Time-Dependent Random Effect Poisson Random Field Model for Polymorphism within and Between Two Related Species

TL;DRAbstract

Molecular evolution is partially driven by mutation, selection, random genetic drift, or combination of the three factors. To quantify the magnitude of these genetic forces, a previously developed time-dependent fixed effect Poisson random field model provides powerful likelihood and Bayesian estimates of mutation rate, selection coefficient, and species divergence time. The assumption of the fixed effect model that selection intensity is constant within a genetic locus but varies across genes is obviously biologically unrealistic, but it serves the original purpose of making statistical inference about selection and divergence between two related species they are individually at mutation-selection-drift inequilibrium. By relaxing the constant selection assumption, this dissertation derives a within-locus random effect model in which the selective intensity of non-synonymous mutation in a gene is treated as a random sample from some underlying normal distribution and applies a Bayesian

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