README.md

ASTER: accurately estimating the number of cell types in single-cell chromatin accessibility data

Installation

ASTER is available on PyPI here and can be installed via

pip install epiaster

You can also install ASTER from GitHub via

git clone git://github.com/BioX-NKU/ASTER.git
cd ASTER
python setup.py install

The dependencies will be automatically installed along with ASTER.

Quick Start

Input

• adata: AnnData object of shape n_obs × n_vars. Rows correspond to cells and columns to genes.
• search_list: List of optional numbers of cell types for the estimation.

Output

• estimated_k: Estimated number of cell types.

ASTER can also be seamlessly integrated with EpiScanpy, a widely-used Python library for epigenomics single cell analysis:

    import episcanpy.api as epi
    import epiaster as aster
    # Load the single-cell chromatin accessibility data as an AnnData object (adata)
    # Run ASTER
    estimated_k = aster.estimate_k(adata, search_list)

The source code for the reproduction of results can be found here.

We also provide a Jupyter Notebook for running ASTER.

Find more details on the Documentation of ASTER.