Associate Professor of Statistical and Population Genomics
- Tutorial Fellow, Somerville College
I am a statistical geneticist with wide ranging interests but am particularly interested in statistical methods development that ultimately facilitates predicting phenotype from genotype. Predicting phenotypes from genotypes is a central goal of personalized medicine, and if done accurately would have major benefits for human health. Increasingly, whole genome sequencing is used to identify pathogenic and hence clinically relevant mutations for patients with Mendelian diseases. However, assessment of risk among individuals without high impact variants, or in the presence of an incompletely penetrant variant, is lacking. Heritability studies suggest common variants contribute substantially to many rare and common diseases with large public health costs, and simulation studies suggest that large genome-wide association studies and polygenic scores may enable sufficiently discriminatory predictors to change standards of care to predict and prevent disease. However, there are a number of hurdles which must be overcome to make this vision a reality, which I seek to work on in my research.
View my full profile on the Department of Statistics website