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Wikipedia article on the R statistics environment and programming language.
Homepage of R for development, resources and, most importantly, download of code and documentation.
The IDE (Integrated Development Environment) that is the de facto standard for R programming and the development of code, projects, packages, and documentation.
The Comprehensive R Archive Network
BioConductor is a bit like CRAN for bioinformatics and computational biology. The most important computational advances in our field are available from here. There is a special focus on high-throughput analysis, and a specific mental model of how data, code and workflows all come together.
A digest of new blog-posts on R - from the introductory to the highly advanced. Sent out once every day or two. Really worthwhile subscription.
(Revolutions Analytics Blog)
(at DataCamp)
(Stackoverflow Data Analytics Team Blog)
Carey and Papin advise novice biologist programmers how to begin. Much of this paper resonates well with our Introduction to R learning units. Good context for a beginning, to get a sense of where we are going with this.
