mpreprocess: A pipeline to perform background correction, dye bias...

In USCbiostats/ENmixUSC: Data preprocessing and quality control for Illumina HumanMethylation450 and MethylationEPIC BeadChip (USC version)

Description

Fuction mpreprocess is a pipeline to easy preprocess steps for Illumina DNA methylation BeadChip. It comprehensively removes background noise and correct bias due to array design, including background correction, dye bias correction, inter-array normalization, probe type bias correction. It will also identify and exclude low quality samples and probes, remove outlier values, and perform imputation.

Usage

    mpreprocess(rgSet,nCores=1,bgParaEst="oob",dyeCorr="RELIC",
                qc=FALSE,qnorm=TRUE,qmethod="quantile1",
                foutlier=TRUE,rmcr=FALSE,impute=FALSE)

Arguments

rgSet	An object of class RGChannelSetExtended, RGChannelSet or MethylSet.
nCores	Number of cores will be used for computation
bgParaEst	Method to estimate background normal distribution parameters. This must be one of the strings: "oob","est", or "neg".
dyeCorr	Dye bias correction, "mean": correction based on averaged red/green ratio; or "RELIC": correction with RELIC method; or "none": no dye bias correction. The default is RELIC
qc	If TRUE, QC will be performed. Low quality samples and CpGs will be excluded before background correction.
qnorm	If TRUE, inter-array quantile normalization will be performed.
qmethod	Quantile normalization method. This should be one of the following strings: "quantile1", "quantile2", or "quantile3". See details in function norm.quantile.
foutlier	If TRUE, outlier and low quality values will be filtered out.
rmcr	TRUE: excluded rows and columns with more than 5% of missing values. FALSE is in default
impute	Whether to impute missing values. If TRUE, k-nearest neighbor's methods will be used for imputation. FALSE is in default.

Details

Fuction mpreprocess is a pipeline that perform methylaiton data preprocessing and quality controls using functions: preprocessENmix, norm.quantile, rcp, QCinfo and rm.outlier. More customized preprocessing steps can be achieved using the individual functions.

Value

a methylation beta value matrix.

Author(s)

Zongli Xu

References

Zongli Xu, Liang Niu, Leping Li and Jack A. Taylor, ENmix: a novel background correction method for Illumina HumanMethylation450 BeadChip. Nucleic Acids Research 2015.

Zongli Xu, Sabine A. S. Langie, Patrick De Boever, Jack A. Taylor1 and Liang Niu, RELIC: a novel dye-bias correction method for Illumina Methylation BeadChip, in review 2016

Liang Niu, Zongli Xu and Jack A. Taylor: RCP: a novel probe design bias correction method for Illumina Methylation BeadChip, Bioinformatics 2016

See Also

Package minfi for classes RGChannelSet and MethylSet

Examples

if(FALSE){
if (require(minfiData)) {
beta=mpreprocess(RGsetEx,nCores=6)

sheet <- read.metharray.sheet(file.path(find.package("minfiData"),"extdata"), pattern = "csv$")
rgSet <- read.metharray.exp(targets = sheet,extended = TRUE)
beta=mpreprocess(rgSet,nCores=6,qc=TRUE,foutlier=TRUE,rmcr=TRUE,impute=TRUE)
}}

USCbiostats/ENmixUSC documentation built on June 1, 2019, 3:55 a.m.