ROGUE: an R Shiny app for RNA sequencing analysis and biomarker discovery

Abstract

Abstract Background The growing power and ever decreasing cost of RNA sequencing (RNA-Seq) technologies have resulted in an explosion of RNA-Seq data production. Comparing gene expression values within RNA-Seq datasets is relatively easy for many interdisciplinary biomedical researchers; however, user-friendly software applications increase the ability of biologists to efficiently explore available datasets. Results Here, we describe ROGUE (RNA-Seq Ontology Graphic User Environment, https://marisshiny.research.chop.edu/ROGUE/ ), a user-friendly R Shiny application that allows a biologist to perform differentially expressed gene analysis, gene ontology and pathway enrichment analysis, potential biomarker identification, and advanced statistical analyses. We use ROGUE to identify potential biomarkers and show unique enriched pathways between various immune cells. Conclusions User-friendly tools for the analysis of next generation sequencing data, such as ROGUE, will allow biologists to efficiently explore their datasets, discover expression patterns, and advance their research by allowing them to develop and test hypotheses.

Keywords

• R Shiny
• RNA-Seq
• Differential expression
• Biomarkers
• GSEA
• Gene ontology