## ---- eval=FALSE, message=FALSE, warning=FALSE----------------------------- # library(LOLA) # library(COCOA) ## ---- eval=FALSE, message=FALSE, warning=FALSE----------------------------- # # the genomic coordinates # signalCoord <- methylData$coordinates # # consider whether centering or scaling is needed # mPCA <- prcomp(x=t(methylData$methylProp), center=TRUE, scale.=FALSE) ## ---- eval=FALSE, message=FALSE, warning=FALSE----------------------------- # # reading in the region sets # # load LOLA database # lolaPath <- paste0("path/to/LOLACore/genomeVersion/") # regionSetDB <- loadRegionDB(lolaPath) # # # metadata about the region sets # loRegionAnno <- regionSetDB$regionAnno # lolaCoreRegionAnno <- loRegionAnno # collections <- c("cistrome_cistrome", "cistrome_epigenome", "codex", # "encode_segmentation", "encode_tfbs", "ucsc_features") # collectionInd <- lolaCoreRegionAnno$collection %in% collections # lolaCoreRegionAnno <- lolaCoreRegionAnno[collectionInd, ] # regionSetName <- lolaCoreRegionAnno$filename # regionSetDescription <- lolaCoreRegionAnno$description # # # the actual region sets # GRList <- GRangesList(regionSetDB$regionGRL[collectionInd]) # # # since we have what we need, we can delete this to free up memory # rm("regionSetDB") ## ---- eval=FALSE, message=FALSE, warning=FALSE----------------------------- # PCsToAnnotate <- paste0("PC", 1:6) # regionSetScores <- runCOCOA(loadingMat=mPCA$rotation, # signalCoord=signalCoord, # GRList=GRList, # PCsToAnnotate=PCsToAnnotate, # scoringMetric="regionMean") # regionSetScores$regionSetName <- regionSetName # regionSetScores$regionSetDescription <- regionSetDescription ## ---- eval=FALSE, message=FALSE, warning=FALSE----------------------------- # View(regionSetScores[order(regionSetScores$PC1, decreasing=TRUE), ]) # View(regionSetScores[order(regionSetScores$PC2, decreasing=TRUE), ]) # # etc.