Center for Genome Interpretation

基因组解释中心

• 批准号: 9351497
• 负责人: Daniel G MacArthur
• 金额: $ 201.4万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-30 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9351497
• 关键词: Big Data; Big Data to Knowledge; Biological; Biological Process; Biology; Biomedical Research; Cardiovascular system; Catalogs; Clinical Data; Communication; Communities; Complex; Computer software; Computing Methodologies; DNA sequencing; Data; Data Aggregation; Data Science; Data Set; Development; Diabetes Mellitus; Diagnosis; Discipline; Disease; Education; Elements; Ensure; Environmental Risk Factor; Epigenetic Process; Genes; Genetic; Genetic Transcription; Genetic Variation; Genome; Genomics; Genotype-Tissue Expression Project; Goals; Home environment; Human; Human Biology; Human Genome; Individual; Inflammatory; Intuition; Joints; Knowledge; Leadership; Location; Medical; Medicine; Mental disorders; Methods; Mission; Modeling; Modification; Molecular; Morbidity - disease rate; Mutation; NCI Scholars Program; Non-Insulin-Dependent Diabetes Mellitus; Pathway interactions; Patients; Phenotype; Population; Prevention; Property; RNA; Research Infrastructure; Research Personnel; Resources; Science; Scientist; Site; Software Engineering; Software Tools; Statistical Models; Structure; Technology; Testing; Therapeutic; Training; Translating; Translations; Travel; Untranslated RNA; Ursidae Family; Variant; Work; analytical method; analytical tool; cell type; clinical phenotype; collaborative approach; comparative; computer science; cost; data resource; data visualization; design; disorder risk; effective therapy; epigenetic regulation; genetic association; genetic variant; genome sequencing; genomic data; human disease; improved; innovation; insight; interoperability; laboratory experiment; massive open online courses; mortality; multidisciplinary; new technology; novel strategies; petabyte; public health relevance; success; tool; user-friendly; web portal

DESCRIPTION (provided by applicant): We propose to create new infrastructure and methods for genomic analysis and apply these to large, complex datasets for type 2 diabetes (T2D), a leading cause of morbidity and mortality that is driven by diverse genetic and environmental factors. This proposal has three primary scientific goals. (1) We will develop infrastructure and analytical tools to harmonize heterogeneous genomic datasets ascertained for the study of complex disease, as demonstrated on DNA sequencing data from over 50,000 individuals; (2) we will design statistical frameworks to identify functional mutations in T2D and analyze their biological consequences, taking advantage of existing data and resources on genetic variation, transcription, and epigenetics; and finally (3) we will democratize access to genomic data by creating user-friendly portals with automated analytical pipelines and intuitive features for data exploration. The software, methods, and web portals we build will help overcome the barriers that currently inhibit the translation of genomic data into biological knowledge and therapeutic insights for T2D.

描述(由申请人提供)：我们建议创建新的基因组分析基础设施和方法，并将其应用于2型糖尿病(T2D)的大型复杂数据集，T2D是由多种遗传和环境因素驱动的发病率和死亡率的主要原因。这项提议有三个主要的科学目标。(1)我们将开发基础设施和分析工具，以协调为研究复杂疾病而确定的不同类型的基因组数据集，如超过50,000人的DNA测序数据所示；(2)我们将设计统计框架，以识别T2D功能突变并分析其生物学后果，利用遗传变异、转录和表观遗传学方面的现有数据和资源；以及(3)我们将通过创建具有自动化分析管道和数据探索直观功能的用户友好门户网站，实现基因组数据访问的民主化。我们建立的软件、方法和门户网站将有助于克服目前阻碍基因组数据转化为T2D的生物学知识和治疗见解的障碍。