期刊论文详细信息
PeerJ Computer Science
A probabilistic model to recover individual genomes from metagenomes
Alexander Schönhuth1  Johannes Dröge2  Alice C. McHardy2 
[1] Centrum Wiskunde & Informatica, Amsterdam, The Netherlands;Computational Biology of Infection Research, Helmholtz Centre for Infection Research, Braunschweig, Germany;
关键词: Binning;    Metagenomics;   
DOI  :  10.7717/peerj-cs.117
来源: DOAJ
【 摘 要 】

Shotgun metagenomics of microbial communities reveal information about strains of relevance for applications in medicine, biotechnology and ecology. Recovering their genomes is a crucial but very challenging step due to the complexity of the underlying biological system and technical factors. Microbial communities are heterogeneous, with oftentimes hundreds of present genomes deriving from different species or strains, all at varying abundances and with different degrees of similarity to each other and reference data. We present a versatile probabilistic model for genome recovery and analysis, which aggregates three types of information that are commonly used for genome recovery from metagenomes. As potential applications we showcase metagenome contig classification, genome sample enrichment and genome bin comparisons. The open source implementation MGLEX is available via the Python Package Index and on GitHub and can be embedded into metagenome analysis workflows and programs.

【 授权许可】

Unknown   

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