simuPOP

simuPOP is a Python-based environment that enables you to simulate various theories about the evolution of the population. Considering that Python is a dynamic and object-oriented programming language, it is an appropriate environment for simulations in biology and consequentially, for the general-purpose of the application.

General-purpose in this case refers to replicating evolutionary processes that are more or less arbitrary. In fact, the program can help you manage a plethora of variables to the very detail, including but not limited to utterly controlled mating schemes, customized chromosome types, mutations, recombination, migration, size changes, so on and so forth.

The application comes with over 70 operators that can cover most aspects of genetic studies. The operators are Python objects that act on a given population and that can be applied before, after and during a life cycle. Examples of operators include k-allele and context sensitive mutation models, uniform and nonuniform gene conversion models, multiplicative or hybrid multi-locus models, nuclear and large Pedigrees ascertainment, etc.

You should know that the program's core is implemented in C++, an environment that can support large-scale simulations. Then again, thanks to the interactive interface, you can define custom genetic effects in Python and test out a wide variety of evolution processes at a finer scale.

It is important to note that the maximum population that you can use in the simulation is only restricted by the RAM memory of your computer, the number of cores and the speed of the processor. As you probably guessed, the higher the aforementioned specifications, the more scalable your simulation in simuPOP.