# Viral Network Analyzer (VirNA): A Novel Minimum Spanning Networks Algorithm for Investigating Viral Evolution

## TL;DR

VirNA is a new tool that uses network analysis to study viral evolution, especially useful for tracking rapid changes in large datasets during pandemics.

## Contribution

VirNA introduces a novel Minimum Spanning Networks algorithm for detailed analysis of viral evolution in large-scale datasets.

## Key findings

- VirNA reconstructs detailed mutation patterns in viral genomes.
- It enables analysis of thousands of sequences with associated metadata.
- The tool provides insights into pathogen evolution over short time periods.

## Abstract

Next Generation Sequencing technologies are essential in public health surveillance for tracking pathogen evolution, spread, and the emergence of new variants. However, the extensive sequencing of viral genomes during recent pandemics has highlighted the limitations of traditional molecular phylogenetic algorithms in capturing fine-grained evolutionary details when analyzed sequences are highly similar and datasets are large-scale. VirNA (Viral Network Analyzer) addresses this challenge by reconstructing detailed mutation patterns and tracing pathogen evolutionary routes in specific geographical regions through Minimum Spanning Networks. It enables users to analyze thousands of sequences, generating networks where nodes represent genomic sequences linked to their metadata, while edges represent potential evolutionary pathways. VirNA is a powerful tool for analyzing large, high-quality datasets, providing detailed insights into rapid pathogen evolution over short time periods, with potential applications in pandemic surveillance.