column_rank: 1-100 matrix column-wise ranking
In LucaGiudice/Simpati: Pathway-based classifier exploits patient similarity network paradigm
Description
Usage
Arguments
Value
Description
column-wise ranks the values and then normalizes them between 1-100
Usage
1
column_rank(geno_p, par = T)
Arguments
geno_p
Matrix of profiles (genes x samples)
par
Boolean. Default TRUE. If FALSE diseable the parallel computing
Value
Produce a new matrix s.t. each gene has the rank of its original value in the sample
LucaGiudice/Simpati documentation built on Jan. 27, 2022, 11:42 p.m.
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Description Usage Arguments Value
Description
column-wise ranks the values and then normalizes them between 1-100
Usage
1 | column_rank(geno_p, par = T)
|
Arguments
geno_p |
Matrix of profiles (genes x samples) |
par |
Boolean. Default TRUE. If FALSE diseable the parallel computing |
Value
Produce a new matrix s.t. each gene has the rank of its original value in the sample
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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