.00) 		0.479
(1.00) 		0.17
(1.00) 		0.712
(1.00) 		0.867
(1.00) 		0.728
(1.00)
1q gain 29 (47%) 33 0.00828
(1.00) 		0.352
(1.00) 		1
(1.00) 		0.403
(1.00) 		0.11
(1.00) 		0.204
(1.00) 		0.968
(1.00) 		0.928
(1.00)
2p gain 10 (16%) 52 0.361
(1.00) 		0.57
(1.00) 		1
(1.00) 		0.0797
(1.00) 		0.112
(1.00) 		0.307
(1.00) 		0.964
(1.00) 		0.867
(1.00)
2q gain 10 (16%) 52 0.361
(1.00) 		0.57
(1.00) 		1
(1.00) 		0.0797
(1.00) 		0.112
(1.00) 		0.307
(1.00) 		0.964
(1.00) 		0.867
(1.00)
3p gain 6 (10%) 56 0.0176
(1.00) 		0.492
(1.00) 		0.106
(1.00) 		0.721
(1.00) 		0.081
(1.00) 		0.0991
(1.00) 		0.531
(1.00) 		0.408
(1.00)
3q gain 7 (11%) 55 0.114
(1.00) 		0.537
(1.00) 		0.106
(1.00) 		0.721
(1.00) 		0.134
(1.00) 		0.453
(1.00) 		0.301
(1.00) 		0.111
(1.00)
4p gain 5 (8%) 57 0.073
(1.00) 		0.093
(1.00) 		1
(1.00) 		0.532
(1.00) 		1
(1.00) 		0.625
(1.00) 		0.189
(1.00) 		0.47
(1.00)
4q gain 5 (8%) 57 0.073
(1.00) 		0.093
(1.00) 		1
(1.00) 		0.532
(1.00) 		1
(1.00) 		0.625
(1.00) 		0.189
(1.00) 		0.47
(1.00)
5p gain 3 (5%) 59 0.215
(1.00) 		0.502
(1.00) 		0.185
(1.00) 		1
(1.00) 		1
(1.00) 		0.157
(1.00)
6q gain 3 (5%) 59 0.111
(1.00) 		0.282
(1.00) 		0.487
(1.00) 		0.625
(1.00) 		0.787
(1.00) 		0.764
(1.00) 		1
(1.00)
7p gain 11 (18%) 51 0.00601
(1.00) 		0.0152
(1.00) 		0.342
(1.00) 		0.281
(1.00) 		0.121
(1.00) 		1
(1.00) 		0.0653
(1.00) 		0.224
(1.00)
7q gain 9 (15%) 53 0.00131
(0.665) 		0.255
(1.00) 		0.605
(1.00) 		0.267
(1.00) 		0.0294
(1.00) 		0.537
(1.00) 		0.549
(1.00) 		0.859
(1.00)
9q gain 4 (6%) 58 0.23
(1.00) 		0.445
(1.00) 		1
(1.00) 		0.0995
(1.00) 		0.245
(1.00) 		0.161
(1.00) 		0.909
(1.00) 		0.407
(1.00)
11p gain 5 (8%) 57 0.805
(1.00) 		0.727
(1.00) 		1
(1.00) 		0.729
(1.00) 		1
(1.00) 		0.422
(1.00) 		1
(1.00)
11q gain 5 (8%) 57 0.805
(1.00) 		0.727
(1.00) 		1
(1.00) 		0.729
(1.00) 		1
(1.00) 		0.422
(1.00) 		1
(1.00)
12p gain 4 (6%) 58 0.103
(1.00) 		1
(1.00) 		0.487
(1.00) 		0.245
(1.00) 		0.668
(1.00) 		0.137
(1.00) 		0.0925
(1.00)
14q gain 5 (8%) 57 0.171
(1.00) 		0.852
(1.00) 		1
(1.00) 		0.515
(1.00) 		0.835
(1.00) 		0.125
(1.00) 		1
(1.00)
15q gain 7 (11%) 55 0.712
(1.00) 		1
(1.00) 		1
(1.00) 		0.533
(1.00) 		0.141
(1.00) 		0.849
(1.00) 		0.712
(1.00)
16q gain 6 (10%) 56 0.0938
(1.00) 		0.0669
(1.00) 		1
(1.00) 		0.00142
(0.716) 		0.0437
(1.00) 		0.792
(1.00) 		0.668
(1.00)
17p gain 3 (5%) 59 0.215
(1.00) 		1
(1.00) 		1
(1.00) 		0.0587
(1.00) 		0.117
(1.00) 		0.084
(1.00) 		0.263
(1.00)
17q gain 9 (15%) 53 0.379
(1.00) 		0.283
(1.00) 		0.407
(1.00) 		0.556
(1.00) 		0.204
(1.00) 		0.083
(1.00) 		0.549
(1.00) 		1
(1.00)
18p gain 4 (6%) 58 0.321
(1.00) 		0.251
(1.00) 		1
(1.00) 		0.83
(1.00) 		1
(1.00) 		0.289
(1.00) 		1
(1.00)
18q gain 4 (6%) 58 0.321
(1.00) 		0.251
(1.00) 		1
(1.00) 		0.83
(1.00) 		1
(1.00) 		0.289
(1.00) 		1
(1.00)
19p gain 6 (10%) 56 0.0938
(1.00) 		0.145
(1.00) 		0.605
(1.00) 		0.749
(1.00) 		0.081
(1.00) 		0.422
(1.00) 		0.426
(1.00) 		0.322
(1.00)
19q gain 7 (11%) 55 0.579
(1.00) 		0.269
(1.00) 		0.605
(1.00) 		0.22
(1.00) 		0.0358
(1.00) 		0.2
(1.00) 		0.573
(1.00) 		0.198
(1.00)
20p gain 13 (21%) 49 0.0917
(1.00) 		0.0878
(1.00) 		1
(1.00) 		0.0546
(1.00) 		0.00261
(1.00) 		0.00697
(1.00) 		0.899
(1.00) 		0.893
(1.00)
20q gain 18 (29%) 44 0.108
(1.00) 		0.119
(1.00) 		1
(1.00) 		0.354
(1.00) 		0.104
(1.00) 		0.281
(1.00) 		0.676
(1.00) 		0.91
(1.00)
21q gain 9 (15%) 53 0.304
(1.00) 		0.601
(1.00) 		1
(1.00) 		0.0995
(1.00) 		0.0294
(1.00) 		0.0108
(1.00) 		0.741
(1.00) 		0.649
(1.00)
22q gain 11 (18%) 51 0.0066
(1.00) 		0.536
(1.00) 		0.661
(1.00) 		0.134
(1.00) 		0.121
(1.00) 		0.584
(1.00) 		0.417
(1.00) 		0.547
(1.00)
2q loss 3 (5%) 59 0.406
(1.00) 		0.282
(1.00) 		0.487
(1.00) 		0.625
(1.00) 		0.117
(1.00) 		0.226
(1.00) 		1
(1.00)
3p loss 4 (6%) 58 0.354
(1.00) 		0.829
(1.00) 		1
(1.00) 		0.473
(1.00) 		1
(1.00) 		1
(1.00) 		0.26
(1.00) 		0.407
(1.00)
3q loss 4 (6%) 58 0.904
(1.00) 		0.376
(1.00) 		1
(1.00) 		0.473
(1.00) 		1
(1.00) 		1
(1.00) 		0.676
(1.00) 		0.407
(1.00)
4p loss 9 (15%) 53 0.0497
(1.00) 		0.736
(1.00) 		0.0915
(1.00) 		0.262
(1.00) 		0.00958
(1.00) 		0.0293
(1.00) 		0.0204
(1.00) 		0.0552
(1.00)
4q loss 10 (16%) 52 0.0115
(1.00) 		1
(1.00) 		0.0436
(1.00) 		0.121
(1.00) 		0.00311
(1.00) 		0.0163
(1.00) 		0.00475
(1.00) 		0.0202
(1.00)
5p loss 14 (23%) 48 0.374
(1.00) 		0.0733
(1.00) 		1
(1.00) 		0.297
(1.00) 		0.478
(1.00) 		0.455
(1.00) 		0.247
(1.00) 		0.652
(1.00)
5q loss 15 (24%) 47 0.306
(1.00) 		0.00756
(1.00) 		1
(1.00) 		0.316
(1.00) 		0.0615
(1.00) 		0.0483
(1.00) 		0.975
(1.00) 		0.658
(1.00)
6p loss 7 (11%) 55 0.444
(1.00) 		0.0769
(1.00) 		1
(1.00) 		0.0519
(1.00) 		0.271
(1.00) 		0.329
(1.00) 		0.851
(1.00)
6q loss 28 (45%) 34 0.00306
(1.00) 		0.731
(1.00) 		0.111
(1.00) 		0.589
(1.00) 		0.111
(1.00) 		0.319
(1.00) 		0.236
(1.00) 		0.796
(1.00)
7p loss 3 (5%) 59 0.78
(1.00) 		0.282
(1.00) 		1
(1.00) 		0.625
(1.00) 		0.117
(1.00) 		0.764
(1.00) 		1
(1.00)
8p loss 11 (18%) 51 0.6
(1.00) 		0.379
(1.00) 		0.0197
(1.00) 		0.971
(1.00) 		0.714
(1.00) 		0.584
(1.00) 		0.00157
(0.791) 		0.224
(1.00)
8q loss 3 (5%) 59 0.882
(1.00) 		0.104
(1.00) 		0.231
(1.00) 		0.658
(1.00) 		0.371
(1.00) 		0.436
(1.00) 		0.084
(1.00) 		1
(1.00)
9p loss 38 (61%) 24 0.257
(1.00) 		0.118
(1.00) 		0.205
(1.00) 		0.353
(1.00) 		0.312
(1.00) 		0.752
(1.00) 		0.714
(1.00) 		0.532
(1.00)
9q loss 30 (48%) 32 0.41
(1.00) 		0.367
(1.00) 		0.748
(1.00) 		0.814
(1.00) 		0.656
(1.00) 		0.579
(1.00) 		0.513
(1.00) 		0.863
(1.00)
11p loss 19 (31%) 43 0.632
(1.00) 		0.018
(1.00) 		0.301
(1.00) 		0.273
(1.00) 		0.372
(1.00) 		0.686
(1.00) 		0.979
(1.00) 		1
(1.00)
11q loss 22 (35%) 40 0.921
(1.00) 		0.447
(1.00) 		0.741
(1.00) 		0.292
(1.00) 		0.754
(1.00) 		0.791
(1.00) 		0.949
(1.00) 		0.658
(1.00)
12p loss 8 (13%) 54 0.811
(1.00) 		0.253
(1.00) 		1
(1.00) 		0.236
(1.00) 		0.89
(1.00) 		0.89
(1.00) 		0.743
(1.00) 		1
(1.00)
12q loss 11 (18%) 51 0.484
(1.00) 		0.148
(1.00) 		0.661
(1.00) 		0.18
(1.00) 		1
(1.00) 		1
(1.00) 		0.909
(1.00) 		1
(1.00)
13q loss 6 (10%) 56 0.938
(1.00) 		0.224
(1.00) 		1
(1.00) 		0.602
(1.00) 		0.65
(1.00) 		1
(1.00) 		0.274
(1.00) 		0.829
(1.00)
14q loss 13 (21%) 49 0.00157
(0.793) 		0.202
(1.00) 		1
(1.00) 		0.653
(1.00) 		0.676
(1.00) 		0.67
(1.00) 		0.722
(1.00) 		0.103
(1.00)
15q loss 6 (10%) 56 0.0471
(1.00) 		0.0669
(1.00) 		1
(1.00) 		0.871
(1.00) 		1
(1.00) 		0.621
(1.00) 		0.322
(1.00)
16p loss 3 (5%) 59 0.215
(1.00) 		0.502
(1.00) 		0.267
(1.00) 		1
(1.00) 		0.583
(1.00) 		0.696
(1.00)
16q loss 12 (19%) 50 0.655
(1.00) 		0.567
(1.00) 		1
(1.00) 		0.26
(1.00) 		0.225
(1.00) 		1
(1.00) 		0.423
(1.00) 		0.123
(1.00)
17p loss 20 (32%) 42 0.269
(1.00) 		0.341
(1.00) 		0.301
(1.00) 		0.326
(1.00) 		0.661
(1.00) 		0.732
(1.00) 		0.705
(1.00) 		0.604
(1.00)
17q loss 4 (6%) 58 0.0754
(1.00) 		1
(1.00) 		0.487
(1.00) 		0.245
(1.00) 		0.161
(1.00) 		0.26
(1.00) 		0.407
(1.00)
18p loss 12 (19%) 50 0.125
(1.00) 		0.781
(1.00) 		1
(1.00) 		0.601
(1.00) 		0.518
(1.00) 		0.172
(1.00) 		0.609
(1.00) 		0.488
(1.00)
18q loss 11 (18%) 51 0.14
(1.00) 		0.843
(1.00) 		1
(1.00) 		0.54
(1.00) 		0.714
(1.00) 		0.323
(1.00) 		0.8
(1.00) 		0.547
(1.00)
19p loss 8 (13%) 54 0.0635
(1.00) 		1
(1.00) 		1
(1.00) 		0.866
(1.00) 		0.89
(1.00) 		1
(1.00) 		0.17
(1.00) 		0.728
(1.00)
19q loss 6 (10%) 56 0.237
(1.00) 		0.868
(1.00) 		1
(1.00) 		0.435
(1.00) 		0.0331
(1.00) 		0.422
(1.00) 		0.792
(1.00) 		1
(1.00)
21q loss 6 (10%) 56 1
(1.00) 		0.66
(1.00) 		0.605
(1.00) 		0.175
(1.00) 		0.157
(1.00) 		0.633
(1.00) 		0.589
(1.00) 		0.186
(1.00)
22q loss 8 (13%) 54 0.168
(1.00) 		0.451
(1.00) 		0.661
(1.00) 		0.717
(1.00) 		0.286
(1.00) 		0.0909
(1.00) 		0.804
(1.00) 		0.859
(1.00)
'6p gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000279 (Fisher's exact test), Q value = 0.14

Table S1.  Gene #10: '6p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 21 23
6P GAIN MUTATED 14 3 11
6P GAIN WILD-TYPE 4 18 12

Figure S1.  Get High-res Image Gene #10: '6p gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'8p gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 9.88e-05 (Fisher's exact test), Q value = 0.051

Table S2.  Gene #14: '8p gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 22 23 17
8P GAIN MUTATED 11 2 0
8P GAIN WILD-TYPE 11 21 17

Figure S2.  Get High-res Image Gene #14: '8p gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'8q gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 5.82e-05 (Fisher's exact test), Q value = 0.03

Table S3.  Gene #15: '8q gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 22 23 17
8Q GAIN MUTATED 15 5 1
8Q GAIN WILD-TYPE 7 18 16

Figure S3.  Get High-res Image Gene #15: '8q gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'13q gain mutation analysis' versus 'METHLYATION_CNMF'

P value = 0.000223 (Fisher's exact test), Q value = 0.11

Table S4.  Gene #20: '13q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 18 21 23
13Q GAIN MUTATED 12 2 4
13Q GAIN WILD-TYPE 6 19 19

Figure S4.  Get High-res Image Gene #20: '13q gain mutation analysis' versus Clinical Feature #2: 'METHLYATION_CNMF'

'13q gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 0.000484 (Fisher's exact test), Q value = 0.25

Table S5.  Gene #20: '13q gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 22 23 17
13Q GAIN MUTATED 13 2 3
13Q GAIN WILD-TYPE 9 21 14

Figure S5.  Get High-res Image Gene #20: '13q gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'16p gain mutation analysis' versus 'MRNASEQ_CNMF'

P value = 0.000386 (Fisher's exact test), Q value = 0.2

Table S6.  Gene #23: '16p gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 22 23 17
16P GAIN MUTATED 7 0 0
16P GAIN WILD-TYPE 15 23 17

Figure S6.  Get High-res Image Gene #23: '16p gain mutation analysis' versus Clinical Feature #5: 'MRNASEQ_CNMF'

'10p loss mutation analysis' versus 'CN_CNMF'

P value = 6.88e-06 (Fisher's exact test), Q value = 0.0035

Table S7.  Gene #49: '10p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 16 12 20 14
10P LOSS MUTATED 9 9 0 7
10P LOSS WILD-TYPE 7 3 20 7

Figure S7.  Get High-res Image Gene #49: '10p loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

'10q loss mutation analysis' versus 'CN_CNMF'

P value = 0.000302 (Fisher's exact test), Q value = 0.15

Table S8.  Gene #50: '10q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 16 12 20 14
10Q LOSS MUTATED 8 10 2 7
10Q LOSS WILD-TYPE 8 2 18 7

Figure S8.  Get High-res Image Gene #50: '10q loss mutation analysis' versus Clinical Feature #1: 'CN_CNMF'

Methods & Data
Input

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

  • Molecular subtypes file = SKCM-NRAS_Hotspot_Mutants.transferedmergedcluster.txt

  • Number of patients = 62

  • Number of significantly arm-level cnvs = 67

  • 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)
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