Streamgraph API

Streamgraph FUNCTION

This API provides a function to create a streamgraph from KEGGaNOG multi-sample output. It visualizes completeness values of pathway groups across multiple samples using a flowing stacked area plot.

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PARAMETERS

PARAMETER	DESCRIPTION
df	Input data as a pandas DataFrame TYPE: pd.DataFrame
figsize	Size of the figure (width, height) TYPE: Tuple[int, int] DEFAULT: (14, 7)
bar_width	Width parameter for sample TYPE: float DEFAULT: 0.6
cmap	Colormap name (e.g. "tab20") or list of HEX colors for groups TYPE: str or List[str] DEFAULT: "tab20"
fill_alpha	Transparency of the filled area TYPE: float DEFAULT: 1.0
edgecolor	Outline color for each stacked area (group layer) TYPE: str or None DEFAULT: None
edge_linewidth	Width of group layer outlines TYPE: float DEFAULT: 0.3
title	Plot title TYPE: str or None DEFAULT: None
title_fontsize	Font size of the title TYPE: float DEFAULT: 16.0
title_color	Font color of the title TYPE: str DEFAULT: "black"
title_weight	Font weight of the title TYPE: str DEFAULT: "normal"
title_style	Font style of the title TYPE: str DEFAULT: "normal"
xlabel	Label for the x-axis TYPE: str DEFAULT: "Samples"
xlabel_fontsize	Font size for x-axis label TYPE: float DEFAULT: 12.0
xlabel_color	Font color of x-axis label TYPE: str DEFAULT: "black"
xlabel_weight	Font weight of x-axis label TYPE: str DEFAULT: "normal"
xlabel_style	Font style of x-axis label TYPE: str DEFAULT: "normal"
ylabel	Label for the y-axis TYPE: str DEFAULT: "Total Completeness"
ylabel_fontsize	Font size for y-axis label TYPE: float DEFAULT: 12.0
ylabel_color	Font color of y-axis label TYPE: str DEFAULT: "black"
ylabel_weight	Font weight of y-axis label TYPE: str DEFAULT: "normal"
ylabel_style	Font style of y-axis label TYPE: str DEFAULT: "normal"
xticks_rotation	Rotation angle of x-axis tick labels TYPE: float DEFAULT: 45.0
xticks_ha	Horizontal alignment of x-axis tick labels TYPE: str DEFAULT: "center"
xticks_fontsize	Font size of x-axis tick labels TYPE: float DEFAULT: 12.0
xticks_color	Font color of x-axis tick labels TYPE: str DEFAULT: "black"
xticks_weight	Font weight of x-axis tick labels TYPE: str DEFAULT: "normal"
xticks_style	Font style of x-axis tick labels TYPE: str DEFAULT: "normal"
grid	Whether to show grid lines TYPE: bool DEFAULT: True
grid_linestyle	Grid line style (e.g. "--") TYPE: str DEFAULT: "--"
grid_alpha	Transparency of grid lines TYPE: float DEFAULT: 0.7
legend_fontsize	Font size of legend labels TYPE: float DEFAULT: 9.0
legend_loc	Legend position keyword TYPE: str DEFAULT: "upper left"
legend_bbox	Manual legend box anchor TYPE: Tuple[float, float] DEFAULT: (1.05, 1)
show_legend	Whether to display legend TYPE: bool DEFAULT: True
background_color	Background color of the figure TYPE: str or None DEFAULT: None

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RETURNS

Returns an object with:

• fig: the Matplotlib figure
• ax: the Matplotlib axis

The object includes .plotfig() and .savefig() methods for visualization or export.

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USAGE EXAMPLE

First, run KEGGaNOG in multi-sample mode:

Where to get demo data? Here

! KEGGaNOG -M -i demo_data/listFile.txt -o KEGGaNOG_multi_output

Then you can visualize pathway group completeness across samples:

import kegganog as kgn
import pandas as pd

df = pd.read_csv("KEGGaNOG_multi_output/merged_pathways.tsv", sep="\t")

kgnstream = kgn.streamgraph(
    df,
    figsize=(14, 7),
    cmap="tab20",
    xlabel="Samples",
    ylabel="Completeness",
    edgecolor="black",
    grid=True
    )

# Show the figure
kgnstream.plotfig()

Sample output:

To save the plot:

kgnstream.savefig("pic_name.png", dpi=600)