{"id":16698332,"url":"https://github.com/lgatto/qsep-manuscript","last_synced_at":"2025-03-14T03:46:04.522Z","repository":{"id":138540225,"uuid":"66014864","full_name":"lgatto/QSep-manuscript","owner":"lgatto","description":"Assessing sub-cellular resolution in  spatial proteomics experiments","archived":false,"fork":false,"pushed_at":"2019-05-18T16:30:59.000Z","size":17490,"stargazers_count":1,"open_issues_count":0,"forks_count":1,"subscribers_count":6,"default_branch":"master","last_synced_at":"2025-01-20T22:55:21.112Z","etag":null,"topics":["proloc","prolocdata","proteomics","spatial-proteomics"],"latest_commit_sha":null,"homepage":null,"language":"TeX","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/lgatto.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":"2016-08-18T16:50:47.000Z","updated_at":"2023-06-29T22:40:48.000Z","dependencies_parsed_at":null,"dependency_job_id":"8dc8f225-b383-4ad1-91c9-2e9cc2e9eefd","html_url":"https://github.com/lgatto/QSep-manuscript","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgatto%2FQSep-manuscript","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgatto%2FQSep-manuscript/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgatto%2FQSep-manuscript/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgatto%2FQSep-manuscript/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lgatto","download_url":"https://codeload.github.com/lgatto/QSep-manuscript/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243521257,"owners_count":20304186,"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":["proloc","prolocdata","proteomics","spatial-proteomics"],"created_at":"2024-10-12T17:51:39.290Z","updated_at":"2025-03-14T03:46:04.464Z","avatar_url":"https://github.com/lgatto.png","language":"TeX","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Assessing sub-cellular resolution in  spatial proteomics experiments\n\n## Abstract\n\nThe sub-cellular localisation of a protein is paramount in defining\nits function, and a protein's mis-localisation is known to lead to\nadverse effect. As a result, numerous experimental techniques and\ndatasets have been published, with the aim to decipher localisation of\nproteins at various scales and resolutions, including high profile\nmass spectrometry-based efforts. Here, we present a tool, termed\n[QSep](https://lgatto.github.io/pRoloc/reference/QSep-class.html), and\na meta-analysis assessing and comparing the sub-cellular resolution of\n28 such mass spectrometry-based spatial proteomics experiments.\n\n## Citation\n\n\u003e *Assessing sub-cellular resolution in spatial proteomics experiments* \n\u003e Laurent Gatto, Lisa M Breckels, Kathryn S Lilley. bioRxiv 377630; doi:\n\u003e [https://doi.org/10.1101/377630](https://www.biorxiv.org/content/10.1101/377630v3).\n\nhas been reviewed and published as \n\n\u003e *Assessing sub-cellular resolution in spatial proteomics experiments*\n\u003e Laurent Gatto, Lisa M Breckels, Kathryn S Lilley (2019) Current Opinion in Chemical Biology, 48, pages 123-149 doi:\n\u003e [https://doi.org/10.1016/j.cbpa.2018.11.015](https://doi.org/10.1016/j.cbpa.2018.11.015).\n\n\nSee also\n\n  *LOPIT-DC: A simpler approach to high-resolution spatial proteomics*\n   Aikaterini Geladaki, Nina Kocevar Britovsek, Lisa M. Breckels, Tom\n   S. Smith, Claire M. Mulvey, Oliver M. Crook, Laurent Gatto, Kathryn\n   S. Lilley bioRxiv 378364; doi:\n   [https://doi.org/10.1101/378364](https://doi.org/10.1101/378364).\n\nfor an application of QSep.\n\n## Reproducible document\n\nTo reproduce this document, you'll need `R` version 3.3.1 or\nlater. Install all packages with\n\n```r\nif (!requireNamespace(\"BiocManager\", quietly = TRUE))\n\tinstall.packages(\"BiocManager\")\nBiocManager::install(c(\"pRoloc\", \"pRolocdata\", \"knitr\"))\n```\n\nClone the git repository\n\n```\ngit clone git@github.com:lgatto/QSep-manuscript.git\n```\n\nIf you have `make`, then typing will re-generate the pdf document\n\n```\nmake qsep.pdf\n```\n\nOtherwise, in `R`\n\n```r\nbioLite(\"rmarkdown\")\nrmarkdown::render(\"qsep.Rnw\", output_format = pdf_document)\n```\n\nThe latter will produce a document with slighly different formatting,\nbut the text, figures and references will be identical.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flgatto%2Fqsep-manuscript","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flgatto%2Fqsep-manuscript","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flgatto%2Fqsep-manuscript/lists"}