Correlation between copy number variations of arm-level result and molecular subtypes
Sarcoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1FX7845
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/C1FX7845
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 80 arm-level events and 8 molecular subtypes across 150 patients, 18 significant findings detected with P value < 0.05 and Q value < 0.25.

  • 9q gain cnv correlated to 'CN_CNMF'.

  • 19p gain cnv correlated to 'CN_CNMF'.

  • 19q gain cnv correlated to 'CN_CNMF'.

  • 21q gain cnv correlated to 'CN_CNMF'.

  • 2p loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF', and 'MRNASEQ_CNMF'.

  • 3p loss cnv correlated to 'METHLYATION_CNMF'.

  • 10p loss cnv correlated to 'MRNASEQ_CNMF'.

  • 10q loss cnv correlated to 'CN_CNMF',  'METHLYATION_CNMF',  'MRNASEQ_CNMF', and 'MRNASEQ_CHIERARCHICAL'.

  • 11p loss cnv correlated to 'CN_CNMF' and 'METHLYATION_CNMF'.

  • 11q loss cnv correlated to 'CN_CNMF'.

  • 16q loss cnv correlated to 'METHLYATION_CNMF'.

  • xq loss cnv correlated to 'METHLYATION_CNMF'.

Results
Overview of the results

Table 1.  Get Full Table Overview of the association between significant copy number variation of 80 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, 18 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 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
10q loss 78 (52%) 72 2.62e-07
(0.000167) 		1.72e-07
(0.00011) 		3.03e-07
(0.000193) 		3.52e-05
(0.0223) 		0.00239
(1.00) 		0.000439
(0.272) 		0.00211
(1.00) 		0.000439
(0.272)
2p loss 47 (31%) 103 0.000307
(0.192) 		5.4e-05
(0.0341) 		0.000292
(0.182) 		0.00109
(0.665) 		0.0223
(1.00) 		0.00159
(0.957) 		0.00884
(1.00) 		0.00159
(0.957)
11p loss 56 (37%) 94 0.000216
(0.136) 		0.000222
(0.139) 		0.549
(1.00) 		0.144
(1.00) 		0.453
(1.00) 		0.313
(1.00) 		0.541
(1.00) 		0.456
(1.00)
9q gain 38 (25%) 112 0.000336
(0.21) 		0.0655
(1.00) 		0.274
(1.00) 		0.0925
(1.00) 		0.112
(1.00) 		0.135
(1.00) 		0.0429
(1.00) 		0.135
(1.00)
19p gain 50 (33%) 100 5.19e-07
(0.00033) 		0.0565
(1.00) 		0.54
(1.00) 		0.212
(1.00) 		0.397
(1.00) 		0.203
(1.00) 		0.32
(1.00) 		0.203
(1.00)
19q gain 36 (24%) 114 1.05e-05
(0.00669) 		0.00904
(1.00) 		0.432
(1.00) 		0.109
(1.00) 		0.216
(1.00) 		0.127
(1.00) 		0.131
(1.00) 		0.127
(1.00)
21q gain 39 (26%) 111 0.000246
(0.154) 		0.00542
(1.00) 		0.251
(1.00) 		0.189
(1.00) 		0.542
(1.00) 		0.43
(1.00) 		0.799
(1.00) 		0.43
(1.00)
3p loss 30 (20%) 120 0.00194
(1.00) 		3.72e-05
(0.0236) 		0.00529
(1.00) 		0.00308
(1.00) 		0.0133
(1.00) 		0.0164
(1.00) 		0.00436
(1.00) 		0.0164
(1.00)
10p loss 68 (45%) 82 0.0302
(1.00) 		0.00232
(1.00) 		0.000257
(0.161) 		0.0234
(1.00) 		0.275
(1.00) 		0.0619
(1.00) 		0.47
(1.00) 		0.0619
(1.00)
11q loss 48 (32%) 102 8.3e-06
(0.00528) 		0.00411
(1.00) 		0.632
(1.00) 		0.0648
(1.00) 		0.077
(1.00) 		0.0658
(1.00) 		0.217
(1.00) 		0.183
(1.00)
16q loss 74 (49%) 76 0.000411
(0.256) 		0.000218
(0.137) 		0.00223
(1.00) 		0.0024
(1.00) 		0.00252
(1.00) 		0.0017
(1.00) 		0.00292
(1.00) 		0.0017
(1.00)
xq loss 58 (39%) 92 0.0864
(1.00) 		4.94e-05
(0.0312) 		0.0623
(1.00) 		0.00496
(1.00) 		0.00753
(1.00) 		0.0013
(0.789) 		0.00102
(0.627) 		0.00426
(1.00)
1p gain 33 (22%) 117 0.000442
(0.273) 		0.000422
(0.262) 		0.146
(1.00) 		0.671
(1.00) 		0.391
(1.00) 		0.626
(1.00) 		0.772
(1.00) 		0.781
(1.00)
1q gain 35 (23%) 115 0.00164
(0.985) 		0.0178
(1.00) 		0.0387
(1.00) 		0.0382
(1.00) 		0.415
(1.00) 		0.206
(1.00) 		0.162
(1.00) 		0.116
(1.00)
2p gain 16 (11%) 134 0.00121
(0.734) 		0.00344
(1.00) 		0.174
(1.00) 		0.079
(1.00) 		0.00345
(1.00) 		0.0208
(1.00) 		0.00598
(1.00) 		0.0208
(1.00)
2q gain 13 (9%) 137 0.0107
(1.00) 		0.096
(1.00) 		0.484
(1.00) 		0.205
(1.00) 		0.0288
(1.00) 		0.0634
(1.00) 		0.038
(1.00) 		0.0634
(1.00)
3p gain 16 (11%) 134 0.0748
(1.00) 		0.0213
(1.00) 		0.0608
(1.00) 		0.146
(1.00) 		0.878
(1.00) 		0.677
(1.00) 		0.512
(1.00) 		0.444
(1.00)
3q gain 15 (10%) 135 0.123
(1.00) 		0.0834
(1.00) 		0.0943
(1.00) 		0.38
(1.00) 		1
(1.00) 		1
(1.00) 		0.566
(1.00) 		0.547
(1.00)
4p gain 34 (23%) 116 0.00348
(1.00) 		0.00155
(0.932) 		0.67
(1.00) 		0.858
(1.00) 		0.0285
(1.00) 		0.0807
(1.00) 		0.0381
(1.00) 		0.0182
(1.00)
4q gain 27 (18%) 123 0.199
(1.00) 		0.0744
(1.00) 		0.863
(1.00) 		1
(1.00) 		0.257
(1.00) 		0.513
(1.00) 		0.0889
(1.00) 		0.247
(1.00)
5p gain 52 (35%) 98 0.000469
(0.289) 		0.011
(1.00) 		0.0695
(1.00) 		1
(1.00) 		0.782
(1.00) 		0.52
(1.00) 		0.29
(1.00) 		0.695
(1.00)
5q gain 43 (29%) 107 0.00313
(1.00) 		0.0288
(1.00) 		0.427
(1.00) 		1
(1.00) 		0.299
(1.00) 		1
(1.00) 		0.0593
(1.00) 		0.85
(1.00)
6p gain 33 (22%) 117 0.000449
(0.277) 		0.00108
(0.657) 		0.0149
(1.00) 		0.00577
(1.00) 		0.0141
(1.00) 		0.00778
(1.00) 		0.00344
(1.00) 		0.031
(1.00)
6q gain 31 (21%) 119 0.00685
(1.00) 		0.00085
(0.521) 		0.0233
(1.00) 		0.00879
(1.00) 		0.00718
(1.00) 		0.00529
(1.00) 		0.0016
(0.96) 		0.0229
(1.00)
7p gain 46 (31%) 104 0.0022
(1.00) 		0.0298
(1.00) 		0.0727
(1.00) 		0.353
(1.00) 		0.283
(1.00) 		0.18
(1.00) 		0.0957
(1.00) 		0.267
(1.00)
7q gain 38 (25%) 112 0.00178
(1.00) 		0.125
(1.00) 		0.554
(1.00) 		0.189
(1.00) 		0.29
(1.00) 		0.135
(1.00) 		0.0878
(1.00) 		0.211
(1.00)
8p gain 34 (23%) 116 0.0103
(1.00) 		0.514
(1.00) 		0.336
(1.00) 		1
(1.00) 		1
(1.00) 		0.812
(1.00) 		0.549
(1.00) 		0.812
(1.00)
8q gain 39 (26%) 111 0.0392
(1.00) 		0.0241
(1.00) 		0.0357
(1.00) 		0.79
(1.00) 		0.974
(1.00) 		0.422
(1.00) 		0.824
(1.00) 		0.422
(1.00)
9p gain 30 (20%) 120 0.0034
(1.00) 		0.062
(1.00) 		0.23
(1.00) 		0.249
(1.00) 		0.112
(1.00) 		0.108
(1.00) 		0.163
(1.00) 		0.108
(1.00)
10p gain 13 (9%) 137 0.0612
(1.00) 		0.0146
(1.00) 		0.827
(1.00) 		0.427
(1.00) 		0.784
(1.00) 		0.689
(1.00) 		0.525
(1.00) 		0.689
(1.00)
10q gain 5 (3%) 145 0.853
(1.00) 		0.0111
(1.00) 		0.629
(1.00) 		0.113
(1.00) 		0.8
(1.00) 		1
(1.00) 		0.209
(1.00) 		1
(1.00)
11p gain 14 (9%) 136 0.11
(1.00) 		0.357
(1.00) 		0.15
(1.00) 		1
(1.00) 		0.618
(1.00) 		0.598
(1.00) 		0.288
(1.00) 		0.598
(1.00)
11q gain 13 (9%) 137 0.667
(1.00) 		0.337
(1.00) 		0.228
(1.00) 		0.616
(1.00) 		0.875
(1.00) 		1
(1.00) 		0.873
(1.00) 		1
(1.00)
12p gain 20 (13%) 130 0.502
(1.00) 		0.042
(1.00) 		0.703
(1.00) 		0.165
(1.00) 		0.405
(1.00) 		0.382
(1.00) 		0.493
(1.00) 		0.382
(1.00)
12q gain 14 (9%) 136 0.599
(1.00) 		0.358
(1.00) 		0.384
(1.00) 		0.799
(1.00) 		0.269
(1.00) 		0.263
(1.00) 		0.323
(1.00) 		0.263
(1.00)
13q gain 7 (5%) 143 0.262
(1.00) 		0.0521
(1.00) 		0.0419
(1.00) 		0.0266
(1.00) 		0.621
(1.00) 		0.16
(1.00) 		0.528
(1.00) 		0.453
(1.00)
14q gain 31 (21%) 119 0.279
(1.00) 		0.0875
(1.00) 		0.219
(1.00) 		0.543
(1.00) 		0.273
(1.00) 		0.118
(1.00) 		0.395
(1.00) 		0.118
(1.00)
15q gain 39 (26%) 111 0.0818
(1.00) 		0.00327
(1.00) 		0.000575
(0.353) 		0.0061
(1.00) 		0.335
(1.00) 		0.798
(1.00) 		0.482
(1.00) 		0.798
(1.00)
16p gain 25 (17%) 125 0.0151
(1.00) 		0.0286
(1.00) 		1
(1.00) 		1
(1.00) 		0.57
(1.00) 		1
(1.00) 		0.728
(1.00) 		1
(1.00)
16q gain 10 (7%) 140 0.138
(1.00) 		0.0757
(1.00) 		0.861
(1.00) 		0.484
(1.00) 		0.0598
(1.00) 		0.576
(1.00) 		0.0929
(1.00) 		0.576
(1.00)
17p gain 37 (25%) 113 0.014
(1.00) 		0.018
(1.00) 		0.513
(1.00) 		0.444
(1.00) 		0.0386
(1.00) 		0.00887
(1.00) 		0.0837
(1.00) 		0.00887
(1.00)
17q gain 34 (23%) 116 0.2
(1.00) 		0.0541
(1.00) 		0.173
(1.00) 		0.616
(1.00) 		0.0128
(1.00) 		0.00173
(1.00) 		0.0385
(1.00) 		0.00173
(1.00)
18p gain 26 (17%) 124 0.0175
(1.00) 		0.0146
(1.00) 		0.952
(1.00) 		0.748
(1.00) 		0.618
(1.00) 		1
(1.00) 		0.933
(1.00) 		0.674
(1.00)
18q gain 22 (15%) 128 0.393
(1.00) 		0.102
(1.00) 		0.631
(1.00) 		1
(1.00) 		0.693
(1.00) 		1
(1.00) 		0.76
(1.00) 		0.802
(1.00)
20p gain 41 (27%) 109 0.0667
(1.00) 		0.166
(1.00) 		0.732
(1.00) 		0.539
(1.00) 		0.547
(1.00) 		0.699
(1.00) 		0.287
(1.00) 		0.699
(1.00)
20q gain 52 (35%) 98 0.00567
(1.00) 		0.047
(1.00) 		1
(1.00) 		0.212
(1.00) 		0.151
(1.00) 		0.226
(1.00) 		0.145
(1.00) 		0.226
(1.00)
22q gain 37 (25%) 113 0.0778
(1.00) 		0.195
(1.00) 		0.428
(1.00) 		0.392
(1.00) 		0.851
(1.00) 		0.547
(1.00) 		0.924
(1.00) 		0.547
(1.00)
xq gain 19 (13%) 131 0.0251
(1.00) 		0.0488
(1.00) 		1
(1.00) 		1
(1.00) 		0.304
(1.00) 		0.336
(1.00) 		0.337
(1.00) 		0.484
(1.00)
1p loss 22 (15%) 128 0.919
(1.00) 		0.151
(1.00) 		0.113
(1.00) 		0.76
(1.00) 		0.68
(1.00) 		0.0219
(1.00) 		0.799
(1.00) 		0.0219
(1.00)
1q loss 20 (13%) 130 0.235
(1.00) 		0.152
(1.00) 		0.683
(1.00) 		0.818
(1.00) 		0.521
(1.00) 		0.537
(1.00) 		0.23
(1.00) 		0.537
(1.00)
2q loss 40 (27%) 110 0.00054
(0.332) 		0.0443
(1.00) 		0.709
(1.00) 		0.721
(1.00) 		0.883
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
3q loss 34 (23%) 116 0.00171
(1.00) 		0.00219
(1.00) 		0.0103
(1.00) 		0.00252
(1.00) 		0.0247
(1.00) 		0.00974
(1.00) 		0.0138
(1.00) 		0.00974
(1.00)
4p loss 25 (17%) 125 0.329
(1.00) 		0.00513
(1.00) 		0.113
(1.00) 		0.486
(1.00) 		0.227
(1.00) 		0.166
(1.00) 		0.206
(1.00) 		0.166
(1.00)
4q loss 27 (18%) 123 0.0123
(1.00) 		0.00171
(1.00) 		0.0779
(1.00) 		0.855
(1.00) 		0.563
(1.00) 		0.178
(1.00) 		0.51
(1.00) 		0.178
(1.00)
5p loss 14 (9%) 136 0.514
(1.00) 		0.438
(1.00) 		0.207
(1.00) 		0.332
(1.00) 		0.122
(1.00) 		0.043
(1.00) 		0.146
(1.00) 		0.043
(1.00)
5q loss 18 (12%) 132 0.155
(1.00) 		0.389
(1.00) 		0.102
(1.00) 		0.383
(1.00) 		0.335
(1.00) 		0.0886
(1.00) 		0.39
(1.00) 		0.0886
(1.00)
6p loss 35 (23%) 115 0.471
(1.00) 		0.6
(1.00) 		0.0799
(1.00) 		0.0516
(1.00) 		0.715
(1.00) 		0.335
(1.00) 		0.647
(1.00) 		0.335
(1.00)
6q loss 25 (17%) 125 0.195
(1.00) 		0.0467
(1.00) 		0.0411
(1.00) 		0.175
(1.00) 		0.217
(1.00) 		0.431
(1.00) 		0.236
(1.00) 		0.431
(1.00)
7p loss 23 (15%) 127 0.106
(1.00) 		0.00108
(0.66) 		0.057
(1.00) 		0.298
(1.00) 		0.631
(1.00) 		0.568
(1.00) 		0.319
(1.00) 		0.568
(1.00)
7q loss 19 (13%) 131 0.641
(1.00) 		0.229
(1.00) 		0.135
(1.00) 		0.391
(1.00) 		0.475
(1.00) 		0.558
(1.00) 		0.475
(1.00) 		0.558
(1.00)
8p loss 31 (21%) 119 0.392
(1.00) 		0.0242
(1.00) 		0.245
(1.00) 		0.357
(1.00) 		0.108
(1.00) 		0.00629
(1.00) 		0.0579
(1.00) 		0.00228
(1.00)
8q loss 21 (14%) 129 0.101
(1.00) 		0.399
(1.00) 		0.73
(1.00) 		0.78
(1.00) 		0.277
(1.00) 		0.474
(1.00) 		0.187
(1.00) 		0.269
(1.00)
9p loss 47 (31%) 103 0.00326
(1.00) 		0.0115
(1.00) 		0.876
(1.00) 		0.0984
(1.00) 		0.511
(1.00) 		0.204
(1.00) 		0.473
(1.00) 		0.3
(1.00)
9q loss 31 (21%) 119 0.0678
(1.00) 		0.018
(1.00) 		0.432
(1.00) 		0.379
(1.00) 		0.595
(1.00) 		0.547
(1.00) 		0.836
(1.00) 		0.682
(1.00)
12p loss 40 (27%) 110 0.00113
(0.684) 		0.0215
(1.00) 		0.441
(1.00) 		0.634
(1.00) 		0.693
(1.00) 		0.886
(1.00) 		0.58
(1.00) 		0.75
(1.00)
12q loss 33 (22%) 117 0.00873
(1.00) 		0.403
(1.00) 		0.943
(1.00) 		0.772
(1.00) 		0.866
(1.00) 		1
(1.00) 		0.755
(1.00) 		0.878
(1.00)
13q loss 75 (50%) 75 0.00309
(1.00) 		0.00106
(0.648) 		0.698
(1.00) 		0.125
(1.00) 		0.252
(1.00) 		0.0991
(1.00) 		0.249
(1.00) 		0.214
(1.00)
14q loss 44 (29%) 106 0.488
(1.00) 		0.00559
(1.00) 		0.00683
(1.00) 		0.367
(1.00) 		0.836
(1.00) 		0.289
(1.00) 		0.479
(1.00) 		0.455
(1.00)
15q loss 25 (17%) 125 0.395
(1.00) 		0.0451
(1.00) 		0.0199
(1.00) 		0.0668
(1.00) 		0.215
(1.00) 		0.151
(1.00) 		0.198
(1.00) 		0.0831
(1.00)
16p loss 42 (28%) 108 0.00152
(0.916) 		0.0664
(1.00) 		0.375
(1.00) 		0.353
(1.00) 		0.395
(1.00) 		0.0856
(1.00) 		0.627
(1.00) 		0.056
(1.00)
17p loss 29 (19%) 121 0.819
(1.00) 		0.111
(1.00) 		0.317
(1.00) 		0.732
(1.00) 		0.668
(1.00) 		0.352
(1.00) 		0.607
(1.00) 		0.234
(1.00)
17q loss 27 (18%) 123 0.0805
(1.00) 		0.0314
(1.00) 		0.00427
(1.00) 		0.11
(1.00) 		0.395
(1.00) 		0.506
(1.00) 		0.657
(1.00) 		0.241
(1.00)
18p loss 36 (24%) 114 0.224
(1.00) 		0.317
(1.00) 		0.268
(1.00) 		0.611
(1.00) 		0.828
(1.00) 		0.547
(1.00) 		0.775
(1.00) 		0.41
(1.00)
18q loss 38 (25%) 112 0.0999
(1.00) 		0.0424
(1.00) 		0.835
(1.00) 		0.599
(1.00) 		0.802
(1.00) 		0.471
(1.00) 		0.653
(1.00) 		0.66
(1.00)
19p loss 11 (7%) 139 0.0887
(1.00) 		0.0321
(1.00) 		0.484
(1.00) 		1
(1.00) 		0.234
(1.00) 		0.79
(1.00) 		0.244
(1.00) 		0.79
(1.00)
19q loss 22 (15%) 128 0.299
(1.00) 		0.141
(1.00) 		0.724
(1.00) 		0.543
(1.00) 		0.0671
(1.00) 		1
(1.00) 		0.078
(1.00) 		1
(1.00)
20p loss 25 (17%) 125 0.724
(1.00) 		0.0261
(1.00) 		0.234
(1.00) 		0.858
(1.00) 		0.596
(1.00) 		1
(1.00) 		0.65
(1.00) 		0.752
(1.00)
20q loss 10 (7%) 140 0.268
(1.00) 		0.0398
(1.00) 		0.275
(1.00) 		0.653
(1.00) 		0.264
(1.00) 		0.576
(1.00) 		0.296
(1.00) 		0.292
(1.00)
21q loss 26 (17%) 124 0.0326
(1.00) 		0.199
(1.00) 		0.519
(1.00) 		0.465
(1.00) 		0.177
(1.00) 		0.513
(1.00) 		0.216
(1.00) 		0.513
(1.00)
22q loss 43 (29%) 107 0.0106
(1.00) 		0.0953
(1.00) 		0.0312
(1.00) 		0.27
(1.00) 		0.422
(1.00) 		0.676
(1.00) 		0.369
(1.00) 		0.676
(1.00)
'9q gain' versus 'CN_CNMF'

P value = 0.000336 (Fisher's exact test), Q value = 0.21

Table S1.  Gene #18: '9q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 41 55 54
9Q GAIN MUTATED 8 24 6
9Q GAIN WILD-TYPE 33 31 48

Figure S1.  Get High-res Image Gene #18: '9q gain' versus Molecular Subtype #1: 'CN_CNMF'

'19p gain' versus 'CN_CNMF'

P value = 5.19e-07 (Fisher's exact test), Q value = 0.00033

Table S2.  Gene #34: '19p gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 41 55 54
19P GAIN MUTATED 14 31 5
19P GAIN WILD-TYPE 27 24 49

Figure S2.  Get High-res Image Gene #34: '19p gain' versus Molecular Subtype #1: 'CN_CNMF'

'19q gain' versus 'CN_CNMF'

P value = 1.05e-05 (Fisher's exact test), Q value = 0.0067

Table S3.  Gene #35: '19q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 41 55 54
19Q GAIN MUTATED 9 24 3
19Q GAIN WILD-TYPE 32 31 51

Figure S3.  Get High-res Image Gene #35: '19q gain' versus Molecular Subtype #1: 'CN_CNMF'

'21q gain' versus 'CN_CNMF'

P value = 0.000246 (Fisher's exact test), Q value = 0.15

Table S4.  Gene #38: '21q gain' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 41 55 54
21Q GAIN MUTATED 7 25 7
21Q GAIN WILD-TYPE 34 30 47

Figure S4.  Get High-res Image Gene #38: '21q gain' versus Molecular Subtype #1: 'CN_CNMF'

'2p loss' versus 'CN_CNMF'

P value = 0.000307 (Fisher's exact test), Q value = 0.19

Table S5.  Gene #43: '2p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 41 55 54
2P LOSS MUTATED 6 28 13
2P LOSS WILD-TYPE 35 27 41

Figure S5.  Get High-res Image Gene #43: '2p loss' versus Molecular Subtype #1: 'CN_CNMF'

'2p loss' versus 'METHLYATION_CNMF'

P value = 5.4e-05 (Chi-square test), Q value = 0.034

Table S6.  Gene #43: '2p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 30 28 15 21 18 35 3
2P LOSS MUTATED 3 9 1 8 4 22 0
2P LOSS WILD-TYPE 27 19 14 13 14 13 3

Figure S6.  Get High-res Image Gene #43: '2p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'2p loss' versus 'MRNASEQ_CNMF'

P value = 0.000292 (Fisher's exact test), Q value = 0.18

Table S7.  Gene #43: '2p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 41 30 32
2P LOSS MUTATED 8 7 20
2P LOSS WILD-TYPE 33 23 12

Figure S7.  Get High-res Image Gene #43: '2p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'3p loss' versus 'METHLYATION_CNMF'

P value = 3.72e-05 (Chi-square test), Q value = 0.024

Table S8.  Gene #45: '3p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 30 28 15 21 18 35 3
3P LOSS MUTATED 3 15 2 6 1 2 1
3P LOSS WILD-TYPE 27 13 13 15 17 33 2

Figure S8.  Get High-res Image Gene #45: '3p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'10p loss' versus 'MRNASEQ_CNMF'

P value = 0.000257 (Fisher's exact test), Q value = 0.16

Table S9.  Gene #59: '10p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 41 30 32
10P LOSS MUTATED 8 14 21
10P LOSS WILD-TYPE 33 16 11

Figure S9.  Get High-res Image Gene #59: '10p loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'10q loss' versus 'CN_CNMF'

P value = 2.62e-07 (Fisher's exact test), Q value = 0.00017

Table S10.  Gene #60: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 41 55 54
10Q LOSS MUTATED 7 39 32
10Q LOSS WILD-TYPE 34 16 22

Figure S10.  Get High-res Image Gene #60: '10q loss' versus Molecular Subtype #1: 'CN_CNMF'

'10q loss' versus 'METHLYATION_CNMF'

P value = 1.72e-07 (Chi-square test), Q value = 0.00011

Table S11.  Gene #60: '10q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 30 28 15 21 18 35 3
10Q LOSS MUTATED 4 12 5 16 9 30 2
10Q LOSS WILD-TYPE 26 16 10 5 9 5 1

Figure S11.  Get High-res Image Gene #60: '10q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'10q loss' versus 'MRNASEQ_CNMF'

P value = 3.03e-07 (Fisher's exact test), Q value = 0.00019

Table S12.  Gene #60: '10q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 41 30 32
10Q LOSS MUTATED 9 17 27
10Q LOSS WILD-TYPE 32 13 5

Figure S12.  Get High-res Image Gene #60: '10q loss' versus Molecular Subtype #3: 'MRNASEQ_CNMF'

'10q loss' versus 'MRNASEQ_CHIERARCHICAL'

P value = 3.52e-05 (Fisher's exact test), Q value = 0.022

Table S13.  Gene #60: '10q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 46 53 4
10Q LOSS MUTATED 34 19 0
10Q LOSS WILD-TYPE 12 34 4

Figure S13.  Get High-res Image Gene #60: '10q loss' versus Molecular Subtype #4: 'MRNASEQ_CHIERARCHICAL'

'11p loss' versus 'CN_CNMF'

P value = 0.000216 (Fisher's exact test), Q value = 0.14

Table S14.  Gene #61: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 41 55 54
11P LOSS MUTATED 22 25 9
11P LOSS WILD-TYPE 19 30 45

Figure S14.  Get High-res Image Gene #61: '11p loss' versus Molecular Subtype #1: 'CN_CNMF'

'11p loss' versus 'METHLYATION_CNMF'

P value = 0.000222 (Chi-square test), Q value = 0.14

Table S15.  Gene #61: '11p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 30 28 15 21 18 35 3
11P LOSS MUTATED 5 19 6 8 1 15 2
11P LOSS WILD-TYPE 25 9 9 13 17 20 1

Figure S15.  Get High-res Image Gene #61: '11p loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'11q loss' versus 'CN_CNMF'

P value = 8.3e-06 (Fisher's exact test), Q value = 0.0053

Table S16.  Gene #62: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3
ALL 41 55 54
11Q LOSS MUTATED 21 22 5
11Q LOSS WILD-TYPE 20 33 49

Figure S16.  Get High-res Image Gene #62: '11q loss' versus Molecular Subtype #1: 'CN_CNMF'

'16q loss' versus 'METHLYATION_CNMF'

P value = 0.000218 (Chi-square test), Q value = 0.14

Table S17.  Gene #69: '16q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 30 28 15 21 18 35 3
16Q LOSS MUTATED 5 14 5 12 9 27 2
16Q LOSS WILD-TYPE 25 14 10 9 9 8 1

Figure S17.  Get High-res Image Gene #69: '16q loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

'xq loss' versus 'METHLYATION_CNMF'

P value = 4.94e-05 (Chi-square test), Q value = 0.031

Table S18.  Gene #80: 'xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

nPatients CLUS_1 CLUS_2 CLUS_3 CLUS_4 CLUS_5 CLUS_6 CLUS_7
ALL 30 28 15 21 18 35 3
XQ LOSS MUTATED 1 10 5 10 10 22 0
XQ LOSS WILD-TYPE 29 18 10 11 8 13 3

Figure S18.  Get High-res Image Gene #80: 'xq loss' versus Molecular Subtype #2: 'METHLYATION_CNMF'

Methods & Data
Input

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

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

  • Number of patients = 150

  • Number of significantly arm-level cnvs = 80

  • 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

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] 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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