Plotting

ROI Visualization functions

cell_map

spatialtis.plotting.cell_map(adata, query, geom='shape', selected_types=None, type_key=None, shape_key=None, centroid_key=None, size=None, title=None, palette=None, display=None, save=None, return_plot=False)[source]

(bokeh) Visualize cells in ROI

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • query (Dict) – A Dict use to select which ROI to display, eg: {“Patients”: “Patient 1”, “ROI”: “ROI3”}, “Patients” and “ROI” are keys in AnnData.obs

  • geom (str) – “shape” or “point”

  • selected_types (Optional[Sequence]) – Select interested cell types to perform analysis

  • type_key (Optional[str]) – The key to store cell types in AnnData.obs (Default: spatialtis.CONFIG.CELL_TYPE_KEY)

  • shape_key (Optional[str]) – The key to store cell shape in AnnData.obs (Default: spatialtis.CONFIG.SHAPE_KEY)

  • centroid_key (Optional[str]) – The key to store cell centroid in AnnData.obs (Default: spatialtis.CONFIG.CENTROID_KEY)

  • size (Optional[Sequence[int]]) – The size of the plot in pixels

  • title (Optional[str]) – The title of the plot

  • palette (Optional[Union[Sequence[str], str]]) – Control the color of plot, sequence of color in hex, or name of palettes

  • display (Optional[bool]) – Whether to display the plot

  • save (Optional[Union[str, pathlib.Path]]) – The path to save your plot

  • return_plot (bool) – Whether to return the plot instance

expression_map

spatialtis.plotting.expression_map(adata, query, selected_types=None, type_key=None, marker_key=None, centroid_key=None, order=None, expression_min=None, expression_max=None, use='bar3d', renderer='canvas', axis_size=(100, 100, 80), size=(800, 500), palette=None, display=None, return_plot=False)[source]

(pyecharts) Visualize marker expression in ROI

Warning

There are problems in saving this plot even in .html. for now please use save bottom.

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • query (Dict) – A Dict use to select which ROI to display, eg: {“Patients”: “Patient 1”, “ROI”: “ROI3”}, “Patients” and “ROI” are keys in AnnData.obs

  • selected_types (Optional[Sequence]) – Select interested cell types to perform analysis

  • type_key (Optional[str]) – The key to store cell types in AnnData.obs (Default: spatialtis.CONFIG.CELL_TYPE_KEY)

  • marker_key (Optional[str]) – The key to store markers in AnnData.var (Default: spatialtis.CONFIG.MARKER_KEY)

  • centroid_key (Optional[str]) – The key to store cell centroid in AnnData.obs (Default: spatialtis.CONFIG.CENTROID_KEY)

  • order (Optional[Sequence]) – array of marker name, display as order

  • expression_min (Optional[float]) – setting threshold for min of expression

  • expression_max (Optional[float]) – setting threshold for max of expression

  • use (str) – Options are “bar3d” and “scatter”

  • renderer (str) – Options are “canvas” and “svg”; “svg” is not perfect at this moment.

  • axis_size (tuple) – the length of x,y,z axis

  • size (tuple) – The size of the plot in pixels

  • palette (Optional[Sequence]) –

    Control the color of plot, sequence of color in hex, or name of palettes

  • display (Optional[bool]) – Whether to display the plot

  • return_plot (bool) – Whether to return the plot instance

cell_neighbors

spatialtis.plotting.cell_neighbors(adata, query, use='interactive', type_key=None, centroid_key=None, neighbors_key=None, **kwargs)[source]

(pyecharts) Visualize cell neighbors in ROI

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • query (Dict) – A Dict use to select which ROI to display, eg: {“Patients”: “Patient 1”, “ROI”: “ROI3”}, “Patients” and “ROI” are keys in AnnData.obs

  • use (str) – Options are “interactive” and “_static”

  • type_key (Optional[str]) – The key to store cell types in AnnData.obs (Default: spatialtis.CONFIG.CELL_TYPE_KEY)

  • centroid_key (Optional[str]) – The key to store cell centroid in AnnData.obs (Default: spatialtis.CONFIG.CENTROID_KEY)

  • neighbors_key (Optional[str]) – The key to store cell neighbors in AnnData.obs

  • **kwargs – Pass to Graph plot (interactive) or Graph plot

cell_communities

spatialtis.plotting.cell_communities(adata, query, min_cell=10, use='interactive', centroid_key=None, community_key=None, neighbors_key=None, **kwargs)[source]

(pyecharts, matplotlib) Visualize cell communities

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • query (Dict) – A Dict use to select which ROI to display, eg: {“Patients”: “Patient 1”, “ROI”: “ROI3”}, “Patients” and “ROI” are keys in AnnData.obs

  • min_cell (int) – Only show communities with at least a number of cells

  • use (str) – Options are “interactive” and “_static”. For big ROI, “interactive” is much faster using WebGL

  • centroid_key (Optional[str]) – The key to store cell centroid in AnnData.obs (Default: spatialtis.CONFIG.CENTROID_KEY)

  • community_key (Optional[str]) – The key to store cell communities in AnnData.obs

  • neighbors_key (Optional[str]) – The key to store cell neighbors in AnnData.obs

  • **kwargs –

    Pass to Graph plot (interactive) or Graph plot

Analysis Visualization functions

plotting.cell_components

spatialtis.plotting.cell_components(adata, groupby, selected_types=None, key=None, **kwargs)[source]

(bokeh) Plotting function for cell components

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • groupby (Sequence[str]) – How your experiments data grouped, (Default: spatialtis.CONFIG.EXP_OBS)

  • selected_types (Optional[Sequence]) – Select interested cell types to perform analysis

  • key (Optional[str]) – The key stores the data for plotting in AnnData.uns

  • **kwargs – Pass to Stacked-bar plot

plotting.cell_co_occurrence

spatialtis.plotting.cell_co_occurrence(adata, groupby=None, selected_types=None, use='dot', key=None, **kwargs)[source]

(matplotlib) plotting function for cell co-occurrence

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • groupby (Optional[Sequence[str]]) – How your experiments data grouped, (Default: spatialtis.CONFIG.EXP_OBS)

  • selected_types (Optional[Sequence]) – Select interested cell types to perform analysis

  • use (str) – Options are “dot” and “heatmap”

  • key (Optional[str]) – The key stores the data for plotting in AnnData.uns

  • **kwargs – Pass to Tri-Dotplot or Heatmap

plotting.cell_density

spatialtis.plotting.cell_density(adata, groupby=None, selected_types=None, key=None, **kwargs)[source]

(bokeh) plotting function for cell density

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • groupby (Optional[Sequence[str]]) – How your experiments data grouped, (Default: spatialtis.CONFIG.EXP_OBS)

  • selected_types (Optional[Sequence]) – Select interested cell types to perform analysis

  • key (Optional[str]) – The key stores the data for plotting in AnnData.uns

  • **kwargs – Pass to Violin plot

plotting.cell_morphology

spatialtis.plotting.cell_morphology(adata, groupby=None, selected_types=None, key=None, **kwargs)[source]

(bokeh) plotting function for cell morphology

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • groupby (Optional[Sequence[str]]) – How your experiments data grouped, (Default: spatialtis.CONFIG.EXP_OBS)

  • selected_types (Optional[Sequence]) – Select interested cell types to perform analysis

  • key (Optional[str]) – The key stores the data for plotting in AnnData.uns

  • **kwargs –

    Pass to Violin plot

plotting.neighborhood_analysis

spatialtis.plotting.neighborhood_analysis(adata, groupby=None, selected_types=None, key=None, use='dot_matrix', **kwargs)[source]

(“dot_matrix”, “heatmap”: matplotlib) plotting function for neighborhood analysis

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • groupby (Optional[Sequence[str]]) – How your experiments data grouped, (Default: spatialtis.CONFIG.EXP_OBS)

  • selected_types (Optional[Sequence]) – Select interested cell types to perform analysis

  • key (Optional[str]) – The key stores the data for plotting in AnnData.uns

  • use (str) – Options are “dot_matrix” and “heatmap”

  • **kwargs –

    Pass to Dot-matrix plot or Heatmap

plotting.spatial_enrichment_analysis

spatialtis.plotting.spatial_enrichment_analysis(adata, groupby=None, selected_types=None, use='dot_matrix', key=None, **kwargs)[source]

(matplotlib) plotting function for plotting enrichment analysis

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • groupby (Optional[Sequence[str]]) – How your experiments data grouped, (Default: spatialtis.CONFIG.EXP_OBS)

  • selected_types (Optional[Sequence]) – Select interested cell types to perform analysis

  • use (str) – Options are “dot_matrix” and “heatmap”

  • key (Optional[str]) – The key stores the data for plotting in AnnData.uns

  • **kwargs –

    Pass to Dot-matrix plot or Heatmap

plotting.spatial_distribution

spatialtis.plotting.spatial_distribution(adata, groupby=None, selected_types=None, key=None, use='dot', **kwargs)[source]

(matplotlib) plotting function for plotting distribution

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • groupby (Optional[Sequence[str]]) – How your experiments data grouped, (Default: spatialtis.CONFIG.EXP_OBS)

  • selected_types (Optional[Sequence]) – Select interested cell types to perform analysis

  • key (Optional[str]) – The key stores the data for plotting in AnnData.uns

  • use (str) – Options are “dot” and “heatmap”

  • **kwargs –

    Pass to Dotplot or Heatmap

plotting.spatial_heterogeneity

spatialtis.plotting.spatial_heterogeneity(adata, groupby=None, key=None, metric='heterogeneity', **kwargs)[source]

(bokeh) plotting function for cell morphology

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • groupby (Optional[Sequence[str]]) – How your experiments data grouped, (Default: spatialtis.CONFIG.EXP_OBS)

  • key (Optional[str]) – The key stores the data for plotting in AnnData.uns

  • metric (str) – “heterogeneity” or “KL”, “KL” only available if you use shannon entropy

  • **kwargs –

    Pass to Violin plot or Stacked-bar plot

plotting.exp_neighcells

spatialtis.plotting.exp_neighcells(adata, key=None, score=0.5, palette=None, **kwargs)[source]

(pyecharts) plotting function for expression influenced by neighbor cells

Parameters

  • adata (anndata._core.anndata.AnnData) – AnnData object for plotting

  • key (Optional[str]) – The key stores the data for plotting in AnnData.uns

  • score (float) – Threshold for score

  • palette (Optional[Sequence]) – Control the color

  • **kwargs – Pass to Sankey plot