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Genome Biol. 2019 Sep 2;20(1):185. doi: 10.1186/s13059-019-1758-4.

Cytoscape Automation: empowering workflow-based network analysis.

Author information

1
Department of Medicine, University of California, La Jolla, San Diego, CA, 92093, USA.
2
University of California, San Francisco, San Francisco, CA, 94143, USA.
3
Bioinformatics Core Facility, Max Planck Institute for Biology of Ageing, Cologne, Germany.
4
Gladstone Institutes, San Francisco, CA, 94158, USA.
5
Department of Medicine, University of California, La Jolla, San Diego, CA, 92093, USA. bdemchak@ucsd.edu.

Abstract

Cytoscape is one of the most successful network biology analysis and visualization tools, but because of its interactive nature, its role in creating reproducible, scalable, and novel workflows has been limited. We describe Cytoscape Automation (CA), which marries Cytoscape to highly productive workflow systems, for example, Python/R in Jupyter/RStudio. We expose over 270 Cytoscape core functions and 34 Cytoscape apps as REST-callable functions with standardized JSON interfaces backed by Swagger documentation. Independent projects to create and publish Python/R native CA interface libraries have reached an advanced stage, and a number of automation workflows are already published.

KEYWORDS:

Cytoscape; Interoperability; Microservice; REST; Reproducibility; Service-oriented architecture; Workflow

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