Data Management and Analysis Core

抽象-数据管理和分析核心。 识别与人类免疫反应相关的生物学特征并预测 开发对疫苗接种的有效免疫反应是该U19联盟的首要目标。 本计划书中的数据管理和分析核心(DMAC)有两个角色来支持这一总体任务 进球。首先，核心将为U19研究产生的所有数据提供可靠的数据管理服务。 它将管理大量未经确认的数据，并及时将数据提交给国家卫生研究院 数据库。其次，DMAC将应用一套计算工具来分析来自人类样本的数据 血清、血浆或外周血单核细胞(PBMC)，以及之前和 在接种疫苗后创造关于有效疫苗介导免疫的生物学基础的新知识。 为了实现这些目标，我们召集了一支由计算生物学家和免疫学家组成的团队，他们具有深度 擅长生成和分析高度复杂的转录本丰度和代谢数据集 简档，谁将支持项目1、2和3实现以下目标： 目的1.为斯坦福HIPC生成的数据提供数据管理服务。DMAC将 提供符合HIPAA标准的高效数据存储、备份和传输，并具有足够的数据安全性和 主体身份的保护。它还将促进项目之间的数据共享，并通过 将数据提交到适当的公共存储库，如NIH、GEO和ImmPort。 目标2：为项目1、2和3提供生物信息学支持，以分析系统免疫学数据 在这些项目中产生的。DMAC将协助本提案中的项目提供各种统计和 生物信息学分析包括差异表达、途径、转录因子、相互作用网络和 根据需要进行其他统计分析。 目的3：从正交数据集中综合分析疫苗免疫的多组学特征， 以及类似研究的公开数据集。发展免疫的整体和系统层面的观点 对疫苗的反应需要(1)能够准确捕获不同 免疫系统各组成部分在疫苗接种反应期间的协调和(2)队列 代表在真实世界中观察到的异质性。在这一目标中，我们将满足这两个标准。

ABSTRACT – Data Management and Analysis Core. Identifying the biological features of the human immune response that correlate with and predict the development of an effective immune response to vaccination is an overarching goal of this U19 consortium. The Data Management and Analysis Core (DMAC) in this proposal has two roles to support this overarching goal. First, the core will provide reliable data management service for all the data generated by the U19 study. It will provide management of large amounts of de-identified data, along with timely data submission to NIH databases. Second, the DMAC will apply a suite of computational tools to analyze data from human samples of serum, plasma, or peripheral blood mononuclear cell (PBMC), and individual immune cells obtained before and after vaccination to create new knowledge about the biological basis for effective vaccine-mediated immunity. To achieve these goals, we have assembled a team of computational biologists and immunologists with deep expertise in the generation and analysis of highly complex datasets of transcript abundance and metabolic profiles, who will support Projects 1, 2, and 3 in the following aims: Aim 1. To provide data management service for the data generated by Stanford HIPC. The DMAC will provide efficient HIPAA-compliant data storage, backup, and transfer with adequate data security and the protection of subject identity. It will also facilitate data sharing between the Projects, and with public by submitting data to appropriate public repositories such as the NIH GEO and ImmPort. Aim 2: Provide bioinformatics support to Projects 1, 2 and 3 for analyzing systems immunology data generated in those projects. The DMAC will assist the Projects in this proposal with various statistical and bioinformatics analysis including differential expression, pathway, transcription factor, interaction network and other statistical analyses as needed. Aim 3: Integrative analysis of multiomics signatures of vaccine immunity from orthogonal data sets, and from public datasets of similar studies. Developing a holistic and system-level view of immune responses to vaccines requires (1) tools that can accurately capture interactions across the diverse components of the immune system as they coordinate during response to vaccination and (2) cohorts representative of the heterogeneity observed in the real world. We will satisfy both criteria in in this aim.