Journal article

RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR

Charity Law, Monther Alhamdoosh, Shian Su, Xueyi Dong, Luyi Tian, Gordon Smyth, Matthew Ritchie

F1000Research | Published : 2018

Abstract

The ability to easily and efficiently analyse RNA-sequencing data is a key strength of the Bioconductor project. Starting with counts summarised at the gene-level, a typical analysis involves pre-processing, exploratory data analysis, differential expression testing and pathway analysis with the results obtained informing future experiments and validation studies. In this workflow article, we analyse RNA-sequencing data from the mouse mammary gland, demonstrating use of the popular edgeR package to import, organise, filter and normalise the data, followed by the limma package with its voom method, linear modelling and empirical Bayes moderation to assess differential expression and perform g..

View full abstract

Citation metrics