[BioC] Mas5 log transformed data

[James W. MacDonald]

Hi Eleonora,

On 4/3/2012 6:45 AM, Eleonora Lusito [guest] wrote:
> Dear BioC users, sorry to bother you, but I'm new in R/Bioconductor. I' would like to analyze microarray HG-U133A chips as from GSE3494 but using Mas5 as background correction and  normalization algorithm. I use the following commands as from library(affy):
> abatch<- ReadAffy()#to read the cel files
> eset.mas5 = mas5(abatch)#to run the Mas5 algorithm
> exprSet.nologs = exprs(eset.mas5)#to get the expression matrix (probesets/genes in rows, chips in columns).
> exprSet = log(exprSet.nologs, 2)# to transform in log2 the absolute gene expression summarized values.
>
> Now the point is: after log2 transformation  I found negative values even using a scaling factor of 600. What am I doing wrong? I tried to use the simpleaffy package  using justMAS as function and setting a tgt = 600, but the problem still remain. Can anyone help me?

I think you might be misunderstanding the scale value in mas5(). The 
math for the scale value is

new.vals = (scale.value/mean.vals) * old.vals

where mean.vals are the trimmed means of the unscaled values and 
old.vals are the unscaled values.

So you are just centering the data, and then multiplying by 600. This 
will not cause negative numbers to become positive.

The usual prescriptive for negative mas5 numbers is to shift all data by 
a constant, so the smallest value is some small positive value. 
Something like

exprs(eset) <- sweep(exprs(eset), abs(min(exprs(eset))) + 5, "+")

then take logs.

Best,

Jim



>
> thanks in advance
>
>
> Eleonora
>
>   -- output of sessionInfo():
>
> R version 2.12.1 (2010-12-16)
> Platform: x86_64-apple-darwin9.8.0/x86_64 (64-bit)
>
>
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-- 
James W. MacDonald, M.S.
Biostatistician
University of Washington
Environmental and Occupational Health Sciences
4225 Roosevelt Way NE, # 100
Seattle WA 98105-6099