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How to score cluster for presence of marker genes?

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A frequent problem that I am faced with is to identify clusters using known lists of markers. I think that one existing approach is to first identify markers and then check if the known markers are among those identified markers. Also, I have used the score_genes function, originally used to identify cell cycle genes. However, I think that a more robust method is possible and probably I am just not aware of it. Does anyone has some experience with this?

Issue Analytics

State:
Created 5 years ago
Comments:6 (3 by maintainers)

Top GitHub Comments

1reaction

fidelramcommented, Oct 11, 2018

@LuckyMD Thanks for sharing your code, I will try it. As for a dataset with very similar cells, I think the pbmc68k has T-cells that are very similar to each other. You can take a quick look at a reduced datase by doing:

adata = sc.datasets.pbmc68k_reduced()
sc.pl.umap(adata, color='bulk_labels')

0reactions

Leprechaun777commented, Feb 14, 2019

How were the bulk labels generated then assigned to cells in the pbmc68k dataset? I’m trying to do the same on my data.

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