This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.
Testing the association between copy number variation 57 arm-level events and 14 clinical features across 184 patients, 23 significant findings detected with Q value < 0.25.
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4q gain cnv correlated to 'GLEASON_SCORE_SECONDARY'.
-
5p gain cnv correlated to 'GLEASON_SCORE_SECONDARY'.
-
9p gain cnv correlated to 'PSA_VALUE'.
-
9q gain cnv correlated to 'PSA_VALUE'.
-
12q gain cnv correlated to 'GLEASON_SCORE_PRIMARY' and 'PSA_VALUE'.
-
17q gain cnv correlated to 'PSA_VALUE'.
-
18p gain cnv correlated to 'PSA_VALUE'.
-
18q gain cnv correlated to 'PSA_VALUE'.
-
19q gain cnv correlated to 'GLEASON_SCORE_SECONDARY'.
-
20q gain cnv correlated to 'GLEASON_SCORE_PRIMARY' and 'PSA_VALUE'.
-
21q gain cnv correlated to 'GLEASON_SCORE_PRIMARY'.
-
4p loss cnv correlated to 'GLEASON_SCORE_PRIMARY'.
-
4q loss cnv correlated to 'GLEASON_SCORE_PRIMARY'.
-
6p loss cnv correlated to 'GLEASON_SCORE_PRIMARY'.
-
9p loss cnv correlated to 'PSA_VALUE'.
-
12q loss cnv correlated to 'PSA_VALUE'.
-
17q loss cnv correlated to 'GLEASON_SCORE_PRIMARY'.
-
18q loss cnv correlated to 'GLEASON_SCORE'.
-
19p loss cnv correlated to 'PSA_RESULT_PREOP'.
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19q loss cnv correlated to 'PSA_RESULT_PREOP'.
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20q loss cnv correlated to 'GLEASON_SCORE_PRIMARY'.
Table 1. Get Full Table Overview of the association between significant copy number variation of 57 arm-level events and 14 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 23 significant findings detected.
Clinical Features |
Time to Death |
AGE |
PATHOLOGY T STAGE |
PATHOLOGY N STAGE |
COMPLETENESS OF RESECTION |
NUMBER OF LYMPH NODES |
GLEASON SCORE COMBINED |
GLEASON SCORE PRIMARY |
GLEASON SCORE SECONDARY |
GLEASON SCORE |
PSA RESULT PREOP |
DAYS TO PREOP PSA |
PSA VALUE |
DAYS TO PSA |
||
nCNV (%) | nWild-Type | logrank test | t-test | Fisher's exact test | Fisher's exact test | Fisher's exact test | t-test | t-test | t-test | t-test | t-test | t-test | t-test | t-test | t-test | |
12q gain | 3 (2%) | 181 |
100 (1.00) |
0.182 (1.00) |
1 (1.00) |
0.286 (1.00) |
0.546 (1.00) |
0.703 (1.00) |
0.858 (1.00) |
1.76e-26 (1.37e-23) |
0.295 (1.00) |
0.95 (1.00) |
0.103 (1.00) |
0.177 (1.00) |
0.000125 (0.0966) |
0.327 (1.00) |
20q gain | 5 (3%) | 179 |
100 (1.00) |
0.0618 (1.00) |
0.0219 (1.00) |
1 (1.00) |
0.355 (1.00) |
0.000785 (0.594) |
0.327 (1.00) |
1.37e-26 (1.08e-23) |
0.99 (1.00) |
0.135 (1.00) |
0.492 (1.00) |
0.62 (1.00) |
0.000273 (0.209) |
0.0846 (1.00) |
4q gain | 3 (2%) | 181 |
100 (1.00) |
0.241 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.000787 (0.594) |
0.858 (1.00) |
0.713 (1.00) |
8.13e-06 (0.00633) |
0.95 (1.00) |
0.935 (1.00) |
0.662 (1.00) |
0.000884 (0.659) |
0.156 (1.00) |
5p gain | 3 (2%) | 181 |
100 (1.00) |
0.719 (1.00) |
0.313 (1.00) |
0.286 (1.00) |
0.164 (1.00) |
0.703 (1.00) |
0.245 (1.00) |
0.32 (1.00) |
8.13e-06 (0.00633) |
0.0498 (1.00) |
0.43 (1.00) |
0.897 (1.00) |
||
9p gain | 7 (4%) | 177 |
100 (1.00) |
0.212 (1.00) |
0.557 (1.00) |
0.0265 (1.00) |
0.65 (1.00) |
0.231 (1.00) |
0.596 (1.00) |
0.636 (1.00) |
0.811 (1.00) |
0.196 (1.00) |
0.181 (1.00) |
0.439 (1.00) |
0.00018 (0.139) |
0.778 (1.00) |
9q gain | 14 (8%) | 170 |
100 (1.00) |
0.393 (1.00) |
0.0324 (1.00) |
0.0055 (1.00) |
0.334 (1.00) |
0.143 (1.00) |
0.0385 (1.00) |
0.0111 (1.00) |
0.477 (1.00) |
0.0388 (1.00) |
0.1 (1.00) |
0.267 (1.00) |
0.000249 (0.192) |
0.847 (1.00) |
17q gain | 4 (2%) | 180 |
100 (1.00) |
0.631 (1.00) |
0.22 (1.00) |
0.0556 (1.00) |
0.607 (1.00) |
0.316 (1.00) |
0.472 (1.00) |
0.341 (1.00) |
0.872 (1.00) |
0.418 (1.00) |
0.749 (1.00) |
0.591 (1.00) |
0.000225 (0.174) |
0.024 (1.00) |
18p gain | 7 (4%) | 177 |
100 (1.00) |
0.371 (1.00) |
0.286 (1.00) |
0.122 (1.00) |
1 (1.00) |
0.518 (1.00) |
0.596 (1.00) |
0.831 (1.00) |
0.37 (1.00) |
0.402 (1.00) |
0.914 (1.00) |
0.359 (1.00) |
0.000202 (0.156) |
0.796 (1.00) |
18q gain | 3 (2%) | 181 |
100 (1.00) |
0.332 (1.00) |
0.313 (1.00) |
1 (1.00) |
1 (1.00) |
0.000787 (0.594) |
0.604 (1.00) |
0.615 (1.00) |
0.751 (1.00) |
0.641 (1.00) |
0.0329 (1.00) |
0.368 (1.00) |
0.000281 (0.215) |
0.887 (1.00) |
19q gain | 3 (2%) | 181 |
100 (1.00) |
0.876 (1.00) |
0.0413 (1.00) |
0.286 (1.00) |
0.546 (1.00) |
0.703 (1.00) |
0.0219 (1.00) |
0.117 (1.00) |
6.74e-67 (5.31e-64) |
0.0226 (1.00) |
0.546 (1.00) |
0.8 (1.00) |
0.99 (1.00) |
0.416 (1.00) |
21q gain | 3 (2%) | 181 |
100 (1.00) |
0.0813 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.000787 (0.594) |
0.245 (1.00) |
1.76e-26 (1.37e-23) |
0.497 (1.00) |
0.258 (1.00) |
0.0349 (1.00) |
0.308 (1.00) |
0.000485 (0.369) |
0.393 (1.00) |
4p loss | 4 (2%) | 180 |
100 (1.00) |
0.886 (1.00) |
0.667 (1.00) |
0.00372 (1.00) |
0.164 (1.00) |
0.122 (1.00) |
0.00728 (1.00) |
1.55e-26 (1.22e-23) |
0.0277 (1.00) |
0.00782 (1.00) |
0.302 (1.00) |
0.722 (1.00) |
||
4q loss | 3 (2%) | 181 |
100 (1.00) |
0.77 (1.00) |
1 (1.00) |
0.286 (1.00) |
0.703 (1.00) |
0.0471 (1.00) |
1.76e-26 (1.37e-23) |
0.114 (1.00) |
0.0498 (1.00) |
0.496 (1.00) |
0.276 (1.00) |
|||
6p loss | 7 (4%) | 177 |
100 (1.00) |
0.122 (1.00) |
0.167 (1.00) |
0.0265 (1.00) |
0.65 (1.00) |
0.179 (1.00) |
0.157 (1.00) |
1.06e-26 (8.33e-24) |
0.785 (1.00) |
0.0437 (1.00) |
0.233 (1.00) |
0.505 (1.00) |
0.363 (1.00) |
0.661 (1.00) |
9p loss | 8 (4%) | 176 |
100 (1.00) |
0.896 (1.00) |
0.0591 (1.00) |
0.0396 (1.00) |
1 (1.00) |
0.266 (1.00) |
0.0592 (1.00) |
0.0224 (1.00) |
0.282 (1.00) |
0.0487 (1.00) |
0.457 (1.00) |
0.668 (1.00) |
0.000256 (0.197) |
0.723 (1.00) |
12q loss | 7 (4%) | 177 |
100 (1.00) |
0.199 (1.00) |
0.219 (1.00) |
0.161 (1.00) |
1 (1.00) |
0.615 (1.00) |
0.17 (1.00) |
0.179 (1.00) |
0.329 (1.00) |
0.109 (1.00) |
0.873 (1.00) |
0.612 (1.00) |
0.00027 (0.207) |
0.67 (1.00) |
17q loss | 4 (2%) | 180 |
100 (1.00) |
0.206 (1.00) |
0.667 (1.00) |
0.363 (1.00) |
0.259 (1.00) |
0.821 (1.00) |
0.126 (1.00) |
1.55e-26 (1.22e-23) |
0.402 (1.00) |
0.138 (1.00) |
0.6 (1.00) |
0.234 (1.00) |
0.982 (1.00) |
0.958 (1.00) |
18q loss | 35 (19%) | 149 |
100 (1.00) |
0.631 (1.00) |
0.211 (1.00) |
0.0237 (1.00) |
0.0705 (1.00) |
0.171 (1.00) |
0.00124 (0.926) |
0.0473 (1.00) |
0.000697 (0.529) |
0.000259 (0.199) |
0.139 (1.00) |
0.979 (1.00) |
0.388 (1.00) |
0.202 (1.00) |
19p loss | 4 (2%) | 180 |
100 (1.00) |
0.00295 (1.00) |
0.401 (1.00) |
1 (1.00) |
0.607 (1.00) |
0.000786 (0.594) |
0.667 (1.00) |
0.93 (1.00) |
0.642 (1.00) |
0.724 (1.00) |
2.74e-05 (0.0213) |
0.196 (1.00) |
0.735 (1.00) |
0.153 (1.00) |
19q loss | 4 (2%) | 180 |
100 (1.00) |
0.00295 (1.00) |
0.401 (1.00) |
1 (1.00) |
0.607 (1.00) |
0.000786 (0.594) |
0.667 (1.00) |
0.93 (1.00) |
0.642 (1.00) |
0.724 (1.00) |
2.74e-05 (0.0213) |
0.196 (1.00) |
0.735 (1.00) |
0.153 (1.00) |
20q loss | 4 (2%) | 180 |
100 (1.00) |
0.362 (1.00) |
0.142 (1.00) |
1 (1.00) |
0.259 (1.00) |
0.000786 (0.594) |
0.667 (1.00) |
1.55e-26 (1.22e-23) |
0.592 (1.00) |
0.724 (1.00) |
0.33 (1.00) |
0.556 (1.00) |
0.0183 (1.00) |
0.528 (1.00) |
1p gain | 5 (3%) | 179 |
100 (1.00) |
0.956 (1.00) |
0.0219 (1.00) |
0.432 (1.00) |
1 (1.00) |
0.957 (1.00) |
0.327 (1.00) |
0.169 (1.00) |
0.661 (1.00) |
0.135 (1.00) |
0.0723 (1.00) |
0.469 (1.00) |
0.572 (1.00) |
0.862 (1.00) |
1q gain | 8 (4%) | 176 |
100 (1.00) |
0.886 (1.00) |
0.0591 (1.00) |
0.599 (1.00) |
0.687 (1.00) |
0.636 (1.00) |
0.213 (1.00) |
0.0116 (1.00) |
0.816 (1.00) |
0.0993 (1.00) |
0.0842 (1.00) |
0.581 (1.00) |
0.739 (1.00) |
0.398 (1.00) |
3p gain | 16 (9%) | 168 |
100 (1.00) |
0.0311 (1.00) |
0.00642 (1.00) |
0.678 (1.00) |
1 (1.00) |
0.504 (1.00) |
0.0396 (1.00) |
0.042 (1.00) |
0.246 (1.00) |
0.00773 (1.00) |
0.596 (1.00) |
0.591 (1.00) |
0.266 (1.00) |
0.163 (1.00) |
3q gain | 20 (11%) | 164 |
100 (1.00) |
0.0102 (1.00) |
0.00513 (1.00) |
0.447 (1.00) |
0.693 (1.00) |
0.439 (1.00) |
0.0728 (1.00) |
0.0182 (1.00) |
0.717 (1.00) |
0.0194 (1.00) |
0.195 (1.00) |
0.442 (1.00) |
0.00473 (1.00) |
0.0674 (1.00) |
4p gain | 4 (2%) | 180 |
100 (1.00) |
0.0813 (1.00) |
0.667 (1.00) |
1 (1.00) |
0.607 (1.00) |
0.000786 (0.594) |
0.379 (1.00) |
0.93 (1.00) |
0.158 (1.00) |
0.418 (1.00) |
0.947 (1.00) |
0.481 (1.00) |
0.00055 (0.418) |
0.821 (1.00) |
7p gain | 33 (18%) | 151 |
100 (1.00) |
0.176 (1.00) |
0.163 (1.00) |
0.195 (1.00) |
0.1 (1.00) |
0.249 (1.00) |
0.0425 (1.00) |
0.131 (1.00) |
0.138 (1.00) |
0.0511 (1.00) |
0.097 (1.00) |
0.336 (1.00) |
0.453 (1.00) |
0.412 (1.00) |
7q gain | 30 (16%) | 154 |
100 (1.00) |
0.338 (1.00) |
0.183 (1.00) |
0.74 (1.00) |
0.137 (1.00) |
0.338 (1.00) |
0.0644 (1.00) |
0.174 (1.00) |
0.168 (1.00) |
0.0728 (1.00) |
0.203 (1.00) |
0.213 (1.00) |
0.596 (1.00) |
0.275 (1.00) |
8p gain | 21 (11%) | 163 |
100 (1.00) |
0.188 (1.00) |
0.193 (1.00) |
0.243 (1.00) |
0.575 (1.00) |
0.985 (1.00) |
0.00388 (1.00) |
0.0511 (1.00) |
0.0147 (1.00) |
0.00317 (1.00) |
0.0816 (1.00) |
0.383 (1.00) |
0.323 (1.00) |
0.191 (1.00) |
8q gain | 34 (18%) | 150 |
100 (1.00) |
0.839 (1.00) |
0.264 (1.00) |
0.335 (1.00) |
0.576 (1.00) |
0.665 (1.00) |
0.00431 (1.00) |
0.00274 (1.00) |
0.274 (1.00) |
0.00886 (1.00) |
0.158 (1.00) |
0.106 (1.00) |
0.909 (1.00) |
0.298 (1.00) |
10p gain | 6 (3%) | 178 |
100 (1.00) |
0.661 (1.00) |
0.739 (1.00) |
1 (1.00) |
0.0785 (1.00) |
0.000785 (0.594) |
0.515 (1.00) |
0.53 (1.00) |
0.0688 (1.00) |
0.173 (1.00) |
0.844 (1.00) |
0.18 (1.00) |
0.488 (1.00) |
0.0537 (1.00) |
10q gain | 7 (4%) | 177 |
100 (1.00) |
0.551 (1.00) |
0.557 (1.00) |
0.494 (1.00) |
0.0475 (1.00) |
0.438 (1.00) |
0.596 (1.00) |
0.744 (1.00) |
0.672 (1.00) |
0.211 (1.00) |
0.545 (1.00) |
0.7 (1.00) |
0.349 (1.00) |
0.235 (1.00) |
11p gain | 8 (4%) | 176 |
100 (1.00) |
0.967 (1.00) |
0.0591 (1.00) |
0.201 (1.00) |
0.456 (1.00) |
0.718 (1.00) |
0.104 (1.00) |
0.0196 (1.00) |
0.534 (1.00) |
0.0672 (1.00) |
0.785 (1.00) |
0.313 (1.00) |
0.000354 (0.271) |
0.555 (1.00) |
11q gain | 8 (4%) | 176 |
100 (1.00) |
0.967 (1.00) |
0.0591 (1.00) |
0.201 (1.00) |
0.456 (1.00) |
0.718 (1.00) |
0.104 (1.00) |
0.0196 (1.00) |
0.534 (1.00) |
0.0672 (1.00) |
0.785 (1.00) |
0.313 (1.00) |
0.000354 (0.271) |
0.555 (1.00) |
16p gain | 9 (5%) | 175 |
100 (1.00) |
0.361 (1.00) |
0.00395 (1.00) |
0.201 (1.00) |
0.732 (1.00) |
0.718 (1.00) |
0.0523 (1.00) |
0.00996 (1.00) |
0.478 (1.00) |
0.063 (1.00) |
0.696 (1.00) |
0.989 (1.00) |
0.574 (1.00) |
0.684 (1.00) |
16q gain | 3 (2%) | 181 |
100 (1.00) |
0.147 (1.00) |
0.313 (1.00) |
1 (1.00) |
1 (1.00) |
0.604 (1.00) |
0.117 (1.00) |
0.295 (1.00) |
0.641 (1.00) |
0.12 (1.00) |
0.56 (1.00) |
|||
1p loss | 4 (2%) | 180 |
100 (1.00) |
0.843 (1.00) |
0.667 (1.00) |
1 (1.00) |
1 (1.00) |
0.000786 (0.594) |
0.285 (1.00) |
0.341 (1.00) |
0.402 (1.00) |
0.309 (1.00) |
0.226 (1.00) |
0.251 (1.00) |
0.784 (1.00) |
0.505 (1.00) |
5p loss | 3 (2%) | 181 |
100 (1.00) |
0.738 (1.00) |
0.0413 (1.00) |
0.0297 (1.00) |
0.546 (1.00) |
0.28 (1.00) |
0.248 (1.00) |
0.117 (1.00) |
0.497 (1.00) |
0.258 (1.00) |
0.533 (1.00) |
0.569 (1.00) |
0.541 (1.00) |
0.468 (1.00) |
5q loss | 5 (3%) | 179 |
100 (1.00) |
0.63 (1.00) |
0.0999 (1.00) |
0.00868 (1.00) |
0.355 (1.00) |
0.167 (1.00) |
0.0129 (1.00) |
0.0167 (1.00) |
0.0625 (1.00) |
0.00471 (1.00) |
0.78 (1.00) |
0.694 (1.00) |
0.731 (1.00) |
0.551 (1.00) |
6q loss | 12 (7%) | 172 |
100 (1.00) |
0.907 (1.00) |
0.33 (1.00) |
0.0251 (1.00) |
1 (1.00) |
0.127 (1.00) |
0.0303 (1.00) |
0.00618 (1.00) |
0.331 (1.00) |
0.00898 (1.00) |
0.154 (1.00) |
0.639 (1.00) |
0.417 (1.00) |
0.514 (1.00) |
8p loss | 59 (32%) | 125 |
100 (1.00) |
0.17 (1.00) |
0.0254 (1.00) |
0.42 (1.00) |
0.122 (1.00) |
0.13 (1.00) |
0.316 (1.00) |
0.0425 (1.00) |
0.00273 (1.00) |
0.521 (1.00) |
0.196 (1.00) |
0.203 (1.00) |
0.329 (1.00) |
0.0927 (1.00) |
8q loss | 10 (5%) | 174 |
100 (1.00) |
0.0507 (1.00) |
0.0386 (1.00) |
0.0739 (1.00) |
0.542 (1.00) |
0.153 (1.00) |
0.0635 (1.00) |
0.122 (1.00) |
0.204 (1.00) |
0.0577 (1.00) |
0.364 (1.00) |
0.422 (1.00) |
0.247 (1.00) |
0.917 (1.00) |
9q loss | 4 (2%) | 180 |
100 (1.00) |
0.0286 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
0.000786 (0.594) |
0.285 (1.00) |
0.93 (1.00) |
0.0859 (1.00) |
0.0921 (1.00) |
0.987 (1.00) |
0.239 (1.00) |
0.000475 (0.362) |
0.49 (1.00) |
10p loss | 13 (7%) | 171 |
100 (1.00) |
0.87 (1.00) |
0.0044 (1.00) |
0.0339 (1.00) |
0.43 (1.00) |
0.256 (1.00) |
0.0226 (1.00) |
0.00421 (1.00) |
0.354 (1.00) |
0.0101 (1.00) |
0.225 (1.00) |
0.589 (1.00) |
0.269 (1.00) |
0.11 (1.00) |
10q loss | 15 (8%) | 169 |
100 (1.00) |
0.788 (1.00) |
0.0892 (1.00) |
0.0112 (1.00) |
0.616 (1.00) |
0.195 (1.00) |
0.00587 (1.00) |
0.0231 (1.00) |
0.026 (1.00) |
0.00162 (1.00) |
0.274 (1.00) |
0.619 (1.00) |
0.0302 (1.00) |
0.177 (1.00) |
12p loss | 17 (9%) | 167 |
100 (1.00) |
0.832 (1.00) |
0.45 (1.00) |
0.00344 (1.00) |
0.539 (1.00) |
0.135 (1.00) |
0.0887 (1.00) |
0.0366 (1.00) |
0.583 (1.00) |
0.0749 (1.00) |
0.463 (1.00) |
0.354 (1.00) |
0.819 (1.00) |
0.519 (1.00) |
13q loss | 28 (15%) | 156 |
100 (1.00) |
0.0895 (1.00) |
0.863 (1.00) |
0.0288 (1.00) |
0.878 (1.00) |
0.189 (1.00) |
0.0201 (1.00) |
0.12 (1.00) |
0.0791 (1.00) |
0.00584 (1.00) |
0.355 (1.00) |
0.945 (1.00) |
0.639 (1.00) |
0.723 (1.00) |
14q loss | 9 (5%) | 175 |
100 (1.00) |
0.349 (1.00) |
0.0821 (1.00) |
0.243 (1.00) |
0.456 (1.00) |
0.543 (1.00) |
0.0249 (1.00) |
0.00996 (1.00) |
0.24 (1.00) |
0.0303 (1.00) |
0.391 (1.00) |
0.43 (1.00) |
0.159 (1.00) |
0.61 (1.00) |
15q loss | 12 (7%) | 172 |
100 (1.00) |
0.835 (1.00) |
0.0127 (1.00) |
0.00362 (1.00) |
1 (1.00) |
0.0738 (1.00) |
0.00802 (1.00) |
0.00102 (0.757) |
0.209 (1.00) |
0.00717 (1.00) |
0.457 (1.00) |
0.44 (1.00) |
0.339 (1.00) |
0.669 (1.00) |
16p loss | 14 (8%) | 170 |
100 (1.00) |
0.989 (1.00) |
0.855 (1.00) |
0.364 (1.00) |
0.267 (1.00) |
0.000778 (0.59) |
0.254 (1.00) |
0.381 (1.00) |
0.406 (1.00) |
0.114 (1.00) |
0.396 (1.00) |
0.197 (1.00) |
0.0137 (1.00) |
0.238 (1.00) |
16q loss | 40 (22%) | 144 |
100 (1.00) |
0.814 (1.00) |
0.204 (1.00) |
0.126 (1.00) |
0.486 (1.00) |
0.26 (1.00) |
0.00641 (1.00) |
0.00513 (1.00) |
0.25 (1.00) |
0.00252 (1.00) |
0.0324 (1.00) |
0.402 (1.00) |
0.707 (1.00) |
0.516 (1.00) |
17p loss | 27 (15%) | 157 |
100 (1.00) |
0.891 (1.00) |
0.0878 (1.00) |
0.00821 (1.00) |
1 (1.00) |
0.0894 (1.00) |
0.00328 (1.00) |
0.00513 (1.00) |
0.147 (1.00) |
0.00237 (1.00) |
0.106 (1.00) |
0.498 (1.00) |
0.142 (1.00) |
0.72 (1.00) |
18p loss | 24 (13%) | 160 |
100 (1.00) |
0.605 (1.00) |
0.122 (1.00) |
0.0721 (1.00) |
0.18 (1.00) |
0.151 (1.00) |
0.00852 (1.00) |
0.0238 (1.00) |
0.0444 (1.00) |
0.00208 (1.00) |
0.192 (1.00) |
0.552 (1.00) |
0.888 (1.00) |
0.218 (1.00) |
20p loss | 7 (4%) | 177 |
100 (1.00) |
0.539 (1.00) |
0.0634 (1.00) |
0.494 (1.00) |
0.65 (1.00) |
0.674 (1.00) |
0.958 (1.00) |
0.0311 (1.00) |
0.252 (1.00) |
0.947 (1.00) |
0.232 (1.00) |
0.594 (1.00) |
0.00488 (1.00) |
0.417 (1.00) |
21q loss | 8 (4%) | 176 |
100 (1.00) |
0.67 (1.00) |
0.121 (1.00) |
0.00251 (1.00) |
1 (1.00) |
0.1 (1.00) |
0.114 (1.00) |
0.0791 (1.00) |
0.3 (1.00) |
0.133 (1.00) |
0.143 (1.00) |
0.394 (1.00) |
0.793 (1.00) |
0.893 (1.00) |
22q loss | 16 (9%) | 168 |
100 (1.00) |
0.911 (1.00) |
0.0562 (1.00) |
0.0112 (1.00) |
0.509 (1.00) |
0.187 (1.00) |
0.00236 (1.00) |
0.000427 (0.326) |
0.156 (1.00) |
0.00351 (1.00) |
0.765 (1.00) |
0.202 (1.00) |
0.543 (1.00) |
0.775 (1.00) |
xq loss | 10 (5%) | 174 |
100 (1.00) |
0.859 (1.00) |
0.276 (1.00) |
0.0739 (1.00) |
1 (1.00) |
0.233 (1.00) |
0.0293 (1.00) |
0.0045 (1.00) |
0.425 (1.00) |
0.0267 (1.00) |
0.386 (1.00) |
0.135 (1.00) |
0.915 (1.00) |
0.542 (1.00) |
P value = 8.13e-06 (t-test), Q value = 0.0063
Table S1. Gene #6: '4q gain' versus Clinical Feature #9: 'GLEASON_SCORE_SECONDARY'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 184 | 3.8 (0.6) |
4Q GAIN MUTATED | 3 | 4.0 (0.0) |
4Q GAIN WILD-TYPE | 181 | 3.8 (0.6) |
Figure S1. Get High-res Image Gene #6: '4q gain' versus Clinical Feature #9: 'GLEASON_SCORE_SECONDARY'

P value = 8.13e-06 (t-test), Q value = 0.0063
Table S2. Gene #7: '5p gain' versus Clinical Feature #9: 'GLEASON_SCORE_SECONDARY'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 184 | 3.8 (0.6) |
5P GAIN MUTATED | 3 | 4.0 (0.0) |
5P GAIN WILD-TYPE | 181 | 3.8 (0.6) |
Figure S2. Get High-res Image Gene #7: '5p gain' versus Clinical Feature #9: 'GLEASON_SCORE_SECONDARY'

P value = 0.00018 (t-test), Q value = 0.14
Table S3. Gene #12: '9p gain' versus Clinical Feature #13: 'PSA_VALUE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 162 | 1.4 (4.5) |
9P GAIN MUTATED | 6 | 0.1 (0.1) |
9P GAIN WILD-TYPE | 156 | 1.5 (4.6) |
Figure S3. Get High-res Image Gene #12: '9p gain' versus Clinical Feature #13: 'PSA_VALUE'

P value = 0.000249 (t-test), Q value = 0.19
Table S4. Gene #13: '9q gain' versus Clinical Feature #13: 'PSA_VALUE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 162 | 1.4 (4.5) |
9Q GAIN MUTATED | 11 | 0.1 (0.1) |
9Q GAIN WILD-TYPE | 151 | 1.5 (4.6) |
Figure S4. Get High-res Image Gene #13: '9q gain' versus Clinical Feature #13: 'PSA_VALUE'

P value = 1.76e-26 (t-test), Q value = 1.4e-23
Table S5. Gene #18: '12q gain' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 184 | 3.5 (0.6) |
12Q GAIN MUTATED | 3 | 4.0 (0.0) |
12Q GAIN WILD-TYPE | 181 | 3.5 (0.6) |
Figure S5. Get High-res Image Gene #18: '12q gain' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

P value = 0.000125 (t-test), Q value = 0.097
Table S6. Gene #18: '12q gain' versus Clinical Feature #13: 'PSA_VALUE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 162 | 1.4 (4.5) |
12Q GAIN MUTATED | 3 | 0.1 (0.0) |
12Q GAIN WILD-TYPE | 159 | 1.5 (4.5) |
Figure S6. Get High-res Image Gene #18: '12q gain' versus Clinical Feature #13: 'PSA_VALUE'

P value = 0.000225 (t-test), Q value = 0.17
Table S7. Gene #21: '17q gain' versus Clinical Feature #13: 'PSA_VALUE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 162 | 1.4 (4.5) |
17Q GAIN MUTATED | 4 | 0.1 (0.1) |
17Q GAIN WILD-TYPE | 158 | 1.5 (4.5) |
Figure S7. Get High-res Image Gene #21: '17q gain' versus Clinical Feature #13: 'PSA_VALUE'

P value = 0.000202 (t-test), Q value = 0.16
Table S8. Gene #22: '18p gain' versus Clinical Feature #13: 'PSA_VALUE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 162 | 1.4 (4.5) |
18P GAIN MUTATED | 6 | 0.1 (0.1) |
18P GAIN WILD-TYPE | 156 | 1.5 (4.6) |
Figure S8. Get High-res Image Gene #22: '18p gain' versus Clinical Feature #13: 'PSA_VALUE'

P value = 0.000281 (t-test), Q value = 0.22
Table S9. Gene #23: '18q gain' versus Clinical Feature #13: 'PSA_VALUE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 162 | 1.4 (4.5) |
18Q GAIN MUTATED | 3 | 0.1 (0.0) |
18Q GAIN WILD-TYPE | 159 | 1.5 (4.5) |
Figure S9. Get High-res Image Gene #23: '18q gain' versus Clinical Feature #13: 'PSA_VALUE'

P value = 6.74e-67 (t-test), Q value = 5.3e-64
Table S10. Gene #24: '19q gain' versus Clinical Feature #9: 'GLEASON_SCORE_SECONDARY'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 184 | 3.8 (0.6) |
19Q GAIN MUTATED | 3 | 5.0 (0.0) |
19Q GAIN WILD-TYPE | 181 | 3.8 (0.6) |
Figure S10. Get High-res Image Gene #24: '19q gain' versus Clinical Feature #9: 'GLEASON_SCORE_SECONDARY'

P value = 1.37e-26 (t-test), Q value = 1.1e-23
Table S11. Gene #25: '20q gain' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 184 | 3.5 (0.6) |
20Q GAIN MUTATED | 5 | 4.0 (0.0) |
20Q GAIN WILD-TYPE | 179 | 3.5 (0.6) |
Figure S11. Get High-res Image Gene #25: '20q gain' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

P value = 0.000273 (t-test), Q value = 0.21
Table S12. Gene #25: '20q gain' versus Clinical Feature #13: 'PSA_VALUE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 162 | 1.4 (4.5) |
20Q GAIN MUTATED | 5 | 0.1 (0.1) |
20Q GAIN WILD-TYPE | 157 | 1.5 (4.6) |
Figure S12. Get High-res Image Gene #25: '20q gain' versus Clinical Feature #13: 'PSA_VALUE'

P value = 1.76e-26 (t-test), Q value = 1.4e-23
Table S13. Gene #26: '21q gain' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 184 | 3.5 (0.6) |
21Q GAIN MUTATED | 3 | 4.0 (0.0) |
21Q GAIN WILD-TYPE | 181 | 3.5 (0.6) |
Figure S13. Get High-res Image Gene #26: '21q gain' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

P value = 1.55e-26 (t-test), Q value = 1.2e-23
Table S14. Gene #28: '4p loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 184 | 3.5 (0.6) |
4P LOSS MUTATED | 4 | 4.0 (0.0) |
4P LOSS WILD-TYPE | 180 | 3.5 (0.6) |
Figure S14. Get High-res Image Gene #28: '4p loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

P value = 1.76e-26 (t-test), Q value = 1.4e-23
Table S15. Gene #29: '4q loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 184 | 3.5 (0.6) |
4Q LOSS MUTATED | 3 | 4.0 (0.0) |
4Q LOSS WILD-TYPE | 181 | 3.5 (0.6) |
Figure S15. Get High-res Image Gene #29: '4q loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

P value = 1.06e-26 (t-test), Q value = 8.3e-24
Table S16. Gene #32: '6p loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 184 | 3.5 (0.6) |
6P LOSS MUTATED | 7 | 4.0 (0.0) |
6P LOSS WILD-TYPE | 177 | 3.5 (0.6) |
Figure S16. Get High-res Image Gene #32: '6p loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

P value = 0.000256 (t-test), Q value = 0.2
Table S17. Gene #36: '9p loss' versus Clinical Feature #13: 'PSA_VALUE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 162 | 1.4 (4.5) |
9P LOSS MUTATED | 7 | 0.1 (0.1) |
9P LOSS WILD-TYPE | 155 | 1.5 (4.6) |
Figure S17. Get High-res Image Gene #36: '9p loss' versus Clinical Feature #13: 'PSA_VALUE'

P value = 0.00027 (t-test), Q value = 0.21
Table S18. Gene #41: '12q loss' versus Clinical Feature #13: 'PSA_VALUE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 162 | 1.4 (4.5) |
12Q LOSS MUTATED | 7 | 0.1 (0.1) |
12Q LOSS WILD-TYPE | 155 | 1.5 (4.6) |
Figure S18. Get High-res Image Gene #41: '12q loss' versus Clinical Feature #13: 'PSA_VALUE'

P value = 1.55e-26 (t-test), Q value = 1.2e-23
Table S19. Gene #48: '17q loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 184 | 3.5 (0.6) |
17Q LOSS MUTATED | 4 | 4.0 (0.0) |
17Q LOSS WILD-TYPE | 180 | 3.5 (0.6) |
Figure S19. Get High-res Image Gene #48: '17q loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

P value = 0.000259 (t-test), Q value = 0.2
Table S20. Gene #50: '18q loss' versus Clinical Feature #10: 'GLEASON_SCORE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 184 | 7.3 (0.8) |
18Q LOSS MUTATED | 35 | 7.9 (1.1) |
18Q LOSS WILD-TYPE | 149 | 7.2 (0.6) |
Figure S20. Get High-res Image Gene #50: '18q loss' versus Clinical Feature #10: 'GLEASON_SCORE'

P value = 2.74e-05 (t-test), Q value = 0.021
Table S21. Gene #51: '19p loss' versus Clinical Feature #11: 'PSA_RESULT_PREOP'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 182 | 10.4 (10.2) |
19P LOSS MUTATED | 4 | 4.5 (1.3) |
19P LOSS WILD-TYPE | 178 | 10.5 (10.3) |
Figure S21. Get High-res Image Gene #51: '19p loss' versus Clinical Feature #11: 'PSA_RESULT_PREOP'

P value = 2.74e-05 (t-test), Q value = 0.021
Table S22. Gene #52: '19q loss' versus Clinical Feature #11: 'PSA_RESULT_PREOP'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 182 | 10.4 (10.2) |
19Q LOSS MUTATED | 4 | 4.5 (1.3) |
19Q LOSS WILD-TYPE | 178 | 10.5 (10.3) |
Figure S22. Get High-res Image Gene #52: '19q loss' versus Clinical Feature #11: 'PSA_RESULT_PREOP'

P value = 1.55e-26 (t-test), Q value = 1.2e-23
Table S23. Gene #54: '20q loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 184 | 3.5 (0.6) |
20Q LOSS MUTATED | 4 | 4.0 (0.0) |
20Q LOSS WILD-TYPE | 180 | 3.5 (0.6) |
Figure S23. Get High-res Image Gene #54: '20q loss' versus Clinical Feature #8: 'GLEASON_SCORE_PRIMARY'

-
Copy number data file = transformed.cor.cli.txt
-
Clinical data file = PRAD-TP.merged_data.txt
-
Number of patients = 184
-
Number of significantly arm-level cnvs = 57
-
Number of selected clinical features = 14
-
Exclude regions that fewer than K tumors have mutations, K = 3
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
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
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
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.
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.