Identification of COVID-19 prognostic markers and therapeutic targets through meta-analysis and validation of Omics data from nasopharyngeal samples

  1. Abhijith Biji
  2. Oyahida Khatun
  3. Shachee Swaraj
  4. Rohan Narayan
  5. Raju S. Rajmani
  6. Rahila Sardar
  7. Deepshikha Satish
  8. Simran Mehta
  9. Hima Bindhu
  10. Madhumol Jeevan
  11. Deepak K. Saini
  12. Amit Singh
  13. Dinesh Gupta
  14. Shashank Tripathi

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Abstract

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  1. Version published to 10.1016/j.ebiom.2021.103525
  2. Version published to 10.1101/2021.02.18.431825v2 on bioRxiv
  3. ScreenIT

    SciScore for 10.1101/2021.02.18.431825: (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
    Data collection and Processing: Transcriptomics and protein abundance data from COVID-19 patient’s naso- and oropharyngeal swab, bronchoalveolar lavage fluid (BALF), and other respiratory specimens were chosen from PubMed, BioRxiv, and MedRxiv using different combinations of keywords like “COVID-19, SARS-CoV-2
    PubMed
    suggested: (PubMed, RRID:SCR_004846)
    BioRxiv
    suggested: (bioRxiv, RRID:SCR_003933)
    The SARS-CoV-2 and COVID-19 collections in the EMBL-EBI PRIDE proteomics database (20) were retrieved and used without any modification.
    PRIDE
    suggested: (Pride-asap, RRID:SCR_012052)
    In the NCBI GEO database (21) the following combination of terms was used to collect relevant datasets: ((covid-19 OR SARS-COV-2
    NCBI GEO
    suggested: None
    Gene Ontology, Interferome Analysis, Cellular and tissue localization analysis: Enriched GO terms were obtained by express analysis on Metascape (24) and plotted using ggplot2 (25).
    Metascape
    suggested: (Metascape, RRID:SCR_016620)
    ggplot2
    suggested: (ggplot2, RRID:SCR_014601)
    The single-cell expression data of transcripts was also obtained from Human Protein Atlas ver20.0 (Available from http://www.proteinatlas.org/).
    http://www.proteinatlas.org/
    suggested: (HPA, RRID:SCR_006710)
    Cytoscape v3.8.0 (30) was used to construct the interaction network for virus-host protein-protein interaction.
    Cytoscape
    suggested: (Cytoscape, RRID:SCR_003032)
    STRING database within the Cytoscape store was used to query the proteins to elucidate the interactions between the proteins significantly altered during SARS-CoV-2 infection.
    STRING
    suggested: (STRING, RRID:SCR_005223)
    Statistical analysis: All statistical analyses and overlaps were performed in the R statistical environment version 4.0.3 via RStudio version 1.3.1093.
    RStudio
    suggested: (RStudio, RRID:SCR_000432)
    Heatmaps were generated using the R package ComplexHeatmap (31).
    ComplexHeatmap
    suggested: (ComplexHeatmap, RRID:SCR_017270)

    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.

  4. Version published to 10.1101/2021.02.18.431825v1 on bioRxiv