This README documents the necessary steps to set up the running environment for scIMGCN.
- scIMGCN is an interpretable, GCN-based cell-type annotation method for single-cell data, offering researchers a deep learning solution for single-cell annotation.
- Current version: 1.0
- Setting up scIMGCN requires an environment with Python 3.8 or newer, along with PyTorch and other necessary machine learning libraries.
- Install all dependencies using pip:
pip install -r requirements.txt. - scIMGCN does not require database configuration.
- Since scIMGCN is primarily used for research and development, it does not have a specific deployment guide. Please integrate it into your project or workflow as needed.
- Please write appropriate tests for your contributions and ensure all tests pass.
- Submit pull requests for any changes. Project maintainers will review according to the project's coding standards.
Tang B., Cheng G., and Gao X. scIMGCN: An Automatic Single-Cell Type Annotation Method Based on Interpretable Graph Convolutional Network. Interdisciplinary Sciences: Computational Life Sciences, 2025.