Data analytics and bioinformatics Core

数据分析和生物信息学核心

• 批准号: 10592413
• 负责人: Alexander Rosenberg
• 金额: $ 47.39万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10592413
• 关键词: Address; Antigens; Area; Atlases; B-Cell Antigen Receptor; B-Lymphocyte Subsets; B-Lymphocytes; B-cell receptor repertoire sequencing; Bioinformatics; Collaborations; Computer software; Consumption; Custom; Data; Data Analyses; Data Analytics; Data Commons; Data Set; Databases; Dideoxy Chain Termination DNA Sequencing; Ensure; Environment; Eye; FAIR principles; Flow Cytometry; Future; Goals; Human; Human Resources; Immunity; Immunologics; Immunology procedure; Individual; Informatics; Infrastructure; Institution; Leadership; Libraries; Lymphoid; Memory B-Lymphocyte; Metadata; Methodology; Methods; Molecular; Mucous Membrane; Nature; Organ; Peripheral; Phenotype; Plasma Cells; Play; Procedures; Process; Reporting; Reproducibility; Research; Research Design; Research Personnel; Resources; Role; Sampling; Sequence Analysis; Services; Software Framework; Standardization; System; Talents; Testing; Tissues; Visualization; Writing; complex data; computerized data processing; data access; data analysis pipeline; data infrastructure; data integration; data integrity; data management; data quality; data sharing; data standards; design; experience; information processing; member; next generation sequencing; programs; repository; single cell analysis; single-cell RNA sequencing; statistics; synergism; technology development; tissue processing; transcriptome; transcriptome sequencing; transcriptomics

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.

核心 D：数据分析和生物信息学核心 项目概要 假设检验研究旨在了解不同物种之间的表型、分子和功能差异 在人类淋巴和外周粘膜组织中发现的抗原特异性 B 细胞亚群，描述于 该提案将依赖于多种“组学”和其他数据丰富的方法以及相应的分析来实现 为了支持这些平台的使用及其相关的数据分析，我们建议提供统一的服务。 以及Core D（数据分析和生物信息学核心）中的集成数据和信息学服务。 核心将涵盖具体目标所反映的三大领域：数据管理、数据处理管道、 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（原始数据到 处理）并分析出处以及所有适当的联系，这将通过创建使该计划受益。 所有项目和核心都可以有效使用的基础设施以及推广良好的数据 在具体目标 2 中，我们建议实施管理实践，从而支持可重复性。 标准化工作流程，涵盖本计划中使用的所有高通量平台（由一个或多个 项目）：RNA-seq、单细胞 RNA-seq、B 细胞受体测序（用于 Sanger 测序以及 谱，通过下一代测序），以及使用半自动的多参数流式细胞术 这将通过标准化整个项目的主要数据处理而使该计划受益。 在具体目标 3 中，我们将提供协作的下游生物信息学。 对所有三个项目的分析和统计支持将作为一种资源使该计划受益。 项目中的所有研究人员都可以使用数据分析来解决他们的假设，并且通过 集中这一职能，我们将节省这种支持，作为分析需求和方法论 重要的是，这也将有助于创建记忆 B 细胞和血浆分子图谱。 跨组织的细胞，整合来自项目的转录组、表型和 B 细胞受体库数据 - 我们将组装这样一个数据集，着眼于未来纳入数据共享环境。 开发这个核心，我们组建了一支强大的团队，拥有经验丰富的领导层和才华横溢的个人 在所涵盖的所有领域展示的专业知识将这三个广泛的领域结合成一个核心将最大限度地发挥作用。 效率、标准化流程并促进整个计划的科学协同作用。