This repository has teaching materials for a 1.5-day, hands-on Introduction to differential gene expression (DGE) analysis workshop. The workshop will lead participants through performing a differential gene expression analysis workflow on RNA-seq count data using R/RStudio. Working knowledge of R is required or completion of the Introduction to R workshop.

• QC on count data using Principal Component Analysis (PCA) and heirarchical clustering
• Using DESeq2 to obtain a list of significantly different genes
• Visualizing expression patterns of differentially expressed genes
• Performing functional analysis on gene lists with R-based tools

These materials are developed for a trainer-led workshop, but also amenable to self-guided learning.

Download the most recent versions of R and RStudio for your laptop:

• R
• RStudio

Note:  When installing the following packages, if you are asked to select (a/s/n) or (y/n), please select “a” or "y" as applicable.

(1) Install the below packages on your laptop from CRAN. You DO NOT have to go to the CRAN webpage; you can use the following function to install them one by one:

install.packages("insert_package_name_in_quotations")
install.packages("insert_package_name_in_quotations")
& so on ...

Note that these package names are case sensitive!

RColorBrewer
pheatmap
ggrepel
devtools
cowplot

(2) Install the below packages from Bioconductor. Run the source() function once, followed by the biocLite() function 9 times for the 9 packages:

source("http://bioconductor.org/biocLite.R") 
biocLite("insert_first_package_name_in_quotations")
biocLite("insert_second_package_name_in_quotations")
& so on ...

Note that these package names are case sensitive!

DESeq2
clusterProfiler
DOSE
org.Hs.eg.db
pathview
DEGreport
rhdf5
tximport

(3) Use a new method of installation from GitHub to install the below packages using the following code:

devtools::install_github("insert_package_name_in_quotations")

stephenturner/annotables
pachterlab/sleuth
COMBINE-lab/wasabi

(4) Finally, please check that all the packages were installed successfully by loading them one at a time using the library() function.

library(DESeq2)
library(ggplot2)
library(RColorBrewer)
library(pheatmap)
library(ggrepel)
library(cowplot)
library(clusterProfiler)
library(DEGreport)
library(org.Hs.eg.db)
library(DOSE)
library(pathview)
library(purrr)
library(rhdf5)
library(tximport)
library(annotables)
library(wasabi)
library(sleuth)

(5) Once all packages have been loaded, run sessionInfo().

sessionInfo()

source("http://bioconductor.org/biocLite.R") 
biocLite(c("RColorBrewer", "pheatmap", "DESeq2", "clusterProfiler", 
           "DOSE", "org.Hs.eg.db", "pathview", "purrr", "DEGreport", "stephenturner/annotables"))

Load the libraries to make sure the packages installed properly:

library(DESeq2)
library(ggplot2)
library(RColorBrewer)
library(pheatmap)
library(clusterProfiler)
library(DEGreport)
library(org.Hs.eg.db)
library(DOSE)
library(pathview)
library(purrr)
library(annotables)

After completion of the workshop, practice of concepts can be explored with these exercises. An answer key is available to check answers.

These materials have been developed by members of the teaching team at the Harvard Chan Bioinformatics Core (HBC). These are open access materials distributed under the terms of the Creative Commons Attribution license (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.