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GSEA on single-cell cluster data

Hello Biostars, I have 10x SC expression data which I have processed using Seurat, and now I wish to test the association of several gene-sets with certain clusters. What approach/R package would you recommend?

I suppose I can run GSEA on the expression of individual cells, but next how do I summarize a cluster?

Thanks!

single-cell gsea r
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updated by marcovicari3 • marcovicari3 • written by roy.granit roy.granit

GSVA tries to estimate the pathway expression levels in every individual sample and then allows you to perform comparisons or unsupervised analysis like clustering on the transformed matrix.

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written by Martombo Martombo

2 answers

Some options:

  • Take the top X cluster markers (genes upregulated in that cluster) and run GSEA (or any other pathway analysis) on those.
  • Calculate the fold changes between that cluster and other clusters and use that as a basis for a pre-ranked list for GSEA.
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written by igor igor

Thanks, not sure about these suggestions, I believe they are correct for pathway over-representation but not for hyper-geometric/GSEA analysis. I was seeking some tool that would take the individual GSEA scores for each cell in a certain cluster and conduct a statistical comparison of these to the scores by cells in rest of cluster/other cluster. Something like GSVA which was suggested here above..

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written by roy.granit roy.granit

Due to the dropouts, the result for individual cells will be extremely noisy. Cluster-level analysis would be much cleaner.

GSEA is not meant for over-representation, but I have seen it used that way many times. Regardless, as I mentioned, there are many other pathway analysis tools that are appropriate for that approach.

Single-sample enrichment approaches like GSVA are fine. However, unless the differences between your sub-populations are dramatic, they may not be able to effectively capture them. This is why I suggested to focus on the genes that are actually differentially expressed.

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written by igor igor

Hi Roy. What do you think about pagoda?

http://hms-dbmi.github.io/scde/pagoda.html

Best, Marco

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written by marcovicari3 • marcovicari3

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