Source code for dynamo.plot.cell_cycle

from anndata import AnnData
from matplotlib.axes import Axes
from typing import Union, Optional

from ..tools.utils import update_dict
from .utils import save_fig


[docs]def cell_cycle_scores( adata: AnnData, cells: Optional[list] = None, save_show_or_return: str = "show", save_kwargs: dict = {}, ) -> Union[None, Axes]: """Plot a heatmap of cells ordered by cell cycle position Parameters ---------- adata: :class:`~anndata.AnnData` cells: a list of cell ids used to subset the adata object. save_show_or_return: Whether to save, show or return the figure. save_kwargs: A dictionary that will passed to the save_fig function. By default it is an empty dictionary and the save_fig function will use the {"path": None, "prefix": 'scatter', "dpi": None, "ext": 'pdf', "transparent": True, "close": True, "verbose": True} as its parameters. Otherwise you can provide a dictionary that properly modify those keys according to your needs. """ import seaborn as sns import matplotlib.pyplot as plt from mpl_toolkits.axes_grid1.axes_divider import make_axes_locatable from matplotlib.pyplot import colorbar if cells is None: cell_cycle_scores = adata.obsm["cell_cycle_scores"].dropna() else: cell_cycle_scores = adata[cells, :].obsm["cell_cycle_scores"].dropna().dropna() cell_cycle_scores.sort_values( ["cell_cycle_phase", "cell_cycle_progress"], ascending=[True, False], inplace=True, ) # based on https://stackoverflow.com/questions/47916205/seaborn-heatmap-move-colorbar-on-top-of-the-plot # answwer 4 # plot heatmap without colorbar ax = sns.heatmap( cell_cycle_scores[["G1-S", "S", "G2-M", "M", "M-G1"]].transpose(), annot=False, xticklabels=False, linewidths=0, cbar=False, ) # # split axes of heatmap to put colorbar ax_divider = make_axes_locatable(ax) # define size and padding of axes for colorbar cax = ax_divider.append_axes("right", size="2%", pad="0.5%", aspect=4, anchor="NW") # make colorbar for heatmap. # Heatmap returns an axes obj but you need to get a mappable obj (get_children) colorbar(ax.get_children()[0], cax=cax, ticks=[-0.9, 0, 0.9]) if save_show_or_return == "save": s_kwargs = { "path": None, "prefix": "plot_direct_graph", "dpi": None, "ext": "pdf", "transparent": True, "close": True, "verbose": True, } s_kwargs = update_dict(s_kwargs, save_kwargs) save_fig(**s_kwargs) elif save_show_or_return == "show": plt.tight_layout() plt.show() elif save_show_or_return == "return": return ax