[BioC] normalizeQuantiles : log2 or not??

[Marcelo Luiz de Laia]

I almost had conviction of that topTable must not have the value "A" 
because I am analyzing single channel intensities. But, I didn't was 
security.
But, when I read my intensities in a exprSet object and normalize it 
with vsn and use limma to check the DE genes, topTable returns the value 
"A". This is not a problem for me. I would like to have security that 
the showed DE genes in topTable are correct, in this case.

Thanks

Marcelo


Marcus Davy escreveu:

>Hi,
>the reason topTable in the limma package didnt provide the statistic A is because you fed in a matrix of *M* values, not an 
>MAList object. Without the A matrix encapsulated within the MAList object, *unweighted* average A values cannot be calculated.
>
>e.g.
> if (length(object at maA)) 
>            fit$Amean <- rowMeans(unwrapdups(object at maA, ndups = ndups, 
>                spacing = spacing), na.rm = TRUE)
>
>Try looking at your channel densities with plotDensities in the limma package. Do the densities look highly right skewed?
>Usually limma analysis is on log2 transformed data.
>
>
>Marcus
>
>
>  
>
>>>>Marcelo Luiz de Laia <mlaia at fcav.unesp.br> 17/02/2005 2:08:15 PM >>>
>>>>        
>>>>
>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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