Clinical utility of SARS-CoV-2 whole genome sequencing in deciphering source of infection

  1. T. Takenouchi
  2. Y.W. Iwasaki
  3. S. Harada
  4. H. Ishizu
  5. Y. Uwamino
  6. S. Uno
  7. A. Osada
  8. K. Abe
  9. N. Hasegawa
  10. M. Murata
  11. T. Takebayashi
  12. K. Fukunaga
  13. H. Saya
  14. Y. Kitagawa
  15. M. Amagai
  16. H. Siomi
  17. K. Kosaki

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Abstract

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  1. Version published to 10.1016/j.jhin.2020.10.014
  2. ScreenIT

    SciScore for 10.1101/2020.05.21.20107599: (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

    Software and Algorithms
    SentencesResources
    Paired-end sequencing was performed on the MiSeq platform (Illumina, CA).
    MiSeq
    suggested: (A5-miseq, RRID:SCR_012148)
    The bioinformatic pipeline used in this study, “Variant calling pipeline for amplicon-based sequencing of the SARS-CoV-2 viral genome”, is available at https://cmg.med.keio.ac.ip/sars-cov-2/.
    bioinformatic
    suggested: (QFAB Bioinformatics, RRID:SCR_012513)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    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.

  3. Version published to 10.1101/2020.05.21.20107599 on medRxiv