Correlation between copy number variations of arm-level result and selected clinical features
Liver Hepatocellular Carcinoma (Primary solid tumor)
15 January 2014  |  analyses__2014_01_15
Maintainer Information
Citation Information
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 selected clinical features. Broad Institute of MIT and Harvard. doi:10.7908/C14X5674
Overview
Introduction

This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.

Summary

Testing the association between copy number variation 80 arm-level events and 8 clinical features across 123 patients, no significant finding detected with Q value < 0.25.

  • No arm-level cnvs related to clinical features.

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 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, no significant finding detected.

Clinical
Features
Time
to
Death
AGE NEOPLASM
DISEASESTAGE
PATHOLOGY
T
STAGE
PATHOLOGY
N
STAGE
PATHOLOGY
M
STAGE
GENDER COMPLETENESS
OF
RESECTION
nCNV (%) nWild-Type logrank test t-test Chi-square test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test Fisher's exact test
1p gain 17 (14%) 106 0.406
(1.00)
0.682
(1.00)
0.719
(1.00)
0.0695
(1.00)
1
(1.00)
0.23
(1.00)
0.282
(1.00)
0.249
(1.00)
1q gain 70 (57%) 53 0.0459
(1.00)
0.634
(1.00)
0.0423
(1.00)
0.0617
(1.00)
0.0846
(1.00)
0.629
(1.00)
0.262
(1.00)
0.885
(1.00)
2p gain 17 (14%) 106 0.889
(1.00)
0.445
(1.00)
0.0473
(1.00)
0.347
(1.00)
0.0449
(1.00)
0.283
(1.00)
0.0612
(1.00)
0.094
(1.00)
2q gain 15 (12%) 108 0.776
(1.00)
0.552
(1.00)
0.206
(1.00)
0.922
(1.00)
0.323
(1.00)
0.293
(1.00)
0.0849
(1.00)
0.249
(1.00)
3p gain 11 (9%) 112 0.288
(1.00)
0.486
(1.00)
0.975
(1.00)
0.81
(1.00)
0.172
(1.00)
1
(1.00)
0.534
(1.00)
0.561
(1.00)
3q gain 12 (10%) 111 0.149
(1.00)
0.42
(1.00)
0.975
(1.00)
0.961
(1.00)
0.172
(1.00)
0.765
(1.00)
1
(1.00)
0.706
(1.00)
4p gain 8 (7%) 115 0.364
(1.00)
0.341
(1.00)
0.999
(1.00)
0.934
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.4
(1.00)
4q gain 4 (3%) 119 0.877
(1.00)
0.315
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.607
(1.00)
1
(1.00)
0.142
(1.00)
5p gain 49 (40%) 74 0.952
(1.00)
0.422
(1.00)
0.319
(1.00)
0.0911
(1.00)
0.281
(1.00)
0.411
(1.00)
1
(1.00)
1
(1.00)
5q gain 37 (30%) 86 0.822
(1.00)
0.433
(1.00)
0.514
(1.00)
0.365
(1.00)
0.553
(1.00)
0.909
(1.00)
0.544
(1.00)
0.715
(1.00)
6p gain 27 (22%) 96 0.262
(1.00)
0.754
(1.00)
0.2
(1.00)
0.927
(1.00)
1
(1.00)
0.0731
(1.00)
0.66
(1.00)
0.355
(1.00)
6q gain 17 (14%) 106 0.289
(1.00)
0.0771
(1.00)
0.0579
(1.00)
0.813
(1.00)
1
(1.00)
0.0155
(1.00)
0.282
(1.00)
0.0847
(1.00)
7p gain 39 (32%) 84 0.819
(1.00)
0.0605
(1.00)
0.646
(1.00)
0.667
(1.00)
0.199
(1.00)
0.829
(1.00)
0.689
(1.00)
0.615
(1.00)
7q gain 40 (33%) 83 0.999
(1.00)
0.271
(1.00)
0.352
(1.00)
0.442
(1.00)
0.214
(1.00)
0.528
(1.00)
1
(1.00)
0.895
(1.00)
8p gain 27 (22%) 96 0.767
(1.00)
0.104
(1.00)
0.357
(1.00)
0.3
(1.00)
0.568
(1.00)
0.205
(1.00)
0.378
(1.00)
0.271
(1.00)
8q gain 65 (53%) 58 0.696
(1.00)
0.607
(1.00)
0.194
(1.00)
0.345
(1.00)
0.616
(1.00)
0.911
(1.00)
0.0621
(1.00)
0.717
(1.00)
9p gain 6 (5%) 117 0.416
(1.00)
0.66
(1.00)
0.367
(1.00)
0.218
(1.00)
1
(1.00)
1
(1.00)
0.67
(1.00)
0.443
(1.00)
9q gain 6 (5%) 117 0.0815
(1.00)
0.827
(1.00)
0.948
(1.00)
0.748
(1.00)
1
(1.00)
1
(1.00)
0.195
(1.00)
0.443
(1.00)
10p gain 18 (15%) 105 0.835
(1.00)
0.0461
(1.00)
0.193
(1.00)
0.25
(1.00)
1
(1.00)
0.295
(1.00)
0.796
(1.00)
1
(1.00)
10q gain 10 (8%) 113 0.648
(1.00)
0.222
(1.00)
0.142
(1.00)
0.563
(1.00)
1
(1.00)
0.183
(1.00)
1
(1.00)
0.822
(1.00)
11p gain 7 (6%) 116 0.89
(1.00)
0.638
(1.00)
0.0375
(1.00)
0.853
(1.00)
1
(1.00)
0.069
(1.00)
0.255
(1.00)
0.0606
(1.00)
11q gain 8 (7%) 115 0.593
(1.00)
0.933
(1.00)
0.0304
(1.00)
0.32
(1.00)
1
(1.00)
0.0539
(1.00)
0.256
(1.00)
0.0824
(1.00)
12p gain 9 (7%) 114 0.205
(1.00)
0.309
(1.00)
0.81
(1.00)
0.719
(1.00)
1
(1.00)
0.728
(1.00)
0.292
(1.00)
0.562
(1.00)
12q gain 13 (11%) 110 0.749
(1.00)
0.2
(1.00)
0.147
(1.00)
0.437
(1.00)
0.323
(1.00)
0.44
(1.00)
0.0164
(1.00)
0.706
(1.00)
13q gain 7 (6%) 116 0.302
(1.00)
0.905
(1.00)
0.502
(1.00)
0.853
(1.00)
0.172
(1.00)
1
(1.00)
0.423
(1.00)
0.443
(1.00)
14q gain 8 (7%) 115 0.906
(1.00)
0.634
(1.00)
0.0783
(1.00)
0.934
(1.00)
1
(1.00)
0.175
(1.00)
1
(1.00)
0.0824
(1.00)
15q gain 11 (9%) 112 0.396
(1.00)
0.933
(1.00)
0.847
(1.00)
0.27
(1.00)
1
(1.00)
0.748
(1.00)
0.534
(1.00)
1
(1.00)
16p gain 10 (8%) 113 0.886
(1.00)
0.36
(1.00)
0.266
(1.00)
0.362
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
16q gain 4 (3%) 119 0.609
(1.00)
0.23
(1.00)
0.844
(1.00)
0.246
(1.00)
1
(1.00)
1
(1.00)
0.629
(1.00)
1
(1.00)
17p gain 12 (10%) 111 0.34
(1.00)
0.42
(1.00)
0.0776
(1.00)
0.504
(1.00)
1
(1.00)
0.765
(1.00)
1
(1.00)
0.48
(1.00)
17q gain 34 (28%) 89 0.246
(1.00)
0.533
(1.00)
0.304
(1.00)
0.162
(1.00)
1
(1.00)
0.0643
(1.00)
0.536
(1.00)
0.119
(1.00)
18p gain 10 (8%) 113 0.388
(1.00)
0.187
(1.00)
0.0424
(1.00)
0.211
(1.00)
1
(1.00)
0.135
(1.00)
0.742
(1.00)
0.0525
(1.00)
18q gain 9 (7%) 114 0.388
(1.00)
0.368
(1.00)
0.0533
(1.00)
0.309
(1.00)
1
(1.00)
0.157
(1.00)
1
(1.00)
0.0431
(1.00)
19p gain 27 (22%) 96 0.404
(1.00)
0.949
(1.00)
0.0421
(1.00)
0.294
(1.00)
0.547
(1.00)
0.0731
(1.00)
0.114
(1.00)
0.257
(1.00)
19q gain 29 (24%) 94 0.41
(1.00)
0.637
(1.00)
0.0583
(1.00)
0.464
(1.00)
0.547
(1.00)
0.0742
(1.00)
0.0813
(1.00)
0.266
(1.00)
20p gain 36 (29%) 87 0.234
(1.00)
0.999
(1.00)
0.671
(1.00)
0.967
(1.00)
1
(1.00)
0.111
(1.00)
0.313
(1.00)
0.445
(1.00)
20q gain 38 (31%) 85 0.294
(1.00)
0.998
(1.00)
0.726
(1.00)
0.92
(1.00)
1
(1.00)
0.106
(1.00)
0.546
(1.00)
0.305
(1.00)
21q gain 11 (9%) 112 0.35
(1.00)
0.773
(1.00)
0.61
(1.00)
0.622
(1.00)
1
(1.00)
1
(1.00)
0.327
(1.00)
0.234
(1.00)
22q gain 15 (12%) 108 0.837
(1.00)
0.782
(1.00)
0.892
(1.00)
0.828
(1.00)
0.351
(1.00)
1
(1.00)
1
(1.00)
0.198
(1.00)
xq gain 21 (17%) 102 0.516
(1.00)
0.0527
(1.00)
0.797
(1.00)
0.6
(1.00)
1
(1.00)
0.571
(1.00)
0.461
(1.00)
0.729
(1.00)
1p loss 34 (28%) 89 0.777
(1.00)
0.952
(1.00)
0.24
(1.00)
0.728
(1.00)
0.17
(1.00)
0.0757
(1.00)
1
(1.00)
0.414
(1.00)
1q loss 11 (9%) 112 0.638
(1.00)
0.14
(1.00)
0.111
(1.00)
0.956
(1.00)
0.0178
(1.00)
0.748
(1.00)
0.534
(1.00)
0.234
(1.00)
2p loss 10 (8%) 113 0.128
(1.00)
0.796
(1.00)
0.901
(1.00)
0.264
(1.00)
1
(1.00)
1
(1.00)
0.742
(1.00)
0.52
(1.00)
2q loss 10 (8%) 113 0.86
(1.00)
0.982
(1.00)
0.982
(1.00)
0.563
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
0.246
(1.00)
3p loss 16 (13%) 107 0.0846
(1.00)
0.972
(1.00)
0.0926
(1.00)
0.0439
(1.00)
0.378
(1.00)
0.256
(1.00)
0.28
(1.00)
0.607
(1.00)
3q loss 8 (7%) 115 0.0337
(1.00)
0.195
(1.00)
0.784
(1.00)
0.417
(1.00)
0.204
(1.00)
1
(1.00)
0.471
(1.00)
1
(1.00)
4p loss 30 (24%) 93 0.656
(1.00)
0.575
(1.00)
0.0982
(1.00)
0.733
(1.00)
0.105
(1.00)
0.09
(1.00)
0.668
(1.00)
0.391
(1.00)
4q loss 40 (33%) 83 0.6
(1.00)
0.519
(1.00)
0.375
(1.00)
0.672
(1.00)
0.199
(1.00)
0.168
(1.00)
0.551
(1.00)
0.282
(1.00)
5p loss 9 (7%) 114 0.407
(1.00)
0.888
(1.00)
0.331
(1.00)
0.757
(1.00)
0.204
(1.00)
1
(1.00)
0.481
(1.00)
0.462
(1.00)
5q loss 13 (11%) 110 0.154
(1.00)
0.687
(1.00)
0.575
(1.00)
0.339
(1.00)
0.235
(1.00)
0.785
(1.00)
1
(1.00)
0.445
(1.00)
6p loss 17 (14%) 106 0.799
(1.00)
0.989
(1.00)
0.958
(1.00)
0.777
(1.00)
0.455
(1.00)
0.0441
(1.00)
0.424
(1.00)
1
(1.00)
6q loss 37 (30%) 86 0.686
(1.00)
0.0867
(1.00)
0.496
(1.00)
0.909
(1.00)
0.214
(1.00)
0.34
(1.00)
0.106
(1.00)
0.942
(1.00)
7p loss 8 (7%) 115 0.426
(1.00)
0.639
(1.00)
0.864
(1.00)
0.395
(1.00)
1
(1.00)
0.711
(1.00)
0.0513
(1.00)
0.562
(1.00)
7q loss 10 (8%) 113 0.34
(1.00)
0.553
(1.00)
0.906
(1.00)
0.42
(1.00)
1
(1.00)
0.735
(1.00)
0.0391
(1.00)
0.301
(1.00)
8p loss 57 (46%) 66 0.155
(1.00)
0.00123
(0.787)
0.0757
(1.00)
0.175
(1.00)
0.054
(1.00)
0.242
(1.00)
0.853
(1.00)
0.712
(1.00)
8q loss 12 (10%) 111 0.414
(1.00)
0.128
(1.00)
0.0188
(1.00)
0.00707
(1.00)
0.204
(1.00)
0.288
(1.00)
0.129
(1.00)
0.852
(1.00)
9p loss 40 (33%) 83 0.0787
(1.00)
0.842
(1.00)
0.132
(1.00)
0.347
(1.00)
0.23
(1.00)
0.131
(1.00)
0.32
(1.00)
0.119
(1.00)
9q loss 42 (34%) 81 0.0171
(1.00)
0.778
(1.00)
0.079
(1.00)
0.542
(1.00)
0.0283
(1.00)
0.0667
(1.00)
0.559
(1.00)
0.0984
(1.00)
10p loss 15 (12%) 108 0.926
(1.00)
0.0217
(1.00)
0.14
(1.00)
0.458
(1.00)
0.294
(1.00)
1
(1.00)
0.0476
(1.00)
0.758
(1.00)
10q loss 27 (22%) 96 0.117
(1.00)
0.53
(1.00)
0.295
(1.00)
0.211
(1.00)
0.455
(1.00)
0.874
(1.00)
0.184
(1.00)
0.227
(1.00)
11p loss 22 (18%) 101 0.919
(1.00)
0.0227
(1.00)
0.453
(1.00)
0.655
(1.00)
0.0534
(1.00)
0.849
(1.00)
1
(1.00)
0.68
(1.00)
11q loss 24 (20%) 99 0.995
(1.00)
0.0609
(1.00)
0.424
(1.00)
0.481
(1.00)
0.0723
(1.00)
0.727
(1.00)
0.815
(1.00)
0.313
(1.00)
12p loss 23 (19%) 100 0.234
(1.00)
0.413
(1.00)
0.369
(1.00)
0.836
(1.00)
0.0827
(1.00)
0.308
(1.00)
1
(1.00)
0.153
(1.00)
12q loss 15 (12%) 108 0.523
(1.00)
0.194
(1.00)
0.187
(1.00)
1
(1.00)
1
(1.00)
0.235
(1.00)
0.785
(1.00)
0.111
(1.00)
13q loss 43 (35%) 80 0.756
(1.00)
0.153
(1.00)
0.25
(1.00)
0.00701
(1.00)
1
(1.00)
0.547
(1.00)
1
(1.00)
0.153
(1.00)
14q loss 40 (33%) 83 0.707
(1.00)
0.579
(1.00)
0.132
(1.00)
0.0556
(1.00)
1
(1.00)
0.469
(1.00)
0.551
(1.00)
0.176
(1.00)
15q loss 25 (20%) 98 0.533
(1.00)
0.527
(1.00)
0.531
(1.00)
0.306
(1.00)
0.0936
(1.00)
0.154
(1.00)
0.357
(1.00)
0.921
(1.00)
16p loss 38 (31%) 85 0.0486
(1.00)
0.259
(1.00)
0.0942
(1.00)
0.21
(1.00)
0.246
(1.00)
0.157
(1.00)
0.841
(1.00)
0.104
(1.00)
16q loss 47 (38%) 76 0.17
(1.00)
0.162
(1.00)
0.2
(1.00)
0.196
(1.00)
0.565
(1.00)
0.235
(1.00)
0.702
(1.00)
0.0688
(1.00)
17p loss 60 (49%) 63 0.293
(1.00)
0.331
(1.00)
0.0753
(1.00)
0.295
(1.00)
0.242
(1.00)
0.306
(1.00)
0.71
(1.00)
0.0692
(1.00)
17q loss 14 (11%) 109 0.771
(1.00)
0.0519
(1.00)
0.15
(1.00)
0.886
(1.00)
0.0178
(1.00)
0.79
(1.00)
0.771
(1.00)
0.858
(1.00)
18p loss 20 (16%) 103 0.142
(1.00)
0.392
(1.00)
0.825
(1.00)
0.538
(1.00)
0.351
(1.00)
0.834
(1.00)
0.805
(1.00)
1
(1.00)
18q loss 22 (18%) 101 0.308
(1.00)
0.385
(1.00)
0.476
(1.00)
0.912
(1.00)
0.378
(1.00)
0.303
(1.00)
0.468
(1.00)
0.908
(1.00)
19p loss 15 (12%) 108 0.0249
(1.00)
0.824
(1.00)
0.959
(1.00)
0.658
(1.00)
0.294
(1.00)
0.795
(1.00)
0.409
(1.00)
0.0995
(1.00)
19q loss 11 (9%) 112 0.113
(1.00)
0.731
(1.00)
0.969
(1.00)
0.956
(1.00)
0.235
(1.00)
0.55
(1.00)
0.534
(1.00)
0.197
(1.00)
20p loss 8 (7%) 115 0.899
(1.00)
0.408
(1.00)
0.536
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
1
(1.00)
20q loss 5 (4%) 118 0.488
(1.00)
0.71
(1.00)
0.142
(1.00)
0.784
(1.00)
1
(1.00)
0.616
(1.00)
1
(1.00)
1
(1.00)
21q loss 33 (27%) 90 0.0135
(1.00)
0.616
(1.00)
0.198
(1.00)
0.695
(1.00)
0.143
(1.00)
0.11
(1.00)
0.0347
(1.00)
0.343
(1.00)
22q loss 25 (20%) 98 0.281
(1.00)
0.904
(1.00)
0.856
(1.00)
0.296
(1.00)
1
(1.00)
0.544
(1.00)
0.491
(1.00)
0.0659
(1.00)
xq loss 15 (12%) 108 0.593
(1.00)
0.244
(1.00)
0.944
(1.00)
0.458
(1.00)
0.294
(1.00)
0.795
(1.00)
0.409
(1.00)
0.505
(1.00)
Methods & Data
Input
  • Copy number data file = transformed.cor.cli.txt

  • Clinical data file = LIHC-TP.merged_data.txt

  • Number of patients = 123

  • Number of significantly arm-level cnvs = 80

  • Number of selected clinical features = 8

  • Exclude regions that fewer than K tumors have mutations, K = 3

Survival analysis

For survival clinical features, the Kaplan-Meier survival curves of tumors with and without gene mutations were plotted and the statistical significance P values were estimated by logrank test (Bland and Altman 2004) using the 'survdiff' function in R

Student's t-test analysis

For continuous numerical clinical features, two-tailed Student's t test with unequal variance (Lehmann and Romano 2005) was applied to compare the clinical values between tumors with and without gene mutations using 't.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

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] Bland and Altman, Statistics notes: The logrank test, BMJ 328(7447):1073 (2004)
[2] Lehmann and Romano, Testing Statistical Hypotheses (3E ed.), New York: Springer. ISBN 0387988645 (2005)
[3] Greenwood and Nikulin, A guide to chi-squared testing, Wiley, New York. ISBN 047155779X (1996)
[4] 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)
[5] 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)