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Automated scRNA-seq filtering

Project description

![alt text](data/dropkick_logo.png)

### Automated cell filtering for single-cell RNA sequencing data.

[![Latest Version][pypi-image]][pypi-url]

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.

[pypi-image]: https://img.shields.io/pypi/v/dropkick [pypi-url]: https://pypi.python.org/pypi/dropkick/

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