Bioconductor version: Release (3.16)
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 (from within R,
enter citation("flowCyBar")
):
To install this package, start R (version "4.2") 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.
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("flowCyBar")
R Script | Analyze flow cytometric data using gate information | |
Reference Manual |
biocViews | CellBasedAssays, Clustering, FlowCytometry, ImmunoOncology, Software, Visualization |
Version | 1.34.0 |
In Bioconductor since | BioC 2.14 (R-3.1) (9 years) |
License | GPL-2 |
Depends | R (>= 3.0.0) |
Imports | gplots, vegan, methods |
LinkingTo | |
Suggests | |
SystemRequirements | |
Enhances | |
URL | http://www.ufz.de/index.php?de=16773 |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report |
Follow Installation instructions to use this package in your R session.
Source Package | flowCyBar_1.34.0.tar.gz |
Windows Binary | flowCyBar_1.34.0.zip |
macOS Binary (x86_64) | flowCyBar_1.34.0.tgz |
macOS Binary (arm64) | flowCyBar_1.34.0.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 |
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