SEQanswers - Biological and technical replicates in expression analysis (DESeq)

Hi,

I've to analyze several RNA-Seq samples. I've samples from several runs, unstraned and straned, and several samples sequenced multiple times ( using different library kit ). I used htseq-count to have the read counts and want now to use DESeq to check for differential expression. So I've biological replicates and technical replicates (same sample sequences several times using a different lib kit. Is that correct ?).

So I did a design matrix. In my example, A.1 means sample A, sequencing 1. A.2 : sample A, sequencing 2,... So A is sequenced two times (One unstranded, one stranded), B three times (One unstranded, two stranded), C one time (one unstraned) and D one time (one stranded). ReplicateGroup is used to put together technical replicates.

Code:

designTable : 

Sample      Condition  Stranded   ReplicateGroup

A.1         Ctrl          No             A

B.1         Treated       No             B

C.1         Treated       No             C

A.2         Ctrl          Yes            A

B.2         Treated       Yes            B

B.3         Treated       Yes            B

D.1         Treated       Yes            D

After that I use DESeq. countTable is the read count matrix.

Code:

cdsFull = newCountDataSet( countTable, designTable )

cdsFull = estimateSizeFactors( cdsFull )

cdsFull = estimateDispersions( cdsFull )

But now I don't know how to fit a model o

n "condition" "stranded" and "replicateGroup".

like that ?

Code:

fit1 = fitNbinomGLMs( cdsFull, count ~ Condition + Stranded + ReplicateGroup )

fit0 = fitNbinomGLMs( cdsFull, count ~ Condition )

pvalsGLM = nbinomGLMTest( fit1, fit0 )

padjGLM = p.adjust( pvalsGLM, method="BH" )

Is it the good way to analyze technical replicated. I read that I have to merge them together.. but I don't think it's a good idea due to the fact that I use different library kits. So I'm stuck...

Thanks a lot in advance

N.