MetaPath: identifying differentially abundant metabolic pathways in metagenomic datasets

TitleMetaPath: identifying differentially abundant metabolic pathways in metagenomic datasets
Publication TypeJournal Articles
Year of Publication2011
AuthorsLiu B, Pop M.
JournalBMC ProceedingsBMC Proceedings
Volume5
Type of Article10.1186/1753-6561-5-S2-S9
ISBN Number1753-6561
Abstract

Enabled by rapid advances in sequencing technology, metagenomic studies aim to characterize entire communities of microbes bypassing the need for culturing individual bacterial members. One major goal of metagenomic studies is to identify specific functional adaptations of microbial communities to their habitats. The functional profile and the abundances for a sample can be estimated by mapping metagenomic sequences to the global metabolic network consisting of thousands of molecular reactions. Here we describe a powerful analytical method (MetaPath) that can identify differentially abundant pathways in metagenomic datasets, relying on a combination of metagenomic sequence data and prior metabolic pathway knowledge.