DESCRIPTION

Package: metacell
Title: Meta cell analysis for single cell RNA-seq data
Version: 0.3.7
Authors@R: 
    person(given = "Amos",
           family = "Tanay",
           role = c("aut", "cre"),
           email = "amos.tanay@weizmann.ac.il")
Description: The MetaCell R package facilitates analysis of
    single cell RNA-seq UMI matrices by computing partitions of a cell
    similarity graph into small (~20-200 typically) homogeneous groups of
    cells which are defined as metacells (MCs). The derived MCs are then
    used for building different representations of the data, allowing
    matrix or 2D graph visualization forming a basis for analysis of cell
    types, subtypes, transcriptional gradients, cell-cycle variation, gene
    modules and their regulatory models and more. More details on the
    usage of the MetaCell pipeline is available in the package vignettes,
    and in papers using it.
License: MIT + file LICENSE
URL: https://github.com/tanaylab/metacell
BugReports: https://github.com/tanaylab/metacell/issues
Depends: 
    R (>= 3.5.0)
Imports:
    cluster,
    cowplot,
    data.table,
    dbscan,
    doMC,
    dplyr,
    entropy,
    ggplot2,
    graph,
    igraph,
    KernSmooth,
    magrittr,
    Matrix,
    matrixStats,
    methods,
    parallel,
    pdist,
    pheatmap,
    plyr,
    RColorBrewer,
    RCurl,
    Rgraphviz,
    svglite,
    slam,
    tidyr,
    tgconfig,
    tgstat,
    tgutil,
    umap,
    zoo
Suggests: 
    knitr,
    rmarkdown,
    SingleCellExperiment,
    S4Vectors
VignetteBuilder: 
    knitr
Remotes: 
    tanaylab/tgconfig,
    tanaylab/tgstat,
    tanaylab/tgutil
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Collate:
    'utils-pipe.R'
    'mc_plot_confusion.r'
    'atlas_project.r'
    'atlas.r'
    'cgraph_gcor_norm.r'
    'cgraph_knn_mcnorm.r'
    'coclust.r'
    'coclust_graph_cov.r'
    'mc2d_force_knn.r'
    'mc2d_plot.r'
    'mc_confusion.r'
    'mc_from_coclust.r'
    'mc_outliers.r'
    'mc_apx_qc.r'
    'mc_plot_cross_mc.r'
    'pipe_vanila.r'
    'scmat_gcors.r'
    'cgraph.r'
    'cgraph_knn.r'
    'cgraph_extmat.r'
    'gset_mc.r'
    'mc.r'
    'mc2d.r'
    'mc_colorize.r'
    'mc_export_tab.r'
    'mc_graphcov.r'
    'mc_plot_marks.r'
    'mc_plot_by_factor.r'
    'mgraph.r'
    'mgraph_knn.r'
    'mgraph_logistic.r'
    'mincost_flow.r'
    'mctnetwork.r'
    'mctnetwork_clust.r'
    'mctnetwork_plot_net.r'
    'gset.r'
    'gset_clust.r'
    'gset_feat_select.r'
    'gset_plot_mats.r'
    'gstats_report.r'
    'scmat_ccor.r'
    'scmat_10x.r'
    'scmat_mars.r'
    'scmat_batch_stat.r'
    'scmat.r'
    'scfigs.r'
    'gstats.r'
    'stat_utils.r'
    'utils.r'
    'scdb.r'
    'mc_apx_qc_cv.r'
    'mc_hierarchy.r'
    'mc_plot_vgels.r'
    'scmat_import.r'
    'gene_names_xref_util.r'
    'metacell-package.r'
    'zzz.r'