Abstract
AbstractPhyloG2P methods link genotype and phenotype by integrating evidence from across a phylogeny. I introduce a Bayesian approach to jointly modelling a continuous trait and a multiple sequence alignment, given a background tree and substitution rate matrix. The aim is to ask whether faster sequence evolution is linked to faster phenotypic evolution. Per-branch substitution rate multipliers (for the alignment) are linked to per-branch variance rates of a Brownian diffusion process (for the trait) via a flexible function. Notably, the method is implemented concisely using the probabilistic programming language Stan. Simulation studies suggest the model can be well estimated using relatively short alignments and reasonably sized trees.
Publisher
Cold Spring Harbor Laboratory