I believe that one needs to know the exact amount/quantity of either the
i.  tissue sample (if you spike before RNA extraction)
ii.  mRNA in the extracted sample (if you spike after RNA extraction)

In case i. the RNA extraction efficiency should also be constant.
In case ii. the the ratio of mRNA to spiked RNA needs to be constant. In a 
crude RNA extract the mRNA content varies between 2-5 %. I'm afraid that 
the exact quantification of the mRNA is not so easy.

Best regards,
Martin








Naomi Altman <naomi@stat.psu.edu>
Sent by: bioconductor-bounces@stat.math.ethz.ch
08.09.2006 15:32

 
        To:     Gordon Smyth <smyth@wehi.EDU.AU>, "Dan Swan" 
<bioinformatics.lists@gmail.com>
        cc:     bioconductor@stat.math.ethz.ch, (bcc: Martin Schumacher/PH/Novartis)
        Subject:        Re: [BioC] BioC normalisations for small array 2 colour data?
        Category: 



Spiking in normalization control probes can also be problematic, as 
the RNA samples have to be equalized before spiking.
This can, I think, be done when the tissues from which the RNA is 
extracted are very similar, and the extraction protocol is very
uniform.  Otherwise, spiking variation just gets added to all the 
other sources of variation.

--Naomi

At 08:07 AM 9/8/2006, Gordon Smyth wrote:
>Dear Dan,
>
>At 08:00 PM 8/09/2006, bioconductor-request@stat.math.ethz.ch wrote:
> >Date: Thu, 7 Sep 2006 13:44:35 +0100
> >From: "Dan Swan" <bioinformatics.lists@gmail.com>
> >Subject: [BioC] BioC normalisations for small array 2 colour data?
> >To: bioconductor@stat.math.ethz.ch
> >
> >Hi,
> >
> >I have some data from a small specialised microarray - 200 genes, 1
> >spiked control, 1 negative control.  This is 2 colour data, with dye
> >swaps.  I was wondering what an appropriate normalisation for this
> >scenario is within Bioconductor given that Lowess is unreliable for
> ><1000 genes?
>
>Are you quoting someone when you say that lowess is unreliable for
><1000 genes? Who? Print-tip loess normalization is routinely applied
>to arrays with around 200 genes in each print-tip group so 200 genes
>is, far from being unusual, pretty much typical for loess normalization.
>
>The real problem with a specialised microarray is the fact that the
>genes are not randomly chosen, indeed they are typically chosen
>because of their likelihood to be differentially expressed. Hence you
>may be in a situation where the majority of genes may be
>differentially expressed. If that is your case then, in my opinion,
>normalization control probes need to be designed into the array in
>the first place to produce reliable results.
>
>Best wishes
>Gordon
>
> >Any pointers would be gratefully recieved.
> >
> >thanks,
> >
> >Dan
> >
> >--
> >Senior Research Associate, Bioinformatics Support Unit,
> >Institute for Cell and Molecular Biosciences,
> >Faculty of Medical Sciences, Framlington Place,
> >University of Newcastle upon Tyne,
> >Newcastle, NE2 4HH
> >Tel: +44 (0)191 222 7253  (Leech offices: Rooms M.2046/M.2046A)
> >Tel: +44 (0)191  246 4833 (Devonshire offices: Rooms G.25/G.26)
> >Website: http://bioinf.ncl.ac.uk/support/
>
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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)
University Park, PA 16802-2111

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