A high-performance, memory-efficient R package for integrating gene expression data from single-cell RNA sequencing experiments. GEDI 2.0 implements a unified generative model for interpretable latent embedding of multi-sample, multi-condition single-cell data.
See the full Documentation in the wiki page.
Python implementation of GEDI 2 is available at:
https://github.com/csglab/gedi2py
- R >= 4.0.0
- C++ Compiler (C++11 or later; default in R >= 4.0)
- Eigen >= 3.3.0 (linear algebra library)
- OpenMP (optional, for parallelization)
The latest stable release is available on CRAN:
install.packages("gedi2")For the most up-to-date version, including minor fixes not yet on CRAN, install directly from GitHub:
# Install devtools if not already installed
install.packages("devtools")
# Install gedi from GitHub
devtools::install_github("csglab/gedi2")If you use GEDI 2.0 in your research, please cite the original paper:
Mikaeili Namini, A., Saberi, A., & Najafabadi, H. S. (2026). Atlas-level single-cell integration and clustering-free differential expression analysis with GEDI 2.0. Bioinformatics. https://doi.org/10.1093/bioinformatics/btag334
All reproducible code, scripts, and resources used in this project are available at: https://github.com/csglab/gedi2_manuscript
Contributions are welcome! Please:
- Fork the repository
- Create a feature branch
- Submit a pull request
Report bugs and request features at: https://github.com/csglab/gedi2/issues
This project is licensed under the MIT License - see the LICENSE file for details.