MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK.
Cancer Genetics, Norwich Medical School, University of East Anglia, Norwich, UK.
Bioinformatics. 2021 Jun 9;37(9):1304-1311. doi: 10.1093/bioinformatics/btaa961.
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.
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.
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.
Supplementary data are available at Bioinformatics online.
人类表型、风险因素、分子特征和治疗干预措施的数据资源丰富，为人群健康科学带来了新的机遇。这些机会伴随着对数据集成、管理和挖掘的需求不断增长，以提高研究效率、减少错误推断并确保可重复的研究。
我们开发了 EpiGraphDB（https://epigraphdb.org/），这是一个包含各种生物医学和流行病学关系的图数据库，以及一个分析平台，以支持在人类人群健康数据科学中使用这些关系。此外，我们还提出了三个案例研究，说明了该平台的价值。第一个案例使用 EpiGraphDB 评估潜在的多效关系，解决系统因果分析中的错误推断问题。在第二个案例研究中，我们说明了蛋白质-蛋白质相互作用数据如何为识别新的药物靶点提供机会。最后一个案例研究将使用孟德尔随机化进行因果推断与从生物医学文献中挖掘出的关系相结合，从不同来源“三角测量”证据。
EpiGraphDB 平台可在 https://epigraphdb.org 上公开获取。复制案例研究结果的代码可在 https://github.com/MRCIEU/epigraphdb 上以使用 API 的 Jupyter 笔记本和使用 R 包的 https://mrcieu.github.io/epigraphdb-r 获得。
补充数据可在生物信息学在线获得。
