vulcan.pathways: Function to calculate pathway enrichment over a ChIP-Seq...

In vulcan: VirtUaL ChIP-Seq data Analysis using Networks

Description

This function applies Gene Set Enrichment Analysis or Rank Enrichment Analysis over a ChIP-Seq signature contained in a vulcan package object

Usage

vulcan.pathways(vobj, pathways, contrast = NULL, method = c("GSEA",
  "REA"), np = 1000)

Arguments

vobj	a list, the output of the 'vulcan.annotate' function
pathways	a list of vectors, one vector of gene identifiers per pathway
contrast	a vector with the name of the two conditions to compare. If method=='REA', contrast can be set to 'all', and Rank Enrichment Analysis will be performed for every sample independently, compared to the mean of the dataset.
method	either 'REA' for Rank Enrichment Analysis or 'GSEA' for Gene Set Enrichment Analysis
np	numeric, only for GSEA, the number of permutations to build the null distribution. Default is 1000

Value

if method=='GSEA', a named vector, with pathway names as names, and the normalized enrichment score of either the GSEA as value. If method=='REA', a matrix, with pathway names as rows and specific contrasts as columns (the method 'REA' allows for multiple contrasts to be calculated at the same time)

Examples

library(vulcandata)
vfile<-tempfile()
vulcandata::vulcansheet(vfile)
#vobj<-vulcan.import(vfile)
vobj<-vulcandata::vulcanexample()
unlink(vfile)
vobj<-vulcan.annotate(vobj,lborder=-10000,rborder=10000,method='sum')
vobj<-vulcan.normalize(vobj)
# Create a dummy pathway list (in entrez ids)
pathways<-list(
   pathwayA=rownames(vobj$normalized)[1:20],
   pathwayB=rownames(vobj$normalized)[21:50]
)
# Which contrast groups can be queried
names(vobj$samples)
results_gsea<-vulcan.pathways(vobj,pathways,contrast=c('t90','t0'),
method='GSEA')
results_rea<-vulcan.pathways(vobj,pathways,contrast=c('all'),method='REA')

vulcan documentation built on Nov. 8, 2020, 8:15 p.m.