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ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data

The study of resistomes using whole metagenomic sequencing enables high-throughput identification of resistance genes in complex microbial communities, such as the human microbiome. Over recent years, sophisticated and diverse pipelines have been established to facilitate raw data processing and ann...

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Autores principales: Dhariwal, Achal, Junges, Roger, Chen, Tsute, Petersen, Fernanda C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7991225/
https://www.ncbi.nlm.nih.gov/pubmed/33796850
http://dx.doi.org/10.1093/nargab/lqab018
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author Dhariwal, Achal
Junges, Roger
Chen, Tsute
Petersen, Fernanda C
author_facet Dhariwal, Achal
Junges, Roger
Chen, Tsute
Petersen, Fernanda C
author_sort Dhariwal, Achal
collection PubMed
description The study of resistomes using whole metagenomic sequencing enables high-throughput identification of resistance genes in complex microbial communities, such as the human microbiome. Over recent years, sophisticated and diverse pipelines have been established to facilitate raw data processing and annotation. Despite the progress, there are no easy-to-use tools for comprehensive visual, statistical and functional analysis of resistome data. Thus, exploration of the resulting large complex datasets remains a key bottleneck requiring robust computational resources and technical expertise, which creates a significant hurdle for advancements in the field. Here, we introduce ResistoXplorer, a user-friendly tool that integrates recent advancements in statistics and visualization, coupled with extensive functional annotations and phenotype collection, to enable high-throughput analysis of common outputs generated from metagenomic resistome studies. ResistoXplorer contains three modules—the ‘Antimicrobial Resistance Gene Table’ module offers various options for composition profiling, functional profiling and comparative analysis of resistome data; the ‘Integration’ module supports integrative exploratory analysis of resistome and microbiome abundance profiles derived from metagenomic samples; finally, the ‘Antimicrobial Resistance Gene List’ module enables users to intuitively explore the associations between antimicrobial resistance genes and the microbial hosts using network visual analytics to gain biological insights. ResistoXplorer is publicly available at http://www.resistoxplorer.no.
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spelling pubmed-79912252021-03-31 ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data Dhariwal, Achal Junges, Roger Chen, Tsute Petersen, Fernanda C NAR Genom Bioinform Standard Article The study of resistomes using whole metagenomic sequencing enables high-throughput identification of resistance genes in complex microbial communities, such as the human microbiome. Over recent years, sophisticated and diverse pipelines have been established to facilitate raw data processing and annotation. Despite the progress, there are no easy-to-use tools for comprehensive visual, statistical and functional analysis of resistome data. Thus, exploration of the resulting large complex datasets remains a key bottleneck requiring robust computational resources and technical expertise, which creates a significant hurdle for advancements in the field. Here, we introduce ResistoXplorer, a user-friendly tool that integrates recent advancements in statistics and visualization, coupled with extensive functional annotations and phenotype collection, to enable high-throughput analysis of common outputs generated from metagenomic resistome studies. ResistoXplorer contains three modules—the ‘Antimicrobial Resistance Gene Table’ module offers various options for composition profiling, functional profiling and comparative analysis of resistome data; the ‘Integration’ module supports integrative exploratory analysis of resistome and microbiome abundance profiles derived from metagenomic samples; finally, the ‘Antimicrobial Resistance Gene List’ module enables users to intuitively explore the associations between antimicrobial resistance genes and the microbial hosts using network visual analytics to gain biological insights. ResistoXplorer is publicly available at http://www.resistoxplorer.no. Oxford University Press 2021-03-24 /pmc/articles/PMC7991225/ /pubmed/33796850 http://dx.doi.org/10.1093/nargab/lqab018 Text en © The Author(s) 2021. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Standard Article
Dhariwal, Achal
Junges, Roger
Chen, Tsute
Petersen, Fernanda C
ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data
title ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data
title_full ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data
title_fullStr ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data
title_full_unstemmed ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data
title_short ResistoXplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data
title_sort resistoxplorer: a web-based tool for visual, statistical and exploratory data analysis of resistome data
topic Standard Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7991225/
https://www.ncbi.nlm.nih.gov/pubmed/33796850
http://dx.doi.org/10.1093/nargab/lqab018
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