API

Graph

gr.aggregate_neighbors(adata, n_layers[, ...])	Aggregate the features from each neighborhood layers and concatenate them, and optionally with the cells' features, into a single vector.
gr.nhood_enrichment(adata, cluster_key[, ...])	A modified version of squidpy's neighborhood enrichment.
gr.remove_long_links(adata[, ...])	Remove links between cells at a distance bigger than a certain percentile of all positive distances.
gr.remove_intra_cluster_links(adata, cluster_key)	Remove links between cells that belong to the same cluster.

Tools

tl.Cluster([n_clusters, covariance_type, ...])	Cluster cells or spots based on the neighborhood aggregated features from CellCharter.
tl.ClusterAutoK(n_clusters[, max_runs, ...])	Identify the best candidates for the number of clusters.
tl.TRVAE(adata[, condition_key, conditions, ...])	scArches's trVAE model adapted to image-based proteomics data.

Plotting

pl.autok_stability(autok[, save, return_ax])	Plot the clustering stability.
pl.nhood_enrichment(adata, cluster_key[, ...])	A modified version of squidpy's function for plotting neighborhood enrichment.
pl.proportion(adata, group_key, label_key[, ...])	Plot the proportion of y_key in x_key.