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Can you tell me some procedures in R, which are able to find differentially expressed genes for a given microarray data?

Moreover,If you can give some ideas related to clustering of significant genes for microarray data, it will be quite helpful for me.

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  • $\begingroup$ See this publication: Morrissey ER, Diaz-Uriarte R. Pomelo II: finding differentially expressed genes. Nucleic Acids Res. 2009. And this website: pomelo2.bioinfo.cnio.es. Note that there are literally dozens of tools and methods used for this purpose and this is just one example. $\endgroup$ – Alexander May 16 '12 at 11:45
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It depends on what kind of data you want to analyze the two i know of is affymetrix oligo-arrays which have the .CEL extension, the bioconductor project provides the affy package for this. The other type of microarrays are cDNA arrays which have two color channel to separate conditions, is mostly done with the lima package.

i'd recommend looking at this class website i took this class myself and the materials are pretty good:

http://cals.arizona.edu/~anling/MCB516/MCB516A.htm

In there you can see that the textbook "Bioconductor case studies" is pretty good source itself. The password for the documents is: bioinformatics.

Other than that i'd recommend you look in these two links which contain some tutorials:

http://www.bioconductor.org/packages/release/bioc/vignettes/affy/inst/doc/affy.pdf

http://www.bioconductor.org/packages/release/bioc/html/limma.html http://www.bioconductor.org/packages/release/bioc/html/affy.html

I have lots more of resources and can help offline with any specific question, just email me (in my profile)

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    $\begingroup$ as an afterthought www.biostars.org has also lots more information on this, it used to be part of the stackexchange network, but for some reason they moved it out. $\endgroup$ – raygozag Apr 16 '12 at 13:35

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