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Why clusters look different in single nuclear RNA Seq.

Hello, I am analyzing single nuclear RNA mouse tissue samples (three conditions). I forced cells to 3000, ran Seurat and my DimPlot( reduction by “umap”) shown below looks very different in the condition_3. My question is, what could be the possible reasons that the condition_3 looks so different in cluster shape?

Thank you!

    condition_1         condition_2         condition_3

enter image description here

snrna clustering seurat
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updated by Kevin Blighe Kevin Blighe • written by snaik • snaik

These three samples are same tissues.

condition_1 is control and condition_2, condition_3 are treatment group.

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updated by Ram Ram • written by snaik • snaik

1 answer

I mean, your question is for you to answer by exploring the data, no? It is good to seek ideas from the community, too.

It can be inferred —but not proven— that, in condition 3, certain cells have become more 'homogenous' than in the other conditions, and that this may be reflective of these cells reacting to the treatment. I say this by observing that big 'ball' of cells on the bottom of condition 3's UMAP, cells which undoubtedly have similar expression profiles comprised of many lowly expressed genes.

In this way, to note, the other cells that form well-defined clusters away from this big ball of cells are of interest and may have evaded effects of the treatment.

I am just hypothesising.

Now, what you can do is perform comparisons across the different identified clusters in order to infer what may be happening.

Kevin

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written by Kevin Blighe Kevin Blighe

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