I've a small question concerning the differential expression analysis in DESeq2. So I've a 16 samples divided into 4 groups (control, ko1, ko2 and ko3 ). so one condition with 4 levels
as i understood form the vignette and previous questions regarding this matter here that performing wald statistics and separata pairwise comparisons would be the best options.
i am using a code like this one:
dds1 <- DESeqDataSetFromHTSeqCount(sampleTable=samples,directory="./",design= ~ condition) dds1 <- DESeq(dds1) res <- results(dds1)
Then pairwise comparison res.ko1 <- results(dds1, contrast=c("condition","ko1","ctrl")) res.ko2 <- results(dds1, contrast=c("condition","ko2","ctrl")) res.ko3 <- results(dds1, contrast=c("condition","ko3","ctrl"))
Now my question is, is it possible in DESeq to get a compined file of the significant DEG in the three cell types containing mainly how is the fold change is. somthing like a list with significant genes and the fold change in each level/ko.
Many thanks in advance