SOAPy_st.pl.show_ccc_netplot

SOAPy_st.pl.show_ccc_netplot(adata: AnnData, sample_id: int | str | None = None, lr_type: Literal['contact', 'secretory'] = 'contact', pos: dict | None = None, cmap: str | None = None, font_size: int = 12, node_size_exp: int = 1, node_size_scaler: int = 1, min_counts: int = 0, ax: Axes | None = None, figsize: tuple = (8, 8), dpi: int = 100, show: bool = True, save: str | None = None, **kwargs) Axes | None

Visualize ligand-receptor interactions between two cell types in spatial omics data using network plot.

Parameters

adataanndata.AnnData

An AnnData object containing spatial omics data and spatial information.

figsizeTuple[float, float], optional

(Width, height) of the figure.

dpifloat, optional

The resolution of the figure.

titlestr, optional

The title of shown figure.

axAxes

A matplotlib axes object.

showbool

Show the plot, do not return axis.

saveUnion[str, PathLike], optional

The path where the image is stored.

lr_type: str

The LR pair to visualise the cci network for. If None, will use spot cci counts across all LR pairs from adata.uns[f’lr_cci_use_label’].

pos: dict

Positions to draw each cell type, format as outputted from running networkx.circular_layout(graph). If not inputted will be generated.

cmap: str

Cmap to use when generating the cell colors, if not already specified by adata.uns[f’use_label_colors’].

font_size: int

Size of the cell type labels.

node_size_scaler: float

Scaler to multiply by node sizes to increase/decrease size.

node_size_exp: int

Increases difference between node sizes by this exponent.

min_counts: int

Minimum no. of LR interactions for connection to be drawn.

kwargsAny

Other params of nx.draw_networkx()

Returns

pos: dict

Dictionary of positions where the nodes are draw if return_pos is True, useful for consistent layouts.

References

Pham, D. et al. Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased

tissues. Nat Commun 14, 7739 (2023).