medianNormalise {beadarray} | R Documentation

## Median normalise data in a matrix

### 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)))

    }

[Package beadarray version 2.30.0 Index]