Statistical methods for detecting differentially abundant features in clinical metagenomic samples.

ABSTRACT: Numerous studies are currently underway to characterize the microbial communities inhabiting our world. These studies aim to dramatically expand our understanding of the microbial biosphere and, more importantly, hope to reveal the secrets of the complex symbiotic relationship between us and our commensal bacterial microflora. An important prerequisite for such discoveries are computational tools that are able to rapidly and accurately compare large datasets generated from complex bacterial communities to identify features that distinguish them.We present a statistical method for comparing clinical metagenomic samples from two treatment populations on the basis of count data (e.g. as obtained through sequencing) to detect differentially abundant features. Our method, Metastats, employs the

SUBMITTER: White JR 

PROVIDER: S-EPMC2661018 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature