Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/51231
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Type: Journal article
Title: Optimal designs for 2-color microarray experiments
Author: Sanchez, P.
Glonek, G.
Citation: Biostatistics, 2009; 10(3):561-574
Publisher: Oxford University Press
Issue Date: 2009
ISSN: 1465-4644
1468-4357
Statement of
Responsibility: 
P. S. Sanchez and G. F. V. Glonek
Abstract: Statisticians can play a crucial role in the design of gene expression studies to ensure the most effective allocation of available resources. This paper considers Pareto optimal designs for gene expression studies involving 2-color microarrays. Pareto optimality enables the recommendation of designs that are particularly efficient for the effects of most interest to biologists. This is relevant in the microarray context where analysis is typically carried out separately for those effects. Our approach will allow for effects of interest that correspond to contrasts rather than solely considering parameters of the linear model. We further develop the approach to cater for additional experimental considerations such as contrasts that are of equal scientific interest. This amounts to partitioning all relevant contrasts into subsets of effects that are of equal importance. Based on the partitions, a penalty is employed in order to recommend designs for complex and varied microarray experiments. Finally, we address the issue of gene-specific dye bias. We illustrate using studies of leukemia and breast cancer.
Keywords: Factorial experiments
Microarrays
Optimal experimental design
DOI: 10.1093/biostatistics/kxp012
Published version: http://dx.doi.org/10.1093/biostatistics/kxp012
Appears in Collections:Aurora harvest 5
Mathematical Sciences publications

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