CIA

CIA (Cluster Independent Annotation) is a cutting-edge computational tool designed to accurately classify cells in scRNA-seq datasets using gene signatures. This tool operates without the need for a fully annotated reference dataset or complex machine learning processes, providing a highly user-friendly and practical solution for cell type annotation.

CIA summarizes the information of each signature expression into a single score value for each cell. By comparing these score values, CIA assigns labels to each cell based on the top-scored signature. CIA can filter scores by their distribution or significance, allowing comparison of genesets with lengths spanning tens to thousands of genes.

CIA is implemented in both R and Python, making it compatible with all major single-cell analysis frameworks like SingleCellExperiment, Seurat, and Scanpy. This compatibility ensures a seamless integration into existing workflows.

Key Features

• Automatic Annotation: Accurately labels cell types in scRNA-seq datasets based on gene signatures.
• Clustering-Free: Operates independently of clustering steps, enabling flexible and rapid data exploration.
• Multi-Language Support: Available in both R and Python to suit diverse user preferences.
• Compatibility: Integrates with popular single-cell data formats (AnnData, SingleCellExperiment, SeuratObject).
• Statistical Analysis: Offers functions for evaluating the quality of signatures and classification performance.
• Documentation and Tutorials: Comprehensive guides to facilitate easy adoption and integration into existing workflows.

Documentation

• Python Package: CIA Python <https://pypi.org/project/cia-python/>_
• Python docs: CIA Python documentation <https://cia-python.readthedocs.io/en/latest/index.html>_
• R Package and Tutorial: CIA R GitHub Repository <https://github.com/ingmbioinfo/CIA_R>_

Installation

You can install the development version of CIA from GitHub with:

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("ingmbioinfo/CIA_R", force = TRUE, dependencies = TRUE)

Installation with conda

You can also install the development version of CIA exploiting CIA_R.yml (in inst folder):

conda env create -n {name} -f CIA_R.yml
conda activate {name}
Rscript -e 'if (!requireNamespace("remotes", quietly=TRUE)) install.packages("remotes", repos="https://cloud.r-project.org"); remotes::install_github("ingmbioinfo/CIA_R", dependencies=TRUE, upgrade="never", build_vignettes=FALSE)'

Development

If you encounter a bug, have usage questions, or want to share ideas and functionality to make this package better, feel free to file an issue.

Code of Conduct

Please note that the CIA project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

License

MIT