Hail is an open-source, scalable framework for exploring and analyzing genomic data.

For genomics applications, Hail can, for example:

Hail is a Python library with a scalable backend built on top of Apache Spark to efficiently analyze gigabyte-scale data on a laptop or terabyte-scale data on a cluster.

Getting Started

To get started using Hail:

Hail uses a continuous deployment approach to software development, which means features, bug fixes, and performance improvements land every day. We recommend updating the software frequently.

User Support

There are many ways to get in touch with the Hail team if you need help using Hail or would like to suggest improvements or new features.

Maintainer

Hail is maintained by a team in the Neale lab at the Stanley Center for Psychiatric Research of the Broad Institute of MIT and Harvard and the Analytic and Translational Genetics Unit of Massachusetts General Hospital.

Contact the Hail team: hail@broadinstitute.org.

Follow Hail on Twitter: @hailgenetics.

Citing Hail

If you use Hail for published work, please cite the software:

Acknowledgements

The Hail team has several sources of funding at the Broad Institute:

We are grateful for generous support from:

We would like to thank Zulip for supporting open-source by providing free hosting, and YourKit, LLC for generously providing free licenses for YourKit Java Profiler for open-source development.