[BioC] Analysing Agilent microarray data

[Francois Pepin]

Salut Christian,

It depends on the normalization scheme that you want. The Feature 
Extraction software offers one set of normalization among many. We use 
the r/gMeanSignal and then do the background correction and 
normalization ourselves (using limma, but others exist). This grants us 
more control and more choice over what happens.

Other people prefer the median signals instead, but we haven't found it 
to make much of a difference.

A lot depends on your experiments and which kinds of technical variation 
are the most prevalent. You would probably be better to explore the data 
by yourself and decide what works well for you.

Francois

Christian Brière wrote:
> Hi,
> 
> I am analysing 1-color Agilent microarray data and I wonder what is the 
> best variable(s) to use among the numerous variables provided by the 
> Feature Extraction software from Agilent.
> Should I use the "ProcessedSignal", which according to Agilent 
> documentation is the signal left after all pre-processing steps have 
> been completed and contains the "Multiplicatively Detrended 
> BackgroundSubtracted Signal" , or the "BGSubSignal" which equals to the 
> feature signal after background subtraction (using a spatial detrend 
> algorithm for background correction), or is it better to import the raw 
> MeanSignal and BGMeanSignal (or Median Signal) and use the limma package 
> to do background  correction (as done in the Agi4x44preprocess package)?
> Does anybody have some experience in using these different feature signals ?
> Thank you for any help
> Christian
> 
> 
> 
> 
> ------------------------------------------------------------------------
> 
> _______________________________________________
> Bioconductor mailing list
> Bioconductor at stat.math.ethz.ch
> https://stat.ethz.ch/mailman/listinfo/bioconductor
> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor