Cytoscape_3/UserManual/Attributes

Clear message

Interaction networks are useful as stand-alone models. However, they are most powerful for answering scientific questions when integrated with additional information. Cytoscape allows the user to add arbitrary node, edge and network information to Cytoscape as node/edge/network attributes. This could include, for example, annotation data on a gene or confidence values in a protein-protein interaction. These attributes can then be visualized in a user-defined way by setting up a mapping from data attributes to visual attributes (colors, shapes, and so on). The section on visual styles discusses this in greater detail.

Cytoscape supports the importing of attribute in some predefined format. Cytoscape can find the right reader based on the file extension of attribute file. The supported file extensions are "attrs" (text file in the format described below), "tsv, tab, csv, net or txt" (comma or tab separated values file), "pvals" (Cytoscape expression matrix) and "xls, xlsx" (Microsost Excel file).

Cytoscape Attribute File Format

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 and edge attribute file names often use the suffix ".attrs".

Node and edge attributes may be loaded at the command line using the –T 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.

Detailed file format (Advanced users)

Every attribute file has one header line that gives the name of the attribute, and optionally some additional meta-information about that attribute. The format is as follows:

attributeName (class=JavaClassName)

The first field is always the attribute name: it cannot contain spaces. If present, the class field defines the name of the class of the attribute values. For example, java.lang.String or String for Strings, java.lang.Double or Double for floating point values, java.lang.Integer or Integer for integer values, etc. If the value is actually a list of values, the class should be the type of the objects in the list. If no class is specified in the header line, Cytoscape will attempt to guess the type from the first value. If the first value contains numbers in a floating point format, Cytoscape will assume java.lang.Double; if the first value contains only numbers with no decimal point, Cytoscape will assume java.lang.Integer; otherwise Cytoscape will assume java.lang.String. Note that the first value can lead Cytoscape astray: for example,

floatingPointAttribute
firstName = 1
secondName = 2.5

In this case, the first value will make Cytoscape think the values should be integers, when in fact they should be floating point numbers. It's safest to explicitly specify the value type to prevent confusion. A better format would be:

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

or

floatingPointAttribute 
firstName = 1.0
secondName = 2.5

Every line past the first line identifies the name of an object (a node in a node attribute file or an edge in a edge attribute file) along with the String representation of the attribute value. The delimiter is always an equals sign; whitespace (spaces and/or tabs) before and after the equals sign is ignored. This means that your names and values can contain whitespace, but object names cannot contain an equals sign and no guarantees are made concerning leading or trailing whitespace. Object names must be the Node ID or Edge ID as seen in the left-most column of the attribute browser if the attribute is to map to anything. These names must be reproduced exactly, including case, or they will not match.

Edge names are all of the form:

sourceName (edgeType) targetName

Specifically, that is

Note that tabs are not allowed in edge names. Tabs can be used to separate the edge name from the "=" delimiter, but not within the edge name itself. Also note that this format is different from the specification of interactions in the SIF file format. To be explicit: a SIF entry for the previous interaction would look like

sourceName edgeType targetName

or

To specify lists of values, use the following syntax:

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

This example shows an attribute whose value is defined as a list of text strings. The first object has three strings, and thus three elements in its list, while the second object has a list with only one element. In the case of a list every attribute value uses list syntax (i.e. parentheses), and each element is of the same class. Again, the class will be inferred if it is not specified in the header line. Lists are not supported by the visual mapper and so can’t be mapped to visual attributes.

Newline Feature

Sometimes it is desirable to for attributes to include linebreaks, such as node labels that extend over two lines. You can acomplish by inserting \n into the attribute value. For example:

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

Import Attribute Table Files

In Cytoscape 3.0, importing delimited text and MS Excel attribute data tables is 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). Also in Cytoscape 3.0, users can select the networks that the imported attributes will be assigned to.

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. Alternatively, you can specify each attribute name from the File → Import → Attribute from Table (text/MS Excel)... user interface.

Basic Operation

The user interface of the "Import Attributes from Table" window is similar to that of the "Import Network from Table" window.

1. Select File → Import → Table → File... ( or URL... if your source data file is accessible through web)

2. Select a data file in the file chooser panel (or enter the URL in the displayed box). This file can be either a text or Excel (.xls) formats.
3. In the "Import Attribute from File" panel, select one of the attribute types. Cytoscape can import node, edge, and network attributes.
4. (Optional) Choose if you would like to import the file for all of the available networks or only selected networks using the check box in the expandable "Network Options" panel (this panel is collapsed by default). Select networks from the list.
5. (Optional) If the table is not properly delimited in the preview panel, change the delimiter in the Text File Import Options panel. The default delimiter is tab. This step is not necessary for Excel Workbooks. )
6. By default, the first column is designated as the primary key. Change the key column if necessary.
7. Click the Import button.

Advanced Options

Mapping Key Attributes to the primary key

In Cytoscape 3.0 both IDs and attributes with primitive data types (string, boolean, floating point, and integer) can be selected as the Key Attribute using the dropdown list provided. Complex attributes such as lists are not supported.

Text File Import Options

For more detail on these options, please see the "Import Free-Format Table Files" section of the user manual in the Creating Networks chapter.

Table Browser

When Cytoscape is started, the Table Browser appears in the bottom CytoPanel. This browser can be hidden and restored using the View → Show/Hide Table Browser menu option. Like other CytoPanels, the browser can be undocked by pressing the little icon in the browser’s top right corner.

To swap between displaying node, edge, and network attributes use the tabs on the bottom of the panel labeled "Node Attributes", "Edge Attributes", and "Network Attributes". Also, in Cytoscape 3.0 data can be imported which is not assigned to any node, edge or network attributes. This data is displayed in Unassigned Tables tab.

In Cytoscape 3.0 there two display modes for table browser: showing only selected nodes/edges attributes or showing all attributes. This configuration can be set using button #1 in the figure. The attribute browser displays attributes belonging to the currently selected network.

Using the three buttons under #2 in the figure, it is possible to make some or all columns visible and hide others or all of them. Also, a new column can be created by pressing button #3 or mutable columns can be deleted y button #4. Button #5 is for writing equation which is explained in ????.

Most attribute values can be edited by double-clicking an attribute cell (only the SUID cannot be edited). Newline characters can be inserted into String attributes either by pressing Enter or by typing "\n". Once finished editing, click outside of the editing cell in the Attribute Browser or press Shift-Enter to save your edits. Pressing Esc while editing will undo any changes.

Attribute rows in the browser can be sorted alphabetically by specific attribute by clicking on a column heading. A new attribute can be created using the Create New Column button (#3), and must be one of four types – integer, string, real number (floating point), or boolean. Attributes can be deleted using the Delete Attributes button (#4). NOTE: Deleting attributes removes them from Cytoscape, not just the attribute browser! To remove attributes from the browser without deleting them, simply unselect the attribute using the Select Column button (#2).

The right-click menu (#6) on the Table Browser has several functions, such as exporting attribute information to spreadsheet applications. For example, use the right-click menu to Select All and then Copy the data, and then paste it into a spreadsheet application.

Loading Gene Expression (Attribute Matrix) Data

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 (File extension is '.pvals'); 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 extension ".pvals", and this file extension is recognized by Cytoscape when browsing for data files (File → Import → Table → File...).

General Procedure

Load an expression attribute matrix file using File → Import → Table → File... to bring up the import window, or by specifying the filename using the -m option at the command line.

Worked Example

For the sample network file sampleData/galFiltered.sif:

Load a sample gene expression data set by going to File → Import → Table → File.... In the resulting window, select the file sampleData/galExpData.pvals. In the combobox 'Import Data to', make sure the selected item is 'Node Attributes'. The identifiers used in this file are the same ones used in the network file sampleData/galFiltered.sif, so the attributes will be mapped to the nodes automatically. 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

Detailed file format (Advanced users)

Expression data files must have extension '.pvals'. 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.

Annotations

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 is a Cytoscape feature which allows you to load, navigate, and assign annotation terms to nodes and edges in a network. Cytoscape has an 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 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. 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

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.

1. Select: File → Import → Table → Public Databases...

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 name.

4. Select Data Type. This should be the type of ID set selected in Attribute list. For example, if you select name 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.

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