[BioC] VSN: narrowing down probe sets for parameter estimation

[Stefan Thomsen]

Dear all,

I am working on an Affymetrix time series data set with high percentages 
(30-40%) and mostly downregulated differentials.

In a previous discussion regarding the question of a suitable normalization 
strategy for such data sets Wolfgang Huber highly recommended to "narrow 
down the probes from which you fit the parameters from all genes (incl. the 
differential ones) to a subset which are enriched for non-changing."

In this context I have two questions:

1) What is the minimum number of genes/probes that should be used for VSN 
parameter estimation? I could extract a list of some hundred 'stable' or 
'low variability' genes from previous microarray studies. Would this number 
be sufficient or do I need bigger probe subsets (thousands of probes, 1/2 
of all probes, etc.)?

2) Is there a straight foward way to implement this into standard R 
packages offerring VSN? In other words, if I perform a VSN parameter 
estimation on my gene/probe subset, how (in R terms) would I subsequently 
apply this to the whole dataset?(My apologies if this is trivial, my 
programming skills are still rather a disgrace :) )

Any comment on these questions would be highly appreciated.

Kind regards,

Stefan

-- 
Dr. Stefan Thomsen
Research Associate

Department of Zoology
University of Cambridge
Downing Street
Cambridge CB2 3EJ

Tel.: +44 1223 336623 
Fax:  +44 1223 336679

stt26 at cam.ac.uk