The University of Arizona

MetaGen: Reference-Free Learning with Multiple Metagenomic Samples

MetaGen: Reference-Free Learning with Multiple Metagenomic Samples

Series: Statistics GIDP Colloquium
Location: ENR2 S395
Presenter: Wenxuan Zhong, Georgia State University

Abstract:  A major goal of metagenomics is to identify and study the entire collection of microbial species in a set of targeted samples. In this talk, I will present a novel statistical metagenomic algorithm that simultaneously identifies microbial species and estimates their abundances without using reference genomes. Compared to reference-free methods based primarily on k-mer distributions or coverage information, the proposed approach achieves a higher species binning accuracy and is particularly powerful when sequencing coverage is low. I will demonstrate the performance of this new method through both simulation and real metagenomic studies. The MetaGen software is available at https://github.com/BioAlgs/MetaGen(link is external).

(Refreshments will be served.)

Department of Mathematics, The University of Arizona 617 N. Santa Rita Ave. P.O. Box 210089 Tucson, AZ 85721-0089 USA Voice: (520) 621-6892 Fax: (520) 621-8322 Contact Us © Copyright 2018 Arizona Board of Regents All rights reserved