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Bioinformatics Vol. 19 no. 11 2003
Pages 1325-1332
© 2003 Oxford University Press

New normalization methods for cDNA microarray data

D.L. Wilson 1,*, M.J. Buckley 1, C.A. Helliwell 2 and I.W. Wilson 2

1 CSIRO Mathematical and Information Sciences, Locked Bag 17 North Ryde 1670 NSW, Australia
2 CSIRO Plant Industry, GPO Box 1600 Canberra ACT 2601, Australia

Received on May 6, 2002 ; revised on September 2, 2002 and December 17, 2002 ; accepted on December 20, 2002

Motivation: The focus of this paper is on two new normalization methods for cDNA microarrays. After the image analysis has been performed on a microarray and before differentially expressed genes can be detected, some form of normalization must be applied to the microarrays. Normalization removes biases towards one or other of the fluorescent dyes used to label each mRNA sample allowing for proper evaluation of differential gene expression.

Results: The two normalization methods that we present here build on previously described non-linear normalization techniques. We extend these techniques by firstly introducing a normalization method that deals with smooth spatial trends in intensity across microarrays, an important issue that must be dealt with. Secondly we deal with normalization of a new type of cDNA microarray experiment that is coming into prevalence, the small scale specialty or ‘boutique’ array, where large proportions of the genes on the microarrays are expected to be highly differentially expressed.

Availability: The normalization methods described in this paper are available via http://www.pi.csiro.au/gena/ in a software suite called tRMA: tools for R Microarray Analysis upon request of the authors. Images and data used in this paper are also available via the same link.

Contact: dwilson{at}gmp.usyd.edu.au

* To whom correspondence should be addressed.


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