Bayesian analysis of gene expression levels: statistical quantification of relative mRNA level across multiple strains or treatments.

ABSTRACT: BACKGROUND:Methods of microarray analysis that suit experimentalists using the technology are vital. Many methodologies discard the quantitative results inherent in cDNA microarray comparisons or cannot be flexibly applied to multifactorial experimental design. Here we present a flexible, quantitative Bayesian framework. This framework can be used to analyze normalized microarray data acquired by any replicated experimental design in which any number of treatments, genotypes, or developmental states are studied using a continuous chain of comparisons. RESULTS:We apply this method to Saccharomyces cerevisiae microarray datasets on the transcriptional response to ethanol shock, to SNF2 and SWI1 deletion in rich and minimal media, and to wild-type and zap1 expression in media with high, mediu

SUBMITTER: Townsend JP 

PROVIDER: S-EPMC151173 | biostudies-literature | 2002

REPOSITORIES: biostudies-literature