Inferring demography from genomic data
I am working on developing new statistical methods to infer demography from genomic data as well as applying these methods to data. Previous analysis of African A. thaliana data has led to new insights about the early history of this important model species. Ongoing work involves looking at changes in gene flow over time and developing new likelihood-free and approximate likelihood methods for demographic inference.
Understanding positive and negative selection in the human genome
While much of the genetic variation in humans is determined by demography, a substantial portion of the variation within and near genes is determined by the action of positive and negative linked selection. I am working on determining the relative contributions of each and testing the power of existing methods to detect these contributions.
Methods for detecting introgression
Recent evidence suggests that introgression is pervasive across the tree of life. However, methods to detect introgression are limited, especially in the case where a reference genome sequence is lacking. I am developing methods that combine powerful machine learning approaches with population genetics theory to elucidate introgressed regions in diverse genomes.