scmagnify.plotting.heatmap#
- scmagnify.plotting.heatmap(data, var_names, modal='GRN', layer='mlm_estimated', cmap='RdBu_r', tkey_cmap='Spectral_r', selected_genes=None, cell_selection=None, sortby='pseudotime', smooth_method='gam', n_splines=4, n_deg=3, n_convolve=30, standard_scale=0, sort=True, col_annos=None, col_cluster=False, row_cluster=False, row_split=None, figsize=(8, 4), dpi=100, show=None, save=None, **kwargs)#
Plot time series for genes as a heatmap.
- Parameters:
data (
AnnData|MuData|GRNMuData) – Single cell data object. Can be ananndata.AnnData,mudata.MuData,scmagnify.GRNMuDatavar_names (
str|list[str]) – Names of variables to use for the plot.modal (
Literal['GRN','ATAC','RNA'] (default:'GRN')) – Modality key (e.g., ‘RNA’, ‘ATAC’) when using multi-modal data.mudata.MuDataorscmagnify.GRNMuDatamust be provided.layer (
str(default:'mlm_estimated')) – Layer inlayers. IfNone, defaults toX.cmap (
str(default:'RdBu_r')) – Colormap name or object. Seematplotlib.cm.tkey_cmap (
str(default:'Spectral_r')) – Colors to use for plotting continuous variables. e.g., pseudotimeselected_genes (
Optional[list[str]] (default:None)) – List of genes to highlight in the heatmap.cell_selection (
Optional[list[str]] (default:None)) – List of cells to plot separately in the heatmap.sortby (
str(default:'pseudotime')) – Observation key to extract time data from.smooth_method (
Literal['gam','convolve','polyfit'] (default:'gam')) – Method used to smooth trends/values.n_splines (
int|None(default:4)) – Number of splines for GAM smoothing.n_deg (
int|None(default:3)) – Polynomial degree for polyfit smoothing.n_convolve (
int|None(default:30)) – Kernel size for convolution along sorted axis.standard_scale (
int(default:0)) – Standardize features over variables (0) or observations (1).sort (
bool(default:True)) – Whether to sort the expression values given bylayer.col_annos (
Optional[list[str]] (default:None)) – List of observation keys to use as column annotations.row_cluster (
bool(default:False)) – Whether to cluster the rows.col_cluster (
bool(default:False)) – Whether to cluster the columns.row_split (
Optional[list[str]] (default:None)) – Observation key to split the rows by.figsize (
tuple(default:(8, 4))) – Figure size.show (
Optional[bool] (default:None)) – Whether to display the figure. IfNone, the figure will be shown by default.save (
Optional[str] (default:None)) – Whether to save the figure. IfTrue, the figure is saved to a file using thewritekey. If astris provided, it is used as the filename, potentially overriding other settings. IfNoneorFalse, the figure is not saved.kwargs – Arguments passed to
ClusterMapPlotter.dpi (int)
- Return type:
ClusterMapPlotter|None- Returns:
ClusterMapPlotter | None Returned when
showis False.