Feng Yu

This paper introduces a Bayesian framework for inferring time-varying selection from ancient DNA data, improving upon previous methods by addressing issues with allele age dependencies.

This paper extends a method to infer temporally variable selection from ancient DNA data, accounting for linkage and epistasis, and applies it to horse pigmentation loci.

This paper introduces a Bayesian framework to infer temporally variable selection from ancient DNA data by modeling genotype likelihoods and sample uncertainties, demonstrating improved selection inference using ancient horse coat color loci.

This paper introduces a Bayesian framework to estimate the timing and strength of natural selection and gene migration from ancient DNA data, applied to ancient chicken samples.

This paper introduces two moment-based approximations for the Wright-Fisher model with natural selection at two linked loci, improving computational efficiency and avoiding distribution support issues.

This paper develops a Bayesian framework to infer natural selection at linked loci using time series allele frequency data and forward simulations, showing improved accuracy with recombination and linkage modeling.

This paper develops a likelihood-based method to estimate natural selection and allele age from time series allele frequency data, showing improved accuracy over existing methods.

This paper develops a numerical scheme for solving the two-locus Wright-Fisher diffusion equation to approximate transition probability densities, improving computational efficiency and performance over existing methods.

This study examines how the order of natural selection and population regulation affects Wright-Fisher model dynamics, showing significant differences under strong selection and linkage disequilibrium.