Package: ctgGEM
Type: Package
Title: Generating Tree Hierarchy Visualizations from Gene Expression
        Data
Version: 1.4.0
Author: Mark Block and Carrie Minette
Maintainer: USD Biomedical Engineering <bicbioeng@gmail.com>
Description: 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.
VignetteBuilder: knitr
License: GPL(>=2)
Encoding: UTF-8
biocViews: GeneExpression, Visualization, Sequencing, SingleCell,
        Clustering, RNASeq, ImmunoOncology, DifferentialExpression,
        MultipleComparison, QualityControl, DataImport
RoxygenNote: 7.1.0
Roxygen: list(markdown = TRUE)
Depends: monocle, SummarizedExperiment,
Imports: Biobase, BiocGenerics, graphics, grDevices, igraph, methods,
        utils, sincell, TSCAN, destiny, HSMMSingleCell
Suggests: BiocStyle, biomaRt, irlba, knitr, VGAM
Collate: 'ctgGEMset-class.R' 'ctgGEMset-methods.R' 'generate_tree.R'
        'makeDestiny.R' 'makeMonocle.R' 'makeSincell.R' 'makeTSCAN.R'
        'plotOriginalTree.R' 'tree2igraph.R'
git_url: https://git.bioconductor.org/packages/ctgGEM
git_branch: RELEASE_3_13
git_last_commit: 0e246e8
git_last_commit_date: 2021-05-19
Date/Publication: 2021-05-19
NeedsCompilation: no
Packaged: 2021-05-19 23:38:45 UTC; biocbuild
Built: R 4.1.0; ; 2021-05-20 07:43:56 UTC; windows
