DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis.

ABSTRACT:

Motivation

Resistance co-occurrence within first-line anti-tuberculosis (TB) drugs is a common phenomenon. Existing methods based on genetic data analysis of Mycobacterium tuberculosis (MTB) have been able to predict resistance of MTB to individual drugs, but have not considered the resistance co-occurrence and cannot capture latent structure of genomic data that corresponds to lineages.

Results

We used a large cohort of TB patients from 16 countries across six continents where whole-genome sequences for each isolate and associated phenotype to anti-TB drugs were obtained using drug susceptibility testing recommended by the World Health Organization. We then proposed an end-to-end multi-task model with deep denoising auto-encoder (DeepAMR) for multiple drug classification an

SUBMITTER: Yang Y 

PROVIDER: S-EPMC6748723 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature