C-MOOR strives to break down barriers to scientific participation by providing online access to real scientific data, analytical tools, mentorship, and opportunities to interact with real scientists. If you’ve never done any programming before, no worries! We’ve got tutorials to get you up to speed. Click on one of the links below for advice on how to get started, depending on your background.

I am …

• Completely new to R
• Familiar with R and want to learn genomics
• An educator interested in using and/or contributing

• Check out our online Intro to R tutorial. You won’t need to sign-up or install anything.

• If you want to dig deeper in to a particular topic, you will need access to R and RStudio so that you can run code yourself. You can do this in one of two ways:

  • Install it yourself, on your own computer. R is open source (free!) and the installation is pretty straightforward, there are some instructions below. R can be installed on Windows, Mac, or Linux.
  • Sign up for an account at https://c-moor.carnegiescience.edu. Accounts are free, though we will need to approve you. You will not need to install anything.

• Check out our RNA-seq tutorials
• Explore our Datasets

• Explore our past courses and workshops
• Get in touch with us
• See who else is using and contributing to C-MOOR

1. Install base R: You can download R from the CRAN repository. Choose your operating system, then download the most recent release of R. Once you’ve downloaded the file, double-click to run it, and it should walk you through the R installation wizard. If you’re not sure about any of the options, choosing the default is a good idea.

2. Install RStudio: Download RStudio from the RStudio website. Find RStudio Desktop, which is completely free, and click the Download button. Once you’ve downloaded the file, double-click to run it, and it should walk you through the R installation wizard. If you’re not sure about any of the options, choosing the default is a good idea.

3. Start Up R and RStudio: Once you’ve installed RStudio you should be able to find and run it just like any other program. You can search for it in the search bar, or find it under the Start Menu (for Windows) or Applications (for Mac).

4. Choose a Tutorial and Get Started!: Find a topic you’re interested in and jump on in! Often tutorials will require you to install additional R packages that are specialized for dealing with particular types of data; instructions for installing any extra packages should be available along with the tutorials.

Most standard R packages can be installed using the install.packages() command. You will need to enter the name of the package you want to install between the parentheses. For example, to install the learnr package:

1. Open RStudio
2. In the interactive R console (bottom left panel), type: install.packages("learnr")
   • You should see a bunch of red text scroll by as R installs the package.
3. Check to see if the package installed properly by loading it using the library() command: library("learnr")
   • If it installed properly, you should not get an error message when you run the library() command.
4. Confirm the package loaded properly:
   • You can use the sessionInfo() command to see all your loaded packages. The most recent package you attached using the library() command should show up as the first item under “other attached packages”.
   • If you don’t want to look through your sessionInfo(), you can use the following command: grep( "learnr", loadedNamespaces(), value=TRUE ) to see if the learnr package is loaded. If it loaded successfully, you should see the output [1]"learnr". If it did not load, you will see character(0).

Many R packages for analyzing biological data R are best installed using BioConductor. First you will need to tell R where to find the BioConductor installation instructions, using source("https://bioconductor.org/biocLite.R"). You will then use the biocLite() command to install the package. You will need to enter the name of the package you want to install between the parentheses. For example, to install the DESeq2 package:

1. Open RStudio
2. In the interactive R console (bottom left panel), type: source("https://bioconductor.org/biocLite.R")
3. In the interactive R console (bottom left panel), type: biocLite("DESeq2")
   • You should see a bunch of red text scroll by as R installs the package.
4. Check to see if the package installed properly by loading it using the library() command: library("DESeq2")
   • If it installed properly, you should not get an error message when you run the library() command.
5. Confirm the package loaded properly:
   • You can use the sessionInfo() command to see all your loaded packages. The most recent package you attached using the library() command should show up as the first item under “other attached packages”.
   • If you don’t want to look through your sessionInfo(), you can use the following command: grep( "DESeq2", loadedNamespaces(), value=TRUE ) to see if the DESeq2 package is loaded. If it loaded successfully, you should see the output [1]"DESeq2". If it did not load, you will see character(0).