ehrapy.plot.rank_features_groups

ehrapy.plot.rank_features_groups(edata, groups=None, n_features=20, feature_symbols=None, key='rank_features_groups', fontsize=8, ncols=4, share_y=True, show=None, save=None, ax=None, **kwds)

Plot ranking of features.

Parameters:

• edata (EHRData | AnnData) – Central data object.

• groups (str | Sequence[str] | None, default: None) – The groups for which to show the feature ranking.

• n_features (int, default: 20) – The number of features to plot.

• feature_symbols (str | None, default: None) – Key for field in .var that stores feature symbols if you do not want to use .var_names.

• key (str | None, default: 'rank_features_groups') – The key of the calculated feature group rankings (default: ‘rank_features_groups’).

• fontsize (int, default: 8) – Fontsize for feature names.

• ncols (int, default: 4) – Number of panels shown per row.

• share_y (bool, default: True) – Controls if the y-axis of each panels should be shared. But passing sharey=False, each panel has its own y-axis range.

• show (bool | None, default: None) – Whether to display the figure or return axis.

• save (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.

Examples

>>> import ehrdata as ed
>>> import ehrapy as ep
>>> edata = ed.dt.mimic_2()
>>> ep.pp.knn_impute(edata)
>>> ep.pp.log_norm(edata, offset=1)
>>> ep.pp.neighbors(edata)
>>> ep.tl.leiden(edata, resolution=0.15, key_added="leiden_0_5")
>>> ep.tl.rank_features_groups(edata, groupby="leiden_0_5")
>>> ep.pl.rank_features_groups(edata, key="rank_features_groups")

Preview: