Package: ctgGEM
Type: Package
Title: Generating Tree Hierarchy Visualizations from Gene Expression
        Data
Version: 0.99.3
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
LazyData: true
biocViews: GeneExpression, Visualization, Sequencing, SingleCell,
        Clustering, RNASeq, ImmunoOncology, DifferentialExpression,
        MultipleComparison, QualityControl, DataImport
RoxygenNote: 7.0.2
Roxygen: list(markdown = TRUE)
Depends: monocle
Imports: Biobase, BiocGenerics, ggplot2, graphics, grDevices, igraph,
        Matrix, methods, SummarizedExperiment, utils
Suggests: BiocStyle, biomaRt, cellTree, destiny, HSMMSingleCell, irlba,
        knitr, sincell, TSCAN, VGAM
Collate: 'ctgGEMset-class.R' 'ctgGEMset-methods.R' 'generate_tree.R'
        'makeCellTree.R' 'makeDestiny.R' 'makeMonocle.R'
        'makeSincell.R' 'makeTSCAN.R' 'plotOriginalTree.R'
        'tree2igraph.R'
git_url: https://git.bioconductor.org/packages/ctgGEM
git_branch: master
git_last_commit: 9655eeb
git_last_commit_date: 2020-02-29
Date/Publication: 2020-03-11
NeedsCompilation: no
Packaged: 2020-03-12 08:01:48 UTC; biocbuild
Built: R 4.0.0; ; 2020-03-12 17:19:50 UTC; windows
