iDEP Web Application for RNA-Seq Data Analysis

Abstract

RNA sequencing (RNA-seq) has become a routine method for transcriptomic profiling. We developed a user-friendly web app called iDEP (integrated differential expression and pathway analysis) to help biologists interpret read counts or other types of expression matrices derived from read mapping. With iDEP, users can easily conduct exploratory data analysis, identify differentially expressed genes, and perform pathway analysis. Due to its intuitive user interface and massive annotation database, iDEP is being widely adopted for interactive analysis of RNA-seq data. Using a public dataset on the effect of heat shock on mouse with and without functional Hsf1, we demonstrate how users can prepare data files and conduct in-depth analysis. We also discuss the importance of critical interpretion of results (avoid p-hacking and rationalizing) and validation of significant pathways by using different methods and independent annotation databases.

Keywords: Bioconductor; DESeq2; Differential gene expression; Gene set enrichment analysis; Integrated differential expression and pathway analysis; Pathway analysis; RNA-seq; Transcriptomic analysis; iDEP.