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GHIST 2024: The First Genomic History Inference Strategies Tournament
Travis J Struck1, Andrew H Vaughn2,3, Austin Daigle4,5
1Department of Molecular and Cellular Biology, University of Arizona, Tucson, AZ, USA.
The Genomic History Inference Strategies Tournament (GHIST) competition evaluated population genetic inference methods. Site frequency spectrum methods dominated, but flexible models excelled in complex evolutionary histories.
Area of Science:
- Population genetics
- Evolutionary biology
- Computational genomics
Background:
- Evaluating population genetic inference methods is complex due to evolutionary history intricacies.
- Model misspecification and self-assessment biases challenge method evaluation.
- Standardized benchmarks are needed for reliable evolutionary history inference.
Purpose of the Study:
- To establish a community-driven competition for evaluating population genomic inference methods.
- To assess the performance of diverse inference strategies across various demographic scenarios.
- To identify strengths and weaknesses of current methods for inferring evolutionary history.
Main Methods:
- The Genomic History Inference Strategies Tournament (GHIST) competition was conducted from July to November 2024.
- Four demographic history challenges were presented: bottleneck, split with isolation, secondary contact, and archaic admixture.
- Participants submitted numerical parameter estimates from error-free VCF files, scored by relative root-mean-squared error.
Main Results:
- Approximately 60 participants competed using diverse computational approaches.
- Methods based on site frequency spectra demonstrated current dominance.
- Flexible model-building approaches showed advantages for complex demographic histories.
Conclusions:
- GHIST provides standardized benchmarks for population genomic inference.
- The competition highlighted the need for improved methods for complex evolutionary scenarios.
- The ongoing GHIST iteration aims to expand challenge diversity for more robust evaluations.
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