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

Author:

Chen Chaoran12ORCID,Nadeau Sarah12,Yared Michael3,Voinov Philippe3,Xie Ning4,Roemer Cornelius25,Stadler Tanja12

Affiliation:

1. Department of Biosystems Science and Engineering, ETH Zürich, CH-4058 Basel, Switzerland

2. Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland

3. Department of Computer Science, ETH Zürich, CH-8092 Zürich, Switzerland

4. Department of Informatics, University of Zurich, CH-8050 Zürich, Switzerland

5. Biozentrum, University of Basel, CH-4056 Basel, Switzerland

Abstract

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.

Funder

Swiss National Science foundation

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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