scanpy.pl.embedding_density

scanpy.pl.embedding_density(adata, basis='umap', *, key=None, groupby=None, group='all', color_map='YlOrRd', bg_dotsize=80, fg_dotsize=180, vmax=1, vmin=0, vcenter=None, norm=None, ncols=4, hspace=0.25, wspace=None, title=None, show=None, save=None, ax=None, return_fig=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 AnnData

The annotated data matrix.

basis str (default: 'umap')

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

key str | None (default: None)

Name of the .obs covariate that contains the density estimates. Alternatively, pass groupby.

groupby str | None (default: None)

Name of the condition used in tl.embedding_density. Alternatively, pass key.

group str | Sequence[str] | None (default: 'all')

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 | str (default: 'YlOrRd')

Matplolib color map to use for density plotting.

bg_dotsize int | None (default: 80)

Dot size for background data points not in the group.

fg_dotsize int | None (default: 180)

Dot size for foreground data points in the group.

vmin int | None (default: 0)

The value representing the lower limit of the color scale. Values smaller than vmin are plotted with the same color as vmin. vmin can be a number, a string, a function or None. If vmin is a string and has the format pN, this is interpreted as a vmin=percentile(N). For example vmin=’p1.5’ is interpreted as the 1.5 percentile. If vmin is function, then vmin is interpreted as the return value of the function over the list of values to plot. For example to set vmin tp the mean of the values to plot, def my_vmin(values): return np.mean(values) and then set vmin=my_vmin. If vmin is None (default) an automatic minimum value is used as defined by matplotlib scatter function. When making multiple plots, vmin can be a list of values, one for each plot. For example vmin=[0.1, 'p1', None, my_vmin]

vmax int | None (default: 1)

The value representing the upper limit of the color scale. The format is the same as for vmin.

vcenter int | None (default: None)

The value representing the center of the color scale. Useful for diverging colormaps. The format is the same as for vmin. Example: sc.pl.umap(adata, color=’TREM2’, vcenter=’p50’, cmap=’RdBu_r’)

ncols int | None (default: 4)

Number of panels per row.

wspace None (default: None)

Adjust the width of the space between multiple panels.

hspace float | None (default: 0.25)

Adjust the height of the space between multiple panels.

return_fig bool | None (default: None)

Return the matplotlib figure.

show bool | None (default: None)

Show the plot, do not return axis.

save bool | str | None (default: 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 Axes | None (default: None)

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

Return type:

Figure | Axes | None

Examples

import scanpy as sc
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'],
)

See also

tl.embedding_density