How to calculate overlap between transposable elements differentially expressed in one experiment, with those expressed in another set of samples?
1
0
Entering edit mode
@rodrigoduarte88-16306
Last seen 4 months ago
United States

Dear all,

I've got a naive question for you, and I would really appreciate your thoughts.

I found some transposable elements (TE) that were differentially expressed in a certain tissue, based on a case-control analysis of RNA-seq data using DESeq2, and a custom-made annotation for TEs. Now, I would like to investigate whether those differentially expressed TEs are expressed in a different tissue, for which I've already obtained raw TE counts in 20 control samples. In this part of my analysis, all samples are part of the same group, so I am not sure how to go on to obtain normalised read counts, to then establish a "basal expression cut-off" and calculate the overlap with TEs differentially expressed in my previous analysis. How do I do this? How do I calculate this overlap? (Would this be a simple overlapping test (e.g., R package "GeneOverlap"), or some hypergeometric probability?)

I found R libraries like TissueEnrich which allow me to match genes of interest to publicly available data, but the TE expression I am interested is not on these databases.

Any ideas?

gene expression enrichment RNA-seq DESeq2 • 383 views
ADD COMMENT
2
Entering edit mode
@mikelove
Last seen 1 hour ago
United States

You have a set of TEs that are DE and you want to see if they are expressed in another tissue. You have 20 samples of this other tissue, and TE counts for those 20 samples.

If I were doing this project, I would start by looking at the histograms of normalized counts for each TE. Then you have to introduce an arbitrary distinction, which is "expressed". Because we have limited sequencing depth, it's possible that the TE is expressed but you still get a count of 0. So then you can fudge a bit and say "expressed" is sufficiently expressed to observe counts above a minimal threshold given your sequencing depth.

ADD COMMENT
0
Entering edit mode

Fantastic! Thanks, Michael! Just one more quick question (for peace of mind): I am using the "~1" design to create this dds object to extract the normalised counts, since I have no groups, right?

ADD REPLY
0
Entering edit mode

Yes that is correct.

ADD REPLY

Login before adding your answer.

Traffic: 360 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