- dynamo.pl.divergence(adata, basis='pca', color=None, cmap='bwr', frontier=True, sym_c=True, *args, **kwargs)
Scatter plot with cells colored by the estimated divergence (and other information if provided).
Cells with negative or positive divergence correspond to possible sink (stable cell types) or possible source (unstable metastable states or progenitors).
AnnData) – an Annodata object with divergence estimated.
str) – the embedding data in which the vector field was reconstructed and RNA divergence was estimated. Defaults to “pca”.
str) – The name of a matplotlib colormap to use for coloring or shading points. Defaults to “bwr”.
bool) – whether to add the frontier. Scatter plots can be enhanced by using transparency (alpha) in order to show area of high density and multiple scatter plots can be used to delineate a frontier. See matplotlib tips & tricks cheatsheet (https://github.com/matplotlib/cheatsheets). Originally inspired by figures from scEU-seq paper: https://science.sciencemag.org/content/367/6482/1151. Defaults to True.
bool) – whether do you want to make the limits of continuous color to be symmetric, normally this should be used for plotting velocity, curl, divergence or other types of data with both positive or negative values. Defaults to True.
ValueError – divergence information not found in adata.
None would be returned by default. If in kwargs save_show_or_return is set to be ‘return’ or ‘all’, the matplotlib axes object of the generated plots would be returned. If return_all is set to be true, the list of colors used and the font color would also be returned. See docs of dynamo.pl.scatters for more information.