cytomapper

This package is for version 3.11 of Bioconductor; for the stable, up-to-date release version, see cytomapper.

Visualization of highly multiplexed imaging cytometry data in R


Bioconductor version: 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>

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

Installation

To install this package, start R (version "4.0") 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")
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 1.0.0
In Bioconductor since BioC 3.11 (R-4.0) (4 years)
License GPL (>= 2)
Depends R (>= 4.0), EBImage, SingleCellExperiment, methods
Imports S4Vectors, RColorBrewer, viridis, utils, SummarizedExperiment, tools, graphics, raster, grDevices, stats
System Requirements
URL https://github.com/BodenmillerGroup/cytomapper
Bug Reports https://github.com/BodenmillerGroup/cytomapper/issues
See More
Suggests BiocStyle, knitr, rmarkdown, testthat
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Build Report 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
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 3.11 Source Archive