Designer Jesse Dee has an entertaining presentation on Slideshare about how to use Powerpoint effectively (although Edward Tufte may assert that such a thing is impossible). These are all things we probably know, but just don't take into consideration enough when we're giving a presentation. According to Dee, the number one most common mistake is lack of preparation.

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.

Previously mentioned LocusZoom has undergone some major updates over the last few months. Many of the bugs mentioned in my previous post are now fixed, and now there's a good bit of documentation available. There are also a few new features, including the ability to add an extra column to your results file to change the plotting symbol to reflect your own custom annotation (i.e. whether the SNP was imputed or genotyped, or the SNP's function).

Hadley Wickham, creator of ggplot2, has posted a 2 hour video on data visualization using R. You can find links to the videos and slides over at Revolutions Blog. Check back here soon. I am working with Hadley to arrange a day-long ggplot2 short course here at Vanderbilt this summer.

*** Update April 25, 2011: This code has gone through a major revision. Please see the updated code and tutorial here. *** A few months ago I showed you in this post how to use some code I wrote to produce manhattan plots in R using ggplot2. The qqman() function I described in the previous post actually calls another function, manhattan(), which has a few options you can set.

Check out this month's table of contents in  Nature Methods. It contains a series of five commissioned Reviews discuss the challenges of visualizing biological data and the visualization tools available to biologists working with genomes, alignments and phylogenies, macromolecular structures, images and systems biology data.

In a previous tutorial I showed you how to create plots faceted by the level of a third variable using ggplot2. A commenter asked about using faceted plots and viewports and reminded me of this function I found in the ggplot2 Google group. The arrange function below is similar to using par(mfrow=c(r,c)) in base graphics to put more than one plot in the same image window.

Update Friday, May 14, 2010: See this newer post on LocusZoom. If you caught Cristen Willer's seminar here a few weeks ago you saw several beautiful figures in the style of a manhattan plot, but zoomed in around a region of interest, with several other useful information overlays.

Found this nice way to visually summarize contingency tables using ggplot2 in R on Hadley Wickham's ggplot2 cheat sheet. Using the same data in my previous post on making scatterplots in small multiples, I'll demonstrate how to use ggfluctuation() to make a fluctuation plot.