{"id":21280602,"url":"https://github.com/borgwardtlab/lmm-lasso","last_synced_at":"2025-07-11T10:32:27.119Z","repository":{"id":69455241,"uuid":"70839406","full_name":"BorgwardtLab/LMM-Lasso","owner":"BorgwardtLab","description":"An implementation of the Lasso model for association mapping and phenotype prediction which corrects for population strucure (Rakitsch et al., Bioinformatics 2013): http://goo.gl/FRmXwI","archived":false,"fork":false,"pushed_at":"2016-10-14T11:42:31.000Z","size":210,"stargazers_count":6,"open_issues_count":0,"forks_count":4,"subscribers_count":2,"default_branch":"master","last_synced_at":"2023-10-20T18:23:27.252Z","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":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/BorgwardtLab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2016-10-13T19:11:27.000Z","updated_at":"2023-06-24T13:25:01.000Z","dependencies_parsed_at":"2023-10-20T18:34:30.658Z","dependency_job_id":null,"html_url":"https://github.com/BorgwardtLab/LMM-Lasso","commit_stats":null,"previous_names":[],"tags_count":0,"template":null,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FLMM-Lasso","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FLMM-Lasso/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FLMM-Lasso/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BorgwardtLab%2FLMM-Lasso/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BorgwardtLab","download_url":"https://codeload.github.com/BorgwardtLab/LMM-Lasso/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":225715541,"owners_count":17512903,"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":"2024-11-21T10:37:18.875Z","updated_at":"2024-11-21T10:37:19.449Z","avatar_url":"https://github.com/BorgwardtLab.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# LMM-lasso\n\nAn implementation of the linear model with sparsity constraints (Lasso model) for association mapping and phenotype prediction, which corrects for population strucure, as described in:\n\n* B. Rakitsch, C. Lippert, O. Stegle, K. Borgwardt (2013) \n**A Lasso Multi-Marker Mixed Model for Association Mapping with Population Structure Correction**,\n_Bioinformatics_ 29(2):206-1 [link](http://bioinformatics.oxfordjournals.org/content/29/2/206)\n\n## Usage\n\nThe folder `code` contains several Python scripts:\n* `lmm_lasso.py` : contains the implementation of the proposed model   \n* `test.py` : an example script  \n\nIna terminal, \n\n```\npython code/test.py\n```\n\nThe plots are saved in a separate folder named `plots`.\n\n\n## Data\n\n\nThe folder `code` contains a subfolder `data` which contains:\n* `poppheno.csv`  \n* `genotypes.csv`  \n\nThe data contains 1000 randomly sampled SNPs from the genotype data of A.thaliana from [Atwell et al.(2010)](http://www.nature.com/nature/journal/v465/n7298/full/nature08800.html). For simulating population-driven effects, we used the real phenotype leaf number at flowering time. Univariate analyses as done in the original paper have shown that the phenotype has an excess of associations when population structure is not accounted for. After correction, the p-values are approximately uniformly distributed.\n\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fborgwardtlab%2Flmm-lasso","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fborgwardtlab%2Flmm-lasso","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fborgwardtlab%2Flmm-lasso/lists"}