Bioinformatics Advance Access originally published online on February 19, 2004
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Bioinformatics 20(8) © Oxford University Press 2004; all rights reserved.
Analysing microarray data using modular regulation analysis
MRC Dunn Human Nutrition Unit, Hills Road, Cambridge, CB2 2XY, UK
Received on June 24, 2003; revised on August 7, 2003; accepted on September 2, 2003
Advance Access Publication February 19, 2004
Motivation: Microarray experiments measure complex changes in the abundance of many mRNAs under different conditions. Current analysis methods cannot distinguish between direct and indirect effects on expression, or calculate the relative importance of mRNAs in effecting responses.
Results: Application of modular regulation analysis to microarray data reveals and quantifies which mRNA changes are important for cellular responses. The mRNAs are clustered, and then we calculate how perturbations alter each cluster and how strongly those clusters affect an output response. The product of these values quantifies how an input changes a response through each cluster.
Two published datasets are analysed. Two mRNA clusters transmit most of the response of yeast doubling time to galactose; one contains mainly galactose metabolic genes, and the other a regulatory gene. Analysis of the response of yeast relative fitness to 2-deoxy-D-glucose reveals that control is distributed between several mRNA clusters, but experimental error limits statistical significance.
Contact: rkc24{at}cam.ac.uk
* To whom correspondence should be addressed.
Present address: Department of Clinical Biochemistry, University of Cambridge, Addenbrooke's Hospital, Box 232, Hills Road, Cambridge, CB2 2QR, UK.