Help Login Create account

Data released on October 06, 2017

Supporting data for "An Architecture for Genomics in a Clinical Setting Using Galaxy and Docker"

Barritault, M; Baudoin, D; Blons, H; Burgun, A; Countouris, H; Digan, W; Laurent-Puig, P; Rance, B (2017): Supporting data for "An Architecture for Genomics in a Clinical Setting Using Galaxy and Docker" GigaScience Database. RIS BibTeX Text

Next Generation Sequencing is used on a daily basis to perform molecular analysis to determine subtypes of disease (e.g. in cancer) and to assist in the selection of the optimal treatment. Clinical bioinformatics handles the manipulation of the data generated by the sequencer, from the generation to the analysis and interpretation. Reproducibility and traceability are crucial issues in a clinical setting.
We have designed an approach based on the Docker container technology and Galaxy, the popular bioinformatics analysis support open-source software. Our solution simplifies the deployment of a small size analytical platform, and simplifies the process for the clinician. From the technical point of view, the tools embedded in the platform are isolated and versioned through docker images. Along the Galaxy platform, we also introduce the AnalysisManager, a solution allowing single-click analysis for the biologists and leveraging standardized bioinformatics APIs. We added a Shiny/R interactive environment to ease the visualization of the outputs.
The platform relies on containers and ensures the data traceability by recording analytical actions, and by associating inputs and outputs of the tools to the EDAM ontology through ReGaTe. The source code is freely available on Github at .

Contact Submitter

Read the peer-reviewed publication(s):

Digan, W., Countouris, H., Barritault, M., Baudoin, D., Laurent-Puig, P., Blons, H., … Rance, B. (2017). An architecture for genomics analysis in a clinical setting using Galaxy and Docker. GigaScience, 6(11), 1–9. doi:10.1093/gigascience/gix099

Additional information:


galaxy regate docker reproducibility 




  • Funding body - Institut National Du Cancer
  • Awardee - W Digan
  • Funding body - SIRIC
  • Award ID - CARPEM
  • Awardee - B Rance
  • Funding body - Cancérop_le _le-de-France
  • Awardee - D Baudoin
  • Funding body - SIRIC
  • Award ID - CARPEM
  • Awardee - H Countouris

Files: (FTP site) Table Settings


File Description
Sample ID
Data Type
File Format
Release Date
Download Link
File Attributes

File NameSample IDData TypeFile FormatSizeRelease Date 
GitHub archivearchive14.44 MB2017-09-29
ReadmeTEXT1.98 KB2017-09-29
Displaying 1-2 of 2 File(s).



Other datasets you might like: