| Chapter title |
It’s DE-licious: A Recipe for Differential Expression Analyses of RNA-seq Experiments Using Quasi-Likelihood Methods in edgeR
|
|---|---|
| Chapter number | 19 |
| Book title |
Statistical Genomics
|
| Published in |
Methods in molecular biology, January 2016
|
| DOI | 10.1007/978-1-4939-3578-9_19 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-3576-5, 978-1-4939-3578-9
|
| Authors |
Aaron T. L. Lun, Yunshun Chen, Gordon K. Smyth, Lun, Aaron T L, Chen, Yunshun, Smyth, Gordon K, Lun, Aaron T. L., Smyth, Gordon K. |
| Editors |
Ewy Mathé, Sean Davis |
| Abstract |
RNA sequencing (RNA-seq) is widely used to profile transcriptional activity in biological systems. Here we present an analysis pipeline for differential expression analysis of RNA-seq experiments using the Rsubread and edgeR software packages. The basic pipeline includes read alignment and counting, filtering and normalization, modelling of biological variability and hypothesis testing. For hypothesis testing, we describe particularly the quasi-likelihood features of edgeR. Some more advanced downstream analysis steps are also covered, including complex comparisons, gene ontology enrichment analyses and gene set testing. The code required to run each step is described, along with an outline of the underlying theory. The chapter includes a case study in which the pipeline is used to study the expression profiles of mammary gland cells in virgin, pregnant and lactating mice. |
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