HaploCoV

HaploCoV performs unsupervised classification and prioritization of SARS-CoV-2 genomes to detect and prioritize emerging viral variants for genomic surveillance.

Key Features:

• Unsupervised classification: Employs unsupervised methods to classify SARS-CoV-2 genomes without pre-labeled data, enabling detection of novel variants as they emerge.
• Rapid detection: Provides rapid identification of viral variants from genomic data to support timely surveillance.
• Integration with classification and nomenclature systems: Supports integration with existing classification and nomenclature systems for interoperability across surveillance frameworks.
• Scoring and prioritization: Implements a scoring system that prioritizes SARS-CoV-2 variants based on potential epidemiological impact.
• Accuracy and reproducibility: Demonstrated accuracy and reproducibility in retrospective analyses of over 11.5 million genome sequences, identifying the majority of variants flagged by international health authorities.

Scientific Applications:

• Genomic surveillance: Enables systematic monitoring of SARS-CoV-2 genomic diversity at regional and global scales.
• Emerging variant detection: Supports rapid identification and prioritization of novel, emerging SARS-CoV-2 variants for public health response.
• Viral evolution monitoring: Facilitates analysis of temporal and spatial patterns to track SARS-CoV-2 evolution and spread.

Methodology:

Applies unsupervised classification and a scoring/prioritization system while exploring SARS-CoV-2 genomic diversity across spatial and temporal dimensions, validated by retrospective analysis of over 11.5 million genome sequences.