CATHAI

CATHAI performs high-resolution clustering of whole genome sequencing (WGS) data to detect and analyze healthcare-associated infection outbreaks by integrating genomic data with associated metadata.

Key Features:

• High-resolution clustering: Performs clustering of related organisms at high resolution to distinguish closely related isolates.
• Whole genome sequencing (WGS) integration: Couples WGS data with associated metadata for combined genomic and contextual analysis.
• Genomic visualization: Produces visual representations of genomic relationships to support interpretation of relatedness among isolates.
• Nosocomial outbreak analysis: Enables detection and analysis of transmission events and relatedness within healthcare settings.

Scientific Applications:

• Disease surveillance: Supports genomic surveillance of healthcare-associated infections (HAIs) using WGS-derived clusters and metadata.
• Outbreak detection: Identifies clusters indicative of nosocomial outbreaks to inform epidemiological investigations.
• Transmission inference: Aids identification of transmission patterns and potential sources of infection within clinical environments.

Methodology:

Performs high-resolution clustering of WGS data, couples genomic data with associated metadata, and generates visual representations of genomic relationships for outbreak detection.