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

[John Fowler]

Gordon Smyth <smyth at ...> writes:
> 
> 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 unpublished studies in my own group.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




HI Gordon,
thank you for the reply.

Any advice in this situation as to the use of Aquantile normalization
(vs. no between arrays normalization) on the data set when analyzing 
it using lmFit in the two channel situation?  I have done the analysis 
both with and without the Aquantile, and I end up with more significantly
different probes =with= Aquantile.

regards,
John 




> >From: John Fowler <fowlerj at ...>
> >Subject: [BioC] Suitability of normalizeBetweenArrays? - arrays with
> >         very    different characteristics


> >Hello all,


> >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
> >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
> >unsure of that, as well.

> >thank you very much,

> >John Fowler
> >Associate Professor
> >Oregon State University