期刊
GENOME MEDICINE
卷 7, 期 -, 页码 -出版社
BMC
DOI: 10.1186/s13073-015-0164-0
关键词
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资金
- Bloomsbury Research Fund
- Fundacao para a Ciencia e Tecnologia
- Medical Research Council UK [MR/K000551/1]
- Wellcome Trust [096249/Z/11/B]
- King Abdullah University of Science and Technology (KAUST)
- Fundação para a Ciência e a Tecnologia [PTDC/SAU-ESA/71208/2006, SFRH/BD/136134/2018] Funding Source: FCT
- Wellcome Trust [096249/Z/11/B] Funding Source: Wellcome Trust
- MRC [MR/K000551/1] Funding Source: UKRI
- Medical Research Council [MR/K000551/1] Funding Source: researchfish
Mycobacterium 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.
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