Parameter identifiability for a profile mixture model of protein evolution
Abstract
A Profile Mixture Model is a model of protein evolution, describing sequence data in which sites are assumed to follow many related substitution processes on a single evolutionary tree. The processes depend in part on different amino acid distributions, or profiles, varying over sites in aligned sequences. A fundamental question for any stochastic model, which must be answered positively to justify model-based inference, is whether the parameters are identifiable from the probability distribution they determine. Here we show that a Profile Mixture Model has identifiable parameters under circumstances in which it is likely to be used for empirical analyses. In particular, for a tree relating 9 or more taxa, both the tree topology and all numerical parameters are generically identifiable when the number of profiles is less than 74.
Cite
@article{arxiv.2007.02185,
title = {Parameter identifiability for a profile mixture model of protein evolution},
author = {Samaneh Yourdkhani and Elizabeth S. Allman and John A. Rhodes},
journal= {arXiv preprint arXiv:2007.02185},
year = {2020}
}