GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning.

ABSTRACT:

Background

Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly and accurate resistance prediction tools are needed to enable public health and clinical practitioners to rapidly diagnose resistance and inform treatment regimens.

Results

We present Translational Genomics platform for Tuberculosis (GenTB), a free and open web-based application to predict antibiotic resistance from next-generation sequence data. The user can choose between two potential predictors, a Random Forest (RF) classifier and a Wide and Deep Neural Network (WDNN) to predict phenotypic resistance to 13 and 10 anti-tubercu

SUBMITTER: Groschel MI 

PROVIDER: S-EPMC8407037 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature