[BioC] 4-color microarrays

[Naomi Altman]

Now after normalization, the question is how to handle the 4 colors per 
spot per array.  I would do single channel analysis using the array as a 
block.  This is described in the Limma Users Guide for 2 colors, and should 
work the same for any number of channels.

Of course, if you have multiple spots per gene or a mix of biological and 
technical replicates you will need a more complex model than limma can handle.

--Naomi

At 01:51 PM 9/9/2005, Henrik Bengtsson wrote:
>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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> >>
> >
> >
> >
> >
>
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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)
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