CovRadar: continuously tracking and filtering SARS-CoV-2 mutations for genomic 
surveillance

Wittig , Alice; Miranda , Fábio; Hölzer, Martin; Altenburg, Tom; Bartoszewicz, Jakub M.; Beyvers, Sebastian; Dieckmann, Marius A.; Genske, Ulrich; Giese, Sven H.; Nowicka, Melania; Richard, Hugues; Schiebenhoefer, Henning; Schmachtenberg, Anna-Juliane; Sieben, Paul; Tang, Ming; Tembrockhaus, Julius; Renard, Bernhard Y.; Fuchs, Stephan

doi:10.1093/bioinformatics/btac411

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

CovRadar: continuously tracking and filtering SARS-CoV-2 mutations for genomic surveillance

MPS-Authors

/persons/resource/persons295643

Altenburg, Tom
IMPRS for Biology and Computation (Anne-Dominique Gindrat), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons295612

Nowicka, Melania
IMPRS for Biology and Computation (Anne-Dominique Gindrat), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

Bioinformatics_Wittig et al_2022.pdf
(Publisher version), 2MB

Supplementary Material (public)

There is no public supplementary material available

Citation

Wittig, A., Miranda, F., Hölzer, M., Altenburg, T., Bartoszewicz, J. M., Beyvers, S., et al. (2022). CovRadar: continuously tracking and filtering SARS-CoV-2 mutations for genomic surveillance. Bioinformatics, 38(17), 4223-4225. doi:10.1093/bioinformatics/btac411.

Cite as: https://hdl.handle.net/21.11116/0000-000E-5667-E

Abstract

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.