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 inanndata.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 whenmode = 'paga_pie'
. If None, don’t show the scatterplot.cbar (
bool
) – Whether to show colorbar whenmode = 'paga_pie'
.ncols (
Optional
[int
]) – Number of columns whenmode = 'bar'
ormode = 'paga'
.sharey (
bool
) – Whether to share y-axis whenmode = 'bar'
.fmt (
str
) – Format when usingmode = 'heatmap'
ormode = '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 formatplotlib.axes.Axes.legend()
, such as ‘loc’ for legend position. Formode = 'paga_pie'
andbasis = '...'
, this controls the placement of the fate probabilities legend.figsize – Size of the figure.
save (
Union
[str
,Path
,None
]) – Filename where to save the plot.kwargs (
Any
) – Keyword arguments forscvelo.pl.paga()
,scanpy.pl.violin()
ormatplotlib.pyplot.bar()
, depending on themode
.
- Return type:
- Returns:
: Nothing, just plots the figure. Optionally saves it based on
save
.