epigraHMM

DOI: 10.18129/B9.bioc.epigraHMM    

Epigenomic R-based analysis with hidden Markov models

Bioconductor version: Release (3.13)

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 "4.1") and enter:

if (!requireNamespace("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 1.0.1
In Bioconductor since BioC 3.13 (R-4.1) (< 6 months)
License MIT + file LICENSE
Depends
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
Links To Me
Build Report  

Package Archives

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

Source Package epigraHMM_1.0.1.tar.gz
Windows Binary epigraHMM_1.0.1.zip (32- & 64-bit)
macOS 10.13 (High Sierra) epigraHMM_1.0.1.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
Old Source Packages for BioC 3.13 Source Archive

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