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.

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.

Cytoscape version 2.7 contains several new features, plus improvements to the performance and usability of the software.

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:

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

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.

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.

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.

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.

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.

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).

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.

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

YJR022W YNR053C
YER116C YDL013W
YNL307C YAL038W
YNL216W YCR012W
YNL216W YGR254W

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

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.

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).

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

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:

network node

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.

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

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

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

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 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.

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 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

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/

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.

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.

Node and edge attribute files are simply formatted: a node attribute file begins with the name of the attribute on the first line (note that it cannot contain spaces). Each following line contains the name of the node, followed by an equals sign and the value of that attribute. Numbers and text strings are the most common attribute types. All values for a given attribute must have the same type. For example:

FunctionalCategory
YAL001C = metabolism
YAR002W = apoptosis
YBL007C = ribosome

An edge attribute file has much the same structure, except that the name of the edge is the source node name, followed by the interaction type in parentheses, followed by the target node name. Directionality counts, so switching the source and target will refer to a different (or perhaps non-existent) edge. The following is an example edge attributes file:

InteractionStrength
YAL001C (pp) YBR043W = 0.82
YMR022W (pd) YDL112C = 0.441
YDL112C (pd) YMR022W = 0.9013

Since Cytoscape treats edge attributes as directional, the second and third edge attribute values refer to two different edges (source and target are reversed, though the nodes involved are the same).

Each attribute is stored in a separate file. Node and edge attribute files use the same format. Node attribute file names often use the suffix ".noa", while edge attribute file names use the suffix ".eda". Cytoscape recognizes these suffixes when browsing for attribute files.

Node and edge attributes may be loaded at the command line using the –n and –e options or via the File → Import menu.

When expression data is loaded using an expression matrix, it is automatically loaded as node attribute data unless explicitly specified otherwise.

Node and edge attributes are attached to nodes and edges, and so are independent of networks. Attributes for a given node or edge will be applied to all copies of that node or edge in all loaded network files, regardless of whether the attribute file or network file is imported first.

Note: In order to import network attributes in Cytoscape 2.4, please go to File → Import → Attribute from Table (text/MS Excel)... or encode them in an XGMML network file (see Supported File Formats for more details).

attributeName (class=JavaClassName)

floatingPointAttribute
firstName = 1
secondName = 2.5

floatingPointAttribute (class=Double)
firstName = 1
secondName = 2.5

floatingPointAttribute 
firstName = 1.0
secondName = 2.5

sourceName (edgeType) targetName

sourceName edgeType targetName

listAttributeName (class=java.lang.String)
firstObjectName = (firstValue::secondValue::thirdValue)
secondObjectName = (onlyOneValue)

newlineAttr
YJL157C = This is a long\nline for a label.

As of Cytoscape 2.4, importing delimited text and MS Excel attribute data tables is now supported. Using this functionality, users can now easily import data that isn't formatted into Cytoscape node or edge attribute file formats (as described above).

Sample Attribute Table 1

The attribute table file should contain a primary key column and at least one attribute column. The maximum number of attribute columns is unlimited. The Alias column is an optional feature, as is using the first row of data as attribute names. Alternatively, you can specify each attribute name from the File → Import → Attribute from Table (text/MS Excel)... user interface.

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.

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.

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.

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.

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.

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

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.

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

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.

Then, follow the three-step process outlined below:

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:

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

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

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.

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.

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.

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.

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:

Cytoscape 2.6.0 and later has additional sample Visual Styles. You can try those samples to understand how Visual Styles change appearence of a network. The following is a list of network views based on sample styles applied to 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).

As of Cytoscape 2.5, the VizMapper has undergone a complete interface redesign. There are three types of components in the new VizMapper:

These editors will be discussed in further detail below.

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

Step 1. Load some sample data

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. Additionally, 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 as sampleStyles.props file in the SampleData directory. You can import the sample file from File → Import → Vizmap Property File.

The Cytoscape VizMapper uses three core concepts:

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:

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

Legend

Node Visual Mappings

Edge Visual Mappings

From Cytoscape 2.8.0, 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 user 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 Custom Graphics Manager. It is a simple GUI component to add/remove images to Cytoscape session.

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

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

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 assuming you save your session, you will not lose your visual properties. No other vizmap.props files are saved during normal operation.

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, meaning you can use it as much as you like. However, if you ever 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 Attribute Browser. 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.

Cytoscape includes a Quick Find feature, which enables you to quickly find nodes and edges.

Using Quick Find is very simple. Here is how it works:

Filters allow you to quickly select multiple nodes or edges of interest by comparing node and edge attributes to properties you specify. For example, you can select all the nodes whose name contains a specific pattern, or whose numeric attribute value falls within a certain range. You can also perform complex selection by defining filters and performing the Boolean operation between them.

Since Cytoscape 2.5, the filters are redesigned to provide more user-friendly interfaces. The newly designed filters preserve most of the functionality of the old filters while introducing more, its API can also be used by other plugins. The old filters are still preserved, because there are still a few features are not implemented in new filters, and many users already got used to the old ones.

By default, you should see a filter icon on the toolbar: . If you click on it, the filters tab on the Control Panel will be selected. You can also access the filters by clicking directly on the tab or by using the Select menu pull-down and choose “Use Filters” menu item. The filters panel initially looks like this:

1. Filter Definition

To create a new filter, click the option button and select “Create new filter” from the list provided. Enter a name for the new filter.

Definition of simple filter

When a new filter is created, it is empty initially. It can be defined by choosing attributes (one at a time) in the Attribute/Filter comboBox and clicking the Add button. Note that in the comboBox each attribute has a prefix, either node. or edge., denoting what type of attribute it is. After add button is clicked, a widget, depended on the item selected, will be added to the definition panel. If the attribute type is text-based (or String), the widget will be a indexed-text-box widget, if numeric attribute, the widget will be a range slider; both are shown below.

For each widget, the name of the attribute it represents is on the left. A NOT checkbox gives the option to get the negation of selection for the widget. There is a trash-can icon on the right. Clicking on the trash-can icon will delete the widget. In this way, the filter definition can be modified after it is defined.

Note that if more than one widget is added on the filter definition panel, the relationship between them is “AND” by default. This relationship can be changed to “OR” by selecting the OR relation in Advanced Panel.

The Advanced panel can be opened by clicking on the plus (+) sign.

There are three rows in the advanced panel:

1. The first row, labeled Save. The two checkboxes (Global and Session) will determine where the filter is saved. By default, filters are saved in individual sessions. If the Global checkbox is checked, the filter will be saved in the global properties file. Note also that the prefix of the filter name in the Current Filter dropdown list reflects where it is saved.

2. The second row, Relation, will determine what Boolean operation (AND or OR) will be applied to each individual widget.

3. Negation checkbox. If this checkbox is checked, the result of the filter will be negated.

Definition of complex filter

In the pull-down list of Attribute/Filter comboBox, there are two sections, the top one is the list of attributes, the bottom one is the list of previously defined filter. Those previously dfined filters can also be used as components of other filters. By combinational use of AND, OR, NOT and pre-defined filters, filters with arbitary complexity can be defined.

3. Apply the filter

If a network is small (number of nodes or edges less than 1000), the filter will be applied dynamically when a widget is added or any value is adjusted. If the network is large, then Apply button should be clicked to apply the filter.

The threshold (1000 by default) can be changed by defining a Cytoscape property value dynamicFilterThreshold.

4. Other filters

In the option menu pulldown, there are menu items “Create new topology filter”, “Create new NodeInteraction filter” and “Create new EdgeInteraction filter”.

Topology Filter

Topology filter will select nodes based on the properties of its near-by nodes (neighbors). To create a topology filter, choose the menu item “Create new topology filter” from the option menu. See below,

Interaction filter

Interaction filters are used to select nodes/edges based on the properties of their neighboring edges/nodes. See below for a node interaction filter.

The old filters is the one existed in previous versions of Cytoscape. Several types of filters are available.

Basic filters allow the selection of multiple nodes or edges according to singe attribute data:

Compound filters allow selection based on the application of pre-existing filters:

Example filters are shipped with the plugin to get started.

To use the old filters, go to Select → Use Old Filters. You will see a filters window which initially looks like the following:

If the first filter is selected, then the window looks as shown:

There are three panels in the Filters window:

The Select → Nodes and Select → Edges menus provide several mechanisms for selecting nodes and edges. Most options are fairly straightforward; however, some need extra explanation.

Select → Nodes → By Name... selects nodes by the node identifier (ID). This is the value seen in the leftmost column of the attribute browser. This does not change, even if the displayed node label changes!

Select → Nodes → From File... selects nodes based on node identifiers found in a specified file. The file format is simply one node id per line:

Node1
Node2
Node3
...

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

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.

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

The giny.model.node interface defines two methods:

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.

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.

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.

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.

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.

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:

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.

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.

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

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

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

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.

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

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.

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... .

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.

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:

(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 ]
...

(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 ]
...

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

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

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.

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

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:

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

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
...

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

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

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
...

python parseAssignmentsToFlatFileFromGoaProject.py gene_association.goa_human xrefs.goa

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))
#-----------------------------------------------------------------------------------

from Notes on memory consumption, Cytoscape User Manual

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

There are a number of ways to change Cytoscape's memory allocation, depending on your preferred method of opening the application. All of them will change Cytoscape's default memory parameters except starting from the command line.

Option A: Command line startup (All operating systems/platforms)

Create a Cytoscape.vmoptions file in the .cytoscape directory. Make sure to add exactly one JVM option per line and that the last line has a line break at the end. The most popular and important option is "-Xmx" followed immediately (no spaces!) by the amount of heap memory. You can add an "M" for megabytes or a "G" for gigabytes. Other options you may use may depend on the particular JVM that you are running. A typical Cytoscape.vmoptions file would look like this:

-Xmx5G
-Xss10M

This file allocates a maximum of 5GiB of heap memory and 10MiB of stack space per thread.

Option B: Using the Cytoscape icon (Windows and/or Linux systems)

Just like with Option A, you can use the Cytoscape.vmoptions file. The problem with Windows is that the lines need to be terminated with a single line feed character (a.k.a. a "newline" character) and must not contain any carriage return characters. This is difficult to accomplish on Windows on which the default is line termination with carriage-return/line-feed pairs. You typically need to use a programmers editor and make sure to set the line-end configuration to line-feeds only! Another option on Windows is to create the Cytoscape.vmoptions file on Mac OS or Linux and then to copy it into the Windows installation directory. N.B.: this is not a problem on Linux! (If you have a 64-bit version of Windows and are running a 64-bit version of Java, you can also try using this Cytoscape.vmoptions file.)

Option C: Using the Cytoscape icon on Mac OS