[BioC] Using RMA normalization on 3 microarray replicates - valid?

[Steve Lianoglou]

Hi,

I'd just like to ask for a point of clarification here:

On Thu, Apr 1, 2010 at 4:46 PM, Kaitlin Louise Bergfield
<kshupe at email.arizona.edu> wrote:
> Hello,
>
> We are using Affymetrix Drosophila microarrays to investigate central
> nervous system gene expression profiles at eight timepoints spanning
> metamorphosis.  Each of the eight timepoints consists of three biological
> replicate samples.  Unfortunately, our final eighth timepoint had to be
> hybridized to version 2.0 arrays, while all our other samples were
> hybridized to version 1.0 arrays.  We have found no way to normalize these
> 24 samples all together.  I have attempted to use RMA normalization on the 3
> replicates from the final timepoint, but find when I do this that I end up
> with vast numbers of identical values in the dataset.

[snip]

> I have been using the following code:
>
> cels <-dir("F:/Restifo Lab/Microarray files/A1 files",
> pattern=".*.CEL", full.names=TRUE)
> batch <- ReadAffy(filenames=cels)
> eset <- rma(batch)
> datamatrix <-exprs(eset)

The "vast numbers of identical values in the dataset" you mention, do
you mean that the numbers across the rows in `datamatrix` are
identical? Or do you mean that *all of the numbers* are quite similar?

Also, I've been working with *-seq data for a while so I forget, but
after the data is rma normalized, are the expression values returned
in log-space or no? (Are the numbers in `datamatrix` in the 2-14
range, or in the 1000's range?)

-steve

-- 
Steve Lianoglou
Graduate Student: Computational Systems Biology
 | Memorial Sloan-Kettering Cancer Center
 | Weill Medical College of Cornell University
Contact Info: http://cbio.mskcc.org/~lianos/contact