ArticleEvolution; international journal of organic evolution2009
Likelihood-based inference in isolation-by-distance models using the spatial distribution of low-frequency alleles.
Article in Evolution; international journal of organic evolution, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- The promise and challenge of spatial inference with the full ancestral recombination graph under Brownian motion.G3 (Bethesda, Md.) · 2025Article
- Identifying Single-Origin Rare Variants in Population Genomic Data.Molecular biology and evolution · 2025Article
- Population genomics of Aedes albopictus across remote Pacific islands for genetic biocontrol considerations.PLoS neglected tropical diseases · 2025Article
- Study design and the sampling of deleterious rare variants in biobank-scale datasets.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- The Evolution of Comparative Phylogeography: Putting the Geography (and More) into Comparative Population Genomics.Genome biology and evolution · 2022Review
- Space is the Place: Effects of Continuous Spatial Structure on Analysis of Population Genetic Data.Genetics · 2020Article
- Transcontinental dispersal ofCommunications biology · 2019Article
- Inferring Recent Demography from Isolation by Distance of Long Shared Sequence Blocks.Genetics · 2017Article
- The Empirical Distribution of Singletons for Geographic Samples of DNA Sequences.Frontiers in genetics · 2017Article
- ASSESSING PHENOTYPIC CORRELATION THROUGH THE MULTIVARIATE PHYLOGENETIC LATENT LIABILITY MODEL.The annals of applied statistics · 2015Article
- Anisotropic isolation by distance: the main orientations of human genetic differentiation.Molecular biology and evolution · 2013Article
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2 authors.
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Abstract
Estimating dispersal distances from population genetic data provides an important alternative to logistically taxing methods for directly observing dispersal. Although methods for estimating dispersal rates between a modest number of discrete demes are well developed, methods of inference applicable to "isolation-by-distance" models are much less established. Here, we present a method for estimating rhosigma(2), the product of population density (rho) and the variance of the dispersal displacement distribution (sigma(2)). The method is based on the assumption that low-frequency alleles are identical by descent. Hence, the extent of geographic clustering of such alleles, relative to their frequency in the population, provides information about rhosigma(2). We show that a novel likelihood-based method can infer this composite parameter with a modest bias in a lattice model of isolation-by-distance. For calculating the likelihood, we use an importance sampling approach to average over the unobserved intraallelic genealogies, where the intraallelic genealogies are modeled as a pure birth process. The approach also leads to a likelihood-ratio test of isotropy of dispersal, that is, whether dispersal distances on two axes are different. We test the performance of our methods using simulations of new mutations in a lattice model and illustrate its use with a dataset from Arabidopsis thaliana.
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