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Quantitative Biology > Populations and Evolution

arXiv:2007.02185 (q-bio)
[Submitted on 4 Jul 2020]

Title:Parameter identifiability for a profile mixture model of protein evolution

Authors: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.
Subjects: Populations and Evolution (q-bio.PE)
MSC classes: 92D15 (Primary) 92D20 (Secondary)
Cite as: arXiv:2007.02185 [q-bio.PE]
  (or arXiv:2007.02185v1 [q-bio.PE] for this version)
  https://doi.org/10.48550/arXiv.2007.02185

Submission history

From: John Rhodes [view email]
[v1] Sat, 4 Jul 2020 21:09:41 UTC (99 KB)
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