{"id":20644642,"url":"https://github.com/epistasislab/autoqtl","last_synced_at":"2026-03-14T07:32:52.410Z","repository":{"id":74011813,"uuid":"519299177","full_name":"EpistasisLab/autoqtl","owner":"EpistasisLab","description":"Automated Quantitative Trait Locus Analysis (AutoQTL)","archived":false,"fork":false,"pushed_at":"2024-03-05T22:12:03.000Z","size":27977,"stargazers_count":8,"open_issues_count":0,"forks_count":3,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-04-16T02:08:15.871Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/EpistasisLab.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,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2022-07-29T17:35:11.000Z","updated_at":"2024-08-05T16:10:40.000Z","dependencies_parsed_at":null,"dependency_job_id":"eb60cf18-a61b-4647-bb99-54e4e2939d67","html_url":"https://github.com/EpistasisLab/autoqtl","commit_stats":null,"previous_names":[],"tags_count":7,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EpistasisLab%2Fautoqtl","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EpistasisLab%2Fautoqtl/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EpistasisLab%2Fautoqtl/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EpistasisLab%2Fautoqtl/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/EpistasisLab","download_url":"https://codeload.github.com/EpistasisLab/autoqtl/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":249183105,"owners_count":21226142,"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":[],"created_at":"2024-11-16T16:17:07.758Z","updated_at":"2026-03-14T07:32:47.362Z","avatar_url":"https://github.com/EpistasisLab.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# autoqtl\n\n[![Logo](./docs/FinalLogo_Big.png)]()\n\nAutoQTL : Automated Quantitative Trait Locus Analysis\n==================================\n\n**AutoQTL** is an automated machine learning tool for QTL analysis.\nThe goal of AutoQTL is to automate QTL analysis by building an analytics pipeline optimized for explaining variation in a quantitative trait given a set of genetic variants. It uses genetic programming (GP) as the search and optimization method. \n\nAutoQTL is recommended to be used as a posthoc analysis to genome-wide association/QTL analysis. AutoQTL aims to provide additional insights into the association of phenotype to genotype including, but not limited to, the detection of non-additive genetic inheritance models and epistatic interactions. Furthermore, our feature importance metrics, in tandem with summary statistics, can provide additional evidence for the identification of putative QTL and targets for gene set enrichment and KEGG pathway analysis. \n\n#geneticsmeetsautoML\n\n## Installing \u0026 Running AutoQTL\n\nWe recommend installing the Python package 'autoqtl' from the pypi repository to run AutoQTL. \n[The package can be found at](https://pypi.org/project/autoqtl/#description) \n\nWe also recommend using conda environments for installing Autoqtl, but it is not necessary. \nRecommended installation:\n```\nconda create --name autoqtl_env python=3.10\nconda activate autoqtl_env\npip install autoqtl\n```\n\nAfter installation, the 'demo.ipynb' jupyter notebook in the tutorials folder can be used as a reference to run AutoQTL.  \n\nAnyone interested in exploring the code base of AutoQTL further, can clone the repository, make a conda environment using the requirements.txt file and try out new things.\n\nThis software is built as part of a proof-of-concept and hence is still under development.  \nWe continue to work on to add new features and functionality to AutoQTL. \nSuggestions are welcome.\n\n## License\n\nPlease see the [repository license](https://github.com/EpistasisLab/autoqtl/blob/master/LICENSE) for licensing and usage information.\nAutoqtl is open source and freely available but citation is required.\n\n## Citing AutoQTL\n\nIf you use AutoQTL in a scientific publication, please consider citing the following paper:\n\nPhilip J. Freda, Attri Ghosh, Elizabeth Zhang, Tianhao Luo, Apurva S. Chitre, Oksana Polesskaya, Celine L. St. Pierre, Jianjun Gao,\nConnor D. Martin, Hao Chen, Angel G. Garcia-Martinez, Tengfei Wang, Wenyan Han, Keita Ishiwari, Paul Meyer, Alexander Lamparelli,\nChristopher P. King, Abraham A. Palmer, Ruowang Li and Jason H. Moore. [Automated quantitative trait locus analysis (AutoQTL)](https://biodatamining.biomedcentral.com/articles/10.1186/s13040-023-00331-3). *BioData Mining* 16, Article number: 14 (2023)\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fepistasislab%2Fautoqtl","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fepistasislab%2Fautoqtl","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fepistasislab%2Fautoqtl/lists"}