[BioC] 4-color microarrays

[Henrik Bengtsson]

A.J. Rossini wrote:
> Interesting -- does anyone know if you need to "compensate" for 4-color? (I 
> know that you _sometimes_ have to for 4-color flow cytometry)
> 
> best,
> -tony

Most likely, yes!  Use affine normalization to do it.  It works for two 
or more channels.  I've got all methods implemented in aroma (search 
google), but I'm about to release a lightweight version of this called 
aroma.light.  For the moment see the below tech report (another version 
submitted) at http://www.maths.lth.se/bioinformatics/publications/:

H. Bengtsson and O. Hössjer, Methodological study of affine 
transformations of gene expression data with proposed normalization 
method, Preprints in Mathematical Sciences 2003:38, Mathematical 
Statistics, Lund University, 2003.

Quantile normalization a la RMA (Affy) would also do, but has more 
degrees of freedom compared to the 2*nbrOfChannels-1 parameters for 
affine normalization.

> On 9/9/05, hdvi <hdvi at well.ox.ac.uk> wrote:
> 
>>Hi
>>
>>We're currently beginning to use microarrays with 4 colors, and I was
>>wondering whether anyone out there had any experience analyzing those
>>using Bioconductor?
>>
>>I've previously used limma for normal microarray analysis and also for
>>arrays with just 1 dye. I've been quite happy with that, but it appears
>>that if I want to continue with that I have to e.g. split the data from
>>each array into two 'pseudo-arrays', which isn't exactly optimal. I
>>won't be doing expression analysis, but I'll need functions for
>>normalizing the data etc. Has anyone tried something similar?

You suggests something like cyclic lowess (since curve-fit normalization 
operates on paired channels by definition).  It has been implemented 
elsewhere, but I suggest to look into affine normalization for this, 
because it is much more natural/intuitive.

Cheers

Henrik

PS. I'm going to MGED in Norway soon, so I'll be online less often. DS.

>>
>>Thanks in advance
>>\Heidi
>>
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> 
> 
> 
>