scanpy.pl.scrublet_score_distribution#
- scanpy.pl.scrublet_score_distribution(adata, *, scale_hist_obs='log', scale_hist_sim='linear', figsize=(8, 3), return_fig=False, show=True, save=None)[source]#
Plot histogram of doublet scores for observed transcriptomes and simulated doublets.
The histogram for simulated doublets is useful for determining the correct doublet score threshold.
Scrublet must have been run previously with the input object.
- Parameters:
- adata
AnnData An AnnData object resulting from
scrublet().- scale_hist_obs
Union[Literal['linear','log','symlog','logit'],str] (default:'log') Set y axis scale transformation in matplotlib for the plot of observed transcriptomes
- scale_hist_sim
Union[Literal['linear','log','symlog','logit'],str] (default:'linear') Set y axis scale transformation in matplotlib for the plot of simulated doublets
- figsize
tuple[float|int,float|int] (default:(8, 3)) width, height
- show
bool(default:True) Show the plot, do not return axis.
- save
str|bool|None(default:None) If
Trueor astr, save the figure. A string is appended to the default filename. Infer the filetype if ending on {'.pdf','.png','.svg'}.
- adata
- Return type:
Figure|Sequence[tuple[Axes,Axes]] |tuple[Axes,Axes] |None- Returns:
If
return_figis True, aFigure. Ifshow==Falsea list ofAxes.
See also
scrublet()Main way of running Scrublet, runs preprocessing, doublet simulation and calling.
scrublet_simulate_doublets()Run Scrublet’s doublet simulation separately for advanced usage.