At the top right of this Github page, click on the Code green button and then download. Store the contents of this folder in a specific directory, from where you will be running the code for this masterclass.

This course will use the R programming language. Download and install R according to your operating system from https://cran.r-project.org/. It is best advised to use version of R > 4.0.0.

Along with R, we will also download Rstudio which is an integrated development environment for R, which will make our interaction with R much easier. Download the (free) version from https://rstudio.com/products/rstudio/download/#download.

Now we will be writing R code inside R studio. Take some time to familiarize yourself with the Rstudio panels. If you are not at all familiar with R, you could follow this tutorial that covers the basic concepts of the R programming language within R studio: https://rstudio-education.github.io/hopr/basics.html.

We will be mostly using R markdown, which is an interactive document that allows us to write reports together with R code to generate outputs such as figures. For a quick summary see https://rmarkdown.rstudio.com/articles_intro.html.

To not re-invent the wheel, researchers create packages, which bundle together useful functions (and potentially datasets) which we can then use directly. This will be essential for our single cell analysis, where we will mostly use the Seurat package https://satijalab.org/seurat/.

For our analysis we will require lots of additional packages, which I have populated in the 00_install_packages.R file. Open this file and run it from within RStudio or from terminal. This process might take a few minutes. If you see the following message it means you already have installed some of the packages. Try then running independently each line in the console (bottom panel in Rstudio).

Updating Loaded Packages One or more of the packages to be updated are currently loaded. Restarting R prior to install is highly recommended. ...

The 01_supervised_learning.Rmd and 02_unsupervised_learning.Rmd files contain simple code to re-create some of the plots I will show in the masterclass. I added them simply for completeness, so feel free to skip them, and you can get back to those if you feel you want to understand some of these concepts better.