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The ViReflow pipeline enables user friendly large scale viral consensus genome reconstruction.
Moshiri, Niema; Fisch, Kathleen M; Birmingham, Amanda; DeHoff, Peter; Yeo, Gene W; Jepsen, Kristen; Laurent, Louise C; Knight, Rob.
  • Moshiri N; Department of Computer Science & Engineering, University of California San Diego, La Jolla, CA, USA. niema@ucsd.edu.
  • Fisch KM; Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA.
  • Birmingham A; Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA.
  • DeHoff P; Center for Computational Biology and Bioinformatics, University of California San Diego, La Jolla, CA, USA.
  • Yeo GW; Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Diego, La Jolla, CA, USA.
  • Jepsen K; Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA.
  • Laurent LC; Stem Cell Program, University of California San Diego, La Jolla, CA, USA.
  • Knight R; Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
Sci Rep ; 12(1): 5077, 2022 03 24.
Article in English | MEDLINE | ID: covidwho-1815587
ABSTRACT
Throughout 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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Software / COVID-19 Type of study: Observational study Topics: Variants Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-09035-w

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Software / COVID-19 Type of study: Observational study Topics: Variants Limits: Humans Language: English Journal: Sci Rep Year: 2022 Document Type: Article Affiliation country: S41598-022-09035-w