This document is licensed under the Creative Commons license, 2006

Authors: The Cytoscape Collaboration

The Cytoscape project is an ongoing collaboration between:

Funding for Cytoscape is provided by a federal grant from the U.S. National Institute of General Medical Sciences (NIGMS) of the National Institutes of Health (NIH) under award number GM070743-01. Corporate funding is provided through a contract from Unilever PLC.

Cytoscape is a project dedicated to building open-source network visualization and analysis software. A software "Core" provides basic functionality to layout and query the network and to visually integrate the network with state data. The Core is extensible through a plug-in architecture, allowing rapid development of additional computational analyses and features.

Cytoscape's roots are in Systems Biology, where it is used for integrating biomolecular interaction networks with high-throughput expression data and other molecular state information. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape allows the visual integration of the network with expression profiles, phenotypes, and other molecular state information, and links the network to databases of functional annotations.

The central organizing metaphor of Cytoscape is a network (graph), with genes, proteins, and molecules represented as nodes and interactions represented as links, i.e. edges, between nodes.

Development

Cytoscape is a collaborative project between the Institute for Systems Biology (Leroy Hood lab), the University of California San Diego (Trey Ideker lab), Memorial Sloan-Kettering Cancer Center (Chris Sander lab), the Institut Pasteur (Benno Schwikowski lab), Agilent Technologies (Annette Adler lab) and the University of California, San Francisco (Bruce Conklin lab).

Visit http://www.cytoscape.org for more information.

License

Cytoscape is protected under the GNU LGPL (Lesser General Public License). The License is included as an appendix to this manual, but can also be found online: http://www.gnu.org/copyleft/lesser.txt. Cytoscape also includes a number of other open source libraries, which are detailed in the Cytoscape_User_Manual/Acknowledgements below.

What’s New in @version@

Cytoscape version @version@ contains several new features, plus improvements to the performance and usability of the software.

Node Custom Graphics

Internally, Cytoscape has Custom Graphics API for developers since 2.3. From this version, end-users can access this feature from standard VizMap GUI. You can add up to nine Custom Graphics objects per node. Each Custom Graphics object has position Visual Property and you can adjust its position from intuitive GUI.

Attribute Functions

Attribute values can now be spreadsheet-like formulas. In particular, an attribute on a node/edge can reference other attributes on the same node/edge. About 40 built-in functions have been provided and it is relatively easy to implement a Cytoscape plug-in of your own to add additional functions. (An example plug-in can be found with the other plug-in tutorials.) Arbitrarily complex arithmetic, string and logical/boolean expressions are supported as well as limited list construction. The syntax closely follows that of Microsoft Excel^tm.

Other New Features and Bug Fixes

• Plugin search: you can now search plugins by keyword(s).
• Many, many bug fixes!

Please Cite Cytoscape!

Cytoscape is a non-profit, open source project. To help make the Cytoscape project sustainable, your support is essential! Since Cytoscape project depends on government/private grants, citation is the most important support for us. When you publish papers/books/posters, please cite the following paper:

• Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T.

  Cytoscape: a software environment for integrated models of biomolecular interaction networks.

  Genome Research 2003 Nov; 13(11):2498-504

Cytoscape is a Java application verified to run on Linux, Windows, and Mac OS X. Although not officially supported, other UNIX platforms such as Solaris or FreeBSD may run Cytoscape if Java version 5 or later is available for the platform.

System requirements

The system requirements for Cytoscape depend on the size of the networks the user wants to load, view and manipulate.

Getting Started

Install Java

If not already installed on your computer, download and install Java SE 5 or 6. Cytoscape 2.5 will no longer run with Java version 1.4.x or lower. You must install Java SE 5 or 6!!!

These can be found at:

Java SE 5 Java SE 6

In general, Java SE 6 is faster than 5. If your machine is compatible with the 6 series, please try version 6.

Install Cytoscape

A quick note on upgrading

There should really be no issue in upgrading. If you have a previous installation you have two options: 1) Starting with a clean slate: For this you should delete your previous installation directory and the .cytoscape directory. 2) Just keep what you have and simply pick a distinct, new directory for installation. In the unlikely event that you should encounter any problem, delete the .props files in your .cytoscape directory. If that doesn't help try deleting the .cytoscape directory. This latter step will cause you to loose all your plugins that you have installed via the plugin manager, so only do that if you are having problems or if you don't mind reinstalling your plugins. The core plugins will not be affected by this step.

There are a number of options for downloading and installing Cytoscape. All options can be downloaded from the http://cytoscape.org website.

• Automatic installation packages exist for Windows, Mac OS X, and Linux platforms.
• You can install Cytoscape from a compressed archive distribution.
• You can build Cytoscape from the source code.

• You can check out the latest and greatest software from our Subversion repository.

Cytoscape installations (regardless of platform) containing the following files and directories:

* From Ideker et al., Science 292:929 (2001)

** Obtained from data hosted at http://www.blueprint.org/bind/bind_downloads.html

** From von Mering et al., Nature, 417:399 (2002) and Lee et al, Science 298:799 (2002)

**** Created from Cytoscape tutorial web page. Original data sets are available at: http://www.cytoscape.org/cgi-bin/moin.cgi/Data_Sets/ from "A merged human interactome" by Andrew Garrow, Yeyejide Adeleye and Guy Warner (Unilever, Safety and Environmental Assurance Center).

Launch the application

Double-click on the icon created by the installer or by running cytoscape.sh from the command line (Linux or Mac OS X) or double-clicking cytoscape.bat (Windows). Alternatively, you can pass the .jar file to Java directly using the command java -Xmx512M -jar cytoscape.jar -p plugins. The -Xmx512M flag tells java to allocate more memory for Cytoscape and the -p plugins option tells cytoscape to load all of the plugins in the plugins directory. Loading the plugins is important because many key features like layouts, filters and the attribute browser are included with Cytoscape as plugins in the plugins directory. See the Command Line chapter for more detail. In Windows, it is also possible to directly double-click the .jar file to launch it. However, this does not allow specification of command-line arguments (such as the location of the plugin directory).

When you succeed in launching Cytoscape, a window will appear that looks like this (captured on Mac OS 10.4):

Note on Memory Consumption

For users interested in loading large networks, the amount of memory needed by Cytoscape will increase. Memory usage depends on both number of network objects (nodes+edges) and the number of attributes. Here are some rough suggestions for memory allocation:

Suggested Memory Size Without View

Suggested Memory Size With View

Overall Memory Size for Cytoscape

To increase the maximum memory size for Cytoscape, you can specify it in a file, residing in the same directory as the Cytoscape executable, called Cytoscape.vmoptions with one option per line and lines separated by linefeeds. The last line must also be followed by a linefeed. The one exception to this rule is the MacOS platform if you are launching Cytoscape by clicking on the Cytoscape icon. (In that case you will have to edit the .../Cytoscape.app/Contents/Info.plist file instead!) For example, if you want to assign 1GB of memory, create the Cytoscape.vmoptions file containing the single line (Do not forget the linefeed at the end of the line!):

-Xmx1GB

Stack Size

There is one more option related to memory allocation. Some of the functions in Cytoscape use larger stack space (a temporary memory for some operations, such as Layout). Since this value is set independently from the Xmx value above, sometimes Layout algorithms fails due to the out of memory error. To avoid this, you can set larger heap size by using the -Xss option. If layout fails for large networks, please try the following:

-Xmx1GB -Xss10M

The option -Xss10M means set the heap size to 10MB. In many cases, this solves out of memory error for Layouts.

Randomly generated scale-free network with 500K nodes and 500k edges: If memory parameters are set properly, you can visualize huge networks. In this example, about 5GB of memory is used by Cytoscape. Stack size is set to 10MB. To use large memory space (4GB+) you need 64-bit version operating system AND 64-bit version Java SE 5 or 6.

Note: Some of the web service clients are multi-thread programs and each thread uses the memory size specified by -Xss option. If web service clients fails due to the out of memory error, please reduce the stack size and try again.

For more details, see How_to_increase_memory_for_Cytoscape.

Note on Directory Location

For the application to work properly, all files should be left in the directory in which they were unpacked. The core Cytoscape application assumes this directory structure when looking for the various libraries needed to run the application. If you are adventurous, you can get creative with the $CLASSPATH and/or the cytoscape.jar manifest file and run Cytoscape from any location you want.

When a network is loaded, Cytoscape will look something like the image below:

The main window here has several components:

• The menu bar at the top (see below for more information about each menu).
• The toolbar, which contains icons for commonly used functions. These functions are also available via the menus. Hover the mouse pointer over an icon and wait momentarily for a description to appear as a tooltip.
• The network management panel (top left panel). This contains an optional network overview pane (shown at the bottom left).
• The main network view window, which displays the network.
• The attribute browser panel (bottom panel), which displays attributes of selected nodes and edges and enables you to modify the values of attributes.

The network management and attribute browser panels are dockable tabbed panels known as CytoPanels. You can undock any of these panels by clicking on the Float Window control in the upper-right corner of the CytoPanel.

If you select this control, e.g. on the attribute browser panel, you will now have two Cytoscape windows, the main window, and a new window labeled CytoPanel 2, similar to the one shown below. Popup will be displayed when you put the mouse pointer on a cell.

Note that CytoPanel 2 now has a Dock Window control. If you select this control, the window will dock onto the main window.

Cytoscape also has an editor that enables you to build and modify networks interactively by dragging and dropping nodes and edges from a palette onto the main network view window. The Node shapes and Edge arrows on the palette are defined by the currently used Visual Style. To edit a network, just select the Editor tab on CytoPanel 1. An example of an editor, with the palette contained in CytoPanel 1 and defined by the BioMoleculeEditor Visual Style, is shown below.

The Menus

File

The File menu contains most basic file functionality: File → Open for opening a Cytoscape session file; File → New for creating a new network, either blank for editing, or from an existing network; File → Save for saving a session file; File → Import for importing data such as networks and attributes; and File → Export for exporting data and images. Also, File → Print allows printing, while File → Quit closes all windows of Cytoscape and exits the program.

Edit

The Edit menu contains Undo and Redo functions which undo and redo edits made in the Attribute Browser, the Network Editor and to layout.

There are also options for creating and destroying views (graphical representations of a network) and networks (the raw network data – not yet visualized), as well as an option for deleting selected nodes and edges from the current network. All deleted nodes and edges can be restored to the network via Edit → Undo. Editing preferences for properties and plugins is found under Edit → Preferences → Properties... .

View

The View menu allows you to display or hide the network management panel (CytoPanel 1), the attribute browser (CytoPanel 2), the Network Overview (in CytoPanel 1), and the VizMapper.

Select

The Select menu contains different options for selecting nodes and edges. It also contains the Select → Use Filters option, which allows filters to be created for automatic selection of portions of a network whose node or edge attributes meet a filtering criterion.

Layout

The Layout menu has an array of features for visually organizing the network. The features in the top portion of the network (Rotate, Scale, Align and Distribute) are tools for manipulating the network visualization. The bottom section of the menu lists a variety of layout algorithms which automatically lay a network out.

Plugins

The Plugins menu contains options for managing (install/update/delete) your plugins and may have options added by plugins that have been installed, such as the Agilent Literature Search or Merge Networks. Depending on which plugins are loaded, the plugins that you see may be different than what appear here.

Help

The Help menu allows you to launch the online help viewer and browse the table of contents for this manual. The “About…” option displays information about the running version of Cytoscape.

Network Management

Cytoscape 2.3 and newer versions allow multiple networks to be loaded at a time, either with or without a view. A network stores all the nodes and edges that are loaded by the user and a view displays them. You can have many views of the same network. Networks (and their optionally associated views) can be organized hierarchically.

An example where a number of networks have been loaded and arranged hierarchically is shown below:

The network manager (top-right tree view in CytoPanel 1) shows the networks that are loaded. Clicking on a network here will make that view active in the main window, if the view exists (green highlighted networks only). Each network has a name and size (number of nodes and edges), which are shown in the network manager. If a network is loaded from a file, the network name is the name of the file.

Some networks are very large (thousands of nodes and edges) and can take a long time to display. For this reason, a network in Cytoscape may not contain a ‘view’. Networks that have a view are highlighted in green and networks that don’t have a view are highlighted in red. You can create or destroy a view for a network by right-clicking the network name in the network manager or by choosing the appropriate option in the Edit menu. You can also destroy previously loaded networks this way. In the picture above, seven networks are loaded, six green ones with views and one red one without a view.

Certain operations in Cytoscape will create new networks. If a new network is created from an old network, for example by selecting a set of nodes in one network and copying these nodes to a new network (via the File → New → Network option), it will be shown as a child of the network that it was derived from. In this way, the relationships between networks that are loaded in Cytoscape can be seen at a glance. Networks in the top part of the tree in the figure above were generated in this manner.

The available network views are also arranged as multiple overlapping windows in the network view window. You can maximize, minimize, and destroy network views by using the normal window controls for your operating system.

Arrange Network Windows

When you work on multiple networks, you can arrange the network view windows from View → Arrange Network Windows. You can re-arrange the network location by these commands.

The Network Overview Window

The network overview window shows an overview (or ‘bird’s eye view’) of the network. It can be used to navigate around a large network view. The blue rectangle indicates the portion of the network currently displayed in the network view window, and it can be dragged with the mouse to view other portions of the network. Zooming in will cause the rectangle to appear smaller and vice versa.

Cytoscape recognizes a number of optional command line arguments, including run-time specification of network files, attribute files, and session files. This is the output generated when the cytoscape is executed with the "-h" or "--help" flag:

usage: java -Xmx512M -jar cytoscape.jar [OPTIONS]
 -h,--help                      Print this message.
 -v,--version                 Print the version number.
 -s,--session <file>        Load a cytoscape session (.cys) file.
 -N,--network <file>     Load a network file (any format).
 -e,--edge-attrs <file>    Load an edge attributes file (edge attribute format).
 -n,--node-attrs <file>   Load a node attributes file (node attribute format).
 -m,--matrix <file>        Load a node attribute matrix file (table).
 -p,--plugin <file>         Load a plugin jar file, directory of jar files,
                                     plugin class name, or plugin jar URL.
 -P,--props <file>         Load cytoscape properties file (Java properties
                                    format) or individual property: -P name=value.
 -V,--vizmap <file>      Load vizmap properties file (Java properties format).

Any file specified for an option may be specified as either a path or as a URL. For example you can specify a network as a file (assuming that myNet.sif exists in the current working directory): cytoscape.sh -N myNet.sif. Or you can specify a network as a URL: cytoscape.sh -N http://example.com/myNet.sif.

All options described above (including plugins) can be loaded from the GUI once Cytoscape is running.

Managing Properties

The Cytoscape Properties editor, accessed via Edit → Preferences → Properties…, is used to specify general and default properties. Properties are now stored in Cytoscape session files, so changes to general properties will be saved as part of the current session, but will only carry over to subsequent sessions if they are set as defaults or exported using the File → Export function.

Cytoscape properties are configurable via Add, Modify and Delete operations.

Some common properties are described below.

Setting Default Properties

It is possible to alter the default properties for Cytoscape.

Edit the properties via Edit → Preferences → Properties... and check the Make Current Cytoscape Properties Default checkbox. This will save the current properties to the .cytoscape directory, where they will then be applied to all of your Cytoscape sessions from that point on. Otherwise, Cytoscape will automatically save the properties used in a particular session inside its .cys session file, while the default properties will be applied at the beginning of subsequent sessions.

Managing Bookmarks

Cytoscape contains a pre-defined list of bookmarks, which point to sample network files located on the Cytoscape web server. Users may add, modify, and delete bookmarks through the Bookmark manager, accessed by going to Edit → Preferences → Bookmarks… .

There are currently two types of bookmarks: network and annotation. Network bookmarks are URLs pointing to network files available on the Internet. These are nomal networks that can be loaded into Cytoscape. The annotation bookmarks are URLs pointing to ontology annotation files. The annotation bookmarks are only used when importing an ontology.

Managing Proxy Servers

You can define and configure a proxy server for Cytoscape by going to Edit → Preferences → Proxies… .

After the proxy server is set, all network traffic related to loading a network from URL will pass through the proxy server. Other plugins use this capability as well. The proxy settings are saved in cytoscape.props. Each time you click the Update button after making a change to the proxy settings, an attempt is made to connect to a well known site on the Internet (e.g., google.com) using your settings. For both success and failure you are notified and for failure you are given an opportunity to change your proxy settings.

If you no longer need to use a proxy to connect to the Internet, simply uncheck the Use Proxy checkbox and click the Update button.

There are 4 different ways of creating networks in Cytoscape:

1. Importing pre-existing, formatted network files.
2. Importing pre-existing, unformatted text or Excel files.
3. Importing networks from Web Service.
4. Creating an empty network and manually adding nodes and edges.

Import Fixed-Format Network Files

Network files can be specified in any of the formats described in the Supported Network Formats chapter. Networks are imported into Cytoscape through the "Import Network" window, which can be accessed by going to File → Import → Network (multiple file types). The network file can either be located directly on the local computer, or found on a remote computer (in which case it will be referenced with a URL).

Load Networks from Local Computer

By default, Cytoscape loads networks from the local computer.

The Import Networks dialog shows a default setting of "Data Source Type: Local," meaning that network files from the local computer will be available for importing. Choose the correct file by clicking on the Select button (only file types that Cytoscape recognizes will be shown), and then load the network by clicking on the Import button. Some sample network files of different types have been included in the sampleData folder in Cytoscape.

Network files in SIF, GML, and XGMML formats may also be loaded directly from the command line using the –N option.

Load Networks from a Remote Computer (URL import)

The Import Networks dialog is also capable of importing network files using a URL. To do this, set the Data Source Type to Remote and insert the appropriate URL, either manually or using URL bookmarks. Bookmarked URLs can be accessed by clicking on the arrow to the right of the text field (see the Bookmark Manager in Preferences for more details on bookmarks). Also, you can drag and drop links from web browser to the URL text box. Once a URL has been specified, click on the Import button to load the network.

Importing networks from URL addresses has an important caveat. Because Cytoscape determines file type primarily (not exclusively) by file extension, it can have trouble importing networks with URLs that don't end in a human readable file name. If Cytoscape does not recognize a meaningful file name and extension in the URL, it will attempt to guess the type of file based on MIME type. If the MIME type is not recognizable to any of our import handlers, then the import will fail.

Another issue for network import is the presence of firewalls, which can affect which files are accessible to a computer. To work around this problem, Cytoscape supports the use of proxy servers. To configure the proxy server, go to Edit → Preferences→ Proxy Server... . This is further described in the Preferences chapter.

Import Free-Format Table Files

Introduced in version 2.4, Cytoscape now supports the import of networks from delimited text files and Excel workbooks using Edit → Import → Network from Table (Text/MS Excel)... . An interactive GUI allows users to specify parsing options for specified files. The screen provides a preview that shows how the file will be parsed given the current configuration. As the configuration changes, the preview updates automatically. In addition to specifying how the file will be parsed, the user must also choose the columns that represent the Source nodes, the Target nodes, and an optional edge interaction type.

Supported Files

The "Import Network from Table" function supports delimited text files and single-sheet Microsoft Excel Workbooks. The following is a sample table file:

source  target  interaction  boolean attribute  string attribute        floating point attribute
YJR022W YNR053C pp      TRUE    abcd12371       1.2344543
YER116C YDL013W pp      TRUE    abcd12372       1.2344543
YNL307C YAL038W pp      FALSE   abcd12373       1.2344543
YNL216W YCR012W pd      TRUE    abcd12374       1.2344543
YNL216W YGR254W pd      TRUE    abcd12375       1.2344543

The network table files should contain at least two columns: source nodes and target nodes. The interaction type is optional in this format. Therefore, a minimal network table looks like the following:

YJR022W YNR053C
YER116C YDL013W
YNL307C YAL038W
YNL216W YCR012W
YNL216W YGR254W

One row in a network table file represents an edge and its edge attributes. This means that a network file is considered a combination of network data and edge attributes. A table may contain columns that aren't meant to be edge attributes. In this case, you can choose not to import those columns by clicking on the column header in the preview window. This function is useful when importing a data table like the following (1):

Unique ID A     Unique ID B     Alternative ID A        Alternative ID B        Aliases A       Aliases B       Interaction detection methods   First author surnames   Pubmed IDs      species A       species B       Interactor types        Source database Interaction ID  Interaction labels      Cross-references        Associated Files        Experiment files        Experiment labels       Different techniques    Different Pubmed articles       Different sources       Weight

7205    5747    TRIP6   PTK2    Q15654  Q05397-1        vv|HPRD Currently not available 14688263|15892868(Marcotte)     Mammalia        Homo sapiens    protein|protein HPRD|Marcotte   0       Thyroid hormone receptor interactor 6-FAK-|PTK2-TRIP6   NA(HPRD)|NA(Marcotte)   HPRD/02859_psimi.xml|other/ORIGINAL_DATA_MARCOTTE.txt   vv(HPRD/02859_psimi.xml)|HPRD(other/ORIGINAL_DATA_MARCOTTE.txt) 17651(ExptRef)|Marcotte 2       2       2       2

4174    7311    MCM5    UBA52   P33992  P62987  neighbouring_reaction   Currently not available 15608231(Reactome)      Homo sapiens    Homo sapiens    protein|protein Reactome        1       P33992-P62988   Reaction:68944<->Reaction:68946(Reactome)|Reaction:68946<->Reaction:68944(Reactome)     other/ORIGINAL_DATA_MARCOTTE.txt        neighbouring_reaction(other/REACTOMEhomo_sapiens.interactions.txt)      Reactome        1       1       1       1

7040    7040    TGFB1   TGFB1   P01137  P01137  nmr: nuclear magnetic resonance Currently not available 8679613 Homo sapiens    Homo sapiens    protein|protein BIND    2       TGFB1-TGFB1-    72085(BIND)     BIND/bind_taxid9606.1.psi.xml   nmr: nuclear magnetic resonance(BIND/bind_taxid9606.1.psi.xml)  NotAvailable    1       1       1       1

This data file is a tab-delimited text and contains network data (interactions), edge attributes, and node attributes. To import network and edge attributes from this table, you need to choose Unique ID A as source, Unique ID B as target, and Interactor types as interaction type. Then you need to turn off columns used for node attributes (Alternative ID A, species B, etc.). Other columns can be imported as edge attributes.

The network import function cannot import node attributes - only edge attributes. To import node attributes from this table, please see the Attributes section of this manual.

Note (1): This data is taken from the A merged human interactome datasets by Andrew Garrow, Yeyejide Adeleye and Guy Warner (Unilever, Safety and Environmental Assurance Center, 12 October 2006). Actual data files are available at http://www.cytoscape.org/cgi-bin/moin.cgi/Data_Sets/

Basic Operations

To import network text/Excel tables, please follow these steps:

1. Select File → Import → Network from Table (Text/MS Excel)...

2. Select a table file by clicking on the Select File button.
3. Define the interaction parameters by specifying which columns of data contain the Source Interaction, Target Interaction, and Interaction Type. Setting the Interaction Type as Default Interaction will result in all interactions being given the value pp; this value can be modified in Advanced Options (below).
4. (Optional) Define edge attribute columns, if applicable. Network table files can have edge attribute columns in addition to network data.

   • Enable/Disable Attribute Column - By left-clicking on a column header in the preview table, you can enable/disable edge attributes. If the header is checked and entries are blue, the column will be imported as an edge attribute. For example, the table below shows that columns 1 through 3 will be used as network data, column 4 will not be imported, and columns 5 and 6 will be imported as edge attributes.

     • 

   • Change Attribute Name and Data Types - If you right-click on a column header in the preview table, you can modify the attribute name and data type. For more detail, see "Modify Attribute Name/Type" below.

5. Click the Import button.

Import List of Nodes Without Edges

Table Import feature supports list of nodes without edges. If you select source column only, it creates a network without interactions. This feature is useful with node expansion function available from some web service clients. Please read the section Importing Networks from External Database for more detail.

Advanced Options

You can select several options by checking the Show Text File Import Options checkbox.

• Delimiter: You can select multiple delimiters for text tables. By default, Tab and Space are selected as delimiters.
• Preview Options: When you select a network table file, the first 100 entries will be displayed in the Preview panel. To display more entries, change the value for this option. If you want to show all entries in the file, select "Show all entries in the file". You will need to click the Reload button to update the Preview panel.
• Attribute Names
  • Transfer first line as attribute names: Selecting this option will cause all edge attribute columns to be named according to the first data entry in that column.
  • Start Import Row: Set which row of the table to begin importing data from. For example, if you want to skip the first 3 rows in the file, set 4 for this option.
  • Comment Line: Rows starting with this character will not be imported. This option can be used to skip comment lines in text files.
• Network Import Options: If the Interaction Type is set to Default Interaction, the value here will be used as the interaction type for all edges.

Modify Attribute Name/Type

Attribute names and data types can be modified here.

• Modify Attribute Name - just enter a new attribute name and click OK.
• Modify Attribute Data Type - The following attribute data types are supported:
  • String
  • Boolean (True/False)
  • Integer
  • Floating Point
  • List of (one of) String/Boolean/Integer/Floating Point

Cytoscape has a basic data type detection function that automatically suggests the attribute data type of a column according to its entries. This can be overridden by selecting the appropriate data type from the radio buttons provided. For lists, a global delimiter must be specified (i.e., all cells in the table must use the same delimiter).

Import Networks from Web Services

From version 2.6.0, Cytoscape has a new feature called Web Service Client Manager. Users can access verious kinds of databases through this function. Please read Importing Networks and Attributes from External Database for more detail.

Edit a New Network

A new, empty network can also be created and nodes and edges manually added. To create an empty network, go to File → New → Network → Empty Network, and then manually add network components using the Editor in CytoPanel 1 (see the Editor chapter for more details).

Cytoscape can read network/pathway files written in the following formats:

• Simple interaction file (SIF or .sif format)
• Nested network format (NNF or .nnf format)
• Graph Markup Language (GML or .gml format)
• XGMML (extensible graph markup and modelling language).
• SBML
• BioPAX
• PSI-MI Level 1 and 2.5
• Delimited text
• Excel Workbook (.xls)

The SIF format specifies nodes and interactions only, while other formats store additional information about network layout and allow network data exchange with a variety of other network programs and data sources. Typically, SIF files are used to import interactions when building a network for the first time, since they are easy to create in a text editor or spreadsheet. Once the interactions have been loaded and network layout has been performed, the network may be saved to GML or XGMML format for interaction with other systems. All file types listed (except Excel) are text files and you can edit and view them in a regular text editor.

SIF Format

The simple interaction format is convenient for building a graph from a list of interactions. It also makes it easy to combine different interaction sets into a larger network, or add new interactions to an existing data set. The main disadvantage is that this format does not include any layout information, forcing Cytoscape to re-compute a new layout of the network each time it is loaded.

Lines in the SIF file specify a source node, a relationship type (or edge type), and one or more target nodes:

nodeA <relationship type> nodeB
nodeC <relationship type> nodeA
nodeD <relationship type> nodeE nodeF nodeB
nodeG
...
nodeY <relationship type> nodeZ

A more specific example is:

node1 typeA node2
node2 typeB node3 node4 node5
node0

The first line identifies two nodes, called node1 and node2, and a single relationship between node1 and node2 of type typeA. The second line specifies three new nodes, node3, node4, and node5; here "node2" refers to the same node as in the first line. The second line also specifies three relationships, all of type typeB and with node2 as the source, with node3, node4, and node5 as the targets. This second form is simply shorthand for specifying multiple relationships of the same type with the same source node. The third line indicates how to specify a node that has no relationships with other nodes. This form is not needed for nodes that do have relationships, since the specification of the relationship implicitly identifies the nodes as well.

Duplicate entries are ignored. Multiple edges between the same nodes must have different edge types. For example, the following specifies two edges between the same pair of nodes, one of type xx and one of type yy:

node1 xx node2
node1 xx node2
node1 yy node2

Edges connecting a node to itself (self-edges) are also allowed:

node1 xx node1

Every node and edge in Cytoscape has an identifying name, most commonly used with the node and edge data attribute structures. Node names must be unique, as identically named nodes will be treated as identical nodes. The name of each node will be the name in this file by default (unless another string is mapped to display on the node using the visual mapper). This is discussed in the section on visual styles. The name of each edge will be formed from the name of the source and target nodes plus the interaction type: for example, sourceName (edgeType) targetName.

The tag <relationship type> can be any string. Whole words or concatenated words may be used to define types of relationships, e.g. geneFusion, cogInference, pullsDown, activates, degrades, inactivates, inhibits, phosphorylates, upRegulates, etc.

Some common interaction types used in the Systems Biology community are as follows:

  pp .................. protein – protein interaction
  pd .................. protein -> DNA
  (e.g. transcription factor binding upstream of a regulating gene.)

Some less common interaction types used are:

  pr .................. protein -> reaction
  rc .................. reaction -> compound
  cr .................. compound -> reaction
  gl .................. genetic lethal relationship
  pm .................. protein-metabolite interaction
  mp .................. metabolite-protein interaction

Delimiters

Whitespace (space or tab) is used to delimit the names in the simple interaction file format. However, in some cases spaces are desired in a node name or edge type. The standard is that, if the file contains any tab characters, then tabs are used to delimit the fields and spaces are considered part of the name. If the file contains no tabs, then any spaces are delimiters that separate names (and names cannot contain spaces).

If your network unexpectedly contains no edges and node names that look like edge names, it probably means your file contains a stray tab that's fooling the parser. On the other hand, if your network has nodes whose names are half of a full name, then you probably meant to use tabs to separate node names with spaces.

Networks in simple interactions format are often stored in files with a .sif extension, and Cytoscape recognizes this extension when browsing a directory for files of this type.

2.7 note : Cytoscape will use URL encode data in node/edge attribute files to properly preserve non-ASCII characters. If this presents a problem, there are two java system properties that can be used to turn off either or both of encoding or decoding :-

Property "cytoscape.encode.attributes" can be set to "false" to turn off writing attribute files with URL encoding.

Property "cytoscape.decode.attributes" can be set to "false" to turn off decoding during reading.

Files using white space will still be read.

NNF

The NNF format is a very simple format that unlike SIF allows the optional assignment of single nested network per node. No other node attributes can be specified. There are only 2 possible line formats:

• A node "node" contained in a "network:"

network node

• 2 nodes linked together contained in a network:

network node1 interaction node2

If a network name (first entry on a line) appeared previously as a node name (in columns 2 or 4), the network will be nested in the node with the same name. Also, if a name that has been previously defined as a network (by being listed in the first column), later appears as a node name (in columns 2 or 4), the previously defined network will be nested in the node with the same name. In summary: any time a name is used as both, a network name , and a node name, this implies that the network will be nested in the node of the same name. Additionally comments may be included on all lines. Comments start with a hash mark '#' and continue to the end of a line. Trailing comments (after data lines) and entirely blank lines anywhere are also permissible. Please note that if you load multiple NNF files in Cytoscape they will be treated like a single, long concatenated NNF file! If you need to embed spaces, tabs or backslashes in a name, you must escape it by preceding it with a backslash, so that, e.g. an embedded backslash becomes two backslashes, an embedded space a backslash followed by a space etc.

Examples

Example 1

Example_1      C
Example_1      network1
network1       A        pp        B
network1       B        pp        A
Example_1      C        pp        B

Example 2

Example_2      M1
Example_2      M2
M1             A
M2             B        pp        C
Example_2      A        pp        B
Example_2      M1       im        M2

Example 3

Example_3      M1       im        M2
Example_3      M3       im        M1
Example_3      M2       im        M3
Example_3      C        pp        M3
Example_3      M2       pp        C
M1             A
M2             A        pp        B
M3             B        pp        C

Example 4

Example_4      M1
root           M3
M1             A        pp        B
M1             B        pp        A
Example_4      C        pp        B
M3             M2
M2             D
M3             E        pp        F
M3             D        pp        F
M3             D        pp        E
Example_4      D        pp        C
Example_4      A        pp        M2
Example_4      B        pp        M3
Example_4      M2       pp        B

Example 5

Example_5      M4
M4             D
M4             M3
M3             M2        pp        C
M2             M1        pp        B
M1             A
M4             C         pp        D

GML Format

In contrast to SIF, GML is a rich graph format language supported by many other network visualization packages. The GML file format specification is available at:

http://www.infosun.fmi.uni-passau.de/Graphlet/GML/

It is generally not necessary to modify the content of a GML file directly. Once a network is built in SIF format and then laid out, the layout is preserved by saving to and loading from GML. Visual attributes specified in a GML file will result in a new visual style named Filename.style when that GML file is loaded.

XGMML Format

XGMML is the XML evolution of GML and is based on the GML definition. In addition to network data, XGMML contains node/edge/network attributes. The XGMML file format specification is available at:

http://www.cs.rpi.edu/~puninj/XGMML/

XGMML is now preferred to GML because it offers the flexibility associated with all XML document types. If you're unsure about which to use, choose XGMML.

2.7 note : There is a java system property "cytoscape.xgmml.repair.bare.ampersands" that can be set to "true" if you have experience trouble reading older files.

This should only be used when an XGMML file or session cannot be read due improperly encoded ampersands, as it slows down the reading process, but this is still preferable to attempting to such files using manual editing.

SBML (Systems Biology Markup Language) Format

The Systems Biology Markup Language (SBML) is an XML format to describe biochemical networks. SBML file format specification is available at:

http://sbml.org/documents/

BioPAX (Biological PAthways eXchange) Format

BioPAX is an OWL (Web Ontology Language) document designed to exchange biological pathways data. The complete set of documents for this format is available at:

http://www.biopax.org/index.html

PSI-MI Format

The PSI-MI format is a data exchange format for protein-protein interactions. It is an XML format used to describe PPI and associated data. PSI-MI XML format specification is available at:

http://psidev.sourceforge.net/mi/xml/doc/user/

Delimited Text Table and Excel Workbook

Cytoscape has native support for Microsoft Excel files (.xls) and delimited text files. The tables in these files can have network data and edge attributes. Users can specify columns containg source nodes, target nodes, interaction types, and edge attributes during file import. Some of the other network analysis tools, such as igraph (http://cneurocvs.rmki.kfki.hu/igraph/), has feature to export graph as simple text files. Cytoscape can read these text files and build networks from them. For more detail, please read the Import Free-Format Tables section section of the Creating Networks chapter.

Network generated by igraph's Watts-Strogatz small-world model (50k nodes and 250k esges) visualized by Cytoscape: You can import networks created by other applications using this Table Import feature.

Node Naming Issues in Cytoscape

Typically, genes are represented by nodes, and interactions (or other biological relationships) are represented by edges between nodes. For compactness, a gene also represents its corresponding protein. Nodes may also be used to represent compounds and reactions (or anything else) instead of genes.

If a network of genes or proteins is to be integrated with Gene Ontology (GO) annotation or gene expression data, the gene names must exactly match the names specified in the other data files. We strongly encourage naming genes and proteins by their systematic ORF name or standard accession number; common names may be displayed on the screen for ease of interpretation, so long as these are available to the program in the annotation directory or in a node attribute file. Cytoscape ships with all yeast ORF-to-common name mappings in a synonym table within the annotation/ directory. Other organisms will be supported in the future.

Why do we recommend using standard gene names? All of the external data formats recognized by Cytoscape provide data associated with particular names of particular objects. For example, a network of protein-protein interactions would list the names of the proteins, and the attribute and expression data would likewise be indexed by the name of the object.

The problem is in connecting data from different data sources that don't necessarily use the same name for the same object. For example, genes are commonly referred to by different names, including a formal "location on the chromosome" identifier and one or more common names that are used by ordinary researchers when talking about that gene. Additionally, database identifiers from every database where the gene is stored may be used to refer to a gene (e.g. protein accession numbers from Swiss-Prot). If one data source uses the formal name while a different data source used a common name or identifier, then Cytoscape must figure out that these two different names really refer to the same biological entity.

Cytoscape has two strategies for dealing with this naming issue, one simple and one more complex. The simple strategy is to assume that every data source uses the same set of names for every object. If this is the case, then Cytoscape can easily connect all of the different data sources.

To handle data sources with different sets of names, as is usually the case when manually integrating gene information from different sources, Cytoscape needs a data server that provides synonym information (see the chapter on Annotation). A synonym table gives a canonical name for each object in a given organism and one or more recognized synonyms for that object. Note that the synonym table itself defines which set of names are the "canonical" names. For example, in budding yeast, the ORF names are commonly used as the canonical names.

If a synonym server is available, then by default Cytoscape will convert every name that appears in a data file to the associated canonical name. Unrecognized names will not be changed. This conversion of names to a common set allows Cytoscape to connect the genes present in different data sources, even if they have different names – as long as those names are recognized by the synonym server.

For this to work, Cytoscape must also be provided with the species to which the objects belong, since the data server requires the species in order to uniquely identify the object referred to by a particular name. This is usually done in Cytoscape by specifying the species name on the command line with the –P option (cytoscape.sh -P "defaultSpeciesName=Saccharomyces cerevisiae") or by editing the properties (under Edit → Preferences → Properties...).

The automatic canonicalization of names can be turned off using the -P option (cytoscape.sh -P canonicalizeName=false") or by editing the properties (under Edit → Preferences → Properties...). This canonicalization of names currently does not apply to expression data. Expression data should use the same names as the other data sources or use the canonical names as defined by the synonym table.

Attribute Formulas

Introduction

As of Cytoscape 2.8, attribute values may be formulas. A typical example is =ABS($otherAttrib + LOG(10.2)). Formulas are modelled after Excel™ but only support references to other attributes at the same node, edge or network. Since Cytoscape attribute names may contain embedded spaces, optional braces around the attribute name (required if the name is not simply a letter followed by one or more letters or digits) is allowed e.g. ${a name with spaces}. Backslashes, opening braces and dollar signs in attribute names have to be escaped with a leading backslash. For example the attribute name ex$am{p\le would have to be written as ${ex\$am\{p\\le}. ID is being treated as a pseudo-attribute. String constants are written with double-quotes ". In order to embed a double-quote or a backslash in a string they have to be escaped with a leading backslash, therefore the string "\ must be written as "\"\\". Formula results must be compatible with the type of the attribute that they have been assigned to. The rules are rather lax though, for example anything can be interpreted as a string and all numeric values will be accepted for a boolean (or logical) attribute where non-zero will be interpreted as true and zero as false. For integer attributes floating point values will be converted using the rules of the Excel™ INT function. Parentheses can be used for grouping and to change evaluation order. The operator precedence rules follow those of standard arithmetic.

Operators

Currently supported operators are the four basic arithmetic operators and the ^ exponentiation operator. +, -, *, and \ are left-associative and ^ is right-associative. The string concatenation operator is &. Supported boolean or logical operators are the comparison operators <, >, <=, >=, =, and <> (not equal).

Supported Functions

Currently we support the following functions:

Cytoscape-specific functions

• Degree -- the degree of a node.

• InDegree -- the indegree of a node.

• OutDegree -- the outdegree of a node.

• SourceID -- the ID of the source node of an edge.
• TargetID -- the ID of the target of an edge.

Numeric Functions

• Abs -- Returns the absolute value of a number.
• ACos -- Returns the arccosine of a number.
• ASin -- Returns the arcsine of a number.
• ATan2 -- Returns the arctangent of two numbers x and y.
• Average -- Returns the average of a group of numbers.
• Cos -- Returns the cosine of an angle given in radians.
• Cosh -- Returns the hyperbolic sine of its argument.
• Count -- Returns the number of numeric values in a list.
• Degrees -- Returns its argument converted from radians to degrees.
• Exp -- Returns e raised to a specified number.
• Ln -- Returns the natural logarithm of a number.
• Log -- Returns the logarithm of a number to a specified base.
• Max -- Returns the maximum of a group of numbers.
• Median -- Returns the median of a list of numbers.
• Min -- Returns the minimum of a group of numbers.
• Mod -- Calculates the modulus of a number.
• Pi -- Returns an approximation of the value of π.
• Radians -- Returns its argument converted from degrees to radians.
• Round -- Rounds a number to a specified number of decimal places.
• Sinh -- Returns the hyperbolic sign of its argument.
• Sin -- Returns the sine of an angle given in radians.
• Sqrt -- Calculates the square root of a number.
• Tan -- returns the tangent of its argument in radians.
• Trunc -- Truncates a number.

String Functions

• Concatenate -- Concatenates two or more pieces of text.
• Left -- Returns a prefix of s string.
• Len -- Returns the length of a string.
• Lower -- Converts a string to lowercase.
• Mid -- Selects a substring of some text.
• Right -- Returns a suffix of a string.
• Substitute -- Replaces some text with other text.

• Text -- Format a number using the Java DecimalFormat class' conventions.

• Upper -- Converts a string to uppercase.
• Value -- Converts a string to a number.

Logical/Boolean Functions

• And -- Returns the logical conjunction of any number of boolean values.
• Not -- Returns the logical negation of a boolean value.
• Or -- Returns the logical disjunction of any number of boolean values.

List Functions

• BList -- creates a list of boolean (a.k.a. logical or truth) values
• First -- Returns the first entry in a list.
• FList -- creates a list of floating point (a.k.a. decimal) numbers
• Last -- Returns the last entry in a list.
• IList -- creates a list of integers (a.k.a. whole numbers)
• Nth -- Returns the n-th entry in a list.
• SList -- creates a list of strings (a.k.a. text objects)

Statistical Functions

• Largest -- the kth largest value in a list.

• GeoMean -- the geometric mean of a set of numbers.

• HarMean -- the harmonic mean of a set of numbers.

• Mode -- the mode of a set of numbers.

• NormDist -- Returns the pdf or CDF of the normal distribution.

• Permut -- Returns the number of permutations for a given number of objects.

• StDev - sample standard deviation.

• Var -- sample variance.

Miscellaneous Functions

• Combin - Returns the number of combinations for a given number of objects.
• If -- Returns one of two alternatives based on a boolean value.

• ListToString -- Returns a string representation of a list.

• Now -- Returns a string representation of the current date and time.
• Today -- returns a string representation of the current date.

Pitfalls

The possibly biggest problem is the referencing of other attributes that have null values. This is not allowed and leads to errors. In order to mitigate this problem we support the following optional syntax for attribute references: ${attribName:defaultValue}. The interpretation is that if attribName is null, then the default value will be used, otherwise the value of the referenced value will be used instead. N.B., the referenced attribute must still be a defined attribute and not an arbitrary name! The other potential problem is when there are circular attribute reference dependencies. Circular dependencies will be detected at formula evaluation time and lead to a runtime error.

Useful Tips

When working with formulas it can be very helpful to open the Cytoscape Error Console. Formula evaluation errors will be logged there.

The Formula Builder

In order to ease the creation of formulas as well as to facilitate discovery of built-in functions we provide a formula builder in our attribute browser. After selecting a non-list attribute cell, you can invoke it by clicking on . This should bring up the Formula Builder which looks like this:

The Formula Builder is a useful tool for discovery of the list of built-in functions. Arguments can either be selected from a list of named attributes or constant values can be entered in a text entry field. A major shortcoming at this time is that the Formula Builder won't let you compose functions with function calls as arguments. If you need the most general functionality, please type the expression directly into a cell.

A Note for Plugin Writers

It is relatively easy to add your own built-in formula functions. A simple function can probably be implemented in 15 to 20 minutes. It can then be registered via the parser and becomes immediately available to the user. It will of course also show up in the drop-down list in the formula builder.

In addition to normal node and edge attribute data, Cytoscape also supports importing gene expression data. Gene expression data are imported using a different file format than normal attributes; however, the resulting attributes are not treated differently by Cytoscape. Gene expression data (like attribute data) can be loaded at any time, but are (generally) only relevant once a network has been loaded.

Data File Format

Gene expression ratios or values are specified over one or more experiments using a text file. Ratios result from a comparison of two expression measurements (experiment vs. control). Some expression platforms, such as Affymetrix, directly measure expression values, without a comparison. The file consists of a header and a number of space- or tab-delimited fields, one line per gene, with the following format:

Identifier [CommonName] value1 value2 ... valueN [pval1 pval2 ... pvalN]

Brackets [ ] indicate fields that are optional.

The first field identifies which Cytoscape node the data refers to. In the simplest case, this is the gene name - exactly as it appears on the network generated by Cytoscape (case sensitive!). Alternatively, this can be some node attribute that identifies the node uniquely, such as a probeset identifier for commercial microarrays.

The next field is an optional common name. It is not used by Cytoscape, and is provided strictly for the user's convenience. With this common name field, the input format is the same as for commonly-used expression data anaysis packages such as SAM (http://www-stat.stanford.edu/~tibs/SAM/).

The next set of columns represent expression values, one per experiment. These can be either absolute expression values or fold change ratios. Each experiment is identified by its experiment name, given in the first line.

Optionally, significance measures such as P values may be provided. These values, generated by many microarray data analysis packages, indicate where the level of gene expression or the fold change appears to be greater than random chance. If you are using significance measures, then your expression file should contain them in a second set of columns after the expression values. The column names for the expression significance measures need to match those of the expression values exactly.

For example, here is an excerpt from the file galExpData.pvals in the Cytoscape sampleData directory:

GENE COMMON gal1RG gal4RG gal80R gal1RG gal4RG gal80R
YHR051W COX6 -0.034 0.111 -0.304 3.75720e-01 1.56240e-02 7.91340e-06
YHR124W NDT80 -0.090 0.007 -0.348 2.71460e-01 9.64330e-01 3.44760e-01
YKL181W PRS1 -0.167 -0.233 0.112 6.27120e-03 7.89400e-04 1.44060e-01
YGR072W UPF3 0.245 -0.471 0.787 4.10450e-04 7.51780e-04 1.37130e-05

This indicates that there is data for three experiments: gal1RG, gal4RG, and gal80R. These names appear two times in the header line: the first time gives the expression values, and the second gives the significance measures. For instance, the second line tells us that in Experiment gal1RG, the gene YHR051W has an expression value of -0.034 with significance measure 3.75720e-01.

Some variations on this basic format are recognized; see the formal file format specification below for more information. Expression data files commonly have the file extensions ".mrna" or ".pvals", and these file extensions are recognized by Cytoscape when browsing for data files.

General Procedure

Load an expression attribute matrix file using File → Import → Attribute/Expression Matrix... to bring up the import window, or by specifying the filename using the -m option at the command line. If you use the command line input, you must enter your expression data by node ID. If you use the dialog box, then you can either load expression data by node ID (the default option), or you can select a node attribute to use in assigning your expression data to your Cytoscape nodes. If you do use a node attribute, then (1) the attribute should already be loaded, and (2) the node attribute value must match the first column in your matrix file.

Worked Example

For the sample network file sampleData/galFiltered.sif:

Option A.

Load a sample gene expression data set by going to File → Import → Attribute/Expression Matrix... . In the resulting window, in the field labeled "Please select an attribute or expression matrix file...", use the Select button to enter sampleData/galExpData.pvals. The identifiers used in this file are the same ones used in the network file sampleData/galFiltered.sif, so you do not need to touch the field labeled "Assign values to nodes using...". A few lines of this file are shown below:

GENE COMMON gal1RG gal4RG gal80R gal1RG gal4RG gal80R
YHR051W COX6 -0.034 0.111 -0.304 3.75720e-01 1.56240e-02 7.91340e-06
YHR124W NDT80 -0.090 0.007 -0.348 2.71460e-01 9.64330e-01 3.44760e-01
YKL181W PRS1 -0.167 -0.233 0.112 6.27120e-03 7.89400e-04 1.44060e-01

Option B.

Step 1. After loading the network, load the node attribute file sampleData/gal.probeset.na, using File → Import → Node attributes... . This file is shown in part below:

Probeset
YHR051W = probeset2
YHR124W = probeset3
YKL181W = probeset4

Step 2. After loading the node attribute file, select the expression data file sampleData.galExpPvals.probeset.pvals, shown in part below:

GENE COMMON gal1RG gal4RG gal80R gal1RG gal4RG gal80R
probeset2 COX6 -0.034 0.111 -0.304 3.75720e-01 1.56240e-02 7.91340e-06
probeset3 NDT80 -0.090 0.007 -0.348 2.71460e-01 9.64330e-01 3.44760e-01
probeset4 PRS1 -0.167 -0.233 0.112 6.27120e-03 7.89400e-04 1.44060e-01

After selecting this file, in the field labeled "Assign values to nodes using...", select Probeset. You will see that this loads exactly the same expression data as in Case 1, but provides extra flexibility in case the node name cannot be used as an identifier.

Detailed file format (Advanced users)

In all expression data files, any whitespace (spaces and/or tabs) is considered a delimiter between adjacent fields. Every line of text is either the header line or contains all the measurements for a particular gene. No name conversion is applied to expression data files.

The names given in the first column of the expression data file should match exactly the names used elsewhere (i.e. in SIF or GML files).

The first line is a header line with one of the following three header formats:

<text> <text> cond1 cond2 ... cond1 cond2 ... [NumSigConds]

<text> <text> cond1 cond2 ...

<tab><tab>RATIOS<tab><tab>...LAMBDAS

The first format specifies that both expression ratios and significance values are included in the file. The first two text tokens (in angled brackets) contain names for each gene, such as the formal and common gene names. The condX token set specifies the names of the experimental conditions; these columns will contain ratio values. This list of condition names must then be duplicated exactly, each spelled the same way and in the same order. Optionally, a final column with the title NumSigConds may be present. If present, this column will contain integer values indicating the number of conditions in which each gene had a statistically significant change according to some threshold.

The second format is similar to the first except that the duplicate column names are omitted, and there is no NumSigConds field. This format specifies data with ratios but no significance values.

The third format specifies an MTX header, which is a commonly used format. Two tab characters precede the RATIOS token. This token is followed by a number of tabs equal to the number of conditions, followed by the LAMBDAS token. This format specifies both ratios and significance values.

Each line after the first is a data line with the following format:

FormalGeneName CommonGeneName ratio1 ratio2 ... [lambda1 lambda2 ...] [numSigConds]

The first two tokens are gene names. The names in the first column are the keys used for node name lookup; these names should be the same as the names used elsewhere in Cytoscape (i.e. in the SIF, GML, or XGMML files). Traditionally in the gene expression microarray community, who defined these file formats, the first token is expected to be the formal name of the gene (in systems where there is a formal naming scheme for genes), while the second is expected to be a synonym for the gene commonly used by biologists, although Cytoscape does not make use of the common name column. The next columns contain floating point values for the ratios, followed by columns with the significance values if specified by the header line. The final column, if specified by the header line, should contain an integer giving the number of significant conditions for that gene. Missing values are not allowed and will confuse the parser. For example, using two consecutive tabs to indicate a missing value will not work; the parser will regard both tabs as a single delimiter and be unable to parse the line correctly.

Optionally, the last line of the file may be a special footer line with the following format:

NumSigGenes int1 int2 ...

This line specified the number of genes that were significantly differentially expressed in each condition. The first text token must be spelled exactly as shown; the rest of the line should contain one integer value for each experimental condition.

Web Service Client Manager

Cytoscape 2.6.0 has a new feature called Web Service Client Manager. This is a framework to manage various kinds of web service clients in Cytoscape. By using web service clients, users can access remote data sources easily.

What is a Web Service?

A web service is a standardized, platform-independent mechanism for machines to interact over the network. These days, many major biological databases publish their data with web service API:

• List of Biological Web Services: http://taverna.sourceforge.net/services

• Web Services at the EBI: http://www.ebi.ac.uk/Tools/webservices/

This enables developers to write a program to access these services. Cytoscape core developer team have developed several sample web service clients using this framework. Cytoscape supports many web services including:

• PSICQUIC: Standard web service for biological interaction data sets. As of July 2010, the following data providers support PSICQUIC:

  • APID
  • ChEMBL

  • BioGrid

  • InnateDB
  • DIP

  • IntAct

  • MatrixDB
  • MPIDB
  • Reactome
  • Reactome-FIs
  • MINT
  • iRefIndex
  • STRING

• Pathway Commons: an open source portal, providing access to multiple integrated data sets, including: Reactome, IntAct, HPRD, HumanCyc, MINT, the MSKCC Cancer Cell Map, and the NCI/Nature Pathway Interaction database.

• NCBI Entrez Gene: a public database of genes, including annotation, sequence and interactions.

• Biomart: an open source biological database engine. Useful for ID/Name mapping.

All of these clients are available as Plugins and users can install them through Plugin Manager.

In the following sections, users learn how to import network from extrenal databases.

Getting Started

To get started, select: File → Import → Network from web services...

Example #1: Retrieving Protein-Protein Interaction Networks from IntAct

• Select: File → Import → Network from web services...

• From the pull-down menu, select the IntAct Web Service Client.

• Enter one or more search terms, such as BRCA1
• Click the Search button.

After confirming the download of interaction data, the network of BRCA1 will be imported and visualized.

Tip: Expanding the Network: Several of the Cytoscape web services provide additional options in the node context menu. To access these options, right-click on a node and select "Use Web Services." For example, in the screenshot to the right, we have loaded the BRCA1 network from IntAct, and have chosen to merge this node's neighbors into the existing network.

Example #2: Retrieving Protein-Protein Interaction Networks from NCBI Entrez Gene

An entry of NCBI Entrez Gene has a section called Interactions. NCBI web service client uses this section to build networks.

• Select: File → Import → Network from web services...

• From the pull-down menu, select the NCBI Web Service Client.

• Enter free-keywords. For example, type human muscular dystrophy.

• Click the Search button.

Network generated from Entrez Gene data: The network above is generated from interaction data matching the keyword human muscular dystrophy. Edge color represents data source type (BIND, BioGRID, or HPRD).

Note: since NCBI client extracts interaction data from a huge dataset, it takes a long time (30 seconds - 5 minutes, depends on machine specifications and network connection) to import large set of interactions.

Example #3: Retrieving Pathways and Networks from Pathway Commons

• Select: File → Import → Network from web services...

• From the pull-down menu, select the Pathway Commons Web Service Client.

Then, follow the three-step process outlined below:

• Step 1: Enter your search term; for example: BRCA1
• Step 2: Select the protein or small molecule of interest. Full details regarding each molecule is shown in the bottom left panel.
• Step 3: Download a specific pathway or interaction network.

Downloading Pathways and Interaction Networks

In Step 3, you can simply double-click on a pathway of interest, or click on the Interaction Networks tab. The Interaction Networks tab enables you to filter interactions by data source and/or interaction type. For example, you can choose to restrict your network to direct physical interactions from HPRD and MINT only:

Pathway Commons Options

You can configure access options from the Options tab. There are two retrieval options:

• Simplified Binary Model: Retrieve a simplified binary network, as inferred from the original BioPAX representation. In this representation, nodes within a network refer to physical entities only, and edges refer to inferred interactions.
• Full Model: Retrieve the full model, as stored in the original BioPAX representation. In this representation, nodes within a network can refer to physical entities and interactions.

By default, the simplified binary model is selected.

Future Directions

As additional web service clients become available, they will be made available via the Cytoscape Plugin Manager. Once installed, these web service clients will be centrally accessible via the same steps defined above:

• File → Import → Network from web services...

Import Attributes from External Database

Some of the web service clients can import attributes from external databases. BioMart client is an example. You can install it from Plugin Manager.

Example 1: Import Additional ID Sets and Annotations from BioMart

• Load a network. In this example, we use galFiltered.sif in sampleData directory.

• File → Import → Import Attributes from BioMart...

• Select Data Source. Since galFiltered.sif is a yeast network, select yeast dataset.

• For Key Attribute section, select ID for Attribute and Data Type should be Ensembl Gene ID. Attribute is the list of available attributes in current Cytoscape session and Data Type is the type of ID set of the attribute. In this case, Cytoscape uses ID as the key for mapping. Because the sample network galFiletred.sif uses Ensemble Gene ID for its node ID, like YOR072W, you need to select Ensembl Gene ID for Data Type. So you need to know the type of ID set (Entrez Gene ID, UniProt Unified Acc. Number, Ensemble Gene ID, etc.) of the attribute selected in the Attribute box.

• Select attributes you want to import. (Note: You cannot select too many attributes at once because BioMart server has maximum number of selectable annotations.)

• Press Import.

• Now you can see the newly imported attributes on the Attribute Browser. You may see some attribute names ends with -TOP if there are multiple attribute values for a node. This is an attribute taken from the first entry of the original list attribute.

Example 2: Import Annotations from NCBI Entrez Gene Database

NCBI Entrez Gene database () can be used as network data source and annotation repository. You can use NCBI web service client to import gene annotations from Entrez Gene.

• File → Import → Import attributes from NCBI Entrez Gene...

• Data Source is fixed to NCBI Entrez Gene.

• Data Type is also fixed to Entrez Gene ID. This means Cytoscape attribute selected in Attribute list should be Entrez Gene ID.

• Select Annotation Category. If you select a category, all of the annotation under the category will be imported (i.e., multiple Cytoscape attributes will be created for each category).

• Press Import. The following is a sample human network (RUAL.subset.sif) annotated by NCBI client.

Use Multiple Services in a Workflow

Web services are useful when you combine the result from multiple data sources.

Example: Import and Annotate Networks

• Import network from IntAct using keyword. In this example, type p53 AND species:mouse.

• Import human orthologs from BioMart.

• Show the othologs as the list of Ensembl Gene ID on the Data Panel. Copy them and use them as the query for IntAct.

• Import Entrez Gene ID from BioMart. Use ensembl attribute for the mapping key.

• Import annotations from NCBI. The resulting networks looks like the following:

Basic Network Navigation

Cytoscape uses a Zoomable User Interface for navigating and viewing networks. ZUIs use two mechanisms for navigation: zooming and panning. Zooming increases or decreases the magnification of a view based on how much or how little a user wants to see. Panning allows users to move the focus of a screen to different parts of a view.

Zoom

Cytoscape provides two mechanisms for zooming: either using mouse gestures or buttons on the toolbar. Use the zooming buttons located on the toolbar to zoom in and out of the interaction network shown in the current network display. Zoom icons are detailed below:

From Left to Right:

• Zoom Out
• Zoom In
• Zoom Selected Region
• Zoom Out to Display all of Current Network

You can also zoom in/out by holding down the right mouse button and moving the mouse to the right (zoom in) or left (zoom out).

Pan

You can pan the network image by holding down the middle mouse button and moving the mouse. You can also pan the image by holding down the left mouse button over the blue box in the Network Overview panel in the lower left hand of the Cytoscape desktop.

Other Mouse Behaviors

Select

Click the left mouse button on a node or edge to select that object. You can hold down the Shift key to select more than one node/edge or you can hold down the left mouse button and drag the mouse to select groups of nodes/edges.

Context

Click the right mouse button on a node/edge to launch a context-sensitive menu with additional information about the node/edge.

Node Context Menu

This menu can change based on the current context. Typically it shows:

• Visual Mapping Bypass
• Nested Network
• Use Web Services

• LinkOut

Nested Network Node Context Submenu

• Set Nested Network
  • Let's the user select any network in Cytoscape as the current nodes nested network. If the current node already has a nested network it will be replaced.
• Delete Nested Network
  • After being selected the current node will no longer have a nested network associated with it. No actual network will be deleted!
• Go to Nested Network
  • After selecting this the network view of the current node's nested network will be the current network view and have the focus. Should a network view for the nested network not exist, it will be created.

Automatic Layout Algorithms

The Layout menu has an array of features for organizing the network visually according to one of several algorithms, aligning and rotating groups of nodes, and adjusting the size of the network. Most of these features are available from plugins that are packaged with Cytoscape 2.3 and above. Cytoscape layouts have three different sources, which are reflected in the Layout menu.

yFiles Layouts

yFiles layouts are a set of commercial layouts which are provided courtesy of yWorks. Due to license restrictions, the detailed parameters for these layouts are not available (there are no yFiles entries in the Settings... dialog). The main layout algorithms provided by yFiles are:

yFiles Circular Layout

This algorithm produces layouts that emphasize group and tree structures within a network. It partitions the network by analyzing its connectivity structure, and arranges the partitions as separate circles. The circles themselves are arranged in a radial tree layout fashion. This algorithm is available by selecting Layout → yFiles → Circular.

yFiles Hierarchical Layout

The hierarchical layout algorithm is good for representing main direction or "flow" within a network. Nodes are placed in hierarchically arranged layers and the ordering of the nodes within each layer is chosen in such a way that minimizes the number of edge crossings. This algorithm is available by selecting Layout → yFiles → Hierarchical.

yFiles Organic Layout

The organic layout algorithm is a kind of spring-embedded algorithm that combines elements of the other algorithms to show the clustered structure of a graph. This algorithm is available by selecting Layout → yFiles → Organic.

Cytoscape Layouts

Cytoscape Layouts are those layouts that have been written or integrated by Cytoscape developers. These layouts are fully integrated with Cytoscape. All Cytoscape Layouts have the option to operate on only the selected nodes, and all provide a Settings... panel to change the parameters of the algorithm. Most of the Cytoscape layouts also partition the graph before performing the layout. In addition, many of these layouts include the option to take either node or edge attributes into account. Some of these layouts are:

Grid Layout

The grid layout is a simple layout the arranges all of the nodes in a square grid. This is the default layout and is always available as part of the Cytoscape core. It is available by selecting Layout → Cytoscape Layouts → Grid Layout. A sample screen shot is shown below:

Force Directed Layout

The force-directed layout is a layout based on the "force-directed" paradigm. This layout is based on the algorithm implemented as part of the excellent prefuse toolkit provided by Jeff Heer. The algorithm is very fast and with the right parameters can provide a very pleasing layout. The Force Directed Layout will also accept a numeric edge attribute to use as a weight for the length of the spring, although this will often require more use of the Settings... dialog to achieve the best layout. This algorithm is available by selecting Layout → Cytoscape Layouts → Force-Directed Layout → (unweighted) or the edge attribute you want to use as a weight. A sample screen shot showing a portion of the galFiltered network provided in sample data is provided below:

Spring-Embedded Layout

The spring-embedded layout is based on a “force-directed” paradigm as implemented by Kamada and Kawai (1988). Network nodes are treated like physical objects that repel each other, such as electrons. The connections between nodes are treated like metal springs attached to the pair of nodes. These springs repel or attract their end points according to a force function. The layout algorithm sets the positions of the nodes in a way that minimizes the sum of forces in the network. This algorithm can be applied to the entire network or a portion of it by selecting the appropriate options from Layout → Cytoscape Layouts → Spring Embedded. A sample screen shot is provided below:

Attribute Circle Layout

The attribute circle layout is a quick, useful layout, particularly for small networks, that will locate all of the nodes in the network around a circle. The node order is determined by a user-selected node attribute. The result is that all nodes with the same value for that attribute are located together around the circle. Using Layout → Cytoscape Layouts → Attribute Circle Layout → attribute to put all nodes around a circle using attribute to position them. The sample screen shot below shows the a subset of the galFiltered network organized by node Degree.

Group Attributes Layout

The group attributes layout is similar to the attribute circle layout described above except that instead of a single circle with all of the nodes, each set of nodes that share the same value for the attribute are laid out in a separate circle. The same network shown above (subset of galFiltered) is shown below, using Layout → Cytoscape Layouts → Attribute Circle Layout → Degree.

Label Force-Directed Layout

The Label Force-Directed Layout is an automatic label repositioning plugin that can be accessed through Layout → Cytoscape Layouts → Label Force-Directed Layout. The layout is designed to be applied to position labels after another network layout is run to position nodes. It is compatible with any node positioning layout. Specific numerical values that the algorithm makes use of can be set by the user through the Layout → Settings... menu. Through adjusting these values, you can control how much you want to spread the labels and/or nodes of the network by.

This label layout can be applied to the entire network, or only to those nodes that are selected (through enabling the Only layout selected nodes option). Upon the application of this plugin, node labels will be repositioned according to the Force-Directed algorithm, using the Default Label Spring Coefficient and Default Label Spring Length fields:

• Default Label Spring Coefficient: The strength of the pull between the label of a node and the node itself. The distance between nodes and their labels will be closer to the Default Label Spring Length if this value is larger.

• Default Label Spring Length: The desired length between the label and the node that the label belongs to.

Users can also choose to move the network nodes. This option can be activated by enabling the Allow nodes to move option. All network nodes (or just the selected ones) will be moved according to the Force-Directed layout algorithm, while making use of the Default Spring Coefficient, Default Spring Length, and Default Percentage (%) fields:

• Default Spring Coefficient: The strength of the pull between a network node and its connected neighbours. The larger the value, the closer the distance between the two objects will be to the Default Spring Length value.

• Default Spring Length: The desired length of an edge that is connecting two network nodes together.

• Default Percentage (%): The percentage of the total Number of Iterations in which you would like the algorithm to move the network nodes as well, in addition to strictly moving the labels.

  • For example: Number of Iterations = 200; Default Percentage (%) = 80. Then the network nodes will be moved for (80% / 100) * 200 = 160 of the 200 iterations.

Other algorithm settings include:

• Default Node Mass: The mass that a default network node should take on. Nodes with a greater node mass require more strength to move.

• Number of Iterations: The total number of times to run the algorithm for each execution of this label layout.

• Reset the label position of all nodes: Reposition the label of each node to their default position.

Note: In order to yield the best layout for the labels, this plugin may need to be executed more than once.

Before

After

JGraph Layouts

Several other alignment algorithms, including a selection from the JGraph project (http://jgraph.sourceforge.net), are also available under the Layout menu.

Layout Parameters

Many layouts have adjustable parameters that are exposed through the Layouts → Settings... menu option. This will pop up the following dialog, which allows you to choose which layout algorithm settings to adjust. The settings presented vary by algorithm and only those algorithms that allow access to their parameters will appear in the drop-down menu at the top of the dialog. Once you've modified a parameter, clicking the "Execute Layout" button will apply the layout. This be repeated until a useful layout is achieved. Settings can be saved using the "Save Settings" button.

Manual Layout

The simplest method to manually organize a network is to click on a node and drag it. If you select multiple nodes, all of the selected nodes will be moved together.

Rotate

Selecting the Layout → Rotate option will open the Rotate window in CytoPanel 5. This function will either rotate the entire network or a selected portion of the network. The image below shows a network with selected nodes rotated.

Before

After

Scale

Selecting the Layout → Scale option will open the Scale window in CytoPanel 5. This function will scale the position of the entire network or of the selected portion of the network. Note that only the position of the nodes will be scaled, not the node sizes. Node size can be adjusted using the VizMapper. The image below shows selected nodes scaled.

Before

After

Align/Distribute/Stack

Selecting the Layout → Align/Distribute option will open the Align/Distribute/Stack window in CytoPanel 5. The Align buttons provide different options for either vertically or horizontally aligning selected nodes against a line. The differences are in what part of the node gets aligned, e.g. the center of the node, the top of the node, the left side of the node. The Distribute buttons evenly distribute selected nodes between the two most distant nodes along either the vertical or horizontal axis. The differences are again a function what part of the node is used as a reference point for the distribution. And the Stack buttons vertically or horizontally stack selected nodes with the full complement of alignment options. The table below provides a decription of what each button does.

Edge Handles

This is a little-known feature! If you select an edge and then Ctrl-left-click on the edge, an edge "handle" will appear. This handle can be used to change the shape of the line. To remove a handle, simply Ctrl-left-click on the handle again.

Two other options under Select → Edges provide further control: "Smooth Selected Edges" turns an edge consisting of line segments into a smoothed bezier curve, and "Straighten Selected Edges" turns a curved edge back into line segments.

Node Movement and Placement

In addition to the ability to click on a node and drag it to a new position, Cytoscape now has the ability to move nodes using the arrow keys on the keyboard. By selecting one or more nodes using the mouse and clicking one of the arrow keys (←, →, ↑, ↓) the selected nodes will move one pixel in the chosen direction. If an arrow key is pressed while holding the Shift key down, the selected nodes will 10 pixels in the chosen direction.

Mouse movement has also been enhanced. If the Shift key is held down while dragging a node, the node will only move horizontally, vertically, or along a 45 degree diagonal.

What is a Visual Style?

One of Cytoscape's strengths in network visualization is the ability to allow users to encode any attribute of their data (name, type, degree, weight, expression data, etc.) as a visual property (such as color, size, transparency, or font type). A set of these encoded or mapped attributes is called a Visual Style and can be created or edited using the Cytoscape VizMapper. With the VizMapper, the visual appearance of your network is easily customized. For example, you can:

• Specify a default color and shape for all nodes.

  • 

• Set node sizes based on the degree of connectivity of the nodes. You can visually see the hub of a network...

  • 

• ...or, set the font size of the node labels instead.

  • 

• Set node widths and heights based on label size.

  • 

• Visualize gene expression data along a color gradient.

  • 

• Encode specific physical entities as different node shapes.

  • 

• Use specific line types to indicate different types of interactions.

  • 

• Control edge transparency (opacity) using edge weights.

  • 

• Control multiple edge visual properties using edge score.

  • 

• Browse extremely-dense networks by controlling the opacity of nodes.

  • 

• Show module locations in a large network.

  • 

• Overlay a subnetwork on a huge interactome using opacity and color control.

  • 

• Add photo/image/graphics on top of nodes.

  • 

Cytoscape 2.6.0 and later versions have additional sample Visual Styles. You can try those samples to examine how Visual Styles change the appearence of a network. The following is a list of network views based upon sample styles applied to the galFiltered.sif network :

The VizMapper can be accessed by going to View → Open VizMapper or by clicking on the VizMapper icon . Also, starting in Cytoscape 2.5, direct access to the VizMapper is provided via a tab on the Control Panel at the left-hand side of the screen (formerly known as CytoPanel 1).

Introduction to the VizMapper User Interface

There are three types of control panels in the VizMapper:

1. Main Panel

   • 

   • This panel allows you to create/delete/view/switch between different visual styles using the Current Visual Style options. The Visual Mapping Browser at the bottom displays the mapping details for a given visual style and is used to edit these details as well.
2. Default Appearance Editor

   • 

   • Clicking on the section labelled "Defaults" on the Main Panel will bring up the Default Appearance Editor, which allows you to visually edit the default appearance of nodes and edges for the selected visual style.
3. Continuous Editors
   • These are editors for continuous mappings, which are mappings from numerical values to visual attributes. They are accessed through the Visual Mapping Browser on the Main Panel.
   • Color Gradient Editor
   • Continuous-to-Discrete Editor
   • Continuous-to-Continuous Editor

These editors will be discussed in further detail below.

Introduction to Visual Styles

The Cytoscape distribution includes several predefined visual styles to get you started. To examine these styles, try out the following example:

Step 1. Load some sample data

• Load a sample session file: From the main menu, select File → Open, and select the file sampleData/galFiltered.cys.

• The session file includes a network, some annotations, and sample visual styles. By default, the galFiltered Style is selected. Gene expression values for each node are colored along a color gradient between red and green (where red represents a low expression ratio and green represents a high expression ratio, using thresholds set for the gal4RGexp experiment bundled with Cytoscape in the sampleData/galExpData.pvals file). Also, node size is mapped to the degree of the node (number of edges connected to the node) and you can see the hubs of the network as larger nodes. See the sample screenshot below:

Step 2. Switch between different Visual Styles

You can change visual styles by making a selection from the Current Visual Style dropdown list (found at the top of the VizMapper Main Panel).

For example, if you select Sample1, a new visual style will be applied to your network, and you will see a white background and round blue nodes. If you zoom in closer, you can see that protein-DNA interactions (specified with the label "pd") are drawn with dashed red edges, whereas protein-protein interactions (specified with the label "pp") are drawn with a solid light blue edge (see sample screenshot below).

Finally, if you select Solid, you can see the graphics below:

This Visual Style does not have mappings except node/edge labels, but you can modify the network graphics by editing Default View.

Additional sample styles are available in the sampleStyles.props file in the SampleData directory. You can import the sample file from File → Import → Vizmap Property File.

Visual Attributes, Graph Attributes and Visual Mappers

The Cytoscape VizMapper uses three core concepts:

• A visual attribute is any visual setting that can be applied to your network. For example, you can change all nodes from circles to squares by changing the node shape visual attribute.

• A network attribute is any data attribute associated with a node or an edge. For example, each edge in a network may be associated with a label, such as “pd” (protein-DNA interactions), or “pp” (protein-protein interactions).

• A visual mapper maps network attributes to visual attributes. For example, a visual mapper can map all protein-DNA interactions to the color blue, and all protein-protein interactions to the color red.

Cytoscape allows a wide variety of visual attributes to be controlled. These are summarized in the tables below.

For each visual attribute, you can specify a default value or define a dynamic visual mapping. Cytoscape currently supports three different types of visual mappers:

1. Passthrough Mapper

   • The values of network attributes are passed directly through to visual attributes. A passthrough mapper is typically used to specify node/edge labels. For example, a passthrough mapper can label all nodes with their common gene names.

2. Discrete Mapper

   • Discrete data attributes are mapped to discrete visual attributes. For example, a discrete mapper can map different types of molecules to different node shapes, such as rectangles for gene products and ellipses for metabolites

3. Continuous Mapper

   • Continuous data are mapped to visual attributes. Depending on the visual attribute, there are three kinds of continuous mappers:

     1. Continuous-to-Continuous Mapper: for example, you can map a continuous numerical value to a node size.

     2. Color Gradient Mapper: This is a special case of continuous-to-continuous mapping. Continuous numerical values are mapped to a color gradient.

     3. Continuous-to-Discrete Mapper: for example, all values below 0 are mapped to square nodes, and all values above 0 are mapped to circular nodes.

   • However, note that there is no way to smoothly morph between circular nodes and square nodes.

The table below shows visual mapper support for each visual property.

Legend

Node Visual Mappings

Edge Visual Mappings

Text Passthrough Mapper (New feature for version 2.8)

In Cytoscape 2.8.0 and later versions, the Passthrough Mapper can recognize some text representations of values. This means, if you have an integer attribute named Node Size Values, you can directly map those values as the Node Size by setting Node Size Values as controlling attribute name for Node Size Passthrough mapping. The following value types are supported:

• Color: Standard color names supported by all browsers or RGB representation in hex

• Numerical Values: Automatically mapped to the specified Visual Property.
• Custom Graphics: URL String. If the URL is valid and an actual image data exists there, Cytoscape automatically downloads the image and maps it to the node.

Examples

1. Color Passthrough Mapping

   • 

2. Node Size Passthrough Mapping

   • 

3. Custom Graphics Passthrough Mapping

   • 

Custom Graphics Manager

For Cytoscape 2.8.0 and later versions, Cytoscape supports Custom Graphics for nodes. You can add all kinds of bitmap images, such as jpg, png, or gif, on the top of network nodes. From the user's point of view, this is simply an addition to the Visual Properties, and you can use same VizMap user interface to map Custom Graphics to nodes. However, before mapping images, you need to prepare Custom Graphics in the Custom Graphics Manager. It is a simple GUI component to add/remove images to or from a Cytoscape session.

(Sample icons used in this section is created by the Crystal Project, distributed under LGPL.)

Adding New Images to Cytoscape

The Custom Graphics Manager supports drag and drop for image files and URLs. If you want to add images from a web browser or local file system, you can drag images from them and drop those images onto the list of images on the left.

If you want to add all images in a folder, press the + button on the bottom of the Custom Graphics Manager window.

Note: When you drag and drop images from web browser, make sure that you are actually dragging the URL for the image. In some cases, images are linked to an HTML page or scripts, and in such cases, this drag and drop feature may not work.

Removing Images

To remove images from the current session's Custom Graphics library, simply select graphics from the list and press the - button.

Resizing Images

You can resize images by typing width/height in the text box. If Keep Aspect Ratio box is checked, the width-height ratio is always synchronized. Any time, you can resize the image to the original size by pressing Original button.

Using Custom Graphics in the VizMapper

Custom Graphics is a new type of Visual Property and you can use them from the standard VizMap user interface. There are nine Custom Graphics Visual Properties (Node Custom Graphics 1 - 9) and they will be displayed in the standard VizMap Default View Editor or Mapping Editors.

Custom Graphics Positions

Each Custom Graphics Visual Property is associated with a position. You can edit their positions by using same UI as Label Position.

Z-Ordering

This number that appears with the Custom Graphics Visual Property represents an ordering of layers. Basic node color and shape are always rendered first, then Node Custom Graphics 1, 2, ..., through 9.

Synchronize Custom Graphics to Node Size

By default, Custom Graphics objects are automatically resized to be consistent with the Node Size Visual Property. To control Custom Graphics size separately, uncheck the Synchronize Custom Graphics Size to Node Size dependency. You can find this check box in the Default Editor's Dependencies panel.

Custom Graphics Selector

To select an Custom Graphics, just click one of them and press Apply. To remove a value from mappings/defaults, select Empty Custom Graphics.

Saving and Loading Custom Graphics

In general, saving and loading Custom Graphics is automatic. When you quit Cytoscape, all of the Custom Graphics in the manager will be saved automatically. There are two types of saving:

1. To session file

   • When you save the current session to a file, the Custom Graphics used in Visual Styles will be saved to that file. For example, if you have a Visual Style with a discrete mapping for Custom Graphics, all Custom Graphics used in the style will be saved to the session file. Other graphics will not be saved in your session file. This is because your image library can be huge when you add thousands of images to the Custom Graphics Manager and it takes very long time to save and load the session file.

2. Automatic saving to .cytoscape/images directory

   • When you select File-->Quit, all of Custom Graphics in the Manager will be saved automatically to your Cytoscape setting directory. Usually, it's YOUR_HOME_DIRECTORY/.cytoscape/images.

In any case, Custom Graphics will be saved automatically to your system or session and will be restored when you restart Cytoscape or load a session.

Visual Styles Tutorials

The following tutorials demonstrate some of the basic VizMapper features. Each tutorial is independent of the others.

Tutorial 1: Create a Basic Visual Style and Set Default Values

The goal of this tutorial is to learn how to create a new Visual Style and set some default values.

Step 1. Load a sample network. From the main menu, select File → Import → Network (Multiple file types), and select sampleData/galFiltered.sif.

Step 2. Open the VizMapper. Select the View → Open VizMapper menu option, or select the VizMapper icon in the main button bar, or click on the VizMapper tab in the Control Panel at the left of the screen. You will now see a VizMapper Main Panel, as shown below.

Step 3. Create a new visual style. Click the Options button, and select Create new visual style... Then enter a name for your new visual style when prompted. You will see an empty visual style in the VizMapper Main Panel, as shown below.

Since no mappings are set up yet, all visual attributes are listed in the Unused Properties category. From this panel, you can create node/edge mappings for all visual properties.

Step 4. Edit default values. Open the Default Appearance Editor by clicking on the Defaults graphics window (shown below) in the VizMapper Main Panel.

Step 5. Change the default node shape. To set the default node shape to triangles, click "Node Shape" in the Default Visual Properties list. A list of available node shapes will be shown. Click on the Triangle icon and then click the Apply button. The Default Appearance Editor will be automatically updated. You can edit other default values by clicking on visual attribute names on the list. In the example shown below, the node shape is set to Triangle, while the node color is set to blue.

Step 6. Apply your settings. When you finish editing, click the Apply button at the bottom of the editor. Your new Visual Style will be applied to the current network, as shown below.

Tutorial 2: Creating a New Visual Style with a Discrete Mapper

The following tutorial demonstrates how to create a new visual style using a discrete mapper. The goal is to draw protein-DNA interactions as dashed blue lines, and protein-protein interactions as solid red lines.

Step 1. Load a sample network. From the main menu, select File → Import → Network (Multiple file types), and select sampleData/galFiltered.sif.

Step 2. Open the VizMapper. Select the View → Open VizMapper menu option, or select the VizMapper icon in the main button bar, or click on the VizMapper tab in the Control Panel at the left of the screen.

Step 3. Create a new visual style. Click the Options button, and select Create new visual style... Name your new style “Tutorial VS2”.

Step 4. Choose a visual attribute. Double click the Edge Color entry listed in Unused Properties. Edge Color will now appear at the top of the list, under the Edge Visual Mapping category (as shown below).

Step 5. Choose a network attribute. Click on the cell to the right of the Edge Color entry and select "interaction" from the dropdown list that appears.

Step 6. Choose a mapping type. Set the Discrete Mapper option as the Mapping Type. All available attribute values for "interaction" will be displayed, as shown below.

Step 7. Set the mapping relationship. Click the empty cell next to "pd" (protein-DNA interactions). On the right side of the cell, ... and X buttons will appear. Click on the ... button. A popup window will appear; select blue, and the change will immediately appear on the network window.

Repeat step 7 for "pp" (protein-protein interactions), but select red as the edge color. Then repeat steps 4 through 7 for the Edge Line Style attribute. You can select the correct line style (dashed or solid) from the dropdown list.

Now your network should show "pd" interactions as dashed blue lines and "pp" interactions as solid red lines. A sample screenshot is provided below.

Tutorial 3: Creating a New Visual Style with a Continuous Mapper

The following tutorial demonstrates how to create a new visual style using a continuous mapper. The goal is to superimpose gene expression data onto a network and display gene expression values along a color gradient.

Step 1. Load a sample network. From the main menu, select File → Import → Network (Multiple file types), and select sampleData/galFiltered.sif.

Step 2. Load sample expression data. From the main menu, select File → Import → Attribute/Expression Matrix, and select sampleData/galExpData/pvals.

Step 3. Open the VizMapper. Select the View → Open VizMapper menu option, or select the VizMapper icon in the main button bar, or click on the VizMapper tab in the Control Panel at the left of the screen.

Step 4. Create a new visual style. Click the Options button, and select Create new visual style... Name your new style “Tutorial VS3”.

Step 5. Choose a visual attribute. Double click the Node Color entry listed in Unused Properties. Node Color will now appear at the top of the list, under the Node Visual Mapping category.

Step 6. Choose a network attribute. Click on the cell to the right of the Node Color entry and select "gal1RGexp" from the dropdown list that appears.

Step 7. Choose a mapping type. Set the Continuous Mapping option as the Mapping Type. This automatically creates a default mapping

Step 8. Define the points where colors will change. Double-click on the black-and-white gradient rectangle next to Graphical View to open the Color Gradient Mapper. Click and drag one point to -1, or type the value in the Range Setting box. Set the second point to 2.

Step 9. Define the colors between points. Double-click on the leftmost triangle (facing left) and a color palette will appear. Choose a shade of yellow and click OK. Double-click on the triangle at -1 and set the color white. For the triangle at 2.000, set its color to red. Set the rightmost triangle to black.

The color gradients will immediately appear in the network window. All nodes with a gal1RGexp value less than –1 will be set to yellow, and all nodes with a gal1RGExp value greater than 2 will be black. Additionally, all values between –1 and 2 will be painted with a white/red color gradient. A sample screenshot is below.

Tutorial 4: How to Use Utilities for Discrete Mappers

The following tutorial demonstrates utilities for editing discrete mappings. The goal of this section is learning how to set and adjust values for discrete mappings automatically.

1. Load a sample network: From the main menu, select File → Import → Network, and select sampleData/galFiltered.sif.

2. Apply layout to the network: From the main menu, select Layout → Cytoscape Layouts → Degree Sorted Circle Layout. This layout algorithm sort nodes in a circle by degree of the nodes. Degrees will be stored as node attribute names Degree after you applied this algorithm.

3. Click the VizMap button on the tool bar.

4. Click Defaults panel on the VizMapper main panel. Default Apearence Editor pops up (see below.)

5. Edit the following visual properties and press Apply. Since you changed opacity of the node, you can see the nodes bihind the front node (see below.)

   • Node Oppacity - 100
   • Edge Color - White
   • Background Color - Black

   

6. Cretate a Discrete Node Color Mapping. Select Degree as controlling attribute.

7. Select Node Color, then right click to show popup menu. Select Generate discrete values → Rainbow 1. It generates different colors for different attribute values as shown below.

8. Cretate a Discrete Node Size Mapping. Select Degree as controlling attribute.

9. Select Node Size and right click to show popup menu. Select Generate Discrete Values → Series (Numbers Only). Type 30 for the first value and click OK. Enter 15 for increment.

10. Apply Force-Directed layout. The final view is shown below:
    

Tutorial 5: Using Custom Graphics in Visual Styles

This tutorial is a quick introduction to the new Custom Graphics feature in Cytoscape 2.8.0.

1. Prepare images. These can be any type of bitmap graphics. In this tutorial, we are going to use theCrystal Project's PNG icons. You can download it from here.

2. Start Cytoscape and select View → Open Custom Graphics Manager

3. Click + button and select an image folder.

4. All images in the folder should appear in the Custom Graphics Manager.

   • 

5. Load a network and apply Degree Sorted Circle Layout. This creates new integer node attribute Degree.

6. Click VizMapper tab in the Control Panel, and select Solid style.

7. Click default view to open Default Appearance Editor.

8. Click NODE_CUSTOM_GRAPHICS_1 and select any of a custom graphics from the list and press Apply.

   • 

9. Open Default Appearance Editor again. Click NODE_OPACITY and set opacity to 0.

   • 

10. Double-click Node Custom Graphics 2 in the ViaMapper panel and create a new Discrete Mapping. Set the controlling attribute name to Degree.

11. For degree value 1, set a Custom Graphics.

12. Open Default Appearance Editor. Click NODE_CUSTOM_GRAPHICS_POSITION_2 and move the position from the center.

13. Apply Force-Directed Layout. Now you can see that all leaf nodes have two Custom Graphics.

    • 

14. Double-click Node Custom Graphics 3 in the VizMapper panel and create a new Continuous Mapping. Set controlling attribute name to Degree.

15. Set a Custom Graphics for nodes with degree grater than 10.

    • 

16. Open th eDefault Appearance Editor and modify NODE_CUSTOM_GRAPHICS_POSITION_3.

17. Edit the default appearance to get a look that suits you. The network should look something like the image below:
    
    
    
    

Advanced Topics

Editing Discrete Mappings

Several utility functions are available for Discrete Mappings. You can use those functions by right clicking anywhere on the Visual Mapping Browser (shown below.)

Automatic Value Generators

• Generate Discrete Values - Functions in this menu category are value generators for discrete mappings. Users can set values for discrete mappings automatically by these functions.

  • Rainbow 1 and Rainbow 2 - These functions try to assign as diverse a set colors as possible for each data value.

    • 

  • Randomize - Randomize colors and numbers. If you use this function for numerical values (node size, opacity, etc.) you need to specify a range. For example, if you want to set values from 1 to 100, you need to type 1-100 in the dialog.

  • Series - Set a series of numbers to the specified mapping.

    • 

  • Fit node size to label - This function is only for node width and height. When the node size is unlocked AND Node Width/Height discrete mappings are available, you can fit the size of each node to its label automatically by selecting this function. See the example below:

    • 

• Modify Discrete Values - Currently, this is only for colors. You can change overall brightness for discrete color mappings.

Edit Selected Values at Once

You can set multiple values at once. First, you need to select rows in which you want to change values then select Edit selected values at once.... A dialog pops up and you can enter the new value for the selected rows.

Visual Property Dependencies

The fourth tab in the Default Editor lists available dependencies that can be established between different visual properties. The two that currently exist are Lock Node Width/Height and Make Arrow Color Match Edge Color.

• Lock Node Width/Height - If this menu item is checked, Node Width and Node Height mappings are ignored and Node Size overrides them. If you want to use Fit node size to label function, you need to unlock this.

• Make Arrow Color Match Edge Color - If this menu item is checked then Edge Source Arrow Color and Edge Target Arrow Color are overridden and Edge Color is used in both cases.

Working with Continuous Mapping Editors

There are three kinds of Continuous Mapping Editors. Each of them are associated with a specific visual attributes:

Range Setting Panel

Each editor has a common section named Range Setting.

1. Handle Value Box - This box displays current value for selected slider handle. Also you can directly type value in this box to move the slider to an exact location.

2. Min/Max Button - Set the overall range of this editor. First time you open the editor, the Min and Max values are set by the range of attribute you selected, i.e., minimum and maximum value of the attribute will be set to the range of this editor. You can change this range anytime you want by pressing this button.

3. Add Handle Button - Add a new handle to the editor.

4. Delete Handle Button - Delete selected handle from the slider widget.

Gradient Editor

The Gradient Editor is an editor for creating continuous mappings for colors. To change the color of each region, just double click the handles (small triangles on the top). A Color gradient will be created only when the editor has two or more handles (see the example below).

Continuous-Continuous Editor

The Continuous-Continuous Editor is for creating mappings between numerical attributes and numerical visual properties (size/opacity). To change the value assigned on Y-axis (the visual property shown in the example above is node size), drag the red squares or double click on the squares to directly type an exact value.

Continuous-Discrete Editor

The Continuous-Discrete Editor is used to create mappings from numerical attribute values to discrete visual properties, such as font, shape, or line style. To edit a value for a specific region, double click on the icon on the track.

Managing Visual Styles

All Cytoscape Visual Style settings are initially loaded from a a default file called vizmap.props that cannot be altered by users. When users make changes to the visual properties, a vizmap.props file is saved in the session file. This means that if you save your session, you will not lose your visual properties. No other vizmap.props files are saved during normal operation.

Saving Visual Styles

Visual styles are automatically saved with the session they were created in. Before Cytoscape exits, you will be prompted to make sure you save the session before quitting. It is also possible to save your visual styles in a file separate from the session file. To do this, navigate to the File → Export → Vizmap Property File menu option and save the properties as a file. This feature can be used to share visual styles with other users.

Importing Visual Styles

To import existing visual styles, navigate to the File → Import → Vizmap Property File menu option and select a vizmap.props file. Imported properties will supplement existing properties or override existing properties if the properties have the same name. You can also specify a visual properties file using the -V command line option (cytoscape.sh -V myVizmap.props). Visual properties loaded from the command line will override any default properties.

Default Visual Styles

It is possible to change the default visual properties for all sessions of Cytoscape. To do this, navigate to the Edit → Preferences → Properties... menu option, check the "Make Current Visual Styles Default" box in the Default Visual Styles section, and click the OK button. This will save the current visual styles as a vizmap.props file to your .cytoscape directory (found in your home directory). These visual styles will then be loaded each time Cytoscape is started.

Bypassing Visual Styles

Cytoscape has a feature that allows users to override visualizations created by the VizMapper for individual nodes and edges. This feature is available by right-clicking on a node or edge and then clicking on the Visual Mapping Bypass menu.

Each visual property of the node or edge is displayed. When a property is overridden, a checkmark appears next to the property and a [Reset <Property Name>] menu option appears directly below it. By clicking this Reset option, the bypass will be removed and the attribute will be displayed as defined by the VizMapper. At the bottom of the menu a Reset All option appears. When clicked, this will remove all bypasses for the specified node or edge. In the example above, you can see the selected node size, color, and shape have been overridden. This is apparent in the appearance of the node itself and by the check marks in the popup menu.

It is important to realize that the Visual Mapping Bypass only works for individual nodes and edges and not for all nodes or edges of a specific type. Using the bypass function is not particularly resource intensive, you can use it as much as you like. However, if you find yourself repeating the same bypasses, then you should consider using the VizMapper instead.

Bypass is accomplished using special attributes with names like node.fillColor and node.shape. These are normal Cytoscape attributes and can be seen and edited in the Data Panel. The value of the attribute is a string representation of a property. For example, color is represented by 3 integers representing the RGB (red, green, blue) value of the color. Different types of properties have different string representations. When in doubt, just use the right click menu to create valid attribute values.

Because bypass values are specified using normal attributes, these attributes will persist between sessions only as long as you save your session. If you don't save your session, you will lose whatever bypass values you set.

Search Bar

You can search for nodes and edges by column value directly through Cytoscape's tool bar. For example, to select nodes or edges with a column value that starts with "STE", type ste* in the search bar. The search is case-insensitive. The * is a wildcard character that matches zero or more characters, while "?" matches exactly one character. So ste? would match "STE2" but would not match "STE12". Searching for ste* would match both.

To search a specific column, you can prefix your search term with the column name followed by a :. For example, to select nodes and edges that have a "COMMON" column value that starts with "STE", use common:ste*. If you don't specify a particular column, all columns will be searched.

Columns with names that contain spaces, quotes, or characters other than letters and numbers currently do not work when searching a specific column. This will be fixed in a future release.

To search for column values that contain special characters you need to escape those characters using a "\". For example, to search for "GO:1232", use the query GO\:1232. The complete list of special characters is:

+ - & | ! ( ) { } [ ] ^ " ~ * ? : \

Note: Escaping characters only works when searching all columns. It currently does not work for column-specific searching. This will be fixed in a future release.

Filters

Cytoscape 3 provides a new user interface for filtering nodes and edges. These tools can be found in the Select panel:

There are two main types of filters: narrowing filters, which can be combined into a tree; and chainable filters, which can only be combined in a linear chain. These can be found in the Filter, and Chain tabs of the Select panel, respectively.

Narrowing Filters

Narrowing filters select nodes and edges based on user-specified constraints. For example, you can use these filters to find edges with a weight between 0 and 5.5, or nodes with degree less than 3. A filter can contain an arbitrary number of sub-filters. To add one to your filter, click on the "+" button.

Interactive Filter Application Mode

Due to the nature of narrowing filters, Cytoscape can apply them to a network efficiently and interactively. Some filters even provide slider controls to quickly explore different thresholds. This is the default behavior on smaller networks. For larger networks, Cytoscape automatically disables this interactivity. You can override this by manually checking the Apply Automatically box above the Apply button:

Cytoscape comes packaged with the following narrowing filters:

Column Filter

This filter will match nodes or edges that have particular column values. For numeric columns, sliders are provided to set thresholds in interactive mode. Otherwise, minimum and maximum values can be keyed in.

From string columns, a variety of matching options are provided:

For example, attribute values can be checked if they contain or match exactly a particular string. The filter can also match against Java-style regular expressions. A checkbox controls whether the matching is done in a case-sensitive way.

Degree Filter

The degree filter matches nodes with a degree that falls within the given minimum and maximum values, inclusive. You can choose whether the filter operates on the in-degree, out-degree or overall (in + out) degree.

Topology Filter

The topology filter matches nodes with a certain number of neighbors which are within a fixed distance away. The thresholds for the neighborhood size and distance can be set independently.

Grouping and Organizing Filters

By default, nodes and edges need to satisfy the constraints of all your filters. You can change this so that instead, only the constraints of at least one filter needs to be met in order to match a node or edge. This behavior is controlled by the Match all/any drop-down box. This appears once your filter has more than one sub-filter. For example, suppose you wanted to match nodes with column COMMON containing ste or cdc, but you only want nodes with degree 5 or more, you'd first construct a filter that looks like this:

This filter will match nodes where COMMON contains ste and cdc. To change this to a logical or operation, drag either of the column filters by its handle onto the other column filter to create a new group. Now change the group's matching behaviour to Match any:

You can also reorder filters by dropping them in-between existing filters.

Chainable Filters

Chainable filters are a more general case of narrowing filters. These filters take nodes and edges, from your selection or a narrowing filter, as input. The nodes and edges in the output of the filter become the input of the next filter in the chain. The output of the last filter becomes the new selection.

Chainable filters can also be reordered by dragging one by the handle and dropping it between existing filters.

Cytoscape currently bundles the following chainable filter:

Interaction Transformer

This transformer will go through all the input edges and add their source nodes, target nodes, or both, to the output. This is useful for selecting nodes that are connected to edges that match a particular filter.

Working with Narrowing and Chainable Filters

The name of active filter appears in the dropdown box at the top of Select panel. Beside this is the options button which will allow you to rename, remove or export the active filter. It also lets you create a new filter, or import filters.

At the bottom of the Select panel, there is an Apply button that will re-apply the active filter. On the opposite side of the progress bar is the cancel button, which will let you interrupt a long-running filter.

Using Cytoscape's Editor, you can build and modify networks interactively by dragging and dropping nodes and edges from a palette onto the main network view window. The palette contains a set of shapes (for nodes) and arrows (for edges). The shapes on the palette are defined by the current Visual Style, with Node Shape and Node Color mapping into the shape and color of a node, and Edge Target Arrow mapping into the target arrow of an edge. An example of an editor, with the palette contained in CytoPanel 1, is shown below.

To edit an existing network, just select the Editor tab in CytoPanel 1. To start editing a new network, create a new network by going to File → New → Network → Empty Network.

To add a node to a network, drag and drop a node shape from the palette onto the canvas. To connect two nodes with an edge, drag and drop an arrow shape onto a node on the canvas. This node becomes the source node of the edge. Move the cursor and a rubber-banded line will follow the cursor. As the cursor passes over another node, that node is highlighted and the rubber-banded line will snap to a connection point on that second node. Click the mouse while over this node and the connection will be established.

You can abort the drawing of the edge by clicking on an empty spot on the palette.

Note that if you change the Visual Style, the palette used by the current network view will also change to be consistent with the mappings in the new Visual Style.

There is also an Edit → Connect Selected Nodes option that, when chosen, creates a clique amongst the selected nodes.

The editor provides accelerators for adding nodes and edges. Control-clicking at a position on the canvas creates a node at that position. The NODE_TYPE attribute of the node will be the same as the NODE_TYPE of the node most recently added, defaulting back to the original visual style. In this manner, you can use control-clicking as a kind of "stamp" to add multiple nodes of the same type to the network. Control-clicking on a node on the canvas starts an edge with its source at that node. Move the cursor and a rubber-banded line will follow the cursor. As the cursor passes over another node, that node is highlighted and the rubber-banded line will snap to a connection point on that second node. Control-click the mouse again and the connection will be established. The EDGE_TYPE attribute of the edge will be the same as the EDGE_TYPE of the edge most recently added, defaulting back to the original visual style. You can abort the drawing of the edge by control-clicking on an empty spot on the palette.

You can delete nodes and edges by selecting a number of nodes and edges, then selecting Edit → Delete Selected Nodes and Edges. You can recover any nodes and edges deleted from a network by going to Edit → Undo. However, note that this will restore all nodes and edges that were previously deleted from the network, not just those deleted by the most recent delete operation.

Add Interactions (SIF Style)

You can also add interactions by typing SIF (Simple Interaction Format) style entries.

1. Select a network you want to add new interactions.

2. Open Editor.

3. Double-click space on the network window. You will be asked to type interaction in SIF style. Try A pp B.

4. New interaction appears on the network.

Introducing Nested Networks

As of version 2.7, Cytoscape gained the ability to associate a nested network with a node. Such a nested network is not the network that the node is contained in but any other network currently defined in Cytoscape. This capability allows for creation of network hierarchies as well as circular relationships. For example, various module-finding plugins make use of nested networks in the overview network that they generate. There each node representing a module contains a nested network.

Creating Nested Networks

There are currently two ways in which a user can create nested networks.

1. By importing a Nested Network Format (NNF) file. (See: ../Network_Formats#NNF).

2. By manually constructing networks and assigning nested networks to individual nodes through the right-click node context menu. (See: ../Navigation_Layout#Nested Network Node Context Submenu)

Visualisation of Nested Networks

Nodes containing nested networks that are zoomed in sufficiently display an image for the nested network. If no current network view exists for the nested network the image will be a default icon, otherwise it will be a low-resolution rendering of the nested network's current layout.

Programmatically Manipulating Nested Networks

The giny.model.node interface defines two methods:

• public void setNestedNetwork(final GraphPerspective graphPerspective); This will assign a "network" (GraphPerspective) to a Node or replace the assigned network at a node if there was a prior existing one. In order to remove a nested network, please pass null to this method.

• public GraphPerspective getNestedNetwork(); If a Node has an associated nested network, it will be returned by this method. If no associated nested network exists, null will be returned instead.

The Plugin Manager

The Plugin Manager, first introduced in Cytoscape 2.5, allows users to quickly and conveniently add extra features to Cytoscape directly from within Cytoscape, eliminating the need for manual searches through different webpages to install and update plugins.

For plugin developer, to enable automatic download of your plugin to Cytoscape users, your plugin should be in compliance with Cytoscape 2.5 or later, and the plugin jar/zip files should be uploaded to the Cytoscape plugin web site at http://cytoscape.org/plugins.php.

Note: 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.

Get New Plugins

To install new features, 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.

The 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. In contrast, the Available for Install folder displays plugins that may be installed. To install and use these plugins, click on the file name and then click on the Install button at the bottom of the window. A license agreement may appear, in which case you must accept it in order to download the plugin. You will then see a progress bar as the plugin is automatically downloaded and installed into your current version of Cytoscape. The progress bar will disappear when the download is complete. Other plugins can then be downloaded, or the manager can be closed by clicking the Close button.

Once a new plugin is added, it can immediately be used. Closing and restarting Cytoscape is not required. For example, installing the MCODE plugin will automatically result in new menu options such as Plugins → MCODE → Start MCODE.

Themes

Some groups of plugins have been released in a single bundle called a "Theme". Installing it will get you the functionality provided by all of the plugins listed within the theme. To see available themes just look under the "Theme" heading under Available for Install. Note that once a theme is installed updates to the included plugins will only be installed when the entire theme has been released with a newer version. If a theme has been installed none of the plugins may be installed or deleted separately.

Troubleshooting

• If an installation error appears, automatic installation of the plugin may not be supported. To manually install the plugin, go to the Cytoscape plugins page (http://cytoscape.org/plugins.php), scroll down to find the plugin, click on the appropriate link to download the file, and then save it in the Cytoscape/plugins folder on your hard drive.

• Cytoscape will require a restart in order to load the manually installed plugin.
• If the plugin does not appear in the Currently Installed folder of the Plugin Manager, then Cytoscape was unable to load the plugin. Your command line will display the error message generated.

Delete Existing Plugins

To delete an existing plugin or theme, go to the Plugin Manager at Plugins → Manage Plugins, click on the appropriate plugin once to select it, and then click the Delete button at the bottom of the manager. It is best to avoid deleting core plugins, as this may cause Cytoscape or other plugins to malfunction. A plugin will be completely deleted after you have restarted Cytoscape.

Update Existing Plugins

Going to Plugins → Update Plugins will result in Cytoscape automatically accessing the Internet to look for updated versions of the plugins you have installed. If newer versions are available, Cytoscape will then display the available updates in the Plugin Manager; otherwise, it will inform you that there are no updatable plugins. When multiple updates are detected, you will have the option to download some or all of the updates. Some updates may require re-accepting the license before the download will begin. All updates require Cytoscape to be restarted in order for the update to be fully installed. After clicking the Update All or Update Selected buttons, a progress bar will appear showing the status of the download; it will disappear once the update is complete, and the Plugin Manager can then be closed by clicking the Close button.

Note: The Update All button will update all listed plugins to the newest available version. If you prefer a different version, select the name and click Update Selected.

Download Plugins from a Custom Site

The Plugin Manager automatically connects to the Cytoscape website and the sites of registered Cytoscape plugins to check for and download any available plugins and updates. To change this setting, open the Plugin Manager (by going to Plugins → Manage Plugins) and click the Settings tab. You may choose a site from a preset list of bookmarks. Alternatively, click the Add button to open the Add new Bookmark dialog and create a new bookmark. After new book mark is created, the Plugin Manager will refresh using that site.

Note: Custom download sites added from the Plugin Manager are not currently saved when you exit Cytoscape.

What are CytoPanels?

CytoPanels are floatable/dockable panels designed to cut down on the number of pop-up windows within Cytoscape and to create a more unified user experience. These panels used to be called CytoPanel 1, 2, and 3. From 2.5, they are named based on their functions. The following screenshot shows the file yeastHighQuality.sif and GO annotations loaded into Cytoscape, performed Force-Directed layout, enable Align and Distribute tools, and then run MCODE plugin for the data sets. In Control Panel (at the left-hand side of the screen), the Network Manager, Network Overview, VizMapper, Filters, and Cytoscape Editor have been loaded. On the bottom of the panel, there is another CytoPanel called Tool Panel. In the Data Panel, the Attribute Browser has been loaded. In addition, Result of the analysis by MCODE plugin is shown in Result Panel (at the right-hand side).

The user can then choose to resize, hide or float CytoPanels. For example, in the screenshot below, the user has chosen to float all panels and toolbar:

Basic Usage

Cytoscape includes four CytoPanels: Control Panel on the left, Tool Panel on the bottom of Control Panel, Data Panel on the bottom, and Result Panel on the right. By default, Control Panel and Data Panel will appear. Result Panel may appear, depending on the mix of Cytoscape plugins that you currently have installed. Tool Panel will appear when you select the following commands under the Layout menu: Rotate, Scale, and Align and Distribute.

All panels can be shown or hidden using the View → Show/Hide functions.

In addition, CytoPanels can be floated or docked by selecting the icon at the top right corner of each CytoPanel. The icon and tooltip will change based on the CytoPanel state. If the CytoPanel is docked, clicking on the icon will float the CytoPanel, as indicated by the “Float Window” tooltip. Alternatively, if the CytoPanel is floating, clicking on the icon will dock the CytoPanel, as indicated by the “Dock Window” tooltip.

What is Level of Detail (LOD)?

In Cytoscape 2.3, a new network rendering engine is being introduced. The goal of the rendering engine is to be able to display large networks (>10,000 nodes), yet retain interactive speed. To accomplish this goal, a technique involving level of detail (LOD) is being used. Based on the number of objects (nodes and edges) being rendered, an appropriate level of detail is chosen. For example, by default, node labels (if present) are only rendered when less than 100 nodes are visible because drawing text is a relatively expensive operation. This can create some unusual behavior. If the screen currently contains 98 nodes, node labels will be displayed. If you pan across the network, such that now 101 nodes are displayed, the node labels will disappear. As another example, if the sum of rendered edges and rendered nodes is greater than or equal to a default value of 2000, a very coarse level of detail is chosen, where edges are always straight lines, nodes are always rectangles, and no antialiasing is done. The default values used to determine these thresholds can be changed by setting properties under Edit → Preferences → Properties... .

Low LOD vs High LOD

With low LOD values, all nodes are displayed as square and anti-alias is turned off. With high LOD values, anti-alias is turned on and nodes are displayed as actual shape user specified in the Visual Style.

Parameters for Controlling LOD

NOTE: The greater these thresholds become, the slower performance will become. If you work with small networks (a few hundred nodes), this shouldn't be a problem, but for large networks it will produce noticeable slowing. The various thresholds are described below.

When printing networks or exporting to formats such as PostScript, the highest level of detail is always chosen, regardless of what is currently being displayed on the screen.

Force to Display Detail

If you want to display every detail of the network regardless of LOD values, you can use View → Show Graphics Details. This option force to display every graphics details. If the network is large, this option slows down rendering speed.

Annotations in Cytoscape are stored as a set of ontologies (e.g. the Gene Ontology, or GO). An ontology consists of a set of controlled vocabulary terms that annotate the objects. For example, using the Gene Ontology, the Saccharomyces Cerevisiae CDC55 gene has a biological process described as “protein biosynthesis”, to which GO has assigned the number 6412 (a GO ID).

GO 8150 biological_process
 GO 7582 physiological processes
   GO 8152 metabolism
    GO 44238 primary metabolism
      GO 19538 protein metabolism
        GO 6412 protein biosynthesis

Graphical View of GO Term 6412: protein biosynthesis

Cytoscape can use this ontology DAG (Directed Acyclic Graph) to annotate objects in networks. The Ontology Server (originally called "BioDataServer") is a Cytoscape feature which allows you to load, navigate, and assign annotation terms to nodes and edges in a network. Cytoscape 2.4 now has an enhanced GUI for loading ontology and associated annotation, enabling you to load both local and remote files.

Ontology and Annotation File Format

The standard file formats used in Cytoscape Ontology Server are OBO and Gene Association. The GO website details these file formats:

• Ontologies and Definitions: http://www.geneontology.org/GO.downloads.shtml#ont

• Current Annotations: http://www.geneontology.org/GO.current.annotations.shtml

OBO File

An OBO file is the ontology DAG itself. This file defines the relationships between ontology terms. Cytoscape 2.4 and onwards can load all ontology files written in OBO format. The full listing of ontology files are available from the Open Biomedical Ontologies (OBO) website:

• OBO Ontology Browser: http://obo.sourceforge.net/browse.html

Sample OBO File - gene_ontology.obo: http://www.geneontology.org/ontology/gene_ontology_edit.obo

format-version: 1.2
date: 27:11:2006 17:12
saved-by: midori
auto-generated-by: OBO-Edit 1.002
subsetdef: goslim_generic "Generic GO slim"
subsetdef: goslim_goa "GOA and proteome slim"
subsetdef: goslim_plant "Plant GO slim"
subsetdef: goslim_yeast "Yeast GO slim"
subsetdef: gosubset_prok "Prokaryotic GO subset"
default-namespace: gene_ontology
remark: cvs version: $Revision: 5.49 $

[Term]
id: GO:0000001
name: mitochondrion inheritance
namespace: biological_process
def: "The distribution of mitochondria, including the mitochondrial genome, into daughter cells after mitosis or meiosis, mediated by interactions between mitochondria and the cytoskeleton." [GOC:mcc, PMID:10873824, PMID:11389764]
synonym: "mitochondrial inheritance" EXACT []
is_a: GO:0048308 ! organelle inheritance
is_a: GO:0048311 ! mitochondrion distribution

[Term]
id: GO:0000002
name: mitochondrial genome maintenance
namespace: biological_process
def: "The maintenance of the structure and integrity of the mitochondrial genome." [GOC:ai]
is_a: GO:0007005 ! mitochondrion organization and biogenesis

Default List of Ontologies

Cytoscape provides a list of ontologies available in OBO format. If an Internet connection is available, Cytoscape will import ontology and annotation files directly from the remote source. The table below lists the included ontologies.

Although Cytoscape can import all kinds of ontologies in OBO format, annotation files are associated with specific ontologies. Therefore, you need to provide the correct ontology-specific annotation file to annotate nodes/edges/networks in Cytoscape. For example, while you can annotate human network data using the GO Full ontology with human Gene Association files, you cannot use a combination of the human Disease Ontology file and human Gene Association files, because the Gene Association file is only compatible with GO.

Visualize and Browse Ontology DAG (for Advanced Users)

Relationships between ontology terms are usually represented as Directed Acyclic Graphs (DAGs). This is a special case of a network (or graph), where nodes are ontology terms and edges are relationships between terms. Originally, Cytoscape used a special data structure called BioDataServer to store ontology DAGs. Starting in version 2.4, ontology data will now be stored in the same data structure as normal networks. This enables users and plugin writers to visualize, browse and manipulate ontology DAGs just like other networks. The following is an example of visualization of an ontology DAG (Generic GO Slim):

Every ontology term and relationship can have attributes. In the OBO files, ontology terms have optional fields such as definition, synonyms, comments, or cross-references. These fields will be imported as node attributes. To browse those attributes, please use the attribute browser (see the example below):

• Note 1: Some ontologies have a lot of terms. For example, the full Gene Ontology contains more than 20,000 terms. If you need to save memory, you can remove this ontology DAG from Network Panel (right-click on the ontology name at the left-hand side of the screen and select Destroy Network).
• Note 2: All ontology DAGs will be saved in the session file. To minimize the session file size, you can delete the Ontology DAG before saving session.

Gene Association File

The Gene Association (GA) file provides annotation only for the Gene Ontology. It is a species-specific annotation file for GO terms. Gene Association files will only work with Gene Ontologies and NOT others!

Sample Gene Association File (gene_association.sgd - annotation file for yeast):

SGD     S000003916      AAD10           GO:0006081      SGD_REF:S000042151|PMID:10572264        ISS             P       aryl-alcohol dehydrogenase (putative)        YJR155W gene    taxon:4932      20020902        SGD
SGD     S000005275      AAD14           GO:0008372      SGD_REF:S000069584      ND              C       aryl-alcohol dehydrogenase (putative)        YNL331C gene    taxon:4932      20010119        SGD

Node Name Mapping

If you have a network file and an attribute file, they should have a common key to map attributes onto network data. If those two do not have a common key, you need to do an extra step to add a shared key. The following is a quick tutorial to learn how to use Gene Name Mapping files.

Import New ID Sets from BioMart

From Cytoscape 2.6.0, you can import various kinds of ID sets from BioMart (http://www.biomart.org/index.html). BioMart web service client is available as a set of plugins. You can install BioMartClient and BioMartUserInterface plugins from Plugin Manager window.

1. Select: File → Import → Import attributes from Biomart...

2. Select a data source. For ID mapping, select one of the Ensemble Genes data set. You need to choose correct species for your network.

3. Select Attribute. If you want to import new ID sets matching current node IDs, select ID.

4. Select Data Type. This should be the type of ID set selected in Attribute list. For example, if you select ID for Attribute and your network uses Entrez Gene ID for its node ID, you need to select EntrezGene ID(s) for Data Type.

5. Select new ID sets from the list. Because BioMart server does not accept query to import lots of annotations at once, you can select only 3-5 attributes for each import.

6. Press Import.

Import Network and Name Mapping Files

1. Download name mapping files. Mapping files are available at: http://chianti.ucsd.edu/kono/genenamemapping.html. In this tutorial, we are going to use dictionary_no_prefix.zip, which is a file set without prefixes for each gene names. Unzip the archive.

2. Load sample network file. Open network import dialog from File-->Import-->Network (multiple file types)... Then click URL radio button and import Human Protein-Protein: Rual et al. (Subnetwork for tutorial).

3. Open attribute table import dialog from File-->Import-->Attribute from Table.

4. Select human.dic_cyto.txt as the input file.

5. Check "Show Text File Import Options and click Transfer first line as attribute names checkbox.

6. Uncheck "Show Text File Import Options and check Mapping Options.

7. Select EntrezGene as Primary Key.

8. Right-click on EntrezGene column name and set the type to String.

9. Do the same for HGNC.

10. Right-click on Other Aliases and select List as the data type.

11. Check Other Aliases as Alias (under "Alias?" checkboxes).

12. Now the Table Import dialog looks like the following screenshot:

    • 

13. Press Import. The network has new names in the text file as attributes.

    • 

At this point, nodes have multiple names including HGNC, UniProt, and EntrezGene ID. You can import other attribute files using these keys. These imported names (IDs) are useful when you import GO Annotation.

Import Ontology and Annotation

Cytoscape 2.4 provides a graphical user interface to import both ontology and annotation files at the same time.

Import Gene Ontology and Gene Association Files

For convenience, Cytoscape has a list of URLs for commonly used ontology data and a complete set of Gene Association files. To import Gene Ontology and Gene Association files for the loaded networks, please follow these steps:

Important: All data sources in the preset list are remote URLs, meaning a network connection is required!

Step 1. Select an Annotation File

• 

  Select File → Import → Ontology and Annotation... to open the "Import Ontology and Annotation" window. From the Annotation dropdown list, select a gene association file for your network. For example, if you want to annotate the yeast network, select "Gene Association file for Saccharomyces cerevisiae".

Step 2. Select an Ontology File

• Select an Ontology data (OBO file) from the Ontology dropdown list. If the file is not loaded yet, it will be shown in red. The first three files are Gene Ontology files. You can load other ontologies, but you need your own annotation file to annotate networks.

Step 3. Import the files

• Once you click the Import button, Cytoscape will start loading OBO and Gene Association files from the remote sources. If you choose GO Full it may take a while since it is a large data file.

Step 4.

• When Cytoscape finishes importing files, the import window will be automatically closed. All attributes mapped by this function have the prefix "annotation" and look like this: annotation.[attribute_name]. All ontologies will be added to the end of the Ontology DAGs branch in the Network Manager.

  • 

Ontology DAGs have some attributes associated with the terms. All attributes associated with ontology terms will have the prefix ontology. They have at least one attribute: ontology.name. For more detailed information about attributes for ontology DAGs, please read the official OBO specification document.

• Note: Cytoscape supports both OBO formats: version 1.0 and 1.2.

Note: Switching Primary Key for Go Annotation Import

If node IDs in a network file are NOT DB_Object_Symbol (3rd column in Gene Association file), you need to select a primary key column. Click Show Mapping Options to change the key. Usually, DB_Object_ID can be an alternative primary key.

Custom Annotation Files for Ontologies Other than GO (for Advanced Users)

• The "Import Ontology and Annotation" function is designed to import general ontology and annotation files. Internally, mapping ontology terms onto existing networks is the same as joining three data tables in Cytoscape. An Ontology DAG, an annotation file, and network data are used in this process (see the example below).

Network Data

Ontology Data

Annotation Data

Mapping Result

If you want to map ontology terms onto network objects, you need to create a custom annotation file. The annotation file should contain at least 2 columns: a primary key and an ontology term ID. The primary key is the value used for mapping between the annotation file and network. Usually, the node/edge ID is used as the primary key, but you may choose any of the available attributes. The Ontology term ID is the key used for mapping between the annotation file and the ontology DAG. Using these data sources, you can annotate network objects in Cytoscape.

Suppose you have a small network:

node_1 pp node_2
node_3 pp node_1
node_2 pp node_3

and you want to annotate this network with Ontology A, which is an ontology DAG available in OBO format. In this case, you need an annotation table file that looks like this:

node_1  OA_0000232
node_2  OA_0000441
node_3  OA_0000702

where OA_*** represents an ontology term ID. This example is a file with the minimum necessary number of columns; however, you can include additional columns that will appear as additional node attributes.

Some ontologies will be used to annotate edges or networks. For example, the Protein-protein interaction ontology is a controlled set of terms for annotating interactions between proteins, so ontology terms should be mapped onto edges (see example below).

node_1 (pp) node_2  MI:0445
node_3 (pp) node_1  MI:0046
node_2 (pp) node_3  MI:0346

The basic operation of the Ontology and Annotation Import function is the same as that of the Attribute Table Import. The main difference is that you need to specify an additional key for mapping:

By selecting a column from the "Key Column in Annotation File" dropdown list, you can specify the key for mapping between ontology terms and the annotation file.

• Note: When you load Gene Association files, Cytoscape uses a special loader program designed only for Gene Association files. Because of this program, all attributes will be named automatically. Also, ontology IDs will be converted into term names and NCBI taxonomy ID will be converted into actual species name. However, for custom annotation files, those processes will not be applied. All ontology terms will be mapped as term IDs.

LinkOut provides a mechanism to link nodes and edges to external web resources within Cytoscape. Right-clicking on a node or edge in Cytoscape view opens a popup menu with a list of web links.

The external links are specified in a linkout.props file which is included in the cytoscape.jar file. The defaults include a number of links such as Entrez, SGD, iHOP, and Google, as well as a number of species-specific links. In addition to the default links, users can customize the LinkOut menu by adding (or removing) links by editing the linkout properties (found under Edit → Preferences → Properties...).

External links are listed as ‘key’-‘value’ pairs in the linkout.props file where key specifies the name of the link and value is the search URL. The LinkOut menus are organized in a hierarchical structure that is specified in the key. Linkout key terms specific for nodes start with the keyword nodelinkouturl, for edges this is edgelinkouturl.

For example, the following entry:

nodelinkouturl.Model Organism DB.SGD (yeast)=http://db.yeastgenome.org/cgi-bin/locus.pl?locus=%ID%

places the SGD link under the yeast submenu. This link will appear in Cytoscape as:

In a similar fashion one can added new submenus.

The %ID% string in the URL is a place-holder for the node label. When the popup menu is generated this marker is substituted with the node label. In the above example, the generated SGD link for the YIM1 protein is:

http://db.yeastgenome.org/cgi-bin/locus.pl?locus\=YIM1

If you want to query based on a different attribute you currently need to specify a different Node Label using the VizMapper.

For edges the mechanism is much the same; however here the placeholders %ID1% and %ID2% reflect the source and target node label respectively.

Currently there is no mechanism to check whether the constructed URL query is correct and if the node label is meaningful. Similarly, there is no ID mapping between various identifiers. For example, a link to NCBI Entrez from a network that uses ensembl gene identifiers as node labels will produce a link to Entrez using ensembl ID, which results in an incorrect link. It is the user's responsibility to ensure that the node label that is used as the search term in the URL link will result in a meaningful link.

Adding or Removing Links

The default links are defined in a linkout.props file contained in linkout.jar. These links are normal java properties and can be edited by going to Edit → Preferences → Properties... . New links can be defined this way as well. New links can be defined at startup in a separate file and loaded from the command line, either by specifying a file containing the links

cytoscape.sh -P new_linout.props

or as individual properties

cytoscape.sh -P nodelinkouturl.yeast.SGD=http://db.yeastgenome.org/cgi-bin/locus.pl?locus\=%ID%

Any links defined on the command line will supersede the default links.

To remove a link from the menu simply delete the property, using Edit → Preferences → Properties... .

Use LinkOut from Attribute Browser

From Cytoscape 2.6.0, you can use LinkOut from Attribute Browser. Basic functionality is the same, and the only difference is the parameter passed to the LinkOut is value in the selected cell.

Cytoscape is built with a number of open source third-party Java libraries. The Cytoscape team gratefully acknowledges the following libraries:

• The Colt Distribution: Open Source Libraries for High Performance Scientific and Technical Computing in Java. Information is available at: http://hoschek.home.cern.ch/hoschek/colt/.

• Graph INterface librarY a.k.a. GINY. Information is available at: http://csbi.sourceforge.net/.

• JDOM. Information is available at: http://www.jdom.org.

• JUnit. Information is available at: http://junit.org.

• JGoodies Looks. Information is available at: http://www.jgoodies.com/freeware/looks/index.html.

• Piccolo. Information is available at: http://www.cs.umd.edu/hcil/jazz/.

• Type-Specific Collections Library, from Sosnoski Software Solutions, Inc. Information is available at: http://www.sosnoski.com/opensrc/tclib/.

• Xerces Java XML parser. Information is available at: http://xml.apache.org/xerces-j/.

• CLI command line parser. Information is available at: http://jakarta.apache.org/commons/cli/.

• FreeHEP library. Information is available at: http://java.freehep.org.

This product includes software developed by the Apache Software Foundation (http://www.apache.org/).

This product includes software developed by the JDOM Project (http://www.jdom.org/).

One-step installation of the Cytoscape software is accomplished using the InstallAnywhere product from ZeroG Software, Inc. (http://zerog.com)

Handlers for the following format still exist in Cytoscape as legacy code, however we strongly recommend using the new formats (OBO + Gene Association) described in the previous section, since they are easier to download directly from the Gene Ontology project and use directly. Currently, users have no access to an import interface for this old format.

Building your own annotation files

The annotation server requires that the gene annotations and associated ontology of controlled vocabulary terms follow a simple format. This simple format was chosen because it is efficient to parse and easy to use.

The flat file formats are explained below:

The Ontology Format

By example (the Gene Ontology - GO):

(curator=GO) (type=all)
0003673 = Gene_Ontology
0003674 = molecular_function [partof: 0003673 ]
0008435 = anticoagulant [isa: 0003674 ]
0016172 = antifreeze [isa: 0003674 ]
0016173 = ice nucleation inhibitor [isa: 0016172 ]
0016209 = antioxidant [isa: 0003674 ]
0045174 = glutathione dehydrogenase (ascorbate) [isa: 0009491 0015038 0016209 0016672 ]
0004362 = glutathione reductase (NADPH) [isa: 0015038 0015933 0016209 0016654 ]
0017019 = myosin phosphatase catalyst [partof: 0017018 ]
...

A second example (KEGG pathway ontology):

(curator=KEGG) (type=Metabolic Pathways)
90001 = Metabolism
80001 = Carbohydrate Metabolism [isa: 90001 ]
80003 = Lipid Metabolism [isa: 90001 ]
80002 = Energy Metabolism [isa: 90001 ]
80004 = Nucleotide Metabolism [isa: 90001 ]
80005 = Amino Acid Metabolism [isa: 90001 ]
80006 = Metabolism of Other Amino Acids [isa: 90001 ]
80007 = Metabolism of Complex Carbohydrates [isa: 90001 ]
...

The format has these required features:

• The first line contains two parenthesized assignments for curator and type. In the GO example above, the ontology file (which is created from the XML that GO provides) nests all three specific ontologies (molecular function, biological process, cellular component) below the 'root' ontology, named 'Gene_Ontology'. (type=all) tells you that all three ontologies are included in that file.

• Following the mandatory title line, there are one or more category lines, each with the form:

  • number0 = name [isa:|partof: number1 number2 ...]

  where isa and partof are terms used in GO; they describe the relation between parent and child terms in the ontology hierarchy.

• The trailing blank before each left square bracket is not required; it is an artifact of the python script that creates these files.

The Annotation Format

By example (from the GO biological process annotation file):

(species=Saccharomyces cerevisiae) (type=Biological Process) (curator=GO)
YMR056C = 0006854
YBR085W = 0006854
YJR155W = 0006081
...

and from KEGG:

(species=Mycobacterium tuberculosis) (type=Metabolic Pathways) (curator=KEGG)
RV0761C = 10
RV0761C = 71
RV0761C = 120
RV0761C = 350
RV0761C = 561
RV1862 = 10
...

The format has these required features:

• The first line contains three parenthesized assignments, for species, type and curator. In the example just above, the annotation file (created for budding yeast from the flat text file maintained by SGD for the Gene Ontology project and available both at their web site and at GO's) shows three yeast ORFs annotated for biological process with respect to GO, as described above.

• Following the mandatory title line, there are one or more annotation lines, each with the form:

  • canonicalName = ontologyTermID

• Once loaded, this annotation (along with the accompanying ontology) can be assigned to nodes in a Cytoscape network. For this to work, the species type of the node must exactly match the species named on the first line of the annotation file. The canonicalName of your node must exactly match the canonicalName present in the annotation file. If you don’t see the expected results when using this feature of Cytoscape, check this again, as getting either of these wrong is a common mistake.

Load Data into Cytoscape

The easiest way to make annotations available to Cytoscape is by loading annotations into the Cytoscape annotation server. This is the default behavior for the official release of Cytoscape.

The Annotation Manifest

You must first create a text file to specify the files you want Cytoscape to load. Here is an example, from a file which (for convenience) we usually call manifest:

ontology=goOntology.txt
annotation=yeastBiologicalProcess.txt
annotation=yeastMolecularFunction.txt
annotation=yeastCellularComponent.txt

Use the Cytoscape -b command line argument to specify the annotation manifest file to read (e.g. -b manifest). Please note that the -s switch, which sets the default species for your data, is required to exactly match the species named in any annotation file you wish to use.

Getting and Reformatting GO Data

The Gene Ontology (GO) project is a valuable source of annotation for the genes of many organisms. In this section we will explain how to:

1. Obtain the GO ontology file
2. Reformat it into the simpler flat file Cytoscape uses
3. Obtain an annotation file (we illustrate with yeast and human annotation)
4. Reformat the annotation files into the simple Cytoscape format

Obtain the GO ontology file

Go to the GO XML FTP (ftp://ftp.geneontology.org/pub/go/xml/) page. Download the latest go-YYYYMM-termdb.xml.gz file.

Reformat GO XML ontology file into a flat file

 gunzip go-YYYYMM-termdb.xml.gz
 python parseGoTermsToFlatFile.py go-YYYYMM-termdb.xml > goOntology.txt

(see below for Python script listing)

Obtain the association file for your organism

GO maintains a list of association files for many organisms; these files associate genes with GO terms. The next step is to get the file for the organism(s) you are interested in, and parse it into the form Cytoscape needs. A list of files may be seen at http://www.geneontology.org/GO.current.annotations.shtml. The rightmost column contains links to tab-delimited files of gene associations, by species. Choose the species you are interested in, and click 'Download'.

Let's use "GO Annotations @ EBI: Human" as an example. After you have downloaded and saved the file, look at the first few lines:

SPTR    O00115  DRN2_HUMAN              GO:0003677      PUBMED:9714827  TAS             F       Deoxyribonuclease II precursor  IPI00010348     protein taxon:9606              SPTR
SPTR    O00115  DRN2_HUMAN              GO:0004519      GOA:spkw        IEA             F       Deoxyribonuclease II precursor  IPI00010348     protein taxon:9606        20020425      SPTR
SPTR    O00115  DRN2_HUMAN              GO:0004531      PUBMED:9714827  TAS             F       Deoxyribonuclease II precursor  IPI00010348     protein taxon:9606              SPTR
...

Note that line wrapping has occurred here, so each line of the actual file is wrapped to two lines. The goal is to create from these lines the following lines:

(species=Homo sapiens) (type=Molecular Function) (curator=GO)
IPI00010348 = 0003677
IPI00010348 = 0004519
IPI00010348 = 0004531
...

or

(species=Homo sapiens) (type=Biological Process) (curator=GO)
NP_001366 = 0006259
NP_001366 = 0006915
NP_005289 = 0007186
NP_647593 = 0006899
...

The first sample contains molecular function annotations for proteins, and each protein is identified by its IPI number. IPI is the International Protein Index, which maintains cross references to the main databases for human, mouse and rat proteomes. The second sample contains biological process annotation, and each protein is identified by its NP (RefSeq) number. These two naming systems, IPI and RefSeq, are two of many that you can use to define canonical names when you run Cytoscape. For budding yeast, it is much easier: the yeast community always uses standard ORF names, and so Cytoscape uses these as canonical names. For human proteins and genes, there is no single standard.

The solution (for those working with human genes or proteins) is, once you have downloaded the annotations file, to:

1. Decide which naming system you want to use.

2. Download ftp://ftp.ebi.ac.uk/pub/databases/GO/goa/HUMAN/xrefs.goa. This cross-reference file, when used strategically, allows you to create Cytoscape-compatible annotation files in which the canonical name is the one most meaningful to you.

3. Examine xrefs.goa to figure out which column contains the names you wish to use.

4. Make a very slight modification to the python script described below, and then

5. Run that script, supplying both xrefs.goa and that annotation file as arguments.

Here are a few sample lines from xrefs.goa:

SP      O00115  IPI00010348             ENSP00000222219;        NP_001366;              BAA28623;AAC77366;AAC35751;AAC39852;BAB55598;AAB51172;AAH10419; 2960,DNASE2     1777,DNASE2
SP      O00116  IPI00010349             ENSP00000324567;ENSP00000264167;        NP_003650;              CAA70591;       327,AGPS        8540,AGPS
SP      O00124  IPI00010353             ENSP00000265616;ENSP00000322580;        NP_005662;              BAA18958;BAA18959;AAH20694;             7993,D8S2298E
...

Note that line wrapping has occurred here – each line in this example starts with the letters SP. See the README file for more information (ftp://ftp.ebi.ac.uk/pub/databases/GO/goa/HUMAN/README).

Finally, run the script to create your three annotation files for human proteins:

• bioproc.anno (GO biological process annotation)

• molfunc.anno (GO molecular function annotation)

• cellcomp.anno (GO cellular component annotation)

using the supplied python script. It may be necessary to modify this script slightly if RefSeq identifiers are not used as canonical names or if you are using a more recent version of Python.

python parseAssignmentsToFlatFileFromGoaProject.py gene_association.goa_human xrefs.goa

(See below for Python script listing)

Python script examples

These scripts, as described above, require Python version 2.2 or later.

Script 1 - parseGoTermsToFlatFile.py

# parseGoTermToFlatFile.py:  translate a GO XML ontology file into a simpler
#  Cytoscape flat file
#-----------------------------------------------------------------------------------
# RCS: $Revision: 1.3 $   $Date: 2003/05/18 00:38:43 $
#-----------------------------------------------------------------------------------
import re, pre, sys
#-----------------------------------------------------------------------------------
def flatFilePrint (id, name, isaIDs, partofIDs):
  isa = ''
  if (len (isaIDs) > 0):
    isa = '[isa: '
    for isaID in isaIDs:
      isa += isaID
      isa += ' '
    isa += ']'
  partof = ''
  if (len (partofIDs) > 0):
    partof = '[partof: '
    for partofID in partofIDs:
      partof += partofID
      partof += ' '
    partof += ']'
  result = '~np~%~/np~s = ~np~%~/np~s ~np~%~/np~s ~np~%~/np~s' ~np~%~/np~ (id, name, isa, partof)
  result = result.strip ()
  if (result == 'isa = isa' or result == 'partof = partof'):
    print >> sys.stderr, 'meaningless term: ~np~%~/np~s' ~np~%~/np~ result
  else:
    print result
#-----------------------------------------------------------------------------------
if (len (sys.argv) != 2):
  print 'usage:  ~np~%~/np~s <someFile.xml>' ~np~%~/np~ sys.argv [0]
  sys.exit ();
inputFilename = sys.argv [1];
print >> sys.stderr,  'reading ~np~%~/np~s...' ~np~%~/np~ inputFilename
text = open (inputFilename).read ()
print >> sys.stderr,  'read ~np~%~/np~d characters' ~np~%~/np~ len (text)
regex = '<go:term .*?>(.*?)</go:term>';
cregex = pre.compile (regex, re.DOTALL)   # . matches newlines
m = pre.findall (cregex, text)
print >> sys.stderr, 'number of go terms: ~np~%~/np~d' ~np~%~/np~ len (m)
regex2 = '<go:accession>GO:(.*?)</go:accession>.*?<go:name>(.*?)</go:name>'
cregex2 = re.compile (regex2, re.DOTALL)
regex3 = '<go:isa\s*rdf:resource="http://www.geneontology.org/go#GO:(.*?)"\s*/>'
cregex3 = re.compile (regex3, re.DOTALL)
regex4 = '<go:part-of\s*rdf:resource="http://www.geneontology.org/go#GO:(.*?)"\s*/>'
cregex4 = re.compile (regex4, re.DOTALL)
goodElements = 0
badElements = 0
print '(curator=GO) (type=all)'
for term in m:
  m2 = re.search (cregex2, term)
  if (m2):
    goodElements += 1;
    id = m2.group (1)
    name = m2.group (2)
    isaIDs = []
    m3 = re.findall (cregex3, term);
    for ref in m3:
      isaIDs.append (ref)
    m4 = re.findall (cregex4, term);
    partofIDs = []
    for ref in m4:
      partofIDs.append (ref)
    flatFilePrint (id, name, isaIDs, partofIDs)
  else:
    badElements += 1;
    print >> sys.stderr, 'no match to m2...'
    print >> sys.stderr, "---------------\n~np~%~/np~s\n------------------" ~np~%~/np~ term
print >> sys.stderr,  'goodElements ~np~%~/np~d' ~np~%~/np~ goodElements
print >> sys.stderr, 'badElements ~np~%~/np~d' ~np~%~/np~ badElements
#--------------------------------------

Script 2 - parseAssignmentsToFlatFileFromGoaProject.py

import sys
#-----------------------------------------------------------------------------------
def fixCanonicalName (rawName):
# for instance, trim 'YBR085W|ANC3' to 'YBR085W'
  bar = rawName.find ('|')
  if (bar < 0):
    return rawName
  return rawName [:bar]
#-----------------------------------------------------------------------------------
def fixGoID (rawID):
  bar = rawID.find (':') + 1
  return rawID [bar:]
#-----------------------------------------------------------------------------------
def readGoaXrefFile (filename):
  lines = open (filename).read().split ('\n')
  result = {}
  for line in lines:
    if (len (line) < 10):
      continue
    tokens = line.split ('\t')
    ipi = tokens [2]
    np = tokens [5]
    semicolon = np.find (';')
    if (semicolon >= 0):
      np = np [:semicolon]
    if (len (ipi) > 0 and len (np) > 0):
      result [ipi] = np
  return result
#-----------------------------------------------------------------------------------
if (len (sys.argv) != 3):
  print 'error!  parse   <gene_associations file from GO> <goa xrefs file> '
  sys.exit ()
associationFilename = sys.argv [1];
xrefsFilename = sys.argv [2]
species = 'Homo sapiens'
ipiToNPHash = readGoaXrefFile (xrefsFilename)
tester = 'IPI00099416'
print 'hash size: ~np~%~/np~d' ~np~%~/np~ len (ipiToNPHash)
print 'test map: ~np~%~/np~s -> NP_054861: ~np~%~/np~s ' ~np~%~/np~ (tester, ipiToNPHash [tester])
bioproc = open ('bioproc.txt', 'w')
molfunc = open ('molfunc.txt', 'w')
cellcomp = open ('cellcomp.txt', 'w')
bioproc.write ('(species=~np~%~/np~s) (type=Biological Process) (curator=GO)\n' ~np~%~/np~ species)
molfunc.write ('(species=~np~%~/np~s) (type=Molecular Function) (curator=GO)\n' ~np~%~/np~ species);
cellcomp.write ('(species=~np~%~/np~s) (type=Cellular Component) (curator=GO)\n' ~np~%~/np~ species);
lines=open(associationFilename).read().split('\n')
sys.stderr.write ('found ~np~%~/np~d lines\n' ~np~%~/np~ len (lines))

for line in lines:
  if (line.find ('!') == 0 or len (line) < 2):
    continue
  tokens = line.split ('\t')
  goOntology = tokens [8]
  goIDraw = tokens [4]
  goID = goIDraw.split (':')[1]
  ipiName = fixCanonicalName (tokens [10])
  if (len (ipiName) < 1):
    continue


  if (not ipiToNPHash.has_key (ipiName)):
    continue
  refseqName = ipiToNPHash [ipiName]
  printName = refseqName
  #printName = ipiName
  if (ipiName == tester):
    print '~np~%~/np~s (~np~%~/np~s) has go term ~np~%~/np~s' ~np~%~/np~ (tester, printName, goID)
  if (goOntology == 'C'):
    cellcomp.write ('~np~%~/np~s = ~np~%~/np~s\n' ~np~%~/np~ (printName, goID))
  elif (goOntology == 'P'):
    bioproc.write ('~np~%~/np~s = ~np~%~/np~s\n' ~np~%~/np~ (printName, goID))
  elif (goOntology == 'F'):
    molfunc.write ('~np~%~/np~s = ~np~%~/np~s\n' ~np~%~/np~ (printName, goID))
#-----------------------------------------------------------------------------------

GNU LESSER GENERAL PUBLIC LICENSE

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