pygot.tools.analysis.TimeSeriesRoadmap

class pygot.tools.analysis.TimeSeriesRoadmap(adata, embedding_key, velocity_key, time_key, sde=False, D=1.0)

Bases: object

Developmental tree inference based on the velocity graph.

Example:

embedding_key = 'X_pca'
velocity_key = 'velocity_pca'
time_key = 'stage_numeric'
cell_type_key = 'clusters'

roadmap = pygot.tl.analysis.TimeSeriesRoadmap(adata, embedding_key, velocity_key, time_key)
roadmap.fit(cell_type_key='clusters', n_neighbors=30)

filtered_state_coupling_list = roadmap.filter_state_coupling(pvalue=0.001) #permutation test to fileter cell type coupling

__init__(adata, embedding_key, velocity_key, time_key, sde=False, D=1.0)

Methods

__init__(adata, embedding_key, velocity_key, ...)
compute_state_coupling([cell_type_key, ...])
export_result()
filter_state_coupling([pvalue, max_cutoff])

compute_state_coupling(cell_type_key='cell_type', n_neighbors=None, permutation_iter_n=100, mutual=True)

export_result()

filter_state_coupling(pvalue=0.001, max_cutoff=0.45)