Author:
Moshiri Niema,Fisch Kathleen M.,Birmingham Amanda,DeHoff Peter,Yeo Gene W.,Jepsen Kristen,Laurent Louise C.,Knight Rob
Abstract
AbstractThroughout the COVID-19 pandemic, massive sequencing and data sharing efforts enabled the real-time surveillance of novel SARS-CoV-2 strains throughout the world, the results of which provided public health officials with actionable information to prevent the spread of the virus. However, with great sequencing comes great computation, and while cloud computing platforms bring high-performance computing directly into the hands of all who seek it, optimal design and configuration of a cloud compute cluster requires significant system administration expertise. We developed ViReflow, a user-friendly viral consensus sequence reconstruction pipeline enabling rapid analysis of viral sequence datasets leveraging Amazon Web Services (AWS) cloud compute resources and the Reflow system. ViReflow was developed specifically in response to the COVID-19 pandemic, but it is general to any viral pathogen. Importantly, when utilized with sufficient compute resources, ViReflow can trim, map, call variants, and call consensus sequences from amplicon sequence data from 1000 SARS-CoV-2 samples at 1000X depth in < 10 min, with no user intervention. ViReflow’s simplicity, flexibility, and scalability make it an ideal tool for viral molecular epidemiological efforts.
Funder
National Science Foundation
Centers for Disease Control and Prevention
Publisher
Springer Science and Business Media LLC
Cited by
15 articles.
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