slideMerge {arrayMagic}R Documentation

Averaging of two colour microarray replicas

Description

The mean of the expression values is calculated separately for each channel. If no se.exprs values are given in exprSetRGObject, se.exprs is set to the standard deviation of the expression values (which is possibly NA). If available it is set to the root-mean-square or the mean of the given se.exprs values depending on the argument seExprsHandling. The root-mean-square can be useful if the se.exprs values are estimated standard deviations based on the same number observations taken from identical distributions.

Usage

slideMerge(exprSetRGObject, slideMergeColumn, sampleAnnotationColumns, seExprsHandling="rootMeanSquare", verbose=TRUE)

Arguments

exprSetRGObject object of class exprSetRG; required; default missing
slideMergeColumn character string specifying the variable of the phenoData object of the exprSetRGObject, which is used to determine replicas; required; default missing
sampleAnnotationColumns vector of character strings; optional; default missing. A vector which contains all phenoData variables relevant for further analysis. The phenoData-annotation should be consistent for replicas. By default the argument sampleAnnotationColumns is missing and all phenoData variables are used.
seExprsHandling character string; either "rootMeanSquare" or "mean"; required; default "rootMeanSquare"
verbose logical; required; default: TRUE

Details

Value

object of class exprSetRG-class, i.e. the "merged" exprSetRGObject

Author(s)

Andreas Buness <a.buness@dkfz.de>

See Also

spotMerge, exprSetRG-class

Examples


  indGreen=1:2
  indRed=3:4
  channels <- matrix( c(indGreen,indRed), nrow=length(indGreen), byrow=FALSE )
  colnames(channels) <- c("green","red")
  exprsMatrix <- matrix(rep(1:10,4),nrow=10,ncol=4,byrow=FALSE)
  phenoMatrix <- matrix(c(c(1,2),c(3,3),c(5,5)),nrow=2,ncol=3,byrow=FALSE)
  colnames(phenoMatrix) <- c("one","two","usedForMerge")
  phenoMatrix <- rbind(phenoMatrix,phenoMatrix)
  eSA <- new("exprSetRG", exprs=exprsMatrix, phenoData=
             new("phenoData", pData=data.frame(phenoMatrix),
                 varLabels=as.list(colnames(phenoMatrix))),
             channels=channels)
  eSM <- slideMerge(exprSetRGObject=eSA, slideMergeColumn="usedForMerge")
  eSAOne <- slideSubset(eSA,j=c(1))
  stopifnot( all(exprs(eSAOne) == exprs(eSM) ))
  stopifnot( all( se.exprs(eSM) == 0 ) )

 

        

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