Understanding and leveraging phenotypic plasticity during metastasis formation - Code

This repo contains the code from the manuscript "Understanding and leveraging phenotypic plasticity during metastasis formation" by Shah et al. See the `README.md` for installation and usage.

 

# Modeling phenotypic plasticity

This README explains the simulations for the manuscript "Understanding and leveraging phenotypic plasticity during metastasis formation". The dataset can be found [here](https://doi.org/10.5281/zenodo.7989753).

Authors: Saumil Shah, Lisa-Marie Philipp, Stefano, Giaimo, Susanne Sebens, Arne Traulsen, Michael Raatz

## Table of Contents

- [Installation](#installation)

- [Usage](#usage)

- [Support](#support)

- [Contributing](#contributing)

- [License](#license)

## Installation

This project runs on python 3. One can obtain a python from the [official website](#https://www.python.org/downloads/) or [`conda`](https://docs.conda.io/projects/conda/en/latest/user-guide/install/download.html#anaconda-or-miniconda), a popular distribution suitable for science. We recommend a more robust alternative for `conda`, [`mamba`](https://mamba.readthedocs.io/en/latest/installation.html).

Please make sure you have the following python packages installed:

- `numpy`

- `scipy`

- `matplotlib`

For `mamba`, run the following in terminal `mamba install numpy scipy matplotlib`.

This project assumes the following directory structure and all the scripts read/write accordingly. All the python scripts, with the extension `.py`, go into the `code` folder.

```sh

.

├── code

├── data

│ ├── base

│ ├── ext1

│ └── ext2

└── figures

├── base

├── ext1

└── ext2

```

## Usage

### description

The script `draft.py`, provided here, allows reproducing all the figures in the main text and supplementary using simulation data found [here](https://doi.org/10.5281/zenodo.7989753). The script `utility.py` has an implementation of the model and a definition of all the model parameters, allowing independent exploration of the model. Some useful functions for plotting are defined in `plotting.py`. The `fig_*.py` scripts contain functions to plot figures in the [manuscript](https://www.biorxiv.org/content/10.1101/2022.11.07.515430v2). Script `draft.py` is a script that calls functions from `fig_*.py` scripts.

### saving plots

To save the plots, change `show` to `False`; in `draft.py`, this is a global variable at the beginning; in functions from `fig_*.py`, this is a keyword argument of the functions. **THIS WILL OVERWRITE EXISTING FIGURES**.

### computing new data

When parameters or the model is changed in `utility.py`, the data must be re-computed. Change `compute` to `True`; in `draft.py`, this is a global variable at the beginning; in functions from `fig_*.py`, this is a keyword argument of the functions. **THIS WILL OVERWRITE EXISTING DATA**.

### runtime

On a machine with the following specifications, it takes about ~2 mins to generate all the data and save all the figures.

```

Model Name: MacBook Air

Model Identifier: MacBookAir10,1

Chip: Apple M1

Number of Cores: 8 (4 performance and 4 efficiency)

Memory: 16 GB

System Version: macOS 12.6 (21G115)

Kernel Version: Darwin 21.6.0

```

## Support

Please email `shah{at}evolbio.mpg.de` for support.

## Contributing

Please email `shah{at}evolbio.mpg.de` for major contributions.

## License

MIT License

Copyright (c) 2023 Saumil Shah