Question: How to calculate overlap between transposable elements differentially expressed in one experiment, with those expressed in another set of samples?
0
gravatar for rodrigo.duarte88
9 months ago by
rodrigo.duarte8820 wrote:

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?

ADD COMMENTlink modified 9 months ago by Michael Love26k • written 9 months ago by rodrigo.duarte8820
Answer: How to calculate overlap between transposable elements differentially expressed
2
gravatar for Michael Love
9 months ago by
Michael Love26k
United States
Michael Love26k wrote:

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 COMMENTlink written 9 months ago by Michael Love26k

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 REPLYlink written 9 months ago by rodrigo.duarte8820

Yes that is correct.

ADD REPLYlink written 9 months ago by Michael Love26k
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