Genetics and Genomics

Purpose: to explore LDHD methods with the potential to assist in modern genetic studies.

Genetics and genomics are undergoing a major change due to the availability and affordability of modern high-throughput measurement technologies, coupled to biobank and electronic health records. Large scale projects are producing vast quantities of molecular data on human as well as cancer cells and pathogens. Such data includes DNA, RNA, methylation, metabonomic and proteomic meaurements. Statistical models are needed to assist scientists in interpreting this high-dimensional data, such as methods for reducing dimensionality, to explore pertinent features and dependencies, and associate variation at the molecular level with multivariate clinical phenotypes or population variation.

Potential topics:
- detecting population structure and admixture in human DNA
- modelling structural variation and evolution in cancer cells
- integrating DNA with other molecular data, such as RNA, methylation, etc
- methods for complex genome-wide association studies involving
(longitudinal) multivariate phenotype data
- characterizing uncertainty and stability of findings

Leaders:
Barbara Engelhardt, Chris Holmes