This is the released version of cytomapper; for the devel version, see cytomapper.
Visualization of highly multiplexed imaging data in RBioconductor version: Release (3.21)
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: 0000-0002-4711-1176 , Nicolas Damond [aut] ORCID: 0000-0003-3027-8989 , Tobias Hoch [ctb], Lasse Meyer [cre, ctb] ORCID: 0000-0002-1660-1199
Maintainer: Lasse Meyer <lasse.meyer at dqbm.uzh.ch>
Citation (from within R, entercitation("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.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("cytomapper")Follow Installation instructions to use this package in your R session.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4