Difference between revisions of "R"
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(Created page with "<div id="APB"> <div class="b1"> R </div> {{dev}} The {{WP|R (programming language)|statistics workbench and programming language}} is an exceptionally well engineered, fre...") |
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| − | The {{WP|R (programming language)|statistics | + | The {{WP|R (programming language)|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 [http://cran.r-project.org/ 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. |
| − | + | <section end=intro /> | |
__TOC__ | __TOC__ | ||
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==Introductory reading== | ==Introductory reading== | ||
<section begin=reading /> | <section begin=reading /> | ||
| + | <div class="reference-box">{{WP|R (programming language)|Wikipedia article}} on the R statistics environment and programming language</div> | ||
<section end=reading /> | <section end=reading /> | ||
| − | == | + | ==Contents== |
| − | |||
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| + | * 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== | ==References== | ||
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==Further reading and resources== | ==Further reading and resources== | ||
| + | *Introductory [[R tutorial]] for this course | ||
| + | *The [[Bioconductor]] project page on this Wiki | ||
| + | |||
| + | <div class="reference-box">[http://www.r-project.org/ The '''R project''' homepage]</div> | ||
| + | <div class="reference-box">[http://cran.r-project.org/ '''CRAN'''–The Comprehensive R Archive Network]</div> | ||
| + | <div class="reference-box">[http://www.bioconductor.org/ The '''Bioconductor project''' homepage]</div> | ||
| + | <div class="reference-box">[http://www.r-bloggers.com/ '''R''' bloggers]</div> | ||
| + | <div class="reference-box">[http://data-mining-tutorials.blogspot.ca/2011/08/data-mining-with-r-rattle-package.html Tutorial on the '''R Rattle''' GUI package]</div> | ||
| + | <div class="reference-box">[http://www.rstudio.com/ide/ The '''R Studio''' IDE]</div> | ||
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[[Category:Applied_Bioinformatics]] | [[Category:Applied_Bioinformatics]] | ||
| + | [[Category:R]] | ||
</div> | </div> | ||
Latest revision as of 00:02, 15 November 2013
R
This page is a placeholder, or under current development; it is here principally to establish the logical framework of the site. The material on this page is correct, but incomplete.
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 page on this Wiki
