Whole genome comparison of Pakistani Corona virus with Chinese and US Strains along with its predictive severity of COVID-19

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Abstract

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  1. SciScore for 10.1101/2020.05.01.072942: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Pakistani FASTA sequences were converted to FastQ format using FASTA-to-Tabular-to-FASTQ tools (Galaxy Version
    Galaxy
    suggested: (Galaxy, RRID:SCR_006281)
    1.1.0) [11] and then mapped against reference genome using BWA MEM v 0.7.17.1 [12]
    BWA
    suggested: (BWA, RRID:SCR_010910)
    Mapped reads were coordinate sorted using SortSam feature and duplicate sequences were marked using MarkDuplicate feature of Picard tool.
    Picard
    suggested: (Picard, RRID:SCR_006525)
    SnpSift Variant type [14] and SnpEff eff was used to annotate variants by custom building of reference sequence databases using SnpEff build v 4.3+T.galaxy4 (Figure. 1) [15]
    SnpEff
    suggested: (SnpEff, RRID:SCR_005191)

    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.
    • No funding statement was detected.
    • 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.