CoV-Spectrum: analysis of globally shared SARS-CoV-2 data to identify and characterize new variants
dc.contributor.author
Chen, Chaoran
dc.contributor.author
Nadeau, Sarah Ann
dc.contributor.author
Yared, Michael
dc.contributor.author
Voinov, Philippe
dc.contributor.author
Xie, Ning
dc.contributor.author
Roemer, Cornelius
dc.contributor.author
Stadler, Tanja
dc.date.accessioned
2022-06-14T14:51:11Z
dc.date.available
2022-02-24T06:07:18Z
dc.date.available
2022-06-14T14:51:11Z
dc.date.issued
2022-03-15
dc.identifier.issn
1367-4803
dc.identifier.issn
1460-2059
dc.identifier.other
10.1093/bioinformatics/btab856
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/533950
dc.identifier.doi
10.3929/ethz-b-000533950
dc.description.abstract
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.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Oxford University Press
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nc/4.0/
dc.title
CoV-Spectrum: analysis of globally shared SARS-CoV-2 data to identify and characterize new variants
en_US
dc.type
Journal Article
dc.rights.license
Creative Commons Attribution-NonCommercial 4.0 International
dc.date.published
2021-12-25
ethz.journal.title
Bioinformatics
ethz.journal.volume
38
en_US
ethz.journal.issue
6
en_US
ethz.journal.abbreviated
Bioinformatics
ethz.pages.start
1735
en_US
ethz.pages.end
1737
en_US
ethz.version.deposit
publishedVersion
en_US
ethz.grant
Real-time monitoring of COVID-19 transmission through phylodynamics
en_US
ethz.grant
Large-scale testing and tracking of SARS-CoV-2 infection and evolution by deep sequencing
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ethz.identifier.wos
ethz.identifier.scopus
ethz.publication.place
Oxford
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02060 - Dep. Biosysteme / Dep. of Biosystems Science and Eng.::09490 - Stadler, Tanja / Stadler, Tanja
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02060 - Dep. Biosysteme / Dep. of Biosystems Science and Eng.::09490 - Stadler, Tanja / Stadler, Tanja
en_US
ethz.grant.agreementno
196267
ethz.grant.agreementno
196348
ethz.grant.fundername
SNF
ethz.grant.fundername
SNF
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.funderDoi
10.13039/501100001711
ethz.grant.program
Special Call on Coronaviruses
ethz.grant.program
Special Call on Coronaviruses
ethz.date.deposited
2022-02-24T06:07:37Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2022-06-14T14:51:17Z
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2023-02-07T03:31:43Z
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true
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