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<tt>MAGScoT</tt>: a fast, lightweight and accurate bin-refinement tool

Malte Rühlemann, Eike Matthias Wacker, David Ellinghaus, André Franke

2022Bioinformatics58 citationsDOIOpen Access PDF

Abstract

MOTIVATION: 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. RESULTS: MAGScoT outperforms popular bin-refinement solutions in terms of quality and quantity of MAGs as well as computation time and resource consumption. AVAILABILITY AND IMPLEMENTATION: MAGScoT is available via GitHub (https://github.com/ikmb/MAGScoT) and as an easy-to-use Docker container (https://hub.docker.com/repository/docker/ikmb/magscot). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Topics & Concepts

Computer scienceLeverage (statistics)MetagenomicsBinData miningSortingTask (project management)Source codeDistributed computingOperating systemAlgorithmArtificial intelligenceEconomicsChemistryBiochemistryManagementGeneGenomics and Phylogenetic StudiesGut microbiota and healthMicrobial Community Ecology and Physiology
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