This pipeline computes the correlation between significant arm-level copy number variations (cnvs) and selected clinical features.
Testing the association between subtypes identified by 44 different clustering approaches and 11 clinical features across 34 patients, 2 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 '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 '5p 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 '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 '10p 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 '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 correlate to 'TOBACCOSMOKINGHISTORYINDICATOR'.
-
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 '18p 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 correlate to 'RADIATIONS.RADIATION.REGIMENINDICATION'.
-
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 '3p 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 '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 '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 do not correlate to any clinical features.
-
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 '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 '21q loss mutation analysis'. These subtypes do not correlate to any clinical features.
Clinical Features |
Time to Death |
AGE |
HISTOLOGICAL TYPE |
RADIATIONS RADIATION REGIMENINDICATION |
NUMBERPACKYEARSSMOKED | STOPPEDSMOKINGYEAR | TOBACCOSMOKINGHISTORYINDICATOR |
DISTANT METASTASIS |
LYMPH NODE METASTASIS |
NUMBER OF LYMPH NODES |
TUMOR STAGECODE |
Statistical Tests | logrank test | t-test | Chi-square test | Fisher's exact test | t-test | t-test | t-test | Fisher's exact test | Fisher's exact test | t-test | t-test |
1p gain |
0.814 (1.00) |
0.0637 (1.00) |
0.136 (1.00) |
1 (1.00) |
0.528 (1.00) |
0.339 (1.00) |
1 (1.00) |
0.917 (1.00) |
|||
1q gain |
0.553 (1.00) |
0.129 (1.00) |
0.217 (1.00) |
0.276 (1.00) |
0.969 (1.00) |
0.862 (1.00) |
0.106 (1.00) |
1 (1.00) |
0.463 (1.00) |
||
2p gain |
0.0598 (1.00) |
0.717 (1.00) |
0.732 (1.00) |
0.201 (1.00) |
0.769 (1.00) |
0.532 (1.00) |
1 (1.00) |
||||
3p gain |
0.688 (1.00) |
0.791 (1.00) |
0.0653 (1.00) |
1 (1.00) |
0.589 (1.00) |
0.22 (1.00) |
0.537 (1.00) |
0.414 (1.00) |
|||
3q gain |
0.113 (1.00) |
0.132 (1.00) |
0.326 (1.00) |
1 (1.00) |
0.268 (1.00) |
0.404 (1.00) |
1 (1.00) |
0.696 (1.00) |
0.565 (1.00) |
||
5p gain |
0.667 (1.00) |
0.495 (1.00) |
0.314 (1.00) |
1 (1.00) |
0.4 (1.00) |
0.822 (1.00) |
0.158 (1.00) |
0.372 (1.00) |
0.164 (1.00) |
||
6p gain |
0.221 (1.00) |
0.191 (1.00) |
0.389 (1.00) |
0.328 (1.00) |
0.235 (1.00) |
0.633 (1.00) |
1 (1.00) |
0.8 (1.00) |
|||
7q gain |
0.268 (1.00) |
0.273 (1.00) |
0.191 (1.00) |
0.0666 (1.00) |
0.321 (1.00) |
0.568 (1.00) |
0.611 (1.00) |
0.556 (1.00) |
|||
8p gain |
0.747 (1.00) |
0.294 (1.00) |
0.868 (1.00) |
1 (1.00) |
0.888 (1.00) |
0.28 (1.00) |
1 (1.00) |
0.443 (1.00) |
|||
8q gain |
0.547 (1.00) |
0.357 (1.00) |
0.629 (1.00) |
1 (1.00) |
0.645 (1.00) |
1 (1.00) |
1 (1.00) |
0.704 (1.00) |
|||
10p gain |
0.283 (1.00) |
0.459 (1.00) |
0.732 (1.00) |
0.539 (1.00) |
0.294 (1.00) |
1 (1.00) |
0.537 (1.00) |
0.414 (1.00) |
|||
12p gain |
0.418 (1.00) |
0.366 (1.00) |
0.0392 (1.00) |
1 (1.00) |
0.218 (1.00) |
0.0559 (1.00) |
1 (1.00) |
0.917 (1.00) |
|||
12q gain |
0.469 (1.00) |
0.575 (1.00) |
0.191 (1.00) |
0.564 (1.00) |
0.321 (1.00) |
0.076 (1.00) |
0.611 (1.00) |
0.556 (1.00) |
|||
14q gain |
0.158 (1.00) |
0.82 (1.00) |
0.732 (1.00) |
1 (1.00) |
0.339 (1.00) |
1 (1.00) |
0.537 (1.00) |
0.593 (1.00) |
|||
15q gain |
0.745 (1.00) |
0.771 (1.00) |
0.732 (1.00) |
0.539 (1.00) |
9.97e-05 (0.0364) |
1 (1.00) |
0.279 (1.00) |
0.00565 (1.00) |
|||
16p gain |
0.745 (1.00) |
0.818 (1.00) |
0.191 (1.00) |
1 (1.00) |
0.769 (1.00) |
1 (1.00) |
0.537 (1.00) |
0.414 (1.00) |
|||
16q gain |
0.205 (1.00) |
0.0653 (1.00) |
1 (1.00) |
1 (1.00) |
1 (1.00) |
||||||
18p gain |
0.355 (1.00) |
0.304 (1.00) |
0.0653 (1.00) |
0.201 (1.00) |
0.401 (1.00) |
1 (1.00) |
0.537 (1.00) |
0.593 (1.00) |
|||
19q gain |
0.104 (1.00) |
0.87 (1.00) |
0.89 (1.00) |
0.000156 (0.0568) |
0.985 (1.00) |
0.439 (1.00) |
1 (1.00) |
0.611 (1.00) |
0.914 (1.00) |
||
20p gain |
0.119 (1.00) |
0.993 (1.00) |
0.178 (1.00) |
0.692 (1.00) |
0.0279 (1.00) |
0.72 (1.00) |
0.675 (1.00) |
0.425 (1.00) |
0.519 (1.00) |
||
20q gain |
0.00689 (1.00) |
0.332 (1.00) |
0.389 (1.00) |
0.714 (1.00) |
0.0279 (1.00) |
0.517 (1.00) |
0.675 (1.00) |
1 (1.00) |
0.872 (1.00) |
||
21q gain |
0.158 (1.00) |
0.0898 (1.00) |
0.732 (1.00) |
0.201 (1.00) |
0.589 (1.00) |
1 (1.00) |
0.537 (1.00) |
0.593 (1.00) |
|||
22q gain |
0.355 (1.00) |
0.167 (1.00) |
0.348 (1.00) |
0.618 (1.00) |
0.671 (1.00) |
1 (1.00) |
0.611 (1.00) |
0.556 (1.00) |
|||
3p loss |
0.403 (1.00) |
0.23 (1.00) |
0.672 (1.00) |
1 (1.00) |
0.193 (1.00) |
0.805 (1.00) |
1 (1.00) |
0.372 (1.00) |
0.247 (1.00) |
||
4p loss |
0.808 (1.00) |
0.317 (1.00) |
0.615 (1.00) |
0.704 (1.00) |
0.265 (1.00) |
0.883 (1.00) |
0.226 (1.00) |
1 (1.00) |
0.269 (1.00) |
||
4q loss |
0.221 (1.00) |
0.796 (1.00) |
0.909 (1.00) |
0.138 (1.00) |
0.937 (1.00) |
0.943 (1.00) |
0.568 (1.00) |
0.126 (1.00) |
0.181 (1.00) |
||
5q loss |
0.277 (1.00) |
0.119 (1.00) |
0.159 (1.00) |
0.683 (1.00) |
0.814 (1.00) |
0.792 (1.00) |
0.371 (1.00) |
1 (1.00) |
0.489 (1.00) |
||
7p loss |
0.838 (1.00) |
0.116 (1.00) |
0.556 (1.00) |
0.0666 (1.00) |
0.977 (1.00) |
0.502 (1.00) |
0.568 (1.00) |
0.611 (1.00) |
0.411 (1.00) |
||
7q loss |
0.00503 (1.00) |
0.391 (1.00) |
0.556 (1.00) |
0.0666 (1.00) |
0.907 (1.00) |
0.222 (1.00) |
0.532 (1.00) |
0.537 (1.00) |
0.383 (1.00) |
||
8p loss |
0.272 (1.00) |
0.708 (1.00) |
0.581 (1.00) |
0.431 (1.00) |
0.387 (1.00) |
1 (1.00) |
1 (1.00) |
0.704 (1.00) |
|||
9p loss |
0.0398 (1.00) |
0.742 (1.00) |
0.556 (1.00) |
0.564 (1.00) |
0.345 (1.00) |
0.532 (1.00) |
1 (1.00) |
0.718 (1.00) |
|||
9q loss |
0.0487 (1.00) |
0.353 (1.00) |
0.653 (1.00) |
1 (1.00) |
0.248 (1.00) |
0.532 (1.00) |
1 (1.00) |
0.718 (1.00) |
|||
10p loss |
0.118 (1.00) |
0.553 (1.00) |
0.835 (1.00) |
0.157 (1.00) |
0.52 (1.00) |
0.167 (1.00) |
0.076 (1.00) |
0.0472 (1.00) |
0.175 (1.00) |
||
10q loss |
0.0684 (1.00) |
0.704 (1.00) |
0.89 (1.00) |
0.328 (1.00) |
0.77 (1.00) |
0.0717 (1.00) |
0.287 (1.00) |
0.0156 (1.00) |
0.111 (1.00) |
||
11p loss |
0.418 (1.00) |
0.535 (1.00) |
0.835 (1.00) |
0.394 (1.00) |
0.119 (1.00) |
0.158 (1.00) |
1 (1.00) |
0.277 (1.00) |
|||
11q loss |
0.838 (1.00) |
0.767 (1.00) |
0.835 (1.00) |
0.157 (1.00) |
0.977 (1.00) |
0.666 (1.00) |
0.339 (1.00) |
0.641 (1.00) |
0.241 (1.00) |
||
12p loss |
0.439 (1.00) |
0.0155 (1.00) |
0.389 (1.00) |
0.644 (1.00) |
0.524 (1.00) |
1 (1.00) |
0.626 (1.00) |
0.261 (1.00) |
|||
13q loss |
0.317 (1.00) |
0.911 (1.00) |
0.721 (1.00) |
0.666 (1.00) |
0.723 (1.00) |
0.642 (1.00) |
1 (1.00) |
0.277 (1.00) |
|||
17p loss |
0.219 (1.00) |
0.249 (1.00) |
0.581 (1.00) |
0.431 (1.00) |
0.568 (1.00) |
0.662 (1.00) |
1 (1.00) |
1 (1.00) |
0.322 (1.00) |
||
17q loss |
0.825 (1.00) |
0.529 (1.00) |
0.653 (1.00) |
1 (1.00) |
0.861 (1.00) |
0.532 (1.00) |
1 (1.00) |
0.718 (1.00) |
|||
18p loss |
0.74 (1.00) |
0.478 (1.00) |
0.0506 (1.00) |
0.0477 (1.00) |
0.0279 (1.00) |
0.235 (1.00) |
1 (1.00) |
0.626 (1.00) |
0.261 (1.00) |
||
18q loss |
0.875 (1.00) |
0.653 (1.00) |
0.0653 (1.00) |
0.157 (1.00) |
0.0279 (1.00) |
0.119 (1.00) |
0.633 (1.00) |
0.372 (1.00) |
0.154 (1.00) |
||
19p loss |
0.34 (1.00) |
0.457 (1.00) |
0.556 (1.00) |
0.0666 (1.00) |
0.693 (1.00) |
1 (1.00) |
1 (1.00) |
||||
21q loss |
0.376 (1.00) |
0.966 (1.00) |
0.89 (1.00) |
0.148 (1.00) |
0.0676 (1.00) |
1 (1.00) |
0.372 (1.00) |
0.672 (1.00) |
Cluster Labels | 1P GAIN MUTATED | 1P GAIN WILD-TYPE |
---|---|---|
Number of samples | 7 | 27 |
Cluster Labels | 1Q GAIN MUTATED | 1Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 15 | 19 |
Cluster Labels | 2P GAIN MUTATED | 2P GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 31 |
Cluster Labels | 3P GAIN MUTATED | 3P GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 31 |
Cluster Labels | 3Q GAIN MUTATED | 3Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 21 | 13 |
Cluster Labels | 5P GAIN MUTATED | 5P GAIN WILD-TYPE |
---|---|---|
Number of samples | 9 | 25 |
Cluster Labels | 6P GAIN MUTATED | 6P GAIN WILD-TYPE |
---|---|---|
Number of samples | 6 | 28 |
Cluster Labels | 7Q GAIN MUTATED | 7Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 4 | 30 |
Cluster Labels | 8P GAIN MUTATED | 8P GAIN WILD-TYPE |
---|---|---|
Number of samples | 4 | 30 |
Cluster Labels | 8Q GAIN MUTATED | 8Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 7 | 27 |
Cluster Labels | 10P GAIN MUTATED | 10P GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 31 |
Cluster Labels | 12P GAIN MUTATED | 12P GAIN WILD-TYPE |
---|---|---|
Number of samples | 6 | 28 |
Cluster Labels | 12Q GAIN MUTATED | 12Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 4 | 30 |
Cluster Labels | 14Q GAIN MUTATED | 14Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 31 |
Cluster Labels | 15Q GAIN MUTATED | 15Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 31 |
P value = 9.97e-05 (t-test), Q value = 0.036
nPatients | Mean (Std.Dev) | |
---|---|---|
ALL | 33 | 1.8 (1.1) |
15Q GAIN MUTATED | 3 | 1.0 (0.0) |
15Q GAIN WILD-TYPE | 30 | 1.9 (1.1) |
Cluster Labels | 16P GAIN MUTATED | 16P GAIN WILD-TYPE |
---|---|---|
Number of samples | 4 | 30 |
Cluster Labels | 16Q GAIN MUTATED | 16Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 31 |
Cluster Labels | 18P GAIN MUTATED | 18P GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 31 |
Cluster Labels | 19Q GAIN MUTATED | 19Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 6 | 28 |
P value = 0.000156 (Fisher's exact test), Q value = 0.057
nPatients | NO | YES |
---|---|---|
ALL | 10 | 24 |
19Q GAIN MUTATED | 6 | 0 |
19Q GAIN WILD-TYPE | 4 | 24 |
Cluster Labels | 20P GAIN MUTATED | 20P GAIN WILD-TYPE |
---|---|---|
Number of samples | 11 | 23 |
Cluster Labels | 20Q GAIN MUTATED | 20Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 12 | 22 |
Cluster Labels | 21Q GAIN MUTATED | 21Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 3 | 31 |
Cluster Labels | 22Q GAIN MUTATED | 22Q GAIN WILD-TYPE |
---|---|---|
Number of samples | 5 | 29 |
Cluster Labels | 3P LOSS MUTATED | 3P LOSS WILD-TYPE |
---|---|---|
Number of samples | 9 | 25 |
Cluster Labels | 4P LOSS MUTATED | 4P LOSS WILD-TYPE |
---|---|---|
Number of samples | 14 | 20 |
Cluster Labels | 4Q LOSS MUTATED | 4Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 5 | 29 |
Cluster Labels | 5Q LOSS MUTATED | 5Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 10 | 24 |
Cluster Labels | 7P LOSS MUTATED | 7P LOSS WILD-TYPE |
---|---|---|
Number of samples | 4 | 30 |
Cluster Labels | 7Q LOSS MUTATED | 7Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 4 | 30 |
Cluster Labels | 8P LOSS MUTATED | 8P LOSS WILD-TYPE |
---|---|---|
Number of samples | 10 | 24 |
Cluster Labels | 9P LOSS MUTATED | 9P LOSS WILD-TYPE |
---|---|---|
Number of samples | 4 | 30 |
Cluster Labels | 9Q LOSS MUTATED | 9Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 3 | 31 |
Cluster Labels | 10P LOSS MUTATED | 10P LOSS WILD-TYPE |
---|---|---|
Number of samples | 7 | 27 |
Cluster Labels | 10Q LOSS MUTATED | 10Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 6 | 28 |
Cluster Labels | 11P LOSS MUTATED | 11P LOSS WILD-TYPE |
---|---|---|
Number of samples | 7 | 27 |
Cluster Labels | 11Q LOSS MUTATED | 11Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 7 | 27 |
Cluster Labels | 12P LOSS MUTATED | 12P LOSS WILD-TYPE |
---|---|---|
Number of samples | 6 | 28 |
Cluster Labels | 13Q LOSS MUTATED | 13Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 8 | 26 |
Cluster Labels | 17P LOSS MUTATED | 17P LOSS WILD-TYPE |
---|---|---|
Number of samples | 10 | 24 |
Cluster Labels | 17Q LOSS MUTATED | 17Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 3 | 31 |
Cluster Labels | 18P LOSS MUTATED | 18P LOSS WILD-TYPE |
---|---|---|
Number of samples | 6 | 28 |
Cluster Labels | 18Q LOSS MUTATED | 18Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 7 | 27 |
Cluster Labels | 19P LOSS MUTATED | 19P LOSS WILD-TYPE |
---|---|---|
Number of samples | 4 | 30 |
Cluster Labels | 21Q LOSS MUTATED | 21Q LOSS WILD-TYPE |
---|---|---|
Number of samples | 6 | 28 |
-
Cluster data file = broad_values_by_arm.mutsig.cluster.txt
-
Clinical data file = CESC-TP.clin.merged.picked.txt
-
Number of patients = 34
-
Number of clustering approaches = 44
-
Number of selected clinical features = 11
-
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 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 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 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.