dupicc {ENmix} | R Documentation

## Methylation duplicates evaluation.

### Description

Calcuate ICC (consistency and twoway) and Pearson's correlation coefficient for each CpG probes. Calculate Pearson's correlation coefficient and methylation differences between duplicate samples.

### Usage

    dupicc(dat,dupid,mvalue=FALSE,center=FALSE,ncores=2,qcflag=FALSE,qc=NULL,detPthre=0.05,nbthre=3)

### Arguments

`dat` | Methylation beta value matrix
`dupid` | A data frame with two variables, id1 and id2, for corresponding duplicates ids in methylation matrix
`mvalue` | Whether to convert to M value for calculation of ICC
`center` | Whether methylation beta values will be centered for calculation of correlation between duplicate samples
`ncores` | Number of core will be used for calculation of ICC
`qcflag` | Whether to perform QC before calculation of ICC
`qc` | QC object from ENmix package
`detPthre` | Detection P value threshold to identify low quality data point
`nbthre` | Number of bead threshold to identify low quality data point

### Value

icc: a data frame contain ICC and P values for each probes

dupcor: a data frame contain Pearson's correlation and averaged absolute difference between duplicates.

### 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.

### Examples

    if(FALSE){
    if (require(minfiData)) {
    sheet <- read.metharray.sheet(file.path(find.package("minfiData"),"extdata"), pattern = "csv$")
    rgSet <- read.metharray.exp(targets = sheet,extended = TRUE)
    mdat=preprocessRaw(rgSet)
    beta=getBeta(mdat,"Illumina")
    dupidx=data.frame(id1=c("5723646052_R02C02","5723646052_R04C01","5723646052_R05C02"),
    id2=c("5723646053_R04C02","5723646053_R05C02","5723646053_R06C02"))
    iccresu<-dupicc(dat=beta,dupid=dupidx)
    }}

[Package ENmix version 1.21.6 Index]