ViralMSA: massively scalable reference-guided multiple sequence alignment of viral genomes
Niema Moshiri
Abstract
MOTIVATION: In molecular epidemiology, the identification of clusters of transmissions typically requires the alignment of viral genomic sequence data. However, existing methods of multiple sequence alignment (MSA) scale poorly with respect to the number of sequences. RESULTS: ViralMSA is a user-friendly reference-guided MSA tool that leverages the algorithmic techniques of read mappers to enable the MSA of ultra-large viral genome datasets. It scales linearly with the number of sequences, and it is able to align tens of thousands of full viral genomes in seconds. However, alignments produced by ViralMSA omit insertions with respect to the reference genome. AVAILABILITY AND IMPLEMENTATION: ViralMSA is freely available at https://github.com/niemasd/ViralMSA as an open-source software project. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.