dynUGENE: an R package for uncertainty-aware gene regulatory network inference, simulation, and visualization

Abstract

Methods for gene regulatory network inference focus on network architecture identification but neglect model selection and simulation. We implement an extension to the dynGENIE3 algorithm that accounts for model uncertainty as an R package, providing users with an easy to use interface for model selection and gene expression profile simulation. Source code is available at https://github.com/tianyu-lu/dynUGENE with a detailed user guide. A webserver with interactive controls is available at https://tianyulu.shinyapps.io/dynUGENE/.