Recommendations for accurate genotyping of SARS-CoV-2 using amplicon-based sequencing of clinical samples

  1. Slawomir Kubik
  2. Ana Claudia Marques
  3. Xiaobin Xing
  4. Janine Silvery
  5. Claire Bertelli
  6. Flavio De Maio
  7. Spyros Pournaras
  8. Tom Burr
  9. Yannis Duffourd
  10. Helena Siemens
  11. Chakib Alloui
  12. Lin Song
  13. Yvan Wenger
  14. Alexandra Saitta
  15. Morgane Macheret
  16. Ewan W. Smith
  17. Philippe Menu
  18. Marion Brayer
  19. Lars M. Steinmetz
  20. Ali Si-Mohammed
  21. Josiane Chuisseu
  22. Richard Stevens
  23. Pantelis Constantoulakis
  24. Michela Sali
  25. Gilbert Greub
  26. Carsten Tiemann
  27. Vicent Pelechano
  28. Adrian Willig
  29. Zhenyu Xu

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Abstract

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  1. Version published to 10.1016/j.cmi.2021.03.029
  2. ScreenIT

    SciScore for 10.1101/2020.12.01.405738: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Mapping to human transcriptome and genome were performed using STAR (ver 2.7) (41) and bwa mem (version 0.7.12-r1039) (42), respectively.
    STAR
    suggested: (STAR, RRID:SCR_015899)
    Read coverage was estimated using bedtools coverage from the bedtools suite (version v2.29.2) (43) for the portion of the viral genome targeted by the amplicons (positions 36-29,844 of the reference genome).
    bedtools
    suggested: (BEDTools, RRID:SCR_006646)
    Read subsampling was performed with samtools v1.9 (44).
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    Statistical analysis: Statistical data analyses were performed using the R software environment for statistical computing (46) and graphics with the ggplot2 package (47).
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    The datasets generated with synthetic SARS-CoV-2 genome and analysed during the current study are available in the Sequence Read Archive (SRA) repository under accession number SUB8654793.
    Sequence Read Archive
    suggested: (DDBJ Sequence Read Archive, RRID:SCR_001370)

    Results from OddPub: Thank you for sharing your 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.
    • No funding statement was detected.
    • 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.

  3. Version published to 10.1101/2020.12.01.405738v2 on bioRxiv
  4. Version published to 10.1101/2020.12.01.405738v1 on bioRxiv