Data Management and Analysis Core

数据管理与分析核心

• 批准号: 10594546
• 负责人: Aris Floratos
• 金额: $ 37.71万
• 依托单位: COLUMBIA UNIVERSITY HEALTH SCIENCES
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-01-01 至 2027-02-28
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10594546
• 关键词: Academic Medical Centers; Bioinformatics; Biological Assay; Biomedical Research; Calibration; Cell Separation; Cell physiology; Cells; Circulation; Clinical; Collaborations; Collection; Communities; Computational Biology; Computer software; Cytomegalovirus; Data; Data Aggregation; Data Analyses; Data Files; Data Set; Data Storage and Retrieval; Dedications; Dendritic Cells; Deposition; Dimensions; Directories; Documentation; Dropout; Ensure; Environment; Flow Cytometry; Funding; Funding Opportunities; Genome; Genomics; Goals; Herbert Irving Comprehensive Cancer Center; High Performance Computing; Human; Human Resources; Image; Immune; Immune response; Immunity; Immunology; Immunotherapy; In Situ; Individual; Infection; Infrastructure; Investigation; Lead; Macrophage; Maps; Memory; Methodology; Modeling; Molecular; Molecular Profiling; Names; Organ; Play; Population; Procedures; Process; Proteomics; Research; Research Personnel; Resource Sharing; Resources; Role; Secure; Services; Side; Standardization; Structure; System; T cell receptor repertoire sequencing; T-Lymphocyte; Tissues; Transcript; United States National Institutes of Health; Vaccination; Vaccines; Viral; Virus; Visualization; Work; biomedical informatics; cell type; computational pipelines; computing resources; dashboard; data curation; data dissemination; data exploration; data integration; data management; data quality; data sharing; data submission; design; experience; genetic signature; high dimensionality; informatics shared resource; innovation; multimodality; novel; operation; pathogenic virus; petabyte; programs; public repository; repository; response; single cell analysis; single-cell RNA sequencing; statistical and machine learning; symposium; terabyte; transcriptomics; user-friendly; web app

DATA MANAGEMENT AND ANALYSIS CORE: PROJECT SUMMARY The goal of the proposed program is to obtain in-depth profiles of how human innate and adaptive immune cells function in response to viral pathogens in tissues and to understand how the circulating responses relate to those in tissues. Using CMV as a model of infection, we aim to identify signatures for tissue-specific control of human immune responses for promoting in situ protective immunity in vaccines and immunotherapies. These efforts will generate thousands of data files representing the results of a diverse collection of assays. The Data Management and Analysis Core (DMAC) will be responsible for aggregating, annotating, organizing, analyzing, and disseminating this data. In that role the Core will serve as a centralized resource to support the shared data management and analysis needs of the Center, offering access to expertise and IT infrastructure that would be impractical to replicate in the context of individual projects. Specifically, the DMAC will: 1. Coordinate data curation, storage, and sharing: Data files will have to be accompanied by appropriate clinical and experimental annotations to support both the program’s own analysis needs as well as requirements for submission to public NIH repositories. The DMAC will coordinate this information in collaboration with the relevant projects and cores and will provide access to authenticated, network accessible storage infrastructure for securely storing and sharing files among investigators. 2. Provide data analysis expertise: The DMAC will provide projects with analytical expertise to guide the execution of computational investigations. Analyses will be standardized by leveraging (and adapting, as needed) validated computational pipelines developed to support the operation of well-established shared resources at the Columbia University Medical Center. The Core will further utilize and enhance novel methodologies for the analysis of single-cell data and for the systems-level delineation of the regulatory programs that preside over cell-state transitions in T cells, dendritic cells, and macrophages.3. Facilitate access to high performance computing infrastructure: The DMAC will provide investigators access to sophisticated IT infrastructure designed specifically to support the needs of biomedical research at the CUMC, including fast, network-accessible disk storage and a powerful computational cluster that is among the most advanced in the nation dedicated to biomedical research. 4. Coordinate data dissemination: A key goal of the HIPC program is timely dissemination of the data generated by all awardees to the public repositories. The process requires the compilation of comprehensive documentation to ensure that the data released are interpretable. The DMAC will be responsible for preparing all necessary data submissions, interfacing with repository personnel and ensuring that submission packages are fully annotated, per repository requirements.

数据管理和分析核心：项目摘要 该计划的目标是深入了解人类先天和适应性免疫如何 细胞响应组织中的病毒病原体而发挥作用，并了解循环反应之间的关系 使用 CMV 作为感染模型，我们的目标是识别组织特异性控制的特征。 人类免疫反应促进疫苗和免疫疗法中的原位保护性免疫。 这些将生成数千个数据文件，代表各种分析集合的结果。 数据管理和分析核心（DMAC）将负责聚合、注释、组织、 核心将作为一个集中资源来分析和传播这些数据。 共享中心的数据管理和分析需求，提供专业知识和 IT 基础设施 具体来说，DMAC 将： 1. 协调数据管理、存储和共享：数据文件必须附有适当的临床资料 和实验注释，以支持程序自身的分析需求以及要求 DMAC 将与 NIH 公共存储库合作协调此信息。 相关项目和核心，并将提供对经过身份验证、网络可访问的存储基础设施的访问 用于在研究人员之间安全地存储和共享文件 2. 提供数据分析专业知识：DMAC 将提供数据分析专业知识。 为项目提供分析专业知识，以指导计算调查的执行。 通过利用（并根据需要调整）经过验证的计算管道来标准化 支持哥伦比亚大学医学中心完善的共享资源的运营。 Core 将进一步利用和增强用于分析单细胞数据和 系统级描述 T 细胞、树突状细胞中主持细胞状态转变的调节程序 细胞和巨噬细胞。3. 促进高性能计算基础设施的使用：DMAC 将 为调查人员提供专门为支持需求而设计的复杂 IT 基础设施的访问权限 CUMC 的生物医学研究，包括快速、可通过网络访问的磁盘存储和强大的 致力于生物医学研究的全国最先进的计算集群之一。 4. 协调数据传播：重债穷国计划的一个关键目标是及时传播数据 由所有获奖者生成到公共存储库的过程需要进行综合汇编。 DMAC 将负责准备文件，以确保发布的数据可解释。 所有必要的数据提交，与存储库人员联系并确保提交包 根据存储库要求进行了完整注释。