quantileNormalise {beadarray} | R Documentation

## Quantile Normalisation for BeadLevelList objects

### Description

Normalizes expression intensities so that the intensities or log-ratios have similar distributions across a series of arrays.

Function is based on the 'normalizeBetweenArrays' function in 'limma'

### Usage

    quantileNormalise(BLData, arrays=1:length(BLData$R[1,]))

### Arguments

`BLData` | can be either an BeadLevelList or BeadSummaryList object
`arrays` | choose a subset of arrays to normalise

### Details

Quantile normalization was proposed by Bolstad et al (2003) for Affymetrix-style single-channel arrays and by Yang and Thorne (2003) for two-color cDNA arrays. 'method="quantile"' ensures that the intensities have the same empirical distribution across arrays and across channels.

### Value

Produces an BeadLevelList or BeadSummaryList (depending on input type) containing normalised intensity values.

### Author(s)

Mark Dunning

### See Also

`qsplineNormalise` `medianNormalise`

### Examples

    data(BSData)

    BSData.q = quantileNormalise(BSData)

    #All distributions are fixed to be the same

    boxplot(BSData.q$R~col(BSData.q$R))

[Package beadarray version 1.0.0 Index]