Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation

By Jean-Marie Cornuet, Filipe Santos, MARK A. Beaumont, Christian P. Robert, Jean-Michel Marin, David J. Balding, Thomas Guillemaud, Arnaud Estoup. Bioinform., 2008

726 citations recorded by the source corpus.

Summary: Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC. Availability: The software DIY ABC is freely available at http://www.montpellier.inra.fr/CBGP/diyabc. Contact: j.cornuet@imperial.ac.uk Supplementary information: Supplementary data are also available at http://www.montpellier.inra.fr/CBGP/diyabc

Subfields: Genetics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/b329cd78191b3f0aa72ba733d1e5f26214713756

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Citations in the corpus

Efficient ancestry and mutation simulation with msprime 1.0 (2021, methodology): “…and methods avoid the bottleneck of parsing text-based file formats to compute these statistics by either developing their own simulators ( e.g ., Cornuet et al. 2008; Lopes et al. 2009) or creating forked versions ( i.e ., modified copies) of existing simulators ( e.g ., Thornton and Andolfatto…”
Bayesian computation: a perspective on the current state, and sampling backwards and forwards (2015, methodology): “Similarly, ABC software is either too speciﬁc, like DIYABC (Cornuet et al. 2008) which addresses only population genetic questions, or too dependent on the ability of the modeller to program simulated outcomes from the model under study.”
Approximate Bayesian computational methods (2011, methodology): “This modeling clearly brings some further stability to the above estimate of π( M = m | y ) and is implemented in the DIYABC software described in Cornuet et al. (2008).”
Approximate Bayesian Computation in Evolution and Ecology (2010, methodology): “…edu/group/hadlylab/ssc/index.html DIYABC This program has a ‘point and click’ interface, allowing the user to build up relatively complex demographic models, for genealogical simulation, which are then analyzed using regression-based ABC, allowing also for model choice (Cornuet et al. 2008).”
Adaptive Multiple Importance Sampling (2009, methodology): “Five data files have been simulated with the software DIYABC (Cornuet et al., 2008), with the following parameter values: n1 =nAnc =10,000, n2 =2000, tdiv =1000 and =0.0005, leading to 1 = A =20, 2 =4 and =0.5.”
Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0) (2010, methodology): “Cornuet et al. [ 26 ] developed the software DIYABC in which a user-friendly interface helps non-expert users to perform historical inference using ABC.”
Phylogeography's past, present, and future: 10 years after Avise, 2000. (2010, methodology): “These ‘‘likelihood-free” ABC methods can approximate the posterior distribution of parameters thereby accomplishing estimation of parameters under an array of complex biogeographic scenarios by simulating data from a coalescent model using parameter values that are randomly drawn from the prior dist”
Adaptive approximate Bayesian computation (2008, methodology): “In this experiment, several simulated datasets have been produced using the software developed by Cornuet et al. (2008), with the following parameter values: N1 = Nanc = 10, 000, N2 = 2, 000, tdiv = 1, 000 and µ = 0 · 0005, out of which one is presented in this paper, but identical conclusions were…”
Constructing summary statistics for approximate Bayesian computation: semi‐automatic approximate Bayesian computation (2012, methodology): “Recently software has been developed to help to implement ABC within population genetics (Cornuet et al., 2008; Lopes et al., 2009) and systems biology (Liepe et al., 2010).”
ABCtoolbox: a versatile toolkit for approximate Bayesian computations (2010, methodology): “In complement to available ABC packages [15-17], ABCtoolbox incorporates several ABC algorithms, handles various types of data by interacting with external simulation programs and includes tools to rigorously validate estimations, a necessary step of any Bayesian inference.”
Do cities represent sources, sinks or isolated islands for urban wild boar population structure? (2017, methodology): “…was considered equally probable, and reliability of scenarios was visualized through principal component analysis, whereby posterior probabilities of scenarios were compared by means of logistic regression, using the closest 1% of simulated data sets to the observed data (Cornuet et al. 2008).”
The global spread of Harmonia axyridis (Coleoptera: Coccinellidae): distribution, dispersal and routes of invasion (2011, methodology): “Interestingly, new DIYABC analyses of microsatellite data, taking into account the above genetic structure within the native range, indicated that populations from western Asia also contributed in a significant manner to the invasive bridgehead population located in eastern North America (E. Lombaer”