Sensitive quantitative detection of SARS-CoV-2 in clinical samples using digital warm-start CRISPR assay

  1. Xiong Ding
  2. Kun Yin
  3. Ziyue Li
  4. Maroun M. Sfeir
  5. Changchun Liu

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

No abstract available

Article activity feed

  1. Version published to 10.1016/j.bios.2021.113218
  2. ScreenIT

    SciScore for 10.1101/2020.11.21.20236109: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: All clinical samples were de-identified and handled in compliance with ethical regulations and the approval of Institutional Review Board of the University of Connecticut Health Center (protocol #: P61067).
    RandomizationSix distinct regions without overlapping areas were randomly captured by the microscopy to cover about 2809 microreactions.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The number of positive spots was counted by using the ImageJ software.
    ImageJ
    suggested: (ImageJ, RRID:SCR_003070)
    The step-by-step operation is described below: Image>Type (8-bit)>Edit>Invert>Image>Adjust (Threshold: 0 and 245)>Apply>Analyze>Analyze Particles>Distribution>List.
    Image>Type
    suggested: None
    Statistics and reproducibility: GraphPad Software Prism 8.0.1 was used to plot real-time fluorescence curves, analyze linear regression, and verify statistical significance between two assay groups.
    GraphPad Software Prism
    suggested: None

    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: Please consider improving the rainbow (“jet”) colormap(s) used on page 4. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    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 10.1101/2020.11.21.20236109v1 on medRxiv