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

[James W. MacDonald]

Hi Suparna,

On 6/11/2012 11:00 AM, 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.

This is to be expected. The HuGene array is a PM-only design, so mas5() 
won't work (because the mas5 algorithm requires subtracting MM from PM, 
and there are no MM probes). In addition, the default for gcrma() is to 
estimate the background for probes based on the GC content, using bins 
of MM probes. Again, without any MM probes, this won't work.

Note however that gcrma() has an 'NCprobe' argument that you can use to 
specify an index of negative control probes. This is a non-trivial thing 
to do, and may be beyond your abilities if you are very new to R and BioC.

To get the index of these probes, you will need to decide which probes 
are negative control probes, and then you can use the indexProbes() 
function, passing a character vector of the negative control probes to 
the genenames argument. This will return a list of indices for each 
probeset that you can unlist() prior to feeding in to gcrma().

Or you could just stick with rma(), like the vast majority of people do.

Best,

Jim


> 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.
>

-- 
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099