Summer Institute in Statistical Genetics
Module 19: Advanced R Programming for Bioinformatics
Instructors: Thomas Lumley and Ken Rice

This page will feature slides from our sessions, exercises for you to complete, and their solutions. Prior to the module, please install an up-to-date version of R on the laptop you will use during the summer institute. R is available from this site.

It may also be helpful to install the base Bioconductor packages; to download and install these, enter the following;


After doing this major download - once! - to download new Bioconductor packages (for example the hexbin package) use the following commands;


Tools for calling C from R - Windows
(For sessions 7/8) Resources for builing R packages under windows are available for download here. Make sure you get the version for your (current) version of R. Once you have installed them, your first command entered at the command line should be e.g.

path C:\Program Files\R\R-2.11.1\bin;%PATH%

...which adds the directory containing R to your path. If you don't know the directory containing R, right-click on the R shortcut icon

Slides and exercises

Script files are posted following each session; these will contain our R code for the exercises. Many exercises will be open-ended - and have many different solutions; the code posted here illustrates possible approaches.

Session 1, Introductions, simulation, debugging, timing (Exercises: .docx, .pdf) (R script file)

Session 2, Graphics (R code for color wheels and boxes in the slides) (Exercises: .docx, .pdf) (R script file)

Session 3, Object Systems (No exercises for this session)

Session 4, Lab exercise (Exercises: .docx, .pdf) (R script file)

Session 5, Packages (Exercises: .docx, .pdf) (R script file and the files it produces, which we have edited a little)

Session 6, XML (SVG Funnel plot example) (Exercises: .docx, .pdf) (R script files: kml.R phage.R)

Session 7, Embedding C code (no exercises for this session)

Session 8, Lab exercise (Exercises: .docx, .pdf) (Nearest neighbour Boxcar filter using .C Boxcar filter using .Call)

Session 9, Handling large datasets (no exercises for this session) (Example use of RSQlist)

Session 10, Lab exercise (Exercises: .docx, .pdf) (R script file)

Datasets and other files for exercises

- more to follow

Other resources

Some recommended books;