scDesigner

scDesigner is a Python Module for modeling and simulating single-cell data with various models built on top of PyTorch.

Features

• Flexible models: Poisson / Negative Binomial / Zero-inflated variants (and more).
• Scalable simulation: GPU-accelerated training and simulation with PyTorch.
• User-friendly interface: implemented with scikit-learn-like API.
• Extensible design: easy to extend to new models and simulators.

Installation guide

Option A: Install the Python package (recommended)

Create a clean environment (optional but recommended):

conda create -n scdesigner python=3.11 -y
conda activate scdesigner

Install:

pip install scdesigner==0.0.6

Option B: Install from source (this repository)

This option is recommended if you want to access the latest features and bug fixes.

git clone https://github.com/krisrs1128/scDesigner.git
cd scDesigner/scdesigner
pip install -e .

Quickstart

After installation, you can import the package in Python:

import scdesigner

You may refer to examples/quickstart.ipynb for basic usage of the package.

Repository Structure

• Examples: examples/
• Python package source: scdesigner/src/scdesigner/
• R wrappers: R/scDesigner/

Contributing

Issues and pull requests are welcome. Please include a minimal reproducible example and relevant environment information.