Skip to content

GeneClust: cofunctional grouping-based feature gene selection for unsupervised scRNA-seq clustering

License

Notifications You must be signed in to change notification settings

ToryDeng/scGeneClust

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

74 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Github license Github language Github version

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. image

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
  1. 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},
}

About

GeneClust: cofunctional grouping-based feature gene selection for unsupervised scRNA-seq clustering

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published