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Galaxy is an open, web-based platform for accessible, reproducible, and transparent computational biomedical research.
  • Accessible: Users without programming experience can easily specify parameters and run tools and workflows.

  • Reproducible: Galaxy captures information so that any user can repeat and understand a complete computational analysis.

  • Transparent: Users share and publish analyses via the web and create Pages, interactive, web-based documents that describe a complete analysis.

This is the Galaxy Community Wiki. It describes all things Galaxy.

Use Galaxy

Galaxy's public web server usegalaxy.org makes analysis tools, genomic data, tutorial demonstrations, persistent workspaces, and publication services available to any scientist. Extensive user documentation applicable to any public or local Galaxy instance is available.


Deploy Galaxy

Galaxy is a free and open source project available to all. Local Galaxy servers can be set up by downloading the Galaxy application.


Community & Project

Galaxy has a large and active user community and many ways to get involved.


  • Users: Share your histories, workflows, visualizations, data libraries, and Galaxy Pages, enabling others to use and learn from them.

  • Developers: Contribute tool definitions to the Galaxy Tool Shed (making it easy for others to use those tools on their installations), and code to the codebase.

  • Everyone: Get Involved!

  • RT @mattdotvaughn: @jxtx This works with "all major cloud platforms" @googlecloud @awscloud @jetstream_cloud @CyVerseOrg #ismbeccb 2017-07-23 06:07:26
  • RT @mattdotvaughn: Super-slick @usegalaxy is agnostic to software packaging backend. Containers. VM. Conda recipes. 🏆 2017-07-23 06:07:26
  • RT @mattdotvaughn: 100,149 history item @UseGalaxy workflow run over 100 plus hours and massive data scale. Awesome 📈⚙️🌠 2017-07-23 06:07:26
  • RT @jmchilton: .@jxtx demonstrating #usegalaxy allows users with no informatics training perform analyses over hundreds of thousands datase… 2017-07-23 06:07:26
  • RT @edamontology: .@rvmngr & al.: The @edamontology and its integration into @galaxyproject. Poster in @F1000research, https://t.co/9zHcLR0… 2017-07-23 06:07:26
  • RT @jxtx: #BOSC2017 @jmchilton On why the best reproducibility stack ever is also the best for HPC environments. https://t.co/b6PEJ9AyoZ 2017-07-23 06:07:26