Affiliation:
1. Department of Computer Science, The University of Memphis, Memphis, TN 38152, USA
Abstract
Determining abundances of microbial genomes in metagenomic samples is an important problem in analyzing metagenomic data. Although homology-based methods are popular, they have shown to be computationally expensive due to the alignment of tens of millions of reads from metagenomic samples to reference genomes of hundreds to thousands of environmental microbial species. We introduce an efficient alignment-free approach to estimate abundances of microbial genomes in metagenomic samples. The approach is based on solving linear and quadratic programs, which are represented by genome-specific markers (GSM). We compared our method against popular alignment-free and homology-based methods. Without contamination, our method was more accurate than other alignment-free methods while being much faster than a homology-based method. In more realistic settings where samples were contaminated with human DNA, our method was the most accurate method in predicting abundance at varying levels of contamination. We achieve higher accuracy than both alignment-free and homology-based methods.
Publisher
World Scientific Pub Co Pte Lt
Subject
Computer Science Applications,Molecular Biology,Biochemistry
Cited by
7 articles.
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