Good Practice in DNA Microarray Analysis 2007
2007 March 9-10 in Heidelberg
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).
| Friday, March 9 - Formulating goals and specific questions Providing needed background information |
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| 09.00-12.15 | Introducing the projects and project specific questions |
Short presentations by participants and monitored discussion |
| 14.00-18.00 | Analysis of data | Work in groups |
| Saturday, March 10 - Performing an appropriate analysis correct interpretation of your results |
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| 09.00-10.30 | First results and refinement of strategies | Short presentations by workgroups. |
| 10.30-12.15 | Short talks about topics related to the projects | Short presentations by teachers. |
| 14.00-16.00 | Performing your analysis | Mentored group work on the computer |
| 16.00-17.00 | Drawing appropriate conclusions | Group discussion |
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 Friday, March 9., at 9am in the German Cancer Research Center (DKFZ) building TP3, seminar room 4. floor. The building lies on the science campus of the university of Heidelberg, "Im Neuenheimer Feld", building 580 within the Technology Park.
This document may be helpful in finding the Neuenheimer Feld in Heidelberg: anfahrt_dkfz.pdf. Unfortunately it is in German only, but contains a number of very detailed maps guiding you to the DKFZ (INF 280).
The practical work will be carried out in the computer room of the IPMB (INF 364, 3rd floor). See course locations
Accomodation
You will need to make your own accommodation arrangements.
• The most useful website for this is the Heidelberg tourist information: http://www.cvb-heidelberg.de.
• The IBIS hotel is a generic budget hotel, close to the train station, and in walking distance from the course venue and from downtown: http://www.ibishotel.com.
• The hotel Frisch is right next to the university campus: http://www.cafe-frisch.de.
Further information
Please contact Ulrich Mansmann: mansmann@ibe.med.uni-muenchen.de.