scanpy.pl.correlation_matrix

scanpy.pl.correlation_matrix#

scanpy.pl.correlation_matrix(adata, groupby, *, show_correlation_numbers=False, dendrogram=None, figsize=None, show=None, save=None, ax=None, vmin=None, vmax=None, vcenter=None, norm=None, **kwds)[source]#

Plot the correlation matrix computed as part of scanpy.tl.dendrogram().

Parameters:
adata AnnData

groupby str

Categorical data column used to create the dendrogram

show_correlation_numbers bool (default: False)

If show_correlation=True, plot the correlation on top of each cell.

dendrogram bool | str | None (default: None)

If True or a valid dendrogram key, a dendrogram based on the hierarchical clustering between the groupby categories is added. The dendrogram is computed using scanpy.tl.dendrogram(). If tl.dendrogram has not been called previously, the function is called with default parameters.

figsize tuple[float, float] | None (default: None)

By default a figure size that aims to produce a squared correlation matrix plot is used. Format is (width, height)

show bool | None (default: None)

Show the plot, do not return axis.

save str | bool | None (default: None)

If True or a str, save the figure. A string is appended to the default filename. Infer the filetype if ending on {'.pdf', '.png', '.svg'}.

ax Axes | None (default: None)

A matplotlib axes object. Only works if plotting a single component.

vmin float | None (default: None)

The value representing the lower limit of the color scale. Values smaller than vmin are plotted with the same color as vmin.

vmax float | None (default: None)

The value representing the upper limit of the color scale. Values larger than vmax are plotted with the same color as vmax.

vcenter float | None (default: None)

The value representing the center of the color scale. Useful for diverging colormaps.

norm Normalize | None (default: None)

Custom color normalization object from matplotlib. See Colormap normalization for details.

**kwds

Only if show_correlation is True: Are passed to matplotlib.pyplot.pcolormesh() when plotting the correlation heatmap. cmap can be used to change the color palette.

Return type:

list[Axes] | None

Returns:

If show=False, returns a list of matplotlib.axes.Axes objects.

Examples

>>> import scanpy as sc
>>> adata = sc.datasets.pbmc68k_reduced()
>>> sc.tl.dendrogram(adata, "bulk_labels")
>>> sc.pl.correlation_matrix(adata, "bulk_labels")
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