Evidence map›Paper›PMID 37961279›Full record

ArticlebioRxiv : the preprint server for biology2024

A general and efficient representation of ancestral recombination graphs.

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

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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, UK.ORCID 0000-0002-3536-6411
Anastasia IgnatievaSchool of Mathematics and Statistics, University of Glasgow, UK.ORCID 0000-0001-6402-9396
Jere KoskelaSchool of Mathematics, Statistics and Physics, Newcastle University, UK.ORCID 0000-0002-2836-8777
Gregor GorjancThe Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, UK.ORCID 0000-0001-8008-2787
Anthony W WohnsBroad Institute of MIT and Harvard, Cambridge, USA.ORCID 0000-0001-7353-1177
Jerome KelleherBig Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, 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
Biotechnology and Biological Sciences Research Council BB/P018653/1NHGRI NIH HHS R01 HG012473NHGRI NIH HHS R56 HG011395
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. This approach is out of step with 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 generalises 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

Ancestral recombination graphs

Identifiers

PMID37961279
PMCPMC10635123

What OpenQuestion holds

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LicenceCC BY
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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.