pycallingcards.plotting.dotplot_bulk#

pycallingcards.plotting.dotplot_bulk(adata_cc, rna, selected_list, num_list, xticklabels=None, group=None, figsize=(12, 15), dotsize=5, cmap='Reds', title='DE binding & RNA', topspace=0.977, sort_by_chrom=False, bysample=False, legend=False, cax=[0.05, 0.085, 0.2, 0.03], save=False)[source]#

Plot ranking of peaks.

Parameters:

  • adata_cc (AnnData) – Anndata of peak.

  • rna (DataFrame) – pd.DataFrame of RNA expression.

  • selected_list (list) – A list of peak to be shown.

  • num_list (list) – The distribution of samples in RNA. eg. the first three columns for RNA is female and the following two columns is male data, then num_list should be [3,2]

  • xticklabels (Optional[list] (default: None)) – xticklabels for the column. If None, it will be the index of adata_cc.obs.

  • group (Optional[str] (default: None)) – The group information in anndata object if (sample*peak). It will read anndata.obs[group].

  • figsize (Tuple[int, int] (default: (12, 15))) – The size of the figure.

  • dotsize (float (default: 5)) – The relative size of dots.

  • cmap (str (default: 'Reds')) – The colormap of the plot.

  • title (str (default: 'DE binding & RNA')) – The title of the plot.

  • topspace (float (default: 0.977)) – Parameter to control the title position.

  • sort_by_chrom (bool (default: False)) – If True, it would sort by chr1, chr2, etc. sort_by_chrom can not be applied to yeast data.

  • bysample (bool (default: False)) – If True, it display one column as a sample. If False, it display one column as a group.

  • legend (bool (default: False)) – If True, it would show the legend.

  • cax (list (default: [0.05, 0.085, 0.2, 0.03])) – The position of the legend for.

  • save (bool (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 would be saved as a png file.

Example:

>>> import pycallingcards as cc
>>> adata_cc = cc.datasets.mouse_brd4_data(data = "CC")
>>> rna = cc.datasets.mouse_brd4_data(data = "RNA")
>>> cc.pl.dotplot_bulk(adata_cc,rna,
               selected_list = ['chr1_72823300_72830641', 'chr1_174913218_174921560',
                'chr4_68545354_68551370', 'chr5_13001870_13004057',
                'chr5_13124523_13131816', 'chr5_13276480_13283561',
                'chr5_16764617_16770523', 'chr5_17080322_17085124',
                'chr7_55291506_55293906', 'chr7_56523379_56528437',
                'chr8_102778665_102784309', 'chr10_57783900_57788071',
                'chr11_46057069_46059464', 'chr12_56507583_56514677',
                'chr14_88460574_88466755', 'chr14_88898126_88902522',
                'chr15_11743635_11745457', 'chr15_11781285_11785784',
                'chr15_11823522_11836910', 'chr19_59158212_59161670',
                'chrY_1241882_1246464', 'chrY_1282449_1287505'] ,
               num_list = [3,3],figsize = [12,8])