A novel statistical algorithm for gene expression analysis helps differentiate pregnane X receptor-dependent and independent mechanisms of toxicity.

ABSTRACT: Genome-wide gene expression profiling has become standard for assessing potential liabilities as well as for elucidating mechanisms of toxicity of drug candidates under development. Analysis of microarray data is often challenging due to the lack of a statistical model that is amenable to biological variation in a small number of samples. Here we present a novel non-parametric algorithm that requires minimal assumptions about the data distribution. Our method for determining differential expression consists of two steps: 1) We apply a nominal threshold on fold change and platform p-value to designate whether a gene is differentially expressed in each treated and control sample relative to the averaged control pool, and 2) We compared the number of samples satisfying criteria in step 1 betw

SUBMITTER: Mongan MA 

PROVIDER: S-EPMC3006344 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature