Evidence map›Paper›PMID 40832282›Full record

ArticlebioRxiv : the preprint server for biology2025

GHIST 2024: The 1st Genomic History Inference Strategies Tournament.

Travis J Struck, Andrew H Vaughn, Austin Daigle, Dylan D Ray, Ekaterina Noskova, Jaison J Sequeira, Svetlana Antonets, Elizaveta Alekseevskaya, Elizaveta Grigoreva, Evgenii Raines and 7 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2025. 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

17 authors.

Travis J StruckDepartment of Molecular and Cellular Biology, University of Arizona, Tucson, AZ, USA.ORCID 0000-0001-7161-5107
Andrew H VaughnCenter for Computational Biology, University of California, Berkeley, CA, USA.ORCID 0000-0003-3113-2981
Austin DaigleCurriculum in Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, NC, USA.ORCID 0000-0001-9732-0163
Dylan D RayDepartment of Genetics, University of North Carolina, Chapel Hill, NC, USA.
Ekaterina NoskovaDepartment of Biology, University of Fribourg, Fribourg, Switzerland.ORCID 0000-0003-1168-0497
Jaison J SequeiraDepartment of Applied Zoology, Mangalore University, Karnataka, India.ORCID 0000-0001-6859-9978
Svetlana AntonetsGenotek Ltd., Moscow, Russia.
Elizaveta AlekseevskayaInstitute of Cytology of the Russian Academy of Sciences, St. Petersburg, Russia.ORCID 0000-0003-4200-1848
Elizaveta GrigorevaGregor Mendel Institute of Molecular Plant Biology, Vienna, Austria.
Evgenii RainesITMO University, St. Petersburg, Russia.
Eilish S McMasterSchool of Life and Environmental Sciences, University of Sydney, Camperdown, Australia.ORCID 0000-0002-7415-8690
Toby G L KovacsSchool of Life and Environmental Sciences, University of Sydney, Camperdown, Australia.ORCID 0000-0001-5322-7928
Aaron P RagsdaleDepartment of Integrative Biology, University of Wisconsin-Madison, Madison, WI, USA.ORCID 0000-0003-0715-3432
Andrés Moreno-EstradaUnidad de Genómica Avanzada (UGA-LANGEBIO), Centro de Investigación y Estudios Avanzados del IPN (Cinvestav), Guanajuato, México.ORCID 0000-0001-8329-8292
Katie E LotterhosDepartment of Marine and Environmental Sciences, Northeastern University Marine Science Center, Nahant, Massachusetts, USA.ORCID 0000-0001-7529-2771
Adam SiepelSimons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.ORCID 0000-0002-3557-7219
Ryan N GutenkunstDepartment of Molecular and Cellular Biology, University of Arizona, Tucson, AZ, USA.ORCID 0000-0002-8659-0579

Funding

UNC Predoc Training Progr in Bioinformatics/Comp BiologyT32GM067553 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ELSTON, TIMOTHY C · 2005 to 2019
$2.5M
Population genomic inferences of history and selection across populations and timeR35GM149235 · NIGMS · UNIVERSITY OF ARIZONA · PI Ryan Gutenkunst · 2023 to 2026
$1.3M
NIGMS NIH HHS R35 GM149235NIGMS NIH HHS T32 GM067553
6 · The paper itself

Abstract

Evaluating population genetic inference methods is challenging due to the complexity of evolutionary histories, potential model misspecification, and unconscious biases in self-assessment. The Genomic History Inference Strategies Tournament (GHIST) is a community-driven competition designed to evaluate methods for inferring evolutionary history from population genomic data. The inaugural GHIST competition ran from July to November 2024 and featured four demographic history inference challenges of varying complexity: a bottleneck model, a split with isolation model, a secondary contact model with demographic complexity, and an archaic admixture model. Data were provided as error-free VCF files, and participants submitted numerical parameter estimates that were scored by relative root mean squared error. Approximately 60 participants competed, using diverse approaches. Results revealed the current dominance of methods based on site frequency spectra, while highlighting the advantages of flexible model-building approaches for complex demographic histories. We discuss insights regarding the competition and outline the next iteration, which is ongoing with expanded challenge diversity. By providing standardized benchmarks and highlighting areas for improvement, GHIST represents a substantial step toward more reliable inference of evolutionary history from genomic data.

Indexed as

competitiondemographic historypopulation genomics

Identifiers

PMID40832282
PMCPMC12363865

What OpenQuestion holds

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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.