{"id":19106763,"url":"https://github.com/bodenmillergroup/imcdataanalysis","last_synced_at":"2025-09-07T04:33:46.237Z","repository":{"id":39899742,"uuid":"306572506","full_name":"BodenmillerGroup/IMCDataAnalysis","owner":"BodenmillerGroup","description":"R based workflow for multiplexed imaging data","archived":false,"fork":false,"pushed_at":"2024-02-12T14:59:40.000Z","size":374312,"stargazers_count":28,"open_issues_count":4,"forks_count":12,"subscribers_count":10,"default_branch":"main","last_synced_at":"2025-01-03T03:10:17.237Z","etag":null,"topics":["bioconductor","image-analysis","single-cell","spatial-analysis"],"latest_commit_sha":null,"homepage":"https://bodenmillergroup.github.io/IMCDataAnalysis/","language":"HTML","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/BodenmillerGroup.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","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}},"created_at":"2020-10-23T08:18:35.000Z","updated_at":"2024-11-23T19:17:44.000Z","dependencies_parsed_at":"2023-01-31T21:46:26.820Z","dependency_job_id":"6d14aa3c-dece-4a1d-9f0c-556aa8bd4b1e","html_url":"https://github.com/BodenmillerGroup/IMCDataAnalysis","commit_stats":null,"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BodenmillerGroup%2FIMCDataAnalysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BodenmillerGroup%2FIMCDataAnalysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BodenmillerGroup%2FIMCDataAnalysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BodenmillerGroup%2FIMCDataAnalysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BodenmillerGroup","download_url":"https://codeload.github.com/BodenmillerGroup/IMCDataAnalysis/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240158820,"owners_count":19757251,"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","image-analysis","single-cell","spatial-analysis"],"created_at":"2024-11-09T04:09:24.648Z","updated_at":"2025-02-22T10:24:45.520Z","avatar_url":"https://github.com/BodenmillerGroup.png","language":"HTML","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.8100220.svg)](https://doi.org/10.5281/zenodo.6806448)\n\n# R based analysis workflow for multiplexed imaging data\n\n\u003c!-- badges: start --\u003e\n[![build](https://github.com/BodenmillerGroup/IMCDataAnalysis/actions/workflows/build.yml/badge.svg)](https://github.com/BodenmillerGroup/IMCDataAnalysis/actions/workflows/build.yml)\n\u003c!-- badges: end --\u003e\n\nR workflow highlighting analyses approaches for multiplexed imaging data.\n\n## Scope\n\nThis workflow explains the use of common R/Bioconductor packages to pre-process and analyse single-cell data obtained from segmented multichannel images.\nWhile we use imaging mass cytometry (IMC) data as an example, the concepts presented here can be applied to images obtained by other technologies (e.g. CODEX, MIBI, mIF, CyCIF, etc.).\nThe workflow can be largely divided into the following parts:\n\n1. Preprocessing (reading in the data, spillover correction)\n2. Image- and cell-level quality control, low-dimensional visualization\n3. Sample/batch effect correction\n4. Cell phenotyping via clustering or classification\n5. Single-cell visualization\n6. Image visualization\n7. Spatial analyses\n\n## Update freeze\n\nThis workflow has been actively developed until December 2023. At that time\nwe used the most recent (`v.0.16.0`) version of `steinbock` to process the \nexample data. If you are having issues when using newer versions of `steinbock`\nplease open an issue [here](https://github.com/BodenmillerGroup/IMCDataAnalysis/issues).\n\n## Usage\n\nTo reproduce the analysis displayed at [https://bodenmillergroup.github.io/IMCDataAnalysis/](https://bodenmillergroup.github.io/IMCDataAnalysis/) clone the repository via:\n\n```\ngit clone https://github.com/BodenmillerGroup/IMCDataAnalysis.git\n```\n\nFor reproducibility purposes, we provide a Docker container [here](https://github.com/BodenmillerGroup/IMCDataAnalysis/pkgs/container/imcdataanalysis).\n\n1. After installing [Docker](https://docs.docker.com/get-docker/) you can first pull the container via:\n\n```\ndocker pull ghcr.io/bodenmillergroup/imcdataanalysis:latest\n```\n\nand then run the container:\n\n```\ndocker run -v /path/to/IMCDataAnalysis:/home/rstudio/IMCDataAnalysis \\\n\t-e PASSWORD=bioc -p 8787:8787  \\\n\tghcr.io/bodenmillergroup/imcdataanalysis:latest\n```\n\n**Of note: it is recommended to use a date-tagged version of the container to ensure reproducibility**. \nThis can be done via:\n\n```\ndocker pull ghcr.io/bodenmillergroup/imcdataanalysis:\u003cyear-month-date\u003e\n```\n\n2. An RStudio server session can be accessed via a browser at `localhost:8787` using `Username: rstudio` and `Password: bioc`.  \n3. Navigate to `IMCDataAnalysis` and open the `IMCDataAnalysis.Rproj` file.  \n4. Code in the individual files can now be executed or the whole workflow can be build by entering `bookdown::render_book()`.\n\n## Feedback\n\nWe provide the workflow as an open-source resource. It does not mean that\nthis workflow is tested on all possible datasets or biological questions and \nthere exist multiple ways of analysing data. It is therefore recommended to\ncheck the results and question their biological interpretation.\n\nIf you notice an issue or missing information, please report an issue\n[here](https://github.com/BodenmillerGroup/IMCDataAnalysis/issues). We also\nwelcome contributions in form of pull requests or feature requests in form of\nissues. Have a look at the source code at:\n\n[https://github.com/BodenmillerGroup/IMCDataAnalysis](https://github.com/BodenmillerGroup/IMCDataAnalysis)\n\n## Contributing guidelines\n\nFor feature requests and bug reports, please raise an issue [here](https://github.com/BodenmillerGroup/IMCDataAnalysis/issues).\n\nFor adding new content to the book please work inside the Docker container as explained above.\nYou can fork the repository, add your changes and open a pull request.\nTo add new libraries to the container please add them to the [Dockerfile](Dockerfile).\n\n## Maintainer\n\n[Daniel Schulz](https://github.com/SchulzDan)  \n\n## Contributors\n\n[Nils Eling](https://github.com/nilseling)\n[Vito Zanotelli](https://github.com/votti)  \n[Daniel Schulz](https://github.com/SchulzDan)  \n[Jonas Windhager](https://github.com/jwindhager)   \n[Michelle Daniel](https://github.com/michdaniel)  \n[Lasse Meyer](https://github.com/lassedochreden)\n\n## Citation\n\nPlease cite the following paper when using the presented workflow in your research:\n\n\u003e  Windhager, J., Zanotelli, V.R.T., Schulz, D. et al. An end-to-end workflow for multiplexed image processing and analysis. Nat Protoc (2023). https://doi.org/10.1038/s41596-023-00881-0\n\n    @article{Windhager2023,\n        author = {Windhager, Jonas and Zanotelli, Vito R.T. and Schulz, Daniel and Meyer, Lasse and Daniel, Michelle and Bodenmiller, Bernd and Eling, Nils},\n        title = {An end-to-end workflow for multiplexed image processing and analysis},\n        year = {2023},\n        doi = {10.1038/s41596-023-00881-0},\n        URL = {https://www.nature.com/articles/s41596-023-00881-0},\n        journal = {Nature Protocols}\n    }\n\n\n## Funding\n\nThe work was funded by the European Union’s Horizon 2020 research and innovation program under Marie Sklodowska-Curie Actions grant agreement No 892225 (N.E) and by the CRUK IMAXT Grand Challenge (J.W.).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbodenmillergroup%2Fimcdataanalysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbodenmillergroup%2Fimcdataanalysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbodenmillergroup%2Fimcdataanalysis/lists"}