Fig. 1
From: ROGUE: an R Shiny app for RNA sequencing analysis and biomarker discovery
A ROGUE R Shiny app graphic user interface. B ROGUE workflow. ROGUE takes raw read counts, normalized counts, or quantified expression values (RPKM, FPKM, TPM) as input. The user can quickly look at the clustering of all samples based on the expression values of all genes, perform differential expression analysis, and compare genes between samples or groups. ROGUE also includes statistical tools for gene set enrichment analysis (GSEA), gene ontology (GO) analysis, biomarker discovery, and dimensionality reduction by t-SNE, PCA, or UMAP