[BioC] dye effects stronger than dye-swaps?

[Naomi Altman]

And then again, there is the dye degradation problem.  If one dye 
severely degrades, then you will get a strong positive correlation.

Try plotting R vs R and G vs G, instead of M vs M.

--Naomi

At 03:56 PM 4/30/2007, Paquet, Agnes wrote:
>Hi Jenny,
>
>There are a couple of other things you can check to make sure you 
>have the correct orientation:
>- if this is a mutant vs. control, the investigator probably know 
>about some upregulated/downregulated genes which caracterize the 
>mutant. You can check the sign of the M values for probes 
>corresponding to these genes to determine the correct orientation of 
>the arrays.
>-  If you have access to the actual image of the arrays, 
>differentially expressed probes should show up with different colors 
>on dye-swapped arrays.
>- Also, if the investigator already checked the expression of some 
>of the genes using another method (like taqman), you could use this 
>as a "true" value and check which arrays have the correct dye orientation.
>
>Regards,
>
>Agnes
>
>________________________________
>
>From: bioconductor-bounces at stat.math.ethz.ch on behalf of Jenny Drnevich
>Sent: Mon 4/30/2007 11:36 AM
>To: bioconductor at stat.math.ethz.ch
>Subject: [BioC] dye effects stronger than dye-swaps?
>
>
>
>Hi everyone,
>
>I have an interesting phenomenon in some microarray data, and
>wondered if anyone else has seen anything like it. It's 2-color data,
>comparing mutant vs. wildtype, 2 replicates plus dye-swaps for a
>total of 4 arrays. The 'dye-swaps', instead of being negatively
>correlated in M-values are instead strongly positively correlated,
>even after within-array normalization. I triple checked to make sure
>I didn't have the phenotypic info wrong, but all of the arrays are
>positively correlated, which leads me to believe that dye-swapping
>wasn't actually done. If you analyze as if it were a dye-swap
>experiment, several thousands of genes still show a dye-effect,
>whereas only dozens of genes show a MUvWT effect.
>
>My question: is it possible that any dye-effects could be so strong,
>even after within-array normalization, and treatment differences so
>small that the arrays could be dye-swaps but still show a positive
>correlation in M-values? Or is it more likely that dye-swapping
>wasn't actually done?  I've tried to look at other dye-swapped data,
>but everything I have has large treatment differences. The PI already
>has the manuscript written, and just came to me to 'confirm' their
>analysis, so I want to be pretty positive before I tell them their
>work may have been wasted (of course, they may still decide to ignore me...)
>
>Thanks,
>Jenny
>
>Jenny Drnevich, Ph.D.
>
>Functional Genomics Bioinformatics Specialist
>W.M. Keck Center for Comparative and Functional Genomics
>Roy J. Carver Biotechnology Center
>University of Illinois, Urbana-Champaign
>
>330 ERML
>1201 W. Gregory Dr.
>Urbana, IL 61801
>USA
>
>ph: 217-244-7355
>fax: 217-265-5066
>e-mail: drnevich at uiuc.edu
>
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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111