Question: DESeq2 paired comparison, unexpected results
0
gravatar for staaln
5 months ago by
staaln0
staaln0 wrote:

I am trying to understand some results from DESeq2. The experiment is as follows: Before and after treatment for 11 individuals. The most significant gene has the following counts: (Before treatment, after treatment) (0,0) (1298,0) (0,0) (0,0) (0,0) (0,0) (0,0) (0,0) (0,0) (0,0)(0,0) (so all individuals have zero counts only, except from the second individual, who has 1298 counts before treatment). The p-value from DESeq2 is: 1.49e-21 (using the default Wald test). Here I have used the DESeq vignette instructions for doing paired comparisons, putting individual (a factor variable) and treatment (before/after) (factor variable) in the colData and specified design = ~ Individual+Treatment. The estimated dispersion is 22. With such a large dispersion estimate it is counterintuitive to me that the p-value becomes so small. When I use the likelihood ratio test (LRT) the gene does not become significant (p=0.41), which makes much more sense to me.

deseq2 • 97 views
ADD COMMENTlink modified 5 months ago by Michael Love25k • written 5 months ago by staaln0
Answer: DESeq2 paired comparison, unexpected results
0
gravatar for Michael Love
5 months ago by
Michael Love25k
United States
Michael Love25k wrote:

I'd recommend LRT for a design like this, where you have many nuisance coefficients to control for.

ADD COMMENTlink written 5 months ago by Michael Love25k
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 16.09
Traffic: 119 users visited in the last hour