transomics2cytoscape 1.0.0
R version: 4.0.2
Bioconductor version: 3.12
Cytoscape: 3.8.1
Cy3D (Cytoscape app): 1.1.3 (1.1.2 or later is required)
KEGGscape (Cytoscape app): 0.9.0
Visualization of trans-omic networks helps biological interpretation by illustrating pathways where the signals are transmitted (Gehlenborg et al., 2010).
To characterize signals that go across multiple omic layers, Yugi and colleagues have proposed a method for network visualization (Yugi et al., 2014) by stacking multiple 2D pathways in a 3D space.
The 3D network visualization was realized by VANTED (Rohn et al., 2012). 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 (Shannon, 2003), Cy3D App, and Cytoscape Automation (Otasek et al., 2019).
This package requires Cytoscape to be installed and you need to run Cytoscape before running the following R code.
BiocManager::install("transomics2cytoscape")
There is a function create3Dnetwork
in transomics2cytoscape.
In the create3Dnetwork
, the following workflow is executed.
create3Dnetwork
has 4 arguments.
The 1st one is a directory path where you put the network files to be layered in 3D space. The 2nd one is a file path of TSV for the Z-axis layout of the network files. The 3rd one is a file path of TSV used to create the edges between the network layers. The last one is a file path of XML used to style Cytoscape.
Files that Cytoscape can import.
You need to put these files in the directory of the 1st argument of
create3Dnetwork
.
You don’t need to put files for the KEGG pathway.
A file that defines network layer index and the Z-height of the network in 3D space. The format is as follows.
layer1 rno04910 600
layer2 galFiltered.sif 400
layer3 rno00010 200
layer4 rno00010 1
The 1st column is the network layer index.
This information is added to the node table column LAYER_INDEX
.
The 2nd column is the KEGG pathway ID or the network file name in the directory
of the 1st argument of create3Dnetwork
.
You don’t need to prepare a network file for the KEGG pathway.
You can import the KEGG pathway simply by writing the KEGG pathway ID.
The last column is the Z-height of the network.
A file that defines trans-omic interactions (i.e., the edges that connect the different network layers). The format is as follows.
layer1 rno:84006 layer2 YMR300C transomicsType1
layer2 YMR300C layer3 rno:100364062 transomicsType2
layer3 rno:100364062 layer4 rno:100364062 transomicsType3
The 1st and 2nd columns are the information about source node of
the trans-omic interaction.
The 3rd and 4th columns are about the target node.
The 1st and 3rd columns are the network layer index.
The 2nd and 4th columns are the name or KEGG object ID that the node should
have.
The last column is the type of the trans-omic interaction.
This information is added to the interaction
column of the edge table.
A Cytoscape style file. For more information about Cytoscape style file, see the Cytoscape user manual. Note that you can only use style properties that are supported by Cy3D.
# suppressPackageStartupMessages(library(dplyr))
# suppressPackageStartupMessages(library(RCy3))
# suppressPackageStartupMessages(library(KEGGREST))
# Sys.setenv(LANGUAGE="en_US.UTF-8")
library(transomics2cytoscape)
networkDataDir <- tempfile(); dir.create(networkDataDir)
sif <- system.file("extdata","galFiltered.sif",package="RCy3")
file.copy(sif, networkDataDir)
networkLayers <- system.file("extdata", "networkLayers.tsv",
package = "transomics2cytoscape")
transomicEdges <- system.file("extdata", "transomicEdges.tsv",
package = "transomics2cytoscape")
stylexml <- system.file("extdata", "transomics.xml",
package = "transomics2cytoscape")
create3Dnetwork(networkDataDir, networkLayers, transomicEdges, stylexml)
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.)
Gehlenborg, N., O’Donoghue, S.I., Baliga, N.S., Goesmann, A., Hibbs, M.A., Kitano, H., et al. (2010) Visualization of omics data for systems biology. Nature Methods, 7, S56–S68.
Otasek, D., Morris, J.H., Bouças, J., Pico, A.R. and Demchak, B. (2019) Cytoscape Automation: Empowering workflow-based network analysis. Genome Biology, 20, 185.
Rohn, H., Junker, A., Hartmann, A., Grafahrend-Belau, E., Treutler, H., Klapperstück, M., et al. (2012) VANTED v2: A framework for systems biology applications. BMC systems biology, 6, 139.
Shannon, P. (2003) Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research, 13, 2498–2504.
Yugi, K., Kubota, H., Toyoshima, Y., Noguchi, R., Kawata, K., Komori, Y., et al. (2014) Reconstruction of insulin signal flow from phosphoproteome and metabolome data. Cell Reports, 8, 1171–1183.