VirusWarn: A mutation-based early warning system to prioritize concerning SARS-CoV-2 and influenza virus variants from sequencing data.

ABSTRACT: The rapid evolution of respiratory viruses is characterized by the emergence of variants with concerning phenotypes that are efficient in antibody escape or show high transmissibility. This necessitates timely identification of such variants by surveillance networks to assist public health interventions. Here, we introduce VirusWarn, a comprehensive system designed for detecting, prioritizing, and warning of emerging virus variants from large genomic datasets. VirusWarn uses both manually-curated rules and machine-learning (ML) classifiers to generate and rank pathogen sequences based on mutations of concern and regions of interest. Validation results for SARS-CoV-2 showed that VirusWarn successfully identifies variants of concern in both assessments, with manual- and ML-derived cri

SUBMITTER: Kirschbaum C 

PROVIDER: S-EPMC11964653 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature