rcp {ENmix} | R Documentation

## 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)
    }

[Package ENmix version 1.28.8 Index]