de.mpg.escidoc.pubman.appbase.FacesBean
English
 
Help Guide Disclaimer Contact us Login
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Book Chapter

Analysis of microarray gene expression data

MPS-Authors

Heydebreck,  Anja von
Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons50613

Vingron,  Martin
Gene regulation (Martin Vingron), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society;

Locator
There are no locators available
Fulltext (public)

Heydebreck.pdf
(Any fulltext), 2MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Huber, W., Heydebreck, A. v., & Vingron, M. (2003). Analysis of microarray gene expression data. In D. J. Balding, M. Bishop, & C. Cannings (Eds.), Handbook of Statistical Genetics (pp. /-/). Chichester [et al]: John Wiley & Sons, Ltd.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0010-8A1B-5
Abstract
This article reviews the methods utilized in processing and analysis of gene expression data generated using DNA microarrays. This type of experiment allows to determine relative levels of mRNA abundance in a set of tissues or cell populations for thousands of genes simultaneously. Naturally, such an experiment requires computational and statistical analysis techniques. At the outset of the processing pipeline, the computational procedures are largely determined by the technology and experimental setup that are used. Subsequently, as more reliable intensity values for genes emerge, pattern discovery methods come into play. The most striking peculiarity of this kind of data is that one usually obtains measurements for thousands of genes for only a much smaller number of conditions. This is at the root of several of the statistical questions discussed here.