Entering edit mode
5.5 years ago
grant.hovhannisyan
★
2.6k
I have RNAseq count data of hybrid yeast at three different temperatures. There are counts from both alleles. I want to find DE genes at different combinations of comparisons.
This is how I model the data in DESeq2:
colData<-data.frame(
allele=factor(c(rep("SC",9), rep("SU",9), levels(c("SC","SU")))),
temperature=factor(rep(c(rep("22",3), rep("33",3), rep("37",3)),2)))
dds <- DESeqDataSetFromMatrix(all_temp_data, colData, formula(~allele+temperature+allele*temperature))
Now, for example, if I want to find DE genes between two alleles at 33 degrees, is the following a correct way of doing it?
dds <- DESeq(dds)
results(dds, contrast=list(c("allele_SU_vs_SC","alleleSU.temperature33")), test="Wald")
Thanks
I also don't think your design is right. If you are looking for interactions, and not main effects, I think you do
or
But that's not what you are asking about right now.
Hi swbarnes2, thanks for reply. You are right, I have confused
*
and:
. But given the right design that you mention, could you please elaborate a bit why my solution is not correct (or point out to relevant literature)? I feel that I don't completely understand how design formulas work.