A1386
Title: An interactive shiny web application for multivariate analysis of transcriptomic data
Authors: Jose Luis Romero Bejar - University of Granada (Spain) [presenting]
Quintin Mesa Romero - Hanami8 (Spain)
Francisco Javier Esquivel - University of Granada (Spain)
Abstract: The growth of transcriptomic technologies such as RNA-seq has produced high-dimensional datasets that require advanced statistical approaches. Multivariate techniques, including principal component analysis (PCA) and cluster analysis, are essential for uncovering biological patterns and reducing complexity. The focus is on reviewing these methodologies and introducing a Shiny-based web application designed to make them accessible to a broader research community. The application enables users to upload gene expression matrices and perform analyses through an intuitive interface, eliminating the need for programming expertise. Core functionalities include data validation, PCA visualization, hierarchical and non-hierarchical clustering with optimal cluster estimation, and differential gene expression analysis with packages such as DESeq2 and edgeR. Interactive plots, tables, and workflow control enhance usability and robustness. This prototype represents a practical step toward democratizing transcriptomic data exploration, bridging the gap between complex computational methods and biological insight in bioinformatics.
