https://github.com/luka-kovacevic/causalregnet
Python package for SCM-based simulation of gene perturbation data and benchmarking of causal structure learning algorithms.
https://github.com/luka-kovacevic/causalregnet
benchmarking causal-discovery causal-machine-learning simulation
Last synced: 6 months ago
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Python package for SCM-based simulation of gene perturbation data and benchmarking of causal structure learning algorithms.
- Host: GitHub
- URL: https://github.com/luka-kovacevic/causalregnet
- Owner: luka-kovacevic
- License: mit
- Created: 2024-01-23T17:09:52.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-01T19:15:24.000Z (9 months ago)
- Last Synced: 2025-03-24T17:52:48.477Z (7 months ago)
- Topics: benchmarking, causal-discovery, causal-machine-learning, simulation
- Language: Python
- Homepage:
- Size: 4.77 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# causalregnet
This is a library for simulating realistic single-cell RNA sequencing data based on a given causal structure, scalable to the dimension of genome-wide gene perturbation screens.
Implementation of method developed in [*"Simulation-based Benchmarking of Causal Structure Learning in Gene Perturbation Experiments"*](https://arxiv.org/abs/2407.06015).
## Installation guide
1. Download the package from GitHub
```
git clone https://github.com/luka-kovacevic/causalregnet
```
2. Navigate to the package
```
cd causalregnet/
```
3. Check your environment (ensure it's the same one you're using to run code)
4. Install the package
```
pip install .
```