Computer Setup (installations) for Code Club

Modified

February 17, 2025


Here, you will find general information about software installations you should do before joining Code Club.

In summary, you only need to be able to access to R and RStudio, preferably via a local installation, and optionally via the Ohio Supercomputer Center (OSC).

If you run into issues or have questions, don’t hesitate to contact one of the Code Club organizers.


1 Install R

Using an OSU-managed computer?

If you are using an OSU computer, you may not have the “administrative privileges” that are needed to install software on your computer the regular way.

However, you should in that case have an OSU application on your computer that allows you to install a selection of approved software, and that selection should include R and RStudio. On Windows, this app seems to be simply called “Software Center”, whereas on Mac, it is called “Ohio State Application Self Service” (names likely vary).

If you can’t find that application, or have trouble installing R and RStudio this way, you should contact OSU IT to help you.

Already have R installed?

  • Please check your version of R – this information is printed to the console when you start R, and you can also get it by typing sessionInfo() and checking the first line of the output.

  • Currently (Spring 2025), we would recommend R version 4.3.0 or higher.

  • To update R, see the bottom of this page for instructions.


2 Install RStudio

RStudio is a so-called Integrated Development Environment (IDE) for R, with side-by-side panes for an R script, an R concole, plots, help documents, and much more. While it is possible to use R without RStudio, RStudio has become the de facto standard for working with R and we can highly recommend it.

To install RStudio, go to the RStudio download page and download and run the installer file for your operating system.


3 Alternative: Use RStudio Server at OSC

Upon request (contact Jelmer), you can get access to the Ohio Supercomputer Center (OSC) Classroom Project for Code Club (PAS1838). This way, you can code in RStudio from your browser rather than with a local installation. This is a good option if you prefer not to install anything or if you run into problems during installations.

After you asked for access to the OSC project, you should receive an email from OSC that you have been added to the Code Club OSC project.

  • If you already have an OSC account, you shouldn’t need to do anything to gain access, although the email may ask you to confirm/accept your being added to project.

  • If you do not yet have an OSC account, the email you received from OSC should have a link to do so. Alternatively, follow the instructions below to sign up and get access to the project.

OSC OnDemand lets you access OSC resources through your browser and run applications like RStudio.

  1. To get started, go to https://ondemand.osc.edu/ and log in with your OSC username and password.

  2. Click on “Interactive Apps” in the blue top bar, and select “RStudio Server” (near the bottom).

  3. Now, you’re on a page from which you can launch an RStudio server that will run on an OSC cluster. Select project PAS1838 in the dropdown menu and change the “Number of hours” to 2. Then click “Launch”.

  4. You will be sent to a page where you can see the status of your “job” It usually starts running within seconds, and the color of the top bar will then switch from blue (“Queued” and then “Starting”) to green (“Running”).

  5. Click “Connect to RStudio Server” at the bottom of the box, and an RStudio Server instance will open.


4 Alternative: Update an existing R installation

Consider updating R if you have an older version of R installed. 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 R:

  • Windows: You can update R from within R. The updateR() function will also take care of updating your packages:

    install.packages("installr")
installr::updateR()

  • Mac: Download and install the latest .pkg file as if you were installing R 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:

my_packages <- installed.packages()
saveRDS(my_packages, "my_packages.rds")

Then, after you’ve installed the latest R version:

my_packages <- readRDS("CurrentPackages.rds")
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!


5 New to R?

If you are completely new to R, we recommend that you go through the online material of a one-day workshop that the Code Club organizers taught in February 2025.

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