Visualization of trans-omic networks helps biological interpretation by illustrating pathways where the signals are transmitted.
To characterize signals that go across multiple omic layers, Yugi and colleagues have proposed a method for network visualization by stacking multiple 2D pathways in a 3D space.
The 3D network visualization was realized by VANTED. However, the visualization relies on time-consuming manual operation. Here we propose transomics2cytoscape, an R package that automatically creates 3D network visualization in combination with Cytoscape, Cy3D App, and Cytoscape Automation.
- Install Cytoscape from https://cytoscape.org/
- Install transomics2cytoscape (see https://www.bioconductor.org/packages/release/bioc/html/transomics2cytoscape.html)
- Run Cytoscape (If Cytoscape is already running, you don't need to run it anymore. transomics2cytoscape works only when 1 Cytoscape [window] is up.)
- Run R.
- Run the following R code. This will import multiple networks and integrate the networks to a 3D space. (This will take a few minutes.)
library(transomics2cytoscape)
networkDataDir <- tempfile(); dir.create(networkDataDir)
networkLayers <- system.file("extdata/usecase1", "yugi2014.tsv",
package = "transomics2cytoscape")
stylexml <- system.file("extdata/usecase1", "yugi2014.xml",
package = "transomics2cytoscape")
suid <- create3Dnetwork(networkDataDir, networkLayers, stylexml)
Next Run the following R code. This will add edges between the network layers. (This code execution finishes faster than before.)
layer1to2 <- system.file("extdata/usecase1", "k2e.tsv",
package = "transomics2cytoscape")
suid <- createTransomicEdges(suid, layer1to2)
layer2to3 <- system.file("extdata/usecase1", "allosteric_ec2rea.tsv", package = "transomics2cytoscape")
suid <- createTransomicEdges(suid, layer2to3)
Then, you should have a 3D view with layered networks and transomic interactions between them. (Note that you need to perform operations such as zooming out or adjusting the camera angle.)