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.

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.

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).

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.

Our lab is looking for a postdoc. See the ad here, reproduced below. POST-DOCTORAL POSITION VANDERBILT CENTER FOR HUMAN GENETICS RESEARCH PROGRAM IN COMPUTATIONAL GENOMICS The Program in Computational Genomics in the CHGR at Vanderbilt University has an immediate opening for a post-doctoral fellow to pursue new and exciting research in human genetics.

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.