{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/bayesian-identification-of-bacterial-strains","title":"Bayesian identification of bacterial strains from sequencing data","arxiv_id":"1511.06546","date":"2016-02-17","proceeding":null,"authors":[],"abstract":"Rapidly assaying the diversity of a bacterial species present in a sample\nobtained from a hospital patient or an evironmental source has become possible\nafter recent technological advances in DNA sequencing. For several applications\nit is important to accurately identify the presence and estimate relative\nabundances of the target organisms from short sequence reads obtained from a\nsample. This task is particularly challenging when the set of interest includes\nvery closely related organisms, such as different strains of pathogenic\nbacteria, which can vary considerably in terms of virulence, resistance and\nspread. Using advanced Bayesian statistical modelling and computation\ntechniques we introduce a novel pipeline for bacterial identification that is\nshown to outperform the currently leading pipeline for this purpose. Our\napproach enables fast and accurate sequence-based identification of bacterial\nstrains while using only modest computational resources. Hence it provides a\nuseful tool for a wide spectrum of applications, including rapid clinical\ndiagnostics to distinguish among closely related strains causing nosocomial\ninfections. The software implementation is available at\nhttps://github.com/PROBIC/BIB","url_abs":"http://arxiv.org/abs/1511.06546v2","url_pdf":"http://arxiv.org/pdf/1511.06546v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"bayesian-identification-of-bacterial-strains","repo_url":"https://github.com/PROBIC/BIB","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"diversity","task_name":"Diversity"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}