4.Normalization {limma}R Documentation

Normalization of Microarray Data

Description

This page gives an overview of the LIMMA functions available to normalize data from spotted two-colour microarrays. Smyth and Speed (2003) give an overview of the normalization techniques implemented in the functions.

Usually data from spotted microarrays will be normalized using normalizeWithinArrays. A minority of data will also be normalized using normalizeBetweenArrays if diagnostic plots suggest a difference in scale between the arrays.

In rare circumstances, data might be normalized using normalizeForPrintorder before using normalizeWithinArrays.

If one is planning analysis of single-channel information from the microarrays rather than analysis of differential expression based on log-ratios, then the data should be normalized using a single channel-normalization technique. Single channel normalization uses further options of the normalizeBetweenArrays function. For more details see the LIMMA User's Guide which includes a section on single-channel normalization.

normalizeWithinArrays uses utility functions loessFit and normalizeRobustSpline. normalizeBetweenArrays uses utility functions normalizeMedians, normalizeMedianDeviations and normalizeQuantiles, none of which need to be called directly by users.

Backgound Correction

Usually one doesn't need to explicitly ask for background correction of the intensities because this is done by default by normalizeWithinArrays, which subtract the background from the foreground intensities before applying the normalization method. This default background correction method can be over-ridden by using backgroundCorrect which offers a number of alternative background correct methods to simple subtraction. Simply use backgroundCorrect to correct the RGList before applying normalizeWithinArrays.

kooperberg is a Bayesian background correction tool designed specifically for GenePix data. kooperberg is not currently used as the default method for GenePix data because it is computationally intensive. It requires several columns of the Genepix data files which are not read in my read.maimages, so you will need to use read.series instead of read.maimages if you wish to use kooperberg.

Author(s)

Gordon Smyth

References

Smyth, G. K., and Speed, T. P. (2003). Normalization of cDNA microarray data. In: METHODS: Selecting Candidate Genes from DNA Array Screens: Application to Neuroscience, D. Carter (ed.). To appear. http://www.statsci.org/smyth/pubs/normalize.pdf


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