chrysalis.plot_heatmap

chrysalis.plot_heatmap(adata: AnnData, figsize: Tuple[int, int] = (5, 7), reorder_comps: bool = False, hexcodes: Optional[List[str]] = None, seed: Optional[int] = None, scaling=True, **kwrgs)

Plot heatmap showing the weights of spatially variable genes for each identified tissue compartment.

Parameters:

• adata – The AnnData data matrix of shape n_obs × n_vars. Rows correspond to cells and columns to genes.

• figsize – Figure size as a tuple.

• reorder_comps – Perform hierarchical clustering to reorder compartments based on the similarity of spatially variable gene weights.

• hexcodes – List of hexadecimal colors to replace the default colormap.

• seed – Random seed, used for mixing colors.

• scaling – Column-wise scaling (x - mean / std).

• kwrgs – Seaborn heatmap keyword arguments.