DESeq2 for TRAP-seq methods
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marypiper • 0
Last seen 10 days ago
United States


I am working to perform a TRAP-seq analysis, and I am struggling with a decision on what is the best method for analysis. Assuming a standard TRAP-seq analysis as described in the following table:

                assay      treatment    ind     ind_n
sample1_IP    | IP       | control    | 1     | 1
sample1_input | input    | control    | 1     | 1
sample2_IP    | IP       | control    | 2     | 2
sample2_input | input    | control    | 2     | 2
sample3_IP    | IP       | control    | 3     | 3
sample3_input | input    | control    | 3     | 3
sample4_IP    | IP       | treated    | 4     | 1
sample4_input | input    | treated    | 4     | 1
sample5_IP    | IP       | treated    | 5     | 2
sample5_input | input    | treated    | 5     | 2
sample6_IP    | IP       | treated    | 6     | 3
sample6_input | input    | treated    | 6     | 3

Without having read any of the literature on the analysis, I thought that I could look for the differences in IP vs. input on the effect of treatment. However, since in TRAP-seq the IP and input are paired by sample, I thought that we should use a paired design, such as: ~ assay + treatment + treatment:ind_n + treatment:assay. Upon talking with the researcher, they were expecting a t-test, which didn't seem the best method to me, but my statistical background is quite limited, so I started looking through the literature. I feel like I have found just about everything, including t-test. I see support for the use of assay + treatment + treatment:assay from this protocols paper, which is relatively recent and seems reasonable with good documentation. However, I am uncertain why there is no inclusion of the paired design.

My main question is whether DESeq2 is still recommended and accurate for determining translational efficiency? And if so, should I be correcting for the paired nature of the samples. Are there other considerations in this specific type of data that would make this not the best method of analysis. I am sorry if there is something key that I am missing.

Thank you for your time and help,


DESeq2 TRAP-seq • 94 views
Entering edit mode
Last seen 1 hour ago
United States

Right, it seems that protocols is following the guidance from this post, which I wrote without considering datasets where there may be per-sample structure within treatment.

You could use your first design to additional account for per-sample variation, and that looks like what I would use if that structure was present.

Entering edit mode

Thanks so much for your quick reply!

Best, Mary


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