ctgGEM

DOI: 10.18129/B9.bioc.ctgGEM  

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 ctgGEM.

Generating Tree Hierarchy Visualizations from Gene Expression Data

Bioconductor version: Release (3.16)

Cell Tree Generator for Gene Expression Matrices (ctgGEM) streamlines the building of cell-state hierarchies from single-cell gene expression data across multiple existing tools for improved comparability and reproducibility. It supports pseudotemporal ordering algorithms and visualization tools from monocle, cellTree, TSCAN, sincell, and destiny, and provides a unified output format for integration with downstream data analysis workflows and Cytoscape.

Author: Mark Block [aut], Carrie Minette [aut], Evgeni Radichev [aut], Etienne Gnimpieba [aut], Mariah Hoffman [aut], USD Biomedical Engineering [aut, cre]

Maintainer: USD Biomedical Engineering <bicbioeng at gmail.com>

Installation

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

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

BiocManager::install("ctgGEM")

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

Documentation

PDF		Reference Manual

Details

biocViews	Clustering, DataImport, DifferentialExpression, GeneExpression, ImmunoOncology, MultipleComparison, QualityControl, RNASeq, Sequencing, SingleCell, Software, Visualization
Version	1.10.0
In Bioconductor since	BioC 3.11 (R-4.0) (3 years)
License	GPL(>=2)
Depends	monocle, SummarizedExperiment
Imports	Biobase, BiocGenerics, graphics, grDevices, igraph, Matrix, methods, utils, sincell, TSCAN
LinkingTo
Suggests	BiocStyle, biomaRt, HSMMSingleCell, irlba, knitr, rmarkdown, VGAM
SystemRequirements
Enhances
URL
Depends On 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/ctgGEM
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/ctgGEM
Package Short Url	https://bioconductor.org/packages/ctgGEM/
Package Downloads Report	Download Stats