Bioinformatics Advance Access originally published online on July 1, 2009
Bioinformatics 2009 25(18):2355-2361; doi:10.1093/bioinformatics/btp407
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Robustness considerations in selecting efficient two-color microarray designs
1Institute of Statistical Research and Training, University of Dhaka, Dhaka 1000, Bangladesh, 2Queen Mary University of London, School of Mathematical Sciences, London E1 4NS, UK, 3Novartis Pharma AG, Lichtstrasse 35, 4002 Basel, Switzerland and 4Abteilung Medizinische Statistik, Universität Göttingen, Humboldtallee 32, D-37073 Göttingen, Germany
*To whom correspondence should be addressed.
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Abstract |
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The main goal of microarray experiments is to select a small subset of genes that are differentially expressed among competing mRNA samples. For a given set of such mRNA samples, it is possible to consider a number of two-color cDNA microarray designs with a fixed number of arrays. Appropriate criteria can be used to select an efficient design from such a set of alternative experimental designs. In practice, however, microarray expression data often contain missing observations and the most efficient design (with complete observations) for a specific setup may not be efficient in the presence of missing observations. In this article, we propose two criteria to address the robustness of microarray designs against missing observations. We demonstrate the simultaneous use of efficiency and robustness criteria to select good microarray designs for both one-factor and multi-factor experiments.
Contact: mlatif{at}isrt.ac.bd
Received on February 11, 2009; revised on June 16, 2009; accepted on June 29, 2009
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