pysumstats.plot¶

pysumstats.plot, a subpackage for generating plots from summary statistics data

Manhattan plot¶

plot.manhattan(fig=None, ax=None, filename=None, sigp=5e-08, sigcolor='black', sugp=1e-05, sugcolor='black', pointcolors=['midnightblue', 'goldenrod'], figsize=(12, 6), highlight=[], highlightcolors=['orange'], title=None, rainbow=False)¶

Create a Manhattan plot.

Parameters:

dataframe – pd.Dataframe containing the following columns: [‘rsid’, ‘chr’, ‘bp’, ‘p’], or pysumstats.SumStats
fig – matplotlib.pyplot figure object to plot to (if not specified a new figure will be created)
ax – matplotlib.pyplot axis to plot to (if not specified a new figure will be created)
filename (str.) – Path to store the figure to (defaults to return fig, ax objects)
sigp (float) – Where to plot significant line(set to a negative number to remove)
sigcolor (str) – Color to use for significant line
sugp (float) – Where to plot significant line (set to a negative number to remove)
sugcolor (str) – Color to use for suggestive line
pointcolors (list) – List of colors to cycle through for plotting SNPs
figsize ((float, float)) – Figure size in inches (width, height)
highlight (list.) – list of SNPs to highlight
highlightcolors (list.) – List of colors to cycle through for highlighting SNPs
title (list.) – Main figure title
rainbow (bool.) – Enble rainbow colors

Returns:

None, or (fig, ax)

QQ plot¶

plot.qqplot(fig=None, ax=None, filename=None, figsize=(8, 8), pointcolor='black', title=None, linecolor='red')¶

Function to generate a QQ-plot.

Parameters:

pvector – 1D-array of p-values
fig – matplotlib.pyplot figure object to plot to (if not specified a new figure will be created)
ax – matplotlib.pyplot axis to plot to (if not specified a new figure will be created)
filename (str.) – Path to store the figure to (defaults to return fig, ax objects)
figsize ((float, float)) – Figure size in inches (width, height)
pointcolor (str.) – Color to use for points
title (str.) – Main figure title.
linecolor (str.) – Color for line x=y

Returns:

None, or (fig, ax)

PZ plot¶

plot.pzplot(twotailed=True, difference_cutoff=0.1, fig=None, ax=None, filename=None, pointcolor='black', differentcolor='red', linecolor='black', differentlinecolor='red', title=None, figsize=(5, 5))¶

Generate a plot comparing the z-value as calculated from the p-value to the z-value as calculated from beta/se

Parameters:

data – 2D-array containing the columns [‘b’, ‘se’, ‘p’]
twotailed (bool) – True if p-value was computed from both ends of the distribution.
difference_cutoff (None or float) – Cut-off to use for highlighting SNPs with different z-values (to disable use None)
fig – matplotlib.pyplot figure object to plot to (if not specified a new figure will be created)
ax – matplotlib.pyplot axis to plot to (if not specified a new figure will be created)
filename (str) – Path to store the figure to (defaults to return fig, ax objects)
pointcolor (str) – Color to use for points
differentcolor (str) – Color to use for points that deviate given difference_cutoff
linecolor (str) – Color to use for the line x=y
differentlinecolor (str) – Color to use for visualizing the difference_cutoff
title (str.) – Main figure title.
figsize ((int, int)) – Figure size

Returns:

None or (fig, ax)

AF plot¶

plot.afplot(other_af, refname='ref_EAF', othername='other_EAF', difference_cutoff=0.1, fig=None, ax=None, filename=None, pointcolor='black', differentcolor='red', linecolor='black', differentlinecolor='red', title=None, figsize=(5, 5))¶

Generate a plot of (differences in) allele frequencies of two summary statistics.

Parameters:

ref_af – 1D-array of reference allele frequencies
other_af – 1D-array of other allele frequencies
refname (str) – Name to use for reference allele frequencies (x-axis label)
othername (str) – Name to use for other allele frequencies (y-axis label)
difference_cutoff (None or float) – Cut-off to use for highlighting SNPs with different allele frequency (to disable use None)
fig – matplotlib.pyplot figure object to plot to (if not specified a new figure will be created)
ax – matplotlib.pyplot axis to plot to (if not specified a new figure will be created)
filename (str) – Path to store the figure to (defaults to return fig, ax objects)
pointcolor (str) – Color to use for points
differentcolor (str) – Color to use for points that deviate given difference_cutoff
linecolor (str) – Color to use for the line x=y
differentlinecolor (str) – Color to use for visualizing the difference_cutoff
title (str.) – Main figure title.
figsize ((int, int)) – Figure size

Returns:

None or (fig, ax)

ZZ plot¶

plot.zzplot(data_y, xname='Z_x', yname='Z_y', twotailed=True, difference_cutoff=0.5, fig=None, ax=None, filename=None, pointcolor='black', differentcolor='red', linecolor='black', differentlinecolor='red', title=None, figsize=(5, 5))¶

Generate a plot comparing the z-values from two GWAS summary statistics

Parameters:

data_x – 2D-array containing the column ‘z’, the columns [‘b’, ‘se’] or the column ‘p’ (this is priority order)
data_y – 2D-array containing the column ‘z’, the columns [‘b’, ‘se’] or the column ‘p’ (this is priority order)
twotailed (bool) – True if p-value was computed from both ends of the distribution.
xname (str) – Name to use for z_values of data_x (x-axis label)
yname (str) – Name to use for z_values of data_y (y-axis label)
difference_cutoff (None or float) – Cut-off to use for highlighting SNPs with different z-values (to disable use None)
fig – matplotlib.pyplot figure object to plot to (if not specified a new figure will be created)
ax – matplotlib.pyplot axis to plot to (if not specified a new figure will be created)
filename (str) – Path to store the figure to (defaults to return fig, ax objects)
pointcolor (str) – Color to use for points
differentcolor (str) – Color to use for points that deviate given difference_cutoff
linecolor (str) – Color to use for the line x=y
differentlinecolor (str) – Color to use for visualizing the difference_cutoff
title (str.) – Main figure title.
figsize ((int, int)) – Figure size

Returns:

None or (fig, ax)