BodenmillerGroup/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.

Getting started

Package details

Bioconductor views DataImport ImmunoOncology MultipleComparison Normalization OneChannel SingleCell Software TwoChannel
Maintainer
LicenseGPL (>= 2)
Version1.5.1
URL https://github.com/BodenmillerGroup/cytomapper
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("BodenmillerGroup/cytomapper")
BodenmillerGroup/cytomapper documentation built on June 9, 2021, 1:01 p.m.