Evidence map›Paper›PMID 39158305›Full record

ArticleMolecular biology and evolution2024

GTRpmix: A Linked General Time-Reversible Model for Profile Mixture Models.

Hector Banos, Thomas K F Wong, Justin Daneau, Edward Susko, Bui Quang Minh, Robert Lanfear, Matthew W Brown, Laura Eme, Andrew J Roger

Abstract read
In one paragraph

Article in Molecular biology and evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Toward a genomic understanding of the tree of life.Molecular biology and evolution · 2026
    Article
  8. Article
  9. Article
  10. Challenges in Assembling the Dated Tree of Life.Genome biology and evolution · 2024
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Hector BanosDepartment of Mathematics, California State University San Bernardino, San Bernardino, CA, USA.ORCID 0000-0001-5769-2544
Thomas K F WongSchool of Computing, College of Engineering and Computing and Cybernetics, Australian National University, Canberra, ACT 2600, Australia.ORCID 0000-0002-0580-6324
Justin DaneauDepartment of Biochemistry and Molecular Biology, Faculty of Medicine, Dalhousie University, Halifax, NS, Canada.ORCID 0009-0008-4061-5292
Edward SuskoDepartment of Mathematics and Statistics, Faculty of Science, Dalhousie University, Halifax, NS, Canada.ORCID 0000-0003-1122-8740
Bui Quang MinhSchool of Computing, College of Engineering and Computing and Cybernetics, Australian National University, Canberra, ACT 2600, Australia.ORCID 0000-0002-5535-6560
Robert LanfearEcology and Evolution, Research School of Biology, College of Science, Australian National University, Canberra, ACT 2600, Australia.ORCID 0000-0002-1140-2596
Matthew W BrownDepartment of Biological Sciences, Mississippi State University, Mississippi State, MS, USA.ORCID 0000-0002-1254-0608
Laura EmeLaboratoire d'Ecologie, systématique et Evolution, Université Paris-Saclay, Gif-sur-Yvette, France.ORCID 0000-0002-0510-8868
Andrew J RogerDepartment of Biochemistry and Molecular Biology, Faculty of Medicine, Dalhousie University, Halifax, NS, Canada.ORCID 0000-0003-1370-9820

Funding

Australian Research Council DP200103151Chan-Zuckerberg InitiativeDivision of Environmental Biology 2100888European Research Council 803151National Science Foundation 2331660NSERCSimons Foundation 735923LPI
6 · The paper itself

Abstract

Profile mixture models capture distinct biochemical constraints on the amino acid substitution process at different sites in proteins. These models feature a mixture of time-reversible models with a common matrix of exchangeabilities and distinct sets of equilibrium amino acid frequencies known as profiles. Combining the exchangeability matrix with each profile generates the matrix of instantaneous rates of amino acid exchange for that profile. Currently, empirically estimated exchangeability matrices (e.g. the LG matrix) are widely used for phylogenetic inference under profile mixture models. However, these were estimated using a single profile and are unlikely optimal for profile mixture models. Here, we describe the GTRpmix model that allows maximum likelihood estimation of a common exchangeability matrix under any profile mixture model. We show that exchangeability matrices estimated under profile mixture models differ from the LG matrix, dramatically improving model fit and topological estimation accuracy for empirical test cases. Because the GTRpmix model is computationally expensive, we provide two exchangeability matrices estimated from large concatenated phylogenomic-supermatrices to be used for phylogenetic analyses. One, called Eukaryotic Linked Mixture (ELM), is designed for phylogenetic analysis of proteins encoded by nuclear genomes of eukaryotes, and the other, Eukaryotic and Archaeal Linked mixture (EAL), for reconstructing relationships between eukaryotes and Archaea. These matrices, combined with profile mixture models, fit data better and have improved topology estimation relative to the LG matrix combined with the same mixture models. Starting with version 2.3.1, IQ-TREE2 allows users to estimate linked exchangeabilities (i.e. amino acid exchange rates) under profile mixture models.

Indexed as

Models, GeneticPhylogenyAmino Acid SubstitutionArchaeaEukaryotaEvolution, MolecularLikelihood Functionsfrequency profile mixturesgeneral time reversible modelmaximum likelihoodmodel of sequence evolutionphylogenetics

Identifiers

PMID39158305
PMCPMC11371462

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.