## ----style, echo = FALSE, results = 'asis'-------------------------------
BiocStyle::markdown()

## ---- message=FALSE, warning=FALSE---------------------------------------
library(minfi)
library(minfiData)
library(sva)

## ----eval=FALSE----------------------------------------------------------
#  source("http://www.bioconductor.org/biocLite.R")
#  biocLite(c("minfiData", "sva"))

## ----eval=FALSE----------------------------------------------------------
#  library(devtools)
#  install_github("hansenlab/tutorial.450k")

## ------------------------------------------------------------------------
baseDir <- system.file("extdata", package="minfiData")
targets <- read.450k.sheet(baseDir)
targets
RGSet <- read.450k.exp(targets = targets)

## ------------------------------------------------------------------------
phenoData <- pData(RGSet)
phenoData[,1:6]

## ------------------------------------------------------------------------
manifest <- getManifest(RGSet)
manifest
head(getProbeInfo(manifest))

## ------------------------------------------------------------------------
MSet <- preprocessRaw(RGSet) 
MSet

## ------------------------------------------------------------------------
head(getMeth(MSet)[,1:3])
head(getUnmeth(MSet)[,1:3])

## ------------------------------------------------------------------------
RSet <- ratioConvert(MSet, what = "both", keepCN = TRUE)
RSet

## ------------------------------------------------------------------------
beta <- getBeta(RSet)

## ------------------------------------------------------------------------
GRset <- mapToGenome(RSet)
GRset

## ------------------------------------------------------------------------
beta <- getBeta(GRset)
M <- getM(GRset)
CN <- getCN(GRset)

## ------------------------------------------------------------------------
sampleNames <- sampleNames(GRset)
probeNames <- featureNames(GRset)
pheno <- pData(GRset)

## ------------------------------------------------------------------------
gr <- granges(GRset)
head(gr, n= 3)

## ------------------------------------------------------------------------
annotation <- getAnnotation(GRset)
names(annotation)

## ------------------------------------------------------------------------
head(getMeth(MSet)[,1:3])
head(getUnmeth(MSet)[,1:3])

## ------------------------------------------------------------------------
qc <- getQC(MSet)
head(qc)
plotQC(qc)

## ------------------------------------------------------------------------
densityPlot(MSet, sampGroups = phenoData$Sample_Group)

## ------------------------------------------------------------------------
densityBeanPlot(MSet, sampGroups = phenoData$Sample_Group)

## ------------------------------------------------------------------------
controlStripPlot(RGSet, controls="BISULFITE CONVERSION II")

## ---- eval=FALSE---------------------------------------------------------
#  qcReport(RGSet, pdf= "qcReport.pdf")

## ------------------------------------------------------------------------
predictedSex <- getSex(GRset, cutoff = -2)$predictedSex
head(predictedSex)

## ------------------------------------------------------------------------
plotSex(getSex(GRset, cutoff = -2))

## ------------------------------------------------------------------------
MSet.illumina <- preprocessIllumina(RGSet, bg.correct = TRUE,
                               normalize = "controls")

## ------------------------------------------------------------------------
MSet.swan <- preprocessSWAN(RGSet)

## ------------------------------------------------------------------------
GRset.quantile <- preprocessQuantile(RGSet, fixOutliers = TRUE,
  removeBadSamples = TRUE, badSampleCutoff = 10.5,
  quantileNormalize = TRUE, stratified = TRUE, 
  mergeManifest = FALSE, sex = NULL)

## ------------------------------------------------------------------------
MSet.noob <- preprocessNoob(RGSet)

## ------------------------------------------------------------------------
GRset.funnorm <- preprocessFunnorm(RGSet)

## ------------------------------------------------------------------------
snps <- getSnpInfo(GRset)
head(snps,10)

## ------------------------------------------------------------------------
GRset <- addSnpInfo(GRset)

## ------------------------------------------------------------------------
GRset <- dropLociWithSnps(GRset, snps=c("SBE","CpG"), maf=0)

## ---- eval=FALSE---------------------------------------------------------
#  library(FlowSorted.Blood.450k)
#  cellCounts <- estimateCellCounts(RGset)

## ------------------------------------------------------------------------
beta <- getBeta(GRset.funnorm)
age  <- pData(GRset.funnorm)$age
dmp <- dmpFinder(beta, pheno = age  , type = "continuous")
head(dmp)

## ------------------------------------------------------------------------
pheno <- pData(GRset.funnorm)$status
designMatrix <- model.matrix(~ pheno)

## ---- eval=FALSE---------------------------------------------------------
#  dmrs <- bumphunter(GRset.funnorm, design = designMatrix,
#               cutoff = 0.2, B=0, type="Beta")

## ---- eval=FALSE---------------------------------------------------------
#  dmrs <- bumphunter(GRset.funnorm, design = designMatrix,
#               cutoff = 0.2, B=1000, type="Beta")

## ---- eval=FALSE---------------------------------------------------------
#  library(doParallel)
#  registerDoParallel(cores = 3)

## ----  eval=FALSE--------------------------------------------------------
#  names(dmrs)
#  head(dmrs$table, n=3)

## ---- eval=FALSE---------------------------------------------------------
#  data("dmrs_B1000_c02")
#  head(dmrs$table)

## ------------------------------------------------------------------------
library(sva)
mval <- getM(GRset)[1:5000,]
pheno <- pData(GRset)
mod <- model.matrix(~as.factor(status), data=pheno)
mod0 <- model.matrix(~1, data=pheno)
sva.results <- sva(mval, mod, mod0)

## ---- eval=FALSE---------------------------------------------------------
#  ab <- compartments(grset.quantile, chr="chr14", resolution=100`1000)

## ------------------------------------------------------------------------
snps <- getSnpBeta(RGSet)
head(snps)

## ------------------------------------------------------------------------
oob <- getOOB(RGSet)

## ------------------------------------------------------------------------
sessionInfo()