Teasing apart the effects of selection and demography on genetic polymorphism remains
one of the major challenges in the analysis of population genomic data. The traditional …

Stochastic simulation is a key tool in population genetics, since the models involved are
often analytically intractable and simulation is usually the only way of obtaining ground-truth …

Abstract Knowledge of genome-wide genealogies for thousands of individuals would
simplify most evolutionary analyses for humans and other species, but has remained …

A central challenge in the analysis of genetic variation is to provide realistic genome
simulation across millions of samples. Present day coalescent simulations do not scale well …

As modern humans migrated out of Africa, they encountered many new environmental
conditions, including greater temperature extremes, different pathogens and higher …

We present a new haplotype-based statistic (nS L) for detecting both soft and hard sweeps
in population genomic data from a single population. We compare our new method with …

Detection of recent natural selection is a challenging problem in population genetics. Here
we introduce the singleton density score (SDS), a method to infer very recent changes in …

Population-scale genomic data sets have given researchers incredible amounts of
information from which to infer evolutionary histories. Concomitant with this flood of data …

Motivation: We have implemented a coalescent simulation program for a structured
population with selection at a single diploid locus. The program includes the functionality of …

Estimating fine-scale recombination maps of Drosophila from population genomic data is a
challenging problem, in particular because of the high background recombination rate. In …