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1 month ago Hi @akbariomgba
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The DESCRIPTION file for this package is:
Package: crupR
Type: Package
Title: an R package to predict condition-specific enhancers from ChIP-seq data
Version: 0.99.0
Authors@R: c(
person("Persia", "Akbari Omgba", email = "omgba@molgen.mpg.de", role = c("cre")),
person("Verena", "Laupert", email = "verena.laupert@bayer.com", role = c("aut")),
person("Martin", "Vingron", email = "vingron@molgen.ppg.com", role = c("aut")))
Description: An R package 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 is the normalization of the ChIP-seq counts.
Step 2 is the actual prediction of active enhancers bin-wise on the whole genome.
Step 3 is the condition-specific clustering of the putative active enhancers.
Step 4 is the search for possible target genes of the condition-specific clusters using RNA-seq counts.
License: GPL-3
Encoding: UTF-8
LazyData: false
Imports:
BSgenome.Mmusculus.UCSC.mm10,
BSgenome.Mmusculus.UCSC.mm9,
BSgenome.Hsapiens.UCSC.hg19,
BSgenome.Hsapiens.UCSC.hg38,
bamsignals,
Rsamtools,
GenomicRanges,
preprocessCore,
randomForest,
rtracklayer,
GenomeInfoDb,
S4Vectors,
parallel,
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,
BSgenome,
reshape2,
magrittr,
stats,
utils,
grDevices
Depends:
R (>= 4.2.0)
Suggests: testthat, BiocStyle, knitr, rmarkdown
biocViews:
DifferentialPeakCalling,
GeneTarget,
FunctionalPrediction,
HistoneModification,
PeakDetection
BiocType: Software
URL: https://github.com/akbariomgba/crupR
RoxygenNote: 7.2.3
VignetteBuilder: knitr
lshep
akbariomgba
PeteHaitch
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