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Bioinformatics Advance Access published online on July 10, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm347
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Correcting for gene-specific dye bias in DNA microarrays using the method of maximum likelihood

Ryan Kelley 1,*, Hoda Feizi 2 and Trey Ideker 2

1Program in Bioinformatics, University of California, San Diego 9500 Gilman Drive, La Jolla, CA 92093-0412
2Department of Bioengineering, University of California, San Diego 9500 Gilman Drive, La Jolla, CA 92093-0412

*To whom correspondence should be addressed. Ryan Kelley, E-mail: rmkelley{at}ucsd.edu


  Abstract

Motivation:In two-color microarray experiments, well known differences exist in the labeling and hybridization efficiency of Cy3 and Cy5 dyes. Previous reports have revealed that these differences can vary on a gene-by-gene basis, an effect termed gene-specific dye bias. If uncorrected, this bias can influence the determination of differentially expressed genes.

Results:We show that the magnitude of the bias scales multiplicatively with signal intensity and is dependent on which nucleotide has been conjugated to the fluorescent dye. A method is proposed to account for gene-specific dye bias within a maximum likelihood error modeling framework. Using two different labeling schemes, we show that correcting for gene-specific dye bias results in the superior identification of differentially expressed genes within this framework. Improvement is also possible in related ANOVA approaches.

Availability:A software implementation of this procedure is freely available at http://cellcircuits.org/VERA.

Contact: rmkelley{at}ucsd.edu

Associate Editor: Dr. Joaquin Dopazo

Received on October 22, 2006; revised on June 21, 2007; accepted on June 27, 2007

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