Coll, FrancescMcNerney, RuthPreston, Mark D.Guerra-Assunção, José AfonsoWarry, AndrewHill-Cawthorne, GrantMallard, KimNair, MridulMiranda, AnabelaAlves, AdrianaPerdigão, JoãoViveiros, MiguelPortugal, IsabelHasan, ZahraHasan, RuminaGlynn, Judith R.Martin, NigelPain, ArnabClark, Taane G.2018-05-142018-05-142015-05-27PURE: 1645018PURE UUID: d8f4e4e6-76c2-4f7c-bb4f-15e9c0e8e9abScopus: 84939257684WOS: 000355073700001PubMed: 26019726ORCID: /0000-0001-9676-6251/work/45270609http://www.scopus.com/inward/record.url?scp=84939257684&partnerID=8YFLogxKPMID: 26019726 WOS:000355073700001Mycobacterium tuberculosis drug resistance (DR) challenges effective tuberculosis disease control. Current molecular tests examine limited numbers of mutations, and although whole genome sequencing approaches could fully characterise DR, data complexity has restricted their clinical application. A library (1,325 mutations) predictive of DR for 15 anti-tuberculosis drugs was compiled and validated for 11 of them using genomic-phenotypic data from 792 strains. A rapid online 'TB-Profiler' tool was developed to report DR and strain-type profiles directly from raw sequences. Using our DR mutation library, in silico diagnostic accuracy was superior to some commercial diagnostics and alternative databases. The library will facilitate sequence-based drug-susceptibility testing.1200673engGenetics(clinical)GeneticsMolecular BiologyMolecular MedicineSDG 3 - Good Health and Well-beingjournal article10.1186/s13073-015-0164-0https://www.scopus.com/pages/publications/84939257684