Recent advances in DNA sequencing technology are enabling fast and cost-effective generation of sequence data. Soon, whole-genome sequencing will become a routine assay, opening up new opportunities for biomedical research and related fields. Several large-scale sequencing projects are currently under way, each with the aim of sequencing the genomes of hundreds or thousands of individuals (either humans or model organisms). Such projects will provide a comprehensive view of genomic variation in different populations and elucidate the relative contribution of various biological mechanisms to evolution. Given this explosion of data, evolutionary biologists now hope to make inference in models of evolution with unprecedented complexity. This workshop will center around recent advances in computation-intensive probabilistic and statistical inference methods for large-scale population genomics, focusing on the crucial role of efficient algorithms and accurate probabilistic modeling.
These presentations were supported in part by an award from the Simons Foundation.