Question: clustering cell population from bulk RNA seq ?
gravatar for julia.majewska
2.5 years ago by
julia.majewska20 wrote:

Hi everyone. I was wondering whether it is possible to do clustering of cell populations after bulk RNA seq? To be more precise, I am sequencing all epithelial cells from lungs. And I am wondering whether there is a clustering algoritm that will allow me to differenciate epithelial cell populations afterwards.

Thanks, J

sequencing rna-seq genome • 1.5k views
ADD COMMENTlink modified 22 months ago by Biostar ♦♦ 20 • written 2.5 years ago by julia.majewska20

Are you trying to differentiate different populations from individual sample? This thread may be relevant: Deconvolution Methods on RNA-Seq Data (Mixed cell types)

ADD REPLYlink written 2.5 years ago by igor11k

It also sounds for me as deconvolution problem (btw, thanks for the thread reference, @igor). You can look on this:

Not all the methods are purely based on mathematics, some uses "pure" cells expression profiles or marker genes, however, I would agree with the answer below by @Devon that single cell/nuclei RNA-seq experiment would be better (although more expensive).

ADD REPLYlink written 22 months ago by aln290
gravatar for Devon Ryan
2.5 years ago by
Devon Ryan97k
Freiburg, Germany
Devon Ryan97k wrote:

tldr: It's theoretically possible, but can be tricky and the results are questionable.

You're looking for "blind signal separation" techniques, such as ICA or NMF. Having said that, I should warn you that (A) these techniques tend to not work terribly well on RNAseq data, since they tend to require that signals sum linearly (RNAseq signals are competitive) and (B) because of that most of the papers will benchmark using microarray data and then say that their methods work with RNAseq too...take that with a large grain of salt. You will need a decent number of samples regardless of the technique you use. Typically you will also need to predefine how many cell types constitute your samples, hopefully you have a ballpark estimate. Note that the more sources you have to separate out the less reliable the expression estimates for each source will be.

If possible, you'd be better off just doing single-cell sequencing. Even just sequencing RNA in nuclei from single cells would be better in my mind.

ADD COMMENTlink written 2.5 years ago by Devon Ryan97k
Please log in to add an answer.


Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 2.3.0
Traffic: 2179 users visited in the last hour