Look and Feel of R Environment

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{http://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf}}
• Bioinformatics and Computational Biology Solutions Using R and Bioconductor (Gentleman et al., 2005) \href{http://www.bioconductor.org/help/publications/books/bioinformatics-and-computational-biology-solutions/}}
• More on this see “Finding Help” section in UCR Manual \href{http://manuals.bioinformatics.ucr.edu/home/R_BioCondManual#TOC-Finding-Help}}

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