Metadata-Version: 2.1
Name: STCAT
Version: 1.0.1
Summary: An automated T cell type annotation tool for scRNA-seq datasets.
Home-page: https://github.com/GuoBioinfoLab/STCAT
License: MIT
Classifier: Programming Language :: Python :: 3.8
Classifier: Operating System :: POSIX :: Linux
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: numpy >=1.19.0
Requires-Dist: pandas >=1.0.5
Requires-Dist: scikit-learn >=0.24.1
Requires-Dist: openpyxl >=3.0.4
Requires-Dist: click >=7.1.2
Requires-Dist: scanpy ==1.9.3
Requires-Dist: leidenalg >=0.8.3

# STCAT  <a href="https://www.python.org/"><img src="https://img.shields.io/badge/python-3.8+-brightgreen.svg" alt="Python Versions" width="80"></a>

STCAT is an automated T cell type annotation tool for scRNA-seq datasets. 
It based on a high-confidence T cell subtypes and states reference. 
The reference can be found in our TCellAtlas portal. 
STCAT can automatically annotate T cell subtypes and states for scRNA-seq data of different conditions and tissues.

# TCellAtlats Website
TCellAtlas is a comprehensive scRNA-seq database focused on T cells, containing 1,654,675 high-quality T cells from 328 samples across 35 conditions and 16 tissues, as well as 47,215 T cells from Smart-seq projects. 
It includes all 68 T cell subtypes and states, making it the most extensive T cell reference database. 
Information of STCAT can be also found in our TCellAtlas portal. 
The database is accessible at [TCellAtlats](https://guolab.wchscu.cn/TCellAtlas/#/).
# Install STCAT
## Using pip
```console
pip install STCAT
```
# Usage 
STCAT expects a raw count matrix as input and can be implemented with only one line of code in Python. 
STCAT expects to use an Anndata object ( .h5ad file format ) as input, and at the same time, a raw count matrix ( reads or UMIs ) is required. 
The file input is in a cell-by-gene format ( cells as rows and genes as columns ). For more information, please see [anndata](https://anndata.readthedocs.io/en/latest/).
As for the annotation result, STCAT will be automatically added to the common anndata format of scRNA-seq analysis for easy viewing.
```python
import scanpy as sc
import STCAT
adata = sc.read_h5ad(<file_path>)
results = STCAT.STCAT(adata)
```
## Example:
[Tutorial](tutorial.ipynb)
