scimap.pl.stacked_barplot

Short description

The sm.pl.stacked_barplot function allows users to generate a stacked barplot of any two columns within the anndata.obs object. It offers two methods- i.e either to plot the absolute number of cells or plot the number of cells as a proportion of total cells (normalized to 100%). The function also incorporates two plotting tools- matplotlib and plotly. When plotly is used, the bar plot is opened in a local browser. This is especially useful when there are a large number of categories and is difficult to match the colors with the keys. plotly allows users to hover over the data and identify the group it belongs to.

Parameters

adata : AnnData object

x_axis : string, required (The default is 'imageid')
Column name of the data that need to be plotted in the x-axis.

y_axis : string, required (The default is 'phenotype')
Column name of the data that need to be plotted in the y-axis.

subset_xaxis : list, optional (The default is None)
Subset x-axis before plotting. Pass in a list of categories. eg- subset_xaxis = ['ROI_1', 'ROI_5']

subset_yaxis : list, optional (The default is None)
Subset y-axis before plotting. Pass in a list of categories. eg- subset_yaxis = ['Celltype_A', 'Celltype_B']

order_xaxis : list, optional (The default is None)
Order x-axis of the plot as needed. Pass in a list of categories. eg- order_xaxis = ['ROI_5', 'ROI_1'] The default is None and will be plotted based on alphabetic order. Please note that if you change the order, pass all categories, failure to do so will generate NaN's.

order_yaxis : list, optional (The default is None)
Order y-axis of the plot as needed. Pass in a list of categories. eg- order_yaxis = ['Celltype_B', 'Celltype_A'] The default is None and will be plotted based on alphabetic order. Please note that if you change the order, pass all categories, failure to do so will generate NaN's.

method : string, optional (The default is 'percent')
Available options: 'percent' and 'absolute'.
1) Use Percent to plot the percent proportion.
2) Use 'absolute' to plot the plot the absolute number.

plot_tool : string, optional (The default is 'matplotlib')
Available options: 'matplotlib' and 'plotly'.
1) matplotlib uses the standard python plotting method
2) plotly opens the plot in a local browser. Advantage is to be able to hover over the plot and retreive data for plots with large number of categories.

matplotlib_cmap : string, optional (The default is None)
Colormap to select colors from. If string, load colormap with that name from matplotlib.

matplotlib_bbox_to_anchor : tuple, optional (The default is (1,1.02))
Bounding box argument used along with matplotlib_legend_loc to control the legend location when using the matplotlib method.

matplotlib_legend_loc : int, optional (The default is 2)
Location of legend used along with matplotlib_bbox_to_anchor to control the legend location when using the matplotlib method.

return_data : bool, optional (The default is False)
When True, return the data used for plotting.

**kwargs : Additional keyword arguments passed to:
1) Pandas DataFrame.plot() when using the matplotlib method.
2) Plotly.bar() when using the plotly method.

Returns

Stacked bar plot. If return_data is set to True, the function also returns a dataframe of the data used for the plotting.

Example

# Plot the absolute number of phenotypes using the matplotlib tool across differnt ROI's
# ROI column is `epidermis_roi` and phenotypes are stored under `phenotype`

sm.pl.stacked_barplot (adata,x_axis='epidermis_roi',y_axis='phenotype',
                     method='absolute',plot_tool='matplotlib',figsize=(10, 10))

# Plot the number of cells normalized to 100% using the plotly tool across differnt ROI's

sm.pl.stacked_barplot (adata,x_axis='epidermis_roi',y_axis='phenotype',
                     method='percent',plot_tool='plotly',color_discrete_sequence=px.colors.qualitative.Alphabet)

# Same as above but visualize only a subset of ROI's and a subset of phenotypes
subset_xaxis = ['epidermis_1', 'epidermis_5', 'epidermis_6']
subset_yaxis = ['APCs', 'Keratinocytes', 'Macrophages']

sm.pl.stacked_barplot (adata,x_axis='epidermis_roi',y_axis='phenotype',
                     subset_xaxis=subset_xaxis,subset_yaxis=subset_yaxis,
                     method='percent',plot_tool='plotly')

# Visualize absolute number of phenotypes and return the data into a dataframe `absolute_number`
absolute_number = sm.pl.stacked_barplot (adata,x_axis='epidermis_roi',y_axis='phenotype',
                     method='absolute',plot_tool='matplotlib', return_data=True)