## ----- echo = false，警告= false --------------------------------------------------------------------------------- -- -- -- -- -library(MIRA) data(exampleBins) plotMIRAProfiles(exampleBins) exScores <- calcMIRAScore(exampleBins, regionSetIDColName="featureID", sampleIDColName="sampleName") # normally sampleType would come from annotation object # but for this example we are manually adding sampleType column sampleType <- c("Condition1", "Condition2") exScores <- cbind(exScores, sampleType) exScores ## ----------------------------------------------------------------------------- data("exampleBSDT", package="MIRA") head(exampleBSDT) ## ---- message=FALSE----------------------------------------------------------- data("exampleRegionSet", package="MIRA") head(exampleRegionSet) ## ---- message=FALSE----------------------------------------------------------- library(MIRA) library(GenomicRanges) # for the `resize`, `width` functions data("exampleRegionSet", package="MIRA") data("exampleBSDT", package="MIRA") ## ----------------------------------------------------------------------------- BSDTList <- list(exampleBSDT) names(BSDTList) <- "Gm06990_1" ## ----------------------------------------------------------------------------- BSDTList <- addMethPropCol(BSDTList) ## ----------------------------------------------------------------------------- mean(width(exampleRegionSet)) ## ----------------------------------------------------------------------------- exampleRegionSet <- resize(exampleRegionSet, 4000, fix="center") mean(width(exampleRegionSet)) ## ----------------------------------------------------------------------------- exampleRegionSetGRL <- GRangesList(exampleRegionSet) names(exampleRegionSetGRL) <- "lymphoblastoid_NRF1" ## ----Aggregate_methylation, message=FALSE, warning=FALSE---------------------- bigBin <- lapply(X=BSDTList, FUN=aggregateMethyl, GRList=exampleRegionSetGRL, binNum=11) bigBinDT <- bigBin[[1]] ## ----Plot profiles, message=FALSE, warning=FALSE------------------------------ sampleName = rep(names(bigBin), nrow(bigBinDT)) bigBinDT = cbind(bigBinDT, sampleName) plotMIRAProfiles(binnedRegDT=bigBinDT) ## ----Scoring, warning=FALSE--------------------------------------------------- sampleScores <- calcMIRAScore(bigBinDT, regionSetIDColName="featureID", sampleIDColName="sampleName") head(sampleScores) ## ---- eval=FALSE-------------------------------------------------------------- # library(LOLA) # pathToDB <- "path/to/LOLACore/hg38" # regionDB <- loadRegionDB(pathToDB)