Rrrrrrrr

After doing a fresh install of OSX Leopard on my Mac and having to re-familiarize with some of my Biostatistics/Microarray education background it was time do a fresh install of R on my machine.

R is a freely available statistical programming language modeled after S programming language. Matthew Keller, a founder of the Richmond R group describes some of R's advantages over other statistical packages as the following:

• Its fast and free


• State of the art: Researchers provide their methods as R packages


• Its second only to MATLAB for graphics

Some points that I would like to add to the list are:

• Its graphs and tables can be used with the ever popular LaTeX


• Its programming/scripting like interface makes it rather extensible


• Its a great starting point for people interested in Biostatistics and Microarrays


• The BioConductor project is primarily based on R


• Did I mention that its free?

R is a rather powerful tool and I consider it to be a must have for any Biostatistician or Bioinformatician's toolset. So check it out, and let me know what you think.

Other Important R Links:

• CRAN, the Comprehensive R Archive Network (similar to perl's CPAN)


• The R Help Mailing List a good place for getting answers to R related questions


• R Seek, a useful tool as google isn't designed to just search for "R"

MIA... the trilogy

This is my third MIA post and I'd like to think that taking time to finish my Master of Bioinformatics degree, get a job, move, and get engaged would be suitable excuses for my lack of posting. But who knows, maybe I'm just not cut out to be a blogger. But as with all good/bad trilogies, things must come to an end so expect this to be my last MIA post.

Currently on the queue of posts that I have begun to write about are the following:

• The R Programming Language


• Links for free Bioinformatics and Biology classes


• Consed's .ace file format


• NCBI's OMIM

If there is anything else that anyone is interested in, leave the topic ideas in the responses.