CytoTree

DOI: 10.18129/B9.bioc.CytoTree  

This package is deprecated. It will probably be removed from Bioconductor. Please refer to the package end-of-life guidelines for more information.

This package is for version 3.16 of Bioconductor. This package has been removed from Bioconductor. For the last stable, up-to-date release version, see CytoTree.

A Toolkit for Flow And Mass Cytometry Data

Bioconductor version: Release (3.16)

A trajectory inference toolkit for flow and mass cytometry data. CytoTree is a valuable tool to build a tree-shaped trajectory using flow and mass cytometry data. The application of CytoTree ranges from clustering and dimensionality reduction to trajectory reconstruction and pseudotime estimation. It offers complete analyzing workflow for flow and mass cytometry data.

Author: Yuting Dai [aut, cre]

Maintainer: Yuting Dai <forlynna at sjtu.edu.cn>

Installation

To install this package, start R (version "4.2") and enter:

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

BiocManager::install("CytoTree")

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

Documentation

PDF		Reference Manual

Details

biocViews	CellBasedAssays, CellBiology, Clustering, FlowCytometry, Network, NetworkInference, Software, Visualization
Version	1.8.0
In Bioconductor since	BioC 3.12 (R-4.0) (2.5 years)
License	GPL-3
Depends	R (>= 4.0), igraph
Imports	FlowSOM, Rtsne, ggplot2, destiny, gmodels, flowUtils, Biobase, Matrix, flowCore, sva, matrixStats, methods, mclust, prettydoc, RANN (>= 2.5), Rcpp (>= 0.12.0), BiocNeighbors, cluster, pheatmap, scatterpie, umap, scatterplot3d, limma, stringr, grDevices, grid, stats
LinkingTo	Rcpp
Suggests	BiocGenerics, knitr, RColorBrewer, rmarkdown, testthat, BiocStyle
SystemRequirements
Enhances
URL	http://www.r-project.org https://github.com/JhuangLab/CytoTree
BugReports	https://github.com/JhuangLab/CytoTree/issues
Depends On Me
Imports Me
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Build Report

Package Archives

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

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