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CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter
BACKGROUND: The rapid expansion of Whole-Genome Sequencing has revolutionized the fields of clinical and food microbiology. However, its implementation as a routine laboratory technique remains challenging due to the growth of data at a faster rate than can be effectively analyzed and critical gaps...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10357626/ https://www.ncbi.nlm.nih.gov/pubmed/37474912 http://dx.doi.org/10.1186/s12859-023-05414-w |
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author | Ortega-Sanz, Irene Barbero-Aparicio, José A. Canepa-Oneto, Antonio Rovira, Jordi Melero, Beatriz |
author_facet | Ortega-Sanz, Irene Barbero-Aparicio, José A. Canepa-Oneto, Antonio Rovira, Jordi Melero, Beatriz |
author_sort | Ortega-Sanz, Irene |
collection | PubMed |
description | BACKGROUND: The rapid expansion of Whole-Genome Sequencing has revolutionized the fields of clinical and food microbiology. However, its implementation as a routine laboratory technique remains challenging due to the growth of data at a faster rate than can be effectively analyzed and critical gaps in bioinformatics knowledge. RESULTS: To address both issues, CamPype was developed as a new bioinformatics workflow for the genomics analysis of sequencing data of bacteria, especially Campylobacter, which is the main cause of gastroenteritis worldwide making a negative impact on the economy of the public health systems. CamPype allows fully customization of stages to run and tools to use, including read quality control filtering, read contamination, reads extension and assembly, bacterial typing, genome annotation, searching for antibiotic resistance genes, virulence genes and plasmids, pangenome construction and identification of nucleotide variants. All results are processed and resumed in an interactive HTML report for best data visualization and interpretation. CONCLUSIONS: The minimal user intervention of CamPype makes of this workflow an attractive resource for microbiology laboratories with no expertise in bioinformatics as a first line method for bacterial typing and epidemiological analyses, that would help to reduce the costs of disease outbreaks, or for comparative genomic analyses. CamPype is publicly available at https://github.com/JoseBarbero/CamPype. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05414-w. |
format | Online Article Text |
id | pubmed-10357626 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-103576262023-07-21 CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter Ortega-Sanz, Irene Barbero-Aparicio, José A. Canepa-Oneto, Antonio Rovira, Jordi Melero, Beatriz BMC Bioinformatics Research BACKGROUND: The rapid expansion of Whole-Genome Sequencing has revolutionized the fields of clinical and food microbiology. However, its implementation as a routine laboratory technique remains challenging due to the growth of data at a faster rate than can be effectively analyzed and critical gaps in bioinformatics knowledge. RESULTS: To address both issues, CamPype was developed as a new bioinformatics workflow for the genomics analysis of sequencing data of bacteria, especially Campylobacter, which is the main cause of gastroenteritis worldwide making a negative impact on the economy of the public health systems. CamPype allows fully customization of stages to run and tools to use, including read quality control filtering, read contamination, reads extension and assembly, bacterial typing, genome annotation, searching for antibiotic resistance genes, virulence genes and plasmids, pangenome construction and identification of nucleotide variants. All results are processed and resumed in an interactive HTML report for best data visualization and interpretation. CONCLUSIONS: The minimal user intervention of CamPype makes of this workflow an attractive resource for microbiology laboratories with no expertise in bioinformatics as a first line method for bacterial typing and epidemiological analyses, that would help to reduce the costs of disease outbreaks, or for comparative genomic analyses. CamPype is publicly available at https://github.com/JoseBarbero/CamPype. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-023-05414-w. BioMed Central 2023-07-20 /pmc/articles/PMC10357626/ /pubmed/37474912 http://dx.doi.org/10.1186/s12859-023-05414-w 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 | Research Ortega-Sanz, Irene Barbero-Aparicio, José A. Canepa-Oneto, Antonio Rovira, Jordi Melero, Beatriz CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter |
title | CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter |
title_full | CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter |
title_fullStr | CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter |
title_full_unstemmed | CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter |
title_short | CamPype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on Campylobacter |
title_sort | campype: an open-source workflow for automated bacterial whole-genome sequencing analysis focused on campylobacter |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10357626/ https://www.ncbi.nlm.nih.gov/pubmed/37474912 http://dx.doi.org/10.1186/s12859-023-05414-w |
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