A travel guide to Cytoscape plugins

Abstract

Cytoscape is open-source software for integration, visualization and analysis of biological networks. It can be extended through Cytoscape plugins, enabling a broad community of scientists to contribute useful features. This growth has occurred organically through the independent efforts of diverse authors, yielding a powerful but heterogeneous set of tools. We present a travel guide to the world of plugins, covering the 152 publicly available plugins for Cytoscape 2.5-2.8. We also describe ongoing efforts to distribute, organize and maintain the quality of the collection.

Figure 1

Statistics for registered Cytoscape plugins. (a) Countries of origin for each plugin based on contact e-mail addresses and affiliations. (b) Bottom, number of downloads for each plugin, sorted by number of total downloads. Top, plugin names are shown for the top 20 plugins. The name and number of downloads for each plugin is in Supplementary Figure 6.

Figure 2

Network analysis workflow. Specific genes or attributes (blue) typically gathered in preparation for network analysis are imported and used for network generation (red). Many different types of networks are available (green) for import, after which Cytoscape visualization enables users to efficiently explore and biologically interpret the network (orange). Subsequent network analysis invokes computational algorithms or statistics to interpret and organize interactions (red). Commonly used plugins associated with each level are listed.

Figure 3

Relationships between Cytoscape plugins and tags. (a,b) Zoomed figure (a) and wide view (b) of relationship map. Orange diamonds, tags; blue rectangles, plugins. The full map of the plugin tags can be found in Supplementary Figure 1. (c) Percentages of plugins with indicated tags. A plugin is counted once for each tag assignment; it is counted multiple times if it is assigned multiple tags. Note that only plugins which passed our basic validation test are shown.

Figure 4

Examples of plugin outputs. (a) AgilentLiteratureSearch plugin. Human transcription factors FOS and JUN are input as an example. A network created by literature mining (left) and abstracts of scientific papers used to derive the network (right) are shown. (b) Application of MCODE to the mouse protein-protein interaction network in BioGRID. Modules extracted from the network are shown. (c) BiNGO plugin. A subnetwork containing dense kinase-substrate interactions is analyzed, with cell cycle related genes found to be enriched.