Evidence map›Paper›PMID 41645058›Full record

ArticleBMC genomics2026

StaphScope: a species-optimized computational pipeline for rapid and accessible Staphylococcus aureus genotyping and surveillance.

Brown Beckley, Vincent Amarh

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. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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.

Brown BeckleyDepartment of Medical Biochemistry, University of Ghana Medical School, Accra, Ghana. brownbeckley94@gmail.com.
Vincent AmarhDepartment of Medical Biochemistry, University of Ghana Medical School, Accra, Ghana.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Staphylococcus aureus, particularly methicillin-resistant S. aureus (MRSA), poses a persistent global health challenge. Genomic surveillance is essential but often hindered by the bioinformatics complexity of integrating multiple, disparate analysis tools. To address this, we developed StaphScope, a specialized computational pipeline for the comprehensive genotyping of S. aureus. Distributed as a single-install Conda package, StaphScope integrates six core analyses-Multi-Locus Sequence typing (MLST), staphylococcal protein A (spa) typing, staphylococcal cassette chromosome mec (SCCmec) characterization, antimicrobial resistance (AMR) profiling, virulence factor screening, and plasmid detection-within a unified workflow. It features intelligent resource management via the Python psutil library for efficient parallel execution. Validation using reference strains showed complete concordance with established types. Analysis of 24 S. aureus genomes identified prevalent lineages (e.g., ST5, ST9), diverse resistance mechanisms, and key virulence determinants, with the pipeline completing all analyses in estimated 10-14 min on a system with 16 CPU cores and 16 GB RAM. StaphScope generates consolidated, interactive HTML reports alongside structured data files (TSV, JSON). By streamlining access to integrated genomic analysis, it supports enhanced surveillance and outbreak response. The tool is available at: https://github.com/bbeckley-hub/staphscope-typing-tool.

Indexed as

Computational BiologyGenotyping TechniquesSoftwareStaphylococcus aureusGenome, BacterialGenomicsGenotypeMultilocus Sequence TypingVirulence FactorsVirulence FactorsAntimicrobial resistanceComputational pipelineGenomic surveillanceGenotypingMRSAStaphylococcus aureusVirulence factorsWhole genome sequencing.

Identifiers

PMID41645058
PMCPMC12977718

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Registered trials

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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.