Package: ChromSCape
Title: Analysis of single-cell epigenomics datasets with a Shiny App
Version: 1.0.0
Authors@R: c(person(given = "Pacome",
           family = "Prompsy",
           role = c("aut", "cre"),
           email = "pacome.prompsy@curie.fr",
           comment = c(ORCID = "0000-0003-4375-7583")),
	   person(given = "Celine",
           family = "Vallot",
           role = c("aut"),
           email = "celine.vallot@curie.fr",
           comment = c(ORCID = "0000-0003-1601-2359")))
Description: ChromSCape - Chromatin landscape profiling for Single Cells - is a ready-to-launch user-friendly Shiny Application for the analysis of single-cell epigenomics datasets (scChIP-seq, scATAC-seq, scCUT&Tag, ...) from aligned data to differential analysis & gene set enrichment analysis. It is highly interactive, enables users to save their analysis and covers a wide range of analytical steps: QC, preprocessing, filtering, batch correction, dimensionality reduction, vizualisation, clustering, differential analysis and gene set analysis. 
License: GPL-3
biocViews: Software, SingleCell, ChIPSeq, ATACSeq, MethylSeq,
        Classification, Clustering, Epigenetics, PrincipalComponent,
        SingleCell, ATACSeq, ChIPSeq, Annotation, BatchEffect,
        MultipleComparison, Normalization, Pathways, Preprocessing,
        QualityControl, ReportWriting, Visualization,
        GeneSetEnrichment, DifferentialPeakCalling
VignetteBuilder: knitr
URL: https://github.com/vallotlab/ChromSCape
BugReports: https://github.com/vallotlab/ChromSCape/issues
Encoding: UTF-8
LazyData: true
Suggests: testthat, knitr, rmarkdown, BiocStyle
RoxygenNote: 7.1.1
Roxygen: list(markdown = TRUE)
Imports: shiny, colourpicker, shinyjs, rtracklayer, shinyFiles,
        shinyhelper, shinycssloaders, Matrix, plotly, shinydashboard,
        colorRamps, kableExtra, viridis, batchelor, BiocParallel,
        parallel, Rsamtools, ggplot2, qualV, stringdist, fs, DT, scran,
        scater, ConsensusClusterPlus, Rtsne, dplyr, tidyr,
        GenomicRanges, IRanges, irlba, rlist, umap, tibble, methods,
        jsonlite, edgeR, stats, graphics, grDevices, utils, S4Vectors,
        SingleCellExperiment, SummarizedExperiment, msigdbr
Depends: R (>= 4.0)
git_url: https://git.bioconductor.org/packages/ChromSCape
git_branch: RELEASE_3_12
git_last_commit: c84df0d
git_last_commit_date: 2020-10-27
Date/Publication: 2020-10-27
NeedsCompilation: no
Packaged: 2020-10-27 23:11:14 UTC; biocbuild
Author: Pacome Prompsy [aut, cre] (<https://orcid.org/0000-0003-4375-7583>),
  Celine Vallot [aut] (<https://orcid.org/0000-0003-1601-2359>)
Maintainer: Pacome Prompsy <pacome.prompsy@curie.fr>
Built: R 4.0.3; ; 2020-11-03 08:19:04 UTC; unix
