Likelihood-Free Inference of Population Structure and Local Adaptation in a Bayesian Hierarchical Model

By Eric Bazin, Kevin J. Dawson, MARK A. Beaumont. 2010

103 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Genetics

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Citations in the corpus

K2-ABC: Approximate Bayesian Computation with Infinite Dimensional Summary Statistics via Kernel Embeddings (2015, methodology): “Originated in population genetics (Beaumont et al., 2002), ABC has been widely used in a broad range of scientific applications including ecology, cosmology, and bioinformatics (Ratmann et al., 2007; Bazin et al., 2010; Schafer & Freeman, 2012).”
Approximate Bayesian Computation in Evolution and Ecology (2010, methodology): “In the more general case, with large numbers of units it will never be feasible to match summary statistics from each unit and Bazin et al. (2010) describe two algorithms for performing hierarchical ABC with large data sets.”
GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation (2014, background): “bution of parameter settings that provide accurate simulation results [20, 3, 18].”
Statistical inference for stochastic simulation models--theory and application. (2011, methodology): “It is advisable to scale the metric d(S,S¢) used for eqn 3 to the variance of the summary statistic s¢, to have a comparable approximation error for each dimension of S (Beaumont et al. 2002; Bazin et al. 2010).”
Constructing summary statistics for approximate Bayesian computation: semi‐automatic approximate Bayesian computation (2012, methodology): “(2009) and Bazin et al. (2010)). However, one particular approach motivated by our theory is to use approximate estimates for each parameter. Such an approach has been used in Wilson et al. (2009), where estimates of the recombination rate under the incorrect demographic model were used as summary s”
MTML-msBayes: Approximate Bayesian comparative phylogeographic inference from multiple taxa and multiple loci with rate heterogeneity (2011, methodology): “…of the information in the data are lost, we expect that a strategy involving genetic distances instead of Euclidian distances might work well for testing multi-taxa hypotheses or alternatively using the first four moments of sets of summary statistics calculated across loci and/or taxa [46,53].”
Pcadapt: An R Package to Perform Genome Scans for Selection Based on Principal Component Analysis (2016, methodology): “We set a lower migration rate for the 50 adaptive SNPs compared with the 950 neutral ones to mimic diversifying selection (Bazin et al. 2010).”
Using Environmental Correlations to Identify Loci Underlying Local Adaptation (2010, methodology): “The island-model framework has been extended to identify loci that have outlying allele frequencies with respect to particular populations (Beaumont and Balding, 2004; Bazin et al., 2010).”