flowCyBar
Analyze flow cytometric data using gate information
Bioconductor version: Release (3.20)
A package to analyze flow cytometric data using gate information to follow population/community dynamics
Author: Joachim Schumann <joachim.schumann at ufz.de>, Christin Koch <christin.koch at ufz.de>, Susanne Günther <susanne.guenther at ufz.de>, Ingo Fetzer <ingo.fetzer at stockholmresilience.su.se>, Susann Müller <susann.mueller at ufz.de>
Maintainer: Joachim Schumann <joachim.schumann at ufz.de>
citation("flowCyBar")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("flowCyBar")
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("flowCyBar")
Analyze flow cytometric data using gate information | R Script | |
Reference Manual |
Details
biocViews | CellBasedAssays, Clustering, FlowCytometry, ImmunoOncology, Software, Visualization |
Version | 1.42.0 |
In Bioconductor since | BioC 2.14 (R-3.1) (10.5 years) |
License | GPL-2 |
Depends | R (>= 3.0.0) |
Imports | gplots, vegan, methods |
System Requirements | |
URL | http://www.ufz.de/index.php?de=16773 |
See More
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Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | flowCyBar_1.42.0.tar.gz |
Windows Binary (x86_64) | flowCyBar_1.42.0.zip (64-bit only) |
macOS Binary (x86_64) | flowCyBar_1.42.0.tgz |
macOS Binary (arm64) | flowCyBar_1.41.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/flowCyBar |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/flowCyBar |
Bioc Package Browser | https://code.bioconductor.org/browse/flowCyBar/ |
Package Short Url | https://bioconductor.org/packages/flowCyBar/ |
Package Downloads Report | Download Stats |