PATO

PATO analyzes large genomic datasets to define core and accessory genomes, characterize population structure, and annotate pathogenic features for pangenomic and comparative genomic studies.

Key Features:

• High-throughput Analysis: Capable of analyzing thousands of genomes simultaneously on a desktop computer.
• Core Software Integration: Leverages MASH, MMSeq2, and Minimap2 for rapid and accurate genomic comparisons.
• Core-genome Definition: Defines core genomes from input genome collections.
• Accessory Genome Properties Analysis: Characterizes accessory genome content and properties.
• Population Structure Characterization: Characterizes population structure among analyzed genomes.
• Annotation of Pathogenic Features: Annotates pathogenic features within genomes.
• Creation of Gene Sharedness Networks: Generates gene sharedness networks to represent gene presence–absence relationships.
• Performance: Performs bioinformatic analyses in minutes with reported speed 20–30 times faster than leading software while maintaining comparable accuracy.
• Integration and Visualization: Implemented as an R package and provides visualization capabilities for result interpretation.

Scientific Applications:

• Microbial genomics: Supports studies of genome variability and population dynamics in microbial systems.
• Infectious disease research: Supports annotation of pathogenic features relevant to infectious disease studies.
• Microbial evolution: Facilitates investigation of evolutionary relationships and dynamics among genomes.
• Antibiotic resistance research: Enables analysis of genomic features and patterns associated with antibiotic resistance mechanisms.

Methodology:

Uses MASH, MMSeq2, and Minimap2 and applies sequence alignment, clustering, and comparative genomics techniques to analyze pangenomic structures in large genomic datasets.