Data Management and Analysis Core

数据管理与分析核心

• 批准号: 10419873
• 负责人: Aris Floratos
• 金额: $ 29.29万
• 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/10419873
• 关键词: Academic Medical Centers; Bioinformatics; Biological Assay; Biomedical Research; Blood Circulation; Calibration; Cell physiology; Cells; Cellular Indexing of Transcriptomes and Epitopes by Sequencing; Clinical; Collaborations; Collection; Communities; Computational Biology; Computer software; Cytomegalovirus; Data; Data Analyses; Data Files; Data Set; Data Storage and Retrieval; Dendritic Cells; Deposition; 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; Information Systems; Infrastructure; Investigation; Lead; Maps; Memory; Methodology; Modeling; Molecular; Molecular Profiling; Names; Organ; Play; Population; Procedures; Process; Proteomics; Research; Research Personnel; Resource Sharing; Resources; Role; Secure; Services; Standardization; Structure; System; T cell receptor repertoire sequencing; T-Lymphocyte; Time; Tissues; Transcript; United States National Institutes of Health; Vaccination; Vaccines; Viral; Virus; Visualization; Work; base; biomedical informatics; cell type; computational pipelines; computing resources; dashboard; data curation; data dissemination; data exploration; data infrastructure; data integration; data management; data quality; data sharing; data submission; design; experience; genetic signature; high dimensionality; informatics shared resource; innovation; macrophage; 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 拟议程序的目标是获得人类先天和适应性免疫的深入概况 细胞对组织中病毒病原体的响应起作用，并了解循环反应如何相关 到组织中的人。使用CMV作为感染模型，我们旨在确定组织特异性控制的特征 用于促进原位保护疫苗和免疫疗法的免疫史的人类免疫复杂。 这些努力将产生数千个数据文件，代表潜水员收集的测定结果。 数据管理和分析核心（DMAC）将负责汇总，注释，组织， 分析并传播此数据。在该角色中，核心将作为支持 中心的共享数据管理和分析需求，提供了获得专业知识和IT基础架构的访问权限 在单个项目的背景下复制是不切实际的。具体来说，DMAC将：1。 协调数据策划，存储和共享：必须通过适当的临床来完成数据文件 和实验注释以支持该计划自己的分析需求以及对 提交给公共NIH存储库。 DMAC将与该信息协调此信息 相关项目和核心，将提供对经过身份验证的网络访问存储基础结构的访问权限 用于在调查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 为项目提供分析专业知识，以指导计算调查的执行。分析将 通过利用（并根据需要适应）确定的计算管道已建立标准化 支持哥伦比亚大学医学中心建立良好共享资源的运作。这 核心将进一步利用并增强新方法，用于分析单细胞数据和 系统级划定主持T细胞中细胞状态过渡的监管程序，树突状介绍 细胞和巨噬细胞3。促进获得高性能计算基础架构的访问：DMAC将 为调查人员提供专门旨在支持需​​求的复杂IT基础架构的访问 CUMC的生物医学研究，包括快速，网络访问的磁盘存储和功能强大 计算群集是全国最先进的群集，致力于生物医学研究。 4。协调数据传播：HIPC程序的关键目标是及时传播数据 由所有获奖者生成的公共存储库。该过程需要综合汇编 文档以确保发布的数据是可解释的。 DMAC将负责准备 所有必要的数据提交，与存储库人员接口并确保提交包裹 根据存储库要求完全注释。