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Optimality Criteria for the Design of 2-Color Microarray Studies

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  • Kerr Kathleen F.

Abstract

We discuss the definition and application of design criteria for evaluating the efficiency of 2-color microarray designs. First, we point out that design optimality criteria are defined differently for the regression and block design settings. This has caused some confusion in the literature and warrants clarification. Linear models for microarray data analysis have equivalent formulations as ANOVA or regression models. However, this equivalence does not extend to design criteria. We discuss optimality criterion, and argue against applying regression-style D-optimality to the microarray design problem. We further disfavor E- and D-optimality (as defined in block design) because they are not attuned to scientific questions of interest.

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  • Kerr Kathleen F., 2012. "Optimality Criteria for the Design of 2-Color Microarray Studies," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(1), pages 1-9, January.
    • Handle: RePEc:bpj:sagmbi:v:11:y:2012:i:1:n:10
    DOI: 10.1515/1544-6115.1583
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    References listed on IDEAS

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    1. Smyth Gordon K, 2004. "Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 3(1), pages 1-28, February.
    2. M. Kathleen Kerr, 2003. "Design Considerations for Efficient and Effective Microarray Studies," Biometrics, The International Biometric Society, vol. 59(4), pages 822-828, December.
    3. R. A. Bailey, 2007. "Designs for two‐colour microarray experiments," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 56(4), pages 365-394, August.
    4. Ernst Wit & Agostino Nobile & Raya Khanin, 2005. "Near‐optimal designs for dual channel microarray studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(5), pages 817-830, November.
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    1. Zhang Runchu & Mukerjee Rahul, 2013. "Highly efficient factorial designs for cDNA microarray experiments: use of approximate theory together with a step-up step-down procedure," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 12(4), pages 489-503, August.

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    optimal design; microarray;

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