The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Distinguishing Migration From Isolation: A Markov Chain Monte Carlo Approach
Abstract
A Markov chain Monte Carlo method for estimating the relative effects of migration and isolation on genetic diversity in a pair of populations from DNA sequence data is developed and tested using simulations. The two populations are assumed to be descended from a panmictic ancestral population at some time in the past and may (or may not) after that be connected by migration. The use of a Markov chain Monte Carlo method allows the joint estimation of multiple demographic parameters in either a Bayesian or a likelihood framework. The parameters estimated include the migration rate for each population, the time since the two populations diverged from a common ancestral population, and the relative size of each of the two current populations and of the common ancestral population. The results show that even a single nonrecombining genetic locus can provide substantial power to test the hypothesis of no ongoing migration and/or to test models of symmetric migration between the two populations. The use of the method is illustrated in an application to mitochondrial DNA sequence data from a fish species: the threespine stickleback (Gasterosteus aculeatus).
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Metadata
- Authors
- Nielsen, R., & Wakeley, J.
- Venue
- Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2001-06-01
- Volume
- 158
- Issue
- 2
- Pages
- 885-896
- ISSN
- 0016-6731 (ISSN-L)
- 1943-2631
- OpenAlex
- W1934545424
- Cited by
- 1,311
- References
- 31
- FWCI
- 11.73
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
