ABCtoolbox: a versatile toolkit for approximate Bayesian computations
Open Access
- 4 March 2010
- journal article
- Published by Springer Science and Business Media LLC in BMC Bioinformatics
- Vol. 11 (1), 116
- https://doi.org/10.1186/1471-2105-11-116
Abstract
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. 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. 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.Keywords
This publication has 28 references indexed in Scilit:
- Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and WindowsMolecular Ecology Resources, 2010
- Bayesian Computation and Model Selection Without LikelihoodsGenetics, 2010
- Efficient Approximate Bayesian Computation Coupled With Markov Chain Monte Carlo Without LikelihoodGenetics, 2009
- Automating approximate Bayesian computation by local linear regressionBMC Genomic Data, 2009
- Inferring population history withDIY ABC: a user-friendly approach to approximate Bayesian computationBioinformatics, 2008
- Fregene: Simulation of realistic sequence-level data in populations and ascertained samplesBMC Bioinformatics, 2008
- SeqAn An efficient, generic C++ library for sequence analysisBMC Bioinformatics, 2008
- Using Likelihood-Free Inference to Compare Evolutionary Dynamics of the Protein Networks of H. pylori and P. falciparumPLoS Computational Biology, 2007
- Sequential Monte Carlo without likelihoodsProceedings of the National Academy of Sciences of the United States of America, 2007
- Mitochondrial gene diversity in the common vole Microtus arvalis shaped by historical divergence and local adaptationsMolecular Ecology, 2004