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Comparative and Functional Genomics
Volume 6, Issue 3, Pages 123-131
Conference Paper

Reassessing Design and Analysis of two-Colour Microarray Experiments Using Mixed Effects Models

1Department of Animal Science, Michigan State University, East Lansing, MI, USA
2Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI, USA
3Department of Animal Science, 1205-I Anthony Hall, Michigan State University, East Lansing 48824-1225, MI, USA

Received 19 January 2005; Accepted 3 February 2005

Copyright © 2005 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Gene expression microarray studies have led to interesting experimental design and statistical analysis challenges. The comparison of expression profiles across populations is one of the most common objectives of microarray experiments. In this manuscript we review some issues regarding design and statistical analysis for two-colour microarray platforms using mixed linear models, with special attention directed towards the different hierarchical levels of replication and the consequent effect on the use of appropriate error terms for comparing experimental groups. We examine the traditional analysis of variance (ANOVA) models proposed for microarray data and their extensions to hierarchically replicated experiments. In addition, we discuss a mixed model methodology for power and efficiency calculations of different microarray experimental designs.