TRANSCRIPTOMIC ANALYSIS IN INFLAMMATORY DISEASES: PUBLIC DATA RESOURCES, ANALYTICAL METHODS, AND A FRAMEWORK FOR REPRODUCIBLE META-ANALYSIS

Abstract

Transcriptomic data reveal how gene expression changes in inflammatory diseases. Thousands of these datasets are now public and free to reuse. This working paper reviews the main resources and methods for this field. It uses inflammatory bowel disease as a running example. The paper has four goals. First, it maps the general repositories and the disease specific databases that supply free data. Second, it describes the standard analysis pipeline for bulk and single cell data. Third, it summarizes shared molecular signatures that recur across inflammatory diseases. Fourth, it proposes a reproducible meta-analysis design that combines many small studies into one larger and more reliable analysis. The paper does not present new experimental results. It is a methods and resource synthesis. Its aim is to give a clear starting point for researchers who want to reuse public transcriptomic data in inflammatory disease research.