ArticleJournal of theoretical biology2018
Evaluating genetic drift in time-series evolutionary analysis.
Article in Journal of theoretical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Whole-genome resequencing of temporally stratified samples reveals substantial loss of haplotype diversity in the highly inbred Scandinavian wolf population.Genome research · 2022Article
- Visualization of Genetic Drift Processes Using the Conserved Collagen 1α1 GXY Domain.Journal of molecular evolution · 2019Article
- Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model.Genetics · 2018Article
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Authors and funding
3 authors.
Funding
Abstract
The Wright-Fisher model is the most popular population model for describing the behaviour of evolutionary systems with a finite population size. Approximations have commonly been used but the model itself has rarely been tested against time-resolved genomic data. Here, we evaluate the extent to which it can be inferred as the correct model under a likelihood framework. Given genome-wide data from an evolutionary experiment, we validate the Wright-Fisher drift model as the better option for describing evolutionary trajectories in a finite population. This was found by evaluating its performance against a Gaussian model of allele frequency propagation. However, we note a range of circumstances under which standard Wright-Fisher drift cannot be correctly identified.
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