12 June 2019 - 9.30am-4.30pm
Room 555, Arts West, University of Melbourne
RNA-seq Differential Gene Expression analysis in R – 12 June
This workshop introduces the analysis of RNA-seq count data using R. This will include reading the data into R, quality control and preprocessing, and performing differential expression analysis and gene set testing, with a focus on the limma-voom analysis workflow. This workshop does not cover the alignment of RNA-seq data to a reference genome in order to generate count data. For an introduction to that topic, refer to our Galaxy-based RNA-seq workshops. Learning outcomes At the end of this workshop you will be able to:
- Read RNA-seq count data into R
- Produce diagnostic plots of the data, carry out quality checks, and recognise common issues
- Perform differential gene expression analysis between two groups to obtain a set of differentially expressed genes
- Annotate differentially expressed genes
- Perform simple gene-set testing analysis
- Download and install R from https://cran.r-project.org/. The latest version is recommended.
- Download and install RStudio from https://www.rstudio.com/products/rstudio/download/. The free version is all you need.
- Install R packages by opening RStudio and copying the following commands into your console:
if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install(c("tidyverse", "edgeR", "Glimma", "gplots", "RColorBrewer", "org.Mm.eg.db", "BiasedUrn"))
- Check you can load the following libraries without issue:
library(edgeR) library(limma) library(Glimma) library(gplots) library(org.Mm.eg.db) library(RColorBrewer)
LAST RUN: June 5, 2019