Prior to the workshop, please complete the following:

Download the data

Please download the data in data.zip. Then, move data.zip to your Desktop and unzip it (usually double-clicking it will work). This contains data files for all BIGslu workshops; you will not need all of the files for each workshop.

If the above link does not work, please try downloading the data with the Download button at https://github.com/BIGslu/workshops/blob/main/setup/data/data.zip.

Install R and RStudio

When you open RStudio, it should look like so with multiple panels. If you see only 1 panel, then you’re likely in R, not RStudio.

Install R packages

Install R packages by running a script in your R console in RStudio (left panel in the above image). Each workshop has an overlapping but unique list of packages. Please select the appropriate script for your workshop from those below.

If prompted, say a to “Update all/some/none? [a/s/n]” and no to “Do you want to install from sources the packages which need compilation? (Yes/no/cancel)”

This can take several minutes.

Intro R

#CRAN packages
install.packages("tidyverse")
#Bioconductor packages
install.packages("BiocManager")
BiocManager::install("limma")

Intro to R and tidyverse, RNA-seq edition:

#CRAN packages
install.packages("tidyverse")
install.packages("ggrepel")
#Bioconductor packages
install.packages("BiocManager")
BiocManager::install("limma")

RNA-seq analysis in R

#CRAN packages
install.packages("tidyverse")
#Bioconductor packages
install.packages("BiocManager")
BiocManager::install(c("edgeR", "biomaRt", "limma"))
#GitHub packages
install.packages("devtools")
devtools::install_github("BIGslu/RNAetc")
devtools::install_github("BIGslu/kimma")

RNA-seq pathway analysis in R

#CRAN packages
install.packages("tidyverse")
#Bioconductor packages
install.packages("BiocManager")
BiocManager::install(c("edgeR", "biomaRt", "limma"))
#GitHub packages
install.packages("devtools")
devtools::install_github("BIGslu/SEARchways")
devtools::install_github("BIGslu/BIGpicture")

Plotting in ggplot

#CRAN packages
install.packages("tidyverse")
#Bioconductor packages
install.packages("BiocManager")
BiocManager::install("limma")
#GitHub packages
install.packages("devtools")
devtools::install_github("BIGslu/kimma")

Linear modeling in R

# CRAN packages
install.packages(c("tidyverse", "lme4", "car"))
# Bioconductor packages
install.packages("BiocManager")
BiocManager::install(c("limma","variancePartition"))
# GitHub packages
install.packages("devtools")
devtools::install_github("BIGslu/kimma")

R packages

# CRAN packages
install.packages(c("devtools", "usethis", "roxygen2"))

Single-cell RNA-seq data visualization

#CRAN packages
install.packages(c("tidyverse", "circlize", "ggalluvial"))
install.packages("Seurat")
#Bioconductor packages
install.packages("BiocManager")
BiocManager::install("ComplexHeatmap")

SEATRAC series

#CRAN packages
install.packages(c("tidyverse"), Ncpus=4)
#Bioconductor packages
install.packages("BiocManager")
BiocManager::install("limma")
#GitHub packages
install.packages("devtools")
devtools::install_github("BIGslu/kimma")

Check R package install

To make sure packages are correctly installed, load each of them individually into R with library( ).

For example, the tidyverse is a meta-package containing multiple packages. It gives the following message when loaded into R. Your exact version numbers way vary slightly.

library(tidyverse)
## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2     
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

In contrast, packages such as limma load silently with no messages.

library(limma)
## Warning: package 'limma' was built under R version 4.4.1

The key is to look for any messages that contain ERROR or there is no package called X. This means the package was not installed correctly. If you see any errors, please come 15 minutes early to the workshop or contact Kim for assistance.