[BioC] Agilent Arrays
huber at ebi.ac.uk
Thu Jun 23 16:29:38 CEST 2005
and why is that important? Also, what is the within gene correlation
between green foreground of array 1 and green foreground of array 2?
<quote who="Naomi Altman">
> I am working with Agilent arrays on which we have spotted many replicates
> of the control spots.
> The within gene correlation between red and green forground is about 0.8
> for the unnormalized data - i.e. pretty high!
> At 03:23 AM 6/23/2005, Wolfgang Huber wrote:
>>for the normalization of arrays where the spotting etc. variability
>>between chips is not strong, you can treat the data from m two-colour
>>arrays as if it were 2*m single colour ones, and use methods like
>>"quantiles" or "vsn".
>>Note that for almost all genes, the hybridization is not limited by the
>>amount of probe DNA, hence the competition between red and gree target is
>>negligible for almost all genes (execept possibly the most highly
>>expressed ones). This justifies treating a two-color array like two
>>Only later when you consider the contrasts of interest for finding
>>differentially expressed genes, you want to make sure that these are not
>>confounded with dye.
>>PS, I think your question is very directly Bioconductor related!
>><quote who="Claus Mayer">
>> > 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
>> > to Affy, if I understand this correctly. This seems to show in the
>> > 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
>> > (differently dyed on different arrays in a loop design) that contained
>> > the same sample (which is quite reassuring). This made me wonder
>> > (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, Id 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
>> > --
>> > 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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