AccuVIR

AccuVIR assembles and polishes viral genomes from third-generation long-read sequencing data, leveraging viral gene structural properties to distinguish true genetic variants from Nanopore sequencing errors for RNA viruses such as Ebola, Zika, and SARS-CoV-2.


Key Features:

  • Error Correction and Polishing: Distinguishes true genetic variants from sequencing errors by leveraging the high density of coding regions in RNA viruses and correcting errors that disrupt gene structures.
  • Path Searching and Sampling: Employs path searching and sampling techniques within sequence alignment graphs to explore alternative sequence paths for assembly or polishing of draft viral genomes.
  • Handling Long Reads: Optimized for long reads from third-generation sequencing technologies such as Nanopore, addressing high per-base error rates in real-time viral sequencing.

Scientific Applications:

  • Virus Evolution Studies: Provides complete and accurate viral genomes to identify genetic variants that inform studies of viral adaptation and evolution.
  • Genotype-Phenotype Relationships: Supports analysis linking viral genotypes to phenotypic properties such as transmissibility and virulence.
  • Real-Time Surveillance: Enables accurate genome reconstruction from long-read sequencing data to support outbreak monitoring and real-time surveillance of emerging viral threats.

Methodology:

Performs path searching and sampling within sequence alignment graphs and evaluates candidate paths against known gene structures to filter sequencing errors that disrupt coding regions.

Topics

Collections

Details

License:
Not licensed
Tool Type:
command-line tool
Programming Languages:
Python
Added:
2/9/2023
Last Updated:
11/24/2024

Operations

Publications

Yu R, Cai D, Sun Y. AccuVIR: an ACCUrate VIRal genome assembly tool for third-generation sequencing data. Bioinformatics. 2022;39(1). doi:10.1093/bioinformatics/btac827. PMID:36610711. PMCID:PMC9825286.

PMID: 36610711
PMCID: PMC9825286
Funding: - Hong Kong Research Grants Council: 11206819, 11217521 - City University of Hong Kong Project: 9678241