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Title: Implementation of a generic ANOVA model for the analysis of gene expression data
P32
Engelen, Kristof; Coessens, Bert; Van Hummelen, Paul; De Brabanter, Jos; De Moor, Bart; Marchal, Kathleen

kristof.engelen@esat.kuleuven.ac.be
ESAT-SCD Bioinformatics

The use of ANOVA (analysis of variance) to preprocess and identify differentially expressed genes in microarrays data is increasingly gaining interest (Kerr, Martin et al., 2000; Jin et al., 2001). ANOVA can be viewed as a special case of multiple linear regression where the explanatory variables are entirely qualitative. The ANOVA approach models the measured expression level of each gene as a linear combination of the major sources of variation (i.e. explanatory variables).
In this study a generic ANOVA model for normalizing mcro-array data was implemented. The implementation has several advantages over previously described models, namely its generic nature with respect to the experimental design, i.e. it can be used to normalize any type of micro-array design.
The MARAN implementation has been made available as a user-friendly web-application (http:// www.esat.kuleuven.ac.be/maran). To provide an extensive normalization procedure for micro-array data, an option for loess-fitting the data, prior to performing the ANOVA analysis, and a module for selecting genes with significantly changing expression have been included on the MARAN website.
[1] Kerr MK, Martin M, Churchill GA (2000) Analysis of variance for gene expression microarray data. J Comput. Biol 7:819-837
[2] Jin W, Riley RM, Wolfinger RD, White KP, Passador-Gurgel G and Gibson G (2001) The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster. Nat. Genet. 29: 389-395