[BioC] Questions about clusterization from the newbie

[tiv_]

Hello, All!
First I'd like to thank all people who are working on
Bioconductor project - you are doing great job!

I'm new to this  list, to R,  to all that biocondactor things, and
actually to the statistics it self... so please
excuse me if I'll ask smith trivial.
I'm doing the clusterization of the microarray data. Here is the
example of my routine
sample.files<-c("1.cel","2.cel","3.cel","4.cel")
sample.names<-c("1.cel","2.cel","3.cel","4.cel")
data<-ReadAffy(filenames=sample.files)
data_rma<-rma(data)
write.exprs(data_rma, file="data_norm_rma.txt")
x<-read.delim("data_norm_rma.txt")

# strange, but mt.teststat(data_rma,data.c) its not working
# without  writing and reading back, is it ok?

data.c<-c(0,0,1,1)
teststat<-mt.teststat(x,data.c)
rawp0<-2*(1-pnorm(abs(teststat)))
procs<-c("Bonferroni")
res<-mt.rawp2adjp(rawp0,procs)
adjp<-res$adjp[order(res$index),]
which<-mt.reject(adjp,0.01)$which[,2]
results<-table2[which,2] #table2 is the annotation table
saveText(results,"sorted_bonf.txt")

As a result I have a list of genes that changed their expression. Can
you give me a hint how can I separate "up regulated" from "down
regulated", must be smiting with t-statistics?

Also I wonder is there any opportunity to cluster .res files? I mean
something like this:
1000_at 75.5    P       447.75085       P       166.3828        P       147.51279       P
1001_at 6.3     A       34.502922       P       48.250244       P       16.545227       A

I tried just to move out all columns with A&P  and use the result as
sours for mt.teststat(x,data.c), but... seems that it's not the right
way.

I'll be happy to read any comments on all this :)

Thanks for your attention,

Tanya