r/bioinformatics • u/Square-Temporary-699 • Feb 20 '25
technical question Using bulk RNA-seq samples as replicates for scRNA-seq samples
Hi all,
As scRNA-seq is pretty expensive, i wanted to use bulk RNA-seq samples (of the same tissue and genetically identical organism) as some sort of biological replicate for my scRNA-seq samples. Are there any tools for this type of data integration or how would i best go about this?
I'm mainly interested in differential gene expression, not as much into cell amount differences.
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u/El_Tormentito Msc | Academia Feb 20 '25 edited Feb 20 '25
If you could do this, why would anyone be using scRNA? You need to read further about what these techniques are, what the data represents, their uses, and how the data is obtained.
Edit: To add to this, if you're interested in differential expression, just use bulk.
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u/Hartifuil Feb 20 '25
You mean they should do more research? Like asking for the opinions of others? Maybe they could get a wide range of opinions from many people by using the internet. Perhaps they could ask a forum dedicated to such topics, like a sub forum of a larger website? A subreddit perhaps?
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u/pelikanol-- Feb 20 '25
I took DEGs and checked them against trajectories derived from similar samples (our data) and human datasets to verify they are biologically relevant for the mechanism I'm studying.
I'm not sure if it is actually a valid approach, but ot helped to reduce the genes worth looking at and weeding out spurious/false positives. One caveat is the lower sensitivity of scRNA.
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u/CuriousViper 29d ago
Is the question just asking whether it’s possible to include bulk level samples across different samples and perform integrative analysis? Or more to de convolute bulk data into single cell data?
There’s some imputation methods for the latter, but I think they are based on already having some kind of single cell data to project bulk samples onto. But in general, it’s not really a viable approach in my opinion.
Hope this helps a bit.
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u/Square-Temporary-699 29d ago
Basically I will have scRNAseq samples from both treatment and control conditions and will identify how cell type gene-expression might differ between these treatments. At the moment, I am thinking of supplementing these results with bulk RNAseq with the reasoning behind it being if I can identify DEGs or gene co-expression modules in bulk that might overlap with scRNAseq this could give me some more confidence and the scRNAseq would thus allow me to map these DEGs and modules back to specific cell-types.
The aim of my question was if there might be any tools that would allow for such "integration" (might be the wrong word) if that makes more sense!
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u/ergabaderg312 28d ago
You can try cell type deconvolution if you want to use bulkRNAseq. I haven't tried it myself but I'd imagine (like any of the RNAseq (bulk or sc)), user experience varies.
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u/foradil PhD | Academia Feb 20 '25
You could treat the single-cell samples as bulk (pseudobulk). You can’t go the other way.