pycallingcards.plotting.rank_peak_groups#

pycallingcards.plotting.rank_peak_groups(adata_cc, groups=None, n_peaks=10, peak_symbols=None, key='binomtest', rankby='pvalues', fontsize=8, ncols=4, sharey=True, show=True, save=False)[source]#

Plot ranking of peaks.

Parameters:

  • adata_cc (AnnData) – Annotated data matrix.

  • groups (Union[str, Sequence[str], None] (default: None)) – The groups used to show the peak ranking.

  • n_peaks (int (default: 10)) – Number of peaks that appear in the returned tables.

  • peak_symbols (Optional[str] (default: None)) – Key for field in .var that stores peak symbols if you do not want to use .var_names.

  • key (Optional[str] (default: 'binomtest')) – Key for the name of the cluster.

  • fontsize (int (default: 8)) – Fontsize for peak names.

  • ncols (int (default: 4)) – Number of panels shown per row.

  • sharey (bool (default: True)) – Controls if the y-axis of each panels will be shared or not. By passing sharey=False, each panel has its own y-axis range.

  • show (Optional[bool] (default: True)) – Controls if the plot shows or not.

  • save (Union[bool, str] (default: False)) – Could be bool or str indicating the file name it would be saved as. If True, a default name would be given and the plot will be saved as a png file.

Example:

>>> import pycallingcards as cc
>>> adata_cc = cc.datasets.mousecortex_data(data="CC")
>>> cc.pl.rank_peak_groups(adata_cc,key = 'binomtest')