DGM Is Dead; Long Live DGM-Star! A Quantization-Theoretic Approach to Gamma Rate Discretization

Modeling substitution rate heterogeneity as a discretized Gamma distribution is standard in phylogenetic inference. Ferretti et al. (2026) have recently demonstrated that the most commonly used equiprobable Gamma rate discretization, known simply as the discrete Gamma model (DGM), substantially overestimates average branch lengths in reconstructed phylogenies when the true rates are drawn from a continuous Gamma distribution. We propose an alternative method to discretize the Gamma rate distribution that considerably reduces the bias in estimated branch lengths and can be used as a drop-in replacement for the standard DGM. The method works especially well on large trees with short branches, yielding up to a 20-fold reduction in bias on simulated phylogenies. It is developed by applying quantization-theoretic tools to the analysis of a simplified star-phylogeny abstraction introduced by Ferretti et al. (2026), where the new method is unbiased by construction. We explain Ferretti et al.'s counterintuitive observation that increasing the number of rate categories can exacerbate the bias of the standard DGM, even though this should in principle make DGM a better approximation to the continuous case, and offer our method as an immediately available alternative.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-10-31
DOI
https://doi.org/10.64898/2026.10.30.763052
Primary Topic
Genomics and Phylogenetic Studies
Type
preprint
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preprint

DGM Is Dead; Long Live DGM-Star! A Quantization-Theoretic Approach to Gamma Rate Discretization

王雨宁, Bùi Quang Minh, Roman Sokolovskii, Nick Goldman et al.
bioRxiv (Cold Spring Harbor Laboratory)
Genomics and Phylogenetic Studies
preprint

DGM Is Dead; Long Live DGM-Star! A Quantization-Theoretic Approach to Gamma Rate Discretization

王雨宁, Bùi Quang Minh, Roman Sokolovskii, Nick Goldman, Alexandros Stamatakis, Thomas Heinis, Ben Bettisworth, Ziheng Yang, SAMUEL J. MARTIN, Oleksiy M. Kozlov, Christoph Stelz, Van Nguyen Hoang
preprint en

Abstract

Modeling substitution rate heterogeneity as a discretized Gamma distribution is standard in phylogenetic inference. Ferretti et al. (2026) have recently demonstrated that the most commonly used equiprobable Gamma rate discretization, known simply as the discrete Gamma model (DGM), substantially overestimates average branch lengths in reconstructed phylogenies when the true rates are drawn from a continuous Gamma distribution. We propose an alternative method to discretize the Gamma rate distribution that considerably reduces the bias in estimated branch lengths and can be used as a drop-in replacement for the standard DGM. The method works especially well on large trees with short branches, yielding up to a 20-fold reduction in bias on simulated phylogenies. It is developed by applying quantization-theoretic tools to the analysis of a simplified star-phylogeny abstraction introduced by Ferretti et al. (2026), where the new method is unbiased by construction. We explain Ferretti et al.'s counterintuitive observation that increasing the number of rate categories can exacerbate the bias of the standard DGM, even though this should in principle make DGM a better approximation to the continuous case, and offer our method as an immediately available alternative.

bioRxiv (Cold Spring Harbor Laboratory)
Karlsruhe Institute of Technology (DE), Australian National University (AU), European Bioinformatics Institute (GB), University of Cambridge (GB), European Molecular Biology Laboratory (FR), European Molecular Biology Laboratory (DE), European Molecular Biology Laboratory (DE), University College London (GB), Imperial College London (GB), Heidelberg Institute for Theoretical Studies (DE), Foundation for Research and Technology Hellas (GR)
Genomics and Phylogenetic Studies
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