Question: DESeq2 LFC thresholding strategy and its affect on p-value adjustment
gravatar for ivn25
8 weeks ago by
ivn2510 wrote:

Dear all,

I am not a statistician and my knowledge of statistics in limited. I have been working on a project where we used RNA seq, and analysed the results with DESeq2 method. I have been experimenting with log 2 fold change thresholding and noticed that p values change whether I set the threshold for lfc inside the results function or I do thresholding manually afterwards. To make it more clear, this is the code I used:


res<- results(dds,
                          contrast = c("treatment", "AICAr", "ctrl"),
                          lfcThreshold = 1, alpha = 0.05)


res<- results(dds,
                          contrast = c("treatment", "AICAr", "ctrl"))
res <- res[abs(res$log2FoldChange) > 1 & padj < 0.05, ]

First strategy seems very conservative - give much larger p-values, and much smaller number of genes that are significantly different. Can someone explain why is this so? Also, what do you think is the better approach?

ADD COMMENTlink modified 8 weeks ago by andres.firrincieli960 • written 8 weeks ago by ivn2510
gravatar for andres.firrincieli
8 weeks ago by
andres.firrincieli960 wrote:


here is the answer: link

Hope this helps

ADD COMMENTlink written 8 weeks ago by andres.firrincieli960
Please log in to add an answer.


Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 1039 users visited in the last hour