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AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata

BACKGROUND: Metagenomics is gaining attention as a powerful tool for identifying how agricultural management practices influence human and animal health, especially in terms of potential to contribute to the spread of antibiotic resistance. However, the ability to compare the distribution and preval...

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Autores principales: Liang, Xiao, Akers, Kyle, Keenum, Ishi, Wind, Lauren, Gupta, Suraj, Chen, Chaoqi, Aldaihani, Reem, Pruden, Amy, Zhang, Liqing, Knowlton, Katharine F., Xia, Kang, Heath, Lenwood S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7944603/
https://www.ncbi.nlm.nih.gov/pubmed/33691615
http://dx.doi.org/10.1186/s12859-021-04035-5
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author Liang, Xiao
Akers, Kyle
Keenum, Ishi
Wind, Lauren
Gupta, Suraj
Chen, Chaoqi
Aldaihani, Reem
Pruden, Amy
Zhang, Liqing
Knowlton, Katharine F.
Xia, Kang
Heath, Lenwood S.
author_facet Liang, Xiao
Akers, Kyle
Keenum, Ishi
Wind, Lauren
Gupta, Suraj
Chen, Chaoqi
Aldaihani, Reem
Pruden, Amy
Zhang, Liqing
Knowlton, Katharine F.
Xia, Kang
Heath, Lenwood S.
author_sort Liang, Xiao
collection PubMed
description BACKGROUND: Metagenomics is gaining attention as a powerful tool for identifying how agricultural management practices influence human and animal health, especially in terms of potential to contribute to the spread of antibiotic resistance. However, the ability to compare the distribution and prevalence of antibiotic resistance genes (ARGs) across multiple studies and environments is currently impossible without a complete re-analysis of published datasets. This challenge must be addressed for metagenomics to realize its potential for helping guide effective policy and practice measures relevant to agricultural ecosystems, for example, identifying critical control points for mitigating the spread of antibiotic resistance. RESULTS: Here we introduce AgroSeek, a centralized web-based system that provides computational tools for analysis and comparison of metagenomic data sets tailored specifically to researchers and other users in the agricultural sector interested in tracking and mitigating the spread of ARGs. AgroSeek draws from rich, user-provided metagenomic data and metadata to facilitate analysis, comparison, and prediction in a user-friendly fashion. Further, AgroSeek draws from publicly-contributed data sets to provide a point of comparison and context for data analysis. To incorporate metadata into our analysis and comparison procedures, we provide flexible metadata templates, including user-customized metadata attributes to facilitate data sharing, while maintaining the metadata in a comparable fashion for the broader user community and to support large-scale comparative and predictive analysis. CONCLUSION: AgroSeek provides an easy-to-use tool for environmental metagenomic analysis and comparison, based on both gene annotations and associated metadata, with this initial demonstration focusing on control of antibiotic resistance in agricultural ecosystems. Agroseek creates a space for metagenomic data sharing and collaboration to assist policy makers, stakeholders, and the public in decision-making. AgroSeek is publicly-available at https://agroseek.cs.vt.edu/. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04035-5.
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spelling pubmed-79446032021-03-10 AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata Liang, Xiao Akers, Kyle Keenum, Ishi Wind, Lauren Gupta, Suraj Chen, Chaoqi Aldaihani, Reem Pruden, Amy Zhang, Liqing Knowlton, Katharine F. Xia, Kang Heath, Lenwood S. BMC Bioinformatics Software BACKGROUND: Metagenomics is gaining attention as a powerful tool for identifying how agricultural management practices influence human and animal health, especially in terms of potential to contribute to the spread of antibiotic resistance. However, the ability to compare the distribution and prevalence of antibiotic resistance genes (ARGs) across multiple studies and environments is currently impossible without a complete re-analysis of published datasets. This challenge must be addressed for metagenomics to realize its potential for helping guide effective policy and practice measures relevant to agricultural ecosystems, for example, identifying critical control points for mitigating the spread of antibiotic resistance. RESULTS: Here we introduce AgroSeek, a centralized web-based system that provides computational tools for analysis and comparison of metagenomic data sets tailored specifically to researchers and other users in the agricultural sector interested in tracking and mitigating the spread of ARGs. AgroSeek draws from rich, user-provided metagenomic data and metadata to facilitate analysis, comparison, and prediction in a user-friendly fashion. Further, AgroSeek draws from publicly-contributed data sets to provide a point of comparison and context for data analysis. To incorporate metadata into our analysis and comparison procedures, we provide flexible metadata templates, including user-customized metadata attributes to facilitate data sharing, while maintaining the metadata in a comparable fashion for the broader user community and to support large-scale comparative and predictive analysis. CONCLUSION: AgroSeek provides an easy-to-use tool for environmental metagenomic analysis and comparison, based on both gene annotations and associated metadata, with this initial demonstration focusing on control of antibiotic resistance in agricultural ecosystems. Agroseek creates a space for metagenomic data sharing and collaboration to assist policy makers, stakeholders, and the public in decision-making. AgroSeek is publicly-available at https://agroseek.cs.vt.edu/. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-021-04035-5. BioMed Central 2021-03-10 /pmc/articles/PMC7944603/ /pubmed/33691615 http://dx.doi.org/10.1186/s12859-021-04035-5 Text en © The Author(s) 2021 Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://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
Liang, Xiao
Akers, Kyle
Keenum, Ishi
Wind, Lauren
Gupta, Suraj
Chen, Chaoqi
Aldaihani, Reem
Pruden, Amy
Zhang, Liqing
Knowlton, Katharine F.
Xia, Kang
Heath, Lenwood S.
AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata
title AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata
title_full AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata
title_fullStr AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata
title_full_unstemmed AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata
title_short AgroSeek: a system for computational analysis of environmental metagenomic data and associated metadata
title_sort agroseek: a system for computational analysis of environmental metagenomic data and associated metadata
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7944603/
https://www.ncbi.nlm.nih.gov/pubmed/33691615
http://dx.doi.org/10.1186/s12859-021-04035-5
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