MOREshiny: a user-friendly application for the inference of phenotype-specific multi-omic regulatory networks

Motivation Deciphering phenotype-specific regulatory mechanisms is key to understanding the molecular basis of complex diseases and traits. However, constructing multi-omic regulatory networks (MO-RNs) is challenging, as it requires integrating heterogeneous omics data, incorporating biological context, and detecting regulatory mechanisms that vary across conditions. The R package MORE (Multi-Omics REgulation) addresses these challenges by applying robust statistical models to infer phenotype-specific regulatory networks from multi-omics data. However, the use of MORE typically requires programming expertise, limiting its accessibility to non-specialist users. To democratize access to advanced multi-omics modeling tools, we present MOREshiny, an interactive web application built on Shiny that extends the module of pathway enrichment analysis and automatically guides the choice of statistical methods. Results MOREshiny enables users to upload multi-omic data, configure their models, and interpret results through a user-friendly interface —-without the need for coding skills. MOREshiny also allows users to download MORE results for their later exploration and study. To demonstrate the utility of MOREshiny, we showcase its functionalities on a multi-omic ovarian cancer dataset to understand regulatory differences between patients who did or did not require chemotherapy. Availability and implementation MOREshiny is freely available for download as a dockerized R Shiny package at https://github.com/BiostatOmics/MOREshiny.