[BioC] How to cope with arrays hybridized at significantly different time.

[Steve Lianoglou]

Hi,

> In hospital-studies most of the time we get more than 200 arrays per
> study.It is evident that the arrays have significant differences  
> among them
> due to different array batch and many other conditions ie technical
> competence, hybridization difference due to time span , circadian  
> rhythm ,
> fresh sample or not->different time from RNA extraction to  
> hybridization ,
> and others. How can we cope with the many uncontrollable factors and  
> be able
> to use 80 , 200 or even a higher number of arrays at the same analysis
> fixing for any of the uncontrollable effects.


This isn't really a direct answer, but perhaps it can lead you to some  
helpful information.

Rafael Irizarry gave a talk at our uni near the end of last year, and  
I remember he made mention that he's found that it's easier to predict  
which lab a microarray comes from than it is to predict which tissue  
it comes from using the gene expression profiles (this is serious  
paraphrasing, and perhaps a gross over representation of what he  
really said).

Anyway, if I remember correctly, he mentioned this in the context of  
talking about his work for the gene expression barcode paper, which  
might be a good read to get you thinking about these problems:

http://www.nature.com/nmeth/journal/v4/n11/full/nmeth1102.html

He also spoke of frozen RMA, which I believe essentially normalizes  
new chips against a (potentially very large) compendium of already  
normalized ones. I'm not sure that it's officially available yet, but  
his grad student (Matthew McCall) at least lists it w/ an R  
implementation here:

http://biostat.jhsph.edu/~mmccall/research.html

So, no real answers here, just some food for thought that might give  
you some ideas.

Hope that helps,
-steve

--
Steve Lianoglou
Graduate Student: Physiology, Biophysics and Systems Biology
Weill Medical College of Cornell University

http://cbio.mskcc.org/~lianos