Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0)

<p>Abstract</p> <p>Background</p> <p>Approximate Bayesian computation (ABC) is a recent flexible class of Monte-Carlo algorithms increasingly used to make model-based inference on complex evolutionary scenarios that have acted on natural populations. The software DIYABC...

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Main Authors: Estoup Arnaud, Ravigné Virgine, Cornuet Jean-Marie
Format: Article
Language:English
Published: BMC 2010-07-01
Series:BMC Bioinformatics
Online Access:http://www.biomedcentral.com/1471-2105/11/401
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spelling doaj-17dcbb5bd22343c39eeea55ad3ed14632020-11-24T23:28:06ZengBMCBMC Bioinformatics1471-21052010-07-0111140110.1186/1471-2105-11-401Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0)Estoup ArnaudRavigné VirgineCornuet Jean-Marie<p>Abstract</p> <p>Background</p> <p>Approximate Bayesian computation (ABC) is a recent flexible class of Monte-Carlo algorithms increasingly used to make model-based inference on complex evolutionary scenarios that have acted on natural populations. The software DIYABC offers a user-friendly interface allowing non-expert users to consider population histories involving any combination of population divergences, admixtures and population size changes. We here describe and illustrate new developments of this software that mainly include (i) inference from DNA sequence data in addition or separately to microsatellite data, (ii) the possibility to analyze five categories of loci considering balanced or non balanced sex ratios: autosomal diploid, autosomal haploid, X-linked, Y-linked and mitochondrial, and (iii) the possibility to perform model checking computation to assess the "goodness-of-fit" of a model, a feature of ABC analysis that has been so far neglected.</p> <p>Results</p> <p>We used controlled simulated data sets generated under evolutionary scenarios involving various divergence and admixture events to evaluate the effect of mixing autosomal microsatellite, mtDNA and/or nuclear autosomal DNA sequence data on inferences. This evaluation included the comparison of competing scenarios and the quantification of their relative support, and the estimation of parameter posterior distributions under a given scenario. We also considered a set of scenarios often compared when making ABC inferences on the routes of introduction of invasive species to illustrate the interest of the new model checking option of DIYABC to assess model misfit.</p> <p>Conclusions</p> <p>Our new developments of the integrated software DIYABC should be particularly useful to make inference on complex evolutionary scenarios involving both recent and ancient historical events and using various types of molecular markers in diploid or haploid organisms. They offer a handy way for non-expert users to achieve model checking computation within an ABC framework, hence filling up a gap of ABC analysis. The software DIYABC V1.0 is freely available at <url>http://www1.montpellier.inra.fr/CBGP/diyabc</url>.</p> http://www.biomedcentral.com/1471-2105/11/401
collection DOAJ
language English
format Article
sources DOAJ
author Estoup Arnaud
Ravigné Virgine
Cornuet Jean-Marie
spellingShingle Estoup Arnaud
Ravigné Virgine
Cornuet Jean-Marie
Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0)
BMC Bioinformatics
author_facet Estoup Arnaud
Ravigné Virgine
Cornuet Jean-Marie
author_sort Estoup Arnaud
title Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0)
title_short Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0)
title_full Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0)
title_fullStr Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0)
title_full_unstemmed Inference on population history and model checking using DNA sequence and microsatellite data with the software DIYABC (v1.0)
title_sort inference on population history and model checking using dna sequence and microsatellite data with the software diyabc (v1.0)
publisher BMC
series BMC Bioinformatics
issn 1471-2105
publishDate 2010-07-01
description <p>Abstract</p> <p>Background</p> <p>Approximate Bayesian computation (ABC) is a recent flexible class of Monte-Carlo algorithms increasingly used to make model-based inference on complex evolutionary scenarios that have acted on natural populations. The software DIYABC offers a user-friendly interface allowing non-expert users to consider population histories involving any combination of population divergences, admixtures and population size changes. We here describe and illustrate new developments of this software that mainly include (i) inference from DNA sequence data in addition or separately to microsatellite data, (ii) the possibility to analyze five categories of loci considering balanced or non balanced sex ratios: autosomal diploid, autosomal haploid, X-linked, Y-linked and mitochondrial, and (iii) the possibility to perform model checking computation to assess the "goodness-of-fit" of a model, a feature of ABC analysis that has been so far neglected.</p> <p>Results</p> <p>We used controlled simulated data sets generated under evolutionary scenarios involving various divergence and admixture events to evaluate the effect of mixing autosomal microsatellite, mtDNA and/or nuclear autosomal DNA sequence data on inferences. This evaluation included the comparison of competing scenarios and the quantification of their relative support, and the estimation of parameter posterior distributions under a given scenario. We also considered a set of scenarios often compared when making ABC inferences on the routes of introduction of invasive species to illustrate the interest of the new model checking option of DIYABC to assess model misfit.</p> <p>Conclusions</p> <p>Our new developments of the integrated software DIYABC should be particularly useful to make inference on complex evolutionary scenarios involving both recent and ancient historical events and using various types of molecular markers in diploid or haploid organisms. They offer a handy way for non-expert users to achieve model checking computation within an ABC framework, hence filling up a gap of ABC analysis. The software DIYABC V1.0 is freely available at <url>http://www1.montpellier.inra.fr/CBGP/diyabc</url>.</p>
url http://www.biomedcentral.com/1471-2105/11/401
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