Hi,
I'm using DESeq2 to analyze RNAseq data. The experiment has 18 conditions (3 different neg. controls and 15 different treatments). In the analysis, I plan to compare each treatment with just one of the neg. controls. I execute this through 15 separate calls to results:
ddssva_de <- DESeq(ddssva)
res1 <- results(ddssva_de, c("condition", "treat1", "ref1"))
res2 <- results(ddssva_de, c("condition", "treat2", "ref1"))
res3 <- results(ddssva_de, c("condition", "treat3", "ref1"))
res4 <- results(ddssva_de, c("condition", "treat4", "ref1"))
res5 <- results(ddssva_de, c("condition", "treat5", "ref1"))
res6 <- results(ddssva_de, c("condition", "treat6", "ref2"))
res7 <- results(ddssva_de, c("condition", "treat7", "ref2"))
res8 <- results(ddssva_de, c("condition", "treat8", "ref2"))
res9 <- results(ddssva_de, c("condition", "treat9", "ref2"))
res10 <- results(ddssva_de, c("condition", "treat10", "ref2"))
res11 <- results(ddssva_de, c("condition", "treat11", "ref3"))
res12 <- results(ddssva_de, c("condition", "treat12", "ref3"))
res13 <- results(ddssva_de, c("condition", "treat13", "ref3"))
res14 <- results(ddssva_de, c("condition", "treat14", "ref3"))
res15 <- results(ddssva_de, c("condition", "treat15", "ref3"))
In doing this, I realize that each results set has adjusted p-values (padj) calculated only using the number of comparisons for that specific contrast while in reality, I am making many, many more comparisons with each additional call to "results."
I would like to further adjust the p-values in each of these results (res1 through res15) taking into account the total number of comparisons made across all 15 calls. What would be a good way to accomplish this?
Thank you.
Thanks for your comment Devon. Perhaps this question is really about where to draw the line for "overkill" with respect to adjusting p-values. If, instead of calling results() 15 times on the same DESeqDataSet, I instead split up the data and create 15 separate DESeqDataSets and call DESeq() on each one separately, I can obtain even more permissive adjusted p-values (and hence more significant genes). Where to draw the line?
That's fitting a different model, so the differences are actually do to that.
Ah, yes. You are correct. That helps me think about this problem in a better way. Thank you!