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BinSPreader: Refine binning results for fuller MAG reconstruction

Despite the recent advances in high-throughput sequencing, metagenome analysis of microbial populations still remains a challenge. In particular, the metagenome-assembled genomes (MAGs) are often fragmented due to interspecies repeats, uneven coverage, and varying strain abundance. MAGs are construc...

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Detalles Bibliográficos
Autores principales: Tolstoganov, Ivan, Kamenev, Yuri, Kruglikov, Roman, Ochkalova, Sofia, Korobeynikov, Anton
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386100/
https://www.ncbi.nlm.nih.gov/pubmed/35992057
http://dx.doi.org/10.1016/j.isci.2022.104770
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author Tolstoganov, Ivan
Kamenev, Yuri
Kruglikov, Roman
Ochkalova, Sofia
Korobeynikov, Anton
author_facet Tolstoganov, Ivan
Kamenev, Yuri
Kruglikov, Roman
Ochkalova, Sofia
Korobeynikov, Anton
author_sort Tolstoganov, Ivan
collection PubMed
description Despite the recent advances in high-throughput sequencing, metagenome analysis of microbial populations still remains a challenge. In particular, the metagenome-assembled genomes (MAGs) are often fragmented due to interspecies repeats, uneven coverage, and varying strain abundance. MAGs are constructed via a binning process that uses features of input data in order to cluster long contigs presumably belonging to the same species. In this work, we present BinSPreader—a binning refiner tool that exploits the assembly graph topology and other connectivity information to refine binning, correct binning errors, and propagate binning to shorter contigs. We show that BinSPreader could increase the completeness of the bins without sacrificing the purity and could predict contigs belonging to several MAGs. BinSPreader is effective in binning shorter contigs that often contain important conservative sequences that might be of great interest to researchers.
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spelling pubmed-93861002022-08-19 BinSPreader: Refine binning results for fuller MAG reconstruction Tolstoganov, Ivan Kamenev, Yuri Kruglikov, Roman Ochkalova, Sofia Korobeynikov, Anton iScience Article Despite the recent advances in high-throughput sequencing, metagenome analysis of microbial populations still remains a challenge. In particular, the metagenome-assembled genomes (MAGs) are often fragmented due to interspecies repeats, uneven coverage, and varying strain abundance. MAGs are constructed via a binning process that uses features of input data in order to cluster long contigs presumably belonging to the same species. In this work, we present BinSPreader—a binning refiner tool that exploits the assembly graph topology and other connectivity information to refine binning, correct binning errors, and propagate binning to shorter contigs. We show that BinSPreader could increase the completeness of the bins without sacrificing the purity and could predict contigs belonging to several MAGs. BinSPreader is effective in binning shorter contigs that often contain important conservative sequences that might be of great interest to researchers. Elsevier 2022-07-19 /pmc/articles/PMC9386100/ /pubmed/35992057 http://dx.doi.org/10.1016/j.isci.2022.104770 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Tolstoganov, Ivan
Kamenev, Yuri
Kruglikov, Roman
Ochkalova, Sofia
Korobeynikov, Anton
BinSPreader: Refine binning results for fuller MAG reconstruction
title BinSPreader: Refine binning results for fuller MAG reconstruction
title_full BinSPreader: Refine binning results for fuller MAG reconstruction
title_fullStr BinSPreader: Refine binning results for fuller MAG reconstruction
title_full_unstemmed BinSPreader: Refine binning results for fuller MAG reconstruction
title_short BinSPreader: Refine binning results for fuller MAG reconstruction
title_sort binspreader: refine binning results for fuller mag reconstruction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9386100/
https://www.ncbi.nlm.nih.gov/pubmed/35992057
http://dx.doi.org/10.1016/j.isci.2022.104770
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