In silico analysis of mutant epitopes in new SARS-CoV-2 lineages suggest global enhanced CD8+ T cell reactivity and also signs of immune response escape

  1. Marco Antônio M. Pretti
  2. Rômulo G. Galvani
  3. Nicole M. Scherer
  4. Alessandro S. Farias
  5. Mariana Boroni

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  1. Version published to 10.1016/j.meegid.2022.105236
  2. Version published to 10.1101/2021.03.09.434584v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.03.09.434584: (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
    Peptide antigenicity was predicted to all supported HLA alleles among the 297 using PRIME (27) with default parameters by providing a list of all binders predicted by netCTLpan (28) and filtering for TAP and Cle scores as previously described (26).
    PRIME
    suggested: (Prime, RRID:SCR_014887)
    Statistical and data analysis: The analysis was conducted on the R environment v4.0, and we used the R packages Biostrings v2.56 for peptide sequence manipulation and alignment, ggmsa v0.0.5 for visualization, and ggpubr v0.3.0 for statistical analysis.
    Biostrings
    suggested: (Biostrings, RRID:SCR_016949)

    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.

  4. Version published to 10.1101/2021.03.09.434584v1 on bioRxiv