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arXiv · 2007.02185

Parameter identifiability for a profile mixture model of protein evolution

Samaneh Yourdkhani·Elizabeth S. Allman·John A. Rhodes
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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.

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Samaneh Yourdkhani, Elizabeth S. Allman, John A. Rhodes. 2020-07-04. Parameter identifiability for a profile mixture model of protein evolution. https://arxiv.org/abs/2007.02185

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