Data Management and Analysis Core

数据管理和分析核心(DSC)将负责执行和支持 对省略中产生的多维和主题元数据集进行生物统计分析和管理- 艾滋病毒项目。将在加州大学旧金山分校数据库平台上创建和维护一个定制项目，以存储、 保护、管理并使所有原始和处理过的生物数据以及未识别的临床数据可供访问 与研究计划有关。我们将与每个项目团队交互以获取数据并提供 为每个人提供统计和生物信息支持。我们还将进行多模态综合分析， 包括跨物种分析，以更好地回答每个项目内部和跨项目的问题 了解疫苗方案和代谢条件如何影响T细胞对病毒的应答 治疗性疫苗接种的结果。 我们将以以下具体目标实现这些目标： 目标1：使用加州大学旧金山分校开发和维护一个集中的数据管理和共享系统 数据库。 -我们将利用UCSF数据库(UCDL)来促进接收、管理和安全存储 生成的各种高维数据类型和元数据或未识别的临床数据 这些项目。 -我们将根据存储原始和已处理数据和注释的通道应用共享数据架构。 -UCDL支持项目和核心团队的所有成员以及 用作将所有原始和已处理的数据和元数据传输到ImmPort和 其他公共数据库。 目标2：为测试与以下相关的项目假设提供统计分析和生物信息支持 疫苗方案、T细胞特征、代谢组学和反弹动力学。 -我们将采用标准化和定制的方法来协调数据集，供所有团队使用。 -我们将与每个项目和核心团队合作，执行所描述的分析，包括 降维、差异分析和与结果的关联。 目标3：整合多模式数据以开发联合免疫和代谢影响的模型 ATI患者的疫苗反应和病毒血症的控制。 -我们将利用这些项目的互补性和最先进的综合分析 技术，包括跨物种分析，以构建与多模式因素有关的模型 纵向免疫和病毒学结果。 -我们将讨论总体组成部分中描述的衔接假设。

The Data Management and Analysis Core (DSC) will be responsible for performing and supporting biostatistical analyses and management of multidimensional and subject metadata sets generated in the OmiT- HIV program. A custom project will be created and maintained on the UCSF Data Library platform to store, secure, curate, and make accessible all raw and processed biological data and de-identified clinical data associated with the research program. We will interface with each project team for data ingestion and provide statistical and bioinformatic support to each. We will additionally perform multi-modal integrative analyses, including cross-species analysis, to answer questions within and across each project toward better understanding how vaccine regimens and metabolic conditions influence T-cell responses to and virologic outcomes of therapeutic vaccination. We will accomplish these goals with the following specific aims: Aim 1: Develop and maintain a centralized system of data management and sharing using the UCSF Data Library. - We will leverage the UCSF Data Library (UCDL) to facilitate the ingestion, curation, and secure storage of the diverse high-dimensional data types and metadata or de-identified clinical data generated across the projects. - We will apply shared data schemas per modality that store raw and processed data and annotations. - The UCDL supports web-based data sharing across all members of project and core teams as well as serves as a staging area for the transfer of all raw and processed data and metadata to ImmPort and other public databases. Aim 2: Provide statistical analysis and bioinformatic support for testing project hypotheses relevant to vaccine regimens, T-cell features, metabolomics, and rebound kinetics. - We will apply standardized and custom approaches to harmonize datasets for use by all teams. - We will work collaboratively with each project and core team to perform described analyses including dimensionality reduction, differential analysis, and association with outcomes. Aim 3: Integrate multi-modal data to develop a model of joint immune and metabolomic influence over vaccine responses and control over viremia in ATI. - We will leverage the complementary nature of these projects and state-of-the-art integrative analysis techniques, including cross-species analysis, to construct models relating multi-modal factors to longitudinal immune and virologic outcomes. - We will address the Bridging Hypotheses described in the Overall component.