Nothing
## ---- echo=FALSE, warning=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)
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