R

R

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The R statistics environment and programming language is an exceptionally well engineered, free (as in free speech) and free (as in free beer) platform for data manipulation and analysis. The number of functions that are included by default is large, there is a very large number of additional, community-generated analysis modules that can be simply imported from dedicated sites (e.g. the Bioconductor project for molecular biology data), or via the CRAN network, and whatever function is not available can be easily programmed. The ability to filter and manipulate data to prepare it for analysis is an absolute requirement in research-centric fields such as ours, where the strategies for analysis are constantly shifting and prepackaged solutions become obsolete almost faster than they can be developed. Besides numerical analysis, R has very powerful and flexible functions for plotting graphical output.

Introductory reading

Wikipedia article on the R statistics environment and programming language

Contents

• High level description of function
  • Packages and libraries
  • Command line and scripts
  • Data types
  • Data input
  • Numerical analysis
  • Graphical analysis
  • Writing your own functions
• Availability
• R-Studio
• Comparison to S etc.
• Comparison to MatLab

References

Further reading and resources

• Introductory R tutorial for this course
• The Bioconductor project

The R project homepage

CRAN–The Comprehensive R Archive Network

The Bioconductor project homepage