ArticleProceedings of the National Academy of Sciences of the United States of America2001
Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2001. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 459 papers.
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459 citing papers in PubMed.
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- CoalMiner: a coalescent model generator forbioRxiv : the preprint server for biology · 2026Article
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- Climate change-driven northward expansion of the mediterranean orchid Ophrys apifera from genetic and ecological perspectives.Scientific reports · 2025Article
- Bayesian Phylodynamic Inference of Multitype Population Trajectories Using Genomic Data.Molecular biology and evolution · 2025Article
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- Effects of Social Structure on Effective Population Size Change Estimates.Evolutionary applications · 2025Article
- Inference and applications of ancestral recombination graphs.Nature reviews. Genetics · 2025Review
- Comparative phylogeographic patterns and processes of the incipient brown seaweedsFrontiers in plant science · 2025Article
399 more citing papers are in PubMed but not listed here.
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Authors and funding
2 authors.
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Abstract
A maximum likelihood estimator based on the coalescent for unequal migration rates and different subpopulation sizes is developed. The method uses a Markov chain Monte Carlo approach to investigate possible genealogies with branch lengths and with migration events. Properties of the new method are shown by using simulated data from a four-population n-island model and a source-sink population model. Our estimation method as coded in migrate is tested against genetree; both programs deliver a very similar likelihood surface. The algorithm converges to the estimates fairly quickly, even when the Markov chain is started from unfavorable parameters. The method was used to estimate gene flow in the Nile valley by using mtDNA data from three human populations.
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