RankSum: transforming the relevance score into ranks for each sample
In weitinging/MinNetRank: An easy and efficient network-based method of integrating multi-omics data for cancer genes discovery
Description
Usage
Arguments
Value
Author(s)
Description
transforming the relevance score into ranks for each sample and calculating the sum of per-sample ranks as population-level gene ranking
Usage
1
RankSum(RelevanceScores)
Arguments
RelevanceScores
the relevance score of gene for each individual sample
Value
matrix
Author(s)
Ting Wei <weitinging@sjtu.edu.cn>; Zhangsheng Yu
Maintainer: Ting Wei <weitinging@sjtu.edu.cn>
weitinging/MinNetRank documentation built on Dec. 29, 2019, 12:26 a.m.
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Description Usage Arguments Value Author(s)
Description
transforming the relevance score into ranks for each sample and calculating the sum of per-sample ranks as population-level gene ranking
Usage
1 | RankSum(RelevanceScores)
|
Arguments
RelevanceScores |
the relevance score of gene for each individual sample |
Value
matrix
Author(s)
Ting Wei <weitinging@sjtu.edu.cn>; Zhangsheng Yu Maintainer: Ting Wei <weitinging@sjtu.edu.cn>
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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