Integrated Exchange and Storage of Current- and Future-Generation Immunogenomic Data

当前和未来一代免疫基因组数据的集成交换和存储

• 批准号: 9888328
• 负责人: JILL Allison HOLLENBACH
• 金额: $ 37.74万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-03-01 至 2022-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9888328
• 关键词: 6p21; Address; Adopted; Alleles; Base Sequence; Basic Science; Biological Models; Bone Marrow; Chromosome 19; Chromosome 6; Clinical; Clinical Data; Clinical Research; Collection; Communities; Complex; Computer software; Consensus Sequence; Coupled; Coupling; Data; Data Analyses; Data Reporting; Data Set; Data Storage and Retrieval; Development; Disease; Docking; Exhibits; Fast Healthcare Interoperability Resources; Future; Future Generations; GB virus C; Gene Structure; Generations; Genes; Genetic; Genetic Polymorphism; Genetic Variation; Genomic Segment; Genotype; Goals; Gold; Guidelines; HLA Antigens; Haplotypes; Health; Healthcare Systems; Human; Human Chromosomes; Human Genome; Immunogenomics; Immunoglobulins; Individual; Killer Cells; Language; Medical; Medical Research; Methods; Modernization; Nomenclature; Organ Transplantation; Output; Patients; Play; Population; Population Genetics; Publications; Receptor Gene; Reporting; Reproducibility; Research; Resources; Rest; Role; Science; Services; Single Nucleotide Polymorphism; Software Tools; Solid; Standardization; Statistical Data Interpretation; Study models; System; Transplant-Related Disorder; Variant; Work; analytical tool; bench to bedside; clinical application; clinical practice; data analysis pipeline; data exchange; data format; data management; data pipeline; data standards; data tools; design; experience; genetic analysis; genetic association; genomic data; health disparity; human data; improved; next generation; open source; operation; portability; precision medicine; programs; receptor; skills; tool; web services

PROJECT SUMMARY/ABSTRACT The goal of the proposed work is to further develop and integrate our software for the analysis, collection, exchange and storage (ACES) of all current and future immunogenomic data. The Human Leukocyte Antigen (HLA) region on human chromosome 6p21 is the most medically important region of the human genome. In the most successful application of precision medicine to date, matching of HLA genotypes is required for bone marrow and solid organ transplantation. HLA molecules have functional interactions with Killer cell Immunoglobulin-like Receptor (KIR) molecules, also recognized to play critical roles in transplantation and disease. The extensive genetic variation of these immunogenomic loci in human populations also makes them model systems in health disparities research. However, because these immunogenomic data have been generated using a wide variety of methods and under different nomenclature systems, cross-study data compatibility has remained an important and debilitating limitation to the field. Recognizing the need to consolidate the data and standardize data analysis in such a broad field, we have developed our Push Immunogenomics to the Next Generation (PING) data-generation system, Toolkit for Immunogenomic Data Exchange and Storage (TIDES) data-management platform, and our Bridging ImmunoGenomic Data-Analysis Workflow Gaps (BIGDAWG) data-analysis pipeline for highly polymorphic genomic data. When coupled with our Genotype List Service, Histoimmunogenetic Markup Language and Minimum Information for Reporting Immunogenomic NGS Genotyping reporting data-exchange standard, our ACES systems will represent a significant advance toward the goal of completely integrated exchange and storage of immunogenomic data. To extend our work of the prior period, we will (1) further develop the TIDES platform as the hub that integrates these systems, services and standards, centralize consensus sequence as the primary data type in immunogenomic research and clinical practice, and develop a service for gene feature enumeration (GFE) that describes HLA and KIR polymorphism by acknowledging underlying gene structure. To facilitate analysis of these data for research and clinical applications, we will (2) extend our BIGDAWG pipeline to handle new data input formats, incorporate new analyses, and export new data formats. BIGDAWG will be adapted as TIDES' primary analysis partner, and will directly, seamlessly accept TIDES outputs. Our tools are designed to maximize the ongoing utility of immunogenomic data for clinical and basic research science. As leaders in the immunogenomics field, we are uniquely suited to address the critical unmet need for standardized, robust ACES of immunogenomic data. The capacity of the systems described here to take these complex, highly polymorphic and medically important data along a complete pipeline from data generation through high-level statistical analysis will be a significant milestone toward the goal of “bench to bedside” precision medicine.

项目概要/摘要 拟议工作的目标是进一步开发和集成我们的软件，用于分析、收集、 所有当前和未来的人类白细胞抗原免疫基因组数据的交换和存储（ACES）。 人类染色体 6p21 上的 (HLA) 区域是人类基因组中医学上最重要的区域。 迄今为止最成功的精准医疗应用，骨骼需要HLA基因型匹配 骨髓和实体移植器官中的 HLA 分子与杀伤细胞具有功能性相互作用。 免疫球蛋白样受体 (KIR) 分子也被认为在移植和移植中发挥关键作用 这些免疫基因组基因座在人群中的广泛遗传变异也使其成为疾病的致病因素。 然而，由于这些免疫基因组数据已被用于健康差异研究中的模型系统。 使用多种方法和不同命名系统生成的交叉研究数据 认识到需要，兼容性仍然是该领域的一个重要且令人衰弱的限制。 为了整合如此广泛的领域的数据并标准化数据分析，我们开发了我们的 Push 下一代免疫基因组学 (PING) 数据生成系统，免疫基因组数据工具包 交换和存储 (TIDES) 数据管理平台以及我们的桥接免疫基因组数据分析 与高度多态性基因组数据结合使用的工作流程差距 (BIGDAWG) 数据分析管道。 我们的基因型列表服务、组织免疫遗传学标记语言和最低报告信息 免疫基因组 NGS 基因分型报告数据交换标准，我们的 ACES 系统将代表 对于免疫基因组数据完全集成的交换和存储的目标具有重要意义。 为了扩展我们前期的工作，我们将（1）进一步开发 TIDES 平台作为集成 这些系统、服务和标准将共识序列集中作为主要数据类型 免疫基因组研究和临床实践，并开发基因特征枚举（GFE）服务 通过合理的潜在基因结构描述 HLA 和 KIR 多态性 以便于分析。 这些数据用于研究和临床应用，我们将 (2) 扩展我们的 BIGDAWG 管道来处理新数据 输入格式、合并新的分析以及导出新的数据格式将被改编为 TIDES。 主要分析合作伙伴，并将直接、无缝地接受 TIDES 输出。 最大限度地提高免疫基因组数据在临床和基础研究科学中的持续效用。 在免疫基因组学领域，我们独特地适合解决标准化、稳健的未满足的关键需求 免疫基因组数据的 ACES 此处描述的系统处理这些复杂的、高度的数据的能力。 从数据生成到高级的完整管道中的多态性和医学上重要的数据 统计分析将是实现“从实验室到临床”精准医学目标的一个重要里程碑。