Characterizing the performance of an antibiotic resistance prediction tool, gnomonicus, using a diverse test set of 2,663 Mycobacterium tuberculosis samples
Rattachement africain : gb, Afrique du Sud. Niveau de preuve : code pays fourni par la source.
Le résumé fourni par la source
Tuberculosis remains a global health problem. Making it easier and quicker to identify which antibiotics an infection is likely to be susceptible to will be a key part of the solution. Whilst whole-genome sequencing offers many advantages, the processing of the genetic reads to produce the relevant public health and clinical information is, surprisingly, often the responsibility of the end user, which inhibits uptake. Here, we characterize how well a freely available tool we have developed, gnomonicus, predicts the antibiotic resistance profile of a sample (given its variant call file) using our implementation of the second edition of the World Health Organization (WHO) catalogue of resistance-associated variants (WHOv2). To facilitate this, we have constructed a diverse test set of 2,663 publicly available Mycobacterium tuberculosis samples, which have both genetic and drug susceptibility testing (DST) data. We have chosen to apply the catalogue such that our tool will return a result of (i) Fail if there are insufficient reads at a genetic locus associated with resistance, (ii) Unknown if a genetic variant in a resistance gene not listed in the catalogue is encountered and (iii) Resistant if three or more short-reads support the presence of a resistance-associated variant. The last step increases the sensitivity for all 15 antibiotics but only reaches significance in a few in our test set. Comparing our results with those of TB-Profiler, an existing tool, highlights the different design choices and demonstrates that the performance of both tools on our diverse test set is comparable. By only considering high-confidence DST results, we show that gnomonicus, in combination with our translation of WHOv2, achieves sensitivities and specificities in excess of 95% for both isoniazid and rifampicin.
Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.
Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Characterizing the performance of an antibiotic resistance prediction tool, gnomonicus, using a diverse test set of 2,663 Mycobacterium tuberculosis samples
- Date Crossref
- 15/12/2025
- Éditeur
- Microbiology Society
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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University of Oxford Nuffield Department of Medicine pays non établi dans la noticeUniversité ou école supérieure
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Oxford Fertility pays non établi dans la noticeÉtablissement de santé
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John Radcliffe Hospital pays non établi dans la noticeÉtablissement de santé
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National Institute for Health and Care Research pays non établi dans la noticeOrganisme public
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Oxford BioMedica (United Kingdom) pays non établi dans la noticeEntreprise
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National Health Laboratory Service Afrique du Sud (code pays fourni par la source)Organisme public
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Ellison Institute of Technology pays non établi dans la noticeStructure de recherche
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Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance pays non établi dans la noticeStructure de recherche
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National & WHO Supranational TB Reference Laboratory Centre for Tuberculosis Johannesburg, Afrique du Sud (pays nommé en fin d’affiliation)Structure de recherche
Nuffield Department of Medicine — University of Oxford, Oxford Fertility et John Radcliffe Hospital, avec 6 autres affiliations. Pays d’affiliation : Afrique du Sud.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.