GHIST 2024: The First Genomic History Inference Strategies Tournament
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 Genomic History Inference Strategies Tournament 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, Genomic History Inference Strategies Tournament represents a substantial step toward more reliable inference of evolutionary history from genomic data.
Authors
- Aaron P. Ragsdale (ORCID: https://orcid.org/0000-0003-0715-3432)
- Elizaveta Grigoreva (ORCID: https://orcid.org/0000-0002-7285-2291)
- Toby G. L. Kovacs (ORCID: https://orcid.org/0000-0001-5322-7928)
- Katie E. Lotterhos (ORCID: https://orcid.org/0000-0001-7529-2771)
- Austin Daigle (ORCID: https://orcid.org/0000-0001-9732-0163)
- Ryan N. Gutenkunst (ORCID: https://orcid.org/0000-0002-8659-0579)
- Dylan D. Ray (ORCID: https://orcid.org/0000-0002-2864-2107)
- Adam Siepel (ORCID: https://orcid.org/0000-0002-3557-7219)
- Evgenii Raines (ORCID: https://orcid.org/0009-0000-0736-8543)
- E. S. Alekseevskaya (ORCID: https://orcid.org/0000-0003-4200-1848)
- Ekaterina Noskova (ORCID: https://orcid.org/0000-0003-1168-0497)
- Andrew H. Vaughn (ORCID: https://orcid.org/0000-0003-3113-2981)
- Travis J. Struck (ORCID: https://orcid.org/0000-0001-7161-5107)
- Jaison Jeevan Sequeira (ORCID: https://orcid.org/0000-0001-6859-9978)
- Andrés Moreno‐Estrada (ORCID: https://orcid.org/0000-0001-8329-8292)
- Eilish S. McMaster (ORCID: https://orcid.org/0000-0002-7415-8690)
- Svetlana Antonets (ORCID: https://orcid.org/0009-0008-1837-4576)
Institutions
- University of North Carolina at Chapel Hill (US)
- Northeastern University (US)
- The University of Sydney (AU)
- University of Wisconsin–Madison (US)
- Gregor Mendel Institute of Molecular Plant Biology (AT)
- University of Arizona (US)
- Austrian Academy of Sciences (AT)
- University of Fribourg (CH)
- ITMO University (RU)
- University of California, San Francisco (US)
- Mangalore University (IN)
- Cold Spring Harbor Laboratory (US)
- ETH Zurich (CH)
- Cooperative Trials Group for Neuro-Oncology (AU)
- Institute of Cytology (RU)
- Institute of Gene Biology (RU)
- Swiss Integrative Center for Human Health (CH)
- Bioinformatics Institute (SG)
- Weizmann Institute of Science (IL)
- Centro de Investigación y de Estudios Avanzados del Instituto Politécnico Nacional (MX)
- University of California, Berkeley (US)
Publication Details
- Journal
- Molecular Biology and Evolution
- Published
- 2025-10-29
- DOI
- https://doi.org/10.1093/molbev/msaf257
- Citations
- 2
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 3.63