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Colony: a framework for reproducible and easy-to-use data analysis pipelines for biomedical research with singularity
Sebastian Eschner1, Mohammad Alabdullah2, Martin Dugas1
1Institute of Medical Informatics, Heidelberg University Hospital, 69120 Heidelberg, Germany.
Summary:
Bioinformatics pipelines should meet the FAIR criteria to enable reproducible analysis. FAIR describes four key requirements for reproducible research: findability, accessibility, interoperability and reusability. Software containers such as Singularity are widely used tools that facilitate the reuse of software across different computing environments. However, many biologists and other researchers find command line tools such as Singularity unfamiliar and do not feel productive when using software via the command line. We present a graphical user interface that allows biologists without programming experience to interact with containerized software. We evaluate the feasibility of our approach with software used at the TRR156.
Availability And Implementation:
Colony can be freely downloaded on its project page: https://clipc-jpg.github.io/ColonyWebsite/. The Colony launcher's code is MIT-licensed and freely available at: https://github.com/clipc-jpg/Colony. All related assets can be found at: https://doi.org/10.7910/DVN/Z3OTWY.
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