STRONG: metagenomics strain resolution on assembly graphs

Genome Biology

Rayan Chikhi¹  A. Murat Eren²  Sergey Nurk³  Robert James⁴  Christopher Quince⁵  Sebastien Raguideau⁵  Orkun S. Soyer⁶  Aaron E. Darling⁷  Antoine Limasset⁸  J. Kimberly Summers⁹ 

[1] Department of Computational Biology, Institut Pasteur, C3BI USR 3756 IP CNRS;Department of Medicine, University of Chicago;Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health;Gut Microbes and Health, Quadram Institute;Organisms and Ecosystems, Earlham Institute;School of Life Sciences, University of Warwick;The iThree institute, University of Technology Sydney;Univ. Lille, CNRS, Inria, UMR 9189 - CRIStAL;Warwick Medical School, University of Warwick;

关键词: Microbiome;    Metagenome;    Strains;    Bayesian;    Microbial community;    Assembly graph;   

DOI  :  10.1186/s13059-021-02419-7

来源: DOAJ

【 摘 要 】

Abstract We introduce STrain Resolution ON assembly Graphs (STRONG), which identifies strains de novo, from multiple metagenome samples. STRONG performs coassembly, and binning into metagenome assembled genomes (MAGs), and stores the coassembly graph prior to variant simplification. This enables the subgraphs and their unitig per-sample coverages, for individual single-copy core genes (SCGs) in each MAG, to be extracted. A Bayesian algorithm, BayesPaths, determines the number of strains present, their haplotypes or sequences on the SCGs, and abundances. STRONG is validated using synthetic communities and for a real anaerobic digestor time series generates haplotypes that match those observed from long Nanopore reads.

【 授权许可】

Unknown