I would like to to a functional enrichment for the top 100 marker genes of a cluster. I really like the interface of sc.queries.enrich using an AnnData object, e.g. like this:
import scanpy as sc adata = sc.datasets.burczynski06() sc.tl.rank_genes_groups(adata, 'groups') sc.queries.enrich(adata, 'normal')
Recently, the default of
rank_genes_groups is to return a list of all genes and not just the top genes. Now, how would I perform a functional enrichment of the top 100 marker genes in a convenient way?
I thought it might be sensible to implement an
n_genes argument for
sc.get.rank_genes_groups_df which could then be passed to sc.queries.enrich, but maybe there is another simple way that I cannot see.