{"id":21015610,"url":"https://github.com/gersteinlab/ngr","last_synced_at":"2026-05-01T05:39:00.459Z","repository":{"id":256315026,"uuid":"186883777","full_name":"gersteinlab/NGR","owner":"gersteinlab","description":"Network-based Gene Ranking of Contribution to Cancer [HM]","archived":false,"fork":false,"pushed_at":"2021-10-04T18:57:46.000Z","size":240,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":9,"default_branch":"master","last_synced_at":"2025-12-31T23:57:25.983Z","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/gersteinlab.png","metadata":{"files":{"readme":"README.txt","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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-05-15T18:40:26.000Z","updated_at":"2024-09-10T00:48:47.000Z","dependencies_parsed_at":"2024-09-10T05:18:58.269Z","dependency_job_id":"3e7b7c73-a8cd-429b-97a5-28e45a35032e","html_url":"https://github.com/gersteinlab/NGR","commit_stats":null,"previous_names":["gersteinlab/ngr"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/gersteinlab/NGR","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gersteinlab%2FNGR","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gersteinlab%2FNGR/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gersteinlab%2FNGR/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gersteinlab%2FNGR/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/gersteinlab","download_url":"https://codeload.github.com/gersteinlab/NGR/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gersteinlab%2FNGR/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32486222,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-30T13:12:12.517Z","status":"online","status_checked_at":"2026-05-01T02:00:05.856Z","response_time":64,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":"2024-11-19T10:10:34.626Z","updated_at":"2026-05-01T05:39:00.434Z","avatar_url":"https://github.com/gersteinlab.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"All code is on GitHub.\n\nAll data sufficient to run the code is on Farnam. In other words, Farnam is sufficient to reproduce all results.\n\nMore data/analyses might be found locally (e.g. gene_gene_matrix for more pathway databases than selected one (KEGG))\n\nFeature extraction is done within each subfolder. Each subfolder has its code/ directory.\n\nEach directory corresponds to a directory/data type. Scripts are to be run locally unless noted otherwise.\n\nPathway extraction and analysis:\nTo extract and analyze pathways: run extract_pathways.Rmd in pathways/code/\n\nTCGA data and feature extraction:\nIn tcga/:\nClinical data in clinical_data/ are provided by Tao Qing of Pusztai lab; see clinical_data/REAMDE.txt if needed.\nTo generate differential expression information: run code/run_tcga-expr.sh locally. Move results and slurm log to code/results/ directory.\nNote on differential expression analysis: currently, emphasis is put on FDR\u003c=0.05 only; no logFC threshold. If logFC threshold is to be enforced, update and rerun code/tcga-diff_exp.R to use glmTreat() for model training: see section 2.12 in edgeR manual for more details.\nDifferential expression analysis results are in code/results/\n\nFor data download, annotation (using ANNOVAR), and feature extraction in somatic and germline TCGA variants, see tcga/README.txt\n\nFor PPI ID conversion, processing, and convesion to matrices, see ppi/README.txt\n\n(Optional, ~ OBSOLETE as new PPIs have been generated and sample-level results are used) PPI metric (e.g. centrality) generation:\nTo generate betweenness centrality results, run (full commands in NGR Board sheet) ppi_centrality_script.sh in ppi/code\nBetweenness centrality results are in ppi/code/results\n\nFor gold standard list generation, see gene_lists/README.txt.\n\nCombined score generation:\nTo merge features and generate combined scores to be used as inputs to the method, locally run in base/:\nNote: This R script is usually run on macbook but should execute successfuly on Farnam as needed if all R packages are installed.\nmodule load R\nRscript merge_features.R -v somatic_MC3\nRscript merge_features.R -v germline\n\nPPI network matrices:\nTo generate PPI matrices to be used by the Python script of the method, run sbatch convert_ppi_network_to_matrix_script.sh in ppi/code/\n\nFor result generation, see method/README.txt\n\nFor method comparison and figure generation (figures or data related to Circos), see analysis/README.txt\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgersteinlab%2Fngr","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgersteinlab%2Fngr","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgersteinlab%2Fngr/lists"}