{"id":20074704,"url":"https://github.com/greenelab/gea_community_detection","last_synced_at":"2025-05-05T21:32:06.937Z","repository":{"id":79359426,"uuid":"60421576","full_name":"greenelab/GEA_Community_Detection","owner":"greenelab","description":"Overrepresentation analysis for KEGG and PID pathways using community detection","archived":false,"fork":false,"pushed_at":"2018-01-07T00:47:34.000Z","size":5238,"stargazers_count":7,"open_issues_count":1,"forks_count":6,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-04-09T04:51:23.059Z","etag":null,"topics":["analysis","detection-network","enrichment-analysis","gene-expression","kegg-pathway","networks","pathway","pathway-analysis","pid"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/greenelab.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2016-06-04T17:16:19.000Z","updated_at":"2024-03-12T12:40:41.000Z","dependencies_parsed_at":"2023-03-12T07:49:31.709Z","dependency_job_id":null,"html_url":"https://github.com/greenelab/GEA_Community_Detection","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/greenelab%2FGEA_Community_Detection","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/greenelab%2FGEA_Community_Detection/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/greenelab%2FGEA_Community_Detection/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/greenelab%2FGEA_Community_Detection/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/greenelab","download_url":"https://codeload.github.com/greenelab/GEA_Community_Detection/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":252580059,"owners_count":21771255,"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":["analysis","detection-network","enrichment-analysis","gene-expression","kegg-pathway","networks","pathway","pathway-analysis","pid"],"created_at":"2024-11-13T14:53:41.987Z","updated_at":"2025-05-05T21:32:04.935Z","avatar_url":"https://github.com/greenelab.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# GEA_Community_Detection\n\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.830568.svg)](https://doi.org/10.5281/zenodo.830568)\n\n## Summary\n\nThis repository performs gene enrichment analysis using either the KEGG,\nor PID databases. The experiment is set up to contain both a control\nand experimental arm where the control arm is enrichment of a gene list of *m*\npathways using only *p*\\% of the genes in each pathway with *a*\\% additional random\ngenes from the ontology. This gene list is then subjected to enrichment analysis\nand the relevant enriched pathways are determined. The experimental condition is \njust like the control except that community detection is performed before enrichment \nanalysis. In particular, one can select Fastgreedy, Walktrap, Infomap, or Multilevel \nas the possible grouping method. For all methods, the F1-score,  false positive ratio, \nand false negative ratio are returned.  \n\nAll figures from the simulations are included in the Paper_Figs folder and results \nfrom the simulations are included in the Data folder as all_iterations_data.csv. \n\n![GEA Flowchart](Paper_Figs/flow_chart.png?raw=true)\n\n## Reproducibility\n\nTo reproduce all analyses including simulations and HGSC applications:\n\n```bash\n# Create and activate reproducible conda environment\nconda env create --force --file environment.yml\nsource activate gea_community_detection\n\n# Data for this project can be downloaded using the script and URL text file\n# located in the Data folder. This is required before running the pipeline.\nbash Data/data_files.sh\n\n# Reproduce all results\nbash Scripts/gea_pipeline.sh\n```\n\n## Contact\n\n* About the code: Lia Harrington (lia.x.harrington.gr@dartmouth.edu)\n\n* About the project or collaboration: Jennifer Doherty\n(jennifer.a.doherty@dartmouth.edu) or\nCasey Greene at (csgreene@mail.med.upenn.edu).\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgreenelab%2Fgea_community_detection","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgreenelab%2Fgea_community_detection","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgreenelab%2Fgea_community_detection/lists"}