Dear Jim,
I pulled all relevant annotation via biomaRt, as biomart was all mappings
of exon array probeset IDs to eg ENTREZID or GENESYMBOL. Than you can go on
from that.

Cheers,
Andreas

2012/6/27 James Perkins <jperkins@biochem.ucl.ac.uk>

> Hi,
>
> I wasn't sure if this was worth starting a new thread for this, since
> my question is very much related to this thread...
>
> Is there any plan to include the "comprehensive" exon array mappings?
>
> E.g. for rat:
>
> If one goes here
>
>
> http://www.affymetrix.com/estore/browse/products.jsp?productId=131489&categoryId=35748&productName=GeneChip-Rat-Exon-1.0-ST-Array#1_1
>
> Then to Technical Documentation tab
>
> And downloads the
>
> "Rat Exon 1.0 ST Array Probeset, and Meta Probeset Files, core, full,
> extended and comprehensive rn4" data
>
>
> http://www.affymetrix.com/Auth/support/downloads/library_files/RaEx-1_0-st-v1.r2.dt1.rn4.ps.zip
>
> There are the core/extended/full ps and mps files here.
>
> However there is also a comprehensive mps file.
>
> Full, core and extended are from 2006.
>
> The comprehensive is from 2010 (and gets updated more regularly), so
> perhaps would be a better file to use for getNetAffx ?
>
> Apologies if this has been covered before. I am never sure of what is
> the best way to analyse exon array data at the gene level.
>
> Thanks,
>
> Jim
>
>
>
>
> On 13 June 2012 21:37, Benilton Carvalho <beniltoncarvalho@gmail.com>
> wrote:
> >
> > please correct the code below to:
> >
> > eset = rma(raw, target='full') ## or 'core', 'extended' (whatever is
> available)
> >
> > and if you want results at the exon level
> >
> > eset = rma(raw, target='probeset')
> > featureData(eset) = getNetAffx(raw, 'probeset')
> >
> > apologies for the mistake below.
> >
> > b
> >
> > On 13 June 2012 20:11, Benilton Carvalho <beniltoncarvalho@gmail.com>
> wrote:
> > > FWIW, remember that you can obtain the contents of the annotation
> > > files (the NA32 Affymetrix files) with:
> > >
> > > library(Biobase)
> > > library(oligo)
> > > raw = read.celfiles(list.celfiles())
> > > eset = rma(raw, target='transcript')
> > > featureData(eset) = getNetAffx(eset, 'transcript')
> > > head(fData(eset))
> > >
> > > b
> > >
> > > On 13 June 2012 15:47, James W. MacDonald <jmacdon@uw.edu> wrote:
> > >> Hi Andreas,
> > >>
> > >>
> > >> On 6/13/2012 3:14 AM, Andreas Heider wrote:
> > >>>
> > >>> Dear mailing list,
> > >>> I know this was on the list couple of times, and I think I read it
> all,
> > >>> but
> > >>> actually I still don't get it right. So here is my problem:
> > >>>
> > >>> I want to be able to work with Mouse Exon 1.0 ST Arrays (NOT Mouse
> Gene
> > >>> 1.0
> > >>> ST) in a similar fashion to eg. HG-U133 arrays.
> > >>> That means, I want to finally have it accessible as an ExpressionSet
> > >>> object
> > >>> with a right Bioconductor annotation assigned. This should include
> GENE
> > >>> SYMBOLS, RefSeq IDs and ENTREZ IDs.
> > >>
> > >>
> > >> The problem here is that you want to do something that AFAIK isn't
> easy to
> > >> do. The Gene ST arrays allow you to summarize all the probes that
> > >> interrogate a particular transcript (e.g., all the exon-level
> probesets are
> > >> collapsed to transcript level, and then you summarize). However, for
> the
> > >> Exon ST arrays that isn't the case, unless there is something in xps
> to
> > >> allow for that - I know next to nothing about that package, so
> Cristian
> > >> Stratowa will have to chime in if I am missing something.
> > >>
> > >> For the Exon chips, you are always summarizing at the same probeset
> level,
> > >> where there are <= 4 probes per probeset, and there can be any number
> of
> > >> probesets that interrogate a given exon. Lots of these probesets
> interrogate
> > >> regions that aren't even transcribed, according to current knowledge
> of the
> > >> genome. When you choose core, extended or full probesets, you are just
> > >> changing the number of probesets being used, not summarizing at a
> different
> > >> level as with the Gene ST chip.
> > >>
> > >> So when you say you want gene symbols, refseq ids and gene ids, what
> exactly
> > >> are you after? If a given probeset is in the intron of a gene do you
> want to
> > >> annotate it as being part of that gene? How about if it is in the UTR
> (or
> > >> really close to the UTR)? What do you want to do with the probesets
> where
> > >> one or more of the probes binds in multiple positions in the genome?
> These
> > >> are all questions that the exonmap package tries to consider, and it
> gets
> > >> really complicated. That's why Affy went with the Gene ST chips - they
> > >> unleashed the Exon chips on us and couldn't sell them because people
> were
> > >> saying WTF do I do with this thing?
> > >>
> > >> I don't think there is an easy or obvious answer to your question. If
> you
> > >> were to come up with what you think are reasonable answers to my
> questions,
> > >> then it wouldn't be much work to extract the chr, start, end from the
> > >> pd.moex.1.0.st.v1 package, and then use GenomicFeatures (e.g.,
> > >>  findOverlaps()) to decide what regions are being interrogated, and
> annotate
> > >> from there.
> > >>
> > >> Best,
> > >>
> > >> Jim
> > >>
> > >>
> > >>
> > >>>
> > >>> I can import it as a AffyBatch and generate an ExpressionSet with
> the help
> > >>> of the Xmap/exonmap supplied CDF, but there is no annotation
> attached to
> > >>> it.
> > >>>
> > >>> OR
> > >>>
> > >>> I can import the CEL files with the "oligo" package as a Exon Array
> object
> > >>> and generate an ExpressionSet from it.
> > >>> However in that case it still have no annotation.
> > >>>
> > >>> Surprisingly on the Bioconductor website there are all packages
> needed to
> > >>> deal with Mouse Gene 1.0 ST arrays but the informtion to work with
> Mouse
> > >>> Exon 1.0 ST arrays seems missing!
> > >>>
> > >>> What am I doing wrong here? Has someone else had such problems?
> > >>>
> > >>> Thanks in advance for your effort,
> > >>> Andreas
> > >>>
> > >>>        [[alternative HTML version deleted]]
> > >>>
> > >>> _______________________________________________
> > >>> Bioconductor mailing list
> > >>> Bioconductor@r-project.org
> > >>> https://stat.ethz.ch/mailman/listinfo/bioconductor
> > >>> Search the archives:
> > >>> http://news.gmane.org/gmane.science.biology.informatics.conductor
> > >>
> > >>
> > >> --
> > >> James W. MacDonald, M.S.
> > >> Biostatistician
> > >> University of Washington
> > >> Environmental and Occupational Health Sciences
> > >> 4225 Roosevelt Way NE, # 100
> > >> Seattle WA 98105-6099
> > >>
> > >>
> > >> _______________________________________________
> > >> Bioconductor mailing list
> > >> Bioconductor@r-project.org
> > >> https://stat.ethz.ch/mailman/listinfo/bioconductor
> > >> Search the archives:
> > >> http://news.gmane.org/gmane.science.biology.informatics.conductor
> >
> > _______________________________________________
> > Bioconductor mailing list
> > Bioconductor@r-project.org
> > https://stat.ethz.ch/mailman/listinfo/bioconductor
> > Search the archives:
> http://news.gmane.org/gmane.science.biology.informatics.conductor
>

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