README.md

Welcome to the workshop of applying Neural Posterior Estimation in inferring historical population sizes!

Before we begin, ensure the following:

1. Operating System: Linux/macOS/Windows (with WSL or an equivalent environment).
2. Hardware:
   • Only CPU is needed for this workshop.
   • GPU usage will be provided in another Notebook.
3. Software:
   • Python 3.9+ sbi0.22.0.
   • conda (or venv) for environment management.
   • Required Python libraries for this tutorial (requirements).

Environment Setup

To run this notebook, please follow these steps:

1. Install conda if you haven’t already.
2. Clone the repository: git clone https://github.com/fbaumdicker/ML-PopGen-Tutorials.git and navigate to the NPEinPopGen directory.
3. Create the environment: conda env create -f popgensbi.yml
4. Activate the environment: conda activate popgensbi
5. Start notebook kernel: python -m ipykernel install --user --name popgensbi --display-name "popgensbi"
6. Launch Jupyter notebook: jupyter notebook.
7. In the Notebook, select the "popgensbi" kernel if prompted.

To run the Snakemake pipeline, please adjust the parameters in the config, and use the following command:

snakemake --use-conda --cores 4