{"id":16698303,"url":"https://github.com/lgatto/proloc","last_synced_at":"2025-04-06T09:07:49.459Z","repository":{"id":4937784,"uuid":"6094658","full_name":"lgatto/pRoloc","owner":"lgatto","description":"A unifying bioinformatics framework for organelle proteomics","archived":false,"fork":false,"pushed_at":"2025-03-27T15:14:06.000Z","size":263750,"stargazers_count":16,"open_issues_count":17,"forks_count":14,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-03-30T07:11:35.459Z","etag":null,"topics":["bioconductor","proteomics","proteomics-data","r","spatial-proteomics","visualisation"],"latest_commit_sha":null,"homepage":"http://lgatto.github.io/pRoloc/","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":"Netflix/SimianArmy","license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/lgatto.png","metadata":{"files":{"readme":"README.md","changelog":"NEWS.md","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":"2012-10-05T18:24:28.000Z","updated_at":"2025-03-29T18:28:23.000Z","dependencies_parsed_at":"2024-12-16T09:22:55.773Z","dependency_job_id":"c08f043a-9c79-4aca-b632-86bad93deb6e","html_url":"https://github.com/lgatto/pRoloc","commit_stats":{"total_commits":1954,"total_committers":29,"mean_commits":67.37931034482759,"dds":0.6432958034800409,"last_synced_commit":"eba38bc3ef223cf99978a83c1979decb6413c3e2"},"previous_names":[],"tags_count":25,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgatto%2FpRoloc","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgatto%2FpRoloc/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgatto%2FpRoloc/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/lgatto%2FpRoloc/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/lgatto","download_url":"https://codeload.github.com/lgatto/pRoloc/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247457800,"owners_count":20941906,"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":["bioconductor","proteomics","proteomics-data","r","spatial-proteomics","visualisation"],"created_at":"2024-10-12T17:51:30.833Z","updated_at":"2025-04-06T09:07:49.257Z","avatar_url":"https://github.com/lgatto.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![codecov.io](https://codecov.io/github/lgatto/pRoloc/coverage.svg?branch=master)](https://codecov.io/github/lgatto/pRoloc?branch=master)\n\n# A unifying bioinformatics framework for spatial proteomics\n\n\u003cimg src=\"https://raw.githubusercontent.com/Bioconductor/BiocStickers/master/pRoloc/pRoloc.png\" height=\"200\"\u003e\u003cimg src=\"https://raw.githubusercontent.com/Bioconductor/BiocStickers/master/pRoloc/pRolocdata.png\" height=\"200\"\u003e\u003cimg src=\"https://raw.githubusercontent.com/Bioconductor/BiocStickers/master/pRoloc/pRolocGUI.png\" height=\"200\"\u003e\n\n\nThe `pRoloc` suite set of software offers a complete software pipeline\nto analyse, visualise and interpret mass spectrometry-based spatial\nproteomics data such, for example, as LOPIT (Localization of Organelle\nProteins by Isotope Tagging), PCP (Protein Correlation Profiling) or\nhyperLOPIT (hyperplexed LOPIT). The suite includes\n[`pRoloc`](http://www.bioconductor.org/packages/release/bioc/html/pRoloc.html),\nthe mail software that focuses on data analysis using state-of-the-art\nmachine learning,\n[`pRolocdata`](http://bioconductor.org/packages/release/data/experiment/html/pRolocdata.html),\nthat distributes numerous datasets, and [`pRolocGUI`](https://lgatto.github.io/pRolocGUI/), that offers\ninteractive visualisations dedicated to spatial proteomics. The\nsoftware are distributed as part of the\nR/[Bioconductor](http://bioconductor.org/) project.\n\n## Getting started\n\nThe `pRoloc` software comes with ample\ndocumentation. The\n[main tutorial](https://lgatto.github.io/pRoloc/articles/v01-pRoloc-tutorial.html) provides\na broad overview of the package and its functionality.  See the\n*Articles* tab for additional manuals.\n\n[`pRolocGUI`](http://www.bioconductor.org/packages/release/bioc/html/pRolocGUI.html)\nalso offer several documentation files.\n\nHere are a set of\n[video tutorial](https://www.youtube.com/playlist?list=PLvIXxpatSLA2loV5Srs2VBpJIYUlVJ4ow)\nthat illustrate the `pRoloc` framework.\n\n## Help\n\nPost your questions on the\n[Bioconductor support site](https://support.bioconductor.org/),\ntagging it with the package name `pRoloc` (the maintainer will\nautomatically be notified by email). If you identify a bug or have a\nfeature request, please open an\n[issue](https://github.com/lgatto/pRoloc/issues) on the github\ndevelopment page.\n\n## Installation\n\nThe preferred installation procedure uses the Bioconductor\ninfrastructure:\n\n```c\n## unless BiocManager is already installed\ninstall.packages(\"BiocManager\")\n## then\nBiocManager::install(\"pRoloc\")\nBiocManager::install(\"pRolocdata\")\nBiocManager::install(\"pRolocGUI\")\n```\n\n### Pre-release/development version\n\nThe pre-release/development code on github can also be installed using\n`BiocManager::install`, as shown below. Note that this requires a\nworking R build environment (i.e `Rtools` on Windows - see\n[here](https://github.com/lgatto/teachingmaterial/wiki/R-package)). New\npre-release features might not be documented not thoroughly tested and\ncould substantially change prior to release. Use at your own risks.\n\n\n```c\n## unless BiocManager is already installed\ninstall.packages(\"BiocManager\")\n## then, install from github\nBiocManager::install(\"lgatto/pRoloc\")\nBiocManager::install(\"lgatto/pRolocdata\")\nBiocManager::install(\"lgatto/pRolocGUI\")\n```\n\n## References:\n\nFor refences about the software, how to use it and spatial proteomics\ndata analysis:\n\n* Crook OM, Breckels LM, Lilley KS, Kirk PWD, Gatto L. A Bioconductor\n  workflow for the Bayesian analysis of spatial proteomics [version 1;\n  peer review: awaiting peer review]. F1000Research 2019, 8:446\n  (https://doi.org/10.12688/f1000research.18636.1)\n\n* Breckels LM, Mulvey CM, Lilley KS and Gatto L. A Bioconductor\n  workflow for processing and analysing spatial proteomics data\n  [version 2; peer review: 2 approved]. F1000Research 2018, 5:2926\n  (https://doi.org/10.12688/f1000research.10411.2)\n\n* Gatto L, Breckels LM, Burger T, Nightingale DJ, Groen AJ, Campbell\n  C, Nikolovski N, Mulvey CM, Christoforou A, Ferro M, Lilley KS. *A\n  foundation for reliable spatial proteomics data analysis* Mol Cell\n  Proteomics. 2014 Aug;13(8):1937-52. doi:\n  10.1074/mcp.M113.036350. Epub 2014 May 20. [PubMed PMID:\n  24846987](http://www.ncbi.nlm.nih.gov/pubmed/24846987)\n\n* Gatto L, Breckels LM, Wieczorek S, Burger T, Lilley\n  KS. *Mass-spectrometry-based spatial proteomics data analysis using\n  pRoloc and pRolocdata* Bioinformatics. 2014 May 1;30(9):1322-4. doi:\n  10.1093/bioinformatics/btu013. Epub 2014 Jan 11. [PubMed PMID:\n  24413670](http://www.ncbi.nlm.nih.gov/pubmed/24413670).\n\nSpecific algorithms available in the software:\n\n* Breckels LM, Gatto L, Christoforou A, Groen AJ, Lilley KS, Trotter\n  MW. *The effect of organelle discovery upon sub-cellular protein\n  localisation* J Proteomics. 2013 Aug 2;88:129-40. doi:\n  10.1016/j.jprot.2013.02.019. Epub 2013 Mar 21. [PubMed PMID:\n  23523639](http://www.ncbi.nlm.nih.gov/pubmed/23523639).\n\n* Breckels LM, Holden S, Wojnar D, Mulvey CMM, Christoforou A, Groen\n  AJ, Kohlbacher O, Lilley KS and Gatto L. *Learning from\n  heterogeneous data sources: an application in spatial proteomics*\n  2015 biorXiv, doi: http://dx.doi.org/10.1101/022152\n\n* Oliver M Crook, Claire M Mulvey, Paul D. W. Kirk, Kathryn S Lilley,\n Laurent Gatto *A Bayesian Mixture Modelling Approach For Spatial\n Proteomics* PLOS Computational Biology\n doi:[10.1371/journal.pcbi.1006516](https://doi.org/10.1371/journal.pcbi.1006516)\n\n\n\n#### More resource\n\n* R and Bioconductor for proteomics\n  [web page](http://lgatto.github.io/RforProteomics/) and\n  [package](http://www.bioconductor.org/packages/release/data/experiment/html/RforProteomics.html)\n\n* Bioconductor proteomics [workflow](http://bioconductor.org/help/workflows/proteomics/)\n\n## Contributing\n\nContributions to the package are more than welcome. If you want to\ncontribute to this package, you should follow the same conventions as\nthe rest of the functions whenever it makes sense to do so. Feel free\nto get in touch (preferable opening a\n[github issue](https://github.com/lgatto/pRoloc/issues/)) to discuss\nany suggestions.\n\nPlease note that this project is released with a\n[Contributor Code of Conduct](https://github.com/lgatto/pRoloc/blob/master/CONDUCT.md).\nBy participating in this project you agree to abide by its terms.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flgatto%2Fproloc","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flgatto%2Fproloc","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flgatto%2Fproloc/lists"}