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Nucleic Acids Res. 2016 Jul 8;44(W1):W3-W10. doi: 10.1093/nar/gkw343. Epub 2016 May 2.

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

Author information

1
Department of Biology, Johns Hopkins University, Baltimore, MD USA.
2
Institut de Biologie Paris-Seine, Université Pierre et Marie Curie, Paris, France.
3
Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA.
4
Department of Computer Science, Albert-Ludwigs-University, Freiburg, Freiburg, Germany Center for Biological Systems Analysis (ZBSA), University of Freiburg, Freiburg, Germany.
5
Academic Computing Services, Penn State University, University Park, PA, USA.
6
Department of Biochemistry and Biophysics, Texas A&M University, College Station, TX, USA.
7
The Genome Analysis Centre, Norwich, United Kingdom.
8
Department of Biology, Johns Hopkins University, Baltimore, MD USA james@taylorlab.org.
9
Department of Biochemistry and Molecular Biology, Penn State University, University Park, PA, USA anton@nekrut.org.
10
The Computational Biology Institute, George Washington University, Washington DC, USA jgoecks@gwu.edu.

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.

PMID:
27137889
PMCID:
PMC4987906
DOI:
10.1093/nar/gkw343
[Indexed for MEDLINE]
Free PMC Article

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