Unified Framework to Evaluate Panmixia and Migration Direction Among Multiple Sampling Locations
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Abstract
For many biological investigations, groups of individuals are genetically sampled from several geographic locations. These sampling locations often do not reflect the genetic population structure. We describe a framework using marginal likelihoods to compare and order structured population models, such as testing whether the sampling locations belong to the same randomly mating population or comparing unidirectional and multidirectional gene flow models. In the context of inferences employing Markov chain Monte Carlo methods, the accuracy of the marginal likelihoods depends heavily on the approximation method used to calculate the marginal likelihood. Two methods, modified thermodynamic integration and a…
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Authors
2Topics & keywords
Keywords
- Panmixia
- Biology
- Sampling (signal processing)
- Genetics
- Computational biology
- Evolutionary biology
- Genetic variation
- Computer science
UN Sustainable Development Goals
- Reduced inequalities
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