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Cytoscape is a well-known bioinformatics tool for displaying and exploring biological networks. R is a powerful programming language and environment for statistical and exploratory data analysis. RCy3 uses CyREST to communicate between R and Cytoscape, allowing any graphs (e.g., igraph, graphNEL or dataframes) to be viewed, explored and manipulated with the Cytoscape point-and-click visual interface. Thus, via RCy3, these two quite different, quite useful bioinformatics software environments are connected, mutually enhancing each other, providing new possibilities for exploring biological data.

Installation

if(!"RCy3" %in% installed.packages()){
    install.packages("BiocManager")
    BiocManager::install("RCy3")
}
library(RCy3)

if(!"ndexr" %in% installed.packages()){
    install.packages("BiocManager")
    BiocManager::install("ndexr")
}
library(ndexr)

Prerequisites

In addition to these packages, you will need:

Finding networks

The Network Data Exchange (NDEx) is a platform for network storage, retrieval and exchange. Developed in close collaboration with Cytoscape, it is a natural partner for Cytoscape network queries and management.

You can start with NDEx by first establishing a connection.

ndexcon <- ndex_connect()

We will use ndexcon throughout the other ndexr calls. For example, a basic search.

networks <- ndex_find_networks(ndexcon, "Breast Cancer")
print(networks[,c("name","externalId","nodeCount","edgeCount")])

That print statement provides a nifty way to browse the search results. You’ll notice that we got results that hit each of the search terms individually, thus including any pathway with “cancer” in the name. That’s perhaps a bit too broad…

networks <- ndex_find_networks(ndexcon, "BRCA")
print(networks[,c("name","externalId","nodeCount","edgeCount")])

Ok. We can work with this list. Let’s use the first hit. Note: you are going to get different hits as this database changes over time, so proceed with any hit you like.

networkId = networks$externalId[1]
network = ndex_get_network(ndexcon, networkId)
print(network)

Viewing networks

If we want to visualize and interact with this network, Cytoscape is our best choice. Both NDEx and Cytoscape work with the CX network data format, so the import can directly be managed by the CyNDEx component of Cytoscape, supported by RCy3…

brca.net.suid <- importNetworkFromNDEx(networkId)