[BioC] two questions regarding Human Gene 1.0 ST arrays

cstrato cstrato at aon.at
Mon Apr 25 21:13:52 CEST 2011


While Exon ST arrays have usually 4 probes per probeset, Gene ST arrays 
have only 1-2 probes per probeset. Thus my personal opinion is not to 
use Gene ST arrays to detect alternative splicing events.

However, there exists e.g. FIRMAGene for this purpose, see:
http://bioinf.wehi.edu.au/folders/firmagene/

Best regards
Christian


On 4/25/11 8:54 PM, Javier Pérez Florido wrote:
> Sorry, I always forget sessionInfo(), see below
>
> You are right, for Human Gene ST arrays and at transcript level, only
> "core" mode exists. However, when:
> fit<-fitPLM(OligoRaw)
> where OligoRaw is the set of Raw data, the size of "fit" object is
> 257,430 and when the following command is executed
>
> OligoEset<-rma(OligoRaw,target="probeset")
>
> OligoEset has 257,430 features. So, the RMA procedure "inside" fitPLM
> function performs a normalization at the probeset level.
>
> On the other hand, summarization using RMA can be performed at the
> transcript level in the following way:
> OligoEset<-rma(OligoRaw,target="core")
>
> which yields around 33000 transcripts.
>
> I'm still confused about the concepts of "probeset" and "transcript" on
> Human Gene Arrays.
>
> For Exon arrays, probesets consists of four individual probes and
> usually target a particular exon of a particular gene. Thus exon-level
> intensity estimates correspond to the probeset-level estimates.
> Probesets are further grouped into transcript clusters enabling
> gene-level estimate to be computed by summarizing data from all probes
> within the transcript cluster.
>
> However, I don't know if I can assert that, for Gene arrays, probesets
> target a particular exon of a particular gene and transcript cluster
> enables gene-level estimates as Exon arrays. The only difference is
> that, for Exon arrays, we have two more "annotation levels" with less
> confidence score (extended and full). Otherwise, what is the utility of
> summarizing at the probeset level on Hu Gene arrays?
>
> This is related to my second question: can HuGene could detect
> alternative splice events reliably? Can HuGene be used as an economical
> exon array for just the well-annotated content (core)?
>
> Thanks again,
> Javier
>
>
> Thanks,
> Javier
>
>
> R version 2.13.0 (2011-04-13)
> Platform: x86_64-pc-mingw32/x64 (64-bit)
>
> locale:
> [1] LC_COLLATE=Spanish_Spain.1252 LC_CTYPE=Spanish_Spain.1252
> LC_MONETARY=Spanish_Spain.1252 LC_NUMERIC=C
> [5] LC_TIME=Spanish_Spain.1252
>
> attached base packages:
> [1] stats graphics grDevices utils datasets methods base
>
> other attached packages:
> [1] pd.hugene.1.0.st.v1_3.0.2 hugene10sttranscriptcluster.db_7.0.1
> org.Hs.eg.db_2.5.0 RSQLite_0.9-4
> [5] DBI_0.2-5 AnnotationDbi_1.14.1 oligo_1.16.0 oligoClasses_1.14.0
> [9] affyPLM_1.28.5 preprocessCore_1.14.0 gcrma_2.24.1 affy_1.30.0
> [13] Biobase_2.12.1
>
> loaded via a namespace (and not attached):
> [1] affxparser_1.24.0 affyio_1.20.0 Biostrings_2.20.0 bit_1.1-6 ff_2.2-1
> IRanges_1.10.0 splines_2.13.0 tools_2.13.0
>
>
>
>
> On 25/04/2011 19:36, cstrato wrote:
>> Dear Javier,
>>
>> Since you do not supply your sessionInfo() it is not possible to
>> answer your question.
>>
>> However, please note that levels core, extended, full do only exist
>> for Exon ST arrays but not for Gene ST arrays.
>>
>> Best regards
>> Christian
>> _._._._._._._._._._._._._._._._._._
>> C.h.r.i.s.t.i.a.n S.t.r.a.t.o.w.a
>> V.i.e.n.n.a A.u.s.t.r.i.a
>> e.m.a.i.l: cstrato at aon.at
>> _._._._._._._._._._._._._._._._._._
>>
>>
>> On 4/25/11 7:24 PM, Javier Pérez Florido wrote:
>>> Dear list,
>>> I have two questions regarding Human Gene 1.0 ST arrays:
>>>
>>> * Both NUSE and RLE plots need a fitted object using fitPLM
>>> function. Now, this function accepts raw data from a set of Hu
>>> Gene 1.0 arrays, but, internally, this function performs a RMA
>>> normalization. What level is used for this normalization? I cannot
>>> choose the level (i.e. core, full, extended) for the "internal"
>>> normalization.
>>> * Are a splicing analysis using Hu Gene 1.0 arrays (core analysis)
>>> and a splicing analysis using Hu Exon 1.0 arrays (core analysis)
>>> equivalent in terms of results?
>>>
>>>
>>> Thanks,
>>> Javier
>>>
>>>
>>> [[alternative HTML version deleted]]
>>>
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>>
>
>



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