bioRxivBioinformaticsPreprint
CovRadar: Continuously tracking and filtering SARS-CoV-2 mutations for molecular surveillance
Alice WittigiD, Fábio Malcher MirandaiD, Martin HölzeriD, Tom AltenburgiD, Jakub M. BartoszewicziD, Sebastian BeyversiD, Marius Alfred DieckmanniD, Ulrich GenskeiD, Sven H. GieseiD, Melania NowickaiD, Hugues RichardiD, Henning SchiebenhoeferiD, Anna-Juliane Schmachtenberg, Paul Sieben, Ming TangiD, Julius Tembrockhaus, Bernhard Y. RenardiD, Stephan FuchsiD
Abstract
The SARS-CoV-2 pandemic underlined the importance of molecular surveillance to track the evolution of the virus and inform public health interventions. Fast analysis, easy visualization and convenient filtering of the latest virus sequences are essential for this purpose. However, access to computational resources, the lack of bioinformatics expertise, and the sheer volume of sequences in public databases complicate surveillance efforts. CovRadar combines an analytical pipeline and a web application designed for the molecular surveillance of the spike gene of SARS-CoV-2, an important vaccine target. The intuitive web front-end focuses on mutations rather than viral lineages and provides easy access to frequencies and spatio-temporal distributions from global sample collections. The data is regularly updated based on a scalable and reproducible analytical back-end. With this platform, we aim to give users, those with or without bioinformatics skills or sufficient computational resources, the possibility to track and explore mutational changes in the SARS-CoV-2 spike gene and to filter, download, and further analyze data that meet their questions and needs. Advanced computational users have the ability to apply the analytical pipeline and data visualization methods locally on their own data. CovRadar is freely accessible at https://covradar.net, source code is available at https://gitlab.com/dacs-hpi/covradar. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=150 SRC="FIGDIR/small/429146v3_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@194a562org.highwire.dtl.DTLVardef@1f5f0d3org.highwire.dtl.DTLVardef@195b5dborg.highwire.dtl.DTLVardef@1d65231_HPS_FORMAT_FIGEXP M_FIG C_FIG
- Citations
- 2
Reproducibility ledger
Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.
Sign in to file a reproducibility report.
Related papers
- coronapp: a Web Application to Annotate and Monitor SARS-CoV-2 Mutations
Daniele Mercatelli, Luca Triboli, … Federico Manuel Giorgi·Journal of Medical VirologyPeer-reviewed·Nov 18, 2020
- Pandemic preparedness through genomic surveillance: Overview of mutations in SARS-CoV-2 over the course of COVID-19 outbreak
Fares Z. Najar, Chelsea L. Murphy, … Pratul K. Agarwal·bioRxiv·Aug 12, 2023
- COVID-MVP: an interactive visualization for tracking SARS-CoV-2 mutations, variants, and prevalence, enabled by curated functional annotations and portable genomics workflow
Muhammad Zohaib Anwar, Ivan S. Gill, … William Hsiao·bioRxiv·Jun 7, 2022
- The SARS-CoV-2 Spike Protein Mutation Explorer: Using an Interactive Application to Improve the Public Understanding of SARS-CoV-2 Variants of Concern
Sarah Iannucci, William T. Harvey, … Edward C. Hutchinson·Journal of Visual Communication in MedicinePeer-reviewed·Jul 3, 2023
- SARS2Mutant: SARS-CoV-2 Amino-Acid Mutation Atlas Database
Karim Rahimian, Ehsan Arefian, … Youping Deng·NAR Genomics and BioinformaticsPeer-reviewed·Mar 29, 2023
- Evolving Insights from SARS-CoV-2 Genome from 200K COVID-19 Patients
Sanket Desai, Aishwarya Rane, … Amit Dutt·bioRxiv·Jan 21, 2021