Statistical methods for studying multidimensional mediators of genetic associations with chronic diseases

Rhian is a statistician with a particular interest in methods for making inferences about cause-effect relationships. Recent advances in omics technologies, which have dramatically changed the nature and scale of observational data, require corresponding developments in statistical methods in order to make sense of this new wealth of information. By focusing on methods for causal mediation analysis and extending them to handle the dimensionality and complexity of proteomic and metabolomic mediators, Rhian aims to be able to answer questions such as: which of the metabolic subtypes of LDL cholesterol lie on the strongest causal pathways from established CVD genes to disease?