Evidence map›Paper›PMID 39404101›Full record

ArticleMolecular biology and evolution2024

RERconverge Expansion: Using Relative Evolutionary Rates to Study Complex Categorical Trait Evolution.

Ruby Redlich, Amanda Kowalczyk, Michael Tene, Heather H Sestili, Kathleen Foley, Elysia Saputra, Nathan Clark, Maria Chikina, Wynn K Meyer, Andreas R Pfenning

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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3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. The genetic foundations of convergent traits.Nature reviews. Genetics · 2026
    Review
  5. Article
  6. Article
  7. Review
  8. Language models reveal a complex sequence basis for adaptive convergent evolution of protein functions.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  9. Review
  10. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors.

Ruby RedlichDepartment of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA.ORCID 0009-0003-1043-2499
Amanda KowalczykDepartment of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA.ORCID 0000-0002-9061-1336
Michael TeneDepartment of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA.ORCID 0009-0001-3763-8847
Heather H SestiliDepartment of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA.ORCID 0000-0002-3944-3429
Kathleen FoleyDepartment of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA.ORCID 0000-0003-0923-1326
Elysia SaputraDepartment of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.ORCID 0000-0002-2572-393X
Nathan ClarkDepartment of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.ORCID 0000-0003-0006-8374
Maria ChikinaDepartment of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA 15260, USA.ORCID 0000-0003-2550-5403
Wynn K MeyerDepartment of Biological Sciences, Lehigh University, Bethlehem, PA 18015, USA.ORCID 0000-0001-7978-3877
Andreas R PfenningDepartment of Computational Biology, Carnegie Mellon University, Pittsburgh, PA 15213, USA.ORCID 0000-0002-3447-9801

Funding

Title: Functional Annotation of Genomes via Phenotypic Convergence within Large Multi-species AlignmentsR01HG009299 · NHGRI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Maria D Chikina, Nathaniel L Clark · 2017 to 2026
$4.1M
High-Throughput Computing for Genomics and Bioinformatics ResearchS10OD028483 · OD · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI LEE, ADRIAN V · 2021 to 2021
$574k
Carnegie Mellon Neuroscience Institute Postdoctoral Fellowship NSF 2046550Carnegie Mellon Neuroscience Institute Postdoctoral Fellowship NSF 20-525NHGRI NIH HHS R01 HG009299NIH HHS S10 OD028483NIH HHS S10OD028483Summer Undergraduate Research FellowshipUniversity of Pittsburgh Center for Research Computing RRID:SCR_022735
6 · The paper itself

Abstract

Comparative genomics approaches seek to associate molecular evolution with the evolution of phenotypes across a phylogeny. Many of these methods lack the ability to analyze non-ordinal categorical traits with more than two categories. To address this limitation, we introduce an expansion to RERconverge that associates shifts in evolutionary rates with the convergent evolution of categorical traits. The categorical RERconverge expansion includes methods for performing categorical ancestral state reconstruction, statistical tests for associating relative evolutionary rates with categorical variables, and a new method for performing phylogeny-aware permutations, "permulations", on categorical traits. We demonstrate our new method on a three-category diet phenotype, and we compare its performance to binary RERconverge analyses and two existing methods for comparative genomic analyses of categorical traits: phylogenetic simulations and a phylogenetic signal based method. We present an analysis of how the categorical permulations scale with the number of species and the number of categories included in the analysis. Our results show that our new categorical method outperforms phylogenetic simulations at identifying genes and enriched pathways significantly associated with the diet phenotypes and that the categorical ancestral state reconstruction drives an improvement in our ability to capture diet-related enriched pathways compared to binary RERconverge when implemented without user input on phenotype evolution. The categorical expansion to RERconverge will provide a strong foundation for applying the comparative method to categorical traits on larger data sets with more species and more complex trait evolution than have previously been analyzed.

Indexed as

Evolution, MolecularPhylogenyAnimalsBiological EvolutionComputer SimulationDietGenomicsModels, GeneticPhenotypeconvergent evolutiondietevolutionary biologygenetics

Identifiers

PMID39404101
PMCPMC11529301

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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.