Data analytics and bioinformatics Core

核心D：数据分析和生物信息学核心 项目摘要 旨在了解表型、分子和功能差异的假设检验研究 在人类淋巴组织和外周粘膜组织中发现的抗原特异性B细胞亚群 这项建议将依赖于几个组学和其他数据丰富的方法和相应的分析来实现 他们的目标。为支持使用这些平台及其相关数据分析，我们建议提供统一的 以及数据分析和生物信息学核心D的综合数据和信息学服务。这个 核心将涵盖具体目标所反映的三个广泛领域：数据管理、数据处理管道、 以及协作性的下游分析。在具体目标1中，我们建议监督和实施系统和 管理捐赠者人口统计和样本处理元数据、结果数据集的流程(原始到 经过处理)，并用所有适当的联系分析来源。这将使计划受益，因为它创建了 可供所有项目和核心高效使用的基础设施，以及促进良好数据 管理实践反过来又支持再生性。在具体目标2中，我们建议实施 标准化工作流以涵盖本计划中使用的所有高吞吐量平台(通过一个或多个 项目)：RNA-seq、单细胞RNA-seq、B细胞受体测序(用于Sanger测序以及 曲目，通过下一代测序)和使用半自动的多参数流式细胞术 接近了。这将通过标准化项目间的主要数据处理而使方案受益，并将 促进结果的可比性。在具体目标3中，我们将提供协作下游生物信息学 为所有三个项目提供分析和统计支持。这将使本计划受益，因为它是一种资源 项目中的所有调查人员都可以访问，以使用数据分析来解决他们的假设，并通过 将这一职能集中起来，我们将把这一支持节约为 项目将会重叠。重要的是，这也将使创建记忆B细胞和血浆的分子图谱成为可能 跨组织细胞，整合项目的转录、表型和B细胞受体谱系数据 -我们将汇编这样一个数据集，以期将来纳入数据共享环境。至 开发这一核心，我们已经组建了一支强大的团队，拥有经验丰富的领导层和有才华的人员 在所涵盖的所有领域都表现出专业知识。将这三大领域合并为一个核心将使 提高效率，标准化流程，促进整个计划的科学协同。

Core D: Data Analytics and Bioinformatics Core Project Summary Hypothesis-testing studies designed to understand the phenotypic, molecular and functional differences between antigen-specific B cell subsets found in human lymphoid and peripheral mucosal tissues that are described in this proposal will rely on several ‘omics and other data-rich approaches and corresponding analyses to achieve their goals. To support use of these platforms and their associated data analyses, we propose to provide unified and integrated data and informatics services in Core D, the Data Analytics and Bioinformatics Core. The core will cover three broad areas as reflected by the Specific Aims: data management, data processing pipelines, and collaborative, downstream analysis. In Specific Aim 1, we propose to oversee and implement systems and processes to manage donor demographic and sample processing metadata, resulting data sets (raw through processed) and analysis provenance with all the appropriate linkages. This will benefit the Program by creating infrastructure that can be efficiently used by all the Projects and Cores as well as promoting good data stewardship practices which in turn, supports reproducibility. In Specific Aim 2, we propose to implement standardized workflows to cover all of the high-throughput platforms used in this Program (by one or more Projects): RNA-seq, single-cell RNA-seq, B cell receptor sequencing (for Sanger sequencing as well as for repertoires, by next-generation sequencing), and multi-parameter flow cytometry using semi-automated approaches. This will benefit the Program by standardizing primary data processing across the Projects and will promote comparability of results. In Specific Aim 3, we will provide collaborative downstream bioinformatics analytical and statistical support for all three Projects. This will benefit the Program by serving as a resource that all Investigators in the Projects can access for using data analyses to address their hypotheses, and by centralizing this function, we will economize this support as the analytical needs and methodologies of the Projects will overlap. Importantly, this will also enable creation of a molecular atlas of memory B cells and plasma cells across tissues, integrating transcriptomic, phenotypic and B cell receptor repertoire data from the Projects - we will assemble such a data set with an eye to future incorporation into a Data Commons environment. To develop this Core, we have assembled a strong team with experienced leadership and talented individuals with demonstrated expertise in all of the areas covered. Combining these three broad areas into a Core will maximize efficiency, standardize process and promote scientific synergy across the Program.