## ----libraries, echo=FALSE, message=FALSE, warning=FALSE---------------------- suppressPackageStartupMessages({ library(RcisTarget) library(RcisTarget.hg19.motifDBs.cisbpOnly.500bp) library(DT) library(data.table) #require(visNetwork) }) ## ----------------------------------------------------------------------------- packageVersion("RcisTarget") ## ----------------------------------------------------------------------------- # Genes to analyze: txtFile <- paste(file.path(system.file('examples', package='RcisTarget')),"hypoxiaGeneSet.txt", sep="/") geneSets <- list(hypoxia=read.table(txtFile, stringsAsFactors=FALSE)[,1]) # Background: txtFile <- paste(file.path(system.file('examples', package='RcisTarget')),"randomGeneSet.txt", sep="/") # for the toy example we will use a few random genes background <- read.table(txtFile, stringsAsFactors=FALSE)[,1] ## ----------------------------------------------------------------------------- # A: Add background <- unique(c(geneSets$hypoxia, background)) # B: Intersect # geneSets$hypoxia <- intersect(geneSets$hypoxia, background) ## ----fig.height=3, fig.width=3------------------------------------------------ gplots::venn(list(background=background, geneLists=unlist(geneSets))) ## ----eval=FALSE--------------------------------------------------------------- # dbPath <- "~/databases/hg19-500bp-upstream-10species.mc9nr.feather" ## ----eval=FALSE--------------------------------------------------------------- # library(RcisTarget) # rankingsDb <- importRankings(dbPath, columns=background) # bgRanking <- reRank(rankingsDb) ## ----eval=FALSE--------------------------------------------------------------- # motifEnrichmentTable <- cisTarget(geneSets, bgRanking, # aucMaxRank=0.03*getNumColsInDB(bgRanking), # geneErnMaxRank=getNumColsInDB(bgRanking), # geneErnMethod = "icistarget") ## ----eval=FALSE--------------------------------------------------------------- # showLogo(motifEnrichmentTable)