[BioC] normalizeQuantiles : log2 or not??

[Marcelo Luiz de Laia]

Hi,

I read a single channel intensities data set in *read.matrix* function 
and proceed a normalization with normalizeQuantiles.

 > y <- normalizeQuantiles(x)

In topTable, I get up and down regulated genes.

topTable showed a M, t, P.Value and B statistics. But, I get the M value 
around 400. In my data set there aren't these values.

When I read the same data with read.exprSet function and proceed a 
normalization with normalizeQuantiles, and proceed a topTable execution, 
I get M, A, t, P.Value and B statistics. The M values are near 400, too.

In another test with the same intensities data, I, in excel, transform 
my intensities datas in log2, set missing values to NA, read it with 
read.exprSet function and proceed a normalization with 
normalizeQuantiles. In this analysis, topTable showed M, A, t, P.Value 
and B statistics. M values is around 3 and P.Value min is 0.0007, but no 
down regulated genes is showed. These results is similar with 
normalization with vsn (with out transformation).

After these results I and my friend are very confused and we don't know 
what we to do! For example, why in the first test, when we use matrix, 
topTable don't return the statistic A and in the next test it returns 
these values? I know that I am wrong, but I am very curious for to know 
what are my mistakes.

My excuses, in advanced, if this doubt is out of the mail list.

Any commentary is very appreciated.

Thanks

Marcelo


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