lleading.edge: lleading edge analysis

In galder-max/GSEAlite: GSEA lite performs simple GSEA analysis with few useful functions

Description

performs the leading edge analysis involving the running sum described in the GSEA methodology.

Usage

lleading.edge(k, s2n)

Arguments

k	boolean vector of length = number of genes. TRUE if the nth gene/row of the expression matrix is found in the gene set to be tested.
s2n	scores between two classes : see snr.SNR or snr.FC

Value

return a list with two elements : essmin is the minimum enrichment score in the running sum; essmax is the maximum enrichment score in the running score.

Author(s)

[e-mail]

See Also

snr.SNR; snr.FC; GSEA.plot

Examples

## generates random scores
scores<-rnorm(10000)

## generate boolean vector with 50 genes present in the 500 highest
   scores
k<-sample(which(rank(scores)<=500),50,rep=F)

## print the leading edge result of 50 random genes vs. 50 genes in top 500
lleading.edge(k,scores) ##top 500
lleading.edge(sample(k),scores) ##random

galder-max/GSEAlite documentation built on Jan. 30, 2021, 10:50 p.m.