Signaling pathways discovery and quantitative analysis from multi-modal data (Available on biorxiv: https://www.biorxiv.org/content/10.1101/2025.02.06.636961v1)
Incytr is an open-source R package to infer cell signaling pathways between cell types with the structure "Ligand-Receptor-Effector Molecule-Target" using multi-modal data and prior knowledge.
Incytr identifies cell signaling pathways from scRNA-seq data alone or integrated with proteomics, phosphoproteomics, and kinase-substrate specificity. The required inputs for Incytr are single-cell transcriptomics data, cell group labels, and user-selected sender and receiver genes which can be any genes measured in the data. The optional inputs include condition labels for the cells, proteomics, phosphoproteomics data, and a predicted kinase-substrate list (see Kinase-Substrate Matching in Supplementary Materials). Below is an overview of the Incytr workflow:
Incytr R package can be easily installed from Github using devtools:
devtools::install_github("ChanghanGitHub/Incytr")
The tutorial is aviable at "vignettes/Analysis_5XAD.Rmd"
An open-source Python package "Incytr-viz" has been developed to provide interactive visualization solutions: https://github.com/cellsignal/incytr-viz