There's no doubt that by now you've noticed that we're big fans of R around here. It's completely free, has superior graphing capabilities, and with all the extension packages available there isn't much it can't do. One of the problems with R especially to new users is that it isn't obvious how to find help when you need it, so I'll try to provide a few resources here.

Both useful and delicious, this two-by-two table pie by Sarah Lowry, Sarah McDougal (my 2nd cousin) and friends of the UW MPH program helps you get genetics done and satisfies the appetite! If only she could mail me the Odds Ratio...Getting Genetics Done by Stephen Turner is licensed under a Creative Commons Attribution (CC BY) License.

Bioinformatics is running a special issue on next generation sequencing, featuring lots of papers on alignment, assembly, Chip-Seq, RNA-Seq, and other related topics. This "virtual issue" will be continually updated as more developments are made. From the editors: Bioinformatics: Next generation sequencing issueGetting Genetics Done by Stephen Turner is licensed under a Creative Commons Attribution (CC BY) License.

Here are citations for the articles discussed at our most recent meeting (June 24). Our next meeting is scheduled for July 17. ~Julia Choi Y, Wijsman EM, Weir BS. Case-control association testing in the presence of unknown relationships. Genet Epidemiol . 2009 Mar 30. [Epub ahead of print] Gao X, Becker LC, Becker DM, Starmer JD, Province MA. Avoiding the high Bonferroni penalty in genome-wide association studies.

For readers at Vanderbilt: At yesterday's R course I found out that Theresa Scott in the Biostatistics department holds a weekly R clinic and encourages new R users who want to learn more to bring any questions about R, or even your own code and data. The R clinic is held weekly on Thursday from 2:00-3:00 in MCN.

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. We've developed our own specialized genetic data simulation software, genomeSIMLA, that's freely available here by request for PC, Mac, and Linux.

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.