This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.
Testing the association between subtypes identified by 64 different clustering approaches and 8 clinical features across 68 patients, 5 significant findings detected with Q value < 0.25.
-
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 correlate to 'LYMPH.NODE.METASTASIS'.
-
2 subtypes identified in current cancer cohort by '3q gain mutation analysis'. These subtypes correlate to 'LYMPH.NODE.METASTASIS'.
-
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 '5p gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '5q gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
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 do not correlate to any clinical features.
-
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 '12q 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 '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 '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.
-
2 subtypes identified in current cancer cohort by 'Xq gain mutation analysis'. These subtypes do not correlate to any clinical features.
-
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 correlate to 'LYMPH.NODE.METASTASIS'.
-
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 '5q 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 '7p loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
2 subtypes identified in current cancer cohort by '7q 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 do not correlate to any clinical features.
-
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 '12p loss mutation analysis'. These subtypes correlate to 'LYMPH.NODE.METASTASIS'.
-
2 subtypes identified in current cancer cohort by '13q loss mutation analysis'. These subtypes do not correlate to any clinical features.
-
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 '16p 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 do not correlate to any clinical features.
-
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 correlate to 'AGE'.
-
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 '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.
Clinical Features |
Time to Death |
AGE | GENDER |
DISTANT METASTASIS |
LYMPH NODE METASTASIS |
COMPLETENESS OF RESECTION |
TUMOR STAGECODE |
NEOPLASM DISEASESTAGE |
Statistical Tests | logrank test | t-test | Fisher's exact test | Chi-square test | Chi-square test | Chi-square test | t-test | Chi-square test |
1p gain |
0.54 (1.00) |
0.223 (1.00) |
1 (1.00) |
0.149 (1.00) |
0.0971 (1.00) |
0.0336 (1.00) |
0.113 (1.00) |
|
1q gain |
0.792 (1.00) |
0.958 (1.00) |
0.208 (1.00) |
0.468 (1.00) |
0.434 (1.00) |
0.715 (1.00) |
0.196 (1.00) |
|
2p gain |
0.393 (1.00) |
0.111 (1.00) |
0.12 (1.00) |
0.505 (1.00) |
0.4 (1.00) |
0.117 (1.00) |
0.555 (1.00) |
|
2q gain |
0.531 (1.00) |
0.219 (1.00) |
0.0875 (1.00) |
0.788 (1.00) |
0.701 (1.00) |
0.442 (1.00) |
0.555 (1.00) |
|
3p gain |
0.848 (1.00) |
0.0422 (1.00) |
1 (1.00) |
0.977 (1.00) |
1.74e-05 (0.00761) |
0.677 (1.00) |
0.00233 (1.00) |
|
3q gain |
0.848 (1.00) |
0.0422 (1.00) |
1 (1.00) |
0.977 (1.00) |
1.74e-05 (0.00761) |
0.677 (1.00) |
0.00233 (1.00) |
|
4p gain |
0.767 (1.00) |
0.209 (1.00) |
0.337 (1.00) |
0.783 (1.00) |
0.836 (1.00) |
0.792 (1.00) |
0.31 (1.00) |
|
5p gain |
0.277 (1.00) |
0.12 (1.00) |
1 (1.00) |
0.768 (1.00) |
0.805 (1.00) |
0.821 (1.00) |
0.887 (1.00) |
|
5q gain |
0.343 (1.00) |
0.147 (1.00) |
1 (1.00) |
0.848 (1.00) |
0.772 (1.00) |
0.613 (1.00) |
0.75 (1.00) |
|
6p gain |
0.143 (1.00) |
0.666 (1.00) |
0.355 (1.00) |
0.117 (1.00) |
0.684 (1.00) |
0.104 (1.00) |
0.426 (1.00) |
|
6q gain |
0.0823 (1.00) |
0.228 (1.00) |
0.476 (1.00) |
0.032 (1.00) |
0.785 (1.00) |
0.034 (1.00) |
0.205 (1.00) |
|
7p gain |
0.456 (1.00) |
0.453 (1.00) |
0.395 (1.00) |
0.832 (1.00) |
0.786 (1.00) |
0.798 (1.00) |
0.813 (1.00) |
|
7q gain |
0.466 (1.00) |
0.442 (1.00) |
0.574 (1.00) |
0.488 (1.00) |
0.623 (1.00) |
0.798 (1.00) |
0.743 (1.00) |
|
8p gain |
0.242 (1.00) |
0.612 (1.00) |
0.305 (1.00) |
0.0707 (1.00) |
0.879 (1.00) |
0.0623 (1.00) |
0.336 (1.00) |
|
8q gain |
0.803 (1.00) |
0.613 (1.00) |
0.454 (1.00) |
0.432 (1.00) |
0.344 (1.00) |
0.694 (1.00) |
0.918 (1.00) |
|
9p gain |
0.84 (1.00) |
0.283 (1.00) |
0.977 (1.00) |
0.97 (1.00) |
0.677 (1.00) |
0.964 (1.00) |
||
9q gain |
0.84 (1.00) |
0.283 (1.00) |
0.977 (1.00) |
0.97 (1.00) |
0.677 (1.00) |
0.964 (1.00) |
||
10p gain |
0.0812 (1.00) |
0.378 (1.00) |
0.337 (1.00) |
0.0606 (1.00) |
0.0389 (1.00) |
0.881 (1.00) |
0.964 (1.00) |
|
12q gain |
0.911 (1.00) |
0.283 (1.00) |
0.448 (1.00) |
0.97 (1.00) |
0.677 (1.00) |
0.985 (1.00) |
||
15q gain |
0.547 (1.00) |
0.319 (1.00) |
0.337 (1.00) |
0.384 (1.00) |
0.305 (1.00) |
0.792 (1.00) |
0.615 (1.00) |
|
16p gain |
0.00325 (1.00) |
0.146 (1.00) |
1 (1.00) |
0.427 (1.00) |
0.36 (1.00) |
0.762 (1.00) |
||
17p gain |
0.308 (1.00) |
0.701 (1.00) |
0.283 (1.00) |
0.0376 (1.00) |
0.025 (1.00) |
0.677 (1.00) |
||
17q gain |
0.143 (1.00) |
0.741 (1.00) |
0.571 (1.00) |
0.587 (1.00) |
0.342 (1.00) |
0.837 (1.00) |
0.788 (1.00) |
|
18q gain |
0.899 (1.00) |
0.631 (1.00) |
1 (1.00) |
0.448 (1.00) |
0.488 (1.00) |
0.677 (1.00) |
0.485 (1.00) |
|
19p gain |
0.897 (1.00) |
0.635 (1.00) |
0.0489 (1.00) |
0.901 (1.00) |
0.85 (1.00) |
0.571 (1.00) |
0.843 (1.00) |
|
19q gain |
0.986 (1.00) |
0.844 (1.00) |
0.0875 (1.00) |
0.788 (1.00) |
0.701 (1.00) |
0.406 (1.00) |
0.808 (1.00) |
|
20p gain |
0.0931 (1.00) |
0.0827 (1.00) |
0.321 (1.00) |
0.691 (1.00) |
0.229 (1.00) |
0.109 (1.00) |
0.818 (1.00) |
|
20q gain |
0.16 (1.00) |
0.0562 (1.00) |
0.52 (1.00) |
0.789 (1.00) |
0.334 (1.00) |
0.0297 (1.00) |
0.707 (1.00) |
|
21q gain |
0.854 (1.00) |
0.631 (1.00) |
0.122 (1.00) |
0.726 (1.00) |
0.651 (1.00) |
0.664 (1.00) |
0.788 (1.00) |
|
22q gain |
0.158 (1.00) |
0.0275 (1.00) |
0.233 (1.00) |
0.788 (1.00) |
0.00755 (1.00) |
0.726 (1.00) |
0.0241 (1.00) |
|
Xq gain |
0.132 (1.00) |
0.194 (1.00) |
1 (1.00) |
0.17 (1.00) |
0.651 (1.00) |
0.772 (1.00) |
0.774 (1.00) |
|
1p loss |
0.783 (1.00) |
0.981 (1.00) |
0.52 (1.00) |
0.873 (1.00) |
0.118 (1.00) |
0.871 (1.00) |
0.13 (1.00) |
|
1q loss |
0.807 (1.00) |
0.0453 (1.00) |
0.61 (1.00) |
0.726 (1.00) |
0.000158 (0.0686) |
0.664 (1.00) |
0.00233 (1.00) |
|
2p loss |
0.283 (1.00) |
0.977 (1.00) |
0.97 (1.00) |
0.677 (1.00) |
0.964 (1.00) |
|||
2q loss |
0.00841 (1.00) |
0.61 (1.00) |
0.912 (1.00) |
0.941 (1.00) |
0.133 (1.00) |
0.997 (1.00) |
||
3p loss |
0.527 (1.00) |
0.781 (1.00) |
0.337 (1.00) |
0.783 (1.00) |
0.836 (1.00) |
0.792 (1.00) |
0.828 (1.00) |
|
3q loss |
0.515 (1.00) |
0.234 (1.00) |
0.283 (1.00) |
0.977 (1.00) |
0.97 (1.00) |
0.762 (1.00) |
||
4p loss |
0.283 (1.00) |
0.893 (1.00) |
1 (1.00) |
0.925 (1.00) |
0.903 (1.00) |
0.971 (1.00) |
0.971 (1.00) |
|
4q loss |
0.235 (1.00) |
0.993 (1.00) |
0.773 (1.00) |
0.845 (1.00) |
0.849 (1.00) |
0.743 (1.00) |
0.826 (1.00) |
|
5q loss |
0.00317 (1.00) |
0.968 (1.00) |
1 (1.00) |
0.726 (1.00) |
0.651 (1.00) |
0.707 (1.00) |
0.964 (1.00) |
|
6q loss |
0.4 (1.00) |
0.857 (1.00) |
0.5 (1.00) |
0.826 (1.00) |
0.879 (1.00) |
0.343 (1.00) |
0.959 (1.00) |
|
7p loss |
0.522 (1.00) |
0.68 (1.00) |
0.0489 (1.00) |
0.901 (1.00) |
0.85 (1.00) |
0.792 (1.00) |
0.0582 (1.00) |
|
7q loss |
0.693 (1.00) |
0.45 (1.00) |
0.233 (1.00) |
0.509 (1.00) |
0.937 (1.00) |
0.578 (1.00) |
0.328 (1.00) |
|
8p loss |
0.151 (1.00) |
0.132 (1.00) |
0.307 (1.00) |
0.559 (1.00) |
0.263 (1.00) |
0.797 (1.00) |
0.413 (1.00) |
|
8q loss |
0.412 (1.00) |
0.834 (1.00) |
0.337 (1.00) |
0.783 (1.00) |
0.85 (1.00) |
0.881 (1.00) |
0.229 (1.00) |
|
9p loss |
0.676 (1.00) |
0.479 (1.00) |
0.773 (1.00) |
0.845 (1.00) |
0.74 (1.00) |
0.489 (1.00) |
0.695 (1.00) |
|
9q loss |
0.316 (1.00) |
0.511 (1.00) |
0.755 (1.00) |
0.848 (1.00) |
0.863 (1.00) |
0.565 (1.00) |
0.79 (1.00) |
|
10p loss |
0.583 (1.00) |
0.0302 (1.00) |
0.547 (1.00) |
0.427 (1.00) |
0.97 (1.00) |
0.417 (1.00) |
||
10q loss |
0.264 (1.00) |
0.57 (1.00) |
0.741 (1.00) |
0.691 (1.00) |
0.569 (1.00) |
0.337 (1.00) |
0.574 (1.00) |
|
11p loss |
0.97 (1.00) |
0.27 (1.00) |
0.337 (1.00) |
0.901 (1.00) |
0.305 (1.00) |
0.792 (1.00) |
0.485 (1.00) |
|
11q loss |
0.135 (1.00) |
0.362 (1.00) |
1 (1.00) |
0.893 (1.00) |
0.834 (1.00) |
0.0641 (1.00) |
0.475 (1.00) |
|
12p loss |
0.318 (1.00) |
0.236 (1.00) |
0.61 (1.00) |
0.338 (1.00) |
0.000336 (0.146) |
0.772 (1.00) |
0.02 (1.00) |
|
13q loss |
0.578 (1.00) |
0.285 (1.00) |
1 (1.00) |
0.288 (1.00) |
0.66 (1.00) |
0.245 (1.00) |
0.224 (1.00) |
|
14q loss |
0.834 (1.00) |
0.415 (1.00) |
0.591 (1.00) |
0.622 (1.00) |
0.229 (1.00) |
0.557 (1.00) |
0.337 (1.00) |
|
15q loss |
0.741 (1.00) |
0.384 (1.00) |
1 (1.00) |
0.913 (1.00) |
0.937 (1.00) |
0.726 (1.00) |
0.908 (1.00) |
|
16p loss |
0.879 (1.00) |
0.487 (1.00) |
1 (1.00) |
0.217 (1.00) |
0.121 (1.00) |
0.0107 (1.00) |
0.287 (1.00) |
|
16q loss |
0.84 (1.00) |
0.31 (1.00) |
0.591 (1.00) |
0.157 (1.00) |
0.347 (1.00) |
0.173 (1.00) |
0.466 (1.00) |
|
17p loss |
0.32 (1.00) |
0.293 (1.00) |
1 (1.00) |
0.06 (1.00) |
0.111 (1.00) |
0.4 (1.00) |
0.756 (1.00) |
|
17q loss |
0.74 (1.00) |
0.0193 (1.00) |
0.283 (1.00) |
0.977 (1.00) |
0.97 (1.00) |
0.762 (1.00) |
||
18p loss |
0.00754 (1.00) |
0.000552 (0.239) |
0.691 (1.00) |
0.788 (1.00) |
0.244 (1.00) |
0.984 (1.00) |
0.843 (1.00) |
|
18q loss |
0.0964 (1.00) |
0.000999 (0.432) |
0.71 (1.00) |
0.925 (1.00) |
0.188 (1.00) |
0.971 (1.00) |
0.929 (1.00) |
|
19p loss |
0.33 (1.00) |
0.223 (1.00) |
0.153 (1.00) |
0.783 (1.00) |
0.836 (1.00) |
0.252 (1.00) |
0.925 (1.00) |
|
21q loss |
0.0315 (1.00) |
0.743 (1.00) |
0.0217 (1.00) |
0.925 (1.00) |
0.903 (1.00) |
0.409 (1.00) |
0.0114 (1.00) |
|
22q loss |
0.861 (1.00) |
0.668 (1.00) |
0.0579 (1.00) |
0.925 (1.00) |
0.561 (1.00) |
0.132 (1.00) |
0.809 (1.00) |
Cluster Labels | 1P GAIN MUTATED | 1P GAIN WILD-TYPE |
---|---|---|
Number of samples | 8 | 60 |
Cluster Labels | 1Q GAIN MUTATED | 1Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 36 | 32 |
Cluster Labels | 2P GAIN MUTATED | 2P GAIN WILD-TYPE |
---|---|---|
Number of samples | 8 | 60 |
Cluster Labels | 2Q GAIN MUTATED | 2Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 7 | 61 |
Cluster Labels | 3P GAIN MUTATED | 3P GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 65 |
P value = 1.74e-05 (Chi-square test), Q value = 0.0076
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 46 | 1 | 20 |
3P GAIN MUTATED | 1 | 1 | 1 |
3P GAIN WILD-TYPE | 45 | 0 | 19 |
Cluster Labels | 3Q GAIN MUTATED | 3Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 65 |
P value = 1.74e-05 (Chi-square test), Q value = 0.0076
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 46 | 1 | 20 |
3Q GAIN MUTATED | 1 | 1 | 1 |
3Q GAIN WILD-TYPE | 45 | 0 | 19 |
Cluster Labels | 4P GAIN MUTATED | 4P GAIN WILD-TYPE |
---|---|---|
Number of samples | 5 | 63 |
Cluster Labels | 5P GAIN MUTATED | 5P GAIN WILD-TYPE |
---|---|---|
Number of samples | 20 | 48 |
Cluster Labels | 5Q GAIN MUTATED | 5Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 14 | 54 |
Cluster Labels | 6P GAIN MUTATED | 6P GAIN WILD-TYPE |
---|---|---|
Number of samples | 13 | 55 |
Cluster Labels | 6Q GAIN MUTATED | 6Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 9 | 59 |
Cluster Labels | 7P GAIN MUTATED | 7P GAIN WILD-TYPE |
---|---|---|
Number of samples | 18 | 50 |
Cluster Labels | 7Q GAIN MUTATED | 7Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 19 | 49 |
Cluster Labels | 8P GAIN MUTATED | 8P GAIN WILD-TYPE |
---|---|---|
Number of samples | 11 | 57 |
Cluster Labels | 8Q GAIN MUTATED | 8Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 33 | 35 |
Cluster Labels | 9P GAIN MUTATED | 9P GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 65 |
Cluster Labels | 9Q GAIN MUTATED | 9Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 65 |
Cluster Labels | 10P GAIN MUTATED | 10P GAIN WILD-TYPE |
---|---|---|
Number of samples | 5 | 63 |
Cluster Labels | 12Q GAIN MUTATED | 12Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 65 |
Cluster Labels | 15Q GAIN MUTATED | 15Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 5 | 63 |
Cluster Labels | 16P GAIN MUTATED | 16P GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 65 |
Cluster Labels | 17P GAIN MUTATED | 17P GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 65 |
Cluster Labels | 17Q GAIN MUTATED | 17Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 17 | 51 |
Cluster Labels | 18Q GAIN MUTATED | 18Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 65 |
Cluster Labels | 19P GAIN MUTATED | 19P GAIN WILD-TYPE |
---|---|---|
Number of samples | 5 | 63 |
Cluster Labels | 19Q GAIN MUTATED | 19Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 7 | 61 |
Cluster Labels | 20P GAIN MUTATED | 20P GAIN WILD-TYPE |
---|---|---|
Number of samples | 12 | 56 |
Cluster Labels | 20Q GAIN MUTATED | 20Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 13 | 55 |
Cluster Labels | 21Q GAIN MUTATED | 21Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 4 | 64 |
Cluster Labels | 22Q GAIN MUTATED | 22Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 7 | 61 |
Cluster Labels | XQ GAIN MUTATED | XQ GAIN WILD-TYPE |
---|---|---|
Number of samples | 4 | 64 |
Cluster Labels | 1P LOSS MUTATED | 1P LOSS WILD-TYPE |
---|---|---|
Number of samples | 13 | 55 |
Cluster Labels | 1Q LOSS MUTATED | 1Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 4 | 64 |
P value = 0.000158 (Chi-square test), Q value = 0.069
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 46 | 1 | 20 |
1Q LOSS MUTATED | 1 | 1 | 2 |
1Q LOSS WILD-TYPE | 45 | 0 | 18 |
Cluster Labels | 2P LOSS MUTATED | 2P LOSS WILD-TYPE |
---|---|---|
Number of samples | 3 | 65 |
Cluster Labels | 2Q LOSS MUTATED | 2Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 4 | 64 |
Cluster Labels | 3P LOSS MUTATED | 3P LOSS WILD-TYPE |
---|---|---|
Number of samples | 5 | 63 |
Cluster Labels | 3Q LOSS MUTATED | 3Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 3 | 65 |
Cluster Labels | 4P LOSS MUTATED | 4P LOSS WILD-TYPE |
---|---|---|
Number of samples | 9 | 59 |
Cluster Labels | 4Q LOSS MUTATED | 4Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 16 | 52 |
Cluster Labels | 5Q LOSS MUTATED | 5Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 4 | 64 |
Cluster Labels | 6Q LOSS MUTATED | 6Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 11 | 57 |
Cluster Labels | 7P LOSS MUTATED | 7P LOSS WILD-TYPE |
---|---|---|
Number of samples | 5 | 63 |
Cluster Labels | 7Q LOSS MUTATED | 7Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 7 | 61 |
Cluster Labels | 8P LOSS MUTATED | 8P LOSS WILD-TYPE |
---|---|---|
Number of samples | 30 | 38 |
Cluster Labels | 8Q LOSS MUTATED | 8Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 5 | 63 |
Cluster Labels | 9P LOSS MUTATED | 9P LOSS WILD-TYPE |
---|---|---|
Number of samples | 16 | 52 |
Cluster Labels | 9Q LOSS MUTATED | 9Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 14 | 54 |
Cluster Labels | 10P LOSS MUTATED | 10P LOSS WILD-TYPE |
---|---|---|
Number of samples | 3 | 65 |
Cluster Labels | 10Q LOSS MUTATED | 10Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 12 | 56 |
Cluster Labels | 11P LOSS MUTATED | 11P LOSS WILD-TYPE |
---|---|---|
Number of samples | 5 | 63 |
Cluster Labels | 11Q LOSS MUTATED | 11Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 8 | 60 |
Cluster Labels | 12P LOSS MUTATED | 12P LOSS WILD-TYPE |
---|---|---|
Number of samples | 4 | 64 |
P value = 0.000336 (Chi-square test), Q value = 0.15
nPatients | N0 | N1 | NX |
---|---|---|---|
ALL | 46 | 1 | 20 |
12P LOSS MUTATED | 2 | 1 | 1 |
12P LOSS WILD-TYPE | 44 | 0 | 19 |
Cluster Labels | 13Q LOSS MUTATED | 13Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 23 | 45 |
Cluster Labels | 14Q LOSS MUTATED | 14Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 22 | 46 |
Cluster Labels | 15Q LOSS MUTATED | 15Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 7 | 61 |
Cluster Labels | 16P LOSS MUTATED | 16P LOSS WILD-TYPE |
---|---|---|
Number of samples | 14 | 54 |
Cluster Labels | 16Q LOSS MUTATED | 16Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 22 | 46 |
Cluster Labels | 17P LOSS MUTATED | 17P LOSS WILD-TYPE |
---|---|---|
Number of samples | 28 | 40 |
Cluster Labels | 17Q LOSS MUTATED | 17Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 3 | 65 |
Cluster Labels | 18P LOSS MUTATED | 18P LOSS WILD-TYPE |
---|---|---|
Number of samples | 7 | 61 |
P value = 0.000552 (t-test), Q value = 0.24
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 63 | 61.6 (14.4) |
18P LOSS MUTATED | 7 | 73.6 (6.4) |
18P LOSS WILD-TYPE | 56 | 60.1 (14.5) |
Cluster Labels | 18Q LOSS MUTATED | 18Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 9 | 59 |
Cluster Labels | 19P LOSS MUTATED | 19P LOSS WILD-TYPE |
---|---|---|
Number of samples | 5 | 63 |
Cluster Labels | 21Q LOSS MUTATED | 21Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 9 | 59 |
Cluster Labels | 22Q LOSS MUTATED | 22Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 9 | 59 |
-
Cluster data file = broad_values_by_arm.mutsig.cluster.txt
-
Clinical data file = LIHC-TP.clin.merged.picked.txt
-
Number of patients = 68
-
Number of clustering approaches = 64
-
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.