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Evaluate single cell data to look at combinations of gene expression within single cells

I have a large single cell data set and I am interested in a certain set of approx 50 genes and I want to evaluate in which combinations that they are expressed within single cells. For example: Cell 1 expresses: gene 1, gene 3, and gene 4 Cell 2 expresses: gene 1, gene 8, gene 18, and gene 17

and then I would like to produce a graph to visualize the combinations that occur or the combos that occur the most (with 50 genes, it is a lot of possible combos, I'm aware)

Does anyone know of any tools to accomplish this? Or a combination of steps I could take to cluster in such a way?

scrna-seq rna-seq analysis

1 answer

You can coexpression networks for cells using WGCNA https://horvath.genetics.ucla.edu/html/CoexpressionNetwork/Rpackages/WGCNA/

Using WGCNA requires at least 20 samples. Also WGCNA analysis is not "stable", which means that the another researcher will find impossible to reproduce the results of WGCNA analysis without having the original script where the WGCNA analysis was done. Also at a close inspection it looks like may modules are generated by chance.

Do you have another suggestion for how I could try to assess this?

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