National Institute of Diabetes and Digestive and Kidney Diseases ATLAS (D2K-ATLAS) Center as an accessible, comprehensive data portfolio for renal and genitourinary development and disease

项目摘要 技术进步使得能够产生大量高度专业化和复杂的 分子数据（例如，单细胞转录组学和多重成像）来研究器官发育、健康和 疾病状态和生物性别之间的差异，在前所未有的规模和细胞分辨率。这 复杂性在这些数据集的组织和管理以及应用方面带来了挑战。 计算方法需要提供易于访问的高级分析和可视化工具，并 利用我们的领域知识，为研究社区提供入口点，以重用数据并提出新的 关于人类健康的问题，并产生新的假设。我们的总体目标是建立联系 在GUDMAP、RBK、KPMP、HuBMAP（每个 我们的团队中有财团的代表），因此具有不同经验水平的研究人员可以找到相关数据， 了解模型系统之间的联系，并通过使用提供的分析工具获得新的见解。我们的愿景 是建立国家糖尿病、消化和肾脏疾病研究所ATLAS（D2 K-ATLAS）作为 肾脏和泌尿生殖系统发育和疾病的全面数据组合。数据驱动 参考数据使得能够使用跨各种参数的高级计算研究进行比较分析， 包括性别、年龄、物种以及健康和疾病环境。提供分析和可视化工具将有助于 知识转让和扩大所提交数据的可用性。目标1）建立一个全面、综合和 联邦航空研究局基于云的数据管理系统，集成了GUDMAP和RBK数据，多物种本体， 促进多研究、多模态和多联盟数据的交叉链接，以及数据的网络应用 探索和访问。目标2）实现基于网络的工具，数据集成，人类和鼠标参考图谱， 和数据可视化，使研究人员能够与质量控制，策划的数据进行交互， 通过开发流程、工具和访问控制策略进行数据收集、管理、发布， 图像注释、质量控制、分析和可视化。目标3）管理、协调、协作， 我们的D2 K-ATLAS中心将促进，沟通和合作， NIDDK、GUDMAP/RBK指导委员会和联合体管理委员会以及调查人员， 实现联盟的目标，包括教育、推广和机会池奖励的管理。这 这一工作将非常重要，因为它提供了精心策划的参考数据集，建立了一致的数据管理 标准，并创建链接到关键的共识解剖学/细胞类型本体。 生物标志物。计算分析既是一种进步，也是一个障碍，需要生物信息学专业知识。 我们的创新提案通过提供分析层和可视化工具， 用户的各种计算专业知识，并创建强大的，数据驱动的参考标准的研究 小鼠和人类肾脏和泌尿生殖系统发育和疾病的社区。

PROJECT SUMMARY Technical advancements have enabled the generation of large amounts of highly specialized and complex molecular data (e.g., single-cell transcriptomics and multiplex imaging) to study organ development, healthy and disease states, and differences between biological sexes at unprecedented scale and cellular resolution. This complexity introduces challenges in the organization and curation of these datasets and in applying computational methods. There is a need to provide accessible advanced analysis and visualization tools, and to utilize our domain knowledge to enable entry points for the research community to reuse data and ask new questions about human health and generate new hypotheses. Our overall objective is to create connections between molecular data of kidney and lower urinary tract present in GUDMAP, RBK, KPMP, HuBMAP (each consortium is represented on our team), so researchers with varying levels of experience can find relevant data, understand connections across model systems, and gain new insight by using provided analysis tools. Our vision is to establish the National Institute of Diabetes and Digestive and Kidney Diseases ATLAS (D2K-ATLAS) as a comprehensive data portfolio for renal and genitourinary development and disease. Curated data-driven reference data enables comparative analysis using advanced computational studies across various parameters, including sex, age, species, and healthy and disease settings. Providing analysis and visualization tools will aid knowledge transfer and broaden the usability of submitted data. Aim 1) Create a comprehensive, integrated, and F.A.I.R. cloud-based data management system integrating GUDMAP and RBK data, multi-species ontologies to facilitate cross-linkage of multi-study, multi-modality, and multi-consortia data, and web applications for data exploration and access. Aim 2) Implement web-based tools, data integration, human and mouse reference atlas, and data visualizations that enable researchers to interact with quality controlled, curated data for advanced analysis by developing processes, tools, and an access control policy for data collection, curation, publication, image annotation, quality control, analysis, and visualization. Aim 3) Administration, coordination, collaboration, dissemination, and outreach by our D2K-ATLAS Center, which will facilitate, communicate, and collaborate with the NIDDK, the GUDMAP/RBK Steering Committees and Consortium Management Boards, and investigators to achieve consortia goals, including education, outreach, and management of the Opportunity Pool awards. This effort will be significant because it provides curated reference datasets, establishes aligned data stewardship standards across the represented consortia and creates a consensus anatomical/cell type ontology linked to key biomarkers. Computational analysis is both an advancement and a barrier, requiring bioinformatics expertise. Our innovative proposal lowers these analysis barriers by providing layers of analysis and visualization tools for users of varied computational expertise and creates robust, data-driven reference standards for the research communities of mouse and human renal and genitourinary development and disease.