Evidence map›Paper›PMID 20667077›Full record

ArticleBMC bioinformatics2010

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

Jean-Marie Cornuet, Virgine Ravigné, Arnaud Estoup

Abstract read
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Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 183 papers.

0numbers the graph read from it
0cells of the map it votes in
183citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

183 citing papers in PubMed.

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  12. Variations in Genetic Diversity of Invasive SpeciesAnimals : an open access journal from MDPI · 2024
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123 more citing papers are in PubMed but not listed here.

4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Jean-Marie CornuetINRA, UMR CBGP (INRA/IRD/Cirad/Montpellier SupAgro), Campus international de Baillarguet, CS 30016, F-34988 Montferrier-sur-Lez cedex, France.
Virgine Ravigné
Arnaud Estoup

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundApproximate 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.

resultsWe 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.

conclusionsOur 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 http://www1.montpellier.inra.fr/CBGP/diyabc.

Indexed as

Biological EvolutionMicrosatellite RepeatsSoftwareAlgorithmsBase SequenceBayes TheoremCell NucleusComputer SimulationDNA, MitochondrialGenetics, PopulationHumansModels, GeneticDNA, Mitochondrial

Identifiers

PMID20667077
PMCPMC2919520

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.