Data Analysis with R.
With the raise of biological, bioinformatic and ecological tools & data, knowing some degree of programming languages is essential for any researcher in life sciences.
R, a programming language and environment for statistical computing and graphics, is heavily used in biological and ecological sciences, and therefore, a must have in any researcher portfolio.
The course consists in different short modules (named "sessions") focusing on a topic related with R. Each session has the objective of introducing a given topic and will be very practical with minimal focus on theory.
In this repository, you can find the slides, R scripts & data for the course.
The easiest way to download all the material is to click on the Code button at the top right of this page and select Download ZIP.
video1.webm
This option will download the entire course material (R Base & R Advanced). If you do not want to download everything (I can understand!), navigate to the Scripts and Slides folders, and download (right click -> download as) only the files related to the version of the course you are interested in (base or advanced).
video2.webm
To get started with R, you need to acquire your own copy. This appendix will show you how to download R as well as RStudio, a software application that makes R easier to use. Both R and RStudio are free and easy to download.
R is maintained by an international team of developers who make the language available through the web page of The Comprehensive R Archive Network. The top of the web page provides three links for downloading R. Follow the link that describes your operating system: Windows, Mac, or Linux.
To install R on Windows, click the “Download R for Windows” link. Then click the “base” link. Next, click the first link at the top of the new page. This link should say something like “Download R 3.0.3 for Windows,” except the 3.0.3 will be replaced by the most current version of R. The link downloads an installer program, which installs the most up-to-date version of R for Windows. Run this program and step through the installation wizard that appears. The wizard will install R into your program files folders and place a shortcut in your Start menu. Note that you’ll need to have all of the appropriate administration privileges to install new software on your machine.
To install R on a Mac, click the “Download R for Mac” link. Next, click on the R-3.0.3 package link (or the package link for the most current release of R). An installer will download to guide you through the installation process, which is very easy. The installer lets you customize your installation, but the defaults will be suitable for most users. I’ve never found a reason to change them. If your computer requires a password before installing new progams, you’ll need it here.
R comes preinstalled on many Linux systems, but you’ll want the newest version of R if yours is out of date. The CRAN website provides files to build R from source on Debian, Redhat, SUSE, and Ubuntu systems under the link “Download R for Linux.” Click the link and then follow the directory trail to the version of Linux you wish to install on. The exact installation procedure will vary depending on the Linux system you use. CRAN guides the process by grouping each set of source files with documentation or README files that explain how to install on your system.
RStudio is an Integrated Development Environment (IDE) for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser. You can download it for free here. Scroll down and choose the installer that fits your OS.
Please, remember that for the use of RStudio is MANDATORY to have R first installed on your PC.