Metadata-Version: 2.1
Name: easydecon
Version: 0.1.0b2
Summary: easydecon
Home-page: https://github.com/sinanugur/easydecon
Author: Sinan U. Umu
Author-email: sinanugur@gmail.com
Keywords: scRNA single-cell high definition spatial transcriptomics deconvolution
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Description-Content-Type: text/markdown
License-File: LICENSE

<img src="easydecon-logo.png" alt="Logo" width=130 style="vertical-align: middle; margin-right: 10px;"/>  

[![PyPI version](https://badge.fury.io/py/easydecon.svg)](https://badge.fury.io/py/easydecon)  
A package to analyze celltypes on high definition spatial profiling assays

Installation
------------
It is recommended to install the package in a virtual environment or a Conda environment. To create a Conda environment, run the following command:

```bash
conda create -n easydecon python=3.11
conda activate easydecon
```

You can install from PyPi:

```bash
pip install easydecon
```

To install directly from GitHub using pip into the active environment, run the following command:

```bash
pip install git+https://github.com/sinanugur/easydecon.git
```

Overview
--------
<img src="easydecon-overview.png" alt="Worfklow Overview"/>

Usage and Documentation
-----------------------
You may find our example notebooks in the `notebooks` folder.

- Demo notebook for a single-cell Anndata object (demo)[https://github.com/sinanugur/easydecon/blob/main/notebooks/demo.ipynb]
- Demo notebook for macrophage markers (demo_macrophage)[https://github.com/sinanugur/easydecon/blob/main/notebooks/demo_macrophage.ipynb]
- Minimal example notebook (minimal)[https://github.com/sinanugur/easydecon/blob/main/notebooks/demo_minimal_example.ipynb]
