cytomapper: Visualization of highly multiplexed imaging data in R

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.

Package details

AuthorNils Eling [aut, cre] (<>), Nicolas Damond [aut] (<>), Tobias Hoch [ctb]
Bioconductor views DataImport ImmunoOncology MultipleComparison Normalization OneChannel SingleCell Software TwoChannel
MaintainerNils Eling <>
LicenseGPL (>= 2)
Package repositoryView on Bioconductor
Installation Install the latest version of this package by entering the following in R:
if (!requireNamespace("BiocManager", quietly = TRUE))


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cytomapper documentation built on Jan. 30, 2021, 2:01 a.m.