Evidence map›Paper›PMID 40986815›Full record

ArticleGenetics2026

A forest is more than its trees: haplotypes and ancestral recombination graphs.

Halley Fritze, Nathaniel Pope, Jerome Kelleher, Peter Ralph

Abstract read
In one paragraph

Article in Genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. A Pandemic-Scale Ancestral Recombination Graph for SARS-CoV-2.bioRxiv : the preprint server for biology · 2025
    Article
  4. Likelihoods for a general class of ARGs under the SMC.bioRxiv : the preprint server for biology · 2025
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Halley FritzeDepartment of Mathematics, University of Oregon, Eugene, Oregon 97403, United States.
Nathaniel PopeInstitute of Evolution and Ecology, Department of Biology, University of Oregon, Eugene, Oregon 97403, United States.ORCID 0000-0001-8409-7812
Jerome KelleherBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom.
Peter RalphDepartment of Mathematics, University of Oregon, Eugene, Oregon 97403, United States.ORCID 0000-0002-9459-6866

Funding

Scaling up computational genomics with tree sequencesR01HG012473 · NHGRI · UNIVERSITY OF OREGON · PI PETER Lochhead RALPH · 2023 to 2026
$2.3M
EPSRC EP/X024881/1NHGRI NIH HHS R01 HG012473NIH NHGRI HG012473
6 · The paper itself

Abstract

Foreshadowing haplotype-based methods of the genomics era, it is an old observation that the "junction" between two distinct haplotypes produced by recombination is inherited as a Mendelian marker. In a genealogical context, this recombination-mediated information reflects the persistence of ancestral haplotypes across local genealogical trees in which they do not represent coalescences. We show how these non-coalescing haplotypes ("locally-unary nodes") may be inserted into ancestral recombination graphs, a compact but information-rich data structure describing the genealogical relationships among recombinant sequences. The resulting ancestral recombination graphs are smaller, faster to compute with, and the additional ancestral information that is inserted is nearly always correct where the initial ancestral recombination graph is correct. We provide efficient algorithms to infer locally-unary nodes within existing ancestral recombination graphs, and explore some consequences for ancestral recombination graphs inferred from real data. To do this, we introduce new metrics of agreement and disagreement between ancestral recombination graphs that, unlike previous methods, consider ancestral recombination graphs as describing relationships between haplotypes rather than just a collection of trees.

Indexed as

HaplotypesModels, GeneticRecombination, GeneticAlgorithmsEvolution, MolecularHumansancestral recombination graphgenealogyhaplotypestree sequence

Identifiers

PMID40986815
PMCPMC12774838

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Registered trials

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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.