omicverse.pl.single_group_boxplot

omicverse.pl.single_group_boxplot(adata, groupby='', color='', type_color_dict=None, title='', ylabel='', kruskal_test=False, figsize=(4, 4), x_ticks_plot=False, legend_plot=True, bbox_to_anchor=(1, 0.55), save=False, point_number=5, save_pathway='', sort=True, scatter_kwargs=None, ax=None, fontsize=12)

adata (AnnData object): The data object containing the information for plotting. groupby (str): The variable used for grouping the data. color (str): The variable used for coloring the data points. type_color_dict (dict): A dictionary mapping group categories to specific colors. title (str): The title for the plot. ylabel (str): The label for the y-axis. kruskal_test (bool): Whether to perform a Kruskal-Wallis test and display the p-value on the plot. figsize (tuple): The size of the plot figure in inches (width, height). x_ticks_plot (bool): Whether to display x-axis tick labels. legend_plot (bool): Whether to display a legend for the groups. bbox_to_anchor (tuple): The position of the legend bbox (x, y) in axes coordinates. save (bool): Whether to save the plot to a file. point_number (int): The number of data points to be plotted for each group. save_pathway (str): The file path for saving the plot (if save is True). sort (bool): Whether to sort the groups based on their mean values. scatter_kwargs (dict): Additional keyword arguments for customizing the scatter plot. ax (matplotlib.axes.Axes): A pre-existing axes object for plotting (optional).

Examples

ov.pl.single_group_boxplot(adata,groupby=’clusters’,

color=’Sox_aucell’, type_color_dict=dict(zip(pd.Categorical(adata.obs[‘clusters’]).categories, adata.uns[‘clusters_colors’])), x_ticks_plot=True, figsize=(5,4), kruskal_test=True, ylabel=’Sox_aucell’, legend_plot=False, bbox_to_anchor=(1,1), title=’Expression’, scatter_kwargs={‘alpha’:0.8,’s’:10,’marker’:’o’},

point_number=15, sort=False, save=False, )