Your Rprofile is a script that R executes every time you launch an R session.

I haven't posted much here recently, but here is a roundup of a few of the links I've shared on Twitter (@genetics_blog) over the last two weeks. Here is a nice tutorial on accessing high-throughput public data (from NCBI) using R and Bioconductor. Cloudnumbers.com , a startup that allows you to run high-performance computing (HPC) applications in the cloud, now supports the previously mentioned R IDE, RStudio.

I just discovered a handy function in R to produce a scatterplot matrix of selected variables in a dataset. The base graphics function is pairs(). Producing these plots can be helpful in exploring your data, especially using the second method below. Try it out on the built in iris dataset.

There are several tools available for conducting a post-hoc analysis of GWAS data looking for enrichment of significant SNPs using literature or pathway based resources. Examples include GRAIL, ALLIGATOR, and WebGestalt among others (see SNPath R Package). Since gene enrichment and pathway analysis essentially evolved from methods for analyzing gene expression data, many of these tools require specific gene identifiers as input.

I wanted to contribute any content and code I post here to the R Programming Wikibook so I made a slight change to the Creative Commons license on this blog. All the written content is now cc-by-sa and all the code here is still open source BSD.

In a previous post I linked to gcol as a quick and intuitive alternative to awk. I just stumbled across yet another set of handy text file manipulation utilities from the creators of the BEAGLE software for GWAS data imputation and analysis.

Jeffrey Breen put together a useful slideshow on accessing databases from R. I use RODBC every single day to access my own local MySQL server from R. I've had trouble with RMySQL, so I've always used RODBC instead after setting up my localhost MySQL server as a Windows data source. Once you get accustomed to accessing your data directly with SQL queries rather than dumping files you'll wonder why you waited so long.

PLINK/SEQ is an open source C/C++ library for analyzing large-scale genome sequencing data. The library can be accessed via the pseq command line tool, or through an R interface. The project is developed independently of PLINK but it's syntax will be familiar to PLINK users. PLINK/SEQ boasts an impressive feature set for a project still in the beta testing phase.

**** UPDATE, May 15 2014 ***** The functions described here have now been wrapped into an R package. View the updated blog post or see the online package vignette for how to install and use. If you'd still like to use the old code described here, you can access this at version 0.0.0 on GitHub.

I love the idea of using R+LaTeX+Sweave for reproducible research. This is even easier now that R has a jazzy new IDE that supports Sweave syntax highlighting and automatic PDF generation. I know I'm going to take some flak for saying this, but let's be honest here... If you're working in the biomedical sciences, chances are, your collaborators have never heard of Sweave. Physicians only use LaTeX during surgery.