Aviad Klein over at My ContRibution wrote a convenient R function to list the classes of all the vectors that make up a data.frame. You would think apply(kyphosis,2,class) would do the job but it doesn't - it calls every vector a character class. Aviad wrote an elegant little function that does the job perfectly without having to load any external package:

Hadley Wickham, creator of ggplot2, an immensely popular framework for Tufte-friendly data visualization using R, is teaching two short courses at Vanderbilt this week. Once we opened registration to Vanderbilt students and staff we instantly filled all the available seats, so unfortunately I wasn't able to announce the course here. But the good news is that Hadley's made all the data, code, and slides from the course available online here.

Update Tuesday, September 14, 2010: Fixed the ylim issue, now it sets the y axis limit based on the smallest observed p-value. A while back Will showed you how to create QQ plots of p-values in Stata and in R using the now-deprecated sma package. A bit later on I showed you how to do the same thing in R using ggplot2.

At the request of a commenter I just wanted to clarify that any code released here for R or anything else is free and open source unless specifically stated otherwise. The open source (GPLv2) license for any code on GGD can be found on this page.Getting Genetics Done by Stephen Turner is licensed under a Creative Commons Attribution (CC BY) License.

A few months ago I covered an algorithm called EMMA (Efficient Mixed-Model Association) implemented in R for simultaneously correct for both population stratification and relatedness in an association study.

I've covered a few topics in the past including the plyr package, which is kind of like "GROUP BY" for R, and the merge function for merging datasets. I only recently found the sqldf package for R, and it's already one of the most useful packages I've ever installed. The main function in the package is sqldf(), which takes a quoted string as an argument. You can treat data frames as tables as if they were in a relational database.

Found this tutorial by Emily Mankin on how to do principal components analysis (PCA) using R. Has a nice example with R code and several good references. The example starts by doing the PCA manually, then uses R's built in prcomp() function to do the same PCA. Principle Components Analysis: A How-To Manual for R Getting Genetics Done by Stephen Turner is licensed under a Creative Commons Attribution (CC BY) License.

Several readers emailed me or left a comment on my previous announcement of Frank Harrell's workshop on using Sweave for reproducible research asking if we could record the seminar. Unfortunately we couldn't record audio or video, but take a look at the Sweave/Latex page on the Biostatistics Dept Wiki.

Frank Harrell, chair of the Biostatistics department here at Vanderbilt, is giving a seminar entitled "Sweave for Reproducible Research and Beautiful Statistical Reports" tomorrow, Wednesday, May 12, 1:30-2:30pm, in the MRBIII Conference Room 1220.

If you attended Frank Harrell's Regression Modeling Strategies course a few weeks ago, you got a chance to see the rms package for R in action. Frank's rms package does regression modeling, testing, estimation, validation, graphics, prediction, and typesetting by storing enhanced model design attributes in the fit.