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HDCytoData

Collection of high-dimensional cytometry benchmark datasets in Bioconductor object formats


Bioconductor version: Release (3.18)

Data package containing a set of publicly available high-dimensional cytometry benchmark datasets, formatted into SummarizedExperiment and flowSet Bioconductor object formats, including all required metadata. Row metadata includes sample IDs, group IDs, patient IDs, reference cell population or cluster labels (where available), and labels identifying 'spiked in' cells (where available). Column metadata includes channel names, protein marker names, and protein marker classes (cell type or cell state).

Author: Lukas M. Weber [aut, cre], Charlotte Soneson [aut]

Maintainer: Lukas M. Weber <lukas.weber.edu at gmail.com>

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

Installation

To install this package, start R (version "4.3") and enter:


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

BiocManager::install("HDCytoData")

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("HDCytoData")
1. HDCytoData package HTML R Script
2. Examples and use cases HTML R Script
3. Contribution guidelines HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews ExperimentData, ExperimentHub, ExpressionData, FlowCytometryData, Homo_sapiens_Data, ImmunoOncologyData, SingleCellData
Version 1.22.0
License MIT + file LICENSE
Depends ExperimentHub, SummarizedExperiment, flowCore
Imports utils, methods
System Requirements
URL https://github.com/lmweber/HDCytoData
Bug Reports https://github.com/lmweber/HDCytoData/issues
See More
Suggests BiocStyle, knitr, rmarkdown, Rtsne, umap, ggplot2, FlowSOM, mclust
Linking To
Enhances
Depends On Me cytofWorkflow
Imports Me
Suggests Me diffcyt
Links To Me
Build Report Build Report

Package Archives

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

Source Package HDCytoData_1.22.0.tar.gz
Windows Binary
macOS Binary (x86_64)
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/HDCytoData
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/HDCytoData
Package Short Url https://bioconductor.org/packages/HDCytoData/
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