ShinyDegSEM: an interactive application for pathway perturbation analysis in gene expression studies

Background: Researchers in biology and bioinformatics are increasingly interested in unraveling the complex mechanisms underlying phenotypic variations. A key challenge lies in identifying perturbed biological pathways and understanding how these perturbations propagate through intricate gene regulatory networks. Results: To address this challenge, we developed ShinyDegSEM, an interactive R Shiny application that leverages structural equation modeling (SEM) to facilitate pathway perturbation analysis in gene expression studies. ShinyDegSEM streamlines identifying differentially expressed genes (DEGs), generating pathway models based on biological knowledge, and evaluating these models to uncover perturbed pathway modules. This article is a tutorial to guide users through the analysis workflow, providing detailed explanations and examples. This feature ensures that even novice researchers can quickly grasp the concepts and apply the tool to their datasets. Conclusions: The application integrates multiple steps, including DEG detection using significance analysis of microarray, perturbed pathway analysis with signaling pathway impact analysis, and SEM-based model refinement and comparison between experimental and control groups. The interactive interface of ShinyDegSEM allows researchers to easily upload their gene expression data, select appropriate criteria for DEG detection and pathway analysis, and visualize the results in intuitive graphs and tables. The tool provides insights into deregulated genes and modified gene-gene relationships within perturbed pathways.