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 (3.20)
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("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 | ||
NEWS | Text |
Details
biocViews | DataImport, ImmunoOncology, MultipleComparison, Normalization, OneChannel, SingleCell, Software, TwoChannel |
Version | 1.17.0 |
In Bioconductor since | BioC 3.11 (R-4.0) (4.5 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 | |
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_1.17.0.tar.gz |
Windows Binary (x86_64) | cytomapper_1.17.0.zip (64-bit only) |
macOS Binary (x86_64) | cytomapper_1.17.0.tgz |
macOS Binary (arm64) | cytomapper_1.17.0.tgz |
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 |