Non-negative control surrogate variables

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Description

Surrogate variables derived from intensity data for non-negative internal control probes. These variables can be modeled in association analysis to adjust for experimental batch effects.

Usage

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ctrlsva(rgSet,percvar=0.9,npc=1,flag=1)

Arguments

rgSet

An object of class RGChannelSet.

percvar

Minimum percentage of data variations can be explained by surrogate variables, range from 0 to 1,default is 0.9

npc

Number of surrogate variables, default is 1

flag

1: select number of surrogate variables based on argument percvar; 2: select number of surrogate variables based on argument npc

Value

ctrlsva: a matrix of surrogate variables (columns) with row corresponding to samples

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

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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)
sva<-ctrl(rgSet)
}}