<img src="vignettes/imgs/cytoviewer_sticker.png" align="right" width="100"/> # cytoviewer <!-- badges: start --> [](https://github.com/BodenmillerGroup/cytoviewer/actions/workflows/docs.yml) [](https://app.codecov.io/gh/BodenmillerGroup/cytoviewer/tree/devel) <!-- badges: end --> An interactive multi-channel image viewer for R. This shiny application allows users to interactively visualize multi-channel images and segmentation masks generated by imaging mass cytometry and other highly multiplexed imaging techniques. The `cytoviewer` package is divided into image-level (Composite and Channels) and cell-level visualization (Masks). It allows users to overlay individual images with segmentation masks, integrates well with [SingleCellExperiment](https://bioconductor.org/packages/release/bioc/html/SingleCellExperiment.html) / [SpatialExperiment](https://bioconductor.org/packages/release/bioc/html/SingleCellExperiment.html) and [CytoImageList](https://www.bioconductor.org/packages/release/bioc/html/cytomapper.html) objects for metadata and image visualization and supports image downloads. Read the **BMC Bioinformatics paper** here: [doi.org/10.1186/s12859-023-05546-z](https://doi.org/10.1186/s12859-023-05546-z). ## Check status | Bioc branch | Checks | |:------------------------------------------:|:--------------------------:| | Release | [](https://github.com/BodenmillerGroup/cytoviewer/actions/workflows/build-checks-release.yml) | | Devel | [](https://github.com/BodenmillerGroup/cytoviewer/actions/workflows/build-checks-devel.yml) | ## Requirements The `cytoviewer` package requires R version \>= 4.0. It builds on data objects and functions contained in the [cytomapper](https://bioconductor.org/packages/release/bioc/html/cytomapper.html) package. ## Installation The `cytoviewer` package can be installed from `Bioconductor` via: ``` r if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("cytoviewer") ``` The development version of `cytoviewer` can be installed from Github via: ``` r if (!requireNamespace("remotes", quietly = TRUE)) install.packages("remotes") remotes::install_github("BodenmillerGroup/cytoviewer") ``` To load the package in your R session, type the following: ``` r library(cytoviewer) ``` ## Basic usage ``` r library(cytoviewer) # Load example datasets library(cytomapper) data("pancreasImages") data("pancreasMasks") data("pancreasSCE") # Use cytoviewer with images, masks and object app <- cytoviewer(image = pancreasImages, mask = pancreasMasks, object = pancreasSCE, img_id = "ImageNb", cell_id = "CellNb") if (interactive()) { shiny::runApp(app) } ``` For more detailed information on package usage and functionality, please refer to <https://bodenmillergroup.github.io/cytoviewer/>. ## Application overview  **(A)** The supported functionality (right) of *cytoviewer* depends on the data inputs (left). To match information between the objects, cell (cell_id) and image (img_id) identifiers can be provided. SCE/SPE = *SingleCellExperiment*/*SpatialExperiment*. **(B)** The graphical user interface of *cytoviewer* is divided into a body, header, and sidebar. The body of *cytoviewer* includes the image viewer, which has three tabs: Composite (Image-level), Channels (Image-level), and Mask (Cell-level). Zooming is supported for Composite and Mask tabs. The package version, R session information, help page, and a drop-down menu for image downloads are located in the header. The sidebar menu has controls for sample selection, image visualization, mask visualization, and general settings. Scale bar: 150 µm **(C)** *cytoviewer* supports different viewing modes. Top: The "channels" tab of image-level visualization displays individual channels. Shown are Ecad (magenta), CD8a (cyan), and CD68 (yellow) marking tumor cells, CD8+ T cells, and myeloid cells, respectively. Center: The "composite" tab of image-level visualization visualizes image composites combining multiple channels. These composite images can be overlayed with cell outlines, which can be colored by cell-specific metadata. Shown here are cell outlines colored by cell area (continous value) and cell type (categorical value; tumor cells in white). Channel color settings are as follows for all markers: Contrast: 2,5; Brightness: 1; Gamma: 1.2. Bottom: The "mask" tab can be used to visualize segmentation masks that can be colored by cell-specific metadata. Shown here are segmentation masks colored by cell area (continuous) and cell type (categorical; tumor cells in magenta). Scale bars: 150 µm. **(D)** "Image appearance" controls can be used to add legends or titles and to change the scale bar length for image-level (top) and cell level (bottom) visualization. The cell-level mask plot depicts tumor (magenta), myeloid (yellow), and CD8+ T cells (cyan). Scale bars: 100 µm. **Adapted from Meyer et al., 2024** ## Contributing For feature requests, please open an issue [here](https://github.com/BodenmillerGroup/cytoviewer/issues). Alternatively, feel free to fork the repository, add your changes and issue a pull request. ## Citation If you are using `cytoviewer` in your work, please cite the paper as: ``` Meyer, L., Eling, N., & Bodenmiller, B. (2024). cytoviewer: an R/Bioconductor package for interactive visualization and exploration of highly multiplexed imaging data. BMC Bioinformatics, doi.org/10.1186/s12859-023-05546-z ``` ## Authors [Lasse Meyer](https://github.com/lassedochreden) lasse.meyer 'at' dqbm.uzh.ch [Nils Eling](https://github.com/nilseling) nils.eling 'at' dqbm.uzh.ch