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Cell Copy Number Plots

Cell Copy Number Plots#

scgenome provides functionality for plotting the copy number of individual cells or clones with chromosomes on the x axis.


import scgenome
import matplotlib.pyplot as plt

adata = scgenome.datasets.OV2295_HMMCopy_reduced()

HMMCopy Copy Number Plot#

The scgenome.pl.plot_cn_profile plots copy number as a scatter plot with copy number on the y axis and the genome on the x axis. Scatter points can be colored using a standard copy number color palette. The value_layer_name arg specifies which layer to use as the y value and state_layer_name which layer to use as the integer copy number state. The obs_id specifies the obs index value to plot.


cell_id = 'SA922-A90554B-R27-C43'

plt.figure(figsize=(10, 2))
scgenome.pl.plot_cn_profile(
    adata, cell_id,
    value_layer_name='copy',
    state_layer_name='state')

scgenome.pl.cn_legend(plt.gca())

Specific chromosomes can also be plotted using the chromosome keyword arg.


plt.figure(figsize=(10, 2))
scgenome.pl.plot_cn_profile(
    adata, cell_id,
    value_layer_name='copy',
    state_layer_name='state',
    chromosome='2',
    squashy=True)

scgenome.pl.cn_legend(plt.gca())

Restrict to a specific region using the start and end arguments.


plt.figure(figsize=(10, 2))
scgenome.pl.plot_cn_profile(
    adata, cell_id,
    value_layer_name='copy',
    state_layer_name='state',
    chromosome='2',
    start=80000000,
    end=200000000,
    squashy=True)

scgenome.pl.cn_legend(plt.gca())

Often the majority of the copy number information is in the range of 0-7 copies. However, limiting the y axis to 0-7 would now show high level amplifications. Set the squashy kwarg to True to use a non-linear scaling to compress the y-axis values, high-lighting the 0-7 copies range while still showing high level amplifications.


plt.figure(figsize=(10, 2))
scgenome.pl.plot_cn_profile(
    adata, cell_id,
    value_layer_name='copy',
    state_layer_name='state',
    squashy=True)

scgenome.pl.cn_legend(plt.gca())

Set rawy=True to show raw copy number values or reads. Below we set value_layer_name=None to use X for the y values, plotting the raw read counts that are stored in X.


plt.figure(figsize=(10, 2))
scgenome.pl.plot_cn_profile(
    adata, cell_id,
    value_layer_name=None)



plt.figure(figsize=(10, 2))
scgenome.pl.plot_profile(adata[:, adata.var['gc'] > 0].var, 'gc')
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