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

Abstract

Analyzing 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