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https://github.com/sgkit-dev/sgkit

Scalable genetics toolkit
https://github.com/sgkit-dev/sgkit

genetics gwas popgen pydata statgen statistical-genetics

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Scalable genetics toolkit

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# sgkit: Scalable genetics toolkit in Python
[![Build](https://github.com/sgkit-dev/sgkit/actions/workflows/build.yml/badge.svg)](https://github.com/sgkit-dev/sgkit/actions/workflows/build.yml)
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[![Docs](https://github.com/sgkit-dev/sgkit/actions/workflows/docs.yml/badge.svg)](https://sgkit-dev.github.io/sgkit/)
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[![Powered by NumFOCUS](https://img.shields.io/badge/powered%20by-NumFOCUS-orange.svg?style=flat&colorA=E1523D&colorB=007D8A)](http://numfocus.org)

Sgkit is a Python package that provides a variety of analytical genetics methods through the use of
general-purpose frameworks such as [Xarray](http://xarray.pydata.org/en/stable/), [Pandas](https://pandas.pydata.org/docs/),
[Dask](https://docs.dask.org/en/latest/) and [Zarr](https://zarr.readthedocs.io/en/stable/).

For more information on using sgkit, see the [documentation](https://sgkit-dev.github.io/sgkit/).

[//]: # (numfocus-fiscal-sponsor-attribution)

The sgkit project uses a [custom governance model](./GOVERNANCE.md)
and is fiscally sponsored by [NumFOCUS](https://numfocus.org/). Consider making
a [tax-deductible donation](https://numfocus.org/donate-to-sgkit) to help the project
pay for developer time, professional services, travel, workshops, and a variety of other needs.