September 18 Friday
Shijia Wang, PhD Assistant Professor，School of Statistics and Data Science, Nankai University
Phylogenetic tree reconstruction is a main task in evolutionary biology.Traditional MCMC methods may suffer from the curse of dimensionality and the local-trap problem. Firstly,we introduce a new combinatorial SMC method, with a novel and efficient proposal distribution. We also explore combining SMC and Gibbs sampling to jointly estimate the phylogenetic trees and evolutionary parameter of genetic datasets. Secondly, we propose an“embarrassingly parallel”method for Bayesian phylogenetic inference, annealed SMC, based on recent advances in the SMC literature such as adaptive determination of annealing parameters.
Finally, we extend our phylogenetic approach to genome wide-association studies, by developing a Bayesian hierarchical model to jointly estimate parameters in linear mixed models(LMM) and the genetic similarity matrixusing genetic sequences and phenotypes. We develop an SMC method to jointly approximate the posterior distributions of the LMM and phylogenetic trees.