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Computational Analysis and Phylogenetic Clustering of SARS-CoV-2 Genomes.
Jolly, Bani; Scaria, Vinod.
  • Jolly B; CSIR Institute of Genomics and Integrative Biology, Mathura Road, Delhi, India.
  • Scaria V; Academy of Scientific and Innovative Research (AcSIR), Kamla Nehru Nagar, Ghaziabad, Uttar Pradesh, India.
Bio Protoc ; 11(8): e3999, 2021 Apr 20.
Article in English | MEDLINE | ID: covidwho-1229580
ABSTRACT
COVID-19, the disease caused by the novel SARS-CoV-2 coronavirus, originated as an isolated outbreak in the Hubei province of China but soon created a global pandemic and is now a major threat to healthcare systems worldwide. Following the rapid human-to-human transmission of the infection, institutes around the world have made efforts to generate genome sequence data for the virus. With thousands of genome sequences for SARS-CoV-2 now available in the public domain, it is possible to analyze the sequences and gain a deeper understanding of the disease, its origin, and its epidemiology. Phylogenetic analysis is a potentially powerful tool for tracking the transmission pattern of the virus with a view to aiding identification of potential interventions. Toward this goal, we have created a comprehensive protocol for the analysis and phylogenetic clustering of SARS-CoV-2 genomes using Nextstrain, a powerful open-source tool for the real-time interactive visualization of genome sequencing data. Approaches to focus the phylogenetic clustering analysis on a particular region of interest are detailed in this protocol.
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Bio Protoc Year: 2021 Document Type: Article Affiliation country: BioProtoc.3999

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Bio Protoc Year: 2021 Document Type: Article Affiliation country: BioProtoc.3999