The Planemo toolkit for developing, deploying, and executing scientific data analyses in Galaxy and beyond
- Simon Bray1,7,
- John Chilton2,7,
- Matthias Bernt3,
- Nicola Soranzo4,
- Marius van den Beek2,
- Bérénice Batut1,
- Helena Rasche5,
- Martin Čech2,
- Peter J.A. Cock6,
- Björn Grüning1 and
- Anton Nekrutenko2
- 1Bioinformatics Group, Department of Computer Science, Albert-Ludwigs-University Freiburg, 79110 Freiburg, Germany;
- 2Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, Pennsylvania 16802, USA;
- 3Department of Computational Biology, Helmholtz Centre for Environmental Research GmbH-UFZ, 04318 Leipzig, Germany;
- 4Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, United Kingdom;
- 5Clinical Bioinformatics Group, Department of Pathology, Erasmus Medical Center, 3015 CN, Rotterdam, The Netherlands; Academie voor de Technologie van Gezondheid en Milieu, Avans Hogeschool, 4818 AJ Breda, The Netherlands;
- 6James Hutton Institute, Invergowrie, Dundee DD2 5DA, United Kingdom
-
↵7 These authors contributed equally to this work.
Abstract
There are thousands of well-maintained high-quality open-source software utilities for all aspects of scientific data analysis. For more than a decade, the Galaxy Project has been providing computational infrastructure and a unified user interface for these tools to make them accessible to a wide range of researchers. To streamline the process of integrating tools and constructing workflows as much as possible, we have developed Planemo, a software development kit for tool and workflow developers and Galaxy power users. Here we outline Planemo's implementation and describe its broad range of functionality for designing, testing, and executing Galaxy tools, workflows, and training material. In addition, we discuss the philosophy underlying Galaxy tool and workflow development, and how Planemo encourages the use of development best practices, such as test-driven development, by its users, including those who are not professional software developers.
Footnotes
-
[Supplemental material is available for this article.]
-
Article published online before print. Article, supplemental material, and publication date are at https://www.genome.org/cgi/doi/10.1101/gr.276963.122.
-
Freely available online through the Genome Research Open Access option.
- Received May 25, 2022.
- Accepted January 11, 2023.
This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.
