Beerli P.. Comparison of Bayesian and maximum-likelihood inference of population genetic parameters. Bioinformatics 22: 341-345

School of Computational Science and Department of Biological Sciences, Florida State University, Tallahassee, FL 32306-4120, USA.
Bioinformatics (Impact Factor: 4.98). 03/2006; 22(3):341-5. DOI: 10.1093/bioinformatics/bti803
Source: PubMed

ABSTRACT Comparison of the performance and accuracy of different inference methods, such as maximum likelihood (ML) and Bayesian inference, is difficult because the inference methods are implemented in different programs, often written by different authors. Both methods were implemented in the program MIGRATE, that estimates population genetic parameters, such as population sizes and migration rates, using coalescence theory. Both inference methods use the same Markov chain Monte Carlo algorithm and differ from each other in only two aspects: parameter proposal distribution and maximization of the likelihood function. Using simulated datasets, the Bayesian method generally fares better than the ML approach in accuracy and coverage, although for some values the two approaches are equal in performance. MOTIVATION: The Markov chain Monte Carlo-based ML framework can fail on sparse data and can deliver non-conservative support intervals. A Bayesian framework with appropriate prior distribution is able to remedy some of these problems. RESULTS: The program MIGRATE was extended to allow not only for ML(-) maximum likelihood estimation of population genetics parameters but also for using a Bayesian framework. Comparisons between the Bayesian approach and the ML approach are facilitated because both modes estimate the same parameters under the same population model and assumptions.

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    • "Historical and contemporary gene flow To estimate historical gene flow between the STRUCTURE clusters and between populations within each STRUCTURE cluster, we used the software package MIGRATE version 3.6 (Beerli, 2006) to estimate the effective number of migrants (2Nm, where N is the effective population size and m is the migration rate per generation ), assuming a migration matrix model with asymmetric migration rates and different population sizes. The MIGRATE software calculates maximum-likelihood (ML) estimates for both historical migration rates and effective population size between pairs of populations using a coalescent approach (Beerli and Felsenstein, 1999 "
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    • "For this reason we also use coalescent methods to estimate the historical population connectivity . Four possible models of gene flow were tested using Migrate-n v. 3.6 ( Beerli 2006) (see Supplementary Table A online). The marginal likelihood of the model was estimated followed by a ranking of the Bayes factor of each one (Beerli and Palczewski 2010). "
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    ABSTRACT: The Andean Altiplano has served as a complex setting throughout its history, driving dynamic processes of diversification in several taxa. We investigated phylogeographic processes in the Telmatobius marmoratus species complex occurring in this region by studying the geographic patterns of genetic variability, genealogies, and historical migration, using the cytochrome b (cyt-b) gene as a marker. DNA sequences from Telmatobius gigas and Telmatobius culeus, Bolivian species with an uncertain taxonomic status, were also included. Additionally, we evaluated the phylogenetic diversity (PD) represented within Chilean protected areas and the complementary contribution from unprotected populations. Phylogenetic reconstructions from 148 cyt-b sequences revealed 4 main clades, one of which corresponded to T. culeus. T. gigas was part of T. marmoratus clade indicating paraphyletic relationships. Haplotypes from Chilean and Bolivian sites were not reciprocally monophyletic. Geographic distribution of lineages, spatial Bayesian analysis, and migration patterns indicated that T. marmoratus displays a weaker geographic structure than expected based on habitat distribution and physiological requirements. Demographic and statistical phylogeography analyses pointed out to a scenario of recent population expansion and high connectivity events of a more recent age than the post Last Glacial Maximum, probably associated to more humid events in Altiplano. PD of T. marmoratus populations within protected areas represents 55.6% of the total estimated PD. The unprotected populations that would contribute the most to PD are Caquena and Quebe (21%). Recent evolutionary processes and paleoclimatic changes, potentially driving shifts in habitat connectivity levels and population sizes, could explain the phylogeographic patterns recovered herein. © The American Genetic Association 2015. All rights reserved. For permissions, please e-mail:
    The Journal of heredity 08/2015; 2015(S1):546-559. DOI:10.1093/jhered/esv039 · 2.09 Impact Factor
    • "Migrate/Migrate-n.html). As suggested in Beerli (2009), a Bayesian method was applied (Beerli 2006) and F ST estimates (h ST ) among localities were used as initial parameters for the calculation of Θ (= 4N e l, where N e is the effective population size and l is the mutation rate) and M (M = m/l, where m is the immigration rate per generation and l is the mutation rate). A Brownian motion model was used and mutation was considered constant over all loci. "
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    ABSTRACT: The transparent goby (Aphia minuta) is a small progenetic goby that displays a short life cycle with an early achievement of reproductive maturity and represents a valuable fishery resource harvested by artisanal fleets in most part of its distributional range. This study was aimed to define genetic variability in A. minuta at five sampling sites within the Mediterranean Sea and one in the Atlantic Ocean through the analysis of 11 nuclear microsatellite loci. Results revealed lower levels at several genetic diversity estimators (HE, HO, NA, RS) in the Atlantic Ocean than in the Mediterranean Sea suggesting the role of past or current demographic events to shape this pattern. The genetic structure was investigated using both classical genetic differentiation descriptors (θST) and Bayesian approaches (STRUCTURE), and defining the current (GENECLASS) and the past migration rates (MIGRATE). The results obtained revealed high genetic structure within the Mediterranean Sea and suggested very low current migration rate. The pattern of historical migration suggested the possible role of hydrographic boundaries to shape genetic structure identified in this species. In addition, the detection of loci under selection, among those analyzed, suggested also the possible implication of selective pressures that are acting on genes connected with the peculiar life cycle of this gobiid fish.
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