The Monarch Initiative: Linking diseases to model organism resources

摘要 生物医学研究人员需要识别新的疾病基因并了解疾病机制；临床医生 需要诊断疾病和优化治疗。对糖尿病的遗传基础有了更深入的了解 疾病有助于实现这两个目标。君主倡议通过整合支离破碎的 数据景观成为世界上最全面的开放的基因型-表型数据集合。我们的 知识图(KG)将跨越多个领域的临床、生物医学和基础科学研究数据链接在一起 支持各种生物体、身体系统和疾病的推理。君主 使用模型生物体数据执行罕见的操作，取得了明显的临床和翻译成功 疾病诊断和基因到疾病的发现，我们的资源已经成为全球标准。同相 II，我们将人类表型本体(HPO)集成到UMLS中；增强了我们的变体优先顺序 算法和Exomiser工具，应用于英国国家卫生服务体系(UK)的30,000名患者； 开发了Biolink模型/API；发布了新的本体(Mondo统一疾病本体、统一 表型本体论(UPheno)和环境条件与处理本体论(ECTO) 将我们KG中统一的数据源数量增加到34个；并对我们的门户网站进行了全面改造。我们将利用这一点 在第三阶段，为使Monch对各种用户和环境更直观而建立的基础如下： 使用新的可视化和工具增强君主门户。以用户需求为导向，迭代 用户测试和反馈，我们建议增强用户体验和门户功能，重点是我们的 致力于改进导航、可视化和查询。 评估、优化和增强疾病诊断、跨物种推理和 基因疾病的发现。我们将开发一个全面的、模块化的评估框架‘PhEval’，它将 使我们能够监控跨物种推理的诊断产量和性能，作为我们的本体和数据 曲线图不断演变。这将有助于基础科学研究人员和临床医生揭示跨物种机制 证据和评估潜在的精确疾病建模策略。 向广泛的翻译社区传播计算工具、数据、服务和教程。我们 将通过以下方式扩展对我们的KG的访问，使用户能够针对不同的域和用例处理KG 简化的下载、API、软件库、R包、Jupyter笔记本和Dockerated资源， 以及培训材料。这将更好地支持生物信息学家和其他研究人员利用我们的 Kg和表型数据在他们的分析。 帝王倡议旨在显著提高动物的利用率、可及性和价值 疾病诊断和发现的模式。

ABSTRACT Biomedical researchers need to identify novel disease genes and understand disease mechanisms; clinicians need to diagnose diseases and optimize treatments. An improved understanding of the genetic basis of disease helps achieve both goals. The Monarch Initiative makes this possible by integrating the fragmented data landscape into the most comprehensive open collection of genotype-phenotype data in the world. Our Knowledge Graph (KG) links together clinical, biomedical, and basic science research data spanning multiple organisms, and supports reasoning across a wide range of organisms, body systems, and diseases. Monarch has achieved demonstrable clinical and translational success using model organism data to perform rare disease diagnosis and gene-to-disease discovery, and our resources have become global standards. In Phase II, we integrated the Human Phenotype Ontology (HPO) into the UMLS; enhanced our variant prioritization algorithms and Exomiser tool, which was applied to 30,000 patients in the National Health Service (UK); developed the Biolink Model/API; released new ontologies (Mondo unified disease ontology, Unified Phenotype Ontology (uPheno), and the Environmental Conditions and Treatments Ontology (ECTO)), raised the number of harmonized data sources in our KG to 34; and overhauled our web Portal. We will leverage this foundation to make Monarch more intuitive for a diversity of users and contexts in phase III as follows: Augment the Monarch Portal with new visualizations and tools. Guided by user requirements, iterative user testing, and feedback, we propose to enhance the user experience and Portal functionality, focusing our work on improvements to Navigation, Visualization, and Query. Evaluate, optimize, and enhance algorithms for disease diagnostics, cross-species inference, and gene-disease discovery. We will develop a comprehensive, modular evaluation framework, ‘PhEval,’ that will allow us to monitor the diagnostic yield and performance of cross-species inference as our ontologies and data graphs evolve. This will assist basic science researchers and clinicians to reveal cross-species mechanistic evidence and evaluate potential precision disease modeling strategies. Disseminate computational tools, data, services, and tutorials to a broad translational community. We will expand access to our KG to enable users to process the KG for different domains and use cases, through simplified downloads, APIs, software libraries, R packages, Jupyter notebooks, and Dockerized resources, along with training materials. This will better support bioinformaticians and other researchers in leveraging our KG and phenotype data in their analyses. The Monarch Initiative aims to significantly improve the utilization, accessibility, and value of animal models for disease diagnosis and discovery.