scanpy.pl.embedding_density

scanpy.pl.embedding_density(adata, basis, key, *, group='all', color_map='YlOrRd', bg_dotsize=80, fg_dotsize=180, vmax=1, vmin=0, ncols=4, hspace=0.25, wspace=None, save=None, show=None, **kwargs)

Plot the density of cells in an embedding (per condition)

Plots the gaussian kernel density estimates (over condition) from the sc.tl.embedding_density() output.

This function was written by Sophie Tritschler and implemented into Scanpy by Malte Luecken.

Parameters
adata : AnnDataAnnData

The annotated data matrix.

basis : strstr

The embedding over which the density was calculated. This embedded representation should be found in adata.obsm['X_[basis]']`.

key : strstr

Name of the .obs covariate that contains the density estimates

group : str, List[str], NoneUnion[str, List[str], None]

The category in the categorical observation annotation to be plotted. For example, ‘G1’ in the cell cycle ‘phase’ covariate. If all categories are to be plotted use group=’all’ (default), If multiple categories want to be plotted use a list (e.g.: [‘G1’, ‘S’]. If the overall density wants to be ploted set group to ‘None’.

color_map : Colormap, strUnion[Colormap, str]

Matplolib color map to use for density plotting.

bg_dotsize : int, NoneOptional[int]

Dot size for background data points not in the group.

fg_dotsize : int, NoneOptional[int]

Dot size for foreground data points in the group.

vmax : int, NoneOptional[int]

Density that corresponds to color bar maximum.

vmin : int, NoneOptional[int]

Density that corresponds to color bar minimum.

ncols : int, NoneOptional[int]

Number of panels per row.

wspace : NoneNone

Adjust the width of the space between multiple panels.

hspace : float, NoneOptional[float]

Adjust the height of the space between multiple panels.

show : bool, NoneOptional[bool]

Show the plot, do not return axis.

save : bool, str, NoneUnion[bool, str, None]

If True or a str, save the figure. A string is appended to the default filename. Infer the filetype if ending on {‘.pdf’, ‘.png’, ‘.svg’}.

ax

A matplotlib axes object. Only works if plotting a single component.

Examples

>>> adata = sc.datasets.pbmc68k_reduced()
>>> sc.tl.umap(adata)
>>> sc.tl.embedding_density(adata, basis='umap', groupby='phase')

Plot all categories be default >>> sc.pl.embedding_density(adata, basis=’umap’, key=’umap_density_phase’)

Plot selected categories >>> sc.pl.embedding_density(adata, basis=’umap’, key=’umap_density_phase’, … group=[‘G1’, ‘S’])