Dear Xavi,
thank you for your fast answer! I agree with your proposed procedure.
However, I don't know how to get to a complete matrix with both datasets (I
mean with R-commands). And is it necessary to have a complete AffyBatch
object of this combined matrix, or is it sufficient to just have "a" matrix?
On the other hand, can't I take raw CEL extracts of both chips, keep only
"best match" probesets of the raw data, combine them into one matrix and
then do the normalization?

Thanks, Andreas

2011/3/10 Sole Acha, Xavi <x.sole@iconcologia.net>

> Dear Andreas,
>
> a possible pipeline (though not necessarily the best one -- suggestions
> welcome) to compare HG-U133 Plus2 and HG-U219 data is:
>
> 1) Download CEL files and normalize both datasets separately using RMA, so
> you don't use Plus2's MM. I believe it is not straightforward to convert
> Plus2 CEL files to U219 or viceversa.
>
> 2) For both array types, keep only probesets with the best match (the most
> comparable between the two array types). You can find this information in
> Affymetrix's website:
>
>
> http://www.affymetrix.com/support/downloads/comparisons/U133PlusVsU219_BestMatch.zip
>
> In this file you have the correspondence between Plus2 and U219 probesets.
> You can build then a complete matrix with all the Plus2 and U219
> hybridizations and only the common probesets, for which you will have to
> create a new ID, since probeset ID's are different for Plus2 and U219
> arrays.
>
> 3) Once you have a common set of probesets for both datasets, you can
> re-normalize all the arrays altogether applying a quantile normalization
> (see package limma).
>
> Although this approach may work for you, please notice that even after
> applying quantile normalization in step 3 you may have a strong batch effect
> in your data, which you must be aware of.
>
> Hope this helps,
>
> Xavi.
>
> ------
> Xavier Solé Acha
> Unitat de Biomarcadors i Susceptibilitat
> Unit of Biomarkers and Susceptibility
> Institut Català d'Oncologia // Catalan Institute of Oncology
> Gran Via de L'Hospitalet 199-203
> 08908 L'Hospitalet de Llobregat, Barcelona, Spain.
> Phone: +34 93 260 71 22 / +34 93 260 71 86 (ext. 7122)
> Fax: +34 93 260 71 88
> E-mail: x.sole (at) iconcologia.net
>
> -----Mensaje original-----
> De: bioconductor-bounces@r-project.org [mailto:
> bioconductor-bounces@r-project.org] En nombre de Andreas Heider
> Enviado el: jueves, 10 de marzo de 2011 9:29
> Para: bioconductor@r-project.org
> Asunto: [BioC] comparing HG-U219 data to HG-U133 data from public databases
>
> Hi bioconductor users,
> I am a PhD student working on stem cells from human umbilical cord blood. I
> got data from our sorted cells relying on the HG-U219 platform from
> Affymetrix. What I want to do is to compare our data to data from public
> databases such as GeneExpressionOmnibus or ArrayExpress, but unfortunately
> these data are all based on the HG-U133 platform.
>
> So my question is: What would be the simplest approach to achieve this?
> What
> would be the best approach to achieve this?
>
> I'm thinking of 2 scenarios:
> First scenario:
> 1. Get an expression table for both datasets (U219 and U133)
> 2. label both datasets with "comparable" identifiers, eg UniGene Id or
> GeneBank A#
> 3. get new expression tables with only entries present in both datasets
>
> Second scenario:
> 1. get raw data of both datasets
> 2. import CEL files from U219 and convert it to U133 format
> 3. combine both datasets into 1
> 4. do normalization of all data together
>
> Please tell me it is possible, and if then how to do it. I'm pretty sure it
> is possible, but I'm a R and BioC novice and don't know every
> function/package.
>
> Thanks in advance, Andreas
>
> PS: Is it problematic that there are only perfect match probes on the
> HG-U219 and no MMs?
>
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>
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