Computational resources for genomic interpretation of type 2 diabetes

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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.