Writing from the previously mentioned intro to R course at the Kennedy Center. If you couldn't make it you can download all the course materials from Theresa Scott's website, under the "Current Teaching Material" heading. Here is a direct link to the PDF for the overview materials that we're going over today, along with the R code from the examples in this guide.

One of the most famous examples of a gene-environment interaction is being scrutinized by evidence from one of the largest meta-analyses on the subject to date. There have been tons of reports claiming or refuting evidence for a statistically significant interaction between a variant in the serotonin transporter gene (5-HTT) and stressful life events and their effect on major depression.

Hierarchical clustering is a technique for grouping samples/data points into categories and subcategories based on a similarity measure. Being the powerful statistical package it is, R has several routines for doing hierarchical clustering. The basic command for doing HC is Nearly all clustering approaches use a concept of distance.

The New York Times published this interesting article on how the ability to design and perform computer simulations is a highly marketable skill for careers across many disciplines.In methodology development we use simulation nearly every day.

I've linked to UCLA's stat computing resources once before on a previous post about choosing the right analysis for the questions your asking and the data types you have.

This week Illumina launched their own personal genome sequencing service. For $48,000 they'll send you the sequence of your entire genome on a Mac computer that you can keep. According to their website, all the sequencing is done in a CLIA-certified clinical lab.

Here's a good paper published online this morning in Nature Reviews Genetics. As the title suggests, the paper covers many of the challenges associated with translating molecular genetic tests into clinical practice. There are tons of references to articles on the ethical, legal, and social issues surrounding genetic testing in health management.

The estout package for Stata is useful for quickly creating nicely formatted tables from a regression analysis for tables or papers. To install it, fire up Stata and type in this command:ssc install estout, replaceStata will automatically download and install the package. Run the regression as you normally would, then use the esttab command (part of the estout package) to create a table using those results.

I know that a lot of you are scrambling to spend your training grant money by next week. If you think you'll ever need to use R, I strongly recommend buying this book: Introductory Statistics with R, by Peter Dalgaard ($48, Amazon). I picked this up a while back and read through most of it in a day or two.

Some of the best figure design ideas come from cartographers. If you've ever read a Tufte book you've seen lots of examples. Let's talk about using color effectively. Penn State geography professor Cindy Brewer's ColorBrewer tool for selecting color schemes for figures has been conveniently packaged into an R library called RColorBrewer.

GWAS reviews are a dime a dozen these days, but I found this one in particular that's a good up-to-date review suitable for people relatively new to the field. While this one has a focus on psychiatric genetics, it has a short summary on topics like positional methods, candidate gene studies, common variation, rare variation, CNVs, GWAS design, and issues concerning power and sample size.