Introduction

In this class, we will be using the R language heavily in class notes, examples and lab exercises. R is free and you can install it like any other program on your computer.

  1. Go to the CRAN website and download it for your Mac or PC. (We assume no one is using Linux; if you are that advanced, then you already know what to do!)

  2. Install the free version of the RStudio Desktop Software.

  3. Go through our install instructions to install the background libraries this course uses.

RStudio makes it very easy to learn and use R, providing a number of useful features that many find indispensable.

About the R language, briefly

If you are used to traditional computing languages, you will find R different in many ways. The basic ideas behind R date back four decades and have a strong flavor of exploration: one can grapple with data, understand its structure, visualize it, summarize it etc. Therefore, a common way people use R is by typing a command and immediately see the results. (Of course, scripts can also be written and fed to R for batch execution.)

The core of R itself is reasonably small, but over time, it has also become a vehicle for researchers to disseminate new tools and methodologies via packages. That is one reason for R’s popularity: there are thousands of packages (10,300+ as of this writing, not to mention over 1,000 for genomic analysis that are part of BioConductor) that extend R in many useful ways.

The CRAN website is something you will consult frequently for both the software, documentation and packages others have developed.

RStudio

We can only cover some important aspects of RStudio here. There are a number of resources online, including Youtube videos that you can consult outside of class.

When you start RStudio, you will get a view similar to what is shown below with perhaps slight differences.