crupR
An R package to predict condition-specific enhancers from ChIP-seq data
Bioconductor version: 3.23 · Package version: 1.4.0
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.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("crupR") Details
| Maintainer | Persia Akbari Omgba <omgba@molgen.mpg.de> |
| Author | Persia Akbari Omgba [cre], Verena Laupert [aut], Martin Vingron [aut] |
| License | GPL-3 |
| URL | https://github.com/akbariomgba/crupR |
| Bug Reports | https://github.com/akbariomgba/crupR/issues |
| Downloads rank | 166 |
| Source branch | RELEASE_3_23 |
| biocViews | DifferentialPeakCalling, FunctionalPrediction, GeneTarget, HistoneModification, PeakDetection, Software |
Download
Dependencies
Depends: R (>= 4.4.0)
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
Suggests: GenomeInfoDb, testthat, BiocStyle, knitr, rmarkdown