pl.plot_covariate

pl.plot_covariate(
    adata,
    covariate='biology',
    color=None,
    name='spanorm',
    **kwargs,
)

Spatially plot the library-size, biology or batch effect modelled for a gene (R plotCovariate).

Parameters

Name	Type	Description	Default
adata		Object holding a SpaNorm fit (see :func:spanormpy.spanorm).	required
covariate		"biology" (default), "ls" or "batch".	'biology'
color		The gene (in adata.var_names) to plot; required, as in R.	None
name		Name of the stored fit.	'spanorm'
**kwargs		Passed to :func:spanormpy.pl.plot_spatial (img, crop, ax, show, …).	{}

Examples

Note

The code below runs when the site is built, on a small pre-fitted subset of HumanDLPFC (301 genes x 4015 spots; spanorm(sample_p=0.05, df_tps=2), spanorm_svg() and spanorm_pca() already applied) that is fitted once per build and loaded as adata. The outputs are those of the code shown.

import spanormpy as sn
# adata: the HumanDLPFC AnnData (raw counts in X, coordinates in obsm["spatial"]),
# already fitted with sn.spanorm(adata, sample_p=0.05, df_tps=2)
# the biology (spatially varying) component learnt for MOBP
ax = sn.pl.plot_covariate(adata, covariate="biology", color="MOBP", size=3)

# the library size effect learnt for MOBP
ax = sn.pl.plot_covariate(adata, covariate="ls", color="MOBP", size=3)