The Genome Aggregation Database (gnomAD)

基因组聚合数据库 (gnomAD)

• 批准号: 10089969
• 负责人: Mark Joseph Daly
• 金额: $ 218.7万
• 依托单位: BROAD INSTITUTE, INC.
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-02-08 至 2026-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10089969
• 关键词: All of Us Research Program; Architecture; Basic Science; Biological; ClinVar; Clinical; Collection; Communities; Computer software; DNA; Data; Data Aggregation; Data Set; Databases; Diagnostic; Disease; Ensure; Frequencies; Funding; Genes; Genetic Variation; Genome; Genomic medicine; Genomics; Genotype; Health; Human; Human Genetics; Individual; Infrastructure; Intuition; Joints; Lead; Link; Maintenance; Maps; Medical Genetics; Methods; Mutation; Natural Selections; Pathogenicity; Phenotype; Population; Production; Publications; Quality Control; Resolution; Resources; Sample Size; Sampling; Scientist; Single Nucleotide Polymorphism; Statistical Data Interpretation; Structure; Training; Untranslated RNA; Variant; Work; base; biobank; cloud based; cohort; cost efficient; data access; data sharing; exome; functional genomics; genetic variant; genome sequencing; genomic data; health care settings; improved; insertion/deletion mutation; large datasets; novel; phenotypic data; pressure; protein expression; rare variant; tool; virtual; web site

Project Summary The Genome Aggregation Database (gnomAD) is a ubiquitous resource for basic research and clinical interpretation. The world’s largest genetic variation resource, the gnomAD dataset is used in virtually all clinical genetic diagnostic pipelines worldwide, and the website has over 20 million page views to date. Here we outline a proposal that will expand the gnomAD resource to millions of samples across diverse global populations. Our proposal will scale variant-calling and quality control to match this sample size, integrate statistical tools and other genomic resources critical to clinical interpretation, and ensure that the data we aggregate will continue to be shared freely with the biomedical community. To accomplish this we will apply a highly computationally efficient strategy to call all classes of variation (including SNVs, small indels, and the mutational spectrum of structural variants) across millions of sequenced samples enriched for under- represented ancestry groups. We will deploy a cloud-based framework for the efficient storage and automated quality control of these very large and heterogeneous sequence data sets using the massively parallel Hail architecture. We will leverage the scale of gnomAD to provide increasingly high-resolution maps of the depletion of functional variation across regions of the genome (highlighting genome regions where natural selection constrains DNA change) and provide statistical frameworks for quantitatively assessing whether the population frequency of a variant is consistent with pathogenicity, linking this information with evidence from the ClinVar resource. We will continue to share all of this data as rapidly and openly as possible with the biomedical community, long before publication. We will support and expand functionality in our widely accessed data browser as well as create scalable and publicly accessible datasets that integrate our variation data with clinical and functional genomic annotations, accessible through API frameworks to empower novel applications of the datasets. We will also provide resources and training to improve the use of gnomAD resources by the clinical genetics and wider biomedical communities.

项目摘要 基因组聚集数据库（GNOMAD）是基础研究和临床的普遍资源 解释。世界上最大的遗传变异资源，GNOMAD数据集用于几乎所有临床 迄今为止，全球遗传诊断管道和该网站的页面浏览量超过2000万。我们在这里 概述将扩大GNOMAD资源的建议 我们的建议将扩展变种和质量控制以匹配此样本量，集成 统计工具和其他对临床解释至关重要的基因组资源，并确保我们的数据 总体将继续与生物医学界自由分享。为此，我们将应用一个 高度计算上有效的策略来调用所有类别的变化（包括SNV，小型Indels和 结构变体的突变光谱）数百万的测序样品富含不足的样品 代表祖先。我们将部署一个基于云的框架，以进行有效的存储和自动化 使用大量平行的冰雹对这些非常大且异质序列数据集的质量控制 建筑学。我们将利用GNOMAD的规模来提供越来越高的高分辨率地图 基因组区域之间功能变化的耗竭（突出了自然的基因组区域 选择会限制DNA的变化），并提供统计框架，用于定量评估是否是否 变体的种群频率与致病性一致，将此信息与来自 Clinvar资源。我们将继续尽可能快速，公开地共享所有这些数据 生物医学界，早在出版之前。我们将支持和扩展我们广泛的功能 访问的数据浏览器以及创建可扩展且可公开访问的数据集以整合我们的变化 具有临床和功能基因组注释的数据，可以通过API框架访问以增强新颖的能力 数据集的应用。我们还将提供资源和培训以改善gnomad的使用 临床遗传学和更广泛的生物医学群落的资源。