From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline

• DOI: 10.12688/f1000research.8987.2
• Publication Date: 2016-08-02T05:20:04Z
• Authors: Yunshun Chen; Aaron T. L. Lun; Gordon K. Smyth
• Keywords: Bioconductor; RNA-Seq; R package

<ns4:p>In recent years, RNA sequencing (RNA-seq) has become a very widely used technology for profiling gene expression. One of the most common aims RNA-seq is to identify genes or molecular pathways that are differentially expressed (DE) between two more biological conditions. This article demonstrates computational workflow detection DE and from data by providing complete analysis an experiment epithelial cell subsets in mouse mammary gland. The uses R software packages open-source Bioconductor project covers all steps pipeline, including alignment read sequences, exploration, differential expression analysis, visualization pathway analysis. Read count quantification conducted using Rsubread package statistical analyses performed edgeR package. quasi-likelihood functionality edgeR.</ns4:p>