vulcan.pathways {vulcan} | R Documentation |
This function applies Gene Set Enrichment Analysis or Rank Enrichment Analysis over a ChIP-Seq signature contained in a vulcan package object
vulcan.pathways(vobj, pathways, contrast = NULL, method = c("GSEA", "REA"), np = 1000)
vobj |
a list, the output of the |
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 |
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)
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')