This repository contains code to reproduce the results of the publication [1].
The code in this repository is also an extensive simulation environment for microbial evolutionary dynamics at microscopic granularity, and may be useful to the grander evolutionary dynamics community for follow-up investigations.
The folder py contains many useful routines for processing the output simulation data. Some of these are directly used for producing the publication figures, while others are useful for exploratory data analysis.
The main simulation package requires openmp, boost, and GSL; all can be installed using standard package managers.
On Mac, openmp is not supported by the default C++ compiled provided by XCode. The simplest way to proceed is to install gcc via a package manager such as homebrew and compile with the corresponding gcc binary.
The data analysis routines are written in Python and are built upon standard scientific Python libraries (numpy, scipy, matplotlib, etc.). numba is also used to accelerate some computations; it can be installed using pip or conda.
The simulation package can be compiled by running make.
The executable lenski_main can be use to run a microbial evolution experiment in-silico. By default it splits replicate simulations over all available threads. If you want to use less threads, cap the number of threads using the OMP_NUM_THREADS environment variable.
The executables lenski_vary_epi and lenski_vary_clonal may be used to reproduce the results of the eLife publication, sweeping over the strength of epistasis and the strength of clonal interference.
If you found the code in this repository useful, please cite the corresponding paper
[1] Boffi Nicholas M., Guo Yipei, Rycroft Chris H., Amir Ariel (2023) How microscopic epistasis and clonal interference shape the fitness trajectory in a spin glass model of microbial long-term evolution eLife 12:RP87895 https://doi.org/10.7554/eLife.87895.1
@article{m_how_2023,
title = {How microscopic epistasis and clonal interference shape the fitness trajectory in a spin glass model of microbial long-term evolution},
volume = {12},
url = {https://elifesciences.org/reviewed-preprints/87895},
doi = {10.7554/eLife.87895},
journal = {eLife},
author = {M, Boffi Nicholas and Yipei, Guo and H, Rycroft Chris and Ariel, Amir},
month = jun,
year = {2023}
}