Computational protocol for analyzing whole-genome sequencing data from Staphylococcus aureus clinical isolates

Simple item page
dc.contributor.authorSánchez-Osuna, Miquel
dc.contributor.authorErill, Ivan
dc.contributor.authorGasch, Oriol
dc.contributor.authorPich, Oscar Q.
dc.date.accessioned2025-07-09T17:55:52Z
dc.date.issued2025-03-21
dc.description.abstractAnalyzing whole-genome sequencing (WGS) data from bacterial isolates is pivotal for understanding virulence and predicting clinical outcomes through association studies. Herein, we present a computational protocol for the detailed analysis of WGS data from Staphylococcus aureus clinical isolates generated with Illumina sequencing. We describe steps for de novo assembly, functional annotation, and genetic characterization of chromosomal and extrachromosomal elements. This approach paves the way for an improved understanding of the interplay between virulence factors, resistome, strain type, and disease severity. For complete details on the use and execution of this protocol, please refer to Sánchez-Osuna et al.1
dc.description.sponsorshipThis work was supported by grants PI19/01911 and PI24/01294 from Instituto de Salud Carlos III (ISCIII) and co-founded by the European Union and by grant CIR2022019 from Institut d’Investigacio´ i Innovacio´ Parc Taul?´ (I3PT). M.S.-O. was the recipient of a Margarita Salas grant awarded by the Ministerio de Universidades. O.G. received a personal research grant from the ‘‘Pla Estrate` gic de Recerca i Innovacio´ en Salut (PERIS)’’ awarded by Departament de Salut de la Generalitat de Catalunya. We also want to acknowledge the CERCA Programme/Generalitat de Catalunya.
dc.description.urihttps://www.sciencedirect.com/science/article/pii/S266616672500019X
dc.format.extent12 pages
dc.genrejournal articles
dc.identifierdoi:10.13016/m27wnf-clml
dc.identifier.citationMiquel Sánchez-Osuna et al., “Computational Protocol for Analyzing Whole-Genome Sequencing Data from Staphylococcus Aureus Clinical Isolates,” STAR Protocols 6, no. 1 (March 21, 2025): 103613, https://doi.org/10.1016/j.xpro.2025.103613.
dc.identifier.urihttps://doi.org/10.1016/j.xpro.2025.103613
dc.identifier.urihttp://hdl.handle.net/11603/39349
dc.language.isoen_US
dc.publisherElsevier
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Biological Sciences Department
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectmicrobiology
dc.subjecthealth sciences
dc.subjectbioinformatics
dc.subjectgenomics
dc.subjectsequence analysis
dc.subjectsequencing
dc.titleComputational protocol for analyzing whole-genome sequencing data from Staphylococcus aureus clinical isolates
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0002-7280-7191

Files

Original bundle

Now showing 1 - 2 of 2
Thumbnail Image
Name:
1s2.0S266616672500019Xmain.pdf
Size:
2.7 MB
Format:
Adobe Portable Document Format
Download
Thumbnail Image
Name:
1s2.0S266616672500019Xmmc1.zip
Size:
694 B
Format:
Unknown data format
Download

Collections

UMBC Faculty Collection
UMBC Biological Sciences Department