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

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 skilled bioinformaticians to perform the analysis. To overcome these issues, University of Dundee researchers have developed the “3D RNA-seq” App, an R shiny App which provides an easy-to-use, flexible and powerful tool for the three-way differential analysis: Differential Expression (DE), Differential Alternative Splicing (DAS) and Differential Transcript Usage (DTU) of RNA-seq data. The full analysis is extremely rapidand can be done within hours. The program integrates Limma, a state-of-the-art, highly rated differential expression analysis tool and adopts best practice for RNA-seq analysis. It runs the analysis through a user-friendly graphical interface, 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 Arabidopsis and mouse RNA-seq data. The program is designed to be run by biologists with minimal bioinformatics experience (or by bioinformaticians) allowing lab scientists to take control of the analysis of their RNA-seq data.

3D RNA-seq analysis pipeline

rna-seq

Availability – The 3D RNA-seq web interface is available at https://ics.hutton.ac.uk/3drnaseq. The R package version (ThreeDRNAseq) is available on Github at https://github.com/wyguo/ThreeDRNAseq

Guo W, Tzioutziou N, Stephen G, Milne I, Calixto C, Waugh R, Brown JWS, Ruxuan Zhang R. (2019) 3D RNA-seq – a powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists. bioRXiv [Epub ahead of print]. [abstract]

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