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DOWNLOADS :

NEW : try the beta version (24)
Download the last stable release : DIYABC-v0.7.3.exe Download the beta release : DIYABC-v1.0.4.46beta.exe
Download the last stable documentation : DIYABC Documentation Download the beta documentation : DIYABC v1.0.4.46beta Documentation

The new version (V1.*) includes the following new features :

           
  • data files can include microsatellite and/or DNA sequence data,
  • five categories of loci are recognized : autosomal haploid, autosomal diploid, X-linked, Y-linked and mitochondrial. Note that X-linked loci can be used for haplo-diploid species (when both sexes have been sampled).
  • two options have been added : one for pre-evaluating model-prior combinations and the other one for checking model and posterior distributions,
  • multithread technology has been implemented to accelerate time-consuming computations when performed on multicore computers.

IMPORTANT NOTE : The reference table file format has been modified so that the new version is incompatible with reference tables obtained with the previous version.

The software DIYABC, as well as the companion notice and manuscript published in Bioinformatics are freely available on this site.

Registering (below) is optional and free. It gives you access to :
  • DIYABC forum where you can post questions to authors or other users, signal bugs, ...
  • the linux cluster version
  • the program sources
  • older (linux/windows) versions


Login  •  Register

Summary :

DIYABC is a computer program with a graphical user interface and a fully click-able environment. It allows population biologists to make 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. DIYABC 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).

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