Overview

May 26, 2022 ยท View on GitHub

Welcom to Viola Package!

.. _here: https://viola-sv.readthedocs.io

.. image:: https://viola-sv.readthedocs.io/en/latest/_static/Viola-logo/JPG/wide.jpg

|PyPI|_ |PyVersion|_ |License|_ |DOI|_ |DOC|_ |COV|_ |Issue|_ |Downloads|_

.. |PyPI| image:: https://img.shields.io/pypi/v/viola-sv .. _PyPI: https://pypi.org/project/Viola-SV/

.. |PyVersion| image:: https://img.shields.io/pypi/pyversions/viola-sv .. _PyVersion: https://pypi.org/project/Viola-SV/

.. |License| image:: https://img.shields.io/pypi/l/viola-sv .. _License: https://pypi.org/project/Viola-SV/

.. |DOI| image:: https://img.shields.io/badge/DOI-10.1093%2Fbioinformatics%2Fbtab662-9cf .. _DOI: https://academic.oup.com/bioinformatics/article/38/2/540/6371863

.. |DOC| image:: https://readthedocs.org/projects/viola-sv/badge/?version=latest .. _DOC: https://viola-sv.readthedocs.io

.. |COV| image:: https://codecov.io/gh/dermasugita/Viola-SV/branch/master/graph/badge.svg?token=G7TI1S6FY2 .. _COV: https://codecov.io/gh/dermasugita/Viola-SV

.. |Issue| image:: https://img.shields.io/badge/issue%20tracking-github-brightgreen .. _Issue: https://github.com/dermasugita/Viola-SV/issues

.. |Downloads| image:: https://pepy.tech/badge/viola-sv/month .. _Downloads: https://pepy.tech/project/viola-sv

Overview

Viola is a flexible and powerful python package designed specifically for analysis of genomic structural variant (SV) signatures. We provide following tools for SV signature analysis:

  • Custom SV classification tool
  • Feature matrix generator
  • SV signature extractor (NMF) with stability evaluation system.

In addition to these, Viola offers a number of other useful utilities, including:

  • VCF filter that accepts genomic coordinates and INFO/FORMAT columns.
  • VCF merging tool with user-defined thresholds.
  • Breakends-to-breakpoint converter with SVTYPE inference.
  • Microhomology inference.
  • VCF-to-BEDPE conversion.
  • Command line tools for light users.

Currently, Viola supports four popular SV callers as input VCF files:

  • Manta
  • Delly
  • Lumpy
  • Gridss

In the future, we plan to support more SV callers!

Installation

The package can be installed with pip:

.. code:: console

$ pip install viola-sv

To import Viola in your script, simply run below:

.. code:: python

import viola

Command line tools:

.. code:: console

$ viola [something]

Prerequisites

Python version 3.6 or newer.

Recommended Environment

  • OS
    • Linux
    • Mac
  • Script Manager
    • Jupyter Notebook/Jupyter Lab
    • Google Colaboratory

Docker support is coming soon!

How to Learn Viola

As a first step we recommend the Quick Start_ page where you can see the basic behaviour of Viola. A good second step is to read the Signature Analysis Tutorial_ page.

For command line interfaces, see CLI tutorial_.

If you want to get a deeper understanding of how Viola objects are structured, how filtering works and how merging works, please refer to the User Guide_.

Manuals for individual classes/methods/functions are available in the API Reference_.

For further discussion, please join our google group_! We're waiting for your comments, ideas, and requests. The questions about how to use Viola-SV are also welcome!

.. _google group: https://groups.google.com/g/viola-users

Documentation

  • Documentation Home_
  • Quick Start_
  • Signature Analysis Tutorial_
  • API Reference_

.. _Documentation Home: https://viola-sv.readthedocs.io/ .. _Quick Start: https://viola-sv.readthedocs.io/en/1.0.x-stable-doc/quickstart.html .. _Signature Analysis Tutorial: https://viola-sv.readthedocs.io/en/1.0.x-stable-doc/signature_analysis.html .. _API Reference: https://viola-sv.readthedocs.io/en/1.0.x-stable-doc/reference/index.html .. _User Guide: https://viola-sv.readthedocs.io/en/1.0.x-stable-doc/userguide/index.html .. _CLI tutorial: https://viola-sv.readthedocs.io/en/1.0.x-stable-doc/userguide/cli.html

Publications

Sugita, I., Matsuyama, S., Dobashi, H., Komura, D. & Ishikawa, S. Viola: a structural variant signature extractor with user-defined classifications. Bioinformatics (2021) doi:10.1093/bioinformatics/btab662.