Author: Moshiri, Niema
Title: ViralMSA: Massively scalable reference-guided multiple sequence alignment of viral genomes Cord-id: l9a7upui Document date: 2020_7_3
ID: l9a7upui
Snippet: 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 scale poorly with respect to the number of sequences. Results ViralMSA is a user-friendly reference-guided multiple sequence alignment tool that leverages the algorithmic techniques of read mappers to enable the multiple sequence alignment of ultra-large viral genome datasets. It scales line
Document: 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 scale poorly with respect to the number of sequences. Results ViralMSA is a user-friendly reference-guided multiple sequence alignment tool that leverages the algorithmic techniques of read mappers to enable the multiple sequence alignment 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. Availability ViralMSA is freely available at https://github.com/niemasd/ViralMSA as an open-source software project. Contact [email protected]
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