Code for "A PDE Model for Protocell Evolution and the Origin of Chromosomes via Multilevel Selection"

This repository accompanies the preprint "A PDE Model for Protocell Evolution and the Origin of Chromosomes via Multilevel Selection", by Daniel B. Cooney, Fernando W. Rossine, Dylan H. Morris, and Simon A. Levin. It includes all of the scripts used to compute numerical finite volume simulations of the dimorphic and trimorphic multilevel selection models and to generate all of the figures in the paper. The repository also includes all of the figures from the paper, as well as the data produced by numerical simulations that require the use of additional scripts for generating figures.

The repository is organized into the following folders: Scripts, Simulation_Outputs, and Figures. All of the scripts can be run using Python 2.7.

The main Python scripts used to compute numerical finite volume simulations are fv_protocell.py (for the dimorphic multilevel competition) and fvfsdtrimorphicdynamics.py (for the trimorphic dynamics). Additional simulations were run in the dimorphic case to compare with analytically calculated steady states in etasteadyfv.py, and additional simulations of the trimorphic multilevel dynamics were run in loopfvtrimorphic.py and etaloopfvtrimorphic.py to generate data for numerical solutions as a function of the relative strength of between-protocell selection and the complementarity of the fast and slow genes, respectively.

For reference, below is a list of figures and the scripts and simulation output files that were used to generate each figure.

• Figure 2.1: Run Gofxfs.py
• Figure 2.2: Run etamodeldensities.py
• Figure 2.3: Run etapeak.py
• Figure 3.1: Run withintrimorphic.py
• Figure 3.2: Run fvfsdtrimorphicdynamics.py for each value of the parameter eta
• Figure 4.1: Run Gofzfd.py
• Figure 4.2: Run fastdimerdensities.py
• Figure 4.3: Run fvprotocell.py with FS and FD options
• Figure 4.4: Run FSvsFDprotocellfitness.py
• Figure 4.5: Run FSvsFDlargelambdacomparison.py
• Figure 4.6: Run etasregimes.py
• Figure 4.7: Run Gofzsd.py
• Figure 4.8: Run slowdimerpeakplot.py
• Figure 5.1: Run fvfsdtrimorphicdynamics.py with "quantity = trajectories"
• Figure 5.2: Run fvfsdtrimorphicdynamics.py to generate data, then run avgGintime.py
• Figure 5.3: Run fvfsdtrimorphicdynamics.py with "quantity = steady"
• Figure 5.4: Run loopfvtrimorphic.py to generate data, then run Gplottrimorphic.py
• Figure 5.5: Run loopfvtrimorphic.py to generate data, then run peakmeantrimorphic.py
• Figure 5.6: Run etaloopfvtrimorphic.py
• Figure B.1: Run etasteadyfv.py with "edge = FS"
• Figure B.2: Run etasteadyfv.py with "edge = FD"