Using Galaxy to Perform Large-Scale Interactive Data Analyses—An Update

Alexander Ostrovsky, Jennifer Lynne Jackson, Dave Bouvier, Dave Clements, Enis Afgan, Daniel James Blankenberg, Michael C. Schatz, Anton Nekrutenko, James Taylor, The Galaxy Team, Delphine Lariviere

Research output: Contribution to journalArticlepeer-review

Abstract

Modern biology continues to become increasingly computational. Datasets are becoming progressively larger, more complex, and more abundant. The computational savviness necessary to analyze these data creates an ongoing obstacle for experimental biologists. Galaxy (galaxyproject.org) provides access to computational biology tools in a web-based interface. It also provides access to major public biological data repositories, allowing private data to be combined with public datasets. Galaxy is hosted on high-capacity servers worldwide and is accessible for free, with an option to be installed locally. This article demonstrates how to employ Galaxy to perform biologically relevant analyses on publicly available datasets. These protocols use both standard and custom tools, serving as a tutorial and jumping-off point for more intensive and/or more specific analyses using Galaxy.

Original languageEnglish (US)
Article numbere31
JournalCurrent Protocols
Volume1
Issue number2
DOIs
StatePublished - Feb 2021

All Science Journal Classification (ASJC) codes

  • Biochemistry, Genetics and Molecular Biology(all)
  • Pharmacology, Toxicology and Pharmaceutics(all)
  • Neuroscience(all)
  • Immunology and Microbiology(all)
  • Health Informatics
  • Medical Laboratory Technology

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