Good Practice in DNA Microarray Analysis 2007

2007 November 30-01 in Munich

This course focuses on problems emerging in projects related to the classification of high-dimensional data and the functional annotation of gene expression data. The focus is on analysing your data and advanced questions on data analysis. There will be approximately as many teachers as participants and the data analysis will be performed in small groups.

Registration is open.

The course is restricted to members of the NGFN

To apply for this course, please send

• a short decription of the project (3 pages - design, principle questions, data generating procedures, analysis, interpretation)
• a list of main problems and needs
• a description of your data
• a short description of your statistical background
• a short description of your computational experiences (data bases, statistical software, ...)

to Prof. Ulrich Mansmann. Additionally, please tell us your NGFN Förderkennziffer(FKZ).

Background Knowledge

Ideally, you are preparing or conducting your project and are highly interested to apply state of the art methods for the analysis of your data. Furthermore, you are preparing a publication and aim at an appropriate presentation and interpretation of your results. This course focuses on problems emerging in projects related to the classification of high-dimensional data and the functional annotation of gene expression data.

Please use the links to software and literature to prepare yourself before the course begins.

R and Bioconductor

In the afternoon exercises you will learn how to analyze data using the statistical computing environment R [http://www.r-project.org] and BioConductor [http://www.bioconductor.org], an open source software for bioinformatics. R sources and package sources can be downloaded from The Comprehensive R Archive Network at http://cran.r-project.org.

This is a course in microarray analysis -- not an introduction to R. Please read the Introduction to R before the course begins.

Bring your own data

The focus of the course is to work on your own data. Bring e.g. genepix files or CEL/CDF or data already processed in R. We will work with your data to derive relevant results. If you expect to have own data only later in the year, it may in fact be advantageous also to register for one of the later courses.

How to find us

We meet at the Klinikum Großhadern, Hörsaaltrakt, Floor K O2, Seminarroom 5, Marchioninistraße 15, 81377 München.
Großhadern lies in the south-west of Munich (map). A detailed how-to-get-there is found here (in german only). For navigating, you might also find the roadmap and the following directions helpful:
• If you arrive in Munich by plane, take the S-bahn S8 ("Airport line") to Marienplatz.
• If you arrive by train, take any S-bahn or U-bahn to Marienplatz.
• From Marienplatz take U6 to final stop Klinikum Großhadern.
• Leaving the platform, you stand inside a glass pyramid (marked in red in the left figure below).

The red pyramid is the Ubahn-station at which you arrive using U6. The building marked in green is your destination.		This is the inside of the clinical center. The seminarrooms are on the upper right next to the letters "KL".

Accomodation

You will need to make your own accommodation arrangements. We recommend rooms at the Hotel Neumayr, which lies in Großhadern close to the clinical center. If you want to stay closer to the center of Munich, we recommend hotels in Schwabing, which is 15min by U-bahn from Großhadern. Have a look at Hotel Hauser, Hotel Lettl, or Renner Hotel Savoy.

Further information

Please contact Ulrich Mansmann: mansmann@ibe.med.uni-muenchen.de.