ArticleBMC bioinformatics2017
BugMat and FindNeighbour: command line and server applications for investigating bacterial relatedness.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Catwalk: identifying closely related sequences in large microbial sequence databases.Microbial genomics · 2022Article
- Infection prevention and control insights from a decade of pathogen whole-genome sequencing.The Journal of hospital infection · 2022Review
- A publicly accessible database forMicrobial genomics · 2020Article
- Hash-Based Core Genome Multilocus Sequence Typing for Clostridium difficile.Journal of clinical microbiology · 2019Article
- Computational pan-genome mapping and pairwise SNP-distance improve detection of Mycobacterium tuberculosis transmission clusters.PLoS computational biology · 2019Article
- GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens.Genome research · 2018Article
- Control of Artifactual Variation in Reported Intersample Relatedness during Clinical Use of a Mycobacterium tuberculosis Sequencing Pipeline.Journal of clinical microbiology · 2018Article
- Observational
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundLarge scale bacterial sequencing has made the determination of genetic relationships within large sequence collections of bacterial genomes derived from the same microbial species an increasingly common task. Solutions to the problem have application to public health (for example, in the detection of possible disease transmission), and as part of divide-and-conquer strategies selecting groups of similar isolates for computationally intensive methods of phylogenetic inference using (for example) maximal likelihood methods. However, the generation and maintenance of distance matrices is computationally intensive, and rapid methods of doing so are needed to allow translation of microbial genomics into public health actions.
resultsWe developed, tested and deployed three solutions. BugMat is a fast C++ application which generates one-off in-memory distance matrices. FindNeighbour and FindNeighbour2 are server-side applications which build, maintain, and persist either complete (for FindNeighbour) or sparse (for FindNeighbour2) distance matrices given a set of sequences. FindNeighbour and BugMat use a variation model to accelerate computation, while FindNeighbour2 uses reference-based compression. Performance metrics show scalability into tens of thousands of sequences, with options for scaling further.
conclusionThree applications, each with distinct strengths and weaknesses, are available for distance-matrix based analysis of large bacterial collections. Deployed as part of the Public Health England solution for M. tuberculosis genomic processing, they will have wide applicability.
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