Getting Started with R
1 New to R?
If you are completely new to R, we recommend watching at least the first couple of videos from OSU’s Mike Sovic’s Youtube playlist of short videos on R, to get started.
Here are some additional resources for learning the basics of R:
A useful and fun written tutorial is R for cats.
For a more systematic and lengthy introduction to R, see A Tutorial Introduction to R (this gets fairly advanced after section 9).
Excellent comprehensive introductions are the R Basics and Visualization classes by Rafael Irizarry that can be freely accessed; you do have to create an account.
OSU TDAI videos:
Also, don’t hesitate to reach out to the Code Club organizers if you have any questions!
2 Miscellaneous R tips
2.1 Installing R packages
CRAN packages
To install an R package that is available at CRAN, the default R package repository, from within R (e.g. in the R console in RStudio), use the install.packages()
function.
The install.packages()
function will handle dependencies within R — i.e., it will install other R packages that your package depends on. Occasionally, when the install function needs to compile a package from source, errors arise that relate to missing system dependencies (i.e. software outside of R).
On Mac and Linux, these system dependencies are best installed outside of R, such as with homebrew
on Mac or apt
on Ubuntu. The errror message you got when trying to install an R package should tell you which system dependencies are needed.
On Windows, you can use the installr
package to install such dependencies or other software from within R — for example:
install.packages("installr") # Install the installr package first
::install.RStudio() # Install RStudio
installlr::install.python() # Install Python installr
Installing packages from Github
To install a package from Github, use either the devtools or the remotes package – for example:
install.packages("remotes") # Install the remotes package
::install_github("kbroman/broman") # Install from a repository using "<username>/<repo-name>" remotes
This will install the package from source, so you will need to make sure you are able to do so by following the instructions in the section right above this one.
Installing packages from Bioconductor
If you’re doing bioinformatic analyses in R, you will probably run into packages that are not on CRAN but on Bioconductor. To install a package from Bioconductor, use the BiocManager package – for example:
install.packages("BiocManager") # Install the BiocManager package
::install("edgeR") # Install the edgeR package from Bioconductor BiocManager
2.2 Updating R
Consider updating R if you have an older version of R installed. As of August 2023, we would recommend to update R if your version is below 4.1.
You can check which version of R you have by looking at the first lines of output when running the following command inside R:
sessionInfo()
To update:
Windows: You can update R from within R. The
updateR()
function will also take care of updating your packages:install.packages("installr") ::updateR() installr
Mac: Download and install the latest
.pkg
file as if you were installing it for the first time.
Re-installing your packages after updating (Mac and Linux)
While the installr::updateR()
function for Windows users takes care of reinstalling your packages along with updating R, Mac and Linux users will have to manually re-install their packages. Some people prefer to re-install these packages on the fly, which can end up being a way to get rid of packages you no longer use.
But if you want immediately reinstall all your packages, run this before you upgrade:
<- installed.packages()
my_packages saveRDS(my_packages, "my_packages.rds")
Then, after you’ve installed the latest R version:
<- readRDS("CurrentPackages.rds")
my_packages install.packages(my_packages[1, ])
This will only work for packages available on CRAN. Of course, you can check your list for Github-only and Bioconductor packages and then install those with their respective commands (see below). Yes, this can be a bit of a hassle!