cellrank.pl.aggregate_fate_probabilities#

cellrank.pl.aggregate_fate_probabilities(adata, mode=AggregationMode.PAGA_PIE, backward=False, lineages=None, cluster_key='clusters', clusters=None, basis=None, cbar=True, ncols=None, sharey=False, fmt='0.2f', xrot=90, legend_kwargs=mappingproxy({'loc': 'best'}), figsize=None, dpi=None, save=None, **kwargs)[source]#

Plot aggregate lineage probabilities at a cluster level.

This can be used to investigate how likely a certain cluster is to go to the terminal states, or in turn to have descended from the initial states. For mode ‘paga’ and ‘paga_pie’, we use PAGA [Wolf et al., 2019].

Parameters:

  • adata (AnnData) – Annotated data object.

  • mode (Literal['bar', 'paga', 'paga_pie', 'violin', 'heatmap', 'clustermap']) –

    Type of plot to show. Valid options are:

    • ’bar’ - barplot, one panel per cluster. The whiskers correspond to the standard error of the mean.

    • ’paga’ - scanpy’s PAGA, one per initial or terminal state, colored in by fate.

    • ’paga_pie’ - scanpy’s PAGA with pie charts indicating aggregated fates.

    • ’violin’ - violin plots, one per initial or terminal state.

    • ’heatmap’ - a heatmap, showing average fates per cluster.

    • ’clustermap’ - same as a heatmap, but with a dendrogram.

  • backward (bool) – Direction of the process.

  • lineages (Union[str, Sequence[str], None]) – Lineages for which to visualize fate probabilities. If None, use all lineages.

  • cluster_key (Optional[str]) – Key in anndata.AnnData.obs containing the clusters.

  • clusters (Union[str, Sequence[str], None]) – Clusters to visualize. If None, all clusters will be plotted.

  • basis (Optional[str]) – Basis for scatterplot to use when mode = 'paga_pie'. If None, don’t show the scatterplot.

  • cbar (bool) – Whether to show colorbar when mode = 'paga_pie'.

  • ncols (Optional[int]) – Number of columns when mode = 'bar' or mode = 'paga'.

  • sharey (bool) – Whether to share y-axis when mode = 'bar'.

  • fmt (str) – Format when using mode = 'heatmap' or mode = 'clustermap'.

  • xrot (float) – Rotation of the labels on the x-axis.

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

  • legend_kwargs (Mapping[str, Any]) – Keyword arguments for matplotlib.axes.Axes.legend(), such as ‘loc’ for legend position. For mode = 'paga_pie' and basis = '...', this controls the placement of the fate probabilities legend.

  • figsize – Size of the figure.

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

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

  • kwargs (Any) – Keyword arguments for scvelo.pl.paga(), scanpy.pl.violin() or matplotlib.pyplot.bar(), depending on the mode.

Return type:

None

Returns:

: Nothing, just plots the figure. Optionally saves it based on save.