beadarrayFilter (version 1.1.0)

varianceplot:

Observe between-array and within-array variances.

Description

plots the between array and the within array variances.

Usage

varianceplot(iccResults, q = 1, delta = 0.5)

Arguments

iccResults

Output from the iccFun function.

q

The quantile use for ICC at which one wants to declare bead types informative. If iccQuant is a vector, then q can take any value from 1 up to the length of iccQuant.

delta

The proposed cutoff point at which a bead type should be declared informative or non-informative.

Examples

require(beadarrayExampleData)
data(exampleSummaryData)
exampleSummaryDatalog2 <- channel(exampleSummaryData, "G")
exampleSummaryDataNorm <- normaliseIllumina(exampleSummaryDatalog2, 
method = "quantile", transform = "none")
aaa<-na.omit(data.frame(I(rownames(exprs(exampleSummaryDataNorm))),exprs(exampleSummaryDataNorm)))
ProbeID <- aaa[,1][1:100]
    eSet <- na.omit(exprs(exampleSummaryDataNorm))[1:100,]
    stddev <- na.omit(se.exprs(exampleSummaryDataNorm))[1:100,]
    nSet <- na.omit(attributes(exampleSummaryDataNorm)$assayData$nObservations)[1:100,]
    seSet<-stddev/sqrt(nSet)
    iccResults<-iccFun(eSet,seSet,nSet,ProbeID =ProbeID ,iccQuant=c(0,0.25,0.5,1),
    diffIcc=TRUE,keepData=TRUE)
    varianceplot(iccResults,q=1,delta=0.8)