[BioC] [Limma] Correcting Dye swap effect

[Naomi Altman]

The simplest way to detect dye effects is to plot M vs M on 
dye-swapped arrays.
These should have negative correlation.  If there is an X on the 
plot, you have lots of dye bias.

The main causes I have seen for this are:

1) bad dye batches
2) ozone degradation of Cy5

Personally, I would not trust a statistical correction under these 
circumstances.

On the other hand, if only a few genes are affected (as you would 
detect from a statistical rather than graphical analysis),
probably correcting for the dye effect is OK.  The effect is then 
likely due to the dye chemistry, not external factors.

--Naomi

At 03:30 AM 11/20/2005, Ron Ophir wrote:
>Hi,
>In Chapter 8.1.2 in Limma users guide there is a description how to
>detecting the Dye effect.
>The example there describes an experiment of Wt vs Mut with two dye
>swaps replicates as follow:
>
>FileName Cy3 Cy5
>File1        wt mu
>File2        mu wt
>File3        wt mu
>File4        mu wt
>
>Let's say that I found a list of gene which are significant due to
>mutant effect and due to dye effect as well. Can I only ignore them or
>can I correct the dye effect?
>I guess that it depends how the dye swaps replicates was prepared. If
>the dye replicates are technical replicates using the block design is
>enough to correct dye effect. If dye replicates are also biological
>replicates they night also represent a batch effect. That is all first
>replicates was sent in one day and the second replicates sent in another
>day, which this difference by itself without dye swap may be a source
>for variation. The second option of dye swap preparation may be
>corrected by ANCOVA (?). Is possible to do it with LIMMA? I know that a
>question about using ANCOVA with LIMMA arose by Naomi Altman but this
>discussion was beyond my knowledge. So back to my questions: Is
>correcting the dye effect is possible in LIMMA? Is ANCOVA is a solution?
>and HOW?
>
>I hope these questions are in the focus of that mailing list,
>Thanks
>Ron
>
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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