Jacopo Verducci
Drug resistant variants detection using an evolutionary algorithm applied on whole genome sequencing data.
Rel. Giovanni Squillero, Pietro Barbiero, Giulio Ferrero, Alberto Paolo Tonda. Politecnico di Torino, Master of science program in Computer Engineering, 2022
Abstract
The excessive usage of antibiotics is driving the rise of antibiotics resistance. The drug susceptibility testing (DST) based on culture for drug resistance detection is the gold standard for managing the Mycobacterium tuberculosis infection. However, these tests are manual and require time, sophisticated laboratory infrastructure and qualified staff able to use the instrument. To provide an alternative to manual DST, in recent years, many software have been created, including Mykrobe, an open source software, that performs anti microbial resistance predictions (AMR) on microbial deep sequencing data. This prediction is performed in a few minutes and doesn’t require qualified staff to run it.
The prediction is possible thanks to a Mykrobe internal database of variants and the relative drug resistances, called panels
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