Most of my research is designed to contribute to understanding
the role of genetic and environmental factors, and their interactions,
in the development of complex diseases. My work covers problems on the
full spectrum of research in this field, from theoretical
statistics to data analysis.
Statistical genetics problems of interest focus on applications of
next-generation sequencing technologies, large scale data integration,
likelihood applications to complex trait gene detection,
genome-wide strategies for testing gene-gene and
gene-environment interaction, methods for
analysing data at the gene/pathway/network level.
The applications I work on focus on finding the genetic and environmental
components of asthma and related phenotypes, and diabetes and its complications.
I am also interested in functional genomics and the analysis of gene expression data.
Mathematical statistics topics I am working on include Bayesian and frequentist
measures of missing data and dependence, general measures of information, and
artificial likelihoods for hypothesis testing.