cytomapper

DOI: 10.18129/B9.bioc.cytomapper  

Visualization of highly multiplexed imaging data in R

Bioconductor version: Release (3.16)

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, cre] , Nicolas Damond [aut] , Tobias Hoch [ctb]

Maintainer: Nils Eling <nils.eling at dqbm.uzh.ch>

Installation

To install this package, start R (version "4.2") and enter:

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

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")

 

HTML	R Script	On disk storage of images
HTML	R Script	Visualization of imaging cytometry data in R
PDF		Reference Manual
Text		NEWS

Details

biocViews	DataImport, ImmunoOncology, MultipleComparison, Normalization, OneChannel, SingleCell, Software, TwoChannel
Version	1.10.1
In Bioconductor since	BioC 3.11 (R-4.0) (3 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
LinkingTo
Suggests	BiocStyle, knitr, rmarkdown, markdown, cowplot, testthat, shinytest
SystemRequirements
Enhances
URL	https://github.com/BodenmillerGroup/cytomapper
BugReports	https://github.com/BodenmillerGroup/cytomapper/issues
Depends On Me	imcdatasets
Imports Me	imcRtools, simpleSeg
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	cytomapper_1.10.1.tar.gz
Windows Binary	cytomapper_1.10.1.zip
macOS Binary (x86_64)	cytomapper_1.10.1.tgz
macOS Binary (arm64)	cytomapper_1.10.1.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
Old Source Packages for BioC 3.16	Source Archive