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BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes

BACKGROUND: Exploring metagenomic contigs and “binning” them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with...

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Autores principales: Pavia, Michael J., Chede, Abhinav, Wu, Zijun, Cadillo-Quiroz, Hinsby, Zhu, Qiyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439608/
https://www.ncbi.nlm.nih.gov/pubmed/37596696
http://dx.doi.org/10.1186/s40168-023-01625-8
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author Pavia, Michael J.
Chede, Abhinav
Wu, Zijun
Cadillo-Quiroz, Hinsby
Zhu, Qiyun
author_facet Pavia, Michael J.
Chede, Abhinav
Wu, Zijun
Cadillo-Quiroz, Hinsby
Zhu, Qiyun
author_sort Pavia, Michael J.
collection PubMed
description BACKGROUND: Exploring metagenomic contigs and “binning” them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure. RESULTS: We present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time. In demonstration of BinaRena’s usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset. CONCLUSIONS: BinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted at https://github.com/qiyunlab/binarena, together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-023-01625-8.
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spelling pubmed-104396082023-08-20 BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes Pavia, Michael J. Chede, Abhinav Wu, Zijun Cadillo-Quiroz, Hinsby Zhu, Qiyun Microbiome Software BACKGROUND: Exploring metagenomic contigs and “binning” them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure. RESULTS: We present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time. In demonstration of BinaRena’s usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset. CONCLUSIONS: BinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted at https://github.com/qiyunlab/binarena, together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40168-023-01625-8. BioMed Central 2023-08-19 /pmc/articles/PMC10439608/ /pubmed/37596696 http://dx.doi.org/10.1186/s40168-023-01625-8 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Software
Pavia, Michael J.
Chede, Abhinav
Wu, Zijun
Cadillo-Quiroz, Hinsby
Zhu, Qiyun
BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes
title BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes
title_full BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes
title_fullStr BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes
title_full_unstemmed BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes
title_short BinaRena: a dedicated interactive platform for human-guided exploration and binning of metagenomes
title_sort binarena: a dedicated interactive platform for human-guided exploration and binning of metagenomes
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439608/
https://www.ncbi.nlm.nih.gov/pubmed/37596696
http://dx.doi.org/10.1186/s40168-023-01625-8
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