Hi all! Back in April 2016, I wrote a post about SLiM 2.0, a software package that I've developed in collaboration with Philipp Messer at Cornell. SLiM 2 runs genetically-explicit individual-based simulations of evolution, on the Mac or on Linux, either at the command line or (on the Mac) in an interactive graphical modelling environment (great for teaching and labs!). SLiM 2 is scriptable, with an R-like scripting language, making it extremely flexible; the manual for SLiM 2 has dozens of example "recipes" for different types of models that can be implemented in SLiM, including genetic structure, population structure, complex types of selection, complex mating systems, and complex temporal model structure. Even relatively complex models (quantitative genetics models backed by explicit loci, kin selection and green-beard models, models of behavioral interactions between individuals, models of social learning, etc.) can be written with just a few lines of script. And yet despite all this flexibility, it's also quite fast, and it works well on computing clusters if you have projects with long runtimes.
What I'm announcing today is that our paper on SLiM 2 has now been published online by Molecular Biology and Evolution. This paper introduces the software and provides an interesting model as an example (a CRISPR/Cas9-based gene drive in an stepping-stone island model with spatial variation in selection acting on the drive allele). It also provides performance comparisons with other forward genetic simulation packages (SFS_CODE and fwdpp). If you're interested in SLiM, this paper is a good place to start; and if you're already using SLiM, it's now the correct paper to cite, not Philipp's 2013 paper on SLiM 1.0.
If you're got questions or feedback about SLiM 2 you can either contact me by email (bhaller squiggly mac point com), or you can post on SLiM's discussion list, slim-discuss. Enjoy!
Haller, B.C., & Messer, P.W. (2016.) SLiM 2: Flexible, interactive forward genetic simulations. Molecular Biology and Evolution (advance access). DOI: 10.1093/molbev/msw211