It is currently Thu Oct 30, 2014 12:11 pm


DIYABC v2.0.4 DOWNLOADS :

Download the windows 32/64 release : diyabc-2.0.4-win32.zip
Download the OS X release : diyabc-2.0.4-mac.dmg
Download the linux 32 release : diyabc-2.0.4-linux32.zip
Download the linux 64 release : diyabc-2.0.4-linux64.zip
Download thenotice document: Notice_DIYABC_v2.0.4.pdf


DIYABC v1.0.4.46 beta DOWNLOADS :

Download the windows release : DIYABC-v1.0.4.46beta.exe
Download the notice document: DIYABC v1.0.4.46beta Documentation

Recommendations for beta version v1.0.4.46 :

           
  • We do not have the capacity to ensure any technical support (i.e. bug corrections or developments) of the presently available version of DIYABC-v1.0.4.46beta. We apologize for this inconvenience. You nevertheless can still use the forum to exchange ideas and advises,
  • We found that the cluster version of DIYABC-v1.0.4.46beta to be very unstable,
  • We found that the Microsoft Windows version of DIYABC-v1.0.4.46beta with graphical interface to be unstable in a Microsoft Windows 7 environment (cf. occurrence of unexplained bugs in this environment). DIYABC-v1.0.4.46beta should be hence preferentially used in a Microsoft Windows XP environment,
  • The reference table file format has been modified so that DIYABC v1.x.x is incompatible with reference tables obtained with the old v.0.xx versions.


The software DIYABC, as well as the companion notice, papers and full examples of DIYABC v2 projects are freely available on this site.

Registering (below) is optional and free. It gives you access to :
  • DIYABC v2 and v1 forums where you can post questions, signal caveats, ...
  • Some full examples of DIYABC v2 projects
  • the program sources and binaries
  • older versions


Login  •  Register

Summary :

DIYABC allows considering complex population histories involving any combination of population divergences, admixtures and population size changes, with population samples potentially collected at different times. DIYABC can be used to compare competing evolutionary scenarios and quantify their relative support, and estimate parameters for one or more scenarios. Eventually, it provides a way to evaluate the amount of confidence that can be put into the various estimations and to achieve model checking computation within an approximate Bayesian computation (ABC) framework. The version 2.0 of the program implements a number of new features and analytical methods allowing extensive analyses of large molecular datasets, including single nucleotide polymorphism (SNP) data.

Screenshot 1 Screenshot 1bis
Screenshot 2 Screenshot 3


Who is online

In total there are 2 users online :: 0 registered, 0 hidden and 2 guests (based on users active over the past 5 minutes)
Most users ever online was 494 on Sun Dec 22, 2013 3:17 pm

Registered users: No registered users
Legend: Administrators, Global moderators, Registered users

Statistics

Total posts 522 • Total topics 281 • Total members 1417 • Our newest member penaloza_x

cron