It's DE-licious: A Recipe for Differential Expression Analyses of RNA-seq Experiments Using Quasi-Likelihood Methods in edgeR

Methods Mol Biol. 2016;1418:391-416. doi: 10.1007/978-1-4939-3578-9_19.

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.

Keywords: Differential expression; Generalized linear models; Quasi-likelihood; RNA-seq; Read alignment; Read counts; Variability.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Computational Biology / methods*
  • Databases, Genetic
  • Gene Expression Profiling / methods*
  • High-Throughput Nucleotide Sequencing*
  • Humans
  • Likelihood Functions*
  • Linear Models
  • Mice
  • Molecular Sequence Annotation
  • Sequence Alignment
  • Sequence Analysis, RNA / methods*
  • Software*