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A general framework for branch length estimation in Ancestral Recombination Graphs.

Yun Deng1, William S DeWitt2,3, Yun S Song1,2,4

  • 1Center for Computational Biology, University of California, Berkeley, CA 94720.

Proceedings of the National Academy of Sciences of the United States of America
|November 25, 2025
PubMed
Summary
This summary is machine-generated.

We developed POLEGON, a novel method for estimating branch lengths in Ancestral Recombination Graphs (ARGs). This approach improves the accuracy of coalescence time estimates and downstream population genetics inferences without relying on complex priors.

Keywords:
Ancestral Recombination Graphbranch length estimationnoninformative prior

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Area of Science:

  • Genomics
  • Population Genetics
  • Bioinformatics

Background:

  • Ancestral Recombination Graphs (ARGs) are crucial for analyzing genomic variation.
  • Estimating coalescence times in ARGs often relies on informative priors from coalescent theory, which can introduce bias and complicate analyses.

Purpose of the Study:

  • To introduce POLEGON, a new method for estimating branch lengths in ARGs using an uninformative prior.
  • To demonstrate POLEGON's ability to provide more accurate coalescence time estimates and improve downstream inferences.

Main Methods:

  • Developed Prior-Oblivious Length Estimation in Genealogies with Oriented Networks (POLEGON).
  • Utilized extensive simulations to evaluate POLEGON's performance under various demographic scenarios.
  • Applied POLEGON to real-world data, including the 1000 Genomes Project and the Human Leukocyte Antigen (HLA) region.

Main Results:

  • POLEGON yields improved estimates of coalescence times compared to traditional methods.
  • The method enhances the accuracy of effective population size and mutation rate inferences.
  • Analysis of 1000 Genomes Project data revealed population-specific histories and mutation signatures.
  • Coalescence times in the HLA region were estimated to exceed 30 million years in multiple segments.

Conclusions:

  • POLEGON offers a robust and accurate approach for estimating ARG branch lengths, overcoming limitations of prior-based methods.
  • The method facilitates more reliable inferences in population genetics and evolutionary studies.
  • POLEGON provides valuable insights into human population history and genetic variation.