Hi Paolo,

Indeed SAM is unable to deal with data sets in which you have single 
arrays for one or more of your experimental conditions.

Have you considered using the 'plgem' package for addressing your 
issue? You could use it to fit an error model on your set of 5 
controls, and to predict data variability also on your single treatment 
array.

To use it, you first have to convert your data into an 'exprSet' object 
with a special type of 'phenoData' slot. For the functions to correctly 
interpret your experimental design, you simply will need to have one of 
your covariates named 'conditionName'. Then assign the value e.g. 
'control' to each of your 5 controls and e.g. 'treatment' to your 
remaining chip. Of course you can use the value of your choice, you 
only have to consistently assign the same value to replicates of a same 
experimental condition (though they have to be distinct for distinct 
conditions!).

Read the vignette for other details and let me know how it worked for 
you!

Good luck!
Norman

Norman Pavelka
Department of Biotechnology and Bioscience
University of Milano-Bicocca
Piazza della Scienza, 2
20126 Milan, Italy

Phone: +39 02 6448 3556
Fax: +39 02 6448 3552

On 19 Aug 2005, at 12:00, Paolo Sirabella wrote:

> From: "Paolo Sirabella" <psirab@libero.it>
> Date: 18 August 2005 14:48:03 GMT+02:00
> To: <bioconductor@stat.math.ethz.ch>
> Subject: [BioC] Siggenes: How to deal with one treatment - five 
> controls problem?
>
>
> Hi,
> I have a very raw question ...
> The following refers to a subset of a more complex data-set: I have 5 
> affy
> arrays (controls: A,B,C,D,P2), corresponding to 2 donors (A,B,C,D) and 
> a
> pool of other 4 different donors (P2). Besides, I have ONE SINGLE ARRAY
> (treatment: P4) corresponding to a pool of 4 donors (two of them are 
> the
> same of the P2 array).
>
> Summarizing: (controls: A,B,C,D,P2) (treatment: P4)
>
> I know, it is a very poor data-set .. but I need to analyze it the 
> same .. I
> planned to use siggenes (two class unpaired), but, correctly, a warning
> popped-up with the message that 'Each group must consist of at least 
> two
> samples.'
> Now I am spending my holidays - yes, working at microarray analysis! - 
> and I
> am far from my lab, from the library and from my handbooks.
>
> Which is, in this case, the more appropriate approach (excluding the
> hypothesis, up to now, of expanding the data-set ..)?
>
> Thank you in advance, and sorry for the .. raw question.
>
> Paolo Sirabella
> psirab@libero.it
>

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