Nothing
## ----style, echo=FALSE, results="asis", message=FALSE-------------------------
knitr::opts_chunk$set(tidy = FALSE,
warning = FALSE,
message = FALSE)
## ----library, echo=FALSE, results='hide', message=FALSE-----------------------
require(minfi)
## -----------------------------------------------------------------------------
require(funtooNorm)
require(minfiData)
# We randomly assign cell types for the purpose of this example.
pData(RGsetEx)$cell_type <- rep(c("type1","type2"),3)
mySampleSet=fromRGChannelSet(RGsetEx)
## -----------------------------------------------------------------------------
origBeta <- getRawBeta(mySampleSet)
origBeta[1:3,1:3]
## -----------------------------------------------------------------------------
plotValidationGraph(mySampleSet, type.fits="PCR")
## ----normalize data-----------------------------------------------------------
mySampleSet=funtooNorm(mySampleSet,type.fits="PCR",ncmp=3)
mySampleSet
normBeta <- getNormBeta(mySampleSet)
normBeta[1:3,1:3]
## -----------------------------------------------------------------------------
#technical replicates are fictional, just for demonstration purposes.
agreement(origBeta, c(1:5,5)) # M for data before the normalization
agreement(normBeta, c(1:5,5)) # M for data after normalization
## -----------------------------------------------------------------------------
library(minfi)
age=pData(RGsetEx)$age
dmp=dmpFinder(getNormM(mySampleSet), age, type="continuous")
dmp[1:2,]
## -----------------------------------------------------------------------------
phenoData <- pData(RGsetEx)[,c("age","sex","status")]
genomerange <- getGRanges(mySampleSet)
grs <- GenomicRatioSet(gr=genomerange,
Beta=normBeta,
preprocessMethod="funtooNorm",
metadata=list(pData=phenoData))
grs
## ----echo=FALSE---------------------------------------------------------------
sessionInfo()
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