Bioconductor 3.22 Released

CytoML

This is the development version of CytoML; for the stable release version, see CytoML.

A GatingML Interface for Cross Platform Cytometry Data Sharing


Bioconductor version: Development (3.23)

Uses platform-specific implemenations of the GatingML2.0 standard to exchange gated cytometry data with other software platforms.

Author: Mike Jiang, Jake Wagner

Maintainer: Mike Jiang <mike at ozette.com>

Citation (from within R, enter citation("CytoML")):

Installation

To install this package, start R (version "4.6") and enter:


if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("CytoML")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

Reference Manual PDF

Details

biocViews DataImport, DataRepresentation, FlowCytometry, ImmunoOncology, Software
Version 2.21.0
In Bioconductor since BioC 3.4 (R-3.3) (9 years)
License AGPL-3.0-only
Depends
Imports cytolib(>= 2.3.10), flowCore(>= 1.99.10), flowWorkspace(>= 4.1.8), openCyto(>= 1.99.2), XML, data.table, jsonlite, RBGL, Rgraphviz, Biobase, methods, graph, graphics, utils, jsonlite, dplyr, grDevices, methods, ggcyto(>= 1.11.4), yaml, stats, tibble
System Requirements xml2, GNU make, C++11
URL https://github.com/RGLab/CytoML
Bug Reports https://github.com/RGLab/CytoML/issues
See More
Suggests testthat, flowWorkspaceData, knitr, rmarkdown, parallel
Linking To cpp11, BH (>= 1.62.0-1), RProtoBufLib, cytolib, Rhdf5lib, flowWorkspace
Enhances
Depends On Me
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Links To Me
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package
Windows Binary (x86_64)
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/CytoML
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/CytoML
Package Short Url https://bioconductor.org/packages/CytoML/
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