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Bioinformatics. 2008 Jan 1;24(1):71-7. Epub 2007 Jul 10.

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

Author information

  • 1Program in Bioinformatics and Department of Bioengineering, University of California, San Diego 9500 Gilman Drive, La Jolla, CA 92093-0412, USA. rmkelley@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

PMID:
17623705
[PubMed - indexed for MEDLINE]
PMCID:
PMC2811084
Free PMC Article

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