cellrank.tl.estimators.GPCCA.compute_lineage_priming

GPCCA.compute_lineage_priming(method='kl_divergence', early_cells=None)

Compute the degree of lineage priming.

It returns a score in [0, 1] where 0 stands for naive and 1 stands for committed.

Parameters

• method (Literal[‘kl_divergence’, ‘entropy’]) –

  The method used to compute the degree of lineage priming. Valid options are:

  • ’kl_divergence’ - as in [Velten et al., 2017], computes KL-divergence between the fate probabilities of a cell and the average fate probabilities. Computation of average fate probabilities can be restricted to a set of user-defined early_cells.

  • ’entropy’ - as in [Setty et al., 2019], computes entropy over a cell’s fate probabilities.

• early_cells (Union[Mapping[str, Sequence[str]], Sequence[str], None]) – Cell IDs or a mask marking early cells. If None, use all cells. Only used when method = 'kl_divergence'. If a dict, the key specifies a cluster key in anndata.AnnData.obs and the values specify cluster labels containing early cells.

Return type

Series

Returns

The priming degree.

Also updates the following field:

• priming_degree - Priming degree.