Optical genome mapping identifies rare structural variations as predisposition factors associated with severe COVID-19

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Abstract

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  1. Eva Chan

    Review 2: "Host genome analysis of structural variations by Optical Genome Mapping provides clinically valuable insights into genes implicated in critical immune, viral infection, and viral replication pathways in patients with severe COVID-19"

    This preprint identifies associations between genomic structural variants and COVID-19 severity uses Optical Genome Mapping. Reviewers find the work unreliable due to control arm demographics and lack of experiments confirming causative, rather than correlative, association.

  2. Abdelazeem Elhabyan

    Review 1: "Host genome analysis of structural variations by Optical Genome Mapping provides clinically valuable insights into genes implicated in critical immune, viral infection, and viral replication pathways in patients with severe COVID-19"

    This preprint identifies associations between genomic structural variants and COVID-19 severity uses Optical Genome Mapping. Reviewers find the work unreliable due to control arm demographics and lack of experiments confirming causative, rather than correlative, association.

  3. Strength of evidence

    Reviewers: Abdelazeem Elhabyan (Tanta University) | 📒📒📒◻️◻️
    Eva Chan (New South Wales Health Pathology) | 📒📒📒◻️◻️

  4. SciScore for 10.1101/2021.01.05.21249190: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: The samples were collected under an approved HAC by the IRB Committee A (IRB REGISTRATION # 1597188-2), Augusta University, GA. Based on the IRB approval, all PHI was removed and all data was anonymized before accessing for the study.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableExpression Analysis: Total RNA was isolated from peripheral blood of 11 asymptomatic patients [(3 Male, 8 female) age range 25-59 years [43.2 (mean) ± 11.3 (Stdev)] and 12 severely ill COVID-19 patients [(6 Male and 6 Female) age range 18-81 years [(61.8 (mean) ± 15.4 (Stdev)], using mRNeasy mini kit (QIAGEN, Germany)

    Table 2: Resources

    No key resources detected.


    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.