Stochastic Models for the Inference of Life Evolution

Simulation of bacterial populations with SLiM

Cury, J., Haller, B. C., Achaz, G., Jay, F.

Peer Community Journal


Simulation of genomic data is a key tool in population genetics, yet, to date, there is no forward-in-time simulator of bacterial populations that is both computationally effi- cient and adaptable to a wide range of scenarios. Here we demonstrate how to simulate bacterial populations with SLiM, a forward-in-time simulator built for eukaryotes. SLiM has gained many users in recent years, due to its speed and power, and has extensive documentation showcasing various scenarios that it can simulate. This paper focuses on a simple demographic scenario, to explore unique aspects of modeling bacteria in SLiM’s scripting language. In addition, we illustrate the flexibility of SLiM by simulating the growth of bacteria on a Petri dish with antibiotic. To foster the development of bac- terial simulations based upon this recipe, we explain the inner workings of its code. We also validate the simulator, by extensively testing the results of simulations against ex- isting simulators, and against theoretical expectations for some summary statistics. This protocol, with the flexibility and power of SLiM, will enable the community to simulate bacterial populations efficiently under a wide range of evolutionary scenarios.


title={Simulation of bacterial populations with SLiM},
author={Cury, Jean and Haller, Benjamin C and Achaz, Guillaume and Jay, Flora},
journal={Peer Community Journal},

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