campmc.pl.assignment

campmc.pl.assignment(adata, *, embedding_key='X_umap', partition_key='camp', colour_metacells=True, title='Metacell Assignments', figsize=(5.0, 5.0), metacell_size=20.0, cell_size=10.0, show=False)

Plot a 2D embedding coloured by CAMP metacell assignments.

Parameters:

adata AnnData

AnnData with partition labels in obs and a 2D embedding in obsm.

embedding_key str (default: 'X_umap')

obsm key for the 2D plot (e.g. X_umap or X_pca).

partition_key str (default: 'camp')

Column in adata.obs with metacell labels.

colour_metacells bool (default: True)

If True, colour cells by metacell and overlay group-mean centroids. If False, grey cells with red centroid markers.

title str (default: 'Metacell Assignments')

Figure title.

figsize tuple[float, float] (default: (5.0, 5.0))

Figure size in inches.

metacell_size float (default: 20.0)

Marker size for metacell centroids.

cell_size float (default: 10.0)

Marker size for single cells.

show bool (default: False)

If True, display via plt.show() and return None.

Return type:

Figure | None

Returns:

The figure when show is false; otherwise None after displaying.

Examples

import campmc as cp
import scanpy as sc
adata = sc.datasets.pbmc68k_reduced()
cp.partition(adata, method="camp3", gamma=50, random_state=0)
cp.pl.assignment(adata, embedding_key="X_umap", show=True)