[BioC] two questions regarding Human Gene 1.0 ST arrays

[Javier Pérez Florido]

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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>