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 (3.20)
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]
Maintainer: Lukas M. Weber <lmweberedu at gmail.com>
citation("diffcyt")
):
Installation
To install this package, start R (version "4.4") 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")
diffcyt workflow | HTML | R Script |
Reference Manual | ||
NEWS | Text | |
LICENSE | Text |
Details
biocViews | CellBasedAssays, CellBiology, Clustering, FeatureExtraction, FlowCytometry, ImmunoOncology, Proteomics, SingleCell, Software |
Version | 1.26.0 |
In Bioconductor since | BioC 3.7 (R-3.5) (6.5 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
Suggests | BiocStyle, knitr, rmarkdown, testthat, HDCytoData, CATALYST |
Linking To | |
Enhances | |
Depends On Me | censcyt, cytofWorkflow |
Imports Me | treeclimbR, treekoR |
Suggests Me | CATALYST, tidytof |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | diffcyt_1.26.0.tar.gz |
Windows Binary (x86_64) | diffcyt_1.26.0.zip (64-bit only) |
macOS Binary (x86_64) | diffcyt_1.26.0.tgz |
macOS Binary (arm64) | diffcyt_1.26.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/diffcyt |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/diffcyt |
Bioc Package Browser | https://code.bioconductor.org/browse/diffcyt/ |
Package Short Url | https://bioconductor.org/packages/diffcyt/ |
Package Downloads Report | Download Stats |