An individual-based evolutionary simulation of the transcription-supercoiling coupling at the whole genome scale.

First, install the required packages (preferably inside a virtual environment):

pip install -r requirements.txt

To run an experiment with the default parameters, just run:

python3 path/to/evotsc_run.py -o `output_folder` -n `final_generation`

You can change parameter values at the top of the evotsc_run.py file.

Simulations can be seamlessly restarted at the last checkpoint (either at the end of a run or after a crash), by running the exact same command again, and completed runs can be extended by passing a larger final_generation argument.

The seed used for each simulation is output in the output_folder/params.txt file.

To reproduce a run, you can pass the seed to the program with the -s SEED parameter.

EvoTSC is licensed under the 3-clause BSD licence, including all Python source files as well as notebooks.

The exact code used for the PLOS Computational Biology paper, as well as the Jupyter notebooks analyzing the resulting data, can be found in the ploscb branch.

The exact code used for the bioRxiv preprint peer-reviewed at PCI Math Comp Biol, as well as the Jupyter notebooks analyzing the resulting data, can be found in the pci branch.

The exact code used for the simulations in Chapters 6 and 7 of my PhD thesis, as well as the Jupyter notebooks analyzing the resulting data, can be found in the phd branch.

The exact code used for the simulations in the Artificial Life journal paper (corresponding to Chapter 4 of my PhD thesis), as well as the Jupyter notebooks analyzing the resulting data, can be found in the alife-journal branch.

The exact code used for the simulations in the Alife21 conference paper, as well as the Jupyter notebooks analyzing the resulting data, can be found in the alife-model branch.