Quality control histogram plot

This visualization function can be launched from class DigitalCellSorter at the stage of post-processing.

From submodule VisualizationFunctions:

class VisualizationFunctions(dataName='dataName', saveDir='', matplotlibMode='Agg', safePlotting=True, verbose=1)

Class of visualization functions for DigitalCellSorter

makeQualityControlHistogramPlot(*args, **kwargs)

Function to calculate QC quality cutoff and visualize it on a histogram

Parameters:

subset: pandas.Series

Data to analyze

cutoff: float

Cutoff to display

plotPathAndName: str, Default None

Text to include in the figure title and file name

N_bins: int, Default 100

Number of bins of the histogram

mito: boolean, Default False

Whether the analysis of mitochondrial genes fraction

displayMeasures: boolean, Default True

Print vertical dashed lines along with mean, median, and standard deviation

precision: int, Default 4

Number of digits after decimal

quantilePlotCutoff: float, Default 0.99

Distributions are cut to display the range from 0 to quantilePlotCutoff

dpi: int, Default 600

Resolution of the figure image

extension: str, Default ‘png’

Format of the figure file

fontScale: float, Default 1.5

Scale most of the figure fonts

includeTitle: boolean, Default False

Whether to include title on the figure

Returns:

None

Usage:

DCS = DigitalCellSorter.DigitalCellSorter()

cutoff = DCS.makeQualityControlHistogramPlot(subset, cutoff)

Example output: