ArticleGenetics2014
Robust forward simulations of recurrent hitchhiking.
Article in Genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Allelic gene conversion softens selective sweeps.Genetics · 2026Article
- The distribution of fitness effects of new mutations in regulatory regions of thebioRxiv : the preprint server for biology · 2026Article
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- Accessible, Realistic Genome Simulation with Selection Using stdpopsim.Molecular biology and evolution · 2025Article
- SimHumanity: Using SLiM 5.0 to run whole-genome simulations of human evolution.bioRxiv : the preprint server for biology · 2025Article
- Accessible, realistic genome simulation with selection using stdpopsim.bioRxiv : the preprint server for biology · 2025Article
- Parameter Scaling in Population Genetics Simulations may Introduce Unintended Background Selection: Considerations for Scaled Simulation Design.Genome biology and evolution · 2025Article
- Population size rescaling significantly biases outcomes of forward-in-time population genetic simulations.Genetics · 2025Article
- Population size rescaling significantly biases outcomes of forward-in-time population genetic simulations.bioRxiv : the preprint server for biology · 2024Article
- Biases in ARG-Based Inference of Historical Population Size in Populations Experiencing Selection.Molecular biology and evolution · 2024Article
- Background Selection From Unlinked Sites Causes Nonindependent Evolution of Deleterious Mutations.Genome biology and evolution · 2024Article
- Enrichment of Hard Sweeps on the X Chromosome in Drosophila melanogaster.Molecular biology and evolution · 2023Article
- On the prospect of achieving accurate joint estimation of selection with population history.Genome biology and evolution · 2022Article
- Inferring Genome-Wide Correlations of Mutation Fitness Effects between Populations.Molecular biology and evolution · 2021Article
- The Impact of Purifying and Background Selection on the Inference of Population History: Problems and Prospects.Molecular biology and evolution · 2021Article
- Deleterious mutation accumulation and the long-term fate of chromosomal inversions.PLoS genetics · 2021Article
- The impact of purifying and background selection on the inference of population history: problems and prospects.bioRxiv : the preprint server for biology · 2021Article
- Article
- Toward an Evolutionarily Appropriate Null Model: Jointly Inferring Demography and Purifying Selection.Genetics · 2020Article
- Exploiting selection at linked sites to infer the rate and strength of adaptation.Nature ecology & evolution · 2019Article
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Authors and funding
2 authors.
Funding
Abstract
Evolutionary forces shape patterns of genetic diversity within populations and contribute to phenotypic variation. In particular, recurrent positive selection has attracted significant interest in both theoretical and empirical studies. However, most existing theoretical models of recurrent positive selection cannot easily incorporate realistic confounding effects such as interference between selected sites, arbitrary selection schemes, and complicated demographic processes. It is possible to quantify the effects of arbitrarily complex evolutionary models by performing forward population genetic simulations, but forward simulations can be computationally prohibitive for large population sizes (>10(5)). A common approach for overcoming these computational limitations is rescaling of the most computationally expensive parameters, especially population size. Here, we show that ad hoc approaches to parameter rescaling under the recurrent hitchhiking model do not always provide sufficiently accurate dynamics, potentially skewing patterns of diversity in simulated DNA sequences. We derive an extension of the recurrent hitchhiking model that is appropriate for strong selection in small population sizes and use it to develop a method for parameter rescaling that provides the best possible computational performance for a given error tolerance. We perform a detailed theoretical analysis of the robustness of rescaling across the parameter space. Finally, we apply our rescaling algorithms to parameters that were previously inferred for Drosophila and discuss practical considerations such as interference between selected sites.
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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.