GeneClust: a cofunctional grouping-based approach for non-redundant feature gene selection in unannotated single-cell RNA-seq

GeneClust is a computational feature selection method for scRNA-seq cell clustering. GeneClust groups genes into clusters from which genes are evaluated and selected with the aim of maximizing relevance, minimizing redundancy and preserving complementarity.

Dependencies

• anndata>=0.8.0
• numpy>=1.21.6
• setuptools>=59.5.0
• scanpy>=1.9.1
• scipy>=1.9.3
• loguru>=0.6.0
• hdbscan>=0.8.29
• sklearn>=0.0.post2
• scikit-learn>=1.2.0
• igraph>=0.10.2
• leidenalg>=0.9.1
• pandas>=1.5.2
• SpaGCN>=1.2.5
• squidpy>=1.2.2
• torch>=1.13.1
• opencv-python>=4.6.0

Installation

1. PyPI

You can directly install the package from PyPI.

pip3 install GeneClust

2. Github

Also, You can download the package from GitHub and install it locally:

git clone https://github.com/ToryDeng/scGeneClust.git
cd scGeneClust/
python3 setup.py install --user

Two Versions of GeneClust

Version	Usage Scenarios
GeneClust-ps	1. The number of cells is small (e.g., several thousand) 2. Cell clustering performance is more important
GeneClust-fast	1. The number of cells is large (e.g., over 50,000) 2. Computational efficiency is more important

Tutorial

For the step-by-step tutorial, please refer to the notebook:

https://github.com/ToryDeng/scGeneClust/blob/main/notebooks/tutorial_scRNA-seq.ipynb

Reproducibility

To reproduce the results and figures presented in our paper, please go to https://github.com/ToryDeng/scGeneClust/tree/main/figures.

Citation

@article{10.1093/bib/bbad042,
    author = {Deng, Tao and Chen, Siyu and Zhang, Ying and Xu, Yuanbin and Feng, Da and Wu, Hao and Sun, Xiaobo},
    title = "{A cofunctional grouping-based approach for non-redundant feature gene selection in unannotated single-cell RNA-seq analysis}",
    journal = {Briefings in Bioinformatics},
    year = {2023},
    month = {02},
    issn = {1477-4054},
    doi = {10.1093/bib/bbad042},
    url = {https://doi.org/10.1093/bib/bbad042},
    note = {bbad042},
    eprint = {https://academic.oup.com/bib/advance-article-pdf/doi/10.1093/bib/bbad042/49126753/bbad042.pdf},
}