Metadata-Version: 2.1
Name: anansescanpy
Version: 0.2.2
Summary: implementation of scANANSE for scanpy objects in Python
Home-page: https://github.com/Arts-of-coding/AnanseScanpy
License: apache 2.0
Keywords: GRN,single-cell,gene expression,open chromatin,arts-of-coding
Author: J Arts (Arts-of-coding)
Author-email: julian.armando.arts@gmail.com
Requires-Python: >=3.8,<4.0
Classifier: License :: Other/Proprietary License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Requires-Dist: anndata (>=0.8.0,<0.9.0)
Requires-Dist: jupyterlab (>=3.3.4,<4.0.0)
Requires-Dist: numpy (>=1.23.3,<2.0.0)
Requires-Dist: pandas (>=1.4.4,<2.0.0)
Requires-Dist: scanpy (>=1.9.1,<2.0.0)
Requires-Dist: scipy (>=1.9.1,<2.0.0)
Project-URL: Repository, https://github.com/Arts-of-coding/AnanseScanpy
Description-Content-Type: text/markdown

## `AnanseScanpy` package: implementation of scANANSE for Scanpy objects in Python
[![Anaconda-Server Badge](https://anaconda.org/bioconda/anansescanpy/badges/version.svg)](https://anaconda.org/bioconda/anansescanpy)
[![PyPI version](https://badge.fury.io/py/anansescanpy.svg)](https://badge.fury.io/py/anansescanpy)
[![install with bioconda](https://img.shields.io/badge/install%20with-bioconda-brightgreen.svg?style=flat)](http://bioconda.github.io/recipes/anansescanpy/README.html)
[![Anaconda-Server Badge](https://anaconda.org/bioconda/anansescanpy/badges/downloads.svg)](https://anaconda.org/bioconda/anansescanpy)

## Installation

The most straightforward way to install the most recent version of AnanseScanpy is via conda using PyPI.

### Install package through Conda
If you have not used Bioconda before, first set up the necessary channels (in this order!). 
You only have to do this once.
```
$ conda config --add channels defaults
$ conda config --add channels bioconda
$ conda config --add channels conda-forge
```

Then install AnanseScanpy with:
```
$ conda install anansescanpy
```

### Install package through PyPI
```
$ pip install anansescanpy
```

### Install package through GitHub
```
git clone https://github.com/Arts-of-coding/AnanseScanpy.git
cd AnanseScanpy
conda env create -f requirements.yaml
conda activate AnanseScanpy
pip install -e .
```

## Start using the package

### Run the package either in the console
```
$ python3
```

### Or run the package in jupyter notebook
```
$ jupyter notebook
```

## For extended documentation see our ipynb vignette with PBMC sample data
### Of which the sample data can be downloaded
```
$ wget https://mbdata.science.ru.nl/jsmits/scANANSE/rna_PBMC.h5ad -O scANANSE/rna_PBMC.h5ad
$ wget https://mbdata.science.ru.nl/jsmits/scANANSE/atac_PBMC.h5ad -O scANANSE/atac_PBMC.h5ad
```

### installing and running anansnake 

Follow the instructions its respective github page, https://github.com/vanheeringen-lab/anansnake
Next automatically use the generated files to run GRN analysis using your single cell cluster data:


```{bash eval=FALSE}
snakemake --use-conda --conda-frontend mamba \
--configfile scANANSE/analysis/config.yaml \
--snakefile scANANSE/anansnake/Snakefile \
--resources mem_mb=48_000 --cores 12
```

### Thanks to:

* Jos Smits and his Seurat equivalent of this package https://github.com/JGASmits/AnanseSeurat
* Siebren Frohlich and his anansnake implementation https://github.com/vanheeringen-lab/anansnake

