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Citations per year

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DIYABC specifications


Unique identifier OMICS_02197
Alternative name Do It Yourself Approximate Bayesian Computation
Software type Package/Module
Interface Graphical user interface
Restrictions to use Academic or non-commercial use
Operating system Unix/Linux, Mac OS, Windows
Programming languages C++
Computer skills Medium
Version 2.1.0
Stability Stable
Maintained Yes




No version available



  • person_outline Arnaud Estoup

Publications for Do It Yourself Approximate Bayesian Computation

DIYABC citations


Full Mitogenomes in the Critically Endangered Kākāpō Reveal Major Post Glacial and Anthropogenic Effects on Neutral Genetic Diversity

PMCID: 5924562
PMID: 29671759
DOI: 10.3390/genes9040220

[…] tive population size (Nef).Finally, we tested for competing bottleneck models and estimated values of demographic parameters using an approximate Bayesian computation (ABC) approach [] implemented in DIYABC 2.1.0 []. We first tested three general models: (1) ‘constant population size through time’; (2) ‘postglacial expansion’; (3) ‘postglacial expansion and recent bottleneck’. We used wide priors […]


DNA barcoding unravels contrasting evolutionary history of two widespread Asian tiger moth species during the Late Pleistocene

PLoS One
PMCID: 5884489
PMID: 29617397
DOI: 10.1371/journal.pone.0194200

[…] an population, but the scenario 1-CG suggests more ancient divergence times (). These demographic scenarios were simulated for comparison using an approximate Bayesian computation (ABC) approach with DIYABC v. 2.1.0 software [,]. The primary sequence data set included three samples of Creatonotos gangis sequences: (i) Southeast Asia (N = 20); (ii) Arabia and South Asia (N = 20); and (iii) Australi […]


Hybridization and differential introgression associated with environmental shifts in a mistletoe species complex

Sci Rep
PMCID: 5882953
PMID: 29615778
DOI: 10.1038/s41598-018-23707-6
call_split See protocol

[…] 8 × 105 years ago. The effective size (N) of the corresponding populations (Pops 1, 2, 3 or the ancestral population) during each time period (e.g., 0–t1, t1–t2) was set to a maximum of 30000.We used DIYABC 2.1 to simulate ten million datasets (2 million per scenario) with the same number of populations, loci and individuals. The most likely scenario was evaluated by comparing posterior probabilit […]


ABrox—A user friendly Python module for approximate Bayesian computation with a focus on model comparison

PLoS One
PMCID: 5843277
PMID: 29518130
DOI: 10.1371/journal.pone.0193981

[…] the R-package abc [] or the Python module ABC-SysBio [] are the domain-independence, meaning that it is not designed for a specific field of research, and its ease of use due to the GUI. The software DIYABC [] is another attempt at simplifying the use of ABC by providing a GUI for experimental biologists. DIYABC provides a convenient way to conduct ABC inferences about population history using SNP […]


Genetic Diversity and Domestication Footprints of Chinese Cherry [Cerasus pseudocerasus (Lindl.) G.Don] as Revealed by Nuclear Microsatellites

Front Plant Sci
PMCID: 5835088
PMID: 29535750
DOI: 10.3389/fpls.2018.00238

[…] DIYABC v2.1.0 software () was used to compare different domestication history models and estimate historical parameters in this study. The Generalized Stepwise Mutation model (GSM) was chosen in DIYAB […]


Comparative phylogeography of Aedes mosquitoes and the role of past climatic change for evolution within Africa

Ecol Evol
PMCID: 5838080
PMID: 29531714
DOI: 10.1002/ece3.3668

[…] (10,000–14,000,000 individuals) encompassing values based on estimates of Ɵ calculated in DNAsp v5 and LAMARC as described above. For both Ae. bromeliae and Ae. lilii datasets, the simulation program DIYABC v2.0.4 (Cornuet, Ravigne, & Estoup, ) was used to analyze both nuclear loci together in the same analysis and to analyze mitochondrial COI sequences separately. In addition, the sequence data o […]

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DIYABC institution(s)
Inra, UMR1062 cbgp, Montpellier, France; Université Montpellier 2, UMR CNRS 5149, I3M, Montpellier, France; Institut de Biologie Computationnelle (IBC), Montpellier, France; CNRS-UM2, Institut de Biologie Computationnelle, LIRMM, Montpellier, France
DIYABC funding source(s)
Supported by French Agence Nationale de la Recherche (ANR-09- BLAN-0145-01), Inra-Jeune Equipe IGGiPop, CBGP HPC computational platform and NUMEV Labex.

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