Galaxy (computational biology)

Galaxy (computational biology)

Stable release 15.03 / 18 March 2015 (2015-03-18)
Development status Active
Written in Python, JavaScript
Operating system Unix-like
Available in English
Type Scientific workflow, data integration, analysis and data publishing
License Academic Free License[1]
Website GalaxyProject.org

Galaxy[2][3][4] is a scientific workflow, data integration,[5][6] and data and analysis persistence and publishing platform that aims to make computational biology accessible to research scientists that do not have computer programming experience. Although it was initially developed for genomics research, it is largely domain agnostic and is now used as a general bioinformatics workflow management system.[7]

Functionality

Galaxy is a scientific workflow system. These systems provide a means to build multi-step computational analyses akin to a recipe. They typically provide a graphical user interface[8] for specifying what data to operate on, what steps to take, and what order to do them in.

Galaxy is also a data integration platform for biological data. It supports data uploads from the user's computer, by URL, and directly from many online resources (such as the UCSC Genome Browser, BioMart and InterMine). Galaxy supports a range of widely used biological data formats, and translation between those formats. Galaxy provides a web interface to many text manipulation utilities, enabling researchers to do their own custom reformatting and manipulation without having to do any programming. Galaxy includes interval manipulation utilities for doing set theoretic operations (e.g. intersection, union, ...) on intervals. Many biological file formats include genomic interval data (a frame of reference, e.g., chromosome or contig name, and start and stop positions), allowing these data to be integrated.

Galaxy was originally written for biological data analysis, particularly genomics. The set of available tools has been greatly expanded over the years and Galaxy is now also used for gene expression, genome assembly, proteomics, epigenomics, transcriptomics and host of other disciplines in the life sciences. The platform itself is actually domain agnostic and can be applied, in theory, to any scientific domain. For example, Galaxy servers exist for image analysis,[9] computational chemistry[10] and drug design,[11] cosmology, climate modeling, social science,[12] and linguistics.

Finally, Galaxy also supports data and analysis persistence and publishing. See Reproducibility and Transparency below.

Project Goals

Galaxy is "an open, web-based platform for performing accessible, reproducible, and transparent genomic science."[13]

Accessibility

Computational biology is a specialized domain that often requires knowledge of computer programming. Galaxy aims to give biomedical researchers access to computational biology without also requiring them to understand computer programming.[14][15] Galaxy does this by stressing a simple user interface[16] over the ability to build complex workflows. This design choice makes it relatively easy to build typical analyses, but more difficult to build complex workflows that include, for example, looping constructs. (See Apache Taverna for an example of a data-driven workflow system that supports looping.[17])

Reproducibility

Reproducibility is a key goal of science: When scientific results are published the publications should include enough information that others can repeat the experiment and get the same results. There have been many recent efforts to extend this goal from the bench (the "wet lab") to computational experiments (the "dry lab") as well. This has proved to be a more difficult task than initially expected.[18]

Galaxy supports reproducibility by capturing sufficient information about every step in a computational analysis, so that the analysis can be repeated, exactly, at any point in the future. This includes keeping track of all input, intermediate, and final datasets, as well as the parameters provided to, and the order of each step of the analysis.

Transparency

Galaxy supports transparency in scientific research by enabling researchers to share any of their Galaxy Objects either publicly, or with specific individuals. Shared items can be examined in detail, rerun at will and copied and modified to test hypotheses.

Galaxy Objects: Histories, Workflows, Datasets and Pages

Galaxy objects are anything that can be saved, persisted, and shared in Galaxy:

Histories
Histories are computational analyses (recipes) run with specified input datasets, computational steps and parameters. Histories include all intermediate and output datasets as well.
Workflows
Workflows are computational analyses that specify all the steps (and parameters) in the analysis, but none of the data. Workflows are used to run the same analysis against multiple sets of input data.
Datasets
Datasets includes any input, intermediate, or output dataset, used or produced in an analysis.
Pages
Histories, workflows and datasets can include user-provided annotation. Galaxy Pages enables the creation of a virtual paper that describes the how and why of the overall experiment. Tight integration of Pages with Histories, Workflows, and Datasets supports this goal.

Availability

Galaxy is available:

  1. As a free public web server,[19] supported by the Galaxy Project.[20] This server includes many bioinformatics tools that are widely useful in many areas of genomics research. Users can create logins, and save histories, workflows, and datasets on the server. These saved items can also be shared with others.
  2. As open-source software that can be downloaded, installed and customized to address specific needs.[21] Galaxy can be installed locally or using a computing cloud.[22]
  3. Public web servers hosted by other organizations.[23] Several organizations with their own Galaxy installation have also opted to make those servers available to others.
  4. As part of the GenomeSpace initiative.

Implementation

Galaxy is open-source software implemented using the Python programming language. It is developed by the Galaxy team[24] at Penn State and Johns Hopkins University, and the Galaxy Community.[25]

Galaxy is extensible, as new command line tools can be integrated and shared within the Galaxy ToolShed.[26]

An example of extending Galaxy is Galaxy-P from the University of Minnesota Supercomputing Institute, which is customized as a data analysis platform for mass spectrometry-based proteomics.[27]

Community

Galaxy is an open source project and the community includes users, organizations that install their own instance, Galaxy developers, and bioinformatics tool developers. The Galaxy project has mailing lists,[28] a community wiki,[29] and annual meetings.[30]

See also

External links

References

  1. ↑ https://wiki.galaxyproject.org/Admin/License
  2. ↑ Goecks, J.; Nekrutenko, A.; Taylor, J.; Galaxy Team, T. (2010). "Galaxy: A comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences". Genome Biology 11 (8): R86. doi:10.1186/gb-2010-11-8-r86. PMC 2945788. PMID 20738864.
  3. ↑ Blankenberg, D.; Kuster, G. V.; Coraor, N.; Ananda, G.; Lazarus, R.; Mangan, M.; Nekrutenko, A.; Taylor, J. (2010). "Galaxy: A Web-Based Genome Analysis Tool for Experimentalists". In Frederick M. Ausubel. Current Protocols in Molecular Biology. pp. Unit Un19.10.Un19–21. doi:10.1002/0471142727.mb1910s89. ISBN 0471142727. PMID 20069535.
  4. ↑ Taylor, J.; Schenck, I.; Blankenberg, D.; Nekrutenko, A. (2007). "Using Galaxy to Perform Large-Scale Interactive Data Analyses". In Andreas D. Baxevanis. Current Protocols in Bioinformatics. pp. Unit Un10.5. doi:10.1002/0471250953.bi1005s19. ISBN 0471250953. PMC 3418382. PMID 18428782.
  5. ↑ Blankenberg, D.; Coraor, N.; Von Kuster, G.; Taylor, J.; Nekrutenko, A.; Galaxy, T. (2011). "Integrating diverse databases into an unified analysis framework: A Galaxy approach". Database 2011: bar011. doi:10.1093/database/bar011. PMC 3092608. PMID 21531983.
  6. ↑ Blankenberg, D.; Gordon, A.; Von Kuster, G.; Coraor, N.; Taylor, J.; Nekrutenko, A.; Galaxy, T. (2010). "Manipulation of FASTQ data with Galaxy". Bioinformatics 26 (14): 1783–1785. doi:10.1093/bioinformatics/btq281. PMC 2894519. PMID 20562416.
  7. ↑ https://wiki.galaxyproject.org/PublicGalaxyServers
  8. ↑ Schatz, M. C. (2010). "The missing graphical user interface for genomics". Genome Biology 11 (8): 128–201. doi:10.1186/gb-2010-11-8-128. PMC 2945776. PMID 20804568.
  9. ↑ http://cloudimaging.net.au/
  10. ↑ Hildebrandt, A. K.; Stöckel, D; Fischer, N. M.; de la Garza, L; Krüger, J; Nickels, S; Röttig, M; Schärfe, C; Schumann, M; Thiel, P; Lenhof, H. P.; Kohlbacher, O; Hildebrandt, A (2014). "Ballaxy: Web services for structural bioinformatics". Bioinformatics 31: 121–2. doi:10.1093/bioinformatics/btu574. PMID 25183489.
  11. ↑ http://osddlinux.osdd.net:8001/
  12. ↑ http://socscicompute.ss.uci.edu/
  13. ↑ Goecks, J.; Nekrutenko, A.; Taylor, J.; Galaxy Team, T. (2010). "Galaxy: A comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences". Genome Biology 11 (8): R86. doi:10.1186/gb-2010-11-8-r86. PMC 2945788. PMID 20738864.
  14. ↑ Blankenberg, D.; Taylor, J.; Nekrutenko, A.; The Galaxy, T. (2011). "Making whole genome multiple alignments usable for biologists". Bioinformatics 27 (17): 2426–8. doi:10.1093/bioinformatics/btr398. PMC 3157923. PMID 21775304.
  15. ↑ Blankenberg, D.; Taylor, J.; Schenck, I.; He, J.; Zhang, Y.; Ghent, M.; Veeraraghavan, N.; Albert, I.; Miller, W.; Makova, K. D.; Hardison, R. C.; Nekrutenko, A. (2007). "A framework for collaborative analysis of ENCODE data: Making large-scale analyses biologist-friendly". Genome Research 17 (6): 960–964. doi:10.1101/gr.5578007. PMC 1891355. PMID 17568012.
  16. ↑ Schatz, M. C. (2010). "The missing graphical user interface for genomics". Genome Biology 11 (8): 128–201. doi:10.1186/gb-2010-11-8-128. PMC 2945776. PMID 20804568.
  17. ↑ Soiland-Reyes, S (2010-12-13). "Looping". The Taverna Knowledge Blog. knowledgeblog.org. Retrieved 28 January 2015.
  18. ↑ Ioannidis, J. P. A.; Allison, D. B.; Ball, C. A.; Coulibaly, I.; Cui, X.; Culhane, A. N. C.; Falchi, M.; Furlanello, C.; Game, L.; Jurman, G.; Mangion, J.; Mehta, T.; Nitzberg, M.; Page, G. P.; Petretto, E.; Van Noort, V. (2008). "Repeatability of published microarray gene expression analyses". Nature Genetics 41 (2): 149–155. doi:10.1038/ng.295. PMID 19174838.
  19. ↑ https://usegalaxy.org/
  20. ↑ http://galaxyproject.org/
  21. ↑ http://getgalaxy.org/
  22. ↑ Afgan, E.; Baker, D.; Coraor, N.; Chapman, B.; Nekrutenko, A.; Taylor, J. (2010). "Galaxy CloudMan: Delivering cloud compute clusters". BMC Bioinformatics 11: S4. doi:10.1186/1471-2105-11-S12-S4. PMC 3040530. PMID 21210983.
  23. ↑ https://wiki.galaxyproject.org/PublicGalaxyServers
  24. ↑ https://wiki.galaxyproject.org/GalaxyTeam
  25. ↑ Lazarus, R.; Taylor, J.; Qiu, W.; Nekrutenko, A. (2008). "Toward the commoditization of translational genomic research: Design and implementation features of the Galaxy genomic workbench". Summit on translational bioinformatics 2008: 56–60. PMC 3041519. PMID 21347127.
  26. ↑ Blankenberg, Daniel; Von Kuster, Gregory; Bouvier, Emil; Baker, Dannon; Afgan, Enis; Stoler, Nicholas; Taylor, James; Nekrutenko, Anton (2014). "Dissemination of scientific software with Galaxy ToolShed". Genome Biology 15 (2): 403. doi:10.1186/gb4161. PMID 25001293.
  27. ↑ Sheynkman, GM; Johnson, JE; Jagtap, PD; Shortreed, MR; Onsongo, G; Frey, BL; Griffin, TJ; Smith, LM (22 August 2014). "Using Galaxy-P to leverage RNA-Seq for the discovery of novel protein variations.". BMC Genomics 15 (703). doi:10.1186/1471-2164-15-703. PMID 25149441.
  28. ↑ https://wiki.galaxyproject.org/MailingLists
  29. ↑ https://wiki.galaxyproject.org/
  30. ↑ https://wiki.galaxyproject.org/Events
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