This is the development version of crupR; for the stable release version, see crupR.
An R package to predict condition-specific enhancers from ChIP-seq dataBioconductor version: Development (3.22)
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.
Author: Persia Akbari Omgba [cre], Verena Laupert [aut], Martin Vingron [aut]
Maintainer: Persia Akbari Omgba <omgba at molgen.mpg.de>
Citation (from within R, entercitation("crupR")): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("crupR")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("crupR")Follow Installation instructions to use this package in your R session.
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