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I'm working with a group that had an outside vendor run four Aglient
2-color oligo arrays for two control samples labeled with Cy3 (C1, C2)
and
four mutants labeled with Cy5 (M1, M2, M3, M4).
Array 1: C1 vs M1
Array 2: C1 vs M2
Array 3: C2 vs M3
Array 4: C2 vs M4
The outside vendor sent them four spreadsheets, one for each array,
containing normalized Cy5/Cy3 log-ratios, Cy5/Cy3 fold changes,
sequence
description and p-values. I don't know what they did to calculate a
p-value
for each n=1 comparison on each array like this. The only information
that
the company that did her analysis gave her her about what they did was
that
they "used Rosetta Resolver to export gene list with log ratios, fold
changes, and p-values." But this was done separately for each of the
four
arrays.
My first question: using this arrangement of samples on the arrays, is
it
possible to directly compare all the controls versus all the mutants?
What
about confounding with the dye (there was no dye swap)? Are C1vsM1 and
C1vsM2 true bio replicates because C1 is used in both comparisons
(same
with the C2 vsM3/M4 comparison)?
The vendor sent "raw" data from Agilent Feature Extraction software,
and it
looks like I may be able to read this into R using read.maimages, but
I
couldn't find an annotation package. The platform is a two color
Agilent
array, design #028005. I checked the BioC annotation pages (
http://www.bioconductor.org/packages/release/data/annotation/) and
there
were a few other agilent chips there, but not this one.
The second question: After I run the analysis, I want to annotate the
topTable genes with GO terms and do a GO enrichment analysis. How
might I
go about doing this without an annotation package?
One last unrelated question: is it appropriate to send a relevant job
opening announcement over the mailing list?
Thanks in advance for any help.
Stephen
-----------------------------------------
Stephen D. Turner, Ph.D.
Bioinformatics Core Director
Department of Public Health Sciences
University of Virginia School of Medicine
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