CovRadar: continuously tracking and filtering SARS-CoV-2 mutations for genomic surveillance
- PMID: 35799354
- DOI: 10.1093/bioinformatics/btac411
CovRadar: continuously tracking and filtering SARS-CoV-2 mutations for genomic surveillance
Abstract
Summary: The ongoing pandemic caused by SARS-CoV-2 emphasizes the importance of genomic surveillance to understand the evolution of the virus, to monitor the viral population, and plan epidemiological responses. Detailed analysis, easy visualization and intuitive filtering of the latest viral sequences are powerful for this purpose. We present CovRadar, a tool for genomic surveillance of the SARS-CoV-2 Spike protein. CovRadar consists of an analytical pipeline and a web application that enable the analysis and visualization of hundreds of thousand sequences. First, CovRadar extracts the regions of interest using local alignment, then builds a multiple sequence alignment, infers variants and consensus and finally presents the results in an interactive app, making accessing and reporting simple, flexible and fast.
Availability and implementation: CovRadar is freely accessible at https://covradar.net, its open-source code is available at https://gitlab.com/dacs-hpi/covradar.
Supplementary information: Supplementary data are available at Bioinformatics online.
© The Author(s) 2022. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
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- ECDC GRANT/2021/008 ECD.12222/European Centers for Disease Control
- 031L0175C/Bundesministerium für Bildung und Forschung
- 01MK21009E/Bundesministerium für Wirtschaft und Klimaschutz Daten- und KI-gestütztes Frühwarnsystem zur Stabilisierung der deutschen Wirtschaft
- 031A537B/German Network for Bioinformatics Infrastructure
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