top_counts_genes¶

besca.pp.top_counts_genes(adata, top_n=10)[source]¶

Give out the genes that contribute the largest fraction to the total UMI counts.

Calculates the genes which contribute the largest fraction of UMI counts to the total: UMI counts (i.e. the most abundant transcripts).

Parameters:

adata (AnnData) – The annotated data matrix.
top_n (int | default = 10) – Integer defining the number of entries to return. If None then the entire table is returned.

Returns:

pandas DataFrame containing the top_n genes

Return type:

DataFrame

Example

>>> import besca as bc
>>> adata = bc.datasets.simulated_pbmc3k_raw()
>>> genes = bc.pp.top_counts_genes(adata)