Title
Reconstructing viral haplotypes using long reads
Abstract
Motivation Most RNA viruses lack strict proofreading during replication. Coupled with a high replication rate, some RNA viruses can form a virus population containing a group of genetically related but different haplotypes. Characterizing the haplotype composition in a virus population is thus important to understand viruses' evolution. Many attempts have been made to reconstruct viral haplotypes using next-generation sequencing (NGS) reads. However, the short length of NGS reads cannot cover distant single-nucleotide variants, making it difficult to reconstruct complete or near-complete haplotypes. Given the fast developments of third-generation sequencing technologies, a new opportunity has arisen for reconstructing full-length haplotypes with long reads. Results In this work, we developed a new tool, RVHaplo to reconstruct haplotypes for known viruses from long reads. We tested it rigorously on both simulated and real viral sequencing data and compared it against other popular haplotype reconstruction tools. The results demonstrated that RVHaplo outperforms the state-of-the-art tools for viral haplotype reconstruction from long reads. Especially, RVHaplo can reconstruct the rare (1% abundance) haplotypes that other tools usually missed.
Year
DOI
Venue
2022
10.1093/bioinformatics/btac089
BIOINFORMATICS
DocType
Volume
Issue
Journal
38
8
ISSN
Citations 
PageRank 
1367-4803
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Dehan Cai100.68
Yanni Sun221921.16