Modified version od ∂a∂i, allowing the use of the dadi.Inference.optimize_anneal for the simulated annealing approach.

This modified version includes the 26 demographic models of divergence used in Rougeux et al. (2017) and in Rougeux et al. (2019) available in modeldemo_mis_new_models.

Please cite this paper if you use demographic models from implemented scripts:
Rougeux, C., Bernatchez, L., & Gagnaire, P.-A. (2017). Modeling the Multiple Facets of Speciation-with-Gene-Flow toward Inferring the Divergence History of Lake Whitefish Species Pairs (Coregonus clupeaformis). Genome Biology and Evolution, 9(8), 2057–2074.

dadi is a powerful method for fitting demographic models to genetic data.

Binary installers are available for OS X and Windows. If you use a binary installer, we still suggest downloading the source, so as to get the documentation, examples and tests.

To install from source, simply run python setup.py install. After that, run a (growing) series of tests on the installation. Change to the tests directory and run python run_tests.py Usage examples are found under the examples directory.

To run this pipeline, put your frequency spectrum into the /Dadi_studied_model/01_Data/ and run the desired models by adjusting scripts to your data from the /Dadi_studied_model/00_inference/ directory. Have fun!