T-Cell Hyperactivation and Paralysis in Severe COVID-19 Infection Revealed by Single-Cell Analysis

  1. Bahire Kalfaoglu
  2. José Almeida-Santos
  3. Chanidapa Adele Tye
  4. Yorifumi Satou
  5. Masahiro Ono

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Abstract

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  1. Version published to 10.3389/fimmu.2020.589380
  2. ScreenIT

    SciScore for 10.1101/2020.05.26.115923: (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
    In silico sorting of CD4 T-cells: We used h5 files of the scRNA-seq dataset (GSE14592616) which were aligned to the human genome (GRCh38) using Cell Ranger, by importing them into the CRAN package Seurat 3.0.57 Single cells with high mitochondrial gene expression (higher than 5%) were excluded from further analyses.
    Seurat
    suggested: (SEURAT, RRID:SCR_007322)
    Pathway analysis: The enrichment of biological pathways in the gene lists was tested by the Bioconductor package clusterProfiler,58 using the Reactome database through the Bioconductor package ReactomePA, and pathways with false discovery rate < 0.01 and q-value < 0.1 were considered significant.
    Reactome
    suggested: (Reactome, RRID:SCR_003485)
    Pseudotime analysis: Trajectories were identified using the Bioconductor package slingshot, assuming that the cluster that show the highest expression of IL7R and CCR7 is the origin.
    Bioconductor
    suggested: (Bioconductor, RRID:SCR_006442)
    The CRAN package ggplot2 was used to apply a generalised additive model of the CRAN package gam to each gene expression data.
    CRAN
    suggested: (CRAN, RRID:SCR_003005)
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)

    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.

  3. Version published to 10.1101/2020.05.26.115923v2 on bioRxiv
  4. Version published to 10.1101/2020.05.26.115923v1 on bioRxiv