[BioC] Extracting Single Channel Intensities in limma

[michael watson (IAH-C)]

I'm not sure I told you enough about the experimental design to get this
right, so if we want to explore this using contrast matrices, I better
add the little detail that might make things more complicated.  

Although I can assume all my negative samples are replicates of the same
thing, I can't assume that all my positive samples are.  It's a *very*
strange experiment, but I have 8 +ve phenotype samples and they are NOT
replicates of one another.  So I actually have a factor with nine levels
(the 8 +ve phenotypes and the control) all against a common reference,
which is the -ve phenotype.  To complicate things further, sometimes the
-ve is labelled Cy5, sometimes Cy3, and only two of the +ve phenotypes
have replication, in the form of a single dye-flip.

This is why I really wanted to extract the single channels and then
construct "dummy" microarray experiments ;-)

-----Original Message-----
From: Sean Davis [mailto:sdavis2 at mail.nih.gov] 
Sent: 01 October 2004 14:08
To: michael watson (IAH-C)
Cc: Bioconductor
Subject: Re: [BioC] Extracting Single Channel Intensities in limma



On Oct 1, 2004, at 8:50 AM, michael watson (IAH-C) wrote:

> You tell me, contrast matrices are a black art when it comes to 
> complicated experiments.
>
> What I have are two conditions, +ve and -ve, and a control.  The 
> design of the experiment is rather odd.  I have arrays that are:
>
> -ve / +ve
> -ve / +ve
> -ve / +ve
> Etc
> Etc
> -ve / Control
>
> What I want are:
>
> -ve / Control
> -ve / Control
> Etc
> +ve / Control
> +ve / Control
> Etc
>
> I figured that by using the methods decsribe in limma, I could 
> subtract the single channel intensity data, and completely re-arrange 
> the experiment such that all of my -ve and +ve values have the control

> as the denominator.
>
> I have no idea if this kind of complex re-arrangement can be done with
> a
> contrast matrix.
>

Perhaps others will help us out also, but it seems to me that you have 
a common reference design, with -ve being the common reference?  If so, 
then you can refer to the limma user guide for direct guidance.  
Following the procedure for making the design matrix in the Guide, you 
will end up with a design matrix with two columns:  positive and 
Control.  The Control coefficient is Control/-ve.  The +ve coefficient 
is looking at +ve/-ve.  If you want -ve/Control and +ve/Control, you 
can specify the contrast matrix as:

makeContrasts(1-Control,positive-Control,levels=design)

This is untested, and I'm no expert, but does it give you what you want?

Sean