Hi everyone 🖖
If you are thinkging about using #nanopore for genomic surveillance in #hospitals, but don't have the #bioinformatics nor command-line skills, don't let that put you off.
'Modernising Medical Microbiology', at @NDMOxford in #Oxford, has developed `OxBreaker': a graphical tool that can help identify budding #outbreaks by #healthcare professionals without having to upload your data to external servers and compromise patient privacy. Worth a read 👇
OxBreaker: species-agnostic pipeline for the analysis of outbreaks using nanopore sequencing
Real-time genomic surveillance may mitigate the spread of health-care-associated infections, but whole-genome sequencing costs and the need for specialised expertise constrain its wide implementation in public health. Here we present ‘ OxBreaker ’, an automated and species-agnostic pipeline optimised for the high-resolution analysis of bacterial and plasmid genomes sequenced via Oxford Nanopore Technologies (ONT). ‘ OxBreaker ’ streamlines the transition from raw reads to phylogenetic inference through automated reference selection and high-accuracy variant calling. It is accessible via a graphical user interface (GUI) that can be easily installed locally and operated by non-specialists. Benchmarking against technical and biological replicates of high-priority pathogens demonstrates high accuracy, with false positive variant rates reduced to 0–4 single-nucleotide polymorphisms (SNPs) for common species. We further validated the pipeline by accurately characterising previously published clonal and plasmid-mediated outbreaks, reproducing established phylogenies with improved accessibility. By providing a stable, scalable, open-source offline-compatible solution that matches the resolution of short-read platforms while maintaining the speed of long-read technology, ‘ OxBreaker ’ is designed to facilitate the adoption of local, real-time genomic surveillance for frontline infection prevention and control. ### Competing Interest Statement The authors have declared no competing interest. NIHR Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance, NIHR207397 NIHR Biomedical Research Centre, Oxford, GB
Because they had phenotypic data on their stuff, they are using the tool to predict phenotypes from their genomic datasets. But that's another story.
