FACSPy.pl.cluster_abundance

FACSPy.pl.cluster_abundance(adata, groupby, cluster_key=None, normalize=True, order=None, figsize=(5, 4), return_dataframe=False, return_fig=False, ax=None, show=True, save=None)

Plots the frequency as a stacked bar chart of a grouping variable per cluster.

Parameters:

• adata (AnnData) – The anndata object of shape n_obs x n_vars where rows correspond to cells and columns to the channels.

• groupby (str) – controls the x axis and the grouping of the data points.

• cluster_key (Optional[str]) – The obs slot where the clusters of interest are stored.

• normalize (bool) – If True, normalizes the frequencies to 1. If False, the y-axis represents the cell counts per cluster.

• order (Optional[list[str]]) – Sets the order of the groupby variable.

• figsize (tuple[float, float]) – Contains the dimensions of the final figure as a tuple of two ints or floats.

• return_dataframe (bool) – If set to True, returns the raw data that are used for plotting as a dataframe.

• return_fig (bool) – If set to True, the figure is returned.

• ax (Optional[Axes]) – A Axes to created from matplotlib to plot into.

• show (bool) – Whether to show the figure. Defaults to True.

• save (Optional[str]) – Expects a file path including the file name. Saves the figure to the indicated path. Defaults to None.

Return type:

Optional[Figure, Axes, DataFrame]]

Returns:

• If show==False a Axes

• If return_fig==True a Figure

• If return_dataframe==True a DataFrame containing the data used for plotting

Examples

import FACSPy as fp

dataset = fp.mouse_lineages()

fp.settings.default_gate = "CD45+"
fp.settings.default_layer = "transformed"

fp.tl.pca(dataset)
fp.tl.neighbors(dataset)
fp.tl.leiden(dataset)

fp.pl.cluster_abundance(
    dataset,
    cluster_key = "CD45+_transformed_leiden",
    groupby = "organ"
)