Tutorial:Introduction to Cytoscape-part2

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Slideshow Introduction to Cytoscape (30 min)
Handout Introduction_to_Cytoscape.pdf (9 pages)

Tutorial Sources Cytoscape Tutorial (Yeyejide Adeleye)
Tutorial Curators Anna Kuchinsky, Scooter Morris, Alex Pico

Cytoscape is an open source software tool for integrating, visualizing, and analyzing data in the context of networks. This tutorial is part two of the Introduction to Cytoscape tutorial and covers:

  1. Plugin Manager
  2. Network and Pathway Resources
  3. Plugin Demos

Plugin Manager

The Plugin Manager allows users to quickly and conveniently add extra features to Cytoscape directly from within Cytoscape, eliminating the need for manual searches through different websites to install and update plugins.

If you do not have Internet access enabled, you will not see the list of available plugins or be able to automatically update existing ones; however, you will still be able to view and delete previously installed plugins.

Install new plugins

  • Go to the Plugin Manager at Plugins -> Manage Plugins. On the left side of the window that pops up, you will see plugin folders labeled Currently Installed and Available for Install. Double-clicking on these will show sub-folders, and then the plugins themselves. To find out more about a specific plugin, click on its name to display some basic information on the right-hand side of the window.
Manage Plugins
  • Currently Installed folder contains a number of default plugins that are fully integrated in every copy of Cytoscape, as well as any additional installed plugins

Note: If you have plugins manually installed in your Cytoscape/plugins/ directory, they will not show up here, and you should avoid installing a second copy.

  • Available for Install folder displays plugins that may be installed.
  • To install jActiveModules: Search for "jactive", expand the Analysis folder and then select jActiveModules v2.23. Note: it may warn that it is not verified to work with this version. This simply means that a new version of Cytoscape was released after the plugin was release. Most plugins will continue to work after point releases.
  • Click on the Install button at the bottom of the window
  • Click on close to exit the Plugin Manager
  • Go to the Plugins menu and jActiveModules should appear in the list of plugins

To manually install a plugin

  • Go to the Cytoscape plugins page (http://cytoscape.org/plugins.html),
  • Scroll down to find the plugin
  • Click on the appropriate link to download the file, and then save it in the Cytoscape_v#.#.#/plugins folder on your hard drive.
  • Cytoscape will require a restart in order to load the manually installed plugin.

Network and Pathway Resources

But what if you don’t have a network? In this section we will cover some of the ways you can retrieve, construct and infer networks and pathways from public sources using Cytoscape and selected plugins.


  • Begin by downloading the GPML-Plugin from the Plugin Manager, which can be found under the Network and Attribute I/O folder.
  • Select File-> Import -> Network from web services
  • From the drop-down menu, select the WikiPathways Web Service Client
  • Enter a search term (‘tca’) and select a species (‘Saccharomyces cerevisiae’)
  • A list of relevant pathways is returned
  • Double-click on ‘Glycolysis and Gluconeogenesis’ to import the pathway

WikiPathways uses the GPML data format, which includes curated coordinates, graphical annotations and labels, in addition to the node and edge network. You can hide the annotation layer using View>Toggle GPML Annotations and then treat the network like any other network in Cytoscape.

Agilent Literature Search

Agilent Literature Search uses text mining technology to generate an "association" network from information extracted from the scientific literature. This can be useful in understanding how genes and proteins may interact in the context of a disease or other biological process.

  • To open Agilent Literature Search, go to Plugins->Agilent Literature Search
  • In Terms, enter "pda1" and "adh1"
  • In Context, enter "glycolysis"
  • Select Use Aliases. Notice the synonym for "adh1"
  • Select Concept Lexicon: Saccharomyces cerevisiae
  • Select Interaction Lexicon: "relaxed"
  • Click the blue Play button to execute the search. Your results will appear in the Query Matches window.
Agilent LitSearch Query Results

Non-default Data Mapping

When mapping data onto imported networks and pathways, you have to be aware of the key identifiers used in both your data and the imported network. For example, your network might have identifiers in an alternative column than "ID", and your data table might have identifiers in an alternative column that the first. The Attribute Importer provides advanced mapping options that allow you to specify which column in your data matches which column in your network.

  • Return to File-> Import->Attribute from Table (Text/MS Excel)
  • Select galExpData.pvals from the sampleData folder and then click on Open.
  • In the Advanced section, click Case Sensitive to deselect
  • In the Advanced section, select Show Text File Import Options
  • In the Delimiter section, select Space
  • In the Attribute Names section, select Transfer first line attribute names
  • Now select Show Mapping Options
  • Change Key Column in Annotation File from “GENE” to “COMMON”, and change Key Attribute for Network from “ID” to “canonicalName”
  • Click on the headers of the second set of redundant columns in the Preview to simply exclude them from import, or rename them by right-clicking
  • Click Import
  • Now go to the VizMapper tab in the Control Panel and locate the Node Color property. Double-click to activate.
  • Choose “gal1RG” and then choose “Continous”
  • Click on the color gradient to open the Gradient Editor
  • Set colors for end points and handles to create a color gradient
  • Notice the visualization of data on all imported pathways and networks!
Data visualization on Pathway

Figure: (left) Color gradient applied to pathway. (right) Same color gradient applied to literature network. Note: pathway and literature networks will look different as new information is incorporated over time

Extending Networks

This plugin also has an interactive feature that lets you expand a network using literature search results.

  • Go to the imported pathway “Glycolysis and Gluconeogenesis” and use the Search box to find “ADH1”
  • Right-click on the node and select Evidence from Literature -> Extend Network from Literature
  • Select and drag new nodes near ADH1, go to Layout -> CyLayouts -> Grid -> Selected Only, reposition grid in available space near ADH1

Note: You may want to update the Default node size for the GPML Visual Style to make the new nodes larger to see node fill color

Extended Network from Literature
  • Notice the automatic data mapping
  • Right-click on edges to new nodes to Evidence from Literature -> Gather Evidence from Literature to load the literature references
  • Right-click on the edge again to Evidence from Literature -> Show Sentences from Literature
  • You can use this procedure to extend known pathways based on literature findings and your visualized data

More Plugin Demos

If continuing from the above tutorial, you may want to restart Cytoscape at this time to clean the slate of unused networks, nodes and attributes. The following plugins all use the same demo file:

  • Go to File-> Open (click ‘Yes’ to losing current session)
  • You should see the Open a Session File Dialog
  • Open the sampleData folder and select galFiltered.cys and then click on Open

Plugin 1: Vista Clara

Usage: explore data in an interactive, visual spreadsheet

Note: If you don't already have the VistaClara plugin installed, you can install it from the Plugin Manager (refer to Section 1.3)

  • Select the VistaClara tab below the Data Panel
  • Click sync
  • It may be helpful to expand or undock the Data Panel
Data Panel

The first column on the left displays the automatically generated heatmap for all of your data. The last columns show the heatmap values for the selected range of data. Note: some columns of data may not be recognized (e.g., gal80R), or may not be properly formatted.

  • To fix the formatting of any column of data, simply right-click on the column header, choose format and the correct value. Try ‘log2 ratio’ for all the fold values in the galFiltered dataset.
  • Right-click on any column and select sort to sort by values
  • Select or drag anywhere in the heatmap to scroll through the data values
  • Select a column of heatmap data to visualize the data on the network
  • Click the play button to cycle through all heatmap columns
  • Notice that a ‘VistaClara’ visual style has been created in the VizMapper. You can select your previous visual styles to return to your custom view at any time

Plugin 2: Cluster Maker

The clusterMaker plugin provides a general framework for clustering and visualizing clusters of Cytoscape node and edge attributes. One of the primary use cases for clusterMaker is to support the analysis of expression data using either hierarchical or k-means clustering. Other uses include the analysis of epistatic mapping (E-MAP) data as well as clustering protein similarity networks to assign nodes to putative protein families.

Usage: perform and visualize cluster analyzes

The ClusterMaker plugin is available from the Plugin Manager (refer to Section 1.3)

  • Select Cluster->Hierarchical cluster from the Plugins menu
  • Use ctrl (or cmd on Macs) to select the three columns of fold value data (gal1RGexp, gal4RGexp, and gal80Rexp)
  • Click Create Clusters Note: this is very fast so don't be surprised if you see the finished dialog immediately
  • Click Visualize Clusters
ClusterMaker TreeView

This is a standard cluster view with the complete heatmap on the left, the selection heatmap in the middle and the gene names on the right.

  • Click Settings… to adjust the contrast, color gradient, or data range
  • Click and drag on the heatmap to select rows; Shift-click on heatmap to select individual columns
  • Select a column and then click Map Colors Onto Network… to create a visual style from the cluster heatmaps, visualizing the data on your network
  • If you select a row in the heatmap and then click Map Colors Onto Network…, a dialog will pop up asking which columns you want to use; select all three and click Animate Vizmap

Now zoom out and watch your network come alive with data! You can use this view to identify “hot spots” in your network. Hit Stop Animation to end the cycle. And use VizMapper to switch back to any prior visual style.

Plugin 3: BiNGO

Usage: perform and visualize overrepresentation analyzes

The BiNGO plugin is available from the Plugin Manager (refer to Section 1.3)

  • Select BiNGO from the Plugins menu
  • Select a subset of nodes from the network, e.g.
    • Select a cluster from the ClusterMaker analysis
    • Select based on sorted or filtered data values in the Data Panel
  • Provide a name for the cluster
  • Review other settings (optional for this tutorial)
  • Click ‘Start BiNGO’
  • You will be greeted with a table of ranked GO terms and statistics, and a network visualization of the GO terms colored by significance, and a legend window explaining the color gradient

The long GO term names can make the network difficult to read. You can use Force-directed layout and Layout>Scale to increase the spacing between nodes. Hierarchical layout is also nice, though the names overlap even worse.

BiNGO demo
  • Play with the cluster selection and BiNGO parameters to explore the analytical possibilities with your data.