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.