Welcome to the Galaxy course webpage
This page provides links to the course materials and example solutions to the exercises for the “Introduction to Galaxy: data manipulation and visualisation” course run by the Graduate School of Life Sciences, University of Cambridge.
title: Introduction to Galaxy: data manipulation and visualisation
description: A Galaxy introduction course covering basic functions, simple data manipulation using use cases and examples and visualisation mostly targeted at first time users.
format: 2 sessions of 3 hours from 9:30 until 16:30
- Locate the different parts of the Galaxy user interface
- Use Galaxy to load data from different sources
- Employ different basic operations on genomic intervals
- Practice building simple workflows
- Solve exercises using Galaxy
- Practical Sessions:
- Course survey:
Galaxy cloud instances
These cloud instances are only available during training session otherwise they are turned off. If you wish to use Galaxy again we recommend using Galaxy main.
- Go to http://220.127.116.11/
The Galaxy course instance(s) will be kept alive one day after the course before being shut down.
If you wish to continue the practical session at your own speed, you are more than welcome to do so on the main Galaxy server at https://usegalaxy.org/. The data you were accessing during the course under the menu ‘Shared Data’ will not be visible but you can download it onto your computer, unzip it and load it into your history from our GitHub repository galaxy-intro, the course Data Libraries are in the ‘data_libraries’ folder.
- Anne Pajon, CRUK Cambridge Institute. Email: Anne . Pajon @cruk.cam.ac.uk
- Jing Su, CRUK Cambridge Institute. Email: Jing . Su @cruk.cam.ac.uk
- Graham Etherington, Sainsbury Laboratory Norwich - ‘An Introduction to Galaxy’
- Galaxy Team (aun1) - Galaxy Screencasts including Finding promoters containing TAF1 binding sites identified from a CHiP-seq experiment
- Galaxy Team (aun1) - ‘Galaxy 101’
- Jeremy Goecks, George Washington University and Aysam Guerler, Johns Hopkins University - Visualization of NGS data