AI Article Synopsis

  • Whole-Genome Sequencing is growing rapidly in clinical and food microbiology, but effective implementation is hindered by data analysis challenges and a lack of bioinformatics expertise.
  • CamPype is a new customizable bioinformatics workflow designed for analyzing sequencing data, particularly for Campylobacter, a major cause of gastroenteritis worldwide, helping to address public health economic impacts.
  • With minimal user intervention and an interactive HTML report for results, CamPype offers an accessible solution for microbiology labs lacking bioinformatics knowledge and can aid in bacterial typing and epidemiological analysis.

Article Abstract

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 .

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10357626PMC
http://dx.doi.org/10.1186/s12859-023-05414-wDOI Listing

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