Author: Thomas Girke

Last update: 15 February, 2016

Alternative formats of this tutorial: .Rmd HTML, .Rmd Source, .R Source, PDF Slides


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) \href{}}
  • Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Gentleman et al., 2005) \href{}}
  • More on this see “Finding Help” section in UCR Manual \href{}}

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:

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