ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2022
A scalable analytical approach from bacterial genomes to epidemiology.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed.
- Review
- Quantifying the predictability of evolution by analysis of coalescent rate variation.Molecular biology and evolution · 2026Article
- Complete genomes reveal a refined map of Mycobacterium tuberculosis genetic diversity across evolutionary scales.Nature communications · 2026Article
- DiagnoDating: diagnostics for dated phylogenies in microbial population genetics.Molecular biology and evolution · 2026Article
- Fast hospital discharge rates blur within-hospital 'transmission footprint' in bacterial genomes, as showcased with Staphylococcus aureus.PLoS computational biology · 2026Article
- Inference of Multiple Mergers while Dating a Pathogen Phylogeny.Systematic biology · 2025Article
- Incorporating Epidemiological Data into the Genomic Analysis of Partially Sampled Infectious Disease Outbreaks.Molecular biology and evolution · 2025Article
- Bayesian Inference of Pathogen Phylogeography using the Structured Coalescent Model.PLoS computational biology · 2025Article
- KmerAperture: Retaining k-mer synteny for alignment-free extraction of core and accessory differences between bacterial genomes.PLoS genetics · 2024Article
- Inference of Infectious Disease Transmission through a Relaxed Bottleneck Using Multiple Genomes Per Host.Molecular biology and evolution · 2024Article
- Article
- Estimating the fitness cost and benefit of antimicrobial resistance from pathogen genomic data.Journal of the Royal Society, Interface · 2023Article
- Distinguishing imported cases from locally acquired cases within a geographically limited genomic sample of an infectious disease.Bioinformatics (Oxford, England) · 2023Article
- Model design for nonparametric phylodynamic inference and applications to pathogen surveillance.Virus evolution · 2023Article
- Scalable and versatile container-based pipelines for de novo genome assembly and bacterial annotation.F1000Research · 2023Review
- A scalable analytical approach from bacterial genomes to epidemiology.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
- Genomic population structures of microbial pathogens.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2022Article
- Epidemiological inference from pathogen genomes: A review of phylodynamic models and applications.Virus evolution · 2022Review
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2 authors.
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Abstract
Recent years have seen a remarkable increase in the practicality of sequencing whole genomes from large numbers of bacterial isolates. The availability of this data has huge potential to deliver new insights into the evolution and epidemiology of bacterial pathogens, but the scalability of the analytical methodology has been lagging behind that of the sequencing technology. Here we present a step-by-step approach for such large-scale genomic epidemiology analyses, from bacterial genomes to epidemiological interpretations. A central component of this approach is the dated phylogeny, which is a phylogenetic tree with branch lengths measured in units of time. The construction of dated phylogenies from bacterial genomic data needs to account for the disruptive effect of recombination on phylogenetic relationships, and we describe how this can be achieved. Dated phylogenies can then be used to perform fine-scale or large-scale epidemiological analyses, depending on the proportion of cases for which genomes are available. A key feature of this approach is computational scalability and in particular the ability to process hundreds or thousands of genomes within a matter of hours. This is a clear advantage of the step-by-step approach described here. We discuss other advantages and disadvantages of the approach, as well as potential improvements and avenues for future research. This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'.
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