PARMAP: A Pan-Genome-Based Computational Framework for Predicting Antimicrobial Resistance.

ABSTRACT: Antimicrobial resistance (AMR) has emerged as one of the most urgent global threats to public health. Accurate detection of AMR phenotypes is critical for reducing the spread of AMR strains. Here, we developed PARMAP (Prediction of Antimicrobial Resistance by MAPping genetic alterations in pan-genome) to predict AMR phenotypes and to identify AMR-associated genetic alterations based on the pan-genome of bacteria by utilizing machine learning algorithms. When we applied PARMAP to 1,597 Neisseria gonorrhoeae strains, it successfully predicted their AMR phenotypes based on a pan-genome analysis. Furthermore, it identified 328 genetic alterations in 23 known AMR genes and discovered many new AMR-associated genetic alterations in ciprofloxacin-resistant N. gonorrhoeae, and it clea

SUBMITTER: Li X 

PROVIDER: S-EPMC7642336 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature