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.

As a graduate student a few years ago, I learned about (and in some cases witnessed) the various phases, fads, and revolutions in the field of human genetics. The mid to late 90's saw a shift from family-based linkage analysis to a plethora of small candidate gene studies. The early 2000's saw the completion of the human genome project, the development of the HapMap project, and the birth of genome-wide association studies.

I've had friends in biochem "wet" labs who've asked me to do some simple statistics on some of their results. This looks like an interesting seminar to attend if you've ever thought about doing a t-test on fold changes in some outcome measure between treatment and control groups, a pretty common outcome in biochemical assays. If the speaker provides slides electronically I'll happily post them here after the seminar.

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.

Vanderbilt Center for Human Genetics Research faculty candidate Goncalo Abecasis will be interviewing for a faculty position here this week. Come check out his seminar - "Sequencing Thousands of Human Genomes" - Friday June 11th, 2-3pm in 512 Light Hall.Getting Genetics Done by Stephen Turner is licensed under a Creative Commons Attribution (CC BY) License.