This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.
Testing the association between copy number variation 74 arm-level results and 11 clinical features across 131 patients, 9 significant findings detected with Q value < 0.25.
-
2p gain cnv correlated to 'GENDER'.
-
4p gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.
-
5q gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.
-
9q gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.
-
14q gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.
-
16p gain cnv correlated to 'Time to Death'.
-
17p gain cnv correlated to 'NUMBER.OF.LYMPH.NODES'.
-
6p loss cnv correlated to 'KARNOFSKY.PERFORMANCE.SCORE'.
-
16q loss cnv correlated to 'TOBACCOSMOKINGHISTORYINDICATOR'.
Table 1. Get Full Table Overview of the association between significant copy number variation of 74 arm-level results and 11 clinical features. Shown in the table are P values (Q values). Thresholded by Q value < 0.25, 9 significant findings detected.
Clinical Features |
Time to Death |
AGE | GENDER |
KARNOFSKY PERFORMANCE SCORE |
NUMBERPACKYEARSSMOKED | TOBACCOSMOKINGHISTORYINDICATOR |
DISTANT METASTASIS |
LYMPH NODE METASTASIS |
NUMBER OF LYMPH NODES |
TUMOR STAGECODE |
NEOPLASM DISEASESTAGE |
||
nCNV (%) | nWild-Type | logrank test | t-test | Fisher's exact test | t-test | t-test | t-test | Fisher's exact test | Chi-square test | t-test | t-test | Fisher's exact test | |
2p gain | 0 (0%) | 106 |
0.584 (1.00) |
0.595 (1.00) |
0.000227 (0.156) |
0.934 (1.00) |
0.741 (1.00) |
0.356 (1.00) |
1 (1.00) |
0.437 (1.00) |
0.492 (1.00) |
0.684 (1.00) |
|
4p gain | 0 (0%) | 123 |
0.0892 (1.00) |
0.819 (1.00) |
0.679 (1.00) |
0.394 (1.00) |
0.000201 (0.138) |
||||||
5q gain | 0 (0%) | 114 |
0.16 (1.00) |
0.55 (1.00) |
0.237 (1.00) |
0.252 (1.00) |
0.914 (1.00) |
0.913 (1.00) |
0.823 (1.00) |
0.377 (1.00) |
0.000102 (0.0701) |
0.367 (1.00) |
|
9q gain | 0 (0%) | 119 |
0.0825 (1.00) |
0.186 (1.00) |
0.496 (1.00) |
0.786 (1.00) |
0.167 (1.00) |
0.975 (1.00) |
0.691 (1.00) |
0.402 (1.00) |
2.87e-06 (0.00199) |
0.00942 (1.00) |
|
14q gain | 0 (0%) | 120 |
0.955 (1.00) |
0.633 (1.00) |
0.467 (1.00) |
0.471 (1.00) |
0.341 (1.00) |
0.728 (1.00) |
0.736 (1.00) |
0.747 (1.00) |
7.1e-05 (0.0489) |
0.689 (1.00) |
|
16p gain | 0 (0%) | 122 |
4.1e-05 (0.0284) |
0.484 (1.00) |
0.228 (1.00) |
0.45 (1.00) |
0.212 (1.00) |
0.721 (1.00) |
0.263 (1.00) |
0.853 (1.00) |
0.068 (1.00) |
0.61 (1.00) |
|
17p gain | 0 (0%) | 124 |
0.305 (1.00) |
0.972 (1.00) |
0.367 (1.00) |
0.974 (1.00) |
0.535 (1.00) |
0.691 (1.00) |
0.402 (1.00) |
3.04e-06 (0.00211) |
0.12 (1.00) |
||
6p loss | 0 (0%) | 113 |
0.994 (1.00) |
0.348 (1.00) |
0.775 (1.00) |
6.63e-05 (0.0457) |
0.655 (1.00) |
0.341 (1.00) |
0.345 (1.00) |
0.264 (1.00) |
0.282 (1.00) |
0.0307 (1.00) |
|
16q loss | 0 (0%) | 116 |
0.718 (1.00) |
0.31 (1.00) |
0.354 (1.00) |
0.191 (1.00) |
0.946 (1.00) |
4.43e-05 (0.0306) |
0.813 (1.00) |
0.0107 (1.00) |
0.344 (1.00) |
0.215 (1.00) |
|
1p gain | 0 (0%) | 116 |
0.083 (1.00) |
0.501 (1.00) |
0.528 (1.00) |
0.494 (1.00) |
0.429 (1.00) |
0.976 (1.00) |
0.783 (1.00) |
0.463 (1.00) |
0.558 (1.00) |
0.226 (1.00) |
|
1q gain | 0 (0%) | 102 |
0.029 (1.00) |
0.0223 (1.00) |
0.809 (1.00) |
0.257 (1.00) |
0.675 (1.00) |
0.845 (1.00) |
0.572 (1.00) |
0.911 (1.00) |
0.849 (1.00) |
0.699 (1.00) |
|
2q gain | 0 (0%) | 121 |
0.62 (1.00) |
0.632 (1.00) |
0.712 (1.00) |
0.257 (1.00) |
0.443 (1.00) |
0.716 (1.00) |
0.551 (1.00) |
0.434 (1.00) |
0.316 (1.00) |
0.0363 (1.00) |
|
3p gain | 0 (0%) | 105 |
0.485 (1.00) |
0.507 (1.00) |
0.459 (1.00) |
0.422 (1.00) |
0.87 (1.00) |
0.938 (1.00) |
0.742 (1.00) |
0.374 (1.00) |
0.262 (1.00) |
0.265 (1.00) |
|
3q gain | 0 (0%) | 94 |
0.207 (1.00) |
0.25 (1.00) |
0.119 (1.00) |
0.846 (1.00) |
0.872 (1.00) |
0.707 (1.00) |
0.643 (1.00) |
0.503 (1.00) |
0.27 (1.00) |
0.61 (1.00) |
|
4q gain | 0 (0%) | 128 |
0.303 (1.00) |
0.515 (1.00) |
1 (1.00) |
0.284 (1.00) |
|||||||
5p gain | 0 (0%) | 92 |
0.797 (1.00) |
0.488 (1.00) |
0.512 (1.00) |
0.135 (1.00) |
0.581 (1.00) |
0.567 (1.00) |
0.602 (1.00) |
0.0104 (1.00) |
0.31 (1.00) |
0.507 (1.00) |
|
6p gain | 0 (0%) | 121 |
0.205 (1.00) |
0.643 (1.00) |
1 (1.00) |
0.616 (1.00) |
0.669 (1.00) |
0.886 (1.00) |
1 (1.00) |
0.447 (1.00) |
0.122 (1.00) |
0.893 (1.00) |
|
6q gain | 0 (0%) | 126 |
0.105 (1.00) |
0.895 (1.00) |
0.33 (1.00) |
0.779 (1.00) |
0.00639 (1.00) |
||||||
7p gain | 0 (0%) | 93 |
0.497 (1.00) |
0.344 (1.00) |
0.516 (1.00) |
0.141 (1.00) |
0.413 (1.00) |
0.0177 (1.00) |
0.361 (1.00) |
0.954 (1.00) |
0.788 (1.00) |
1 (1.00) |
|
7q gain | 0 (0%) | 96 |
0.583 (1.00) |
0.631 (1.00) |
0.0238 (1.00) |
0.141 (1.00) |
0.256 (1.00) |
0.127 (1.00) |
0.88 (1.00) |
0.879 (1.00) |
0.535 (1.00) |
0.508 (1.00) |
|
8p gain | 0 (0%) | 117 |
0.902 (1.00) |
0.185 (1.00) |
1 (1.00) |
0.821 (1.00) |
0.214 (1.00) |
0.304 (1.00) |
1 (1.00) |
0.834 (1.00) |
0.0016 (1.00) |
0.867 (1.00) |
|
8q gain | 0 (0%) | 92 |
0.558 (1.00) |
0.573 (1.00) |
0.827 (1.00) |
0.896 (1.00) |
0.322 (1.00) |
0.715 (1.00) |
0.635 (1.00) |
0.993 (1.00) |
0.165 (1.00) |
0.74 (1.00) |
|
9p gain | 0 (0%) | 118 |
0.037 (1.00) |
0.0242 (1.00) |
0.183 (1.00) |
0.842 (1.00) |
0.0265 (1.00) |
0.119 (1.00) |
0.744 (1.00) |
0.319 (1.00) |
0.00161 (1.00) |
0.489 (1.00) |
|
10p gain | 0 (0%) | 106 |
0.87 (1.00) |
0.993 (1.00) |
0.614 (1.00) |
0.73 (1.00) |
0.56 (1.00) |
0.372 (1.00) |
1 (1.00) |
0.607 (1.00) |
0.666 (1.00) |
0.801 (1.00) |
|
10q gain | 0 (0%) | 124 |
0.402 (1.00) |
0.113 (1.00) |
1 (1.00) |
0.689 (1.00) |
0.648 (1.00) |
0.609 (1.00) |
0.866 (1.00) |
0.535 (1.00) |
|||
11p gain | 0 (0%) | 125 |
0.0551 (1.00) |
0.109 (1.00) |
0.336 (1.00) |
0.0875 (1.00) |
0.618 (1.00) |
0.183 (1.00) |
1 (1.00) |
0.217 (1.00) |
0.1 (1.00) |
0.523 (1.00) |
|
11q gain | 0 (0%) | 124 |
0.297 (1.00) |
0.301 (1.00) |
0.191 (1.00) |
0.792 (1.00) |
0.997 (1.00) |
0.649 (1.00) |
1 (1.00) |
0.302 (1.00) |
0.321 (1.00) |
0.737 (1.00) |
|
12p gain | 0 (0%) | 107 |
0.847 (1.00) |
0.723 (1.00) |
1 (1.00) |
0.245 (1.00) |
0.978 (1.00) |
0.699 (1.00) |
0.713 (1.00) |
0.446 (1.00) |
0.0101 (1.00) |
0.374 (1.00) |
|
12q gain | 0 (0%) | 114 |
0.36 (1.00) |
0.464 (1.00) |
0.237 (1.00) |
0.347 (1.00) |
0.532 (1.00) |
0.561 (1.00) |
0.422 (1.00) |
0.553 (1.00) |
0.0816 (1.00) |
0.427 (1.00) |
|
13q gain | 0 (0%) | 110 |
0.383 (1.00) |
0.597 (1.00) |
1 (1.00) |
0.64 (1.00) |
0.145 (1.00) |
0.672 (1.00) |
0.165 (1.00) |
0.174 (1.00) |
0.871 (1.00) |
0.481 (1.00) |
|
15q gain | 0 (0%) | 127 |
0.0836 (1.00) |
0.828 (1.00) |
1 (1.00) |
0.922 (1.00) |
|||||||
16q gain | 0 (0%) | 119 |
0.00157 (1.00) |
0.319 (1.00) |
0.0733 (1.00) |
0.468 (1.00) |
0.439 (1.00) |
0.0896 (1.00) |
0.483 (1.00) |
0.849 (1.00) |
0.0525 (1.00) |
0.489 (1.00) |
|
17q gain | 0 (0%) | 109 |
0.691 (1.00) |
0.923 (1.00) |
0.792 (1.00) |
0.0945 (1.00) |
0.438 (1.00) |
0.0874 (1.00) |
1 (1.00) |
0.882 (1.00) |
0.936 (1.00) |
1 (1.00) |
|
18p gain | 0 (0%) | 110 |
0.885 (1.00) |
0.99 (1.00) |
0.785 (1.00) |
0.469 (1.00) |
0.375 (1.00) |
0.0858 (1.00) |
0.705 (1.00) |
0.623 (1.00) |
0.679 (1.00) |
1 (1.00) |
|
18q gain | 0 (0%) | 124 |
0.026 (1.00) |
0.788 (1.00) |
1 (1.00) |
0.848 (1.00) |
0.232 (1.00) |
0.664 (1.00) |
0.838 (1.00) |
0.269 (1.00) |
1 (1.00) |
||
19p gain | 0 (0%) | 120 |
0.631 (1.00) |
0.892 (1.00) |
0.729 (1.00) |
0.257 (1.00) |
0.377 (1.00) |
0.834 (1.00) |
0.776 (1.00) |
0.648 (1.00) |
0.0478 (1.00) |
0.279 (1.00) |
|
19q gain | 0 (0%) | 107 |
0.327 (1.00) |
0.962 (1.00) |
0.309 (1.00) |
0.345 (1.00) |
0.4 (1.00) |
0.83 (1.00) |
1 (1.00) |
0.919 (1.00) |
0.731 (1.00) |
0.431 (1.00) |
|
20p gain | 0 (0%) | 83 |
0.324 (1.00) |
0.844 (1.00) |
0.143 (1.00) |
0.753 (1.00) |
0.435 (1.00) |
0.992 (1.00) |
0.609 (1.00) |
0.367 (1.00) |
0.419 (1.00) |
0.876 (1.00) |
|
20q gain | 0 (0%) | 78 |
0.734 (1.00) |
0.387 (1.00) |
1 (1.00) |
0.48 (1.00) |
0.279 (1.00) |
0.558 (1.00) |
0.559 (1.00) |
0.503 (1.00) |
0.402 (1.00) |
0.508 (1.00) |
|
21q gain | 0 (0%) | 107 |
0.437 (1.00) |
0.216 (1.00) |
1 (1.00) |
0.907 (1.00) |
0.639 (1.00) |
0.492 (1.00) |
0.813 (1.00) |
0.677 (1.00) |
0.929 (1.00) |
0.259 (1.00) |
|
22q gain | 0 (0%) | 120 |
0.0761 (1.00) |
0.544 (1.00) |
0.729 (1.00) |
0.606 (1.00) |
0.487 (1.00) |
0.0612 (1.00) |
0.551 (1.00) |
0.405 (1.00) |
0.54 (1.00) |
0.689 (1.00) |
|
Xq gain | 0 (0%) | 125 |
0.43 (1.00) |
0.7 (1.00) |
0.641 (1.00) |
0.473 (1.00) |
0.472 (1.00) |
0.455 (1.00) |
0.167 (1.00) |
0.0933 (1.00) |
0.523 (1.00) |
||
2p loss | 0 (0%) | 124 |
0.588 (1.00) |
0.654 (1.00) |
0.679 (1.00) |
0.904 (1.00) |
0.238 (1.00) |
0.983 (1.00) |
0.691 (1.00) |
0.167 (1.00) |
0.523 (1.00) |
||
2q loss | 0 (0%) | 116 |
0.0327 (1.00) |
0.985 (1.00) |
0.354 (1.00) |
0.904 (1.00) |
0.226 (1.00) |
0.677 (1.00) |
0.813 (1.00) |
0.0296 (1.00) |
0.13 (1.00) |
0.0898 (1.00) |
|
3p loss | 0 (0%) | 122 |
0.943 (1.00) |
0.645 (1.00) |
0.228 (1.00) |
0.494 (1.00) |
0.957 (1.00) |
1 (1.00) |
0.597 (1.00) |
0.862 (1.00) |
0.361 (1.00) |
||
4p loss | 0 (0%) | 106 |
0.503 (1.00) |
0.922 (1.00) |
1 (1.00) |
0.0948 (1.00) |
0.541 (1.00) |
0.434 (1.00) |
0.497 (1.00) |
0.0965 (1.00) |
0.261 (1.00) |
0.371 (1.00) |
|
4q loss | 0 (0%) | 107 |
0.682 (1.00) |
0.738 (1.00) |
0.795 (1.00) |
0.0948 (1.00) |
0.905 (1.00) |
0.305 (1.00) |
0.462 (1.00) |
0.944 (1.00) |
0.807 (1.00) |
0.941 (1.00) |
|
5p loss | 0 (0%) | 120 |
0.225 (1.00) |
0.452 (1.00) |
0.143 (1.00) |
0.0998 (1.00) |
0.802 (1.00) |
0.41 (1.00) |
0.736 (1.00) |
0.946 (1.00) |
0.973 (1.00) |
0.293 (1.00) |
|
5q loss | 0 (0%) | 101 |
0.854 (1.00) |
0.61 (1.00) |
0.632 (1.00) |
0.305 (1.00) |
0.345 (1.00) |
0.391 (1.00) |
0.346 (1.00) |
0.182 (1.00) |
0.291 (1.00) |
0.129 (1.00) |
|
6q loss | 0 (0%) | 104 |
0.332 (1.00) |
0.906 (1.00) |
0.62 (1.00) |
0.148 (1.00) |
0.374 (1.00) |
0.377 (1.00) |
0.316 (1.00) |
0.216 (1.00) |
0.286 (1.00) |
0.132 (1.00) |
|
8p loss | 0 (0%) | 85 |
0.352 (1.00) |
0.464 (1.00) |
0.301 (1.00) |
0.41 (1.00) |
0.149 (1.00) |
0.835 (1.00) |
0.91 (1.00) |
0.57 (1.00) |
0.863 (1.00) |
0.843 (1.00) |
|
8q loss | 0 (0%) | 125 |
0.957 (1.00) |
0.0819 (1.00) |
0.641 (1.00) |
0.847 (1.00) |
0.98 (1.00) |
0.691 (1.00) |
0.582 (1.00) |
0.894 (1.00) |
0.215 (1.00) |
||
9p loss | 0 (0%) | 93 |
0.982 (1.00) |
0.58 (1.00) |
0.278 (1.00) |
0.374 (1.00) |
0.284 (1.00) |
0.526 (1.00) |
0.22 (1.00) |
0.478 (1.00) |
0.892 (1.00) |
0.422 (1.00) |
|
9q loss | 0 (0%) | 95 |
0.812 (1.00) |
0.876 (1.00) |
0.185 (1.00) |
0.651 (1.00) |
0.198 (1.00) |
0.886 (1.00) |
0.291 (1.00) |
0.609 (1.00) |
0.0671 (1.00) |
0.409 (1.00) |
|
10p loss | 0 (0%) | 113 |
0.481 (1.00) |
0.896 (1.00) |
1 (1.00) |
0.0186 (1.00) |
0.804 (1.00) |
0.224 (1.00) |
0.559 (1.00) |
0.388 (1.00) |
0.0409 (1.00) |
0.932 (1.00) |
|
10q loss | 0 (0%) | 105 |
0.427 (1.00) |
0.0231 (1.00) |
0.805 (1.00) |
0.134 (1.00) |
0.744 (1.00) |
0.766 (1.00) |
0.778 (1.00) |
0.671 (1.00) |
0.849 (1.00) |
0.772 (1.00) |
|
11p loss | 0 (0%) | 89 |
0.617 (1.00) |
0.271 (1.00) |
0.833 (1.00) |
0.135 (1.00) |
0.982 (1.00) |
0.249 (1.00) |
0.243 (1.00) |
0.789 (1.00) |
0.241 (1.00) |
0.336 (1.00) |
|
11q loss | 0 (0%) | 100 |
0.882 (1.00) |
0.619 (1.00) |
0.815 (1.00) |
0.708 (1.00) |
0.343 (1.00) |
0.884 (1.00) |
0.536 (1.00) |
0.794 (1.00) |
0.258 (1.00) |
0.724 (1.00) |
|
12p loss | 0 (0%) | 126 |
0.937 (1.00) |
0.298 (1.00) |
0.33 (1.00) |
0.678 (1.00) |
0.39 (1.00) |
1 (1.00) |
0.619 (1.00) |
0.877 (1.00) |
0.387 (1.00) |
||
12q loss | 0 (0%) | 125 |
0.125 (1.00) |
0.314 (1.00) |
0.336 (1.00) |
0.857 (1.00) |
0.318 (1.00) |
1 (1.00) |
0.0362 (1.00) |
0.462 (1.00) |
0.195 (1.00) |
||
13q loss | 0 (0%) | 113 |
0.874 (1.00) |
0.685 (1.00) |
0.24 (1.00) |
0.0159 (1.00) |
0.723 (1.00) |
0.308 (1.00) |
1 (1.00) |
0.481 (1.00) |
0.582 (1.00) |
0.387 (1.00) |
|
14q loss | 0 (0%) | 109 |
0.21 (1.00) |
0.241 (1.00) |
0.28 (1.00) |
0.772 (1.00) |
0.719 (1.00) |
0.677 (1.00) |
1 (1.00) |
0.406 (1.00) |
0.676 (1.00) |
0.849 (1.00) |
|
15q loss | 0 (0%) | 116 |
0.472 (1.00) |
0.824 (1.00) |
0.528 (1.00) |
0.763 (1.00) |
0.883 (1.00) |
0.00922 (1.00) |
1 (1.00) |
0.755 (1.00) |
0.946 (1.00) |
0.518 (1.00) |
|
16p loss | 0 (0%) | 117 |
0.459 (1.00) |
0.205 (1.00) |
0.188 (1.00) |
0.0945 (1.00) |
0.443 (1.00) |
0.00096 (0.655) |
1 (1.00) |
0.137 (1.00) |
0.976 (1.00) |
0.649 (1.00) |
|
17p loss | 0 (0%) | 94 |
0.392 (1.00) |
0.602 (1.00) |
0.824 (1.00) |
0.856 (1.00) |
0.338 (1.00) |
0.73 (1.00) |
0.716 (1.00) |
0.711 (1.00) |
0.769 (1.00) |
0.777 (1.00) |
|
17q loss | 0 (0%) | 126 |
0.887 (1.00) |
0.407 (1.00) |
1 (1.00) |
0.77 (1.00) |
0.526 (1.00) |
0.29 (1.00) |
1 (1.00) |
0.0247 (1.00) |
0.0658 (1.00) |
||
18p loss | 0 (0%) | 113 |
0.329 (1.00) |
0.0554 (1.00) |
0.392 (1.00) |
0.295 (1.00) |
0.674 (1.00) |
0.892 (1.00) |
0.189 (1.00) |
0.867 (1.00) |
0.847 (1.00) |
0.684 (1.00) |
|
18q loss | 0 (0%) | 97 |
0.0978 (1.00) |
0.0375 (1.00) |
0.167 (1.00) |
0.57 (1.00) |
0.253 (1.00) |
0.565 (1.00) |
0.635 (1.00) |
0.929 (1.00) |
0.824 (1.00) |
0.777 (1.00) |
|
19p loss | 0 (0%) | 123 |
0.341 (1.00) |
0.913 (1.00) |
1 (1.00) |
0.929 (1.00) |
0.641 (1.00) |
0.0861 (1.00) |
0.00234 (1.00) |
0.265 (1.00) |
0.00166 (1.00) |
||
19q loss | 0 (0%) | 128 |
0.000889 (0.608) |
0.9 (1.00) |
0.572 (1.00) |
0.692 (1.00) |
|||||||
20p loss | 0 (0%) | 126 |
0.714 (1.00) |
0.479 (1.00) |
1 (1.00) |
0.0292 (1.00) |
0.9 (1.00) |
0.64 (1.00) |
0.538 (1.00) |
||||
21q loss | 0 (0%) | 118 |
0.996 (1.00) |
0.000838 (0.574) |
1 (1.00) |
0.00136 (0.928) |
0.894 (1.00) |
0.397 (1.00) |
0.295 (1.00) |
0.00863 (1.00) |
0.616 (1.00) |
0.0642 (1.00) |
|
22q loss | 0 (0%) | 106 |
0.115 (1.00) |
0.518 (1.00) |
0.799 (1.00) |
0.187 (1.00) |
0.808 (1.00) |
0.264 (1.00) |
0.859 (1.00) |
0.711 (1.00) |
0.627 (1.00) |
0.888 (1.00) |
|
Xq loss | 0 (0%) | 128 |
0.31 (1.00) |
0.858 (1.00) |
1 (1.00) |
0.349 (1.00) |
0.0942 (1.00) |
1 (1.00) |
0.0658 (1.00) |
P value = 0.000227 (Fisher's exact test), Q value = 0.16
Table S1. Gene #3: '2p gain' versus Clinical Feature #3: 'GENDER'
nPatients | FEMALE | MALE |
---|---|---|
ALL | 33 | 98 |
2P GAIN CNV | 14 | 11 |
2P GAIN WILD-TYPE | 19 | 87 |
Figure S1. Get High-res Image Gene #3: '2p gain' versus Clinical Feature #3: 'GENDER'
![](D3V3.png)
P value = 0.000201 (t-test), Q value = 0.14
Table S2. Gene #7: '4p gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 98 | 1.9 (3.8) |
4P GAIN CNV | 5 | 0.2 (0.4) |
4P GAIN WILD-TYPE | 93 | 2.0 (3.8) |
Figure S2. Get High-res Image Gene #7: '4p gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'
![](D7V9.png)
P value = 0.000102 (t-test), Q value = 0.07
Table S3. Gene #10: '5q gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 98 | 1.9 (3.8) |
5Q GAIN CNV | 11 | 0.3 (0.5) |
5Q GAIN WILD-TYPE | 87 | 2.1 (3.9) |
Figure S3. Get High-res Image Gene #10: '5q gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'
![](D10V9.png)
P value = 2.87e-06 (t-test), Q value = 0.002
Table S4. Gene #18: '9q gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 98 | 1.9 (3.8) |
9Q GAIN CNV | 9 | 0.0 (0.0) |
9Q GAIN WILD-TYPE | 89 | 2.1 (3.9) |
Figure S4. Get High-res Image Gene #18: '9q gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'
![](D18V9.png)
P value = 7.1e-05 (t-test), Q value = 0.049
Table S5. Gene #26: '14q gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 98 | 1.9 (3.8) |
14Q GAIN CNV | 6 | 0.2 (0.4) |
14Q GAIN WILD-TYPE | 92 | 2.0 (3.9) |
Figure S5. Get High-res Image Gene #26: '14q gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'
![](D26V9.png)
P value = 4.1e-05 (logrank test), Q value = 0.028
Table S6. Gene #28: '16p gain' versus Clinical Feature #1: 'Time to Death'
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 124 | 32 | 0.1 - 131.2 (7.0) |
16P GAIN CNV | 9 | 5 | 2.2 - 9.7 (5.1) |
16P GAIN WILD-TYPE | 115 | 27 | 0.1 - 131.2 (7.0) |
Figure S6. Get High-res Image Gene #28: '16p gain' versus Clinical Feature #1: 'Time to Death'
![](D28V1.png)
P value = 3.04e-06 (t-test), Q value = 0.0021
Table S7. Gene #30: '17p gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 98 | 1.9 (3.8) |
17P GAIN CNV | 5 | 0.0 (0.0) |
17P GAIN WILD-TYPE | 93 | 2.0 (3.8) |
Figure S7. Get High-res Image Gene #30: '17p gain' versus Clinical Feature #9: 'NUMBER.OF.LYMPH.NODES'
![](D30V9.png)
P value = 6.63e-05 (t-test), Q value = 0.046
Table S8. Gene #48: '6p loss' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 37 | 78.1 (16.3) |
6P LOSS CNV | 4 | 90.0 (0.0) |
6P LOSS WILD-TYPE | 33 | 76.7 (16.7) |
Figure S8. Get High-res Image Gene #48: '6p loss' versus Clinical Feature #4: 'KARNOFSKY.PERFORMANCE.SCORE'
![](D48V4.png)
P value = 4.43e-05 (t-test), Q value = 0.031
Table S9. Gene #64: '16q loss' versus Clinical Feature #6: 'TOBACCOSMOKINGHISTORYINDICATOR'
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 80 | 2.8 (1.2) |
16Q LOSS CNV | 11 | 3.6 (0.5) |
16Q LOSS WILD-TYPE | 69 | 2.7 (1.2) |
Figure S9. Get High-res Image Gene #64: '16q loss' versus Clinical Feature #6: 'TOBACCOSMOKINGHISTORYINDICATOR'
![](D64V6.png)
-
Mutation data file = broad_values_by_arm.mutsig.cluster.txt
-
Clinical data file = BLCA-TP.clin.merged.picked.txt
-
Number of patients = 131
-
Number of significantly arm-level cnvs = 74
-
Number of selected clinical features = 11
-
Exclude genes 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 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
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.
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.