I am trying to perform DGE analysis for a time series data. I am using DESeq2 for the analysis.
Upon searching the closes match I can get to what I am trying to do is here:
I went through the latest vignette and not able to correlate what was explained earlier with the last version.
I have samples from 4 time points (age). Each time point has at least 3 replicates. The experiment is as follows
SampleID Age Sample_41 6M Sample_42 6M Sample_44 6M Sample_45 12M Sample_46 12M Sample_47 12M Sample_48 18M Sample_49 18M Sample_50 18M Sample_51 18M Sample_52 21M Sample_53 21M Sample_54 21M
What I want to get is LFC and qvalues for geneX across the 4 time points. So this way we can determine genes that are not constant, LFC changed as per age or dropped.
If I want to compare with 6 months as ref, that is easy
ddsMat_MouseAge<-DESeqDataSetFromMatrix(MouseAge,expSummary_MouseAge,~Age) ddsMat_MouseAge$Age <- relevel(ddsMat_MouseAge$Age, ref = "6M")
But this is NOT what I want.
Do i need to perform "contrast" with each combination and then perform a union?
res <- results(dds,contrast=c("Age","M6","M12")) save the output, then the next comparison. res <- results(dds,contrast=c("Age","M12","M18")) and likes?
At the seqAnswer link (see top) the code suggested was:
results(dds, contrast=list("6M", c("12M","18M","21M")), listValues=c(1, -1/3))
Repeat above for each age: 6M, 12M,18M,21M
Does this also hold true now with the latest version of DESeq2? If you can also explain the listValues part that as I don't get it.