Evidence map›Paper›PMID 42265598›Full record

ArticleBMC bioinformatics2026

EcoliTyper: a species-optimized computational pipeline for comprehensive genotyping and surveillance of Escherichia coli.

Brown Beckley, Vincent Amarh

Abstract read
In one paragraph

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

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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.

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

backgroundEscherichia coli is a major bacterial pathogen associated with a high global burden of disease. Effective surveillance requires integrated genomic analysis, but current methods rely on multiple independent tools for sequence typing, serotyping, plasmid screening, and profiling of antimicrobial resistance (AMR) and virulence factors. This fragmented workflow could complicates analysis and hinders standardized reporting.

resultsWe developed EcoliTyper, a computational pipeline that executes a comprehensive set of E. coli genotyping analyses in a single automated workflow. The tool performs species confirmation (via fastANI), assembly quality control, Multi-Locus Sequence Typing (MLST), serotyping (O and H antigens), CH typing (FumC and FimH), Clermont phylogrouping, pathotype classification, and screening for AMR genes, virulence factors, plasmid replicons, biocide and heavy metal resistance markers. It includes cross-genome pattern discovery to summarise gene frequencies and contextualises results using a manually curated lineage database of high-risk clones. All results are compiled into an interactive, gene-centric HTML report, together with TSV, JSON, and plain text files. On a system with 16 CPU cores, EcoliTyper processed 60 E. coli genomes in approximately 129 min. AVAILABILITY: EcoliTyper is freely available under the MIT license at https://github.com/bbeckley-hub/EcoliTyper and is distributed as a self-contained Conda package.

conclusionEcoliTyper addresses workflow fragmentation in E. coli genomics by integrating multiple typing methods into a single, efficient pipeline. By providing structured, multi-format outputs and contextual data, it facilitates rapid isolate characterisation for surveillance and epidemiological studies.

Indexed as

Computational BiologyEscherichia coliGenotyping TechniquesSoftwareGenome, BacterialGenotypeMultilocus Sequence TypingAntimicrobial Resistance (AMR)BioinformaticsClermont typingEscherichia coliMLSTPipelineSerotypingSurveillance

Identifiers

PMID42265598
PMCPMC13480193

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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.