REDEL-shiny: A user-friendly interface for exploring differential expression landscapes integrating clustering, ontology, and co-expression-based enrichment

Abstract

RNA-seq is a standard approach for studying gene expression in grapevine, yet downstream bioinformatics remains a bottleneck. Existing tools cover only parts of the workflow and require varying expertise. Scripted R tools such as DiCoExpress support differential and co-expression analysis but require programming skills (1). Standalone web services such as g:Profiler, DAVID, Enrichr, and ShinyGO provide functional enrichment but are disconnected from analysis workflows and optimized for model organisms with well-curated databases (2–5). More advanced web interfaces for omics integration, co-expression, and network inference (RFLOMICS, AskoR, DIANE) still lack grapevine-specific support for multiple genome and annotation versions, limiting access to specialized resources (6–8). No existing tool provides an integrated, code-free solution addressing these species-specific needs.

We present REDEL-shiny, built on REDEL (R project for Exploring Differential Expression Landscapes), an R package integrating differential expression, clustering, ontology enrichment, and co-expression analysis. REDEL-shiny provides a workflow from raw counts to interpretation: data upload and validation, quality control (PCA, sample correlation), TMM normalization, and differential gene expression analysis using edgeR (9) and limma-voom (10). Visualizations include volcano plots, MAplots, and heatmaps. The tool supports complex designs with up to three biological factors and one batch factor.

Functional analysis is integrated in the same interface: Gene Ontology enrichment (topGO (11), clusterProfiler (12)), gene set enrichment analysis (fgsea (13)), KEGG pathway visualization (pathview (14)), GO term reduction (rrvgo (15), GOSemSim (16)), and co-expression clustering (coseq (17)). Planned features include MapMan pathway mapping using Mercator annotations (18,19). Built-in grapevine gene identifier conversion simplifies access to organism-specific databases.

The application is containerized with Docker and validated with 3 grapevine datasets represent-ing factorial, paired, and two-groupdesigns. The differential expression module is functional, with functional enrichment and network analysis modules under active development. This tool aims to lower the bioinformatics barrier for grapevine researchers, enabling autonomous transcriptomicanalyses.

Source code: REDEL R package: https://forge.inrae.fr/egfv/bioinfo/redel; REDEL-shiny: https://forge.inrae.fr/egfv/bioinfo/redel-shiny

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