The Galaxy Web-based workflow management system is a hugely popular system in bioinformatics with an enormous international user community.

In addition, Galaxy has a large community of developers interested in many different topics - from ecology to human genetics. There is great interest in improving Galaxy's usability and accessibility for scientists and citizens who may use the platform for ecology, medical, and many other diverse applications. However, the Galaxy system was originally developed to support sequence data analysis and continues to play a huge role in this space. Because of the emphasis on usability and accessibility, it is very likely that Galaxy may in future become an important tool for members of the public to understand their own personal genomes.

In Galaxy, users upload or import data and then perform various computations on the data. Files and data sets created by users appear in "Histories" in the right side of the Galaxy UI. When users create files that can be recognized by IGB, Galaxy displays a "Display in IGB" link that allows IGB to access the file and display it. When users click this link – which goes to a REST endpoint in Galaxy – a new link is created that sends the user to a page at Bioviz.org, which contains javascript code that in turn hits a REST endpoint within IGB running on localhost, the user's computer. Via this mechanism, data can flow from Galaxy into IGB running on the user's desktop.

Internally within IGB, this is accomplished using the "bookmarks API" originally developed to support user-generated bookmarks. Supporting Galaxy-to-IGB connectivity via this mechanism is a bit of hack and makes for a very ugly REST endpoint. We would like to improve and generalize this endpoint to enable Galaxy and other similar cloud-based workflow systems to use IGB for visualization.

Because Galaxy has many thousands of users, it is important for Galaxy-to-IGB integration to work extremely well. The issues in this epic focus on improving the Galaxy-to-IGB user experience so that more people will learn about and be able to use IGB for their research or personal interests.

Ann has attended two Galaxy Community meetings with the goal of learning about the Galaxy code base and improve Galaxy-to-IGB user experience.

For the issues in this epic, you will often need to build and run your own local Galaxy instance. For this, you need to know about some basic resources for developing Galaxy. If you get stuck or need help, check out the following links:

• Galaxy "main" site at Penn State University - https://usegalaxy.org
• Galaxy project github - https://github.com/galaxyproject
• Galaxy code base on github - https://github.com/galaxyproject/galaxy
• Gitter site for developers to ask and answer questions (like slack) - https://gitter.im/galaxyproject/dev
• Training materials - https://github.com/galaxyproject/training-material

And of course, before you begin work on a new task, search Jira for Galaxy-related issues and familiarize yourself with past work.

Update July 2020: We have an EC2 with Galaxy deployed. Log in as ubuntu@usegalaxy.bioviz.org.