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.

A live webcast of the House Committee on Energy and Commerce hearing on “Direct-to-Consumer Genetic Testing and the Consequences to the Public Health" is available at this link. I had trouble viewing the webcast in firefox - had to save the link and open it with VLC media player to get it working. You can also follow the #HouseDTC hastag on Twitter.

Jeff Barret (@jcbarret on Twitter) over at Genomes Unzipped (@GenomesUnzipped) has posted a nice guide for the uninitiated on how to read a GWAS paper. Barret outlines five critical areas that readers should pay attention to: sample size, quality control, confounding (including population substructure), the replication requirement, and biological significance.

You can find two nice recaps of last week's personalized medicine policy forum on Genomics Law Report and 23andMe's blog, The Spittoon.

For those of you not following GGD on Twitter you may not have seen this - California State Senator Alex Padilla and 23andMe are hosting a policy forum entitled "Genomics and the Consumer: The Present and Future of Personalized Medicine" today in San Francisco.

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.

Next week Brent Anderson with Illumina will be hosting a seminar series showcasing presentations from Vanderbilt scientists using Illumina technology to power their next-generation sequencing studies.

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 while back, Stephen wrote a very nice post about converting PLINK output to a CSV file. If you are like me, you have used this a thousand times -- enough to get tired of typing lots of SED commands. I just crafted a little BASH script that accomplishes the same effect with a single easy to type command. Insert the following text into your .bashrc file.

Researchers in the ENGAGE consortium used a clever technique to leverage genome-wide expression data to select or prioritize genes for GWAS analysis. The investigators published the novel candidate genes for obesity in this month's PLoS Genetics, but I think the method they used here is more interesting.

NYU PhD student Drew Conway has compiled a very nice list of 10 reasons why grad students should blog. I've been writing GGD for a little over a year now and it's been a great way to extend my own network past the Vanderbilt walls, participate in lively discussions with other scientists oceans away, and to write stuff that people actually read and find useful.