Correlation between copy number variations of arm-level result and selected clinical features
Esophageal Carcinoma (Primary solid tumor)
16 April 2014  |  analyses__2014_04_16
Maintainer Information
Citation Information
doi:10.7908/C1R78CTN
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/C1R78CTN
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 79 arm-level events and 8 clinical features across 56 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 79 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 NUMBERPACKYEARSSMOKED
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 t-test
1p gain 9 (16%) 47 0.43
(1.00) 		0.0454
(1.00) 		0.435
(1.00) 		0.298
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00) 		0.234
(1.00)
1q gain 19 (34%) 37 0.5
(1.00) 		0.0583
(1.00) 		0.545
(1.00) 		0.768
(1.00) 		0.858
(1.00) 		1
(1.00) 		0.243
(1.00) 		0.874
(1.00)
2p gain 20 (36%) 36 0.811
(1.00) 		0.698
(1.00) 		0.0213
(1.00) 		0.254
(1.00) 		0.793
(1.00) 		0.484
(1.00) 		1
(1.00) 		0.0948
(1.00)
2q gain 13 (23%) 43 0.976
(1.00) 		0.61
(1.00) 		0.402
(1.00) 		0.787
(1.00) 		1
(1.00) 		0.721
(1.00) 		0.37
(1.00) 		0.963
(1.00)
3p gain 8 (14%) 48 0.347
(1.00) 		0.967
(1.00) 		0.283
(1.00) 		0.254
(1.00) 		0.676
(1.00) 		0.14
(1.00) 		0.32
(1.00) 		0.8
(1.00)
3q gain 28 (50%) 28 0.235
(1.00) 		0.00569
(1.00) 		0.823
(1.00) 		0.847
(1.00) 		0.867
(1.00) 		0.848
(1.00) 		1
(1.00) 		0.501
(1.00)
4p gain 3 (5%) 53 0.529
(1.00) 		0.375
(1.00) 		0.789
(1.00) 		0.315
(1.00) 		0.731
(1.00) 		1
(1.00)
4q gain 3 (5%) 53 0.55
(1.00) 		0.394
(1.00) 		0.994
(1.00) 		0.187
(1.00) 		1
(1.00) 		1
(1.00) 		0.207
(1.00)
5p gain 22 (39%) 34 0.805
(1.00) 		0.988
(1.00) 		0.03
(1.00) 		0.779
(1.00) 		0.232
(1.00) 		0.167
(1.00) 		1
(1.00) 		0.885
(1.00)
5q gain 4 (7%) 52 0.39
(1.00) 		0.718
(1.00) 		0.324
(1.00) 		1
(1.00) 		0.266
(1.00) 		0.552
(1.00) 		1
(1.00)
6p gain 7 (12%) 49 0.521
(1.00) 		0.704
(1.00) 		0.802
(1.00) 		0.712
(1.00) 		0.64
(1.00) 		1
(1.00) 		0.259
(1.00)
6q gain 5 (9%) 51 0.732
(1.00) 		0.281
(1.00) 		0.588
(1.00) 		0.363
(1.00) 		0.27
(1.00) 		1
(1.00) 		1
(1.00)
7p gain 37 (66%) 19 0.93
(1.00) 		0.971
(1.00) 		0.21
(1.00) 		0.912
(1.00) 		0.0683
(1.00) 		1
(1.00) 		1
(1.00) 		0.616
(1.00)
7q gain 27 (48%) 29 0.188
(1.00) 		0.532
(1.00) 		0.182
(1.00) 		0.571
(1.00) 		0.76
(1.00) 		0.843
(1.00) 		0.707
(1.00) 		0.196
(1.00)
8p gain 20 (36%) 36 0.487
(1.00) 		0.936
(1.00) 		0.529
(1.00) 		0.588
(1.00) 		0.928
(1.00) 		0.151
(1.00) 		1
(1.00) 		0.339
(1.00)
8q gain 32 (57%) 24 0.994
(1.00) 		0.748
(1.00) 		0.687
(1.00) 		0.608
(1.00) 		0.75
(1.00) 		0.44
(1.00) 		0.268
(1.00) 		0.0292
(1.00)
9p gain 8 (14%) 48 0.143
(1.00) 		0.838
(1.00) 		0.0551
(1.00) 		0.0861
(1.00) 		0.0993
(1.00) 		1
(1.00) 		0.585
(1.00) 		0.0182
(1.00)
9q gain 14 (25%) 42 0.073
(1.00) 		0.3
(1.00) 		0.105
(1.00) 		0.0258
(1.00) 		0.704
(1.00) 		1
(1.00) 		0.18
(1.00) 		0.00324
(1.00)
10p gain 8 (14%) 48 0.298
(1.00) 		0.73
(1.00) 		0.171
(1.00) 		1
(1.00) 		0.869
(1.00) 		0.245
(1.00) 		0.585
(1.00) 		0.378
(1.00)
10q gain 8 (14%) 48 0.41
(1.00) 		0.479
(1.00) 		0.0444
(1.00) 		0.532
(1.00) 		0.0395
(1.00) 		0.0245
(1.00) 		0.585
(1.00) 		0.419
(1.00)
11p gain 12 (21%) 44 0.671
(1.00) 		0.284
(1.00) 		0.84
(1.00) 		0.613
(1.00) 		0.245
(1.00) 		1
(1.00) 		1
(1.00) 		0.577
(1.00)
11q gain 10 (18%) 46 0.781
(1.00) 		0.121
(1.00) 		0.937
(1.00) 		0.867
(1.00) 		0.248
(1.00) 		1
(1.00) 		1
(1.00) 		0.403
(1.00)
12p gain 22 (39%) 34 0.648
(1.00) 		0.872
(1.00) 		0.177
(1.00) 		0.247
(1.00) 		0.929
(1.00) 		0.404
(1.00) 		0.46
(1.00) 		0.132
(1.00)
12q gain 15 (27%) 41 0.673
(1.00) 		0.776
(1.00) 		0.0694
(1.00) 		0.816
(1.00) 		0.704
(1.00) 		0.289
(1.00) 		1
(1.00) 		0.0612
(1.00)
13q gain 8 (14%) 48 0.646
(1.00) 		0.289
(1.00) 		0.204
(1.00) 		0.366
(1.00) 		0.595
(1.00) 		0.245
(1.00) 		0.0778
(1.00) 		0.165
(1.00)
14q gain 17 (30%) 39 0.718
(1.00) 		0.307
(1.00) 		0.758
(1.00) 		0.686
(1.00) 		0.0425
(1.00) 		0.613
(1.00) 		0.0901
(1.00) 		0.672
(1.00)
15q gain 7 (12%) 49 0.262
(1.00) 		0.975
(1.00) 		0.961
(1.00) 		0.544
(1.00) 		0.619
(1.00) 		1
(1.00) 		0.259
(1.00) 		0.616
(1.00)
16p gain 14 (25%) 42 0.652
(1.00) 		0.772
(1.00) 		0.00542
(1.00) 		0.246
(1.00) 		0.911
(1.00) 		1
(1.00) 		0.18
(1.00) 		0.804
(1.00)
16q gain 12 (21%) 44 0.562
(1.00) 		0.665
(1.00) 		0.0267
(1.00) 		0.388
(1.00) 		0.497
(1.00) 		1
(1.00) 		0.18
(1.00) 		0.798
(1.00)
17p gain 12 (21%) 44 0.587
(1.00) 		0.275
(1.00) 		0.872
(1.00) 		0.703
(1.00) 		0.746
(1.00) 		1
(1.00) 		0.18
(1.00) 		0.0712
(1.00)
17q gain 16 (29%) 40 0.72
(1.00) 		0.875
(1.00) 		0.483
(1.00) 		0.265
(1.00) 		0.0751
(1.00) 		0.303
(1.00) 		0.416
(1.00) 		0.0203
(1.00)
18p gain 19 (34%) 37 0.0919
(1.00) 		0.552
(1.00) 		0.336
(1.00) 		0.588
(1.00) 		0.793
(1.00) 		0.151
(1.00) 		0.703
(1.00) 		0.867
(1.00)
18q gain 7 (12%) 49 0.618
(1.00) 		0.336
(1.00) 		0.802
(1.00) 		1
(1.00) 		1
(1.00) 		0.404
(1.00) 		1
(1.00) 		0.516
(1.00)
19p gain 10 (18%) 46 0.481
(1.00) 		0.442
(1.00) 		0.202
(1.00) 		0.874
(1.00) 		0.00456
(1.00) 		0.0402
(1.00) 		0.326
(1.00) 		0.194
(1.00)
19q gain 11 (20%) 45 0.834
(1.00) 		0.093
(1.00) 		0.0449
(1.00) 		0.69
(1.00) 		0.00659
(1.00) 		0.0402
(1.00) 		0.333
(1.00) 		0.176
(1.00)
20p gain 29 (52%) 27 0.877
(1.00) 		0.0102
(1.00) 		0.482
(1.00) 		0.921
(1.00) 		0.46
(1.00) 		0.848
(1.00) 		0.707
(1.00) 		0.459
(1.00)
20q gain 30 (54%) 26 0.488
(1.00) 		0.00177
(1.00) 		0.493
(1.00) 		0.246
(1.00) 		0.275
(1.00) 		0.349
(1.00) 		0.712
(1.00) 		0.446
(1.00)
21q gain 6 (11%) 50 0.273
(1.00) 		0.9
(1.00) 		0.882
(1.00) 		0.32
(1.00) 		0.729
(1.00) 		1
(1.00) 		0.578
(1.00)
22q gain 15 (27%) 41 0.787
(1.00) 		0.2
(1.00) 		0.824
(1.00) 		1
(1.00) 		0.0256
(1.00) 		1
(1.00) 		1
(1.00) 		0.512
(1.00)
xq gain 15 (27%) 41 0.479
(1.00) 		0.695
(1.00) 		0.837
(1.00) 		0.164
(1.00) 		1
(1.00) 		0.776
(1.00) 		0.0929
(1.00) 		0.864
(1.00)
1p loss 7 (12%) 49 0.499
(1.00) 		0.155
(1.00) 		0.0122
(1.00) 		0.544
(1.00) 		1
(1.00) 		0.0722
(1.00) 		0.259
(1.00) 		0.349
(1.00)
1q loss 5 (9%) 51 0.121
(1.00) 		0.235
(1.00) 		0.00968
(1.00) 		0.416
(1.00) 		0.137
(1.00) 		0.0615
(1.00) 		0.552
(1.00) 		0.681
(1.00)
2p loss 3 (5%) 53 0.131
(1.00) 		0.442
(1.00) 		0.601
(1.00) 		1
(1.00) 		0.0933
(1.00) 		1
(1.00) 		0.376
(1.00)
2q loss 7 (12%) 49 0.452
(1.00) 		0.667
(1.00) 		0.761
(1.00) 		1
(1.00) 		0.15
(1.00) 		0.638
(1.00) 		1
(1.00) 		0.586
(1.00)
3p loss 33 (59%) 23 0.535
(1.00) 		0.157
(1.00) 		0.513
(1.00) 		0.405
(1.00) 		0.123
(1.00) 		0.0698
(1.00) 		0.704
(1.00) 		0.733
(1.00)
3q loss 6 (11%) 50 0.579
(1.00) 		0.258
(1.00) 		0.197
(1.00) 		1
(1.00) 		0.514
(1.00) 		0.622
(1.00) 		0.578
(1.00) 		0.173
(1.00)
4p loss 33 (59%) 23 0.66
(1.00) 		0.688
(1.00) 		0.587
(1.00) 		0.405
(1.00) 		0.929
(1.00) 		0.237
(1.00) 		0.252
(1.00) 		0.621
(1.00)
4q loss 26 (46%) 30 0.188
(1.00) 		0.00788
(1.00) 		0.0667
(1.00) 		0.666
(1.00) 		0.569
(1.00) 		0.843
(1.00) 		1
(1.00) 		0.913
(1.00)
5p loss 13 (23%) 43 0.279
(1.00) 		0.171
(1.00) 		0.198
(1.00) 		0.799
(1.00) 		0.112
(1.00) 		0.738
(1.00) 		0.37
(1.00) 		0.221
(1.00)
5q loss 25 (45%) 31 0.2
(1.00) 		0.69
(1.00) 		0.303
(1.00) 		0.134
(1.00) 		0.372
(1.00) 		0.554
(1.00) 		0.121
(1.00) 		0.511
(1.00)
6p loss 11 (20%) 45 0.81
(1.00) 		0.332
(1.00) 		0.669
(1.00) 		0.237
(1.00) 		0.349
(1.00) 		0.491
(1.00) 		1
(1.00) 		0.772
(1.00)
6q loss 10 (18%) 46 0.291
(1.00) 		0.659
(1.00) 		0.755
(1.00) 		1
(1.00) 		0.122
(1.00) 		0.462
(1.00) 		0.326
(1.00) 		0.412
(1.00)
7p loss 4 (7%) 52 0.863
(1.00) 		0.736
(1.00) 		0.799
(1.00) 		0.564
(1.00) 		0.192
(1.00) 		1
(1.00) 		0.47
(1.00) 		0.505
(1.00)
7q loss 6 (11%) 50 0.922
(1.00) 		0.556
(1.00) 		0.611
(1.00) 		0.163
(1.00) 		0.845
(1.00) 		0.622
(1.00) 		0.578
(1.00) 		0.206
(1.00)
8p loss 22 (39%) 34 0.477
(1.00) 		0.727
(1.00) 		0.307
(1.00) 		0.554
(1.00) 		0.358
(1.00) 		0.165
(1.00) 		0.13
(1.00) 		0.189
(1.00)
8q loss 4 (7%) 52 0.632
(1.00) 		0.928
(1.00) 		0.905
(1.00) 		0.175
(1.00) 		1
(1.00) 		1
(1.00) 		1
(1.00)
9p loss 31 (55%) 25 0.697
(1.00) 		0.235
(1.00) 		0.605
(1.00) 		0.218
(1.00) 		0.0631
(1.00) 		0.0829
(1.00) 		0.72
(1.00) 		0.841
(1.00)
9q loss 18 (32%) 38 0.854
(1.00) 		0.92
(1.00) 		0.638
(1.00) 		0.394
(1.00) 		0.39
(1.00) 		0.0566
(1.00) 		0.703
(1.00) 		0.347
(1.00)
10p loss 14 (25%) 42 0.0318
(1.00) 		0.0736
(1.00) 		0.352
(1.00) 		1
(1.00) 		0.404
(1.00) 		0.303
(1.00) 		1
(1.00) 		0.361
(1.00)
10q loss 18 (32%) 38 0.177
(1.00) 		0.772
(1.00) 		0.275
(1.00) 		0.696
(1.00) 		1
(1.00) 		0.0233
(1.00) 		0.703
(1.00) 		0.277
(1.00)
11p loss 16 (29%) 40 0.904
(1.00) 		0.543
(1.00) 		0.0319
(1.00) 		0.409
(1.00) 		0.92
(1.00) 		0.794
(1.00) 		1
(1.00) 		0.0667
(1.00)
11q loss 20 (36%) 36 0.104
(1.00) 		0.796
(1.00) 		0.0396
(1.00) 		0.197
(1.00) 		0.745
(1.00) 		0.66
(1.00) 		1
(1.00) 		0.0128
(1.00)
12p loss 10 (18%) 46 0.866
(1.00) 		0.0988
(1.00) 		0.13
(1.00) 		0.202
(1.00) 		0.402
(1.00) 		0.0609
(1.00) 		0.143
(1.00) 		0.142
(1.00)
12q loss 8 (14%) 48 0.731
(1.00) 		0.193
(1.00) 		0.0314
(1.00) 		0.74
(1.00) 		0.595
(1.00) 		0.245
(1.00) 		0.0778
(1.00) 		0.155
(1.00)
13q loss 25 (45%) 31 0.429
(1.00) 		0.298
(1.00) 		0.65
(1.00) 		0.923
(1.00) 		0.87
(1.00) 		0.44
(1.00) 		0.0631
(1.00) 		0.527
(1.00)
14q loss 9 (16%) 47 0.367
(1.00) 		0.171
(1.00) 		0.0673
(1.00) 		0.254
(1.00) 		0.118
(1.00) 		1
(1.00) 		0.108
(1.00) 		0.993
(1.00)
15q loss 13 (23%) 43 0.171
(1.00) 		0.501
(1.00) 		0.5
(1.00) 		0.571
(1.00) 		1
(1.00) 		0.262
(1.00) 		1
(1.00) 		0.543
(1.00)
16p loss 12 (21%) 44 0.908
(1.00) 		0.694
(1.00) 		0.41
(1.00) 		0.787
(1.00) 		0.746
(1.00) 		0.262
(1.00) 		0.348
(1.00) 		0.7
(1.00)
16q loss 12 (21%) 44 0.318
(1.00) 		0.431
(1.00) 		0.323
(1.00) 		0.209
(1.00) 		0.599
(1.00) 		0.187
(1.00) 		0.348
(1.00) 		0.587
(1.00)
17p loss 19 (34%) 37 0.422
(1.00) 		0.0511
(1.00) 		0.0409
(1.00) 		0.581
(1.00) 		0.111
(1.00) 		0.277
(1.00) 		0.105
(1.00) 		0.324
(1.00)
17q loss 4 (7%) 52 0.0319
(1.00) 		0.796
(1.00) 		0.596
(1.00) 		1
(1.00) 		0.634
(1.00) 		1
(1.00) 		0.0935
(1.00) 		0.151
(1.00)
18p loss 17 (30%) 39 0.922
(1.00) 		0.147
(1.00) 		0.474
(1.00) 		0.204
(1.00) 		0.397
(1.00) 		0.76
(1.00) 		0.228
(1.00) 		0.0936
(1.00)
18q loss 30 (54%) 26 0.701
(1.00) 		0.195
(1.00) 		0.603
(1.00) 		0.92
(1.00) 		0.319
(1.00) 		0.451
(1.00) 		1
(1.00) 		0.711
(1.00)
19p loss 18 (32%) 38 0.951
(1.00) 		0.402
(1.00) 		0.435
(1.00) 		0.431
(1.00) 		0.235
(1.00) 		1
(1.00) 		0.703
(1.00) 		0.413
(1.00)
19q loss 14 (25%) 42 0.65
(1.00) 		0.638
(1.00) 		0.645
(1.00) 		0.901
(1.00) 		0.23
(1.00) 		1
(1.00) 		0.398
(1.00) 		0.826
(1.00)
20p loss 6 (11%) 50 0.255
(1.00) 		0.965
(1.00) 		0.417
(1.00) 		0.544
(1.00) 		0.514
(1.00) 		1
(1.00) 		0.578
(1.00)
21q loss 32 (57%) 24 0.477
(1.00) 		0.109
(1.00) 		0.185
(1.00) 		0.925
(1.00) 		0.394
(1.00) 		0.84
(1.00) 		0.12
(1.00) 		0.148
(1.00)
22q loss 19 (34%) 37 0.869
(1.00) 		0.218
(1.00) 		0.512
(1.00) 		0.289
(1.00) 		0.185
(1.00) 		0.204
(1.00) 		0.423
(1.00) 		0.939
(1.00)
xq loss 12 (21%) 44 0.971
(1.00) 		0.757
(1.00) 		0.0585
(1.00) 		0.0103
(1.00) 		0.328
(1.00) 		0.69
(1.00) 		1
(1.00) 		0.0769
(1.00)
Methods & Data
Input

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

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

  • Number of patients = 56

  • Number of significantly arm-level cnvs = 79

  • 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)
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