[BioC] Suitability of normalizeBetweenArrays? - arrays with very different characteristics

[Gordon Smyth]

Dear Martin,

Considering that this discussion is about normalizeBetweeenArrays, 
the first port of call for enlightenment should be:

?normalizeBetweenArrays

Best wishes
Gordon

At 04:09 PM 24/04/2007, martin.schumacher at novartis.com wrote:
>Dear Gordon,
>
>What is Aquantile?? Can you give us some enlightment?
>
>Best,
>Martin
>
>
>Gordon Smyth <smyth at wehi.EDU.AU>
>Sent by: bioconductor-bounces at stat.math.ethz.ch
>24.04.2007 02:10
>To John Fowler <fowlerj at science.oregonstate.edu>
>cc bioconductor at stat.math.ethz.ch
>Subject [BioC] Suitability of normalizeBetweenArrays? - arrays with 
>very different characteristics
>
>Dear John,
>
>You do need to normalize between arrays if you want to do a single
>channel analysis. It is true that normalization is more difficult if
>there are very large differences between samples, but you have to do
>the best you can. I personally use Aquantile in most cases, based on
>unpublished studies in my own group.
>
>Best wishes
>Gordon
>
> >Date: Sun, 22 Apr 2007 03:07:55 +0000 (UTC)
> >From: John Fowler <fowlerj at science.oregonstate.edu>
> >Subject: [BioC] Suitability of normalizeBetweenArrays? - arrays with
> >         very    different characteristics
> >To: bioconductor at stat.math.ethz.ch
> >
> >Hello all,
> >
> >I am looking for advice on whether it is suitable to use
> >normalizeBetweenArrays
> >(in limma) in my two-color array experiment.  Secondarily, if it is NOT
> >appropriate, would that also preclude doing a single channel analysis of my
> >data?  It seems that the User's Guide indicates that some form of 
> normalizing
> >between arrays is recommended before doing the single channel analysis.
> >
> >I have a 3x2 loop design, with three different developmental stages & two
> >different genotypes, four replicates each.  I am using spotted long oligo
> >arrays, two colors.  Because the two genotypes have very few expression
> >differences between them, but two of the developmental stages appear
> >to be VERY
> >different, the results on my arrays are also different.  On arrays
> >in which the
> >same developmental stage, but different genotypes, are used, the data are
> >primarily clustered around M=0, distributed along the A axis.  And,
> >as you would
> >expect, when the very different developmental stages of the same 
> genotype are
> >used, the amount of variation in M (and presumably in A, as well, although
> >that's more difficult to see) is obvious in the plots.
> >
> >So, is it in-advisable to use normalizeBetweenArrays in this case?  My best
> >guess as to the most appropriate method to use would be 
> "Aquantile", but I am
> >unsure of that, as well.
> >
> >I would be happy for suggestions on these questions -
> >
> >thank you very much,
> >John
> >
> >John Fowler
> >Associate Professor
> >Oregon State University