Target of the course

The course is aimed at scientists that are already involved in analysing genomic data. Attendees should bring with them data, or specific methodological innovations that they want to work on in collaboration with the organizers and other attendees. Participants should have sufficient minimal background on biological, statistical and computational aspects of microarray data and preferably be used to the R statistical environment.

The scope of the course

The focus will be on analysing and interpreting DNA microarray data but other topics will also be covered. Among these: visualization, machine learning and exploratory analyses will be emphasized. Methods for quality control and for making use of biological metadata in a structured way will be demonstrated.

The technical background and software

Ideally, participant are interested in mathematical and statistical problems and are familiar with at least one programming language. This course focusses on the practical side of gene expression data analysis. However, data analysis without understanding the statistical background is in general impossible. We strongly recommend participants to refresh their mathematical and programming skills before attending the course.

The computational aspects are a relevant part of the course. During the labs the software used will be R and tools from the Bioconductor project.
A knowledge of the R statistical software is welcome even if not necessary.

For more information on the software used follow the links below.

Hardware requirements

Participants are invited to bring their laptops with their favorite tools for analysing microarray experiments as well as their data-set that they can possibly share with other participants in the lab sessions.

We do have computer lab support for the participants in case a personal laptop is not available.