The Ensembl COVID-19 resource: ongoing integration of public SARS-CoV-2 data

  1. Nishadi H De Silva
  2. Jyothish Bhai
  3. Marc Chakiachvili
  4. Bruno Contreras-Moreira
  5. Carla Cummins
  6. Adam Frankish
  7. Astrid Gall
  8. Thiago Genez
  9. Kevin L Howe
  10. Sarah E Hunt
  11. Fergal J Martin
  12. Benjamin Moore
  13. Denye Ogeh
  14. Anne Parker
  15. Andrew Parton
  16. Magali Ruffier
  17. Manoj Pandian Sakthivel
  18. Dan Sheppard
  19. John Tate
  20. Anja Thormann
  21. David Thybert
  22. Stephen J Trevanion
  23. Andrea Winterbottom
  24. Daniel R Zerbino
  25. Robert D Finn
  26. Paul Flicek
  27. Andrew D Yates

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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; the first virus to be encompassed within the Ensembl platform. This resource incorporates a new Ensembl gene set, multiple variant sets, and annotation from several relevant resources aligned to the reference SARS-CoV-2 assembly. Since the first release in May 2020, the content has been regularly updated using our new rapid release workflow, 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.

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  1. Version published to 10.1093/nar/gkab889
  2. Version published to 10.1101/2020.12.18.422865v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2020.12.18.422865: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  4. Version published to 10.1101/2020.12.18.422865v1 on bioRxiv