Skip to main content

Automated scRNA-seq filtering

Project description

Dropkick Logo

Automated cell filtering for single-cell RNA sequencing data.

Latest Version


dropkick works primarily with scanpy’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 (brew install gcc for Mac users).

Install from PyPI:

pip install dropkick

Or compile from source:

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 single-cell analysis suite.

Usage from command line:

dropkick run path/to/counts.h5ad

Output will be saved in a new .h5ad file containing cell probability scores, labels, and model parameters.

You can also run the dropkick.qc module from terminal for a quick look at the total UMI distribution and ambient genes, saved as *_qc.png:

dropkick qc path/to/counts.h5ad

See dropkick_tutorial.ipynb for an interactive walkthrough of the dropkick pipeline and its outputs.

Full documentation is available at KenLauLab.github.io/dropkick.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

dropkick-1.2.6.tar.gz (114.3 kB view hashes)

Uploaded source

Built Distribution

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page