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cytomapper

This is the released version of cytomapper; for the devel version, see cytomapper.

Visualization of highly multiplexed imaging data in R


Bioconductor version: Release (3.22)

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] ORCID iD ORCID: 0000-0002-4711-1176 , Nicolas Damond [aut] ORCID iD ORCID: 0000-0003-3027-8989 , Tobias Hoch [ctb], Lasse Meyer [cre, ctb] ORCID iD ORCID: 0000-0002-1660-1199

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

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

Installation

To install this package, start R (version "4.5") 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")
On disk storage of images HTML R Script
Visualization of imaging cytometry data in R HTML R Script
Reference Manual PDF
NEWS Text

Details

Version 1.22.0
In Bioconductor since BioC 3.11 (R-4.0) (5.5 years)
License GPL (>= 2)
Depends R (>= 4.0), EBImage, SingleCellExperiment, methods
System Requirements
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Package Archives

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

Source Package cytomapper_1.22.0.tar.gz
Windows Binary (x86_64) cytomapper_1.21.0.zip (64-bit only)
macOS Binary (x86_64) cytomapper_1.22.0.tgz
macOS Binary (arm64) cytomapper_1.22.0.tgz
Source Repository git clone https://git.bioconductor.org/packages/cytomapper
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/cytomapper
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