{"id":18014338,"url":"https://github.com/bodenmillergroup/imcrtools","last_synced_at":"2025-04-08T03:16:57.781Z","repository":{"id":37904936,"uuid":"209026974","full_name":"BodenmillerGroup/imcRtools","owner":"BodenmillerGroup","description":"An R package for handling and analysing imaging mass cytometry data","archived":false,"fork":false,"pushed_at":"2024-10-29T09:11:43.000Z","size":55088,"stargazers_count":20,"open_issues_count":9,"forks_count":10,"subscribers_count":14,"default_branch":"devel","last_synced_at":"2024-10-29T11:01:34.554Z","etag":null,"topics":["imc","r","single-cell","spatial"],"latest_commit_sha":null,"homepage":"https://bodenmillergroup.github.io/imcRtools/","language":"R","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/BodenmillerGroup.png","metadata":{"files":{"readme":"README.md","changelog":"NEWS","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":"2019-09-17T10:40:22.000Z","updated_at":"2024-10-29T09:11:34.000Z","dependencies_parsed_at":"2023-01-21T12:33:43.428Z","dependency_job_id":"4e8c347b-fd5a-4244-a844-82497b59d37c","html_url":"https://github.com/BodenmillerGroup/imcRtools","commit_stats":{"total_commits":398,"total_committers":8,"mean_commits":49.75,"dds":"0.15577889447236182","last_synced_commit":"3cb8e3ae3e6f7261c322150c7d9818886260f687"},"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BodenmillerGroup%2FimcRtools","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BodenmillerGroup%2FimcRtools/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BodenmillerGroup%2FimcRtools/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/BodenmillerGroup%2FimcRtools/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/BodenmillerGroup","download_url":"https://codeload.github.com/BodenmillerGroup/imcRtools/tar.gz/refs/heads/devel","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247767237,"owners_count":20992548,"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":["imc","r","single-cell","spatial"],"created_at":"2024-10-30T04:07:59.925Z","updated_at":"2025-04-08T03:16:57.763Z","avatar_url":"https://github.com/BodenmillerGroup.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cimg src=\"vignettes/imcRtools_sticker.png\" align=\"right\" alt=\"\" width=\"100\" /\u003e\n\n# imcRtools\n\n\u003c!-- badges: start --\u003e\n[![codecov](https://codecov.io/gh/BodenmillerGroup/imcRtools/branch/master/graph/badge.svg)](https://codecov.io/gh/BodenmillerGroup/imcRtools)\n[![docs](https://github.com/BodenmillerGroup/imcRtools/actions/workflows/docs.yml/badge.svg?branch=master)](https://github.com/BodenmillerGroup/imcRtools/actions/workflows/docs.yml)\n\u003c!-- badges: end --\u003e\n\nThis R/Bioconductor package contains helper functions to analyse IMC (or other multiplexed imaging) data.\n\nIts official package page can be found here: [https://bioconductor.org/packages/imcRtools](https://bioconductor.org/packages/imcRtools)\n\n**Bug notice: we discovered and fixed a bug in the `testInteractions` function in version below 1.5.5 which affected `SingleCellExperiment` or `SpatialExperiment` objects in which cells were not grouped by image. Please install the newest version of `imcRtools` directly from Github as explained below.**  \n\n## Check status\n\n| Bioc branch | Checks |\n|:-----------:|:------:|\n| Release     |[![build-check-release](https://github.com/BodenmillerGroup/imcRtools/actions/workflows/build-checks-release.yml/badge.svg?branch=devel)](https://github.com/BodenmillerGroup/imcRtools/actions/workflows/build-checks-release.yml)|\n| Devel       |[![build-check-devel](https://github.com/BodenmillerGroup/imcRtools/actions/workflows/build-checks-devel.yml/badge.svg?branch=devel)](https://github.com/BodenmillerGroup/imcRtools/actions/workflows/build-checks-devel.yml)|\n\n## Introduction\n\nHighly multiplexed imaging techniques such as imaging mass cytometry (IMC), \nmultiplexed ion beam imaging (MIBI) and cyclic immunofluorescence techniques\nacquire read-outs of the expression of tens of protein in a spatially resolved\nmanner.\n\nThis R package supports the handling and analysis of imaging mass cytometry \nand other highly multiplexed imaging data. The main functionality includes \nreading in single-cell data after image segmentation and measurement, data \nformatting to perform channel spillover correction and a number of spatial \nanalysis approaches. First, cell-cell interactions are detected via spatial \ngraph construction; these graphs can be visualized with cells representing \nnodes and interactions representing edges. Furthermore, per cell, its direct \nneighbours are summarized to allow spatial clustering. Per image/grouping \nlevel, interactions between types of cells are counted, averaged and \ncompared against random permutations. In that way, types of cells that \ninteract more (attraction) or less (avoidance) frequently than expected by \nchance are detected. \n\n## Installation\n\nThe `imcRtools` package can be installed from `Bioconductor` via:\n\n```r\nif (!requireNamespace(\"BiocManager\", quietly = TRUE))\n    install.packages(\"BiocManager\")\n\nBiocManager::install(\"imcRtools\")\n```\n\nThe development version of `imcRtools` can be installed from Github via:\n\n```r\nif (!requireNamespace(\"remotes\", quietly = TRUE))\n    install.packages(\"remotes\")\n\nremotes::install_github(\"BodenmillerGroup/imcRtools\")\n```\n\n## Getting help\n\nThe analysis of highly multiplexed imaging data requires multiple pre-processing\nand diverse analysis steps.\n\n1. Processing of raw data and segmentation: The \n[ImcSegmentationPipeline](https://github.com/BodenmillerGroup/ImcSegmentationPipeline) and \nthe [steinbock](https://github.com/BodenmillerGroup/steinbock) \nlibrary can be used to process and segment IMC data. The\n`imcRtools` package provides reader functions for outputs generated by these \napproaches.  \n\n2. Single-cell analysis using the [Bioconductor](https://www.bioconductor.org/) framework: The \n[Orchestrating Single-Cell Analysis with Bioconductor](https://bioconductor.org/books/release/OSCA/)\nbook is an excellent resource for beginners and advanced analysis concerning\nsingle-cell data. Common analysis steps include dimensionality reduction, \nunsupervised clustering for cell type detection and data visualization.\nThe `imcRtools` package supports data structures that fully\nintegrate with the analysis presented in the OSCA book.  \n\n3. Handling multiplexed images in R: the \n[cytomapper](https://www.bioconductor.org/packages/release/bioc/html/cytomapper.html)\nBioconductor package provides functions and data structure to handle and \nanalyse highly multiplexed imaging data (images, masks and single-cell data)\nnatively in R.\n\n## Citation\n\nPlease cite the following paper when using `imcRtools` 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## Contributing\n\nFor feature requests, please open an issue [here](https://github.com/BodenmillerGroup/imcRtools/issues).\n\nAlternatively, you can fork the repository, add your change and issue a pull request.\n\n## Maintainer\n\n**Daniel Schulz**\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbodenmillergroup%2Fimcrtools","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbodenmillergroup%2Fimcrtools","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbodenmillergroup%2Fimcrtools/lists"}