rcp: Illumina methylation array probe type bias correction

In xuz1/ENmix: Quality control and analysis tools for Illumina DNA methylation BeadChip

Illumina methylation array probe type bias correction

Description

Probe design type bias correction using Regression on Correlated Probes (RCP) method

Usage

        rcp(mdat, dist=25, quantile.grid=seq(0.001,0.999,by=0.001), qcscore = NULL,
 nbthre=3, detPthre=0.000001)

Arguments

mdat	An object of class methDataSet or MethylSet.
dist	Maximum distance in base pair between type I and type II probe pairs for regression calibration
quantile.grid	Quantile grid used in linear regression
qcscore	Data quality infomation object, the output from function QCinfo. If the object is provied, low quality data points as defined by detection p value threshold (detPthre) or number of bead threshold (nbthre) will be set as missing values.
detPthre	Detection P value threshold to define low qualitye data points
nbthre	Number of beads threshold to define low qualitye data points, nbthre=3 in default.

Details

The function will first identify type I and type II probe pairs within a specified distance, and then perform linear regression calibration between the probe types. With the estimates the function will then adjust type II data using type I data as references.

Value

A beta value matrix

Author(s)

Liang Niu, Zongli Xu

References

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

Examples

if (require(minfiData)) {
#methDataSet as input
path <- file.path(find.package("minfiData"),"extdata")
rgSet <- readidat(path = path,recursive = TRUE)
qc=QCinfo(rgSet)
mdat=preprocessENmix(rgSet,QCinfo=qc,nCores=6)
mdat=norm.quantile(mdat,method="quantile1")
beta=rcp(mdat)

#methylset as input
sheet <- read.metharray.sheet(file.path(find.package("minfiData"),"extdata"),
 pattern = "csv$")
rgSet <- read.metharray.exp(targets = sheet,extended = TRUE)
qc=QCinfo(rgSet)
mdat=preprocessENmix(rgSet,QCinfo=qc,nCores=6)
mdat=norm.quantile(mdat,method="quantile1")
beta=rcp(mdat)
}

xuz1/ENmix documentation built on Aug. 5, 2023, 7:11 a.m.