[BioC] vsn with a reference set

[Roumyana Yordanova]

Dear Wolfgang,

I run your example and got this graph (attached). It seems the figure on 
the lower left (the normalization with the reference) is not scaled 
properly.
If I use vsn2 with just a matrix instead of AffyBatch object the scaling 
is fine. Am I missing something?
Thank you.

Roumyana

Wolfgang Huber wrote:

>Dear Roumyana
>
>they are on the glog2 scale
>
>   glog2(x) = log2( x + sqrt (x^2 + b^2) )
>
>where b is of the order of the microarray background intensity, so glog2
>is (up to a constant) the same as log2 for intensities well above
>background, x>>b. The effect of the sqrt-term is similar to what is
>called "background correction" in other approaches, namely to prevent
>the argument of the log2 function to become zero or negative.
>
>So you can treat the output of vsn2 like log2-transformed intensities,
>their differences as log2-fold-changes, etc.
>
>Best wishes
> Wolfgang
>
>------------------------------------------------------------------
>Wolfgang Huber  EBI/EMBL  Cambridge UK  http://www.ebi.ac.uk/huber
>
>
>26/03/2008 17:11 Roumyana Yordanova a écrit
>  
>
>>Dear Wolfgang,
>>
>>Thank you. My version of R was old and vsn2 did not work with AffyBatch
>>objects.
>>However, when I run it with 2.6.2  I got very small numbers (also
>>negative) for
>>x2 = exprs(justvsn(a2, ref=refvsn)). Are x2 the actual intensities or I
>>need to process them further?
>>
>>Roumyana
>>
>>Wolfgang Huber wrote:
>>
>>    
>>
>>>Roumyana Yordanova wrote:
>>>
>>>      
>>>
>>>>Dear Dr. Huber,
>>>>
>>>>I have a question regarding using vsn with a reference set.
>>>>I used it like this:
>>>>
>>>>ref <-ReadAffy(filenames=files.ref)
>>>>test <-ReadAffy(filenames=files.test)
>>>>ref.vsn <-justvsn(ref)
>>>>test.vsn <-justvsn(test,reference=ref.vsn)
>>>>
>>>>and got this error message
>>>>Error in vsnMatrix(m, reference, strata, optimpar = list(cvg.niter =
>>>>4L),: nrow(reference)' must be equal to 'nrow(x)'.
>>>>
>>>>I guess I am not using it right. Can you advise. Thank you very much.
>>>>
>>>>Sincerely,
>>>>Roumyana Yordanova
>>>>        
>>>>
>>>Dear Roumyana
>>>
>>>you will need to generate a "vsn" object that contains the actual
>>>model fit parameters, by using the function vsn2 on your object 'ref':
>>>
>>>You can then apply the model to the data in 'ref' by using 'predict',
>>>and you can obtain a reference normalisation using vsn2 or justvsn
>>>with the parameter 'ref' set. Please see the example below.
>>>
>>>Please also consider using the Bioconductor mailing list for this type
>>>of questions!
>>>
>>>
>>>library("vsn")
>>>library("affydata")
>>>
>>>data("Dilution")
>>>
>>>a1 = Dilution[, 1:3]
>>>a2 = Dilution[, 4  ]
>>>
>>>refvsn = vsn2(a1)
>>>x1 = predict(refvsn, a1)
>>>
>>>x2 = justvsn(a2, ref=refvsn)
>>>
>>>x = justvsn(Dilution)
>>>par(mfrow=c(2,2))
>>>for(i in 1:4)
>>>  plot(exprs(x)[,i],
>>>       if(i<=3) exprs(x1)[,i] else exprs(x2)[,1],
>>>       pch=".")
>>>
>>>
>>>
>>>
>>>Best wishes
>>>  Wolfgang
>>>
>>>------------------------------------------------------------------
>>>Wolfgang Huber  EBI/EMBL  Cambridge UK  http://www.ebi.ac.uk/huber
>>>      
>>>
>
>  
>
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