cellrank.tl.estimators.GPCCA.compute_macrostates¶
-
GPCCA.
compute_macrostates
(n_states=None, n_cells=30, use_min_chi=False, cluster_key=None, en_cutoff=0.7, p_thresh=1e-15)[source]¶ Compute the macrostates.
- Parameters
n_states¶ (
Union
[int
,Tuple
[int
,int
],List
[int
],Dict
[str
,int
],None
]) – Number of macrostates. If None, use the eigengap heuristic.n_cells¶ (
Optional
[int
]) – Number of most likely cells from each macrostate to select.use_min_chi¶ (
bool
) – Whether to usemsmtools.analysis.dense.gpcca.GPCCA.minChi()
to calculate the number of macrostates. If True,n_states
corresponds to a closed interval [min, max] inside of which the potentially optimal number of macrostates is searched.cluster_key¶ (
Optional
[str
]) – If a key to cluster labels is given, names and colors of the states will be associated with the clusters.en_cutoff¶ (
Optional
[float
]) – Ifcluster_key
is given, this parameter determines when an approximate recurrent class will be labelled as ‘Unknown’, based on the entropy of the distribution of cells over transcriptomic clusters.p_thresh¶ (
float
) – If cell cycle scores were provided, a Wilcoxon rank-sum test is conducted to identify cell-cycle states. If the test returns a positive statistic and a p-value smaller thanp_thresh
, a warning will be issued.
- Returns
Nothing, but updates the following fields:
- Return type