PathSingle is a Python package for pathway analysis of single-cell RNA-seq data.
Project description
PathSingle: A Biochemical Pathway Analysis Tool for Single-Cell Data
Overview
PathSingle is a Python-based pathway analysis tool tailored for single-cell data analysis. It employs a unique graph-based algorithm to enable the analysis of diverse cellular states, such as T cell subtypes. Designed to be open-source, extensible, and computationally efficient, PathSingle provides researchers with a versatile framework for uncovering biologically meaningful insights from high-dimensional single-cell transcriptomics data.
Key Features
- Tailored for single-cell RNA-seq data analysis
- Unique graph-based algorithm for pathway analysis
- Efficient classification of diverse cellular states
- Open-source and extensible
- Computationally efficient
Installation
pip install pathsingle Or Simply clone this repository using git clone command.
Quick Start
anndata = sc.read('./data/activity_df.csv', delimiter=',', cache=False)
calc_activity(anndata)
Usage
For detailed usage instructions, please refer to the notebooks in the code folder, which demonstrate single-cell RNA-seq data processing using PathSingle.
The pathway_db subfolder contains scripts for building and customizing the pathways database.
Supported Pathways
PathSingle currently supports 357 curated pathways. Click the link to view the full list. List of supported pathways.
Contributing
We welcome contributions! Please see our Contributing Guidelines for more information on how to get involved.
License
PathSingle is available under the MIT license. See the LICENSE file for more details.
Support
For questions, issues, or feature requests, please open an issue on our GitHub repository.
For additional support, contact: zurkin at yahoo dot com.
Acknowledgments
We thank the scientific community for their valuable feedback and contributions to this project.
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