Author: Thomas Girke

Last update: 01 May, 2017

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One of the main attractions of using the R ( environment is the ease with which users can write their own programs and custom functions. The R programming syntax is extremely easy to learn, even for users with no previous programming experience. Once the basic R programming control structures are understood, users can use the R language as a powerful environment to perform complex custom analyses of almost any type of data (Gentleman , 2008).

Why Programming in R?

  • Powerful statistical environment and programming language
  • Facilitates reproducible research
  • Efficient data structures make programming very easy
  • Ease of implementing custom functions
  • 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

R Basics

The previous Rbasics tutorial provides a general introduction to the usage of the R environment and its basic command syntax. More details can be found in the R & BioConductor manual here.

Code Editors for R

Several excellent code editors are available that provide functionalities like R syntax highlighting, auto code indenting and utilities to send code/functions to the R console.

Programming in R using RStudio
Programming in R using Vim or Emacs

Finding Help

Reference list on R programming (selection)

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