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

[Richard Friedman]

Jim and list,

	Thank you for bringing the NCprobe option to my attention.
I did not know that it had been implemented.

Does anyone out there have  a list of negative control probes more
Human st 1.0 and for Mouse st 1.0 ?

Thanks and best wishes,
Rich


On Jun 11, 2012, at 11:18 AM, James W. MacDonald wrote:

> 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
>
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