Abstract

RNA sequencing (RNA-seq) data is by now the most common method to study differential gene expression. Here we present a pipeline from RNA-seq generation to analysis with examples based on our own barley anther and meiocyte transcriptome. The bioinformatics pipeline will give everyone, from a beginner to a more experienced user, the possibility to analyze their datasets and identify significantly differentially expressed genes. It also allows differential alternative splicing analysis which will become increasingly common due to the high regulatory impact on the gene expression. We describe use of the Galaxy interface for RNA-seq read quantification and the 3D RNA-seq app for the downstream data analysis.

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