[BioC] Standard error in summarization ExpressionSets
Martin Morgan
mtmorgan at fhcrc.org
Wed Jun 11 18:55:36 CEST 2008
Richard Pearson wrote:
> 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")
also assayData(eset)[["se.exprs"]], which might have a more familiar
feel to it. Both return NULL when se.exprs is not present.
Martin
>
> 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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>>
>
--
Martin Morgan
Computational Biology / Fred Hutchinson Cancer Research Center
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PO Box 19024 Seattle, WA 98109
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