An interactive single cell web portal identifies gene and cell networks in COVID-19 host responses

  1. Kang Jin
  2. Eric E. Bardes
  3. Alexis Mitelpunkt
  4. Jake Y. Wang
  5. Surbhi Bhatnagar
  6. Soma Sengupta
  7. Daniel Pomeranz Krummel
  8. Marc E. Rothenberg
  9. Bruce J. Aronow

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Abstract

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  1. Version published to 10.1016/j.isci.2021.103115
  2. Version published to 10.1101/2021.06.07.447287v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.06.07.447287: (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
    Generation of ToppCell gene modules: ToppCell (https://toppcell.cchmc.org/) was designed to parallelly analyze transcriptional profiles of single-cell datasets by organizing differential expressed gene modules in a customized hierarchical order.
    ToppCell
    suggested: None
    All gene modules in our study were curated in COVID-19 Atlas (https://toppcell.cchmc.org/biosystems/go/index3/COVID-19_Atlas) and ImmuneMap (https://toppcell.cchmc.org/biosystems/go/index3/ImmuneMap) on the ToppCell website.
    ImmuneMap
    suggested: None
    Genes in each gene module were sent to ToppGene platform as input for enrichment in different domains.
    ToppGene
    suggested: ( ToppGene Suite , RRID:SCR_005726)
    Generation of Functional Association Heatmap using ToppCluster: Genes in gene modules of selected cell types or sub-clusters were sent to ToppCluster (https://toppcluster.cchmc.org/).
    ToppCluster
    suggested: ( ToppCluster , RRID:SCR_001503)
    Morpheus was used for visualization of the heatmap (https://software.broadinstitute.org/morpheus/).
    https://software.broadinstitute.org/morpheus/
    suggested: (Morpheus by Broad Institute, RRID:SCR_017386)
    Public single-cell RNA-seq datasets of PBMC in COVID-19 patients are available on NCBI Gene Expression Omnibus and European Genome-phenome Archive, including GSE150728, GSE155673, GSE150861, GSE149689 and EGAS00001004571 (or FastGenomics).
    Gene Expression Omnibus
    suggested: (Gene Expression Omnibus (GEO, RRID:SCR_005012)

    Results from OddPub: Thank you for sharing your code and data.

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    There are several limitations in our study. Different studies used various standards of COVID-19 severity definition. To generalize conclusions, we simplified disease conditions into several universal groups. Prospectively, a standardized definition of disease stages will assist to the accuracy of future studies. Additionally, the timing of sample collection was not considered as a variable in this study, rather disease stages were used to consolidate data across samples. We lack follow-up data of patients with sequela, which will be helpful for understanding the long-haul effects of the disease.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.06.07.447287v1 on bioRxiv