Identifier Mapping in Cytoscape: idmapper

Inferring the data source

From within Cytoscape, a user initiates an ID mapping operation by right-clicking on the header of a column containing identifiers in the Table Panel. In the most common cases the type of identifier can be guessed by idmapper based on the its format. Table 1 shows the supported data sources and example identifier formats. The app looks at the first ten entries and choose the source from the option that matches corresponding regular expressions. This number of identifiers iteratively sampled is set by a static variable called N_Iterations. The algorithm for inferring the data source is implemented in IdGuess.java.

Cytoscape tasks

There are two different tasks supported by the idmapper app. ColumnMappingTask is activated by the right-click mouse event on a table header. It infers the current table and column from the information that comes from the mouse event. In order to support automation, we added MapColumnCommandTask as an analog that is exposed specifically for Commands and CyREST access. These tasks eventually result in the same algorithms being invoked.

Cytoscape graphical user interface (GUI)

The idmapper app provides the same basic functionality of the BridgeDb app with less fuss. Users do not have to install it, launch it, make configuration decisions or think about which database they are accessing. The app comes bundled with every Cytoscape release. As such it usage in Cytoscape via the interactive GUI (graphical user interface) is documented in the Cytoscape manual, http://manual.cytoscape.org/en/stable/Node_and_Edge_Column_Data.html#mapping-identifiers.

To map an identifier from one source to another, right click on the column header of your identifier. Select the option to Map Column to bring up the idmapper dialog (Figure 1).

The idmapper dialog presents a few choices the user can override before performing ID mapping. The default Species is determined by the previous selection made per network, providing a "smart and sticky" behavior. The available choices for the identifier data sources are determined by the species. The Map from data source is automatically selected based on an inspection of the first ten identifiers found in the column clicked on by the user. This can easily be overridden by the pull down menu. The To data source must be selected by the user; Ensembl is presented by default. Finally, the Force single checkbox offers to simplify the results of ID mapping by ignoring one-to-many cases and only keeping the first result. If the option is off, a list of results will appear in the column. This can easily be overridden by clicking the toggled checkbox.

Cytoscape command line interface

The command interface does not use the same tasks as the GUI. In the GUI use case, the app knows the current context of where the command was activated, i.e., the network, table and column. This information must explicitly be provided as paramaters to the command interface to perform the same operation. Thus, in addition to species, mapFrom, mapTo and forceSingle, the command line operation of idmapper also requires networkName, table and columnName (see next section for more details).

Cytoscape automation

In the scripting environment, idmapper provides all of its functionality in a single call (Figure 2). This means that identifier mapping can be incorporated into Cytoscape automation workflows with a single additional command.

Figure 2. Swagger documented function.

The functionality of idmapper is contained in this singular function: map column.

The map column function takes the following parameters:

With Cytoscape running, the map column function can be called from any scripting environment or programming language that supports REST calls. In the case of R and Python scripts, there are dedicated packages to make this even easier. The RCy3 package wraps this command in an R function called mapTableColumn to conform to other table functions (https://www.bioconductor.org/packages/release/bioc/html/RCy3.html). The py2cytoscape library similarly provides this command as a python function, cyclient.idmapper.map_column (https://github.com/cytoscape/py2cytoscape).

A sample script demonstrates how to map identifiers via RCy3, covering the most common use cases (https://github.com/cytoscape/RCy3/blob/master/vignettes/Identifier-mapping.Rmd).

Case 1: Species-specific considerations

The Yeast Perturbation sample network provided with Cytoscape can be loaded from the Starter Panel and provides gene identifiers of the form “YDL194W”. These are actually Ensembl-supported identifiers for Yeast, distinct from the typical “ENSXXXG00000123456” form as presented in Table 1. This presents a special case that users will need to be aware of when selecting species and source database or mapFrom in the GUI. In terms of automation, you could generate a new column of Entrez Gene IDs in this network with these calls:

(RCy3): mapTableColumn(column=’name’, species=’Yeast’, 
                map.from=’Ensembl’, map.to=’Entrez␣Gene’)

(py2cytoscape): cyclient.idmapper.map_column(source_column=’name’, species=’Yeast’, 
                source_selection=’Ensembl’, target_selection=’Entrez␣Gene’)

Case 2: From proteins to genes

When working with protein interaction networks, for example those from the STRING database (see https://apps.cytoscape.org/apps/stringapp), you may want to translate to gene identifiers. The idmapper app supports this case as well, but one should be aware of the assumptions involved when making this translation. Since most genes encode for many proteins, you may have many-to-one mappings in your results. For all human networks imported from STRING using the StringApp⁵, the following commands will perform an ID mapping from Uniprot-TrEMBL (proteins) to Ensembl (genes):

(RCy3): mapTableColumn(column=’canonical␣name’, species=’Human’,
                map.from=’Uniprot–TrEMBL’, map.to=’Ensembl’)
(py2cytoscape): cyclient.idmapper.map_column(source_column=’canonical␣name’,
                species=’Human’, source_selection=’Uniprot–TrEMBL’,
                target_selection=’Ensembl’)