{"id":22213219,"url":"https://github.com/benhid/sequoya","last_synced_at":"2025-07-27T12:31:05.249Z","repository":{"id":57465763,"uuid":"119516521","full_name":"benhid/Sequoya","owner":"benhid","description":"Solving Multiple Sequence Alignment (MSA) problems with multi-objective metaheuristics","archived":false,"fork":false,"pushed_at":"2020-03-10T13:17:47.000Z","size":116596,"stargazers_count":17,"open_issues_count":3,"forks_count":3,"subscribers_count":3,"default_branch":"master","last_synced_at":"2024-12-02T11:57:14.883Z","etag":null,"topics":["metaheuristics","msa","multiple-sequence-alignment","optimization","python","sequence-alignments"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/benhid.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2018-01-30T09:53:29.000Z","updated_at":"2024-04-02T00:13:33.000Z","dependencies_parsed_at":"2022-09-15T01:20:34.471Z","dependency_job_id":null,"html_url":"https://github.com/benhid/Sequoya","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benhid%2FSequoya","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benhid%2FSequoya/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benhid%2FSequoya/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benhid%2FSequoya/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/benhid","download_url":"https://codeload.github.com/benhid/Sequoya/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":227802878,"owners_count":17822113,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["metaheuristics","msa","multiple-sequence-alignment","optimization","python","sequence-alignments"],"created_at":"2024-12-02T21:09:05.956Z","updated_at":"2024-12-02T21:09:06.620Z","avatar_url":"https://github.com/benhid.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp\u003e\n  \u003cbr/\u003e\n  \u003cimg src=docs/sequoya-black.png alt=\"Logo\"\u003e\n  \u003cbr/\u003e\n\u003c/p\u003e\n\n\u003chr\u003e\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\n*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\u003e \"M2Align: parallel multiple sequence alignment with a multi-objective metaheuristic\". Cristian Zambrano-Vega, Antonio J. Nebro José García-Nieto, José F. Aldana-Montes. Bioinformatics, Volume 33, Issue 19, 1 October 2017, Pages 3011–3017 ([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 \u003cmaster-ip\u003e:8786 --nprocs \u003ctotal-cores\u003e --nthreads 1\n```\n\n## Authors\n### Active development team\n* [Antonio Benítez-Hidalgo](https://benhid.com/) \u003cantonio.b@uma.es\u003e\n* [Antonio J. Nebro](http://www.lcc.uma.es/%7Eantonio/) \u003cantonio@lcc.uma.es\u003e\n\n## License\nThis project is licensed under the terms of the MIT - see the [LICENSE](LICENSE) file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenhid%2Fsequoya","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbenhid%2Fsequoya","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenhid%2Fsequoya/lists"}