API

Preprocessing

Preprocessing utilities for multimodal single-cell data based on scanpy and muon

pp.preprocessing(mudata[, n_pcs_rna, ...])

Preprocess multimodal single-cell data stored in a MuData object.

Tools

tl.PalantirExtension(mudata)	Trajectory inference using the Palantir algorithm on MuData objects.
tl.CellRankExtension(mudata)	Trajectory inference using the CellRank Pseudotime Kernel on MuData objects.
tl.pearson_correlation(mudata, key1, key2[, ...])	Compute the Pearson correlation coefficient between two variables stored in mudata.obs.
tl.spearman_correlation(mudata, key1, key2)	Compute the Spearman rank correlation between two variables stored in mudata.obs.
tl.fate_concentration_index(mudata[, ...])	Compute the correlation between fate concentration and pseudotime.
tl.terminal_pseudotime_enrichment(mudata[, ...])	Compute the average pseudotime enrichment across terminal states.
tl.terminal_state_silhouette(mudata[, ...])	Compute the silhouette score for terminal states.

Plotting

pl.plot_tree(mudata[, embedding_key, ...])	Compute and visualize a principal tree from fate probabilities, using [FSKA22].
pl.plot_trends(mudata, ptf, gene[, ...])	Plot branch-specific dynamics of transcription factor expression and gene activity.
pl.plot_fate_probabilities(mudata[, ...])	Plot lineage fate probabilities on a low-dimensional embedding.
pl.plot_embedding(mudata[, embedding_key, ...])	Plot a low-dimensional embedding of cells colored by a given observation.