Metadata-Version: 2.4
Name: scanpro
Version: 0.4.0
Summary: Single-Cell Analysis of Proportions
Home-page: https://github.com/loosolab/scanpro
Author: Loosolab
Author-email: yousef.alayoubi@mpi-bn.mpg.de
License: MIT
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: statsmodels
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: seaborn
Requires-Dist: patsy
Dynamic: author
Dynamic: author-email
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
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# Scanpro: robust proportion analysis for single cell resolution data
Scanpro is a modular tool for proportion analysis, seamlessly integrating into widely accepted frameworks in the python environment. Scanpro is fast, accurate, support datasets without replicates, and is intended to be used by bioinformatics experts and beginners.

<img src="docs/source/figures/scanpro_workflow.png" width=75% height=55%>

## Install
### PyPi

`pip install scanpro`

### From source: 
- clone the repository
```
git clone https://gitlab.gwdg.de/loosolab/software/scanpro.git
```
- navigate to scanpro directory
```
cd scanpro
```
- then run 
```
pip install .
```
## Quick start
To run the tool import and call the function `scanpro`:
```
from scanpro import scanpro

out = scanpro(adata, clusters_col='clusters', conds_col='condition', samples_col='sample')

```

- If samples_col is not given or set to None, the dataset is assumed to be not replicated and scanpro will run the bootstrapping method.

To show the results, run
```out.results```. 

You can plot the results by calling ```out.plot()```.

## Documentation

A detailed documentation can be found here: [Manual](https://scanpro.readthedocs.io/en/latest/).

## Citation

Alayoubi, Y., Bentsen, M. & Looso, M. Scanpro is a tool for robust proportion analysis of single-cell resolution data. *Sci Rep* **14**, 15581 (2024). [https://doi.org/10.1038/s41598-024-66381-7](https://doi.org/10.1038/s41598-024-66381-7)
