Introduction to R

Author: Thomas Girke

Last update: 21 June, 2016

Alternative formats of this vignette: Single-page .Rmd HTML, .Rmd, .R Old Slides .pdf

Overview

What is R?

R is a powerful statistical environment and programming language for the analysis and visualization of data. The associated Bioconductor and CRAN package repositories provide many additional R packages for statistical data analysis for a wide array of research areas. The R software is free and runs on all common operating systems.

Why Using R?

• Complete statistical environment and programming language
• Efficient functions and data structures for data analysis
• Powerful graphics
• Access to fast growing number of analysis packages
• Most widely used language in bioinformatics
• Is standard for data mining and biostatistical analysis
• Technical advantages: free, open-source, available for all OSs

Books and Documentation

• simpleR - Using R for Introductory Statistics (John Verzani, 2004) - URL
• Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Gentleman et al., 2005) - URL
• More on this see “Finding Help” section in UCR Manual - URL

R Working Environments

Working environments (IDEs) for R

R Projects and Interfaces

Some R working environments with support for syntax highlighting and utilities to send code to the R console:

• RStudio: excellent choice for beginners (Cheat Sheet)
• Basic R code editors provided by Rguis
• gedit, Rgedit, RKWard, Eclipse, Tinn-R, Notepad++, NppToR
• Vim-R-Tmux: R working environment based on vim and tmux
• Emacs (ESS add-on package)

Example: RStudio

New integrated development environment (IDE) for R. Highly functional for both beginners and advanced.

RStudio IDE

Some userful shortcuts: Ctrl+Enter (send code), Ctrl+Shift+C (comment/uncomment), Ctrl+1/2 (switch window focus)

Example: Vim-R-Tmux

Terminal-based Working Environment for R: Vim-R-Tmux

Vim-R-Tmux IDE for R