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Bioinformatics Advance Access originally published online on July 28, 2006
Bioinformatics 2006 22(20):2547-2553; doi:10.1093/bioinformatics/btl412
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Variance stabilization and normalization for one-color microarray data using a data-driven multiscale approach

E. S. Motakis 1, G. P. Nason 1,*, P. Fryzlewicz 1 and G. A. Rutter 2

1 Department of Mathematics, University of Bristol Bristol, UK
2 Department of Biochemistry, University of Bristol Bristol, UK

*To whom correspondence should be addressed.

Motivation: Many standard statistical techniques are effective on data that are normally distributed with constant variance. Microarray data typically violate these assumptions since they come from non-Gaussian distributions with a non-trivial mean–variance relationship. Several methods have been proposed that transform microarray data to stabilize variance and draw its distribution towards the Gaussian. Some methods, such as log or generalized log, rely on an underlying model for the data. Others, such as the spread-versus-level plot, do not. We propose an alternative data-driven multiscale approach, called the Data-Driven Haar–Fisz for microarrays (DDHFm) with replicates. DDHFm has the advantage of being ‘distribution-free’ in the sense that no parametric model for the underlying microarray data is required to be specified or estimated; hence, DDHFm can be applied very generally, not just to microarray data.

Results: DDHFm achieves very good variance stabilization of microarray data with replicates and produces transformed intensities that are approximately normally distributed. Simulation studies show that it performs better than other existing methods. Application of DDHFm to real one-color cDNA data validates these results.

Availability: The R package of the Data-Driven Haar–Fisz transform (DDHFm) for microarrays is available in Bioconductor and CRAN.

Contact: g.p.nason{at}bristol.ac.uk

Received on November 4, 2005; revised on July 4, 2006; accepted on July 21, 2006

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