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clusterExperiment

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

Compare Clusterings for Single-Cell Sequencing

Bioconductor version: Development (3.18)

Provides functionality for running and comparing many different clusterings of single-cell sequencing data or other large mRNA Expression data sets.

Author: Elizabeth Purdom [aut, cre, cph], Davide Risso [aut]

Maintainer: Elizabeth Purdom <epurdom at stat.berkeley.edu>

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

Installation

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

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

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

BiocManager::install("clusterExperiment")

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("clusterExperiment")
clusterExperiment Vignette HTML R Script
Working with Large Datasets HTML R Script
Reference Manual PDF
NEWS Text

Details

biocViews Clustering, RNASeq, Sequencing, SingleCell, Software
Version 2.21.0
In Bioconductor since BioC 3.4 (R-3.3) (7 years)
License Artistic-2.0
Depends R (>= 3.6.0), SingleCellExperiment, SummarizedExperiment(>= 1.15.4), BiocGenerics
Imports methods, NMF, RColorBrewer, ape (>= 5.0), cluster, stats, limma, howmany, locfdr, matrixStats, graphics, parallel, BiocSingular, kernlab, stringr, S4Vectors, grDevices, DelayedArray(>= 0.7.48), HDF5Array(>= 1.7.10), Matrix, Rcpp, edgeR, scales, zinbwave, phylobase, pracma, mbkmeans
Linking To Rcpp
Suggests BiocStyle, knitr, testthat, MAST, Rtsne, scran, igraph, rmarkdown
System Requirements
Enhances
URL
Bug Reports https://github.com/epurdom/clusterExperiment/issues
See More
Depends On Me netSmooth
Imports Me
Suggests Me netDx, slingshot, tradeSeq
Links To Me
Build Report  

Package Archives

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

Source Package clusterExperiment_2.21.0.tar.gz
Windows Binary clusterExperiment_2.21.0.zip
macOS Binary (x86_64) clusterExperiment_2.21.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/clusterExperiment
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/clusterExperiment
Bioc Package Browser https://code.bioconductor.org/browse/clusterExperiment/
Package Short Url https://bioconductor.org/packages/clusterExperiment/
Package Downloads Report Download Stats