2020
DOI: 10.1016/j.ijmm.2020.151399
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Resistance Sniffer: An online tool for prediction of drug resistance patterns of Mycobacterium tuberculosis isolates using next generation sequencing data

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Cited by 22 publications
(19 citation statements)
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“…TBProfiler v3.0.4 23 was used to analyze all 222 genomes in-silico to infer phylogenetic lineages and drug resistance profiles using small variants and big deletions associated with drug resistance that are present in a robust library of recently updated mutation database which contains new anti-TB drugs such as cycloserine, delamanid, bedaquiline, clofazimine, para-aminosalicylic acid, linezolid and ethionamide [commit b2af444 on 21st December 2020 ( https://github.com/jodyphelan/tbdb )] using freebayes 28 as the variant calling option. In order to validate the results, Mykrobe predictor 29 and Resistance Sniffer 30 was used to analyze the newly sequenced Nigerian samples for comparison.…”
Section: Methodsmentioning
confidence: 99%
“…TBProfiler v3.0.4 23 was used to analyze all 222 genomes in-silico to infer phylogenetic lineages and drug resistance profiles using small variants and big deletions associated with drug resistance that are present in a robust library of recently updated mutation database which contains new anti-TB drugs such as cycloserine, delamanid, bedaquiline, clofazimine, para-aminosalicylic acid, linezolid and ethionamide [commit b2af444 on 21st December 2020 ( https://github.com/jodyphelan/tbdb )] using freebayes 28 as the variant calling option. In order to validate the results, Mykrobe predictor 29 and Resistance Sniffer 30 was used to analyze the newly sequenced Nigerian samples for comparison.…”
Section: Methodsmentioning
confidence: 99%
“…Studies on epistatic networks relevant to DR and virulence evolution will allow predicting outbreaks of DR infections in advance at the time of formation of an epistatic background of antibiotic resistance. This idea was realized in our recent software tool, Resistance Sniffer, which uses NGS data to predict Mtb isolates, which potentially may develop DR in the course of antibiotic therapy [35].…”
Section: Discussionmentioning
confidence: 99%
“…Understanding the stepwise molecular processes of the accumulation of initial prerequisite mutations acting as a gateway for the emergence of MDR is another gap in our knowledge [34]. Knowing the ways of escaping the fitness cost of DR mutations by MDR-TB will uncover molecular targets for new antibiotics and allow predicting Mtb clinical isolates with a potential to develop MDR in the near future [35].…”
Section: Introductionmentioning
confidence: 99%
“…An important drawback to the general application of these approaches as diagnostic tools is that they just provide predictions. Although genotypic-phenotypic linkage seems to be strong in the case of mutation driven resistance [156] and stand-alone informatic tools have been developed to link genotypic-phenotypic information [157] , in the case of resistance genes the phenotype of resistance depends not only on the ARG, but also on its genomic context [24] . Further, sequence-based approaches cannot identify as yet unknown mechanisms of resistance that may contribute to the phenotype.…”
Section: Whole-genome Based Diagnosis and Epidemiology Of Antibiotic Resistancementioning
confidence: 99%