{"id":21015615,"url":"https://github.com/gersteinlab/pcawgadditivevariance","last_synced_at":"2026-03-17T23:34:24.464Z","repository":{"id":146424699,"uuid":"132359327","full_name":"gersteinlab/pcawgAdditiveVariance","owner":"gersteinlab","description":null,"archived":false,"fork":false,"pushed_at":"2018-05-06T17:30:25.000Z","size":5819,"stargazers_count":1,"open_issues_count":0,"forks_count":1,"subscribers_count":25,"default_branch":"master","last_synced_at":"2026-01-02T05:00:42.991Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Matlab","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.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,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-05-06T17:07:03.000Z","updated_at":"2024-07-25T03:04:12.000Z","dependencies_parsed_at":null,"dependency_job_id":"6fea5394-3f07-4b32-9708-bc1a42b701a7","html_url":"https://github.com/gersteinlab/pcawgAdditiveVariance","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/gersteinlab/pcawgAdditiveVariance","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gersteinlab%2FpcawgAdditiveVariance","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gersteinlab%2FpcawgAdditiveVariance/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gersteinlab%2FpcawgAdditiveVariance/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gersteinlab%2FpcawgAdditiveVariance/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/gersteinlab","download_url":"https://codeload.github.com/gersteinlab/pcawgAdditiveVariance/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/gersteinlab%2FpcawgAdditiveVariance/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30635176,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-17T22:38:22.569Z","status":"ssl_error","status_checked_at":"2026-03-17T22:38:11.804Z","response_time":56,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":"2024-11-19T10:10:34.823Z","updated_at":"2026-03-17T23:34:24.410Z","avatar_url":"https://github.com/gersteinlab.png","language":"Matlab","funding_links":[],"categories":[],"sub_categories":[],"readme":"# pcawgAdditiveVariance\n\nThis repository consist of code relevant for additive variance analysis performed on PCAWG mutations.\n\nFollowing dependencies are required to run this workflow.\n\nFunSeq2 (http://funseq2.gersteinlab.org/)\n\nPython\n\nMatlab\n\nGCTA (http://cnsgenomics.com/software/gcta/#Overview)\n\nThis workflow consist of two components.\n\n1) pre-processing step \n    In this step we generate summary file for each cancer cohort.\n   \n    *******************\n    \n    Two input files are needed for this step. \n    a) PCAWG driver mutation list and b)FunSeq2 output file(in BED format) \n    \n    Usage:\n    generateSummaryInfo.py -d \u003cdriverFile\u003e -I \u003cfunSeqOutFile\u003e -O \u003coutSummaryFile\u003e\n    generateSummaryInfo.py (-h | --help)\n\n\n2) post-processing steps\n\n   Pipeline is run by calling additive_variance_demo.m\n\n   *******************\n\n   Full pipeline requires the following inputs:\n\n    - in bedFiles folder:\n      cohortName.null.bed\n      cohortName.obs.bed\n\n   - in summaryFiles folder:\n     cohortName.null.summary.txt\n     cohortName.obs.summary.txt\n\n   and generates the output cohortName.txt in the results folder.\n\n  A gcta executable is required (Linux version is included, Windows and Mac versions are available from cnsgenomics.com/software/gcta), which should be placed in the gctaFiles folder.\n\n*******************\n\nCurrent pipeline is set up to call only final stage, which summarizes the results from precomputed intermediate outputs.\nOutputs are computed from the Breast-AdenoCa cohort with randomized samples used for both null and obs conditions.\nResults text file shows calculated additive variance for each funseq threshold, which is ~0 (1e-6), along with associated p-values (0.5 indicates that no significant genetic variance was found).\nValues of -1 in the results file for funseq thresholds 5 and 6 indicate that insufficient data was found at these thresholds.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgersteinlab%2Fpcawgadditivevariance","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgersteinlab%2Fpcawgadditivevariance","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgersteinlab%2Fpcawgadditivevariance/lists"}