Correlation between copy number variations of arm-level result and selected clinical features
Liver Hepatocellular Carcinoma (Primary solid tumor)
16 April 2014
|
analyses__2014_04_16
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/C1PZ57FJ
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 149 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 | 20 (13%) | 129 |
0.667 (1.00) |
0.958 (1.00) |
0.683 (1.00) |
0.0745 (1.00) |
1 (1.00) |
0.596 (1.00) |
0.0841 (1.00) |
0.271 (1.00) |
| 1q gain | 85 (57%) | 64 |
0.0789 (1.00) |
0.638 (1.00) |
0.022 (1.00) |
0.00523 (1.00) |
0.587 (1.00) |
0.314 (1.00) |
0.178 (1.00) |
0.613 (1.00) |
| 2p gain | 24 (16%) | 125 |
0.894 (1.00) |
0.452 (1.00) |
0.664 (1.00) |
0.726 (1.00) |
0.058 (1.00) |
0.654 (1.00) |
0.0123 (1.00) |
0.162 (1.00) |
| 2q gain | 19 (13%) | 130 |
0.825 (1.00) |
0.76 (1.00) |
0.807 (1.00) |
0.979 (1.00) |
0.321 (1.00) |
0.422 (1.00) |
0.01 (1.00) |
0.298 (1.00) |
| 3p gain | 13 (9%) | 136 |
0.379 (1.00) |
0.403 (1.00) |
0.976 (1.00) |
0.665 (1.00) |
0.197 (1.00) |
0.8 (1.00) |
0.252 (1.00) |
0.718 (1.00) |
| 3q gain | 14 (9%) | 135 |
0.207 (1.00) |
0.346 (1.00) |
0.976 (1.00) |
0.898 (1.00) |
0.197 (1.00) |
1 (1.00) |
0.567 (1.00) |
0.732 (1.00) |
| 4p gain | 12 (8%) | 137 |
0.0796 (1.00) |
0.338 (1.00) |
0.619 (1.00) |
0.701 (1.00) |
1 (1.00) |
0.582 (1.00) |
0.539 (1.00) |
0.851 (1.00) |
| 4q gain | 4 (3%) | 145 |
0.802 (1.00) |
0.453 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.612 (1.00) |
0.643 (1.00) |
0.128 (1.00) |
| 5p gain | 58 (39%) | 91 |
0.503 (1.00) |
0.434 (1.00) |
0.165 (1.00) |
0.0282 (1.00) |
0.294 (1.00) |
0.389 (1.00) |
0.865 (1.00) |
0.891 (1.00) |
| 5q gain | 44 (30%) | 105 |
0.472 (1.00) |
0.294 (1.00) |
0.656 (1.00) |
0.495 (1.00) |
0.557 (1.00) |
0.78 (1.00) |
0.467 (1.00) |
0.519 (1.00) |
| 6p gain | 39 (26%) | 110 |
0.133 (1.00) |
0.69 (1.00) |
0.532 (1.00) |
0.64 (1.00) |
1 (1.00) |
0.254 (1.00) |
0.449 (1.00) |
0.486 (1.00) |
| 6q gain | 21 (14%) | 128 |
0.414 (1.00) |
0.165 (1.00) |
0.142 (1.00) |
0.86 (1.00) |
1 (1.00) |
0.0639 (1.00) |
0.636 (1.00) |
0.193 (1.00) |
| 7p gain | 47 (32%) | 102 |
0.371 (1.00) |
0.131 (1.00) |
0.579 (1.00) |
0.312 (1.00) |
0.189 (1.00) |
0.524 (1.00) |
0.368 (1.00) |
0.672 (1.00) |
| 7q gain | 48 (32%) | 101 |
0.802 (1.00) |
0.276 (1.00) |
0.462 (1.00) |
0.289 (1.00) |
0.213 (1.00) |
0.624 (1.00) |
1 (1.00) |
0.831 (1.00) |
| 8p gain | 28 (19%) | 121 |
0.694 (1.00) |
0.113 (1.00) |
0.236 (1.00) |
0.213 (1.00) |
1 (1.00) |
0.202 (1.00) |
0.83 (1.00) |
0.234 (1.00) |
| 8q gain | 74 (50%) | 75 |
0.913 (1.00) |
0.773 (1.00) |
0.317 (1.00) |
0.551 (1.00) |
1 (1.00) |
0.711 (1.00) |
0.0289 (1.00) |
0.83 (1.00) |
| 9p gain | 6 (4%) | 143 |
0.798 (1.00) |
0.662 (1.00) |
0.367 (1.00) |
0.16 (1.00) |
1 (1.00) |
1 (1.00) |
0.678 (1.00) |
0.433 (1.00) |
| 9q gain | 6 (4%) | 143 |
0.198 (1.00) |
0.828 (1.00) |
0.912 (1.00) |
0.694 (1.00) |
1 (1.00) |
1 (1.00) |
0.208 (1.00) |
0.433 (1.00) |
| 10p gain | 21 (14%) | 128 |
0.711 (1.00) |
0.0972 (1.00) |
0.415 (1.00) |
0.286 (1.00) |
1 (1.00) |
0.452 (1.00) |
0.81 (1.00) |
1 (1.00) |
| 10q gain | 13 (9%) | 136 |
0.416 (1.00) |
0.241 (1.00) |
0.475 (1.00) |
0.594 (1.00) |
1 (1.00) |
0.355 (1.00) |
0.372 (1.00) |
0.594 (1.00) |
| 11p gain | 10 (7%) | 139 |
0.9 (1.00) |
0.68 (1.00) |
0.0399 (1.00) |
0.447 (1.00) |
1 (1.00) |
0.0535 (1.00) |
0.741 (1.00) |
0.102 (1.00) |
| 11q gain | 9 (6%) | 140 |
0.594 (1.00) |
0.567 (1.00) |
0.0316 (1.00) |
0.59 (1.00) |
1 (1.00) |
0.0601 (1.00) |
1 (1.00) |
0.0911 (1.00) |
| 12p gain | 14 (9%) | 135 |
0.837 (1.00) |
0.377 (1.00) |
0.952 (1.00) |
0.849 (1.00) |
1 (1.00) |
0.482 (1.00) |
0.159 (1.00) |
0.718 (1.00) |
| 12q gain | 18 (12%) | 131 |
0.544 (1.00) |
0.265 (1.00) |
0.569 (1.00) |
0.56 (1.00) |
0.344 (1.00) |
0.179 (1.00) |
0.0181 (1.00) |
0.609 (1.00) |
| 13q gain | 8 (5%) | 141 |
0.103 (1.00) |
0.639 (1.00) |
0.688 (1.00) |
0.825 (1.00) |
0.171 (1.00) |
1 (1.00) |
0.712 (1.00) |
0.493 (1.00) |
| 14q gain | 8 (5%) | 141 |
0.907 (1.00) |
0.638 (1.00) |
0.027 (1.00) |
0.936 (1.00) |
1 (1.00) |
0.207 (1.00) |
1 (1.00) |
0.0691 (1.00) |
| 15q gain | 14 (9%) | 135 |
0.0891 (1.00) |
0.803 (1.00) |
0.819 (1.00) |
0.352 (1.00) |
1 (1.00) |
1 (1.00) |
0.567 (1.00) |
0.855 (1.00) |
| 16p gain | 12 (8%) | 137 |
0.978 (1.00) |
0.335 (1.00) |
0.255 (1.00) |
0.184 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
| 16q gain | 5 (3%) | 144 |
0.594 (1.00) |
0.205 (1.00) |
0.797 (1.00) |
0.142 (1.00) |
1 (1.00) |
1 (1.00) |
0.378 (1.00) |
1 (1.00) |
| 17p gain | 13 (9%) | 136 |
0.444 (1.00) |
0.492 (1.00) |
0.19 (1.00) |
0.473 (1.00) |
1 (1.00) |
0.602 (1.00) |
1 (1.00) |
0.49 (1.00) |
| 17q gain | 39 (26%) | 110 |
0.27 (1.00) |
0.44 (1.00) |
0.558 (1.00) |
0.438 (1.00) |
1 (1.00) |
0.0735 (1.00) |
0.255 (1.00) |
0.0792 (1.00) |
| 18p gain | 10 (7%) | 139 |
0.311 (1.00) |
0.192 (1.00) |
0.013 (1.00) |
0.174 (1.00) |
1 (1.00) |
0.163 (1.00) |
0.741 (1.00) |
0.0371 (1.00) |
| 18q gain | 9 (6%) | 140 |
0.357 (1.00) |
0.373 (1.00) |
0.0167 (1.00) |
0.277 (1.00) |
1 (1.00) |
0.189 (1.00) |
1 (1.00) |
0.0309 (1.00) |
| 19p gain | 30 (20%) | 119 |
0.468 (1.00) |
0.941 (1.00) |
0.123 (1.00) |
0.59 (1.00) |
0.511 (1.00) |
0.134 (1.00) |
0.0934 (1.00) |
0.223 (1.00) |
| 19q gain | 34 (23%) | 115 |
0.48 (1.00) |
0.926 (1.00) |
0.125 (1.00) |
0.578 (1.00) |
0.548 (1.00) |
0.186 (1.00) |
0.162 (1.00) |
0.149 (1.00) |
| 20p gain | 43 (29%) | 106 |
0.456 (1.00) |
0.506 (1.00) |
0.319 (1.00) |
0.656 (1.00) |
1 (1.00) |
0.147 (1.00) |
0.267 (1.00) |
0.573 (1.00) |
| 20q gain | 45 (30%) | 104 |
0.529 (1.00) |
0.51 (1.00) |
0.368 (1.00) |
0.55 (1.00) |
1 (1.00) |
0.123 (1.00) |
0.368 (1.00) |
0.47 (1.00) |
| 21q gain | 13 (9%) | 136 |
0.51 (1.00) |
0.769 (1.00) |
0.446 (1.00) |
0.397 (1.00) |
1 (1.00) |
0.8 (1.00) |
0.372 (1.00) |
0.344 (1.00) |
| 22q gain | 19 (13%) | 130 |
0.395 (1.00) |
0.64 (1.00) |
0.879 (1.00) |
0.694 (1.00) |
0.344 (1.00) |
0.844 (1.00) |
0.804 (1.00) |
0.332 (1.00) |
| xq gain | 28 (19%) | 121 |
0.928 (1.00) |
0.0511 (1.00) |
0.953 (1.00) |
0.791 (1.00) |
1 (1.00) |
0.233 (1.00) |
0.52 (1.00) |
0.529 (1.00) |
| 1p loss | 37 (25%) | 112 |
0.916 (1.00) |
0.397 (1.00) |
0.535 (1.00) |
0.484 (1.00) |
1 (1.00) |
0.0646 (1.00) |
0.564 (1.00) |
0.407 (1.00) |
| 1q loss | 11 (7%) | 138 |
0.655 (1.00) |
0.27 (1.00) |
0.839 (1.00) |
0.599 (1.00) |
0.197 (1.00) |
1 (1.00) |
1 (1.00) |
0.21 (1.00) |
| 2p loss | 11 (7%) | 138 |
0.0601 (1.00) |
0.812 (1.00) |
0.833 (1.00) |
0.279 (1.00) |
1 (1.00) |
1 (1.00) |
0.53 (1.00) |
0.54 (1.00) |
| 2q loss | 13 (9%) | 136 |
0.365 (1.00) |
0.871 (1.00) |
0.936 (1.00) |
0.594 (1.00) |
1 (1.00) |
0.8 (1.00) |
1 (1.00) |
0.28 (1.00) |
| 3p loss | 19 (13%) | 130 |
0.0825 (1.00) |
0.795 (1.00) |
0.167 (1.00) |
0.0155 (1.00) |
0.344 (1.00) |
0.235 (1.00) |
0.214 (1.00) |
0.575 (1.00) |
| 3q loss | 10 (7%) | 139 |
0.0322 (1.00) |
0.228 (1.00) |
0.823 (1.00) |
0.272 (1.00) |
0.197 (1.00) |
0.748 (1.00) |
0.512 (1.00) |
1 (1.00) |
| 4p loss | 31 (21%) | 118 |
0.439 (1.00) |
0.714 (1.00) |
0.0474 (1.00) |
0.335 (1.00) |
0.0658 (1.00) |
0.144 (1.00) |
0.686 (1.00) |
0.272 (1.00) |
| 4q loss | 48 (32%) | 101 |
0.334 (1.00) |
0.182 (1.00) |
0.198 (1.00) |
0.365 (1.00) |
0.213 (1.00) |
0.189 (1.00) |
0.372 (1.00) |
0.21 (1.00) |
| 5p loss | 10 (7%) | 139 |
0.526 (1.00) |
0.682 (1.00) |
0.261 (1.00) |
0.599 (1.00) |
0.197 (1.00) |
1 (1.00) |
0.317 (1.00) |
0.487 (1.00) |
| 5q loss | 14 (9%) | 135 |
0.217 (1.00) |
0.882 (1.00) |
0.457 (1.00) |
0.198 (1.00) |
0.223 (1.00) |
1 (1.00) |
1 (1.00) |
0.534 (1.00) |
| 6p loss | 17 (11%) | 132 |
0.758 (1.00) |
0.844 (1.00) |
0.63 (1.00) |
0.395 (1.00) |
0.389 (1.00) |
0.0196 (1.00) |
0.29 (1.00) |
1 (1.00) |
| 6q loss | 46 (31%) | 103 |
0.824 (1.00) |
0.0514 (1.00) |
0.214 (1.00) |
0.85 (1.00) |
0.239 (1.00) |
0.225 (1.00) |
0.471 (1.00) |
0.951 (1.00) |
| 7p loss | 8 (5%) | 141 |
0.0629 (1.00) |
0.642 (1.00) |
0.923 (1.00) |
0.596 (1.00) |
1 (1.00) |
0.727 (1.00) |
0.0563 (1.00) |
0.548 (1.00) |
| 7q loss | 11 (7%) | 138 |
0.194 (1.00) |
0.408 (1.00) |
0.861 (1.00) |
0.364 (1.00) |
1 (1.00) |
0.57 (1.00) |
0.0238 (1.00) |
0.266 (1.00) |
| 8p loss | 74 (50%) | 75 |
0.317 (1.00) |
0.00162 (1.00) |
0.106 (1.00) |
0.46 (1.00) |
0.0763 (1.00) |
0.39 (1.00) |
0.867 (1.00) |
0.584 (1.00) |
| 8q loss | 15 (10%) | 134 |
0.653 (1.00) |
0.938 (1.00) |
0.276 (1.00) |
0.0344 (1.00) |
0.223 (1.00) |
0.274 (1.00) |
0.0262 (1.00) |
1 (1.00) |
| 9p loss | 46 (31%) | 103 |
0.0772 (1.00) |
0.941 (1.00) |
0.0498 (1.00) |
0.411 (1.00) |
0.213 (1.00) |
0.0449 (1.00) |
0.203 (1.00) |
0.205 (1.00) |
| 9q loss | 48 (32%) | 101 |
0.0179 (1.00) |
0.877 (1.00) |
0.0395 (1.00) |
0.404 (1.00) |
0.0251 (1.00) |
0.0279 (1.00) |
0.372 (1.00) |
0.226 (1.00) |
| 10p loss | 17 (11%) | 132 |
0.921 (1.00) |
0.0468 (1.00) |
0.062 (1.00) |
0.245 (1.00) |
0.249 (1.00) |
0.833 (1.00) |
0.0668 (1.00) |
0.869 (1.00) |
| 10q loss | 30 (20%) | 119 |
0.172 (1.00) |
0.456 (1.00) |
0.245 (1.00) |
0.298 (1.00) |
0.411 (1.00) |
0.9 (1.00) |
0.146 (1.00) |
0.345 (1.00) |
| 11p loss | 24 (16%) | 125 |
0.726 (1.00) |
0.104 (1.00) |
0.492 (1.00) |
0.762 (1.00) |
0.0437 (1.00) |
1 (1.00) |
0.65 (1.00) |
0.684 (1.00) |
| 11q loss | 27 (18%) | 122 |
0.981 (1.00) |
0.131 (1.00) |
0.509 (1.00) |
0.577 (1.00) |
0.0658 (1.00) |
1 (1.00) |
0.663 (1.00) |
0.445 (1.00) |
| 12p loss | 27 (18%) | 122 |
0.211 (1.00) |
0.959 (1.00) |
0.379 (1.00) |
0.601 (1.00) |
0.0826 (1.00) |
0.467 (1.00) |
1 (1.00) |
0.122 (1.00) |
| 12q loss | 16 (11%) | 133 |
0.294 (1.00) |
0.559 (1.00) |
0.11 (1.00) |
0.933 (1.00) |
1 (1.00) |
0.299 (1.00) |
0.285 (1.00) |
0.0887 (1.00) |
| 13q loss | 52 (35%) | 97 |
0.721 (1.00) |
0.234 (1.00) |
0.0986 (1.00) |
0.00196 (1.00) |
1 (1.00) |
0.252 (1.00) |
0.861 (1.00) |
0.521 (1.00) |
| 14q loss | 45 (30%) | 104 |
0.65 (1.00) |
0.995 (1.00) |
0.385 (1.00) |
0.115 (1.00) |
1 (1.00) |
0.269 (1.00) |
0.464 (1.00) |
0.382 (1.00) |
| 15q loss | 29 (19%) | 120 |
0.921 (1.00) |
0.491 (1.00) |
0.505 (1.00) |
0.227 (1.00) |
0.0826 (1.00) |
0.0814 (1.00) |
0.674 (1.00) |
1 (1.00) |
| 16p loss | 42 (28%) | 107 |
0.0157 (1.00) |
0.163 (1.00) |
0.192 (1.00) |
0.206 (1.00) |
0.201 (1.00) |
0.178 (1.00) |
0.853 (1.00) |
0.172 (1.00) |
| 16q loss | 53 (36%) | 96 |
0.126 (1.00) |
0.052 (1.00) |
0.296 (1.00) |
0.17 (1.00) |
0.553 (1.00) |
0.408 (1.00) |
1 (1.00) |
0.32 (1.00) |
| 17p loss | 75 (50%) | 74 |
0.107 (1.00) |
0.462 (1.00) |
0.0725 (1.00) |
0.241 (1.00) |
0.243 (1.00) |
0.522 (1.00) |
0.504 (1.00) |
0.147 (1.00) |
| 17q loss | 19 (13%) | 130 |
0.744 (1.00) |
0.355 (1.00) |
0.178 (1.00) |
0.535 (1.00) |
0.0258 (1.00) |
0.58 (1.00) |
0.804 (1.00) |
0.706 (1.00) |
| 18p loss | 27 (18%) | 122 |
0.675 (1.00) |
0.854 (1.00) |
0.758 (1.00) |
0.357 (1.00) |
0.432 (1.00) |
0.299 (1.00) |
0.521 (1.00) |
0.784 (1.00) |
| 18q loss | 30 (20%) | 119 |
0.785 (1.00) |
0.741 (1.00) |
0.789 (1.00) |
0.779 (1.00) |
0.472 (1.00) |
0.197 (1.00) |
0.209 (1.00) |
0.611 (1.00) |
| 19p loss | 16 (11%) | 133 |
0.0274 (1.00) |
0.958 (1.00) |
0.929 (1.00) |
0.545 (1.00) |
0.273 (1.00) |
0.662 (1.00) |
0.285 (1.00) |
0.111 (1.00) |
| 19q loss | 11 (7%) | 138 |
0.1 (1.00) |
0.734 (1.00) |
0.961 (1.00) |
0.828 (1.00) |
0.197 (1.00) |
0.57 (1.00) |
0.53 (1.00) |
0.175 (1.00) |
| 20p loss | 8 (5%) | 141 |
0.302 (1.00) |
0.349 (1.00) |
0.388 (1.00) |
0.491 (1.00) |
1 (1.00) |
0.207 (1.00) |
1 (1.00) |
1 (1.00) |
| 20q loss | 4 (3%) | 145 |
0.74 (1.00) |
0.969 (1.00) |
0.969 (1.00) |
0.512 (1.00) |
1 (1.00) |
0.612 (1.00) |
1 (1.00) |
1 (1.00) |
| 21q loss | 40 (27%) | 109 |
0.0696 (1.00) |
0.732 (1.00) |
0.275 (1.00) |
0.789 (1.00) |
0.142 (1.00) |
0.169 (1.00) |
0.0385 (1.00) |
0.331 (1.00) |
| 22q loss | 31 (21%) | 118 |
0.375 (1.00) |
0.276 (1.00) |
0.73 (1.00) |
0.174 (1.00) |
1 (1.00) |
0.395 (1.00) |
0.535 (1.00) |
0.189 (1.00) |
| xq loss | 20 (13%) | 129 |
0.541 (1.00) |
0.299 (1.00) |
0.64 (1.00) |
0.383 (1.00) |
0.321 (1.00) |
0.441 (1.00) |
0.465 (1.00) |
0.798 (1.00) |
Methods & Data
Input
-
Copy number data file = transformed.cor.cli.txt
-
Clinical data file = LIHC-TP.merged_data.txt
-
Number of patients = 149
-
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)
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Broad Institute TCGA GDAC as part of the TCGA Research Network.
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