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

Bioinformatics. 2022 Dec 13;38(24):5430-5433. doi: 10.1093/bioinformatics/btac694.


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 ( and as an easy-to-use Docker container (

Supplementary information: Supplementary data are available at Bioinformatics online.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms*
  • Metagenome
  • Metagenomics
  • Microbiota*