Hail

Cloud-native genomic dataframes and batch computing

Description

Hail is an open-source framework for scalable genetic data analysis. To get started using Hail, see the documentation, join the discussion forum, and chat with the Hail team and other users on the Hail gitter.

Hail is pre-alpha software and under active development. If you're interested to get involved, see the Development category of the discussion forum and chat with the Hail team and other developers on the Hail development gitter.

We encourage use of the discussion forum for user and dev support, feature requests, and sharing your Hail-powered science. Please report any suspected bugs directly to issues.

The Hail team is based 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 [email protected].

Programming language: Python

License: MIT License

Tags: Science And Data Analysis     Big Data     Machine Learning     Hadoop     Spark     Genetics    

Latest version: v0.2.61

README

Hail

Hail is an open-source, general-purpose, Python-based data analysis tool 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 is exposed as a Python library, using primitives for distributed queries and linear algebra implemented in Scala, Spark, and increasingly C++.

See the documentation for more info on using Hail.

Community

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.

Contribute

If you'd like to discuss or contribute to the development of methods or infrastructure, please:

• see the For Software Developers section of the installation guide for info on compiling Hail
• chat with us about development in our Zulip chatroom
• visit the Development Forum for longer-form discussions <!--- - read this post (coming soon!) for tips on submitting a successful Pull Request to our repository --->

Hail uses a continuous deployment approach to software development, which means we frequently add new features. We update users about changes to Hail via the Discussion Forum. We recommend creating an account on the Discussion Forum so that you can subscribe to these updates as well.

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 at [email protected].

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
print(hl.citation())

Which will look like:

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

Acknowledgements

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

• The Stanley Center for Psychiatric Research, which together with Neale Lab has provided an incredibly supportive and stimulating home.
• Principal Investigators Benjamin Neale and Daniel MacArthur, whose scientific leadership has been essential for solving the right problems.
• Jeremy Wertheimer, whose strategic advice and generous philanthropy have been essential for growing the impact of Hail.

We are grateful for generous support from:

• The National Institute of Diabetes and Digestive and Kidney Diseases
• The National Institute of Mental Health
• The National Human Genome Research Institute
• The Chan Zuckerberg Initiative

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.