Tuesday, October 6, 2009

R Commander: A Basic Statistics GUI for R

R is a great tool with lots of resources for genetics, genome-wide association studies, and many other biological applications.  We've covered several places to find help in R in the past, but if you're still apprehensive about diving into R's command-line interface, fear not.  The R commander is a graphical user interface (GUI) for R that works under Windows, Linux, and Mac.  It features a data editor that looks a lot like an Excel spreadsheet or Stata's data editor.  It also has menus and clicky-boxes to do lots of basic analyses and for producing graphics without ever typing a single command.

R commander depends on lots of other packages to function properly, so to install it along with all it's dependencies, type this in at the R command line:

install.packages("Rcmdr", dependencies=TRUE)

Note that this may take 5-10 minutes depending on your connection since it's downloading lots of extra packages, but you only need to do that once.  Now that it's installed, any time you want to load it, open R and type:


If you're familiar with Stata or SPSS you should find the menus and dialog boxes intuitive and self-explanatory. I've put in a couple screenshots below showing R commander's data editor, GLM tool, and graphics menu.

There are a few other GUIs for R that I've never used, including Rattle (the R Analytical Tool To Learn Easily), and JGR (Java Gui for R).  If you prefer one of these to Rcmdr, let us here why in the comments!

The R Commander: A Basic-Statistics GUI for R

1 comment:

  1. R Commander also looks a lot like Minitab; people familiar with Minitab should have little trouble getting started with R Commander, once they figure out how to load data.
    I've not used Rattle, but I've tried JGR and find little or no advantage to it over the default Windows or Mac installation. In fact, it seems to be nearly a straight-up copy of the Mac interface for R. Maybe I've missed something.
    Of the front-ends for R that I've tried, R Commander seems to be the easiest to get started with. Deducer, Red R and R Analytic Flow all seem promising, too, though I've not been able to get Deducer to install correctly, Red R is still very much a beta product and Analytic Flow always seems to be incompatible with the latest versions of R.


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Getting Genetics Done by Stephen Turner is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License.