Site2Target
An R package to associate peaks and target genes
Bioconductor version: 3.24 · Package version: 1.5.0
Other Bioconductor versions
devel is the development version; release is the current stable one.
3.24 (devel), 3.23 (release)
Statistics implemented for both peak-wise and gene-wise associations. In peak-wise associations, the p-value of the target genes of a given set of peaks are calculated. Negative binomial or Poisson distributions can be used for modeling the unweighted peaks targets and log-nromal can be used to model the weighted peaks. In gene-wise associations a table consisting of a set of genes, mapped to specific peaks, is generated using the given rules.
Installation
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("Site2Target")Details
| Maintainer | Peyman Zarrineh <peyman.zarrineh@manchester.ac.uk> |
| Author | Peyman Zarrineh [cre, aut] (ORCID: <https://orcid.org/0000-0003-4820-4101>) |
| License | GPL-2 |
| Bug Reports | https://github.com/fls-bioinformatics-core/Site2Target/issues |
| Source branch | devel |
| Build report | Bioconductor build system, r-universe |
| biocViews | Annotation, ChIPSeq, Epigenetics, GeneExpression, GeneTarget, Software |
| Package Short Url | https://bioconductor.org/packages/Site2Target/ |
Citation
From within R, enter citation("Site2Target"):
Peyman Zarrineh. Site2Target: An R package to associate peaks and target genes. doi:10.18129/B9.bioc.Site2Target, R package version 1.5.0, https://bioconductor.org/packages/Site2Target.
Generated from the package metadata; it may differ from the package's own citation.
Documentation
Download
Follow the installation instructions to use this package in your R session.
| Source package | Site2Target_1.5.0.tar.gz |
| Windows binary (x86_64) | Site2Target_1.5.0.zip |
| macOS binary (arm64) | Site2Target_1.5.0.tgz |
| macOS binary (x86_64) | Site2Target_1.5.0.tgz |
Dependencies
Depends: R (>= 4.4)
Imports: S4Vectors, stats, utils, BiocGenerics, GenomeInfoDb, MASS, IRanges, GenomicRanges
Suggests: BiocStyle, knitr, rmarkdown, testthat (>= 3.0.0)