[BioC] Replicate data and p-values

[Mike Schaffer]

I'm fairly new to Bioconductor and had a basic question about  
*recommended* steps to analyze replicate data.  I apologize if this has  
been covered, but I've scoured the message archives and couldn't find  
any examples to guide me.

I'd like to look at 3 biological replicates of treated vs. untreated  
cells and determine p-values for over- or under-expression of each  
gene.  We're using in-house spotted long oligo two-color microarrays  
and scanning with GenePix.

I've read in my experiment layout, gal file, and gpr data using:
------------------------------------------------------------------------ 
-
exp.layout<- 
read.marrayLayout(fname=galfile,ngr=8,ngc=4,nsr=21,nsc=20,skip=37,ctl.co 
l=6);
exp.targets<-read.marrayInfo(fname=layoutfile)
exp.genes<-read.marrayInfo(fname=galfile,labels=4,skip=37)
exp.raw<-read.marrayRaw(fnames,path=datadir,exp.Gf="F532  
Median",exp.Gb="B532 Median",exp.Rf="F635 Median",exp.Rb="B635  
Median",exp.W="Flags",skip=30,layout=exp.layout,gnames=exp.genes,targets 
=exp.targets)
       :
       :
other filtering here
       :
       :
exp.norm <- maNorm(exp.filtered,n="s")
------------------------------------------------------------------------ 
-

I've also generated LOWESS normalized data by spotting pin and now  
would like to determine the significance of changes I see.  I've seen  
limma and multtest for doing this but have been unable to determine if  
these functions are compatible with how I've imported my data or how to  
call them correctly.

Can anyone point me in the right direction given that I have my  
filtered/normalized data from the three runs in a variable called  
exp.norm?  Also, should I normalize ACROSS arrays in addition to within  
arrays prior to the p-value calculation?  What syntax is used for this?

Thanks.

--
Mike Schaffer