[BioC] gcrma problem while processing HuGene-1_0-st-v1 genechip from Affymetrix

[cstrato]

Dear Suparna,

In principle you could use package xps to run mas5 for HuGene arrays, 
however, I would suggest to stay with rma (which xps also supports).

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
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On 6/11/12 5:00 PM, suparna mitra wrote:
> Hi,
>   I am very new to biocondunctor and microaray. I have limited experience
> with R.
> I am trying to use biocondunctor for analyzing HuGene-1_0-st-v1 microarray
> data. I selectected different normalization method (rma, gcrma and mas5).
> For my data rma worked but for for gcrma and mas5 both I have problem.
> For gcrma it gives me a error like: Computing affinitiesError:
> length(prlen) == 1 is not TRUE
>
> And for mas 5 it seems working but I get only a whole list of NA.
>
> Here is what I have done.
>
>> mydata<- ReadAffy()
>> mydata
> AffyBatch object
> size of arrays=1050x1050 features (16 kb)
> cdf=HuGene-1_0-st-v1 (32321 affyids)
> number of samples=18
> number of genes=32321
> annotation=hugene10stv1
>
>> eset<- rma(mydata)
> Background correcting
> Normalizing
> Calculating Expression
>> eset_justrma=justRMA()
>> eset_mas5<- mas5(mydata)
> background correction: mas
> PM/MM correction : mas
> expression values: mas
> background correcting...done.
> 32321 ids to be processed
> |                    |
> |####################|
>> eset_gcrma<- gcrma(mydata)
> Adjusting for optical effect..................Done.
> Computing affinitiesError: length(prlen) == 1 is not TRUE   Here is the
> error
>
>> eset_justrma # this worked fine
> ExpressionSet (storageMode: lockedEnvironment)
> assayData: 32321 features, 18 samples
>    element names: exprs, se.exprs
> protocolData
>    sampleNames: MC1_(HuGene-1_0-st-v1).CEL MC10_(HuGene-1_0-st-v1).CEL ...
> MC9_(HuGene-1_0-st-v1).CEL (18 total)
>    varLabels: ScanDate
>    varMetadata: labelDescription
> phenoData
>    sampleNames: MC1_(HuGene-1_0-st-v1).CEL MC10_(HuGene-1_0-st-v1).CEL ...
> MC9_(HuGene-1_0-st-v1).CEL (18 total)
>    varLabels: sample
>    varMetadata: labelDescription
> featureData: none
> experimentData: use 'experimentData(object)'
> Annotation: hugene10stv1
>> eset_mas5 # this seems worked fine but resulted all NA
> ExpressionSet (storageMode: lockedEnvironment)
> assayData: 32321 features, 18 samples
>    element names: exprs, se.exprs
> protocolData
>    sampleNames: MC1_(HuGene-1_0-st-v1).CEL MC10_(HuGene-1_0-st-v1).CEL ...
> MC9_(HuGene-1_0-st-v1).CEL (18 total)
>    varLabels: ScanDate
>    varMetadata: labelDescription
> phenoData
>    sampleNames: MC1_(HuGene-1_0-st-v1).CEL MC10_(HuGene-1_0-st-v1).CEL ...
> MC9_(HuGene-1_0-st-v1).CEL (18 total)
>    varLabels: sample
>    varMetadata: labelDescription
> featureData: none
> experimentData: use 'experimentData(object)'
> Annotation: hugene10stv1
>> write.exprs(eset_justrma,file="eset_justrma.csv")
>> write.exprs(eset_mas5,file="eset_mas5.csv")
>> write.exprs(eset,file="eset.csv")
>
> Any help in this will be really great. Being a novice, I am very sorry if I
> am doing any silly mistake.
> Thanks a lot,
> Suparna.
>