[BioC] About weight function for Agilent data

[Nataliya Yeremenko]

I have seen here in the BioC topics several threads concerning weighting of
the Agilent data, howeever I didn't understand how important it is,
how does it influence linear models and differential expression testing.

In particular Agilent Feature extraction performs quite a lot of 
flagging and do normalization itself.
What kind of flags is important to set for weight zero?
Should control spots be weighted zero as well?
Is it wise to use processed intensities (and do not use withinarray 
normalisation of Limma) instead of raw data?
There are number of between normalisations, but which one to use?


-- 
Dr. Nataliya Yeremenko 

Universiteit van Amsterdam
Faculty of Science
IBED/AMB (Aquatische Microbiologie)
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NL-1018WS Amsterdam
the Netherlands

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