The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update

• Published in: Nucleic acids research Vol. 44; no. W1; pp. W3 - W10
• Main Authors: Afgan, Enis, Baker, Dannon, van den Beek, Marius, Blankenberg, Daniel, Bouvier, Dave, Čech, Martin, Chilton, John, Clements, Dave, Coraor, Nate, Eberhard, Carl, Grüning, Björn, Guerler, Aysam, Hillman-Jackson, Jennifer, Von Kuster, Greg, Rasche, Eric, Soranzo, Nicola, Turaga, Nitesh, Taylor, James, Nekrutenko, Anton, Goecks, Jeremy
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 08.07.2016
• Subjects: Bioengineering; Biomedical Research; Computational Biology - methods; Computational Biology - statistics & numerical data; Databases, Genetic; Datasets as Topic - statistics & numerical data; Humans; Internet; Life Sciences; Reproducibility of Results; User-Computer Interface; Web Server issue
• ISSN: 0305-1048; 1362-4962
• DOI: 10.1093/nar/gkw343

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.