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 whenmethod = 'kl_divergence'
. If adict
, the key specifies a cluster key inanndata.AnnData.obs
and the values specify cluster labels containing early cells.
- Return type
- Returns
The priming degree.
Also updates the following field:
priming_degree
- Priming degree.