Pathway-directed weighted testing procedures for the integrative analysis of gene expression and metabolomic data.

ABSTRACT: We explore the utility of p-value weighting for enhancing the power to detect differential metabolites in a two-sample setting. Related gene expression information is used to assign an a priori importance level to each metabolite being tested. We map the gene expression to a metabolite through pathways and then gene expression information is summarized per-pathway using gene set enrichment tests. Through simulation we explore four styles of enrichment tests and four weight functions to convert the gene information into a meaningful p-value weight. We implement the p-value weighting on a prostate cancer metabolomic dataset. Gene expression on matched samples is used to construct the weights. Under certain regulatory conditions, the use of weighted p-values does not inflate the type I error

SUBMITTER: Poisson LM 

PROVIDER: S-EPMC3525328 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature