MentaLiST

MentaLiST implements a k-mer voting algorithm to perform multi-locus sequence typing (MLST) on core genome (cgMLST) and whole-genome (wgMLST) schemes for high-resolution bacterial genotyping.

Key Features:

• K-mer voting algorithm: Uses a k-mer counting voting approach to assign alleles and determine sequence types across MLST schemes.
• Implementation language: Implemented in the Julia programming language.
• Performance: Demonstrated to be faster than existing MLST callers while maintaining or exceeding their accuracy.
• Scalability: Processes MLST schemes involving up to thousands of genes, including cgMLST and wgMLST.
• Resource efficiency: Requires limited computational resources.

Scientific Applications:

• Hospital outbreak surveillance: Provides high-resolution genotyping of bacterial pathogens for detection and investigation of nosocomial outbreaks.
• Foodborne pathogen surveillance: Supports high-resolution typing for investigation and tracking of foodborne pathogen outbreaks.
• Epidemiological tracking: Enables tracking of infection spread and investigation of pathogen population structure at fine resolution.

Methodology:

MentaLiST implements a k-mer voting algorithm based on k-mer counting, is implemented in Julia, and has been validated on real and simulated datasets.