Phylogeny and Metadata Network Database for Epidemiologic Surveillance
G. L. Stott, L. Lyu, G. Veytsel, J. Kuo, R. Lewis, A. Brown, K. Fujimoto, J. Bahl
Abstract
AO_SCPLOWBSTRACTC_SCPLOWThe 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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