SLiM workshops generally cover a broad set of topics across SLiM. First we cover foundational material:

• An introduction to SLiM
• The chromosome hierarchy
• The population hierarchy
• An overview of Eidos
• Demography
• Recombination
• SLiMgui features and shortcuts

Next come intermediate topics such as:

• Selective sweeps
• Callbacks I: fitness() callbacks
• Callbacks II: mateChoice() callbacks
• Callbacks III: modifyChild() callbacks
• Quantitative traits
• Non-Wright–Fisher models
• Separate sexes
• Modeling haploidy

And then at the end of the workshop we reach advanced topics such as:

• Continuous-space models
• Tree-sequence recording
• Nucleotide-based models
• Multispecies simulations
• Running SLiM at the command line

In the online version of the workshop, the pacing of the material is entirely up to you. It isn't recommended to skip material or jump around, especially toward the beginning, since the workshop is designed to build; if you skip ahead, you may find that you get lost because you're missing essential background information. A better idea, perhaps, is to do the workshop in order, but just stop when it gets to more advanced/obscure topics that don't interest you. One natural stopping point, if you just want a bare-bones introduction to SLiM's basic architecture, would be to stop at the end of the "foundational material" – i.e., after worksheet 8, or if you have no interest in learning about using SLiMgui, after worksheet 6. However, that would end before you get to the topic of callbacks, which are pretty central to SLiM if you want to make more than very basic models. So then another natural stopping point would be after worksheet 12 on modifyChild() callbacks. Once you reach that point, it's probably safer to skip ahead if a given topic really doesn't interest you; but be aware that even the later worksheets do sometimes introduce useful concepts and techniques that are unrelated to their focal topic. If you plan to write complex models in SLiM, then among the more advanced topics I would urge you to do #14, on non-Wright-Fisher models, and #19, on tree-sequence recording; these are topics that every serious SLiM modeler ought to understand, even if you decide not to take advantage of these features. Finally, if you plan to run SLiM at the command line, particularly with multiple jobs on a computing cluster, #23 is essential knowledge. Pretty much all the material is also in the SLiM manual, so you can cut the workshop short and learn the rest from the manual if that is better for you.

In-person, the last day of the workshop is generally mostly "open modeling" time – attendees can work on their own models, while asking questions and receiving help. Many attendees find this to be the most valuable part of the workshop, since they can put their new knowledge to work on their own research problems while receiving one-on-one guidance. On the last day there are also sometimes presentations from more experienced attendees on SLiM-related topics that are not otherwise covered in the workshop; in the past, for example, we have had presentations on ABC (Approximate Bayesian Computation) and machine learning using SLiM.

See the information for attendees for more information on how to apply, hardware and software requirements, etc.

See the SLiM home page for listings of upcoming workshops