Liu, Yi, Elsworth, Benjamin, Erola, Pau, Haberland, Valeriia, Hemani, Gibran, Lyon, Matt, Zheng, Jie, Lloyd, Oliver, Vabistsevits, Marina and Gaunt, Tom R. (2020) EpiGraphDB: a database and data mining platform for health data science. Bioinformatics. ISSN 1367-4803

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Abstract

Motivation: The wealth of data resources on human phenotypes, risk factors, molecular traits and therapeutic interventions presents new opportunities for population health sciences. These oppor-tunities are paralleled by a growing need for data integration, curation and mining to increase re-search efficiency, reduce mis-inference and ensure reproducible research. Results: We developed EpiGraphDB (https://epigraphdb.org/), a graph database containing an array of different biomedical and epidemiological relationships and an analytical platform to sup-port their use in human population health data science. In addition, we present three case studies that illustrate the value of this platform. The first uses EpiGraphDB to evaluate potential pleiotropic relationships, addressing mis-inference in systematic causal analysis. In the second case study, we illustrate how protein-protein interaction data offer opportunities to identify new drug targets. The final case study integrates causal inference using Mendelian randomization with relationships mined from the biomedical literature to “triangulate” evidence from different sources. Availability: The EpiGraphDB platform is openly available at https://epigraphdb.org. Code for repli-cating case study results is available at https://github.com/MRCIEU/epigraphdb as Jupyter note-books using the API, and https://mrcieu.github.io/epigraphdb-r using the R package. Contact: yi6240.liu@bristol.ac.uk, ben.elsworth@bristol.ac.uk, Tom.Gaunt@bristol.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.

Item Type:	Article
Faculty \ School:	Faculty of Medicine and Health Sciences > Norwich Medical School
Related URLs:	https://www.biorxiv.org/content/10.1101/...
Depositing User:	LivePure Connector
Date Deposited:	03 Nov 2020 01:06
Last Modified:	29 Dec 2020 00:53
URI:	https://ueaeprints.uea.ac.uk/id/eprint/77497
DOI:	10.1093/bioinformatics/btaa961

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