{ "info": { "author": "Joseph D. Romano", "author_email": "jdromano2@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Environment :: Console", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Natural Language :: English", "Programming Language :: Python :: 3.6", "Topic :: Scientific/Engineering :: Bio-Informatics" ], "description": "# `VenomSeq`\nA next-generation sequencing workflow for discovering therapeutic associations between venoms and human disease.\n\n[![Build Status](https://travis-ci.com/JDRomano2/venomseq.svg?branch=master)](https://travis-ci.com/JDRomano2/venomseq)\n[![Coverage Status](https://coveralls.io/repos/github/JDRomano2/venomseq/badge.svg?branch=master)](https://coveralls.io/github/JDRomano2/venomseq?branch=master)\n- - -\n## What is this?\nVenoms provide an incredible opportunity for drug discovery. Over the course of human history, thousands of therapeutic uses for venoms have been discovered, and recent decades have seen a number of these be turned into FDA-approved drugs. However, most of these effects were discovered accidentally, and the rest were only found as the result of decades of systematic research.\n\n`VenomSeq` is a tool that aims to change this, providing a new way to generate high-thoughput sequencing data for perturbational differential expression analysis of venoms applied to human cell lines in a scalable, inexpensive manner.\n\nWe are preparing a preprint describing `VenomSeq` in-depth, and will post a link here as soon as one is available.\n\nThis python package contains the algorithms and data structures needed for analyzing the data generated by `VenomSeq`.\n- - -\n## System requirements\n`VenomSeq` has been tested with Python 3.6 on both MacOS 10.14.2 and Windows 10. If you would like to help us test on currently unsupported platforms, please submit an issue or pull request.\n- - -\n## Installing\nFrom source:\n```\ngit clone https://github.com/JDRomano2/venomseq\ncd venomseq\npip3 install .\n```\nFrom PyPI:\n```\npip3 install venomseq\n```\n\n- - -\n## Running an example\nThe Jupyter Notebook file located at `doc/examples/Visualizations.ipynb` provides an example of loading an existing `VenomSeq` analysis into memory and creating several visualizations that explain the results. 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