Evidence map›Paper›PMID 42420823›Full record

ArticleBMC genomics2026

StaphSCAN: a genomic surveillance framework for Staphylococcus aureus.

Riccardo Bollini, Valeria Cento

Abstract read
In one paragraph

Article in BMC genomics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Riccardo BolliniDepartment of Public Health, Experimental and Forensic Medicine, University of Pavia, Pavia, Italy. riccardo.bollini@hunimed.eu.ORCID https://orcid.org/0009-0001-9839-4380
Valeria CentoDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStaphylococcus aureus is a leading cause of hospital- and community-acquired infections. While Whole Genome Sequencing (WGS) has become the gold standard for surveillance, extracting actionable epidemiological data typically requires assembling fragmented workflows of disparate software tools. We introduce StaphSCAN, a modular, open-source Python tool designed to streamline S. aureus genomic analysis.

resultsStaphSCAN integrates essential typing methods (MLST, spa typing, SCCmec typing, capsular typing) with the detection of antimicrobial resistance (AMR), virulence, and biofilm-associated genes. It produces a comprehensive, normalized tabular report suitable for immediate interpretation. We validated StaphSCAN using a public dataset of 404 clinical S. aureus genomes collected in 2019 during a study conducted by the StaphNET-SA network. The tool successfully characterized the population structure, replicating the main key findings, demonstrating high throughput and reliability.

conclusionsIn conclusion, StaphSCAN provides a lightweight framework for S. aureus genomics, facilitating rapid genomic surveillance.

Indexed as

Genome, BacterialGenomicsSoftwareStaphylococcus aureusDrug Resistance, BacterialHumansStaphylococcal InfectionsWhole Genome SequencingBacteriaBioinformaticsMRSAStaphylococcus aureusSurveillanceWhole-genome sequencing

Identifiers

PMID42420823
PMCPMC13632141

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.