Correlation between copy number variations of arm-level result and selected clinical features
Stomach Adenocarcinoma (Primary solid tumor)
23 September 2013
|
analyses__2013_09_23
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
(2013):
Correlation between copy number variations of arm-level result and selected clinical features.
Broad Institute of MIT and Harvard.
doi:10.7908/C1FB519W
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 11 clinical features across 305 patients, 3 significant findings detected with Q value < 0.25.
-
16P GAIN MUTATION ANALYSIS cnv correlated to 'PATHOLOGY.M.STAGE'.
-
16Q GAIN MUTATION ANALYSIS cnv correlated to 'PATHOLOGY.M.STAGE'.
-
XQ GAIN MUTATION ANALYSIS cnv correlated to 'NUMBER.OF.LYMPH.NODES'.
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 11 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 3 significant findings detected.
|
Clinical Features |
Time to Death |
AGE |
NEOPLASM DISEASESTAGE |
PATHOLOGY T STAGE |
PATHOLOGY N STAGE |
PATHOLOGY M STAGE |
GENDER |
HISTOLOGICAL TYPE |
RADIATIONS RADIATION REGIMENINDICATION |
COMPLETENESS OF RESECTION |
NUMBER OF LYMPH NODES |
||
| 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 | Chi-square test | Fisher's exact test | Fisher's exact test | t-test | |
| 16P GAIN MUTATION ANALYSIS | 42 (14%) | 263 |
0.525 (1.00) |
0.217 (1.00) |
0.00977 (1.00) |
0.416 (1.00) |
0.548 (1.00) |
9.04e-05 (0.0784) |
0.612 (1.00) |
0.889 (1.00) |
0.0573 (1.00) |
0.173 (1.00) |
0.182 (1.00) |
| 16Q GAIN MUTATION ANALYSIS | 32 (10%) | 273 |
0.928 (1.00) |
0.444 (1.00) |
0.00218 (1.00) |
0.541 (1.00) |
0.701 (1.00) |
2.11e-06 (0.00184) |
0.85 (1.00) |
0.817 (1.00) |
0.16 (1.00) |
0.0656 (1.00) |
0.139 (1.00) |
| XQ GAIN MUTATION ANALYSIS | 44 (14%) | 261 |
0.0696 (1.00) |
0.939 (1.00) |
0.0697 (1.00) |
0.117 (1.00) |
0.0321 (1.00) |
1 (1.00) |
0.0656 (1.00) |
0.012 (1.00) |
0.599 (1.00) |
0.449 (1.00) |
0.000261 (0.226) |
| 1P GAIN MUTATION ANALYSIS | 32 (10%) | 273 |
0.689 (1.00) |
0.59 (1.00) |
0.741 (1.00) |
0.559 (1.00) |
0.8 (1.00) |
0.269 (1.00) |
0.444 (1.00) |
0.0147 (1.00) |
1 (1.00) |
0.771 (1.00) |
0.205 (1.00) |
| 1Q GAIN MUTATION ANALYSIS | 72 (24%) | 233 |
0.884 (1.00) |
0.9 (1.00) |
0.964 (1.00) |
0.267 (1.00) |
0.488 (1.00) |
0.0742 (1.00) |
0.411 (1.00) |
0.0198 (1.00) |
0.362 (1.00) |
0.928 (1.00) |
0.319 (1.00) |
| 2P GAIN MUTATION ANALYSIS | 51 (17%) | 254 |
0.314 (1.00) |
0.819 (1.00) |
0.708 (1.00) |
0.292 (1.00) |
0.45 (1.00) |
0.608 (1.00) |
0.532 (1.00) |
0.172 (1.00) |
0.606 (1.00) |
0.278 (1.00) |
0.285 (1.00) |
| 2Q GAIN MUTATION ANALYSIS | 46 (15%) | 259 |
0.2 (1.00) |
0.712 (1.00) |
0.641 (1.00) |
0.585 (1.00) |
0.224 (1.00) |
0.529 (1.00) |
0.329 (1.00) |
0.723 (1.00) |
0.6 (1.00) |
0.334 (1.00) |
0.32 (1.00) |
| 3P GAIN MUTATION ANALYSIS | 38 (12%) | 267 |
0.221 (1.00) |
0.654 (1.00) |
0.901 (1.00) |
0.809 (1.00) |
0.778 (1.00) |
1 (1.00) |
0.724 (1.00) |
0.661 (1.00) |
0.602 (1.00) |
0.696 (1.00) |
0.0932 (1.00) |
| 3Q GAIN MUTATION ANALYSIS | 60 (20%) | 245 |
0.129 (1.00) |
0.0883 (1.00) |
0.899 (1.00) |
0.463 (1.00) |
0.768 (1.00) |
0.188 (1.00) |
1 (1.00) |
0.974 (1.00) |
1 (1.00) |
0.346 (1.00) |
0.124 (1.00) |
| 4P GAIN MUTATION ANALYSIS | 12 (4%) | 293 |
0.725 (1.00) |
0.981 (1.00) |
0.201 (1.00) |
0.125 (1.00) |
0.289 (1.00) |
0.765 (1.00) |
0.379 (1.00) |
0.831 (1.00) |
1 (1.00) |
0.288 (1.00) |
0.336 (1.00) |
| 4Q GAIN MUTATION ANALYSIS | 7 (2%) | 298 |
0.24 (1.00) |
0.625 (1.00) |
0.644 (1.00) |
0.792 (1.00) |
0.55 (1.00) |
0.177 (1.00) |
0.709 (1.00) |
0.0141 (1.00) |
1 (1.00) |
0.502 (1.00) |
0.585 (1.00) |
| 5P GAIN MUTATION ANALYSIS | 68 (22%) | 237 |
0.865 (1.00) |
0.313 (1.00) |
0.484 (1.00) |
0.485 (1.00) |
0.833 (1.00) |
0.845 (1.00) |
0.675 (1.00) |
0.0457 (1.00) |
0.188 (1.00) |
0.456 (1.00) |
0.978 (1.00) |
| 5Q GAIN MUTATION ANALYSIS | 25 (8%) | 280 |
0.934 (1.00) |
0.63 (1.00) |
0.482 (1.00) |
0.297 (1.00) |
0.244 (1.00) |
0.875 (1.00) |
0.67 (1.00) |
0.0902 (1.00) |
0.454 (1.00) |
0.533 (1.00) |
0.125 (1.00) |
| 6P GAIN MUTATION ANALYSIS | 57 (19%) | 248 |
0.91 (1.00) |
0.427 (1.00) |
0.535 (1.00) |
0.344 (1.00) |
0.94 (1.00) |
0.201 (1.00) |
0.652 (1.00) |
0.0379 (1.00) |
0.0249 (1.00) |
0.196 (1.00) |
0.244 (1.00) |
| 6Q GAIN MUTATION ANALYSIS | 46 (15%) | 259 |
0.368 (1.00) |
0.44 (1.00) |
0.46 (1.00) |
0.652 (1.00) |
0.828 (1.00) |
0.309 (1.00) |
0.745 (1.00) |
0.107 (1.00) |
0.0113 (1.00) |
0.0841 (1.00) |
0.679 (1.00) |
| 7P GAIN MUTATION ANALYSIS | 137 (45%) | 168 |
0.296 (1.00) |
0.226 (1.00) |
0.794 (1.00) |
0.931 (1.00) |
0.529 (1.00) |
0.467 (1.00) |
0.157 (1.00) |
0.842 (1.00) |
0.705 (1.00) |
0.814 (1.00) |
0.261 (1.00) |
| 7Q GAIN MUTATION ANALYSIS | 115 (38%) | 190 |
0.139 (1.00) |
0.291 (1.00) |
0.886 (1.00) |
0.997 (1.00) |
0.219 (1.00) |
0.0675 (1.00) |
0.276 (1.00) |
0.867 (1.00) |
1 (1.00) |
0.535 (1.00) |
0.154 (1.00) |
| 8P GAIN MUTATION ANALYSIS | 124 (41%) | 181 |
0.523 (1.00) |
0.0642 (1.00) |
0.782 (1.00) |
0.0719 (1.00) |
0.918 (1.00) |
0.214 (1.00) |
0.19 (1.00) |
0.807 (1.00) |
0.448 (1.00) |
0.125 (1.00) |
0.655 (1.00) |
| 8Q GAIN MUTATION ANALYSIS | 167 (55%) | 138 |
0.197 (1.00) |
0.0143 (1.00) |
0.278 (1.00) |
0.0631 (1.00) |
0.97 (1.00) |
0.355 (1.00) |
0.906 (1.00) |
0.238 (1.00) |
0.463 (1.00) |
0.39 (1.00) |
0.389 (1.00) |
| 9P GAIN MUTATION ANALYSIS | 38 (12%) | 267 |
0.767 (1.00) |
0.873 (1.00) |
0.397 (1.00) |
0.0957 (1.00) |
0.195 (1.00) |
0.44 (1.00) |
0.86 (1.00) |
0.0164 (1.00) |
0.212 (1.00) |
0.777 (1.00) |
0.721 (1.00) |
| 9Q GAIN MUTATION ANALYSIS | 45 (15%) | 260 |
0.677 (1.00) |
0.775 (1.00) |
0.335 (1.00) |
0.257 (1.00) |
0.335 (1.00) |
0.854 (1.00) |
0.508 (1.00) |
0.0546 (1.00) |
0.276 (1.00) |
0.651 (1.00) |
0.126 (1.00) |
| 10P GAIN MUTATION ANALYSIS | 72 (24%) | 233 |
0.914 (1.00) |
0.962 (1.00) |
0.37 (1.00) |
0.397 (1.00) |
0.941 (1.00) |
0.723 (1.00) |
0.89 (1.00) |
0.626 (1.00) |
0.67 (1.00) |
0.66 (1.00) |
0.975 (1.00) |
| 10Q GAIN MUTATION ANALYSIS | 51 (17%) | 254 |
0.716 (1.00) |
0.404 (1.00) |
0.286 (1.00) |
0.676 (1.00) |
0.684 (1.00) |
0.93 (1.00) |
1 (1.00) |
0.924 (1.00) |
0.332 (1.00) |
0.62 (1.00) |
0.409 (1.00) |
| 11P GAIN MUTATION ANALYSIS | 32 (10%) | 273 |
0.472 (1.00) |
0.675 (1.00) |
0.394 (1.00) |
0.267 (1.00) |
0.117 (1.00) |
0.269 (1.00) |
0.344 (1.00) |
0.667 (1.00) |
0.543 (1.00) |
0.551 (1.00) |
0.438 (1.00) |
| 11Q GAIN MUTATION ANALYSIS | 37 (12%) | 268 |
0.0848 (1.00) |
0.86 (1.00) |
0.79 (1.00) |
0.516 (1.00) |
0.0222 (1.00) |
0.624 (1.00) |
0.212 (1.00) |
0.671 (1.00) |
0.599 (1.00) |
0.88 (1.00) |
0.687 (1.00) |
| 12P GAIN MUTATION ANALYSIS | 60 (20%) | 245 |
0.311 (1.00) |
0.136 (1.00) |
0.402 (1.00) |
0.0206 (1.00) |
0.0519 (1.00) |
0.471 (1.00) |
1 (1.00) |
0.224 (1.00) |
0.352 (1.00) |
0.072 (1.00) |
0.87 (1.00) |
| 12Q GAIN MUTATION ANALYSIS | 55 (18%) | 250 |
0.405 (1.00) |
0.286 (1.00) |
0.388 (1.00) |
0.0585 (1.00) |
0.0318 (1.00) |
0.817 (1.00) |
0.76 (1.00) |
0.264 (1.00) |
1 (1.00) |
0.319 (1.00) |
0.765 (1.00) |
| 13Q GAIN MUTATION ANALYSIS | 100 (33%) | 205 |
0.149 (1.00) |
0.996 (1.00) |
0.916 (1.00) |
0.366 (1.00) |
0.924 (1.00) |
0.244 (1.00) |
0.804 (1.00) |
0.518 (1.00) |
1 (1.00) |
0.841 (1.00) |
0.93 (1.00) |
| 14Q GAIN MUTATION ANALYSIS | 14 (5%) | 291 |
0.447 (1.00) |
0.242 (1.00) |
0.775 (1.00) |
0.577 (1.00) |
0.0402 (1.00) |
0.337 (1.00) |
0.411 (1.00) |
0.23 (1.00) |
1 (1.00) |
0.0191 (1.00) |
0.166 (1.00) |
| 15Q GAIN MUTATION ANALYSIS | 24 (8%) | 281 |
0.622 (1.00) |
0.942 (1.00) |
0.403 (1.00) |
0.93 (1.00) |
0.0458 (1.00) |
0.368 (1.00) |
0.385 (1.00) |
0.879 (1.00) |
1 (1.00) |
0.358 (1.00) |
0.858 (1.00) |
| 17P GAIN MUTATION ANALYSIS | 21 (7%) | 284 |
0.368 (1.00) |
0.507 (1.00) |
0.119 (1.00) |
0.455 (1.00) |
0.927 (1.00) |
0.0288 (1.00) |
0.649 (1.00) |
0.202 (1.00) |
0.396 (1.00) |
0.0145 (1.00) |
0.789 (1.00) |
| 17Q GAIN MUTATION ANALYSIS | 37 (12%) | 268 |
0.806 (1.00) |
0.828 (1.00) |
0.679 (1.00) |
0.648 (1.00) |
0.764 (1.00) |
0.0151 (1.00) |
0.473 (1.00) |
0.807 (1.00) |
0.599 (1.00) |
0.102 (1.00) |
0.995 (1.00) |
| 18P GAIN MUTATION ANALYSIS | 54 (18%) | 251 |
0.215 (1.00) |
0.0143 (1.00) |
0.794 (1.00) |
0.556 (1.00) |
0.185 (1.00) |
0.504 (1.00) |
0.645 (1.00) |
0.0217 (1.00) |
0.00233 (1.00) |
0.195 (1.00) |
0.185 (1.00) |
| 18Q GAIN MUTATION ANALYSIS | 37 (12%) | 268 |
0.383 (1.00) |
0.0524 (1.00) |
0.286 (1.00) |
0.274 (1.00) |
0.315 (1.00) |
0.152 (1.00) |
1 (1.00) |
0.0102 (1.00) |
0.0409 (1.00) |
0.238 (1.00) |
0.352 (1.00) |
| 19P GAIN MUTATION ANALYSIS | 39 (13%) | 266 |
0.117 (1.00) |
0.228 (1.00) |
0.24 (1.00) |
0.0361 (1.00) |
0.0691 (1.00) |
0.0522 (1.00) |
0.114 (1.00) |
0.0273 (1.00) |
0.221 (1.00) |
0.0392 (1.00) |
0.091 (1.00) |
| 19Q GAIN MUTATION ANALYSIS | 53 (17%) | 252 |
0.0259 (1.00) |
0.498 (1.00) |
0.369 (1.00) |
0.0864 (1.00) |
0.0468 (1.00) |
0.113 (1.00) |
0.215 (1.00) |
0.0981 (1.00) |
0.0191 (1.00) |
0.0772 (1.00) |
0.0306 (1.00) |
| 20P GAIN MUTATION ANALYSIS | 163 (53%) | 142 |
0.931 (1.00) |
0.868 (1.00) |
0.607 (1.00) |
0.162 (1.00) |
0.458 (1.00) |
0.487 (1.00) |
0.0138 (1.00) |
0.241 (1.00) |
0.709 (1.00) |
0.55 (1.00) |
0.0847 (1.00) |
| 20Q GAIN MUTATION ANALYSIS | 191 (63%) | 114 |
0.381 (1.00) |
0.315 (1.00) |
0.45 (1.00) |
0.0994 (1.00) |
0.344 (1.00) |
0.0529 (1.00) |
0.015 (1.00) |
0.0395 (1.00) |
0.715 (1.00) |
0.11 (1.00) |
0.191 (1.00) |
| 21Q GAIN MUTATION ANALYSIS | 18 (6%) | 287 |
0.946 (1.00) |
0.622 (1.00) |
0.696 (1.00) |
0.484 (1.00) |
0.912 (1.00) |
1 (1.00) |
1 (1.00) |
0.129 (1.00) |
0.35 (1.00) |
0.583 (1.00) |
0.869 (1.00) |
| 22Q GAIN MUTATION ANALYSIS | 23 (8%) | 282 |
0.0838 (1.00) |
0.917 (1.00) |
0.132 (1.00) |
0.187 (1.00) |
0.433 (1.00) |
1 (1.00) |
1 (1.00) |
0.735 (1.00) |
1 (1.00) |
0.84 (1.00) |
0.894 (1.00) |
| 1P LOSS MUTATION ANALYSIS | 38 (12%) | 267 |
0.792 (1.00) |
0.713 (1.00) |
0.153 (1.00) |
0.646 (1.00) |
0.646 (1.00) |
0.0534 (1.00) |
0.724 (1.00) |
0.412 (1.00) |
1 (1.00) |
0.151 (1.00) |
0.499 (1.00) |
| 1Q LOSS MUTATION ANALYSIS | 17 (6%) | 288 |
0.468 (1.00) |
0.46 (1.00) |
0.608 (1.00) |
0.253 (1.00) |
0.695 (1.00) |
0.0393 (1.00) |
1 (1.00) |
0.839 (1.00) |
1 (1.00) |
0.151 (1.00) |
0.761 (1.00) |
| 2P LOSS MUTATION ANALYSIS | 15 (5%) | 290 |
0.466 (1.00) |
0.82 (1.00) |
0.598 (1.00) |
0.753 (1.00) |
0.744 (1.00) |
0.158 (1.00) |
0.283 (1.00) |
0.0564 (1.00) |
0.0412 (1.00) |
0.151 (1.00) |
0.319 (1.00) |
| 2Q LOSS MUTATION ANALYSIS | 18 (6%) | 287 |
0.653 (1.00) |
0.87 (1.00) |
0.902 (1.00) |
0.922 (1.00) |
0.849 (1.00) |
0.224 (1.00) |
0.804 (1.00) |
0.0419 (1.00) |
0.058 (1.00) |
0.166 (1.00) |
0.33 (1.00) |
| 3P LOSS MUTATION ANALYSIS | 54 (18%) | 251 |
0.497 (1.00) |
0.549 (1.00) |
0.936 (1.00) |
0.603 (1.00) |
0.236 (1.00) |
0.101 (1.00) |
0.878 (1.00) |
0.342 (1.00) |
1 (1.00) |
0.209 (1.00) |
0.0253 (1.00) |
| 3Q LOSS MUTATION ANALYSIS | 32 (10%) | 273 |
0.389 (1.00) |
0.219 (1.00) |
0.572 (1.00) |
0.0314 (1.00) |
0.495 (1.00) |
0.729 (1.00) |
0.85 (1.00) |
0.481 (1.00) |
1 (1.00) |
0.627 (1.00) |
0.273 (1.00) |
| 4P LOSS MUTATION ANALYSIS | 108 (35%) | 197 |
0.552 (1.00) |
0.359 (1.00) |
0.161 (1.00) |
0.0548 (1.00) |
0.722 (1.00) |
0.19 (1.00) |
0.54 (1.00) |
0.657 (1.00) |
0.249 (1.00) |
0.451 (1.00) |
0.176 (1.00) |
| 4Q LOSS MUTATION ANALYSIS | 106 (35%) | 199 |
0.642 (1.00) |
0.15 (1.00) |
0.36 (1.00) |
0.17 (1.00) |
0.28 (1.00) |
0.705 (1.00) |
0.0653 (1.00) |
0.621 (1.00) |
0.242 (1.00) |
0.709 (1.00) |
0.191 (1.00) |
| 5P LOSS MUTATION ANALYSIS | 38 (12%) | 267 |
0.92 (1.00) |
0.856 (1.00) |
0.172 (1.00) |
0.829 (1.00) |
0.802 (1.00) |
0.915 (1.00) |
1 (1.00) |
0.487 (1.00) |
0.602 (1.00) |
1 (1.00) |
0.404 (1.00) |
| 5Q LOSS MUTATION ANALYSIS | 65 (21%) | 240 |
0.39 (1.00) |
0.473 (1.00) |
0.0398 (1.00) |
0.944 (1.00) |
0.509 (1.00) |
0.438 (1.00) |
0.775 (1.00) |
0.231 (1.00) |
0.644 (1.00) |
0.534 (1.00) |
0.562 (1.00) |
| 6P LOSS MUTATION ANALYSIS | 29 (10%) | 276 |
0.31 (1.00) |
0.358 (1.00) |
0.615 (1.00) |
0.805 (1.00) |
0.636 (1.00) |
0.23 (1.00) |
0.231 (1.00) |
0.0614 (1.00) |
1 (1.00) |
0.957 (1.00) |
0.627 (1.00) |
| 6Q LOSS MUTATION ANALYSIS | 40 (13%) | 265 |
0.974 (1.00) |
0.626 (1.00) |
0.487 (1.00) |
0.56 (1.00) |
0.858 (1.00) |
0.051 (1.00) |
0.12 (1.00) |
0.343 (1.00) |
0.6 (1.00) |
1 (1.00) |
0.823 (1.00) |
| 7P LOSS MUTATION ANALYSIS | 12 (4%) | 293 |
0.147 (1.00) |
0.998 (1.00) |
0.435 (1.00) |
0.104 (1.00) |
0.876 (1.00) |
0.547 (1.00) |
0.379 (1.00) |
0.611 (1.00) |
1 (1.00) |
1 (1.00) |
0.466 (1.00) |
| 7Q LOSS MUTATION ANALYSIS | 22 (7%) | 283 |
0.0539 (1.00) |
0.447 (1.00) |
0.617 (1.00) |
0.0375 (1.00) |
0.782 (1.00) |
0.545 (1.00) |
0.267 (1.00) |
0.2 (1.00) |
1 (1.00) |
0.941 (1.00) |
0.207 (1.00) |
| 8P LOSS MUTATION ANALYSIS | 53 (17%) | 252 |
0.695 (1.00) |
0.198 (1.00) |
0.424 (1.00) |
0.448 (1.00) |
0.232 (1.00) |
0.498 (1.00) |
0.442 (1.00) |
0.0958 (1.00) |
0.35 (1.00) |
0.307 (1.00) |
0.0913 (1.00) |
| 8Q LOSS MUTATION ANALYSIS | 17 (6%) | 288 |
0.35 (1.00) |
0.423 (1.00) |
0.893 (1.00) |
0.0167 (1.00) |
0.519 (1.00) |
0.339 (1.00) |
0.61 (1.00) |
0.508 (1.00) |
0.333 (1.00) |
0.179 (1.00) |
0.229 (1.00) |
| 9P LOSS MUTATION ANALYSIS | 91 (30%) | 214 |
0.114 (1.00) |
0.219 (1.00) |
0.267 (1.00) |
0.192 (1.00) |
0.587 (1.00) |
0.349 (1.00) |
0.524 (1.00) |
0.32 (1.00) |
0.203 (1.00) |
0.527 (1.00) |
0.753 (1.00) |
| 9Q LOSS MUTATION ANALYSIS | 66 (22%) | 239 |
0.27 (1.00) |
0.823 (1.00) |
0.205 (1.00) |
0.182 (1.00) |
0.972 (1.00) |
0.0111 (1.00) |
0.67 (1.00) |
0.911 (1.00) |
0.0417 (1.00) |
0.315 (1.00) |
0.193 (1.00) |
| 10P LOSS MUTATION ANALYSIS | 35 (11%) | 270 |
0.41 (1.00) |
0.252 (1.00) |
0.0151 (1.00) |
0.155 (1.00) |
0.208 (1.00) |
0.212 (1.00) |
1 (1.00) |
0.269 (1.00) |
0.186 (1.00) |
0.199 (1.00) |
0.21 (1.00) |
| 10Q LOSS MUTATION ANALYSIS | 41 (13%) | 264 |
0.477 (1.00) |
0.0125 (1.00) |
0.425 (1.00) |
0.214 (1.00) |
0.639 (1.00) |
1 (1.00) |
0.734 (1.00) |
0.159 (1.00) |
0.239 (1.00) |
0.655 (1.00) |
0.618 (1.00) |
| 11P LOSS MUTATION ANALYSIS | 40 (13%) | 265 |
0.113 (1.00) |
0.903 (1.00) |
0.778 (1.00) |
0.267 (1.00) |
0.892 (1.00) |
0.115 (1.00) |
0.607 (1.00) |
0.00401 (1.00) |
1 (1.00) |
0.0703 (1.00) |
0.34 (1.00) |
| 11Q LOSS MUTATION ANALYSIS | 37 (12%) | 268 |
0.144 (1.00) |
0.391 (1.00) |
0.176 (1.00) |
0.681 (1.00) |
0.31 (1.00) |
0.107 (1.00) |
0.281 (1.00) |
0.322 (1.00) |
0.599 (1.00) |
0.181 (1.00) |
0.197 (1.00) |
| 12P LOSS MUTATION ANALYSIS | 38 (12%) | 267 |
0.571 (1.00) |
0.148 (1.00) |
0.051 (1.00) |
0.0761 (1.00) |
0.0357 (1.00) |
0.631 (1.00) |
0.479 (1.00) |
0.0198 (1.00) |
1 (1.00) |
0.366 (1.00) |
0.537 (1.00) |
| 12Q LOSS MUTATION ANALYSIS | 29 (10%) | 276 |
0.673 (1.00) |
0.206 (1.00) |
0.811 (1.00) |
0.389 (1.00) |
0.242 (1.00) |
0.262 (1.00) |
0.842 (1.00) |
0.417 (1.00) |
0.507 (1.00) |
0.726 (1.00) |
0.714 (1.00) |
| 13Q LOSS MUTATION ANALYSIS | 29 (10%) | 276 |
0.227 (1.00) |
0.491 (1.00) |
0.587 (1.00) |
1 (1.00) |
0.647 (1.00) |
0.0615 (1.00) |
0.319 (1.00) |
0.923 (1.00) |
0.136 (1.00) |
0.0677 (1.00) |
0.46 (1.00) |
| 14Q LOSS MUTATION ANALYSIS | 71 (23%) | 234 |
0.966 (1.00) |
0.284 (1.00) |
0.088 (1.00) |
0.211 (1.00) |
0.306 (1.00) |
0.00947 (1.00) |
0.89 (1.00) |
0.957 (1.00) |
0.666 (1.00) |
0.144 (1.00) |
0.682 (1.00) |
| 15Q LOSS MUTATION ANALYSIS | 56 (18%) | 249 |
0.895 (1.00) |
0.188 (1.00) |
0.721 (1.00) |
0.0109 (1.00) |
0.767 (1.00) |
0.225 (1.00) |
0.227 (1.00) |
0.000754 (0.653) |
0.0233 (1.00) |
0.665 (1.00) |
0.189 (1.00) |
| 16P LOSS MUTATION ANALYSIS | 60 (20%) | 245 |
0.223 (1.00) |
0.00604 (1.00) |
0.598 (1.00) |
0.467 (1.00) |
0.232 (1.00) |
0.538 (1.00) |
0.883 (1.00) |
0.111 (1.00) |
0.627 (1.00) |
0.63 (1.00) |
0.576 (1.00) |
| 16Q LOSS MUTATION ANALYSIS | 70 (23%) | 235 |
0.117 (1.00) |
0.125 (1.00) |
0.386 (1.00) |
0.436 (1.00) |
0.707 (1.00) |
0.14 (1.00) |
0.33 (1.00) |
0.0547 (1.00) |
0.2 (1.00) |
0.526 (1.00) |
0.979 (1.00) |
| 17P LOSS MUTATION ANALYSIS | 103 (34%) | 202 |
0.277 (1.00) |
0.787 (1.00) |
0.626 (1.00) |
0.103 (1.00) |
0.881 (1.00) |
0.706 (1.00) |
0.322 (1.00) |
0.016 (1.00) |
0.0459 (1.00) |
0.158 (1.00) |
0.209 (1.00) |
| 17Q LOSS MUTATION ANALYSIS | 45 (15%) | 260 |
0.902 (1.00) |
0.48 (1.00) |
0.417 (1.00) |
0.555 (1.00) |
0.203 (1.00) |
0.524 (1.00) |
0.414 (1.00) |
0.399 (1.00) |
0.276 (1.00) |
1 (1.00) |
0.763 (1.00) |
| 18P LOSS MUTATION ANALYSIS | 79 (26%) | 226 |
0.547 (1.00) |
0.773 (1.00) |
0.387 (1.00) |
0.451 (1.00) |
0.952 (1.00) |
0.902 (1.00) |
0.504 (1.00) |
0.536 (1.00) |
0.196 (1.00) |
0.838 (1.00) |
0.203 (1.00) |
| 18Q LOSS MUTATION ANALYSIS | 102 (33%) | 203 |
0.95 (1.00) |
0.381 (1.00) |
0.249 (1.00) |
0.0401 (1.00) |
0.857 (1.00) |
0.802 (1.00) |
0.321 (1.00) |
0.721 (1.00) |
1 (1.00) |
0.811 (1.00) |
0.0847 (1.00) |
| 19P LOSS MUTATION ANALYSIS | 70 (23%) | 235 |
0.275 (1.00) |
0.216 (1.00) |
0.659 (1.00) |
0.89 (1.00) |
0.776 (1.00) |
0.893 (1.00) |
0.265 (1.00) |
0.205 (1.00) |
0.2 (1.00) |
0.802 (1.00) |
0.202 (1.00) |
| 19Q LOSS MUTATION ANALYSIS | 53 (17%) | 252 |
0.454 (1.00) |
0.0613 (1.00) |
0.832 (1.00) |
0.704 (1.00) |
0.55 (1.00) |
0.932 (1.00) |
0.645 (1.00) |
0.028 (1.00) |
0.35 (1.00) |
0.452 (1.00) |
0.524 (1.00) |
| 20P LOSS MUTATION ANALYSIS | 17 (6%) | 288 |
0.4 (1.00) |
0.342 (1.00) |
0.286 (1.00) |
1 (1.00) |
0.505 (1.00) |
0.00596 (1.00) |
0.0382 (1.00) |
0.694 (1.00) |
0.0521 (1.00) |
0.192 (1.00) |
0.966 (1.00) |
| 21Q LOSS MUTATION ANALYSIS | 105 (34%) | 200 |
0.779 (1.00) |
0.0254 (1.00) |
0.218 (1.00) |
0.0167 (1.00) |
0.964 (1.00) |
0.705 (1.00) |
0.0494 (1.00) |
0.968 (1.00) |
0.238 (1.00) |
0.94 (1.00) |
0.647 (1.00) |
| 22Q LOSS MUTATION ANALYSIS | 90 (30%) | 215 |
0.345 (1.00) |
0.493 (1.00) |
0.491 (1.00) |
0.0413 (1.00) |
0.679 (1.00) |
0.365 (1.00) |
0.52 (1.00) |
0.361 (1.00) |
0.0254 (1.00) |
0.483 (1.00) |
0.151 (1.00) |
| XQ LOSS MUTATION ANALYSIS | 38 (12%) | 267 |
0.892 (1.00) |
0.941 (1.00) |
0.739 (1.00) |
0.106 (1.00) |
0.6 (1.00) |
0.689 (1.00) |
0.00132 (1.00) |
0.795 (1.00) |
0.212 (1.00) |
0.00948 (1.00) |
0.462 (1.00) |
'16P GAIN MUTATION STATUS' versus 'PATHOLOGY.M.STAGE'
P value = 9.04e-05 (Fisher's exact test), Q value = 0.078
Table S1. Gene #28: '16P GAIN MUTATION STATUS' versus Clinical Feature #6: 'PATHOLOGY.M.STAGE'
| nPatients | M0 | M1 | MX |
|---|---|---|---|
| ALL | 271 | 20 | 14 |
| 16P GAIN MUTATED | 29 | 6 | 7 |
| 16P GAIN WILD-TYPE | 242 | 14 | 7 |
Figure S1. Get High-res Image Gene #28: '16P GAIN MUTATION STATUS' versus Clinical Feature #6: 'PATHOLOGY.M.STAGE'
'16Q GAIN MUTATION STATUS' versus 'PATHOLOGY.M.STAGE'
P value = 2.11e-06 (Fisher's exact test), Q value = 0.0018
Table S2. Gene #29: '16Q GAIN MUTATION STATUS' versus Clinical Feature #6: 'PATHOLOGY.M.STAGE'
| nPatients | M0 | M1 | MX |
|---|---|---|---|
| ALL | 271 | 20 | 14 |
| 16Q GAIN MUTATED | 19 | 6 | 7 |
| 16Q GAIN WILD-TYPE | 252 | 14 | 7 |
Figure S2. Get High-res Image Gene #29: '16Q GAIN MUTATION STATUS' versus Clinical Feature #6: 'PATHOLOGY.M.STAGE'
'XQ GAIN MUTATION STATUS' versus 'NUMBER.OF.LYMPH.NODES'
P value = 0.000261 (t-test), Q value = 0.23
Table S3. Gene #40: 'XQ GAIN MUTATION STATUS' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'
| nPatients | Mean (Std.Dev) | |
|---|---|---|
| ALL | 267 | 5.0 (7.5) |
| XQ GAIN MUTATED | 38 | 2.4 (3.7) |
| XQ GAIN WILD-TYPE | 229 | 5.4 (7.9) |
Figure S3. Get High-res Image Gene #40: 'XQ GAIN MUTATION STATUS' versus Clinical Feature #11: 'NUMBER.OF.LYMPH.NODES'
Methods & Data
Input
-
Copy number data file = transformed.cor.cli.txt
-
Clinical data file = STAD-TP.clin.merged.picked.txt
-
Number of patients = 305
-
Number of significantly arm-level cnvs = 79
-
Number of selected clinical features = 11
-
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)
Copyright © 2013
Broad Institute TCGA GDAC as part of the TCGA Research Network.
All rights reserved.