A year of COVID-19 GWAS results from the GRASP portal reveals potential genetic risk factors

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Abstract

No abstract available

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  1. SciScore for 10.1101/2021.06.08.21258507: (What is this?)

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

    Table 1: Rigor

    Ethicsnot detected.
    Sex as a biological variableParticipants were enrolled at ages ranging from 37 to 73 and are 51.16% female.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Analyses: Each GWAS was conducted with SAIGE v0.38,13 which controls for population stratification, relatedness and case-control imbalance, and adjusted for baseline age (at enrollment), sex and 10 genetic principal components.
    SAIGE
    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: We detected the following sentences addressing limitations in the study:
    Our study has some limitations. Most importantly, our data and the work of others support large health disparities between EUR and non-EUR individuals related to COVID-19 throughout the ongoing pandemic. Despite an over-representation proportionally among cases and those with severe and fatal outcomes, the non-EUR component of UKB is a proportionally small sample limiting our statistical power to address population-specific genetic variants contributing to health outcomes. Moving forward we feel that having a diverse set of results with different phenotype definitions, sex-specific, ancestry-specific, and including external group summary statistics, all in a common genome reference and annotation framework may maximize the chance for new studies to cross-replicate or meta-analyze results as Covid-19 genetic studies continue to grow.

    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.

    Results from scite Reference Check: We found no unreliable references.


    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.