Analysing gene expression data from DNA microarrays to identify candidate genes

Microarray data analysis can be divided into two tasks: grouping of genes t o discover broad patterns of biological behaviour, and filtering of genes t o identify specific genes of interest. Whereas the gene-grouping task is la rgely addressed by cluster analysis, the gene-filtering task relies primari ly on hypothesis testing. This review article surveys analytical methods fo r the gene-filtering task. Various types of data analysis are discussed for four basic types of experimental protocols: a comparison of two biological samples; a comparison of two biological conditions; each represented by a set of replicate samples; a comparison of multiple biological conditions; a nd analysis of covariate information. Copyright (C) 2001 John Wiley & Sons, Ltd.