Simulated genetic data in a hierarchical metapopulation structure

The data are linked to a research article entitled: “Interactions between microenvironment, selection and genetic architecture drive multiscale adaptation in a simulation experiment” in Journal of Evolutionary Biology (see References).

In this research on multiscale adaptation, we simulated a hierarchical metapopulation structure with four populations, two environments per population and three patches per environment, in a two-step procedure:

an initialization step without selection, with eight combinations of mutation type, selfing rate and QTL number parameters (2 modes each); out of 200,000 simulated generations in each case, we chose one with appropriate characteristics as a starting point for the next step;

a selection step with all possible combinations of the following parameters: environmental pattern (4 modes), environmental range (5 modes), selection intensity (4 modes), fecundity (3 modes).

This resulted in 240 scenarios for each initialized metapopulation, i.e. 1,920 scenarios in total. Each scenario was replicated 10 times, i.e. 19,200 simulation runs.

The archive includes all data needed to reproduce the simulations and analyses, or to re-use the simulated metapopulations for other analyses. It has the following structure (further detailed below):

NemoScripts directory contains the Nemo input files used to perform simulations for the initialization step and the selection step;

RScripts directory contains the R scripts to read the Nemo output files, compute synthetic variables(*), and produce the figures as they appear in the publication and supplementary material (*: long computations, therefore we also directly provide those synthetic variables in the Data directory);

Data directory contains the Nemo output files, the synthetic variables, and other data needed to reproduce the figures; this directory can be used as a working directory for the R scripts (recommended).

Running the following command in a terminal tar –xzvf Archive_PC_SOM_IS_FL.tar  will create a directory named Archive_PC_SOM_IS_FL, which detailed content is described in the README.pdf file.
Warning: the extracted archive is large (460Go, >40,000 files) and extraction may take some time.