This project is intended to provide a test case for Matt Osmond's sparg software, which estimates dispersal rates and locates genetic ancestors with genome-wide genealogies.
First, we created an individual-based forward simulation roughly approximating the demographic history of A. thaliana, as per Fulgione and Hancock (2018), coded up using the R-package slendr and the forward simulation software SLiM. The genomes of the present day populations were then sampled throughout the population ranges and analyzed on Python, using sparg, to infer the dispersal rate and origin of the ancestors. This was then compared to the actual dispersal rate and origin used to model the populations, giving us an idea of how well sparg performs on genomes sampled from populations with complex histories.
The R script used to set up the basic geographical boundaries and population dynamics can be found in the home directory. The files in the model directory generated by this R script can be found in model/. Note that there are two SLiM scripts provided here: script_original.slim is the default backend skeleton script that slendr uses to run the forward simulations on SLiM, and script.slim is the edited SLiM script (see below) that can be run from the command line (without needing to use slendr) using a dedicated bash script.
The SLiM script generated by this code does not capture the selfing behavior of A. thaliana, so we next wrote a bash script that edits the SLiM script to get the behavior we want.
Since slendr is not available on CRAN yet, installing it on a cluster is somewhat tedious. Thus, we wanted a simple bash script that uses the model directory and the edited SLiM script to do what the slim() function would do in slendr - given some parameter values, run the simulation and output the tree sequence of sampled individuals at the end.
These bash scripts can be found in bash/.
To be completed.
To be completed.
- Fulgione, A. and Hancock, A.M. (2018), Archaic lineages broaden our view on the history of Arabidopsis thaliana. New Phytol, 219: 1194-1198. https://doi.org/10.1111/nph.15244