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Statistical Applications in Genetics and Molecular Biology

Editor-in-Chief: Stumpf, Michael P.H.

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Optimality Criteria for the Design of 2-Color Microarray Studies

Kathleen F. Kerr1

1University of Washington

Citation Information: Statistical Applications in Genetics and Molecular Biology. Volume 11, Issue 1, Pages 1–9, ISSN (Online) 1544-6115, DOI: 10.1515/1544-6115.1583, January 2012

Publication History

Published Online:
2012-01-13

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.

Keywords: optimal design; microarray

Citing Articles

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[1]
Rahul Mukerjee and S. Huda
Annals of the Institute of Statistical Mathematics, 2015

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