ABCtoolbox: a versatile toolkit for approximate Bayesian computations.

Détails

Ressource 1Télécharger: BIB_C966F74A3943.P001.pdf (620.91 [Ko])
Etat: Public
Version: Final published version
ID Serval
serval:BIB_C966F74A3943
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
ABCtoolbox: a versatile toolkit for approximate Bayesian computations.
Périodique
BMC Bioinformatics
Auteur⸱e⸱s
Wegmann D., Leuenberger C., Neuenschwander S., Excoffier L.
ISSN
1471-2105[electronic], 1471-2105[linking]
Statut éditorial
Publié
Date de publication
2010
Volume
11
Numéro
1
Pages
116
Langue
anglais
Résumé
BACKGROUND: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. RESULTS: Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. CONCLUSION: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.
Mots-clé
Animals, Arvicolinae/genetics, Bayes Theorem, Evolution, Molecular, Female, Genetics, Population, Male, Microsatellite Repeats/genetics, Software
Pubmed
Web of science
Open Access
Oui
Création de la notice
23/02/2010 8:51
Dernière modification de la notice
20/08/2019 15:44
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