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CoV-Spectrum: analysis of globally shared SARS-CoV-2 data to identify and characterize new variants

Chen, Chaoran ; Nadeau, Sarah ; Yared, Michael ; Voinov, Philippe ; Xie, Ning ; Roemer, Cornelius ; Stadler, Tanja Alkan, Can

Bioinformatics, 2022-03, Vol.38 (6), p.1735-1737 [Periódico revisado por pares]

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Título:
CoV-Spectrum: analysis of globally shared SARS-CoV-2 data to identify and characterize new variants
Autor: Chen, Chaoran ; Nadeau, Sarah ; Yared, Michael ; Voinov, Philippe ; Xie, Ning ; Roemer, Cornelius ; Stadler, Tanja
Alkan, Can
Assuntos: Amino Acids ; Applications Notes ; COVID-19 ; Humans ; Mutation ; SARS-CoV-2
É parte de: Bioinformatics, 2022-03, Vol.38 (6), p.1735-1737
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Descrição: Abstract Summary The CoV-Spectrum website supports the identification of new SARS-CoV-2 variants of concern and the tracking of known variants. Its flexible amino acid and nucleotide mutation search allows querying of variants before they are designated by a lineage nomenclature system. The platform brings together SARS-CoV-2 data from different sources and applies analyses. Results include the proportion of different variants over time, their demographic and geographic distributions, common mutations, hospitalization and mortality probabilities, estimates for transmission fitness advantage and insights obtained from wastewater samples. Availability and implementation CoV-Spectrum is available at https://cov-spectrum.org. The code is released under the GPL-3.0 license at https://github.com/cevo-public/cov-spectrum-website.
Editor: England: Oxford University Press
Idioma: Inglês

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