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!! That reassured... Yes, I am reading it as a phenoData Matrix and using it as vector
Perfect! I have never done DESeq with pairwise comparison but I have used DEXSeq which is almost same as DESeq. I guess you are doing it right. Good luck.