Our groups develop and apply novel computational and statistical methods to address important questions in human genetics and healthcare. Previously we developed computationally efficient and statistically powerful prediction methods to predict the value of human traits in biobank (anthropometry, lipids, blood cells, cancers, cardiovascular diseases, psychiatric disorders and others) based on genetic information obtained from diverse populations. While continuing working in the field of genetic risk prediction, we are also interested in biological interpretation of GWAS, gene by environment analysis, integration of GWAS and single cell data, and other related areas. We advocate open and reproducible science. Our methods and analysis scripts are publicly available on the github.
We are part of the Department of Biological Sciences and the Department of Statistics at Purdue University. We are also part of the university wide Social-genomics initiative.