? Laboratory Core The laboratory core will serve the various goals of the Center and generate data for specific research proposals. The team requires a unique genomics facility for generating, processing, and analyzing the high-dimensional multi-omics data for addressing the science developed in the Center. We have developed a team of wet and dry lab scientists uniquely positioned to fulfill these goals, leveraging the extensive genomics expertise of PIs Carlos Bustamante and Michael Snyder. The personnel in these groups have expertise in the subjects required to complete the tasks in an accurate, timely fashion. First, we will generate genomic and ancestry data on each subject using an array designed by the Bustamante lab in collaboration with Illumina. We will use the Multi-Ethnic Genomewide Association (MEGA) array, a cost-effective genome-wide genotyping platform developed in collaboration between Illumina and the Bustamante lab and led by the Personnel outlined in this proposal. We will perform downstream genotype analysis and ancestry estimation (genomic, locus-specific and fine-scale sub-continental inference) for use in all downstream studies as a predictor of interest or to control for population stratification. Second, we will develop integrated omics profiles (e.g., genomics, transcriptomics, metabolomics, metagenomics) data on individuals outlined in the research proposal. Here, we describe the resources available to the PIs as well as the high-performance compute cluster that will serve as the hub for data processing, QC and preliminary analysis. We outline the ample equipment, resources, personnel and facilities for generating integrative personal omics profiles (iPOP) that we will use for analyses. Third, we will assist other groups in the Center with omics activities, and develop resources for sharing results with the community. We have extensive expertise in genomics, population genetics, and genetic epidemiology and will assist Center researchers in downstream analyses. The data will be processed and analyzed on a secure cluster, however we recognize the importance of disseminating our results. We will develop a web resource with relevant summary statistics where applicable to preserve anonymity. This repository can also serve for protocol and descriptive information about the study. Our team has extensive experience with NIH- funded initiatives and is committed to serving the goals of the NIMHD center, including collaborations at Stanford and with other investigators.

National Institute of Health (NIH)
National Institute on Minority Health and Health Disparities (NIMHD)
Specialized Center--Cooperative Agreements (U54)
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Special Emphasis Panel (ZMD1)
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Stanford University
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Basu, Sanjay; Raghavan, Sridharan; Wexler, Deborah J et al. (2018) Characteristics Associated With Decreased or Increased Mortality Risk From Glycemic Therapy Among Patients With Type 2 Diabetes and High Cardiovascular Risk: Machine Learning Analysis of the ACCORD Trial. Diabetes Care 41:604-612
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