- GPCCA.compute_macrostates(n_states=None, n_cells=30, use_min_chi=False, cluster_key=None, en_cutoff=0.7, p_thresh=1e-15)¶
Compute the macrostates.
bool) – Whether to use
pygpcca.GPCCA.minChi()to calculate the number of macrostates. If True,
n_statescorresponds to a closed interval [min, max] inside of which the potentially optimal number of macrostates is searched.
float]) – If
cluster_keyis given, this parameter determines when an approximate recurrent class will be labeled as ‘Unknown’, based on the entropy of the distribution of cells over transcriptomic clusters.
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 than
p_thresh, a warning will be issued.
Nothing, but updates the following fields:
- Return type