[BioC] Agilent Arrays

Gordon Smyth smyth at wehi.edu.au
Fri Jun 24 16:07:47 CEST 2005

My experience is that Agilent arrays respond to the same analysis methods 
as do other two colour arrays, apart from using global loess instead of 
print-tip loess normalisation. The generally high quality just means that 
you get more benefit from the analysis. We have found for example that 
accommodating dye-effects into the linear model particularly important for 
Agilent arrays. You might well have more confidence in analysing the red 
and green channels individually for Agilent arrays, but this is not the 
same as treating the arrays as two one-channel arrays. See for example 
lmscFit() in the limma package.


>Claus Mayer claus at bioss.ac.uk
>Wed Jun 22 19:18:19 CEST 2005
>Dear all!
>Apologies for asking a question which is not directly Bioconductor
>related: After some experience with spotted 2-channel arrays and
>Affydata, I am currently analysing my first data set based on Agilent
>arrays. I know that packages like marray or limma have facilities to
>read these data and that they can be normalised and analysed like any
>other 2-colour-arrays. On the other hand the printing technology of
>these arrays (using inkjet-printing of 60mer oligos) is closer in spirit
>to Affy, if I understand this correctly. This seems to show in the data
>as well. For example the strongest correlations I found in the single
>channel (log-)intensities was not between the two channels observed on
>the same slide (like with spotted arrays), but between the two channels
>(differently dyed on different arrays in a loop design) that contained
>the same sample (which is quite reassuring). This made me wonder whether
>(once dye and array effects have been removed by some normalisation
>method) with Agilent arrays one might really use single channel
>intensities as measures of gene expression instead of reducing them to
>the log-ratio only as is usually done for two-channel data.
>This would have consequences on the way these arrays should be
>normalised (rather by a multichip method than individually) and also
>allow more flexibility in the design of experiments.
>As I said before this is my first Agilent data set, so I would be
>interested to hear opinions of others with more experience. Before I
>start to re-invent the wheel here, I’d be also interested to know
>whether any of you is aware of tools, software, papers, etc
>with the analysis of Agilent array data specifically (rather than just
>applying standard methods for 2-coloured cDNA -arrays).
>Any help/comments appreciated
>  Claus-D. Mayer                       | http://www.bioss.ac.uk
>  Biomathematics & Statistics Scotland | email: claus at bioss.ac.uk
>  Rowett Research Institute            | Telephone: +44 (0) 1224 716652
>  Aberdeen AB21 9SB, Scotland, UK.     | Fax: +44 (0) 1224 715349

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