Alberto Valdeolivas: firstname.lastname@example.org ; Date: 08/01/2020
This vignette shows a comparison between the protein interaction sources used in the NicheNet method and the ones available on Omnipath.
NicheNet ( https://github.com/saeyslab/nichenetr ) is a method to predict ligand-target links between interacting cells by combining their data with prior knowledge on signaling and gene regulatory networks (Browaeys et al 2019). NicheNet has already been applied to predict upstream niche signals driving Kupffer cell differentiation (Bonnardel et al. 2019).
The figure below shows a graphical representation of the NicheNet workflow. Interactions inferred from several complementary ligand-receptor, signaling and gene regulatory data sources were aggregated in respective integrated networks from which ligand-target regulatory potential scores were calculated. This model of prior information on potential ligand-target links can then be used to infer active ligand-target links between interacting cells. NicheNet prioritizes ligands according to their activity (i.e., how well they predict observed changes in gene expression in the receiver cell) and looks for affected targets with high potential to be regulated by these prioritized ligands(Browaeys et al 2019).