Package: crupR
Type: Package
Title: An R package to predict condition-specific enhancers from ChIP-seq data
Version: 1.3.0
Authors@R: c(
   person("Persia", "Akbari Omgba", email = "omgba@molgen.mpg.de", role = c("cre")),
   person("Verena", "Laupert", role = c("aut")),
   person("Martin", "Vingron", email = "vingron@molgen.ppg.com", role = c("aut")))
Description: An R package that offers a workflow to predict condition-specific enhancers from ChIP-seq data.
    The prediction of regulatory units is done in four main steps:
    Step 1 - the normalization of the ChIP-seq counts.
    Step 2 - the prediction of active enhancers binwise on the whole genome.
    Step 3 - the condition-specific clustering of the putative active enhancers.
    Step 4 - the detection of possible target genes of the condition-specific clusters using RNA-seq counts.
License: GPL-3
Encoding: UTF-8
LazyData: false
Imports: 
    bamsignals,
    Rsamtools,
    GenomicRanges,
    preprocessCore,
    randomForest,
    rtracklayer,
    Seqinfo,
    S4Vectors,
    ggplot2,
    matrixStats,
    dplyr,
    IRanges,
    GenomicAlignments,
    GenomicFeatures,
    TxDb.Mmusculus.UCSC.mm10.knownGene,
    TxDb.Mmusculus.UCSC.mm9.knownGene,
    TxDb.Hsapiens.UCSC.hg19.knownGene,
    TxDb.Hsapiens.UCSC.hg38.knownGene,
    reshape2,
    magrittr,
    stats,
    utils,
    grDevices,
    SummarizedExperiment,
    BiocParallel,
    fs,
    methods
Depends:
    R (>= 4.4.0)
Suggests: GenomeInfoDb, testthat, BiocStyle, knitr, rmarkdown
biocViews:
    DifferentialPeakCalling,
    GeneTarget,
    FunctionalPrediction,
    HistoneModification,
    PeakDetection
BiocType: Software
URL: https://github.com/akbariomgba/crupR
BugReports: https://github.com/akbariomgba/crupR/issues
RoxygenNote: 7.3.2
VignetteBuilder: knitr
git_url: https://git.bioconductor.org/packages/crupR
git_branch: devel
git_last_commit: f02dafa
git_last_commit_date: 2025-10-29
Repository: Bioconductor 3.23
