Hail is an open-source, general-purpose, Python-based data analysis library with additional data types and methods for working with genomic data.

Hail is built to scale and has first-class support for multi-dimensional structured data, like the genomic data in a genome-wide association study (GWAS).

Hail's backend is implemented in Python, Scala, Java, and Apache Spark.

See the documentation for more info on using Hail. Post to the Discussion Forum for user support and feature requests. Chat with the Hail team and user community in Hail's Zulip chatroom.

Hail is actively developed with new features and performance improvements integrated weekly. See the changelog for more information.


Hail has been widely adopted in academia and industry, including as the analysis platform for the genome aggregation database and UK Biobank rapid GWAS. Learn more about Hail-powered science.


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 at hail@broadinstitute.org.

Citing Hail

If you use Hail for published work, please cite the software. You can get a citation for the version of Hail you installed by executing:

import hail as hl

Which will look like:

Hail Team. Hail 0.2.13-81ab564db2b4. https://github.com/hail-is/hail/releases/tag/0.2.13.

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.