Our broad goal is to better understand how genetic variation leads to phenotypic variation for complex traits including disease susceptibility and drug response. We develop systems approaches to complex trait prediction by building computational models that leverage and integrate similarity in genetic, transcriptomic or other omics-level data. Our current focus is understanding the degree of transferability of genetic association results and implicated genes across diverse populations; we hope to reduce the contribution of genomics to health disparities.

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