DGEAR: a web-based application for differential gene expression analysis and downstream functional insights

The rapid expansion of transcriptomic data has necessitated the development of efficient and scalable analytical frameworks for Differential Gene Expression (DGE) Analysis. We present a web-based tool implementing the DGEAR (Differential Gene Expression Analysis with R), designed using a three-tier architecture to enhance usability, performance, and modularity. The system comprises a frontend user interface (UI) for seamless data submission and visualization, a middleware processing layer handling computational tasks with an Application Programming Interface, and a backend data layer for secure data management and efficient execution of statistical analyses. The DGEAR algorithm integrates multiple statistical methods and an ensemble model with a cut-off-based majority voting strategy, ensuring robustness, flexibility, and accuracy in identifying differentially expressed genes from microarray and RNA-seq datasets. Furthermore, DGEAR integrates gene set enrichment analysis and PPI network construction, giving a major head start in downstream analysis. The web tool supports custom parameter selection, data visualization, and end-to-end encryption, making it securely accessible to researchers and clinicians. Generated output data can be directly accessible and can be downloaded by the user. This platform significantly streamlines transcriptomic analysis, providing an intuitive, high-performance environment for bioinformatics investigations, and is publicly available at https://dgear.compbiosysnbu.in/ .