Unit

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

  1. James Taylor1,
  2. Ian Schenck2,
  3. Dan Blankenberg2,
  4. Anton Nekrutenko2

Published Online: 1 SEP 2007

DOI: 10.1002/0471250953.bi1005s19

Current Protocols in Bioinformatics

Current Protocols in Bioinformatics

How to Cite

Taylor, J., Schenck, I., Blankenberg, D. and Nekrutenko, A. 2007. Using Galaxy to Perform Large-Scale Interactive Data Analyses. Current Protocols in Bioinformatics. 19:10.5:10.5.1–10.5.25.

Author Information

  1. 1

    New York University, New York, New York

  2. 2

    Penn State University, University Park, Pennsylvania

Publication History

  1. Published Online: 1 SEP 2007
  2. Published Print: SEP 2007

This is not the most recent version of the article. View current version (1 JUN 2012)

Abstract

While most experimental biologists know where to download genomic data, few have a concrete plan on how to analyze it. This situation can be corrected by: (1) providing unified portals serving genomic data and (2) building Web applications to allow flexible retrieval and on-the-fly analyses of the data. Powerful resources, such as the UCSC Genome Browser already address the first issue. The second issue, however, remains open. For example, how to find human protein-coding exons with the highest density of single nucleotide polymorphisms (SNPs) and extract orthologous sequences from all sequenced mammals? Indeed, one can access all relevant data from the UCSC Genome Browser. But once the data is downloaded how would one deal with millions of SNPs and gigabytes of alignments? Galaxy (http://g2.bx.psu.edu) is designed specifically for that purpose. It amplifies the strengths of existing resources (such as UCSC Genome Browser) by allowing the user to access and, most importantly, analyze data within a single interface in an unprecedented number of ways. Curr. Protoc. Bioinform. 19:10.5.1-10.5.25. © 2007 by John Wiley & Sons, Inc.

Keywords:

  • comparative genomics;
  • genomic alignments;
  • Web application;
  • genomic sequences