ACE2 and FURIN variants are potential predictors of SARS-CoV-2 outcome: A time to implement precision medicine against COVID-19

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Abstract

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  1. SciScore for 10.1101/2020.05.16.099176: (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
    The genetic data of non-Finnish European, East Asian and African American populations were obtained from the gnomAD repository 41, which contain data on a total of 125,748 exomes and 71,702 genomes (https://gnomad.broadinstitute.org/).
    https://gnomad.broadinstitute.org/
    suggested: (Genome Aggregation Database, RRID:SCR_014964)
    Statistical analysis: The missense variants were defined as deleterious when predicted to be damaging, probably damaging, disease causing and deleterious by the five algorithms applied, SIFT 50, PolyPhen-2 HumVar, PolyPhen-2 HumDiv 51, MutationTaster 52 and LRT score 53 and/or CADD (Combined Annotation-Dependent Depletion) score of more than 20 54.
    SIFT
    suggested: (SIFT, RRID:SCR_012813)
    PolyPhen-2
    suggested: None
    MutationTaster
    suggested: (MutationTaster, RRID:SCR_010777)
    The significance of the differences in MAFs between different populations was calculated using Chi-Square test, using the R software (https://www.r-project.org/).
    https://www.r-project.org/
    suggested: (R Project for Statistical Computing, RRID:SCR_001905)
    Structural Analysis: All the identified ACE2 missense exon variants were mapped, modeled, and analyzed using Pymol modeling software (https://pymol.org/2/).
    Pymol
    suggested: (PyMOL, RRID:SCR_000305)

    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 24. 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.