MetaGen: reference-free learning with multiple metagenomic samples

MetaGen: reference-free learning with multiple metagenomic samples

Abstract A major goal of metagenomics is to identify and study the entire collection of microbial species in a set of targeted samples. We describe a statistical metagenomic algorithm that simultaneously identifies microbial species and estimates their abundances without using reference genomes. As...

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Bibliographic Details
Main Authors: Xin Xing, Jun S. Liu, Wenxuan Zhong
Format: Article
Language:English
Published: BMC 2017-10-01
Series:Genome Biology
Subjects:
Metagenomics
Binning
Mixture model
Multinomial
Unsupervised learning
Online Access:http://link.springer.com/article/10.1186/s13059-017-1323-y

Internet

http://link.springer.com/article/10.1186/s13059-017-1323-y

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