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epigraHMM

This is the development version of epigraHMM; for the stable release version, see epigraHMM.

Epigenomic R-based analysis with hidden Markov models

Bioconductor version: Development (3.18)

epigraHMM provides a set of tools for the analysis of epigenomic data based on hidden Markov Models. It contains two separate peak callers, one for consensus peaks from biological or technical replicates, and one for differential peaks from multi-replicate multi-condition experiments. In differential peak calling, epigraHMM provides window-specific posterior probabilities associated with every possible combinatorial pattern of read enrichment across conditions.

Author: Pedro Baldoni [aut, cre]

Maintainer: Pedro Baldoni <pedrobaldoni at gmail.com>

Citation (from within R, enter citation("epigraHMM")):

Installation

To install this package, start R (version "4.3") and enter: 

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("epigraHMM")

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("epigraHMM")
Consensus and Differential Peak Calling With epigraHMM HTML R Script
Reference Manual PDF
NEWS Text
LICENSE Text

Details

biocViews ATACSeq, ChIPSeq, DNaseSeq, Epigenetics, HiddenMarkovModel, Software
Version 1.9.1
In Bioconductor since BioC 3.13 (R-4.1) (2 years)
License MIT + file LICENSE
Depends R (>= 3.5.0)
Imports Rcpp, magrittr, data.table, SummarizedExperiment, methods, GenomeInfoDb, GenomicRanges, rtracklayer, IRanges, Rsamtools, bamsignals, csaw, S4Vectors, limma, stats, Rhdf5lib, rhdf5, Matrix, MASS, scales, ggpubr, ggplot2, GreyListChIP, pheatmap, grDevices
Linking To Rcpp, RcppArmadillo, Rhdf5lib
Suggests testthat, knitr, rmarkdown, BiocStyle, BSgenome.Rnorvegicus.UCSC.rn4, gcapc, chromstaRData
System Requirements GNU make
Enhances
URL
See More
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report  

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package epigraHMM_1.9.1.tar.gz
Windows Binary epigraHMM_1.9.1.zip
macOS Binary (x86_64) epigraHMM_1.9.1.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/epigraHMM
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/epigraHMM
Bioc Package Browser https://code.bioconductor.org/browse/epigraHMM/
Package Short Url https://bioconductor.org/packages/epigraHMM/
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