epigraHMM

DOI: 10.18129/B9.bioc.epigraHMM    

This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see epigraHMM.

Epigenomic R-based analysis with hidden Markov models

Bioconductor version: 3.15

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>

Installation

To install this package, start R (version "4.2") and enter:

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

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")

 

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

Details

biocViews	ATACSeq, ChIPSeq, DNaseSeq, Epigenetics, HiddenMarkovModel, Software
Version	1.4.0
In Bioconductor since	BioC 3.13 (R-4.1) (1.5 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
LinkingTo	Rcpp, RcppArmadillo, Rhdf5lib
Suggests	testthat, knitr, rmarkdown, BiocStyle, BSgenome.Rnorvegicus.UCSC.rn4, gcapc, chromstaRData
SystemRequirements	GNU make
Enhances
URL
Depends On Me
Imports Me
Suggests Me
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Build Report

Package Archives

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

Source Package	epigraHMM_1.4.0.tar.gz
Windows Binary	epigraHMM_1.4.0.zip
macOS Binary (x86_64)	epigraHMM_1.4.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/epigraHMM
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/epigraHMM
Package Short Url	https://bioconductor.org/packages/epigraHMM/
Package Downloads Report	Download Stats