[BioC] Normalization of bi-modal expression data

[Naomi Altman]

Did you remove the Agilent controls before 
looking at the intensity distribution?

--Naomi

At 06:01 AM 2/3/2009, Christian Brière wrote:
>Hi!
>
>I am new in microarray analysis and in using Bioconductor. I need to
>analyse expression data from monocolor Agilent microarrays (105K).  To
>my surprise, for each array (controls as well as treated samples) the
>distribution of intensity data is bi-modal. Furthermore, it seems that
>more than 10% of the genes are differentially expressed between controls
>and treated samples. Therefore, I wonder what is the best method to use
>in such case for between arrays normalization. I was told that median or
>quantile normalization was not adequate. Should  Invariant Set or VSN
>normalization be better, and what are the packages to use for that ?
>Thanks for your help
>
>--
>
>Christian Brière
>UMR CNRS-UPS 5546
>BP42617 Auzeville
>F-31326 Castanet-Tolosan (France)
>tel: +33(0)5 62 19 35 90
>Fax: +33(0)5 62 19 35 02
>E-mail: briere at scsv.ups-tlse.fr <mailto:briere at scsv.ups-tlse.fr>
>
>http://www.scsv.ups-tlse.fr
>http://www.gdr2688.ups-tlse.fr <http://www.gdr2688.ups-tlse.fr/index.php>
>http://www.ifr40.cnrs.fr
>
>
>
>
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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111