Computational resources for genomic interpretation of type 2 diabetes

描述（由申请人提供）：我们建议创建用于基因组分析的新基础设施和方法，并将其应用于2型糖尿病（T2 D）的大型复杂数据集，这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。该计划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，以协调复杂疾病研究中确定的异质基因组数据集，如来自50，000多人的DNA测序数据所示;（2）我们将设计统计框架，以识别T2 D中的功能突变并分析其生物学后果，利用遗传变异，转录和表观遗传学的现有数据和资源;最后（3）我们将通过创建具有自动分析管道和直观数据探索功能的用户友好门户网站，使基因组数据的访问民主化。我们构建的软件、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T2 D生物学知识和治疗见解的障碍。

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.