Evidence map›Paper›PMID 39013109›Full record

ArticleGenetics2024

A general and efficient representation of ancestral recombination graphs.

Yan Wong, Anastasia Ignatieva, Jere Koskela, Gregor Gorjanc, Anthony W Wohns, Jerome Kelleher

Abstract read
In one paragraph

Article in Genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

66 citing papers in PubMed.

  1. Article
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  9. Ancient DNA from shells reveals delayed genomic erosion and rapid immune adaptation in the critically endangered black abalone.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
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  16. Review
  17. Polarising SNPs Without Outgroup.Molecular ecology resources · 2026
    Article
  18. Article
  19. Article
  20. Article

6 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Yan WongBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.ORCID 0000-0002-3536-6411
Anastasia IgnatievaSchool of Mathematics and Statistics, University of Glasgow, Glasgow G12 8TA, UK.ORCID 0000-0001-6402-9396
Jere KoskelaSchool of Mathematics, Statistics and Physics, Newcastle University, Newcastle NE1 7RU, UK.ORCID 0000-0002-2836-8777
Gregor GorjancThe Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh EH25 9RG, UK.ORCID 0000-0001-8008-2787
Anthony W WohnsBroad Institute of MIT and Harvard, Cambridge, MA 02142, USA.ORCID 0000-0001-7353-1177
Jerome KelleherBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, UK.ORCID 0000-0002-7894-5253

Funding

Scaling up computational genomics with tree sequencesR01HG012473 · NHGRI · UNIVERSITY OF OREGON · PI PETER Lochhead RALPH · 2023 to 2026
$2.3M
Scaling up computational genomics with tree sequencesR56HG011395 · NHGRI · UNIVERSITY OF OREGON · PI RALPH, PETER LOCHHEAD · 2021 to 2021
$557k
BBSRC BBS/E/D/30002275EPSRC EP/X024881/1NHGRI NIH HHS R01 HG012473NHGRI NIH HHS R56 HG011395NIH HHS HG011395Robertson Foundation
6 · The paper itself

Abstract

As a result of recombination, adjacent nucleotides can have different paths of genetic inheritance and therefore the genealogical trees for a sample of DNA sequences vary along the genome. The structure capturing the details of these intricately interwoven paths of inheritance is referred to as an ancestral recombination graph (ARG). Classical formalisms have focused on mapping coalescence and recombination events to the nodes in an ARG. However, this approach is out of step with some modern developments, which do not represent genetic inheritance in terms of these events or explicitly infer them. We present a simple formalism that defines an ARG in terms of specific genomes and their intervals of genetic inheritance, and show how it generalizes these classical treatments and encompasses the outputs of recent methods. We discuss nuances arising from this more general structure, and argue that it forms an appropriate basis for a software standard in this rapidly growing field.

Indexed as

Models, GeneticRecombination, GeneticEvolution, MolecularGenomeHumansSoftwareancestral recombination graphs

Identifiers

PMID39013109
PMCPMC11373519

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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.