Methods development using gene expression data to understand the genetic architecture of disease

We are developing new methods to use gene expression data to identify sets of genes whose expression is associated with disease. These gene sets can help in the understanding of disease etiology and prioritize potential causal genes after a genetic association study. We plan to apply our new methods to integrate gene expression information from the GTeX project with genetic association data from the UK Biobank.

Katie received her PhD in Genomics & Computational Biology from the University of Pennsylvania. For her thesis work, she developed a new statistical method to detect natural selection using genomic data. She also studied the genetic basis of a variety of diseases, including heart disease and migraine headache. Through these experiences, Katie has developed an interest in developing methods to understand the genetics of complex traits, with a focus on methods that could help discover or prioritize potential drug targets. She has been performing research in this area since June 2019, when she started her postdoc in the lab of Alkes Price.