Data Management & Analysis Core: IDEAL shapes vaccine response, susceptibility to respiratory infectious disease and asthma

项目摘要：理想数据管理核心(DMC) 被提议的早期生命免疫发展(理想)项目的首要目标是使用系统 生物学描述儿童免疫轨迹，以确定关键临床结果的内型，如 如疫苗反应性、呼吸道感染和哮喘。为了支持这一努力，数据管理 核心(DMC)将建立和维护基于云的发现环境，包括数据存储和 用于执行临床数据的综合系统分析、实验室样本管理和高级 量纲分析结果。DMC将促进理想项目和核心之间的合作 包括数据共享、提交到公共储存库以及与外部研究社区的接触。 DMC的广泛目标是可靠的数据捕获和保留、持续质量保证(QA)以及 综合分析的访问/计算资源。我们通过三个具体目标来阐明这些目标， 包括建立用于数据捕获、管理和分析的数字基础设施；严格的质量 控制(QC)和质量保证；以及用于分析的生物统计和生物信息学专业知识。 我们的数据管理架构是在改进机构能力的基础上设计的，以实现可靠 基于云的临床数据管理、实验分析QC/QA和分析支持。我们一直在努力 与BCH研究计算部密切合作，为理想的合作者实施一个系统，该系统将 将安全性和可靠性与可访问性和最先进的计算工具和资源相结合。我们的 与更传统的基于服务器的体系结构相比，该方法提供了许多优势，其中最重要的是 用于综合分析和科学发现的卓有成效的协作计算环境。 任何这种范围和规模的科学努力都需要强大的数据管理计划、基础设施和 行动。事实上，如果没有链接这些数据的环境，就不可能有实际的数据集成 站台。DMC的综合功能是利用理想项目的独特优势所必需的 和核心转化为科学协同效应。我们希望我们的集成发现环境将增强科学 价值和生产力的整体理想研究。DMC将使我们能够发现内型特定的 分子和通路，可作为预测临床结果的预后和/或可操作的生物标记物 和/或代表将理想转向健康的干预措施的目标。

PROJECT SUMMARY: IDEAL Data Management Core (DMC) The overarching goal of the proposed immune development in early life (IDEAL) project is to employ systems biology to characterize childhood immune trajectories in order to define endotypes of key clinical outcomes such as vaccine responsiveness, respiratory infection and asthma. In support of this effort, the Data Management Core (DMC) will establish and maintain a cloud-based discovery environment, consisting of data storage and computational tools to perform integrative systems analyses of clinical data, lab sample management, and high dimensional assay results. The DMC will facilitate collaborations between the IDEAL Projects and Cores including data sharing, submission to public repositories, and engagement with the external research community. The broad goals of the DMC are reliable data capture and retention, ongoing quality assurance (QA), and access/computational resources for integrative analyses. We articulate these goals through three Specific Aims, including establishment of digital infrastructure for data capture, management, and analysis; rigorous quality control (QC) and QA; and biostatistical and bioinformatics expertise for analysis. Our data management architecture is designed on the basis of improved institutional capabilities for reliable cloud-based clinical data management, experimental assay QC/QA, and analytic support. We have worked closely with the BCH Research Computing Department to implement a system for IDEAL collaborators that will combine security and reliability with accessibility and state-of-the-art computational tools and resources. Our approach offers many advantages over more traditional server-based architecture, not the least of which is a fruitful collaborative computing environment for integrative analyses and scientific discovery. Any scientific endeavor of this scope and scale requires robust data management plans, infrastructure, and operations. Indeed, there can be no practical integration of data without an environment to link these data across platforms. The DMC’s integrative function is necessary to leverage the distinct strengths of the IDEAL projects and cores into scientific synergies. We expect our integrated discovery environment will augment the scientific value and productivity of the overall IDEAL study. The DMC will enable us to discover endotype-specific molecules and pathways, that may serve as prognostic and/or actionable biomarkers to predict clinical outcomes and/or that represent targets for interventions that redirect IDEAL towards health.