The research in my group is designed to contribute to understanding
the role of genetic, genomic and environmental factors, and their interactions,
in the development of complex diseases. Our research covers problems on the
full spectrum of research in this field, from theoretical
statistics to data analysis. The applications include finding the
genetic and environmental components of asthma and related traits, and of neuropsychiatric phenotypes.
Statistical genetics problems of interest focus on applications of
genetics/genomics technologies, and large scale data integration.
We are interested in models and statistical methods for binary, quantitative and longitudinal traits,
genome-wide strategies for testing gene-gene and gene-environment interaction,
and methods for analyzing expression data from RNA-sequencing studies. We have also
developed methodology for analyzing the genome-wide data at the gene, region, pathway
and network level for common and rare variants. Current focus is on methods for integrating 'omics' data
such as expression, methylation, microbiome and variation for understanding the molecular basis of disease.
Mathematical statistics topics include Bayesian and frequentist
measures of missing data and dependence, general measures of information, and