slendr: A Simulation Framework for Spatiotemporal Population Genetics

slendrR Documentation

A Simulation Framework for Spatiotemporal Population Genetics


A framework for simulating spatially explicit genomic data which leverages real cartographic information for programmatic and visual encoding of spatiotemporal population dynamics on real geographic landscapes. Population genetic models are then automatically executed by the 'SLiM' software behind the scenes, using a custom built-in simulation 'SLiM' script. Additionally, fully abstract spatial models not tied to a specific geographic location are supported, and users can also simulate data from standard, non-spatial, random-mating models. These can be simulated either with the 'SLiM' built-in back-end script, or using an efficient coalescent population genetics simulator 'msprime' with a custom-built 'Python' script bundled with the R package. Simulated genomic data is saved in a tree-sequence format and can be loaded, manipulated, and summarised using tree-sequence functionality via an R interface to the 'Python' module 'tskit'. Complete model configuration, simulation and analysis pipelines can be therefore constructed without a need to leave the R environment, eliminating friction between disparate tools for population genetic simulations and data analysis.


You can find installation instructions, reference manual, and tutorials at


Maintainer: Martin Petr (ORCID)

See Also

Useful links:

slendr documentation built on June 22, 2024, 6:56 p.m.