Reference : binny: an automated binning algorithm to recover high-quality genomes from complex me...
E-prints/Working papers : Already available on another site
Life sciences : Environmental sciences & ecology
Life sciences : Genetics & genetic processes
Systems Biomedicine
http://hdl.handle.net/10993/50004
binny: an automated binning algorithm to recover high-quality genomes from complex metagenomic datasets 2021.12.22.473795
English
Hickl, Oskar mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core]
Teixeira Queiros, Pedro mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Systems Ecology >]
Wilmes, Paul mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Systems Ecology]
May, Patrick mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core]
Heintz-Buschart, Anna [> >]
23-Dec-2021
Cold Spring Harbor Laboratory
No
[en] binning ; metagenomic reconstructed genomes ; metagenomics
[en] The reconstruction of genomes is a critical step in genome-resolved metagenomics as well as for multi-omic data integration from microbial communities. Here, we present binny, a binning tool that produces high-quality metagenome-assembled genomes from both contiguous and highly fragmented genomes. Based on established metrics, binny outperforms existing state-of-the-art binning methods and finds unique genomes that could not be detected by other methods.binny uses k-mer-composition and coverage by metagenomic reads for iterative, non-linear dimension reduction of genomic signatures as well as subsequent automated contig clustering with cluster assessment using lineage-specific marker gene sets.When compared to five widely used binning algorithms, binny recovers the most near-complete (\>95 pure, \>90 complete) and high-quality (\>90 pure, \>70 complete) genomes from simulated data sets from the Critical Assessment of Metagenome Interpretation (CAMI) initiative, as well as from a real-world benchmark comprised of metagenomes from various environments. binny is implemented as Snakemake workflow and available from https://github.com/a-h-b/binny.Competing Interest StatementThe authors have declared no competing interest.
Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) ; Luxembourg Centre for Systems Biomedicine (LCSB): Eco-Systems Biology (Wilmes Group)
Fonds National de la Recherche - FnR
Researchers ; Professionals ; Students ; General public
http://hdl.handle.net/10993/50004
10.1101/2021.12.22.473795
https://www.biorxiv.org/content/early/2021/12/23/2021.12.22.473795
https://www.biorxiv.org/content/10.1101/2021.12.22.473795v1.abstract
FnR ; FNR11823097 > Paul Wilmes > MICROH-DTU > Microbiomes In One Health > 01/09/2018 > 28/02/2025 > 2017

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