Understanding the contribution of genetics and the environment to T2D and other metabolic traits.

Using tools from statistical genetics and machine learning we are interested in elucidating the contribution of genetics and the environment to T2D and other metabolic traits.  New datasets such as the UK Biobank provide both detailed phenotypic, environmental and genetic data for approximately 500K individuals.  We plan to build upon tools developed by the statistical genetics community such GCTA and BOLT-REML to help quantify both the contribution of genetics and these environmental variables for our traits of interest

Chirag Lakhani received his PhD in mathematics from the North Carolina State University under the supervision of Amassa Fauntleroy. His dissertation research was in the area of algebraic geometry where he studied the deformations of a class of algebraic varieties that were of interest to string theorists studying mirror symmetry. After graduate school he spent time in industry where he helped implement data processing pipelines in the Hadoop/Spark environment as well as productionize a transaction classifier for credit card data. His current research interests can broadly described as trying to systematically understand the genetic and environmental contributions of disease.