dotools_py.pl.lineplot

dotools_py.pl.lineplot(adata, x_axis, features, hue=None, figsize=(6, 5), ax=None, palette='tab10', title=None, xticks_rotation=None, xticks_order=None, ylim=None, ylabel='LogMean(nUMI)', legend_title=None, legend_loc='right', legend_repel=None, path=None, filename='lineplot.svg', show=False, estimator='logmean', markersize=8)

Lineplot for AnnData.

Parameters:

adata AnnData

Annotated data matrix

x_axis str

Name of a categorical column in adata.obs to groupby.

features str | list

A valid feature in adata.var_names or column in adata.obs with continuous values.

hue Union[str, Literal['features']] (default: None)

Name of a second categorical column in adata.obs to use additionally to groupby. If several features are provided, set to features.

figsize tuple (default: (6, 5))

Figure size, the format is (width, height).

ax Axes (default: None)

Matplotlib axes to use for plotting. If not set, a new figure will be generated.

palette str | dict (default: 'tab10')

String denoting matplotlib colormap. A dictionary with the categories available in adata.obs[x_axis] or adata.obs[hue] if hue is not None can also be provided. The format is {category:color}.

title str (default: None)

Title for the figure.

xticks_rotation int | None (default: None)

Rotation of the X-axis ticks.

xticks_order list (default: None)

Order for the categories in adata.obs[x_axis].

ylim tuple[int, int] (default: None)

Set limit for Y-axis.

ylabel str (default: 'LogMean(nUMI)')

Label for the Y-axis.

legend_title str (default: None)

Title for the legend.

legend_loc Literal['right', 'axis'] (default: 'right')

Location of the legend.

legend_repel dict (default: None)

Additional arguments pass to adjust_text <https://adjusttext.readthedocs.io/en/latest/>_.

path str | PathLike[str] | Path (default: None)

Path to the folder to save the figure.

filename str (default: 'lineplot.svg')

Name of file to use when saving the figure.

show bool (default: False)

If set to False, returns a dictionary with the matplotlib axes.

estimator Literal['logmean', 'mean'] (default: 'logmean')

If set to logmean, the mean will be calculated after undoing the log. The returned mean expression is also represented in log-space.

markersize int (default: 8)

Radius of the markers

Return type:

Axes | dict | None

Returns:

Depending on show, returns the plot if set to True or a dictionary with the axes.

Example

Plot the expression for a gene across several groups.

import dotools_py as do
adata = do.dt.example_10x_processed()
do.pl.lineplot(adata, 'condition', 'CD4', hue = 'annotation')

Plot the distribution of several genes at the same time.

do.pl.lineplot(adata, 'condition', ['CD4', 'CD79A'], hue = 'features')