scanpy.tl.score_genes

scanpy.tl.score_genes(adata, gene_list, *, ctrl_as_ref=True, ctrl_size=50, gene_pool=None, n_bins=25, score_name='score', random_state=0, copy=False, use_raw=None, layer=None)

Score a set of genes [Satija et al., 2015].

The score is the average expression of a set of genes subtracted with the average expression of a reference set of genes. The reference set is randomly sampled from the gene_pool for each binned expression value.

This reproduces the approach in Seurat [Satija et al., 2015] and has been implemented for Scanpy by Davide Cittaro.

Parameters:

adata

The annotated data matrix.

gene_list

The list of gene names used for score calculation.

ctrl_as_ref default: True

Allow the algorithm to use the control genes as reference. Will be changed to False in scanpy 2.0.

ctrl_size default: 50

Number of reference genes to be sampled from each bin. If len(gene_list) is not too low, you can set ctrl_size=len(gene_list).

gene_pool default: None

Genes for sampling the reference set. Default is all genes.

n_bins default: 25

Number of expression level bins for sampling.

score_name default: 'score'

Name of the field to be added in .obs.

random_state default: 0

The random seed for sampling.

copy default: False

Copy adata or modify it inplace.

use_raw default: None

Whether to use raw attribute of adata. Defaults to True if .raw is present.

Changed in version 1.4.5: Default value changed from False to None.

layer default: None

Key from adata.layers whose value will be used to perform tests on.

Returns:

Returns None if copy=False, else returns an AnnData object. Sets the following field:

adata.obs[score_name]numpy.ndarray (dtype float)

Scores of each cell.

Examples

See this notebook.