3D RNA-seq: A powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists

Wenbin Guo, Nikoleta Tzioutziou, Gordon Stephen, Iain Milne, Cristiane Calixto, Robbie Waugh, John W. S. Brown (Lead / Corresponding author), Runxuan Zhang (Lead / Corresponding author)

Research output: Contribution to journalArticlepeer-review

36 Citations (Scopus)
179 Downloads (Pure)


RNA-sequencing (RNA-seq) analysis of gene expression and alternative splicing should be routine and robust but is often a bottleneck for biologists because of different and complex analysis programs and reliance on specialized bioinformatics skills. We have developed the ‘3D RNA-seq’ App, an R shiny App and web-based pipeline for the comprehensive analysis of RNA-seq data from any organism. It represents an easy-to-use, flexible and powerful tool for analysis of both gene and transcript-level gene expression to identify differential gene/transcript expression, differential alternative splicing and differential transcript usage (3D) as well as isoform switching from RNA-seq data. 3D RNA-seq integrates state-of-the-art differential expression analysis tools and adopts best practice for RNA-seq analysis. The program is designed to be run by biologists with minimal bioinformatics experience (or by bioinformaticians) allowing lab scientists to analyse their RNA-seq data. It achieves this by operating through a user-friendly graphical interface which automates the data flow through the programs in the pipeline. The comprehensive analysis performed by 3D RNA-seq is extremely rapid and accurate, can handle complex experimental designs, allows user setting of statistical parameters, visualizes the results through graphics and tables, and generates publication quality figures such as heat-maps, expression profiles and GO enrichment plots. The utility of 3D RNA-seq is illustrated by analysis of data from a time-series of cold-treated Arabidopsis plants and from dexamethasone-treated male and female mouse cortex and hypothalamus data identifying dexamethasone-induced sex- and brain region-specific differential gene expression and alternative splicing.

Original languageEnglish
Number of pages14
JournalRNA Biology
Issue number11
Early online date19 Dec 2020
Publication statusPublished - 2 Nov 2021


  • Arabidopsis
  • RNA-seq
  • dexamethasone
  • differential alternative splicing
  • differential gene/transcript expression
  • differential transcript usage
  • interactive GUI
  • mouse
  • time-series

ASJC Scopus subject areas

  • Molecular Biology
  • Cell Biology


Dive into the research topics of '3D RNA-seq: A powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists'. Together they form a unique fingerprint.

Cite this