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Introduction to Galaxy

Iowa Initiative
in Human Genetics
University of Iowa

**A workshop for the University of Iowa community

Instructor: Dave Clements

April 19: Two workshops:**

8:30am-12pm University of Iowa Biology Building B20
Map (This workshop is full.)
1:30pm-5pm University of Iowa Hardin Info Commons East Room
214 Hardin, map, floorplan


Registration is open to any member of the University of Iowa community. The workshops are free, but advanced registration is required.

Register Now


Are you a biomedical researcher who needs to do complex analysis on large datasets?

Galaxy is an open, web-based platform for data intensive biomedical research that enables non-bioinformaticians to create, run, tune, and share their own bioinformatic analyses.

This hands-on workshop will teach participants how to integrate data, and perform simple and complex analysis within Galaxy. It will also cover data visualization and visual analytics, and how to share and reuse your bioinformatic analyses, all from within Galaxy.

No programming or Linux command line experience is required.


AM Time PM Time Topic
8:30 1:30 Welcome, Intro
Introduction to Galaxy and the Galaxy community
8:50 1:50 Basic Analysis with Galaxy
Walk though a worked, hands-on example demonstrating basic analysis within Galaxy
9:50 2:50 Visualization & Visual Analytics in Galaxy
Learn to use Galaxy's built-in visualization capabilities. We'll also demonstrate Galaxy's visual analytics support, using the tight coupling of visualization and analyses to iteratively guide analysis.
10:15 3:15 Break
10:40 3:40 Manage, Reuse and Share your Analyses with Galaxy
Use Galaxy to record every step, parameter setting, and dataset used in an analysis; share/publish analysis and resulting datasets; and to create generic workflows that can be run on different sets of input data.
11:05 4:05 Intro to NGS Analysis with Galaxy
Use Galaxy to integrate and analyze your high throughput sequencing data.
12:00 5:00 Done



Amazon Web Services

This workshop is generously supported by an AWS in Education grant award, and the Iowa Initiative in Human Genetics


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