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        "author": "Antonio Ben\u00edtez-Hidalgo",
        "author_email": "antonio.b@uma.es",
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        "classifiers": [
            "Development Status :: 3 - Alpha",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering :: Bio-Informatics"
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        "description": "<p>\n  <br/>\n  <img src=docs/sequoya-black.png alt=\"Sequoya\">\n  <br/>\n</p>\n\n<hr>\n\n# Solving Multiple Sequence Alignments with Python\n[![Build Status](https://img.shields.io/travis/benhid/Sequoya.svg?style=flat-square)](https://travis-ci.org/benhid/Sequoya)\n[![PyPI License](https://img.shields.io/pypi/l/Sequoya.svg?style=flat-square)]()\n[![PyPI Python version](https://img.shields.io/pypi/pyversions/Sequoya.svg?style=flat-square)]()\n\nSequoya is an open source software tool aimed at for solving *M*ultiple *S*equence *A*lignment problems with multi-objective metaheuristics.\n\nThis tool implements a distributed async version of the [M2Align](https://github.com/KhaosResearch/M2Align) algorithm as shown in:\n\n> \"M2Align: parallel multiple sequence alignment with a multi-objective metaheuristic\". Cristian Zambrano-Vega, Antonio J. Nebro Jos\u00e9 Garc\u00eda-Nieto, Jos\u00e9 F. Aldana-Montes. Bioinformatics, Volume 33, Issue 19, 1 October 2017, Pages 3011\u20133017 ([DOI](https://doi.org/10.1093/bioinformatics/btx338)).\n\n## Features\n* **Score functions**:\n    * Sum of pairs,\n    * Star,\n    * Minimum entropy,\n    * Percentage of non-gaps,\n    * Percentage of totally conserved columns,\n    * STRIKE.\n* **Algorithm**:\n    * NSGA-II,\n    * Distributed NSGA-II\n* **Crossover operator**:\n    * Single-point crossover (`GapSequenceSolutionSinglePoint`).\n* **Mutation operators**:\n    * Shift closest gap group (`ShiftClosedGapGroups`),\n    * Shift gap group (`ShiftGapGroup`),\n    * Random gap insertion (`OneRandomGapInsertion`),\n    * Merge two random adjacent gaps group (`TwoRandomAdjacentGapGroup`),\n    * Multiple mutation (`MultipleMSAMutation`).\n\n## Install\nTo download and install Sequoya just clone the Git repository hosted in GitHub:\n\n```console\ngit clone https://github.com/benhid/Sequoya.git\ncd Sequoya\npython setup.py install\n```\n\nOr via *pip*:\n\n```console\npip install Sequoya\n```\n\n## Usage\nExamples of running Sequoya are located in the [`examples`](examples/) folder:\n\n### Dask distributed\n\nFor running Sequoya in a cluster of machines, first [setup a network](http://distributed.dask.org/en/latest/setup.html) \nwith at least one `dask-cheduler` node and several `dask-worker` nodes:\n\n```console\nconda create --name dask-cluster\nconda activate dask-cluster\n\npip install git+https://github.com/benhid/Sequoya.git@develop\n```\n\nThen, on the master node run:\n\n```console\ndask-scheduler\n```\n\nOn each slave node run:\n\n```console\ndask-worker <master-ip>:8786 --nprocs <total-cores> --nthreads 1\n```\n\n## Authors\n### Active development team\n* [Antonio Ben\u00edtez-Hidalgo](https://benhid.com/) <antonio.b@uma.es>\n* [Antonio J. Nebro](http://www.lcc.uma.es/%7Eantonio/) <antonio@lcc.uma.es>\n\n## License\nThis project is licensed under the terms of the MIT - see the [LICENSE](LICENSE) file for details.",
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