stlearn.pl.cluster_plot

stlearn.pl.cluster_plot(adata: AnnData, title: str | None = None, figsize: tuple[float, float] | None = None, cmap: str = 'default', use_label: str | None = None, list_clusters: str | list[str] | None = None, ax: Axes | None = None, fig: Figure | None = None, show_plot: bool = True, show_axis: bool = False, show_image: bool = True, show_color_bar: bool = True, zoom_coord: tuple[float, float, float, float] | None = None, crop: bool = True, margin: float = 100, size: float = 5, image_alpha: float = 1.0, cell_alpha: float = 1.0, fname: str | None = None, dpi: int = 120, show_subcluster: bool = False, show_cluster_labels: bool = False, show_trajectories: bool = False, reverse: bool = False, show_node: bool = False, threshold_spots: int = 5, text_box_size: float = 5, color_bar_size: float = 10, bbox_to_anchor: tuple[float, float] | None = (1, 1), trajectory_node_size: int = 10, trajectory_alpha: float = 1.0, trajectory_width: float = 2.5, trajectory_edge_color: str = '#f4efd3', trajectory_arrowsize: int = 17) → AnnData | None[source]

Allows the visualization of a cluster results as the discretes values of dot points in the Spatial transcriptomics array. We also support to visualize the spatial trajectory results

Parameters:

  • adata – Annotated data matrix.

  • title – Title name of the figure.

  • figsize – Figure size with the format (width,height).

  • cmap – Color map to use for continous variables or discretes variables (e.g. viridis, Set1,…).

  • use_label – Key for the label use in adata.obs (e.g. leiden,…).

  • list_clusters – A set of cluster to be displayed in the figure (e.g. [0,1,2,3]).

  • ax – A matplotlib axes object.

  • show_plot – Option to display the figure.

  • show_image – Option to display the H&E image.

  • show_color_bar – Option to display color bar.

  • crop – Option to crop the figure based on the spot locations.

  • margin – Margin to crop.

  • size – Spot size to display in figure.

  • image_alpha – Opacity of H&E image.

  • cell_alpha – Opacity of spots/cells.

  • use_raw – Option to use adata.raw data.

  • fname – Output path to the output if user want to save the figure.

  • dpi – Dots per inch values for the output.

  • show_subcluster – Display the subcluster in the figure.

  • show_cluster_labels – Display the labels of clusters.

  • show_trajectories – Display the spatial trajectory analysis results.

  • reverse – Reverse the direction of spatial trajectories.

  • show_node – Show node of PAGA graph mapping in spatial.

  • threshold_spots – The number of spots threshold for not display the subcluster labels

  • text_box_size – The font size in the box of labels.

  • color_bar_size – The size of color bar.

  • bbox_to_anchor – Set the position of box of color bar. Default is (1,1)

Examples

>>> import stlearn as st
>>> adata = st.datasets.visium_sge(sample_id="V1_Breast_Cancer_Block_A_Section_1")
>>> label = "leiden"
>>> st.pl.cluster_plot(adata, use_label = label, show_trajectories = True)