flowCyBar

This is the released version of flowCyBar; for the devel version, see 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 (from within R, enter 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 PDF R Script
Reference Manual PDF

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
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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_1.42.0.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/
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