[BioC] how to design model in DESeq

[wang peter]

dear all:
       i have a question how to design model  in DESeq.

my data is composed of 35 samples, have two factor
time and treatment

i want to find DE genes cross the time, considering control
how to design the model?
such is my coding.

counts <- read.table("expression-table.txt",row.names=1)
design<- data.frame(row.names=colnames(counts), treatment=
c(rep('control',6),rep('treated',24),rep('control',5)), time=
c('0h','0h','0h','24h','24h','24h','0h','0h','0h','6h','6h','6h','6h','12h','12h','12h','12h','18h','18h','18h','18h',
             '24h','24h','24h','36h','36h','36h','48h','48h','48h','6h','12h','18h','36h','48h'))
cds <- newCountDataSet(counts, design

cds <- estimateSizeFactors(cds)
cds <- estimateDispersions(cds)
fit1 <-fitNbinomGLMs(cds, count ~ treatment + time)
fit0 <-fitNbinomGLMs(cds, count ~ treatment)

pvalsGLM <-nbinomGLMTest(fit1, fit0)
padjGLM <-p.adjust(pvalsGLM, method = "BH")

-- 
shan gao
Room 231(Dr.Fei lab)
Boyce Thompson Institute
Cornell University
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