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A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog
The human gut microbiota performs functions that are essential for the maintenance of the host physiology. However, characterizing the functioning of microbial communities in relation to the host remains challenging in reference-based metagenomic analyses. Indeed, as taxonomic and functional analyse...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936653/ https://www.ncbi.nlm.nih.gov/pubmed/33709074 http://dx.doi.org/10.1093/nargab/lqab009 |
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author | Borderes, Marianne Gasc, Cyrielle Prestat, Emmanuel Galvão Ferrarini, Mariana Vinga, Susana Boucinha, Lilia Sagot, Marie-France |
author_facet | Borderes, Marianne Gasc, Cyrielle Prestat, Emmanuel Galvão Ferrarini, Mariana Vinga, Susana Boucinha, Lilia Sagot, Marie-France |
author_sort | Borderes, Marianne |
collection | PubMed |
description | The human gut microbiota performs functions that are essential for the maintenance of the host physiology. However, characterizing the functioning of microbial communities in relation to the host remains challenging in reference-based metagenomic analyses. Indeed, as taxonomic and functional analyses are performed independently, the link between genes and species remains unclear. Although a first set of species-level bins was built by clustering co-abundant genes, no reference bin set is established on the most used gut microbiota catalog, the Integrated Gene Catalog (IGC). With the aim to identify the best suitable method to group the IGC genes, we benchmarked nine taxonomy-independent binners implementing abundance-based, hybrid and integrative approaches. To this purpose, we designed a simulated non-redundant gene catalog (SGC) and computed adapted assessment metrics. Overall, the best trade-off between the main metrics is reached by an integrative binner. For each approach, we then compared the results of the best-performing binner with our expected community structures and applied the method to the IGC. The three approaches are distinguished by specific advantages, and by inherent or scalability limitations. Hybrid and integrative binners show promising and potentially complementary results but require improvements to be used on the IGC to recover human gut microbial species. |
format | Online Article Text |
id | pubmed-7936653 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-79366532021-03-10 A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog Borderes, Marianne Gasc, Cyrielle Prestat, Emmanuel Galvão Ferrarini, Mariana Vinga, Susana Boucinha, Lilia Sagot, Marie-France NAR Genom Bioinform Methart The human gut microbiota performs functions that are essential for the maintenance of the host physiology. However, characterizing the functioning of microbial communities in relation to the host remains challenging in reference-based metagenomic analyses. Indeed, as taxonomic and functional analyses are performed independently, the link between genes and species remains unclear. Although a first set of species-level bins was built by clustering co-abundant genes, no reference bin set is established on the most used gut microbiota catalog, the Integrated Gene Catalog (IGC). With the aim to identify the best suitable method to group the IGC genes, we benchmarked nine taxonomy-independent binners implementing abundance-based, hybrid and integrative approaches. To this purpose, we designed a simulated non-redundant gene catalog (SGC) and computed adapted assessment metrics. Overall, the best trade-off between the main metrics is reached by an integrative binner. For each approach, we then compared the results of the best-performing binner with our expected community structures and applied the method to the IGC. The three approaches are distinguished by specific advantages, and by inherent or scalability limitations. Hybrid and integrative binners show promising and potentially complementary results but require improvements to be used on the IGC to recover human gut microbial species. Oxford University Press 2021-03-01 /pmc/articles/PMC7936653/ /pubmed/33709074 http://dx.doi.org/10.1093/nargab/lqab009 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methart Borderes, Marianne Gasc, Cyrielle Prestat, Emmanuel Galvão Ferrarini, Mariana Vinga, Susana Boucinha, Lilia Sagot, Marie-France A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog |
title | A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog |
title_full | A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog |
title_fullStr | A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog |
title_full_unstemmed | A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog |
title_short | A comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog |
title_sort | comprehensive evaluation of binning methods to recover human gut microbial species from a non-redundant reference gene catalog |
topic | Methart |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936653/ https://www.ncbi.nlm.nih.gov/pubmed/33709074 http://dx.doi.org/10.1093/nargab/lqab009 |
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