Online Program Home
My Program

Abstract Details

Activity Number: 480 - Novel Statistical Methods for Bioinformatics and Computational Biology
Type: Invited
Date/Time: Wednesday, July 31, 2019 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics in Genomics and Genetics
Abstract #300469 Presentation
Title: Reference-Free Learning with Multiple Metagenomic Samples
Author(s): Wenxuan Zhong*
Companies: University of Georgia
Keywords: metagenomics; matrix decomposition; reference-free methods; binning methods

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.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2019 program