medianNormalise: Median normalise data in a matrix

In markdunning/beadarray-devel: Quality assessment and low-level analysis for Illumina BeadArray data

Description

Normalises expression intensities so that the intensities or log-ratios have equal median values across a series of arrays (columns).

Usage

medianNormalise(exprs, log=TRUE)

Arguments

exprs	a matrix of expression values
log	if TRUE then do a log2 transformation prior to normalising

Details

Normalisation is intended to remove from the expression measures any systematic trends which arise from the microarray technology rather than from differences between the probes or between the target RNA samples hybridized to the arrays.

For median normalisation, the intensity for each gene is adjusted by subtracting the median of all genes on the array and then adding the median across all arrays. The effect is that each array then has the same median value.

Value

Produces a matrix of normalised intensity values (on the log2 scale by default) with the same dimensions as exprs.

Author(s)

Mark Dunning

Examples

if(require(beadarrayExampleData)){

data(exampleSummaryData)

exampleSummaryData.log2 <- channel(exampleSummaryData,"G")

exampleSummaryData.med = assayDataElementReplace(exampleSummaryData.log2, "exprs", medianNormalise(exprs(exampleSummaryData.log2)))

}

markdunning/beadarray-devel documentation built on May 21, 2019, noon