Skip to main content

A read visualizer for structural variants

Project description

https://raw.githubusercontent.com/svviz/svviz/master/docs/example.png

svviz

Author: Noah Spies

Latest version: pypi

svviz visualizes high-throughput sequencing data relevant to a structural variant. Only reads supporting the variant or the reference allele will be shown. svviz can operate in both an interactive web browser view to closely inspect individual variants, or in batch mode, allowing multiple variants (annotated in a VCF file) to be analyzed simultaneously.

Visit the project site for a tour of the features and example output.

Quickstart

svviz has been tested on Mac OS X and Linux, and should work on Windows, although that has not been tested.

  1. Ensure that you have a working compiler by following these instructions (OS X only) and that python and the python package pip are installed.

  2. Install the latest version of svviz from github using the following terminal command: sudo pip install -U svviz. (The sudo may not be necessary depending on your setup.)

  3. Run the following command, which downloads example data and runs it through svviz: svviz demo. After several processing steps, a web browser window should open, with separate, interactive views of the reference and alternate alleles.

See the documentation for more detailed help, or run svviz -h to get help on command line arguments.

Please submit bug reports or feature requests on the github issue tracker.

Publication

svviz has been published in Bioinformatics. If you found svviz useful for your research, please cite svviz as follows:

Spies N, Zook JM, Salit M, Sidow A. 2015. svviz: a read viewer for validating structural variants. Bioinformatics doi:bioinformatics/btv478.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

svviz-1.6.2.tar.gz (317.3 kB view hashes)

Uploaded Source

Built Distribution

svviz-1.6.2-cp36-cp36m-macosx_10_9_x86_64.whl (340.8 kB view hashes)

Uploaded CPython 3.6m macOS 10.9+ x86-64

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page