{"id":16509181,"url":"https://github.com/pwilmart/smith_spc_2018","last_synced_at":"2026-04-19T17:10:31.938Z","repository":{"id":94499282,"uuid":"170240939","full_name":"pwilmart/Smith_SpC_2018","owner":"pwilmart","description":"A large-scale spectral counting data analysis using PAW pipeline, edgeR, R, and Jupyter notebooks","archived":false,"fork":false,"pushed_at":"2019-09-06T17:27:29.000Z","size":21309,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-07-24T01:58:42.006Z","etag":null,"topics":["edger","jupyter-notebooks","paw-pipeline","proteomics","r","spectral-counting","statistical-analysis"],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/pwilmart.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,"publiccode":null,"codemeta":null}},"created_at":"2019-02-12T02:53:07.000Z","updated_at":"2019-09-06T17:27:31.000Z","dependencies_parsed_at":null,"dependency_job_id":"f50c6299-dc26-4830-ba8b-3ac41a05e230","html_url":"https://github.com/pwilmart/Smith_SpC_2018","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/pwilmart/Smith_SpC_2018","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pwilmart%2FSmith_SpC_2018","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pwilmart%2FSmith_SpC_2018/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pwilmart%2FSmith_SpC_2018/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pwilmart%2FSmith_SpC_2018/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/pwilmart","download_url":"https://codeload.github.com/pwilmart/Smith_SpC_2018/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/pwilmart%2FSmith_SpC_2018/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":278646783,"owners_count":26021512,"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","status":"online","status_checked_at":"2025-10-06T02:00:05.630Z","response_time":65,"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":["edger","jupyter-notebooks","paw-pipeline","proteomics","r","spectral-counting","statistical-analysis"],"created_at":"2024-10-11T15:49:14.171Z","updated_at":"2025-10-06T17:04:57.534Z","avatar_url":"https://github.com/pwilmart.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Smith_SpC_2018\n\nA large-scale spectral counting data analysis using PAW pipeline, edgeR, R, and Jupyter notebooks.\n\n### Phil Wilmarth, OHSU\n#### February 2019\n\nThe data is from a [recent study](https://www.sciencedirect.com/science/article/pii/S0002939418301193) where human retinal and choroidal endothelial cells were compared. The study was 5 donor eyes where retinal and choroidal cells were collected and cultured in a paired design. The cell lysates from each of the 10 cell cultures were profiled using large-scale separations with a fast-scanning linear ion trap. There were about half a million MS2 scans per sample for a dataset size of a little over 5 million. The data are available at the PRIDE archive ([PXD005972](https://www.ebi.ac.uk/pride/archive/projects/PXD005972)).\n\nThere is a direct link to the rendered [notebook HTML file](https://pwilmart.github.io/TMT_analysis_examples/Smith_2018_edgeR.html).\n\n---\n\nA few relevant files from the archive are present in the repository:\n\n- analysis_overview.pptx - summary of the data analysis steps\n- quant_protein_summary_8.txt - a grouped protein summary file\n- edgeR_input.txt - data extracted from results file for edgeR analysis\n- edgeR_results.txt - statistical testing results\n- HCEC_HREC_quant_protein_summary_sprot.xlsx - final summary sheet\n  - proteomics data from quant_protein_summary_8.txt\n  - statistical results from edgeR\n  - extra protein annotations\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpwilmart%2Fsmith_spc_2018","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpwilmart%2Fsmith_spc_2018","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpwilmart%2Fsmith_spc_2018/lists"}