{"id":31805730,"url":"https://github.com/theislab/campa","last_synced_at":"2025-10-11T02:57:49.759Z","repository":{"id":40432639,"uuid":"419387118","full_name":"theislab/campa","owner":"theislab","description":"Conditional Autoencoders for Multiplexed Pixel Analysis","archived":false,"fork":false,"pushed_at":"2022-11-25T14:07:57.000Z","size":94260,"stargazers_count":16,"open_issues_count":6,"forks_count":5,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-09-14T04:58:07.819Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://campa.readthedocs.io","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/theislab.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":"CONTRIBUTING.rst","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2021-10-20T15:26:52.000Z","updated_at":"2025-07-06T21:18:17.000Z","dependencies_parsed_at":"2022-08-20T01:41:40.602Z","dependency_job_id":null,"html_url":"https://github.com/theislab/campa","commit_stats":null,"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"purl":"pkg:github/theislab/campa","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/theislab%2Fcampa","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/theislab%2Fcampa/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/theislab%2Fcampa/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/theislab%2Fcampa/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/theislab","download_url":"https://codeload.github.com/theislab/campa/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/theislab%2Fcampa/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279005953,"owners_count":26084009,"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":"2025-10-11T02:00:06.511Z","response_time":55,"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":"2025-10-11T02:57:47.818Z","updated_at":"2025-10-11T02:57:49.755Z","avatar_url":"https://github.com/theislab.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"CAMPA - Conditional Autoencoder for Multiplexed Pixel Analysis\n~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\n\nCAMPA is a framework for quantiative analysis of subcellular multi-channel imaging data.\nIt consists of a workflow that generates consistent subcellular landmarks (CSLs)\nusing conditional Variational Autoencoders (cVAE).\nThe output of the CAMPA workflow is an `anndata`_ object that contains interpretable\nper-cell features summarizing the molecular composition\nand spatial arrangement of CSLs inside each cell.\n\n.. raw:: html\n\n    \u003cp align=\"center\"\u003e\n        \u003ca href=\"https://www.biorxiv.org/content/10.1101/2022.05.07.490900v1\"\u003e\n            \u003cimg src=\"https://raw.githubusercontent.com/theislab/campa/main/docs/source/_static/img/Figure1ab.jpg\"\n             width=\"600px\" alt=\"CAMPA title figure\"\u003e\n        \u003c/a\u003e\n    \u003c/p\u003e\n\nVisit our `documentation`_ for installation and usage examples.\n\n\nManuscript\n----------\nPlease see our preprint\n*\"Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps\"*\n(`Spitzer, Berry et al. (2022)`_) to learn more.\n\n\nInstallation\n------------\n\nCAMPA was developed for Python 3.9 and can be installed by running::\n\n    pip install campa\n\n\nContributing\n------------\nWe are happy about any contributions! Before you start, check out our `contributing guide \u003cCONTRIBUTING.rst\u003e`_.\n\n.. _anndata: https://anndata.readthedocs.io/en/stable/\n.. _documentation: https://campa.readthedocs.io/en/stable/\n.. _`data and experiment paths`: https://campa.readthedocs.io/en/stable/overview.html#campa-config\n.. _`Spitzer, Berry et al. (2022)`: https://www.biorxiv.org/content/10.1101/2022.05.07.490900v1\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftheislab%2Fcampa","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftheislab%2Fcampa","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftheislab%2Fcampa/lists"}