This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.
Testing the association between subtypes identified by 71 different clustering approaches and 8 clinical features across 493 patients, 6 significant findings detected with Q value < 0.25.
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2 subtypes identified in current cancer cohort by '1p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '1q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '2p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '2q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '3p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '3q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '4p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '4q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '5p gain mutation analysis'. These subtypes correlate to 'AGE'.
-
2 subtypes identified in current cancer cohort by '5q gain mutation analysis'. These subtypes correlate to 'AGE'.
-
2 subtypes identified in current cancer cohort by '6p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '6q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '7p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '7q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '8p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '8q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '9p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '9q gain mutation analysis'. These subtypes correlate to 'PATHOLOGY.T'.
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2 subtypes identified in current cancer cohort by '10p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '10q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '11p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '11q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '12p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '12q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '13q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '14q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '15q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '16p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '16q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '17p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '17q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '18p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '18q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '19p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '19q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '20p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '20q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '21q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '22q gain mutation analysis'. These subtypes do not correlate to any clinical features.
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2 subtypes identified in current cancer cohort by 'Xq gain mutation analysis'. These subtypes do not correlate to any clinical features.
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2 subtypes identified in current cancer cohort by '1p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '1q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '2p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '2q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '3p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '3q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '4p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '4q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '6p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '6q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '8p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '8q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '9p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '9q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '10p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '10q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '11p loss mutation analysis'. These subtypes correlate to 'Time to Death'.
-
2 subtypes identified in current cancer cohort by '11q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '13q loss mutation analysis'. These subtypes correlate to 'PATHOLOGY.T'.
-
2 subtypes identified in current cancer cohort by '14q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '15q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '16q loss mutation analysis'. These subtypes correlate to 'PATHOLOGY.T'.
-
2 subtypes identified in current cancer cohort by '17p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '17q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '18p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '18q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '19p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '20p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '21q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '22q loss mutation analysis'. These subtypes do not correlate to any clinical features.
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2 subtypes identified in current cancer cohort by 'Xq loss mutation analysis'. These subtypes do not correlate to any clinical features.
Clinical Features |
Time to Death |
AGE | GENDER |
KARNOFSKY PERFORMANCE SCORE |
PATHOLOGY T |
PATHOLOGY N |
PATHOLOGICSPREAD(M) |
TUMOR STAGE |
Statistical Tests | logrank test | t-test | Fisher's exact test | t-test | Chi-square test | Fisher's exact test | Fisher's exact test | Chi-square test |
1p gain |
0.498 (1.00) |
0.942 (1.00) |
1 (1.00) |
0.57 (1.00) |
0.141 (1.00) |
1 (1.00) |
0.622 (1.00) |
|
1q gain |
0.96 (1.00) |
0.185 (1.00) |
0.565 (1.00) |
0.115 (1.00) |
0.0393 (1.00) |
0.33 (1.00) |
0.803 (1.00) |
0.0519 (1.00) |
2p gain |
0.58 (1.00) |
0.14 (1.00) |
0.201 (1.00) |
0.563 (1.00) |
0.821 (1.00) |
1 (1.00) |
0.206 (1.00) |
0.308 (1.00) |
2q gain |
0.411 (1.00) |
0.205 (1.00) |
0.0387 (1.00) |
0.159 (1.00) |
0.909 (1.00) |
0.702 (1.00) |
0.208 (1.00) |
0.39 (1.00) |
3p gain |
0.95 (1.00) |
0.429 (1.00) |
0.243 (1.00) |
0.649 (1.00) |
0.264 (1.00) |
0.295 (1.00) |
0.198 (1.00) |
|
3q gain |
0.575 (1.00) |
0.948 (1.00) |
1 (1.00) |
0.0261 (1.00) |
0.386 (1.00) |
0.359 (1.00) |
0.164 (1.00) |
0.357 (1.00) |
4p gain |
0.235 (1.00) |
0.875 (1.00) |
0.72 (1.00) |
0.473 (1.00) |
0.369 (1.00) |
0.616 (1.00) |
0.117 (1.00) |
|
4q gain |
0.653 (1.00) |
0.389 (1.00) |
1 (1.00) |
0.725 (1.00) |
0.369 (1.00) |
0.616 (1.00) |
0.303 (1.00) |
|
5p gain |
0.124 (1.00) |
0.000246 (0.131) |
0.116 (1.00) |
0.563 (1.00) |
0.203 (1.00) |
1 (1.00) |
0.783 (1.00) |
0.286 (1.00) |
5q gain |
0.297 (1.00) |
0.00037 (0.196) |
0.156 (1.00) |
0.482 (1.00) |
0.2 (1.00) |
0.615 (1.00) |
0.594 (1.00) |
0.397 (1.00) |
6p gain |
0.224 (1.00) |
0.236 (1.00) |
1 (1.00) |
0.836 (1.00) |
1 (1.00) |
1 (1.00) |
0.881 (1.00) |
|
6q gain |
0.183 (1.00) |
0.442 (1.00) |
0.663 (1.00) |
0.57 (1.00) |
1 (1.00) |
0.569 (1.00) |
0.622 (1.00) |
|
7p gain |
0.862 (1.00) |
0.314 (1.00) |
0.0846 (1.00) |
0.893 (1.00) |
0.281 (1.00) |
0.599 (1.00) |
0.0451 (1.00) |
0.184 (1.00) |
7q gain |
0.517 (1.00) |
0.38 (1.00) |
0.0673 (1.00) |
0.699 (1.00) |
0.119 (1.00) |
1 (1.00) |
0.00661 (1.00) |
0.0419 (1.00) |
8p gain |
0.574 (1.00) |
0.761 (1.00) |
0.0417 (1.00) |
0.757 (1.00) |
0.00292 (1.00) |
1 (1.00) |
0.462 (1.00) |
0.00061 (0.323) |
8q gain |
0.856 (1.00) |
0.427 (1.00) |
0.192 (1.00) |
0.471 (1.00) |
0.00984 (1.00) |
0.657 (1.00) |
1 (1.00) |
0.00114 (0.596) |
9p gain |
0.123 (1.00) |
0.0377 (1.00) |
0.0232 (1.00) |
0.718 (1.00) |
1 (1.00) |
0.616 (1.00) |
0.402 (1.00) |
|
9q gain |
0.769 (1.00) |
0.97 (1.00) |
0.457 (1.00) |
0.000104 (0.0556) |
1 (1.00) |
0.356 (1.00) |
0.151 (1.00) |
|
10p gain |
0.72 (1.00) |
0.511 (1.00) |
0.422 (1.00) |
0.442 (1.00) |
1 (1.00) |
0.233 (1.00) |
0.419 (1.00) |
|
10q gain |
0.511 (1.00) |
0.169 (1.00) |
0.123 (1.00) |
0.881 (1.00) |
1 (1.00) |
0.489 (1.00) |
0.573 (1.00) |
|
11p gain |
0.974 (1.00) |
0.8 (1.00) |
0.608 (1.00) |
0.115 (1.00) |
0.0557 (1.00) |
1 (1.00) |
0.16 (1.00) |
0.0409 (1.00) |
11q gain |
0.317 (1.00) |
0.811 (1.00) |
0.409 (1.00) |
0.0861 (1.00) |
1 (1.00) |
0.713 (1.00) |
0.0737 (1.00) |
|
12p gain |
0.111 (1.00) |
0.115 (1.00) |
0.364 (1.00) |
0.404 (1.00) |
0.0631 (1.00) |
1 (1.00) |
0.122 (1.00) |
0.0347 (1.00) |
12q gain |
0.142 (1.00) |
0.167 (1.00) |
0.364 (1.00) |
0.404 (1.00) |
0.0631 (1.00) |
0.748 (1.00) |
0.122 (1.00) |
0.0347 (1.00) |
13q gain |
0.291 (1.00) |
0.851 (1.00) |
0.779 (1.00) |
0.366 (1.00) |
1 (1.00) |
1 (1.00) |
0.323 (1.00) |
|
14q gain |
0.438 (1.00) |
0.524 (1.00) |
1 (1.00) |
0.0107 (1.00) |
1 (1.00) |
0.569 (1.00) |
0.166 (1.00) |
|
15q gain |
0.868 (1.00) |
0.939 (1.00) |
0.779 (1.00) |
0.411 (1.00) |
0.46 (1.00) |
0.462 (1.00) |
0.494 (1.00) |
|
16p gain |
0.611 (1.00) |
0.0654 (1.00) |
0.212 (1.00) |
0.4 (1.00) |
0.751 (1.00) |
0.0837 (1.00) |
0.713 (1.00) |
0.71 (1.00) |
16q gain |
0.487 (1.00) |
0.0864 (1.00) |
0.106 (1.00) |
0.191 (1.00) |
0.641 (1.00) |
0.143 (1.00) |
1 (1.00) |
0.71 (1.00) |
17p gain |
0.456 (1.00) |
0.533 (1.00) |
0.795 (1.00) |
0.294 (1.00) |
0.501 (1.00) |
0.149 (1.00) |
0.137 (1.00) |
|
17q gain |
0.143 (1.00) |
0.539 (1.00) |
0.647 (1.00) |
0.161 (1.00) |
0.521 (1.00) |
0.607 (1.00) |
0.553 (1.00) |
0.434 (1.00) |
18p gain |
0.0884 (1.00) |
0.782 (1.00) |
0.0223 (1.00) |
0.884 (1.00) |
1 (1.00) |
0.333 (1.00) |
0.525 (1.00) |
|
18q gain |
0.0884 (1.00) |
0.782 (1.00) |
0.0223 (1.00) |
0.884 (1.00) |
1 (1.00) |
0.333 (1.00) |
0.525 (1.00) |
|
19p gain |
0.935 (1.00) |
0.703 (1.00) |
1 (1.00) |
0.161 (1.00) |
0.769 (1.00) |
0.301 (1.00) |
0.251 (1.00) |
0.24 (1.00) |
19q gain |
0.884 (1.00) |
0.709 (1.00) |
0.683 (1.00) |
0.161 (1.00) |
0.689 (1.00) |
0.359 (1.00) |
0.174 (1.00) |
0.233 (1.00) |
20p gain |
0.274 (1.00) |
0.268 (1.00) |
0.0127 (1.00) |
0.315 (1.00) |
0.00892 (1.00) |
0.485 (1.00) |
0.0429 (1.00) |
0.0259 (1.00) |
20q gain |
0.428 (1.00) |
0.22 (1.00) |
0.0195 (1.00) |
0.315 (1.00) |
0.0138 (1.00) |
0.485 (1.00) |
0.106 (1.00) |
0.042 (1.00) |
21q gain |
0.339 (1.00) |
0.324 (1.00) |
0.851 (1.00) |
0.161 (1.00) |
0.386 (1.00) |
1 (1.00) |
1 (1.00) |
0.837 (1.00) |
22q gain |
0.964 (1.00) |
0.83 (1.00) |
0.526 (1.00) |
0.207 (1.00) |
1 (1.00) |
0.251 (1.00) |
0.502 (1.00) |
|
Xq gain |
0.44 (1.00) |
0.723 (1.00) |
0.0546 (1.00) |
0.915 (1.00) |
1 (1.00) |
0.0733 (1.00) |
0.0997 (1.00) |
|
1p loss |
0.877 (1.00) |
0.0984 (1.00) |
0.565 (1.00) |
0.115 (1.00) |
0.0198 (1.00) |
0.607 (1.00) |
0.45 (1.00) |
0.0535 (1.00) |
1q loss |
0.779 (1.00) |
0.599 (1.00) |
0.644 (1.00) |
0.127 (1.00) |
1 (1.00) |
0.756 (1.00) |
0.192 (1.00) |
|
2p loss |
0.471 (1.00) |
0.932 (1.00) |
0.506 (1.00) |
0.152 (1.00) |
1 (1.00) |
1 (1.00) |
0.51 (1.00) |
|
2q loss |
0.856 (1.00) |
0.983 (1.00) |
0.344 (1.00) |
0.303 (1.00) |
1 (1.00) |
1 (1.00) |
0.736 (1.00) |
|
3p loss |
0.556 (1.00) |
0.355 (1.00) |
0.0797 (1.00) |
0.906 (1.00) |
0.0152 (1.00) |
0.462 (1.00) |
0.0145 (1.00) |
0.0166 (1.00) |
3q loss |
0.948 (1.00) |
0.0175 (1.00) |
0.000815 (0.429) |
0.573 (1.00) |
0.287 (1.00) |
0.702 (1.00) |
0.729 (1.00) |
0.613 (1.00) |
4p loss |
0.0602 (1.00) |
0.558 (1.00) |
0.854 (1.00) |
0.0176 (1.00) |
0.013 (1.00) |
1 (1.00) |
0.808 (1.00) |
0.106 (1.00) |
4q loss |
0.0183 (1.00) |
0.992 (1.00) |
0.841 (1.00) |
0.0261 (1.00) |
0.00121 (0.635) |
0.607 (1.00) |
0.174 (1.00) |
0.0308 (1.00) |
6p loss |
0.235 (1.00) |
0.187 (1.00) |
0.00303 (1.00) |
0.499 (1.00) |
0.757 (1.00) |
0.189 (1.00) |
0.439 (1.00) |
0.841 (1.00) |
6q loss |
0.548 (1.00) |
0.719 (1.00) |
0.127 (1.00) |
0.851 (1.00) |
0.99 (1.00) |
0.0592 (1.00) |
0.868 (1.00) |
0.787 (1.00) |
8p loss |
0.512 (1.00) |
0.0949 (1.00) |
0.281 (1.00) |
0.0817 (1.00) |
0.53 (1.00) |
0.322 (1.00) |
0.429 (1.00) |
0.51 (1.00) |
8q loss |
0.279 (1.00) |
0.915 (1.00) |
0.0469 (1.00) |
0.00419 (1.00) |
0.814 (1.00) |
0.608 (1.00) |
0.244 (1.00) |
0.832 (1.00) |
9p loss |
0.0111 (1.00) |
0.0624 (1.00) |
0.0128 (1.00) |
0.0261 (1.00) |
0.16 (1.00) |
0.745 (1.00) |
0.0209 (1.00) |
0.0805 (1.00) |
9q loss |
0.00542 (1.00) |
0.034 (1.00) |
0.0155 (1.00) |
0.0473 (1.00) |
0.0199 (1.00) |
1 (1.00) |
0.0035 (1.00) |
0.00325 (1.00) |
10p loss |
0.507 (1.00) |
0.49 (1.00) |
0.565 (1.00) |
0.0261 (1.00) |
0.000803 (0.423) |
1 (1.00) |
0.803 (1.00) |
0.863 (1.00) |
10q loss |
0.742 (1.00) |
0.258 (1.00) |
0.268 (1.00) |
0.0535 (1.00) |
0.000794 (0.419) |
0.621 (1.00) |
0.677 (1.00) |
0.68 (1.00) |
11p loss |
3.9e-05 (0.0209) |
0.943 (1.00) |
0.663 (1.00) |
0.639 (1.00) |
0.141 (1.00) |
0.569 (1.00) |
0.775 (1.00) |
|
11q loss |
0.148 (1.00) |
0.638 (1.00) |
0.43 (1.00) |
0.735 (1.00) |
0.264 (1.00) |
1 (1.00) |
0.821 (1.00) |
|
13q loss |
0.0012 (0.63) |
0.0513 (1.00) |
0.334 (1.00) |
0.00419 (1.00) |
6.37e-05 (0.034) |
1 (1.00) |
0.0394 (1.00) |
0.0144 (1.00) |
14q loss |
0.251 (1.00) |
0.203 (1.00) |
0.265 (1.00) |
0.508 (1.00) |
0.019 (1.00) |
0.0682 (1.00) |
0.142 (1.00) |
0.0258 (1.00) |
15q loss |
0.257 (1.00) |
0.13 (1.00) |
1 (1.00) |
0.305 (1.00) |
0.417 (1.00) |
0.408 (1.00) |
0.432 (1.00) |
|
16q loss |
0.0864 (1.00) |
0.0696 (1.00) |
0.663 (1.00) |
2.67e-07 (0.000143) |
1 (1.00) |
0.569 (1.00) |
0.0497 (1.00) |
|
17p loss |
0.0387 (1.00) |
0.658 (1.00) |
0.288 (1.00) |
0.0473 (1.00) |
0.14 (1.00) |
1 (1.00) |
0.0396 (1.00) |
0.24 (1.00) |
17q loss |
0.697 (1.00) |
0.831 (1.00) |
0.232 (1.00) |
0.102 (1.00) |
1 (1.00) |
1 (1.00) |
0.561 (1.00) |
|
18p loss |
0.317 (1.00) |
0.106 (1.00) |
0.626 (1.00) |
0.518 (1.00) |
0.1 (1.00) |
0.691 (1.00) |
0.204 (1.00) |
0.374 (1.00) |
18q loss |
0.699 (1.00) |
0.22 (1.00) |
0.268 (1.00) |
0.518 (1.00) |
0.566 (1.00) |
0.702 (1.00) |
0.292 (1.00) |
0.735 (1.00) |
19p loss |
0.000514 (0.273) |
0.89 (1.00) |
0.612 (1.00) |
0.00347 (1.00) |
1 (1.00) |
1 (1.00) |
0.0853 (1.00) |
|
20p loss |
0.751 (1.00) |
0.967 (1.00) |
1 (1.00) |
0.725 (1.00) |
1 (1.00) |
1 (1.00) |
0.745 (1.00) |
|
21q loss |
0.779 (1.00) |
0.944 (1.00) |
1 (1.00) |
0.00547 (1.00) |
0.359 (1.00) |
0.45 (1.00) |
0.24 (1.00) |
|
22q loss |
0.228 (1.00) |
0.0446 (1.00) |
0.344 (1.00) |
0.209 (1.00) |
1 (1.00) |
1 (1.00) |
0.121 (1.00) |
|
Xq loss |
0.507 (1.00) |
0.749 (1.00) |
0.102 (1.00) |
0.562 (1.00) |
1 (1.00) |
0.602 (1.00) |
0.403 (1.00) |
Cluster Labels | 1P GAIN MUTATED | 1P GAIN WILD-TYPE |
---|---|---|
Number of samples | 5 | 488 |
Cluster Labels | 1Q GAIN MUTATED | 1Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 32 | 461 |
Cluster Labels | 2P GAIN MUTATED | 2P GAIN WILD-TYPE |
---|---|---|
Number of samples | 48 | 445 |
Cluster Labels | 2Q GAIN MUTATED | 2Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 49 | 444 |
Cluster Labels | 3P GAIN MUTATED | 3P GAIN WILD-TYPE |
---|---|---|
Number of samples | 7 | 486 |
Cluster Labels | 3Q GAIN MUTATED | 3Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 27 | 466 |
Cluster Labels | 4P GAIN MUTATED | 4P GAIN WILD-TYPE |
---|---|---|
Number of samples | 8 | 485 |
Cluster Labels | 4Q GAIN MUTATED | 4Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 8 | 485 |
Cluster Labels | 5P GAIN MUTATED | 5P GAIN WILD-TYPE |
---|---|---|
Number of samples | 141 | 352 |
P value = 0.000246 (t-test), Q value = 0.13
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 492 | 60.6 (12.2) |
5P GAIN MUTATED | 141 | 63.7 (12.0) |
5P GAIN WILD-TYPE | 351 | 59.3 (12.1) |
Cluster Labels | 5Q GAIN MUTATED | 5Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 156 | 337 |
P value = 0.00037 (t-test), Q value = 0.2
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 492 | 60.6 (12.2) |
5Q GAIN MUTATED | 155 | 63.5 (12.3) |
5Q GAIN WILD-TYPE | 337 | 59.2 (11.9) |
Cluster Labels | 6P GAIN MUTATED | 6P GAIN WILD-TYPE |
---|---|---|
Number of samples | 6 | 487 |
Cluster Labels | 6Q GAIN MUTATED | 6Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 5 | 488 |
Cluster Labels | 7P GAIN MUTATED | 7P GAIN WILD-TYPE |
---|---|---|
Number of samples | 127 | 366 |
Cluster Labels | 7Q GAIN MUTATED | 7Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 129 | 364 |
Cluster Labels | 8P GAIN MUTATED | 8P GAIN WILD-TYPE |
---|---|---|
Number of samples | 14 | 479 |
Cluster Labels | 8Q GAIN MUTATED | 8Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 34 | 459 |
Cluster Labels | 9P GAIN MUTATED | 9P GAIN WILD-TYPE |
---|---|---|
Number of samples | 8 | 485 |
Cluster Labels | 9Q GAIN MUTATED | 9Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 8 | 485 |
P value = 0.000104 (Chi-square test), Q value = 0.056
nPatients | T1 | T2 | T3 | T4 |
---|---|---|---|---|
ALL | 242 | 64 | 176 | 11 |
9Q GAIN MUTATED | 2 | 2 | 2 | 2 |
9Q GAIN WILD-TYPE | 240 | 62 | 174 | 9 |
Cluster Labels | 10P GAIN MUTATED | 10P GAIN WILD-TYPE |
---|---|---|
Number of samples | 6 | 487 |
Cluster Labels | 10Q GAIN MUTATED | 10Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 4 | 489 |
Cluster Labels | 11P GAIN MUTATED | 11P GAIN WILD-TYPE |
---|---|---|
Number of samples | 17 | 476 |
Cluster Labels | 11Q GAIN MUTATED | 11Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 15 | 478 |
Cluster Labels | 12P GAIN MUTATED | 12P GAIN WILD-TYPE |
---|---|---|
Number of samples | 78 | 415 |
Cluster Labels | 12Q GAIN MUTATED | 12Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 78 | 415 |
Cluster Labels | 13Q GAIN MUTATED | 13Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 14 | 479 |
Cluster Labels | 14Q GAIN MUTATED | 14Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 5 | 488 |
Cluster Labels | 15Q GAIN MUTATED | 15Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 14 | 479 |
Cluster Labels | 16P GAIN MUTATED | 16P GAIN WILD-TYPE |
---|---|---|
Number of samples | 65 | 428 |
Cluster Labels | 16Q GAIN MUTATED | 16Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 58 | 435 |
Cluster Labels | 17P GAIN MUTATED | 17P GAIN WILD-TYPE |
---|---|---|
Number of samples | 16 | 477 |
Cluster Labels | 17Q GAIN MUTATED | 17Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 22 | 471 |
Cluster Labels | 18P GAIN MUTATED | 18P GAIN WILD-TYPE |
---|---|---|
Number of samples | 18 | 475 |
Cluster Labels | 18Q GAIN MUTATED | 18Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 18 | 475 |
Cluster Labels | 19P GAIN MUTATED | 19P GAIN WILD-TYPE |
---|---|---|
Number of samples | 25 | 468 |
Cluster Labels | 19Q GAIN MUTATED | 19Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 28 | 465 |
Cluster Labels | 20P GAIN MUTATED | 20P GAIN WILD-TYPE |
---|---|---|
Number of samples | 66 | 427 |
Cluster Labels | 20Q GAIN MUTATED | 20Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 68 | 425 |
Cluster Labels | 21Q GAIN MUTATED | 21Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 33 | 460 |
Cluster Labels | 22Q GAIN MUTATED | 22Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 25 | 468 |
Cluster Labels | XQ GAIN MUTATED | XQ GAIN WILD-TYPE |
---|---|---|
Number of samples | 11 | 482 |
Cluster Labels | 1P LOSS MUTATED | 1P LOSS WILD-TYPE |
---|---|---|
Number of samples | 32 | 461 |
Cluster Labels | 1Q LOSS MUTATED | 1Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 21 | 472 |
Cluster Labels | 2P LOSS MUTATED | 2P LOSS WILD-TYPE |
---|---|---|
Number of samples | 10 | 483 |
Cluster Labels | 2Q LOSS MUTATED | 2Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 11 | 482 |
Cluster Labels | 3P LOSS MUTATED | 3P LOSS WILD-TYPE |
---|---|---|
Number of samples | 304 | 189 |
Cluster Labels | 3Q LOSS MUTATED | 3Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 73 | 420 |
Cluster Labels | 4P LOSS MUTATED | 4P LOSS WILD-TYPE |
---|---|---|
Number of samples | 35 | 458 |
Cluster Labels | 4Q LOSS MUTATED | 4Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 28 | 465 |
Cluster Labels | 6P LOSS MUTATED | 6P LOSS WILD-TYPE |
---|---|---|
Number of samples | 58 | 435 |
Cluster Labels | 6Q LOSS MUTATED | 6Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 82 | 411 |
Cluster Labels | 8P LOSS MUTATED | 8P LOSS WILD-TYPE |
---|---|---|
Number of samples | 94 | 399 |
Cluster Labels | 8Q LOSS MUTATED | 8Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 37 | 456 |
Cluster Labels | 9P LOSS MUTATED | 9P LOSS WILD-TYPE |
---|---|---|
Number of samples | 87 | 406 |
Cluster Labels | 9Q LOSS MUTATED | 9Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 92 | 401 |
Cluster Labels | 10P LOSS MUTATED | 10P LOSS WILD-TYPE |
---|---|---|
Number of samples | 32 | 461 |
Cluster Labels | 10Q LOSS MUTATED | 10Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 48 | 445 |
Cluster Labels | 11P LOSS MUTATED | 11P LOSS WILD-TYPE |
---|---|---|
Number of samples | 5 | 488 |
P value = 3.9e-05 (logrank test), Q value = 0.021
nPatients | nDeath | Duration Range (Median), Month | |
---|---|---|---|
ALL | 490 | 158 | 0.1 - 111.0 (35.2) |
11P LOSS MUTATED | 5 | 4 | 1.8 - 28.5 (12.1) |
11P LOSS WILD-TYPE | 485 | 154 | 0.1 - 111.0 (35.5) |
Cluster Labels | 11Q LOSS MUTATED | 11Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 7 | 486 |
Cluster Labels | 13Q LOSS MUTATED | 13Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 31 | 462 |
P value = 6.37e-05 (Chi-square test), Q value = 0.034
nPatients | T1 | T2 | T3 | T4 |
---|---|---|---|---|
ALL | 242 | 64 | 176 | 11 |
13Q LOSS MUTATED | 11 | 1 | 15 | 4 |
13Q LOSS WILD-TYPE | 231 | 63 | 161 | 7 |
Cluster Labels | 14Q LOSS MUTATED | 14Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 158 | 335 |
Cluster Labels | 15Q LOSS MUTATED | 15Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 12 | 481 |
Cluster Labels | 16Q LOSS MUTATED | 16Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 5 | 488 |
P value = 2.67e-07 (Chi-square test), Q value = 0.00014
nPatients | T1 | T2 | T3 | T4 |
---|---|---|---|---|
ALL | 242 | 64 | 176 | 11 |
16Q LOSS MUTATED | 2 | 0 | 1 | 2 |
16Q LOSS WILD-TYPE | 240 | 64 | 175 | 9 |
Cluster Labels | 17P LOSS MUTATED | 17P LOSS WILD-TYPE |
---|---|---|
Number of samples | 25 | 468 |
Cluster Labels | 17Q LOSS MUTATED | 17Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 12 | 481 |
Cluster Labels | 18P LOSS MUTATED | 18P LOSS WILD-TYPE |
---|---|---|
Number of samples | 46 | 447 |
Cluster Labels | 18Q LOSS MUTATED | 18Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 48 | 445 |
Cluster Labels | 19P LOSS MUTATED | 19P LOSS WILD-TYPE |
---|---|---|
Number of samples | 4 | 489 |
Cluster Labels | 20P LOSS MUTATED | 20P LOSS WILD-TYPE |
---|---|---|
Number of samples | 6 | 487 |
Cluster Labels | 21Q LOSS MUTATED | 21Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 32 | 461 |
Cluster Labels | 22Q LOSS MUTATED | 22Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 11 | 482 |
Cluster Labels | XQ LOSS MUTATED | XQ LOSS WILD-TYPE |
---|---|---|
Number of samples | 7 | 486 |
-
Cluster data file = broad_values_by_arm.mutsig.cluster.txt
-
Clinical data file = KIRC-TP.clin.merged.picked.txt
-
Number of patients = 493
-
Number of clustering approaches = 71
-
Number of selected clinical features = 8
-
Exclude small clusters that include fewer than K patients, 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 two tumor subtypes using 't.test' function in R
For binary clinical features, 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.