[BioC] Standard error in summarization ExpressionSets

Richard Pearson richard.pearson at postgrad.manchester.ac.uk
Wed Jun 11 18:35:12 CEST 2008


Hi Rodrigo

I think the se.exprs() method disappeared a release or two ago. You can still get this data by using:

assayDataElement(eset, "se.exprs")

There are a few methods that I am aware of that give standard errors. In addition to fitPLM(), I believe you can also get standard errors from RMA using:

expresso(affybatch, bgcorrect.method="rma"
, normalize.method="quantiles", pmcorrect.method="pmonly"
, summary.method="medianpolish")

Also, MBEI (Li and Wong) will give standard errors:

expresso(affybatch
, normalize.method="invariantset", bg.correct=FALSE
, pmcorrect.method="pmonly", summary.method="liwong")
)

My personal recommendation for getting standard errors would be to use mmgmos() from the package puma (though I might be biased :-)

You could also look at the function bgx() in the package of the same name

HTH

Richard.


James W. MacDonald wrote:
> Hi Rodrigo,
> 
> Rodrigo Santamaría Vicente wrote:
>> Hi there!,
>> After performing normalization-summarization with any of the available 
>> functions (rma, mas5, plier, etc.), I get an ExpressionSet class. It 
>> inherits from eSet class, but it seems to loss the se.exprs() method 
>> to get the standard errors for the summarized expression levels.
>> My question is: how could I get the standard errors from the 
>> ExpressionSet returned by rma, mas5 or any other method? if these 
>> methods do not return standard errors, why? are them unimportant? is 
>> there any method that computes them?
> 
> None of the methods you mention return standard errors. If you want 
> standard errors, you might use the affyPLM package. For instance the 
> fitPLM() function will return values very similar to rma(), but with 
> standard errors.
> 
> Best,
> 
> Jim
> 
> 
>>
>> Thanks in advance!
>> Rodrigo
>>
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> 

-- 
Richard D. Pearson             richard.pearson at postgrad.manchester.ac.uk
School of Computer Science,    http://www.cs.man.ac.uk/~pearsonr
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