TIME-DEPENDENT RANDOM EFFECT POISSON RANDOM FIELD MODEL FOR POLYMORPHISM WITHIN AND BETWEEN TWO RELATED SPECIES

摘要: TIME-DEPENDENT RANDOM EFFECT POISSON FIELD MODEL FOR POLYMORPHISM WITHIN AND BETWEEN TWO RELATED SPECIES by Shilei Zhou Dr. Amei Amei, Examination Committee Chair Associate Professor of Mathematical Sciences University Nevada Las Vegas Molecular evolution is partially driven mutation, selection, random genetic drift, or combination the three factors. To quantify magnitude these forces, a previously developed time-dependent fixed effect Poisson field model provides powerful likelihood and Bayesian estimates mutation rate, selection coefficient, species divergence time. The assumption that intensity constant within locus but varies across genes obviously biologically unrealistic, it serves original purpose making statistical inference about between two related they are individually at mutation-selection-drift inequilibrium. By relaxing assumption, this dissertation derives within-locus in which selective non-synonymous gene treated as iii sample from some underlying normal distribution applies framework to make various parameters. Also, new N-ADAM-mixing Markov chain Monte Carlo sampler created provide better sampling strategy fastens convergence speed. Furthermore, conquer computational cost proposes MPI parallel computing scheme boosts calculation speed ten times.