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Plot variants on the human mitochondrial genome.

Project description

mitoviz Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public. Documentation Status Python 3

Plot variants on the human mitochondrial genome.


mitoviz is a simple python package to plot human mitochondrial variants on a graphical representation of the human mitochondrial genome. It currently supports plotting variants stored in a VCF file.

Variants are shown according to their heteroplasmic fraction (HF), plotting variants with HF = 1.0 on the outer border of the mitochondrial circle, those with HF = 0.0 on the inner border and all the others according to their actual HF value.

Mitochondrial plot with HF

If the HF information is not available, variants will all be shown in the middle of the mitochondrial circle.

Mitochondrial plot without HF


mitoviz can be used both from the command line and as a python module.

Command Line

Given a VCF file with human mitochondrial variants (sample.vcf), plotting them is fairly simple:

$ mitoviz sample.vcf

An image named mitoviz.png will be created in the current directory.

If you want to provide a specific filename where the plot will be saved, just add the --output option with the desired path:

$ mitoviz sample.vcf --output my_mt_plot.png

Python Module

Import mitoviz and use its plot_vcf function to use it in your own script:

from mitoviz import plot_vcf

my_plot = plot_vcf("sample.vcf")

In this case, no plot will be shown until a call to is made. It is possible to save the resulting plot using the save option and to provide a specific file where the plot will be saved using the output option:

from mitoviz import plot_vcf

plot_vcf("sample.vcf", save=True, output="my_mt_plot.png")

Please refer to the Usage section of the documentation for further information.


PLEASE NOTE: HmtNote only supports Python >= 3.6!

The preferred installation method for mitoviz is using pip:

$ pip install mitoviz

Please refer to the Installation section of the documentation for further information.


This package was created with Cookiecutter and the cc-pypackage project template.


0.1.0 (2019-12-27)

  • First release.

Project details

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