[BioC] normalizeQuantiles : log2 or not??
Marcelo Luiz de Laia
mlaia at fcav.unesp.br
Thu Feb 17 13:37:50 CET 2005
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
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.
Marcus Davy escreveu:
>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.
> 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.
>>>>Marcelo Luiz de Laia <mlaia at fcav.unesp.br> 17/02/2005 2:08:15 PM >>>
>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.
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