Metadata-Version: 1.2
Name: dropkick
Version: 1.0.0
Summary: Automated scRNA-seq filtering
Home-page: https://github.com/KenLauLab/dropkick
Author: Cody Heiser
Author-email: codyheiser49@gmail.com
License: UNKNOWN
Description: # dropkick
        Automated cell filtering for single-cell RNA sequencing data.
        
        `dropkick` works primarily with [**Scanpy**](https://icb-scanpy.readthedocs-hosted.com/en/stable/)'s `AnnData` objects, and accepts input files in `.h5ad` or flat (`.csv`, `.tsv`) format. It also writes outputs to `.h5ad` files when called from the terminal.
        
        ---
        Installation via `pip` or from source requires a Fortran compiler. For Mac users, `brew install gcc` will take care of this.
        
        #### Install from PyPI:
        ```bash
        pip install dropkick
        ```
        
        #### Or compile from source:
        ```bash
        git clone https://github.com/KenLauLab/dropkick.git
        cd dropkick
        python setup.py install
        ```
        
        ---
        `dropkick` can be run as a command line tool, or interactively with the [`scanpy`](https://icb-scanpy.readthedocs-hosted.com/en/stable/) single-cell analysis suite.
        
        #### Usage from command line:
        ```bash
        python -m dropkick path/to/counts.h5ad
        ```
        
        Output will be saved in a new `.h5ad` file containing __dropkick__ scores, labels, and model parameters.
        
        See [`dropkick_tutorial.ipynb`](dropkick_tutorial.ipynb) for an interactive walkthrough of the `dropkick` pipeline and its outputs.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Topic :: Scientific/Engineering
Requires-Python: >=3.6
