HTSanalyzeR (version 2.24.0)

getTopGeneSets: Select top significant gene sets from GSEA results

Description

This is a generic function.

When implemented as the S4 method of class GSCA, this function selects top significant gene sets from GSEA results for user-specified gene collections. If 'ntop' is given, then top 'ntop' significant gene sets in gene set collections 'gscs' will be selected and their names will be returned. If 'allSig=TRUE', then all significant (adjusted p-value < 'pValueCutoff' see help("analyze")) gene sets will be selected and their names will be returned.

To use this function for objects of class GSCA:

getTopGeneSets(object, resultName, gscs, ntop=NULL, allSig=FALSE)

Usage

getTopGeneSets(object, ...)

Arguments

object

an object. When this function is implemented as the S4 method of class GSCA, this argument is an object of class GSCA.

...

other arguments (see below for the arguments supported by the method of class GSCA)

Value

a list of character vectors, each of which contains the names of top significant gene sets for each gene set collection

Examples

## Not run: 
# library(org.Dm.eg.db)
# library(KEGG.db)
# ##load data for enrichment analyses
# data("KcViab_Data4Enrich")
# ##select hits
# hits <- names(KcViab_Data4Enrich)[which(abs(KcViab_Data4Enrich) > 2)]
# ##set up a list of gene set collections
# PW_KEGG <- KeggGeneSets(species = "Dm")
# gscList <- list(PW_KEGG = PW_KEGG)
# ##create an object of class 'GSCA'
# gsca <- new("GSCA", listOfGeneSetCollections=gscList, geneList =
# KcViab_Data4Enrich, hits = hits)
# ##print summary of gsca
# summarize(gsca)
# ##do preprocessing (KcViab_Data4Enrich has already been preprocessed)
# gsca <- preprocess(gsca, species="Dm", initialIDs = "Entrez.gene", 
# keepMultipleMappings = TRUE, duplicateRemoverMethod = "max", 
# orderAbsValue = FALSE)
# ##print summary of gsca again
# summarize(gsca)
# ##do hypergeometric tests and GSEA
# gsca <- analyze(gsca, para = list(pValueCutoff = 0.05, pAdjustMethod 
# = "BH", nPermutations = 1000, minGeneSetSize = 100,exponent = 1))
# ##print summary of results
# summarize(gsca, what="Result")
# ##print top significant gene sets in GO.BP
# topPWKEGG<-getTopGeneSets(gsca, "GSEA.results", "PW_KEGG", allSig=TRUE)
# ## End(Not run)