Network propagation in the cytoscape cyberinfrastructure

Abstract

Network propagation is an important and widely used algorithm in systems biology, with applications in protein function prediction, disease gene prioritization, and patient stratification. However, up to this point it has required significant expertise to run. Here we extend the popular network analysis program Cytoscape to perform network propagation as an integrated function. Such integration greatly increases the access to network propagation by putting it in the hands of biologists and linking it to the many other types of network analysis and visualization available through Cytoscape. We demonstrate the power and utility of the algorithm by identifying mutations conferring resistance to Vemurafenib.

Fig 1. Example uses of diffusion.

a. Diffusion of heat from a single query gene in the upper left, denoted with a green diamond, demonstrates that heat diffusion recapitulates network distance to the query set. b. A local network hypothesis for Vemurafenib resistance in cell line LOX-IMVI, correcting for a responsive cell line, A375. LOX-IMVI mutated genes appear outlined in red. The original Vemurafenib query genes appear as green diamonds. Three interaction types are present in this network: Grey dotted lines are protein-protein binding interactions, green arrows indicate control of localization, and blue arrows indicate phosphorylation.

Fig 2. Cytoscape example screenshots.

a. Cytoscape after a simple diffusion query. The selection filter is set to pick the top 10 percent most relevant genes by rank to the input query. b. The filter settings for the selection of the subnetwork that is closely related to the Vemurafenib genes and the mutations in the LOX-IMVI cell line, but not the A375 genes. c. The filter settings for the original the query’s first neighbors that were not in the result network from step 15.