Use of Genomics to Track Coronavirus Disease Outbreaks, New Zealand

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Abstract

No abstract available

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  1. SciScore for 10.1101/2020.10.28.20221853: (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
    Genomes assigned to the B.1.1.1. lineage (n = 4,544) were subsampled to include 1,996 most recent-in-time sequences along with four outgroup (non-B.1.1.1.) sequences, and were aligned with those from the recent New Zealand outbreak (n = 140) using MAFFT (v 7)22 employing the FFT-NS-2 progressive alignment algorithm.
    MAFFT
    suggested: (MAFFT, RRID:SCR_011811)
    Bayesian phylogenetic analyses were performed using BEAST 2.523.
    BEAST
    suggested: (BEAST, RRID:SCR_010228)
    Phylogenetic trees were annotated using FigTree (v 1.4)25 and Tree of Life (v 4)26.
    FigTree
    suggested: (FigTree, RRID:SCR_008515)

    Results from OddPub: Thank you for sharing your code.


    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.