PRAP

PRAP performs comprehensive identification and pan-genomic analysis of antibiotic resistance genes (ARGs) across multiple genomes to characterize ARG distribution and predict allele-associated resistance phenotypes.

Key Features:

• Integration of Databases: Integrates the Comprehensive Antibiotic Resistance Database (CARD) and ResFinder to identify ARGs from various sequence file formats.
• Pan-Genome Approach: Employs a pan-genomic framework to characterize ARG distribution patterns within pathogen populations.
• Advanced Annotation and Analysis: Uses detailed annotations and applies a random forest classifier to predict the impact of alleles on resistance phenotypes.
• Visualization and Outputs: Generates files and visualizations representing pan-resistome features.
• Demonstrated Efficacy: Validated by analysis of 26 Salmonella enterica isolates from Shanghai, China, identifying ARGs and visualizing pan-resistome features.

Scientific Applications:

• ARG Surveillance: Characterizing ARG diversity and distribution across isolate collections to support surveillance studies.
• Horizontal Gene Transfer Studies: Investigating horizontal gene transfer and its influence on resistance patterns within pathogen populations.
• Genotype–Phenotype Association: Predicting allele-associated resistance phenotypes to elucidate genotype–phenotype relationships.
• Pathogen Evolution and Resistance Management: Supporting analyses of pathogen evolution and resistance management by integrating pan-genomic and ARG data.

Methodology:

Implemented in Python3; integrates CARD and ResFinder for ARG identification, uses a pan-genomic framework and detailed annotations, and applies a random forest classifier for allele impact prediction.