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 opportunities are paralleled by a growing need for data integration, curation and mining to increase research 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 support 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 replicating case study results is available at https://github.com/MRCIEU/epigraphdb as Jupyter notebooks using the API, and https://mrcieu.github.io/epigraphdb-r using the R package.
Contact yi6240.liu{at}bristol.ac.uk, ben.elsworth{at}bristol.ac.uk, Tom.Gaunt{at}bristol.ac.uk
Competing Interest Statement
Tom Gaunt and Gibran Hemani receive research funding from GlaxoSmithKline and Biogen. Valeriia Haberland has previously been supported by funding from GlaxoSmithKline.
Footnotes
4 Further details on the inhouse results by EpiGraphDB members are available from Appendix 2 in the supplementary materials.
5 Information and metrics are based on latest version of EpiGraphDB platform (version 0.3.0, 21 April 2020).
6 Details on the list of pleiotropic genes are reported in Supplementary Table 4.
8 Supplementary Table 5 reports the full list of identified proteins with druggability information.
