cellrank.tl.estimators.CFLARE.plot_lineage_drivers_correlation

CFLARE.plot_lineage_drivers_correlation(lineage_x, lineage_y, color=None, gene_sets=None, gene_sets_colors=None, use_raw=False, cmap='RdYlBu_r', fontsize=12, adjust_text=False, legend_loc='best', figsize=(4, 4), dpi=None, save=None, show=True, **kwargs)

Show scatter plot of gene-correlations between two lineages.

Optionally, you can pass a dict of gene names that will be annotated in the plot.

Parameters
  • lineage_x (str) – Name of the lineage on the x-axis.

  • lineage_y (str) – Name of the lineage on the y-axis.

  • color (Optional[str]) – Key in anndata.AnnData.var or anndata.AnnData.varm, preferring for the former.

  • gene_sets (Optional[Dict[str, Sequence[str]]]) – Gene sets annotations of the form {‘gene_set_name’: [‘gene_1’, ‘gene_2’], …}.

  • gene_sets_colors (Optional[Sequence[str]]) – List of colors where each entry corresponds to a gene set from genes_sets. If None and keys in gene_sets correspond to lineage names, use the lineage colors. Otherwise, use default colors.

  • use_raw (bool) – Whether to access anndata.AnnData.raw or not.

  • cmap (str) – Colormap to use.

  • fontsize (int) – Size of the text when plotting gene_sets.

  • adjust_text (bool) – Whether to automatically adjust text in order to reduce overlap.

  • legend_loc (Optional[str]) – Position of the legend. If None, don’t show the legend. Only used when gene_sets != None.

  • figsize (Optional[Tuple[float, float]]) – Size of the figure.

  • dpi (Optional[int]) – Dots per inch.

  • save (Union[str, Path, None]) – Filename where to save the plot.

  • show (bool) – If False, return matplotlib.pyplot.Axes.

  • kwargs (Any) – Keyword arguments for scanpy.pl.scatter().

Return type

Optional[Axes]

Returns

The axes object, if show = False. Nothing, just plots the figure. Optionally saves it based on save.

Notes

This plot is based on the following notebook by Maren Büttner.