Abstract

High-throughput data production technologies, particularly ‘next-generation’ DNA sequencing, have ushered in widespread and disruptive changes to biomedical research. Making sense of the large datasets produced by these technologies requires sophisticated statistical and computational methods, as well as substantial computational power. This has led to an acute crisis in life sciences, as researchers without informatics training attempt to perform computation-dependent analyses. Since 2005, the Galaxy project has worked to address this problem by providing a framework that makes advanced computational tools usable by non experts. Galaxy seeks to make data-intensive research more accessible, transparent and reproducible by providing a Web-based environment in which users can perform computational analyses and have all of the details automatically tracked for later inspection, publication, or reuse. In this report we highlight recently added features enabling biomedical analyses on a large scale.

Highlights

  • Started in 2005, Galaxy enables biologists without programming and systems administration expertise to perform computational analysis through the Web [1]

  • Histories, workflows and visualizations can all be shared with individuals, or they can be shared via the Web using links such as https://usegalaxy.org/u/jeremy/h/ hpac-exome-analysis Galaxy objects can be published; published items are listed together and available to all users

  • We have recently extended this interface to include citations so that scientists can reference the methods used in their analysis

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Summary

Introduction

Started in 2005, Galaxy (https://galaxyproject.org) enables biologists without programming and systems administration expertise to perform computational analysis through the Web [1]. Using the Galaxy GUI, users can upload their own data or retrieve data from public databases, choose analysis tools, set tool inputs and parameters and run tools. The Galaxy GUI includes a workflow editor where users can create automated, multistep analyses using drag and drop.

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