Dynamics of severe acute respiratory syndrome coronavirus 2 genome variants in the feces during convalescence

  1. Yi Xu
  2. Lu Kang
  3. Zijie Shen
  4. Xufang Li
  5. Weili Wu
  6. Wentai Ma
  7. Chunxiao Fang
  8. Fengxia Yang
  9. Xuan Jiang
  10. Sitang Gong
  11. Li Zhang
  12. Mingkun Li

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  1. ScreenIT

    SciScore for 10.1101/2020.07.30.230102: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the ethics review committee of Guangzhou Women and Children’s Medical Center.
    Consent: Written informed consents were obtained from the legal guardians of all children.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Clean reads were mapped to SARS-CoV-2 reference genome Wuhan-Hu-1 (GenBank MN908947.3) using BWA mem v0.7.12 (11), followed by duplicate reads removal with Picard v2.18.22 (http://broadinstitute.github.io/picard).
    BWA
    suggested: (BWA, RRID:SCR_010910)
    Picard
    suggested: (Picard, RRID:SCR_006525)
    Mpileup files were generated with samtools v1.8 (12).
    samtools
    suggested: (SAMTOOLS, RRID:SCR_002105)
    Intra-host variants were identified using VarScan v2.3.9 and an in-house script (13).
    VarScan
    suggested: (VARSCAN, RRID:SCR_006849)
    Criteria for variants included: (1) sequencing depth ≥ 50, (2) minor allele frequency ≥ 5%, (3) minor allele frequency ≥ 2% on each strand, (4) minor allele counts ≥ 10 on each strand, (5) strand bias of the minor allele < 10 fold, (6) minor allele was supported by the inner part of the read (excluding 10 base pairs on each end), and (7) minor allele was supported by ≥ 10 reads that were classified as Betacoronavirus by Kraken v2.0.8-beta (14) on each strand.
    Kraken
    suggested: (Kraken, RRID:SCR_005484)
    The ratio of the number of non-synonymous substitutions per non-synonymous site (Ka) to the number of synonymous substitutions per synonymous site (Ks) was calculated using KaKs_Calculator 2.0 (15) with the MS method.
    KaKs_Calculator
    suggested: None

    Results from OddPub: Thank you for sharing your data.

    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.

  2. Version published to 10.1016/j.jgg.2020.10.002
  3. Version published to 10.1101/2020.07.30.230102v1 on bioRxiv