slendr

slendr leverages real cartographic information to simulate spatially-explicit genomic data and model spatiotemporal population dynamics.

Key Features:

• Spatial population encoding: Users programmatically and visually encode spatial population ranges and their temporal dynamics, including population displacements, expansions, and contractions.
• Real and abstract landscapes: Simulations run on real Earth landscapes or on abstract custom maps.
• Population events: Splits and gene-flow events between populations are scheduled using a declarative language.
• Non-spatial model support: slendr simulates data from traditional, non-spatial models using either a SLiM simulation back-end script or an alternative built-in coalescent msprime back end.
• Tree-sequence integration: An R-idiomatic interface to the tskit library enables tree-sequence processing and analysis.

Scientific Applications:

• Spatio-temporal population genetics: Building and evaluating complex spatio-temporal population genetic models that incorporate isolation by distance, local mate choice, or uneven distribution of resources.
• Geospatial evolutionary analysis: Performing efficient, reproducible simulations of spatio-temporal genomic data entirely within the R environment, leveraging its libraries for geospatial data analysis, statistics, and visualization.

Methodology:

slendr implements simulations in R with a SLiM simulation back-end script bundled with the package, and provides an alternative built-in coalescent msprime back end for non-spatial models.