The effective control of multidrug resistant tuberculosis (MDR-TB) relies upon the timely diagnosis and correct treatment of all tuberculosis cases. Whole genome sequencing (WGS) has great potential as a method for the rapid diagnosis of drug resistant Mycobacterium tuberculosis (Mtb) isolates. This method overcomes most of the problems that are associated with current phenotypic drug susceptibility testing. However, the application of WGS in the clinical setting has been deterred by data complexities and skill requirements for implementing the technologies as well as clinical interpretation of the next generation sequencing (NGS) data. The proposed diagnostic application was drawn upon recent discoveries of patterns of Mtb clade-specific genetic polymorphisms associated with antibiotic resistance. A catalogue of genetic determinants of resistance to thirteen anti-TB drugs for each phylogenetic clade was created. A computational algorithm for the identification of states of diagnostic polymorphisms was implemented as an online software tool, Resistance Sniffer (http://resistance-sniffer.bi.up.ac.za/), and as a stand-alone software tool to predict drug resistance in Mtb isolates using complete or partial genome datasets in different file formats including raw Illumina fastq read files. The program was validated on sequenced Mtb isolates with data on antibiotic resistance trials available from GMTV database and from the TB Platform of South African Medical Research Council (SAMRC), Pretoria. The program proved to be suitable for probabilistic prediction of drug resistance profiles of individual strains and large sequence data sets.

耐多药结核病（MDR-TB）的有效控制取决于对所有结核病病例的及时诊断和正确治疗。全基因组测序（WGS）作为快速诊断耐药性结核分枝杆菌的方法具有巨大潜力（MTB）分离株。该方法克服了与当前表型药物敏感性测试相关的大多数问题。但是，WGS在临床环境中的应用受到实施该技术的数据复杂性和技能要求以及下一代测序（NGS）数据的临床解释的阻碍。拟议的诊断应用是基于最近发现的与抗生素抗性相关的Mtb进化枝特异性遗传多态性模式而得出的。建立了针对每个系统进化枝对十三种抗结核药物产生耐药性的遗传决定因素目录。作为在线软件工具Resistance Sniffer（http://resistance-sniffer.bi.up.ac.za/），实现了一种用于诊断多态性状态识别的计算算法，fastq读取文件。该程序已通过GMTV数据库和比勒陀利亚南非医学研究理事会（SAMRC）的TB平台获得的抗生素抗药性试验数据，在测序的Mtb分离株上进行了验证。该程序被证明适合于个别菌株和大序列数据集的耐药谱的概率预测。