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GalaxyTrakr: a distributed analysis tool for public health whole genome sequence data accessible to non-bioinformaticians

BACKGROUND: Processing and analyzing whole genome sequencing (WGS) is computationally intense: a single Illumina MiSeq WGS run produces ~ 1 million 250-base-pair reads for each of 24 samples. This poses significant obstacles for smaller laboratories, or laboratories not affiliated with larger projec...

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Autores principales: Gangiredla, Jayanthi, Rand, Hugh, Benisatto, Daniel, Payne, Justin, Strittmatter, Charles, Sanders, Jimmy, Wolfgang, William J., Libuit, Kevin, Herrick, James B., Prarat, Melanie, Toro, Magaly, Farrell, Thomas, Strain, Errol
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877046/
https://www.ncbi.nlm.nih.gov/pubmed/33568057
http://dx.doi.org/10.1186/s12864-021-07405-8
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author Gangiredla, Jayanthi
Rand, Hugh
Benisatto, Daniel
Payne, Justin
Strittmatter, Charles
Sanders, Jimmy
Wolfgang, William J.
Libuit, Kevin
Herrick, James B.
Prarat, Melanie
Toro, Magaly
Farrell, Thomas
Strain, Errol
author_facet Gangiredla, Jayanthi
Rand, Hugh
Benisatto, Daniel
Payne, Justin
Strittmatter, Charles
Sanders, Jimmy
Wolfgang, William J.
Libuit, Kevin
Herrick, James B.
Prarat, Melanie
Toro, Magaly
Farrell, Thomas
Strain, Errol
author_sort Gangiredla, Jayanthi
collection PubMed
description BACKGROUND: Processing and analyzing whole genome sequencing (WGS) is computationally intense: a single Illumina MiSeq WGS run produces ~ 1 million 250-base-pair reads for each of 24 samples. This poses significant obstacles for smaller laboratories, or laboratories not affiliated with larger projects, which may not have dedicated bioinformatics staff or computing power to effectively use genomic data to protect public health. Building on the success of the cloud-based Galaxy bioinformatics platform (http://galaxyproject.org), already known for its user-friendliness and powerful WGS analytical tools, the Center for Food Safety and Applied Nutrition (CFSAN) at the U.S. Food and Drug Administration (FDA) created a customized ‘instance’ of the Galaxy environment, called GalaxyTrakr (https://www.galaxytrakr.org), for use by laboratory scientists performing food-safety regulatory research. The goal was to enable laboratories outside of the FDA internal network to (1) perform quality assessments of sequence data, (2) identify links between clinical isolates and positive food/environmental samples, including those at the National Center for Biotechnology Information sequence read archive (https://www.ncbi.nlm.nih.gov/sra/), and (3) explore new methodologies such as metagenomics. GalaxyTrakr hosts a variety of free and adaptable tools and provides the data storage and computing power to run the tools. These tools support coordinated analytic methods and consistent interpretation of results across laboratories. Users can create and share tools for their specific needs and use sequence data generated locally and elsewhere. RESULTS: In its first full year (2018), GalaxyTrakr processed over 85,000 jobs and went from 25 to 250 users, representing 53 different public and state health laboratories, academic institutions, international health laboratories, and federal organizations. By mid-2020, it has grown to 600 registered users and processed over 450,000 analytical jobs. To illustrate how laboratories are making use of this resource, we describe how six institutions use GalaxyTrakr to quickly analyze and review their data. Instructions for participating in GalaxyTrakr are provided. CONCLUSIONS: GalaxyTrakr advances food safety by providing reliable and harmonized WGS analyses for public health laboratories and promoting collaboration across laboratories with differing resources. Anticipated enhancements to this resource will include workflows for additional foodborne pathogens, viruses, and parasites, as well as new tools and services.
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spelling pubmed-78770462021-02-11 GalaxyTrakr: a distributed analysis tool for public health whole genome sequence data accessible to non-bioinformaticians Gangiredla, Jayanthi Rand, Hugh Benisatto, Daniel Payne, Justin Strittmatter, Charles Sanders, Jimmy Wolfgang, William J. Libuit, Kevin Herrick, James B. Prarat, Melanie Toro, Magaly Farrell, Thomas Strain, Errol BMC Genomics Software BACKGROUND: Processing and analyzing whole genome sequencing (WGS) is computationally intense: a single Illumina MiSeq WGS run produces ~ 1 million 250-base-pair reads for each of 24 samples. This poses significant obstacles for smaller laboratories, or laboratories not affiliated with larger projects, which may not have dedicated bioinformatics staff or computing power to effectively use genomic data to protect public health. Building on the success of the cloud-based Galaxy bioinformatics platform (http://galaxyproject.org), already known for its user-friendliness and powerful WGS analytical tools, the Center for Food Safety and Applied Nutrition (CFSAN) at the U.S. Food and Drug Administration (FDA) created a customized ‘instance’ of the Galaxy environment, called GalaxyTrakr (https://www.galaxytrakr.org), for use by laboratory scientists performing food-safety regulatory research. The goal was to enable laboratories outside of the FDA internal network to (1) perform quality assessments of sequence data, (2) identify links between clinical isolates and positive food/environmental samples, including those at the National Center for Biotechnology Information sequence read archive (https://www.ncbi.nlm.nih.gov/sra/), and (3) explore new methodologies such as metagenomics. GalaxyTrakr hosts a variety of free and adaptable tools and provides the data storage and computing power to run the tools. These tools support coordinated analytic methods and consistent interpretation of results across laboratories. Users can create and share tools for their specific needs and use sequence data generated locally and elsewhere. RESULTS: In its first full year (2018), GalaxyTrakr processed over 85,000 jobs and went from 25 to 250 users, representing 53 different public and state health laboratories, academic institutions, international health laboratories, and federal organizations. By mid-2020, it has grown to 600 registered users and processed over 450,000 analytical jobs. To illustrate how laboratories are making use of this resource, we describe how six institutions use GalaxyTrakr to quickly analyze and review their data. Instructions for participating in GalaxyTrakr are provided. CONCLUSIONS: GalaxyTrakr advances food safety by providing reliable and harmonized WGS analyses for public health laboratories and promoting collaboration across laboratories with differing resources. Anticipated enhancements to this resource will include workflows for additional foodborne pathogens, viruses, and parasites, as well as new tools and services. BioMed Central 2021-02-10 /pmc/articles/PMC7877046/ /pubmed/33568057 http://dx.doi.org/10.1186/s12864-021-07405-8 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
Gangiredla, Jayanthi
Rand, Hugh
Benisatto, Daniel
Payne, Justin
Strittmatter, Charles
Sanders, Jimmy
Wolfgang, William J.
Libuit, Kevin
Herrick, James B.
Prarat, Melanie
Toro, Magaly
Farrell, Thomas
Strain, Errol
GalaxyTrakr: a distributed analysis tool for public health whole genome sequence data accessible to non-bioinformaticians
title GalaxyTrakr: a distributed analysis tool for public health whole genome sequence data accessible to non-bioinformaticians
title_full GalaxyTrakr: a distributed analysis tool for public health whole genome sequence data accessible to non-bioinformaticians
title_fullStr GalaxyTrakr: a distributed analysis tool for public health whole genome sequence data accessible to non-bioinformaticians
title_full_unstemmed GalaxyTrakr: a distributed analysis tool for public health whole genome sequence data accessible to non-bioinformaticians
title_short GalaxyTrakr: a distributed analysis tool for public health whole genome sequence data accessible to non-bioinformaticians
title_sort galaxytrakr: a distributed analysis tool for public health whole genome sequence data accessible to non-bioinformaticians
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877046/
https://www.ncbi.nlm.nih.gov/pubmed/33568057
http://dx.doi.org/10.1186/s12864-021-07405-8
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