MAGScoT: a fast, lightweight and accurate bin-refinement tool | Zendy

Malte Rühlemann | Zendy; Eike Matthias Wacker | Zendy; David Ellinghaus | Zendy; André Franke | Zendy

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MAGScoT: a fast, lightweight and accurate bin-refinement tool

Author(s) -

Malte Rühlemann,

Eike Matthias Wacker,

David Ellinghaus,

André Franke

Publication year - 2022

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btac694

Subject(s) - computer science , leverage (statistics) , metagenomics , bin , data mining , sorting , task (project management) , source code , distributed computing , operating system , algorithm , artificial intelligence , biochemistry , chemistry , gene , management , economics

Recovery of metagenome-assembled genomes (MAGs) from shotgun metagenomic data is an important task for the comprehensive analysis of microbial communities from variable sources. Single binning tools differ in their ability to leverage specific aspects in MAG reconstruction, the use of ensemble binning refinement tools is often time consuming and computational demand increases with community complexity. We introduce MAGScoT, a fast, lightweight and accurate implementation for the reconstruction of highest-quality MAGs from the output of multiple genome-binning tools.

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