cytomapper

DOI: 10.18129/B9.bioc.cytomapper    

Visualization of highly multiplexed imaging cytometry data in R

Bioconductor version: Release (3.11)

Highly multiplexed imaging cytometry acquires the single-cell expression of selected proteins in a spatially-resolved fashion. These measurements can be visualized 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 visualized on segmented cell areas. This package contains functions for the visualization of multiplexed read-outs and cell-level information obtained by multiplexed imaging cytometry. The main functions of this package allow 1. the visualization of pixel-level information across multiple channels and 2. the display of cell-level information (expression and/or metadata) on segmentation masks.

Author: Nils Eling [aut, cre] , Nicolas Damond [aut]

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

Installation

To install this package, start R (version "4.0") and enter:

if (!requireNamespace("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	Visualization of imaging cytometry data in R
PDF		Reference Manual
Text		NEWS

Details

biocViews	DataImport, ImmunoOncology, MultipleComparison, Normalization, OneChannel, SingleCell, Software, TwoChannel
Version	1.0.0
In Bioconductor since	BioC 3.11 (R-4.0) (0.5 years)
License	GPL (>= 2)
Depends	R (>= 4.0), EBImage, SingleCellExperiment, methods
Imports	S4Vectors, RColorBrewer, viridis, utils, SummarizedExperiment, tools, graphics, raster, grDevices, stats
LinkingTo
Suggests	BiocStyle, knitr, rmarkdown, testthat
SystemRequirements
Enhances
URL	https://github.com/BodenmillerGroup/cytomapper
BugReports	https://github.com/BodenmillerGroup/cytomapper/issues
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report

Package Archives

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

Source Package	cytomapper_1.0.0.tar.gz
Windows Binary	cytomapper_0.99.5.zip
macOS 10.13 (High Sierra)	cytomapper_1.0.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/cytomapper
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/cytomapper
Package Short Url	https://bioconductor.org/packages/cytomapper/
Package Downloads Report	Download Stats
Old Source Packages for BioC 3.11	Source Archive