FACSPy.pl.metadata

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FACSPy.pl.metadata#

FACSPy.pl.metadata(adata, marker, groupby, splitby=None, cmap=None, stat_test='Kruskal', order=None, figsize=(3, 3), return_dataframe=False, return_fig=False, ax=None, show=True, save=None, **kwargs)#

Plots the frequency of the metadata columns.

Parameters:

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

  • marker (str) – The channel to be displayed. Has to be in adata.var_names

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

  • splitby (Optional[str]) – The parameter controlling additional split along the groupby-axis.

  • cmap (Optional[str]) – Sets the colormap for plotting. Can be continuous or categorical, depending on the input data. When set, both seaborns ‘palette’ and ‘cmap’ parameters will use this value

  • stat_test (Optional[str]) – Statistical test that is used for the p-value calculation. One of Kruskal and Wilcoxon. Defaults to Kruskal.

  • order (Optional[Union`[:py:class:`list[str], str]]) – specifies the order of x-values.

  • 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 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.

  • kwargs – keyword arguments ultimately passed to sns.stripplot.

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
AnnData object with n_obs × n_vars = 615936 × 22
obs: 'sample_ID', 'file_name', 'condition', 'sex'
var: 'pns', 'png', 'pne', 'pnr', 'type', 'pnn'
uns: 'metadata', 'panel', 'workspace', 'gating_cols', 'dataset_status_hash'
obsm: 'gating'
layers: 'compensated', 'transformed'
>>> fp.pl.metadata(
...     dataset,
...     groupby = "condition",
...     splitby = "sex"
... )
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