I am finding it a bit hard to comprehend a case where multiple conditions are to be compared and find myself confused with the multifactor part of the DESeq Vignette..

Basically I have four tissues (conditions) and would like to find DE genes for all pairwise comparisons across all conditions. Is the following pairwise comparison approach in DESeq right?

>design
condition    libType
 1            single-end
 1            single-end
 1            single-end
 1            single-end
 1            single-end
 1            single-end
 1            single-end
 1            single-end
 1            single-end
 2            single-end
 2            single-end
 2            single-end
 3            single-end
 3            single-end
 3            single-end
 4            single-end
 4            single-end
 4            single-end
 4            single-end
 4            single-end
 4            single-end


cds <- newCountDataSet( ceiling(RawCountData), conds )
cds <- estimateSizeFactors( cds )
sizeFactors( cds )
cds<-estimateDispersions(cds)

#contrasts for differential expression in DE
 res12<-nbinomTest(cds,1,2)
 res13<-nbinomTest(cds,1,3)
 res23<-nbinomTest(cds,2,3)
 res24<-nbinomTest(cds,2,4)
 res34<-nbinomTest(cds,3,4)

Any better ways of doing it? Also as an extension, I am not sure yet, if the condition 1 and 4 have different time points (which I presume to be, however, I am not interested in time point specificty), will this by any chance change the approach?

Thanks!