Xiaoyang Dai

This paper extends Mendelian randomisation to founder-haplotype data in Diversity Outbred mice, showing founder-effect patterns improve causal inference compared to scalar coding.

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 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.