DESeq2 for TRAP-seq methods
1
0
Entering edit mode
marypiper • 0
@4ba24ed8
Last seen 10 days ago
United States

Hi,

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,

Mary

DESeq2 TRAP-seq • 94 views
ADD COMMENT
1
Entering edit mode
@mikelove
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.

ADD COMMENT
0
Entering edit mode

Thanks so much for your quick reply!

Best, Mary

ADD REPLY

Login before adding your answer.

Traffic: 504 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6