Differential gene expression workshop

Audience	Computational Skills	Prerequisites	Duration
Biologists	Intermediate R	Introduction to R	1.5-day workshop (~10 hours of trainer-led time)

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.

Learning Objectives

• 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.

Contents

Differential Gene Expression (DGE) using RNA-seq raw counts data

Lessons	Duration
Setting up and DGE overview	70 min
Introduction to count normalization	60 min
QC using principal component analysis (PCA) and heirarchical clustering	90 min
Getting started with DESeq2	70 min
Pairwise comparisons with DEseq2	45 min
Visualization of DGE analysis results	45 min
Summary of DGE workflow	15 min
Complex designs with DESeq2 (LRT)	60 min
Functional Analysis	85 min

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Installation Requirements

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)

Practical exercises

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

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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.