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epigraHMM

This is the released version of epigraHMM; for the devel version, see epigraHMM.

All versions 3.24 (devel), 3.23 (release), 3.22, 3.21, 3.20, 3.19, 3.18, 3.17, 3.16, 3.15, 3.14, 3.13

Epigenomic R-based analysis with hidden Markov models


Bioconductor version: Release (3.23)

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")):

Pedro Baldoni. epigraHMM: Epigenomic R-based analysis with hidden Markov models. doi:10.18129/B9.bioc.epigraHMM, R package version 1.20.2, https://bioconductor.org/packages/epigraHMM.

Generated from the package metadata; it may differ from the package's own citation.

Installation

To install this package, start R (version "4.6") 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")
Consensus and Differential Peak Calling With epigraHMM HTML R Script
Reference ManualPDF
NEWSText
LICENSEText

Details

biocViews ATACSeq, ChIPSeq, DNaseSeq, Epigenetics, HiddenMarkovModel, Software
Version1.20.2
In Bioconductor sinceBioC 3.13 (R-4.1) (5.5 years)
License MIT + file LICENSE
Depends R (>= 3.5.0)
Imports Rcpp, magrittr, data.table, SummarizedExperiment, methods, Seqinfo, GenomicRanges, rtracklayer, IRanges, Rsamtools, csaw, S4Vectors, limma, stats, Rhdf5lib, rhdf5, Matrix, MASS, scales, ggpubr, ggplot2, GreyListChIP, pheatmap, grDevices
System RequirementsGNU make
URL
See More
Suggests GenomeInfoDb, testthat, knitr, rmarkdown, BiocStyle, BSgenome.Hsapiens.UCSC.hg19, gcapc, genomationData
Linking To Rcpp, RcppArmadillo, Rhdf5lib
Enhances
Depends On Me
Imports Me
Suggests Me
Links To Me
Build Report Build Report, r-universe

Package Archives

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

Source Package epigraHMM_1.20.2.tar.gz
Windows Binary (x86_64) epigraHMM_1.20.2.zip
macOS Binary (big-sur-x86_64) epigraHMM_1.20.2.tgz
macOS Binary (sonoma-arm64) epigraHMM_1.20.2.tgz
Source Repositorygit 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 ReportDownload Stats
Old Source Packages for BioC 3.23Source Archive