Getting started with microarray analysis in R
Follow instruction on how to install R and Bioconductor packages from:
The Bioconductor website has links to introductory course material, overview of functions, etc.
One useful site is: http://faculty.ucr.edu/~tgirke/manuals.htm
Download a nice Windows editor for R scripts:
http://www.sciviews.org/Tinn-R/, select Setup for Tinn-R, old stable version (18.104.22.168)
First practical: Introduction to R
In this practical you will learn how to read data into R, perform simple functions and make plots. The instructions, an input file and a list of basic R functions
are to be found in Getting started in R.
Using microarray-related packages in R
We give a yearly MGC course "Analysis of microarray gene expression data". All course lectures and practicals are available online.
To learn to use R for microarray data analysis, practise with the following modules from
For additional scripts see the R user group website: http://chromium.liacs.nl/R_users/
- Practical: Normalization in R
- Differential gene expression in R
- Pathway analysis using the globaltest
Remember: the learning curve is steep! In the beginning, be prepared for lots of error messages etc. that are best solved by finding people around you who have some experience in R.
At Human Genetics, these include: Peter-Bram 't Hoen, Judith Boer, Maarten van Iterson, and Henk Buermans.
Renee de Menezes gives a special R course on microarray analysis, including more statistics. This course is given when there are enough people interested. The course material can
be found at http://dial.liacs.nl/Courses/CMSB%20Courses.html and contains some overlap with practical modules in the MGC course.
When you are interested, please contact Judith Boer .
Open source data analysis tools that use R in the background
There are open source data analysis tools that include many of the options of Spotfire and R,
e.g. BRB-ArrayTools at http://linus.nci.nih.gov/~brb/download_3_5_0.htm.
Judith Boer, Human Genetics, LUMC. Updated 13/11/09