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]