stlearn.pl.gene_plot¶
- stlearn.pl.gene_plot(adata: AnnData, gene_symbols: Optional[Union[str, list]] = None, threshold: Optional[float] = None, method: str = 'CumSum', contour: bool = False, step_size: Optional[int] = None, title: Optional[str] = None, figsize: Optional[Tuple[float, float]] = None, cmap: Optional[str] = 'Spectral_r', use_label: Optional[str] = None, list_clusters: Optional[list] = None, ax: Optional[Axes] = None, fig: Optional[Figure] = None, show_plot: Optional[bool] = True, show_axis: Optional[bool] = False, show_image: Optional[bool] = True, show_color_bar: Optional[bool] = True, color_bar_label: Optional[str] = '', zoom_coord: Optional[float] = None, crop: Optional[bool] = True, margin: Optional[bool] = 100, size: Optional[float] = 7, image_alpha: Optional[float] = 1.0, cell_alpha: Optional[float] = 0.7, use_raw: Optional[bool] = False, fname: Optional[str] = None, dpi: Optional[int] = 120, vmin: Optional[float] = None, vmax: Optional[float] = None) Optional[AnnData] [source]¶
Allows the visualization of a single gene or multiple genes as the values of dot points or contour in the Spatial transcriptomics array.
- 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, louvain,…).
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.
gene_symbols – Single gene (str) or multiple genes (list) that user wants to display. It should be available in adata.var_names.
threshold – Threshold to display genes in the figure.
method – Method to combine multiple genes: ‘CumSum’ is cummulative sum of genes expression values, ‘NaiveMean’ is the mean of the genes expression values.
contour – Option to show the contour plot.
step_size – Determines the number and positions of the contour lines / regions.
Examples
>>> import stlearn as st >>> adata = st.datasets.example_bcba() >>> genes = ["BRCA1","BRCA2"] >>> st.pl.gene_plot(adata, gene_symbols = genes)