Correlation between copy number variations of arm-level result and molecular subtypes
Uveal Melanoma (Primary solid tumor)
17 October 2014  |  analyses__2014_10_17
Maintainer Information
Citation Information
doi:10.7908/C1XK8DH1
Maintained by TCGA GDAC Team (Broad Institute/MD Anderson Cancer Center/Harvard Medical School)
Cite as Broad Institute TCGA Genome Data Analysis Center (2014): Correlation between copy number variations of arm-level result and molecular subtypes. Broad Institute of MIT and Harvard. doi:10.7908/C1XK8DH1
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and molecular subtypes.

Summary

Testing the association between copy number variation 49 arm-level events and 8 molecular subtypes across 80 patients, 34 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 6p gain cnv correlated to 'CN_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_CNMF',  'MIRSEQ_CHIERARCHICAL', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 6q gain cnv correlated to 'MRNASEQ_CNMF',  'MIRSEQ_CNMF', and 'MIRSEQ_CHIERARCHICAL'.

  • 8q gain cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_CNMF',  'MIRSEQ_CHIERARCHICAL',  'MIRSEQ_MATURE_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 3p loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_CNMF',  'MIRSEQ_CHIERARCHICAL',  'MIRSEQ_MATURE_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 3q loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CNMF',  'MRNASEQ_CHIERARCHICAL',  'MIRSEQ_CNMF',  'MIRSEQ_CHIERARCHICAL',  'MIRSEQ_MATURE_CNMF', and 'MIRSEQ_MATURE_CHIERARCHICAL'.

  • 6q 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 49 arm-level 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, 34 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 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 Fisher's exact test
8q gain 53 (66%) 27 1e-05
(0.00392) 		1e-05
(0.00392) 		4e-05
(0.0148) 		1e-05
(0.00392) 		5e-05
(0.0183) 		1e-05
(0.00392) 		1e-05
(0.00392) 		5e-05
(0.0183)
3p loss 43 (54%) 37 1e-05
(0.00392) 		1e-05
(0.00392) 		1e-05
(0.00392) 		1e-05
(0.00392) 		1e-05
(0.00392) 		1e-05
(0.00392) 		1e-05
(0.00392) 		1e-05
(0.00392)
3q loss 43 (54%) 37 1e-05
(0.00392) 		1e-05
(0.00392) 		1e-05
(0.00392) 		1e-05
(0.00392) 		1e-05
(0.00392) 		1e-05
(0.00392) 		1e-05
(0.00392) 		1e-05
(0.00392)
6p gain 39 (49%) 41 0.00026
(0.0941) 		0.0039
(1.00) 		0.00026
(0.0941) 		0.00027
(0.0972) 		1e-05
(0.00392) 		3e-05
(0.0111) 		0.0031
(1.00) 		5e-05
(0.0183)
6q gain 16 (20%) 64 0.00579
(1.00) 		0.00251
(0.884) 		0.00037
(0.133) 		0.00088
(0.315) 		4e-05
(0.0148) 		0.00015
(0.0544) 		0.00623
(1.00) 		0.00088
(0.315)
6q loss 17 (21%) 63 7e-05
(0.0255) 		0.00327
(1.00) 		0.0508
(1.00) 		0.00502
(1.00) 		0.11
(1.00) 		0.0294
(1.00) 		0.00433
(1.00) 		0.00252
(0.885)
1q gain 8 (10%) 72 0.715
(1.00) 		0.714
(1.00) 		0.701
(1.00) 		0.803
(1.00) 		0.206
(1.00) 		0.156
(1.00) 		0.314
(1.00) 		0.826
(1.00)
2p gain 10 (12%) 70 0.315
(1.00) 		1
(1.00) 		0.0377
(1.00) 		0.116
(1.00) 		0.117
(1.00) 		0.199
(1.00) 		0.658
(1.00) 		0.00819
(1.00)
2q gain 8 (10%) 72 0.393
(1.00) 		0.715
(1.00) 		0.0549
(1.00) 		0.111
(1.00) 		0.312
(1.00) 		0.0163
(1.00) 		0.422
(1.00) 		0.00247
(0.872)
4p gain 7 (9%) 73 0.0273
(1.00) 		0.282
(1.00) 		0.151
(1.00) 		0.12
(1.00) 		0.775
(1.00) 		0.548
(1.00) 		0.365
(1.00) 		0.296
(1.00)
4q gain 4 (5%) 76 0.159
(1.00) 		0.271
(1.00) 		0.398
(1.00) 		0.344
(1.00) 		0.329
(1.00) 		0.808
(1.00) 		0.512
(1.00) 		0.302
(1.00)
5p gain 3 (4%) 77 0.161
(1.00) 		0.442
(1.00) 		0.784
(1.00) 		0.108
(1.00) 		1
(1.00) 		0.0756
(1.00) 		1
(1.00) 		0.842
(1.00)
5q gain 3 (4%) 77 0.163
(1.00) 		0.439
(1.00) 		0.782
(1.00) 		0.108
(1.00) 		1
(1.00) 		0.0762
(1.00) 		1
(1.00) 		0.838
(1.00)
7p gain 9 (11%) 71 0.163
(1.00) 		0.127
(1.00) 		1
(1.00) 		0.742
(1.00) 		0.658
(1.00) 		0.221
(1.00) 		0.895
(1.00) 		0.433
(1.00)
7q gain 8 (10%) 72 0.0556
(1.00) 		0.0303
(1.00) 		0.89
(1.00) 		0.448
(1.00) 		0.273
(1.00) 		0.359
(1.00) 		0.689
(1.00) 		0.268
(1.00)
8p gain 33 (41%) 47 0.00111
(0.395) 		0.00111
(0.395) 		0.00253
(0.885) 		0.00435
(1.00) 		0.0407
(1.00) 		0.0202
(1.00) 		0.0322
(1.00) 		0.0257
(1.00)
9p gain 6 (8%) 74 0.233
(1.00) 		0.176
(1.00) 		0.402
(1.00) 		0.638
(1.00) 		0.741
(1.00) 		0.907
(1.00) 		0.087
(1.00) 		0.937
(1.00)
9q gain 5 (6%) 75 0.51
(1.00) 		0.0378
(1.00) 		0.838
(1.00) 		0.839
(1.00) 		0.342
(1.00) 		0.974
(1.00) 		0.00797
(1.00) 		0.719
(1.00)
11p gain 9 (11%) 71 0.166
(1.00) 		0.539
(1.00) 		1
(1.00) 		0.74
(1.00) 		0.272
(1.00) 		0.245
(1.00) 		0.546
(1.00) 		0.281
(1.00)
11q gain 10 (12%) 70 0.317
(1.00) 		0.829
(1.00) 		0.909
(1.00) 		0.83
(1.00) 		0.146
(1.00) 		0.172
(1.00) 		0.544
(1.00) 		0.285
(1.00)
12p gain 3 (4%) 77 0.162
(1.00) 		0.442
(1.00) 		0.0906
(1.00) 		0.0102
(1.00) 		1
(1.00) 		0.00996
(1.00) 		1
(1.00) 		0.125
(1.00)
12q gain 3 (4%) 77 0.161
(1.00) 		0.44
(1.00) 		0.0885
(1.00) 		0.00952
(1.00) 		1
(1.00) 		0.00994
(1.00) 		1
(1.00) 		0.125
(1.00)
13q gain 6 (8%) 74 0.105
(1.00) 		1
(1.00) 		0.737
(1.00) 		0.753
(1.00) 		0.645
(1.00) 		0.105
(1.00) 		1
(1.00) 		0.0605
(1.00)
14q gain 3 (4%) 77 0.0378
(1.00) 		0.441
(1.00) 		0.589
(1.00) 		0.329
(1.00) 		1
(1.00) 		0.185
(1.00) 		1
(1.00) 		0.729
(1.00)
16p gain 4 (5%) 76 1
(1.00) 		0.439
(1.00) 		1
(1.00) 		0.438
(1.00) 		0.413
(1.00) 		0.0264
(1.00) 		0.38
(1.00) 		1
(1.00)
17p gain 8 (10%) 72 0.0809
(1.00) 		0.803
(1.00) 		0.389
(1.00) 		0.22
(1.00) 		0.392
(1.00) 		0.00993
(1.00) 		0.543
(1.00) 		0.283
(1.00)
17q gain 9 (11%) 71 0.218
(1.00) 		1
(1.00) 		0.422
(1.00) 		0.311
(1.00) 		0.271
(1.00) 		0.0179
(1.00) 		0.412
(1.00) 		0.353
(1.00)
20p gain 8 (10%) 72 0.00937
(1.00) 		0.569
(1.00) 		0.39
(1.00) 		0.219
(1.00) 		0.31
(1.00) 		0.18
(1.00) 		0.317
(1.00) 		0.695
(1.00)
20q gain 9 (11%) 71 0.00203
(0.719) 		0.539
(1.00) 		0.144
(1.00) 		0.0566
(1.00) 		0.247
(1.00) 		0.247
(1.00) 		0.414
(1.00) 		0.911
(1.00)
21q gain 14 (18%) 66 0.00309
(1.00) 		0.196
(1.00) 		0.104
(1.00) 		0.0129
(1.00) 		0.926
(1.00) 		0.165
(1.00) 		0.527
(1.00) 		0.162
(1.00)
22q gain 6 (8%) 74 0.106
(1.00) 		0.644
(1.00) 		0.153
(1.00) 		0.221
(1.00) 		0.645
(1.00) 		0.00656
(1.00) 		0.729
(1.00) 		0.059
(1.00)
xq gain 10 (12%) 70 0.39
(1.00) 		0.0934
(1.00) 		0.108
(1.00) 		0.139
(1.00) 		0.157
(1.00) 		0.0556
(1.00) 		0.367
(1.00) 		0.366
(1.00)
1p loss 19 (24%) 61 0.0044
(1.00) 		0.0523
(1.00) 		0.781
(1.00) 		0.663
(1.00) 		0.318
(1.00) 		0.00897
(1.00) 		0.461
(1.00) 		0.052
(1.00)
1q loss 3 (4%) 77 0.0383
(1.00) 		0.169
(1.00) 		0.217
(1.00) 		0.322
(1.00) 		0.42
(1.00) 		0.492
(1.00) 		0.0685
(1.00) 		0.0732
(1.00)
4q loss 3 (4%) 77 1
(1.00) 		0.791
(1.00) 		0.592
(1.00) 		0.602
(1.00) 		1
(1.00) 		0.612
(1.00) 		0.379
(1.00) 		0.622
(1.00)
5q loss 3 (4%) 77 0.45
(1.00) 		0.109
(1.00) 		0.0883
(1.00) 		0.17
(1.00) 		0.595
(1.00) 		0.185
(1.00) 		0.204
(1.00) 		0.841
(1.00)
8p loss 9 (11%) 71 0.0303
(1.00) 		0.344
(1.00) 		0.0371
(1.00) 		0.023
(1.00) 		0.199
(1.00) 		0.163
(1.00) 		0.139
(1.00) 		0.0313
(1.00)
8q loss 3 (4%) 77 0.786
(1.00) 		0.602
(1.00) 		1
(1.00) 		0.791
(1.00) 		0.795
(1.00) 		1
(1.00) 		1
(1.00) 		0.839
(1.00)
9p loss 8 (10%) 72 0.109
(1.00) 		0.0415
(1.00) 		0.344
(1.00) 		0.151
(1.00) 		0.184
(1.00) 		0.254
(1.00) 		0.151
(1.00) 		0.399
(1.00)
9q loss 7 (9%) 73 0.167
(1.00) 		0.0749
(1.00) 		0.593
(1.00) 		0.239
(1.00) 		0.0911
(1.00) 		0.401
(1.00) 		0.0867
(1.00) 		0.155
(1.00)
11p loss 3 (4%) 77 0.0373
(1.00) 		0.236
(1.00) 		0.0432
(1.00) 		0.108
(1.00) 		0.223
(1.00) 		0.249
(1.00) 		0.283
(1.00) 		0.188
(1.00)
12p loss 3 (4%) 77 0.788
(1.00) 		0.604
(1.00) 		1
(1.00) 		0.789
(1.00) 		0.792
(1.00) 		1
(1.00) 		0.769
(1.00) 		1
(1.00)
13q loss 3 (4%) 77 1
(1.00) 		0.17
(1.00) 		0.593
(1.00) 		0.603
(1.00) 		0.794
(1.00) 		0.61
(1.00) 		0.559
(1.00) 		0.626
(1.00)
15q loss 4 (5%) 76 0.155
(1.00) 		0.0492
(1.00) 		0.83
(1.00) 		0.826
(1.00) 		1
(1.00) 		0.662
(1.00) 		0.814
(1.00) 		0.565
(1.00)
16p loss 3 (4%) 77 1
(1.00) 		0.437
(1.00) 		0.591
(1.00) 		0.606
(1.00) 		0.794
(1.00) 		0.771
(1.00) 		0.561
(1.00) 		0.625
(1.00)
16q loss 16 (20%) 64 0.0212
(1.00) 		0.132
(1.00) 		0.0961
(1.00) 		0.013
(1.00) 		0.933
(1.00) 		0.00625
(1.00) 		0.358
(1.00) 		0.242
(1.00)
19p loss 3 (4%) 77 0.452
(1.00) 		0.604
(1.00) 		0.782
(1.00) 		1
(1.00) 		0.598
(1.00) 		0.00287
(0.999) 		0.561
(1.00) 		0.281
(1.00)
19q loss 3 (4%) 77 0.454
(1.00) 		0.603
(1.00) 		0.782
(1.00) 		1
(1.00) 		0.597
(1.00) 		0.00257
(0.897) 		0.56
(1.00) 		0.279
(1.00)
xq loss 12 (15%) 68 0.339
(1.00) 		0.0384
(1.00) 		0.321
(1.00) 		0.266
(1.00) 		0.392
(1.00) 		0.0489
(1.00) 		0.102
(1.00) 		0.0725
(1.00)
'6p gain' versus 'CN_CNMF'

P value = 0.00026 (Fisher's exact test), Q value = 0.094

Table S1.  Gene #8: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 22 36 22
6P GAIN MUTATED 9 26 4
6P GAIN WILD-TYPE 13 10 18

Figure S1.  Get High-res Image Gene #8: '6p gain' versus Molecular Subtype #1: 'CN_CNMF'

'6p gain' versus 'MRNASEQ_CNMF'

P value = 0.00026 (Fisher's exact test), Q value = 0.094

Table S2.  Gene #8: '6p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 15 35
6P GAIN MUTATED 8 5 26
6P GAIN WILD-TYPE 22 10 9

Figure S2.  Get High-res Image Gene #8: '6p gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'6p gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 0.00027 (Fisher's exact test), Q value = 0.097

Table S3.  Gene #8: '6p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 29 33 18
6P GAIN MUTATED 9 25 5
6P GAIN WILD-TYPE 20 8 13

Figure S3.  Get High-res Image Gene #8: '6p gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'6p gain' versus 'MIRSEQ_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S4.  Gene #8: '6p gain' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 34 16 29
6P GAIN MUTATED 10 4 24
6P GAIN WILD-TYPE 24 12 5

Figure S4.  Get High-res Image Gene #8: '6p gain' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'6p gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 3e-05 (Fisher's exact test), Q value = 0.011

Table S5.  Gene #8: '6p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 8 12 18 24 10 7
6P GAIN MUTATED 2 5 16 5 8 2
6P GAIN WILD-TYPE 6 7 2 19 2 5

Figure S5.  Get High-res Image Gene #8: '6p gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'6p gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 5e-05 (Fisher's exact test), Q value = 0.018

Table S6.  Gene #8: '6p gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 20 11 32 10
6P GAIN MUTATED 2 4 23 6
6P GAIN WILD-TYPE 18 7 9 4

Figure S6.  Get High-res Image Gene #8: '6p gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'6q gain' versus 'MRNASEQ_CNMF'

P value = 0.00037 (Fisher's exact test), Q value = 0.13

Table S7.  Gene #9: '6q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 15 35
6Q GAIN MUTATED 1 1 14
6Q GAIN WILD-TYPE 29 14 21

Figure S7.  Get High-res Image Gene #9: '6q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'6q gain' versus 'MIRSEQ_CNMF'

P value = 4e-05 (Fisher's exact test), Q value = 0.015

Table S8.  Gene #9: '6q gain' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 34 16 29
6Q GAIN MUTATED 1 1 13
6Q GAIN WILD-TYPE 33 15 16

Figure S8.  Get High-res Image Gene #9: '6q gain' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'6q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 0.00015 (Fisher's exact test), Q value = 0.054

Table S9.  Gene #9: '6q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 8 12 18 24 10 7
6Q GAIN MUTATED 0 2 10 0 2 1
6Q GAIN WILD-TYPE 8 10 8 24 8 6

Figure S9.  Get High-res Image Gene #9: '6q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'8q gain' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S10.  Gene #13: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 22 36 22
8Q GAIN MUTATED 21 12 20
8Q GAIN WILD-TYPE 1 24 2

Figure S10.  Get High-res Image Gene #13: '8q gain' versus Molecular Subtype #1: 'CN_CNMF'

'8q gain' versus 'METHLYATION_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S11.  Gene #13: '8q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 33 18 29
8Q GAIN MUTATED 31 12 10
8Q GAIN WILD-TYPE 2 6 19

Figure S11.  Get High-res Image Gene #13: '8q gain' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'8q gain' versus 'MRNASEQ_CNMF'

P value = 4e-05 (Fisher's exact test), Q value = 0.015

Table S12.  Gene #13: '8q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 15 35
8Q GAIN MUTATED 27 12 14
8Q GAIN WILD-TYPE 3 3 21

Figure S12.  Get High-res Image Gene #13: '8q gain' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'8q gain' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S13.  Gene #13: '8q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 29 33 18
8Q GAIN MUTATED 27 12 14
8Q GAIN WILD-TYPE 2 21 4

Figure S13.  Get High-res Image Gene #13: '8q gain' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'8q gain' versus 'MIRSEQ_CNMF'

P value = 5e-05 (Fisher's exact test), Q value = 0.018

Table S14.  Gene #13: '8q gain' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 34 16 29
8Q GAIN MUTATED 31 8 13
8Q GAIN WILD-TYPE 3 8 16

Figure S14.  Get High-res Image Gene #13: '8q gain' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'8q gain' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S15.  Gene #13: '8q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 8 12 18 24 10 7
8Q GAIN MUTATED 8 2 10 22 4 6
8Q GAIN WILD-TYPE 0 10 8 2 6 1

Figure S15.  Get High-res Image Gene #13: '8q gain' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'8q gain' versus 'MIRSEQ_MATURE_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S16.  Gene #13: '8q gain' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 32 29 12
8Q GAIN MUTATED 30 10 10
8Q GAIN WILD-TYPE 2 19 2

Figure S16.  Get High-res Image Gene #13: '8q gain' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'8q gain' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 5e-05 (Fisher's exact test), Q value = 0.018

Table S17.  Gene #13: '8q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 20 11 32 10
8Q GAIN MUTATED 18 9 13 10
8Q GAIN WILD-TYPE 2 2 19 0

Figure S17.  Get High-res Image Gene #13: '8q gain' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'3p loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S18.  Gene #32: '3p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 22 36 22
3P LOSS MUTATED 22 2 19
3P LOSS WILD-TYPE 0 34 3

Figure S18.  Get High-res Image Gene #32: '3p loss' versus Molecular Subtype #1: 'CN_CNMF'

'3p loss' versus 'METHLYATION_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S19.  Gene #32: '3p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 33 18 29
3P LOSS MUTATED 33 9 1
3P LOSS WILD-TYPE 0 9 28

Figure S19.  Get High-res Image Gene #32: '3p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'3p loss' versus 'MRNASEQ_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S20.  Gene #32: '3p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 15 35
3P LOSS MUTATED 30 10 3
3P LOSS WILD-TYPE 0 5 32

Figure S20.  Get High-res Image Gene #32: '3p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'3p loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S21.  Gene #32: '3p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 29 33 18
3P LOSS MUTATED 29 2 12
3P LOSS WILD-TYPE 0 31 6

Figure S21.  Get High-res Image Gene #32: '3p loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'3p loss' versus 'MIRSEQ_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S22.  Gene #32: '3p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 34 16 29
3P LOSS MUTATED 30 11 2
3P LOSS WILD-TYPE 4 5 27

Figure S22.  Get High-res Image Gene #32: '3p loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'3p loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S23.  Gene #32: '3p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 8 12 18 24 10 7
3P LOSS MUTATED 8 1 1 24 2 7
3P LOSS WILD-TYPE 0 11 17 0 8 0

Figure S23.  Get High-res Image Gene #32: '3p loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'3p loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S24.  Gene #32: '3p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 32 29 12
3P LOSS MUTATED 30 4 8
3P LOSS WILD-TYPE 2 25 4

Figure S24.  Get High-res Image Gene #32: '3p loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'3p loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S25.  Gene #32: '3p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 20 11 32 10
3P LOSS MUTATED 20 7 5 10
3P LOSS WILD-TYPE 0 4 27 0

Figure S25.  Get High-res Image Gene #32: '3p loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'3q loss' versus 'CN_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S26.  Gene #33: '3q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 22 36 22
3Q LOSS MUTATED 22 2 19
3Q LOSS WILD-TYPE 0 34 3

Figure S26.  Get High-res Image Gene #33: '3q loss' versus Molecular Subtype #1: 'CN_CNMF'

'3q loss' versus 'METHLYATION_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S27.  Gene #33: '3q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 33 18 29
3Q LOSS MUTATED 33 9 1
3Q LOSS WILD-TYPE 0 9 28

Figure S27.  Get High-res Image Gene #33: '3q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'3q loss' versus 'MRNASEQ_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S28.  Gene #33: '3q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 30 15 35
3Q LOSS MUTATED 30 10 3
3Q LOSS WILD-TYPE 0 5 32

Figure S28.  Get High-res Image Gene #33: '3q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'3q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S29.  Gene #33: '3q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 29 33 18
3Q LOSS MUTATED 29 2 12
3Q LOSS WILD-TYPE 0 31 6

Figure S29.  Get High-res Image Gene #33: '3q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'3q loss' versus 'MIRSEQ_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S30.  Gene #33: '3q loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 34 16 29
3Q LOSS MUTATED 30 11 2
3Q LOSS WILD-TYPE 4 5 27

Figure S30.  Get High-res Image Gene #33: '3q loss' versus Molecular Subtype #5: 'MIRSEQ_CNMF'

'3q loss' versus 'MIRSEQ_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S31.  Gene #33: '3q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6
ALL 8 12 18 24 10 7
3Q LOSS MUTATED 8 1 1 24 2 7
3Q LOSS WILD-TYPE 0 11 17 0 8 0

Figure S31.  Get High-res Image Gene #33: '3q loss' versus Molecular Subtype #6: 'MIRSEQ_CHIERARCHICAL'

'3q loss' versus 'MIRSEQ_MATURE_CNMF'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S32.  Gene #33: '3q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 32 29 12
3Q LOSS MUTATED 30 4 8
3Q LOSS WILD-TYPE 2 25 4

Figure S32.  Get High-res Image Gene #33: '3q loss' versus Molecular Subtype #7: 'MIRSEQ_MATURE_CNMF'

'3q loss' versus 'MIRSEQ_MATURE_CHIERARCHICAL'

P value = 1e-05 (Fisher's exact test), Q value = 0.0039

Table S33.  Gene #33: '3q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4
ALL 20 11 32 10
3Q LOSS MUTATED 20 7 5 10
3Q LOSS WILD-TYPE 0 4 27 0

Figure S33.  Get High-res Image Gene #33: '3q loss' versus Molecular Subtype #8: 'MIRSEQ_MATURE_CHIERARCHICAL'

'6q loss' versus 'CN_CNMF'

P value = 7e-05 (Fisher's exact test), Q value = 0.025

Table S34.  Gene #36: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 22 36 22
6Q LOSS MUTATED 12 4 1
6Q LOSS WILD-TYPE 10 32 21

Figure S34.  Get High-res Image Gene #36: '6q loss' versus Molecular Subtype #1: 'CN_CNMF'

Methods & Data
Input

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

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

  • Number of patients = 80

  • Number of significantly arm-level cnvs = 49

  • 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

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

In addition to the links below, the full results of the analysis summarized in this report can also be downloaded programmatically using firehose_get, or interactively from either the Broad GDAC website or TCGA Data Coordination Center Portal.

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] 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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