Thanks to reduced cost of sequencing and library preparation, it is now possible to conduct a well-replicated RNA-Seq study for less than a few thousand dollars. However, if unforeseen problems arise, such as insufficient sequencing depth or batch effects, the cost and time required for analysis can escalate, ultimately far exceeding that of the original experiment. Running a “mock” analysis using a well documented, published data analysis from start to finish is often a good way to learn the limitations and strengths of analysis methods, which helps to plan an experiment. Toward this end, this article describes a straightforward analysis of an RNA-Seq data set from tomato, using materials developed for the UNC Charlotte 2014 Workshop on Next-Generation Sequencing (WiNGS). For the workshop, we developed hands-on computer labs introducing experimental design, data processing, data analysis, and biological interpretation for RNA-Seq expression experiments. Here, we present a protocol for RNA-Seq data analysis taken from the workshop, focusing on data analysis using edgeR and visualization of RNA-Seq expression data using Integrated Genome Browser, a highly interactive, flexible genome visualization tool.
Analysis and Visualization of RNA-Seq Expression Data Using RStudio, Bioconductor, and Integrated Genome Browser
Loraine AE, Blakley IC, Jagadeesan S, Harper J, Miller G, Firon N. (2015) Analysis and Visualization of RNA-Seq Expression Data Using RStudio, Bioconductor, and Integrated Genome Browser. Methods Mol Biol 1284:481-501. [abstract]