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cytomapper

This is the development version of cytomapper; for the stable release version, see cytomapper.

Visualization of highly multiplexed imaging data in R


Bioconductor version: Development (3.19)

Highly multiplexed imaging acquires the single-cell expression of selected proteins in a spatially-resolved fashion. These measurements can be visualised across multiple length-scales. First, pixel-level intensities represent the spatial distributions of feature expression with highest resolution. Second, after segmentation, expression values or cell-level metadata (e.g. cell-type information) can be visualised on segmented cell areas. This package contains functions for the visualisation of multiplexed read-outs and cell-level information obtained by multiplexed imaging technologies. The main functions of this package allow 1. the visualisation of pixel-level information across multiple channels, 2. the display of cell-level information (expression and/or metadata) on segmentation masks and 3. gating and visualisation of single cells.

Author: Nils Eling [aut] , Nicolas Damond [aut] , Tobias Hoch [ctb], Lasse Meyer [cre, ctb]

Maintainer: Lasse Meyer <lasse.meyer at dqbm.uzh.ch>

Citation (from within R, enter citation("cytomapper")):

Installation

To install this package, start R (version "4.4") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("cytomapper")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("cytomapper")
On disk storage of images HTML R Script
Visualization of imaging cytometry data in R HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews DataImport, ImmunoOncology, MultipleComparison, Normalization, OneChannel, SingleCell, Software, TwoChannel
Version 1.15.2
In Bioconductor since BioC 3.11 (R-4.0) (4 years)
License GPL (>= 2)
Depends R (>= 4.0), EBImage, SingleCellExperiment, methods
Imports SpatialExperiment, S4Vectors, BiocParallel, HDF5Array, DelayedArray, RColorBrewer, viridis, utils, SummarizedExperiment, tools, graphics, raster, grDevices, stats, ggplot2, ggbeeswarm, svgPanZoom, svglite, shiny, shinydashboard, matrixStats, rhdf5, nnls
System Requirements
URL https://github.com/BodenmillerGroup/cytomapper
Bug Reports https://github.com/BodenmillerGroup/cytomapper/issues
See More
Suggests BiocStyle, knitr, rmarkdown, markdown, cowplot, testthat, shinytest
Linking To
Enhances
Depends On Me imcdatasets
Imports Me cytoviewer, imcRtools, simpleSeg
Suggests Me spicyWorkflow
Links To Me
Build Report Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package cytomapper_1.15.2.tar.gz
Windows Binary cytomapper_1.15.2.zip
macOS Binary (x86_64) cytomapper_1.15.2.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/cytomapper
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/cytomapper
Bioc Package Browser https://code.bioconductor.org/browse/cytomapper/
Package Short Url https://bioconductor.org/packages/cytomapper/
Package Downloads Report Download Stats