The LungMAP Data Coordination Center for Next Gen Systems Biology of Respiration

下一代呼吸生物学系统 LungMAP 数据协调中心

• 批准号: 9815844
• 负责人: Bruce J Aronow
• 金额: $ 120.63万
• 依托单位: CINCINNATI CHILDRENS HOSP MED CTR
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-23 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9815844
• 关键词: 3-Dimensional; Accountability; Adopted; Adult; Anatomy; Atlases; Awareness; BRAIN initiative; Benchmarking; Biological Assay; Cell Communication; Cells; Cellular Structures; Childhood; Clinical Data; Collaborations; Collection; Communication; Communities; Complex; Data; Data Analyses; Data Coordinating Center; Data Provenance; Data Science; Data Set; Deposition; Development; Dimensions; Disease; Engineering; Ensure; Environment; Fostering; Funding; Gap Junctions; Generations; Genomics; Goals; Human; Image; Image Analysis; Individual; Ingestion; Institutes; Knowledge; Laboratories; Leadership; Link; Lung; Lung diseases; Maps; Metadata; Methods; Modeling; Molecular; Molecular Profiling; Monitor; Morphology; Neonatal; Ontology; Operations Research; Organ; Pathogenesis; Patient Representative; Phase; Positioning Attribute; Process; Protocols documentation; Reproducibility of Results; Research; Research Personnel; Resolution; Resource Sharing; Respiration; Running; Science; Secure; Services; Specialist; Specific qualifier value; Standardization; Structural Models; Structure; Systems Biology; Technology; Time; Tissue imaging; United States National Institutes of Health; Validation; Variant; Work; application programming interface; base; body system; cell type; cloud storage; computerized data processing; data access; data format; data hub; data integration; data portal; data resource; data sharing; data visualization; experience; high resolution imaging; human tissue; improved; insight; interactive tool; interoperability; literacy; lung development; lung maturation; molecular imaging; multidimensional data; multidisciplinary; multiple omics; new technology; online resource; outreach; programs; repository; single-cell RNA sequencing; skills training; social; success; tool; web site; web-enabled

PROJECT SUMMARY The LungMAP 2 initiative will create detailed molecular maps of the neonatal, pediatric and early adult human lung to enable improved understanding of functionally and anatomically defined cell types. The Data Coordination Center (DCC) will serve as the nexus of LungMAP 2's collective knowledge and activities. The DCC is responsible for data collation, re-analysis, and integration; secondary annotation tracking; developing tools to facilitate collection, sharing and data dissemination; operating a web resource for data, expertise, and collaboration; and coordinating activities across the Research Centers (RCs) and Human Tissue Core. The DCC will also facilitate literacy for investigator use of developed tools and best practices for analysis, data provenance and metadata annotation, and engage the larger research community. To host the DCC, we have assembled a multidisciplinary team with data network leadership, along with leaders in single-cell genomics, image analysis, functional inference, and data re-utilization. The DCC leverages unique expertise at CCHMC, UCSC, and the Broad Institute to interoperate pulmonary-oriented single-cell and high-resolution imaging data with other atlas programs. We also include world-renowned pulmonary researchers into our leadership team to ensure the data and knowledge we provide to the research community has the greatest scientific impact. Collectively, we propose to accelerate the LungMAP scientific agenda by coordinating efforts across funded Centers, the NIH, and the pulmonary research community; cross-validate, annotate, deposit and link Consortium datasets and metadata that encompass molecular -omics, imaging, and associated structural models; and enable sharing of data, results, and models within LungMAP and the research community. The datasets and results derived from the RCs are expected to yield significant new insights into lung maturation, intra-donor variation and disease pathogenesis. To ensure the underlying data produced by the RCs is findable, accessible, interoperable and re-usable (FAIR), the DCC will work closely with the RCs to establish and share best practices, coordinate metadata annotation, ensure studies are sufficiently powered, assist with the deposition of harmonized data of high integrity to secure repositories, and provide data access and standardized analysis workflows. Through the continued development of structured ontologies and metadata frameworks, RC-derived datasets will be annotated and harmonized using emerging best practices. The DCC will support the ingestion and validation of data and analysis from new technologies as they emerge. We will support the generation of centralized, cloud-enabled data processing workflows that are compatible with external initiatives such as HubMAP, BRAIN, and the HCA. We expect that providing these functions in a web-enabled LungMAP Commons will promote interaction across many stakeholders. This will position the LungMAP DCC to become a hub for data sharing, data integration, collaboration and hypothesis generation for investigators studying lung development and disease.

项目概要 LungMAP 2 计划将创建新生儿、儿童和早期成人的详细分子图谱 肺，以便更好地了解功能和解剖学上定义的细胞类型。数据 协调中心 (DCC) 将作为 LungMAP 2 集体知识和活动的纽带。这 DCC负责数据整理、重新分析、整合；二次注释跟踪；发展 促进收集、共享和数据传播的工具；运营数据、专业知识和网络资源 合作;协调研究中心 (RC) 和人体组织核心的活动。这 DCC 还将促进研究者使用已开发工具和分析、数据最佳实践的能力 出处和元数据注释，并吸引更大的研究社区。为了主办 DCC，我们有 组建了一支具有数据网络领导力的多学科团队，以及单细胞基因组学领域的领导者， 图像分析、函数推理和数据再利用。 DCC 利用 CCHMC 的独特专业知识， UCSC 和布罗德研究所互操作面向肺部的单细胞和高分辨率成像数据 与其他 Atlas 程序。我们还将世界知名的肺部研究人员纳入我们的领导团队，以 确保我们向研究界提供的数据和知识具有最大的科学影响。 总的来说，我们建议通过协调各资助机构的努力来加速 LungMAP 科学议程 中心、NIH 和肺部研究界；交叉验证、注释、存放和链接 包含分子组学、成像和相关结构的联盟数据集和元数据 模型；并支持在 LungMAP 和研究界内共享数据、结果和模型。 来自 RC 的数据集和结果预计将为肺部带来重要的新见解 成熟、供体内部变异和疾病发病机制。确保底层数据产生 RC 是可查找、可访问、可互操作和可重用的 (FAIR)，DCC 将与 RC 密切合作，以 建立和分享最佳实践，协调元数据注释，确保研究有足够的动力， 协助将高度完整性的统一数据存储到安全存储库，并提供数据访问 以及标准化的分析工作流程。通过结构化本体的持续发展和 元数据框架、RC 派生的数据集将使用新兴的最佳实践进行注释和协调。 DCC 将支持新技术出现时的数据提取和验证以及分析。 我们将支持生成兼容的集中式、支持云的数据处理工作流程 与 HubMAP、BRAIN 和 HCA 等外部计划合作。我们希望在一个 支持网络的 LungMAP Commons 将促进许多利益相关者之间的互动。这将定位 LungMAP DCC 将成为数据共享、数据集成、协作和假设生成的中心 研究肺部发育和疾病的研究人员。