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UNIT 10.5 Using Galaxy to Perform Large-Scale Interactive Data Analyses

  1. Jennifer Hillman-Jackson1,
  2. Dave Clements2,
  3. Daniel Blankenberg1,
  4. James Taylor2,
  5. Anton Nekrutenko1,
  6. Galaxy Team1,2

Published Online: 1 JUN 2012

DOI: 10.1002/0471250953.bi1005s38

Current Protocols in Bioinformatics

Current Protocols in Bioinformatics

How to Cite

Hillman-Jackson, J., Clements, D., Blankenberg, D., Taylor, J., Nekrutenko, A. and Team, G. 2012. Using Galaxy to Perform Large-Scale Interactive Data Analyses. Current Protocols in Bioinformatics. 38:10.5:10.5.1–10.5.47.

Author Information

  1. 1

    Penn State University, University Park, Pennsylvania

  2. 2

    Emory University, Atlanta, Georgia

Publication History

  1. Published Online: 1 JUN 2012


Innovations in biomedical research technologies continue to provide experimental biologists with novel and increasingly large genomic and high-throughput data resources to be analyzed. As creating and obtaining data has become easier, the key decision faced by many researchers is a practical one: where and how should an analysis be performed? Datasets are large and analysis tool set-up and use is riddled with complexities outside of the scope of core research activities. The authors believe that Galaxy provides a powerful solution that simplifies data acquisition and analysis in an intuitive Web application, granting all researchers access to key informatics tools previously only available to computational specialists working in Unix-based environments. We will demonstrate through a series of biomedically relevant protocols how Galaxy specifically brings together (1) data retrieval from public and private sources, for example, UCSC's Eukaryote and Microbial Genome Browsers, (2) custom tools (wrapped Unix functions, format standardization/conversions, interval operations), and 3rd-party analysis tools. Curr. Protoc. Bioinform. 38:10.5.1-10.5.47. © 2012 by John Wiley & Sons, Inc.


  • Galaxy;
  • comparative genomics;
  • genomic alignments;
  • Web application;
  • genome variation