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Bioconductor - diffcyt

diffcyt

This is the released version of diffcyt; for the devel version, see diffcyt.

Differential discovery in high-dimensional cytometry via high-resolution clustering

Bioconductor version: Release (3.21)

Statistical methods for differential discovery analyses in high-dimensional cytometry data (including flow cytometry, mass cytometry or CyTOF, and oligonucleotide-tagged cytometry), based on a combination of high-resolution clustering and empirical Bayes moderated tests adapted from transcriptomics.

Author: Lukas M. Weber [aut, cre] ORCID: 0000-0002-3282-1730

Maintainer: Lukas M. Weber <lmweb012 at gmail.com>

Citation (from within R, enter citation("diffcyt")): Installation

To install this package, start R (version "4.5") and enter:


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

BiocManager::install("diffcyt")

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("diffcyt")

Details biocViews CellBasedAssays, CellBiology, Clustering, FeatureExtraction, FlowCytometry, ImmunoOncology, Proteomics, SingleCell, Software Version 1.28.0 In Bioconductor since BioC 3.7 (R-3.5) (7 years) License MIT + file LICENSE Depends R (>= 3.4.0) Imports flowCore, FlowSOM, SummarizedExperiment, S4Vectors, limma, edgeR, lme4, multcomp, dplyr, tidyr, reshape2, magrittr, stats, methods, utils, grDevices, graphics, ComplexHeatmap, circlize, grid System Requirements URL https://github.com/lmweber/diffcyt Bug Reports https://github.com/lmweber/diffcyt/issues See More Package Archives

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

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