iSeq
This is the development version of iSeq; for the stable release version, see iSeq.
Bayesian Hierarchical Modeling of ChIP-seq Data Through Hidden Ising Models
Bioconductor version: Development (3.22)
Bayesian hidden Ising models are implemented to identify IP-enriched genomic regions from ChIP-seq data. They can be used to analyze ChIP-seq data with and without controls and replicates.
Author: Qianxing Mo
Maintainer: Qianxing Mo <qianxing.mo at moffitt.org>
Citation (from within R, enter
citation("iSeq")):
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("iSeq")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("iSeq")| iSeq | R Script | |
| Reference Manual | ||
| NEWS | Text |
Details
| biocViews | ChIPSeq, Sequencing, Software |
| Version | 1.61.0 |
| In Bioconductor since | BioC 2.7 (R-2.12) (15 years) |
| License | GPL (>= 2) |
| Depends | R (>= 2.10.0) |
| Imports | |
| System Requirements | |
| URL |
See More
| Suggests | |
| Linking To | |
| Enhances | |
| Depends On Me | |
| Imports Me | |
| Suggests Me | |
| Links To Me | |
| Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
| Source Package | iSeq_1.61.0.tar.gz |
| Windows Binary (x86_64) | iSeq_1.61.0.zip |
| macOS Binary (x86_64) | iSeq_1.61.0.tgz |
| macOS Binary (arm64) | iSeq_1.61.0.tgz |
| Source Repository | git clone https://git.bioconductor.org/packages/iSeq |
| Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/iSeq |
| Bioc Package Browser | https://code.bioconductor.org/browse/iSeq/ |
| Package Short Url | https://bioconductor.org/packages/iSeq/ |
| Package Downloads Report | Download Stats |