Many scientists use networks to visualize complex relationships among organisms, such as viruses and their hosts. As scientists work with increasing amounts of data and the expectation of reproducible computational analyses increases, many users of network visualization programs are turning to scripted analyses instead of using software controlled by a graphical user interface (GUI).

To address the challenge in efficiently visualizing networks across many datasets or with updated datasets, we have created tutorials of common workflows that can be scripted with the R programming language for use with Cytoscape. Cytoscape is open-source software that is popular for the visualization of networks. Using the R package RCy3, which sends CyREST commands to Cytoscape, this poster will demonstrate a walkthrough using a few simple commands to visualize complex networks in Cytoscape and to customize these visualizations (e.g. changing node/edge sizes, color, shapes, and layouts). The network visualization workflow will be demonstrated using a virus-host co-occurrence network; this workflow would be applicable to analyses of virus-host networks from laboratory and environmental samples. The customizations demonstrated will be based on network properties and on taxonomic attributes associated with viruses or hosts. Given the general nature of visualization in Cytoscape this process can also be applied to metabolic interactions (e.g. in metagenomes), protein-protein interaction networks, etc.. The benefit of these workflows is that they allow users to quickly share and recreate their visualization methods, thereby creating more robust and reproducible analyses. Further development is in progress to facilitate scripting of not only the visualization of networks in Cytoscape, but also more complex network analysis tools (i.e. Cytoscape plugins).