| Dye Bias Correction in Dual-labeled cDNA Microarray Gene Expression Measurements Barry A. Rosenzweig,1 P. Scott Pine,1 Olen E. Domon,2 Suzanne
M. Morris,2 James J. Chen,2 and Frank D. Sistare1 1Center for Drug Evaluation and Research, U.S. Food and Drug Administration,
Laurel, Maryland, USA; 2National Center for Toxicological Research,
U.S. Food and Drug Administration, Jefferson, Arkansas, USA Abstract
A significant limitation to the analytical accuracy and precision of dual-labeled spotted cDNA microarrays is the signal error due to dye bias. Transcript-dependent dye bias may be due to gene-specific differences of incorporation of two distinctly different chemical dyes and the resultant differential hybridization efficiencies of these two chemically different targets for the same probe. Several approaches were used to assess and minimize the effects of dye bias on fluorescent hybridization signals and maximize the experimental design efficiency of a cell culture experiment. Dye bias was measured at the individual transcript level within each batch of simultaneously processed arrays by replicate dual-labeled split-control sample hybridizations and accounted for a significant component of fluorescent signal differences. This transcript-dependent dye bias alone could introduce unacceptably high numbers of both false-positive and false-negative signals. We found that within a given set of concurrently processed hybridizations, the bias is remarkably consistent and therefore measurable and correctable. The additional microarrays and reagents required for paired technical replicate dye-swap corrections commonly performed to control for dye bias could be costly to end users. Incorporating split-control microarrays within a set of concurrently processed hybridizations to specifically measure dye bias can eliminate the need for technical dye swap replicates and reduce microarray and reagent costs while maintaining experimental accuracy and technical precision. These data support a practical and more efficient experimental design to measure and mathematically correct for dye bias. Key words: cDNA, dye bias, dye swap, genomics, microarray. Environ Health Perspect 112:480-487 (2004) . doi:10.1289/txg.6694 available via http://dx.doi.org/ [Online 15 January 2004]
This article is part of the mini-monograph "Application of Genomics to Mechanism-Based Risk Assessment." Address correspondence to B.A. Rosenzweig, Division of Applied Pharmacology Research (HFD-910) , Center for Drug Evaluation and Research, U.S. FDA, 10903 New Hampshire Ave., Life Sciences Building 64, Silver Spring, MD 20993 USA. Telephone: (301) 796-0125. Fax: (301) 796-9818. E-mail: rosenzweigb@cder.fda.gov The authors declare they have no competing financial interests. Received 22 August 2003 ; accepted 12 January 2004.
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