Nucleic Acids ResearchBioinformaticsPeer-reviewed journal article
The Ensembl COVID-19 resource: Ongoing integration of public SARS-CoV-2 data
Nishadi H. De SilvaiD, Jyothish N Nair Thulasee BhaiiD, Marc ChakiachviliiD, Bruno Contreras‐MoreiraiD, Carla A. CumminsiD, Adam FrankishiD, Astrid GalliD, Thiago A. L. GeneziD, Kevin HoweiD, Sarah E HuntiD, Fergal J. MartiniD, Benjamin MooreiD, Denye Nathaniel OgehiD, Anne Parker, Andrew PartoniD, Magali RuffieriD, Manoj Pandian SakthiveliD, Dan SheppardiD, John G. TateiD, Anja ThormanniD, David ThybertiD, Stephen J. TrevanioniD, Andrea WinterbottomiD, Daniel R. ZerbinoiD, Robert D. FinniD, , Andrew D. YatesiD
Abstract
The COVID-19 pandemic has seen unprecedented use of SARS-CoV-2 genome sequencing for epidemiological tracking and identification of emerging variants. Understanding the potential impact of these variants on the infectivity of the virus and the efficacy of emerging therapeutics and vaccines has become a cornerstone of the fight against the disease. To support the maximal use of genomic information for SARS-CoV-2 research, we launched the Ensembl COVID-19 browser, incorporating a new Ensembl gene set, multiple variant sets (including novel variation calls), and annotation from several relevant resources integrated into the reference SARS-CoV-2 assembly. This work included key adaptations of existing Ensembl genome annotation methods to model ribosomal slippage, stringent filters to elucidate the highest confidence variants and utilisation of our comparative genomics pipelines on viruses for the first time. Since May 2020, the content has been regularly updated and tools such as the Ensembl Variant Effect Predictor have been integrated. The Ensembl COVID-19 browser is freely available at https://covid-19.ensembl.org.
- organism: virus
- assay: whole-genome sequencing
- research focus: variant calling
- approach: statistical model
- Citations
- 9
- FWCI
- 0.71
- Field percentile
- top 25%
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