TY - JOUR T1 - 3D RNA-seq - a powerful and flexible tool for rapid and accurate differential expression and alternative splicing analysis of RNA-seq data for biologists JF - bioRxiv DO - 10.1101/656686 SP - 656686 AU - Wenbin Guo AU - Nikoleta Tzioutziou AU - Gordon Stephen AU - Iain Milne AU - Cristiane Calixto AU - Robbie Waugh AU - John W. S. Brown AU - Runxuan Zhang Y1 - 2019/01/01 UR - http://biorxiv.org/content/early/2019/05/31/656686.abstract N2 - 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, we 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. ER -