Phylogeny and Metadata Network Database for Epidemiologic Surveillance

  1. Garrick Stott
  2. Leke Lyu
  3. Gabriella Veytsel
  4. Jacky Kuo
  5. Ryan Lewis
  6. Armand Brown
  7. Kayo Fujimoto
  8. Justin Bahl

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Abstract

The ongoing SARS-CoV-2 pandemic has highlighted the difficulty in integrating disparate data sources for epidemiologic surveillance. To address this challenge, we have created a graph database to integrate phylogenetic trees, associated metadata, and community surveillance data for phylodynamic inference. As an example use case, we divided 22,713 SARS-CoV-2 samples into 5 groups, generated maximum likelihood trees, and inferred a potential transmission network from a forest of minimum spanning trees built on patristic distances between samples. We then used Cytoscape to visualize the resultant graphs.

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    SciScore for 10.1101/2022.04.19.488067: (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
    Each Newick file is parsed by a python script which generates a CSV file of edges in the TAG.
    python
    suggested: None
    Another option is to use Gephi, but to use this tool, users need to start listening for data streams in Gephi before executing an APOC graph streaming query to push the data to the app.[6] Alternatively, users can connect using the Neo4j plugin for Cytoscape.[7] We found this option to be the most intuitive and sustainable for ad-hoc visualization since you can remotely connect to the graph using a read only user account on the database.
    Gephi
    suggested: (Gephi, RRID:SCR_004293)

    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.

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

    About SciScore

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  2. Version published to 10.1101/2022.04.19.488067v1 on bioRxiv