clusterPlots

clusterPlots ¶

clusterPlots(
    data,
    groupBy,
    subsample=100000,
    palette="viridis",
    useRaw=False,
    size=None,
    outputDir=None,
    show=True,
    returnData=False,
    returnFig=False,
    sdataTable=None,
    **kwargs
)

Plot cluster labels on an existing UMAP embedding.

A convenience wrapper: clusterPlots(adata, groupBy="leiden") is sp.pl.umap(adata, color="leiden") with a palette default suited to cluster labels. Requires an embedding in obsm['umap'], so run sp.tl.umap first.

Parameters:

Name	Type	Description	Default
`data`	`(AnnData \| SpatialData \| str, required)`	The cell table. An `AnnData`, a path to an `.h5ad` file, a `SpatialData` object, or a path to a `.zarr` SpatialData store.	required
`groupBy`	`(str, required)`	Column in `obs` holding the cluster labels to colour by.	required
`subsample`	`int`	Accepted for signature compatibility with scimap. The current implementation plots every cell; subsample the object yourself if you need to.	`100000`
`palette`	`str`	Matplotlib colormap name used to build the discrete palette.	`'viridis'`
`useRaw`	`bool`	Accepted for signature compatibility with scimap; it has no effect when colouring by a label column.	`False`
`size`	`float`	Point size.	`None`
`outputDir`	`str`	Directory to save the figure in.	`None`
`show`	`bool`	Call `plt.show()` before returning.	`True`
`returnData`	`bool`	Return the plotted `DataFrame` instead of drawing.	`False`
`returnFig`	`bool`	Return `(fig, axes)`.	`False`
`sdataTable`	`str`	Which `SpatialData` table to read.	`None`
`**kwargs`	`dict`	Forwarded to `sp.pl.umap`.	`{}`

Returns:

Name	Type	Description
`result`	`None \| DataFrame \| tuple`	Whatever `sp.pl.umap` returns for the same arguments.

Example

adata = sp.tl.cluster(adata, method="leiden", label="leiden")
adata = sp.tl.umap(adata)
sp.pl.clusterPlots(adata, groupBy="leiden")