Transomics2cytoscape: an automated software for interpretable 2.5-dimensional visualization of trans-omic networks

Area of Science:

• Bioinformatics
• Computational Biology
• Systems Biology

Background:

• Biochemical network visualization is crucial for interpreting omics data.
• Multi-omics data analysis necessitates visualization methods that integrate diverse data types.
• Current 2.5D trans-omics network visualization relies heavily on manual, time-consuming processes.

Purpose of the Study:

• To develop an automated R package for 2.5D trans-omics network visualization.
• To streamline the process of interpreting multi-omics and trans-omics data.
• To facilitate rapid updates and redrawing of networks aligned with ongoing data analysis.

Main Methods:

• Development of the R Bioconductor package 'transomics2cytoscape'.
• Implementation of automated 2.5D visualization techniques for stacked omics layers.
• Validation using trans-omics networks from published literature.

Main Results:

• 'transomics2cytoscape' enables rapid, automated 2.5D visualization of trans-omics networks.
• The package can visualize complex networks within minutes.
• Facilitates iterative network-based interpretation of multi-omics data.

Conclusions:

• 'transomics2cytoscape' significantly reduces the manual effort required for 2.5D trans-omics network visualization.
• The package supports dynamic network updates, crucial for multi-omics data analysis progression.
• Enables efficient network-based mechanistic interpretation of omics data.